NASA Astrophysics Data System (ADS)
Strogatz, Steven
Everyone is familiar with the small-world phenomenon: soon after meeting a stranger, we are often suprised to discover that we have a mutual friend, or that we are somehow linked by a short chain of friends. In this talk, I'll present evidence that the small-world phenomenon is more than a curiosity of social networks — it is actually a general property of large, sparse networks whose topology is neither completely regular nor completely random. To check this idea, Duncan Watts and I have analyzed three networks of scientific interest: the neural network of the nematode worm C. elegans, the electrical power grid of the western United States, and the collaboration graph of actors in feature films. All three are small worlds, in the sense that the average number of "handshakes" separating any two members is extremely small (close to the theoretical lower limit set by a random graph). Yet at the same time, all three networks exhibit much more local clustering than a random net, demonstrating that they are not random. I'll also discuss a class of model networks that interpolate between regular lattices and random graphs. Previous theoretical research on complex systems in a wide range of disciplines has focused almost exclusively on networks that are either regular or random. Real networks often lie somewhere in between. Our mathematical model shows that networks in this middle ground tend to exhibit the small-world phenomenon, thanks to the presence of a few long-range edges that link parts of the graph that would otherwise be far apart. Furthermore, we find that when various dynamical systems are coupled in a small-world fashion, they exhibit much greater propagation speed, computational power, and synchronizability than their locally connected, regular counterparts. We explore the implications of these results for simple models of disease spreading, global computation in cellular automata, and collective locking of biological oscillators.
Epidemics in small world networks
NASA Astrophysics Data System (ADS)
Telo da Gama, M. M.; Nunes, A.
2006-03-01
For many infectious diseases, a small-world network on an underlying regular lattice is a suitable simplified model for the contact structure of the host population. It is well known that the contact network, described in this setting by a single parameter, the small-world parameter p, plays an important role both in the short term and in the long term dynamics of epidemic spread. We have studied the effect of the network structure on models of immune for life diseases and found that in addition to the reduction of the effective transmission rate, through the screening of infectives, spatial correlations may strongly enhance the stochastic fluctuations. As a consequence, time series of unforced Susceptible-Exposed-Infected-Recovered (SEIR) models provide patterns of recurrent epidemics with realistic amplitudes, suggesting that these models together with complex networks of contacts are the key ingredients to describe the prevaccination dynamical patterns of diseases such as measles and pertussis. We have also studied the role of the host contact strucuture in pathogen antigenic variation, through its effect on the final outcome of an invasion by a viral strain of a population where a very similar virus is endemic. Similar viral strains are modelled by the same infection and reinfection parameters, and by a given degree of cross immunity that represents the antigenic distance between the competing strains. We have found, somewhat surprisingly, that clustering on the network decreases the potential to sustain pathogen diversity.
Brain networks: small-worlds, after all?
NASA Astrophysics Data System (ADS)
Muller, Lyle; Destexhe, Alain; Rudolph-Lilith, Michelle
2014-10-01
Since its introduction, the ‘small-world’ effect has played a central role in network science, particularly in the analysis of the complex networks of the nervous system. From the cellular level to that of interconnected cortical regions, many analyses have revealed small-world properties in the networks of the brain. In this work, we revisit the quantification of small-worldness in neural graphs. We find that neural graphs fall into the ‘borderline’ regime of small-worldness, residing close to that of a random graph, especially when the degree sequence of the network is taken into account. We then apply recently introducted analytical expressions for clustering and distance measures, to study this borderline small-worldness regime. We derive theoretical bounds for the minimal and maximal small-worldness index for a given graph, and by semi-analytical means, study the small-worldness index itself. With this approach, we find that graphs with small-worldness equivalent to that observed in experimental data are dominated by their random component. These results provide the first thorough analysis suggesting that neural graphs may reside far away from the maximally small-world regime.
Collective dynamics of `small-world' networks
NASA Astrophysics Data System (ADS)
Watts, Duncan J.; Strogatz, Steven H.
1998-06-01
Networks of coupled dynamical systems have been used to model biological oscillators, Josephson junction arrays,, excitable media, neural networks, spatial games, genetic control networks and many other self-organizing systems. Ordinarily, the connection topology is assumed to be either completely regular or completely random. But many biological, technological and social networks lie somewhere between these two extremes. Here we explore simple models of networks that can be tuned through this middle ground: regular networks `rewired' to introduce increasing amounts of disorder. We find that these systems can be highly clustered, like regular lattices, yet have small characteristic path lengths, like random graphs. We call them `small-world' networks, by analogy with the small-world phenomenon, (popularly known as six degrees of separation). The neural network of the worm Caenorhabditis elegans, the power grid of the western United States, and the collaboration graph of film actors are shown to be small-world networks. Models of dynamical systems with small-world coupling display enhanced signal-propagation speed, computational power, and synchronizability. In particular, infectious diseases spread more easily in small-world networks than in regular lattices.
Disrupted Small-World Networks in Schizophrenia
ERIC Educational Resources Information Center
Liu, Yong; Liang, Meng; Zhou, Yuan; He, Yong; Hao, Yihui; Song, Ming; Yu, Chunshui; Liu, Haihong; Liu, Zhening; Jiang, Tianzi
2008-01-01
The human brain has been described as a large, sparse, complex network characterized by efficient small-world properties, which assure that the brain generates and integrates information with high efficiency. Many previous neuroimaging studies have provided consistent evidence of "dysfunctional connectivity" among the brain regions in…
Metastable configurations of small-world networks.
Heylen, R; Skantzos, N S; Blanco, J Busquets; Bollé, D
2006-01-01
We calculate the number of metastable configurations of Ising small-world networks that are constructed upon superimposing sparse Poisson random graphs onto a one-dimensional chain. Our solution is based on replicated transfer-matrix techniques. We examine the denegeracy of the ground state and find a jump in the entropy of metastable configurations exactly at the crossover between the small-world and the Poisson random graph structures. We also examine the difference in entropy between metastable and all possible configurations, for both ferromagnetic and bond-disordered long-range couplings. PMID:16486247
Metastable configurations of small-world networks
NASA Astrophysics Data System (ADS)
Heylen, R.; Skantzos, N. S.; Blanco, J. Busquets; Bollé, D.
2006-01-01
We calculate the number of metastable configurations of Ising small-world networks that are constructed upon superimposing sparse Poisson random graphs onto a one-dimensional chain. Our solution is based on replicated transfer-matrix techniques. We examine the denegeracy of the ground state and find a jump in the entropy of metastable configurations exactly at the crossover between the small-world and the Poisson random graph structures. We also examine the difference in entropy between metastable and all possible configurations, for both ferromagnetic and bond-disordered long-range couplings.
Synchronization on small-world networks
NASA Astrophysics Data System (ADS)
Hong, H.; Choi, M. Y.; Kim, Beom Jun
2002-02-01
We investigate collective synchronization in a system of coupled oscillators on small-world networks. The order parameters that measure synchronization of phases and frequencies are introduced and analyzed by means of dynamic simulations and finite-size scaling. Phase synchronization is observed to emerge in the presence of even a tiny fraction P of shortcuts and to display saturated behavior for P>~0.5. This indicates that the same synchronizability as the random network (P=1) can be achieved with relatively small number of shortcuts. The transient behavior of the synchronization, obtained from the measurement of the relaxation time, is also discussed.
Turbulence in small-world networks
NASA Astrophysics Data System (ADS)
Cosenza, M. G.; Tucci, K.
2002-03-01
The transition to turbulence via spatiotemporal intermittency is investigated in the context of coupled maps defined on small-world networks. The local dynamics is given by the Chaté-Manneville minimal map previously used in studies of spatiotemporal intermittency in ordered lattice. The critical boundary separating laminar and turbulent regimes is calculated on the parameter space of the system, given by the coupling strength and the rewiring probability of the network. Windows of relaminarization are present in some regions of the parameter space. New features arise in small-world networks; for instance, the character of the transition to turbulence changes from second-order to a first-order phase transition at some critical value of the rewiring probability. A linear relation characterizing the change in the order of the phase transition is found. The global quantity used as order parameter for the transition also exhibits nontrivial collective behavior for some values of the parameters. These models may describe several processes occurring in nonuniform media where the degree of disorder can be continuously varied through a parameter.
Laing, Carlo R.
2016-01-01
We consider a network of coupled excitatory and inhibitory theta neurons which is capable of supporting stable spatially-localized “bump” solutions. We randomly add long-range and simultaneously remove short-range connections within the network to form a small-world network and investigate the effects of this rewiring on the existence and stability of the bump solution. We consider two limits in which continuum equations can be derived; bump solutions are fixed points of these equations. We can thus use standard numerical bifurcation analysis to determine the stability of these bumps and to follow them as parameters (such as rewiring probabilities) are varied. We find that under some rewiring schemes bumps are quite robust, whereas in other schemes they can become unstable via Hopf bifurcation or even be destroyed in saddle-node bifurcations. PMID:27378897
A small world network of prime numbers
NASA Astrophysics Data System (ADS)
Chandra, Anjan Kumar; Dasgupta, Subinay
2005-11-01
According to Goldbach conjecture, any even number can be broken up as the sum of two prime numbers: n=p+q. We construct a network where each node is a prime number and corresponding to every even number n, we put a link between the component primes p and q. In most cases, an even number can be broken up in many ways, and then we chose one decomposition with a probability |p-q|α. Through computation of average shortest distance and clustering coefficient, we conclude that for α>-1.8 the network is of small world type and for α<-1.8 it is of regular type. We also present a theoretical justification for such behaviour.
Synchronous firings in small-world networks of excitable nodes
NASA Astrophysics Data System (ADS)
Gu, Weifeng; Liao, Xuhong; Zhang, Lisheng; Huang, Xuhui; Hu, Gang; Mi, Yuanyuan
2013-04-01
The phenomenon of synchronous firings is investigated in excitable small-world networks (ESWNs) of 2D lattices. Two sharply different types of patterns, wavelet turbulence (WT) patterns and synchronous firing (SF) patterns, and the associated transitions and hysteresis are found in wide parameter regions and in different excitable models. The WT state is maintained by wavelet defects while the SF state is due to iterative excitations between majority nodes and minority nodes where defects do not play essential roles. Moreover, a dominant phase-advanced driving method is applied to explain how self-sustained SFs can be maintained in ESWN and why SF and WT states show distinctive characteristic features. Since excitability of node and small-world network structure are two essential ingredients of some neural subsystems and SFs are important for many neural functions, the results in this paper are thus expected to be instructive for understanding the dynamics of some neural networks.
A new small-world network created by Cellular Automata
NASA Astrophysics Data System (ADS)
Ruan, Yuhong; Li, Anwei
2016-08-01
In this paper, we generate small-world networks by the Cellular Automaton based on starting with one-dimensional regular networks. Besides the common properties of small-world networks with small average shortest path length and large clustering coefficient, the small-world networks generated in this way have other properties: (i) The edges which are cut in the regular network can be controlled that whether the edges are reconnected or not, and (ii) the number of the edges of the small-world network model equals the number of the edges of the original regular network. In other words, the average degree of the small-world network model equals to the average degree of the original regular network.
Circulant Graph Modeling Deterministic Small-World Networks
NASA Astrophysics Data System (ADS)
Zhao, Chenggui
In recent years, many research works have revealed some technological networks including internet to be small-world networks, which is attracting attention from computer scientists. One can decide if or not a real network is Small-world by whether it has high local clustering and small average path distance which are the two distinguishing characteristics of small-world networks. So far, researchers have presented many small-world models by dynamically evolving a deterministic network into a small world one by stochastic adding vertices and edges to original networks. Rather few works focused on deterministic models. In this paper, as a important kind of Cayley graph, the circulant graph is proposed as models of deterministic small-world networks, thinking if its simple structures and significant adaptability. It shows circulant graph constructed in this document takes on the two expected characteristics of small word. This work should be useful because circulant graph has serviced as some models of communication and computer networks. The small world characteristic will be helpful to design and analysis of structure and performance.
Small-World Propensity and Weighted Brain Networks
Muldoon, Sarah Feldt; Bridgeford, Eric W.; Bassett, Danielle S.
2016-01-01
Quantitative descriptions of network structure can provide fundamental insights into the function of interconnected complex systems. Small-world structure, diagnosed by high local clustering yet short average path length between any two nodes, promotes information flow in coupled systems, a key function that can differ across conditions or between groups. However, current techniques to quantify small-worldness are density dependent and neglect important features such as the strength of network connections, limiting their application in real-world systems. Here, we address both limitations with a novel metric called the Small-World Propensity (SWP). In its binary instantiation, the SWP provides an unbiased assessment of small-world structure in networks of varying densities. We extend this concept to the case of weighted brain networks by developing (i) a standardized procedure for generating weighted small-world networks, (ii) a weighted extension of the SWP, and (iii) a method for mapping observed brain network data onto the theoretical model. In applying these techniques to compare real-world brain networks, we uncover the surprising fact that the canonical biological small-world network, the C. elegans neuronal network, has strikingly low SWP. These metrics, models, and maps form a coherent toolbox for the assessment and comparison of architectural properties in brain networks. PMID:26912196
Small-World Propensity and Weighted Brain Networks
NASA Astrophysics Data System (ADS)
Muldoon, Sarah Feldt; Bridgeford, Eric W.; Bassett, Danielle S.
2016-02-01
Quantitative descriptions of network structure can provide fundamental insights into the function of interconnected complex systems. Small-world structure, diagnosed by high local clustering yet short average path length between any two nodes, promotes information flow in coupled systems, a key function that can differ across conditions or between groups. However, current techniques to quantify small-worldness are density dependent and neglect important features such as the strength of network connections, limiting their application in real-world systems. Here, we address both limitations with a novel metric called the Small-World Propensity (SWP). In its binary instantiation, the SWP provides an unbiased assessment of small-world structure in networks of varying densities. We extend this concept to the case of weighted brain networks by developing (i) a standardized procedure for generating weighted small-world networks, (ii) a weighted extension of the SWP, and (iii) a method for mapping observed brain network data onto the theoretical model. In applying these techniques to compare real-world brain networks, we uncover the surprising fact that the canonical biological small-world network, the C. elegans neuronal network, has strikingly low SWP. These metrics, models, and maps form a coherent toolbox for the assessment and comparison of architectural properties in brain networks.
Small-World Network Spectra in Mean-Field Theory
NASA Astrophysics Data System (ADS)
Grabow, Carsten; Grosskinsky, Stefan; Timme, Marc
2012-05-01
Collective dynamics on small-world networks emerge in a broad range of systems with their spectra characterizing fundamental asymptotic features. Here we derive analytic mean-field predictions for the spectra of small-world models that systematically interpolate between regular and random topologies by varying their randomness. These theoretical predictions agree well with the actual spectra (obtained by numerical diagonalization) for undirected and directed networks and from fully regular to strongly random topologies. These results may provide analytical insights to empirically found features of dynamics on small-world networks from various research fields, including biology, physics, engineering, and social science.
