Transportation Network Topologies
Holmes, Bruce J.; Scott, John
2004-01-01
A discomforting reality has materialized on the transportation scene: our existing air and ground infrastructures will not scale to meet our nation's 21st century demands and expectations for mobility, commerce, safety, and security. The consequence of inaction is diminished quality of life and economic opportunity in the 21st century. Clearly, new thinking is required for transportation that can scale to meet to the realities of a networked, knowledge-based economy in which the value of time is a new coin of the realm. This paper proposes a framework, or topology, for thinking about the problem of scalability of the system of networks that comprise the aviation system. This framework highlights the role of integrated communication-navigation-surveillance systems in enabling scalability of future air transportation networks. Scalability, in this vein, is a goal of the recently formed Joint Planning and Development Office for the Next Generation Air Transportation System. New foundations for 21st thinking about air transportation are underpinned by several technological developments in the traditional aircraft disciplines as well as in communication, navigation, surveillance and information systems. Complexity science and modern network theory give rise to one of the technological developments of importance. Scale-free (i.e., scalable) networks represent a promising concept space for modeling airspace system architectures, and for assessing network performance in terms of scalability, efficiency, robustness, resilience, and other metrics. The paper offers an air transportation system topology as framework for transportation system innovation. Successful outcomes of innovation in air transportation could lay the foundations for new paradigms for aircraft and their operating capabilities, air transportation system architectures, and airspace architectures and procedural concepts. The topology proposed considers air transportation as a system of networks, within which
Transportation Network Topologies
Alexandrov, Natalia (Editor)
2004-01-01
The existing U.S. hub-and-spoke air transportation system is reaching saturation. Major aspects of the current system, such as capacity, safety, mobility, customer satisfaction, security, communications, and ecological effects, require improvements. The changing dynamics - increased presence of general aviation, unmanned autonomous vehicles, military aircraft in civil airspace as part of homeland defense - contributes to growing complexity of airspace. The system has proven remarkably resistant to change. NASA Langley Research Center and the National Institute of Aerospace conducted a workshop on Transportation Network Topologies on 9-10 December 2003 in Williamsburg, Virginia. The workshop aimed to examine the feasibility of traditional methods for complex system analysis and design as well as potential novel alternatives in application to transportation systems, identify state-of-the-art models and methods, conduct gap analysis, and thus to lay a foundation for establishing a focused research program in complex systems applied to air transportation.
On the topology of optical transport networks
International Nuclear Information System (INIS)
Cardenas, J P; Santiago, A; Losada, J C; Benito, R M; Mouronte, M L
2010-01-01
Synchronous Digital Hierarchy (SDH) is the standard technology for information transmission in broadband optical networks. Unlike systems with unplanned growth, such as those of natural origin or the Internet network, the SDH systems are strictly planned as rings, meshes, stars or tree-branches structures designed to connect different equipments. In spite of that, we have found that the SDH network operated by Telefonica in Spain shares remarkable topological properties with other real complex networks as a product of its evolution since 1992. In fact, we have found power-law scaling in the degree distribution (N·P(k) = k -γ ) and small-world networks properties. The complexity found in SDH systems was reproduced by two models of complex networks, one of them considers real planning directives that take into account geographical and technological variables and the other one is based in the compatibility among SDH equipments.
Topological Effects and Performance Optimization in Transportation Continuous Network Design
Directory of Open Access Journals (Sweden)
Jianjun Wu
2014-01-01
Full Text Available Because of the limitation of budget, in the planning of road works, increased efforts should be made on links that are more critical to the whole traffic system. Therefore, it would be helpful to model and evaluate the vulnerability and reliability of the transportation network when the network design is processing. This paper proposes a bilevel transportation network design model, in which the upper level is to minimize the performance of the network under the given budgets, while the lower level is a typical user equilibrium assignment problem. A new solution approach based on particle swarm optimization (PSO method is presented. The topological effects on the performance of transportation networks are studied with the consideration of three typical networks, regular lattice, random graph, and small-world network. Numerical examples and simulations are presented to demonstrate the proposed model.
Alexandrov, Natalia (Technical Monitor); Kuby, Michael; Tierney, Sean; Roberts, Tyler; Upchurch, Christopher
2005-01-01
This report reviews six classes of models that are used for studying transportation network topologies. The report is motivated by two main questions. First, what can the "new science" of complex networks (scale-free, small-world networks) contribute to our understanding of transport network structure, compared to more traditional methods? Second, how can geographic information systems (GIS) contribute to studying transport networks? The report defines terms that can be used to classify different kinds of models by their function, composition, mechanism, spatial and temporal dimensions, certainty, linearity, and resolution. Six broad classes of models for analyzing transport network topologies are then explored: GIS; static graph theory; complex networks; mathematical programming; simulation; and agent-based modeling. Each class of models is defined and classified according to the attributes introduced earlier. The paper identifies some typical types of research questions about network structure that have been addressed by each class of model in the literature.
Synchronization and Control of Halo-Chaos in Beam Transport Network with Small World Topology
International Nuclear Information System (INIS)
Liu Qiang; Fang Jinqing; Li Yong
2007-01-01
The synchronous conditions of two kinds of the small-world (SW) network are studied. The small world topology can affect on dynamical behaviors of the beam transport network (BTN) largely, if the BTN is constructed with the SW topology, the global linear coupling and special linear feedback can realize the synchronization control of beam halo-chaos as well as periodic state in the BTN with the SW topology, respectively. This important result can provide an effective way for the experimental study and the engineering design of the BTN in the high-current accelerator driven radioactive clean nuclear power systems, and may have potential use in prospective applications for halo-chaos secure communication.
Energy Technology Data Exchange (ETDEWEB)
Kalb, Jeffrey L.; Lee, David S.
2008-01-01
Emerging high-bandwidth, low-latency network technology has made network-based architectures both feasible and potentially desirable for use in satellite payload architectures. The selection of network topology is a critical component when developing these multi-node or multi-point architectures. This study examines network topologies and their effect on overall network performance. Numerous topologies were reviewed against a number of performance, reliability, and cost metrics. This document identifies a handful of good network topologies for satellite applications and the metrics used to justify them as such. Since often multiple topologies will meet the requirements of the satellite payload architecture under development, the choice of network topology is not easy, and in the end the choice of topology is influenced by both the design characteristics and requirements of the overall system and the experience of the developer.
Empirical investigation of topological and weighted properties of a bus transport network from China
Shu-Min, Feng; Bao-Yu, Hu; Cen, Nie; Xiang-Hao, Shen; Yu-Sheng, Ci
2016-03-01
Many bus transport networks (BTNs) have evolved into directed networks. A new representation model for BTNs is proposed, called directed-space P. The bus transport network of Harbin (BTN-H) is described as a directed and weighted complex network by the proposed representation model and by giving each node weights. The topological and weighted properties are revealed in detail. In-degree and out-degree distributions, in-weight and out-weight distributions are presented as an exponential law, respectively. There is a strong relation between in-weight and in-degree (also between out-weight and out-degree), which can be fitted by a power function. Degree-degree and weight-weight correlations are investigated to reveal that BTN-H has a disassortative behavior as the nodes have relatively high degree (or weight). The disparity distributions of out-degree and in-degree follow an approximate power-law. Besides, the node degree shows a near linear increase with the number of routes that connect to the corresponding station. These properties revealed in this paper can help public transport planners to analyze the status quo of the BTN in nature. Project supported by the National High Technology Research and Development Program of China (Grant No. 2014AA110304).
Tsiotas, Dimitrios; Polyzos, Serafeim
2018-02-01
This article studies the topological consistency of spatial networks due to node aggregation, examining the changes captured between different network representations that result from nodes' grouping and they refer to the same socioeconomic system. The main purpose of this study is to evaluate what kind of topological information remains unalterable due to node aggregation and, further, to develop a framework for linking the data of an empirical network with data of its socioeconomic environment, when the latter are available for hierarchically higher levels of aggregation, in an effort to promote the interdisciplinary research in the field of complex network analysis. The research question is empirically tested on topological and socioeconomic data extracted from the Greek Maritime Network (GMN) that is modeled as a non-directed multilayer (bilayer) graph consisting of a port-layer, where nodes represent ports, and a prefecture-layer, where nodes represent coastal and insular prefectural groups of ports. The analysis highlights that the connectivity (degree) of the GMN is the most consistent aspect of this multilayer network, which preserves both the topological and the socioeconomic information through node aggregation. In terms of spatial analysis and regional science, such effects illustrate the effectiveness of the prefectural administrative division for the functionality of the Greek maritime transportation system. Overall, this approach proposes a methodological framework that can enjoy further applications about the grouping effects induced on the network topology, providing physical, technical, socioeconomic, strategic or political insights.
Banks, Natalie Clare; Paini, Dean Ronald; Bayliss, Kirsty Louise; Hodda, Michael
2015-02-01
More people and goods are moving further and more frequently via many different trade and transport networks under current trends of globalisation. These networks can play a major role in the unintended introduction of exotic species to new locations. With the continuing rise in global trade, more research attention is being focused on the role of networks in the spread of invasive species. This represents an emerging field of research in invasion science and the substantial knowledge being generated within other disciplines can provide ecologists with new tools with which to study invasions. For the first time, we synthesise studies from several perspectives, approaches and disciplines to derive the fundamental characteristics of network topology determining the likelihood of spread of organisms via trade and transport networks. These characteristics can be used to identify critical points of vulnerability within these networks and enable the development of more effective strategies to prevent invasions. © 2014 John Wiley & Sons Ltd/CNRS.
Wireless sensor network topology control
Zuk, Olexandr; Romanjuk, Valeriy; Sova, Oleg
2010-01-01
Topology control process for the wireless sensor network is considered. In this article the use of rule base for making decision on the search of optimum network topology is offered for the realization of different aims of network management.
Quist, Daniel A [Los Alamos, NM; Gavrilov, Eugene M [Los Alamos, NM; Fisk, Michael E [Jemez, NM
2008-01-15
A method enables the topology of an acyclic fully propagated network to be discovered. A list of switches that comprise the network is formed and the MAC address cache for each one of the switches is determined. For each pair of switches, from the MAC address caches the remaining switches that see the pair of switches are located. For each pair of switches the remaining switches are determined that see one of the pair of switches on a first port and the second one of the pair of switches on a second port. A list of insiders is formed for every pair of switches. It is determined whether the insider for each pair of switches is a graph edge and adjacent ones of the graph edges are determined. A symmetric adjacency matrix is formed from the graph edges to represent the topology of the data link network.
OPTIMAL NETWORK TOPOLOGY DESIGN
Yuen, J. H.
1994-01-01
This program was developed as part of a research study on the topology design and performance analysis for the Space Station Information System (SSIS) network. It uses an efficient algorithm to generate candidate network designs (consisting of subsets of the set of all network components) in increasing order of their total costs, and checks each design to see if it forms an acceptable network. This technique gives the true cost-optimal network, and is particularly useful when the network has many constraints and not too many components. It is intended that this new design technique consider all important performance measures explicitly and take into account the constraints due to various technical feasibilities. In the current program, technical constraints are taken care of by the user properly forming the starting set of candidate components (e.g. nonfeasible links are not included). As subsets are generated, they are tested to see if they form an acceptable network by checking that all requirements are satisfied. Thus the first acceptable subset encountered gives the cost-optimal topology satisfying all given constraints. The user must sort the set of "feasible" link elements in increasing order of their costs. The program prompts the user for the following information for each link: 1) cost, 2) connectivity (number of stations connected by the link), and 3) the stations connected by that link. Unless instructed to stop, the program generates all possible acceptable networks in increasing order of their total costs. The program is written only to generate topologies that are simply connected. Tests on reliability, delay, and other performance measures are discussed in the documentation, but have not been incorporated into the program. This program is written in PASCAL for interactive execution and has been implemented on an IBM PC series computer operating under PC DOS. The disk contains source code only. This program was developed in 1985.
Animal transportation networks
Perna, Andrea; Latty, Tanya
2014-01-01
Many group-living animals construct transportation networks of trails, galleries and burrows by modifying the environment to facilitate faster, safer or more efficient movement. Animal transportation networks can have direct influences on the fitness of individuals, whereas the shape and structure of transportation networks can influence community dynamics by facilitating contacts between different individuals and species. In this review, we discuss three key areas in the study of animal transportation networks: the topological properties of networks, network morphogenesis and growth, and the behaviour of network users. We present a brief primer on elements of network theory, and then discuss the different ways in which animal groups deal with the fundamental trade-off between the competing network properties of travel efficiency, robustness and infrastructure cost. We consider how the behaviour of network users can impact network efficiency, and call for studies that integrate both network topology and user behaviour. We finish with a prospectus for future research. PMID:25165598
Optimal Network-Topology Design
Li, Victor O. K.; Yuen, Joseph H.; Hou, Ting-Chao; Lam, Yuen Fung
1987-01-01
Candidate network designs tested for acceptability and cost. Optimal Network Topology Design computer program developed as part of study on topology design and analysis of performance of Space Station Information System (SSIS) network. Uses efficient algorithm to generate candidate network designs consisting of subsets of set of all network components, in increasing order of total costs and checks each design to see whether it forms acceptable network. Technique gives true cost-optimal network and particularly useful when network has many constraints and not too many components. Program written in PASCAL.
Topological Rankings in Communication Networks
DEFF Research Database (Denmark)
Aabrandt, Andreas; Hansen, Vagn Lundsgaard; Træholt, Chresten
2015-01-01
In the theory of communication the central problem is to study how agents exchange information. This problem may be studied using the theory of connected spaces in topology, since a communication network can be modelled as a topological space such that agents can communicate if and only...... if they belong to the same path connected component of that space. In order to study combinatorial properties of such a communication network, notions from algebraic topology are applied. This makes it possible to determine the shape of a network by concrete invariants, e.g. the number of connected components...
Coverings, Networks and Weak Topologies
Czech Academy of Sciences Publication Activity Database
Dow, A.; Junnila, H.; Pelant, Jan
2006-01-01
Roč. 53, č. 2 (2006), s. 287-320 ISSN 0025-5793 R&D Projects: GA ČR GA201/97/0216 Institutional research plan: CEZ:AV0Z10190503 Keywords : Banach spaces * weak topologies * networks topologies Subject RIV: BA - General Mathematics
Network topology descriptions in hybrid networks
Grosso, P.; Brown, A.; Cedeyn, A.; Dijkstra, F.; van der Ham, J.; Patil, A.; Primet, P.; Swany, M.; Zurawski, J.
2010-01-01
The NML-WG goal is to define a schema for describing topologies of hybrid networks. This schema is in first instance intended for: • lightpath provisioning applications to exchange topology information intra and inter domain; • reporting performance metrics. This document constitutes Deliverable 1
Topology of molecular interaction networks
Winterbach, W.; Van Mieghem, P.; Reinders, M.; Wang, H.; De Ridder, D.
2013-01-01
Molecular interactions are often represented as network models which have become the common language of many areas of biology. Graphs serve as convenient mathematical representations of network models and have themselves become objects of study. Their topology has been intensively researched over
DEFF Research Database (Denmark)
Yu, Hao; Yan, Ying; Berger, Michael Stubert
2009-01-01
Carrier Ethernet is becoming a favorable access technology for Next Generation Network (NGN). The features of cost-efficiency, operation flexibility and high bandwidth have a great attraction to service providers. However, to achieve these characteristics, Carrier Ethernet needs to have Quality o....... This work has been carried out as a part of the research project HIPT (High quality IP network for IPTV and VoIP) founded by Danish Advanced Technology Foundation....
Topological Analysis of Wireless Networks (TAWN)
2016-05-31
19b. TELEPHONE NUMBER (Include area code) 31-05-2016 FINAL REPORT 12-02-2015 -- 31-05-2016 Topological Analysis of Wireless Networks (TAWN) Robinson...Release, Distribution Unlimited) N/A The goal of this project was to develop topological methods to detect and localize vulnerabilities of wireless... topology U U U UU 32 Michael Robinson 202-885-3681 Final Report: May 2016 Topological Analysis of Wireless Networks Principal Investigator: Prof. Michael
Topological Indices of Textual Identity Networks.
Leazer, Gregory H.; Furner, Jonathan
1999-01-01
Reports on a continuing investigation of intertextual networks. Describes how intertextual networks can be modeled as directed graphs and extends this to matrix representations. Discusses topological index values of these networks and speculates how topological index values might be used in the estimation of retrieval values in information…
How to model wireless mesh networks topology
International Nuclear Information System (INIS)
Sanni, M L; Hashim, A A; Anwar, F; Ali, S; Ahmed, G S M
2013-01-01
The specification of network connectivity model or topology is the beginning of design and analysis in Computer Network researches. Wireless Mesh Networks is an autonomic network that is dynamically self-organised, self-configured while the mesh nodes establish automatic connectivity with the adjacent nodes in the relay network of wireless backbone routers. Researches in Wireless Mesh Networks range from node deployment to internetworking issues with sensor, Internet and cellular networks. These researches require modelling of relationships and interactions among nodes including technical characteristics of the links while satisfying the architectural requirements of the physical network. However, the existing topology generators model geographic topologies which constitute different architectures, thus may not be suitable in Wireless Mesh Networks scenarios. The existing methods of topology generation are explored, analysed and parameters for their characterisation are identified. Furthermore, an algorithm for the design of Wireless Mesh Networks topology based on square grid model is proposed in this paper. The performance of the topology generated is also evaluated. This research is particularly important in the generation of a close-to-real topology for ensuring relevance of design to the intended network and validity of results obtained in Wireless Mesh Networks researches
Toward Optimal Transport Networks
Alexandrov, Natalia; Kincaid, Rex K.; Vargo, Erik P.
2008-01-01
Strictly evolutionary approaches to improving the air transport system a highly complex network of interacting systems no longer suffice in the face of demand that is projected to double or triple in the near future. Thus evolutionary approaches should be augmented with active design methods. The ability to actively design, optimize and control a system presupposes the existence of predictive modeling and reasonably well-defined functional dependences between the controllable variables of the system and objective and constraint functions for optimization. Following recent advances in the studies of the effects of network topology structure on dynamics, we investigate the performance of dynamic processes on transport networks as a function of the first nontrivial eigenvalue of the network's Laplacian, which, in turn, is a function of the network s connectivity and modularity. The last two characteristics can be controlled and tuned via optimization. We consider design optimization problem formulations. We have developed a flexible simulation of network topology coupled with flows on the network for use as a platform for computational experiments.
Topological protection of multiparticle dissipative transport
Loehr, Johannes; Loenne, Michael; Ernst, Adrian; de Las Heras, Daniel; Fischer, Thomas M.
2016-06-01
Topological protection allows robust transport of localized phenomena such as quantum information, solitons and dislocations. The transport can be either dissipative or non-dissipative. Here, we experimentally demonstrate and theoretically explain the topologically protected dissipative motion of colloidal particles above a periodic hexagonal magnetic pattern. By driving the system with periodic modulation loops of an external and spatially homogeneous magnetic field, we achieve total control over the motion of diamagnetic and paramagnetic colloids. We can transport simultaneously and independently each type of colloid along any of the six crystallographic directions of the pattern via adiabatic or deterministic ratchet motion. Both types of motion are topologically protected. As an application, we implement an automatic topologically protected quality control of a chemical reaction between functionalized colloids. Our results are relevant to other systems with the same symmetry.
Symmetric Topological Phases and Tensor Network States
Jiang, Shenghan
Classification and simulation of quantum phases are one of main themes in condensed matter physics. Quantum phases can be distinguished by their symmetrical and topological properties. The interplay between symmetry and topology in condensed matter physics often leads to exotic quantum phases and rich phase diagrams. Famous examples include quantum Hall phases, spin liquids and topological insulators. In this thesis, I present our works toward a more systematically understanding of symmetric topological quantum phases in bosonic systems. In the absence of global symmetries, gapped quantum phases are characterized by topological orders. Topological orders in 2+1D are well studied, while a systematically understanding of topological orders in 3+1D is still lacking. By studying a family of exact solvable models, we find at least some topological orders in 3+1D can be distinguished by braiding phases of loop excitations. In the presence of both global symmetries and topological orders, the interplay between them leads to new phases termed as symmetry enriched topological (SET) phases. We develop a framework to classify a large class of SET phases using tensor networks. For each tensor class, we can write down generic variational wavefunctions. We apply our method to study gapped spin liquids on the kagome lattice, which can be viewed as SET phases of on-site symmetries as well as lattice symmetries. In the absence of topological order, symmetry could protect different topological phases, which are often referred to as symmetry protected topological (SPT) phases. We present systematic constructions of tensor network wavefunctions for bosonic symmetry protected topological (SPT) phases respecting both onsite and spatial symmetries.
Synchronization in complex networks with switching topology
International Nuclear Information System (INIS)
Wang, Lei; Wang, Qing-guo
2011-01-01
This Letter investigates synchronization issues of complex dynamical networks with switching topology. By constructing a common Lyapunov function, we show that local and global synchronization for a linearly coupled network with switching topology can be evaluated by the time average of second smallest eigenvalues corresponding to the Laplacians of switching topology. This result is quite powerful and can be further used to explore various switching cases for complex dynamical networks. Numerical simulations illustrate the effectiveness of the obtained results in the end. -- Highlights: → Synchronization of complex networks with switching topology is investigated. → A common Lyapunov function is established for synchronization of switching network. → The common Lyapunov function is not necessary to monotonically decrease with time. → Synchronization is determined by the second smallest eigenvalue of its Laplacian. → Synchronization criterion can be used to investigate various switching cases.
Machine Learning Topological Invariants with Neural Networks
Zhang, Pengfei; Shen, Huitao; Zhai, Hui
2018-02-01
In this Letter we supervisedly train neural networks to distinguish different topological phases in the context of topological band insulators. After training with Hamiltonians of one-dimensional insulators with chiral symmetry, the neural network can predict their topological winding numbers with nearly 100% accuracy, even for Hamiltonians with larger winding numbers that are not included in the training data. These results show a remarkable success that the neural network can capture the global and nonlinear topological features of quantum phases from local inputs. By opening up the neural network, we confirm that the network does learn the discrete version of the winding number formula. We also make a couple of remarks regarding the role of the symmetry and the opposite effect of regularization techniques when applying machine learning to physical systems.
Spectrum-Based and Collaborative Network Topology Analysis and Visualization
Hu, Xianlin
2013-01-01
Networks are of significant importance in many application domains, such as World Wide Web and social networks, which often embed rich topological information. Since network topology captures the organization of network nodes and links, studying network topology is very important to network analysis. In this dissertation, we study networks by…
Litinski, Daniel; Kesselring, Markus S.; Eisert, Jens; von Oppen, Felix
2017-07-01
We present a scalable architecture for fault-tolerant topological quantum computation using networks of voltage-controlled Majorana Cooper pair boxes and topological color codes for error correction. Color codes have a set of transversal gates which coincides with the set of topologically protected gates in Majorana-based systems, namely, the Clifford gates. In this way, we establish color codes as providing a natural setting in which advantages offered by topological hardware can be combined with those arising from topological error-correcting software for full-fledged fault-tolerant quantum computing. We provide a complete description of our architecture, including the underlying physical ingredients. We start by showing that in topological superconductor networks, hexagonal cells can be employed to serve as physical qubits for universal quantum computation, and we present protocols for realizing topologically protected Clifford gates. These hexagonal-cell qubits allow for a direct implementation of open-boundary color codes with ancilla-free syndrome read-out and logical T gates via magic-state distillation. For concreteness, we describe how the necessary operations can be implemented using networks of Majorana Cooper pair boxes, and we give a feasibility estimate for error correction in this architecture. Our approach is motivated by nanowire-based networks of topological superconductors, but it could also be realized in alternative settings such as quantum-Hall-superconductor hybrids.
Directory of Open Access Journals (Sweden)
Daniel Litinski
2017-09-01
Full Text Available We present a scalable architecture for fault-tolerant topological quantum computation using networks of voltage-controlled Majorana Cooper pair boxes and topological color codes for error correction. Color codes have a set of transversal gates which coincides with the set of topologically protected gates in Majorana-based systems, namely, the Clifford gates. In this way, we establish color codes as providing a natural setting in which advantages offered by topological hardware can be combined with those arising from topological error-correcting software for full-fledged fault-tolerant quantum computing. We provide a complete description of our architecture, including the underlying physical ingredients. We start by showing that in topological superconductor networks, hexagonal cells can be employed to serve as physical qubits for universal quantum computation, and we present protocols for realizing topologically protected Clifford gates. These hexagonal-cell qubits allow for a direct implementation of open-boundary color codes with ancilla-free syndrome read-out and logical T gates via magic-state distillation. For concreteness, we describe how the necessary operations can be implemented using networks of Majorana Cooper pair boxes, and we give a feasibility estimate for error correction in this architecture. Our approach is motivated by nanowire-based networks of topological superconductors, but it could also be realized in alternative settings such as quantum-Hall–superconductor hybrids.
Distribution network topology identification based on synchrophasor
Directory of Open Access Journals (Sweden)
Stefania Conti
2018-03-01
Full Text Available A distribution system upgrade moving towards Smart Grid implementation is necessary to face the proliferation of distributed generators and electric vehicles, in order to satisfy the increasing demand for high quality, efficient, secure, reliable energy supply. This perspective requires taking into account system vulnerability to cyber attacks. An effective attack could destroy stored information about network structure, historical data and so on. Countermeasures and network applications could be made impracticable since most of them are based on the knowledge of network topology. Usually, the location of each link between nodes in a network is known. Therefore, the methods used for topology identification determine if a link is open or closed. When no information on the location of the network links is available, these methods become totally unfeasible. This paper presents a method to identify the network topology using only nodal measures obtained by means of phasor measurement units.
Inferring network topology from complex dynamics
International Nuclear Information System (INIS)
Shandilya, Srinivas Gorur; Timme, Marc
2011-01-01
Inferring the network topology from dynamical observations is a fundamental problem pervading research on complex systems. Here, we present a simple, direct method for inferring the structural connection topology of a network, given an observation of one collective dynamical trajectory. The general theoretical framework is applicable to arbitrary network dynamical systems described by ordinary differential equations. No interference (external driving) is required and the type of dynamics is hardly restricted in any way. In particular, the observed dynamics may be arbitrarily complex; stationary, invariant or transient; synchronous or asynchronous and chaotic or periodic. Presupposing a knowledge of the functional form of the dynamical units and of the coupling functions between them, we present an analytical solution to the inverse problem of finding the network topology from observing a time series of state variables only. Robust reconstruction is achieved in any sufficiently long generic observation of the system. We extend our method to simultaneously reconstructing both the entire network topology and all parameters appearing linear in the system's equations of motion. Reconstruction of network topology and system parameters is viable even in the presence of external noise that distorts the original dynamics substantially. The method provides a conceptually new step towards reconstructing a variety of real-world networks, including gene and protein interaction networks and neuronal circuits.
Topological Taxonomy of Water Distribution Networks
Directory of Open Access Journals (Sweden)
Carlo Giudicianni
2018-04-01
Full Text Available Water Distribution Networks (WDNs can be regarded as complex networks and modeled as graphs. In this paper, Complex Network Theory is applied to characterize the behavior of WDNs from a topological point of view, reviewing some basic metrics, exploring their fundamental properties and the relationship between them. The crucial aim is to understand and describe the topology of WDNs and their structural organization to provide a novel tool of analysis which could help to find new solutions to several arduous problems of WDNs. The aim is to understand the role of the topological structure in the WDNs functioning. The methodology is applied to 21 existing networks and 13 literature networks. The comparison highlights some topological peculiarities and the possibility to define a set of best design parameters for ex-novo WDNs that could also be used to build hypothetical benchmark networks retaining the typical structure of real WDNs. Two well-known types of network ((a square grid; and (b random graph are used for comparison, aiming at defining a possible mathematical model for WDNs. Finally, the interplay between topology and some performance requirements of WDNs is discussed.
DETECTION OF TOPOLOGICAL PATTERNS IN PROTEIN NETWORKS.
Energy Technology Data Exchange (ETDEWEB)
MASLOV,S.SNEPPEN,K.
2003-11-17
Complex networks appear in biology on many different levels: (1) All biochemical reactions taking place in a single cell constitute its metabolic network, where nodes are individual metabolites, and edges are metabolic reactions converting them to each other. (2) Virtually every one of these reactions is catalyzed by an enzyme and the specificity of this catalytic function is ensured by the key and lock principle of its physical interaction with the substrate. Often the functional enzyme is formed by several mutually interacting proteins. Thus the structure of the metabolic network is shaped by the network of physical interactions of cell's proteins with their substrates and each other. (3) The abundance and the level of activity of each of the proteins in the physical interaction network in turn is controlled by the regulatory network of the cell. Such regulatory network includes all of the multiple mechanisms in which proteins in the cell control each other including transcriptional and translational regulation, regulation of mRNA editing and its transport out of the nucleus, specific targeting of individual proteins for degradation, modification of their activity e.g. by phosphorylation/dephosphorylation or allosteric regulation, etc. To get some idea about the complexity and interconnectedness of protein-protein regulations in baker's yeast Saccharomyces Cerevisiae in Fig. 1 we show a part of the regulatory network corresponding to positive or negative regulations that regulatory proteins exert on each other. (4) On yet higher level individual cells of a multicellular organism exchange signals with each other. This gives rise to several new networks such as e.g. nervous, hormonal, and immune systems of animals. The intercellular signaling network stages the development of a multicellular organism from the fertilized egg. (5) Finally, on the grandest scale, the interactions between individual species in ecosystems determine their food webs. An
Plasma transport in mixed magnetic topologies
International Nuclear Information System (INIS)
Hegna, C.C.; Callen, J.D.
1992-12-01
A simple model is introduced to illustrate some features concerning anomalous transport associated with magnetic turbulence. For magnetic topologies that are described as bands of stochasticity separated by regions with good flux surfaces, the transport coefficients deviate significantly from those describing completely stochastic magnetic fields. It is possible to have the electron heat diffusivity exceed a runaway electron diffusion coefficient, despite the existence of widespread magnetic stochasticity. Comparing the ratios of transport coefficients is not an accurate way to determine whether anomalous plasma transport is controlled by electrostatic or electromagnetic fluctuations
On topological properties of sierpinski networks
International Nuclear Information System (INIS)
Imran, Muhammad; Sabeel-e-Hafi; Gao, Wei; Reza Farahani, Mohammad
2017-01-01
Sierpinski graphs constitute an extensively studied class of graphs of fractal nature applicable in topology, mathematics of Tower of Hanoi, computer science, and elsewhere. A large number of properties like physico-chemical properties, thermodynamic properties, chemical activity, biological activity, etc. are determined by the chemical applications of graph theory. These properties can be characterized by certain graph invariants referred to as topological indices. In QRAR/QSPR study these graph invariants has played a vital role. In this paper, we study the molecular topological properties of Sierpinski networks and derive the analytical closed formulas for the atom-bond connectivity (ABC) index, geometric-arithmetic (GA) index, and fourth and fifth version of these topological indices for Sierpinski networks denoted by S(n, k).
Routing in Networks with Random Topologies
Bambos, Nicholas
1997-01-01
We examine the problems of routing and server assignment in networks with random connectivities. In such a network the basic topology is fixed, but during each time slot and for each of tis input queues, each server (node) is either connected to or disconnected from each of its queues with some probability.
Network-topology-adaptive quantum conference protocols
International Nuclear Information System (INIS)
Zhang Sheng; Wang Jian; Tang Chao-Jing; Zhang Quan
2011-01-01
As an important application of the quantum network communication, quantum multiparty conference has made multiparty secret communication possible. Previous quantum multiparty conference schemes based on quantum data encryption are insensitive to network topology. However, the topology of the quantum network significantly affects the communication efficiency, e.g., parallel transmission in a channel with limited bandwidth. We have proposed two distinctive protocols, which work in two basic network topologies with efficiency higher than the existing ones. We first present a protocol which works in the reticulate network using Greeberger—Horne—Zeilinger states and entanglement swapping. Another protocol, based on quantum multicasting with quantum data compression, which can improve the efficiency of the network, works in the star-like network. The security of our protocols is guaranteed by quantum key distribution and one-time-pad encryption. In general, the two protocols can be applied to any quantum network where the topology can be equivalently transformed to one of the two structures we propose in our protocols. (general)
Molecular network topology and reliability for multipurpose diagnosis
Directory of Open Access Journals (Sweden)
Jalil MA
2011-10-01
Full Text Available MA Jalil1, N Moongfangklang2,3, K Innate4, S Mitatha3, J Ali5, PP Yupapin41Ibnu Sina Institute of Fundamental Science Studies, Nanotechnology Research Alliance, University of Technology Malaysia, Johor Bahru, Malaysia; 2School of Information and Communication Technology, Phayao University, Phayao, Thailand; 3Hybrid Computing Research Laboratory, Faculty of Engineering, King Mongkut's Institute of Technology Ladkrabang, Bangkok, Thailand; 4Nanoscale Science and Engineering Research Alliance, Advanced Research Center for Photonics, Faculty of Science, King Mongkut's Institute of Technology Ladkrabang, Bangkok, Thailand; 5Institute of Advanced Photonics Science, Nanotechnology Research Alliance, University of Technology Malaysia, Johor Bahru, MalaysiaAbstract: This investigation proposes the use of molecular network topology for drug delivery and diagnosis network design. Three modules of molecular network topologies, such as bus, star, and ring networks, are designed and manipulated based on a micro- and nanoring resonator system. The transportation of the trapping molecules by light in the network is described and the theoretical background is reviewed. The quality of the network is analyzed and calculated in terms of signal transmission (ie, signal to noise ratio and crosstalk effects. Results obtained show that a bus network has advantages over star and ring networks, where the use of mesh networks is possible. In application, a thin film network can be fabricated in the form of a waveguide and embedded in artificial bone, which can be connected to the required drug targets. The particular drug/nutrient can be transported to the required targets via the particular network used.Keywords: molecular network, network reliability, network topology, drug network, multi-access network
Tensor Network Wavefunctions for Topological Phases
Ware, Brayden Alexander
The combination of quantum effects and interactions in quantum many-body systems can result in exotic phases with fundamentally entangled ground state wavefunctions--topological phases. Topological phases come in two types, both of which will be studied in this thesis. In topologically ordered phases, the pattern of entanglement in the ground state wavefunction encodes the statistics of exotic emergent excitations, a universal indicator of a phase that is robust to all types of perturbations. In symmetry protected topological phases, the entanglement instead encodes a universal response of the system to symmetry defects, an indicator that is robust only to perturbations respecting the protecting symmetry. Finding and creating these phases in physical systems is a motivating challenge that tests all aspects--analytical, numerical, and experimental--of our understanding of the quantum many-body problem. Nearly three decades ago, the creation of simple ansatz wavefunctions--such as the Laughlin fractional quantum hall state, the AKLT state, and the resonating valence bond state--spurred analytical understanding of both the role of entanglement in topological physics and physical mechanisms by which it can arise. However, quantitative understanding of the relevant phase diagrams is still challenging. For this purpose, tensor networks provide a toolbox for systematically improving wavefunction ansatz while still capturing the relevant entanglement properties. In this thesis, we use the tools of entanglement and tensor networks to analyze ansatz states for several proposed new phases. In the first part, we study a featureless phase of bosons on the honeycomb lattice and argue that this phase can be topologically protected under any one of several distinct subsets of the crystalline lattice symmetries. We discuss methods of detecting such phases with entanglement and without. In the second part, we consider the problem of constructing fixed-point wavefunctions for
Topology Optimisation of Wireless Sensor Networks
Directory of Open Access Journals (Sweden)
Thike Aye Min
2016-01-01
Full Text Available Wireless sensor networks are widely used in a variety of fields including industrial environments. In case of a clustered network the location of cluster head affects the reliability of the network operation. Finding of the optimum location of the cluster head, therefore, is critical for the design of a network. This paper discusses the optimisation approach, based on the brute force algorithm, in the context of topology optimisation of a cluster structure centralised wireless sensor network. Two examples are given to verify the approach that demonstrate the implementation of the brute force algorithm to find an optimum location of the cluster head.
Optimal topologies for maximizing network transmission capacity
Chen, Zhenhao; Wu, Jiajing; Rong, Zhihai; Tse, Chi K.
2018-04-01
It has been widely demonstrated that the structure of a network is a major factor that affects its traffic dynamics. In this work, we try to identify the optimal topologies for maximizing the network transmission capacity, as well as to build a clear relationship between structural features of a network and the transmission performance in terms of traffic delivery. We propose an approach for designing optimal network topologies against traffic congestion by link rewiring and apply them on the Barabási-Albert scale-free, static scale-free and Internet Autonomous System-level networks. Furthermore, we analyze the optimized networks using complex network parameters that characterize the structure of networks, and our simulation results suggest that an optimal network for traffic transmission is more likely to have a core-periphery structure. However, assortative mixing and the rich-club phenomenon may have negative impacts on network performance. Based on the observations of the optimized networks, we propose an efficient method to improve the transmission capacity of large-scale networks.
Biological transportation networks: Modeling and simulation
Albi, Giacomo
2015-09-15
We present a model for biological network formation originally introduced by Cai and Hu [Adaptation and optimization of biological transport networks, Phys. Rev. Lett. 111 (2013) 138701]. The modeling of fluid transportation (e.g., leaf venation and angiogenesis) and ion transportation networks (e.g., neural networks) is explained in detail and basic analytical features like the gradient flow structure of the fluid transportation network model and the impact of the model parameters on the geometry and topology of network formation are analyzed. We also present a numerical finite-element based discretization scheme and discuss sample cases of network formation simulations.
Dynamical networks with topological self-organization
Zak, M.
2001-01-01
Coupled evolution of state and topology of dynamical networks is introduced. Due to the well organized tensor structure, the governing equations are presented in a canonical form, and required attractors as well as their basins can be easily implanted and controlled.
Complex brain networks: From topological communities to clustered
Indian Academy of Sciences (India)
Complex brain networks: From topological communities to clustered dynamics ... Recent research has revealed a rich and complicated network topology in the cortical connectivity of mammalian brains. ... Pramana – Journal of Physics | News.
Spectral Analysis of Rich Network Topology in Social Networks
Wu, Leting
2013-01-01
Social networks have received much attention these days. Researchers have developed different methods to study the structure and characteristics of the network topology. Our focus is on spectral analysis of the adjacency matrix of the underlying network. Recent work showed good properties in the adjacency spectral space but there are few…
Scheduling and Topology Design in Networks with Directional Antennas
2017-05-19
Scheduling and Topology Design in Networks with Directional Antennas Thomas Stahlbuhk, Nathaniel M. Jones, Brooke Shrader Lincoln Laboratory...controllers must choose which pairs of nodes should communicate in order to establish a topology over which traffic can be sent. Additionally...interacting effects of topology design and transmission scheduling in wireless networks, in particular focusing on networks where nodes are divided into
Topology Control in Aerial Multi-Beam Directional Networks
2017-04-24
Topology Control in Aerial Multi-Beam Directional Networks Brian Proulx, Nathaniel M. Jones, Jennifer Madiedo, Greg Kuperman {brian.proulx, njones...significant interference. Topology control (i.e., selecting a subset of neighbors to communicate with) is vital to reduce the interference. Good topology ...underlying challenges to topology control in multi-beam direction networks. Two topology control algorithms are developed: a centralized algorithm
Modeling the quantum to classical crossover in topologically disordered networks
International Nuclear Information System (INIS)
Schijven, P; Kohlberger, J; Blumen, A; Mülken, O
2012-01-01
We model transport in topologically disordered networks that are subjected to an environment that induces classical diffusion. The dynamics is phenomenologically described within the framework of the recently introduced quantum stochastic walk, allowing study of the crossover between coherent transport and purely classical diffusion. To study the transport efficiency, we connect our system with a source and a drain and provide a detailed analysis of their effects. We find that the coupling to the environment removes all effects of localization and quickly leads to classical transport. Furthermore, we find that on the level of the transport efficiency, the system can be well described by reducing it to a two-node network (a dimer). (paper)
Topology evolution in macromolecular networks
Kryven, I.
2014-01-01
Governed by various intermolecular forces, molecular networks tend to evolve from simple to very complex formations that have random structure. This randomness in the connectivity of the basic units can still be captured employing distributional description of the state of the system; the evolution
Topology control with IPD network creation games
International Nuclear Information System (INIS)
Scholz, Jan C; Greiner, Martin O W
2007-01-01
Network creation games couple a two-players game with the evolution of network structure. A vertex player may increase its own payoff with a change of strategy or with a modification of its edge-defined neighbourhood. By referring to the iterated prisoners dilemma (IPD) game we show that this evolutionary dynamics converges to network-Nash equilibria, where no vertex is able to improve its payoff. The resulting network structure exhibits a strong dependence on the parameter of the payoff matrix. Degree distributions and cluster coefficients are also strongly affected by the specific interactions chosen for the neighbourhood exploration. This allows network creation games to be seen as a promising artificial-social-systems approach for a distributive topology control of complex networked systems
Systemic risk on different interbank network topologies
Lenzu, Simone; Tedeschi, Gabriele
2012-09-01
In this paper we develop an interbank market with heterogeneous financial institutions that enter into lending agreements on different network structures. Credit relationships (links) evolve endogenously via a fitness mechanism based on agents' performance. By changing the agent's trust on its neighbor's performance, interbank linkages self-organize themselves into very different network architectures, ranging from random to scale-free topologies. We study which network architecture can make the financial system more resilient to random attacks and how systemic risk spreads over the network. To perturb the system, we generate a random attack via a liquidity shock. The hit bank is not automatically eliminated, but its failure is endogenously driven by its incapacity to raise liquidity in the interbank network. Our analysis shows that a random financial network can be more resilient than a scale free one in case of agents' heterogeneity.
Topological transport from a black hole
Directory of Open Access Journals (Sweden)
Dmitry Melnikov
2018-03-01
Full Text Available In this paper the low temperature zero-frequency transport in a 2+1-dimensional theory dual to a dyonic black hole is discussed. It is shown that transport exhibits topological features: the transverse electric and heat conductivities satisfy the Wiedemann–Franz law of free electrons; the direct heat conductivity is measured in units of the central charge of CFT2+1, while the direct electric conductivity vanishes; the thermoelectric conductivity is non-zero at vanishing temperature, while the O(T behavior, controlled by the Mott relation, is subleading. Provided that the entropy of the black hole, and the dual system, is non-vanishing at T=0, the observations indicate that the dyonic black hole describes a ħ→0 limit of a highly degenerate topological state, in which the black hole charge measures the density of excited non-abelian quasiparticles. The holographic description gives further evidence that non-abelian nature of quasiparticles can be determined by the low temperature behavior of the thermoelectric transport.
Fermionic topological quantum states as tensor networks
Wille, C.; Buerschaper, O.; Eisert, J.
2017-06-01
Tensor network states, and in particular projected entangled pair states, play an important role in the description of strongly correlated quantum lattice systems. They do not only serve as variational states in numerical simulation methods, but also provide a framework for classifying phases of quantum matter and capture notions of topological order in a stringent and rigorous language. The rapid development in this field for spin models and bosonic systems has not yet been mirrored by an analogous development for fermionic models. In this work, we introduce a tensor network formalism capable of capturing notions of topological order for quantum systems with fermionic components. At the heart of the formalism are axioms of fermionic matrix-product operator injectivity, stable under concatenation. Building upon that, we formulate a Grassmann number tensor network ansatz for the ground state of fermionic twisted quantum double models. A specific focus is put on the paradigmatic example of the fermionic toric code. This work shows that the program of describing topologically ordered systems using tensor networks carries over to fermionic models.
Characterizing granular networks using topological metrics
Dijksman, Joshua A.; Kovalcinova, Lenka; Ren, Jie; Behringer, Robert P.; Kramar, Miroslav; Mischaikow, Konstantin; Kondic, Lou
2018-04-01
We carry out a direct comparison of experimental and numerical realizations of the exact same granular system as it undergoes shear jamming. We adjust the numerical methods used to optimally represent the experimental settings and outcomes up to microscopic contact force dynamics. Measures presented here range from microscopic through mesoscopic to systemwide characteristics of the system. Topological properties of the mesoscopic force networks provide a key link between microscales and macroscales. We report two main findings: (1) The number of particles in the packing that have at least two contacts is a good predictor for the mechanical state of the system, regardless of strain history and packing density. All measures explored in both experiments and numerics, including stress-tensor-derived measures and contact numbers depend in a universal manner on the fraction of nonrattler particles, fNR. (2) The force network topology also tends to show this universality, yet the shape of the master curve depends much more on the details of the numerical simulations. In particular we show that adding force noise to the numerical data set can significantly alter the topological features in the data. We conclude that both fNR and topological metrics are useful measures to consider when quantifying the state of a granular system.
Topology Optimization of Active Transport Flows
DEFF Research Database (Denmark)
Andreasen, Casper Schousboe
2017-01-01
Fluid flows with particle transport are common in many industrial processes and components. The design of components for addition or removal of particles as well as mixing or stratification is of great importance in the specific processes. This work presents a methodology to apply topology....... The paper present the design and optimization of a particle separator and the important interpolation for modeling both solids, fluids and particles with a monolithic problem formulation. The interplay with the physics behind the model are discussed and the influence of parameters are demonstrated....
Characterizing the topology of probabilistic biological networks.
Todor, Andrei; Dobra, Alin; Kahveci, Tamer
2013-01-01
Biological interactions are often uncertain events, that may or may not take place with some probability. This uncertainty leads to a massive number of alternative interaction topologies for each such network. The existing studies analyze the degree distribution of biological networks by assuming that all the given interactions take place under all circumstances. This strong and often incorrect assumption can lead to misleading results. In this paper, we address this problem and develop a sound mathematical basis to characterize networks in the presence of uncertain interactions. Using our mathematical representation, we develop a method that can accurately describe the degree distribution of such networks. We also take one more step and extend our method to accurately compute the joint-degree distributions of node pairs connected by edges. The number of possible network topologies grows exponentially with the number of uncertain interactions. However, the mathematical model we develop allows us to compute these degree distributions in polynomial time in the number of interactions. Our method works quickly even for entire protein-protein interaction (PPI) networks. It also helps us find an adequate mathematical model using MLE. We perform a comparative study of node-degree and joint-degree distributions in two types of biological networks: the classical deterministic networks and the more flexible probabilistic networks. Our results confirm that power-law and log-normal models best describe degree distributions for both probabilistic and deterministic networks. Moreover, the inverse correlation of degrees of neighboring nodes shows that, in probabilistic networks, nodes with large number of interactions prefer to interact with those with small number of interactions more frequently than expected. We also show that probabilistic networks are more robust for node-degree distribution computation than the deterministic ones. all the data sets used, the software
Topology dependent epidemic spreading velocity in weighted networks
International Nuclear Information System (INIS)
Duan, Wei; Qiu, Xiaogang; Quax, Rick; Lees, Michael; Sloot, Peter M A
2014-01-01
Many diffusive processes occur on structured networks with weighted links, such as disease spread by airplane transport or information diffusion in social networks or blogs. Understanding the impact of weight-connectivity correlations on epidemic spreading in weighted networks is crucial to support decision-making on disease control and other diffusive processes. However, a real understanding of epidemic spreading velocity in weighted networks is still lacking. Here we conduct a numerical study of the velocity of a Reed–Frost epidemic spreading process in various weighted network topologies as a function of the correlations between edge weights and node degrees. We find that a positive weight-connectivity correlation leads to a faster epidemic spreading compared to an unweighted network. In contrast, we find that both uncorrelated and negatively correlated weight distributions lead to slower spreading processes. In the case of positive weight-connectivity correlations, the acceleration of spreading velocity is weak when the heterogeneity of weight distribution increases. (paper)
Optimization-based topology identification of complex networks
International Nuclear Information System (INIS)
Tang Sheng-Xue; Chen Li; He Yi-Gang
2011-01-01
In many cases, the topological structures of a complex network are unknown or uncertain, and it is of significance to identify the exact topological structure. An optimization-based method of identifying the topological structure of a complex network is proposed in this paper. Identification of the exact network topological structure is converted into a minimal optimization problem by using the estimated network. Then, an improved quantum-behaved particle swarm optimization algorithm is used to solve the optimization problem. Compared with the previous adaptive synchronization-based method, the proposed method is simple and effective and is particularly valid to identify the topological structure of synchronization complex networks. In some cases where the states of a complex network are only partially observable, the exact topological structure of a network can also be identified by using the proposed method. Finally, numerical simulations are provided to show the effectiveness of the proposed method. (general)
Novel topological descriptors for analyzing biological networks
Directory of Open Access Journals (Sweden)
Varmuza Kurt K
2010-06-01
Full Text Available Abstract Background Topological descriptors, other graph measures, and in a broader sense, graph-theoretical methods, have been proven as powerful tools to perform biological network analysis. However, the majority of the developed descriptors and graph-theoretical methods does not have the ability to take vertex- and edge-labels into account, e.g., atom- and bond-types when considering molecular graphs. Indeed, this feature is important to characterize biological networks more meaningfully instead of only considering pure topological information. Results In this paper, we put the emphasis on analyzing a special type of biological networks, namely bio-chemical structures. First, we derive entropic measures to calculate the information content of vertex- and edge-labeled graphs and investigate some useful properties thereof. Second, we apply the mentioned measures combined with other well-known descriptors to supervised machine learning methods for predicting Ames mutagenicity. Moreover, we investigate the influence of our topological descriptors - measures for only unlabeled vs. measures for labeled graphs - on the prediction performance of the underlying graph classification problem. Conclusions Our study demonstrates that the application of entropic measures to molecules representing graphs is useful to characterize such structures meaningfully. For instance, we have found that if one extends the measures for determining the structural information content of unlabeled graphs to labeled graphs, the uniqueness of the resulting indices is higher. Because measures to structurally characterize labeled graphs are clearly underrepresented so far, the further development of such methods might be valuable and fruitful for solving problems within biological network analysis.
Mechanized extraction of topology anti-patterns in wireless networks
Woehrle, M.; Bakhshi, R.; Mousavi, M.R.; Derrick, J.; Gnesi, S.; Latella, D.; Treharne, H.
2012-01-01
Exhaustive and mechanized formal verification of wireless networks is hampered by the huge number of possible topologies and the large size of the actual networks. However, the generic communication structure in such networks allows for reducing the root causes of faults to faulty (sub-)topologies,
Shuffle-Exchange Mesh Topology for Networks-on-Chip
Sabbaghi-Nadooshan, Reza; Modarressi, Mehdi; Sarbazi-Azad, Hamid
2010-01-01
The mesh topology has been used in a variety of interconnection network applications especially for NoC designs due to its desirable properties in VLSI implementation. In this chapter, we proposed a new topology based on the shuffle-exchange topology, the 2D
Functional Topology of Evolving Urban Drainage Networks
Yang, Soohyun; Paik, Kyungrock; McGrath, Gavan S.; Urich, Christian; Krueger, Elisabeth; Kumar, Praveen; Rao, P. Suresh C.
2017-11-01
We investigated the scaling and topology of engineered urban drainage networks (UDNs) in two cities, and further examined UDN evolution over decades. UDN scaling was analyzed using two power law scaling characteristics widely employed for river networks: (1) Hack's law of length (L)-area (A) [L∝Ah] and (2) exceedance probability distribution of upstream contributing area (δ) [P>(A≥δ>)˜aδ-ɛ]. For the smallest UDNs ((A≥δ>) plots for river networks are abruptly truncated, those for UDNs display exponential tempering [P>(A≥δ>)=aδ-ɛexp>(-cδ>)]. The tempering parameter c decreases as the UDNs grow, implying that the distribution evolves in time to resemble those for river networks. However, the power law exponent ɛ for large UDNs tends to be greater than the range reported for river networks. Differences in generative processes and engineering design constraints contribute to observed differences in the evolution of UDNs and river networks, including subnet heterogeneity and nonrandom branching.
Effects of network topology on wealth distributions
International Nuclear Information System (INIS)
Garlaschelli, Diego; Loffredo, Maria I
2008-01-01
We focus on the problem of how the wealth is distributed among the units of a networked economic system. We first review the empirical results documenting that in many economies the wealth distribution is described by a combination of the log-normal and power-law behaviours. We then focus on the Bouchaud-Mezard model of wealth exchange, describing an economy of interacting agents connected through an exchange network. We report analytical and numerical results showing that the system self-organizes towards a stationary state whose associated wealth distribution depends crucially on the underlying interaction network. In particular, we show that if the network displays a homogeneous density of links, the wealth distribution displays either the log-normal or the power-law form. This means that the first-order topological properties alone (such as the scale-free property) are not enough to explain the emergence of the empirically observed mixed form of the wealth distribution. In order to reproduce this nontrivial pattern, the network has to be heterogeneously divided into regions with a variable density of links. We show new results detailing how this effect is related to the higher-order correlation properties of the underlying network. In particular, we analyse assortativity by degree and the pairwise wealth correlations, and discuss the effects that these properties have on each other
Characterizing Topology of Probabilistic Biological Networks.
Todor, Andrei; Dobra, Alin; Kahveci, Tamer
2013-09-06
Biological interactions are often uncertain events, that may or may not take place with some probability. Existing studies analyze the degree distribution of biological networks by assuming that all the given interactions take place under all circumstances. This strong and often incorrect assumption can lead to misleading results. Here, we address this problem and develop a sound mathematical basis to characterize networks in the presence of uncertain interactions. We develop a method that accurately describes the degree distribution of such networks. We also extend our method to accurately compute the joint degree distributions of node pairs connected by edges. The number of possible network topologies grows exponentially with the number of uncertain interactions. However, the mathematical model we develop allows us to compute these degree distributions in polynomial time in the number of interactions. It also helps us find an adequate mathematical model using maximum likelihood estimation. Our results demonstrate that power law and log-normal models best describe degree distributions for probabilistic networks. The inverse correlation of degrees of neighboring nodes shows that, in probabilistic networks, nodes with large number of interactions prefer to interact with those with small number of interactions more frequently than expected.
Discovering the Network Topology: An Efficient Approach for SDN
Directory of Open Access Journals (Sweden)
Leonardo OCHOA-ADAY
2016-11-01
Full Text Available Network topology is a physical description of the overall resources in the network. Collecting this information using efficient mechanisms becomes a critical task for important network functions such as routing, network management, quality of service (QoS, among many others. Recent technologies like Software-Defined Networks (SDN have emerged as promising approaches for managing the next generation networks. In order to ensure a proficient topology discovery service in SDN, we propose a simple agents-based mechanism. This mechanism improves the overall efficiency of the topology discovery process. In this paper, an algorithm for a novel Topology Discovery Protocol (SD-TDP is described. This protocol will be implemented in each switch through a software agent. Thus, this approach will provide a distributed solution to solve the problem of network topology discovery in a more simple and efficient way.
Acoustic topological insulator and robust one-way sound transport
He, Cheng; Ni, Xu; Ge, Hao; Sun, Xiao-Chen; Chen, Yan-Bin; Lu, Ming-Hui; Liu, Xiao-Ping; Chen, Yan-Feng
2016-12-01
Topological design of materials enables topological symmetries and facilitates unique backscattering-immune wave transport. In airborne acoustics, however, the intrinsic longitudinal nature of sound polarization makes the use of the conventional spin-orbital interaction mechanism impossible for achieving band inversion. The topological gauge flux is then typically introduced with a moving background in theoretical models. Its practical implementation is a serious challenge, though, due to inherent dynamic instabilities and noise. Here we realize the inversion of acoustic energy bands at a double Dirac cone and provide an experimental demonstration of an acoustic topological insulator. By manipulating the hopping interaction of neighbouring ’atoms’ in this new topological material, we successfully demonstrate the acoustic quantum spin Hall effect, characterized by robust pseudospin-dependent one-way edge sound transport. Our results are promising for the exploration of new routes for experimentally studying topological phenomena and related applications, for example, sound-noise reduction.
Inferring epidemic network topology from surveillance data.
Directory of Open Access Journals (Sweden)
Xiang Wan
Full Text Available The transmission of infectious diseases can be affected by many or even hidden factors, making it difficult to accurately predict when and where outbreaks may emerge. One approach at the moment is to develop and deploy surveillance systems in an effort to detect outbreaks as timely as possible. This enables policy makers to modify and implement strategies for the control of the transmission. The accumulated surveillance data including temporal, spatial, clinical, and demographic information, can provide valuable information with which to infer the underlying epidemic networks. Such networks can be quite informative and insightful as they characterize how infectious diseases transmit from one location to another. The aim of this work is to develop a computational model that allows inferences to be made regarding epidemic network topology in heterogeneous populations. We apply our model on the surveillance data from the 2009 H1N1 pandemic in Hong Kong. The inferred epidemic network displays significant effect on the propagation of infectious diseases.
M.J. van der Leij (Marco)
2003-01-01
textabstractIn a circular city model, I consider network design and pricing decisions for a single fast transport connection that faces competition from a slower but better accessible transport mode. To access the fast transport network individuals have to make complementary trips by slow mode. This
Topology Identification of General Dynamical Network with Distributed Time Delays
International Nuclear Information System (INIS)
Zhao-Yan, Wu; Xin-Chu, Fu
2009-01-01
General dynamical networks with distributed time delays are studied. The topology of the networks are viewed as unknown parameters, which need to be identified. Some auxiliary systems (also called the network estimators) are designed to achieve this goal. Both linear feedback control and adaptive strategy are applied in designing these network estimators. Based on linear matrix inequalities and the Lyapunov function method, the sufficient condition for the achievement of topology identification is obtained. This method can also better monitor the switching topology of dynamical networks. Illustrative examples are provided to show the effectiveness of this method. (general)
Bulk and edge spin transport in topological magnon insulators
Rückriegel, A.; Brataas, A.; Duine, R.A.
2018-01-01
We investigate the spin transport properties of a topological magnon insulator, a magnetic insulator characterized by topologically nontrivial bulk magnon bands and protected magnon edge modes located in the bulk band gaps. Employing the Landau-Lifshitz-Gilbert phenomenology, we calculate the spin
The topology and dynamics of complex networks
Dezso, Zoltan
We start with a brief introduction about the topological properties of real networks. Most real networks are scale-free, being characterized by a power-law degree distribution. The scale-free nature of real networks leads to unexpected properties such as the vanishing epidemic threshold. Traditional methods aiming to reduce the spreading rate of viruses cannot succeed on eradicating the epidemic on a scale-free network. We demonstrate that policies that discriminate between the nodes, curing mostly the highly connected nodes, can restore a finite epidemic threshold and potentially eradicate the virus. We find that the more biased a policy is towards the hubs, the more chance it has to bring the epidemic threshold above the virus' spreading rate. We continue by studying a large Web portal as a model system for a rapidly evolving network. We find that the visitation pattern of a news document decays as a power law, in contrast with the exponential prediction provided by simple models of site visitation. This is rooted in the inhomogeneous nature of the browsing pattern characterizing individual users: the time interval between consecutive visits by the same user to the site follows a power law distribution, in contrast with the exponential expected for Poisson processes. We show that the exponent characterizing the individual user's browsing patterns determines the power-law decay in a document's visitation. Finally, we turn our attention to biological networks and demonstrate quantitatively that protein complexes in the yeast, Saccharomyces cerevisiae, are comprised of a core in which subunits are highly coexpressed, display the same deletion phenotype (essential or non-essential) and share identical functional classification and cellular localization. The results allow us to define the deletion phenotype and cellular task of most known complexes, and to identify with high confidence the biochemical role of hundreds of proteins with yet unassigned functionality.
Employing Deceptive Dynamic Network Topology Through Software-Defined Networking
2014-03-01
actions. From [64] . . . . . 37 xi THIS PAGE INTENTIONALLY LEFT BLANK xii List of Acronyms and Abbreviations ACL Access Control List API Application...can be extremely useful in topology mapping through various latency-based geolocation methods [35], [36], [37]. PING 1 7 2 . 2 0 . 5 . 2 ( 1 7 2 . 2 0...defined northbound Applica- tion Programming Interfaces ( APIs ). Figure 3.1: Software-Defined Network Architecture. From [8] 29 3.3 SDN OpenFlow
Chiral topological phases from artificial neural networks
Kaubruegger, Raphael; Pastori, Lorenzo; Budich, Jan Carl
2018-05-01
Motivated by recent progress in applying techniques from the field of artificial neural networks (ANNs) to quantum many-body physics, we investigate to what extent the flexibility of ANNs can be used to efficiently study systems that host chiral topological phases such as fractional quantum Hall (FQH) phases. With benchmark examples, we demonstrate that training ANNs of restricted Boltzmann machine type in the framework of variational Monte Carlo can numerically solve FQH problems to good approximation. Furthermore, we show by explicit construction how n -body correlations can be kept at an exact level with ANN wave functions exhibiting polynomial scaling with power n in system size. Using this construction, we analytically represent the paradigmatic Laughlin wave function as an ANN state.
Hypergraph topological quantities for tagged social networks
Zlatić, Vinko; Ghoshal, Gourab; Caldarelli, Guido
2009-09-01
Recent years have witnessed the emergence of a new class of social networks, which require us to move beyond previously employed representations of complex graph structures. A notable example is that of the folksonomy, an online process where users collaboratively employ tags to resources to impart structure to an otherwise undifferentiated database. In a recent paper, we proposed a mathematical model that represents these structures as tripartite hypergraphs and defined basic topological quantities of interest. In this paper, we extend our model by defining additional quantities such as edge distributions, vertex similarity and correlations as well as clustering. We then empirically measure these quantities on two real life folksonomies, the popular online photo sharing site Flickr and the bookmarking site CiteULike. We find that these systems share similar qualitative features with the majority of complex networks that have been previously studied. We propose that the quantities and methodology described here can be used as a standard tool in measuring the structure of tagged networks.
Network topology of an experimental futures exchange
Wang, S. C.; Tseng, J. J.; Tai, C. C.; Lai, K. H.; Wu, W. S.; Chen, S. H.; Li, S. P.
2008-03-01
Many systems of different nature exhibit scale free behaviors. Economic systems with power law distribution in the wealth are one of the examples. To better understand the working behind the complexity, we undertook an experiment recording the interactions between market participants. A Web server was setup to administer the exchange of futures contracts whose liquidation prices were coupled to event outcomes. After free registration, participants started trading to compete for the money prizes upon maturity of the futures contracts at the end of the experiment. The evolving `cash' flow network was reconstructed from the transactions between players. We show that the network topology is hierarchical, disassortative and small-world with a power law exponent of 1.02±0.09 in the degree distribution after an exponential decay correction. The small-world property emerged early in the experiment while the number of participants was still small. We also show power law-like distributions of the net incomes and inter-transaction time intervals. Big winners and losers are associated with high degree, high betweenness centrality, low clustering coefficient and low degree-correlation. We identify communities in the network as groups of the like-minded. The distribution of the community sizes is shown to be power-law distributed with an exponent of 1.19±0.16.
Bulk and edge spin transport in topological magnon insulators
Rückriegel, Andreas; Brataas, Arne; Duine, Rembert A.
2018-02-01
We investigate the spin transport properties of a topological magnon insulator, a magnetic insulator characterized by topologically nontrivial bulk magnon bands and protected magnon edge modes located in the bulk band gaps. Employing the Landau-Lifshitz-Gilbert phenomenology, we calculate the spin current driven through a normal metal |topological magnon insulator |normal metal heterostructure by a spin accumulation imbalance between the metals, with and without random lattice defects. We show that bulk and edge transport are characterized by different length scales. This results in a characteristic system size where the magnon transport crosses over from being bulk dominated for small systems to edge dominated for larger systems. These findings are generic and relevant for topological transport in systems of nonconserved bosons.
Topological quantization of energy transport in micromechanical and nanomechanical lattices
Chien, Chih-Chun; Velizhanin, Kirill A.; Dubi, Yonatan; Ilic, B. Robert; Zwolak, Michael
2018-03-01
Topological effects typically discussed in the context of quantum physics are emerging as one of the central paradigms of physics. Here, we demonstrate the role of topology in energy transport through dimerized micro- and nanomechanical lattices in the classical regime, i.e., essentially "masses and springs." We show that the thermal conductance factorizes into topological and nontopological components. The former takes on three discrete values and arises due to the appearance of edge modes that prevent good contact between the heat reservoirs and the bulk, giving a length-independent reduction of the conductance. In essence, energy input at the boundary mostly stays there, an effect robust against disorder and nonlinearity. These results bridge two seemingly disconnected disciplines of physics, namely topology and thermal transport, and suggest ways to engineer thermal contacts, opening a direction to explore the ramifications of topological properties on nanoscale technology.
Robust quantum network architectures and topologies for entanglement distribution
Das, Siddhartha; Khatri, Sumeet; Dowling, Jonathan P.
2018-01-01
Entanglement distribution is a prerequisite for several important quantum information processing and computing tasks, such as quantum teleportation, quantum key distribution, and distributed quantum computing. In this work, we focus on two-dimensional quantum networks based on optical quantum technologies using dual-rail photonic qubits for the building of a fail-safe quantum internet. We lay out a quantum network architecture for entanglement distribution between distant parties using a Bravais lattice topology, with the technological constraint that quantum repeaters equipped with quantum memories are not easily accessible. We provide a robust protocol for simultaneous entanglement distribution between two distant groups of parties on this network. We also discuss a memory-based quantum network architecture that can be implemented on networks with an arbitrary topology. We examine networks with bow-tie lattice and Archimedean lattice topologies and use percolation theory to quantify the robustness of the networks. In particular, we provide figures of merit on the loss parameter of the optical medium that depend only on the topology of the network and quantify the robustness of the network against intermittent photon loss and intermittent failure of nodes. These figures of merit can be used to compare the robustness of different network topologies in order to determine the best topology in a given real-world scenario, which is critical in the realization of the quantum internet.
Topological resilience in non-normal networked systems
Asllani, Malbor; Carletti, Timoteo
2018-04-01
The network of interactions in complex systems strongly influences their resilience and the system capability to resist external perturbations or structural damages and to promptly recover thereafter. The phenomenon manifests itself in different domains, e.g., parasitic species invasion in ecosystems or cascade failures in human-made networks. Understanding the topological features of the networks that affect the resilience phenomenon remains a challenging goal for the design of robust complex systems. We hereby introduce the concept of non-normal networks, namely networks whose adjacency matrices are non-normal, propose a generating model, and show that such a feature can drastically change the global dynamics through an amplification of the system response to exogenous disturbances and eventually impact the system resilience. This early stage transient period can induce the formation of inhomogeneous patterns, even in systems involving a single diffusing agent, providing thus a new kind of dynamical instability complementary to the Turing one. We provide, first, an illustrative application of this result to ecology by proposing a mechanism to mute the Allee effect and, second, we propose a model of virus spreading in a population of commuters moving using a non-normal transport network, the London Tube.
Topology Design for Directional Range Extension Networks with Antenna Blockage
2017-03-19
this is equivalent to the Hamiltonian Path Problem, which is NP- hard . More work on computationally efficient topology formation and maintenance... formation and maintenance of low-degree air topologies. 1 I. INTRODUCTION Tactical military networks both on land and at sea often have restricted...constraints on the number of antenna beams that a pod can support, a string topology formation and maintenance algorithm may be the best design choice
Traffic Management for Next Generation Transport Networks
DEFF Research Database (Denmark)
Yu, Hao
required by the next generation transport network to provide Quality-of-Service (QoS) guaranteed video services. Augmenting network capacity and upgrading network nodes indicate long deployment period, replacement of equipment and thus significant cost to the network service providers. This challenge may...... slacken the steps of some network operators towards providing IPTV services. In this dissertation, the topology-based hierarchical scheduling scheme is proposed to tackle the problem addressed. The scheme simplifies the deployment process by placing an intelligent switch with centralized traffic...... management functions at the edge of the network, scheduling traffic on behalf of the other nodes. The topology-based hierarchical scheduling scheme is able to provide outstanding flow isolation due to its centralized scheduling ability, which is essential for providing IPTV services. In order to reduce...
Characterization of Static/Dynamic Topological Routing For Grid Networks
DEFF Research Database (Denmark)
Gutierrez Lopez, Jose Manuel; Cuevas, Ruben; Riaz, M. Tahir
2009-01-01
Grid or 2D Mesh structures are becoming one of the most attractive network topologies to study. They can be used in many different fields raging from future broadband networks to multiprocessors structures. In addition, the high requirements of future services and applications demand more flexible...... and adaptive networks. Topological routing in grid networks is a simple and efficient alternative to traditional routing techniques, e.g. routing tables, and the paper extends this kind of routing providing a "Dynamic" attribute. This new property attempts to improve the overall network performance for future...
SIMULATION OF WIRELESS SENSOR NETWORK WITH HYBRID TOPOLOGY
Directory of Open Access Journals (Sweden)
J. Jaslin Deva Gifty
2016-03-01
Full Text Available The design of low rate Wireless Personal Area Network (WPAN by IEEE 802.15.4 standard has been developed to support lower data rates and low power consuming application. Zigbee Wireless Sensor Network (WSN works on the network and application layer in IEEE 802.15.4. Zigbee network can be configured in star, tree or mesh topology. The performance varies from topology to topology. The performance parameters such as network lifetime, energy consumption, throughput, delay in data delivery and sensor field coverage area varies depending on the network topology. In this paper, designing of hybrid topology by using two possible combinations such as star-tree and star-mesh is simulated to verify the communication reliability. This approach is to combine all the benefits of two network model. The parameters such as jitter, delay and throughput are measured for these scenarios. Further, MAC parameters impact such as beacon order (BO and super frame order (SO for low power consumption and high channel utilization, has been analysed for star, tree and mesh topology in beacon disable mode and beacon enable mode by varying CBR traffic loads.
ELeaRNT: Evolutionary Learning of Rich Neural Network Topologies
National Research Council Canada - National Science Library
Matteucci, Matteo
2006-01-01
In this paper we present ELeaRNT an evolutionary strategy which evolves rich neural network topologies in order to find an optimal domain specific non linear function approximator with a good generalization performance...
A Technique for Presenting a Deceptive Dynamic Network Topology
2013-03-01
more complicated network topologies in our experiments. We used a Watts- Strogatz [35] model to generate a synthetic topology for experimentation due...generated Watts- Strogatz model except for the intelligent router and the web server. The actual router used does not impact the results of our experiment...library for the Python [43] programming language. NetworkX provides two features useful for this experiment. It was used to generate a Watts- Strogatz model
Tight Network Topology Dependent Bounds on Rounds of Communication
Chattopadhyay, Arkadev; Langberg, Michael; Li, Shi; Rudra, Atri
2016-01-01
We prove tight network topology dependent bounds on the round complexity of computing well studied $k$-party functions such as set disjointness and element distinctness. Unlike the usual case in the CONGEST model in distributed computing, we fix the function and then vary the underlying network topology. This complements the recent such results on total communication that have received some attention. We also present some applications to distributed graph computation problems. Our main contri...
Energy efficient topology control algorithm for wireless mesh networks
CSIR Research Space (South Africa)
Aron, FO
2008-08-01
Full Text Available The control of the topology of a network makes it possible for the network nodes to reduce their power of transmission while ensuring that network connectivity is preserved. This paper explains the need for energy consumption control in Wireless...
Throughput Analysis of Large Wireless Networks with Regular Topologies
Directory of Open Access Journals (Sweden)
Hong Kezhu
2007-01-01
Full Text Available The throughput of large wireless networks with regular topologies is analyzed under two medium-access control schemes: synchronous array method (SAM and slotted ALOHA. The regular topologies considered are square, hexagon, and triangle. Both nonfading channels and Rayleigh fading channels are examined. Furthermore, both omnidirectional antennas and directional antennas are considered. Our analysis shows that the SAM leads to a much higher network throughput than the slotted ALOHA. The network throughput in this paper is measured in either bits-hops per second per Hertz per node or bits-meters per second per Hertz per node. The exact connection between the two measures is shown for each topology. With these two fundamental units, the network throughput shown in this paper can serve as a reliable benchmark for future works on network throughput of large networks.
Throughput Analysis of Large Wireless Networks with Regular Topologies
Directory of Open Access Journals (Sweden)
Kezhu Hong
2007-04-01
Full Text Available The throughput of large wireless networks with regular topologies is analyzed under two medium-access control schemes: synchronous array method (SAM and slotted ALOHA. The regular topologies considered are square, hexagon, and triangle. Both nonfading channels and Rayleigh fading channels are examined. Furthermore, both omnidirectional antennas and directional antennas are considered. Our analysis shows that the SAM leads to a much higher network throughput than the slotted ALOHA. The network throughput in this paper is measured in either bits-hops per second per Hertz per node or bits-meters per second per Hertz per node. The exact connection between the two measures is shown for each topology. With these two fundamental units, the network throughput shown in this paper can serve as a reliable benchmark for future works on network throughput of large networks.
Default cascades in complex networks: topology and systemic risk.
Roukny, Tarik; Bersini, Hugues; Pirotte, Hugues; Caldarelli, Guido; Battiston, Stefano
2013-09-26
The recent crisis has brought to the fore a crucial question that remains still open: what would be the optimal architecture of financial systems? We investigate the stability of several benchmark topologies in a simple default cascading dynamics in bank networks. We analyze the interplay of several crucial drivers, i.e., network topology, banks' capital ratios, market illiquidity, and random vs targeted shocks. We find that, in general, topology matters only--but substantially--when the market is illiquid. No single topology is always superior to others. In particular, scale-free networks can be both more robust and more fragile than homogeneous architectures. This finding has important policy implications. We also apply our methodology to a comprehensive dataset of an interbank market from 1999 to 2011.
Topological phononic insulator with robust pseudospin-dependent transport
Xia, Bai-Zhan; Liu, Ting-Ting; Huang, Guo-Liang; Dai, Hong-Qing; Jiao, Jun-Rui; Zang, Xian-Guo; Yu, De-Jie; Zheng, Sheng-Jie; Liu, Jian
2017-09-01
Topological phononic states, which facilitate unique acoustic transport around defects and disorders, have significantly revolutionized our scientific cognition of acoustic systems. Here, by introducing a zone folding mechanism, we realize the topological phase transition in a double Dirac cone of the rotatable triangular phononic crystal with C3 v symmetry. We then investigate the distinct topological edge states on two types of interfaces of our phononic insulators. The first one is a zigzag interface which simultaneously possesses a symmetric mode and an antisymmetric mode. Hybridization of the two modes leads to a robust pseudospin-dependent one-way propagation. The second one is a linear interface with a symmetric mode or an antisymmetric mode. The type of mode is dependent on the topological phase transition of the phononic insulators. Based on the rotatability of triangular phononic crystals, we consider several complicated contours defined by the topological zigzag interfaces. Along these contours, the acoustic waves can unimpededly transmit without backscattering. Our research develops a route for the exploration of the topological phenomena in experiments and provides an excellent framework for freely steering the acoustic backscattering-immune propagation within topological phononic structures.
Phase coherent transport in hybrid superconductor-topological insulator devices
Finck, Aaron
2015-03-01
Heterostructures of superconductors and topological insulators are predicted to host unusual zero energy bound states known as Majorana fermions, which can robustly store and process quantum information. Here, I will discuss our studies of such heterostructures through phase-coherent transport, which can act as a unique probe of Majorana fermions. We have extensively explored topological insulator Josephson junctions through SQUID and single-junction diffraction patterns, whose unusual behavior give evidence for low-energy Andreev bound states. In topological insulator devices with closely spaced normal and superconducting leads, we observe prominent Fabry-Perot oscillations, signifying gate-tunable, quasi-ballistic transport that can elegantly interact with Andreev reflection. Superconducting disks deposited on the surface of a topological insulator generate Aharonov-Bohm-like oscillations, giving evidence for unusual states lying near the interface between the superconductor and topological insulator surface. Our results point the way towards sophisticated interferometers that can detect and read out the state of Majorana fermions in topological systems. This work was done in collaboration with Cihan Kurter, Yew San Hor, and Dale Van Harlingen. We acknowledge funding from Microsoft Project Q.
Topology-function conservation in protein-protein interaction networks.
Davis, Darren; Yaveroğlu, Ömer Nebil; Malod-Dognin, Noël; Stojmirovic, Aleksandar; Pržulj, Nataša
2015-05-15
Proteins underlay the functioning of a cell and the wiring of proteins in protein-protein interaction network (PIN) relates to their biological functions. Proteins with similar wiring in the PIN (topology around them) have been shown to have similar functions. This property has been successfully exploited for predicting protein functions. Topological similarity is also used to guide network alignment algorithms that find similarly wired proteins between PINs of different species; these similarities are used to transfer annotation across PINs, e.g. from model organisms to human. To refine these functional predictions and annotation transfers, we need to gain insight into the variability of the topology-function relationships. For example, a function may be significantly associated with specific topologies, while another function may be weakly associated with several different topologies. Also, the topology-function relationships may differ between different species. To improve our understanding of topology-function relationships and of their conservation among species, we develop a statistical framework that is built upon canonical correlation analysis. Using the graphlet degrees to represent the wiring around proteins in PINs and gene ontology (GO) annotations to describe their functions, our framework: (i) characterizes statistically significant topology-function relationships in a given species, and (ii) uncovers the functions that have conserved topology in PINs of different species, which we term topologically orthologous functions. We apply our framework to PINs of yeast and human, identifying seven biological process and two cellular component GO terms to be topologically orthologous for the two organisms. © The Author 2015. Published by Oxford University Press.
Inferring topologies of complex networks with hidden variables.
Wu, Xiaoqun; Wang, Weihan; Zheng, Wei Xing
2012-10-01
Network topology plays a crucial role in determining a network's intrinsic dynamics and function, thus understanding and modeling the topology of a complex network will lead to greater knowledge of its evolutionary mechanisms and to a better understanding of its behaviors. In the past few years, topology identification of complex networks has received increasing interest and wide attention. Many approaches have been developed for this purpose, including synchronization-based identification, information-theoretic methods, and intelligent optimization algorithms. However, inferring interaction patterns from observed dynamical time series is still challenging, especially in the absence of knowledge of nodal dynamics and in the presence of system noise. The purpose of this work is to present a simple and efficient approach to inferring the topologies of such complex networks. The proposed approach is called "piecewise partial Granger causality." It measures the cause-effect connections of nonlinear time series influenced by hidden variables. One commonly used testing network, two regular networks with a few additional links, and small-world networks are used to evaluate the performance and illustrate the influence of network parameters on the proposed approach. Application to experimental data further demonstrates the validity and robustness of our method.
Topology influences performance in the associative memory neural networks
International Nuclear Information System (INIS)
Lu Jianquan; He Juan; Cao Jinde; Gao Zhiqiang
2006-01-01
To explore how topology affects performance within Hopfield-type associative memory neural networks (AMNNs), we studied the computational performance of the neural networks with regular lattice, random, small-world, and scale-free structures. In this Letter, we found that the memory performance of neural networks obtained through asynchronous updating from 'larger' nodes to 'smaller' nodes are better than asynchronous updating in random order, especially for the scale-free topology. The computational performance of associative memory neural networks linked by the above-mentioned network topologies with the same amounts of nodes (neurons) and edges (synapses) were studied respectively. Along with topologies becoming more random and less locally disordered, we will see that the performance of associative memory neural network is quite improved. By comparing, we show that the regular lattice and random network form two extremes in terms of patterns stability and retrievability. For a network, its patterns stability and retrievability can be largely enhanced by adding a random component or some shortcuts to its structured component. According to the conclusions of this Letter, we can design the associative memory neural networks with high performance and minimal interconnect requirements
Topologically determined optimal stochastic resonance responses of spatially embedded networks
International Nuclear Information System (INIS)
Gosak, Marko; Marhl, Marko; Korosak, Dean
2011-01-01
We have analyzed the stochastic resonance phenomenon on spatial networks of bistable and excitable oscillators, which are connected according to their location and the amplitude of external forcing. By smoothly altering the network topology from a scale-free (SF) network with dominating long-range connections to a network where principally only adjacent oscillators are connected, we reveal that besides an optimal noise intensity, there is also a most favorable interaction topology at which the best correlation between the response of the network and the imposed weak external forcing is achieved. For various distributions of the amplitudes of external forcing, the optimal topology is always found in the intermediate regime between the highly heterogeneous SF network and the strong geometric regime. Our findings thus indicate that a suitable number of hubs and with that an optimal ratio between short- and long-range connections is necessary in order to obtain the best global response of a spatial network. Furthermore, we link the existence of the optimal interaction topology to a critical point indicating the transition from a long-range interactions-dominated network to a more lattice-like network structure.
Evaluation of Topology-Aware Broadcast Algorithms for Dragonfly Networks
Energy Technology Data Exchange (ETDEWEB)
Dorier, Matthieu; Mubarak, Misbah; Ross, Rob; Li, Jianping Kelvin; Carothers, Christopher D.; Ma, Kwan-Liu
2016-09-12
Two-tiered direct network topologies such as Dragonflies have been proposed for future post-petascale and exascale machines, since they provide a high-radix, low-diameter, fast interconnection network. Such topologies call for redesigning MPI collective communication algorithms in order to attain the best performance. Yet as increasingly more applications share a machine, it is not clear how these topology-aware algorithms will react to interference with concurrent jobs accessing the same network. In this paper, we study three topology-aware broadcast algorithms, including one designed by ourselves. We evaluate their performance through event-driven simulation for small- and large-sized broadcasts (in terms of both data size and number of processes). We study the effect of different routing mechanisms on the topology-aware collective algorithms, as well as their sensitivity to network contention with other jobs. Our results show that while topology-aware algorithms dramatically reduce link utilization, their advantage in terms of latency is more limited.
Context-Based Topology Control for Wireless Mesh Networks
Directory of Open Access Journals (Sweden)
Pragasen Mudali
2016-01-01
Full Text Available Topology Control has been shown to provide several benefits to wireless ad hoc and mesh networks. However these benefits have largely been demonstrated using simulation-based evaluations. In this paper, we demonstrate the negative impact that the PlainTC Topology Control prototype has on topology stability. This instability is found to be caused by the large number of transceiver power adjustments undertaken by the prototype. A context-based solution is offered to reduce the number of transceiver power adjustments undertaken without sacrificing the cumulative transceiver power savings and spatial reuse advantages gained from employing Topology Control in an infrastructure wireless mesh network. We propose the context-based PlainTC+ prototype and show that incorporating context information in the transceiver power adjustment process significantly reduces topology instability. In addition, improvements to network performance arising from the improved topology stability are also observed. Future plans to add real-time context-awareness to PlainTC+ will have the scheme being prototyped in a software-defined wireless mesh network test-bed being planned.
Deciphering the imprint of topology on nonlinear dynamical network stability
International Nuclear Information System (INIS)
Nitzbon, J; Schultz, P; Heitzig, J; Kurths, J; Hellmann, F
2017-01-01
Coupled oscillator networks show complex interrelations between topological characteristics of the network and the nonlinear stability of single nodes with respect to large but realistic perturbations. We extend previous results on these relations by incorporating sampling-based measures of the transient behaviour of the system, its survivability, as well as its asymptotic behaviour, its basin stability. By combining basin stability and survivability we uncover novel, previously unknown asymptotic states with solitary, desynchronized oscillators which are rotating with a frequency different from their natural one. They occur almost exclusively after perturbations at nodes with specific topological properties. More generally we confirm and significantly refine the results on the distinguished role tree-shaped appendices play for nonlinear stability. We find a topological classification scheme for nodes located in such appendices, that exactly separates them according to their stability properties, thus establishing a strong link between topology and dynamics. Hence, the results can be used for the identification of vulnerable nodes in power grids or other coupled oscillator networks. From this classification we can derive general design principles for resilient power grids. We find that striving for homogeneous network topologies facilitates a better performance in terms of nonlinear dynamical network stability. While the employed second-order Kuramoto-like model is parametrised to be representative for power grids, we expect these insights to transfer to other critical infrastructure systems or complex network dynamics appearing in various other fields. (paper)
Analysis of Network Topologies Underlying Ethylene Growth Response Kinetics.
Prescott, Aaron M; McCollough, Forest W; Eldreth, Bryan L; Binder, Brad M; Abel, Steven M
2016-01-01
Most models for ethylene signaling involve a linear pathway. However, measurements of seedling growth kinetics when ethylene is applied and removed have resulted in more complex network models that include coherent feedforward, negative feedback, and positive feedback motifs. The dynamical responses of the proposed networks have not been explored in a quantitative manner. Here, we explore (i) whether any of the proposed models are capable of producing growth-response behaviors consistent with experimental observations and (ii) what mechanistic roles various parts of the network topologies play in ethylene signaling. To address this, we used computational methods to explore two general network topologies: The first contains a coherent feedforward loop that inhibits growth and a negative feedback from growth onto itself (CFF/NFB). In the second, ethylene promotes the cleavage of EIN2, with the product of the cleavage inhibiting growth and promoting the production of EIN2 through a positive feedback loop (PFB). Since few network parameters for ethylene signaling are known in detail, we used an evolutionary algorithm to explore sets of parameters that produce behaviors similar to experimental growth response kinetics of both wildtype and mutant seedlings. We generated a library of parameter sets by independently running the evolutionary algorithm many times. Both network topologies produce behavior consistent with experimental observations, and analysis of the parameter sets allows us to identify important network interactions and parameter constraints. We additionally screened these parameter sets for growth recovery in the presence of sub-saturating ethylene doses, which is an experimentally-observed property that emerges in some of the evolved parameter sets. Finally, we probed simplified networks maintaining key features of the CFF/NFB and PFB topologies. From this, we verified observations drawn from the larger networks about mechanisms underlying ethylene
Analysis of Network Topologies Underlying Ethylene Growth Response Kinetics
Directory of Open Access Journals (Sweden)
Aaron M. Prescott
2016-08-01
Full Text Available Most models for ethylene signaling involve a linear pathway. However, measurements of seedling growth kinetics when ethylene is applied and removed have resulted in more complex network models that include coherent feedforward, negative feedback, and positive feedback motifs. However, the dynamical responses of the proposed networks have not been explored in a quantitative manner. Here, we explore (i whether any of the proposed models are capable of producing growth-response behaviors consistent with experimental observations and (ii what mechanistic roles various parts of the network topologies play in ethylene signaling. To address this, we used computational methods to explore two general network topologies: The first contains a coherent feedforward loop that inhibits growth and a negative feedback from growth onto itself (CFF/NFB. In the second, ethylene promotes the cleavage of EIN2, with the product of the cleavage inhibiting growth and promoting the production of EIN2 through a positive feedback loop (PFB. Since few network parameters for ethylene signaling are known in detail, we used an evolutionary algorithm to explore sets of parameters that produce behaviors similar to experimental growth response kinetics of both wildtype and mutant seedlings. We generated a library of parameter sets by independently running the evolutionary algorithm many times. Both network topologies produce behavior consistent with experimental observations and analysis of the parameter sets allows us to identify important network interactions and parameter constraints. We additionally screened these parameter sets for growth recovery in the presence of sub-saturating ethylene doses, which is an experimentally-observed property that emerges in some of the evolved parameter sets. Finally, we probed simplified networks maintaining key features of the CFF/NFB and PFB topologies. From this, we verified observations drawn from the larger networks about mechanisms
Nanoscale electron transport at the surface of a topological insulator
Bauer, Sebastian; Bobisch, Christian A.
2016-04-01
The use of three-dimensional topological insulators for disruptive technologies critically depends on the dissipationless transport of electrons at the surface, because of the suppression of backscattering at defects. However, in real devices, defects are unavoidable and scattering at angles other than 180° is allowed for such materials. Until now, this has been studied indirectly by bulk measurements and by the analysis of the local density of states in close vicinity to defect sites. Here, we directly measure the nanoscale voltage drop caused by the scattering at step edges, which occurs if a lateral current flows along a three-dimensional topological insulator. The experiments were performed using scanning tunnelling potentiometry for thin Bi2Se3 films. So far, the observed voltage drops are small because of large contributions of the bulk to the electronic transport. However, for the use of ideal topological insulating thin films in devices, these contributions would play a significant role.
Stabilization Strategies of Supply Networks with Stochastic Switched Topology
Directory of Open Access Journals (Sweden)
Shukai Li
2013-01-01
Full Text Available In this paper, a dynamical supply networks model with stochastic switched topology is presented, in which the stochastic switched topology is dependent on a continuous time Markov process. The goal is to design the state-feedback control strategies to stabilize the dynamical supply networks. Based on Lyapunov stability theory, sufficient conditions for the existence of state feedback control strategies are given in terms of matrix inequalities, which ensure the robust stability of the supply networks at the stationary states and a prescribed H∞ disturbance attenuation level with respect to the uncertain demand. A numerical example is given to illustrate the effectiveness of the proposed method.
Small Worlds in the Tree Topologies of Wireless Sensor Networks
DEFF Research Database (Denmark)
Qiao, Li; Lingguo, Cui; Baihai, Zhang
2010-01-01
In this study, the characteristics of small worlds are investigated in the context of the tree topologies of wireless sensor networks. Tree topologies, which construct spatial graphs with larger characteristic path lengths than random graphs and small clustering coefficients, are ubiquitous...... in wireless sensor networks. Suffering from the link rewiring or the link addition, the characteristic path length of the tree topology reduces rapidly and the clustering coefficient increases greatly. The variety of characteristic path length influences the time synchronization characteristics of wireless...... sensor networks greatly. With the increase of the link rewiring or the link addition probability, the time synchronization error decreases drastically. Two novel protocols named LEACH-SW and TREEPSI-SW are proposed to improve the performances of the sensor networks, in which the small world...
Connected Dominating Set Based Topology Control in Wireless Sensor Networks
He, Jing
2012-01-01
Wireless Sensor Networks (WSNs) are now widely used for monitoring and controlling of systems where human intervention is not desirable or possible. Connected Dominating Sets (CDSs) based topology control in WSNs is one kind of hierarchical method to ensure sufficient coverage while reducing redundant connections in a relatively crowded network.…
Design and implementation of a topology control scheme for wireless mesh networks
CSIR Research Space (South Africa)
Mudali, P
2009-09-01
Full Text Available The Wireless Mesh Network (WMN) backbone is usually comprised of stationary nodes but the transient nature of wireless links results in changing network topologies. Topology Control (TC) aims to preserve network connectivity in ad hoc and mesh...
Quantum transport in topological semimetals under magnetic fields
Lu, Hai-Zhou; Shen, Shun-Qing
2017-06-01
Topological semimetals are three-dimensional topological states of matter, in which the conduction and valence bands touch at a finite number of points, i.e., the Weyl nodes. Topological semimetals host paired monopoles and antimonopoles of Berry curvature at the Weyl nodes and topologically protected Fermi arcs at certain surfaces. We review our recent works on quantum transport in topological semimetals, according to the strength of the magnetic field. At weak magnetic fields, there are competitions between the positive magnetoresistivity induced by the weak anti-localization effect and negative magnetoresistivity related to the nontrivial Berry curvature. We propose a fitting formula for the magnetoconductivity of the weak anti-localization. We expect that the weak localization may be induced by inter-valley effects and interaction effect, and occur in double-Weyl semimetals. For the negative magnetoresistance induced by the nontrivial Berry curvature in topological semimetals, we show the dependence of the negative magnetoresistance on the carrier density. At strong magnetic fields, specifically, in the quantum limit, the magnetoconductivity depends on the type and range of the scattering potential of disorder. The high-field positive magnetoconductivity may not be a compelling signature of the chiral anomaly. For long-range Gaussian scattering potential and half filling, the magnetoconductivity can be linear in the quantum limit. A minimal conductivity is found at the Weyl nodes although the density of states vanishes there.
Topological dynamics of vortex-line networks in hexagonal manganites
Xue, Fei; Wang, Nan; Wang, Xueyun; Ji, Yanzhou; Cheong, Sang-Wook; Chen, Long-Qing
2018-01-01
The two-dimensional X Y model is the first well-studied system with topological point defects. On the other hand, although topological line defects are common in three-dimensional systems, the evolution mechanism of line defects is not fully understood. The six domains in hexagonal manganites converge to vortex lines in three dimensions. Using phase-field simulations, we predicted that during the domain coarsening process, the vortex-line network undergoes three types of basic topological changes, i.e., vortex-line loop shrinking, coalescence, and splitting. It is shown that the vortex-antivortex annihilation controls the scaling dynamics.
A Review of the Topologies Used in Smart Water Meter Networks: A Wireless Sensor Network Application
Marais, Jaco; Malekian, Reza; Ye, Ning; Wang, Ruchuan
2016-01-01
This paper presents several proposed and existing smart utility meter systems as well as their communication networks to identify the challenges of creating scalable smart water meter networks. Network simulations are performed on 3 network topologies (star, tree, and mesh) to determine their suitability for smart water meter networks. The simulations found that once a number of nodes threshold is exceeded the network’s delay increases dramatically regardless of implemented topology. This thr...
Analysis on the urban street network of Korea: Connections between topology and meta-information
Lee, Byoung-Hwa; Jung, Woo-Sung
2018-05-01
Cities consist of infrastructure that enables transportation, which can be considered as topology in abstract terms. Once cities are physically organized in terms of infrastructure, people interact with each other to form the values, which can be regarded as the meta-information of the cities. The topology and meta-information coevolve together as the cities are developed. In this study, we investigate the relationship between the topology and meta-information for a street network, which has aspects of both a complex network and planar graph. The degree of organization of a street structure determines the efficiency and productivity of the city in that they act as blood vessels to transport people, goods, and information. We analyze the topological aspect of a street network using centralities including the betweenness, closeness, straightness, and information. We classify the cities into several groups that share common meta-information based on the centrality, indicating that the topological factor of the street structure is closely related to meta-information through coevolution. We also obtain the coevolution in the planned cities using the regularity. Another footprint is the relation between the street segment length and the population, which shows the sublinear scaling.
Topology design and performance analysis of an integrated communication network
Li, V. O. K.; Lam, Y. F.; Hou, T. C.; Yuen, J. H.
1985-01-01
A research study on the topology design and performance analysis for the Space Station Information System (SSIS) network is conducted. It is begun with a survey of existing research efforts in network topology design. Then a new approach for topology design is presented. It uses an efficient algorithm to generate candidate network designs (consisting of subsets of the set of all network components) in increasing order of their total costs, and checks each design to see if it forms an acceptable network. This technique gives the true cost-optimal network, and is particularly useful when the network has many constraints and not too many components. The algorithm for generating subsets is described in detail, and various aspects of the overall design procedure are discussed. Two more efficient versions of this algorithm (applicable in specific situations) are also given. Next, two important aspects of network performance analysis: network reliability and message delays are discussed. A new model is introduced to study the reliability of a network with dependent failures. For message delays, a collection of formulas from existing research results is given to compute or estimate the delays of messages in a communication network without making the independence assumption. The design algorithm coded in PASCAL is included as an appendix.
Spatial analysis of bus transport networks using network theory
Shanmukhappa, Tanuja; Ho, Ivan Wang-Hei; Tse, Chi Kong
2018-07-01
In this paper, we analyze the bus transport network (BTN) structure considering the spatial embedding of the network for three cities, namely, Hong Kong (HK), London (LD), and Bengaluru (BL). We propose a novel approach called supernode graph structuring for modeling the bus transport network. A static demand estimation procedure is proposed to assign the node weights by considering the points of interests (POIs) and the population distribution in the city over various localized zones. In addition, the end-to-end delay is proposed as a parameter to measure the topological efficiency of the bus networks instead of the shortest distance measure used in previous works. With the aid of supernode graph representation, important network parameters are analyzed for the directed, weighted and geo-referenced bus transport networks. It is observed that the supernode concept has significant advantage in analyzing the inherent topological behavior. For instance, the scale-free and small-world behavior becomes evident with supernode representation as compared to conventional or regular graph representation for the Hong Kong network. Significant improvement in clustering, reduction in path length, and increase in centrality values are observed in all the three networks with supernode representation. The correlation between topologically central nodes and the geographically central nodes reveals the interesting fact that the proposed static demand estimation method for assigning node weights aids in better identifying the geographically significant nodes in the network. The impact of these geographically significant nodes on the local traffic behavior is demonstrated by simulation using the SUMO (Simulation of Urban Mobility) tool which is also supported by real-world empirical data, and our results indicate that the traffic speed around a particular bus stop can reach a jammed state from a free flow state due to the presence of these geographically important nodes. A comparison
Robustness Analysis of Real Network Topologies Under Multiple Failure Scenarios
DEFF Research Database (Denmark)
Manzano, M.; Marzo, J. L.; Calle, E.
2012-01-01
on topological characteristics. Recently approaches also consider the services supported by such networks. In this paper we carry out a robustness analysis of five real backbone telecommunication networks under defined multiple failure scenarios, taking into account the consequences of the loss of established......Nowadays the ubiquity of telecommunication networks, which underpin and fulfill key aspects of modern day living, is taken for granted. Significant large-scale failures have occurred in the last years affecting telecommunication networks. Traditionally, network robustness analysis has been focused...... connections. Results show which networks are more robust in response to a specific type of failure....
Robust network topologies for generating switch-like cellular responses.
Directory of Open Access Journals (Sweden)
Najaf A Shah
2011-06-01
Full Text Available Signaling networks that convert graded stimuli into binary, all-or-none cellular responses are critical in processes ranging from cell-cycle control to lineage commitment. To exhaustively enumerate topologies that exhibit this switch-like behavior, we simulated all possible two- and three-component networks on random parameter sets, and assessed the resulting response profiles for both steepness (ultrasensitivity and extent of memory (bistability. Simulations were used to study purely enzymatic networks, purely transcriptional networks, and hybrid enzymatic/transcriptional networks, and the topologies in each class were rank ordered by parametric robustness (i.e., the percentage of applied parameter sets exhibiting ultrasensitivity or bistability. Results reveal that the distribution of network robustness is highly skewed, with the most robust topologies clustering into a small number of motifs. Hybrid networks are the most robust in generating ultrasensitivity (up to 28% and bistability (up to 18%; strikingly, a purely transcriptional framework is the most fragile in generating either ultrasensitive (up to 3% or bistable (up to 1% responses. The disparity in robustness among the network classes is due in part to zero-order ultrasensitivity, an enzyme-specific phenomenon, which repeatedly emerges as a particularly robust mechanism for generating nonlinearity and can act as a building block for switch-like responses. We also highlight experimentally studied examples of topologies enabling switching behavior, in both native and synthetic systems, that rank highly in our simulations. This unbiased approach for identifying topologies capable of a given response may be useful in discovering new natural motifs and in designing robust synthetic gene networks.
Topology for efficient information dissemination in ad-hoc networking
Jennings, E.; Okino, C. M.
2002-01-01
In this paper, we explore the information dissemination problem in ad-hoc wirless networks. First, we analyze the probability of successful broadcast, assuming: the nodes are uniformly distributed, the available area has a lower bould relative to the total number of nodes, and there is zero knowledge of the overall topology of the network. By showing that the probability of such events is small, we are motivated to extract good graph topologies to minimize the overall transmissions. Three algorithms are used to generate topologies of the network with guaranteed connectivity. These are the minimum radius graph, the relative neighborhood graph and the minimum spanning tree. Our simulation shows that the relative neighborhood graph has certain good graph properties, which makes it suitable for efficient information dissemination.
Network topology of olivine-basalt partial melts
Skemer, Philip; Chaney, Molly M.; Emmerich, Adrienne L.; Miller, Kevin J.; Zhu, Wen-lu
2017-07-01
The microstructural relationship between melt and solid grains in partially molten rocks influences many physical properties, including permeability, rheology, electrical conductivity and seismic wave speeds. In this study, the connectivity of melt networks in the olivine-basalt system is explored using a systematic survey of 3-D X-ray microtomographic data. Experimentally synthesized samples with 2 and 5 vol.% melt are analysed as a series of melt tubules intersecting at nodes. Each node is characterized by a coordination number (CN), which is the number of melt tubules that intersect at that location. Statistically representative volumes are described by coordination number distributions (CND). Polyhedral grains can be packed in many configurations yielding different CNDs, however widely accepted theory predicts that systems with small dihedral angles, such as olivine-basalt, should exhibit a predominant CN of four. In this study, melt objects are identified with CN = 2-8, however more than 50 per cent are CN = 4, providing experimental verification of this theoretical prediction. A conceptual model that considers the role of heterogeneity in local grain size and melt fraction is proposed to explain the formation of nodes with CN ≠ 4. Correctly identifying the melt network topology is essential to understanding the relationship between permeability and porosity, and hence the transport properties of partial molten mantle rocks.
Topology-induced critical current enhancement in Josephson networks
International Nuclear Information System (INIS)
Silvestrini, P.; Russo, R.; Corato, V.; Ruggiero, B.; Granata, C.; Rombetto, S.; Russo, M.; Cirillo, M.; Trombettoni, A.; Sodano, P.
2007-01-01
We investigate the properties of Josephson junction networks with inhomogeneous architecture. The networks are shaped as 'square comb' planar lattices on which Josephson junctions link superconducting islands arranged in the plane to generate the pertinent topology. Compared to the behavior of reference linear arrays, the temperature dependencies of the Josephson currents of the branches of the network exhibit relevant differences. The observed phenomena evidence new and surprising behavior of superconducting Josephson arrays
Topology-induced critical current enhancement in Josephson networks
Energy Technology Data Exchange (ETDEWEB)
Silvestrini, P. [Dipartimento d' Ingegneria dell' Informazione, Seconda Universita di Napoli, Aversa (Italy); Istituto di Cibernetica ' E. Caianiello' del CNR, Pozzuoli (Italy)], E-mail: p.silvestrini@cib.na.cnr.it; Russo, R. [Istituto di Cibernetica ' E. Caianiello' del CNR, Pozzuoli (Italy); Corato, V. [Dipartimento d' Ingegneria dell' Informazione, Seconda Universita di Napoli, Aversa (Italy); Ruggiero, B.; Granata, C.; Rombetto, S.; Russo, M. [Istituto di Cibernetica ' E. Caianiello' del CNR, Pozzuoli (Italy); Cirillo, M. [Dipartimento di Fisica and INFM, Universita di Roma ' Tor Vergata' , 00173 Roma (Italy); Trombettoni, A. [International School for Advanced Studies and Sezione INFN, Via Beirut 2/4, 34104 Trieste (Italy); Sodano, P. [International School for Advanced Studies and Sezione INFN, Via Beirut 2/4, 34104 Trieste (Italy); Dipartimento di Fisica, Universita di Perugia, 06123 Perugia, and Sezione INFN, Perugia (Italy); Progetto Lagrange, Fondazione C.R.T. e Fondazione I.S.I., Dipartimento di Fisica, Politecnico di Torino, Corso Duca degli Abruzzi 24, 10124 Torino (Italy)
2007-10-29
We investigate the properties of Josephson junction networks with inhomogeneous architecture. The networks are shaped as 'square comb' planar lattices on which Josephson junctions link superconducting islands arranged in the plane to generate the pertinent topology. Compared to the behavior of reference linear arrays, the temperature dependencies of the Josephson currents of the branches of the network exhibit relevant differences. The observed phenomena evidence new and surprising behavior of superconducting Josephson arrays.
Influence of network topology on the swelling of polyelectrolyte nanogels
Rizzi, Leandro G.; Levin, Yan
2016-01-01
It is well-known that the swelling behavior of ionic nanogels depends on their cross-link density, however it is unclear how different topologies should affect the response of the polyelectrolyte network. Here we perform Monte Carlo simulations to obtain the equilibrium properties of ionic nanogels as a function of salt concentration $C_s$ and the fraction $f$ of ionizable groups in a polyelectrolyte network formed by cross-links of functionality $z$. Our results indicate that the network wit...
Data center networks topologies, architectures and fault-tolerance characteristics
Liu, Yang; Veeraraghavan, Malathi; Lin, Dong; Hamdi, Mounir
2013-01-01
This SpringerBrief presents a survey of data center network designs and topologies and compares several properties in order to highlight their advantages and disadvantages. The brief also explores several routing protocols designed for these topologies and compares the basic algorithms to establish connections, the techniques used to gain better performance, and the mechanisms for fault-tolerance. Readers will be equipped to understand how current research on data center networks enables the design of future architectures that can improve performance and dependability of data centers. This con
Modeling and dynamical topology properties of VANET based on complex networks theory
Energy Technology Data Exchange (ETDEWEB)
Zhang, Hong; Li, Jie, E-mail: prof.li@foxmail.com [School of Civil Engineering and Mechanics, Huazhong University of Science and Technology, Wuhan, 430074 (China)
2015-01-15
Vehicular Ad hoc Network (VANET) is a special subset of multi-hop Mobile Ad hoc Networks in which vehicles can not only communicate with each other but also with the fixed equipments along the roads through wireless interfaces. Recently, it has been discovered that essential systems in real world share similar properties. When they are regarded as networks, among which the dynamic topology structure of VANET system is an important issue. Many real world networks are actually growing with preferential attachment like Internet, transportation system and telephone network. Those phenomena have brought great possibility in finding a strategy to calibrate and control the topology parameters which can help find VANET topology change regulation to relieve traffic jam, prevent traffic accident and improve traffic safety. VANET is a typical complex network which has its basic characteristics. In this paper, we focus on the macroscopic Vehicle-to-Infrastructure (V2I) and Vehicle-to-Vehicle (V2V) inter-vehicle communication network with complex network theory. In particular, this paper is the first one to propose a method analyzing the topological structure and performance of VANET and present the communications in VANET from a new perspective. Accordingly, we propose degree distribution, clustering coefficient and the short path length of complex network to implement our strategy by numerical example and simulation. All the results demonstrate that VANET shows small world network features and is characterized by a truncated scale-free degree distribution with power-law degree distribution. The average path length of the network is simulated numerically, which indicates that the network shows small-world property and is rarely affected by the randomness. What’s more, we carry out extensive simulations of information propagation and mathematically prove the power law property when γ > 2. The results of this study provide useful information for VANET optimization from a
Electronic transport in bismuth selenide in the topological insulator regime
Kim, Dohun
The 3D topological insulators (TIs) have an insulating bulk but spin-momentum coupled metallic surface states stemming from band inversion due to strong spin-orbit interaction, whose existence is guaranteed by the topology of the band structure of the insulator. While the STI surface state has been studied spectroscopically by e.g. photoemission and scanned probes, transport experiments have failed to demonstrate clear signature of the STI due to high level of bulk conduction. In this thesis, I present experimental results on the transport properties of TI material Bi2Se3 in the absence of bulk conduction (TI regime), achieved by applying novel p-type doping methods. Field effect transistors consisting of thin (thickness: 5-17 nm) Bi2Se3 are fabricated by mechanical exfoliation of single crystals, and a combination of conventional dielectric (300 nm thick SiO2) and electrochemical or chemical gating methods are used to move the Fermi energy through the surface Dirac point inside bulk band gap, revealing the ambipolar gapless nature of transport in the Bi2Se3 surface states. The minimum conductivity of the topological surface state is understood within the self-consistent theory of Dirac electrons in the presence of charged impurities. The intrinsic finite-temperature resistivity of the topological surface state due to electron-acoustic phonon scattering is measured to be 60 times larger than that of graphene largely due to the smaller Fermi and sound velocities in Bi2Se 3, which will have implications for topological electronic devices operating at room temperature. Along with semi-classical Boltzmann transport, I also discuss 2D weak anti-localization (WAL) behavior of the topological surface states. By investigating gate-tuned WAL behavior in thin (5-17 nm) TI films, I show that WAL in the TI regime is extraordinarily sensitive to the hybridization induced quantum mechanical tunneling between top and bottom topological surfaces, and interplay of phase coherence
Topological Embedding Feature Based Resource Allocation in Network Virtualization
Directory of Open Access Journals (Sweden)
Hongyan Cui
2014-01-01
Full Text Available Virtualization provides a powerful way to run multiple virtual networks on a shared substrate network, which needs accurate and efficient mathematical models. Virtual network embedding is a challenge in network virtualization. In this paper, considering the degree of convergence when mapping a virtual network onto substrate network, we propose a new embedding algorithm based on topology mapping convergence-degree. Convergence-degree means the adjacent degree of virtual network’s nodes when they are mapped onto a substrate network. The contributions of our method are as below. Firstly, we map virtual nodes onto the substrate nodes with the maximum convergence-degree. The simulation results show that our proposed algorithm largely enhances the network utilization efficiency and decreases the complexity of the embedding problem. Secondly, we define the load balance rate to reflect the load balance of substrate links. The simulation results show our proposed algorithm achieves better load balance. Finally, based on the feature of star topology, we further improve our embedding algorithm and make it suitable for application in the star topology. The test result shows it gets better performance than previous works.
Fermi arc mediated entropy transport in topological semimetals
McCormick, Timothy M.; Watzman, Sarah J.; Heremans, Joseph P.; Trivedi, Nandini
2018-05-01
The low-energy excitations of topological Weyl semimetals are composed of linearly dispersing Weyl fermions that act as monopoles of Berry curvature in the bulk momentum space. Furthermore, on the surface there exist topologically protected Fermi arcs at the projections of these Weyl points. We propose a pathway for entropy transport involving Fermi arcs on one surface connecting to Fermi arcs on the other surface via the bulk Weyl monopoles. We present results for the temperature and magnetic field dependence of the magnetothermal conductance of this conveyor belt channel. The circulating currents result in a net entropy transport without any net charge transport. We provide results for the Fermi arc mediated magnetothermal conductivity in the low-field semiclassical limit as well as in the high-field ultraquantum limit, where only chiral Landau levels are involved. Our work provides a proposed signature of Fermi arc mediated magnetothermal transport and sets the stage for utilizing and manipulating the topological Fermi arcs in thermal applications.
Topology of the Erasmus student mobility network
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.
Optimal urban networks via mass transportation
Buttazzo, Giuseppe; Stepanov, Eugene; Solimini, Sergio
2009-01-01
Recently much attention has been devoted to the optimization of transportation networks in a given geographic area. One assumes the distributions of population and of services/workplaces (i.e. the network's sources and sinks) are known, as well as the costs of movement with/without the network, and the cost of constructing/maintaining it. Both the long-term optimization and the short-term, "who goes where" optimization are considered. These models can also be adapted for the optimization of other types of networks, such as telecommunications, pipeline or drainage networks. In the monograph we study the most general problem settings, namely, when neither the shape nor even the topology of the network to be constructed is known a priori.
Topological data analysis of contagion maps for examining spreading processes on networks.
Taylor, Dane; Klimm, Florian; Harrington, Heather A; Kramár, Miroslav; Mischaikow, Konstantin; Porter, Mason A; Mucha, Peter J
2015-07-21
Social and biological contagions are influenced by the spatial embeddedness of networks. Historically, many epidemics spread as a wave across part of the Earth's surface; however, in modern contagions long-range edges-for example, due to airline transportation or communication media-allow clusters of a contagion to appear in distant locations. Here we study the spread of contagions on networks through a methodology grounded in topological data analysis and nonlinear dimension reduction. We construct 'contagion maps' that use multiple contagions on a network to map the nodes as a point cloud. By analysing the topology, geometry and dimensionality of manifold structure in such point clouds, we reveal insights to aid in the modelling, forecast and control of spreading processes. Our approach highlights contagion maps also as a viable tool for inferring low-dimensional structure in networks.
Topological data analysis of contagion maps for examining spreading processes on networks
Taylor, Dane; Klimm, Florian; Harrington, Heather A.; Kramár, Miroslav; Mischaikow, Konstantin; Porter, Mason A.; Mucha, Peter J.
2015-07-01
Social and biological contagions are influenced by the spatial embeddedness of networks. Historically, many epidemics spread as a wave across part of the Earth's surface; however, in modern contagions long-range edges--for example, due to airline transportation or communication media--allow clusters of a contagion to appear in distant locations. Here we study the spread of contagions on networks through a methodology grounded in topological data analysis and nonlinear dimension reduction. We construct `contagion maps' that use multiple contagions on a network to map the nodes as a point cloud. By analysing the topology, geometry and dimensionality of manifold structure in such point clouds, we reveal insights to aid in the modelling, forecast and control of spreading processes. Our approach highlights contagion maps also as a viable tool for inferring low-dimensional structure in networks.
Topological data analysis of contagion maps for examining spreading processes on networks
Taylor, Dane; Klimm, Florian; Harrington, Heather A.; Kramá r, Miroslav; Mischaikow, Konstantin; Porter, Mason A.; Mucha, Peter J.
2015-01-01
Social and biological contagions are influenced by the spatial embeddedness of networks. Historically, many epidemics spread as a wave across part of the Earth's surface; however, in modern contagions long-range edges - for example, due to airline transportation or communication media - allow clusters of a contagion to appear in distant locations. Here we study the spread of contagions on networks through a methodology grounded in topological data analysis and nonlinear dimension reduction. We construct 'contagion maps' that use multiple contagions on a network to map the nodes as a point cloud. By analysing the topology, geometry and dimensionality of manifold structure in such point clouds, we reveal insights to aid in the modelling, forecast and control of spreading processes. Our approach highlights contagion maps also as a viable tool for inferring low-dimensional structure in networks.
Topological data analysis of contagion maps for examining spreading processes on networks
Taylor, Dane
2015-07-21
Social and biological contagions are influenced by the spatial embeddedness of networks. Historically, many epidemics spread as a wave across part of the Earth\\'s surface; however, in modern contagions long-range edges - for example, due to airline transportation or communication media - allow clusters of a contagion to appear in distant locations. Here we study the spread of contagions on networks through a methodology grounded in topological data analysis and nonlinear dimension reduction. We construct \\'contagion maps\\' that use multiple contagions on a network to map the nodes as a point cloud. By analysing the topology, geometry and dimensionality of manifold structure in such point clouds, we reveal insights to aid in the modelling, forecast and control of spreading processes. Our approach highlights contagion maps also as a viable tool for inferring low-dimensional structure in networks.
Discriminative topological features reveal biological network mechanisms
Directory of Open Access Journals (Sweden)
Levovitz Chaya
2004-11-01
Full Text Available Abstract Background Recent genomic and bioinformatic advances have motivated the development of numerous network models intending to describe graphs of biological, technological, and sociological origin. In most cases the success of a model has been evaluated by how well it reproduces a few key features of the real-world data, such as degree distributions, mean geodesic lengths, and clustering coefficients. Often pairs of models can reproduce these features with indistinguishable fidelity despite being generated by vastly different mechanisms. In such cases, these few target features are insufficient to distinguish which of the different models best describes real world networks of interest; moreover, it is not clear a priori that any of the presently-existing algorithms for network generation offers a predictive description of the networks inspiring them. Results We present a method to assess systematically which of a set of proposed network generation algorithms gives the most accurate description of a given biological network. To derive discriminative classifiers, we construct a mapping from the set of all graphs to a high-dimensional (in principle infinite-dimensional "word space". This map defines an input space for classification schemes which allow us to state unambiguously which models are most descriptive of a given network of interest. Our training sets include networks generated from 17 models either drawn from the literature or introduced in this work. We show that different duplication-mutation schemes best describe the E. coli genetic network, the S. cerevisiae protein interaction network, and the C. elegans neuronal network, out of a set of network models including a linear preferential attachment model and a small-world model. Conclusions Our method is a first step towards systematizing network models and assessing their predictability, and we anticipate its usefulness for a number of communities.