Geometric assortative growth model for small-world networks.
Shang, Yilun
2014-01-01
It has been shown that both humanly constructed and natural networks are often characterized by small-world phenomenon and assortative mixing. In this paper, we propose a geometrically growing model for small-world networks. The model displays both tunable small-world phenomenon and tunable assortativity. We obtain analytical solutions of relevant topological properties such as order, size, degree distribution, degree correlation, clustering, transitivity, and diameter. It is also worth noting that the model can be viewed as a generalization for an iterative construction of Farey graphs. PMID:24578661
Geographical effect on small-world network synchronization
NASA Astrophysics Data System (ADS)
Yin, Chuan-Yang; Wang, Bing-Hong; Wang, Wen-Xu; Chen, Guan-Rong
2008-02-01
We investigate the geographical effect on the synchronization of small-world oscillator networks. We construct small-world geographical networks by randomly adding links to one- and two-dimensional regular lattices, and we find that the synchronizability is a nonmonotonic function of both the coupling strength and the geographical distance of randomly added shortcuts. Our findings demonstrate that the geographical effect plays an important role in network synchronization, which may shed some light on the study of collective dynamics of complex networks.
Characterization and control of small-world networks
NASA Astrophysics Data System (ADS)
Pandit, S. A.; Amritkar, R. E.
1999-08-01
Recently, Watts and Strogatz [Nature (London) 393, 440 (1998)] offered an interesting model of small-world networks. Here we concretize the concept of a ``faraway'' connection in a network by defining a far edge. Our definition is algorithmic and independent of any external parameters such as topology of the underlying space of the network. We show that it is possible to control the spread of an epidemic by using the knowledge of far edges. We also suggest a model for better product advertisement using the far edges. Our findings indicate that the number of far edges can be a good intrinsic parameter to characterize small-world phenomena.
Cascading failures of interdependent modular small-world networks
NASA Astrophysics Data System (ADS)
Zhu, Guowei; Wang, Xianpei; Tian, Meng; Dai, Dangdang; Long, Jiachuan; Zhang, Qilin
2016-07-01
Much empirical evidence shows that many real-world networks fall into the broad class of small-world networks and have a modular structure. The modularity has been revealed to have an important effect on cascading failure in isolated networks. However, the corresponding results for interdependent modular small-world networks remain missing. In this paper, we investigate the relationship between cascading failures and the intra-modular rewiring probabilities and inter-modular connections under different coupling preferences, i.e. random coupling with modules (RCWM), assortative coupling in modules (ACIM) and assortative coupling with modules (ACWM). The size of the largest connected component is used to evaluate the robustness from global and local perspectives. Numerical results indicate that increasing intra-modular rewiring probabilities and inter-modular connections can improve the robustness of interdependent modular small-world networks under intra-attacks and inter-attacks. Meanwhile, experiments on three coupling strategies demonstrate that ACIM has a better effect on preventing the cascading failures compared with RCWM and ACWM. These results can be helpful to allocate and optimize the topological structure of interdependent modular small-world networks to improve the robustness of such networks.
Distance Preferences Small-World Communication Topology for Agent Network
NASA Astrophysics Data System (ADS)
Wu, Zhengping; Wang, Renming
In multi-agent system (MAS), the communication topology of agent network plays a very important role in its collaboration. Small-world networks are the networks with high local clustering and small average path length, and the communication networks of MAS can be analyzed within the frame of small-world topology. Yet the real multiagent communication networks are abundant and the classical WS small-world model is not suitable for all cases. In this paper, two new small-world network models are presented. One is based on random graph substrate and local nodes preference reconnection and the other is based on regular graph substrate and long-range nodes preference reconnection. The characteristic of the network parameter such as the clustering coefficients, average path length, and eigenvalue λ2 and λn of the Laplacian matrix for these two models and WS model is studied. The consensus problem that based on these three models is also studied. An example is given and the conclusions are made in the end.
Is it really a small world - network connectivity revisited
NASA Astrophysics Data System (ADS)
Barzel, Baruch; Biham, Ofer
2010-03-01
Networks are useful for describing systems of interacting objects, the applications include chemical and metabolic systems, food webs as well as social networks. Lately, it was found that many of these networks display some common topological features, such as high clustering, small average path length and a power-law degree distribution. These topological features are commonly related to the network's functionality. However, the topology alone does not account for the nature of the interactions in the network and their strength. In this talk we will introduce a method for evaluating the correlations between pairs of nodes in the network. These correlations depend both on the topology and on the functionality of the network. A network with high connectivity displays strong correlations between its interacting nodes and thus features small-world functionality. The method can be used to obtain the correlation matrix or to evaluate the correlation function of the network. Certain networks display a typical correlation length. The connectivity of a network is then defined as the ratio between this correlation length and the average path length of the network. Using this method one can distinguish between a topological small world and a functional small world, where the latter is characterized by long range correlations and high connectivity. Clearly, networks which share the same topology, may have different connectivities, based on the nature and strength of their interactions.
Evolution to a small-world network with chaotic units
NASA Astrophysics Data System (ADS)
Gong, P.; van Leeuwen, C.
2004-07-01
We investigated the mutually supporting role of chaotic activity and evolving structure in a complex network. An initially randomly coupled network with chaotic activation is adaptively rewired according to dynamic coherence between its units. The evolving network reaches a small-world structure. Meanwhile, collective network activity tends to an intermittent dynamic clustering regime. Spontaneous chaotic activity and adaptively evolving structure jointly enhance signal propagation capacity.
Can recurrence networks show small-world property?
NASA Astrophysics Data System (ADS)
Jacob, Rinku; Harikrishnan, K. P.; Misra, R.; Ambika, G.
2016-08-01
Recurrence networks are complex networks, constructed from time series data, having several practical applications. Though their properties when constructed with the threshold value ɛ chosen at or just above the percolation threshold of the network are quite well understood, what happens as the threshold increases beyond the usual operational window is still not clear from a complex network perspective. The present Letter is focused mainly on the network properties at intermediate-to-large values of the recurrence threshold, for which no systematic study has been performed so far. We argue, with numerical support, that recurrence networks constructed from chaotic attractors with ɛ equal to the usual recurrence threshold or slightly above cannot, in general, show small-world property. However, if the threshold is further increased, the recurrence network topology initially changes to a small-world structure and finally to that of a classical random graph as the threshold approaches the size of the strange attractor.
A small-world network model of facial emotion recognition.
Takehara, Takuma; Ochiai, Fumio; Suzuki, Naoto
2016-01-01
Various models have been proposed to increase understanding of the cognitive basis of facial emotions. Despite those efforts, interactions between facial emotions have received minimal attention. If collective behaviours relating to each facial emotion in the comprehensive cognitive system could be assumed, specific facial emotion relationship patterns might emerge. In this study, we demonstrate that the frameworks of complex networks can effectively capture those patterns. We generate 81 facial emotion images (6 prototypes and 75 morphs) and then ask participants to rate degrees of similarity in 3240 facial emotion pairs in a paired comparison task. A facial emotion network constructed on the basis of similarity clearly forms a small-world network, which features an extremely short average network distance and close connectivity. Further, even if two facial emotions have opposing valences, they are connected within only two steps. In addition, we show that intermediary morphs are crucial for maintaining full network integration, whereas prototypes are not at all important. These results suggest the existence of collective behaviours in the cognitive systems of facial emotions and also describe why people can efficiently recognize facial emotions in terms of information transmission and propagation. For comparison, we construct three simulated networks--one based on the categorical model, one based on the dimensional model, and one random network. The results reveal that small-world connectivity in facial emotion networks is apparently different from those networks, suggesting that a small-world network is the most suitable model for capturing the cognitive basis of facial emotions. PMID:26315136
The Problem of Thresholding in Small-World Network Analysis
Langer, Nicolas; Pedroni, Andreas; Jäncke, Lutz
2013-01-01
Graph theory deterministically models networks as sets of vertices, which are linked by connections. Such mathematical representation of networks, called graphs are increasingly used in neuroscience to model functional brain networks. It was shown that many forms of structural and functional brain networks have small-world characteristics, thus, constitute networks of dense local and highly effective distal information processing. Motivated by a previous small-world connectivity analysis of resting EEG-data we explored implications of a commonly used analysis approach. This common course of analysis is to compare small-world characteristics between two groups using classical inferential statistics. This however, becomes problematic when using measures of inter-subject correlations, as it is the case in commonly used brain imaging methods such as structural and diffusion tensor imaging with the exception of fibre tracking. Since for each voxel, or region there is only one data point, a measure of connectivity can only be computed for a group. To empirically determine an adequate small-world network threshold and to generate the necessary distribution of measures for classical inferential statistics, samples are generated by thresholding the networks on the group level over a range of thresholds. We believe that there are mainly two problems with this approach. First, the number of thresholded networks is arbitrary. Second, the obtained thresholded networks are not independent samples. Both issues become problematic when using commonly applied parametric statistical tests. Here, we demonstrate potential consequences of the number of thresholds and non-independency of samples in two examples (using artificial data and EEG data). Consequently alternative approaches are presented, which overcome these methodological issues. PMID:23301043
Collective relaxation dynamics of small-world networks
NASA Astrophysics Data System (ADS)
Grabow, Carsten; Grosskinsky, Stefan; Kurths, Jürgen; Timme, Marc
2015-05-01
Complex networks exhibit a wide range of collective dynamic phenomena, including synchronization, diffusion, relaxation, and coordination processes. Their asymptotic dynamics is generically characterized by the local Jacobian, graph Laplacian, or a similar linear operator. The structure of networks with regular, small-world, and random connectivities are reasonably well understood, but their collective dynamical properties remain largely unknown. Here we present a two-stage mean-field theory to derive analytic expressions for network spectra. A single formula covers the spectrum from regular via small-world to strongly randomized topologies in Watts-Strogatz networks, explaining the simultaneous dependencies on network size N , average degree k , and topological randomness q . We present simplified analytic predictions for the second-largest and smallest eigenvalue, and numerical checks confirm our theoretical predictions for zero, small, and moderate topological randomness q , including the entire small-world regime. For large q of the order of one, we apply standard random matrix theory, thereby overarching the full range from regular to randomized network topologies. These results may contribute to our analytic and mechanistic understanding of collective relaxation phenomena of network dynamical systems.
Epidemiology Model on Shortcut and Small World Networks
NASA Astrophysics Data System (ADS)
Shanker, O.; Hogg, Tad
We show that the behavior of an epidemiology model depends sensitively on the shortcut density in the shortcut network. This is consistent with an earlier work on other processes on the shortcut network. We analytically study the reason for the sensitivity. The shortcut network is similar to the small world network, and it has the advantage that the model dependence on the shortcut density can be analytically studied. The model would be relevant to the spread of diseases in human, animal, plant or other populations, to the spread of viruses in computer networks, or to the spread of social contagion in social networks. It would also be relevant in understanding the variations in the load on routers connecting different computer networks, as the network topology gets extended by the addition of new links, and in analyzing the placement of certain special sensors in a sensor network laid out in a non-random way with some shortcut links.
Coherence Resonance of Small World Networks with Adaptive Coupling
NASA Astrophysics Data System (ADS)
Miyakawa, Kenji
2015-06-01
The phenomenon of coherence resonance (CR) in small world networks with adaptive coupling is investigated by modeling a real experimental situation with a photosensitive Belousov-Zhabotinsky reaction. We show that both spatial synchronization and temporal coherence of noise-induced firings can be considerably improved by adjusting control parameters, such as the degree of connectivity and the coupling strength. A small fraction of possible long-range connections is enough to obtain a great enhancement in CR.
Phase multistability in a dynamical small world network
Shabunin, A. V.
2015-01-15
The effect of phase multistability is explored in a small world network of periodic oscillators with diffusive couplings. The structure of the network represents a ring with additional non-local links, which spontaneously arise and vanish between arbitrary nodes. The dynamics of random couplings is modeled by “birth” and “death” stochastic processes by means of the cellular automate approach. The evolution of the network under gradual increasing of the number of random couplings goes through stages of phases fluctuations and spatial cluster formation. Finally, in the presence of non-local couplings the phase multistability “dies” and only the in-phase regime survives.
Phase multistability in a dynamical small world network.
Shabunin, A V
2015-01-01
The effect of phase multistability is explored in a small world network of periodic oscillators with diffusive couplings. The structure of the network represents a ring with additional non-local links, which spontaneously arise and vanish between arbitrary nodes. The dynamics of random couplings is modeled by "birth" and "death" stochastic processes by means of the cellular automate approach. The evolution of the network under gradual increasing of the number of random couplings goes through stages of phases fluctuations and spatial cluster formation. Finally, in the presence of non-local couplings the phase multistability "dies" and only the in-phase regime survives. PMID:25637920
Hawks and Doves on small-world networks
NASA Astrophysics Data System (ADS)
Tomassini, Marco; Luthi, Leslie; Giacobini, Mario
2006-01-01
We explore the Hawk-Dove game on networks with topologies ranging from regular lattices to random graphs with small-world networks in between. This is done by means of computer simulations using several update rules for the population evolutionary dynamics. We find the overall result that cooperation is sometimes inhibited and sometimes enhanced in those network structures, with respect to the mixing population case. The differences are due to different update rules and depend on the gain-to-cost ratio. We analyze and qualitatively explain this behavior by using local topological arguments.
Mandala Networks: ultra-small-world and highly sparse graphs
NASA Astrophysics Data System (ADS)
Sampaio Filho, Cesar I. N.; Moreira, André A.; Andrade, Roberto F. S.; Herrmann, Hans J.; Andrade, José S.
2015-03-01
The increasing demands in security and reliability of infrastructures call for the optimal design of their embedded complex networks topologies. The following question then arises: what is the optimal layout to fulfill best all the demands? Here we present a general solution for this problem with scale-free networks, like the Internet and airline networks. Precisely, we disclose a way to systematically construct networks which are robust against random failures. Furthermore, as the size of the network increases, its shortest path becomes asymptotically invariant and the density of links goes to zero, making it ultra-small world and highly sparse, respectively. The first property is ideal for communication and navigation purposes, while the second is interesting economically. Finally, we show that some simple changes on the original network formulation can lead to an improved topology against malicious attacks.
Mandala networks: ultra-small-world and highly sparse graphs.