Towards Optimal Transport Networks
Directory of Open Access Journals (Sweden)
Erik P. Vargo
2010-08-01
Full Text Available Our ultimate goal is to design transportation net- works whose dynamic performance metrics (e.g. pas- senger throughput, passenger delay, and insensitivity to weather disturbances are optimized. Here the fo- cus is on optimizing static features of the network that are known to directly aﬀect the network dynamics. First, we present simulation results which support a connection between maximizing the ﬁrst non-trivial eigenvalue of a network's Laplacian and superior air- port network performance. Then, we explore the ef- fectiveness of a tabu search heuristic for optimizing this metric by comparing experimental results to the- oretical upper bounds. We also consider generating upper bounds on a network's algebraic connectivity via the solution of semideﬁnite programming (SDP relaxations. A modiﬁcation of an existing subgraph extraction algorithm is implemented to explore the underlying regional structures in the U.S. airport net- work, with the hope that the resulting localized struc- tures can be optimized independently and reconnected via a "backbone" network to achieve superior network performance.
Early-warning signals of topological collapse in interbank networks
Squartini, Tiziano; Van Lelyveld, Iman; Garlaschelli, Diego
2013-01-01
The financial crisis clearly illustrated the importance of characterizing the level of 'systemic' risk associated with an entire credit network, rather than with single institutions. However, the interplay between financial distress and topological changes is still poorly understood. Here we analyze
Analysis of Degree 5 Chordal Rings for Network Topologies
DEFF Research Database (Denmark)
Riaz, M. Tahir; Pedersen, Jens Myrup; Bujnowski, Sławomir
2011-01-01
This paper presents an analysis of degree 5 chordal rings, from a network topology point of view. The chordal rings are mainly evaluated with respect to average distance and diameter. We derive approximation expressions for the related ideal graphs, and show that these matches the real chordal...
Impact of network topology on synchrony of oscillatory power grids
Energy Technology Data Exchange (ETDEWEB)
Rohden, Martin; Sorge, Andreas; Witthaut, Dirk [Network Dynamics, Max Planck Institute for Dynamics and Self-Organization (MPIDS), 37077 Göttingen (Germany); Timme, Marc [Network Dynamics, Max Planck Institute for Dynamics and Self-Organization (MPIDS), 37077 Göttingen (Germany); Faculty of Physics, Georg August Universität Göttingen, Göttingen (Germany)
2014-03-15
Replacing conventional power sources by renewable sources in current power grids drastically alters their structure and functionality. In particular, power generation in the resulting grid will be far more decentralized, with a distinctly different topology. Here, we analyze the impact of grid topologies on spontaneous synchronization, considering regular, random, and small-world topologies and focusing on the influence of decentralization. We model the consumers and sources of the power grid as second order oscillators. First, we analyze the global dynamics of the simplest non-trivial (two-node) network that exhibit a synchronous (normal operation) state, a limit cycle (power outage), and coexistence of both. Second, we estimate stability thresholds for the collective dynamics of small network motifs, in particular, star-like networks and regular grid motifs. For larger networks, we numerically investigate decentralization scenarios finding that decentralization itself may support power grids in exhibiting a stable state for lower transmission line capacities. Decentralization may thus be beneficial for power grids, regardless of the details of their resulting topology. Regular grids show a specific sharper transition not found for random or small-world grids.
Topological properties of random wireless networks
Indian Academy of Sciences (India)
Wireless networks in which the node locations are random are best modelled as random geometric graphs (RGGs). In addition to their extensive application in the modelling of wireless networks, RGGs ﬁnd many new applications and are being studied in their own right. In this paper we ﬁrst provide a brief introduction to the ...
Network topology and interbank credit risk
International Nuclear Information System (INIS)
González-Avella, Juan Carlos; Hoffmann de Quadros, Vanessa; Iglesias, José Roberto
2016-01-01
Modern financial systems are greatly entangled. They exhibit a complex interdependence, including a network of bilateral exposures in the interbank market. The most frequent interaction consists in operations where institutions with surplus liquidity lend to those with a liquidity shortage. These loans may be interpreted as links between the banks and the links display features in some way representative of scale-free networks. While the interbank market is responsible for efficient liquidity allocation, it also introduces the possibility for systemic risk via financial contagion. Insolvency of one bank can propagate through links leading to insolvency of other banks. In this paper, we explore the characteristics of financial contagion in interbank networks whose distribution of links approaches a power law, as well as we improve previous models by introducing a simple mechanism to describe banks’ balance sheets, that are obtained from information on network connectivity. By varying the parameters for the creation of the network, several interbank networks are built, in which the concentration of debt and credit comes from the distribution of links. The results suggest that more connected networks that have a high concentration of credit are more resilient to contagion than other types of networks analyzed.
LARGE-SCALE TOPOLOGICAL PROPERTIES OF MOLECULAR NETWORKS.
Energy Technology Data Exchange (ETDEWEB)
MASLOV,S.SNEPPEN,K.
2003-11-17
Bio-molecular networks lack the top-down design. Instead, selective forces of biological evolution shape them from raw material provided by random events such as gene duplications and single gene mutations. As a result individual connections in these networks are characterized by a large degree of randomness. One may wonder which connectivity patterns are indeed random, while which arose due to the network growth, evolution, and/or its fundamental design principles and limitations? Here we introduce a general method allowing one to construct a random null-model version of a given network while preserving the desired set of its low-level topological features, such as, e.g., the number of neighbors of individual nodes, the average level of modularity, preferential connections between particular groups of nodes, etc. Such a null-model network can then be used to detect and quantify the non-random topological patterns present in large networks. In particular, we measured correlations between degrees of interacting nodes in protein interaction and regulatory networks in yeast. It was found that in both these networks, links between highly connected proteins are systematically suppressed. This effect decreases the likelihood of cross-talk between different functional modules of the cell, and increases the overall robustness of a network by localizing effects of deleterious perturbations. It also teaches us about the overall computational architecture of such networks and points at the origin of large differences in the number of neighbors of individual nodes.
Connectivity, topology and dynamics in climate networks
Czech Academy of Sciences Publication Activity Database
Paluš, Milan; Hartman, David; Hlinka, Jaroslav; Vejmelka, Martin
2012-01-01
Roč. 14, - (2012), s. 8397 ISSN 1607-7962. [European Geosciences Union General Assembly 2012. 22.04.2012-27.04.2012, Vienna] R&D Projects: GA ČR GCP103/11/J068 Institutional support: RVO:67985807 Keywords : complex networks * climate network * connectivity * entropy rate * El Nino Southern Oscillation * North Atlantic Oscillation Subject RIV: BB - Applied Statistics, Operational Research
Custom Topology Generation for Network-on-Chip
DEFF Research Database (Denmark)
Stuart, Matthias Bo; Sparsø, Jens
2007-01-01
This paper compares simulated annealing and tabu search for generating custom topologies for applications with periodic behaviour executing on a network-on-chip. The approach differs from previous work by starting from a fixed mapping of IP-cores to routers and performing design space exploration...... around an initial topology. The tabu search has been modified from its normally encountered form to allow easier escaping from local minima. A number of synthetic benchmarks are used for tuning the parameters of both heuristics and for testing the quality of the solutions each heuristic produces...
Regime-dependent topological properties of biofuels networks
Czech Academy of Sciences Publication Activity Database
Krištoufek, Ladislav; Janda, K.; Zilberman, D.
2013-01-01
Roč. 86, č. 2 (2013), 40-1-40-12 ISSN 1434-6028 R&D Projects: GA ČR GA402/09/0965 Grant - others:GA UK(CZ) 118310; GA ČR(CZ) GAP402/11/0948 Program:GA Institutional support: RVO:67985556 Keywords : topology * biofuels * correlations Subject RIV: AH - Economics Impact factor: 1.463, year: 2013 http://library.utia.cas.cz/separaty/2013/E/kristoufek-regime-dependent topological properties of biofuels networks.pdf
Enabling Controlling Complex Networks with Local Topological Information.
Li, Guoqi; Deng, Lei; Xiao, Gaoxi; Tang, Pei; Wen, Changyun; Hu, Wuhua; Pei, Jing; Shi, Luping; Stanley, H Eugene
2018-03-15
Complex networks characterize the nature of internal/external interactions in real-world systems including social, economic, biological, ecological, and technological networks. Two issues keep as obstacles to fulfilling control of large-scale networks: structural controllability which describes the ability to guide a dynamical system from any initial state to any desired final state in finite time, with a suitable choice of inputs; and optimal control, which is a typical control approach to minimize the cost for driving the network to a predefined state with a given number of control inputs. For large complex networks without global information of network topology, both problems remain essentially open. Here we combine graph theory and control theory for tackling the two problems in one go, using only local network topology information. For the structural controllability problem, a distributed local-game matching method is proposed, where every node plays a simple Bayesian game with local information and local interactions with adjacent nodes, ensuring a suboptimal solution at a linear complexity. Starring from any structural controllability solution, a minimizing longest control path method can efficiently reach a good solution for the optimal control in large networks. Our results provide solutions for distributed complex network control and demonstrate a way to link the structural controllability and optimal control together.
Finding quasi-optimal network topologies for information transmission in active networks.
Baptista, Murilo S; de Carvalho, Josué X; Hussein, Mahir S
2008-01-01
This work clarifies the relation between network circuit (topology) and behaviour (information transmission and synchronization) in active networks, e.g. neural networks. As an application, we show how one can find network topologies that are able to transmit a large amount of information, possess a large number of communication channels, and are robust under large variations of the network coupling configuration. This theoretical approach is general and does not depend on the particular dynamic of the elements forming the network, since the network topology can be determined by finding a Laplacian matrix (the matrix that describes the connections and the coupling strengths among the elements) whose eigenvalues satisfy some special conditions. To illustrate our ideas and theoretical approaches, we use neural networks of electrically connected chaotic Hindmarsh-Rose neurons.
Finding quasi-optimal network topologies for information transmission in active networks.
Directory of Open Access Journals (Sweden)
Murilo S Baptista
Full Text Available This work clarifies the relation between network circuit (topology and behaviour (information transmission and synchronization in active networks, e.g. neural networks. As an application, we show how one can find network topologies that are able to transmit a large amount of information, possess a large number of communication channels, and are robust under large variations of the network coupling configuration. This theoretical approach is general and does not depend on the particular dynamic of the elements forming the network, since the network topology can be determined by finding a Laplacian matrix (the matrix that describes the connections and the coupling strengths among the elements whose eigenvalues satisfy some special conditions. To illustrate our ideas and theoretical approaches, we use neural networks of electrically connected chaotic Hindmarsh-Rose neurons.
Critical conducting networks in disordered solids: ac universality from topological arguments
DEFF Research Database (Denmark)
Milovanov, A.V.; Juul Rasmussen, Jens
2001-01-01
This paper advocates an unconventional description of charge transport processes in disordered solids, which brings together the ideas of fractal geometry, percolation theory, and topology of manifolds. We demonstrate that the basic features of ac conductivity in disordered materials as seen...... in various experiments are reproduced with remarkable accuracy by the conduction properties of percolating fractal networks near the threshold of percolation. The universal character of ac conductivity in three embedding dimensions is discussed in connection with the available experimental data. An important...
International Nuclear Information System (INIS)
Zhang Li-Sheng; Mi Yuan-Yuan; Gu Wei-Feng; Hu Gang
2014-01-01
All dynamic complex networks have two important aspects, pattern dynamics and network topology. Discovering different types of pattern dynamics and exploring how these dynamics depend on network topologies are tasks of both great theoretical importance and broad practical significance. In this paper we study the oscillatory behaviors of excitable complex networks (ECNs) and find some interesting dynamic behaviors of ECNs in oscillatory probability, the multiplicity of oscillatory attractors, period distribution, and different types of oscillatory patterns (e.g., periodic, quasiperiodic, and chaotic). In these aspects, we further explore strikingly sharp differences among network dynamics induced by different topologies (random or scale-free topologies) and different interaction structures (symmetric or asymmetric couplings). The mechanisms behind these differences are explained physically. (interdisciplinary physics and related areas of science and technology)
Topological networks for quantum communication between distant qubits
Lang, Nicolai; Büchler, Hans Peter
2017-11-01
Efficient communication between qubits relies on robust networks, which allow for fast and coherent transfer of quantum information. It seems natural to harvest the remarkable properties of systems characterized by topological invariants to perform this task. Here, we show that a linear network of coupled bosonic degrees of freedom, characterized by topological bands, can be employed for the efficient exchange of quantum information over large distances. Important features of our setup are that it is robust against quenched disorder, all relevant operations can be performed by global variations of parameters, and the time required for communication between distant qubits approaches linear scaling with their distance. We demonstrate that our concept can be extended to an ensemble of qubits embedded in a two-dimensional network to allow for communication between all of them.
A Reconfigurable Mesh-Ring Topology for Bluetooth Sensor Networks
Directory of Open Access Journals (Sweden)
Ben-Yi Wang
2018-05-01
Full Text Available In this paper, a Reconfigurable Mesh-Ring (RMR algorithm is proposed for Bluetooth sensor networks. The algorithm is designed in three stages to determine the optimal configuration of the mesh-ring network. Firstly, a designated root advertises and discovers its neighboring nodes. Secondly, a scatternet criterion is built to compute the minimum number of piconets and distributes the connection information for piconet and scatternet. Finally, a peak-search method is designed to determine the optimal mesh-ring configuration for various sizes of networks. To maximize the network capacity, the research problem is formulated by determining the best connectivity of available mesh links. During the formation and maintenance phases, three possible configurations (including piconet, scatternet, and hybrid are examined to determine the optimal placement of mesh links. The peak-search method is a systematic approach, and is implemented by three functional blocks: the topology formation block generates the mesh-ring topology, the routing efficiency block computes the routing performance, and the optimum decision block introduces a decision-making criterion to determine the optimum number of mesh links. Simulation results demonstrate that the optimal mesh-ring configuration can be determined and that the scatternet case achieves better overall performance than the other two configurations. The RMR topology also outperforms the conventional ring-based and cluster-based mesh methods in terms of throughput performance for Bluetooth configurable networks.
Statistical mechanics of polymer networks of any topology
International Nuclear Information System (INIS)
Duplantier, B.
1989-01-01
The statistical mechanics is considered of any polymer network with a prescribed topology, in dimension d, which was introduced previously. The basic direct renormalization theory of the associated continuum model is established. It has a very simple multiplicative structure in terms of the partition functions of the star polymers constituting the vertices of the network. A calculation is made to O(ε 2 ), where d = 4 -ε, of the basic critical dimensions σ L associated with any L=leg vertex (L ≥ 1). From this infinite series of critical exponents, any topology-dependent critical exponent can be derived. This is applied to the configuration exponent γ G of any network G to O(ε 2 ), including L-leg star polymers. The infinite sets of contact critical exponents θ between multiple points of polymers or between the cores of several star polymers are also deduced. As a particular case, the three exponents θ 0 , θ 1 , θ 2 calculated by des Cloizeaux by field-theoretic methods are recovered. The limiting exact logarithmic laws are derived at the upper critical dimension d = 4. The results are generalized to the series of topological exponents of polymer networks near a surface and of tricritical polymers at the Θ-point. Intersection properties of networks of random walks can be studied similarly. The above factorization theory of the partition function of any polymer network over its constituting L-vertices also applies to two dimensions, where it can be related to conformal invariance. The basic critical exponents σ L and thus any topological polymer exponents are then exactly known. Principal results published elsewhere are recalled
Charge and Spin Transport in Spin-orbit Coupled and Topological Systems
Ndiaye, Papa Birame
2017-01-01
for next-generation technology, three classes of systems that possibly enhance the spin and charge transport efficiency: (i)- topological insulators, (ii)- spin-orbit coupled magnonic systems, (iii)- topological magnetic textures (skyrmions and 3Q magnetic
Radiation-Induced Topological Disorder in Irradiated Network Structures
International Nuclear Information System (INIS)
Hobbs, Linn W.
2002-12-01
This report summarizes results of a research program investigating the fundamental principles underlying the phenomenon of topological disordering in a radiation environment. This phenomenon is known popularly as amorphization, but is more formally described as a process of radiation-induced structural arrangement that leads in crystals to loss of long-range translational and orientational correlations and in glasses to analogous alteration of connectivity topologies. The program focus has been on a set compound ceramic solids with directed bonding exhibiting structures that can be described as networks. Such solids include SiO2, Si3N4, SiC, which are of interest to applications in fusion energy production, nuclear waste storage, and device manufacture involving ion implantation or use in radiation fields. The principal investigative tools comprise a combination of experimental diffraction-based techniques, topological modeling, and molecular-dynamics simulations that have proven a rich source of information in the preceding support period. The results from the present support period fall into three task areas. The first comprises enumeration of the rigidity constraints applying to (1) more complex ceramic structures (such as rutile, corundum, spinel and olivine structures) that exhibit multiply polytopic coordination units or multiple modes of connecting such units, (2) elemental solids (such as graphite, silicon and diamond) for which a correct choice of polytope is necessary to achieve correct representation of the constraints, and (3) compounds (such as spinel and silicon carbide) that exhibit chemical disorder on one or several sublattices. With correct identification of the topological constraints, a unique correlation is shown to exist between constraint and amorphizability which demonstrates that amorphization occurs at a critical constraint loss. The second task involves the application of molecular dynamics (MD) methods to topologically-generated models
Influence of network topology on the swelling of polyelectrolyte nanogels.
Rizzi, L G; Levin, Y
2016-03-21
It is well-known that the swelling behavior of ionic nanogels depends on their cross-link density; however, it is unclear how different topologies should affect the response of the polyelectrolyte network. Here we perform Monte Carlo simulations to obtain the equilibrium properties of ionic nanogels as a function of salt concentration Cs and the fraction f of ionizable groups in a polyelectrolyte network formed by cross-links of functionality z. Our results indicate that the network with cross-links of low connectivity result in nanogel particles with higher swelling ratios. We also confirm a de-swelling effect of salt on nanogel particles.
Topology Recognition and Leader Election in Colored Networks
Dereniowski, Dariusz; Pelc, Andrzej
2016-01-01
Topology recognition and leader election are fundamental tasks in distributed computing in networks. The first of them requires each node to find a labeled isomorphic copy of the network, while the result of the second one consists in a single node adopting the label 1 (leader), with all other nodes adopting the label 0 and learning a path to the leader. We consider both these problems in networks whose nodes are equipped with not necessarily distinct labels called colors, and ports at each n...
Geography versus topology in the European Ownership Network
International Nuclear Information System (INIS)
Vitali, Stefania; Battiston, Stefano
2011-01-01
In this paper, we investigate the network of ownership relationships among European firms and its embedding in the geographical space. We carry out a detailed analysis of geographical distances between pairs of nodes, connected by edges or by shortest paths of varying length. In particular, we study the relation between geographical distance and network distance in comparison with a random spatial network model. While the distribution of geographical distance can be fairly well reproduced, important deviations appear in the network distance and in the size of the largest strongly connected component. Our results show that geographical factors allow us to capture several features of the network, while the deviations quantify the effect of additional economic factors at work in shaping the topology. The analysis is relevant to other types of geographically embedded networks and sheds light on the link formation process in the presence of spatial constraints.
Topology Counts: Force Distributions in Circular Spring Networks
Heidemann, Knut M.; Sageman-Furnas, Andrew O.; Sharma, Abhinav; Rehfeldt, Florian; Schmidt, Christoph F.; Wardetzky, Max
2018-02-01
Filamentous polymer networks govern the mechanical properties of many biological materials. Force distributions within these networks are typically highly inhomogeneous, and, although the importance of force distributions for structural properties is well recognized, they are far from being understood quantitatively. Using a combination of probabilistic and graph-theoretical techniques, we derive force distributions in a model system consisting of ensembles of random linear spring networks on a circle. We show that characteristic quantities, such as the mean and variance of the force supported by individual springs, can be derived explicitly in terms of only two parameters: (i) average connectivity and (ii) number of nodes. Our analysis shows that a classical mean-field approach fails to capture these characteristic quantities correctly. In contrast, we demonstrate that network topology is a crucial determinant of force distributions in an elastic spring network. Our results for 1D linear spring networks readily generalize to arbitrary dimensions.
Topology Counts: Force Distributions in Circular Spring Networks.
Heidemann, Knut M; Sageman-Furnas, Andrew O; Sharma, Abhinav; Rehfeldt, Florian; Schmidt, Christoph F; Wardetzky, Max
2018-02-09
Filamentous polymer networks govern the mechanical properties of many biological materials. Force distributions within these networks are typically highly inhomogeneous, and, although the importance of force distributions for structural properties is well recognized, they are far from being understood quantitatively. Using a combination of probabilistic and graph-theoretical techniques, we derive force distributions in a model system consisting of ensembles of random linear spring networks on a circle. We show that characteristic quantities, such as the mean and variance of the force supported by individual springs, can be derived explicitly in terms of only two parameters: (i) average connectivity and (ii) number of nodes. Our analysis shows that a classical mean-field approach fails to capture these characteristic quantities correctly. In contrast, we demonstrate that network topology is a crucial determinant of force distributions in an elastic spring network. Our results for 1D linear spring networks readily generalize to arbitrary dimensions.
Developmental time windows for axon growth influence neuronal network topology.
Lim, Sol; Kaiser, Marcus
2015-04-01
Early brain connectivity development consists of multiple stages: birth of neurons, their migration and the subsequent growth of axons and dendrites. Each stage occurs within a certain period of time depending on types of neurons and cortical layers. Forming synapses between neurons either by growing axons starting at similar times for all neurons (much-overlapped time windows) or at different time points (less-overlapped) may affect the topological and spatial properties of neuronal networks. Here, we explore the extreme cases of axon formation during early development, either starting at the same time for all neurons (parallel, i.e., maximally overlapped time windows) or occurring for each neuron separately one neuron after another (serial, i.e., no overlaps in time windows). For both cases, the number of potential and established synapses remained comparable. Topological and spatial properties, however, differed: Neurons that started axon growth early on in serial growth achieved higher out-degrees, higher local efficiency and longer axon lengths while neurons demonstrated more homogeneous connectivity patterns for parallel growth. Second, connection probability decreased more rapidly with distance between neurons for parallel growth than for serial growth. Third, bidirectional connections were more numerous for parallel growth. Finally, we tested our predictions with C. elegans data. Together, this indicates that time windows for axon growth influence the topological and spatial properties of neuronal networks opening up the possibility to a posteriori estimate developmental mechanisms based on network properties of a developed network.
Effects of topologies on signal propagation in feedforward networks
Zhao, Jia; Qin, Ying-Mei; Che, Yan-Qiu
2018-01-01
We systematically investigate the effects of topologies on signal propagation in feedforward networks (FFNs) based on the FitzHugh-Nagumo neuron model. FFNs with different topological structures are constructed with same number of both in-degrees and out-degrees in each layer and given the same input signal. The propagation of firing patterns and firing rates are found to be affected by the distribution of neuron connections in the FFNs. Synchronous firing patterns emerge in the later layers of FFNs with identical, uniform, and exponential degree distributions, but the number of synchronous spike trains in the output layers of the three topologies obviously differs from one another. The firing rates in the output layers of the three FFNs can be ordered from high to low according to their topological structures as exponential, uniform, and identical distributions, respectively. Interestingly, the sequence of spiking regularity in the output layers of the three FFNs is consistent with the firing rates, but their firing synchronization is in the opposite order. In summary, the node degree is an important factor that can dramatically influence the neuronal network activity.
Distributed Energy-Efficient Topology Control Algorithm in Home M2M Networks
Lee, Chao-Yang; Yang, Chu-Sing
2012-01-01
Because machine-to-machine (M2M) technology enables machines to communicate with each other without human intervention, it could play a big role in sensor network systems. Through wireless sensor network (WSN) gateways, various information can be collected by sensors for M2M systems. For home M2M networks, this study proposes a distributed energy-efficient topology control algorithm for both topology construction and topology maintenance. Topology control is an effective method of enhancing e...
Topological transport in Dirac nodal-line semimetals
Rui, W. B.; Zhao, Y. X.; Schnyder, Andreas P.
2018-04-01
Topological nodal-line semimetals are characterized by one-dimensional Dirac nodal rings that are protected by the combined symmetry of inversion P and time-reversal T . The stability of these Dirac rings is guaranteed by a quantized ±π Berry phase and their low-energy physics is described by a one-parameter family of (2+1)-dimensional quantum field theories exhibiting the parity anomaly. Here we study the Berry-phase supported topological transport of P T -invariant nodal-line semimetals. We find that small inversion breaking allows for an electric-field-induced anomalous transverse current, whose universal component originates from the parity anomaly. Due to this Hall-like current, carriers at opposite sides of the Dirac nodal ring flow to opposite surfaces when an electric field is applied. To detect the topological currents, we propose a dumbbell device, which uses surface states to filter charges based on their momenta. Suggestions for experiments and device applications are discussed.
Bulk-edge correspondence in topological transport and pumping
Imura, Ken-Ichiro; Yoshimura, Yukinori; Fukui, Takahiro; Hatsugai, Yasuhiro
2018-03-01
The bulk-edge correspondence (BEC) refers to a one-to-one relation between the bulk and edge properties ubiquitous in topologically nontrivial systems. Depending on the setup, BEC manifests in different forms and govern the spectral and transport properties of topological insulators and semimetals. Although the topological pump is theoretically old, BEC in the pump has been established just recently [1] motivated by the state-of-the-art experiments using cold atoms [2, 3]. The center of mass (CM) of a system with boundaries shows a sequence of quantized jumps in the adiabatic limit associated with the edge states. Despite that the bulk is adiabatic, the edge is inevitably non-adiabatic in the experimental setup or in any numerical simulations. Still the pumped charge is quantized and carried by the bulk. Its quantization is guaranteed by a compensation between the bulk and edges. We show that in the presence of disorder the pumped charge continues to be quantized despite the appearance of non-quantized jumps.
Topological isomorphisms of human brain and financial market networks
Directory of Open Access Journals (Sweden)
Petra E Vértes
2011-09-01
Full Text Available Although metaphorical and conceptual connections between the human brain and the financial markets have often been drawn, rigorous physical or mathematical underpinnings of this analogy remain largely unexplored. Here, we apply a statistical and graph theoretic approach to the study of two datasets - the timeseries of 90 stocks from the New York Stock Exchange over a three-year period, and the fMRI-derived timeseries acquired from 90 brain regions over the course of a 10 min-long functional MRI scan of resting brain function in healthy volunteers. Despite the many obvious substantive differences between these two datasets, graphical analysis demonstrated striking commonalities in terms of global network topological properties. Both the human brain and the market networks were non-random, small-world, modular, hierarchical systems with fat-tailed degree distributions indicating the presence of highly connected hubs. These properties could not be trivially explained by the univariate time series statistics of stock price returns. This degree of topological isomorphism suggests that brains and markets can be regarded broadly as members of the same family of networks. The two systems, however, were not topologically identical. The financial market was more efficient and more modular - more highly optimised for information processing - than the brain networks; but also less robust to systemic disintegration as a result of hub deletion. We conclude that the conceptual connections between brains and markets are not merely metaphorical; rather these two information processing systems can be rigorously compared in the same mathematical language and turn out often to share important topological properties in common to some degree. There will be interesting scientific arbitrage opportunities in further work at the graph theoretically-mediated interface between systems neuroscience and the statistical physics of financial markets.
Topological isomorphisms of human brain and financial market networks.
Vértes, Petra E; Nicol, Ruth M; Chapman, Sandra C; Watkins, Nicholas W; Robertson, Duncan A; Bullmore, Edward T
2011-01-01
Although metaphorical and conceptual connections between the human brain and the financial markets have often been drawn, rigorous physical or mathematical underpinnings of this analogy remain largely unexplored. Here, we apply a statistical and graph theoretic approach to the study of two datasets - the time series of 90 stocks from the New York stock exchange over a 3-year period, and the fMRI-derived time series acquired from 90 brain regions over the course of a 10-min-long functional MRI scan of resting brain function in healthy volunteers. Despite the many obvious substantive differences between these two datasets, graphical analysis demonstrated striking commonalities in terms of global network topological properties. Both the human brain and the market networks were non-random, small-world, modular, hierarchical systems with fat-tailed degree distributions indicating the presence of highly connected hubs. These properties could not be trivially explained by the univariate time series statistics of stock price returns. This degree of topological isomorphism suggests that brains and markets can be regarded broadly as members of the same family of networks. The two systems, however, were not topologically identical. The financial market was more efficient and more modular - more highly optimized for information processing - than the brain networks; but also less robust to systemic disintegration as a result of hub deletion. We conclude that the conceptual connections between brains and markets are not merely metaphorical; rather these two information processing systems can be rigorously compared in the same mathematical language and turn out often to share important topological properties in common to some degree. There will be interesting scientific arbitrage opportunities in further work at the graph-theoretically mediated interface between systems neuroscience and the statistical physics of financial markets.
Evaluating the Limits of Network Topology Inference Via Virtualized Network Emulation
2015-06-01
virtualized environment. First, we automatically build topological ground truth according to various network generation models and create emulated Cisco ...to various network generation models and create emulated Cisco router networks by leveraging and modifying existing emulation software. We then au... markets , to verifying compliance with policy, as in recent “network neutrality” rules established in the United States. The Internet is a network of
Correlations in the degeneracy of structurally controllable topologies for networks
Campbell, Colin; Aucott, Steven; Ruths, Justin; Ruths, Derek; Shea, Katriona; Albert, Réka
2017-04-01
Many dynamic systems display complex emergent phenomena. By directly controlling a subset of system components (nodes) via external intervention it is possible to indirectly control every other component in the system. When the system is linear or can be approximated sufficiently well by a linear model, methods exist to identify the number and connectivity of a minimum set of external inputs (constituting a so-called minimal control topology, or MCT). In general, many MCTs exist for a given network; here we characterize a broad ensemble of empirical networks in terms of the fraction of nodes and edges that are always, sometimes, or never a part of an MCT. We study the relationships between the measures, and apply the methodology to the T-LGL leukemia signaling network as a case study. We show that the properties introduced in this report can be used to predict key components of biological networks, with potentially broad applications to network medicine.
Network synchronization: optimal and pessimal scale-free topologies
Energy Technology Data Exchange (ETDEWEB)
Donetti, Luca [Departamento de Electronica y Tecnologia de Computadores and Instituto de Fisica Teorica y Computacional Carlos I, Facultad de Ciencias, Universidad de Granada, 18071 Granada (Spain); Hurtado, Pablo I; Munoz, Miguel A [Departamento de Electromagnetismo y Fisica de la Materia and Instituto Carlos I de Fisica Teorica y Computacional Facultad de Ciencias, Universidad de Granada, 18071 Granada (Spain)], E-mail: mamunoz@onsager.ugr.es
2008-06-06
By employing a recently introduced optimization algorithm we construct optimally synchronizable (unweighted) networks for any given scale-free degree distribution. We explore how the optimization process affects degree-degree correlations and observe a generic tendency toward disassortativity. Still, we show that there is not a one-to-one correspondence between synchronizability and disassortativity. On the other hand, we study the nature of optimally un-synchronizable networks, that is, networks whose topology minimizes the range of stability of the synchronous state. The resulting 'pessimal networks' turn out to have a highly assortative string-like structure. We also derive a rigorous lower bound for the Laplacian eigenvalue ratio controlling synchronizability, which helps understanding the impact of degree correlations on network synchronizability.
Network synchronization: optimal and pessimal scale-free topologies
International Nuclear Information System (INIS)
Donetti, Luca; Hurtado, Pablo I; Munoz, Miguel A
2008-01-01
By employing a recently introduced optimization algorithm we construct optimally synchronizable (unweighted) networks for any given scale-free degree distribution. We explore how the optimization process affects degree-degree correlations and observe a generic tendency toward disassortativity. Still, we show that there is not a one-to-one correspondence between synchronizability and disassortativity. On the other hand, we study the nature of optimally un-synchronizable networks, that is, networks whose topology minimizes the range of stability of the synchronous state. The resulting 'pessimal networks' turn out to have a highly assortative string-like structure. We also derive a rigorous lower bound for the Laplacian eigenvalue ratio controlling synchronizability, which helps understanding the impact of degree correlations on network synchronizability
Static analysis of topology-dependent broadcast networks
DEFF Research Database (Denmark)
Nanz, Sebastian; Nielson, Flemming; Nielson, Hanne Riis
2010-01-01
changing network topology is a crucial ingredient. In this paper, we develop a static analysis that automatically constructs an abstract transition system, labelled by actions and connectivity information, to yield a mobility-preserving finite abstraction of the behaviour of a network expressed......Broadcast semantics poses significant challenges over point-to-point communication when it comes to formal modelling and analysis. Current approaches to analysing broadcast networks have focused on fixed connectivities, but this is unsuitable in the case of wireless networks where the dynamically...... in a process calculus with asynchronous local broadcast. Furthermore, we use model checking based on a 3-valued temporal logic to distinguish network behaviour which differs under changing connectivity patterns. (C) 2009 Elsevier Inc. All rights reserved....
Topology dependent epidemic spreading velocity in weighted networks
Duan, W.; Quax, R.; Lees, M.; Qiu, X.; Sloot, P.M.A.
2014-01-01
Many diffusive processes occur on structured networks with weighted links, such as disease spread by airplane transport or information diffusion in social networks or blogs. Understanding the impact of weight-connectivity correlations on epidemic spreading in weighted networks is crucial to support
DEFF Research Database (Denmark)
Kirstein, Jonas Kjeld; Albrechtsen, Hans-Jørgen; Rygaard, Martin
2014-01-01
Topological clustering was investigated to simplify a complex water distribution network of Copenhagen, Denmark, into recogniz- able water movement patterns. This made it possible to assess the general transport of the water and to suggest strategic sampling locations. Through a topological...... the samples’ comparability over time, and locations, where samples represent the distributed and consumed water in the Nørrebro district....
Correlation and network topologies in global and local stock indices
DEFF Research Database (Denmark)
Nobi, A.; Lee, S.; Kim, D. H.
2014-01-01
the crises. A significant change in the network topologies was observed due to the financial crises in both markets. The Jaccard similarities identified the change in the market state due to a crisis in both markets. The dynamic change of the Jaccard index can be used as an indicator of systemic risk......We examined how the correlation and network structure of the global indices and local Korean indices have changed during years 2000-2012. The average correlations of the global indices increased with time, while the local indices showed a decreasing trend except for drastic changes during...... or precursors of the crisis. (C) 2014 Elsevier B.V. All rights reserved....
Correlation and network topologies in global and local stock indices
Nobi, Ashadun; Lee, Sungmin; Kim, Doo Hwan; Lee, Jae Woo
2014-07-01
We examined how the correlation and network structure of the global indices and local Korean indices have changed during years 2000-2012. The average correlations of the global indices increased with time, while the local indices showed a decreasing trend except for drastic changes during the crises. A significant change in the network topologies was observed due to the financial crises in both markets. The Jaccard similarities identified the change in the market state due to a crisis in both markets. The dynamic change of the Jaccard index can be used as an indicator of systemic risk or precursors of the crisis.
Hocking, John G
1988-01-01
""As textbook and reference work, this is a valuable addition to the topological literature."" - Mathematical ReviewsDesigned as a text for a one-year first course in topology, this authoritative volume offers an excellent general treatment of the main ideas of topology. It includes a large number and variety of topics from classical topology as well as newer areas of research activity.There are four set-theoretic chapters, followed by four primarily algebraic chapters. Chapter I covers the fundamentals of topological and metrical spaces, mappings, compactness, product spaces, the Tychonoff t
Impact of network topology on self-organized criticality
Hoffmann, Heiko
2018-02-01
The general mechanisms behind self-organized criticality (SOC) are still unknown. Several microscopic and mean-field theory approaches have been suggested, but they do not explain the dependence of the exponents on the underlying network topology of the SOC system. Here, we first report the phenomena that in the Bak-Tang-Wiesenfeld (BTW) model, sites inside an avalanche area largely return to their original state after the passing of an avalanche, forming, effectively, critically arranged clusters of sites. Then, we hypothesize that SOC relies on the formation process of these clusters, and present a model of such formation. For low-dimensional networks, we show theoretically and in simulation that the exponent of the cluster-size distribution is proportional to the ratio of the fractal dimension of the cluster boundary and the dimensionality of the network. For the BTW model, in our simulations, the exponent of the avalanche-area distribution matched approximately our prediction based on this ratio for two-dimensional networks, but deviated for higher dimensions. We hypothesize a transition from cluster formation to the mean-field theory process with increasing dimensionality. This work sheds light onto the mechanisms behind SOC, particularly, the impact of the network topology.
Sampling Algorithms of Pure Network Topologies: Stability and Separability of Metric Embeddings
National Research Council Canada - National Science Library
Airoldi, Edoardo M
2005-01-01
... has become a central theme for KDD. The intuition behind the plethora of approaches relies upon a few basic types of networks, which are identified by specific local and global topological properties, and which the authors term "pure" topology types...
Classification of data patterns using an autoassociative neural network topology
Dietz, W. E.; Kiech, E. L.; Ali, M.
1989-01-01
A diagnostic expert system based on neural networks is developed and applied to the real-time diagnosis of jet and rocket engines. The expert system methodologies are based on the analysis of patterns of behavior of physical mechanisms. In this approach, fault diagnosis is conceptualized as the mapping or association of patterns of sensor data to patterns representing fault conditions. The approach addresses deficiencies inherent in many feedforward neural network models and greatly reduces the number of networks necessary to identify the existence of a fault condition and estimate the duration and severity of the identified fault. The network topology used in the present implementation of the diagnostic system is described, as well as the training regimen used and the response of the system to inputs representing both previously observed and unknown fault scenarios. Noise effects on the integrity of the diagnosis are also evaluated.
Influence of magnetic topology on transport and stability in stellarators
Energy Technology Data Exchange (ETDEWEB)
Castejon, F [Laboratorio Nacional de Fusion. Asociacion Euratom/Ciemat, 28040-Madrid (Spain); Fujisawa, A [National Institute for Fusion Science Oroshi-cho, Toki-shi, Gifu, 509-5292 (Japan); Ida, K [National Institute for Fusion Science Oroshi-cho, Toki-shi, Gifu, 509-5292 (Japan); Talmadge, J N [University of Wisconsin-Madison, Madison, Wisconsin 53706 (United States); Estrada, T [Laboratorio Nacional de Fusion. Asociacion Euratom/Ciemat, 28040-Madrid (Spain); Lopez-Bruna, D [Laboratorio Nacional de Fusion. Asociacion Euratom/Ciemat, 28040-Madrid (Spain); Hidalgo, C [Laboratorio Nacional de Fusion. Asociacion Euratom/Ciemat, 28040-Madrid (Spain); Krupnik, L [Institute of Plasma Physics, NSC ' KIPT' , Kharkov (Ukraine); Melnikov, A [Institute of Nuclear Fusion, RRC ' Kurchatov Institute' , Moscow (Russian Federation)
2005-12-15
The influence of the magnetic topology on transport and stability has been investigated in four stellarators: an almost shearless medium size flexible heliac (TJ-II), a medium size and a large heliotron (CHS and LHD) with shear, and a quasihelically symmetric device (HSX) with moderate shear. All of these have variable rotational transform profiles and magnetic ripples. Using these capabilities, bifurcated states can appear and plasma can jump from one to another with subsequent changes in the transport properties. Low rational values of {iota}/2{pi} can create transport barriers in LHD and TJ-II when they are located close to the plasma core or at the edge. The key ingredient for transport barriers is a positive and sheared electric field. Internal transport barriers also appear in CHS, but the role of rationals is not clear yet in this device. The time evolution of the electric field shows the onset of a bifurcation triggered either by the rational or by the presence of the ion and electron roots. The electric potential inside ITBs follows the ECE-temperature profile in a fast time scale. The plasma stability properties and its effect on the viscosity are also studied in the HSX, and the influence of the dynamics of rational surface is studied in the LHD and TJ-II stellarators.
Influence of magnetic topology on transport and stability in stellarators
International Nuclear Information System (INIS)
Castejon, F; Fujisawa, A; Ida, K; Talmadge, J N; Estrada, T; Lopez-Bruna, D; Hidalgo, C; Krupnik, L; Melnikov, A
2005-01-01
The influence of the magnetic topology on transport and stability has been investigated in four stellarators: an almost shearless medium size flexible heliac (TJ-II), a medium size and a large heliotron (CHS and LHD) with shear, and a quasihelically symmetric device (HSX) with moderate shear. All of these have variable rotational transform profiles and magnetic ripples. Using these capabilities, bifurcated states can appear and plasma can jump from one to another with subsequent changes in the transport properties. Low rational values of ι/2π can create transport barriers in LHD and TJ-II when they are located close to the plasma core or at the edge. The key ingredient for transport barriers is a positive and sheared electric field. Internal transport barriers also appear in CHS, but the role of rationals is not clear yet in this device. The time evolution of the electric field shows the onset of a bifurcation triggered either by the rational or by the presence of the ion and electron roots. The electric potential inside ITBs follows the ECE-temperature profile in a fast time scale. The plasma stability properties and its effect on the viscosity are also studied in the HSX, and the influence of the dynamics of rational surface is studied in the LHD and TJ-II stellarators
Self-organized topology of recurrence-based complex networks
International Nuclear Information System (INIS)
Yang, Hui; Liu, Gang
2013-01-01
With the rapid technological advancement, network is almost everywhere in our daily life. Network theory leads to a new way to investigate the dynamics of complex systems. As a result, many methods are proposed to construct a network from nonlinear time series, including the partition of state space, visibility graph, nearest neighbors, and recurrence approaches. However, most previous works focus on deriving the adjacency matrix to represent the complex network and extract new network-theoretic measures. Although the adjacency matrix provides connectivity information of nodes and edges, the network geometry can take variable forms. The research objective of this article is to develop a self-organizing approach to derive the steady geometric structure of a network from the adjacency matrix. We simulate the recurrence network as a physical system by treating the edges as springs and the nodes as electrically charged particles. Then, force-directed algorithms are developed to automatically organize the network geometry by minimizing the system energy. Further, a set of experiments were designed to investigate important factors (i.e., dynamical systems, network construction methods, force-model parameter, nonhomogeneous distribution) affecting this self-organizing process. Interestingly, experimental results show that the self-organized geometry recovers the attractor of a dynamical system that produced the adjacency matrix. This research addresses a question, i.e., “what is the self-organizing geometry of a recurrence network?” and provides a new way to reproduce the attractor or time series from the recurrence plot. As a result, novel network-theoretic measures (e.g., average path length and proximity ratio) can be achieved based on actual node-to-node distances in the self-organized network topology. The paper brings the physical models into the recurrence analysis and discloses the spatial geometry of recurrence networks
A preliminary investigation on the topology of Chinese climate networks
International Nuclear Information System (INIS)
Ge-Li, Wang; Tsonis, Anastasios A
2009-01-01
Complex networks have been studied across many fields of science in recent years. In this paper, we give a brief introduction of networks, then follow the original works by Tsonis et al (2004, 2006) starting with data of the surface temperature from 160 Chinese weather observations to investigate the topology of Chinese climate networks. Results show that the Chinese climate network exhibits a characteristic of regular, almost fully connected networks, which means that most nodes in this case have the same number of links, and so-called super nodes with a very large number of links do not exist there. In other words, though former results show that nodes in the extratropical region provide a property of scale-free networks, they still have other different local fine structures inside. We also detect the community of the Chinese climate network by using a Bayesian technique; the effective number of communities of the Chinese climate network is about four in this network. More importantly, this technique approaches results in divisions which have connections with physics and dynamics; the division into communities may highlight the aspects of the dynamics of climate variability. (geophysics, astronomy and astrophysics)
Virtual network embedding in cross-domain network based on topology and resource attributes
Zhu, Lei; Zhang, Zhizhong; Feng, Linlin; Liu, Lilan
2018-03-01
Aiming at the network architecture ossification and the diversity of access technologies issues, this paper researches the cross-domain virtual network embedding algorithm. By analysing the topological attribute from the local and global perspective of nodes in the virtual network and the physical network, combined with the local network resource property, we rank the embedding priority of the nodes with PCA and TOPSIS methods. Besides, the link load distribution is considered. Above all, We proposed an cross-domain virtual network embedding algorithm based on topology and resource attributes. The simulation results depicts that our algorithm increases the acceptance rate of multi-domain virtual network requests, compared with the existing virtual network embedding algorithm.
Foreign currency exchange network topology across the 2008 credit crisis
Sharif, Shamshuritawati; Ap, Nuraisah Che; Ruslan, Nuraimi
2017-05-01
A stable world currency exchange rate is a very important aspect to be considered for a developed country, i.e Malaysia. A better understanding about the currencies itself is needed nowadays. This project is about to understanding the fluctuation and to identify the most influential world currencies in the three different cases; before credit crisis, during credit crisis and after credit crisis. A network topology approach is use to examine the interrelationship between currencies based on correlation analysis. With this point of view, those relationships can be measured by a correlation structure among the currencies. The network can be analyse by filtering the important information using minimum spanning tree (MST) and interpret it using degree centrality as the centrality measure. This topology will give a useful guide to understand the behaviour and determine the most influential currency in the network as a part of a complex system. All currencies are compared among the three different cases; before credit crisis, during credit crisis and after credit crisis period. The result of this project shows that Unites State Dollar (USD), Brazilian Real (BRL), United Kingdom Pound (EUR) and Danish Krone (DKK) are the most influential currencies before the credit crisis period. With respect to during the credit crisis, New Zealand Dollar (NZD) dominates the network and it is followed by Singapore Dollar (SGD) for after the credit crisis period.
International Nuclear Information System (INIS)
Wei Duqu; Luo Xiaoshu
2007-01-01
In this paper, we investigate coherence resonance (CR) and noise-induced synchronization in Hindmarsh-Rose (HR) neural network with three different types of topologies: regular, random, and small-world. It is found that the additive noise can induce CR in HR neural network with different topologies and its coherence is optimized by a proper noise level. It is also found that as coupling strength increases the plateau in the measure of coherence curve becomes broadened and the effects of network topology is more pronounced simultaneously. Moreover, we find that increasing the probability p of the network topology leads to an enhancement of noise-induced synchronization in HR neurons network.
Uncovering transcriptional regulation of metabolism by using metabolic network topology
DEFF Research Database (Denmark)
Patil, Kiran Raosaheb; Nielsen, Jens
2005-01-01
in the metabolic network that follow a common transcriptional response. Thus, the algorithm enables identification of so-called reporter metabolites (metabolites around which the most significant transcriptional changes occur) and a set of connected genes with significant and coordinated response to genetic......Cellular response to genetic and environmental perturbations is often reflected and/or mediated through changes in the metabolism, because the latter plays a key role in providing Gibbs free energy and precursors for biosynthesis. Such metabolic changes are often exerted through transcriptional...... therefore developed an algorithm that is based on hypothesis-driven data analysis to uncover the transcriptional regulatory architecture of metabolic networks. By using information on the metabolic network topology from genome-scale metabolic reconstruction, we show that it is possible to reveal patterns...
Topology and computational performance of attractor neural networks
International Nuclear Information System (INIS)
McGraw, Patrick N.; Menzinger, Michael
2003-01-01
To explore the relation between network structure and function, we studied the computational performance of Hopfield-type attractor neural nets with regular lattice, random, small-world, and scale-free topologies. The random configuration is the most efficient for storage and retrieval of patterns by the network as a whole. However, in the scale-free case retrieval errors are not distributed uniformly among the nodes. The portion of a pattern encoded by the subset of highly connected nodes is more robust and efficiently recognized than the rest of the pattern. The scale-free network thus achieves a very strong partial recognition. The implications of these findings for brain function and social dynamics are suggestive
Topological properties of complex networks in protein structures
Kim, Kyungsik; Jung, Jae-Won; Min, Seungsik
2014-03-01
We study topological properties of networks in structural classification of proteins. We model the native-state protein structure as a network made of its constituent amino-acids and their interactions. We treat four structural classes of proteins composed predominantly of α helices and β sheets and consider several proteins from each of these classes whose sizes range from amino acids of the Protein Data Bank. Particularly, we simulate and analyze the network metrics such as the mean degree, the probability distribution of degree, the clustering coefficient, the characteristic path length, the local efficiency, and the cost. This work was supported by the KMAR and DP under Grant WISE project (153-3100-3133-302-350).
Epidemic Network Failures in Optical Transport Networks
DEFF Research Database (Denmark)
Ruepp, Sarah Renée; Katsikas, Dimitrios; Fagertun, Anna Manolova
2013-01-01
This paper presents a failure propagation model for transport networks which are affected by epidemic failures. The network is controlled using the GMPLS protocol suite. The Susceptible Infected Disabled (SID) epidemic model is investigated and new signaling functionality of GMPLS to support...
Topological structure and mechanics of glassy polymer networks.
Elder, Robert M; Sirk, Timothy W
2017-11-22
The influence of chain-level network architecture (i.e., topology) on mechanics was explored for unentangled polymer networks using a blend of coarse-grained molecular simulations and graph-theoretic concepts. A simple extension of the Watts-Strogatz model is proposed to control the graph properties of the network such that the corresponding physical properties can be studied with simulations. The architecture of polymer networks assembled with a dynamic curing approach were compared with the extended Watts-Strogatz model, and found to agree surprisingly well. The final cured structures of the dynamically-assembled networks were nearly an intermediate between lattice and random connections due to restrictions imposed by the finite length of the chains. Further, the uni-axial stress response, character of the bond breaking, and non-affine displacements of fully-cured glassy networks were analyzed as a function of the degree of disorder in the network architecture. It is shown that the architecture strongly affects the network stability, flow stress, onset of bond breaking, and ultimate stress while leaving the modulus and yield point nearly unchanged. The results show that internal restrictions imposed by the network architecture alter the chain-level response through changes to the crosslink dynamics in the flow regime and through the degree of coordinated chain failure at the ultimate stress. The properties considered here are shown to be sensitive to even incremental changes to the architecture and, therefore, the overall network architecture, beyond simple defects, is predicted to be a meaningful physical parameter in the mechanics of glassy polymer networks.
Transport on the surface of a topological insulator
International Nuclear Information System (INIS)
Vargiamidis, V.; Vasilopoulos, P.
2014-01-01
We study theoretically dc and ac transport on the surface of a three-dimensional topological insulator when its time-reversal symmetry is broken. Starting with a Kubo formula, we derive an explicit expression for the dc Hall conductivity, valid for finite temperatures. At zero temperature this expression gives the dc half-quantum Hall conductivity, provided the Fermi level lies in the gap. Corrections when the Fermi level is outside the gap and scattering by impurities are quantified. The longitudinal conductivity is also examined. At finite frequencies, we find a modified Drude term in σ xx (ω) and logarithmic, frequency-dependent corrections in σ yx (ω). The ac Hall conductivity exhibits a robust logarithmic singularity for excitation energies equal to the gapwidth. For these energies, we also find that the power spectrum, which is pertinent to optical experiments, exhibits drastic increase. The Hall conductivity remains almost unaffected for temperatures up to approximately 300 K
Topology identification of the complex networks with non-delayed and delayed coupling
International Nuclear Information System (INIS)
Guo Wanli; Chen Shihua; Sun Wen
2009-01-01
In practical situation, there exists many uncertain information in complex networks, such as the topological structures. So the topology identification is an important issue in the research of the complex networks. Based on LaSalle's invariance principle, in this Letter, an adaptive controlling method is proposed to identify the topology of a weighted general complex network model with non-delayed and delayed coupling. Finally, simulation results show that the method is effective.
Adaptive approach to global synchronization of directed networks with fast switching topologies
International Nuclear Information System (INIS)
Qin Buzhi; Lu Xinbiao
2010-01-01
Global synchronization of directed networks with switching topologies is investigated. It is found that if there exists at least one directed spanning tree in the network with the fixed time-average topology and the time-average topology is achieved sufficiently fast, the network will reach global synchronization for appreciate coupling strength. Furthermore, this appreciate coupling strength may be obtained by local adaptive approach. A sufficient condition about the global synchronization is given. Numerical simulations verify the effectiveness of the adaptive strategy.
A method of network topology optimization design considering application process characteristic
Wang, Chunlin; Huang, Ning; Bai, Yanan; Zhang, Shuo
2018-03-01
Communication networks are designed to meet the usage requirements of users for various network applications. The current studies of network topology optimization design mainly considered network traffic, which is the result of network application operation, but not a design element of communication networks. A network application is a procedure of the usage of services by users with some demanded performance requirements, and has obvious process characteristic. In this paper, we first propose a method to optimize the design of communication network topology considering the application process characteristic. Taking the minimum network delay as objective, and the cost of network design and network connective reliability as constraints, an optimization model of network topology design is formulated, and the optimal solution of network topology design is searched by Genetic Algorithm (GA). Furthermore, we investigate the influence of network topology parameter on network delay under the background of multiple process-oriented applications, which can guide the generation of initial population and then improve the efficiency of GA. Numerical simulations show the effectiveness and validity of our proposed method. Network topology optimization design considering applications can improve the reliability of applications, and provide guidance for network builders in the early stage of network design, which is of great significance in engineering practices.
Observations and analysis of self-similar branching topology in glacier networks
Bahr, D.B.; Peckham, S.D.
1996-01-01
Glaciers, like rivers, have a branching structure which can be characterized by topological trees or networks. Probability distributions of various topological quantities in the networks are shown to satisfy the criterion for self-similarity, a symmetry structure which might be used to simplify future models of glacier dynamics. Two analytical methods of describing river networks, Shreve's random topology model and deterministic self-similar trees, are applied to the six glaciers of south central Alaska studied in this analysis. Self-similar trees capture the topological behavior observed for all of the glaciers, and most of the networks are also reasonably approximated by Shreve's theory. Copyright 1996 by the American Geophysical Union.
Local, distributed topology control for large-scale wireless ad-hoc networks
Nieberg, T.; Hurink, Johann L.
In this document, topology control of a large-scale, wireless network by a distributed algorithm that uses only locally available information is presented. Topology control algorithms adjust the transmission power of wireless nodes to create a desired topology. The algorithm, named local power
Fault-Tolerant Topology Selection for TTEthernet Networks
DEFF Research Database (Denmark)
Gavrilut, Voica Maria; Tamas-Selicean, Domitian; Pop, Paul
2015-01-01
Many safety-critical real-time applications are implemented using distributed architectures, composed of heterogeneous processing elements (PEs) interconnected in a network. In this paper, we are interested in the TTEthernet protocol, which is a deterministic, synchronized and congestion-free net......Many safety-critical real-time applications are implemented using distributed architectures, composed of heterogeneous processing elements (PEs) interconnected in a network. In this paper, we are interested in the TTEthernet protocol, which is a deterministic, synchronized and congestion......-free network protocol based on the IEEE 802.3 Ethernet standard and compliant with ARINC 664p7. TTEthernet supports three types of traffic: static time-triggered (TT) traffic and dynamic traffic, which is further subdivided into Rate Constrained (RC) traffic that has bounded end-to-end latencies, and Best...... a fault-tolerant network topology, consisting of redundant physical links and network switches, such that the architecture cost is minimized, the applications are fault-tolerant to a given number of permanent faults occurring in the communication network, and the timing constraints of the TT and RC...
An algebraic topological method for multimodal brain networks comparison
Directory of Open Access Journals (Sweden)
Tiago eSimas
2015-07-01
Full Text Available Understanding brain connectivity is one of the most important issues in neuroscience. Nonetheless, connectivity data can reflect either functional relationships of brain activities or anatomical connections between brain areas. Although both representations should be related, this relationship is not straightforward. We have devised a powerful method that allows different operations between networks that share the same set of nodes, by embedding them in a common metric space, enforcing transitivity to the graph topology. Here, we apply this method to construct an aggregated network from a set of functional graphs, each one from a different subject. Once this aggregated functional network is constructed, we use again our method to compare it with the structural connectivity to identify particular brain regions that differ in both modalities (anatomical and functional. Remarkably, these brain regions include functional areas that form part of the classical resting state networks. We conclude that our method -based on the comparison of the aggregated functional network- reveals some emerging features that could not be observed when the comparison is performed with the classical averaged functional network.
A Review of the Topologies Used in Smart Water Meter Networks: A Wireless Sensor Network Application
Directory of Open Access Journals (Sweden)
Jaco Marais
2016-01-01
Full Text Available This paper presents several proposed and existing smart utility meter systems as well as their communication networks to identify the challenges of creating scalable smart water meter networks. Network simulations are performed on 3 network topologies (star, tree, and mesh to determine their suitability for smart water meter networks. The simulations found that once a number of nodes threshold is exceeded the network’s delay increases dramatically regardless of implemented topology. This threshold is at a relatively low number of nodes (50 and the use of network topologies such as tree or mesh helps alleviate this problem and results in lower network delays. Further simulations found that the successful transmission of application layer packets in a 70-end node tree network can be improved by 212% when end nodes only transmit data to their nearest router node. The relationship between packet success rate and different packet sizes was also investigated and reducing the packet size with a factor of 16 resulted in either 156% or 300% increases in the amount of successfully received packets depending on the network setup.
Evolutionary Topology of a Currency Network in Asia
Feng, Xiaobing; Wang, Xiaofan
Although recently there are extensive research on currency network using minimum spanning trees approach, the knowledge about the actual evolution of a currency web in Asia is still limited. In the paper, we study the structural evolution of an Asian network using daily exchange rate data. It was found that the correlation between Asian currencies and US Dollar, the previous regional key currency has become weaker and the intra-Asia interactions have increased. This becomes more salient after the exchange rate reform of China. Different from the previous studies, we further reveal that it is the trade volume, national wealth gap and countries growth cycle that has contributed to the evolutionary topology of the minimum spanning tree. These findings provide a valuable platform for theoretical modeling and further analysis.
Big data analytics for the virtual network topology reconfiguration use case
Gifre Renom, Lluís; Morales Alcaide, Fernando; Velasco Esteban, Luis Domingo; Ruiz Ramírez, Marc
2016-01-01
ABNO's OAM Handler is extended with big data analytics capabilities to anticipate traffic changes in volume and direction. Predicted traffic is used to trigger virtual network topology re-optimization. When the virtual topology needs to be reconfigured, predicted and current traffic matrices are used to find the optimal topology. A heuristic algorithm to adapt current virtual topology to meet both actual demands and expected traffic matrix is proposed. Experimental assessment is carried ou...