Sampaio Filho, Cesar I N; Moreira, André A; Andrade, Roberto F S; Herrmann, Hans J; Andrade, José S
2015-01-01
The increasing demands in security and reliability of infrastructures call for the optimal design of their embedded complex networks topologies. The following question then arises: what is the optimal layout to fulfill best all the demands? Here we present a general solution for this problem with scale-free networks, like the Internet and airline networks. Precisely, we disclose a way to systematically construct networks which are robust against random failures. Furthermore, as the size of the network increases, its shortest path becomes asymptotically invariant and the density of links goes to zero, making it ultra-small world and highly sparse, respectively. The first property is ideal for communication and navigation purposes, while the second is interesting economically. Finally, we show that some simple changes on the original network formulation can lead to an improved topology against malicious attacks. PMID:25765450
Small-world property evaluated by exchanging network topology
NASA Astrophysics Data System (ADS)
Suzuki, Tomoya; Okazawa, Masayuki; Ohkura, Kuniaki
2015-03-01
The present study quantified the degree of the small-world (SW) property defined by Watts, and evaluated its achievement level to characterize complex networks. However, because this process has a combinatorial optimization problem, we applied the chaos neural network (CNN) and the simulated annealing (SA), and confirmed their performance in terms of optimized values and numerical costs. Next, we visualized the original network and its optimized networks whose SW property was maximized or minimized by exchanging the original network topology. As a result, although CNN and SA require huge computational time, we confirmed that they can evaluate the SW property and even real SW networks still have plenty of room to enlarge their own SW property.
Modular effects on epidemic dynamics in small-world networks
NASA Astrophysics Data System (ADS)
Zhao, H.; Gao, Z. Y.
2007-08-01
Many real-world networks are characterized by modular structure. In this letter, modular effects on epidemic spreading of susceptible-infected-refractory-susceptible (SIRS) model in small-world networks are investigated. Simulation results show that, together with the disorder of the inter-module connections and mean degree of the system the modular structure may affect the synchronization behavior in propagation. More importantly, it is found that the interplay between mean degree and modular structure may lead to a nonmonotone variation of the synchronization behavior in the system.
Corona graphs as a model of small-world networks
NASA Astrophysics Data System (ADS)
Lv, Qian; Yi, Yuhao; Zhang, Zhongzhi
2015-11-01
We introduce recursive corona graphs as a model of small-world networks. We investigate analytically the critical characteristics of the model, including order and size, degree distribution, average path length, clustering coefficient, and the number of spanning trees, as well as Kirchhoff index. Furthermore, we study the spectra for the adjacency matrix and the Laplacian matrix for the model. We obtain explicit results for all the quantities of the recursive corona graphs, which are similar to those observed in real-life networks.
Synchronization landscapes in small-world-connected computer networks
NASA Astrophysics Data System (ADS)
Guclu, Hasan
In this thesis we study synchronization phenomena in natural and artificial coupled multi-component systems, applicable to the scalability of parallel discrete-event simulation for systems with asynchronous dynamics. We also study the role of various complex communication topologies as synchronization networks. We analyze the properties of the virtual time horizon or synchronization landscape (corresponding to the progress of the processing elements) of these networks by using the framework of non-equilibrium surface growth. When the communication topology mimics that of the short-range interacting underlying system, the virtual time horizon exhibits Kardar-Parisi-Zhang-like kinetic roughening. Although the virtual times, oil average, progress at a nonzero rate, their statistical spread diverges with the number of processing elements, hindering efficient data collection. We show that when the synchronization topology is extended to include quenched random communication links (small-world links) between the processing elements, they make a close-to-uniform progress with a nonzero rate, without global synchronization. This leads to a fully scalable parallel simulation for underlying systems with asynchronous dynamics and short-range interactions. We study both short-range and small-world synchronization topologies in one- and two-dimensional systems. We also provide a coarse-grained description for the small-world-synchronized virtual-time horizon and compare the findings to those obtained by "simulating the simulations" based on the exact algorithmic rules. We also present numerical results for the evolution of the virtual-tithe horizon oil scale-free Barabasi-Albert networks serving as communication topology among the processing elements. Finally, we investigate to what extent small-world couplings (extending the original local relaxational dynamics through the random links) lead to the suppression of extreme fluctuations in the synchronization landscape. In the
Modeling Epidemics with Dynamic Small-World Networks
NASA Astrophysics Data System (ADS)
Kaski, Kimmo; Saramäki, Jari
2005-06-01
In this presentation a minimal model for describing the spreading of an infectious disease, such as influenza, is discussed. Here it is assumed that spreading takes place on a dynamic small-world network comprising short- and long-range infection events. Approximate equations for the epidemic threshold as well as the spreading dynamics are derived and they agree well with numerical discrete time-step simulations. Also the dependence of the epidemic saturation time on the initial conditions is analysed and a comparison with real-world data is made.
Epidemics with pathogen mutation on small-world networks
NASA Astrophysics Data System (ADS)
Shao, Zhi-Gang; Tan, Zhi-Jie; Zou, Xian-Wu; Jin, Zhun-Zhi
2006-05-01
We study the dynamical behavior of the epidemiological model with pathogen mutation on small-world networks, and discuss the influence of the immunity duration τR, the cross-immunity threshold hthr, and system size N on epidemic dynamics. A decaying oscillation occurs because of the interplay between the immune response and the pathogen mutation. These results have implications for the interpretation of longitudinal epidemiological data on strain abundance, and they will be helpful to assess the threat of highly pathogenic and mutative viruses, such as avian influenza.
Critical behavior of epidemic spreading in dynamic small world networks
NASA Astrophysics Data System (ADS)
Stone, Thomas; McKay, Susan
2010-03-01
Dynamic small-world (DSW) contact networks model populations that have fixed short range links but time varying stochastic long range links between individuals, such as in mobile populations. The measure of mobility is given by a parameter p that is directly analogous to the rewiring parameter in standard small-world networks. This study investigates the relative effects of vaccinations and avoidance of infected individuals in a susceptible-infected-recovered (SIR) epidemic model on a DSW network. We derive (1) the critical mobility required for an outbreak to occur as a function of the disease's infectivity, recovery rate, avoidance rate, and vaccination rate and (2) an expression to calculate the amount of vaccination and/or avoidance necessary to prevent the disease-free to endemic transition. Agreement between these calculated points and numerical simulation is excellent. We then show via finite size scaling that the transition is indeed a continuous phase transition and find the associated critical exponent. From this and other scaling relations at the critical point we can comment on the model's potential universality.
Growing Homophilic Networks Are Natural Navigable Small Worlds
Malkov, Yury A.; Ponomarenko, Alexander
2016-01-01
Navigability, an ability to find a logarithmically short path between elements using only local information, is one of the most fascinating properties of real-life networks. However, the exact mechanism responsible for the formation of navigation properties remained unknown. We show that navigability can be achieved by using only two ingredients present in the majority of networks: network growth and local homophily, giving a persuasive answer how the navigation appears in real-life networks. A very simple algorithm produces hierarchical self-similar optimally wired navigable small world networks with exponential degree distribution by using only local information. Adding preferential attachment produces a scale-free network which has shorter greedy paths, but worse (power law) scaling of the information extraction locality (algorithmic complexity of a search). Introducing saturation of the preferential attachment leads to truncated scale-free degree distribution that offers a good tradeoff between these parameters and can be useful for practical applications. Several features of the model are observed in real-life networks, in particular in the brain neural networks, supporting the earlier suggestions that they are navigable. PMID:27348120
Optimal transport in time-varying small-world networks
NASA Astrophysics Data System (ADS)
Chen, Qu; Qian, Jiang-Hai; Zhu, Liang; Han, Ding-Ding
2016-03-01
The time-order of interactions, which is regulated by some intrinsic activity, surely plays a crucial role regarding the transport efficiency of transportation systems. Here we study the optimal transport structure by measure of the length of time-respecting paths. Our network is built from a two-dimensional regular lattice, and long-range connections are allocated with probability Pi j˜rij -α , where ri j is the Manhattan distance. By assigning each shortcut an activity rate subjected to its geometric distance τi j˜rij -C , long-range links become active intermittently, leading to the time-varying dynamics. We show that for 0
Evolution of quantum strategies on a small-world network
NASA Astrophysics Data System (ADS)
Li, Q.; Iqbal, A.; Chen, M.; Abbott, D.
2012-11-01
In this paper, quantum strategies are introduced within evolutionary games in order to investigate the evolution of quantum strategies on a small-world network. Initially, certain quantum strategies are taken from the full quantum space at random and assigned to the agents who occupy the nodes of the network. Then, they play n-person quantum games with their neighbors according to the physical model of a quantum game. After the games are repeated a large number of times, a quantum strategy becomes the dominant strategy in the population, which is played by the majority of agents. However, if the number of strategies is increased, while the total number of agents remains constant, the dominant strategy almost disappears in the population because of an adverse environment, such as low fractions of agents with different strategies. On the contrary, if the total number of agents rises with the increase of the number of strategies, the dominant strategy re-emerges in the population. In addition, from results of the evolution, it can be found that the fractions of agents with the dominant strategy in the population decrease with the increase of the number of agents n in a n-person game independent of which game is employed. If both classical and quantum strategies evolve on the network, a quantum strategy can outperform the classical ones and prevail in the population.
Algebraic approach to small-world network models
NASA Astrophysics Data System (ADS)
Rudolph-Lilith, Michelle; Muller, Lyle E.
2014-01-01
We introduce an analytic model for directed Watts-Strogatz small-world graphs and deduce an algebraic expression of its defining adjacency matrix. The latter is then used to calculate the small-world digraph's asymmetry index and clustering coefficient in an analytically exact fashion, valid nonasymptotically for all graph sizes. The proposed approach is general and can be applied to all algebraically well-defined graph-theoretical measures, thus allowing for an analytical investigation of finite-size small-world graphs.
Phase Transitions in Some Epidemic Models Defined on Small-World Networks
NASA Astrophysics Data System (ADS)
Agiza, H. N.; Elgazzar, A. S.; Youssef, S. A.
Some modified versions of susceptible-infected-recovered-susceptible (SIRS) model are defined on small-world networks. Latency, incubation and variable susceptibility are separately included. Phase transitions in these models are studied. Then inhomogeneous models are introduced. In some cases, the application of the models to small-world networks is shown to increase the epidemic region.
NASA Astrophysics Data System (ADS)
Zhou, Guangye; Li, Chengren; Li, Tingting; Yang, Yi; Wang, Chen; He, Fangjun; Sun, Jingchang
2016-09-01
Some typical dual-ring erbium-doped fiber lasers with hyperchaos behaviors are taken as nodes to construct two kinds of small-world networks-NW and WS networks. Based on Lyapunov stability theorem, the appropriate controllers are designed and the outer synchronization between the small-world networks with diverse structures and different node numbers is further investigated. The simulation results show that the perfect synchronization between the complex small-world networks is realized, which is of potential application for all optical communication network.
Low-rank network decomposition reveals structural characteristics of small-world networks
NASA Astrophysics Data System (ADS)
Barranca, Victor J.; Zhou, Douglas; Cai, David
2015-12-01
Small-world networks occur naturally throughout biological, technological, and social systems. With their prevalence, it is particularly important to prudently identify small-world networks and further characterize their unique connection structure with respect to network function. In this work we develop a formalism for classifying networks and identifying small-world structure using a decomposition of network connectivity matrices into low-rank and sparse components, corresponding to connections within clusters of highly connected nodes and sparse interconnections between clusters, respectively. We show that the network decomposition is independent of node indexing and define associated bounded measures of connectivity structure, which provide insight into the clustering and regularity of network connections. While many existing network characterizations rely on constructing benchmark networks for comparison or fail to describe the structural properties of relatively densely connected networks, our classification relies only on the intrinsic network structure and is quite robust with respect to changes in connection density, producing stable results across network realizations. Using this framework, we analyze several real-world networks and reveal new structural properties, which are often indiscernible by previously established characterizations of network connectivity.
Self-Organized Criticality in Small-World Networks Based on the Social Balance Dynamics
NASA Astrophysics Data System (ADS)
Meng, Qing-Kuan
2011-11-01
A node model is proposed to study the self-organized criticality in the small-world networks which represent the social networks. Based on the node model and the social balance dynamics, the social networks are mapped to the thermodynamic systems and the phenomena are studied with physical methods. It is found that the avalanche in the small-world networks at the critical state satisfies the power-law distribution spatially and temporally.
The small world phenomenon and assortative mixing in Polish corporate board and director networks
NASA Astrophysics Data System (ADS)
Sankowska, Anna; Siudak, Dariusz
2016-02-01
This paper investigates the corporate board and director networks in the Polish capital market in 2014. We examined real board and director networks in comparison with networks that were randomly constructed. Through empirical analyses, we demonstrated that the real networks have the characteristics of small-world networks. In addition, the networks are assortative and highly clustered, which imposes certain behaviors on them.
From brain to earth and climate systems: Small-world interaction networks or not?
NASA Astrophysics Data System (ADS)
Bialonski, Stephan; Horstmann, Marie-Therese; Lehnertz, Klaus
2010-03-01
We consider recent reports on small-world topologies of interaction networks derived from the dynamics of spatially extended systems that are investigated in diverse scientific fields such as neurosciences, geophysics, or meteorology. With numerical simulations that mimic typical experimental situations, we have identified an important constraint when characterizing such networks: indications of a small-world topology can be expected solely due to the spatial sampling of the system along with the commonly used time series analysis based approaches to network characterization.
Scale-free networks which are highly assortative but not small world
NASA Astrophysics Data System (ADS)
Small, Michael; Xu, Xiaoke; Zhou, Jin; Zhang, Jie; Sun, Junfeng; Lu, Jun-An
2008-06-01
Uncorrelated scale-free networks are necessarily small world (and, in fact, smaller than small world). Nonetheless, for scale-free networks with correlated degree distribution this may not be the case. We describe a mechanism to generate highly assortative scale-free networks which are not small world. We show that it is possible to generate scale-free networks, with arbitrary degree exponent γ>1 , such that the average distance between nodes in the network is large. To achieve this, nodes are not added to the network with preferential attachment. Instead, we greedily optimize the assortativity of the network. The network generation scheme is physically motivated, and we show that the recently observed global network of Avian Influenza outbreaks arises through a mechanism similar to what we present here. Simulations show that this network exhibits very similar physical characteristics (very high assortativity, clustering, and path length).
Fractal and Small-World Networks Formed by Self-Organized Critical Dynamics
NASA Astrophysics Data System (ADS)
Watanabe, Akitomo; Mizutaka, Shogo; Yakubo, Kousuke
2015-11-01
We propose a dynamical model in which a network structure evolves in a self-organized critical (SOC) manner and explain a possible origin of the emergence of fractal and small-world networks. Our model combines a network growth and its decay by failures of nodes. The decay mechanism reflects the instability of large functional networks against cascading overload failures. It is demonstrated that the dynamical system surely exhibits SOC characteristics, such as power-law forms of the avalanche size distribution, the cluster size distribution, and the distribution of the time interval between intermittent avalanches. During the network evolution, fractal networks are spontaneously generated when networks experience critical cascades of failures that lead to a percolation transition. In contrast, networks far from criticality have small-world structures. We also observe the crossover behavior from fractal to small-world structure in the network evolution.
Storage capacity and retrieval time of small-world neural networks
Oshima, Hiraku; Odagaki, Takashi
2007-09-15
To understand the influence of structure on the function of neural networks, we study the storage capacity and the retrieval time of Hopfield-type neural networks for four network structures: regular, small world, random networks generated by the Watts-Strogatz (WS) model, and the same network as the neural network of the nematode Caenorhabditis elegans. Using computer simulations, we find that (1) as the randomness of network is increased, its storage capacity is enhanced; (2) the retrieval time of WS networks does not depend on the network structure, but the retrieval time of C. elegans's neural network is longer than that of WS networks; (3) the storage capacity of the C. elegans network is smaller than that of networks generated by the WS model, though the neural network of C. elegans is considered to be a small-world network.