Manetti, Marco
2015-01-01
This is an introductory textbook on general and algebraic topology, aimed at anyone with a basic knowledge of calculus and linear algebra. It provides full proofs and includes many examples and exercises. The covered topics include: set theory and cardinal arithmetic; axiom of choice and Zorn's lemma; topological spaces and continuous functions; connectedness and compactness; Alexandrov compactification; quotient topologies; countability and separation axioms; prebasis and Alexander's theorem; the Tychonoff theorem and paracompactness; complete metric spaces and function spaces; Baire spaces; homotopy of maps; the fundamental group; the van Kampen theorem; covering spaces; Brouwer and Borsuk's theorems; free groups and free product of groups; and basic category theory. While it is very concrete at the beginning, abstract concepts are gradually introduced. It is suitable for anyone needing a basic, comprehensive introduction to general and algebraic topology and its applications.
Influence of magnetic topology on transport and stability in Stellerators
International Nuclear Information System (INIS)
Castejon, F.; Fujisawa, A.; Ida, K.; Talmadge, J.N.; Estrada, T.; Lopez-Bruna, D.; Hidalgo, C.
2005-01-01
The influence of magnetic topology on transport and stability has been studied in four different stellarators: An almost shear less medium size flexible heliac (TJ-II), a medium size and a large heliotron (CHS and LHD) with shear, and a quasi helically symmetric device (HSX) with moderate shear. All of them can vary their rotational transform profiles, especially TJ-II that can do it by a factor of more than 2. LHD and HSX can vary their confinement properties by modifying their respective magnetic ripples. CHS has proven that the electric field can jump between the electron and ion roots. Experiments in these stellarators have allowed us to determine how transport and stability are modified when the magnetic topology is changed, and to understand better the mechanisms that act in the different devices. Low rational values of ?/2? can create transport barriers in LHD and TJ-II when they are located close to the plasma core or at the edge. This has been done either by scanning the rotational transform, driving currents using ECCD, or inducing OH currents. In this way it is demonstrated that low order rationals are not always deleterious for confinement but can be beneficial. The key ingredient to understand this fact is the appearance of a positive and sheared electric field in these plasmas, which is created by the additional non-ambipolar fluxes that appear due to the presence of the rationals. Moreover, the electric field approximately vanishes inside the island, which creates a sheared flow in its vicinity. LHD and TJ-II experiments indicate that it is possible to create ITBs in the plasma without the presence of low order rationals. This occurs when the electric field is created by neoclassical mechanisms and the electron root appears in the plasma core. ITBs also appear in CHS but the role of rationals is not clear yet in this device. The time evolution of the electric field has been studied and fast transitions have been found between high and low confinement
Influence of magnetic topology on transport and stability in Stellerators
Energy Technology Data Exchange (ETDEWEB)
Castejon, F.; Fujisawa, A.; Ida, K.; Talmadge, J.N.; Estrada, T.; Lopez-Bruna, D.; Hidalgo, C.
2005-07-01
The influence of magnetic topology on transport and stability has been studied in four different stellarators: An almost shear less medium size flexible heliac (TJ-II), a medium size and a large heliotron (CHS and LHD) with shear, and a quasi helically symmetric device (HSX) with moderate shear. All of them can vary their rotational transform profiles, especially TJ-II that can do it by a factor of more than 2. LHD and HSX can vary their confinement properties by modifying their respective magnetic ripples. CHS has proven that the electric field can jump between the electron and ion roots. Experiments in these stellarators have allowed us to determine how transport and stability are modified when the magnetic topology is changed, and to understand better the mechanisms that act in the different devices. Low rational values of ?/2? can create transport barriers in LHD and TJ-II when they are located close to the plasma core or at the edge. This has been done either by scanning the rotational transform, driving currents using ECCD, or inducing OH currents. In this way it is demonstrated that low order rationals are not always deleterious for confinement but can be beneficial. The key ingredient to understand this fact is the appearance of a positive and sheared electric field in these plasmas, which is created by the additional non-ambipolar fluxes that appear due to the presence of the rationals. Moreover, the electric field approximately vanishes inside the island, which creates a sheared flow in its vicinity. LHD and TJ-II experiments indicate that it is possible to create ITBs in the plasma without the presence of low order rationals. This occurs when the electric field is created by neoclassical mechanisms and the electron root appears in the plasma core. ITBs also appear in CHS but the role of rationals is not clear yet in this device. The time evolution of the electric field has been studied and fast transitions have been found between high and low confinement
Elastic and transport properties of topological semimetal ZrTe
Guo, San-Dong; Wang, Yue-Hua; Lu, Wan-Li
2017-11-01
Topological semimetals may have substantial applications in electronics, spintronics, and quantum computation. Recently, ZrTe was predicted as a new type of topological semimetal due to the coexistence of Weyl fermions and massless triply degenerate nodal points. In this work, the elastic and transport properties of ZrTe are investigated by combining the first-principles calculations and semiclassical Boltzmann transport theory. Calculated elastic constants prove the mechanical stability of ZrTe, and the bulk modulus, shear modulus, Young’s modulus, and Poisson’s ratio also are calculated. It is found that spin-orbit coupling (SOC) has slightly enhanced effects on the Seebeck coefficient, which along the a(b) and c directions for pristine ZrTe at 300 K is 46.26 μVK-1 and 80.20 μVK-1, respectively. By comparing the experimental electrical conductivity of ZrTe (300 K) with the calculated value, the scattering time is determined as 1.59 × 10-14 s. The predicted room-temperature electronic thermal conductivity along the a(b) and c directions is 2.37 {{Wm}}-1{{{K}}}-1 and 2.90 {{Wm}}-1{{{K}}}-1, respectively. The room-temperature lattice thermal conductivity is predicted as 17.56 {{Wm}}-1{{{K}}}-1 and 43.08 {{Wm}}-1{{{K}}}-1 along the a(b) and c directions, showing very strong anisotropy. Calculated results show that isotope scattering produces an observable effect on lattice thermal conductivity. To observably reduce lattice thermal conductivity by nanostructures, the characteristic length should be smaller than 70 nm, based on cumulative lattice thermal conductivity with respect to the phonon mean free path (MFP) at 300 K. It is noted that the average room-temperature lattice thermal conductivity of ZrTe is slightly higher than that of isostructural MoP, which is due to larger phonon lifetimes and smaller Grüneisen parameters. Finally, the total thermal conductivity as a function of temperature is predicted for pristine ZrTe. Our works provide valuable
The Topological Analysis of Urban Transit System as a Small-World Network
Zhaosheng Yang; Huxing Zhou; Peng Gao; Hong Chen; Nan Zhang
2011-01-01
This paper proposes a topological analysis of urban transit system based on a functional representation network constructed from the urban transit system in Beijing. The representation gives a functional view on nodes named a transit line. Statistical measures are computed and introduced in complex network analysis. It shows that the urban transit system forms small-world networks and exhibits properties different from random networks and regular networks. Furthermore, the topological propert...
Control of polymer network topology in semi-batch systems
Wang, Rui; Olsen, Bradley; Johnson, Jeremiah
Polymer networks invariably possess topological defects: loops of different orders. Since small loops (primary loops and secondary loops) both lower the modulus of network and lead to stress concentration that causes material failure at low deformation, it is desirable to greatly reduce the loop fraction. We have shown that achieving loop fraction close to zero is extremely difficult in the batch process due to the slow decay of loop fraction with the polymer concentration and chain length. Here, we develop a modified kinetic graph theory that can model network formation reactions in semi-batch systems. We demonstrate that the loop fraction is not sensitive to the feeding policy if the reaction volume maintains constant during the network formation. However, if we initially put concentrated solution of small junction molecules in the reactor and continuously adding polymer solutions, the fractions of both primary loop and higher-order loops will be significantly reduced. There is a limiting value (nonzero) of loop fraction that can be achieved in the semi-batch system in condition of extremely slow feeding rate. This minimum loop fraction only depends on a single dimensionless variable, the product of concentration and with single chain pervaded volume, and defines an operating zone in which the loop fraction of polymer networks can be controlled through adjusting the feeding rate of the semi-batch process.
Scaling in public transport networks
Directory of Open Access Journals (Sweden)
C. von Ferber
2005-01-01
Full Text Available We analyse the statistical properties of public transport networks. These networks are defined by a set of public transport routes (bus lines and the stations serviced by these. For larger networks these appear to possess a scale-free structure, as it is demonstrated e.g. by the Zipf law distribution of the number of routes servicing a given station or for the distribution of the number of stations which can be visited from a chosen one without changing the means of transport. Moreover, a rather particular feature of the public transport network is that many routes service common subsets of stations. We discuss the possibility of new scaling laws that govern intrinsic properties of such subsets.
Development of Active External Network Topology Module for Floodlight SDN Controller
Directory of Open Access Journals (Sweden)
A. A. Noskov
2015-01-01
Full Text Available Traditional network architecture is inflexible and complicated. This observation has led to a paradigm shift towards software-defined networking (SDN, where network management level is separated from data forwarding level. This change was made possible by control plane transfer from the switching equipment to software modules that run on a dedicated server, called the controller (or network operating system, or network applications, that work with this controller. Methods of representation, storage and communication interfaces with network topology elements are the most important aspects of network operating systems available to SDN user because performance of some key controller modules is heavily dependent on internal representation of the network topology. Notably, firewall and routing modules are examples of such modules. This article describes the methods used for presentation and storage of network topologies, as well as interface to the corresponding Floodlight modules. An alternative algorithm has been suggested and developed for message exchange conveying network topology alterations between the controller and network applications. Proposed algorithm makes implementation of module alerting based on subscription to the relevant events. API for interaction between controller and network applications has been developed. This algorithm and API formed the base for Topology Tracker module capable to inform network applications about the changes that had occurred in the network topology and also stores compact representation of the network to speed up the interaction process.
Inferring topologies via driving-based generalized synchronization of two-layer networks
Wang, Yingfei; Wu, Xiaoqun; Feng, Hui; Lu, Jun-an; Xu, Yuhua
2016-05-01
The interaction topology among the constituents of a complex network plays a crucial role in the network’s evolutionary mechanisms and functional behaviors. However, some network topologies are usually unknown or uncertain. Meanwhile, coupling delays are ubiquitous in various man-made and natural networks. Hence, it is necessary to gain knowledge of the whole or partial topology of a complex dynamical network by taking into consideration communication delay. In this paper, topology identification of complex dynamical networks is investigated via generalized synchronization of a two-layer network. Particularly, based on the LaSalle-type invariance principle of stochastic differential delay equations, an adaptive control technique is proposed by constructing an auxiliary layer and designing proper control input and updating laws so that the unknown topology can be recovered upon successful generalized synchronization. Numerical simulations are provided to illustrate the effectiveness of the proposed method. The technique provides a certain theoretical basis for topology inference of complex networks. In particular, when the considered network is composed of systems with high-dimension or complicated dynamics, a simpler response layer can be constructed, which is conducive to circuit design. Moreover, it is practical to take into consideration perturbations caused by control input. Finally, the method is applicable to infer topology of a subnetwork embedded within a complex system and locate hidden sources. We hope the results can provide basic insight into further research endeavors on understanding practical and economical topology inference of networks.
Continuous Learning of a Multilayered Network Topology in a Video Camera Network
Directory of Open Access Journals (Sweden)
Zou Xiaotao
2009-01-01
Full Text Available Abstract A multilayered camera network architecture with nodes as entry/exit points, cameras, and clusters of cameras at different layers is proposed. Unlike existing methods that used discrete events or appearance information to infer the network topology at a single level, this paper integrates face recognition that provides robustness to appearance changes and better models the time-varying traffic patterns in the network. The statistical dependence between the nodes, indicating the connectivity and traffic patterns of the camera network, is represented by a weighted directed graph and transition times that may have multimodal distributions. The traffic patterns and the network topology may be changing in the dynamic environment. We propose a Monte Carlo Expectation-Maximization algorithm-based continuous learning mechanism to capture the latent dynamically changing characteristics of the network topology. In the experiments, a nine-camera network with twenty-five nodes (at the lowest level is analyzed both in simulation and in real-life experiments and compared with previous approaches.
Continuous Learning of a Multilayered Network Topology in a Video Camera Network
Directory of Open Access Journals (Sweden)
Xiaotao Zou
2009-01-01
Full Text Available A multilayered camera network architecture with nodes as entry/exit points, cameras, and clusters of cameras at different layers is proposed. Unlike existing methods that used discrete events or appearance information to infer the network topology at a single level, this paper integrates face recognition that provides robustness to appearance changes and better models the time-varying traffic patterns in the network. The statistical dependence between the nodes, indicating the connectivity and traffic patterns of the camera network, is represented by a weighted directed graph and transition times that may have multimodal distributions. The traffic patterns and the network topology may be changing in the dynamic environment. We propose a Monte Carlo Expectation-Maximization algorithm-based continuous learning mechanism to capture the latent dynamically changing characteristics of the network topology. In the experiments, a nine-camera network with twenty-five nodes (at the lowest level is analyzed both in simulation and in real-life experiments and compared with previous approaches.
Minimum Interference Planar Geometric Topology in Wireless Sensor Networks
Nguyen, Trac N.; Huynh, Dung T.
The approach of using topology control to reduce interference in wireless sensor networks has attracted attention of several researchers. There are at least two definitions of interference in the literature. In a wireless sensor network the interference at a node may be caused by an edge that is transmitting data [15], or it occurs because the node itself is within the transmission range of another [3], [1], [6]. In this paper we show that the problem of assigning power to nodes in the plane to yield a planar geometric graph whose nodes have bounded interference is NP-complete under both interference definitions. Our results provide a rigorous proof for a theorem in [15] whose proof is unconvincing. They also address one of the open issues raised in [6] where Halldórsson and Tokuyama were concerned with the receiver model of node interference, and derived an O(sqrt {Δ}) upper bound for the maximum node interference of a wireless ad hoc network in the plane (Δ is the maximum interference of the so-called uniform radius network). The question as to whether this problem is NP-complete in the 2-dimensional case was left open.
A note on the consensus finding problem in communication networks with switching topologies
Haskovec, Jan
2014-01-01
In this note, we discuss the problem of consensus finding in communication networks of agents with dynamically switching topologies. In particular, we consider the case of directed networks with unbalanced matrices of communication rates. We
Comparing the Reliability of Regular Topologies on a Backbone Network. A Case Study
DEFF Research Database (Denmark)
Cecilio, Sergio Labeage; Gutierrez Lopez, Jose Manuel; Riaz, M. Tahir
2009-01-01
The aim of this paper is to compare the reliability of regular topologies on a backbone network. The study is focused on a large-scale fiberoptic network. Different regular topological solutions as single ring, double ring or 4-Regular grid are applied to the case study, and compared in terms...
Network topology exploration of mesh-based coarse-grain reconfigurable architectures
Bansal, N.; Gupta, S.; Dutt, N.D.; Nicolau, A.; Gupta, R.
2004-01-01
Several coarse-grain reconfigurable architectures proposed recently consist of a large number of processing elements (PEs) connected in a mesh-like network topology. We study the effects of three aspects of network topology exploration on the performance of applications on these architectures: (a)
Augmented Topological Descriptors of Pore Networks for Material Science.
Ushizima, D; Morozov, D; Weber, G H; Bianchi, A G C; Sethian, J A; Bethel, E W
2012-12-01
One potential solution to reduce the concentration of carbon dioxide in the atmosphere is the geologic storage of captured CO2 in underground rock formations, also known as carbon sequestration. There is ongoing research to guarantee that this process is both efficient and safe. We describe tools that provide measurements of media porosity, and permeability estimates, including visualization of pore structures. Existing standard algorithms make limited use of geometric information in calculating permeability of complex microstructures. This quantity is important for the analysis of biomineralization, a subsurface process that can affect physical properties of porous media. This paper introduces geometric and topological descriptors that enhance the estimation of material permeability. Our analysis framework includes the processing of experimental data, segmentation, and feature extraction and making novel use of multiscale topological analysis to quantify maximum flow through porous networks. We illustrate our results using synchrotron-based X-ray computed microtomography of glass beads during biomineralization. We also benchmark the proposed algorithms using simulated data sets modeling jammed packed bead beds of a monodispersive material.
Chimeras in a network of three oscillator populations with varying network topology
DEFF Research Database (Denmark)
Martens, Erik Andreas
2010-01-01
this system as a model system, we discuss for the first time the influence of network topology on the existence of so-called chimera states. In this context, the network with three populations represents an interesting case because the populations may either be connected as a triangle, or as a chain, thereby......-like. By showing that chimera states only exist for a bounded set of parameter values, we demonstrate that their existence depends strongly on the underlying network structures, and conclude that chimeras exist on networks with a chain-like character....
Interdependent networks - Topological percolation research and application in finance
Zhou, Di
This dissertation covers the two major parts of my Ph.D. research: i) developing a theoretical framework of complex networks and applying simulation and numerical methods to study the robustness of the network system, and ii) applying statistical physics concepts and methods to quantitatively analyze complex systems and applying the theoretical framework to study real-world systems. In part I, we focus on developing theories of interdependent networks as well as building computer simulation models, which includes three parts: 1) We report on the effects of topology on failure propagation for a model system consisting of two interdependent networks. We find that the internal node correlations in each of the networks significantly changes the critical density of failures, which can trigger the total disruption of the two-network system. Specifically, we find that the assortativity within a single network decreases the robustness of the entire system. 2) We study the percolation behavior of two interdependent scale-free (SF) networks under random failure of 1-p fraction of nodes. We find that as the coupling strength q between the two networks reduces from 1 (fully coupled) to 0 (no coupling), there exist two critical coupling strengths q1 and q2 , which separate the behaviors of the giant component as a function of p into three different regions, and for q2 relationship both analytically and numerically. We study a starlike network of n Erdos-Renyi (ER), SF networks and a looplike network of n ER networks, and we find for starlike networks, their phase transition regions change with n, but for looplike networks the phase regions change with average degree k . In part II, we apply concepts and methods developed in statistical physics to study economic systems. We analyze stock market indices and foreign exchange daily returns for 60 countries over the period of 1999-2012. We build a multi-layer network model based on different correlation measures, and introduce a
Scaling-Laws of Flow Entropy with Topological Metrics of Water Distribution Networks
Giovanni Francesco Santonastaso; Armando Di Nardo; Michele Di Natale; Carlo Giudicianni; Roberto Greco
2018-01-01
Robustness of water distribution networks is related to their connectivity and topological structure, which also affect their reliability. Flow entropy, based on Shannon’s informational entropy, has been proposed as a measure of network redundancy and adopted as a proxy of reliability in optimal network design procedures. In this paper, the scaling properties of flow entropy of water distribution networks with their size and other topological metrics are studied. To such aim, flow entropy, ma...
2017-01-01
Although deep learning approaches have had tremendous success in image, video and audio processing, computer vision, and speech recognition, their applications to three-dimensional (3D) biomolecular structural data sets have been hindered by the geometric and biological complexity. To address this problem we introduce the element-specific persistent homology (ESPH) method. ESPH represents 3D complex geometry by one-dimensional (1D) topological invariants and retains important biological information via a multichannel image-like representation. This representation reveals hidden structure-function relationships in biomolecules. We further integrate ESPH and deep convolutional neural networks to construct a multichannel topological neural network (TopologyNet) for the predictions of protein-ligand binding affinities and protein stability changes upon mutation. To overcome the deep learning limitations from small and noisy training sets, we propose a multi-task multichannel topological convolutional neural network (MM-TCNN). We demonstrate that TopologyNet outperforms the latest methods in the prediction of protein-ligand binding affinities, mutation induced globular protein folding free energy changes, and mutation induced membrane protein folding free energy changes. Availability: weilab.math.msu.edu/TDL/ PMID:28749969
Time-Dependent Liquid Transport on a Biomimetic Topological Surface.
Yu, Cunlong; Li, Chuxin; Gao, Can; Dong, Zhichao; Wu, Lei; Jiang, Lei
2018-05-02
Liquid drops impacting on a solid surface is a familiar phenomenon. On rainy days, it is quite important for leaves to drain off impacting raindrops. Water can bounce off or flow down a water-repellent leaf easily, but with difficulty on a hydrophilic leaf. Here, we show an interesting phenomenon in which impacting drops on the hydrophilic pitcher rim of Nepenthes alata can spread outward to prohibit water filling the pitcher tank. We mimic the peristome surface through a designed 3D printing and replicating way and report a time-dependently switchable liquid transport based on biomimetic topological structures, where surface curvature can work synergistically with the surface microtextures to manipulate the switchable spreading performance. Motived by this strange behavior, we construct a large-scaled peristome-mimetic surface in a 3D profile, demonstrating the ability to reduce the need to mop or to squeegee drops that form during the drop impacting process on pipes or other curved surfaces in food processing, moisture transfer, heat management, etc.
Logistic control in automated transportation networks
Ebben, Mark
2001-01-01
Increasing congestion problems lead to a search for alternative transportation systems. Automated transportation networks, possibly underground, are an option. Logistic control systems are essential for future implementations of such automated transportation networks. This book contributes to the
Quantitative Efficiency Evaluation Method for Transportation Networks
Directory of Open Access Journals (Sweden)
Jin Qin
2014-11-01
Full Text Available An effective evaluation of transportation network efficiency/performance is essential to the establishment of sustainable development in any transportation system. Based on a redefinition of transportation network efficiency, a quantitative efficiency evaluation method for transportation network is proposed, which could reflect the effects of network structure, traffic demands, travel choice, and travel costs on network efficiency. Furthermore, the efficiency-oriented importance measure for network components is presented, which can be used to help engineers identify the critical nodes and links in the network. The numerical examples show that, compared with existing efficiency evaluation methods, the network efficiency value calculated by the method proposed in this paper can portray the real operation situation of the transportation network as well as the effects of main factors on network efficiency. We also find that the network efficiency and the importance values of the network components both are functions of demands and network structure in the transportation network.
An Improved Topology-Potential-Based Community Detection Algorithm for Complex Network
Directory of Open Access Journals (Sweden)
Zhixiao Wang
2014-01-01
Full Text Available Topology potential theory is a new community detection theory on complex network, which divides a network into communities by spreading outward from each local maximum potential node. At present, almost all topology-potential-based community detection methods ignore node difference and assume that all nodes have the same mass. This hypothesis leads to inaccuracy of topology potential calculation and then decreases the precision of community detection. Inspired by the idea of PageRank algorithm, this paper puts forward a novel mass calculation method for complex network nodes. A node’s mass obtained by our method can effectively reflect its importance and influence in complex network. The more important the node is, the bigger its mass is. Simulation experiment results showed that, after taking node mass into consideration, the topology potential of node is more accurate, the distribution of topology potential is more reasonable, and the results of community detection are more precise.
Graphs, Ideal Flow, and the Transportation Network
Teknomo, Kardi
2016-01-01
This lecture discusses the mathematical relationship between network structure and network utilization of transportation network. Network structure means the graph itself. Network utilization represent the aggregation of trajectories of agents in using the network graph. I show the similarity and relationship between the structural pattern of the network and network utilization.
Fracture network topology and characterization of structural permeability
Hansberry, Rowan; King, Rosalind; Holford, Simon
2017-04-01
There are two fundamental requirements for successful geothermal development: elevated temperatures at accessible depths, and a reservoir from which fluids can be extracted. The Australian geothermal sector has successfully targeted shallow heat, however, due in part to the inherent complexity of targeting permeability, obtaining adequate flow rates for commercial production has been problematic. Deep sedimentary aquifers are unlikely to be viable geothermal resources due to the effects of diagenetic mineral growth on rock permeability. Therefore, it is likely structural permeability targets, exploiting natural or induced fracture networks will provide the primary means for fluid flow in geothermal, as well as unconventional gas, reservoirs. Recent research has focused on the pattern and generation of crustal stresses across Australia, while less is known about the resultant networks of faults, joints, and veins that can constitute interconnected sub-surface permeability pathways. The ability of a fracture to transmit fluid is controlled by the orientation and magnitude of the in-situ stress field that acts on the fracture walls, rock strength, and pore pressure, as well as fracture properties such as aperture, orientation, and roughness. Understanding the distribution, orientation and character of fractures is key to predicting structural permeability. This project focuses on extensive mapping of fractures over various scales in four key Australian basins (Cooper, Otway, Surat and Perth) with the potential to host geothermal resources. Seismic attribute analysis is used in concert with image logs from petroleum wells, and field mapping to identify fracture networks that are usually not resolved in traditional seismic interpretation. We use fracture network topology to provide scale-invariant characterisation of fracture networks from multiple data sources to assess similarity between data sources, and fracture network connectivity. These results are compared with
Research on social communication network evolution based on topology potential distribution
Zhao, Dongjie; Jiang, Jian; Li, Deyi; Zhang, Haisu; Chen, Guisheng
2011-12-01
Aiming at the problem of social communication network evolution, first, topology potential is introduced to measure the local influence among nodes in networks. Second, from the perspective of topology potential distribution the method of network evolution description based on topology potential distribution is presented, which takes the artificial intelligence with uncertainty as basic theory and local influence among nodes as essentiality. Then, a social communication network is constructed by enron email dataset, the method presented is used to analyze the characteristic of the social communication network evolution and some useful conclusions are got, implying that the method is effective, which shows that topology potential distribution can effectively describe the characteristic of sociology and detect the local changes in social communication network.
Proceedings of the International Symposium on Topological Aspects of Critical Systems and Networks
Yakubo, Kousuke; Amitsuka, Hiroshi; Ishikawa, Goo; Machino, Kazuo; Nakagaki, Toshiyuki; Tanda, Satoshi; Yamada, Hideto; Kichiji, Nozomi
2007-07-01
I. General properties of networks. Physics of network security / Y.-C. Lai, X. Wand and C. H. Lai. Multi-state interacting particle systems on scale-free networks / N. Masuda and N. Konno. Homotopy Reduction of Complex Networks 18 / Y. Hiraoka and T. Ichinomiya. Analysis of the Susceptible-Infected-Susceptible Model on Complex Network / T. Ichinomiya -- II. Complexity in social science. Innovation and Development in a Random Lattice / J. Lahtinen. Long-tailed distributions in biological systems: revisit to Lognormals / N. Kobayashi ... [et al.]. Two-class structure of income distribution in the USA:exponential bulk and power-law tail / V. M. Yakovenko and A. Christian Silva. Power Law distributions in two community currencies / N. Kichiji and M. Nishibe -- III. Patterns in biological objects. Stoichiometric network analysis of nonlinear phenomena in rection mechanism for TWC converters / M. Marek ... [et al.]. Collective movement and morphogenesis of epithelial cells / H. Haga and K. Kawabata. Indecisive behavior of amoeba crossing an environmental barrier / S. Takagi ... [et al.]. Effects of amount of food on path selection in the transport network of an amoeboid organism / T. Nakagaki ... [et al.]. Light scattering study in double network gels / M. Fukunaya ... [et al.].Blood flow velocity in the choroid in punctate inner choroidopathy and Vogt-Koyanagi-Harada disease; amd multifractal analysis of choroidal blood flow in age-related macular degeneration / K. Yoshida ... [et al.]. Topological analysis of placental arteries: correlation with neonatal growth / H. Yamada and K. Yakubo -- IV. Criticality in pure and applied physics. Droplets in Disordered Metallic Quantum Critical Systems / A. H. Castro Neto and B. A. Jones. Importance of static disorder and inhomogeneous cooperative dynamics in heavy-fermion metals / O. O. Bernal. Competition between spin glass and Antiferromagnetic phases in heavy fermion materials / S. Sullow. Emergent Phases via Fermi surface
Laurito, Andres; The ATLAS collaboration
2017-01-01
Simulation is an important tool to validate the performance impact of control decisions in Software Defined Networks (SDN). Yet, the manual modeling of complex topologies that may change often during a design process can be a tedious error-prone task. We present TopoGen, a general purpose architecture and tool for systematic translation and generation of network topologies. TopoGen can be used to generate network simulation models automatically by querying information available at diverse sources, notably SDN controllers. The DEVS modeling and simulation framework facilitates a systematic translation of structured knowledge about a network topology into a formal modular and hierarchical coupling of preexisting or new models of network entities (physical or logical). TopoGen can be flexibly extended with new parsers and generators to grow its scope of applicability. This permits to design arbitrary workflows of topology transformations. We tested TopoGen in a network engineering project for the ATLAS detector ...
Laurito, Andres; The ATLAS collaboration
2018-01-01
Simulation is an important tool to validate the performance impact of control decisions in Software Defined Networks (SDN). Yet, the manual modeling of complex topologies that may change often during a design process can be a tedious error-prone task. We present TopoGen, a general purpose architecture and tool for systematic translation and generation of network topologies. TopoGen can be used to generate network simulation models automatically by querying information available at diverse sources, notably SDN controllers. The DEVS modeling and simulation framework facilitates a systematic translation of structured knowledge about a network topology into a formal modular and hierarchical coupling of preexisting or new models of network entities (physical or logical). TopoGen can be flexibly extended with new parsers and generators to grow its scope of applicability. This permits to design arbitrary workflows of topology transformations. We tested TopoGen in a network engineering project for the ATLAS detector ...
Directory of Open Access Journals (Sweden)
Hui He
2013-01-01
Full Text Available It is of great significance to research the early warning system for large-scale network security incidents. It can improve the network system’s emergency response capabilities, alleviate the cyber attacks’ damage, and strengthen the system’s counterattack ability. A comprehensive early warning system is presented in this paper, which combines active measurement and anomaly detection. The key visualization algorithm and technology of the system are mainly discussed. The large-scale network system’s plane visualization is realized based on the divide and conquer thought. First, the topology of the large-scale network is divided into some small-scale networks by the MLkP/CR algorithm. Second, the sub graph plane visualization algorithm is applied to each small-scale network. Finally, the small-scale networks’ topologies are combined into a topology based on the automatic distribution algorithm of force analysis. As the algorithm transforms the large-scale network topology plane visualization problem into a series of small-scale network topology plane visualization and distribution problems, it has higher parallelism and is able to handle the display of ultra-large-scale network topology.
Topology and robustness in the Drosophila segment polarity network.
Directory of Open Access Journals (Sweden)
Nicholas T Ingolia
2004-06-01
Full Text Available A complex hierarchy of genetic interactions converts a single-celled Drosophila melanogaster egg into a multicellular embryo with 14 segments. Previously, von Dassow et al. reported that a mathematical model of the genetic interactions that defined the polarity of segments (the segment polarity network was robust (von Dassow et al. 2000. As quantitative information about the system was unavailable, parameters were sampled randomly. A surprisingly large fraction of these parameter sets allowed the model to maintain and elaborate on the segment polarity pattern. This robustness is due to the positive feedback of gene products on their own expression, which induces individual cells in a model segment to adopt different stable expression states (bistability corresponding to different cell types in the segment polarity pattern. A positive feedback loop will only yield multiple stable states when the parameters that describe it satisfy a particular inequality. By testing which random parameter sets satisfy these inequalities, I show that bistability is necessary to form the segment polarity pattern and serves as a strong predictor of which parameter sets will succeed in forming the pattern. Although the original model was robust to parameter variation, it could not reproduce the observed effects of cell division on the pattern of gene expression. I present a modified version that incorporates recent experimental evidence and does successfully mimic the consequences of cell division. The behavior of this modified model can also be understood in terms of bistability in positive feedback of gene expression. I discuss how this topological property of networks provides robust pattern formation and how large changes in parameters can change the specific pattern produced by a network.
Expected Number of Fixed Points in Boolean Networks with Arbitrary Topology.
Mori, Fumito; Mochizuki, Atsushi
2017-07-14
Boolean network models describe genetic, neural, and social dynamics in complex networks, where the dynamics depend generally on network topology. Fixed points in a genetic regulatory network are typically considered to correspond to cell types in an organism. We prove that the expected number of fixed points in a Boolean network, with Boolean functions drawn from probability distributions that are not required to be uniform or identical, is one, and is independent of network topology if only a feedback arc set satisfies a stochastic neutrality condition. We also demonstrate that the expected number is increased by the predominance of positive feedback in a cycle.
International Nuclear Information System (INIS)
Ni, Xu; He, Cheng; Sun, Xiao-Chen; Liu, Xiao-ping; Lu, Ming-Hui; Chen, Yan-Feng; Feng, Liang
2015-01-01
Recent explorations of topology in physical systems have led to a new paradigm of condensed matters characterized by topologically protected states and phase transition, for example, topologically protected photonic crystals enabled by magneto-optical effects. However, in other wave systems such as acoustics, topological states cannot be simply reproduced due to the absence of similar magnetics-related sound–matter interactions in naturally available materials. Here, we propose an acoustic topological structure by creating an effective gauge magnetic field for sound using circularly flowing air in the designed acoustic ring resonators. The created gauge magnetic field breaks the time-reversal symmetry, and therefore topological properties can be designed to be nontrivial with non-zero Chern numbers and thus to enable a topological sonic crystal, in which the topologically protected acoustic edge-state transport is observed, featuring robust one-way propagation characteristics against a variety of topological defects and impurities. Our results open a new venue to non-magnetic topological structures and promise a unique approach to effective manipulation of acoustic interfacial transport at will. (paper)
Directory of Open Access Journals (Sweden)
WenJun Zhang
2014-06-01
Full Text Available In present study we used self-organizing map (SOM neural network to conduct the non-supervisory clustering of invertebrate orders in rice field. Four topological functions, i.e., cossintopf, sincostopf, acossintopf, and expsintopf, established on the template in toolbox of Matlab, were used in SOM neural network learning. Results showed that clusters were different when using different topological functions because different topological functions will generate different spatial structure of neurons in neural network. We may chose these functions and results based on comparison with the practical situation.
2013-05-01
Interconnection ( OSI ) network model for the engine control application. Figure 1 summarizes the OSI network model, which is comprised by 7 layers [21]. In...59th International Instrumentation Symposium; http://www.isa.org Approved for public release; distribution unlimited. 7 Figure 1: OSI Network...21st International Conference on, pages 3–7. IEEE, 2011. [9] LAN Network Topologies. http://www.firewall.cx/networking-topics/general- networking/103
Altered network topology in pediatric traumatic brain injury
Dennis, Emily L.; Rashid, Faisal; Babikian, Talin; Mink, Richard; Babbitt, Christopher; Johnson, Jeffrey; Giza, Christopher C.; Asarnow, Robert F.; Thompson, Paul M.
2017-11-01
Outcome after a traumatic brain injury (TBI) is quite variable, and this variability is not solely accounted for by severity or demographics. Identifying sub-groups of patients who recover faster or more fully will help researchers and clinicians understand sources of this variability, and hopefully lead to new therapies for patients with a more prolonged recovery profile. We have previously identified two subgroups within the pediatric TBI patient population with different recovery profiles based on an ERP-derived (event-related potential) measure of interhemispheric transfer time (IHTT). Here we examine structural network topology across both patient groups and healthy controls, focusing on the `rich-club' - the core of the network, marked by high degree nodes. These analyses were done at two points post-injury - 2-5 months (post-acute), and 13-19 months (chronic). In the post-acute time-point, we found that the TBI-slow group, those showing longitudinal degeneration, showed hyperconnectivity within the rich-club nodes relative to the healthy controls, at the expense of local connectivity. There were minimal differences between the healthy controls and the TBI-normal group (those patients who show signs of recovery). At the chronic phase, these disruptions were no longer significant, but closer analysis showed that this was likely due to the loss of power from a smaller sample size at the chronic time-point, rather than a sign of recovery. We have previously shown disruptions to white matter (WM) integrity that persist and progress over time in the TBI-slow group, and here we again find differences in the TBI-slow group that fail to resolve over the first year post-injury.
UPGRADE FOR HARDWARE/SOFTWARE SERVER AND NETWORK TOPOLOGY IN INFORMATION SYSTEMS
Directory of Open Access Journals (Sweden)
Oleksii O. Kaplun
2011-02-01
Full Text Available The network modernization, educational information systems software and hardware updates problem is actual in modern term of information technologies prompt development. There are server applications and network topology of Institute of Information Technology and Learning Tools of National Academy of Pedagogical Sciences of Ukraine analysis and their improvement methods expound in the article. The article materials represent modernization results implemented to increase network efficiency and reliability, decrease response time in Institute’s network information systems. The article gives diagrams of network topology before upgrading and after finish of optimization and upgrading processes.
Regions, Networks and Fluids: Anaemia and Social Topology
Mol, A.M.; Law, John
1994-01-01
This is a paper about the topological presuppositions that frame the performance of social similarity and difference. It argues that 'the social' does not exist as a single spatial type, but rather performs itself in a recursive and topologically heterogeneous manner. Using material drawn from a
Exploitation of complex network topology for link prediction in biological interactomes
Alanis Lobato, Gregorio
2014-01-01
In this work, we propose three novel and powerful approaches for the prediction of interactions in biological networks and conclude that it is possible to mine the topology of these complex system representations and produce reliable
Comparing Mycobacterium tuberculosis genomes using genome topology networks.
Jiang, Jianping; Gu, Jianlei; Zhang, Liang; Zhang, Chenyi; Deng, Xiao; Dou, Tonghai; Zhao, Guoping; Zhou, Yan
2015-02-14
Over the last decade, emerging research methods, such as comparative genomic analysis and phylogenetic study, have yielded new insights into genotypes and phenotypes of closely related bacterial strains. Several findings have revealed that genomic structural variations (SVs), including gene gain/loss, gene duplication and genome rearrangement, can lead to different phenotypes among strains, and an investigation of genes affected by SVs may extend our knowledge of the relationships between SVs and phenotypes in microbes, especially in pathogenic bacteria. In this work, we introduce a 'Genome Topology Network' (GTN) method based on gene homology and gene locations to analyze genomic SVs and perform phylogenetic analysis. Furthermore, the concept of 'unfixed ortholog' has been proposed, whose members are affected by SVs in genome topology among close species. To improve the precision of 'unfixed ortholog' recognition, a strategy to detect annotation differences and complete gene annotation was applied. To assess the GTN method, a set of thirteen complete M. tuberculosis genomes was analyzed as a case study. GTNs with two different gene homology-assigning methods were built, the Clusters of Orthologous Groups (COG) method and the orthoMCL clustering method, and two phylogenetic trees were constructed accordingly, which may provide additional insights into whole genome-based phylogenetic analysis. We obtained 24 unfixable COG groups, of which most members were related to immunogenicity and drug resistance, such as PPE-repeat proteins (COG5651) and transcriptional regulator TetR gene family members (COG1309). The GTN method has been implemented in PERL and released on our website. The tool can be downloaded from http://homepage.fudan.edu.cn/zhouyan/gtn/ , and allows re-annotating the 'lost' genes among closely related genomes, analyzing genes affected by SVs, and performing phylogenetic analysis. With this tool, many immunogenic-related and drug resistance-related genes
Biological transportation networks: Modeling and simulation
Albi, Giacomo; Artina, Marco; Foransier, Massimo; Markowich, Peter A.
2015-01-01
We present a model for biological network formation originally introduced by Cai and Hu [Adaptation and optimization of biological transport networks, Phys. Rev. Lett. 111 (2013) 138701]. The modeling of fluid transportation (e.g., leaf venation
Chen, Qing; Zhang, Jinxiu; Hu, Ze
2017-02-23
This article investigates the dynamic topology control problemof satellite cluster networks (SCNs) in Earth observation (EO) missions by applying a novel metric of stability for inter-satellite links (ISLs). The properties of the periodicity and predictability of satellites' relative position are involved in the link cost metric which is to give a selection criterion for choosing the most reliable data routing paths. Also, a cooperative work model with reliability is proposed for the situation of emergency EO missions. Based on the link cost metric and the proposed reliability model, a reliability assurance topology control algorithm and its corresponding dynamic topology control (RAT) strategy are established to maximize the stability of data transmission in the SCNs. The SCNs scenario is tested through some numeric simulations of the topology stability of average topology lifetime and average packet loss rate. Simulation results show that the proposed reliable strategy applied in SCNs significantly improves the data transmission performance and prolongs the average topology lifetime.
Capacity Extension of Software Defined Data Center Networks With Jellyfish Topology
DEFF Research Database (Denmark)
Mehmeri, Victor; Vegas Olmos, Juan José; Tafur Monroy, Idelfonso
We present a performance analysis of Jellyfish topology with Software-Defined commodity switches for Data Center networks. Our results show up to a 2-fold performance gain when compared to a Spanning Tree Protocol implementation.......We present a performance analysis of Jellyfish topology with Software-Defined commodity switches for Data Center networks. Our results show up to a 2-fold performance gain when compared to a Spanning Tree Protocol implementation....
Impact of Network Coding on Delay and Throughput in Practical Wireless Chain Topologies
DEFF Research Database (Denmark)
Hundebøll, Martin; Rein, Stephan Alexander; Fitzek, Frank
2013-01-01
In this paper, we present results from a practical evaluation of network coding in a setup consisting of eight nodes deployed in a chain topology. With the tradition pure relaying, delay increases dramatically as the network gets congested, and here network coding helps to moderate this increase ...
Knabe, Johannes F; Nehaniv, Chrystopher L; Schilstra, Maria J
2008-01-01
Methods that analyse the topological structure of networks have recently become quite popular. Whether motifs (subgraph patterns that occur more often than in randomized networks) have specific functions as elementary computational circuits has been cause for debate. As the question is difficult to resolve with currently available biological data, we approach the issue using networks that abstractly model natural genetic regulatory networks (GRNs) which are evolved to show dynamical behaviors. Specifically one group of networks was evolved to be capable of exhibiting two different behaviors ("differentiation") in contrast to a group with a single target behavior. In both groups we find motif distribution differences within the groups to be larger than differences between them, indicating that evolutionary niches (target functions) do not necessarily mold network structure uniquely. These results show that variability operators can have a stronger influence on network topologies than selection pressures, especially when many topologies can create similar dynamics. Moreover, analysis of motif functional relevance by lesioning did not suggest that motifs were of greater importance to the functioning of the network than arbitrary subgraph patterns. Only when drastically restricting network size, so that one motif corresponds to a whole functionally evolved network, was preference for particular connection patterns found. This suggests that in non-restricted, bigger networks, entanglement with the rest of the network hinders topological subgraph analysis.
Gene regulatory and signaling networks exhibit distinct topological distributions of motifs
Ferreira, Gustavo Rodrigues; Nakaya, Helder Imoto; Costa, Luciano da Fontoura
2018-04-01
The biological processes of cellular decision making and differentiation involve a plethora of signaling pathways and gene regulatory circuits. These networks in turn exhibit a multitude of motifs playing crucial parts in regulating network activity. Here we compare the topological placement of motifs in gene regulatory and signaling networks and observe that it suggests different evolutionary strategies in motif distribution for distinct cellular subnetworks.
Review of Network Topologies and Protection Principles in Marine and Offshore Applications
DEFF Research Database (Denmark)
Ciontea, Catalin-Iosif; Bak, Claus Leth; Blaabjerg, Frede
2015-01-01
An electric fault that is not cleared is harmful in land applications, but in marine and offshore sector it can have catastrophic consequences. If the protection system fails to operate properly, the following situation may occur: blackouts, fire, loss of propulsion, delays in transportation......, collision with the cliff, reef or other ships and electrical shocks to humans. In order to cope with the unwanted effects of a fault, several protection strategies are applied, but complexity of the marine and offshore applications is continuously increasing, so protection needs to overcome more and more...... challenges. As result, development of new protection techniques that can offer improved functionalities compared to the actual solutions for marine and offshore applications is needed. This paper reviews the network topologies in such applications and presents the requirements of a system able to protect...
Energy-Aware Topology Evolution Model with Link and Node Deletion in Wireless Sensor Networks
Directory of Open Access Journals (Sweden)
Xiaojuan Luo
2012-01-01
Full Text Available Based on the complex network theory, a new topological evolving model is proposed. In the evolution of the topology of sensor networks, the energy-aware mechanism is taken into account, and the phenomenon of change of the link and node in the network is discussed. Theoretical analysis and numerical simulation are conducted to explore the topology characteristics and network performance with different node energy distribution. We find that node energy distribution has the weak effect on the degree distribution P(k that evolves into the scale-free state, nodes with more energy carry more connections, and degree correlation is nontrivial disassortative. Moreover, the results show that, when nodes energy is more heterogeneous, the network is better clustered and enjoys higher performance in terms of the network efficiency and the average path length for transmitting data.
Toward a Robust Method of Presenting a Rich, Interconnected Deceptive Network Topology
2015-03-01
SDN Software - Defined Networking SNOS Systemic Network Obfuscation System SSH Secure Shell TCP Transmission Control Protocol TTL time to...same DeTracer functionality directly on routers. One particularly interesting research area would be the use of Software - Defined Networking ( SDN ) to...Hughes, “Employing deceptive dynamic network topology through software - defined networking ,” M.S. thesis, Dept. Comput. Sci., Naval
Enquiry into the Topology of Plasma Membrane-Localized PIN Auxin Transport Components.
Nodzyński, Tomasz; Vanneste, Steffen; Zwiewka, Marta; Pernisová, Markéta; Hejátko, Jan; Friml, Jiří
2016-11-07
Auxin directs plant ontogenesis via differential accumulation within tissues depending largely on the activity of PIN proteins that mediate auxin efflux from cells and its directional cell-to-cell transport. Regardless of the developmental importance of PINs, the structure of these transporters is poorly characterized. Here, we present experimental data concerning protein topology of plasma membrane-localized PINs. Utilizing approaches based on pH-dependent quenching of fluorescent reporters combined with immunolocalization techniques, we mapped the membrane topology of PINs and further cross-validated our results using available topology modeling software. We delineated the topology of PIN1 with two transmembrane (TM) bundles of five α-helices linked by a large intracellular loop and a C-terminus positioned outside the cytoplasm. Using constraints derived from our experimental data, we also provide an updated position of helical regions generating a verisimilitude model of PIN1. Since the canonical long PINs show a high degree of conservation in TM domains and auxin transport capacity has been demonstrated for Arabidopsis representatives of this group, this empirically enhanced topological model of PIN1 will be an important starting point for further studies on PIN structure-function relationships. In addition, we have established protocols that can be used to probe the topology of other plasma membrane proteins in plants. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.
International Nuclear Information System (INIS)
Hobbs, L.W.; Jesurum, C.E.; Pulim, V.
1997-01-01
Topology is shown to govern the arrangement of connected structural elements in network glasses such as silica and related radiation-amorphized network compounds: A topological description of such topologically-disordered arrangements is possible which utilizes a characteristic unit of structure--the local cluster--not far in scale from the unit cells in crystalline arrangements. Construction of credible glass network structures and their aberration during cascade disordering events during irradiation can be effected using local assembly rules based on modification of connectivity-based assembly rules derived for crystalline analogues. These topological approaches may provide useful complementary information to that supplied by molecular dynamics about re-ordering routes and final configurations in irradiated glasses. (authors)
Energy Technology Data Exchange (ETDEWEB)
Hobbs, L.W. [Massachusetts Institute of Technology, Dept. of Materials Science and Engineering, Cambridge, MA (United States); Jesurum, C.E. [Massachusetts Institute of Technology, Dept. of Mathematics, Cambridge, MA (United States); Pulim, V. [Massachusetts Institute of Technology, Lab. for Computer Science, Cambridge, MA (United States)
1997-07-01
Topology is shown to govern the arrangement of connected structural elements in network glasses such as silica and related radiation-amorphized network compounds: A topological description of such topologically-disordered arrangements is possible which utilizes a characteristic unit of structure--the local cluster--not far in scale from the unit cells in crystalline arrangements. Construction of credible glass network structures and their aberration during cascade disordering events during irradiation can be effected using local assembly rules based on modification of connectivity-based assembly rules derived for crystalline analogues. These topological approaches may provide useful complementary information to that supplied by molecular dynamics about re-ordering routes and final configurations in irradiated glasses. (authors)
Directory of Open Access Journals (Sweden)
Y. Damchi
2015-09-01
Full Text Available Most studies in relay coordination have focused solely on coordination of overcurrent relays while distance relays are used as the main protection of transmission lines. Since, simultaneous coordination of these two types of relays can provide a better protection, in this paper, a new approach is proposed for simultaneous coordination of distance and directional overcurrent relays (D&DOCRs. Also, pursued by most of the previously published studies, the settings of D&DOCRs are usually determined based on a main network topology which may result in mis-coordination of relays when changes occur in the network topology. In the proposed method, in order to have a robust coordination, network topology changes are taken into account in the coordination problem. In the new formulation, coordination constraints for different network topologies are added to those of the main topology. A complex nonlinear optimization problem is derived to find the desirable relay settings. Then, the problem is solved using hybridized genetic algorithm (GA with linear programming (LP method (HGA. The proposed method is evaluated using the IEEE 14-bus test system. According to the results, a feasible and robust solution is obtained for D&DOCRs coordination while all constraints, which are due to different network topologies, are satisfied.
Fault-tolerant topology in the wireless sensor networks for energy depletion and random failure
International Nuclear Information System (INIS)
Liu Bin; Dong Ming-Ru; Yin Rong-Rong; Yin Wen-Xiao
2014-01-01
Nodes in the wireless sensor networks (WSNs) are prone to failure due to energy depletion and poor environment, which could have a negative impact on the normal operation of the network. In order to solve this problem, in this paper, we build a fault-tolerant topology which can effectively tolerate energy depletion and random failure. Firstly, a comprehensive failure model about energy depletion and random failure is established. Then an improved evolution model is presented to generate a fault-tolerant topology, and the degree distribution of the topology can be adjusted. Finally, the relation between the degree distribution and the topological fault tolerance is analyzed, and the optimal value of evolution model parameter is obtained. Then the target fault-tolerant topology which can effectively tolerate energy depletion and random failure is obtained. The performances of the new fault tolerant topology are verified by simulation experiments. The results show that the new fault tolerant topology effectively prolongs the network lifetime and has strong fault tolerance. (general)
Real-space mapping of topological invariants using artificial neural networks
Carvalho, D.; García-Martínez, N. A.; Lado, J. L.; Fernández-Rossier, J.
2018-03-01
Topological invariants allow one to characterize Hamiltonians, predicting the existence of topologically protected in-gap modes. Those invariants can be computed by tracing the evolution of the occupied wave functions under twisted boundary conditions. However, those procedures do not allow one to calculate a topological invariant by evaluating the system locally, and thus require information about the wave functions in the whole system. Here we show that artificial neural networks can be trained to identify the topological order by evaluating a local projection of the density matrix. We demonstrate this for two different models, a one-dimensional topological superconductor and a two-dimensional quantum anomalous Hall state, both with spatially modulated parameters. Our neural network correctly identifies the different topological domains in real space, predicting the location of in-gap states. By combining a neural network with a calculation of the electronic states that uses the kernel polynomial method, we show that the local evaluation of the invariant can be carried out by evaluating a local quantity, in particular for systems without translational symmetry consisting of tens of thousands of atoms. Our results show that supervised learning is an efficient methodology to characterize the local topology of a system.
Heuristic urban transportation network design method, a multilayer coevolution approach
Ding, Rui; Ujang, Norsidah; Hamid, Hussain bin; Manan, Mohd Shahrudin Abd; Li, Rong; Wu, Jianjun
2017-08-01
The design of urban transportation networks plays a key role in the urban planning process, and the coevolution of urban networks has recently garnered significant attention in literature. However, most of these recent articles are based on networks that are essentially planar. In this research, we propose a heuristic multilayer urban network coevolution model with lower layer network and upper layer network that are associated with growth and stimulate one another. We first use the relative neighbourhood graph and the Gabriel graph to simulate the structure of rail and road networks, respectively. With simulation we find that when a specific number of nodes are added, the total travel cost ratio between an expanded network and the initial lower layer network has the lowest value. The cooperation strength Λ and the changeable parameter average operation speed ratio Θ show that transit users' route choices change dramatically through the coevolution process and that their decisions, in turn, affect the multilayer network structure. We also note that the simulated relation between the Gini coefficient of the betweenness centrality, Θ and Λ have an optimal point for network design. This research could inspire the analysis of urban network topology features and the assessment of urban growth trends.
Papapostolou, Vassilios
2017-09-11
Enstrophy is an intrinsic feature of turbulent flows, and its transport properties are essential for the understanding of premixed flame-turbulence interaction. The interrelation between the enstrophy transport and flow topologies, which can be assigned to eight categories based on the three invariants of the velocity-gradient tensor, has been analysed here. The enstrophy transport conditional on flow topologies in turbulent premixed flames has been analysed using a Direct Numerical Simulation database representing the corrugated flamelets (CF), thin reaction zones (TRZ) and broken reaction zones (BRZ) combustion regimes. The flame in the CF regime exhibits considerable flame-generated enstrophy, and the dilatation rate and baroclinic torque contributions to the enstrophy transport act as leading order sink and source terms, respectively. Consequently, flow topologies associated with positive dilatation rate values, contribute significantly to the enstrophy transport in the CF regime. By contrast, enstrophy decreases from the unburned to the burned gas side for the cases representing the TRZ and BRZ regimes, with diminishing influences of dilatation rate and baroclinic torque. The enstrophy transport in the TRZ and BRZ regimes is governed by the vortex-stretching and viscous dissipation contributions, similar to non-reacting flows, and topologies existing for all values of dilatation rate remain significant contributors.
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.
Automated and comprehensive link engineering supporting branched, ring, and mesh network topologies
Farina, J.; Khomchenko, D.; Yevseyenko, D.; Meester, J.; Richter, A.
2016-02-01
Link design, while relatively easy in the past, can become quite cumbersome with complex channel plans and equipment configurations. The task of designing optical transport systems and selecting equipment is often performed by an applications or sales engineer using simple tools, such as custom Excel spreadsheets. Eventually, every individual has their own version of the spreadsheet as well as their own methodology for building the network. This approach becomes unmanageable very quickly and leads to mistakes, bending of the engineering rules and installations that do not perform as expected. We demonstrate a comprehensive planning environment, which offers an efficient approach to unify, control and expedite the design process by controlling libraries of equipment and engineering methodologies, automating the process and providing the analysis tools necessary to predict system performance throughout the system and for all channels. In addition to the placement of EDFAs and DCEs, performance analysis metrics are provided at every step of the way. Metrics that can be tracked include power, CD and OSNR, SPM, XPM, FWM and SBS. Automated routine steps assist in design aspects such as equalization, padding and gain setting for EDFAs, the placement of ROADMs and transceivers, and creating regeneration points. DWDM networks consisting of a large number of nodes and repeater huts, interconnected in linear, branched, mesh and ring network topologies, can be designed much faster when compared with conventional design methods. Using flexible templates for all major optical components, our technology-agnostic planning approach supports the constant advances in optical communications.
M-Polynomials and Topological Indices of Dominating David Derived Networks
Directory of Open Access Journals (Sweden)
Kang Shin Min
2018-03-01
Full Text Available There is a strong relationship between the chemical characteristics of chemical compounds and their molecular structures. Topological indices are numerical values associated with the chemical molecular graphs that help to understand the physical features, chemical reactivity, and biological activity of chemical compound. Thus, the study of the topological indices is important. M-polynomial helps to recover many degree-based topological indices for example Zagreb indices, Randic index, symmetric division idex, inverse sum index etc. In this article we compute M-polynomials of dominating David derived networks of the first type, second type and third type of dimension n and find some topological properties by using these M-polynomials. The results are plotted using Maple to see the dependence of topological indices on the involved parameters.
Wen, Hongwei; Liu, Yue; Rekik, Islem; Wang, Shengpei; Zhang, Jishui; Zhang, Yue; Peng, Yun; He, Huiguang
2017-08-01
Tourette syndrome (TS) is a childhood-onset neurobehavioral disorder. Although previous TS studies revealed structural abnormalities in distinct corticobasal ganglia circuits, the topological alterations of the whole-brain white matter (WM) structural networks remain poorly understood. Here, we used diffusion MRI probabilistic tractography and graph theoretical analysis to investigate the topological organization of WM networks in 44 drug-naive TS children and 41 age- and gender-matched healthy children. The WM networks were constructed by estimating inter-regional connectivity probability and the topological properties were characterized using graph theory. We found that both TS and control groups showed an efficient small-world organization in WM networks. However, compared to controls, TS children exhibited decreased global and local efficiency, increased shortest path length and small worldness, indicating a disrupted balance between local specialization and global integration in structural networks. Although both TS and control groups showed highly similar hub distributions, TS children exhibited significant decreased nodal efficiency, mainly distributed in the default mode, language, visual, and sensorimotor systems. Furthermore, two separate networks showing significantly decreased connectivity in TS group were identified using network-based statistical (NBS) analysis, primarily composed of the parieto-occipital cortex, precuneus, and paracentral lobule. Importantly, we combined support vector machine and multiple kernel learning frameworks to fuse multiple levels of network topological features for classification of individuals, achieving high accuracy of 86.47%. Together, our study revealed the disrupted topological organization of structural networks related to pathophysiology of TS, and the discriminative topological features for classification are potential quantitative neuroimaging biomarkers for clinical TS diagnosis. Hum Brain Mapp 38:3988-4008, 2017
Next Generation Reliable Transport Networks
DEFF Research Database (Denmark)
Zhang, Jiang
the wavelength and fiber assignment problem is proposed and implemented for avionic optical transport networks. Simulation results give out resource consumptions and prove the efficiency of the proposed mechanisms. Finally, a Home Environment Service Knowledge Management system is proposed. Through ontology...... technologies, a knowledge base is constructed to represent the whole information of a home environment. By applying the reasoner tool, the proposed system manages to keep the consistency in a home environment and helps all software configure and update procedures across multiple vendors....... of criticality and security, there are certain physical or logical segregation requirements between the avionic systems. Such segregations can be implemented on the proposed avionic networks with different hierarchies. In order to fulfill the segregation requirements, a tailored heuristic approach for solving...