Damage spreading in spatial and small-world random Boolean networks
NASA Astrophysics Data System (ADS)
Lu, Qiming; Teuscher, Christof
2014-02-01
The study of the response of complex dynamical social, biological, or technological networks to external perturbations has numerous applications. Random Boolean networks (RBNs) are commonly used as a simple generic model for certain dynamics of complex systems. Traditionally, RBNs are interconnected randomly and without considering any spatial extension and arrangement of the links and nodes. However, most real-world networks are spatially extended and arranged with regular, power-law, small-world, or other nonrandom connections. Here we explore the RBN network topology between extreme local connections, random small-world, and pure random networks, and study the damage spreading with small perturbations. We find that spatially local connections change the scaling of the Hamming distance at very low connectivities (K¯≪1) and that the critical connectivity of stability Ks changes compared to random networks. At higher K¯, this scaling remains unchanged. We also show that the Hamming distance of spatially local networks scales with a power law as the system size N increases, but with a different exponent for local and small-world networks. The scaling arguments for small-world networks are obtained with respect to the system sizes and strength of spatially local connections. We further investigate the wiring cost of the networks. From an engineering perspective, our new findings provide the key design trade-offs between damage spreading (robustness), the network's wiring cost, and the network's communication characteristics.
Comparative effects of avoidance and vaccination in disease spread on a dynamic small-world network
NASA Astrophysics Data System (ADS)
Stone, Thomas E.; Jones, Matthew M.; McKay, Susan R.
2010-12-01
Dynamic small-world contact networks have fixed short range links and time-varying stochastic long range links. They are used to model mobile populations or as minimal models for traditional small-world networks. Here we study the relative effects of vaccinations and avoidance of infected individuals in a susceptible-infected-recovered (SIR) epidemic model on a dynamic small-world network. We derive the critical mobility required for an outbreak to occur as a function of the disease’s infectivity, recovery rate, avoidance rate, and vaccination rate. We also derive an expression that allows us to calculate the amount of vaccination and/or avoidance necessary to prevent an epidemic. Calculated quantities show excellent agreement with simulations.
Chaotic burst synchronization in a two-small-world-layer neuronal network
NASA Astrophysics Data System (ADS)
Zheng, Yanhong; Wang, Haixia
2015-09-01
Chaotic burst synchronization in a two-small-world-layer neuronal network is studied in this paper. For a neuronal network coupled by two single-small-world-layer networks with link probability differences between layers, the two-layer network can achieve synchrony as the interlayer coupling strength increases. When chaotic layer network is coupled with chaotic-burst-synchronization layer network, the latter is dominant at small interlayer coupling strength, so it can make the layer with the irregular pattern show some regular and also exhibit the same pattern with the other layer. However, when chaotic layer is coupled with firing synchronization layer, the ordered layer is dominated by a disordered one with the interlayer coupling strength increasing. When the interlayer coupling strength is large enough, both networks are chaotic burst synchronization. Therefore, the synchronous states strongly depend on the interlayer coupling strength and the link probability. Moreover, the spatiotemporal pattern synchronization between the networks is robust to small noise.
Damage spreading in spatial and small-world random boolean networks
Lu, Qiming; Teuscher, Christof
2008-01-01
Random Boolean Networks (RBNs) are often used as generic models for certain dynamics of complex systems, ranging from social networks, neural networks, to gene or protein interaction networks. Traditionally, RBNs are interconnected randomly and without considering any spatial arrangement of the links and nodes. However, most real-world networks are spatially extended and arranged with regular, small-world, or other non-random connections. Here we explore the RBN network topology between extreme local connections, random small-world, and random networks, and study the damage spreading with small perturbations. We find that spatially local connections change the scaling of the relevant component at very low connectivities ({bar K} << 1) and that the critical connectivity of stability K{sub s} changes compared to random networks. At higher {bar K}, this scaling remains unchanged. We also show that the relevant component of spatially local networks scales with a power-law as the system size N increases, but with a different exponent for local and small-world networks. The scaling behaviors are obtained by finite-size scaling. We further investigate the wiring cost of the networks. From an engineering perspective, our new findings provide the key trade-offs between damage spreading (robustness), the network wiring cost, and the network's communication characteristics.
NASA Astrophysics Data System (ADS)
Walker, David M.; Allingham, David; Lee, Heung Wing Joseph; Small, Michael
2010-02-01
Small world network models have been effective in capturing the variable behaviour of reported case data of the SARS coronavirus outbreak in Hong Kong during 2003. Simulations of these models have previously been realized using informed “guesses” of the proposed model parameters and tested for consistency with the reported data by surrogate analysis. In this paper we attempt to provide statistically rigorous parameter distributions using Approximate Bayesian Computation sampling methods. We find that such sampling schemes are a useful framework for fitting parameters of stochastic small world network models where simulation of the system is straightforward but expressing a likelihood is cumbersome.
Renormalization and small-world model of fractal quantum repeater networks
Wei, Zong-Wen; Wang, Bing-Hong; Han, Xiao-Pu
2013-01-01
Quantum networks provide access to exchange of quantum information. The primary task of quantum networks is to distribute entanglement between remote nodes. Although quantum repeater protocol enables long distance entanglement distribution, it has been restricted to one-dimensional linear network. Here we develop a general framework that allows application of quantum repeater protocol to arbitrary quantum repeater networks with fractal structure. Entanglement distribution across such networks is mapped to renormalization. Furthermore, we demonstrate that logarithmical times of recursive such renormalization transformations can trigger fractal to small-world transition, where a scalable quantum small-world network is achieved. Our result provides new insight into quantum repeater theory towards realistic construction of large-scale quantum networks. PMID:23386977
Majority-vote model on a dynamic small-world network
NASA Astrophysics Data System (ADS)
Stone, Thomas E.; McKay, Susan R.
2015-02-01
Dynamic small-world networks combine short-range interactions within a fixed neighborhood with stochastic long-range interactions. The probability of a long-range link occurring instead of a short-range one is a measure of the mobility of a population. Here, the critical properties of the majority-vote model with noise on a two-dimensional dynamic small-world lattice are investigated via Monte Carlo simulation and finite size scaling analyses. We construct the order-disorder phase diagram and find the critical exponents associated with the continuous phase transition. Findings are consistent with previous results indicating that a model's transitions on static and dynamic small-world networks are in the same universality class.
Damage Spreading in Spatial and Small-world Random Boolean Networks
Lu, Qiming; Teuscher, Christof
2014-02-18
The study of the response of complex dynamical social, biological, or technological networks to external perturbations has numerous applications. Random Boolean Networks (RBNs) are commonly used a simple generic model for certain dynamics of complex systems. Traditionally, RBNs are interconnected randomly and without considering any spatial extension and arrangement of the links and nodes. However, most real-world networks are spatially extended and arranged with regular, power-law, small-world, or other non-random connections. Here we explore the RBN network topology between extreme local connections, random small-world, and pure random networks, and study the damage spreading with small perturbations. We find that spatially local connections change the scaling of the relevant component at very low connectivities ($\\bar{K} \\ll 1$) and that the critical connectivity of stability $K_s$ changes compared to random networks. At higher $\\bar{K}$, this scaling remains unchanged. We also show that the relevant component of spatially local networks scales with a power-law as the system size N increases, but with a different exponent for local and small-world networks. The scaling behaviors are obtained by finite-size scaling. We further investigate the wiring cost of the networks. From an engineering perspective, our new findings provide the key design trade-offs between damage spreading (robustness), the network's wiring cost, and the network's communication characteristics.
GENERAL: Complete and phase synchronization in a heterogeneous small-world neuronal network
NASA Astrophysics Data System (ADS)
Han, Fang; Lu, Qi-Shao; Wiercigroch, Marian; Ji, Quan-Bao
2009-02-01
Synchronous firing of neurons is thought to be important for information communication in neuronal networks. This paper investigates the complete and phase synchronization in a heterogeneous small-world chaotic Hindmarsh-Rose neuronal network. The effects of various network parameters on synchronization behaviour are discussed with some biological explanations. Complete synchronization of small-world neuronal networks is studied theoretically by the master stability function method. It is shown that the coupling strength necessary for complete or phase synchronization decreases with the neuron number, the node degree and the connection density are increased. The effect of heterogeneity of neuronal networks is also considered and it is found that the network heterogeneity has an adverse effect on synchrony.
Extraction of Network Topology From Multi-Electrode Recordings: Is there a Small-World Effect?
Gerhard, Felipe; Pipa, Gordon; Lima, Bruss; Neuenschwander, Sergio; Gerstner, Wulfram
2011-01-01
The simultaneous recording of the activity of many neurons poses challenges for multivariate data analysis. Here, we propose a general scheme of reconstruction of the functional network from spike train recordings. Effective, causal interactions are estimated by fitting generalized linear models on the neural responses, incorporating effects of the neurons’ self-history, of input from other neurons in the recorded network and of modulation by an external stimulus. The coupling terms arising from synaptic input can be transformed by thresholding into a binary connectivity matrix which is directed. Each link between two neurons represents a causal influence from one neuron to the other, given the observation of all other neurons from the population. The resulting graph is analyzed with respect to small-world and scale-free properties using quantitative measures for directed networks. Such graph-theoretic analyses have been performed on many complex dynamic networks, including the connectivity structure between different brain areas. Only few studies have attempted to look at the structure of cortical neural networks on the level of individual neurons. Here, using multi-electrode recordings from the visual system of the awake monkey, we find that cortical networks lack scale-free behavior, but show a small, but significant small-world structure. Assuming a simple distance-dependent probabilistic wiring between neurons, we find that this connectivity structure can account for all of the networks’ observed small-world ness. Moreover, for multi-electrode recordings the sampling of neurons is not uniform across the population. We show that the small-world-ness obtained by such a localized sub-sampling overestimates the strength of the true small-world structure of the network. This bias is likely to be present in all previous experiments based on multi-electrode recordings. PMID:21344015
Evolving Apollonian networks with small-world scale-free topologies
NASA Astrophysics Data System (ADS)
Zhang, Zhongzhi; Rong, Lili; Zhou, Shuigeng
2006-10-01
We propose two types of evolving networks: evolutionary Apollonian networks (EANs) and general deterministic Apollonian networks (GDANs), established by simple iteration algorithms. We investigate the two networks by both simulation and theoretical prediction. Analytical results show that both networks follow power-law degree distributions, with distribution exponents continuously tuned from 2 to 3. The accurate expression of clustering coefficient is also given for both networks. Moreover, the investigation of the average path length of EAN and the diameter of GDAN reveals that these two types of networks possess small-world feature. In addition, we study the collective synchronization behavior on some limitations of the EAN.
A small-world and scale-free network generated by Sierpinski Pentagon
NASA Astrophysics Data System (ADS)
Chen, Jin; Le, Anbo; Wang, Qin; Xi, Lifeng
2016-05-01
The Sierpinski Pentagon is used to construct evolving networks, whose nodes are all solid regular pentagons in the construction of the Sierpinski Pentagon up to the stage t and any two nodes are neighbors if and only if the intersection of corresponding pentagons is non-empty and non-singleton. We show that such networks have the small-world and scale-free effects, but are not fractal scaling.
NASA Astrophysics Data System (ADS)
Yu, Haitao; Guo, Xinmeng; Wang, Jiang; Deng, Bin; Wei, Xile
2015-10-01
The phenomenon of vibrational resonance is investigated in adaptive Newman-Watts small-world neuronal networks, where the strength of synaptic connections between neurons is modulated based on spike-timing-dependent plasticity. Numerical results demonstrate that there exists appropriate amplitude of high-frequency driving which is able to optimize the neural ensemble response to the weak low-frequency periodic signal. The effect of networked vibrational resonance can be significantly affected by spike-timing-dependent plasticity. It is shown that spike-timing-dependent plasticity with dominant depression can always improve the efficiency of vibrational resonance, and a small adjusting rate can promote the transmission of weak external signal in small-world neuronal networks. In addition, the network topology plays an important role in the vibrational resonance in spike-timing-dependent plasticity-induced neural systems, where the system response to the subthreshold signal is maximized by an optimal network structure. Furthermore, it is demonstrated that the introduction of inhibitory synapses can considerably weaken the phenomenon of vibrational resonance in the hybrid small-world neuronal networks with spike-timing-dependent plasticity.
Self-organizing Ising model of artificial financial markets with small-world network topology
NASA Astrophysics Data System (ADS)
Zhao, Haijie; Zhou, Jie; Zhang, Anghui; Su, Guifeng; Zhang, Yi
2013-01-01
We study a self-organizing Ising-like model of artificial financial markets with underlying small-world (SW) network topology. The asset price dynamics results from the collective decisions of interacting agents which are located on a small-world complex network (the nodes symbolize the agents of a financial market). The model incorporates the effects of imitation, the impact of external news and private information. We also investigate the influence of different network topologies, from regular lattice to random graph, on the asset price dynamics by adjusting the probability of the rewiring procedure. We find that a specific combination of model parameters reproduce main stylized facts of real-world financial markets.
A small-world network derived from the deterministic uniform recursive tree by line graph operation
NASA Astrophysics Data System (ADS)
Hou, Pengfeng; Zhao, Haixing; Mao, Yaping; Wang, Zhao
2016-03-01
The deterministic uniform recursive tree ({DURT}) is one of the deterministic versions of the uniform recursive tree ({URT}). Zhang et al (2008 Eur. Phys. J. B 63 507-13) studied the properties of DURT, including its topological characteristics and spectral properties. Although DURT shows a logarithmic scaling with the size of the network, DURT is not a small-world network since its clustering coefficient is zero. Lu et al (2012 Physica A 391 87-92) proposed a deterministic small-world network by adding some edges with a simple rule in each DURT iteration. In this paper, we intoduce a method for constructing a new deterministic small-world network by the line graph operation in each DURT iteration. The line graph operation brings about cliques at each node of the previous given graph, and the resulting line graph possesses larger clustering coefficients. On the other hand, this operation can decrease the diameter at almost one, then giving the analytic solutions to several topological characteristics of the model proposed. Supported by The Ministry of Science and Technology 973 project (No. 2010C B334708); National Science Foundation of China (Nos. 61164005, 11161037, 11101232, 11461054, 11551001); The Ministry of education scholars and innovation team support plan of Yangtze River (No. IRT1068); Qinghai Province Nature Science Foundation Project (Nos. 2012-Z-943, 2014-ZJ-907).
Altered Small-World Brain Networks in Schizophrenia Patients during Working Memory Performance
He, Hao; Sui, Jing; Yu, Qingbao; Turner, Jessica A.; Ho, Beng-Choon; Sponheim, Scott R.; Manoach, Dara S.; Clark, Vincent P.; Calhoun, Vince D.