Effect of network topology on the spreading of technologies
International Nuclear Information System (INIS)
Kocsis, G.; Kun, F.
2007-01-01
statistics. We showed that the topology of social contacts of agents plays a significant role in the spreading of telecommunication technologies. To make the model more realistic we considered networks of agents with small-world and scale-free properties. Based on computer simulations we showed that a complex system of a large number of local communities is more favorable for the spreading of technologies than a fully interconnected one
Transport on river networks: A dynamical approach
Zaliapin, I; Foufoula-Georgiou, E; Ghil, M
2017-01-01
This study is motivated by problems related to environmental transport on river networks. We establish statistical properties of a flow along a directed branching network and suggest its compact parameterization. The downstream network transport is treated as a particular case of nearest-neighbor hierarchical aggregation with respect to the metric induced by the branching structure of the river network. We describe the static geometric structure of a drainage network by a tree, referred to as...
Brain Network Analysis: Separating Cost from Topology Using Cost-Integration
Ginestet, Cedric E.; Nichols, Thomas E.; Bullmore, Ed T.; Simmons, Andrew
2011-01-01
A statistically principled way of conducting brain network analysis is still lacking. Comparison of different populations of brain networks is hard because topology is inherently dependent on wiring cost, where cost is defined as the number of edges in an unweighted graph. In this paper, we evaluate the benefits and limitations associated with using cost-integrated topological metrics. Our focus is on comparing populations of weighted undirected graphs that differ in mean association weight, using global efficiency. Our key result shows that integrating over cost is equivalent to controlling for any monotonic transformation of the weight set of a weighted graph. That is, when integrating over cost, we eliminate the differences in topology that may be due to a monotonic transformation of the weight set. Our result holds for any unweighted topological measure, and for any choice of distribution over cost levels. Cost-integration is therefore helpful in disentangling differences in cost from differences in topology. By contrast, we show that the use of the weighted version of a topological metric is generally not a valid approach to this problem. Indeed, we prove that, under weak conditions, the use of the weighted version of global efficiency is equivalent to simply comparing weighted costs. Thus, we recommend the reporting of (i) differences in weighted costs and (ii) differences in cost-integrated topological measures with respect to different distributions over the cost domain. We demonstrate the application of these techniques in a re-analysis of an fMRI working memory task. We also provide a Monte Carlo method for approximating cost-integrated topological measures. Finally, we discuss the limitations of integrating topology over cost, which may pose problems when some weights are zero, when multiplicities exist in the ranks of the weights, and when one expects subtle cost-dependent topological differences, which could be masked by cost-integration. PMID:21829437
Brain network analysis: separating cost from topology using cost-integration.
Directory of Open Access Journals (Sweden)
Cedric E Ginestet
Full Text Available A statistically principled way of conducting brain network analysis is still lacking. Comparison of different populations of brain networks is hard because topology is inherently dependent on wiring cost, where cost is defined as the number of edges in an unweighted graph. In this paper, we evaluate the benefits and limitations associated with using cost-integrated topological metrics. Our focus is on comparing populations of weighted undirected graphs that differ in mean association weight, using global efficiency. Our key result shows that integrating over cost is equivalent to controlling for any monotonic transformation of the weight set of a weighted graph. That is, when integrating over cost, we eliminate the differences in topology that may be due to a monotonic transformation of the weight set. Our result holds for any unweighted topological measure, and for any choice of distribution over cost levels. Cost-integration is therefore helpful in disentangling differences in cost from differences in topology. By contrast, we show that the use of the weighted version of a topological metric is generally not a valid approach to this problem. Indeed, we prove that, under weak conditions, the use of the weighted version of global efficiency is equivalent to simply comparing weighted costs. Thus, we recommend the reporting of (i differences in weighted costs and (ii differences in cost-integrated topological measures with respect to different distributions over the cost domain. We demonstrate the application of these techniques in a re-analysis of an fMRI working memory task. We also provide a Monte Carlo method for approximating cost-integrated topological measures. Finally, we discuss the limitations of integrating topology over cost, which may pose problems when some weights are zero, when multiplicities exist in the ranks of the weights, and when one expects subtle cost-dependent topological differences, which could be masked by cost-integration.
Guaranteed cost control of mobile sensor networks with Markov switching topologies.
Zhao, Yuan; Guo, Ge; Ding, Lei
2015-09-01
This paper investigates the consensus seeking problem of mobile sensor networks (MSNs) with random switching topologies. The network communication topologies are composed of a set of directed graphs (or digraph) with a spanning tree. The switching of topologies is governed by a Markov chain. The consensus seeking problem is addressed by introducing a global topology-aware linear quadratic (LQ) cost as the performance measure. By state transformation, the consensus problem is transformed to the stabilization of a Markovian jump system with guaranteed cost. A sufficient condition for global mean-square consensus is derived in the context of stochastic stability analysis of Markovian jump systems. A computational algorithm is given to synchronously calculate both the sub-optimal consensus controller gains and the sub-minimum upper bound of the cost. The effectiveness of the proposed design method is illustrated by three numerical examples. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.
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 .
Debnath, Lokenath
2010-01-01
This article is essentially devoted to a brief historical introduction to Euler's formula for polyhedra, topology, theory of graphs and networks with many examples from the real-world. Celebrated Konigsberg seven-bridge problem and some of the basic properties of graphs and networks for some understanding of the macroscopic behaviour of real…
Low-dimensional morphospace of topological motifs in human fMRI brain networks
Directory of Open Access Journals (Sweden)
Sarah E. Morgan
2018-06-01
Full Text Available We present a low-dimensional morphospace of fMRI brain networks, where axes are defined in a data-driven manner based on the network motifs. The morphospace allows us to identify the key variations in healthy fMRI networks in terms of their underlying motifs, and we observe that two principal components (PCs can account for 97% of the motif variability. The first PC of the motif distribution is correlated with efficiency and inversely correlated with transitivity. Hence this axis approximately conforms to the well-known economical small-world trade-off between integration and segregation in brain networks. Finally, we show that the economical clustering generative model proposed by Vértes et al. (2012 can approximately reproduce the motif morphospace of the real fMRI brain networks, in contrast to other generative models. Overall, the motif morphospace provides a powerful way to visualize the relationships between network properties and to investigate generative or constraining factors in the formation of complex human brain functional networks. Motifs have been described as the building blocks of complex networks. Meanwhile, a morphospace allows networks to be placed in a common space and can reveal the relationships between different network properties and elucidate the driving forces behind network topology. We combine the concepts of motifs and morphospaces to create the first motif morphospace of fMRI brain networks. Crucially, the morphospace axes are defined by the motifs, in a data-driven manner. We observe strong correlations between the networks’ positions in morphospace and their global topological properties, suggesting that motif morphospaces are a powerful way to capture the topology of networks in a low-dimensional space and to compare generative models of brain networks. Motif morphospaces could also be used to study other complex networks’ topologies.
Multi-planed unified switching topologies
Chen, Dong; Heidelberger, Philip; Sugawara, Yutaka
2017-07-04
An apparatus and method for extending the scalability and improving the partitionability of networks that contain all-to-all links for transporting packet traffic from a source endpoint to a destination endpoint with low per-endpoint (per-server) cost and a small number of hops. An all-to-all wiring in the baseline topology is decomposed into smaller all-to-all components in which each smaller all-to-all connection is replaced with star topology by using global switches. Stacking multiple copies of the star topology baseline network creates a multi-planed switching topology for transporting packet traffic. Point-to-point unified stacking method using global switch wiring methods connects multiple planes of a baseline topology by using the global switches to create a large network size with a low number of hops, i.e., low network latency. Grouped unified stacking method increases the scalability (network size) of a stacked topology.
Optimization of communication network topology for navigation sharing among distributed satellites
Dang, Zhaohui; Zhang, Yulin
2013-01-01
Navigation sharing among distributed satellites is quite important for coordinated motion and collision avoidance. This paper proposes optimization methods of the communication network topology to achieve navigation sharing. The whole communication network constructing by inter-satellite links are considered as a topology graph. The aim of this paper is to find the communication network topology with minimum communication connections' number (MCCN) in different conditions. It has found that the communication capacity and the number of channels are two key parameters affecting the results. The model of MCCN topology for navigation sharing is established and corresponding method is designed. Two main scenarios, viz., homogeneous case and heterogeneous case, are considered. For the homogeneous case where each member has the same communication capacity, it designs a construction method (Algorithm 1) to find the MCCN topology. For the heterogeneous case, it introduces a modified genetic algorithm (Algorithm 2) to find the MCCN topology. When considering the fact that the number of channels is limited, the Algorithm 2 is further modified by adding a penalized term in the fitness function. The effectiveness of these algorithms is all proved in theoretical. Three examples are further tested to illustrate the methods developed in this paper.
Broadcasting Topology and Routing Information in Computer Networks
1985-05-01
DOWN\\ linki inki FIgwre 1.2.1: Topology Problem Example messages from node 2 before receiving the first DOWN message from node 3. Now assume that before...node to each of the link’s end nodes. 54 link.1 cc 4 1 -. distances to linki Figue 3.4.2: SPTA Port Distance Table Example An example of these
Charge-spin Transport in Surface-disordered Three-dimensional Topological Insulators
Peng, Xingyue
As one of the most promising candidates for the building block of the novel spintronic circuit, the topological insulator (TI) has attracted world-wide interest of study. Robust topological order protected by time-reversal symmetry (TRS) makes charge transport and spin generation in TIs significantly different from traditional three-dimensional (3D) or two-dimensional (2D) electronic systems. However, to date, charge transport and spin generation in 3D TIs are still primarily modeled as single-surface phenomena, happening independently on top and bottom surfaces. In this dissertation, I will demonstrate via both experimental findings and theoretical modeling that this "single surface'' theory neither correctly describes a realistic 3D TI-based device nor reveals the amazingly distinct physical picture of spin transport dynamics in 3D TIs. Instead, I present a new viewpoint of the spin transport dynamics where the role of the insulating yet topologically non-trivial bulk of a 3D TI becomes explicit. Within this new theory, many mysterious transport and magneto-transport anomalies can be naturally explained. The 3D TI system turns out to be more similar to its low dimensional sibling--2D TI rather than some other systems sharing the Dirac dispersion, such as graphene. This work not only provides valuable fundamental physical insights on charge-spin transport in 3D TIs, but also offers important guidance to the design of 3D TI-based spintronic devices.
Charge and Spin Transport in Spin-orbit Coupled and Topological Systems
Ndiaye, Papa Birame
2017-10-31
In the search for low power operation of microelectronic devices, spin-based solutions have attracted undeniable increasing interest due to their intrinsic magnetic nonvolatility. The ability to electrically manipulate the magnetic order using spin-orbit interaction, associated with the recent emergence of topological spintronics with its promise of highly efficient charge-to-spin conversion in solid state, offer alluring opportunities in terms of system design. Although the related technology is still at its infancy, this thesis intends to contribute to this engaging field by investigating the nature of the charge and spin transport in spin-orbit coupled and topological systems using quantum transport methods. We identified three promising building blocks for next-generation technology, three classes of systems that possibly enhance the spin and charge transport efficiency: (i)- topological insulators, (ii)- spin-orbit coupled magnonic systems, (iii)- topological magnetic textures (skyrmions and 3Q magnetic state). Chapter 2 reviews the basics and essential concepts used throughout the thesis: the spin-orbit coupling, the mathematical notion of topology and its importance in condensed matter physics, then topological magnetism and a zest of magnonics. In Chapter 3, we study the spin-orbit torques at the magnetized interfaces of 3D topological insulators. We demonstrated that their peculiar form, compared to other spin-orbit torques, have important repercussions in terms of magnetization reversal, charge pumping and anisotropic damping. In Chapter 4, we showed that the interplay between magnon current jm and magnetization m in homogeneous ferromagnets with Dzyaloshinskii-Moriya (DM) interaction, produces a field-like torque as well as a damping-like torque. These DM torques mediated by spin wave can tilt the imeaveraged magnetization direction and are similar to Rashba torques for electronic systems. Moreover, the DM torque is more efficient when magnons are
Buchin, K.; Buchin, M.; Wagner, D.; Wattenhofer, R.
2007-01-01
Information between two nodes in a network is sent based on the network topology, the structure of links connecting pairs of nodes of a network. The task of topology control is to choose a connecting subset from all possible links such that the overall network performance is good. For instance, a
Scaling-Laws of Flow Entropy with Topological Metrics of Water Distribution Networks
Directory of Open Access Journals (Sweden)
Giovanni Francesco Santonastaso
2018-01-01
Full Text Available Robustness of water distribution networks is related to their connectivity and topological structure, which also affect their reliability. Flow entropy, based on Shannon’s informational entropy, has been proposed as a measure of network redundancy and adopted as a proxy of reliability in optimal network design procedures. In this paper, the scaling properties of flow entropy of water distribution networks with their size and other topological metrics are studied. To such aim, flow entropy, maximum flow entropy, link density and average path length have been evaluated for a set of 22 networks, both real and synthetic, with different size and topology. The obtained results led to identify suitable scaling laws of flow entropy and maximum flow entropy with water distribution network size, in the form of power–laws. The obtained relationships allow comparing the flow entropy of water distribution networks with different size, and provide an easy tool to define the maximum achievable entropy of a specific water distribution network. An example of application of the obtained relationships to the design of a water distribution network is provided, showing how, with a constrained multi-objective optimization procedure, a tradeoff between network cost and robustness is easily identified.
Shvets, Gennady B.; Khanikaev, Alexander B.; Ma, Tzuhsuan; Lai, Kueifu
2015-09-01
Science thrives on analogies, and a considerable number of inventions and discoveries have been made by pursuing an unexpected connection to a very different field of inquiry. For example, photonic crystals have been referred to as "semiconductors of light" because of the far-reaching analogies between electron propagation in a crystal lattice and light propagation in a periodically modulated photonic environment. However, two aspects of electron behavior, its spin and helicity, escaped emulation by photonic systems until recent invention of photonic topological insulators (PTIs). The impetus for these developments in photonics came from the discovery of topologically nontrivial phases in condensed matter physics enabling edge states immune to scattering. The realization of topologically protected transport in photonics would circumvent a fundamental limitation imposed by the wave equation: inability of reflections-free light propagation along sharply bent pathway. Topologically protected electromagnetic states could be used for transporting photons without any scattering, potentially underpinning new revolutionary concepts in applied science and engineering. I will demonstrate that a PTI can be constructed by applying three types of perturbations: (a) finite bianisotropy, (b) gyromagnetic inclusion breaking the time-reversal (T) symmetry, and (c) asymmetric rods breaking the parity (P) symmetry. We will experimentally demonstrate (i) the existence of the full topological bandgap in a bianisotropic, and (ii) the reflectionless nature of wave propagation along the interface between two PTIs with opposite signs of the bianisotropy.
Directory of Open Access Journals (Sweden)
Sinisa Pajevic
2009-01-01
Full Text Available Cascading activity is commonly found in complex systems with directed interactions such as metabolic networks, neuronal networks, or disease spreading in social networks. Substantial insight into a system's organization can be obtained by reconstructing the underlying functional network architecture from the observed activity cascades. Here we focus on Bayesian approaches and reduce their computational demands by introducing the Iterative Bayesian (IB and Posterior Weighted Averaging (PWA methods. We introduce a special case of PWA, cast in nonparametric form, which we call the normalized count (NC algorithm. NC efficiently reconstructs random and small-world functional network topologies and architectures from subcritical, critical, and supercritical cascading dynamics and yields significant improvements over commonly used correlation methods. With experimental data, NC identified a functional and structural small-world topology and its corresponding traffic in cortical networks with neuronal avalanche dynamics.
Akiki, Teddy J; Averill, Christopher L; Wrocklage, Kristen M; Scott, J Cobb; Averill, Lynnette A; Schweinsburg, Brian; Alexander-Bloch, Aaron; Martini, Brenda; Southwick, Steven M; Krystal, John H; Abdallah, Chadi G
2018-08-01
Disruption in the default mode network (DMN) has been implicated in numerous neuropsychiatric disorders, including posttraumatic stress disorder (PTSD). However, studies have largely been limited to seed-based methods and involved inconsistent definitions of the DMN. Recent advances in neuroimaging and graph theory now permit the systematic exploration of intrinsic brain networks. In this study, we used resting-state functional magnetic resonance imaging (fMRI), diffusion MRI, and graph theoretical analyses to systematically examine the DMN connectivity and its relationship with PTSD symptom severity in a cohort of 65 combat-exposed US Veterans. We employed metrics that index overall connectivity strength, network integration (global efficiency), and network segregation (clustering coefficient). Then, we conducted a modularity and network-based statistical analysis to identify DMN regions of particular importance in PTSD. Finally, structural connectivity analyses were used to probe whether white matter abnormalities are associated with the identified functional DMN changes. We found decreased DMN functional connectivity strength to be associated with increased PTSD symptom severity. Further topological characterization suggests decreased functional integration and increased segregation in subjects with severe PTSD. Modularity analyses suggest a spared connectivity in the posterior DMN community (posterior cingulate, precuneus, angular gyrus) despite overall DMN weakened connections with increasing PTSD severity. Edge-wise network-based statistical analyses revealed a prefrontal dysconnectivity. Analysis of the diffusion networks revealed no alterations in overall strength or prefrontal structural connectivity. DMN abnormalities in patients with severe PTSD symptoms are characterized by decreased overall interconnections. On a finer scale, we found a pattern of prefrontal dysconnectivity, but increased cohesiveness in the posterior DMN community and relative sparing
The effect of the neural activity on topological properties of growing neural networks.
Gafarov, F M; Gafarova, V R
2016-09-01
The connectivity structure in cortical networks defines how information is transmitted and processed, and it is a source of the complex spatiotemporal patterns of network's development, and the process of creation and deletion of connections is continuous in the whole life of the organism. In this paper, we study how neural activity influences the growth process in neural networks. By using a two-dimensional activity-dependent growth model we demonstrated the neural network growth process from disconnected neurons to fully connected networks. For making quantitative investigation of the network's activity influence on its topological properties we compared it with the random growth network not depending on network's activity. By using the random graphs theory methods for the analysis of the network's connections structure it is shown that the growth in neural networks results in the formation of a well-known "small-world" network.
Müller, Viktor; Perdikis, Dionysios; von Oertzen, Timo; Sleimen-Malkoun, Rita; Jirsa, Viktor; Lindenberger, Ulman
2016-01-01
Resting-state and task-related recordings are characterized by oscillatory brain activity and widely distributed networks of synchronized oscillatory circuits. Electroencephalographic recordings (EEG) were used to assess network structure and network dynamics during resting state with eyes open and closed, and auditory oddball performance through phase synchronization between EEG channels. For this assessment, we constructed a hyper-frequency network (HFN) based on within- and cross-frequency coupling (WFC and CFC, respectively) at 10 oscillation frequencies ranging between 2 and 20 Hz. We found that CFC generally differentiates between task conditions better than WFC. CFC was the highest during resting state with eyes open. Using a graph-theoretical approach (GTA), we found that HFNs possess small-world network (SWN) topology with a slight tendency to random network characteristics. Moreover, analysis of the temporal fluctuations of HFNs revealed specific network topology dynamics (NTD), i.e., temporal changes of different graph-theoretical measures such as strength, clustering coefficient, characteristic path length (CPL), local, and global efficiency determined for HFNs at different time windows. The different topology metrics showed significant differences between conditions in the mean and standard deviation of these metrics both across time and nodes. In addition, using an artificial neural network approach, we found stimulus-related dynamics that varied across the different network topology metrics. We conclude that functional connectivity dynamics (FCD), or NTD, which was found using the HFN approach during rest and stimulus processing, reflects temporal and topological changes in the functional organization and reorganization of neuronal cell assemblies.
Acquisition management of the Global Transportation Network
2001-08-02
This report discusses the acquisition management of the Global transportation Network by the U.S. Transportation Command. This report is one in a series of audit reports addressing DoD acquisition management of information technology systems. The Glo...
Effect of the social influence on topological properties of user-object bipartite networks
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.
Zhang, Ying; Chen, Wei; Liang, Jixing; Zheng, Bingxin; Jiang, Shengming
2015-12-01
It is expected that in the near future wireless sensor network (WSNs) will be more widely used in the mobile environment, in applications such as Autonomous Underwater Vehicles (AUVs) for marine monitoring and mobile robots for environmental investigation. The sensor nodes' mobility can easily cause changes to the structure of a network topology, and lead to the decline in the amount of transmitted data, excessive energy consumption, and lack of security. To solve these problems, a kind of efficient Topology Control algorithm for node Mobility (TCM) is proposed. In the topology construction stage, an efficient clustering algorithm is adopted, which supports sensor node movement. It can ensure the balance of clustering, and reduce the energy consumption. In the topology maintenance stage, the digital signature authentication based on Error Correction Code (ECC) and the communication mechanism of soft handover are adopted. After verifying the legal identity of the mobile nodes, secure communications can be established, and this can increase the amount of data transmitted. Compared to some existing schemes, the proposed scheme has significant advantages regarding network topology stability, amounts of data transferred, lifetime and safety performance of the network.
Interplay between Graph Topology and Correlations of Third Order in Spiking Neuronal Networks.
Directory of Open Access Journals (Sweden)
Stojan Jovanović
2016-06-01
Full Text Available The study of processes evolving on networks has recently become a very popular research field, not only because of the rich mathematical theory that underpins it, but also because of its many possible applications, a number of them in the field of biology. Indeed, molecular signaling pathways, gene regulation, predator-prey interactions and the communication between neurons in the brain can be seen as examples of networks with complex dynamics. The properties of such dynamics depend largely on the topology of the underlying network graph. In this work, we want to answer the following question: Knowing network connectivity, what can be said about the level of third-order correlations that will characterize the network dynamics? We consider a linear point process as a model for pulse-coded, or spiking activity in a neuronal network. Using recent results from theory of such processes, we study third-order correlations between spike trains in such a system and explain which features of the network graph (i.e. which topological motifs are responsible for their emergence. Comparing two different models of network topology-random networks of Erdős-Rényi type and networks with highly interconnected hubs-we find that, in random networks, the average measure of third-order correlations does not depend on the local connectivity properties, but rather on global parameters, such as the connection probability. This, however, ceases to be the case in networks with a geometric out-degree distribution, where topological specificities have a strong impact on average correlations.
Interplay between Graph Topology and Correlations of Third Order in Spiking Neuronal Networks.
Jovanović, Stojan; Rotter, Stefan
2016-06-01
The study of processes evolving on networks has recently become a very popular research field, not only because of the rich mathematical theory that underpins it, but also because of its many possible applications, a number of them in the field of biology. Indeed, molecular signaling pathways, gene regulation, predator-prey interactions and the communication between neurons in the brain can be seen as examples of networks with complex dynamics. The properties of such dynamics depend largely on the topology of the underlying network graph. In this work, we want to answer the following question: Knowing network connectivity, what can be said about the level of third-order correlations that will characterize the network dynamics? We consider a linear point process as a model for pulse-coded, or spiking activity in a neuronal network. Using recent results from theory of such processes, we study third-order correlations between spike trains in such a system and explain which features of the network graph (i.e. which topological motifs) are responsible for their emergence. Comparing two different models of network topology-random networks of Erdős-Rényi type and networks with highly interconnected hubs-we find that, in random networks, the average measure of third-order correlations does not depend on the local connectivity properties, but rather on global parameters, such as the connection probability. This, however, ceases to be the case in networks with a geometric out-degree distribution, where topological specificities have a strong impact on average correlations.
Arnold, D.; Hess, M.
2017-01-01
This article takes a fresh look at the multiple power relations between state, capital and labor in global production networks. Moving beyond debates about public vs. private governance, it brings together Antonio Gramsci’s concepts of hegemony and the integral state with Michel Foucault’s concepts of governmentality and the “dipositive” in order to analyze the power topologies that permeate global production networks. Using the Cambodian garment production network as example, we scrutinize t...
Adaptive Duty-Cycling to Enhance Topology Control Schemes in Wireless Sensor Networks
Cha, Myungsu; Kim, Mihui; Kim, Dongsoo S.; Choo, Hyunseung
2014-01-01
To prolong the network lifetime, various scheduling approaches that schedule wireless devices of nodes to switch between active and sleep states have been studied. Topology control schemes are one of the scheduling approaches that can extend the network lifetime and reduce the additional communication delays at the same time. However, they do not guarantee that all nodes have the same lifetime. They reduce the network coverage and prevent seamless communications. This paper proposes an adapti...
Reconstruction of network topology using status-time-series data
Pandey, Pradumn Kumar; Badarla, Venkataramana
2018-01-01
Uncovering the heterogeneous connection pattern of a networked system from the available status-time-series (STS) data of a dynamical process on the network is of great interest in network science and known as a reverse engineering problem. Dynamical processes on a network are affected by the structure of the network. The dependency between the diffusion dynamics and structure of the network can be utilized to retrieve the connection pattern from the diffusion data. Information of the network structure can help to devise the control of dynamics on the network. In this paper, we consider the problem of network reconstruction from the available status-time-series (STS) data using matrix analysis. The proposed method of network reconstruction from the STS data is tested successfully under susceptible-infected-susceptible (SIS) diffusion dynamics on real-world and computer-generated benchmark networks. High accuracy and efficiency of the proposed reconstruction procedure from the status-time-series data define the novelty of the method. Our proposed method outperforms compressed sensing theory (CST) based method of network reconstruction using STS data. Further, the same procedure of network reconstruction is applied to the weighted networks. The ordering of the edges in the weighted networks is identified with high accuracy.
Extending Topological Approaches to Microseismic-Derived 3D Fracture Networks
Urbancic, T.; Bosman, K.; Baig, A.; Ardakani, E. P.
2017-12-01
Fracture topology is important for determining the fluid-flow characteristics of a fracture network. In most unconventional petroleum applications, flow through subsurface fracture networks is the primary source of production, as matrix permeability is often in the nanodarcy range. Typical models of reservoir discrete fracture networks (DFNs) are constructed using fracture orientation and average spacing, without consideration of how the connectivity of the fracture network aids the percolation of hydrocarbons back to the wellbore. Topological approaches to DFN characterization have been developed and extensively used in analysis of outcrop data and aerial photography. Such study of the surface expression of fracture networks is straight-forward, and the physical form of the observed fractures is directly reflected in the parameters used to describe the topology. However, this analysis largely ignores the three-dimensional nature of natural fracture networks, which is difficult to define accurately in geological studies. SMTI analysis of microseismic event distributions can produce DFNs, where each event is represented by a penny-shaped crack with radius and orientation determined from the frequency content of the waveforms and assessment of the slip instability of the potential fracture planes, respectively. Analysis of the geometric relationships between a set of fractures can provide details of intersections between fractures, and thus the topological characteristics of the fracture network. Extension of existing 2D topology approaches to 3D fracture networks is non-trivial. In the 2D case, a fracture intersection is a single point (node), and branches connect adjacent nodes along fractures. For the 3D case, intersection "nodes" become lines, and connecting nodes to find branches becomes more complicated. There are several parameters defined in 2D topology to quantify the connectivity of the fracture network. Equivalent quantities must be defined and calibrated
Topological probability and connection strength induced activity in complex neural networks
International Nuclear Information System (INIS)
Du-Qu, Wei; Bo, Zhang; Dong-Yuan, Qiu; Xiao-Shu, Luo
2010-01-01
Recent experimental evidence suggests that some brain activities can be assigned to small-world networks. In this work, we investigate how the topological probability p and connection strength C affect the activities of discrete neural networks with small-world (SW) connections. Network elements are described by two-dimensional map neurons (2DMNs) with the values of parameters at which no activity occurs. It is found that when the value of p is smaller or larger, there are no active neurons in the network, no matter what the value of connection strength is; for a given appropriate connection strength, there is an intermediate range of topological probability where the activity of 2DMN network is induced and enhanced. On the other hand, for a given intermediate topological probability level, there exists an optimal value of connection strength such that the frequency of activity reaches its maximum. The possible mechanism behind the action of topological probability and connection strength is addressed based on the bifurcation method. Furthermore, the effects of noise and transmission delay on the activity of neural network are also studied. (general)
Topology control of tactical wireless sensor networks using energy efficient zone routing
Directory of Open Access Journals (Sweden)
Preetha Thulasiraman
2016-02-01
Full Text Available The US Department of Defense (DoD routinely uses wireless sensor networks (WSNs for military tactical communications. Sensor node die-out has a significant impact on the topology of a tactical WSN. This is problematic for military applications where situational data is critical to tactical decision making. To increase the amount of time all sensor nodes remain active within the network and to control the network topology tactically, energy efficient routing mechanisms must be employed. In this paper, we aim to provide realistic insights on the practical advantages and disadvantages of using established routing techniques for tactical WSNs. We investigate the following established routing algorithms: direct routing, minimum transmission energy (MTE, Low Energy Adaptive Cluster Head routing (LEACH, and zone clustering. Based on the node die out statistics observed with these algorithms and the topological impact the node die outs have on the network, we develop a novel, energy efficient zone clustering algorithm called EZone. Via extensive simulations using MATLAB, we analyze the effectiveness of these algorithms on network performance for single and multiple gateway scenarios and show that the EZone algorithm tactically controls the topology of the network, thereby maintaining significant service area coverage when compared to the other routing algorithms.
Qiu, Xiangzhe; Zhang, Yanjun; Feng, Hongbo; Jiang, Donglang
2016-01-01
Recent studies have demonstrated alterations in the topological organization of structural brain networks in diabetes mellitus (DM). However, the DM-related changes in the topological properties in functional brain networks are unexplored so far. We therefore used fluoro-D-glucose positron emission tomography (FDG-PET) data to construct functional brain networks of 73 DM patients and 91 sex- and age-matched normal controls (NCs), followed by a graph theoretical analysis. We found that both DM patients and NCs had a small-world topology in functional brain network. In comparison to the NC group, the DM group was found to have significantly lower small-world index, lower normalized clustering coefficients and higher normalized characteristic path length. Moreover, for diabetic patients, the nodal centrality was significantly reduced in the right rectus, the right cuneus, the left middle occipital gyrus, and the left postcentral gyrus, and it was significantly increased in the orbitofrontal region of the left middle frontal gyrus, the left olfactory region, and the right paracentral lobule. Our results demonstrated that the diabetic brain was associated with disrupted topological organization in the functional PET network, thus providing functional evidence for the abnormalities of brain networks in DM.
Directory of Open Access Journals (Sweden)
Qiu eXiangzhe
2016-05-01
Full Text Available Recent studies have demonstrated alterations in the topological organization of structural brain networks in diabetes mellitus (DM. However, the DM-related changes in the topological properties in functional brain networks are almost unexplored so far. We therefore used fluoro-D-glucose positron emission tomography (FDG-PET data to construct functional brain networks of 73 DM patients and 91 sex- and age-matched normal controls (NCs, followed by a graph theoretical analysis. We found that both DM patients and NCs had a small-world topology in functional brain network. In comparison to the NC group, the DM group was found to have significantly lower small-world index, lower normalized clustering coefficients and higher normalized shortest path length. Moreover, for diabetic patients, the nodal centrality was significantly reduced in the right rectus, the right cuneus, the left middle occipital gyrus, and the left postcentral gyrus, and it was significantly increased in the orbitofrontal region of the left middle frontal gyrus, the left olfactory region, and the right paracentral lobule. Our results demonstrated that the diabetic brain was associated with disrupted topological organization in the functional PET network, thus providing the functional evidence for the abnormalities of brain networks in DM.
Aggregation of topological motifs in the Escherichia coli transcriptional regulatory network
Directory of Open Access Journals (Sweden)
Barabási Albert-László
2004-01-01
Full Text Available Abstract Background Transcriptional regulation of cellular functions is carried out through a complex network of interactions among transcription factors and the promoter regions of genes and operons regulated by them.To better understand the system-level function of such networks simplification of their architecture was previously achieved by identifying the motifs present in the network, which are small, overrepresented, topologically distinct regulatory interaction patterns (subgraphs. However, the interaction of such motifs with each other, and their form of integration into the full network has not been previously examined. Results By studying the transcriptional regulatory network of the bacterium, Escherichia coli, we demonstrate that the two previously identified motif types in the network (i.e., feed-forward loops and bi-fan motifs do not exist in isolation, but rather aggregate into homologous motif clusters that largely overlap with known biological functions. Moreover, these clusters further coalesce into a supercluster, thus establishing distinct topological hierarchies that show global statistical properties similar to the whole network. Targeted removal of motif links disintegrates the network into small, isolated clusters, while random disruptions of equal number of links do not cause such an effect. Conclusion Individual motifs aggregate into homologous motif clusters and a supercluster forming the backbone of the E. coli transcriptional regulatory network and play a central role in defining its global topological organization.
Geometric dependence of Nb-Bi2Te3-Nb topological Josephson junction transport parameters
International Nuclear Information System (INIS)
Molenaar, C G; Leusink, D P; Brinkman, A; Wang, X L
2014-01-01
Superconductor-topological insulator–superconductor Josephson junctions have been fabricated in order to study the width dependence of the critical current, normal state resistance and flux periodicity of the critical current modulation in an external field. Previous literature reports suggest anomalous scaling in topological junctions due to the presence of Majorana bound states. However, for most realized devices, one would expect that trivial 2π-periodic Andreev levels dominate transport. We also observe anomalous scaling behaviour of junction parameters, but the scaling can be well explained by mere geometric effects, such as the parallel bulk conductivity shunt and flux focusing. (paper)
Distributed topology control algorithm to conserve energy in heterogeneous wireless mesh networks
CSIR Research Space (South Africa)
Aron, FO
2008-07-01
Full Text Available in performance with the resulting topology being a sub-network of the one generated by [11]. Li and Halpern [13] further propose the small minimum energy communication network (SMECN). In this algorithm, each node u initially broadcasts a “hello” message... algorithm that runs in each node is presented as follows:- Phase1: Establishing the accessible neighbourhood topology. In this stage, node u broadcasts a “hello” message using its full power, max uP . The nodes that receive the “hello” message form...
Spatiotemporal Recurrent Convolutional Networks for Traffic Prediction in Transportation Networks.
Yu, Haiyang; Wu, Zhihai; Wang, Shuqin; Wang, Yunpeng; Ma, Xiaolei
2017-06-26
Predicting large-scale transportation network traffic has become an important and challenging topic in recent decades. Inspired by the domain knowledge of motion prediction, in which the future motion of an object can be predicted based on previous scenes, we propose a network grid representation method that can retain the fine-scale structure of a transportation network. Network-wide traffic speeds are converted into a series of static images and input into a novel deep architecture, namely, spatiotemporal recurrent convolutional networks (SRCNs), for traffic forecasting. The proposed SRCNs inherit the advantages of deep convolutional neural networks (DCNNs) and long short-term memory (LSTM) neural networks. The spatial dependencies of network-wide traffic can be captured by DCNNs, and the temporal dynamics can be learned by LSTMs. An experiment on a Beijing transportation network with 278 links demonstrates that SRCNs outperform other deep learning-based algorithms in both short-term and long-term traffic prediction.
Membrane topology of rat sodium-coupled neutral amino acid transporter 2 (SNAT2).
Ge, Yudan; Gu, Yanting; Wang, Jiahong; Zhang, Zhou
2018-07-01
Sodium-coupled neutral amino acid transporter 2 (SNAT2) is a subtype of the amino acid transport system A that is widely expressed in mammalian tissues. It plays critical roles in glutamic acid-glutamine circulation, liver gluconeogenesis and other biological pathway. However, the topology of the SNAT2 amino acid transporter is unknown. Here we identified the topological structure of SNAT2 using bioinformatics analysis, Methoxy-polyethylene glycol maleimide (mPEG-Mal) chemical modification, protease cleavage assays, immunofluorescence and examination of glycosylation. Our results show that SNAT2 contains 11 transmembrane domains (TMDs) with an intracellular N terminus and an extracellular C terminus. Three N-glycosylation sites were verified at the largest extracellular loop. This model is consistent with the previous model of SNAT2 with the exception of a difference in number of glycosylation sites. This is the first time to confirm the SNAT2 membrane topology using experimental methods. Our study on SNAT2 topology provides valuable structural information of one of the solute carrier family 38 (SLC38) members. Copyright © 2018 Elsevier B.V. All rights reserved.
Wei, Qi; Tian, Ye; Zuo, Shu-Yu; Cheng, Ying; Liu, Xiao-Jun
2017-03-01
Acoustic topological states support sound propagation along the boundary in a one-way direction with inherent robustness against defects and disorders, leading to the revolution of the manipulation on acoustic waves. A variety of acoustic topological states relying on circulating fluid, chiral coupling, or temporal modulation have been proposed theoretically. However, experimental demonstration has so far remained a significant challenge, due to the critical limitations such as structural complexity and high losses. Here, we experimentally demonstrate an acoustic anomalous Floquet topological insulator in a waveguide network. The acoustic gapless edge states can be found in the band gap when the waveguides are strongly coupled. The scheme features simple structure and high-energy throughput, leading to the experimental demonstration of efficient and robust topologically protected sound propagation along the boundary. The proposal may offer a unique, promising application for design of acoustic devices in acoustic guiding, switching, isolating, filtering, etc.
Complex brain networks: From topological communities to clustered ...
Indian Academy of Sciences (India)
functional connectivity of the human brain has shown that both types of brain networks share .... the areas and also of the whole network, the Pearson correlation coefficient r and ..... Several areas important for intercommunity communication.
Rahman, P. A.
2018-05-01
This scientific paper deals with the two-level backbone computer networks with arbitrary topology. A specialized method, offered by the author for calculation of the stationary availability factor of the two-level backbone computer networks, based on the Markov reliability models for the set of the independent repairable elements with the given failure and repair rates and the methods of the discrete mathematics, is also discussed. A specialized algorithm, offered by the author for analysis of the network connectivity, taking into account different kinds of the network equipment failures, is also observed. Finally, this paper presents an example of calculation of the stationary availability factor for the backbone computer network with the given topology.
Castellano, Claudio; Pastor-Satorras, Romualdo
2017-10-01
The largest eigenvalue of a network's adjacency matrix and its associated principal eigenvector are key elements for determining the topological structure and the properties of dynamical processes mediated by it. We present a physically grounded expression relating the value of the largest eigenvalue of a given network to the largest eigenvalue of two network subgraphs, considered as isolated: the hub with its immediate neighbors and the densely connected set of nodes with maximum K -core index. We validate this formula by showing that it predicts, with good accuracy, the largest eigenvalue of a large set of synthetic and real-world topologies. We also present evidence of the consequences of these findings for broad classes of dynamics taking place on the networks. As a by-product, we reveal that the spectral properties of heterogeneous networks built according to the linear preferential attachment model are qualitatively different from those of their static counterparts.
Identifying partial topology of complex dynamical networks via a pinning mechanism
Zhu, Shuaibing; Zhou, Jin; Lu, Jun-an
2018-04-01
In this paper, we study the problem of identifying the partial topology of complex dynamical networks via a pinning mechanism. By using the network synchronization theory and the adaptive feedback controlling method, we propose a method which can greatly reduce the number of nodes and observers in the response network. Particularly, this method can also identify the whole topology of complex networks. A theorem is established rigorously, from which some corollaries are also derived in order to make our method more cost-effective. Several numerical examples are provided to verify the effectiveness of the proposed method. In the simulation, an approach is also given to avoid possible identification failure caused by inner synchronization of the drive network.
Topological spin transport of photons: the optical Magnus effect and Berry phase
International Nuclear Information System (INIS)
Bliokh, K.Yu.; Bliokh, Yu.P.
2004-01-01
The Letter develops a modified geometrical optics (GO) of smoothly inhomogeneous isotropic medium, which takes into account two topological phenomena: Berry phase and the optical Magnus effect. Taking into account the correspondence between a quasi-classical motion of a quantum particle with a spin and GO of an electromagnetic wave in smoothly inhomogeneous media, we have introduced the standard gauge potential associated with the degeneracy in the wave momentum space. This potential corresponds to the magnetic-monopole-like field (Berry curvature), which causes the topological spin (polarization) transport of photons. The deviations of waves of right-hand and left-hand polarization occur in the opposite directions and orthogonally to the principal direction of motion. This produces a spin current directed across the principal motion. The situation is similar to the anomalous Hall effect for electrons. In addition, a simple scheme of the experiment allowing one to observe the topological spin splitting of photons has been suggested
International Nuclear Information System (INIS)
Chen, Hua-Jun; Shi, Hai-Bin; Jiang, Long-Feng; Li, Lan; Chen, Rong
2018-01-01
To investigate structural brain connectome alterations in cirrhotic patients with prior overt hepatic encephalopathy (OHE). Seventeen cirrhotic patients with prior OHE (prior-OHE), 18 cirrhotic patients without prior OHE (non-prior-OHE) and 18 healthy controls (HC) underwent diffusion tensor imaging. Neurocognitive functioning was assessed with Psychometric Hepatic Encephalopathy Score (PHES). Using a probabilistic fibre tracking approach, we depicted the whole-brain structural network as a connectivity matrix of 90 regions (derived from the Automated Anatomic Labeling atlas). Graph theory-based analyses were performed to analyse topological properties of the brain network. The analysis of variance showed significant group effects on several topological properties, including network strength, global efficiency and local efficiency. A progressive decrease trend for these metrics was found from non-prior-OHE to prior-OHE, compared with HC. Among the three groups, the regions with altered nodal efficiency were mainly distributed in the frontal and occipital cortices, paralimbic system and subcortical regions. The topological metrics, such as network strength and global efficiency, were correlated with PHES among cirrhotic patients. The cirrhotic patients developed structural brain connectome alterations; this is aggravated by prior OHE episode. Disrupted topological organization of the brain structural network may account for cognitive impairments related to prior OHE. (orig.)
Energy Technology Data Exchange (ETDEWEB)
Chen, Hua-Jun [Fujian Medical University Union Hospital, Department of Radiology, Fuzhou (China); The First Affiliated Hospital of Nanjing Medical University, Department of Radiology, Nanjing (China); Shi, Hai-Bin [The First Affiliated Hospital of Nanjing Medical University, Department of Radiology, Nanjing (China); Jiang, Long-Feng [The First Affiliated Hospital of Nanjing Medical University, Department of Infectious Diseases, Nanjing (China); Li, Lan [Fujian Medical University Union Hospital, Department of Radiology, Fuzhou (China); Chen, Rong [University of Maryland School of Medicine, Department of Diagnostic Radiology and Nuclear Medicine, Baltimore, MD (United States); Beijing Institute of Technology, Advanced Innovation Center for Intelligent Robots and Systems, Beijing (China)
2018-01-15
To investigate structural brain connectome alterations in cirrhotic patients with prior overt hepatic encephalopathy (OHE). Seventeen cirrhotic patients with prior OHE (prior-OHE), 18 cirrhotic patients without prior OHE (non-prior-OHE) and 18 healthy controls (HC) underwent diffusion tensor imaging. Neurocognitive functioning was assessed with Psychometric Hepatic Encephalopathy Score (PHES). Using a probabilistic fibre tracking approach, we depicted the whole-brain structural network as a connectivity matrix of 90 regions (derived from the Automated Anatomic Labeling atlas). Graph theory-based analyses were performed to analyse topological properties of the brain network. The analysis of variance showed significant group effects on several topological properties, including network strength, global efficiency and local efficiency. A progressive decrease trend for these metrics was found from non-prior-OHE to prior-OHE, compared with HC. Among the three groups, the regions with altered nodal efficiency were mainly distributed in the frontal and occipital cortices, paralimbic system and subcortical regions. The topological metrics, such as network strength and global efficiency, were correlated with PHES among cirrhotic patients. The cirrhotic patients developed structural brain connectome alterations; this is aggravated by prior OHE episode. Disrupted topological organization of the brain structural network may account for cognitive impairments related to prior OHE. (orig.)
Directory of Open Access Journals (Sweden)
Wingender Edgar
2008-05-01
Full Text Available Abstract Background Currently, there is a gap between purely theoretical studies of the topology of large bioregulatory networks and the practical traditions and interests of experimentalists. While the theoretical approaches emphasize the global characterization of regulatory systems, the practical approaches focus on the role of distinct molecules and genes in regulation. To bridge the gap between these opposite approaches, one needs to combine 'general' with 'particular' properties and translate abstract topological features of large systems into testable functional characteristics of individual components. Here, we propose a new topological parameter – the pairwise disconnectivity index of a network's element – that is capable of such bridging. Results The pairwise disconnectivity index quantifies how crucial an individual element is for sustaining the communication ability between connected pairs of vertices in a network that is displayed as a directed graph. Such an element might be a vertex (i.e., molecules, genes, an edge (i.e., reactions, interactions, as well as a group of vertices and/or edges. The index can be viewed as a measure of topological redundancy of regulatory paths which connect different parts of a given network and as a measure of sensitivity (robustness of this network to the presence (absence of each individual element. Accordingly, we introduce the notion of a path-degree of a vertex in terms of its corresponding incoming, outgoing and mediated paths, respectively. The pairwise disconnectivity index has been applied to the analysis of several regulatory networks from various organisms. The importance of an individual vertex or edge for the coherence of the network is determined by the particular position of the given element in the whole network. Conclusion Our approach enables to evaluate the effect of removing each element (i.e., vertex, edge, or their combinations from a network. The greatest potential value of
Directory of Open Access Journals (Sweden)
Pengfei Guo
2014-01-01
Full Text Available This paper deals with the fault detection problem for a class of discrete-time wireless networked control systems described by switching topology with uncertainties and disturbances. System states of each individual node are affected not only by its own measurements, but also by other nodes’ measurements according to a certain network topology. As the topology of system can be switched in a stochastic way, we aim to design H∞ fault detection observers for nodes in the dynamic time-delay systems. By using the Lyapunov method and stochastic analysis techniques, sufficient conditions are acquired to guarantee the existence of the filters satisfying the H∞ performance constraint, and observer gains are derived by solving linear matrix inequalities. Finally, an illustrated example is provided to verify the effectiveness of the theoretical results.
Li, Ning; Cürüklü, Baran; Bastos, Joaquim; Sucasas, Victor; Fernandez, Jose Antonio Sanchez; Rodriguez, Jonathan
2017-05-04
The aim of the Smart and Networking Underwater Robots in Cooperation Meshes (SWARMs) project is to make autonomous underwater vehicles (AUVs), remote operated vehicles (ROVs) and unmanned surface vehicles (USVs) more accessible and useful. To achieve cooperation and communication between different AUVs, these must be able to exchange messages, so an efficient and reliable communication network is necessary for SWARMs. In order to provide an efficient and reliable communication network for mission execution, one of the important and necessary issues is the topology control of the network of AUVs that are cooperating underwater. However, due to the specific properties of an underwater AUV cooperation network, such as the high mobility of AUVs, large transmission delays, low bandwidth, etc., the traditional topology control algorithms primarily designed for terrestrial wireless sensor networks cannot be used directly in the underwater environment. Moreover, these algorithms, in which the nodes adjust their transmission power once the current transmission power does not equal an optimal one, are costly in an underwater cooperating AUV network. Considering these facts, in this paper, we propose a Probabilistic Topology Control (PTC) algorithm for an underwater cooperating AUV network. In PTC, when the transmission power of an AUV is not equal to the optimal transmission power, then whether the transmission power needs to be adjusted or not will be determined based on the AUV's parameters. Each AUV determines their own transmission power adjustment probability based on the parameter deviations. The larger the deviation, the higher the transmission power adjustment probability is, and vice versa. For evaluating the performance of PTC, we combine the PTC algorithm with the Fuzzy logic Topology Control (FTC) algorithm and compare the performance of these two algorithms. The simulation results have demonstrated that the PTC is efficient at reducing the transmission power
Directory of Open Access Journals (Sweden)
Ning Li
2017-05-01
Full Text Available The aim of the Smart and Networking Underwater Robots in Cooperation Meshes (SWARMs project is to make autonomous underwater vehicles (AUVs, remote operated vehicles (ROVs and unmanned surface vehicles (USVs more accessible and useful. To achieve cooperation and communication between different AUVs, these must be able to exchange messages, so an efficient and reliable communication network is necessary for SWARMs. In order to provide an efficient and reliable communication network for mission execution, one of the important and necessary issues is the topology control of the network of AUVs that are cooperating underwater. However, due to the specific properties of an underwater AUV cooperation network, such as the high mobility of AUVs, large transmission delays, low bandwidth, etc., the traditional topology control algorithms primarily designed for terrestrial wireless sensor networks cannot be used directly in the underwater environment. Moreover, these algorithms, in which the nodes adjust their transmission power once the current transmission power does not equal an optimal one, are costly in an underwater cooperating AUV network. Considering these facts, in this paper, we propose a Probabilistic Topology Control (PTC algorithm for an underwater cooperating AUV network. In PTC, when the transmission power of an AUV is not equal to the optimal transmission power, then whether the transmission power needs to be adjusted or not will be determined based on the AUV’s parameters. Each AUV determines their own transmission power adjustment probability based on the parameter deviations. The larger the deviation, the higher the transmission power adjustment probability is, and vice versa. For evaluating the performance of PTC, we combine the PTC algorithm with the Fuzzy logic Topology Control (FTC algorithm and compare the performance of these two algorithms. The simulation results have demonstrated that the PTC is efficient at reducing the
Inferring time-varying network topologies from gene expression data.
Rao, Arvind; Hero, Alfred O; States, David J; Engel, James Douglas
2007-01-01
Most current methods for gene regulatory network identification lead to the inference of steady-state networks, that is, networks prevalent over all times, a hypothesis which has been challenged. There has been a need to infer and represent networks in a dynamic, that is, time-varying fashion, in order to account for different cellular states affecting the interactions amongst genes. In this work, we present an approach, regime-SSM, to understand gene regulatory networks within such a dynamic setting. The approach uses a clustering method based on these underlying dynamics, followed by system identification using a state-space model for each learnt cluster--to infer a network adjacency matrix. We finally indicate our results on the mouse embryonic kidney dataset as well as the T-cell activation-based expression dataset and demonstrate conformity with reported experimental evidence.
Non-local electron transport through normal and topological ladder-like atomic systems
Kurzyna, Marcin; Kwapiński, Tomasz
2018-05-01
We propose a locally protected ladder-like atomic system (nanoconductor) on a substrate that is insensitive to external perturbations. The system corresponds to coupled atomic chains fabricated on different surfaces. Electron transport properties of such conductors are studied theoretically using the model tight-binding Su-Schriffer-Hegger (SSH) Hamiltonian and Green's function formalism. We have found that the conductance of the system is almost insensitive to single adatoms and oscillates as a function of the side chain length with very large periods. Non-local character of the electron transport was observed also for topological SSH chains where nontrivial end states survive in the presence of disturbances as well as for different substrates. We have found that the careful inspection of the density of states or charge waves can provide the information about the atom energy levels and hopping amplitudes. Moreover, the ladder-like geometry allows one to distinguish between normal and topological zero-energy states. It is important that topological chains do not reveal Friedel oscillations which are observed in non-topological chains.
Directory of Open Access Journals (Sweden)
Wingender Edgar
2009-05-01
Full Text Available Abstract Background The identification of network motifs as statistically over-represented topological patterns has become one of the most promising topics in the analysis of complex networks. The main focus is commonly made on how they operate by means of their internal organization. Yet, their contribution to a network's global architecture is poorly understood. However, this requires switching from the abstract view of a topological pattern to the level of its instances. Here, we show how a recently proposed metric, the pairwise disconnectivity index, can be adapted to survey if and which kind of topological patterns and their instances are most important for sustaining the connectivity within a network. Results The pairwise disconnectivity index of a pattern instance quantifies the dependency of the pairwise connections between vertices in a network on the presence of this pattern instance. Thereby, it particularly considers how the coherence between the unique constituents of a pattern instance relates to the rest of a network. We have applied the method exemplarily to the analysis of 3-vertex topological pattern instances in the transcription networks of a bacteria (E. coli, a unicellular eukaryote (S. cerevisiae and higher eukaryotes (human, mouse, rat. We found that in these networks only very few pattern instances break lots of the pairwise connections between vertices upon the removal of an instance. Among them network motifs do not prevail. Rather, those patterns that are shared by the three networks exhibit a conspicuously enhanced pairwise disconnectivity index. Additionally, these are often located in close vicinity to each other or are even overlapping, since only a small number of genes are repeatedly present in most of them. Moreover, evidence has gathered that the importance of these pattern instances is due to synergistic rather than merely additive effects between their constituents. Conclusion A new method has been proposed
Exploitation of genetic interaction network topology for the prediction of epistatic behavior
Alanis Lobato, Gregorio
2013-10-01
Genetic interaction (GI) detection impacts the understanding of human disease and the ability to design personalized treatment. The mapping of every GI in most organisms is far from complete due to the combinatorial amount of gene deletions and knockdowns required. Computational techniques to predict new interactions based only on network topology have been developed in network science but never applied to GI networks.We show that topological prediction of GIs is possible with high precision and propose a graph dissimilarity index that is able to provide robust prediction in both dense and sparse networks.Computational prediction of GIs is a strong tool to aid high-throughput GI determination. The dissimilarity index we propose in this article is able to attain precise predictions that reduce the universe of candidate GIs to test in the lab. © 2013 Elsevier Inc.
Exploitation of genetic interaction network topology for the prediction of epistatic behavior
Alanis Lobato, Gregorio; Cannistraci, Carlo; Ravasi, Timothy
2013-01-01
Genetic interaction (GI) detection impacts the understanding of human disease and the ability to design personalized treatment. The mapping of every GI in most organisms is far from complete due to the combinatorial amount of gene deletions and knockdowns required. Computational techniques to predict new interactions based only on network topology have been developed in network science but never applied to GI networks.We show that topological prediction of GIs is possible with high precision and propose a graph dissimilarity index that is able to provide robust prediction in both dense and sparse networks.Computational prediction of GIs is a strong tool to aid high-throughput GI determination. The dissimilarity index we propose in this article is able to attain precise predictions that reduce the universe of candidate GIs to test in the lab. © 2013 Elsevier Inc.
Topological Origin of the Network Dilation Anomaly in Ion-Exchanged Glasses
Wang, Mengyi; Smedskjaer, Morten M.; Mauro, John C.; Sant, Gaurav; Bauchy, Mathieu
2017-11-01
Ion exchange is commonly used to strengthen oxide glasses. However, the resulting stuffed glasses usually do not reach the molar volume of as-melted glasses of similar composition—a phenomenon known as the network dilation anomaly. This behavior seriously limits the potential for the chemical strengthening of glasses and its origin remains one of the mysteries of glass science. Here, based on molecular dynamics simulations of sodium silicate glasses coupled with topological constraint theory, we show that the topology of the atomic network controls the extent of ion-exchange-induced dilation. We demonstrate that isostatic glasses do not show any network dilation anomaly. This is found to arise from the combined absence of floppy modes of deformation and internal eigenstress in isostatic atomic networks.
International Nuclear Information System (INIS)
Yang Dong-Sheng; Liu Zhen-Wei; Liu Zhao-Bing; Zhao Yan
2012-01-01
The networked synchronization problem of a class of master-slave chaotic systems with time-varying communication topologies is investigated in this paper. Based on algebraic graph theory and matrix theory, a simple linear state feedback controller is designed to synchronize the master chaotic system and the slave chaotic systems with a time-varying communication topology connection. The exponential stability of the closed-loop networked synchronization error system is guaranteed by applying Lyapunov stability theory. The derived novel criteria are in the form of linear matrix inequalities (LMIs), which are easy to examine and tremendously reduce the computation burden from the feedback matrices. This paper provides an alternative networked secure communication scheme which can be extended conveniently. An illustrative example is given to demonstrate the effectiveness of the proposed networked synchronization method. (general)
Small Strain Topological Effects of Biopolymer Networks with Rigid Cross-Links
Zagar, G.; Onck, P. R.; Van der Giessen, E.; Garikipati, K; Arruda, EM
2010-01-01
Networks of cross-linked filamentous biopolymers form topological structures characterized by L, T and X cross-link types of connectivity 2, 3 and 4, respectively. The distribution of cross-links over these three types proofs to be very important for the initial elastic shear stiffness of isotropic
Robust spatial memory maps in flickering neuronal networks: a topological model
Dabaghian, Yuri; Babichev, Andrey; Memoli, Facundo; Chowdhury, Samir; Rice University Collaboration; Ohio State University Collaboration
It is widely accepted that the hippocampal place cells provide a substrate of the neuronal representation of the environment--the ``cognitive map''. However, hippocampal network, as any other network in the brain is transient: thousands of hippocampal neurons die every day and the connections formed by these cells constantly change due to various forms of synaptic plasticity. What then explains the remarkable reliability of our spatial memories? We propose a computational approach to answering this question based on a couple of insights. First, we propose that the hippocampal cognitive map is fundamentally topological, and hence it is amenable to analysis by topological methods. We then apply several novel methods from homology theory, to understand how dynamic connections between cells influences the speed and reliability of spatial learning. We simulate the rat's exploratory movements through different environments and study how topological invariants of these environments arise in a network of simulated neurons with ``flickering'' connectivity. We find that despite transient connectivity the network of place cells produces a stable representation of the topology of the environment.