2012-01-01
Impairment of working memory (WM) performance in schizophrenia patients (SZ) is well-established. Compared to healthy controls (HC), SZ patients show aberrant blood oxygen level dependent (BOLD) activations and disrupted functional connectivity during WM performance. In this study, we examined the small-world network metrics computed from functional magnetic resonance imaging (fMRI) data collected as 35 HC and 35 SZ performed a Sternberg Item Recognition Paradigm (SIRP) at three WM load levels. Functional connectivity networks were built by calculating the partial correlation on preprocessed time courses of BOLD signal between task-related brain regions of interest (ROIs) defined by group independent component analysis (ICA). The networks were then thresholded within the small-world regime, resulting in undirected binarized small-world networks at different working memory loads. Our results showed: 1) at the medium WM load level, the networks in SZ showed a lower clustering coefficient and less local efficiency compared with HC; 2) in SZ, most network measures altered significantly as the WM load level increased from low to medium and from medium to high, while the network metrics were relatively stable in HC at different WM loads; and 3) the altered structure at medium WM load in SZ was related to their performance during the task, with longer reaction time related to lower clustering coefficient and lower local efficiency. These findings suggest brain connectivity in patients with SZ was more diffuse and less strongly linked locally in functional network at intermediate level of WM when compared to HC. SZ show distinctly inefficient and variable network structures in response to WM load increase, comparing to stable highly clustered network topologies in HC. PMID:22701611
Phase Transitions of an Epidemic Spreading Model in Small-World Networks
NASA Astrophysics Data System (ADS)
Hua, Da-Yin; Gao, Ke
2011-06-01
We propose a modified susceptible-infected-refractory-susceptible (SIRS) model to investigate the global oscillations of the epidemic spreading in Watts—Strogatz (WS) small-world networks. It is found that when an individual immunity does not change or decays slowly in an immune period, the system can exhibit complex transition from an infecting stationary state to a large amplitude sustained oscillation or an absorbing state with no infection. When the immunity decays rapidly in the immune period, the transition to the global oscillation disappears and there is no oscillation. Furthermore, based on the spatio-temporal evolution patterns and the phase diagram, it is disclosed that a long immunity period takes an important role in the emergence of the global oscillation in small-world networks.
Spatial prisoner's dilemma game with volunteering in Newman-Watts small-world networks
NASA Astrophysics Data System (ADS)
Wu, Zhi-Xi; Xu, Xin-Jian; Chen, Yong; Wang, Ying-Hai
2005-03-01
A modified spatial prisoner’s dilemma game with voluntary participation in Newman-Watts small-world networks is studied. Some reasonable ingredients are introduced to the game evolutionary dynamics: each agent in the network is a pure strategist and can only take one of three strategies (cooperator, defector, and loner); its strategical transformation is associated with both the number of strategical states and the magnitude of average profits, which are adopted and acquired by its coplayers in the previous round of play; a stochastic strategy mutation is applied when it gets into the trouble of local commons that the agent and its neighbors are in the same state and get the same average payoffs. In the case of very low temptation to defect, it is found that agents are willing to participate in the game in typical small-world region and intensive collective oscillations arise in more random region.
An Epidemic Model on Small-World Networks and Ring Vaccination
NASA Astrophysics Data System (ADS)
Ahmed, E.; Hegazi, A. S.; Elgazzar, A. S.
A modified version of susceptible-infected-recovered-susceptible (SIRS) model for the outbreaks of foot-and-mouth disease (FMD) is introduced. The model is defined on small-world networks, and a ring vaccination programme is included. This model can be a theoretical explanation for the nonlocal interactions in epidemic spreading. Ring vaccination is capable of eradicating FMD provided that the probability of infection is high enough. Also an analytical approximation for this model is studied.
Trapping on Weighted Tetrahedron Koch Networks with Small-World Property
NASA Astrophysics Data System (ADS)
Dai, Meifeng; Xie, Qi; Xi, Lifeng
2013-04-01
In this paper, we present weighted tetrahedron Koch networks depending on a weight factor. According to their self-similar construction, we obtain the analytical expressions of the weighted clustering coefficient and average weighted shortest path (AWSP). The obtained solutions show that the weighted tetrahedron Koch networks exhibits small-world property. Then, we calculate the average receiving time (ART) on weighted-dependent walks, which is the sum of mean first-passage times (MFPTs) for all nodes absorpt at the trap located at a hub node. We find that the ART exhibits a sublinear or linear dependence on network order.
Chaotic phase synchronization in small-world networks of bursting neurons
NASA Astrophysics Data System (ADS)
Yu, Haitao; Wang, Jiang; Deng, Bin; Wei, Xile; Wong, Y. K.; Chan, W. L.; Tsang, K. M.; Yu, Ziqi
2011-03-01
We investigate the chaotic phase synchronization in a system of coupled bursting neurons in small-world networks. A transition to mutual phase synchronization takes place on the bursting time scale of coupled oscillators, while on the spiking time scale, they behave asynchronously. It is shown that phase synchronization is largely facilitated by a large fraction of shortcuts, but saturates when it exceeds a critical value. We also study the external chaotic phase synchronization of bursting oscillators in the small-world network by a periodic driving signal applied to a single neuron. It is demonstrated that there exists an optimal small-world topology, resulting in the largest peak value of frequency locking interval in the parameter plane, where bursting synchronization is maintained, even with the external driving. The width of this interval increases with the driving amplitude, but decrease rapidly with the network size. We infer that the externally applied driving parameters outside the frequency locking region can effectively suppress pathologically synchronized rhythms of bursting neurons in the brain.
Neural progenitors organize in small-world networks to promote cell proliferation
Malmersjö, Seth; Rebellato, Paola; Smedler, Erik; Planert, Henrike; Kanatani, Shigeaki; Liste, Isabel; Nanou, Evanthia; Sunner, Hampus; Abdelhady, Shaimaa; Zhang, Songbai; Andäng, Michael; El Manira, Abdeljabbar; Silberberg, Gilad; Arenas, Ernest; Uhlén, Per
2013-01-01
Coherent network activity among assemblies of interconnected cells is essential for diverse functions in the adult brain. However, cellular networks before formations of chemical synapses are poorly understood. Here, embryonic stem cell-derived neural progenitors were found to form networks exhibiting synchronous calcium ion (Ca2+) activity that stimulated cell proliferation. Immature neural cells established circuits that propagated electrical signals between neighboring cells, thereby activating voltage-gated Ca2+ channels that triggered Ca2+ oscillations. These network circuits were dependent on gap junctions, because blocking prevented electrotonic transmission both in vitro and in vivo. Inhibiting connexin 43 gap junctions abolished network activity, suppressed proliferation, and affected embryonic cortical layer formation. Cross-correlation analysis revealed highly correlated Ca2+ activities in small-world networks that followed a scale-free topology. Graph theory predicts that such network designs are effective for biological systems. Taken together, these results demonstrate that immature cells in the developing brain organize in small-world networks that critically regulate neural progenitor proliferation. PMID:23576737
Phase synchronization of bursting neurons in clustered small-world networks
NASA Astrophysics Data System (ADS)
Batista, C. A. S.; Lameu, E. L.; Batista, A. M.; Lopes, S. R.; Pereira, T.; Zamora-López, G.; Kurths, J.; Viana, R. L.
2012-07-01
We investigate the collective dynamics of bursting neurons on clustered networks. The clustered network model is composed of subnetworks, each of them presenting the so-called small-world property. This model can also be regarded as a network of networks. In each subnetwork a neuron is connected to other ones with regular as well as random connections, the latter with a given intracluster probability. Moreover, in a given subnetwork each neuron has an intercluster probability to be connected to the other subnetworks. The local neuron dynamics has two time scales (fast and slow) and is modeled by a two-dimensional map. In such small-world network the neuron parameters are chosen to be slightly different such that, if the coupling strength is large enough, there may be synchronization of the bursting (slow) activity. We give bounds for the critical coupling strength to obtain global burst synchronization in terms of the network structure, that is, the probabilities of intracluster and intercluster connections. We find that, as the heterogeneity in the network is reduced, the network global synchronizability is improved. We show that the transitions to global synchrony may be abrupt or smooth depending on the intercluster probability.
Phase transitions in small-world systems: application to functional brain networks
NASA Astrophysics Data System (ADS)
Gadjiev, B. R.; Progulova, T. B.
2015-04-01
In the present paper the problem of symmetry breaking in the systems with a small- world property is considered. The obtained results are applied to the description of the functional brain networks. Origin of the entropy of fractal and multifractal small-world systems is discussed. Applying the maximum entropy principle the topology of these networks has been determined. The symmetry of the regular subgroup of a small-world system is described by a discrete subgroup of the Galilean group. The algorithm of determination of this group and transformation properties of the order parameter have been proposed. The integer basis of the irreducible representation is constructed and a free energy functional is introduced. It has been shown that accounting the presence of random connections leads to an integro- differential equation for the order parameter. For q-exponential distributions an equation of motion for the order parameter takes the form of a fractional differential equation. We consider the system that is described by a two-component order parameter and discuss the features of the spatial distribution of solutions.
Effects of immunity on global oscillations in epidemic spreading in small-world networks
NASA Astrophysics Data System (ADS)
Gao, Ke; Hua, Da-yin
2010-08-01
Considering a decay of an individual immunity, we investigated a susceptible-infectedrefractory-susceptible (SIRS) model in Watts-Strogatz (WS) small-word networks. It is found that when an individual immunity does not change or decays slowly in an immune period, the system can exhibit a transition from a stationary state to a large amplitude sustained oscillation. When the immunity decays rapidly in the immune period, the transition disappears and there is no oscillation. Furthermore, based on the spatio-temporal evolution patterns, it is disclosed that a long immunity period takes an important role in the emergence of the global oscillation in small world networks.
Synchronization of Coupled Oscillators on Newman Watts Small-World Networks
NASA Astrophysics Data System (ADS)
Guan, Jian-Yue; Xu, Xin-Jian; Wu, Zhi-Xi; Wang, Ying-Hai
2006-06-01
We investigate the collection behaviour of coupled phase oscillators on Newman-Watts small-world networks in one and two dimensions. Each component of the network is assumed as an oscillator and each interacts with the others following the Kuramoto model. We then study the onset of global synchronization of phases and frequencies based on dynamic simulations and finite-size scaling. Both the phase and frequency synchronization are observed to emerge in the presence of a tiny fraction of shortcuts and enhanced with the increases of nearest neighbours and lattice dimensions.
Excitement and synchronization of small-world neuronal networks with short-term synaptic plasticity.
Han, Fang; Wiercigroch, Marian; Fang, Jian-An; Wang, Zhijie
2011-10-01
Excitement and synchronization of electrically and chemically coupled Newman-Watts (NW) small-world neuronal networks with a short-term synaptic plasticity described by a modified Oja learning rule are investigated. For each type of neuronal network, the variation properties of synaptic weights are examined first. Then the effects of the learning rate, the coupling strength and the shortcut-adding probability on excitement and synchronization of the neuronal network are studied. It is shown that the synaptic learning suppresses the over-excitement, helps synchronization for the electrically coupled network but impairs synchronization for the chemically coupled one. Both the introduction of shortcuts and the increase of the coupling strength improve synchronization and they are helpful in increasing the excitement for the chemically coupled network, but have little effect on the excitement of the electrically coupled one. PMID:21956933
Laplacian spectra of a class of small-world networks and their applications
Liu, Hongxiao; Dolgushev, Maxim; Qi, Yi; Zhang, Zhongzhi
2015-01-01
One of the most crucial domains of interdisciplinary research is the relationship between the dynamics and structural characteristics. In this paper, we introduce a family of small-world networks, parameterized through a variable d controlling the scale of graph completeness or of network clustering. We study the Laplacian eigenvalues of these networks, which are determined through analytic recursive equations. This allows us to analyze the spectra in depth and to determine the corresponding spectral dimension. Based on these results, we consider the networks in the framework of generalized Gaussian structures, whose physical behavior is exemplified on the relaxation dynamics and on the fluorescence depolarization under quasiresonant energy transfer. Although the networks have the same number of nodes (beads) and edges (springs) as the dual Sierpinski gaskets, they display rather different dynamic behavior. PMID:25762195
Fractional diffusion on circulant networks: emergence of a dynamical small world
NASA Astrophysics Data System (ADS)
Riascos, A. P.; Mateos, José L.
2015-07-01
In this paper, we study fractional random walks on networks defined from the equivalent of the fractional diffusion equation in graphs. We explore this process analytically in circulant networks; in particular, interacting cycles and limit cases such as a ring and a complete graph. From the spectra and the eigenvectors of the Laplacian matrix, we deduce explicit results for different quantities that characterize this dynamical process. We obtain analytical expressions for the fractional transition matrix, the fractional degrees and the average probability of return of the random walker. Also, we discuss the Kemeny constant, which gives the average number of steps necessary to reach any site of the network. Throughout this work, we analyze the mechanisms behind fractional transport on circulant networks and how this long-range process dynamically induces the small-world property in different structures.
Heterogeneous delay-induced asynchrony and resonance in a small-world neuronal network system
NASA Astrophysics Data System (ADS)
Yu, Wen-Ting; Tang, Jun; Ma, Jun; Yang, Xianqing
2016-06-01
A neuronal network often involves time delay caused by the finite signal propagation time in a given biological network. This time delay is not a homogenous fluctuation in a biological system. The heterogeneous delay-induced asynchrony and resonance in a noisy small-world neuronal network system are numerically studied in this work by calculating synchronization measure and spike interval distribution. We focus on three different delay conditions: double-values delay, triple-values delay, and Gaussian-distributed delay. Our results show the following: 1) the heterogeneity in delay results in asynchronous firing in the neuronal network, and 2) maximum synchronization could be achieved through resonance given that the delay values are integer or half-integer times of each other.
Abe, Jun; Bomze, David; Cremasco, Viviana; Scandella, Elke; Stein, Jens V.; Turley, Shannon J.; Ludewig, Burkhard
2016-01-01
Fibroblastic reticular cells (FRCs) form the cellular scaffold of lymph nodes (LNs) and establish distinct microenvironmental niches to provide key molecules that drive innate and adaptive immune responses and control immune regulatory processes. Here, we have used a graph theory-based systems biology approach to determine topological properties and robustness of the LN FRC network in mice. We found that the FRC network exhibits an imprinted small-world topology that is fully regenerated within 4 wk after complete FRC ablation. Moreover, in silico perturbation analysis and in vivo validation revealed that LNs can tolerate a loss of approximately 50% of their FRCs without substantial impairment of immune cell recruitment, intranodal T cell migration, and dendritic cell-mediated activation of antiviral CD8+ T cells. Overall, our study reveals the high topological robustness of the FRC network and the critical role of the network integrity for the activation of adaptive immune responses. PMID:27415420
Impact of mobility structure on optimization of small-world networks of mobile agents
NASA Astrophysics Data System (ADS)
Lee, Eun; Holme, Petter
2016-06-01
In ad hoc wireless networking, units are connected to each other rather than to a central, fixed, infrastructure. Constructing and maintaining such networks create several trade-off problems between robustness, communication speed, power consumption, etc., that bridges engineering, computer science and the physics of complex systems. In this work, we address the role of mobility patterns of the agents on the optimal tuning of a small-world type network construction method. By this method, the network is updated periodically and held static between the updates. We investigate the optimal updating times for different scenarios of the movement of agents (modeling, for example, the fat-tailed trip distances, and periodicities, of human travel). We find that these mobility patterns affect the power consumption in non-trivial ways and discuss how these effects can best be handled.