Directory of Open Access Journals (Sweden)
Mingrui eXia
2016-04-01
Full Text Available White matter (WM tracts serve as important material substrates for information transfer across brain regions. However, the topological roles of WM tracts in global brain communications and their underlying microstructural basis remain poorly understood. Here, we employed diffusion magnetic resonance imaging and graph-theoretical approaches to identify the pivotal WM connections in human whole-brain networks and further investigated their wiring substrates (including WM microstructural organization and physical consumption and topological contributions to the brain’s network backbone. We found that the pivotal WM connections with highly topological-edge centrality were primarily distributed in several long-range cortico-cortical connections (including the corpus callosum, cingulum and inferior fronto-occipital fasciculus and some projection tracts linking subcortical regions. These pivotal WM connections exhibited high levels of microstructural organization indicated by diffusion measures (the fractional anisotropy, the mean diffusivity and the axial diffusivity and greater physical consumption indicated by streamline lengths, and contributed significantly to the brain’s hubs and the rich-club structure. Network motif analysis further revealed their heavy participations in the organization of communication blocks, especially in routes involving inter-hemispheric heterotopic and extremely remote intra-hemispheric systems. Computational simulation models indicated the sharp decrease of global network integrity when attacking these highly centralized edges. Together, our results demonstrated high building-cost consumption and substantial communication capacity contributions for pivotal WM connections, which deepens our understanding of the topological mechanisms that govern the organization of human connectomes.
Directory of Open Access Journals (Sweden)
Qing Chen
2017-02-01
Full Text Available This article investigates the dynamic topology control problemof satellite cluster networks (SCNs in Earth observation (EO missions by applying a novel metric of stability for inter-satellite links (ISLs. The properties of the periodicity and predictability of satellites’ relative position are involved in the link cost metric which is to give a selection criterion for choosing the most reliable data routing paths. Also, a cooperative work model with reliability is proposed for the situation of emergency EO missions. Based on the link cost metric and the proposed reliability model, a reliability assurance topology control algorithm and its corresponding dynamic topology control (RAT strategy are established to maximize the stability of data transmission in the SCNs. The SCNs scenario is tested through some numeric simulations of the topology stability of average topology lifetime and average packet loss rate. Simulation results show that the proposed reliable strategy applied in SCNs significantly improves the data transmission performance and prolongs the average topology lifetime.
Integrated topology optimisation of multi-energy networks
Mazairac, L.A.J.; Salenbien, R.; Vanhoudt, D.; Desmedt, J.; Vries, de B.
2015-01-01
Multi-carrier hybrid energy distribution net- works provide flexibility in case of network malfunctions, energy shortages and price fluctuations through energy conversion and storage. Therefore hybrid networks can cope with large-scale integration of distributed and intermittent renewable energy
Optimal topology to minimizing congestion in connected communication complex network
Benyoussef, M.; Ez-Zahraouy, H.; Benyoussef, A.
In this paper, a new model of the interdependent complex network is proposed, based on two assumptions that (i) the capacity of a node depends on its degree, and (ii) the traffic load depends on the distribution of the links in the network. Based on these assumptions, the presented model proposes a method of connection not based on the node having a higher degree but on the region containing hubs. It is found that the final network exhibits two kinds of degree distribution behavior, depending on the kind and the way of the connection. This study reveals a direct relation between network structure and traffic flow. It is found that pc the point of transition between the free flow and the congested phase depends on the network structure and the degree distribution. Moreover, this new model provides an improvement in the traffic compared to the results found in a single network. The same behavior of degree distribution found in a BA network and observed in the real world is obtained; except for this model, the transition point between the free phase and congested phase is much higher than the one observed in a network of BA, for both static and dynamic protocols.
Fibril growth kinetics link buffer conditions and topology of 3D collagen I networks.
Kalbitzer, Liv; Pompe, Tilo
2018-02-01
Three-dimensional fibrillar networks reconstituted from collagen I are widely used as biomimetic scaffolds for in vitro and in vivo cell studies. Various physicochemical parameters of buffer conditions for in vitro fibril formation are well known, including pH-value, ion concentrations and temperature. However, there is a lack of a detailed understanding of reconstituting well-defined 3D network topologies, which is required to mimic specific properties of the native extracellular matrix. We screened a wide range of relevant physicochemical buffer conditions and characterized the topology of the reconstituted 3D networks in terms of mean pore size and fibril diameter. A congruent analysis of fibril formation kinetics by turbidimetry revealed the adjustment of the lateral growth phase of fibrils by buffer conditions to be key in the determination of pore size and fibril diameter of the networks. Although the kinetics of nucleation and linear growth phase were affected by buffer conditions as well, network topology was independent of those two growth phases. Overall, the results of our study provide necessary insights into how to engineer 3D collagen matrices with an independent control over topology parameters, in order to mimic in vivo tissues in in vitro experiments and tissue engineering applications. The study reports a comprehensive analysis of physicochemical conditions of buffer solutions to reconstitute defined 3D collagen I matrices. By a combined analysis of network topology, i.e., pore size and fibril diameter, and the kinetics of fibril formation we can reveal the dependence of 3D network topology on buffer conditions, such as pH-value, phosphate concentration and sodium chloride content. With those results we are now able to provide engineering strategies to independently tune the topology parameters of widely used 3D collagen scaffolds based on the buffer conditions. By that, we enable the straightforward mimicking of extracellular matrices of in vivo
Space evolution model and empirical analysis of an urban public transport network
Sui, Yi; Shao, Feng-jing; Sun, Ren-cheng; Li, Shu-jing
2012-07-01
This study explores the space evolution of an urban public transport network, using empirical evidence and a simulation model validated on that data. Public transport patterns primarily depend on traffic spatial-distribution, demands of passengers and expected utility of investors. Evolution is an iterative process of satisfying the needs of passengers and investors based on a given traffic spatial-distribution. The temporal change of urban public transport network is evaluated both using topological measures and spatial ones. The simulation model is validated using empirical data from nine big cities in China. Statistical analyses on topological and spatial attributes suggest that an evolution network with traffic demands characterized by power-law numerical values which distribute in a mode of concentric circles tallies well with these nine cities.
Network Performance Improvement under Epidemic Failures in Optical Transport Networks
DEFF Research Database (Denmark)
Fagertun, Anna Manolova; Ruepp, Sarah Renée
2013-01-01
In this paper we investigate epidemic failure spreading in large- scale GMPLS-controlled transport networks. By evaluating the effect of the epidemic failure spreading on the network, we design several strategies for cost-effective network performance improvement via differentiated repair times....... First we identify the most vulnerable and the most strategic nodes in the network. Then, via extensive simulations we show that strategic placement of resources for improved failure recovery has better performance than randomly assigning lower repair times among the network nodes. Our OPNET simulation...... model can be used during the network planning process for facilitating cost- effective network survivability design....
Synchronization propensity in networks of dynamical systems: A purely topological indicator
Fasani, S.; Rinaldi, S.
2012-01-01
Synchronization in networks of identical dynamical systems is enhanced by the number of manifolds in which synchrony of groups of systems is conserved or reinforced. Since the number of these invariant manifolds depends only on the coupling architecture of the network, it can be proposed as a purely topological indicator of synchronization propensity. The proposal is empirically validated through the detailed study of an ecological application.
Cannistraci, Carlo
2013-06-21
Motivation: Most functions within the cell emerge thanks to protein-protein interactions (PPIs), yet experimental determination of PPIs is both expensive and time-consuming. PPI networks present significant levels of noise and incompleteness. Predicting interactions using only PPI-network topology (topological prediction) is difficult but essential when prior biological knowledge is absent or unreliable.Methods: Network embedding emphasizes the relations between network proteins embedded in a low-dimensional space, in which protein pairs that are closer to each other represent good candidate interactions. To achieve network denoising, which boosts prediction performance, we first applied minimum curvilinear embedding (MCE), and then adopted shortest path (SP) in the reduced space to assign likelihood scores to candidate interactions. Furthermore, we introduce (i) a new valid variation of MCE, named non-centred MCE (ncMCE); (ii) two automatic strategies for selecting the appropriate embedding dimension; and (iii) two new randomized procedures for evaluating predictions.Results: We compared our method against several unsupervised and supervisedly tuned embedding approaches and node neighbourhood techniques. Despite its computational simplicity, ncMCE-SP was the overall leader, outperforming the current methods in topological link prediction.Conclusion: Minimum curvilinearity is a valuable non-linear framework that we successfully applied to the embedding of protein networks for the unsupervised prediction of novel PPIs. The rationale for our approach is that biological and evolutionary information is imprinted in the non-linear patterns hidden behind the protein network topology, and can be exploited for predicting new protein links. The predicted PPIs represent good candidates for testing in high-throughput experiments or for exploitation in systems biology tools such as those used for network-based inference and prediction of disease-related functional modules. The
Dynamics in small worlds of tree topologies of wireless sensor networks
DEFF Research Database (Denmark)
Li, Qiao; Zhang, Baihai; Fan, Zhun
2012-01-01
Tree topologies, which construct spatial graphs with large characteristic path lengths and small clustering coefficients, are ubiquitous in deployments of wireless sensor networks. Small worlds are investigated in tree-based networks. Due to link additions, characteristic path lengths reduce...... rapidly and clustering coefficients increase greatly. A tree abstract, Cayley tree, is considered for the study of the navigation algorithm, which runs automatically in the small worlds of tree-based networks. In the further study, epidemics in the small worlds of tree-based wireless sensor networks...
Study on the evolutionary optimization of the topology of network control systems
DEFF Research Database (Denmark)
Zhou, Z.; Chen, B.; Wang, H.
2010-01-01
Computer networks have been very popular in enterprise applications. However, optimisation of network designs that allows networks to be used more efficiently in industrial environment and enterprise applications remains an interesting research topic. This article mainly discusses the topology...... control network are considered in the optimisation process. In respect to the evolutionary algorithm design, an improved arena algorithm is proposed for the construction of the non-dominated set of the population. In addition, for the evaluation of individuals, the integrated use of the dominative...
Backoff-stage synchronization in three-hop string-topology wireless networks with hidden nodes
Sanada, Kosuke; Sekiya, Hiroo; Komuro, Nobuyoshi; Sakata, Shiro
In IEEE 802.11 wireless multi-hop networks, each node works individually and their individual operations generate entire network dynamics. It is important to clarify the network dynamics in wireless multi-hop networks for designing and constructing multi-hop communication networks. This paper presents the network-dynamics investigations for three-hop string-topology wireless network in detail. From the investigations, a “backoff-stage synchronization” phenomenon, which is mutuality between hidden nodes, is found. The mechanism of the backoff-stage synchronization is expressed and the sufficient conditions for the synchronization occurrence are given. This phenomenon gives some impacts on the IEEE 802.11 multi-hop-network communications.
Dynamics of topological solitons, knotted streamlines, and transport of cargo in liquid crystals
Sohn, Hayley R. O.; Ackerman, Paul J.; Boyle, Timothy J.; Sheetah, Ghadah H.; Fornberg, Bengt; Smalyukh, Ivan I.
2018-05-01
Active colloids and liquid crystals are capable of locally converting the macroscopically supplied energy into directional motion and promise a host of new applications, ranging from drug delivery to cargo transport at the mesoscale. Here we uncover how topological solitons in liquid crystals can locally transform electric energy to translational motion and allow for the transport of cargo along directions dependent on frequency of the applied electric field. By combining polarized optical video microscopy and numerical modeling that reproduces both the equilibrium structures of solitons and their temporal evolution in applied fields, we uncover the physical underpinnings behind this reconfigurable motion and study how it depends on the structure and topology of solitons. We show that, unexpectedly, the directional motion of solitons with and without the cargo arises mainly from the asymmetry in rotational dynamics of molecular ordering in liquid crystal rather than from the asymmetry of fluid flows, as in conventional active soft matter systems.
Network module detection: Affinity search technique with the multi-node topological overlap measure.
Li, Ai; Horvath, Steve
2009-07-20
Many clustering procedures only allow the user to input a pairwise dissimilarity or distance measure between objects. We propose a clustering method that can input a multi-point dissimilarity measure d(i1, i2, ..., iP) where the number of points P can be larger than 2. The work is motivated by gene network analysis where clusters correspond to modules of highly interconnected nodes. Here, we define modules as clusters of network nodes with high multi-node topological overlap. The topological overlap measure is a robust measure of interconnectedness which is based on shared network neighbors. In previous work, we have shown that the multi-node topological overlap measure yields biologically meaningful results when used as input of network neighborhood analysis. We adapt network neighborhood analysis for the use of module detection. We propose the Module Affinity Search Technique (MAST), which is a generalized version of the Cluster Affinity Search Technique (CAST). MAST can accommodate a multi-node dissimilarity measure. Clusters grow around user-defined or automatically chosen seeds (e.g. hub nodes). We propose both local and global cluster growth stopping rules. We use several simulations and a gene co-expression network application to argue that the MAST approach leads to biologically meaningful results. We compare MAST with hierarchical clustering and partitioning around medoid clustering. Our flexible module detection method is implemented in the MTOM software which can be downloaded from the following webpage: http://www.genetics.ucla.edu/labs/horvath/MTOM/
Study on the evolutionary optimisation of the topology of network control systems
Zhou, Zude; Chen, Benyuan; Wang, Hong; Fan, Zhun
2010-08-01
Computer networks have been very popular in enterprise applications. However, optimisation of network designs that allows networks to be used more efficiently in industrial environment and enterprise applications remains an interesting research topic. This article mainly discusses the topology optimisation theory and methods of the network control system based on switched Ethernet in an industrial context. Factors that affect the real-time performance of the industrial control network are presented in detail, and optimisation criteria with their internal relations are analysed. After the definition of performance parameters, the normalised indices for the evaluation of the topology optimisation are proposed. The topology optimisation problem is formulated as a multi-objective optimisation problem and the evolutionary algorithm is applied to solve it. Special communication characteristics of the industrial control network are considered in the optimisation process. In respect to the evolutionary algorithm design, an improved arena algorithm is proposed for the construction of the non-dominated set of the population. In addition, for the evaluation of individuals, the integrated use of the dominative relation method and the objective function combination method, for reducing the computational cost of the algorithm, are given. Simulation tests show that the performance of the proposed algorithm is preferable and superior compared to other algorithms. The final solution greatly improves the following indices: traffic localisation, traffic balance and utilisation rate balance of switches. In addition, a new performance index with its estimation process is proposed.
Topology determines force distributions in one-dimensional random spring networks
Heidemann, Knut M.; Sageman-Furnas, Andrew O.; Sharma, Abhinav; Rehfeldt, Florian; Schmidt, Christoph F.; Wardetzky, Max
2018-02-01
Networks of elastic fibers are ubiquitous in biological systems and often provide mechanical stability to cells and tissues. Fiber-reinforced materials are also common in technology. An important characteristic of such materials is their resistance to failure under load. Rupture occurs when fibers break under excessive force and when that failure propagates. Therefore, it is crucial to understand force distributions. Force distributions within such networks are typically highly inhomogeneous and are not well understood. Here we construct a simple one-dimensional model system with periodic boundary conditions by randomly placing linear springs on a circle. We consider ensembles of such networks that consist of N nodes and have an average degree of connectivity z but vary in topology. Using a graph-theoretical approach that accounts for the full topology of each network in the ensemble, we show that, surprisingly, the force distributions can be fully characterized in terms of the parameters (N ,z ) . Despite the universal properties of such (N ,z ) ensembles, our analysis further reveals that a classical mean-field approach fails to capture force distributions correctly. We demonstrate that network topology is a crucial determinant of force distributions in elastic spring networks.
On the Feasibility of Wireless Multimedia Sensor Networks over IEEE 802.15.5 Mesh Topologies.
Garcia-Sanchez, Antonio-Javier; Losilla, Fernando; Rodenas-Herraiz, David; Cruz-Martinez, Felipe; Garcia-Sanchez, Felipe
2016-05-05
Wireless Multimedia Sensor Networks (WMSNs) are a special type of Wireless Sensor Network (WSN) where large amounts of multimedia data are transmitted over networks composed of low power devices. Hierarchical routing protocols typically used in WSNs for multi-path communication tend to overload nodes located within radio communication range of the data collection unit or data sink. The battery life of these nodes is therefore reduced considerably, requiring frequent battery replacement work to extend the operational life of the WSN system. In a wireless sensor network with mesh topology, any node may act as a forwarder node, thereby enabling multiple routing paths toward any other node or collection unit. In addition, mesh topologies have proven advantages, such as data transmission reliability, network robustness against node failures, and potential reduction in energy consumption. This work studies the feasibility of implementing WMSNs in mesh topologies and their limitations by means of exhaustive computer simulation experiments. To this end, a module developed for the Synchronous Energy Saving (SES) mode of the IEEE 802.15.5 mesh standard has been integrated with multimedia tools to thoroughly test video sequences encoded using H.264 in mesh networks.
On the Feasibility of Wireless Multimedia Sensor Networks over IEEE 802.15.5 Mesh Topologies
Directory of Open Access Journals (Sweden)
Antonio-Javier Garcia-Sanchez
2016-05-01
Full Text Available Wireless Multimedia Sensor Networks (WMSNs are a special type of Wireless Sensor Network (WSN where large amounts of multimedia data are transmitted over networks composed of low power devices. Hierarchical routing protocols typically used in WSNs for multi-path communication tend to overload nodes located within radio communication range of the data collection unit or data sink. The battery life of these nodes is therefore reduced considerably, requiring frequent battery replacement work to extend the operational life of the WSN system. In a wireless sensor network with mesh topology, any node may act as a forwarder node, thereby enabling multiple routing paths toward any other node or collection unit. In addition, mesh topologies have proven advantages, such as data transmission reliability, network robustness against node failures, and potential reduction in energy consumption. This work studies the feasibility of implementing WMSNs in mesh topologies and their limitations by means of exhaustive computer simulation experiments. To this end, a module developed for the Synchronous Energy Saving (SES mode of the IEEE 802.15.5 mesh standard has been integrated with multimedia tools to thoroughly test video sequences encoded using H.264 in mesh networks.
International Nuclear Information System (INIS)
Daminelli, Simone; Thomas, Josephine Maria; Durán, Claudio; Vittorio Cannistraci, Carlo
2015-01-01
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
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
Regular Topologies for Gigabit Wide-Area Networks. Volume 1
Shacham, Nachum; Denny, Barbara A.; Lee, Diane S.; Khan, Irfan H.; Lee, Danny Y. C.; McKenney, Paul
1994-01-01
In general terms, this project aimed at the analysis and design of techniques for very high-speed networking. The formal objectives of the project were to: (1) Identify switch and network technologies for wide-area networks that interconnect a large number of users and can provide individual data paths at gigabit/s rates; (2) Quantitatively evaluate and compare existing and proposed architectures and protocols, identify their strength and growth potentials, and ascertain the compatibility of competing technologies; and (3) Propose new approaches to existing architectures and protocols, and identify opportunities for research to overcome deficiencies and enhance performance. The project was organized into two parts: 1. The design, analysis, and specification of techniques and protocols for very-high-speed network environments. In this part, SRI has focused on several key high-speed networking areas, including Forward Error Control (FEC) for high-speed networks in which data distortion is the result of packet loss, and the distribution of broadband, real-time traffic in multiple user sessions. 2. Congestion Avoidance Testbed Experiment (CATE). This part of the project was done within the framework of the DARTnet experimental T1 national network. The aim of the work was to advance the state of the art in benchmarking DARTnet's performance and traffic control by developing support tools for network experimentation, by designing benchmarks that allow various algorithms to be meaningfully compared, and by investigating new queueing techniques that better satisfy the needs of best-effort and reserved-resource traffic. This document is the final technical report describing the results obtained by SRI under this project. The report consists of three volumes: Volume 1 contains a technical description of the network techniques developed by SRI in the areas of FEC and multicast of real-time traffic. Volume 2 describes the work performed under CATE. Volume 3 contains the source
Topological structure of the space of phenotypes: the case of RNA neutral networks.
Directory of Open Access Journals (Sweden)
Jacobo Aguirre
Full Text Available The evolution and adaptation of molecular populations is constrained by the diversity accessible through mutational processes. RNA is a paradigmatic example of biopolymer where genotype (sequence and phenotype (approximated by the secondary structure fold are identified in a single molecule. The extreme redundancy of the genotype-phenotype map leads to large ensembles of RNA sequences that fold into the same secondary structure and can be connected through single-point mutations. These ensembles define neutral networks of phenotypes in sequence space. Here we analyze the topological properties of neutral networks formed by 12-nucleotides RNA sequences, obtained through the exhaustive folding of sequence space. A total of 4(12 sequences fragments into 645 subnetworks that correspond to 57 different secondary structures. The topological analysis reveals that each subnetwork is far from being random: it has a degree distribution with a well-defined average and a small dispersion, a high clustering coefficient, and an average shortest path between nodes close to its minimum possible value, i.e. the Hamming distance between sequences. RNA neutral networks are assortative due to the correlation in the composition of neighboring sequences, a feature that together with the symmetries inherent to the folding process explains the existence of communities. Several topological relationships can be analytically derived attending to structural restrictions and generic properties of the folding process. The average degree of these phenotypic networks grows logarithmically with their size, such that abundant phenotypes have the additional advantage of being more robust to mutations. This property prevents fragmentation of neutral networks and thus enhances the navigability of sequence space. In summary, RNA neutral networks show unique topological properties, unknown to other networks previously described.
Niu, Haijing; Wang, Jinhui; Zhao, Tengda; Shu, Ni; He, Yong
2012-01-01
The human brain is a highly complex system that can be represented as a structurally interconnected and functionally synchronized network, which assures both the segregation and integration of information processing. Recent studies have demonstrated that a variety of neuroimaging and neurophysiological techniques such as functional magnetic resonance imaging (MRI), diffusion MRI and electroencephalography/magnetoencephalography can be employed to explore the topological organization of human brain networks. However, little is known about whether functional near infrared spectroscopy (fNIRS), a relatively new optical imaging technology, can be used to map functional connectome of the human brain and reveal meaningful and reproducible topological characteristics. We utilized resting-state fNIRS (R-fNIRS) to investigate the topological organization of human brain functional networks in 15 healthy adults. Brain networks were constructed by thresholding the temporal correlation matrices of 46 channels and analyzed using graph-theory approaches. We found that the functional brain network derived from R-fNIRS data had efficient small-world properties, significant hierarchical modular structure and highly connected hubs. These results were highly reproducible both across participants and over time and were consistent with previous findings based on other functional imaging techniques. Our results confirmed the feasibility and validity of using graph-theory approaches in conjunction with optical imaging techniques to explore the topological organization of human brain networks. These results may expand a methodological framework for utilizing fNIRS to study functional network changes that occur in association with development, aging and neurological and psychiatric disorders.
Turner, Alexander P; Caves, Leo S D; Stepney, Susan; Tyrrell, Andy M; Lones, Michael A
2017-01-01
This paper describes the artificial epigenetic network, a recurrent connectionist architecture that is able to dynamically modify its topology in order to automatically decompose and solve dynamical problems. The approach is motivated by the behavior of gene regulatory networks, particularly the epigenetic process of chromatin remodeling that leads to topological change and which underlies the differentiation of cells within complex biological organisms. We expected this approach to be useful in situations where there is a need to switch between different dynamical behaviors, and do so in a sensitive and robust manner in the absence of a priori information about problem structure. This hypothesis was tested using a series of dynamical control tasks, each requiring solutions that could express different dynamical behaviors at different stages within the task. In each case, the addition of topological self-modification was shown to improve the performance and robustness of controllers. We believe this is due to the ability of topological changes to stabilize attractors, promoting stability within a dynamical regime while allowing rapid switching between different regimes. Post hoc analysis of the controllers also demonstrated how the partitioning of the networks could provide new insights into problem structure.
Implementing a Topology Management Algorithm for Mobile Ad-Hoc Networks
Directory of Open Access Journals (Sweden)
Mrinal K. Naskar
2008-01-01
Full Text Available In this paper, we propose to maintain the topology of a MANET by suitably selecting multiple coordinators among the nodes constituting the MANET. The maintenance of topology in a mobile ad–hoc network is of primary importance because the routing techniques can only work if we have a connected network. Thus of the burning issues at present is to device algorithms which ensure that the network topology is always maintained. The basic philosophy behind our algorithm is to isolate two coordinators amongst the system based on positional data. Once elected, they are entrusted with the responsibility to emit signals of different frequencies while the other nodes individually decide the logic they need to follow in order to maintain the topology, thereby greatly reducing the overhead. As far as our knowledge goes, we are the first ones to introduce the concept of multiple coordinators which not only reduces the workload of the coordinator, but also eliminates the need of different signal ranges thereby ensuring greater efficiency. We have simulated the algorithm with the help of a number of robots using embedded systems. The results we have obtained have been quite encouraging.
Probing the topological properties of complex networks modeling short written texts.
Directory of Open Access Journals (Sweden)
Diego R Amancio
Full Text Available In recent years, graph theory has been widely employed to probe several language properties. More specifically, the so-called word adjacency model has been proven useful for tackling several practical problems, especially those relying on textual stylistic analysis. The most common approach to treat texts as networks has simply considered either large pieces of texts or entire books. This approach has certainly worked well-many informative discoveries have been made this way-but it raises an uncomfortable question: could there be important topological patterns in small pieces of texts? To address this problem, the topological properties of subtexts sampled from entire books was probed. Statistical analyses performed on a dataset comprising 50 novels revealed that most of the traditional topological measurements are stable for short subtexts. When the performance of the authorship recognition task was analyzed, it was found that a proper sampling yields a discriminability similar to the one found with full texts. Surprisingly, the support vector machine classification based on the characterization of short texts outperformed the one performed with entire books. These findings suggest that a local topological analysis of large documents might improve its global characterization. Most importantly, it was verified, as a proof of principle, that short texts can be analyzed with the methods and concepts of complex networks. As a consequence, the techniques described here can be extended in a straightforward fashion to analyze texts as time-varying complex networks.
Broad-scale small-world network topology induces optimal synchronization of flexible oscillators
International Nuclear Information System (INIS)
Markovič, Rene; Gosak, Marko; Marhl, Marko
2014-01-01
The discovery of small-world and scale-free properties of many man-made and natural complex networks has attracted increasing attention. Of particular interest is how the structural properties of a network facilitate and constrain its dynamical behavior. In this paper we study the synchronization of weakly coupled limit-cycle oscillators in dependence on the network topology as well as the dynamical features of individual oscillators. We show that flexible oscillators, characterized by near zero values of divergence, express maximal correlation in broad-scale small-world networks, whereas the non-flexible (rigid) oscillators are best correlated in more heterogeneous scale-free networks. We found that the synchronization behavior is governed by the interplay between the networks global efficiency and the mutual frequency adaptation. The latter differs for flexible and rigid oscillators. The results are discussed in terms of evolutionary advantages of broad-scale small-world networks in biological systems
International Nuclear Information System (INIS)
Wilson, Mark
2012-01-01
The effects of network topology on the static structural, mechanical and dynamic properties of MX 2 network-forming liquids (with tetrahedral short-range order) are discussed. The network topology is controlled via a single model parameter (the anion polarizability) which effectively constrains the inter-tetrahedral linkages in a physically transparent manner. Critically, it is found to control the balance between the stability of corner- and edge-sharing tetrahedra. A potential rigidity transformation is investigated. The vibrational density of states is investigated, using an instantaneous normal model analysis, as a function of both anion polarizability and temperature. A low frequency peak is seen to appear and is shown to be correlated with the fraction of cations which are linked through solely edge-sharing structural motifs. A modified effective mean atom coordination number is proposed which allows the appearance of the low frequency feature to be understood in terms of a mean field rigidity percolation threshold. (paper)
DEFF Research Database (Denmark)
Soberano de Oliveira, Ana Paula; Patil, Kiran Raosaheb; Nielsen, Jens
2008-01-01
is to use the topology of bio-molecular interaction networks in order to constrain the solution space. Such approaches systematically integrate the existing biological knowledge with the 'omics' data. Results: Here we introduce a hypothesis-driven method that integrates bio-molecular network topology......Background: Uncovering the operating principles underlying cellular processes by using 'omics' data is often a difficult task due to the high-dimensionality of the solution space that spans all interactions among the bio-molecules under consideration. A rational way to overcome this problem...... with transcriptome data, thereby allowing the identification of key biological features (Reporter Features) around which transcriptional changes are significantly concentrated. We have combined transcriptome data with different biological networks in order to identify Reporter Gene Ontologies, Reporter Transcription...
Hemispheric lateralization of topological organization in structural brain networks.
Caeyenberghs, Karen; Leemans, Alexander
2014-09-01
The study on structural brain asymmetries in healthy individuals plays an important role in our understanding of the factors that modulate cognitive specialization in the brain. Here, we used fiber tractography to reconstruct the left and right hemispheric networks of a large cohort of 346 healthy participants (20-86 years) and performed a graph theoretical analysis to investigate this brain laterality from a network perspective. Findings revealed that the left hemisphere is significantly more "efficient" than the right hemisphere, whereas the right hemisphere showed higher values of "betweenness centrality" and "small-worldness." In particular, left-hemispheric networks displayed increased nodal efficiency in brain regions related to language and motor actions, whereas the right hemisphere showed an increase in nodal efficiency in brain regions involved in memory and visuospatial attention. In addition, we found that hemispheric networks decrease in efficiency with age. Finally, we observed significant gender differences in measures of global connectivity. By analyzing the structural hemispheric brain networks, we have provided new insights into understanding the neuroanatomical basis of lateralized brain functions. Copyright © 2014 Wiley Periodicals, Inc.
Space station common module network topology and hardware development
Anderson, P.; Braunagel, L.; Chwirka, S.; Fishman, M.; Freeman, K.; Eason, D.; Landis, D.; Lech, L.; Martin, J.; Mccorkle, J.
1990-01-01
Conceptual space station common module power management and distribution (SSM/PMAD) network layouts and detailed network evaluations were developed. Individual pieces of hardware to be developed for the SSM/PMAD test bed were identified. A technology assessment was developed to identify pieces of equipment requiring development effort. Equipment lists were developed from the previously selected network schematics. Additionally, functional requirements for the network equipment as well as other requirements which affected the suitability of specific items for use on the Space Station Program were identified. Assembly requirements were derived based on the SSM/PMAD developed requirements and on the selected SSM/PMAD network concepts. Basic requirements and simplified design block diagrams are included. DC remote power controllers were successfully integrated into the DC Marshall Space Flight Center breadboard. Two DC remote power controller (RPC) boards experienced mechanical failure of UES 706 stud-mounted diodes during mechanical installation of the boards into the system. These broken diodes caused input to output shorting of the RPC's. The UES 706 diodes were replaced on these RPC's which eliminated the problem. The DC RPC's as existing in the present breadboard configuration do not provide ground fault protection because the RPC was designed to only switch the hot side current. If ground fault protection were to be implemented, it would be necessary to design the system so the RPC switched both the hot and the return sides of power.
Learning and innovative elements of strategy adoption rules expand cooperative network topologies.
Wang, Shijun; Szalay, Máté S; Zhang, Changshui; Csermely, Peter
2008-04-09
Cooperation plays a key role in the evolution of complex systems. However, the level of cooperation extensively varies with the topology of agent networks in the widely used models of repeated games. Here we show that cooperation remains rather stable by applying the reinforcement learning strategy adoption rule, Q-learning on a variety of random, regular, small-word, scale-free and modular network models in repeated, multi-agent Prisoner's Dilemma and Hawk-Dove games. Furthermore, we found that using the above model systems other long-term learning strategy adoption rules also promote cooperation, while introducing a low level of noise (as a model of innovation) to the strategy adoption rules makes the level of cooperation less dependent on the actual network topology. Our results demonstrate that long-term learning and random elements in the strategy adoption rules, when acting together, extend the range of network topologies enabling the development of cooperation at a wider range of costs and temptations. These results suggest that a balanced duo of learning and innovation may help to preserve cooperation during the re-organization of real-world networks, and may play a prominent role in the evolution of self-organizing, complex systems.
Boaretto, B. R. R.; Budzinski, R. C.; Prado, T. L.; Kurths, J.; Lopes, S. R.
2018-05-01
It is known that neural networks under small-world topology can present anomalous synchronization and nonstationary behavior for weak coupling regimes. Here, we propose methods to suppress the anomalous synchronization and also to diminish the nonstationary behavior occurring in weakly coupled neural network under small-world topology. We consider a network of 2000 thermally sensitive identical neurons, based on the model of Hodgkin-Huxley in a small-world topology, with the probability of adding non local connection equal to p = 0 . 001. Based on experimental protocols to suppress anomalous synchronization, as well as nonstationary behavior of the neural network dynamics, we make use of (i) external stimulus (pulsed current); (ii) biologic parameters changing (neuron membrane conductance changes); and (iii) body temperature changes. Quantification analysis to evaluate phase synchronization makes use of the Kuramoto's order parameter, while recurrence quantification analysis, particularly the determinism, computed over the easily accessible mean field of network, the local field potential (LFP), is used to evaluate nonstationary states. We show that the methods proposed can control the anomalous synchronization and nonstationarity occurring for weak coupling parameter without any effect on the individual neuron dynamics, neither in the expected asymptotic synchronized states occurring for large values of the coupling parameter.
Network topology: patterns and mechanisms in plant-herbivore and host-parasitoid food webs.
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.
Yi, Li-Ye; Liang, Xia; Liu, Da-Ming; Sun, Bo; Ying, Sun; Yang, Dong-Bo; Li, Qing-Bin; Jiang, Chuan-Lu; Han, Ying
2015-10-01
Neuroimaging studies have demonstrated both structural and functional abnormalities in widespread brain regions in patients with subcortical vascular mild cognitive impairment (svMCI). However, whether and how these changes alter functional brain network organization remains largely unknown. We recruited 21 patients with svMCI and 26 healthy control (HC) subjects who underwent resting-state functional magnetic resonance imaging scans. Graph theory-based network analyses were used to investigate alterations in the topological organization of functional brain networks. Compared with the HC individuals, the patients with svMCI showed disrupted global network topology with significantly increased path length and modularity. Modular structure was also impaired in the svMCI patients with a notable rearrangement of the executive control module, where the parietal regions were split out and grouped as a separate module. The svMCI patients also revealed deficits in the intra- and/or intermodule connectivity of several brain regions. Specifically, the within-module degree was decreased in the middle cingulate gyrus while it was increased in the left anterior insula, medial prefrontal cortex and cuneus. Additionally, increased intermodule connectivity was observed in the inferior and superior parietal gyrus, which was associated with worse cognitive performance in the svMCI patients. Together, our results indicate that svMCI patients exhibit dysregulation of the topological organization of functional brain networks, which has important implications for understanding the pathophysiological mechanism of svMCI. © 2015 John Wiley & Sons Ltd.
Disorder Effects in Charge Transport and Spin Response of Topological Insulators
Zhao, Lukas Zhonghua
Topological insulators are a class of solids in which the non-trivial inverted bulk band structure gives rise to metallic surface states that are robust against impurity backscattering. First principle calculations predicted Bi2Te3, Sb2Te3 and Bi2Se3 to be three-dimensional (3D) topological insulators with a single Dirac cone on the surface. The topological surface states were subsequently observed by angle-resolved photoemission (ARPES) and scanning tunneling microscopy (STM). The investigations of charge transport through topological surfaces of 3D topological insulators, however, have faced a major challenge due to large charge carrier densities in the bulk donated by randomly distributed defects such as vacancies and antisites. This bulk disorder intermixes surface and bulk conduction channels, thereby complicating access to the low-energy (Dirac point) charge transport or magnetic response and resulting in the relatively low measured carrier mobilities. Moreover, charge inhomogeneity arising from bulk disorder can result in pronounced nanoscale spatial fluctuations of energy on the surface, leading to the formation of surface `puddles' of different carrier types. Great efforts have been made to combat the undesirable effects of disorder in 3D topological insulators and to reduce bulk carriers through chemical doping, nanostructure fabrication, and electric gating. In this work we have developed a new way to reduce bulk carrier densities using high-energy electron irradiation, thereby allowing us access to the topological surface quantum channels. We also found that disorder in 3D topological insulators can be beneficial. It can play an important part in enabling detection of unusual magnetic response from Dirac fermions and in uncovering new excitations, namely surface superconductivity in Dirac `puddles'. In Chapter 3 we show how by using differential magnetometry we could probe spin rotation in the 3D topological material family (Bi2Se 3, Bi2Te3 and Sb2Te3
Optimal transport on supply-demand networks.
Chen, Yu-Han; Wang, Bing-Hong; Zhao, Li-Chao; Zhou, Changsong; Zhou, Tao
2010-06-01
In the literature, transport networks are usually treated as homogeneous networks, that is, every node has the same function, simultaneously providing and requiring resources. However, some real networks, such as power grids and supply chain networks, show a far different scenario in which nodes are classified into two categories: supply nodes provide some kinds of services, while demand nodes require them. In this paper, we propose a general transport model for these supply-demand networks, associated with a criterion to quantify their transport capacities. In a supply-demand network with heterogeneous degree distribution, its transport capacity strongly depends on the locations of supply nodes. We therefore design a simulated annealing algorithm to find the near optimal configuration of supply nodes, which remarkably enhances the transport capacity compared with a random configuration and outperforms the degree target algorithm, the betweenness target algorithm, and the greedy method. This work provides a start point for systematically analyzing and optimizing transport dynamics on supply-demand networks.
Effects of network resolution on topological properties of human neocortex
DEFF Research Database (Denmark)
Romero-Garcia, Rafael; Atienza, Mercedes; Clemmensen, Line Katrine Harder
2012-01-01
Graph theoretical analyses applied to neuroimaging datasets have provided valuable insights into the large-scale anatomical organization of the human neocortex. Most of these studies were performed with different cortical scales leading to cortical networks with different levels of small-world or......Graph theoretical analyses applied to neuroimaging datasets have provided valuable insights into the large-scale anatomical organization of the human neocortex. Most of these studies were performed with different cortical scales leading to cortical networks with different levels of small...
Topological Reorganization of the Default Mode Network in Severe Male Obstructive Sleep Apnea
Directory of Open Access Journals (Sweden)
Liting Chen
2018-06-01
Full Text Available Impaired spontaneous regional activity and altered topology of the brain network have been observed in obstructive sleep apnea (OSA. However, the mechanisms of disrupted functional connectivity (FC and topological reorganization of the default mode network (DMN in patients with OSA remain largely unknown. We explored whether the FC is altered within the DMN and examined topological changes occur in the DMN in patients with OSA using a graph theory analysis of resting-state functional magnetic resonance imaging data and evaluated the relationship between neuroimaging measures and clinical variables. Resting-state data were obtained from 46 male patients with untreated severe OSA and 46 male good sleepers (GSs. We specifically selected 20 DMN subregions to construct the DMN architecture. The disrupted FC and topological properties of the DMN in patients with OSA were characterized using graph theory. The OSA group showed significantly decreased FC of the anterior–posterior DMN and within the posterior DMN, and also showed increased FC within the DMN. The DMN exhibited small-world topology in both OSA and GS groups. Compared to GSs, patients with OSA showed a decreased clustering coefficient (Cp and local efficiency, and decreased nodal centralities in the left posterior cingulate cortex and dorsal medial prefrontal cortex, and increased nodal centralities in the ventral medial prefrontal cortex and the right parahippocampal cortex. Finally, the abnormal DMN FC was significantly related to Cp, path length, global efficiency, and Montreal cognitive assessment score. OSA showed disrupted FC within the DMN, which may have contributed to the observed topological reorganization. These findings may provide further evidence of cognitive deficits in patients with OSA.
A Dynamic Game on Network Topology for Counterinsurgency Applications
2015-03-26
multicollinearity within the factors. All VIF values are adequately low, indicating the variance for each factor estimated in the model is not significantly...impacted by multicollinearity with other factors. 71 Table 9. 9/11 Hijacker Network Results Summary of Fit R2 0.5061 Adjusted R2 0.4536 Root Mean
Towards an optimal topology for hybrid energy networks
Mazairac, L.A.J.; Salenbien, R.; de Vries, B.
2015-01-01
Existing networks do not have the quantitative and qualitative capacity to facilitate the transition towards distributed renewable energy sources. Irregular production of energy over time at different locations will alter the current patters of energy flow, necessitating the implementation of short-
Directory of Open Access Journals (Sweden)
Xinwei Wang
2017-01-01
Full Text Available Topology detection for output-coupling weighted complex dynamical networks with two types of time delays is investigated in this paper. Different from existing literatures, coupling delay and transmission delay are simultaneously taken into account in the output-coupling network. Based on the idea of the state observer, we build the drive-response system and apply LaSalle’s invariance principle to the error dynamical system of the drive-response system. Several convergent criteria are deduced in the form of algebraic inequalities. Some numerical simulations for the complex dynamical network, with node dynamics being chaotic, are given to verify the effectiveness of the proposed scheme.
Resting-State Network Topology Differentiates Task Signals across the Adult Life Span.
Chan, Micaela Y; Alhazmi, Fahd H; Park, Denise C; Savalia, Neil K; Wig, Gagan S
2017-03-08
Brain network connectivity differs across individuals. For example, older adults exhibit less segregated resting-state subnetworks relative to younger adults (Chan et al., 2014). It has been hypothesized that individual differences in network connectivity impact the recruitment of brain areas during task execution. While recent studies have described the spatial overlap between resting-state functional correlation (RSFC) subnetworks and task-evoked activity, it is unclear whether individual variations in the connectivity pattern of a brain area (topology) relates to its activity during task execution. We report data from 238 cognitively normal participants (humans), sampled across the adult life span (20-89 years), to reveal that RSFC-based network organization systematically relates to the recruitment of brain areas across two functionally distinct tasks (visual and semantic). The functional activity of brain areas (network nodes) were characterized according to their patterns of RSFC: nodes with relatively greater connections to nodes in their own functional system ("non-connector" nodes) exhibited greater activity than nodes with relatively greater connections to nodes in other systems ("connector" nodes). This "activation selectivity" was specific to those brain systems that were central to each of the tasks. Increasing age was accompanied by less differentiated network topology and a corresponding reduction in activation selectivity (or differentiation) across relevant network nodes. The results provide evidence that connectional topology of brain areas quantified at rest relates to the functional activity of those areas during task. Based on these findings, we propose a novel network-based theory for previous reports of the "dedifferentiation" in brain activity observed in aging. SIGNIFICANCE STATEMENT Similar to other real-world networks, the organization of brain networks impacts their function. As brain network connectivity patterns differ across
Price, G Dean; Howitt, Susan M
2014-09-01
This mini-review addresses advances in understanding the transmembrane topologies of two unrelated, single-subunit bicarbonate transporters from cyanobacteria, namely BicA and SbtA. BicA is a Na(+)-dependent bicarbonate transporter that belongs to the SulP/SLC26 family that is widespread in both eukaryotes and prokaryotes. Topology mapping of BicA via the phoA/lacZ fusion reporter method identified 12 transmembrane helices with an unresolved hydrophobic region just beyond helix 8. Re-interpreting this data in the light of a recent topology study on rat prestin leads to a consensus topology of 14 transmembrane domains with a 7+7 inverted repeat structure. SbtA is also a Na(+)-dependent bicarbonate transporter, but of considerably higher affinity (Km 2-5 μM versus >100 μM for BicA). Whilst SbtA is widespread in cyanobacteria and a few bacteria, it appears to be absent from eukaryotes. Topology mapping of SbtA via the phoA/lacZ fusion reporter method identified 10 transmembrane helices. The topology consists of a 5+5 inverted repeat, with the two repeats separated by a large intracellular loop. The unusual location of the N and C-termini outside the cell raises the possibility that SbtA forms a novel fold, not so far identified by structural and topological studies on transport proteins.
Jin, Nana; Wu, Deng; Gong, Yonghui; Bi, Xiaoman; Jiang, Hong; Li, Kongning; Wang, Qianghu
2014-01-01
An increasing number of experiments have been designed to detect intracellular and intercellular molecular interactions. Based on these molecular interactions (especially protein interactions), molecular networks have been built for using in several typical applications, such as the discovery of new disease genes and the identification of drug targets and molecular complexes. Because the data are incomplete and a considerable number of false-positive interactions exist, protein interactions from different sources are commonly integrated in network analyses to build a stable molecular network. Although various types of integration strategies are being applied in current studies, the topological properties of the networks from these different integration strategies, especially typical applications based on these network integration strategies, have not been rigorously evaluated. In this paper, systematic analyses were performed to evaluate 11 frequently used methods using two types of integration strategies: empirical and machine learning methods. The topological properties of the networks of these different integration strategies were found to significantly differ. Moreover, these networks were found to dramatically affect the outcomes of typical applications, such as disease gene predictions, drug target detections, and molecular complex identifications. The analysis presented in this paper could provide an important basis for future network-based biological researches. PMID:25243127
Directory of Open Access Journals (Sweden)
Xinbo Ai
2014-11-01
Full Text Available Topological measures are crucial to describe, classify and understand complex networks. Lots of measures are proposed to characterize specific features of specific networks, but the relationships among these measures remain unclear. Taking into account that pulling networks from different domains together for statistical analysis might provide incorrect conclusions, we conduct our investigation with data observed from the same network in the form of simultaneously measured time series. We synthesize a transfer entropy-based framework to quantify the relationships among topological measures, and then to provide a holistic scenario of these measures by inferring a drive-response network. Techniques from Symbolic Transfer Entropy, Effective Transfer Entropy, and Partial Transfer Entropy are synthesized to deal with challenges such as time series being non-stationary, finite sample effects and indirect effects. We resort to kernel density estimation to assess significance of the results based on surrogate data. The framework is applied to study 20 measures across 2779 records in the Technology Exchange Network, and the results are consistent with some existing knowledge. With the drive-response network, we evaluate the influence of each measure by calculating its strength, and cluster them into three classes, i.e., driving measures, responding measures and standalone measures, according to the network communities.
Optimal transportation networks models and theory
Bernot, Marc; Morel, Jean-Michel
2009-01-01
The transportation problem can be formalized as the problem of finding the optimal way to transport a given measure into another with the same mass. In contrast to the Monge-Kantorovitch problem, recent approaches model the branched structure of such supply networks as minima of an energy functional whose essential feature is to favour wide roads. Such a branched structure is observable in ground transportation networks, in draining and irrigation systems, in electrical power supply systems and in natural counterparts such as blood vessels or the branches of trees. These lectures provide mathematical proof of several existence, structure and regularity properties empirically observed in transportation networks. The link with previous discrete physical models of irrigation and erosion models in geomorphology and with discrete telecommunication and transportation models is discussed. It will be mathematically proven that the majority fit in the simple model sketched in this volume.
Optimising Transport in a Homogeneous Network
WEAIRE, DENIS LAWRENCE
2004-01-01
PUBLISHED Many situations in physics, biology, and engineering consist of the transport of some physical quantity through a network of narrow channels. The ability of a network to transport such a quantity in every direction can be described by the average conductivity associated with it. When the flow through each channel is conserved and derives from a potential function, we show that there exists an upper bound of the average conductivity and explicitly give the expression f...
Optimizing transport in a homogeneous network
WEAIRE, DENIS LAWRENCE
2004-01-01
PUBLISHED Many situations in physics, biology, and engineering consist of the transport of some physical quantity through a network of narrow channels. The ability of a network to transport such a quantity in every direction can be described by the average conductivity associated with it. When the flow through each channel is conserved and derives from a potential function, we show that there exists an upper bound of the average conductivity and explicitly give the expression f...
Topological Vulnerability Evaluation Model Based on Fractal Dimension of Complex Networks.
Directory of Open Access Journals (Sweden)
Li Gou
Full Text Available With an increasing emphasis on network security, much more attentions have been attracted to the vulnerability of complex networks. In this paper, the fractal dimension, which can reflect space-filling capacity of networks, is redefined as the origin moment of the edge betweenness to obtain a more reasonable evaluation of vulnerability. The proposed model combining multiple evaluation indexes not only overcomes the shortage of average edge betweenness's failing to evaluate vulnerability of some special networks, but also characterizes the topological structure and highlights the space-filling capacity of networks. The applications to six US airline networks illustrate the practicality and effectiveness of our proposed method, and the comparisons with three other commonly used methods further validate the superiority of our proposed method.
Topology of Innovation Spaces in the Knowledge Networks Emerging through Questions-And-Answers
Andjelković, Miroslav; Tadić, Bosiljka; Mitrović Dankulov, Marija; Rajković, Milan; Melnik, Roderick
2016-01-01
The communication processes of knowledge creation represent a particular class of human dynamics where the expertise of individuals plays a substantial role, thus offering a unique possibility to study the structure of knowledge networks from online data. Here, we use the empirical evidence from questions-and-answers in mathematics to analyse the emergence of the network of knowledge contents (or tags) as the individual experts use them in the process. After removing extra edges from the network-associated graph, we apply the methods of algebraic topology of graphs to examine the structure of higher-order combinatorial spaces in networks for four consecutive time intervals. We find that the ranking distributions of the suitably scaled topological dimensions of nodes fall into a unique curve for all time intervals and filtering levels, suggesting a robust architecture of knowledge networks. Moreover, these networks preserve the logical structure of knowledge within emergent communities of nodes, labeled according to a standard mathematical classification scheme. Further, we investigate the appearance of new contents over time and their innovative combinations, which expand the knowledge network. In each network, we identify an innovation channel as a subgraph of triangles and larger simplices to which new tags attach. Our results show that the increasing topological complexity of the innovation channels contributes to network’s architecture over different time periods, and is consistent with temporal correlations of the occurrence of new tags. The methodology applies to a wide class of data with the suitable temporal resolution and clearly identified knowledge-content units. PMID:27171149
Slow, bursty dynamics as a consequence of quenched network topologies
Ådor, Géza
2014-04-01
Bursty dynamics of agents is shown to appear at criticality or in extended Griffiths phases, even in case of Poisson processes. I provide numerical evidence for a power-law type of intercommunication time distributions by simulating the contact process and the susceptible-infected-susceptible model. This observation suggests that in the case of nonstationary bursty systems, the observed non-Poissonian behavior can emerge as a consequence of an underlying hidden Poissonian network process, which is either critical or exhibits strong rare-region effects. On the contrary, in time-varying networks, rare-region effects do not cause deviation from the mean-field behavior, and heterogeneity-induced burstyness is absent.
Slow, bursty dynamics as a consequence of quenched network topologies.
Ódor, Géza
2014-04-01
Bursty dynamics of agents is shown to appear at criticality or in extended Griffiths phases, even in case of Poisson processes. I provide numerical evidence for a power-law type of intercommunication time distributions by simulating the contact process and the susceptible-infected-susceptible model. This observation suggests that in the case of nonstationary bursty systems, the observed non-Poissonian behavior can emerge as a consequence of an underlying hidden Poissonian network process, which is either critical or exhibits strong rare-region effects. On the contrary, in time-varying networks, rare-region effects do not cause deviation from the mean-field behavior, and heterogeneity-induced burstyness is absent.
Network neighborhood analysis with the multi-node topological overlap measure.
Li, Ai; Horvath, Steve
2007-01-15
The goal of neighborhood analysis is to find a set of genes (the neighborhood) that is similar to an initial 'seed' set of genes. Neighborhood analysis methods for network data are important in systems biology. If individual network connections are susceptible to noise, it can be advantageous to define neighborhoods on the basis of a robust interconnectedness measure, e.g. the topological overlap measure. Since the use of multiple nodes in the seed set may lead to more informative neighborhoods, it can be advantageous to define multi-node similarity measures. The pairwise topological overlap measure is generalized to multiple network nodes and subsequently used in a recursive neighborhood construction method. A local permutation scheme is used to determine the neighborhood size. Using four network applications and a simulated example, we provide empirical evidence that the resulting neighborhoods are biologically meaningful, e.g. we use neighborhood analysis to identify brain cancer related genes. An executable Windows program and tutorial for multi-node topological overlap measure (MTOM) based analysis can be downloaded from the webpage (http://www.genetics.ucla.edu/labs/horvath/MTOM/).
AlignNemo: a local network alignment method to integrate homology and topology.
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Giovanni Ciriello
Full Text Available Local network alignment is an important component of the analysis of protein-protein interaction networks that may lead to the identification of evolutionary related complexes. We present AlignNemo, a new algorithm that, given the networks of two organisms, uncovers subnetworks of proteins that relate in biological function and topology of interactions. The discovered conserved subnetworks have a general topology and need not to correspond to specific interaction patterns, so that they more closely fit the models of functional complexes proposed in the literature. The algorithm is able to handle sparse interaction data with an expansion process that at each step explores the local topology of the networks beyond the proteins directly interacting with the current solution. To assess the performance of AlignNemo, we ran a series of benchmarks using statistical measures as well as biological knowledge. Based on reference datasets of protein complexes, AlignNemo shows better performance than other methods in terms of both precision and recall. We show our solutions to be biologically sound using the concept of semantic similarity applied to Gene Ontology vocabularies. The binaries of AlignNemo and supplementary details about the algorithms and the experiments are available at: sourceforge.net/p/alignnemo.
A model for phosphate glass topology considering the modifying ion sub-network
DEFF Research Database (Denmark)
Hermansen, Christian; Mauro, J.C.; Yue, Yuanzheng
2014-01-01
In the present paper we establish a temperature dependent constraint model of alkali phosphate glasses considering the structural and topological role of the modifying ion sub-network constituted by alkali ions and their non-bonding oxygen coordination spheres. The model is consistent with availa......In the present paper we establish a temperature dependent constraint model of alkali phosphate glasses considering the structural and topological role of the modifying ion sub-network constituted by alkali ions and their non-bonding oxygen coordination spheres. The model is consistent...... with available structural data by NMR and molecular dynamics simulation and dynamic data such glass transition temperature (Tg) and liquid fragility (m). Alkali phosphate glasses are exemplary systems for developing constraint model since the modifying cation network plays an important role besides the primary...... phosphate network. The proposed topological model predicts the changing trend of the Tg and m with increasing alkali oxide content for alkali phosphate glasses, including an anomalous minimum at around 20 mol% alkali oxide content. We find that the minimum in Tg and m is caused by increased connectivity...
International Nuclear Information System (INIS)
Li, Jian; Dueñas-Osorio, Leonardo; Chen, Changkun; Shi, Congling
2016-01-01
As infrastructure systems evolve, their design, maintenance, and optimal performance require mature tools from system reliability theory, as well as principles to handle emerging system features, such as controllability. This paper conducts a comparative study of the connectivity reliability (CR) and topological controllability (TC) of infrastructure systems in terms of three aspects: topology, robustness, and node importance. Taking eight city-level power transmission networks and thousands of artificial networks as examples, this paper reveals that a dense and homogeneous network topology is better to satisfy CR and TC requirements, than more common sparse and heterogeneous networks when node attributes are generic. It is observed that the average degree's impact on CR is more significant than on TC, while degree heterogeneity is more significant on TC. When node attributes are accounted for, for generators the reliability-based node importance measure may underestimate some important nodes in terms of TC, and vice versa—an issue not observed for substation nodes. The findings in this paper suggest a potential new direction to enhance reliability-based design by integrating it with emerging controllability-based measures relevant in the future as infrastructure networks increase reliance on information systems. - Highlights: • Compares connectivity reliability (CR) and topological controllability (TC) metrics. • Develops a controllability index and a controllability-based node importance metric. • CR is more sensitive to degree while TC is more sensitive to degree heterogeneity. • CR-based importance measures match TC-based measures for substation nodes. • CR- and TC-based measures are complementary to identify important generator nodes.
Evidence for fish dispersal from spatial analysis of stream network topology
Hitt, N.P.; Angermeier, P.L.
2008-01-01
Developing spatially explicit conservation strategies for stream fishes requires an understanding of the spatial structure of dispersal within stream networks. We explored spatial patterns of stream fish dispersal by evaluating how the size and proximity of connected streams (i.e., stream network topology) explained variation in fish assemblage structure and how this relationship varied with local stream size. We used data from the US Environmental Protection Agency's Environmental Monitoring and Assessment Program in wadeable streams of the Mid-Atlantic Highlands region (n = 308 sites). We quantified stream network topology with a continuous analysis based on the rate of downstream flow accumulation from sites and with a discrete analysis based on the presence of mainstem river confluences (i.e., basin area >250 km2) within 20 fluvial km (fkm) from sites. Continuous variation in stream network topology was related to local species richness within a distance of ???10 fkm, suggesting an influence of fish dispersal within this spatial grain. This effect was explained largely by catostomid species, cyprinid species, and riverine species, but was not explained by zoogeographic regions, ecoregions, sampling period, or spatial autocorrelation. Sites near mainstem river confluences supported greater species richness and abundance of catostomid, cyprinid, and ictalurid fishes than did sites >20 fkm from such confluences. Assemblages at sites on the smallest streams were not related to stream network topology, consistent with the hypothesis that local stream size regulates the influence of regional dispersal. These results demonstrate that the size and proximity of connected streams influence the spatial distribution of fish and suggest that these influences can be incorporated into the designs of stream bioassessments and reserves to enhance management efficacy. ?? 2008 by The North American Benthological Society.
Wang, Junjing; Qiu, Shijun; Xu, Yong; Liu, Zhenyin; Wen, Xue; Hu, Xiangshu; Zhang, Ruibin; Li, Meng; Wang, Wensheng; Huang, Ruiwang
2014-09-01
Temporal lobe epilepsy (TLE) is one of the most common forms of drug-resistant epilepsy. Previous studies have indicated that the TLE-related impairments existed in extensive local functional networks. However, little is known about the alterations in the topological properties of whole brain functional networks. In this study, we acquired resting-state BOLD-fMRI (rsfMRI) data from 26 TLE patients and 25 healthy controls, constructed their whole brain functional networks, compared the differences in topological parameters between the TLE patients and the controls, and analyzed the correlation between the altered topological properties and the epilepsy duration. The TLE patients showed significant increases in clustering coefficient and characteristic path length, but significant decrease in global efficiency compared to the controls. We also found altered nodal parameters in several regions in the TLE patients, such as the bilateral angular gyri, left middle temporal gyrus, right hippocampus, triangular part of left inferior frontal gyrus, left inferior parietal but supramarginal and angular gyri, and left parahippocampus gyrus. Further correlation analysis showed that the local efficiency of the TLE patients correlated positively with the epilepsy duration. Our results indicated the disrupted topological properties of whole brain functional networks in TLE patients. Our findings indicated the TLE-related impairments in the whole brain functional networks, which may help us to understand the clinical symptoms of TLE patients and offer a clue for the diagnosis and treatment of the TLE patients. Copyright © 2014 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.