Integration of neuroblasts into a two-dimensional small world neuronal network
NASA Astrophysics Data System (ADS)
Schneider-Mizell, Casey; Zochowski, Michal; Sander, Leonard
2009-03-01
Neurogenesis in the adult brain has been suggested to be important for learning and functional robustness to the neuronal death. New neurons integrate themselves into existing neuronal networks by moving into a target destination, extending axonal and dendritic processes, and inducing synaptogenesis to connect to active neurons. We hypothesize that increased plasticity of the network to novel stimuli can arise from activity-dependent cell and process motility rules. In complement to a similar in vitro model, we investigate a computational model of a two-dimensional small world network of integrate and fire neurons. After steady-state activity is reached in the extant network, we introduce new neurons which move, stop, and connect themselves through rules governed by position and firing rate.
Effects of channel noise on firing coherence of small-world Hodgkin-Huxley neuronal networks
NASA Astrophysics Data System (ADS)
Sun, X. J.; Lei, J. Z.; Perc, M.; Lu, Q. S.; Lv, S. J.
2011-01-01
We investigate the effects of channel noise on firing coherence of Watts-Strogatz small-world networks consisting of biophysically realistic HH neurons having a fraction of blocked voltage-gated sodium and potassium ion channels embedded in their neuronal membranes. The intensity of channel noise is determined by the number of non-blocked ion channels, which depends on the fraction of working ion channels and the membrane patch size with the assumption of homogeneous ion channel density. We find that firing coherence of the neuronal network can be either enhanced or reduced depending on the source of channel noise. As shown in this paper, sodium channel noise reduces firing coherence of neuronal networks; in contrast, potassium channel noise enhances it. Furthermore, compared with potassium channel noise, sodium channel noise plays a dominant role in affecting firing coherence of the neuronal network. Moreover, we declare that the observed phenomena are independent of the rewiring probability.
Novkovic, Mario; Onder, Lucas; Cupovic, Jovana; Abe, Jun; Bomze, David; Cremasco, Viviana; Scandella, Elke; Stein, Jens V; Bocharov, Gennady; Turley, Shannon J; Ludewig, Burkhard
2016-07-01
Fibroblastic reticular cells (FRCs) form the cellular scaffold of lymph nodes (LNs) and establish distinct microenvironmental niches to provide key molecules that drive innate and adaptive immune responses and control immune regulatory processes. Here, we have used a graph theory-based systems biology approach to determine topological properties and robustness of the LN FRC network in mice. We found that the FRC network exhibits an imprinted small-world topology that is fully regenerated within 4 wk after complete FRC ablation. Moreover, in silico perturbation analysis and in vivo validation revealed that LNs can tolerate a loss of approximately 50% of their FRCs without substantial impairment of immune cell recruitment, intranodal T cell migration, and dendritic cell-mediated activation of antiviral CD8+ T cells. Overall, our study reveals the high topological robustness of the FRC network and the critical role of the network integrity for the activation of adaptive immune responses. PMID:27415420
Quantification of degeneracy in Hodgkin-Huxley neurons on Newman-Watts small world network.
Man, Menghua; Zhang, Ya; Ma, Guilei; Friston, Karl; Liu, Shanghe
2016-08-01
Degeneracy is a fundamental source of biological robustness, complexity and evolvability in many biological systems. However, degeneracy is often confused with redundancy. Furthermore, the quantification of degeneracy has not been addressed for realistic neuronal networks. The objective of this paper is to characterize degeneracy in neuronal network models via quantitative mathematic measures. Firstly, we establish Hodgkin-Huxley neuronal networks with Newman-Watts small world network architectures. Secondly, in order to calculate the degeneracy, redundancy and complexity in the ensuing networks, we use information entropy to quantify the information a neuronal response carries about the stimulus - and mutual information to measure the contribution of each subset of the neuronal network. Finally, we analyze the interdependency of degeneracy, redundancy and complexity - and how these three measures depend upon network architectures. Our results suggest that degeneracy can be applied to any neuronal network as a formal measure, and degeneracy is distinct from redundancy. Qualitatively degeneracy and complexity are more highly correlated over different network architectures, in comparison to redundancy. Quantitatively, the relationship between both degeneracy and redundancy depends on network coupling strength: both degeneracy and redundancy increase with complexity for small coupling strengths; however, as coupling strength increases, redundancy decreases with complexity (in contrast to degeneracy, which is relatively invariant). These results suggest that the degeneracy is a general topologic characteristic of neuronal networks, which could be applied quantitatively in neuroscience and connectomics. PMID:27155043
Ordering spatiotemporal chaos in discrete neural networks with small-world connections
NASA Astrophysics Data System (ADS)
Wei, Du Qu; Shu Luo, Xiao
2007-06-01
We investigate ordering of spatiotemporal chaos in two-dimensional map neuron (2DMN) networks with small-world (SW) connections, in which each neuron exhibits chaotic spiking-bursting behavior, focusing on the dependence of the spatiotemporal evolution on the topological randomness p. It is found that as the randomness p is increased, the chaotic spiking bursts become appreciably and more and more synchronized in space and coherent in time, and the maximal spatiotemporal order appears at a particular value of randomness p. However, if the randomness p is further increased, the temporal regularity is apparently destroyed, although spatial synchronization is enhanced. These phenomena imply that topological randomness can tame the spatiotemporal chaos in the 2DMN networks with SW connections. The comparison between this work and previous studies is made and it is found that the 2DMN network with small-world connections captures well the maximal spatiotemporal order. Our results may provide a useful tip for understanding the properties of collective dynamics in coupled real neurons.
Transmission and control of an emerging influenza pandemic in a small-world airline network.
Hsu, Chaug-Ing; Shih, Hsien-Hung
2010-01-01
The avian influenza virus H5N1 and the 2009 swine flu H1N1 are potentially serious pandemic threats to human health, and air travel readily facilitates the spread of infectious diseases. However, past studies have not yet incorporated the effects of air travel on the transmission of influenza in the construction of mathematical epidemic models. Therefore, this paper focused on the human-to-human transmission of influenza, and investigated the effects of air travel activities on an influenza pandemic in a small-world network. These activities of air travel include passengers' consolidation, conveyance and distribution in airports and flights. Dynamic transmission models were developed to assess the expected burdens of the pandemic, with and without control measures. This study also investigated how the small-world properties of an air transportation network facilitate the spread of influenza around the globe. The results show that, as soon as the influenza is spread to the top 50 global airports, the transmission is greatly accelerated. Under the constraint of limited resources, a strategy that first applies control measures to the top 50 airports after day 13 and then soon afterwards to all other airports may result in remarkable containment effectiveness. As the infectiousness of the disease increases, it will expand the scale of the pandemic, and move the start time of the pandemic ahead. PMID:19887149
Scaling of Directed Dynamical Small-World Networks with Random Responses
NASA Astrophysics Data System (ADS)
Zhu, Chen-Ping; Xiong, Shi-Jie; Tian, Ying-Jie; Li, Nan; Jiang, Ke-Sheng
2004-05-01
A dynamical model of small-world networks, with directed links which describe various correlations in social and natural phenomena, is presented. Random responses of sites to the input message are introduced to simulate real systems. The interplay of these ingredients results in the collective dynamical evolution of a spinlike variable S(t) of the whole network. The global average spreading length
Kim, Beom Jun; Trusina, Ala; Holme, Petter; Minnhagen, Petter; Chung, Jean S; Choi, M Y
2002-08-01
A two-dimensional small-world-type network, subject to spatial prisoners' dilemma dynamics and containing an influential node defined as a special node, with a finite density of directed random links to the other nodes in the network, is numerically investigated. It is shown that the degree of cooperation does not remain at a steady state level but displays a punctuated equilibrium-type behavior manifested by the existence of sudden breakdowns of cooperation. The breakdown of cooperation is linked to an imitation of a successful selfish strategy of the influential node. It is also found that while the breakdown of cooperation occurs suddenly, its recovery requires longer time. This recovery time may, depending on the degree of steady state cooperation, either increase or decrease with an increasing number of long-range connections. PMID:12241214
Sparsely-synchronized brain rhythm in a small-world neural network
NASA Astrophysics Data System (ADS)
Kim, Sang-Yoon; Lim, Woochang
2013-07-01
Sparsely-synchronized cortical rhythms, associated with diverse cognitive functions, have been observed in electric recordings of brain activity. At the population level, cortical rhythms exhibit small-amplitude fast oscillations while at the cellular level, individual neurons show stochastic firings sparsely at a much lower rate than the population rate. We study the effect of network architecture on sparse synchronization in an inhibitory population of subthreshold Morris-Lecar neurons (which cannot fire spontaneously without noise). Previously, sparse synchronization was found to occur for cases of both global coupling ( i.e., regular all-to-all coupling) and random coupling. However, a real neural network is known to be non-regular and non-random. Here, we consider sparse Watts-Strogatz small-world networks which interpolate between a regular lattice and a random graph via rewiring. We start from a regular lattice with only short-range connections and then investigate the emergence of sparse synchronization by increasing the rewiring probability p for the short-range connections. For p = 0, the average synaptic path length between pairs of neurons becomes long; hence, only an unsynchronized population state exists because the global efficiency of information transfer is low. However, as p is increased, long-range connections begin to appear, and global effective communication between distant neurons may be available via shorter synaptic paths. Consequently, as p passes a threshold p th (}~ 0.044), sparsely-synchronized population rhythms emerge. However, with increasing p, longer axon wirings become expensive because of their material and energy costs. At an optimal value p* DE (}~ 0.24) of the rewiring probability, the ratio of the synchrony degree to the wiring cost is found to become maximal. In this way, an optimal sparse synchronization is found to occur at a minimal wiring cost in an economic small-world network through trade-off between synchrony and
Effects of distance-dependent delay on small-world neuronal networks
NASA Astrophysics Data System (ADS)
Zhu, Jinjie; Chen, Zhen; Liu, Xianbin
2016-04-01
We study firing behaviors and the transitions among them in small-world noisy neuronal networks with electrical synapses and information transmission delay. Each neuron is modeled by a two-dimensional Rulkov map neuron. The distance between neurons, which is a main source of the time delay, is taken into consideration. Through spatiotemporal patterns and interspike intervals as well as the interburst intervals, the collective behaviors are revealed. It is found that the networks switch from resting state into intermittent firing state under Gaussian noise excitation. Initially, noise-induced firing behaviors are disturbed by small time delays. Periodic firing behaviors with irregular zigzag patterns emerge with an increase of the delay and become progressively regular after a critical value is exceeded. More interestingly, in accordance with regular patterns, the spiking frequency doubles compared with the former stage for the spiking neuronal network. A growth of frequency persists for a larger delay and a transition to antiphase synchronization is observed. Furthermore, it is proved that these transitions are generic also for the bursting neuronal network and the FitzHugh-Nagumo neuronal network. We show these transitions due to the increase of time delay are robust to the noise strength, coupling strength, network size, and rewiring probability.
Yu, Qingbao; Sui, Jing; Rachakonda, Srinivas; He, Hao; Pearlson, Godfrey; Calhoun, Vince D.
2011-01-01
The functional architecture of the human brain has been extensively described in terms of complex networks characterized by efficient small-world features. Recent functional magnetic resonance imaging (fMRI) studies have found altered small-world topological properties of brain functional networks in patients with schizophrenia (SZ) during the resting state. However, little is known about the small-world properties of brain networks in the context of a task. In this study, we investigated the topological properties of human brain functional networks derived from fMRI during an auditory oddball (AOD) task. Data were obtained from 20 healthy controls and 20 SZ; A left and a right task-related network which consisted of the top activated voxels in temporal lobe of each hemisphere were analyzed separately. All voxels were detected by group independent component analysis. Connectivity of the left and right task-related networks were estimated by partial correlation analysis and thresholded to construct a set of undirected graphs. The small-worldness values were decreased in both hemispheres in SZ. In addition, SZ showed longer shortest path length and lower global efficiency only in the left task-related networks. These results suggested small-world attributes are altered during the AOD task-related networks in SZ which provided further evidences for brain dysfunction of connectivity in SZ. PMID:21369355
Mean first-passage time on a family of small-world treelike networks
NASA Astrophysics Data System (ADS)
Li, Long; Sun, Weigang; Wang, Guixiang; Xu, Guanghui
2014-10-01
In this paper, we obtain exact scalings of mean first-passage time (MFPT) of random walks on a family of small-world treelike networks formed by two parameters, which includes three kinds. First, we determine the MFPT for a trapping problem with an immobile trap located at the initial node, which is defined as the average of the first-passage times (FPTs) to the trap node over all possible starting nodes, and it scales linearly with network size N in large networks. We then analytically obtain the partial MFPT (PMFPT) which is the mean of FPTs from the trap node to all other nodes and show that it increases with N as N ln N. Finally we establish the global MFPT (GMFPT), which is the average of FPTs over all pairs of nodes. It also grows with N as N ln N in the large limit of N. For these three kinds of random walks, we all obtain the analytical expressions of the MFPT and they all increase with network parameters. In addition, our method for calculating the MFPT is based on the self-similar structure of the considered networks and avoids the calculations of the Laplacian spectra.
An evolutionary inspection game with labour unions on small-world networks
NASA Astrophysics Data System (ADS)
Kamal, Salahuddin M.; Al-Hadeethi, Yas; Abolaban, Fouad A.; Al-Marzouki, Fahd M.; Perc, Matjaž
2015-03-01
We study an evolutionary inspection game where agents can chose between working and shirking. The evolutionary process is staged on a small-world network, through which agents compare their incomes and, based on the outcome, decide which strategy to adopt. Moreover, we introduce union members that have certain privileges, of which the extent depends on the bargaining power of the union. We determine how the union affects the overall performance of the firm that employs the agents, and what are its influences on the employees. We find that, depending on its bargaining power, the union has significant leverage to deteriorate the productivity of a firm, and consequently also to lower the long-run benefits of the employees.
Synchronization transition of identical phase oscillators in a directed small-world network.
Tönjes, Ralf; Masuda, Naoki; Kori, Hiroshi
2010-09-01
We numerically study a directed small-world network consisting of attractively coupled, identical phase oscillators. While complete synchronization is always stable, it is not always reachable from random initial conditions. Depending on the shortcut density and on the asymmetry of the phase coupling function, there exists a regime of persistent chaotic dynamics. By increasing the density of shortcuts or decreasing the asymmetry of the phase coupling function, we observe a discontinuous transition in the ability of the system to synchronize. Using a control technique, we identify the bifurcation scenario of the order parameter. We also discuss the relation between dynamics and topology and remark on the similarity of the synchronization transition to directed percolation. PMID:20887048
NASA Astrophysics Data System (ADS)
Zhang, Ying-Yue; Chen, Tian-Lun
2006-03-01
In this paper, we introduce a modified small-world network added with new links with preferential connection instead of adding randomly, then we apply Bak-Sneppen (BS) evolution model on this network. Several dynamical character of the model such as the evolution graph, f0 avalanche, the critical exponent D and τ, and the distribution of mutation times of all the nodes, show particular behaviors different from those of the model based on the regular network and the small-world network.
Small-world network model of propagation of the AIDS epidemic
NASA Astrophysics Data System (ADS)
Shi, Pengliang; Small, Michael
2004-03-01
Sexual contact and intravenus drug-use are the most common modes of transmission of HIV-AIDS. In this paper, homogenerous and heterogeneous models are proposed to model the dynamics in a system contains Small-World clusters. Four high risk groups: intravenus drug-users (D); homosexuals (H); individuals with multiple-sexual partners (M) and prostitutes (P), are classified using two models. Both networks are embedded among a background (low-risk) population using rich-get-richer preferential attachment. When a network is established, an epidemic is simulated in it by seeding randomly. We compare the two epidemic networks in detail and consider the effect of different levels of control policies in both. This study highlights two main conclusions: (i) set high protection coefficient for a massive-linkage-vertex (i.e. protect the highly connected individuals); and, (ii) a quick removal for the infected massive-linkage-veterx from the network is essential (rapidly quarantine infected individuals). While these conclusions may be intuitive, they indicate a necessary change of public policy toward prostitution in some developing countries such as China and India. An active effort to prevent possible infection from super-spreader is recommended.
Phase synchronization of non-Abelian oscillators on small-world networks
NASA Astrophysics Data System (ADS)
Gu, Zhi-Ming; Zhao, Ming; Zhou, Tao; Zhu, Chen-Ping; Wang, Bing-Hong
2007-02-01
In this Letter, by extending the concept of Kuramoto oscillator to the left-invariant flow on general Lie group, we investigate the generalized phase synchronization on networks. The analyses and simulations of some typical dynamical systems on Watts Strogatz networks are given, including the n-dimensional torus, the identity component of 3-dimensional general linear group, the special unitary group, and the special orthogonal group. In all cases, the greater disorder of networks will predict better synchronizability, and the small-world effect ensures the global synchronization for sufficiently large coupling strength. The collective synchronized behaviors of many dynamical systems, such as the integrable systems, the two-state quantum systems and the top systems, can be described by the present phase synchronization frame. In addition, it is intuitive that the low-dimensional systems are more easily to synchronize, however, to our surprise, we found that the high-dimensional systems display obviously synchronized behaviors in regular networks, while these phenomena cannot be observed in low-dimensional systems.
She, Qi; Chen, Guanrong; Chan, Rosa H. M.
2016-01-01
The amount of publicly accessible experimental data has gradually increased in recent years, which makes it possible to reconsider many longstanding questions in neuroscience. In this paper, an efficient framework is presented for reconstructing functional connectivity using experimental spike-train data. A modified generalized linear model (GLM) with L1-norm penalty was used to investigate 10 datasets. These datasets contain spike-train data collected from the entorhinal-hippocampal region in the brains of rats performing different tasks. The analysis shows that entorhinal-hippocampal network of well-trained rats demonstrated significant small-world features. It is found that the connectivity structure generated by distance-dependent models is responsible for the observed small-world features of the reconstructed networks. The models are utilized to simulate a subset of units recorded from a large biological neural network using multiple electrodes. Two metrics for quantifying the small-world-ness both suggest that the reconstructed network from the sampled nodes estimates a more prominent small-world-ness feature than that of the original unknown network when the number of recorded neurons is small. Finally, this study shows that it is feasible to adjust the estimated small-world-ness results based on the number of neurons recorded to provide a more accurate reference of the network property. PMID:26902707
Emergence of Small-World Anatomical Networks in Self-Organizing Clustered Neuronal Cultures
de Santos-Sierra, Daniel; Sendiña-Nadal, Irene; Leyva, Inmaculada; Almendral, Juan A.; Anava, Sarit; Ayali, Amir; Papo, David; Boccaletti, Stefano
2014-01-01
In vitro primary cultures of dissociated invertebrate neurons from locust ganglia are used to experimentally investigate the morphological evolution of assemblies of living neurons, as they self-organize from collections of separated cells into elaborated, clustered, networks. At all the different stages of the culture's development, identification of neurons' and neurites' location by means of a dedicated software allows to ultimately extract an adjacency matrix from each image of the culture. In turn, a systematic statistical analysis of a group of topological observables grants us the possibility of quantifying and tracking the progression of the main network's characteristics during the self-organization process of the culture. Our results point to the existence of a particular state corresponding to a small-world network configuration, in which several relevant graph's micro- and meso-scale properties emerge. Finally, we identify the main physical processes ruling the culture's morphological transformations, and embed them into a simplified growth model qualitatively reproducing the overall set of experimental observations. PMID:24489675
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; Decuzzi, Paolo; Gentile, Francesco
2015-02-01
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. PMID:25515929
Transmission of severe acute respiratory syndrome in dynamical small-world networks
NASA Astrophysics Data System (ADS)
Masuda, Naoki; Konno, Norio; Aihara, Kazuyuki
2004-03-01
The outbreak of severe acute respiratory syndrome (SARS) is still threatening the world because of a possible resurgence. In the current situation that effective medical treatments such as antiviral drugs are not discovered yet, dynamical features of the epidemics should be clarified for establishing strategies for tracing, quarantine, isolation, and regulating social behavior of the public at appropriate costs. Here we propose a network model for SARS epidemics and discuss why superspreaders emerged and why SARS spread especially in hospitals, which were key factors of the recent outbreak. We suggest that superspreaders are biologically contagious patients, and they may amplify the spreads by going to potentially contagious places such as hospitals. To avoid mass transmission in hospitals, it may be a good measure to treat suspected cases without hospitalizing them. Finally, we indicate that SARS probably propagates in small-world networks associated with human contacts and that the biological nature of individuals and social group properties are factors more important than the heterogeneous rates of social contacts among individuals. This is in marked contrast with epidemics of sexually transmitted diseases or computer viruses to which scale-free network models often apply.
Isles within islets: The lattice origin of small-world networks in pancreatic tissues
NASA Astrophysics Data System (ADS)
Barua, Amlan K.; Goel, Pranay
2016-02-01
The traditional computational model of the pancreatic islets of Langerhans is a lattice of β-cells connected with gap junctions. Numerous studies have investigated the behavior of networks of coupled β-cells and have shown that gap junctions synchronize bursting strongly. This simplistic architecture of islets, however, seems increasingly untenable at the face of recent experimental advances. In a microfluidics experiment on isolated islets, Rocheleau et al. (2004) showed a failure of penetration of excitation when one end received high glucose and other end was not excited sufficiently; this suggested that gap junctions may not be efficient at inducing synchrony throughout the islet. Recently, Stozer et al. (2013) have argued that the functional networks of β-cells in an islet are small world. Their results implicate the existence of a few long-range connections among cells in the network. The physiological reason underlying this claim is not well understood. These studies cast doubt on the original lattice model that largely predict an all-or-none synchrony among the cells. Here we have attempted to reconcile these observations in a unified framework. We assume that cells in the islet are coupled randomly to their nearest neighbors with some probability, p. We simulated detailed β-cell bursting in such islets. By varying p systematically we were led to network parameters similar to those obtained by Stozer et al. (2013). We find that the networks within islets break up into components giving rise to smaller isles within the super structure-isles-within-islets, as it were. This structure can also account for the partial excitation seen by Rocheleau et al. (2004). Our updated view of islet architecture thus explains the paradox how islets can have strongly synchronizing gap junctions, and be weakly coordinated at the same time.
The dynamic consequences of cooperation and competition in small-world networks.
Fernández-Rosales, Iván Y; Liebovitch, Larry S; Guzmán-Vargas, Lev
2015-01-01
We present a study of the social dynamics among cooperative and competitive actors interacting on a complex network that has a small-world topology. In this model, the state of each actor depends on its previous state in time, its inertia to change, and the influence of its neighboring actors. Using numerical simulations, we determine how the distribution of final states of the actors and measures of the distances between the values of the actors at local and global levels, depend on the number of cooperative to competitive actors and the connectivity of the actors in the network. We find that similar numbers of cooperative and competitive actors yield the lowest values for the local and global measures of the distances between the values of the actors. On the other hand, when the number of either cooperative or competitive actors dominate the system, then the divergence is largest between the values of the actors. Our findings make new testable predictions on how the dynamics of a conflict depends on the strategies chosen by groups of actors and also have implications for the evolution of behaviors. PMID:25927995
The Dynamic Consequences of Cooperation and Competition in Small-World Networks
Fernández-Rosales, Iván Y.; Liebovitch, Larry S.; Guzmán-Vargas, Lev
2015-01-01
We present a study of the social dynamics among cooperative and competitive actors interacting on a complex network that has a small-world topology. In this model, the state of each actor depends on its previous state in time, its inertia to change, and the influence of its neighboring actors. Using numerical simulations, we determine how the distribution of final states of the actors and measures of the distances between the values of the actors at local and global levels, depend on the number of cooperative to competitive actors and the connectivity of the actors in the network. We find that similar numbers of cooperative and competitive actors yield the lowest values for the local and global measures of the distances between the values of the actors. On the other hand, when the number of either cooperative or competitive actors dominate the system, then the divergence is largest between the values of the actors. Our findings make new testable predictions on how the dynamics of a conflict depends on the strategies chosen by groups of actors and also have implications for the evolution of behaviors. PMID:25927995
NASA Astrophysics Data System (ADS)
Yilmaz, Ergin; Baysal, Veli; Ozer, Mahmut; Perc, Matjaž
2016-02-01
We study the effects of an autapse, which is mathematically described as a self-feedback loop, on the propagation of weak, localized pacemaker activity across a Newman-Watts small-world network consisting of stochastic Hodgkin-Huxley neurons. We consider that only the pacemaker neuron, which is stimulated by a subthreshold periodic signal, has an electrical autapse that is characterized by a coupling strength and a delay time. We focus on the impact of the coupling strength, the network structure, the properties of the weak periodic stimulus, and the properties of the autapse on the transmission of localized pacemaker activity. Obtained results indicate the existence of optimal channel noise intensity for the propagation of the localized rhythm. Under optimal conditions, the autapse can significantly improve the propagation of pacemaker activity, but only for a specific range of the autaptic coupling strength. Moreover, the autaptic delay time has to be equal to the intrinsic oscillation period of the Hodgkin-Huxley neuron or its integer multiples. We analyze the inter-spike interval histogram and show that the autapse enhances or suppresses the propagation of the localized rhythm by increasing or decreasing the phase locking between the spiking of the pacemaker neuron and the weak periodic signal. In particular, when the autaptic delay time is equal to the intrinsic period of oscillations an optimal phase locking takes place, resulting in a dominant time scale of the spiking activity. We also investigate the effects of the network structure and the coupling strength on the propagation of pacemaker activity. We find that there exist an optimal coupling strength and an optimal network structure that together warrant an optimal propagation of the localized rhythm.
NASA Astrophysics Data System (ADS)
Zhang, Zhongzhi; Lin, Yuan; Guo, Xiaoye
2015-06-01
The eigenvalues of the transition matrix for random walks on a network play a significant role in the structural and dynamical aspects of the network. Nevertheless, it is still not well understood how the eigenvalues behave in small-world and scale-free networks, which describe a large variety of real systems. In this paper, we study the eigenvalues for the transition matrix of a network that is simultaneously scale-free, small-world, and clustered. We derive explicit simple expressions for all eigenvalues and their multiplicities, with the spectral density exhibiting a power-law form. We then apply the obtained eigenvalues to determine the mixing time and random target access time for random walks, both of which exhibit unusual behaviors compared with those for other networks, signaling discernible effects of topologies on spectral features. Finally, we use the eigenvalues to count spanning trees in the network.
Effects of inspections in small world social networks with different contagion rules
NASA Astrophysics Data System (ADS)
Muñoz, Francisco; Nuño, Juan Carlos; Primicerio, Mario
2015-08-01
We study the way the structure of social links determines the effects of random inspections on a population formed by two types of individuals, e.g. tax-payers and tax-evaders (free riders). It is assumed that inspections occur in a larger scale than the population relaxation time and, therefore, a unique initial inspection is performed on a population that is completely formed by tax-evaders. Besides, the inspected tax-evaders become tax-payers forever. The social network is modeled as a Watts-Strogatz Small World whose topology can be tuned in terms of a parameter p ∈ [ 0 , 1 ] from regular (p = 0) to random (p = 1). Two local contagion rules are considered: (i) a continuous one that takes the proportion of neighbors to determine the next status of an individual (node) and (ii) a discontinuous (threshold rule) that assumes a minimum number of neighbors to modify the current state. In the former case, irrespective of the inspection intensity ν, the equilibrium population is always formed by tax-payers. In the mean field approach, we obtain the characteristic time of convergence as a function of ν and p. For the threshold contagion rule, we show that the response of the population to the intensity of inspections ν is a function of the structure of the social network p and the willingness of the individuals to change their state, r. It is shown that sharp transitions occur at critical values of ν that depends on p and r. We discuss these results within the context of tax evasion and fraud where the strategies of inspection could be of major relevance.