Crowdsourcing Physical Network Topology Mapping With Net.Tagger
2016-03-01
Markup Language LAMP Linux Apache MySQL PHP NANOG North American Network Operators Group NGO Non-Government Organization NPS Naval Postgraduate School...project’s choices closely mirror the archetypal Linux Apache MySQL PHP (LAMP) stack with a minor change to the database component, placing it on par...ahead of Windows’ third place 3.5% [54]. Technologically, it is not possible to port or cross-compile net.Tagger’s java - based Android code directly to
Analysis of topological relationships and network properties in the interactions of human beings.
Directory of Open Access Journals (Sweden)
Ye Yuan
Full Text Available In the animal world, various kinds of collective motions have been found and proven to be efficient ways of carrying out some activities such as searching for food and avoiding predators. Many scholars research the interactions of collective behaviors of human beings according to the rules of collective behaviors of animals. Based on the Lennard-Jones potential function and a self-organization process, our paper proposes a topological communication model to simulate the collective behaviors of human beings. In the results of simulations, we find various types of collective behavior and fission behavior and discover the threshold for the emergence of collective behavior, which is the range five to seven for the number of topology K. According to the analysis of network properties of the model, the in-degree of individuals is always equal to the number of topology. In the stable state, the out-degrees of individuals distribute around the value of the number of topology K, except that the out-degree of a single individual is approximately double the out-degrees of the other individuals. In addition, under different initial conditions, some features of different kinds of networks emerge from the model. We also find the leader and herd mentality effects in the characteristics of the behaviors of human beings in our model. Thus, this work could be used to discover how to promote the emergence of beneficial group behaviors and prevent the emergence of harmful behaviors.
Energy Technology Data Exchange (ETDEWEB)
Kashuba, Oleksiy; Trauzettel, Bjoern [Institut fuer Theoretische Physik und Astrophysik, Universitaet Wuerzburg, 97074 Wuerzburg (Germany); Timm, Carsten [Institut fuer Theoretische Physik, TU Dresden, 01062 Dresden (Germany)
2016-07-01
The system with multiple Majorana states coupled to the normal lead can potentially support the interaction between Majorana fermions and electrons. Such system can be implemented by several floating topological superconducting wires with large charging energy asymmetrically coupled to two normal leads. The analysis of the renormalization flow shows that there is a single fixed point - the strong coupling limit of isotropic antiferromagnetic Kondo model. The topological Kondo-like interaction leads also to the selective renormalization of the tunneling coefficients, strongly enhancing one component and suppressing others. Thus, charging energy crucially changes the transport properties of the system leading to the universal single-channel conductance independently from the values of the initial leads-wires coupling.
Transport, shot noise, and topology in AC-driven dimer arrays
Niklas, Michael; Benito, Mónica; Kohler, Sigmund; Platero, Gloria
2016-11-01
We analyze an AC-driven dimer chain connected to a strongly biased electron source and drain. It turns out that the resulting transport exhibits fingerprints of topology. They are particularly visible in the driving-induced current suppression and the Fano factor. Thus, shot noise measurements provide a topological phase diagram as a function of the driving parameters. The observed phenomena can be explained physically by a mapping to an effective time-independent Hamiltonian and the emergence of edge states. Moreover, by considering quantum dissipation, we determine the requirements for the coherence properties in a possible experimental realization. For the computation of the zero-frequency noise, we develop an efficient method based on matrix-continued fractions.
Online Expansion Technology for Dynamic Topology Changing ZigBee Wireless Sensor Networks
Directory of Open Access Journals (Sweden)
Md. Emdadul Haque
2014-03-01
Full Text Available In ZigBee, the router capable devices have restriction to accept a number of devices as children devices. A router capable device can not allow any new device to join as a child device if it reaches to the maximum capacity of children or depth limit. According to ZigBee specification each device has a permanent 64-bit MAC address. If a device joins a ZigBee network, it receives a short 16-bit MAC address from the parent device. If a device can not join a network, it isolates from the network and becomes an orphan node even though address spaces are available in the network. The orphan problem becomes worse when the topology of the network changes dynamically. In this paper we propose an online expansion technology to connect the maximum number of devices specially for dynamic topology changing ZigBee wireless sensor networks. The proposed technology shares available address spaces of the router devices to reduce the number of orphan nodes in the network.
Inference of neuronal network spike dynamics and topology from calcium imaging data
Directory of Open Access Journals (Sweden)
Henry eLütcke
2013-12-01
Full Text Available Two-photon calcium imaging enables functional analysis of neuronal circuits by inferring action potential (AP occurrence ('spike trains' from cellular fluorescence signals. It remains unclear how experimental parameters such as signal-to-noise ratio (SNR and acquisition rate affect spike inference and whether additional information about network structure can be extracted. Here we present a simulation framework for quantitatively assessing how well spike dynamics and network topology can be inferred from noisy calcium imaging data. For simulated AP-evoked calcium transients in neocortical pyramidal cells, we analyzed the quality of spike inference as a function of SNR and data acquisition rate using a recently introduced peeling algorithm. Given experimentally attainable values of SNR and acquisition rate, neural spike trains could be reconstructed accurately and with up to millisecond precision. We then applied statistical neuronal network models to explore how remaining uncertainties in spike inference affect estimates of network connectivity and topological features of network organization. We define the experimental conditions suitable for inferring whether the network has a scale-free structure and determine how well hub neurons can be identified. Our findings provide a benchmark for future calcium imaging studies that aim to reliably infer neuronal network properties.
Strategy development management of Multimodal Transport Network
Directory of Open Access Journals (Sweden)
Nesterova Natalia S.
2016-01-01
Full Text Available The article gives a brief overview of works on the development of transport infrastructure for multimodal transportation and integration of Russian transport system into the international transport corridors. The technology for control of the strategy, that changes shape and capacity of Multi-modal Transport Network (MTN, is considered as part of the methodology for designing and development of MTN. This technology allows to carry out strategic and operational management of the strategy implementation based on the use of the balanced scorecard.
Rzucidlo, Justyna K; Roseman, Paige L; Laurienti, Paul J; Dagenbach, Dale
2013-01-01
Graph-theory based analyses of resting state functional Magnetic Resonance Imaging (fMRI) data have been used to map the network organization of the brain. While numerous analyses of resting state brain organization exist, many questions remain unexplored. The present study examines the stability of findings based on this approach over repeated resting state and working memory state sessions within the same individuals. This allows assessment of stability of network topology within the same state for both rest and working memory, and between rest and working memory as well. fMRI scans were performed on five participants while at rest and while performing the 2-back working memory task five times each, with task state alternating while they were in the scanner. Voxel-based whole brain network analyses were performed on the resulting data along with analyses of functional connectivity in regions associated with resting state and working memory. Network topology was fairly stable across repeated sessions of the same task, but varied significantly between rest and working memory. In the whole brain analysis, local efficiency, Eloc, differed significantly between rest and working memory. Analyses of network statistics for the precuneus and dorsolateral prefrontal cortex revealed significant differences in degree as a function of task state for both regions and in local efficiency for the precuneus. Conversely, no significant differences were observed across repeated sessions of the same state. These findings suggest that network topology is fairly stable within individuals across time for the same state, but also fluid between states. Whole brain voxel-based network analyses may prove to be a valuable tool for exploring how functional connectivity changes in response to task demands.
Directory of Open Access Journals (Sweden)
Justyna K Rzucidlo
Full Text Available BACKGROUND: Graph-theory based analyses of resting state functional Magnetic Resonance Imaging (fMRI data have been used to map the network organization of the brain. While numerous analyses of resting state brain organization exist, many questions remain unexplored. The present study examines the stability of findings based on this approach over repeated resting state and working memory state sessions within the same individuals. This allows assessment of stability of network topology within the same state for both rest and working memory, and between rest and working memory as well. METHODOLOGY/PRINCIPAL FINDINGS: fMRI scans were performed on five participants while at rest and while performing the 2-back working memory task five times each, with task state alternating while they were in the scanner. Voxel-based whole brain network analyses were performed on the resulting data along with analyses of functional connectivity in regions associated with resting state and working memory. Network topology was fairly stable across repeated sessions of the same task, but varied significantly between rest and working memory. In the whole brain analysis, local efficiency, Eloc, differed significantly between rest and working memory. Analyses of network statistics for the precuneus and dorsolateral prefrontal cortex revealed significant differences in degree as a function of task state for both regions and in local efficiency for the precuneus. Conversely, no significant differences were observed across repeated sessions of the same state. CONCLUSIONS/SIGNIFICANCE: These findings suggest that network topology is fairly stable within individuals across time for the same state, but also fluid between states. Whole brain voxel-based network analyses may prove to be a valuable tool for exploring how functional connectivity changes in response to task demands.
Topological derivatives of eigenvalues and neural networks in identification of imperfections
International Nuclear Information System (INIS)
Grzanek, M; Nowakowski, A; Sokolowski, J
2008-01-01
Numerical method for identification of imperfections is devised for elliptic spectral problems. The neural networks are employed for numerical solution. The topological derivatives of eigenvalues are used in the learning procedure of the neural networks. The topological derivatives of eigenvalues are determined by the methods of asymptotic analysis in singularly perturbed geometrical domains. The convergence of the numerical method in a probabilistic setting is analysed. The method is presented for the identification of small singular perturbations of the boundary of geometrical domain, however the framework is general and can be used for numerical solutions of inverse problems in the presence of small imperfections in the interior of the domain. Some numerical results are given for elliptic spectral problem in two spatial dimensions.
The Effects of Topology on Throughput Capacity of Large Scale Wireless Networks
Directory of Open Access Journals (Sweden)
Qiuming Liu
2017-03-01
Full Text Available In this paper, we jointly consider the inhomogeneity and spatial dimension in large scale wireless networks. We study the effects of topology on the throughput capacity. This problem is inherently difﬁcult since it is complex to handle the interference caused by simultaneous transmission. To solve this problem, we, according to the inhomogeneity of topology, divide the transmission into intra-cluster transmission and inter-cluster transmission. For the intra-cluster transmission, a spheroidal percolation model is constructed. The spheroidal percolation model guarantees a constant rate when a power control strategy is adopted. We also propose a cube percolation mode for the inter-cluster transmission. Different from the spheroidal percolation model, a constant transmission rate can be achieved without power control. For both transmissions, we propose a routing scheme with ﬁve phases. By comparing the achievable rate of each phase, we get the rate bottleneck, which is the throughput capacity of the network.
Musculoskeletal networks reveal topological disparity in mammalian neck evolution.
Arnold, Patrick; Esteve-Altava, Borja; Fischer, Martin S
2017-12-13
The increase in locomotor and metabolic performance during mammalian evolution was accompanied by the limitation of the number of cervical vertebrae to only seven. In turn, nuchal muscles underwent a reorganization while forelimb muscles expanded into the neck region. As variation in the cervical spine is low, the variation in the arrangement of the neck muscles and their attachment sites (i.e., the variability of the neck's musculoskeletal organization) is thus proposed to be an important source of neck disparity across mammals. Anatomical network analysis provides a novel framework to study the organization of the anatomical arrangement, or connectivity pattern, of the bones and muscles that constitute the mammalian neck in an evolutionary context. Neck organization in mammals is characterized by a combination of conserved and highly variable network properties. We uncovered a conserved regionalization of the musculoskeletal organization of the neck into upper, mid and lower cervical modules. In contrast, there is a varying degree of complexity or specialization and of the integration of the pectoral elements. The musculoskeletal organization of the monotreme neck is distinctively different from that of therian mammals. Our findings reveal that the limited number of vertebrae in the mammalian neck does not result in a low musculoskeletal disparity when examined in an evolutionary context. However, this disparity evolved late in mammalian history in parallel with the radiation of certain lineages (e.g., cetartiodactyls, xenarthrans). Disparity is further facilitated by the enhanced incorporation of forelimb muscles into the neck and their variability in attachment sites.
Tan, J. C.; Bennett, T. D.; Cheetham, A. K.
2010-01-01
The mechanical properties of seven zeolitic imidazolate frameworks (ZIFs) based on five unique network topologies have been systematically characterized by single-crystal nanoindentation studies. We demonstrate that the elastic properties of ZIF crystal structures are strongly correlated to the framework density and the underlying porosity. For the systems considered here, the elastic modulus was found to range from 3 to 10 GPa, whereas the hardness property lies between 300 MPa and 1.1 GPa. ...
Finite-time consensus for leader-following multi-agent systems over switching network topologies
International Nuclear Information System (INIS)
Sun Feng-Lan; Zhu Wei
2013-01-01
Finite-time consensus problem of the leader-following multi-agent system under switching network topologies is studied in this paper. Based on the graph theory, matrix theory, homogeneity with dilation, and LaSalle's invariance principle, the control protocol of each agent using local information is designed, and the detailed analysis of the leader-following finite-time consensus is provided. Some examples and simulation results are given to illustrate the effectiveness of the obtained theoretical results
Spatiotemporal Recurrent Convolutional Networks for Traffic Prediction in Transportation Networks
Directory of Open Access Journals (Sweden)
Haiyang Yu
2017-06-01
Full Text Available Predicting large-scale transportation network traffic has become an important and challenging topic in recent decades. Inspired by the domain knowledge of motion prediction, in which the future motion of an object can be predicted based on previous scenes, we propose a network grid representation method that can retain the fine-scale structure of a transportation network. Network-wide traffic speeds are converted into a series of static images and input into a novel deep architecture, namely, spatiotemporal recurrent convolutional networks (SRCNs, for traffic forecasting. The proposed SRCNs inherit the advantages of deep convolutional neural networks (DCNNs and long short-term memory (LSTM neural networks. The spatial dependencies of network-wide traffic can be captured by DCNNs, and the temporal dynamics can be learned by LSTMs. An experiment on a Beijing transportation network with 278 links demonstrates that SRCNs outperform other deep learning-based algorithms in both short-term and long-term traffic prediction.
Woolley-Meza, O.; Thiemann, C.; Grady, D.; Lee, J. J.; Seebens, H.; Blasius, B.; Brockmann, D.
2011-12-01
We present a comparative network-theoretic analysis of the two largest global transportation networks: the worldwide air-transportation network (WAN) and the global cargo-ship network (GCSN). We show that both networks exhibit surprising statistical similarities despite significant differences in topology and connectivity. Both networks exhibit a discontinuity in node and link betweenness distributions which implies that these networks naturally segregate into two different classes of nodes and links. We introduce a technique based on effective distances, shortest paths and shortest path trees for strongly weighted symmetric networks and show that in a shortest path tree representation the most significant features of both networks can be readily seen. We show that effective shortest path distance, unlike conventional geographic distance measures, strongly correlates with node centrality measures. Using the new technique we show that network resilience can be investigated more precisely than with contemporary techniques that are based on percolation theory. We extract a functional relationship between node characteristics and resilience to network disruption. Finally we discuss the results, their implications and conclude that dynamic processes that evolve on both networks are expected to share universal dynamic characteristics.
Directory of Open Access Journals (Sweden)
Yaou Liu
Full Text Available OBJECTIVE: To investigate the topological alterations of the whole-brain white-matter (WM structural networks in patients with neuromyelitis optica (NMO. METHODS: The present study involved 26 NMO patients and 26 age- and sex-matched healthy controls. WM structural connectivity in each participant was imaged with diffusion-weighted MRI and represented in terms of a connectivity matrix using deterministic tractography method. Graph theory-based analyses were then performed for the characterization of brain network properties. A multiple linear regression analysis was performed on each network metric between the NMO and control groups. RESULTS: The NMO patients exhibited abnormal small-world network properties, as indicated by increased normalized characteristic path length, increased normalized clustering and increased small-worldness. Furthermore, largely similar hub distributions of the WM structural networks were observed between NMO patients and healthy controls. However, regional efficiency in several brain areas of NMO patients was significantly reduced, which were mainly distributed in the default-mode, sensorimotor and visual systems. Furthermore, we have observed increased regional efficiency in a few brain regions such as the orbital parts of the superior and middle frontal and fusiform gyri. CONCLUSION: Although the NMO patients in this study had no discernible white matter T2 lesions in the brain, we hypothesize that the disrupted topological organization of WM networks provides additional evidence for subtle, widespread cerebral WM pathology in NMO.
Effect of dataset selection on the topological interpretation of protein interaction networks
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Robertson David L
2005-09-01
Full Text Available Abstract Background Studies of the yeast protein interaction network have revealed distinct correlations between the connectivity of individual proteins within the network and the average connectivity of their neighbours. Although a number of biological mechanisms have been proposed to account for these findings, the significance and influence of the specific datasets included in these studies has not been appreciated adequately. Results We show how the use of different interaction data sets, such as those resulting from high-throughput or small-scale studies, and different modelling methodologies for the derivation pair-wise protein interactions, can dramatically change the topology of these networks. Furthermore, we show that some of the previously reported features identified in these networks may simply be the result of experimental or methodological errors and biases. Conclusion When performing network-based studies, it is essential to define what is meant by the term "interaction" and this must be taken into account when interpreting the topologies of the networks generated. Consideration must be given to the type of data included and appropriate controls that take into account the idiosyncrasies of the data must be selected
Directory of Open Access Journals (Sweden)
Yinyin Yuan
Full Text Available Inferring regulatory relationships among many genes based on their temporal variation in transcript abundance has been a popular research topic. Due to the nature of microarray experiments, classical tools for time series analysis lose power since the number of variables far exceeds the number of the samples. In this paper, we describe some of the existing multivariate inference techniques that are applicable to hundreds of variables and show the potential challenges for small-sample, large-scale data. We propose a directed partial correlation (DPC method as an efficient and effective solution to regulatory network inference using these data. Specifically for genomic data, the proposed method is designed to deal with large-scale datasets. It combines the efficiency of partial correlation for setting up network topology by testing conditional independence, and the concept of Granger causality to assess topology change with induced interruptions. The idea is that when a transcription factor is induced artificially within a gene network, the disruption of the network by the induction signifies a genes role in transcriptional regulation. The benchmarking results using GeneNetWeaver, the simulator for the DREAM challenges, provide strong evidence of the outstanding performance of the proposed DPC method. When applied to real biological data, the inferred starch metabolism network in Arabidopsis reveals many biologically meaningful network modules worthy of further investigation. These results collectively suggest DPC is a versatile tool for genomics research. The R package DPC is available for download (http://code.google.com/p/dpcnet/.
Protection of Passive Optical Networks by Using Ring Topology and Tunable Splitters
Directory of Open Access Journals (Sweden)
Pavel Lafata
2013-01-01
Full Text Available This article proposes an innovative method for protecting of passive optical networks (PONs, especially the central optical unit – optical line termination (OLT. PON networks are typically used in modern high-speed access networks, but there are also several specific applications, such as in business, army or science sector, which require a complex protection and backup system against failures and malfunctions. A standard tree or star topologies, which are usually used for PON networks, are significantly vulnerable mainly against the malfunctions and failures of OLT unit or feeder optical cable. The method proposed in this paper is focused on forming PON network with ring topology using passive optical splitters. The main idea is based on the possibility of placing both OLT units (primary and secondary on the opposite sides of the ring, which can potentially increase the resistance of network. This method is described in the article and scenarios and calculations using symmetric or tunable asymmetric passive optical splitters are included as well.
The influence of passenger flow on the topology characteristics of urban rail transit networks
Hu, Yingyue; Chen, Feng; Chen, Peiwen; Tan, Yurong
2017-05-01
Current researches on the network characteristics of metro networks are generally carried out on topology networks without passenger flows running on it, thus more complex features of the networks with ridership loaded on it cannot be captured. In this study, we incorporated the load of metro networks, passenger volume, into the exploration of network features. Thus, the network can be examined in the context of operation, which is the ultimate purpose of the existence of a metro network. To this end, section load was selected as an edge weight to demonstrate the influence of ridership on the network, and a weighted calculation method for complex network indicators and robustness were proposed to capture the unique behaviors of a metro network with passengers flowing in it. The proposed method was applied on Beijing Subway. Firstly, the passenger volume in terms of daily origin and destination matrix was extracted from exhausted transit smart card data. Using the established approach and the matrix as weighting, common indicators of complex network including clustering coefficient, betweenness and degree were calculated, and network robustness were evaluated under potential attacks. The results were further compared to that of unweighted networks, and it suggests indicators of the network with consideration of passenger volumes differ from that without ridership to some extent, and networks tend to be more vulnerable than that without load on it. The significance sequence for the stations can be changed. By introducing passenger flow weighting, actual operation status of the network can be reflected more accurately. It is beneficial to determine the crucial stations and make precautionary measures for the entire network’s operation security.
Thermoelectric Transport by Surface States in Bi2Se3-Based Topological Insulator Thin Films
International Nuclear Information System (INIS)
Li Long-Long; Xu Wen
2015-01-01
We develop a tractable theoretical model to investigate the thermoelectric (TE) transport properties of surface states in topological insulator thin films (TITFs) of Bi 2 Se 3 at room temperature. The hybridization between top and bottom surface states in the TITF plays a significant role. With the increasing hybridization-induced surface gap, the electrical conductivity and electron thermal conductivity decrease while the Seebeck coefficient increases. This is due to the metal-semiconductor transition induced by the surface-state hybridization. Based on these TE transport coefficients, the TE figure-of-merit ZT is evaluated. It is shown that ZT can be greatly improved by the surface-state hybridization. Our theoretical results are pertinent to the exploration of the TE transport properties of surface states in TITFs and to the potential application of Bi 2 Se 3 -based TITFs as high-performance TE materials and devices. (paper)
Transport properties of the topological Kondo insulator SmB6 under the irradiation of light
International Nuclear Information System (INIS)
Zhu Guo-Bao; Yang Hui-Min
2016-01-01
In this paper, we study transport properties of the X point in the Brillouin zone of the topological Kondo insulator SmB 6 under the application of a circularly polarized light. The transport properties at high-frequency regime and low-frequency regime as a function of the ratio ( κ ) of the Dresselhaus-like and Rashba-like spin–orbit parameter are studied based on the Floquet theory and Boltzmann equation respectively. The sign of Hall conductivity at high-frequency regime can be reversed by the ratio κ and the amplitude of the light. The amplitude of the current can be enhanced by the ratio κ . Our findings provide a way to control the transport properties of the Dirac materials at low-frequency regime. (paper)
Pal, Anirban; Picu, Catalin; Lupulescu, Marian V.
We study the mechanical behavior of two-dimensional, stochastically microcracked continua in the range of crack densities close to, and above the transport percolation threshold. We show that these materials retain stiffness up to crack densities much larger than the transport percolation threshold, due to topological interlocking of sample sub-domains. Even with a linear constitutive law for the continuum, the mechanical behavior becomes non-linear in the range of crack densities bounded by the transport and stiffness percolation thresholds. The effect is due to the fractal nature of the fragmentation process and is not linked to the roughness of individual cracks. We associate this behavior to that of itacolumite, a sandstone that exhibits unusual flexibility.
Hopping in the Crowd to Unveil Network Topology
Asllani, Malbor; Carletti, Timoteo; Di Patti, Francesca; Fanelli, Duccio; Piazza, Francesco
2018-04-01
We introduce a nonlinear operator to model diffusion on a complex undirected network under crowded conditions. We show that the asymptotic distribution of diffusing agents is a nonlinear function of the nodes' degree and saturates to a constant value for sufficiently large connectivities, at variance with standard diffusion in the absence of excluded-volume effects. Building on this observation, we define and solve an inverse problem, aimed at reconstructing the a priori unknown connectivity distribution. The method gathers all the necessary information by repeating a limited number of independent measurements of the asymptotic density at a single node, which can be chosen randomly. The technique is successfully tested against both synthetic and real data and is also shown to estimate with great accuracy the total number of nodes.
Strategies for optical transport network recovery under epidemic network failures
DEFF Research Database (Denmark)
Ruepp, Sarah Renée; Fagertun, Anna Manolova; Kosteas, Vasileios
2015-01-01
The current trend in deploying automatic control plane solutions for increased flexibility in the optical transport layer leads to numerous advantages for both the operators and the customers, but also pose challenges related to the stability of the network and its ability to operate in a robust...... manner under different failure scenarios. This work evaluates two rerouting strategies and proposes four policies for failure handling in a connection-oriented optical transport network, under generalized multiprotocol label switching control plane. The performance of the strategies and the policies......, and that there exist a clear trade-off between policy performance and network resource consumption, which must be addressed by network operators for improved robustness of their transport infrastructures. Applying proactive methods for avoiding areas where epidemic failures spread results in 50% less connections...
Dirac-Screening Stabilized Surface-State Transport in a Topological Insulator
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Christoph Brüne
2014-12-01
Full Text Available We report magnetotransport studies on a gated strained HgTe device. This material is a three-dimensional topological insulator and exclusively shows surface-state transport. Remarkably, the Landau-level dispersion and the accuracy of the Hall quantization remain unchanged over a wide density range (3×10^{11} cm^{−2}
International Nuclear Information System (INIS)
Wang Haiyan; Chen Xiongwen; Zhou Xiaoying; Zhang Lebo; Zhou Guanghui
2012-01-01
We study the electronic structure and transport for Dirac electron on the surface of a three-dimensional (3D) topological insulator attached to an electromagnetic superlattice. It is found that, by means of the transfer-matrix method, the number of electronic tunneling channels for magnetic barriers in antiparallel alignment is larger than that in parallel alignment, which stems to the energy band structures. Interestingly, a remarkable semiconducting transport behavior appears in this system with a strong magnetic barrier due to low energy band nearly paralleling to the Fermi level. Consequently, there is only small incident angle transport in the higher energy region when the system is modulated mainly by the higher electric barriers. We further find that the spatial distribution of the spin polarization oscillates periodically in the incoming region, but it is almost in-plane with a fixed direction in the transmitting region. The results may provide a further understanding of the nature of 3D TI surface states, and may be useful in the design of topological insulator-based electronic devices such as collimating electron beam.
Directory of Open Access Journals (Sweden)
Danielle S Bassett
2010-04-01
Full Text Available Nervous systems are information processing networks that evolved by natural selection, whereas very large scale integrated (VLSI computer circuits have evolved by commercially driven technology development. Here we follow historic intuition that all physical information processing systems will share key organizational properties, such as modularity, that generally confer adaptivity of function. It has long been observed that modular VLSI circuits demonstrate an isometric scaling relationship between the number of processing elements and the number of connections, known as Rent's rule, which is related to the dimensionality of the circuit's interconnect topology and its logical capacity. We show that human brain structural networks, and the nervous system of the nematode C. elegans, also obey Rent's rule, and exhibit some degree of hierarchical modularity. We further show that the estimated Rent exponent of human brain networks, derived from MRI data, can explain the allometric scaling relations between gray and white matter volumes across a wide range of mammalian species, again suggesting that these principles of nervous system design are highly conserved. For each of these fractal modular networks, the dimensionality of the interconnect topology was greater than the 2 or 3 Euclidean dimensions of the space in which it was embedded. This relatively high complexity entailed extra cost in physical wiring: although all networks were economically or cost-efficiently wired they did not strictly minimize wiring costs. Artificial and biological information processing systems both may evolve to optimize a trade-off between physical cost and topological complexity, resulting in the emergence of homologous principles of economical, fractal and modular design across many different kinds of nervous and computational networks.
Directory of Open Access Journals (Sweden)
Jiu-Jiu Chen
2017-11-01
Full Text Available The study for exotic topological effects of sound has attracted uprising interests in fundamental physics and practical applications. Based on the concept of valley pseudospin, we demonstrate the topological valley transport of plate-mode waves in a homogenous thin plate with periodic stubbed surface, where a deterministic two-fold Dirac degeneracy is form by two plate modes. We show that the topological property can be controlled by the height of stubs deposited on the plate. By adjusting the relative heights of adjacent stubs, the valley vortex chirality and band inversion are induced, giving rise to a phononic analog of valley Hall phase transition. We further numerically demonstrate the valley states of plate-mode waves with robust topological protection. Our results provide a new route to design unconventional elastic topological insulators and will significantly broaden its practical application in the engineering field.
Calculating degree-based topological indices of dominating David derived networks
Ahmad, Muhammad Saeed; Nazeer, Waqas; Kang, Shin Min; Imran, Muhammad; Gao, Wei
2017-12-01
An important area of applied mathematics is the Chemical reaction network theory. The behavior of real world problems can be modeled by using this theory. Due to applications in theoretical chemistry and biochemistry, it has attracted researchers since its foundation. It also attracts pure mathematicians because it involves interesting mathematical structures. In this report, we compute newly defined topological indices, namely, Arithmetic-Geometric index (AG1 index), SK index, SK1 index, and SK2 index of the dominating David derived networks [1, 2, 3, 4, 5].
The topology of a causal network for the Chinese financial system
Gao, Bo; Ren, Ruo-en
2013-07-01
The paper builds a causal network for the Chinese financial system based on the Granger causality of company risks, studies its different topologies in crisis and bull period, and applies the centrality to explain individual risk and prevent systemic risk. The results show that this causal network possesses both small-world phenomenon and scale-free property, and has a little different average distance, clustering coefficient, and degree distribution in different periods, and financial institutions with high centrality not only have large individual risk, but also are important for systemic risk immunization.
A note on the consensus finding problem in communication networks with switching topologies
Haskovec, Jan
2014-05-07
In this note, we discuss the problem of consensus finding in communication networks of agents with dynamically switching topologies. In particular, we consider the case of directed networks with unbalanced matrices of communication rates. We formulate sufficient conditions for consensus finding in terms of strong connectivity of the underlying directed graphs and prove that, given these conditions, consensus is found asymptotically. Moreover, we show that this consensus is an emergent property of the system, being encoded in its dynamics and not just an invariant of its initial configuration. © 2014 © 2014 Taylor & Francis.
Oil Transport Networks in Europe
Directory of Open Access Journals (Sweden)
Igbal Guliyev
2014-01-01
Full Text Available The author examines the problems and prospects of crude oil and petroleum products transportation market on the European continent. Particular attention is paid to the possibilities of the planned pipeline routes and new supplies of oil and petroleum products. European Union countries have large reserves of hydrocarbons, but it is not enough to fully satisfy domestic consumption. Improved pipeline infrastructure both within the EU and oil pipelines from other countries is an important economic and social factor. Recent developments of this year especially emphasize the importance of strengthening the energy security in the foreign policy of the state. For transporting fuel energy in Europe used the following types of transport: marine (sea and river, truck, railway, and pipeline. It seems necessary to mention the fact that the role of pipeline transport is particularly high in the oil and gas industry. Pipeline transport has an important impact on the formation and developmen t of the fuel and energy complex of the state, as well as regions, as its integral part. An effective system of crude oil and petroleum products pipelines is an important tool for the implementation of public policies, policies at the EU level, allowing the country to regulate the supply of crude oil and petroleum products to the overseas and domestic markets.
Directory of Open Access Journals (Sweden)
Xiaogang Qi
2015-01-01
Full Text Available Wireless sensor network (WSN is a classical self-organizing communication network, and its topology evolution currently becomes one of the attractive issues in this research field. Accordingly, the problem is divided into two subproblems: one is to design a new preferential attachment method and the other is to analyze the dynamics of the network topology evolution. To solve the first subproblem, a revised PageRank algorithm, called Con-rank, is proposed to evaluate the node importance upon the existing node contraction, and then a novel preferential attachment is designed based on the node importance calculated by the proposed Con-rank algorithm. To solve the second one, we firstly analyze the network topology evolution dynamics in a theoretical way and then simulate the evolution process. Theoretical analysis proves that the network topology evolution of our model agrees with power-law distribution, and simulation results are well consistent with our conclusions obtained from the theoretical analysis and simultaneously show that our topology evolution model is superior to the classic BA model in the average path length and the clustering coefficient, and the network topology is more robust and can tolerate the random attacks.
Energy Technology Data Exchange (ETDEWEB)
Park, Ji Eun; Kim, Ho Sung; Kim, Sang Joon; Shim, Woo Hyun [University of Ulsan College of Medicine, Department of Radiology and Research Institute of Radiology, Asan Medical Center, Songpa-Gu, Seoul (Korea, Republic of); Kim, Jeong Hoon [University of Ulsan College of Medicine, Department of Neurosurgery, Asan Medical Center, Seoul (Korea, Republic of)
2016-03-15
The need for information regarding functional alterations in patients with brain gliomas is increasing, but little is known about the functional consequences of focal brain tumors throughout the entire brain. Using resting-state functional MR imaging (rs-fMRI), this study assessed functional connectivity in patients with supratentorial brain gliomas with possible alterations in long-distance connectivity and network topology. Data from 36 patients with supratentorial brain gliomas and 12 healthy subjects were acquired using rs-fMRI. The functional connectivity matrix (FCM) was created using 32 pairs of cortical seeds on Talairach coordinates in each individual subject. Local and distant connectivity were calculated using z-scores in the individual patient's FCM, and the averaged FCM of patients was compared with that of healthy subjects. Weighted network analysis was performed by calculating local efficiency, global efficiency, clustering coefficient, and small-world topology, and compared between patients and healthy controls. When comparing the averaged FCM of patients with that of healthy controls, the patients showed decreased long-distance, inter-hemispheric connectivity (0.32 ± 0.16 in patients vs. 0. 42 ± 0.15 in healthy controls, p = 0.04). In network analysis, patients showed increased local efficiency (p < 0.05), but global efficiency, clustering coefficient, and small-world topology were relatively preserved compared to healthy subjects. Patients with supratentorial brain gliomas showed decreased long-distance connectivity while increased local efficiency and preserved small-world topology. The results of this small case series may provide a better understanding of the alterations of functional connectivity in patients with brain gliomas across the whole brain scale. (orig.)
Exploitation of complex network topology for link prediction in biological interactomes
Alanis Lobato, Gregorio
2014-06-01
The network representation of the interactions between proteins and genes allows for a holistic perspective of the complex machinery underlying the living cell. However, the large number of interacting entities within the cell makes network construction a daunting and arduous task, prone to errors and missing information. Fortunately, the structure of biological networks is not different from that of other complex systems, such as social networks, the world-wide web or power grids, for which growth models have been proposed to better understand their structure and function. This means that we can design tools based on these models in order to exploit the topology of biological interactomes with the aim to construct more complete and reliable maps of the cell. In this work, we propose three novel and powerful approaches for the prediction of interactions in biological networks and conclude that it is possible to mine the topology of these complex system representations and produce reliable and biologically meaningful information that enriches the datasets to which we have access today.
Guo, Hao; Cao, Xiaohua; Liu, Zhifen; Li, Haifang; Chen, Junjie; Zhang, Kerang
2012-12-05
Resting state functional brain networks have been widely studied in brain disease research. However, it is currently unclear whether abnormal resting state functional brain network metrics can be used with machine learning for the classification of brain diseases. Resting state functional brain networks were constructed for 28 healthy controls and 38 major depressive disorder patients by thresholding partial correlation matrices of 90 regions. Three nodal metrics were calculated using graph theory-based approaches. Nonparametric permutation tests were then used for group comparisons of topological metrics, which were used as classified features in six different algorithms. We used statistical significance as the threshold for selecting features and measured the accuracies of six classifiers with different number of features. A sensitivity analysis method was used to evaluate the importance of different features. The result indicated that some of the regions exhibited significantly abnormal nodal centralities, including the limbic system, basal ganglia, medial temporal, and prefrontal regions. Support vector machine with radial basis kernel function algorithm and neural network algorithm exhibited the highest average accuracy (79.27 and 78.22%, respectively) with 28 features (Pdisorder is associated with abnormal functional brain network topological metrics and statistically significant nodal metrics can be successfully used for feature selection in classification algorithms.
European intermodal freight transport network
Saeedi, Hamid; Wiegmans, Bart; Behdani, Behzad; Zuidwijk, Rob
2017-01-01
The analysis of market structure and concentration measures for the Intermodal Freight Transport (IFT) market is important to avoid market failure and to find the areas for policy making to promote IFT market share. This analysis can be performed for separate segments, for example, the market for
Aberrant topological patterns of brain structural network in temporal lobe epilepsy.
Yasuda, Clarissa Lin; Chen, Zhang; Beltramini, Guilherme Coco; Coan, Ana Carolina; Morita, Marcia Elisabete; Kubota, Bruno; Bergo, Felipe; Beaulieu, Christian; Cendes, Fernando; Gross, Donald William
2015-12-01
Although altered large-scale brain network organization in patients with temporal lobe epilepsy (TLE) has been shown using morphologic measurements such as cortical thickness, these studies, have not included critical subcortical structures (such as hippocampus and amygdala) and have had relatively small sample sizes. Here, we investigated differences in topological organization of the brain volumetric networks between patients with right TLE (RTLE) and left TLE (LTLE) with unilateral hippocampal atrophy. We performed a cross-sectional analysis of 86 LTLE patients, 70 RTLE patients, and 116 controls. RTLE and LTLE groups were balanced for gender (p = 0.64), seizure frequency (Mann-Whitney U test, p = 0.94), age (p = 0.39), age of seizure onset (p = 0.21), and duration of disease (p = 0.69). Brain networks were constructed by thresholding correlation matrices of volumes from 80 cortical/subcortical regions (parcellated with Freesurfer v5.3 https://surfer.nmr.mgh.harvard.edu/) that were then analyzed using graph theoretical approaches. We identified reduced cortical/subcortical connectivity including bilateral hippocampus in both TLE groups, with the most significant interregional correlation increases occurring within the limbic system in LTLE and contralateral hemisphere in RTLE. Both TLE groups demonstrated less optimal topological organization, with decreased global efficiency and increased local efficiency and clustering coefficient. LTLE also displayed a more pronounced network disruption. Contrary to controls, hub nodes in both TLE groups were not distributed across whole brain, but rather found primarily in the paralimbic/limbic and temporal association cortices. Regions with increased centrality were concentrated in occipital lobes for LTLE and contralateral limbic/temporal areas for RTLE. These findings provide first evidence of altered topological organization of the whole brain volumetric network in TLE, with disruption of the coordinated patterns of
Global Optimization for Transport Network Expansion and Signal Setting
Liu, Haoxiang; Wang, David Z. W.; Yue, Hao
2015-01-01
This paper proposes a model to address an urban transport planning problem involving combined network design and signal setting in a saturated network. Conventional transport planning models usually deal with the network design problem and signal setting problem separately. However, the fact that network capacity design and capacity allocation determined by network signal setting combine to govern the transport network performance requires the optimal transport planning to consider the two pr...
Topology control algorithm for wireless sensor networks based on Link forwarding
Pucuo, Cairen; Qi, Ai-qin
2018-03-01
The research of topology control could effectively save energy and increase the service life of network based on wireless sensor. In this paper, a arithmetic called LTHC (link transmit hybrid clustering) based on link transmit is proposed. It decreases expenditure of energy by changing the way of cluster-node’s communication. The idea is to establish a link between cluster and SINK node when the cluster is formed, and link-node must be non-cluster. Through the link, cluster sends information to SINK nodes. For the sake of achieving the uniform distribution of energy on the network, prolongate the network survival time, and improve the purpose of communication, the communication will cut down much more expenditure of energy for cluster which away from SINK node. In the two aspects of improving the traffic and network survival time, we find that the LTCH is far superior to the traditional LEACH by experiments.
Directory of Open Access Journals (Sweden)
B. Basterra-Beroiz
2018-08-01
Full Text Available For the first time since its formulation in 1986, the theoretical approach proposed by Helmis, Heinrich and Straube (HHS model, which considers the contribution of topological restrictions from entanglements to the swelling of polymer networks, is applied to experimental data. The main aspects and key equations are reviewed and their application is illustrated for unfilled rubber compounds. The HHS model is based on real networks and gives new perspectives to the interpretation of experimental swelling data for which the entanglement contributions are usually neglected by considering phantom network models. This investigation applies a reliable constrained-chain approach through a deformation-dependent tube model for defining the elastic contribution of swollen networks, which is one of the main limitations on the applicability of classical (affine Flory-Rehner and (non-affine phantom models. This short communication intends to provide a baseline for the application and validation of this modern approach for a broader class of rubber materials.
Motif formation and industry specific topologies in the Japanese business firm network
Maluck, Julian; Donner, Reik V.; Takayasu, Hideki; Takayasu, Misako
2017-05-01
Motifs and roles are basic quantities for the characterization of interactions among 3-node subsets in complex networks. In this work, we investigate how the distribution of 3-node motifs can be influenced by modifying the rules of an evolving network model while keeping the statistics of simpler network characteristics, such as the link density and the degree distribution, invariant. We exemplify this problem for the special case of the Japanese Business Firm Network, where a well-studied and relatively simple yet realistic evolving network model is available, and compare the resulting motif distribution in the real-world and simulated networks. To better approximate the motif distribution of the real-world network in the model, we introduce both subgraph dependent and global additional rules. We find that a specific rule that allows only for the merging process between nodes with similar link directionality patterns reduces the observed excess of densely connected motifs with bidirectional links. Our study improves the mechanistic understanding of motif formation in evolving network models to better describe the characteristic features of real-world networks with a scale-free topology.
Social networks, big data and transport planning
Energy Technology Data Exchange (ETDEWEB)
Ruiz Sanchez, T.; Lidon Mars Aicart, M. del; Arroyo Lopez, M.R.; Serna Nocedal, A.
2016-07-01
The characteristics of people who are related or tied to each individual affects her activitytravel behavior. That influence is especially associated to social and recreational activities, which are increasingly important. Collecting high quality data from those social networks is very difficult, because respondents are asked about their general social life, which is most demanding to remember that specific facts. On the other hand, currently there are different potential sources of transport data, which is characterized by the huge amount of information available, the velocity with it is obtained and the variety of format in which is presented. This sort of information is commonly known as Big Data. In this paper we identify potential sources of social network related big data that can be used in Transport Planning. Then, a review of current applications in Transport Planning is presented. Finally, some future prospects of using social network related big data are highlighted. (Author)
Designing Structure-Dependent MPC-Based AGC Schemes Considering Network Topology
Directory of Open Access Journals (Sweden)
Young-Sik Jang
2015-04-01
Full Text Available This paper presents the important features of structure-dependent model predictive control (MPC-based approaches for automatic generation control (AGC considering network topology. Since power systems have various generators under different topologies, it is necessary to reflect the characteristics of generators in power networks and the control system structures in order to improve the dynamic performance of AGC. Specifically, considering control system structures is very important because not only can the topological problems be reduced, but also a computing system for AGC in a bulk-power system can be realized. Based on these considerations, we propose new schemes in the proposed controller for minimizing inadvertent line flows and computational burden, which strengthen the advantages of MPC-based approach for AGC. Analysis and simulation results in the IEEE 39-bus model system show different dynamic behaviors among structure-dependent control schemes and possible improvements in computational burden via the proposed control scheme while system operators in each balancing area consider physical load reference ramp constraints among generators.
Systematic study of transport via surface and bulk states in Bi2Te3 topological insulator
de Castro, S.; Peres, M. L.; Chitta, V. A.; Gratens, X.; Soares, D. A. W.; Fornari, C. I.; Rappl, P. H. O.; Abramof, E.; Oliveira, N. F., Jr.
2016-07-01
We performed magnetoresistance measurements on Bi2Te3 thin film in the temperature range of T = 1.2-4.0 K and for magnetic fields up to 2 T. The curves exhibited anomalous behavior for temperatures below 4.0 K. Different temperature intervals revealed electrical transport through different conductive channels with clear signatures of weak antilocalization. The magnetoresistance curves were explained using the Hikami-Larkin-Nagaoka model and the 2D Dirac modified model. The comparison between the parameters obtained from the two models revealed the transport via topological surface states and bulk states. In addition, a superconductive like transition is observed for the lowest temperatures and we suggest that this effect can be originated from the misfit dislocations caused by strain, giving rise to a superconductive channel between the interface of the film and the substrate.
Towards 100 gigabit carrier ethernet transport networks
DEFF Research Database (Denmark)
Rasmussen, Anders; Zhang, Jiang; Yu, Hao
2010-01-01
technology, making the use of Ethernet as a convergence layer for Next Generation Networks a distinct possibility. Triple Play services, in particular IPTV, are expected to be a main drivers for carrier Ethernet, however, a number of challenges must be addressed including QoS enabled control plane, enhanced......Ethernet as a transport technology has, up to now, lacked the features such as network layer architecture, customer separation and manageability that carriers require for wide-scale deployment. However, with the advent of PBB-TE and TMPLS, it is now possible to use Ethernet as a transport...
Transport of Dirac fermions on the surface of strong topological insulator and graphene
Energy Technology Data Exchange (ETDEWEB)
Kundu, Arijit
2012-06-14
In this dissertation I study electronic transport through Dirac Fermions on the surface of strong topological insulator and graphene. I start by reviewing the physics of topological insulator and graphene and the low energy effective theory for the electronic states of the surface of a 3D strong topological insulator and graphene. Using this theory the electronic structure of the surface states of strong topological insulators of geometries with large surface to bulk ratio like nanowire and thin film are obtained. Then the energy spectrum and the spin-parity structure of the eigenstates for a finite size topological insulator quantum dot of the shape of a nanotube are considered. Numerical calculations show that even at the lowest energy scales, the ''spin-surface locking'' is broken, that is, the spin direction in a topologically protected surface mode is not locked to the surface. The calculations also show the existence of ''zero-momentum'' modes, and sub-gap states localized near the ''caps'' of the dot. Both the energy spectrum and the spin texture of the eigenstates are basically reproduced from an analytical surface Dirac fermion description. The results are compared to microscopic calculations using a tight-binding model for a strong topological insulator in a finite-length nanowire geometry, which shows qualitative similarity. Then, a theoretical study of electron-phonon scattering effects in thin films made of a strong topological insulator is presented. Phonons are modeled by isotropic elastic continuum theory with stress-free boundary conditions, and the interaction with the helical surface Dirac fermions is mediated by the deformation potential. The temperature-dependent electrical resistivity ρ(T) and the quasi-particle decay rate Γ(T) observable in photo-emission are computed numerically. The low and high-temperature power laws for both quantities are obtained analytically. Detailed
Testing statistical self-similarity in the topology of river networks
Troutman, Brent M.; Mantilla, Ricardo; Gupta, Vijay K.
2010-01-01
Recent work has demonstrated that the topological properties of real river networks deviate significantly from predictions of Shreve's random model. At the same time the property of mean self-similarity postulated by Tokunaga's model is well supported by data. Recently, a new class of network model called random self-similar networks (RSN) that combines self-similarity and randomness has been introduced to replicate important topological features observed in real river networks. We investigate if the hypothesis of statistical self-similarity in the RSN model is supported by data on a set of 30 basins located across the continental United States that encompass a wide range of hydroclimatic variability. We demonstrate that the generators of the RSN model obey a geometric distribution, and self-similarity holds in a statistical sense in 26 of these 30 basins. The parameters describing the distribution of interior and exterior generators are tested to be statistically different and the difference is shown to produce the well-known Hack's law. The inter-basin variability of RSN parameters is found to be statistically significant. We also test generator dependence on two climatic indices, mean annual precipitation and radiative index of dryness. Some indication of climatic influence on the generators is detected, but this influence is not statistically significant with the sample size available. Finally, two key applications of the RSN model to hydrology and geomorphology are briefly discussed.
Feedback topology and XOR-dynamics in Boolean networks with varying input structure
Ciandrini, L.; Maffi, C.; Motta, A.; Bassetti, B.; Cosentino Lagomarsino, M.
2009-08-01
We analyze a model of fixed in-degree random Boolean networks in which the fraction of input-receiving nodes is controlled by the parameter γ . We investigate analytically and numerically the dynamics of graphs under a parallel XOR updating scheme. This scheme is interesting because it is accessible analytically and its phenomenology is at the same time under control and as rich as the one of general Boolean networks. We give analytical formulas for the dynamics on general graphs, showing that with a XOR-type evolution rule, dynamic features are direct consequences of the topological feedback structure, in analogy with the role of relevant components in Kauffman networks. Considering graphs with fixed in-degree, we characterize analytically and numerically the feedback regions using graph decimation algorithms (Leaf Removal). With varying γ , this graph ensemble shows a phase transition that separates a treelike graph region from one in which feedback components emerge. Networks near the transition point have feedback components made of disjoint loops, in which each node has exactly one incoming and one outgoing link. Using this fact, we provide analytical estimates of the maximum period starting from topological considerations.
A Cluster-Based Dual-Adaptive Topology Control Approach in Wireless Sensor Networks
Gui, Jinsong; Zhou, Kai; Xiong, Naixue
2016-01-01
Multi-Input Multi-Output (MIMO) can improve wireless network performance. Sensors are usually single-antenna devices due to the high hardware complexity and cost, so several sensors are used to form virtual MIMO array, which is a desirable approach to efficiently take advantage of MIMO gains. Also, in large Wireless Sensor Networks (WSNs), clustering can improve the network scalability, which is an effective topology control approach. The existing virtual MIMO-based clustering schemes do not either fully explore the benefits of MIMO or adaptively determine the clustering ranges. Also, clustering mechanism needs to be further improved to enhance the cluster structure life. In this paper, we propose an improved clustering scheme for virtual MIMO-based topology construction (ICV-MIMO), which can determine adaptively not only the inter-cluster transmission modes but also the clustering ranges. Through the rational division of cluster head function and the optimization of cluster head selection criteria and information exchange process, the ICV-MIMO scheme effectively reduces the network energy consumption and improves the lifetime of the cluster structure when compared with the existing typical virtual MIMO-based scheme. Moreover, the message overhead and time complexity are still in the same order of magnitude. PMID:27681731
A Cluster-Based Dual-Adaptive Topology Control Approach in Wireless Sensor Networks
Directory of Open Access Journals (Sweden)
Jinsong Gui
2016-09-01
Full Text Available Multi-Input Multi-Output (MIMO can improve wireless network performance. Sensors are usually single-antenna devices due to the high hardware complexity and cost, so several sensors are used to form virtual MIMO array, which is a desirable approach to efficiently take advantage of MIMO gains. Also, in large Wireless Sensor Networks (WSNs, clustering can improve the network scalability, which is an effective topology control approach. The existing virtual MIMO-based clustering schemes do not either fully explore the benefits of MIMO or adaptively determine the clustering ranges. Also, clustering mechanism needs to be further improved to enhance the cluster structure life. In this paper, we propose an improved clustering scheme for virtual MIMO-based topology construction (ICV-MIMO, which can determine adaptively not only the inter-cluster transmission modes but also the clustering ranges. Through the rational division of cluster head function and the optimization of cluster head selection criteria and information exchange process, the ICV-MIMO scheme effectively reduces the network energy consumption and improves the lifetime of the cluster structure when compared with the existing typical virtual MIMO-based scheme. Moreover, the message overhead and time complexity are still in the same order of magnitude.
A Cluster-Based Dual-Adaptive Topology Control Approach in Wireless Sensor Networks.
Gui, Jinsong; Zhou, Kai; Xiong, Naixue
2016-09-25
Multi-Input Multi-Output (MIMO) can improve wireless network performance. Sensors are usually single-antenna devices due to the high hardware complexity and cost, so several sensors are used to form virtual MIMO array, which is a desirable approach to efficiently take advantage of MIMO gains. Also, in large Wireless Sensor Networks (WSNs), clustering can improve the network scalability, which is an effective topology control approach. The existing virtual MIMO-based clustering schemes do not either fully explore the benefits of MIMO or adaptively determine the clustering ranges. Also, clustering mechanism needs to be further improved to enhance the cluster structure life. In this paper, we propose an improved clustering scheme for virtual MIMO-based topology construction (ICV-MIMO), which can determine adaptively not only the inter-cluster transmission modes but also the clustering ranges. Through the rational division of cluster head function and the optimization of cluster head selection criteria and information exchange process, the ICV-MIMO scheme effectively reduces the network energy consumption and improves the lifetime of the cluster structure when compared with the existing typical virtual MIMO-based scheme. Moreover, the message overhead and time complexity are still in the same order of magnitude.
Feedback topology and XOR-dynamics in Boolean networks with varying input structure.
Ciandrini, L; Maffi, C; Motta, A; Bassetti, B; Cosentino Lagomarsino, M
2009-08-01
We analyze a model of fixed in-degree random Boolean networks in which the fraction of input-receiving nodes is controlled by the parameter gamma. We investigate analytically and numerically the dynamics of graphs under a parallel XOR updating scheme. This scheme is interesting because it is accessible analytically and its phenomenology is at the same time under control and as rich as the one of general Boolean networks. We give analytical formulas for the dynamics on general graphs, showing that with a XOR-type evolution rule, dynamic features are direct consequences of the topological feedback structure, in analogy with the role of relevant components in Kauffman networks. Considering graphs with fixed in-degree, we characterize analytically and numerically the feedback regions using graph decimation algorithms (Leaf Removal). With varying gamma , this graph ensemble shows a phase transition that separates a treelike graph region from one in which feedback components emerge. Networks near the transition point have feedback components made of disjoint loops, in which each node has exactly one incoming and one outgoing link. Using this fact, we provide analytical estimates of the maximum period starting from topological considerations.
Masó, Joan; Serral, Ivette; McCallum, Ian; Blonda, Palma; Plag, Hans-Peter
2016-04-01
ConnectinGEO (Coordinating an Observation Network of Networks EnCompassing saTellite and IN-situ to fill the Gaps in European Observations" is an H2020 Coordination and Support Action with the primary goal of linking existing Earth Observation networks with science and technology (S&T) communities, the industry sector, the Group on Earth Observations (GEO), and Copernicus. The project will end in February 2017. ConnectinGEO will initiate a European Network of Earth Observation Networks (ENEON) that will encompass space-based, airborne and in-situ observations networks. ENEON will be composed of project partners representing thematic observation networks along with the GEOSS Science and Technology Stakeholder Network, GEO Communities of Practices, Copernicus services, Sentinel missions and in-situ support data representatives, representatives of the European space-based, airborne and in-situ observations networks. This communication presents the complex panorama of Earth Observations Networks in Europe. The list of networks is classified by discipline, variables, geospatial scope, etc. We also capture the membership and relations with other networks and umbrella organizations like GEO. The result is a complex interrelation between networks that can not be clearly expressed in a flat list. Technically the networks can be represented as nodes with relations between them as lines connecting the nodes in a graph. We have chosen RDF as a language and an AllegroGraph 3.3 triple store that is visualized in several ways using for example Gruff 5.7. Our final aim is to identify gaps in the EO Networks and justify the need for a more structured coordination between them.
Secure Adaptive Topology Control for Wireless Ad-Hoc Sensor Networks
Directory of Open Access Journals (Sweden)
Yen-Chieh Ouyang
2010-02-01
Full Text Available This paper presents a secure decentralized clustering algorithm for wireless ad-hoc sensor networks. The algorithm operates without a centralized controller, operates asynchronously, and does not require that the location of the sensors be known a priori. Based on the cluster-based topology, secure hierarchical communication protocols and dynamic quarantine strategies are introduced to defend against spam attacks, since this type of attacks can exhaust the energy of sensor nodes and will shorten the lifetime of a sensor network drastically. By adjusting the threshold of infected percentage of the cluster coverage, our scheme can dynamically coordinate the proportion of the quarantine region and adaptively achieve the cluster control and the neighborhood control of attacks. Simulation results show that the proposed approach is feasible and cost effective for wireless sensor networks.
Wu, Kai; Taki, Yasuyuki; Sato, Kazunori; Hashizume, Hiroshi; Sassa, Yuko; Takeuchi, Hikaru; Thyreau, Benjamin; He, Yong; Evans, Alan C.; Li, Xiaobo; Kawashima, Ryuta; Fukuda, Hiroshi
2013-01-01
Recent studies have demonstrated developmental changes of functional brain networks derived from functional connectivity using graph theoretical analysis, which has been rapidly translated to studies of brain network organization. However, little is known about sex- and IQ-related differences in the topological organization of functional brain networks during development. In this study, resting-state fMRI (rs-fMRI) was used to map the functional brain networks in 51 healthy children. We then ...
Hub location problems in transportation networks
DEFF Research Database (Denmark)
Gelareh, Shahin; Nickel, Stefan
2011-01-01
In this paper we propose a 4-index formulation for the uncapacitated multiple allocation hub location problem tailored for urban transport and liner shipping network design. This formulation is very tight and most of the tractable instances for MIP solvers are optimally solvable at the root node....... also introduce fixed cost values for Australian Post (AP) dataset....
Transport Network Technologies – Study and Testing
DEFF Research Database (Denmark)
Bozorgebrahimi, K.; Channegowda, M.; Colmenero, A.
Following on from the theoretical research into Carrier Class Transport Network Technologies (CCTNTs) documented in DJ1.1.1, this report describes the extensive testing performed by JRA1 Task 1. The tests covered EoMPLS, Ethernet OAM, Synchronous Ethernet, PBB-TE, MPLS-TP, OTN and GMPLS...
Effects of threshold on the topology of gene co-expression networks.
Couto, Cynthia Martins Villar; Comin, César Henrique; Costa, Luciano da Fontoura
2017-09-26
Several developments regarding the analysis of gene co-expression profiles using complex network theory have been reported recently. Such approaches usually start with the construction of an unweighted gene co-expression network, therefore requiring the selection of a suitable threshold defining which pairs of vertices will be connected. We aimed at addressing such an important problem by suggesting and comparing five different approaches for threshold selection. Each of the methods considers a respective biologically-motivated criterion for electing a potentially suitable threshold. A set of 21 microarray experiments from different biological groups was used to investigate the effect of applying the five proposed criteria to several biological situations. For each experiment, we used the Pearson correlation coefficient to measure the relationship between each gene pair, and the resulting weight matrices were thresholded considering several values, generating respective adjacency matrices (co-expression networks). Each of the five proposed criteria was then applied in order to select the respective threshold value. The effects of these thresholding approaches on the topology of the resulting networks were compared by using several measurements, and we verified that, depending on the database, the impact on the topological properties can be large. However, a group of databases was verified to be similarly affected by most of the considered criteria. Based on such results, it can be suggested that when the generated networks present similar measurements, the thresholding method can be chosen with greater freedom. If the generated networks are markedly different, the thresholding method that better suits the interests of each specific research study represents a reasonable choice.
The entire network topology display system of terminal communication access network
An Yi
2016-01-01
Now order terminal communication access network is network technology in Shanxi Province is diversiform, device type complex, lack of unified technical standard, the terminal communication access network management system of construction constitutes a great obstacle. Need to build a “unified communication interface and communication standard, unified communications network management” of the terminal communication access network cut in the integrated network management system, for the termina...
Effects of behavioral patterns and network topology structures on Parrondo’s paradox
Ye, Ye; Cheong, Kang Hao; Cen, Yu-Wan; Xie, Neng-Gang
2016-11-01
A multi-agent Parrondo’s model based on complex networks is used in the current study. For Parrondo’s game A, the individual interaction can be categorized into five types of behavioral patterns: the Matthew effect, harmony, cooperation, poor-competition-rich-cooperation and a random mode. The parameter space of Parrondo’s paradox pertaining to each behavioral pattern, and the gradual change of the parameter space from a two-dimensional lattice to a random network and from a random network to a scale-free network was analyzed. The simulation results suggest that the size of the region of the parameter space that elicits Parrondo’s paradox is positively correlated with the heterogeneity of the degree distribution of the network. For two distinct sets of probability parameters, the microcosmic reasons underlying the occurrence of the paradox under the scale-free network are elaborated. Common interaction mechanisms of the asymmetric structure of game B, behavioral patterns and network topology are also revealed.
Hébert-Dufresne, Laurent; Grochow, Joshua A; Allard, Antoine
2016-08-18
We introduce a network statistic that measures structural properties at the micro-, meso-, and macroscopic scales, while still being easy to compute and interpretable at a glance. Our statistic, the onion spectrum, is based on the onion decomposition, which refines the k-core decomposition, a standard network fingerprinting method. The onion spectrum is exactly as easy to compute as the k-cores: It is based on the stages at which each vertex gets removed from a graph in the standard algorithm for computing the k-cores. Yet, the onion spectrum reveals much more information about a network, and at multiple scales; for example, it can be used to quantify node heterogeneity, degree correlations, centrality, and tree- or lattice-likeness. Furthermore, unlike the k-core decomposition, the combined degree-onion spectrum immediately gives a clear local picture of the network around each node which allows the detection of interesting subgraphs whose topological structure differs from the global network organization. This local description can also be leveraged to easily generate samples from the ensemble of networks with a given joint degree-onion distribution. We demonstrate the utility of the onion spectrum for understanding both static and dynamic properties on several standard graph models and on many real-world networks.
Noh, Hyun Ji; Ponting, Chris P; Boulding, Hannah C; Meader, Stephen; Betancur, Catalina; Buxbaum, Joseph D; Pinto, Dalila; Marshall, Christian R; Lionel, Anath C; Scherer, Stephen W; Webber, Caleb
2013-06-01
Autism Spectrum Disorders (ASD) are highly heritable and characterised by impairments in social interaction and communication, and restricted and repetitive behaviours. Considering four sets of de novo copy number variants (CNVs) identified in 181 individuals with autism and exploiting mouse functional genomics and known protein-protein interactions, we identified a large and significantly interconnected interaction network. This network contains 187 genes affected by CNVs drawn from 45% of the patients we considered and 22 genes previously implicated in ASD, of which 192 form a single interconnected cluster. On average, those patients with copy number changed genes from this network possess changes in 3 network genes, suggesting that epistasis mediated through the network is extensive. Correspondingly, genes that are highly connected within the network, and thus whose copy number change is predicted by the network to be more phenotypically consequential, are significantly enriched among patients that possess only a single ASD-associated network copy number changed gene (p = 0.002). Strikingly, deleted or disrupted genes from the network are significantly enriched in GO-annotated positive regulators (2.3-fold enrichment, corrected p = 2×10(-5)), whereas duplicated genes are significantly enriched in GO-annotated negative regulators (2.2-fold enrichment, corrected p = 0.005). The direction of copy change is highly informative in the context of the network, providing the means through which perturbations arising from distinct deletions or duplications can yield a common outcome. These findings reveal an extensive ASD-associated molecular network, whose topology indicates ASD-relevant mutational deleteriousness and that mechanistically details how convergent aetiologies can result extensively from CNVs affecting pathways causally implicated in ASD.
GH32 family activity: a topological approach through protein contact networks.
Cimini, Sara; Di Paola, Luisa; Giuliani, Alessandro; Ridolfi, Alessandra; De Gara, Laura
2016-11-01
The application of Protein Contact Networks methodology allowed to highlight a novel response of border region between the two domains to substrate binding. Glycoside hydrolases (GH) are enzymes that mainly hydrolyze the glycosidic bond between two carbohydrates or a carbohydrate and a non-carbohydrate moiety. These enzymes are involved in many fundamental and diverse biological processes in plants. We have focused on the GH32 family, including enzymes very similar in both sequence and structure, each having however clear specificities of substrate preferences and kinetic properties. Structural and topological differences among proteins of the GH32 family have been here identified by means of an emerging approach (Protein Contact network, PCN) based on the formalization of 3D structures as contact networks among amino-acid residues. The PCN approach proved successful in both reconstructing the already known functional domains and in identifying the structural counterpart of the properties of GH32 enzymes, which remain uncertain, like their allosteric character. The main outcome of the study was the discovery of the activation upon binding of the border (cleft) region between the two domains. This reveals the allosteric nature of the enzymatic activity for all the analyzed forms in the GH32 family, a character yet to be highlighted in biochemical studies. Furthermore, we have been able to recognize a topological signature (graph energy) of the different affinity of the enzymes towards small and large substrates.
A Novel Topology Control Approach to Maintain the Node Degree in Dynamic Wireless Sensor Networks
Directory of Open Access Journals (Sweden)
Yuanjiang Huang
2014-03-01
Full Text Available Topology control is an important technique to improve the connectivity and the reliability of Wireless Sensor Networks (WSNs by means of adjusting the communication range of wireless sensor nodes. In this paper, a novel Fuzzy-logic Topology Control (FTC is proposed to achieve any desired average node degree by adaptively changing communication range, thus improving the network connectivity, which is the main target of FTC. FTC is a fully localized control algorithm, and does not rely on location information of neighbors. Instead of designing membership functions and if-then rules for fuzzy-logic controller, FTC is constructed from the training data set to facilitate the design process. FTC is proved to be accurate, stable and has short settling time. In order to compare it with other representative localized algorithms (NONE, FLSS, k-Neighbor and LTRT, FTC is evaluated through extensive simulations. The simulation results show that: firstly, similar to k-Neighbor algorithm, FTC is the best to achieve the desired average node degree as node density varies; secondly, FTC is comparable to FLSS and k-Neighbor in terms of energy-efficiency, but is better than LTRT and NONE; thirdly, FTC has the lowest average maximum communication range than other algorithms, which indicates that the most energy-consuming node in the network consumes the lowest power.
A novel topology control approach to maintain the node degree in dynamic wireless sensor networks.
Huang, Yuanjiang; Martínez, José-Fernán; Díaz, Vicente Hernández; Sendra, Juana
2014-03-07
Topology control is an important technique to improve the connectivity and the reliability of Wireless Sensor Networks (WSNs) by means of adjusting the communication range of wireless sensor nodes. In this paper, a novel Fuzzy-logic Topology Control (FTC) is proposed to achieve any desired average node degree by adaptively changing communication range, thus improving the network connectivity, which is the main target of FTC. FTC is a fully localized control algorithm, and does not rely on location information of neighbors. Instead of designing membership functions and if-then rules for fuzzy-logic controller, FTC is constructed from the training data set to facilitate the design process. FTC is proved to be accurate, stable and has short settling time. In order to compare it with other representative localized algorithms (NONE, FLSS, k-Neighbor and LTRT), FTC is evaluated through extensive simulations. The simulation results show that: firstly, similar to k-Neighbor algorithm, FTC is the best to achieve the desired average node degree as node density varies; secondly, FTC is comparable to FLSS and k-Neighbor in terms of energy-efficiency, but is better than LTRT and NONE; thirdly, FTC has the lowest average maximum communication range than other algorithms, which indicates that the most energy-consuming node in the network consumes the lowest power.
Networks of neuroblastoma cells on porous silicon substrates reveal a small world topology
Marinaro, Giovanni; La Rocca, Rosanna; Toma, Andrea; Barberio, Marianna; Cancedda, Laura; Di Fabrizio, Enzo M.; Decuzzi, Paolo C W; Gentile, Francesco T.
2015-01-01
The human brain is a tightly interweaving network of neural cells where the complexity of the network is given by the large number of its constituents and its architecture. The topological structure of neurons in the brain translates into its increased computational capabilities, low energy consumption, and nondeterministic functions, which differentiate human behavior from artificial computational schemes. In this manuscript, we fabricated porous silicon chips with a small pore size ranging from 8 to 75 nm and large fractal dimensions up to Df ∼ 2.8. In culturing neuroblastoma N2A cells on the described substrates, we found that those cells adhere more firmly to and proliferate on the porous surfaces compared to the conventional nominally flat silicon substrates, which were used as controls. More importantly, we observed that N2A cells on the porous substrates create highly clustered, small world topology patterns. We conjecture that neurons with a similar architecture may elaborate information more efficiently than in random or regular grids. Moreover, we hypothesize that systems of neurons on nano-scale geometry evolve in time to form networks in which the propagation of information is maximized. This journal is
Chen, Jianhuai; Chen, Yun; Gao, Qingqiang; Chen, Guotao; Dai, Yutian; Yao, Zhijian; Lu, Qing
2018-05-01
Despite increasing understanding of the cerebral functional changes and structural abnormalities in erectile dysfunction, alterations in the topological organization of brain networks underlying psychogenic erectile dysfunction remain unclear. Here, based on the diffusion tensor image data of 25 patients and 26 healthy controls, we investigated the topological organization of brain structural networks and its correlations with the clinical variables using the graph theoretical analysis. Patients displayed a preserved overall small-world organization and exhibited a less connectivity strength in the left inferior frontal gyrus, amygdale and the right inferior temporal gyrus. Moreover, an abnormal hub pattern was observed in patients, which might disturb the information interactions of the remaining brain network. Additionally, the clustering coefficient of the left hippocampus was positively correlated with the duration of patients and the normalized betweenness centrality of the right anterior cingulate gyrus and the left calcarine fissure were negatively correlated with the sum scores of the 17-item Hamilton Depression Rating Scale. These findings suggested that the damaged white matter and the abnormal hub distribution of the left prefrontal and limbic cortex might contribute to the pathogenesis of psychogenic erectile dysfunction and provided new insights into the understanding of the pathophysiological mechanisms of psychogenic erectile dysfunction.
Topology-selective jamming of fully-connected, code-division random-access networks
Polydoros, Andreas; Cheng, Unjeng
1990-01-01
The purpose is to introduce certain models of topology selective stochastic jamming and examine its impact on a class of fully-connected, spread-spectrum, slotted ALOHA-type random access networks. The theory covers dedicated as well as half-duplex units. The dominant role of the spatial duty factor is established, and connections with the dual concept of time selective jamming are discussed. The optimal choices of coding rate and link access parameters (from the users' side) and the jamming spatial fraction are numerically established for DS and FH spreading.
Topological patterns in street networks of self-organized urban settlements
Buhl, J.; Gautrais, J.; Reeves, N.; Solé, R. V.; Valverde, S.; Kuntz, P.; Theraulaz, G.
2006-02-01
Many urban settlements result from a spatially distributed, decentralized building process. Here we analyze the topological patterns of organization of a large collection of such settlements using the approach of complex networks. The global efficiency (based on the inverse of shortest-path lengths), robustness to disconnections and cost (in terms of length) of these graphs is studied and their possible origins analyzed. A wide range of patterns is found, from tree-like settlements (highly vulnerable to random failures) to meshed urban patterns. The latter are shown to be more robust and efficient.
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)
Maxwell rigidity and topological constraints in amorphous phase-change networks
International Nuclear Information System (INIS)
Micoulaut, M.; Otjacques, C.; Raty, J.-Y.; Bichara, C.
2011-01-01
By analyzing first-principles molecular-dynamics simulations of different telluride amorphous networks, we develop a method for the enumeration of radial and angular topological constraints, and show that the phase diagram of the most popular system Ge-Sb-Te can be split into two compositional elastic phases: a tellurium rich flexible phase and a stressed rigid phase that contains most of the materials used in phase-change applications. This sound atomic scale insight should open new avenues for the understanding of phase-change materials and other complex amorphous materials from the viewpoint of rigidity.
Neural-Network Quantum States, String-Bond States, and Chiral Topological States
Glasser, Ivan; Pancotti, Nicola; August, Moritz; Rodriguez, Ivan D.; Cirac, J. Ignacio
2018-01-01
Neural-network quantum states have recently been introduced as an Ansatz for describing the wave function of quantum many-body systems. We show that there are strong connections between neural-network quantum states in the form of restricted Boltzmann machines and some classes of tensor-network states in arbitrary dimensions. In particular, we demonstrate that short-range restricted Boltzmann machines are entangled plaquette states, while fully connected restricted Boltzmann machines are string-bond states with a nonlocal geometry and low bond dimension. These results shed light on the underlying architecture of restricted Boltzmann machines and their efficiency at representing many-body quantum states. String-bond states also provide a generic way of enhancing the power of neural-network quantum states and a natural generalization to systems with larger local Hilbert space. We compare the advantages and drawbacks of these different classes of states and present a method to combine them together. This allows us to benefit from both the entanglement structure of tensor networks and the efficiency of neural-network quantum states into a single Ansatz capable of targeting the wave function of strongly correlated systems. While it remains a challenge to describe states with chiral topological order using traditional tensor networks, we show that, because of their nonlocal geometry, neural-network quantum states and their string-bond-state extension can describe a lattice fractional quantum Hall state exactly. In addition, we provide numerical evidence that neural-network quantum states can approximate a chiral spin liquid with better accuracy than entangled plaquette states and local string-bond states. Our results demonstrate the efficiency of neural networks to describe complex quantum wave functions and pave the way towards the use of string-bond states as a tool in more traditional machine-learning applications.
Impact of the topology of global macroeconomic network on the spreading of economic crises.
Lee, Kyu-Min; Yang, Jae-Suk; Kim, Gunn; Lee, Jaesung; Goh, Kwang-Il; Kim, In-mook
2011-03-31
Throughout economic history, the global economy has experienced recurring crises. The persistent recurrence of such economic crises calls for an understanding of their generic features rather than treating them as singular events. The global economic system is a highly complex system and can best be viewed in terms of a network of interacting macroeconomic agents. In this regard, from the perspective of collective network dynamics, here we explore how the topology of the global macroeconomic network affects the patterns of spreading of economic crises. Using a simple toy model of crisis spreading, we demonstrate that an individual country's role in crisis spreading is not only dependent on its gross macroeconomic capacities, but also on its local and global connectivity profile in the context of the world economic network. We find that on one hand clustering of weak links at the regional scale can significantly aggravate the spread of crises, but on the other hand the current network structure at the global scale harbors higher tolerance of extreme crises compared to more "globalized" random networks. These results suggest that there can be a potential hidden cost in the ongoing globalization movement towards establishing less-constrained, trans-regional economic links between countries, by increasing vulnerability of the global economic system to extreme crises.
Aguirre, Jacobo; Buldú, Javier M; Manrubia, Susanna C
2009-12-01
Networks of selectively neutral genotypes underlie the evolution of populations of replicators in constant environments. Previous theoretical analysis predicted that such populations will evolve toward highly connected regions of the genome space. We first study the evolution of populations of replicators on simple networks and quantify how the transient time to equilibrium depends on the initial distribution of sequences on the neutral network, on the topological properties of the latter, and on the mutation rate. Second, network neutrality is broken through the introduction of an energy for each sequence. This allows to study the competition between two features (neutrality and energetic stability) relevant for survival and subjected to different selective pressures. In cases where the two features are negatively correlated, the population experiences sudden migrations in the genome space for values of the relevant parameters that we calculate. The numerical study of larger networks indicates that the qualitative behavior to be expected in more realistic cases is already seen in representative examples of small networks.
Aguirre, Jacobo; Buldú, Javier M.; Manrubia, Susanna C.
2009-12-01
Networks of selectively neutral genotypes underlie the evolution of populations of replicators in constant environments. Previous theoretical analysis predicted that such populations will evolve toward highly connected regions of the genome space. We first study the evolution of populations of replicators on simple networks and quantify how the transient time to equilibrium depends on the initial distribution of sequences on the neutral network, on the topological properties of the latter, and on the mutation rate. Second, network neutrality is broken through the introduction of an energy for each sequence. This allows to study the competition between two features (neutrality and energetic stability) relevant for survival and subjected to different selective pressures. In cases where the two features are negatively correlated, the population experiences sudden migrations in the genome space for values of the relevant parameters that we calculate. The numerical study of larger networks indicates that the qualitative behavior to be expected in more realistic cases is already seen in representative examples of small networks.
Topology Control with Anisotropic and Sector Turning Antennas in Ad-hoc and Sensor Networks
Directory of Open Access Journals (Sweden)
V. Černý
2011-01-01
Full Text Available During the last several years, technological advances have allowed the development of small, cheap, embedded, independent and rather powerful radio devices that can self-organise into data networks. Such networks are usually called ad-hoc networks or, sometimes, depending on the application field, sensor networks. One of the first standards for ad-hoc networks to impose itself as a fully industrial framework for data gathering and control over such devices is IEEE 802.15.4 and, on top of it, its pair network architecture: ZigBee. In the case of multiple radio devices clamped into a small geographical area, the lack of radio bandwidth becomes a major problem, leading to multiple data losses and unnecessary power drain from the batteries of these small devices. This problem is usually perceived as interference. The deployment of appropriate topology control mechanisms (TC can solve interference. All of these algorithms calculate TC on the basis of isotropic antenna radiation patterns in the horizontal plane.
Two-Dimensional Dirac Fermions in a Topological Insulator: Transport in the Quantum Limit
Energy Technology Data Exchange (ETDEWEB)
Analytis, J.G.; /SIMES, Stanford /SLAC /Stanford U., Geballe Lab /Stanford U., Appl. Phys. Dept.; McDonald, R.D.; /Los Alamos; Riggs, S.C.; /Natl. High Mag. Field Lab.; Chu, J.-H.; /SIMES, Stanford /SLAC /Stanford U., Geballe Lab /Stanford U., Appl. Phys. Dept.; Boebinger, G.S.; /Natl. High Mag. Field Lab.; Fisher, I.R.; /SIMES, Stanford /SLAC /Stanford U., Geballe Lab /Stanford U., Appl. Phys. Dept.
2011-08-12
Pulsed magnetic fields of up to 55T are used to investigate the transport properties of the topological insulator Bi{sub 2}Se{sub 3} in the extreme quantum limit. For samples with a bulk carrier density of n = 2.9 x 10{sup 16} cm{sup -3}, the lowest Landau level of the bulk 3D Fermi surface is reached by a field of 4T. For fields well beyond this limit, Shubnikov-de Haas oscillations arising from quantization of the 2D surface state are observed, with the {nu} = 1 Landau level attained by a field of {approx} 35T. These measurements reveal the presence of additional oscillations which occur at fields corresponding to simple rational fractions of the integer Landau indices.
Network Theory: A Primer and Questions for Air Transportation Systems Applications
Holmes, Bruce J.
2004-01-01
A new understanding (with potential applications to air transportation systems) has emerged in the past five years in the scientific field of networks. This development emerges in large part because we now have a new laboratory for developing theories about complex networks: The Internet. The premise of this new understanding is that most complex networks of interest, both of nature and of human contrivance, exhibit a fundamentally different behavior than thought for over two hundred years under classical graph theory. Classical theory held that networks exhibited random behavior, characterized by normal, (e.g., Gaussian or Poisson) degree distributions of the connectivity between nodes by links. The new understanding turns this idea on its head: networks of interest exhibit scale-free (or small world) degree distributions of connectivity, characterized by power law distributions. The implications of scale-free behavior for air transportation systems include the potential that some behaviors of complex system architectures might be analyzed through relatively simple approximations of local elements of the system. For air transportation applications, this presentation proposes a framework for constructing topologies (architectures) that represent the relationships between mobility, flight operations, aircraft requirements, and airspace capacity, and the related externalities in airspace procedures and architectures. The proposed architectures or topologies may serve as a framework for posing comparative and combinative analyses of performance, cost, security, environmental, and related metrics.
Jiao, Bingqing; Zhang, Delong; Liang, Aiying; Liang, Bishan; Wang, Zengjian; Li, Junchao; Cai, Yuxuan; Gao, Mengxia; Gao, Zhenni; Chang, Song; Huang, Ruiwang; Liu, Ming
2017-10-01
Previous studies have indicated a tight linkage between resting-state functional connectivity of the human brain and creative ability. This study aimed to further investigate the association between the topological organization of resting-state brain networks and creativity. Therefore, we acquired resting-state fMRI data from 22 high-creativity participants and 22 low-creativity participants (as determined by their Torrance Tests of Creative Thinking scores). We then constructed functional brain networks for each participant and assessed group differences in network topological properties before exploring the relationships between respective network topological properties and creative ability. We identified an optimized organization of intrinsic brain networks in both groups. However, compared with low-creativity participants, high-creativity participants exhibited increased global efficiency and substantially decreased path length, suggesting increased efficiency of information transmission across brain networks in creative individuals. Using a multiple linear regression model, we further demonstrated that regional functional integration properties (i.e., the betweenness centrality and global efficiency) of brain networks, particularly the default mode network (DMN) and sensorimotor network (SMN), significantly predicted the individual differences in creative ability. Furthermore, the associations between network regional properties and creative performance were creativity-level dependent, where the difference in the resource control component may be important in explaining individual difference in creative performance. These findings provide novel insights into the neural substrate of creativity and may facilitate objective identification of creative ability. Copyright © 2017 Elsevier B.V. All rights reserved.
Automatic discovery of the communication network topology for building a supercomputer model
Sobolev, Sergey; Stefanov, Konstantin; Voevodin, Vadim
2016-10-01
The Research Computing Center of Lomonosov Moscow State University is developing the Octotron software suite for automatic monitoring and mitigation of emergency situations in supercomputers so as to maximize hardware reliability. The suite is based on a software model of the supercomputer. The model uses a graph to describe the computing system components and their interconnections. One of the most complex components of a supercomputer that needs to be included in the model is its communication network. This work describes the proposed approach for automatically discovering the Ethernet communication network topology in a supercomputer and its description in terms of the Octotron model. This suite automatically detects computing nodes and switches, collects information about them and identifies their interconnections. The application of this approach is demonstrated on the "Lomonosov" and "Lomonosov-2" supercomputers.
Online Particle Detection by Neural Networks Based on Topologic Calorimetry Information
Ciodaro, T; The ATLAS collaboration; Damazio, D; de Seixas, JM
2011-01-01
This paper presents the last results from the Ringer algorithm, which is based on artificial neural networks for the electron identification at the online filtering system of the ATLAS particle detector, in the context of the LHC experiment at CERN. The algorithm performs topological feature extraction over the ATLAS calorimetry information (energy measurements). Later, the extracted information is presented to a neural network classifier. Studies showed that the Ringer algorithm achieves high detection efficiency, while keeping the false alarm rate low. Optimizations, guided by detailed analysis, reduced the algorithm execution time in 59%. Also, the payload necessary to store the Ringer algorithm information represents less than 6.2 percent of the total filtering system amount
Entraining the topology and the dynamics of a network of phase oscillators
Sendiña-Nadal, I.; Leyva, I.; Buldú, J. M.; Almendral, J. A.; Boccaletti, S.
2009-04-01
We show that the topology and dynamics of a network of unsynchronized Kuramoto oscillators can be simultaneously controlled by means of a forcing mechanism which yields a phase locking of the oscillators to that of an external pacemaker in connection with the reshaping of the network’s degree distribution. The entrainment mechanism is based on the addition, at regular time intervals, of unidirectional links from oscillators that follow the dynamics of a pacemaker to oscillators in the pristine graph whose phases hold a prescribed phase relationship. Such a dynamically based rule in the attachment process leads to the emergence of a power-law shape in the final degree distribution of the graph whenever the network is entrained to the dynamics of the pacemaker. We show that the arousal of a scale-free distribution in connection with the success of the entrainment process is a robust feature, characterizing different networks’ initial configurations and parameters.
Nickerson, Naomi H; Li, Ying; Benjamin, Simon C
2013-01-01
A scalable quantum computer could be built by networking together many simple processor cells, thus avoiding the need to create a single complex structure. The difficulty is that realistic quantum links are very error prone. A solution is for cells to repeatedly communicate with each other and so purify any imperfections; however prior studies suggest that the cells themselves must then have prohibitively low internal error rates. Here we describe a method by which even error-prone cells can perform purification: groups of cells generate shared resource states, which then enable stabilization of topologically encoded data. Given a realistically noisy network (≥10% error rate) we find that our protocol can succeed provided that intra-cell error rates for initialisation, state manipulation and measurement are below 0.82%. This level of fidelity is already achievable in several laboratory systems.
Robust node estimation and topology discovery for large-scale networks
Alouini, Mohamed-Slim
2017-02-23
Various examples are provided for node estimation and topology discovery for networks. In one example, a method includes receiving a packet having an identifier from a first node; adding the identifier to another transmission packet based on a comparison between the first identifier and existing identifiers associated with the other packet; adjusting a transmit probability based on the comparison; and transmitting the other packet based on a comparison between the transmit probability and a probability distribution. In another example, a system includes a network device that can adds an identifier received in a packet to a list including existing identifiers and adjust a transmit probability based on a comparison between the identifiers; and transmit another packet based on a comparison between the transmit probability and a probability distribution. In another example, a method includes determining a quantity of sensor devices based on a plurality of identifiers received in a packet.
Robust node estimation and topology discovery for large-scale networks
Alouini, Mohamed-Slim; Douik, Ahmed S.; Aly, Salah A.; Al-Naffouri, Tareq Y.
2017-01-01
Various examples are provided for node estimation and topology discovery for networks. In one example, a method includes receiving a packet having an identifier from a first node; adding the identifier to another transmission packet based on a comparison between the first identifier and existing identifiers associated with the other packet; adjusting a transmit probability based on the comparison; and transmitting the other packet based on a comparison between the transmit probability and a probability distribution. In another example, a system includes a network device that can adds an identifier received in a packet to a list including existing identifiers and adjust a transmit probability based on a comparison between the identifiers; and transmit another packet based on a comparison between the transmit probability and a probability distribution. In another example, a method includes determining a quantity of sensor devices based on a plurality of identifiers received in a packet.
Energy-Aware Topology Control Strategy for Human-Centric Wireless Sensor Networks
Directory of Open Access Journals (Sweden)
Roc Meseguer
2014-02-01
Full Text Available The adoption of mobile and ubiquitous solutions that involve participatory or opportunistic sensing increases every day. This situation has highlighted the relevance of optimizing the energy consumption of these solutions, because their operation depends on the devices’ battery lifetimes. This article presents a study that intends to understand how the prediction of topology control messages in human-centric wireless sensor networks can be used to help reduce the energy consumption of the participating devices. In order to do that, five research questions have been defined and a study based on simulations was conducted to answer these questions. The obtained results help identify suitable mobile computing scenarios where the prediction of topology control messages can be used to save energy of the network nodes. These results also allow estimating the percentage of energy saving that can be expected, according to the features of the work scenario and the participants behavior. Designers of mobile collaborative applications that involve participatory or opportunistic sensing, can take advantage of these findings to increase the autonomy of their solutions.
Network-based statistical comparison of citation topology of bibliographic databases
Šubelj, Lovro; Fiala, Dalibor; Bajec, Marko
2014-01-01
Modern bibliographic databases provide the basis for scientific research and its evaluation. While their content and structure differ substantially, there exist only informal notions on their reliability. Here we compare the topological consistency of citation networks extracted from six popular bibliographic databases including Web of Science, CiteSeer and arXiv.org. The networks are assessed through a rich set of local and global graph statistics. We first reveal statistically significant inconsistencies between some of the databases with respect to individual statistics. For example, the introduced field bow-tie decomposition of DBLP Computer Science Bibliography substantially differs from the rest due to the coverage of the database, while the citation information within arXiv.org is the most exhaustive. Finally, we compare the databases over multiple graph statistics using the critical difference diagram. The citation topology of DBLP Computer Science Bibliography is the least consistent with the rest, while, not surprisingly, Web of Science is significantly more reliable from the perspective of consistency. This work can serve either as a reference for scholars in bibliometrics and scientometrics or a scientific evaluation guideline for governments and research agencies. PMID:25263231
The climatogenetic factors and the transport network
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Vasile MAXIM
2010-03-01
Full Text Available The article analyses the climatogenic factors and how they influence the transport system (network of the Republic of Moldova. The following climatogenetic factors were analysed: dynamic, physical-geographic, etc. as well as some specific climatic elements as the temperature of the air, cloud amount, humidity, direction and speed of the wind. As a conclusion it can be mentioned that when tracing the terrestrial transport system it is necessary to take into consideration the climatic factors which directly influence this field of human activity.
Bobbert, F S L; Lietaert, K; Eftekhari, A A; Pouran, B; Ahmadi, S M; Weinans, H; Zadpoor, A A
2017-01-01
Porous biomaterials that simultaneously mimic the topological, mechanical, and mass transport properties of bone are in great demand but are rarely found in the literature. In this study, we rationally designed and additively manufactured (AM) porous metallic biomaterials based on four different
Leveraging Fog Computing for Scalable IoT Datacenter Using Spine-Leaf Network Topology
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K. C. Okafor
2017-01-01
Full Text Available With the Internet of Everything (IoE paradigm that gathers almost every object online, huge traffic workload, bandwidth, security, and latency issues remain a concern for IoT users in today’s world. Besides, the scalability requirements found in the current IoT data processing (in the cloud can hardly be used for applications such as assisted living systems, Big Data analytic solutions, and smart embedded applications. This paper proposes an extended cloud IoT model that optimizes bandwidth while allowing edge devices (Internet-connected objects/devices to smartly process data without relying on a cloud network. Its integration with a massively scaled spine-leaf (SL network topology is highlighted. This is contrasted with a legacy multitier layered architecture housing network services and routing policies. The perspective offered in this paper explains how low-latency and bandwidth intensive applications can transfer data to the cloud (and then back to the edge application without impacting QoS performance. Consequently, a spine-leaf Fog computing network (SL-FCN is presented for reducing latency and network congestion issues in a highly distributed and multilayer virtualized IoT datacenter environment. This approach is cost-effective as it maximizes bandwidth while maintaining redundancy and resiliency against failures in mission critical applications.
Cogoni, Marco; Busonera, Giovanni; Anedda, Paolo; Zanetti, Gianluigi
2015-01-01
We generalize previous studies on critical phenomena in communication networks [1,2] by adding computational capabilities to the nodes. In our model, a set of tasks with random origin, destination and computational structure is distributed on a computational network, modeled as a graph. By varying the temperature of a Metropolis Montecarlo, we explore the global latency for an optimal to suboptimal resource assignment at a given time instant. By computing the two-point correlation function for the local overload, we study the behavior of the correlation distance (both for links and nodes) while approaching the congested phase: a transition from peaked to spread g(r) is seen above a critical (Montecarlo) temperature Tc. The average latency trend of the system is predicted by averaging over several network traffic realizations while maintaining a spatially detailed information for each node: a sharp decrease of performance is found over Tc independently of the workload. The globally optimized computational resource allocation and network routing defines a baseline for a future comparison of the transition behavior with respect to existing routing strategies [3,4] for different network topologies.
Network topology and functional connectivity disturbances precede the onset of Huntington's disease.
Harrington, Deborah L; Rubinov, Mikail; Durgerian, Sally; Mourany, Lyla; Reece, Christine; Koenig, Katherine; Bullmore, Ed; Long, Jeffrey D; Paulsen, Jane S; Rao, Stephen M
2015-08-01
Cognitive, motor and psychiatric changes in prodromal Huntington's disease have nurtured the emergent need for early interventions. Preventive clinical trials for Huntington's disease, however, are limited by a shortage of suitable measures that could serve as surrogate outcomes. Measures of intrinsic functional connectivity from resting-state functional magnetic resonance imaging are of keen interest. Yet recent studies suggest circumscribed abnormalities in resting-state functional magnetic resonance imaging connectivity in prodromal Huntington's disease, despite the spectrum of behavioural changes preceding a manifest diagnosis. The present study used two complementary analytical approaches to examine whole-brain resting-state functional magnetic resonance imaging connectivity in prodromal Huntington's disease. Network topology was studied using graph theory and simple functional connectivity amongst brain regions was explored using the network-based statistic. Participants consisted of gene-negative controls (n = 16) and prodromal Huntington's disease individuals (n = 48) with various stages of disease progression to examine the influence of disease burden on intrinsic connectivity. Graph theory analyses showed that global network interconnectivity approximated a random network topology as proximity to diagnosis neared and this was associated with decreased connectivity amongst highly-connected rich-club network hubs, which integrate processing from diverse brain regions. However, functional segregation within the global network (average clustering) was preserved. Functional segregation was also largely maintained at the local level, except for the notable decrease in the diversity of anterior insula intermodular-interconnections (participation coefficient), irrespective of disease burden. In contrast, network-based statistic analyses revealed patterns of weakened frontostriatal connections and strengthened frontal-posterior connections that evolved as disease
Becoming-Topologies of Education: Deformations, Networks and the Database Effect
Thompson, Greg; Cook, Ian
2015-01-01
This article uses topological approaches to suggest that education is becoming-topological. Analyses presented in a recent double-issue of "Theory, Culture & Society" are used to demonstrate the utility of topology for education. In particular, the article explains education's topological character through examining the global…
Park, Chang-Hyun; Lee, Seungyup; Kim, Taewon; Won, Wang Yeon; Lee, Kyoung-Uk
2017-10-01
Schizophrenia displays connectivity deficits in the brain, but the literature has shown inconsistent findings about alterations in global efficiency of brain functional networks. We supposed that such inconsistency at the whole brain level may be due to a mixture of different portions of global efficiency at sub-brain levels. Accordingly, we considered measuring portions of global efficiency in two aspects: spatial portions by considering sub-brain networks and topological portions by considering contributions to global efficiency according to direct and indirect topological connections. We proposed adjacency and indirect adjacency as new network parameters attributable to direct and indirect topological connections, respectively, and applied them to graph-theoretical analysis of brain functional networks constructed from resting state fMRI data of 22 patients with schizophrenia and 22 healthy controls. Group differences in the network parameters were observed not for whole brain and hemispheric networks, but for regional networks. Alterations in adjacency and indirect adjacency were in opposite directions, such that adjacency increased, but indirect adjacency decreased in patients with schizophrenia. Furthermore, over connections in frontal and parietal regions, increased adjacency was associated with more severe negative symptoms, while decreased adjacency was associated with more severe positive symptoms of schizophrenia. This finding indicates that connectivity deficits associated with positive and negative symptoms of schizophrenia may involve topologically different paths in the brain. In patients with schizophrenia, although changes in global efficiency may not be clearly shown, different alterations in brain functional networks according to direct and indirect topological connections could be revealed at the regional level. Copyright © 2017 Elsevier B.V. All rights reserved.
Research on the Topological Properties of Air Quality Index Based on a Complex Network
Directory of Open Access Journals (Sweden)
Yongli Zhang
2018-04-01
Full Text Available To analyze the dynamic characteristics of air quality for enforcing effective measures to prevent and evade air pollution harm, air quality index (AQI time series data was selected and transformed into a symbol sequence consisting of characters (H, M, L through the coarse graining process; then each 6-symbols series was treated as one vertex by time sequence to construct the AQI directed-weighted network; finally the centrality, clusterability, and ranking of the AQI network were analyzed. The results indicated that vertex strength and cumulative strength distribution, vertex strength and strength rank presented power law distributions, and the AQI network is a scale-free network. Only 17 vertices possessed a higher weighted clustering coefficient; meanwhile weighted clustering coefficient and vertex strength didn’t show a strong correlation. The AQI network did not have an obvious central tendency towards intermediaries in general, but 20.55% of vertices accounted for nearly 1/2 of the intermediaries, and the varieties still existed. The mean distance of 68.4932% of vertices was 6.120–9.973, the AQI network did not have obvious small-world phenomena, the conversion of AQI patterns presented the characteristics of periodicity and regularity, and 20.2055% of vertices had high proximity prestige. The vertices fell into six islands, the AQI pattern indicating heavy or serious air pollution lasting six days always lingered for a long time. The number of triads 2-012 was the largest, and the AQI network followed the transitivity model. The study has instructional significance in understanding time change regulation of air quality in Beijing, opening a new way for time series prediction research. Additionally, the factors causing the change of topological properties should be analyzed in the future research.
Structural Properties of the Brazilian Air Transportation Network
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GUILHERME S. COUTO
2015-09-01
Full Text Available The air transportation network in a country has a great impact on the local, national and global economy. In this paper, we analyze the air transportation network in Brazil with complex network features to better understand its characteristics. In our analysis, we built networks composed either by national or by international flights. We also consider the network when both types of flights are put together. Interesting conclusions emerge from our analysis. For instance, Viracopos Airport (Campinas City is the most central and connected airport on the national flights network. Any operational problem in this airport separates the Brazilian national network into six distinct subnetworks. Moreover, the Brazilian air transportation network exhibits small world characteristics and national connections network follows a power law distribution. Therefore, our analysis sheds light on the current Brazilian air transportation infrastructure, bringing a novel understanding that may help face the recent fast growth in the usage of the Brazilian transport network.
Structural Properties of the Brazilian Air Transportation Network.
Couto, Guilherme S; da Silva, Ana Paula Couto; Ruiz, Linnyer B; Benevenuto, Fabrício
2015-09-01
The air transportation network in a country has a great impact on the local, national and global economy. In this paper, we analyze the air transportation network in Brazil with complex network features to better understand its characteristics. In our analysis, we built networks composed either by national or by international flights. We also consider the network when both types of flights are put together. Interesting conclusions emerge from our analysis. For instance, Viracopos Airport (Campinas City) is the most central and connected airport on the national flights network. Any operational problem in this airport separates the Brazilian national network into six distinct subnetworks. Moreover, the Brazilian air transportation network exhibits small world characteristics and national connections network follows a power law distribution. Therefore, our analysis sheds light on the current Brazilian air transportation infrastructure, bringing a novel understanding that may help face the recent fast growth in the usage of the Brazilian transport network.
Loepfe, Lasse; Cabrales, Antonio; Sánchez, Angel
2013-01-01
The 2007-2008 financial crisis solidified the consensus among policymakers that a macro-prudential approach to regulation and supervision should be adopted. The currently preferred policy option is the regulation of capital requirements, with the main focus on combating procyclicality and on identifying the banks that have a high systemic importance, those that are "too big to fail". Here we argue that the concept of systemic risk should include the analysis of the system as a whole and we explore systematically the most important properties for policy purposes of networks topology on resistance to shocks. In a thorough study going from analytical models to empirical data, we show two sharp transitions from safe to risky regimes: 1) diversification becomes harmful with just a small fraction (~2%) of the shocks sampled from a fat tailed shock distributions and 2) when large shocks are present a critical link density exists where an effective giant cluster forms and most firms become vulnerable. This threshold depends on the network topology, especially on modularity. Firm size heterogeneity has important but diverse effects that are heavily dependent on shock characteristics. Similarly, degree heterogeneity increases vulnerability only when shocks are directed at the most connected firms. Furthermore, by studying the structure of the core of the transnational corporation network from real data, we show that its stability could be clearly increased by removing some of the links with highest centrality betweenness. Our results provide a novel insight and arguments for policy makers to focus surveillance on the connections between firms, in addition to capital requirements directed at the nodes.
A fault-tolerant small world topology control model in ad hoc networks for search and rescue
Tan, Mian; Fang, Ling; Wu, Yue; Zhang, Bo; Chang, Bowen; Holme, Petter; Zhao, Jing
2018-02-01
Due to their self-organized, multi-hop and distributed characteristics, ad hoc networks are useful in search and rescue. Topology control models need to be designed for energy-efficient, robust and fast communication in ad hoc networks. This paper proposes a topology control model which specializes for search and rescue-Compensation Small World-Repeated Game (CSWRG)-which integrates mobility models, constructing small world networks and a game-theoretic approach to the allocation of resources. Simulation results show that our mobility models can enhance the communication performance of the constructed small-world networks. Our strategy, based on repeated game, can suppress selfish behavior and compensate agents that encounter selfish or faulty neighbors. This model could be useful for the design of ad hoc communication networks.
Detecting and diagnosing SSME faults using an autoassociative neural network topology
Ali, M.; Dietz, W. E.; Kiech, E. L.
1989-01-01
An effort is underway at the University of Tennessee Space Institute to develop diagnostic expert system methodologies based on the analysis of patterns of behavior of physical mechanisms. In this approach, fault diagnosis is conceptualized as the mapping or association of patterns of sensor data to patterns representing fault conditions. Neural networks are being investigated as a means of storing and retrieving fault scenarios. Neural networks offer several powerful features in fault diagnosis, including (1) general pattern matching capabilities, (2) resistance to noisy input data, (3) the ability to be trained by example, and (4) the potential for implementation on parallel computer architectures. This paper presents (1) an autoassociative neural network topology, i.e. the network input and output is identical when properly trained, and hence learning is unsupervised; (2) the training regimen used; and (3) the response of the system to inputs representing both previously observed and unkown fault scenarios. The effects of noise on the integrity of the diagnosis are also evaluated.
Sabour, Mohammad Reza; Moftakhari Anasori Movahed, Saman
2017-02-01
The soil sorption partition coefficient logK oc is an indispensable parameter that can be used in assessing the environmental risk of organic chemicals. In order to predict soil sorption partition coefficient for different and even unknown compounds in a fast and accurate manner, a radial basis function neural network (RBFNN) model was developed. Eight topological descriptors of 800 organic compounds were used as inputs of the model. These 800 organic compounds were chosen from a large and very diverse data set. Generalized Regression Neural Network (GRNN) was utilized as the function in this neural network model due to its capability to adapt very quickly. Hence, it can be used to predict logK oc for new chemicals, as well. Out of total data set, 560 organic compounds were used for training and 240 to test efficiency of the model. The obtained results indicate that the model performance is very well. The correlation coefficients (R2) for training and test sets were 0.995 and 0.933, respectively. The root-mean square errors (RMSE) were 0.2321 for training set and 0.413 for test set. As the results for both training and test set are extremely satisfactory, the proposed neural network model can be employed not only to predict logK oc of known compounds, but also to be adaptive for prediction of this value precisely for new products that enter the market each year. Copyright © 2016 Elsevier Ltd. All rights reserved.
The Effects of Long-term Abacus Training on Topological Properties of Brain Functional Networks.
Weng, Jian; Xie, Ye; Wang, Chunjie; Chen, Feiyan
2017-08-18
Previous studies in the field of abacus-based mental calculation (AMC) training have shown that this training has the potential to enhance a wide variety of cognitive abilities. It can also generate specific changes in brain structure and function. However, there is lack of studies investigating the impact of AMC training on the characteristics of brain networks. In this study, utilizing graph-based network analysis, we compared topological properties of brain functional networks between an AMC group and a matched control group. Relative to the control group, the AMC group exhibited higher nodal degrees in bilateral calcarine sulcus and increased local efficiency in bilateral superior occipital gyrus and right cuneus. The AMC group also showed higher nodal local efficiency in right fusiform gyrus, which was associated with better math ability. However, no relationship was significant in the control group. These findings provide evidence that long-term AMC training may improve information processing efficiency in visual-spatial related regions, which extend our understanding of training plasticity at the brain network level.
International Nuclear Information System (INIS)
Laajalehto, Tatu; Kuosa, Maunu; Mäkilä, Tapio; Lampinen, Markku; Lahdelma, Risto
2014-01-01
Heating and cooling have a major role in the energy sector, covering 46% of total final energy use worldwide. District heating (DH) is a significant technology for improving the energy efficiency of heating systems in communities, because it enables waste heat sources to be utilised economically and therefore significantly reduces the environmental impacts of power generation. As a result of new and more stringent construction regulations for buildings, the heat demands of individual buildings are decreasing and more energy-efficient heating systems have to be developed. In this study, the energy efficiency of a new DH system which includes both a new control system called mass flow control and a new network design called a ring network is examined. A topology in the Helsinki region is studied by using a commercial DH network modelling tool, Grades Heating. The district heating network is attached to a wood-burning heat station which has a heat recovery system in use. Examination is performed by means of both technical and economic analysis. The new non-linear temperature programme that is required is adopted for supply and return temperatures, which allows greater temperature cooling and smaller flow rates. Lower district heating water temperatures are essential when reducing the heat losses in the network and heat production. Mass flow control allows smaller pressure drops in the network and thus reduces the pumping power. The aim of this study was to determine the most energy-efficient DH water supply temperatures in the case network. If the ring network design is utilised, the district heating system is easier to control. As a result the total heat consumption within the heating season is reduced compared to traditional DH systems. On the basis of the results, the new DH system is significantly more energy-efficient in the case network that was examined than the traditional design. For example, average energy losses within the constraints (which consist of heat
Topology of the Italian airport network: A scale-free small-world network with a fractal structure?
International Nuclear Information System (INIS)
Guida, Michele; Maria, Funaro
2007-01-01
In this paper, for the first time we analyze the structure of the Italian Airport Network (IAN) looking at it as a mathematical graph and investigate its topological properties. We find that it has very remarkable features, being like a scale-free network, since both the degree and the 'betweenness centrality' distributions follow a typical power-law known in literature as a Double Pareto Law. From a careful analysis of the data, the Italian Airport Network turns out to have a self-similar structure. In short, it is characterized by a fractal nature, whose typical dimensions can be easily determined from the values of the power-law scaling exponents. Moreover, we show that, according to the period examined, these distributions exhibit a number of interesting features, such as the existence of some 'hubs', i.e. in the graph theory's jargon, nodes with a very large number of links, and others most probably associated with geographical constraints. Also, we find that the IAN can be classified as a small-world network because the average distance between reachable pairs of airports grows at most as the logarithm of the number of airports. The IAN does not show evidence of 'communities' and this result could be the underlying reason behind the smallness of the value of the clustering coefficient, which is related to the probability that two nearest neighbors of a randomly chosen airport are connected
A study of topologies and protocols for fiber optic local area network
Yeh, C.; Gerla, M.; Rodrigues, P.
1985-01-01
The emergence of new applications requiring high data traffic necessitates the development of high speed local area networks. Optical fiber is selected as the transmission medium due to its inherent advantages over other possible media and the dual optical bus architecture is shown to be the most suitable topology. Asynchronous access protocols, including token, random, hybrid random/token, and virtual token schemes, are developed and analyzed. Exact expressions for insertion delay and utilization at light and heavy load are derived, and intermediate load behavior is investigated by simulation. A new tokenless adaptive scheme whose control depends only on the detection of activity on the channel is shown to outperform round-robin schemes under uneven loads and multipacket traffic and to perform optimally at light load. An approximate solution to the queueing delay for an oscillating polling scheme under chaining is obtained and results are compared with simulation. Solutions to the problem of building systems with a large number of stations are presented, including maximization of the number of optical couplers, and the use of passive star/bus topologies, bridges and gateways.
A Novel Topology Link-Controlling Approach for Active Defense of a Node in a Network
Directory of Open Access Journals (Sweden)
Jun Li
2017-03-01
Full Text Available With the rapid development of virtual machine technology and cloud computing, distributed denial of service (DDoS attacks, or some peak traffic, poses a great threat to the security of the network. In this paper, a novel topology link control technique and mitigation attacks in real-time environments is proposed. Firstly, a non-invasive method of deploying virtual sensors in the nodes is built, which uses the resource manager of each monitored node as a sensor. Secondly, a general topology-controlling approach of resisting the tolerant invasion is proposed. In the proposed approach, a prediction model is constructed by using copula functions for predicting the peak of a resource through another resource. The result of prediction determines whether or not to initiate the active defense. Finally, a minority game with incomplete strategy is employed to suppress attack flows and improve the permeability of the normal flows. The simulation results show that the proposed approach is very effective in protecting nodes.
Wang, Yiheng; Liu, Tong; Xu, Dong; Shi, Huidong; Zhang, Chaoyang; Mo, Yin-Yuan; Wang, Zheng
2016-01-22
The hypo- or hyper-methylation of the human genome is one of the epigenetic features of leukemia. However, experimental approaches have only determined the methylation state of a small portion of the human genome. We developed deep learning based (stacked denoising autoencoders, or SdAs) software named "DeepMethyl" to predict the methylation state of DNA CpG dinucleotides using features inferred from three-dimensional genome topology (based on Hi-C) and DNA sequence patterns. We used the experimental data from immortalised myelogenous leukemia (K562) and healthy lymphoblastoid (GM12878) cell lines to train the learning models and assess prediction performance. We have tested various SdA architectures with different configurations of hidden layer(s) and amount of pre-training data and compared the performance of deep networks relative to support vector machines (SVMs). Using the methylation states of sequentially neighboring regions as one of the learning features, an SdA achieved a blind test accuracy of 89.7% for GM12878 and 88.6% for K562. When the methylation states of sequentially neighboring regions are unknown, the accuracies are 84.82% for GM12878 and 72.01% for K562. We also analyzed the contribution of genome topological features inferred from Hi-C. DeepMethyl can be accessed at http://dna.cs.usm.edu/deepmethyl/.
Distributed reconfigurable control strategies for switching topology networked multi-agent systems.
Gallehdari, Z; Meskin, N; Khorasani, K
2017-11-01
In this paper, distributed control reconfiguration strategies for directed switching topology networked multi-agent systems are developed and investigated. The proposed control strategies are invoked when the agents are subject to actuator faults and while the available fault detection and isolation (FDI) modules provide inaccurate and unreliable information on the estimation of faults severities. Our proposed strategies will ensure that the agents reach a consensus while an upper bound on the team performance index is ensured and satisfied. Three types of actuator faults are considered, namely: the loss of effectiveness fault, the outage fault, and the stuck fault. By utilizing quadratic and convex hull (composite) Lyapunov functions, two cooperative and distributed recovery strategies are designed and provided to select the gains of the proposed control laws such that the team objectives are guaranteed. Our proposed reconfigurable control laws are applied to a team of autonomous underwater vehicles (AUVs) under directed switching topologies and subject to simultaneous actuator faults. Simulation results demonstrate the effectiveness of our proposed distributed reconfiguration control laws in compensating for the effects of sudden actuator faults and subject to fault diagnosis module uncertainties and unreliabilities. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.
Research on centrality of urban transport network nodes
Wang, Kui; Fu, Xiufen
2017-05-01
Based on the actual data of urban transport in Guangzhou, 19,150 bus stations in Guangzhou (as of 2014) are selected as nodes. Based on the theory of complex network, the network model of Guangzhou urban transport is constructed. By analyzing the degree centrality index, betweenness centrality index and closeness centrality index of nodes in the network, the level of centrality of each node in the network is studied. From a different point of view to determine the hub node of Guangzhou urban transport network, corresponding to the city's key sites and major transfer sites. The reliability of the network is determined by the stability of some key nodes (transport hub station). The research of network node centralization can provide a theoretical basis for the rational allocation of urban transport network sites and public transport system planning.
The effect of network topologies on the spreading of technological developments
International Nuclear Information System (INIS)
Kocsis, Gergely; Kun, Ferenc
2008-01-01
We study an agent-based model, as a special type of opinion dynamics, of the spreading of innovations in socio-economic systems varying the topology of agents' social contacts. The agents are organized on a square lattice where the connections are rewired with a certain probability. We show that the degree polydispersity and long range connections of agents can facilitate, but can also hinder the spreading of new technologies, depending on the amount of advantages provided by the innovation. We determine the critical fraction of innovative agents required to initiate spreading and to obtain a significant technological progress. As the fraction of innovative agents approaches the critical value, the spreading process slows down analogously to the critical slowing down observed at continuous phase transitions. The characteristic timescale at the critical point proved to have the same scaling as the average shortest path of the underlying social network. The model captures some relevant features of the spreading of innovations in telecommunication technologies
Zhang, Xue; Acencio, Marcio Luis; Lemke, Ney
2016-01-01
Essential proteins/genes are indispensable to the survival or reproduction of an organism, and the deletion of such essential proteins will result in lethality or infertility. The identification of essential genes is very important not only for understanding the minimal requirements for survival of an organism, but also for finding human disease genes and new drug targets. Experimental methods for identifying essential genes are costly, time-consuming, and laborious. With the accumulation of sequenced genomes data and high-throughput experimental data, many computational methods for identifying essential proteins are proposed, which are useful complements to experimental methods. In this review, we show the state-of-the-art methods for identifying essential genes and proteins based on machine learning and network topological features, point out the progress and limitations of current methods, and discuss the challenges and directions for further research. PMID:27014079
Cocco, Alex P.; Nakajo, Arata; Chiu, Wilson K. S.
2017-12-01
We present a fully analytical, heuristic model - the "Analytical Transport Network Model" - for steady-state, diffusive, potential flow through a 3-D network. Employing a combination of graph theory, linear algebra, and geometry, the model explicitly relates a microstructural network's topology and the morphology of its channels to an effective material transport coefficient (a general term meant to encompass, e.g., conductivity or diffusion coefficient). The model's transport coefficient predictions agree well with those from electrochemical fin (ECF) theory and finite element analysis (FEA), but are computed 0.5-1.5 and 5-6 orders of magnitude faster, respectively. In addition, the theory explicitly relates a number of morphological and topological parameters directly to the transport coefficient, whereby the distributions that characterize the structure are readily available for further analysis. Furthermore, ATN's explicit development provides insight into the nature of the tortuosity factor and offers the potential to apply theory from network science and to consider the optimization of a network's effective resistance in a mathematically rigorous manner. The ATN model's speed and relative ease-of-use offer the potential to aid in accelerating the design (with respect to transport), and thus reducing the cost, of energy materials.
Directory of Open Access Journals (Sweden)
Ning Li
2016-11-01
Full Text Available Because wireless sensor networks (WSNs have been widely used in recent years, how to reduce their energy consumption and interference has become a major issue. Topology control is a common and effective approach to improve network performance, such as reducing the energy consumption and network interference, improving the network connectivity, etc. Many topology control algorithms reduce network interference by dynamically adjusting the node transmission range. However, reducing the network interference by adjusting the transmission range is probabilistic. Therefore, in this paper, we analyze the probability of interference-optimality for the WSNs and prove that the probability of interference-optimality increases with the increasing of the original transmission range. Under a specific transmission range, the probability reaches the maximum value when the transmission range is 0.85r in homogeneous networks and 0.84r in heterogeneous networks. In addition, we also prove that when the network is energy-efficient, the network is also interference-optimal with probability 1 both in the homogeneous and heterogeneous networks.
Network harness: bundles of routes in public transport networks
Berche, B.; von Ferber, C.; Holovatch, T.
2009-12-01
Public transport routes sharing the same grid of streets and tracks are often found to proceed in parallel along shorter or longer sequences of stations. Similar phenomena are observed in other networks built with space consuming links such as cables, vessels, pipes, neurons, etc. In the case of public transport networks (PTNs) this behavior may be easily worked out on the basis of sequences of stations serviced by each route. To quantify this behavior we use the recently introduced notion of network harness. It is described by the harness distribution P(r, s): the number of sequences of s consecutive stations that are serviced by r parallel routes. For certain PTNs that we have analyzed we observe that the harness distribution may be described by power laws. These power laws indicate a certain level of organization and planning which may be driven by the need to minimize the costs of infrastructure and secondly by the fact that points of interest tend to be clustered in certain locations of a city. This effect may be seen as a result of the strong interdependence of the evolutions of both the city and its PTN. To further investigate the significance of the empirical results we have studied one- and two-dimensional models of randomly placed routes modeled by different types of walks. While in one dimension an analytic treatment was successful, the two dimensional case was studied by simulations showing that the empirical results for real PTNs deviate significantly from those expected for randomly placed routes.
Network topologies and dynamics leading to endotoxin tolerance and priming in innate immune cells.
Directory of Open Access Journals (Sweden)
Yan Fu
Full Text Available The innate immune system, acting as the first line of host defense, senses and adapts to foreign challenges through complex intracellular and intercellular signaling networks. Endotoxin tolerance and priming elicited by macrophages are classic examples of the complex adaptation of innate immune cells. Upon repetitive exposures to different doses of bacterial endotoxin (lipopolysaccharide or other stimulants, macrophages show either suppressed or augmented inflammatory responses compared to a single exposure to the stimulant. Endotoxin tolerance and priming are critically involved in both immune homeostasis and the pathogenesis of diverse inflammatory diseases. However, the underlying molecular mechanisms are not well understood. By means of a computational search through the parameter space of a coarse-grained three-node network with a two-stage Metropolis sampling approach, we enumerated all the network topologies that can generate priming or tolerance. We discovered three major mechanisms for priming (pathway synergy, suppressor deactivation, activator induction and one for tolerance (inhibitor persistence. These results not only explain existing experimental observations, but also reveal intriguing test scenarios for future experimental studies to clarify mechanisms of endotoxin priming and tolerance.