Luongo, Francisco J; Zimmerman, Chris A; Horn, Meryl E; Sohal, Vikaas S
2016-05-01
Sequential patterns of prefrontal activity are believed to mediate important behaviors, e.g., working memory, but it remains unclear exactly how they are generated. In accordance with previous studies of cortical circuits, we found that prefrontal microcircuits in young adult mice spontaneously generate many more stereotyped sequences of activity than expected by chance. However, the key question of whether these sequences depend on a specific functional organization within the cortical microcircuit, or emerge simply as a by-product of random interactions between neurons, remains unanswered. We observed that correlations between prefrontal neurons do follow a specific functional organization-they have a small-world topology. However, until now it has not been possible to directly link small-world topologies to specific circuit functions, e.g., sequence generation. Therefore, we developed a novel analysis to address this issue. Specifically, we constructed surrogate data sets that have identical levels of network activity at every point in time but nevertheless represent various network topologies. We call this method shuffling activity to rearrange correlations (SHARC). We found that only surrogate data sets based on the actual small-world functional organization of prefrontal microcircuits were able to reproduce the levels of sequences observed in actual data. As expected, small-world data sets contained many more sequences than surrogate data sets with randomly arranged correlations. Surprisingly, small-world data sets also outperformed data sets in which correlations were maximally clustered. Thus the small-world functional organization of cortical microcircuits, which effectively balances the random and maximally clustered regimes, is optimal for producing stereotyped sequential patterns of activity. PMID:26888108
Zhang, Jiang; Lin, Xiaohong; Fu, Genyu; Sai, Liyang; Chen, Huafu; Yang, Jianbo; Wang, Mingwen; Liu, Qi; Yang, Gang; Zhang, Junran; Yuan, Zhen
2016-01-01
Deception is not a rare occurrence among human behaviors; however, the present brain mapping techniques are insufficient to reveal the neural mechanism of deception under spontaneous or controlled conditions. Interestingly, functional near-infrared spectroscopy (fNIRS) has emerged as a highly promising neuroimaging technique that enables continuous and noninvasive monitoring of changes in blood oxygenation and blood volume in the human brain. In this study, fNIRS was used in combination with complex network theory to extract the attribute features of the functional brain networks underling deception in subjects exhibiting spontaneous or controlled behaviors. Our findings revealed that the small-world networks of the subjects engaged in spontaneous behaviors exhibited greater clustering coefficients, shorter average path lengths, greater average node degrees, and stronger randomness compared with those of subjects engaged in control behaviors. Consequently, we suggest that small-world network topology is capable of distinguishing well between spontaneous and controlled deceptions. PMID:27126145
Zhang, Jiang; Lin, Xiaohong; Fu, Genyu; Sai, Liyang; Chen, Huafu; Yang, Jianbo; Wang, Mingwen; Liu, Qi; Yang, Gang; Zhang, Junran; Yuan, Zhen
2016-01-01
Deception is not a rare occurrence among human behaviors; however, the present brain mapping techniques are insufficient to reveal the neural mechanism of deception under spontaneous or controlled conditions. Interestingly, functional near-infrared spectroscopy (fNIRS) has emerged as a highly promising neuroimaging technique that enables continuous and noninvasive monitoring of changes in blood oxygenation and blood volume in the human brain. In this study, fNIRS was used in combination with complex network theory to extract the attribute features of the functional brain networks underling deception in subjects exhibiting spontaneous or controlled behaviors. Our findings revealed that the small-world networks of the subjects engaged in spontaneous behaviors exhibited greater clustering coefficients, shorter average path lengths, greater average node degrees, and stronger randomness compared with those of subjects engaged in control behaviors. Consequently, we suggest that small-world network topology is capable of distinguishing well between spontaneous and controlled deceptions. PMID:27126145
NASA Astrophysics Data System (ADS)
Kim, Sang-Yoon; Lim, Woochang
2015-11-01
We consider a clustered network with small-world subnetworks of inhibitory fast spiking interneurons and investigate the effect of intermodular connection on the emergence of fast sparsely synchronized rhythms by varying both the intermodular coupling strength Jinter and the average number of intermodular links per interneuron Msyn(inter ). In contrast to the case of nonclustered networks, two kinds of sparsely synchronized states such as modular and global synchronization are found. For the case of modular sparse synchronization, the population behavior reveals the modular structure, because the intramodular dynamics of subnetworks make some mismatching. On the other hand, in the case of global sparse synchronization, the population behavior is globally identical, independently of the cluster structure, because the intramodular dynamics of subnetworks make perfect matching. We introduce a realistic cross-correlation modularity measure, representing the matching degree between the instantaneous subpopulation spike rates of the subnetworks, and examine whether the sparse synchronization is global or modular. Depending on its magnitude, the intermodular coupling strength Jinter seems to play "dual" roles for the pacing between spikes in each subnetwork. For large Jinter, due to strong inhibition it plays a destructive role to "spoil" the pacing between spikes, while for small Jinter it plays a constructive role to "favor" the pacing between spikes. Through competition between the constructive and the destructive roles of Jinter, there exists an intermediate optimal Jinter at which the pacing degree between spikes becomes maximal. In contrast, the average number of intermodular links per interneuron Msyn(inter ) seems to play a role just to favor the pacing between spikes. With increasing Msyn(inter ), the pacing degree between spikes increases monotonically thanks to the increase in the degree of effectiveness of global communication between spikes. Furthermore, we
NASA Astrophysics Data System (ADS)
Zhang, Jianbao; Ma, Zhongjun; Chen, Guanrong
2014-06-01
All edges in the classical Watts and Strogatz's small-world network model are unweighted and cooperative (positive). By introducing competitive (negative) inter-cluster edges and assigning edge weights to mimic more realistic networks, this paper develops a modified model which possesses co-competitive weighted couplings and cluster structures while maintaining the common small-world network properties of small average shortest path lengths and large clustering coefficients. Based on theoretical analysis, it is proved that the new model with inter-cluster co-competition balance has an important dynamical property of robust cluster synchronous pattern formation. More precisely, clusters will neither merge nor split regardless of adding or deleting nodes and edges, under the condition of inter-cluster co-competition balance. Numerical simulations demonstrate the robustness of the model against the increase of the coupling strength and several topological variations.
Zhang, Jianbao; Ma, Zhongjun; Chen, Guanrong
2014-06-15
All edges in the classical Watts and Strogatz's small-world network model are unweighted and cooperative (positive). By introducing competitive (negative) inter-cluster edges and assigning edge weights to mimic more realistic networks, this paper develops a modified model which possesses co-competitive weighted couplings and cluster structures while maintaining the common small-world network properties of small average shortest path lengths and large clustering coefficients. Based on theoretical analysis, it is proved that the new model with inter-cluster co-competition balance has an important dynamical property of robust cluster synchronous pattern formation. More precisely, clusters will neither merge nor split regardless of adding or deleting nodes and edges, under the condition of inter-cluster co-competition balance. Numerical simulations demonstrate the robustness of the model against the increase of the coupling strength and several topological variations.
Fekete, Tomer; Beacher, Felix D C C; Cha, Jiook; Rubin, Denis; Mujica-Parodi, Lilianne R
2014-01-15
Near infrared spectroscopy (NIRS) is an emerging imaging technique that is relatively inexpensive, portable, and particularly well suited for collecting data in ecological settings. Therefore, it holds promise as a potential neurodiagnostic for young children. We set out to explore whether NIRS could be utilized in assessing the risk of developmental psychopathology in young children. A growing body of work indicates that temperament at young age is associated with vulnerability to psychopathology later on in life. In particular, it has been shown that low effortful control (EC), which includes the focusing and shifting of attention, inhibitory control, perceptual sensitivity, and a low threshold for pleasure, is linked to conditions such as anxiety, depression and attention deficit hyperactivity disorder (ADHD). Physiologically, EC has been linked to a control network spanning among other sites the prefrontal cortex. Several psychopathologies, such as depression and ADHD, have been shown to result in compromised small-world network properties. Therefore we set out to explore the relationship between EC and the small-world properties of PFC using NIRS. NIRS data were collected from 44 toddlers, ages 3-5, while watching naturalistic stimuli (movie clips). Derived complex network measures were then correlated to EC as derived from the Children's Behavior Questionnaire (CBQ). We found that reduced levels of EC were associated with compromised small-world properties of the prefrontal network. Our results suggest that the longitudinal NIRS studies of complex network properties in young children hold promise in furthering our understanding of developmental psychopathology. PMID:23863519
Yu, Haitao; Guo, Xinmeng; Wang, Jiang; Deng, Bin; Wei, Xile
2014-09-01
The phenomenon of stochastic resonance in Newman-Watts small-world neuronal networks is investigated when the strength of synaptic connections between neurons is adaptively adjusted by spike-time-dependent plasticity (STDP). It is shown that irrespective of the synaptic connectivity is fixed or adaptive, the phenomenon of stochastic resonance occurs. The efficiency of network stochastic resonance can be largely enhanced by STDP in the coupling process. Particularly, the resonance for adaptive coupling can reach a much larger value than that for fixed one when the noise intensity is small or intermediate. STDP with dominant depression and small temporal window ratio is more efficient for the transmission of weak external signal in small-world neuronal networks. In addition, we demonstrate that the effect of stochastic resonance can be further improved via fine-tuning of the average coupling strength of the adaptive network. Furthermore, the small-world topology can significantly affect stochastic resonance of excitable neuronal networks. It is found that there exists an optimal probability of adding links by which the noise-induced transmission of weak periodic signal peaks. PMID:25273205
Yu, Haitao; Guo, Xinmeng; Wang, Jiang Deng, Bin; Wei, Xile
2014-09-01
The phenomenon of stochastic resonance in Newman-Watts small-world neuronal networks is investigated when the strength of synaptic connections between neurons is adaptively adjusted by spike-time-dependent plasticity (STDP). It is shown that irrespective of the synaptic connectivity is fixed or adaptive, the phenomenon of stochastic resonance occurs. The efficiency of network stochastic resonance can be largely enhanced by STDP in the coupling process. Particularly, the resonance for adaptive coupling can reach a much larger value than that for fixed one when the noise intensity is small or intermediate. STDP with dominant depression and small temporal window ratio is more efficient for the transmission of weak external signal in small-world neuronal networks. In addition, we demonstrate that the effect of stochastic resonance can be further improved via fine-tuning of the average coupling strength of the adaptive network. Furthermore, the small-world topology can significantly affect stochastic resonance of excitable neuronal networks. It is found that there exists an optimal probability of adding links by which the noise-induced transmission of weak periodic signal peaks.
NASA Astrophysics Data System (ADS)
Zhang, Ying-Yue; Yang, Qiu-Ying; Chen, Tian-Lun
2007-07-01
We introduce a modified small-world network adding new links with nonlinearly preferential connection instead of adding randomly, then we apply Bak-Sneppen (BS) evolution model on this network. We study several important structural properties of our network such as the distribution of link-degree, the maximum link-degree, and the length of the shortest path. We further argue several dynamical characteristics of the model such as the important critical value fc, the f0 avalanche, and the mutating condition, and find that those characteristics show particular behaviors.
Age-Related Differences in the Modulation of Small-World Brain Networks during a Go/NoGo Task
Hong, Xiangfei; Liu, Yuelu; Sun, Junfeng; Tong, Shanbao
2016-01-01
Although inter-regional phase synchrony of neural oscillations has been proposed as a plausible mechanism for response control, little is known about the possible effects due to normal aging. We recorded multi-channel electroencephalography (EEG) from healthy younger and older adults in a Go/NoGo task, and examined the aging effects on synchronous brain networks with graph theoretical analysis. We found that in both age groups, brain networks in theta, alpha or beta band for either response execution (Go) or response inhibition (NoGo) condition showed prominent small-world property. Furthermore, small-world property of brain networks showed significant differences between different task conditions. Further analyses of node degree suggested that frontal-central theta band phase synchrony was enhanced during response inhibition, whereas during response execution, increased phase synchrony was observed in beta band over central-parietal regions. More interestingly, these task-related modulations on brain networks were well preserved and even more robust in older adults compared with younger adults. Taken together, our findings not only suggest that response control involves synchronous brain networks in functionally-distinct frequency bands, but also indicate an increase in the recruitment of brain network resources due to normal aging. PMID:27242512
NASA Astrophysics Data System (ADS)
Yuan, Wu-Jie; Luo, Xiao-Shu; Jiang, Pin-Qun
2007-02-01
In this paper, we propose a new model of weighted small-world biological neural networks based on biophysical Hodgkin-Huxley neurons with side-restrain mechanism. Then we study excitement properties of the model under alternating current (AC) stimulation. The study shows that the excitement properties in the networks are preferably consistent with the behavior properties of a brain nervous system under different AC stimuli, such as refractory period and the brain neural excitement response induced by different intensities of noise and coupling. The results of the study have reference worthiness for the brain nerve electrophysiology and epistemological science.
Massobrio, Paolo; Pasquale, Valentina; Martinoia, Sergio
2015-01-01
The spontaneous activity of cortical networks is characterized by the emergence of different dynamic states. Although several attempts were accomplished to understand the origin of these dynamics, the underlying factors continue to be elusive. In this work, we specifically investigated the interplay between network topology and spontaneous dynamics within the framework of self-organized criticality (SOC). The obtained results support the hypothesis that the emergence of critical states occurs in specific complex network topologies. By combining multi-electrode recordings of spontaneous activity of in vitro cortical assemblies with theoretical models, we demonstrate that different ‘connectivity rules’ drive the network towards different dynamic states. In particular, scale-free architectures with different degree of small-worldness account better for the variability observed in experimental data, giving rise to different dynamic states. Moreover, in relationship with the balance between excitation and inhibition and percentage of inhibitory hubs, the simulated cortical networks fall in a critical regime. PMID:26030608
Small-World Synchronized Computing Networks for Scalable Parallel Discrete-Event Simulations
NASA Astrophysics Data System (ADS)
Guclu, Hasan; Korniss, Gyorgy; Toroczkai, Zoltan; Novotny, Mark A.
We study the scalability of parallel discrete-event simulations for arbitrary short-range interacting systems with asynchronous dynamics. When the synchronization topology mimics that of the short-range interacting underlying system, the virtual time horizon (corresponding to the progress of the processing elements) exhibits Kardar-Parisi-Zhang-like kinetic roughening. Although the virtual times, on average, progress at a nonzero rate, their statistical spread diverges with the number of processing elements, hindering efficient data collection. We show that when the synchronization topology is extended to include quenched random communication links between the processing elements, they make a close-to-uniform progress with a nonzero rate, without global synchronization. We discuss in detail a coarse-grained description for the small-world synchronized virtual time horizon and compare the findings to those obtained by simulating the simulations based on the exact algorithmic rules.
Gong, Longyan; Tong, Peiqing
2006-11-01
The von Neumann entropy for an electron in periodic, disorder, and quasiperiodic quantum small-world networks (QSWN's) is studied numerically. For the disorder QSWN's, the derivative of the spectrum-averaged von Neumann entropy is maximal at a certain density of shortcut links p*, which can be as a signature of the localization-delocalization transition of electron states. The transition point p* is agreement with that obtained by the level statistics method. For the quasiperiodic QSWN's, it is found that there are two regions of the potential parameter. The behaviors of electron states in different regions are similar to that of periodic and disorder QSWN's, respectively. PMID:17279964
Noise influence on spike activation in a Hindmarsh–Rose small-world neural network
NASA Astrophysics Data System (ADS)
Zhe, Sun; Micheletto, Ruggero
2016-07-01
We studied the role of noise in neural networks, especially focusing on its relation to the propagation of spike activity in a small sized system. We set up a source of information using a single neuron that is constantly spiking. This element called initiator x o feeds spikes to the rest of the network that is initially quiescent and subsequently reacts with vigorous spiking after a transitional period of time. We found that noise quickly suppresses the initiator’s influence and favors spontaneous spike activity and, using a decibel representation of noise intensity, we established a linear relationship between noise amplitude and the interval from the initiator’s first spike and the rest of the network activation. We studied the same process with networks of different sizes (number of neurons) and found that the initiator x o has a measurable influence on small networks, but as the network grows in size, spontaneous spiking emerges disrupting its effects on networks of more than about N = 100 neurons. This suggests that the mechanism of internal noise generation allows information transmission within a small neural neighborhood, but decays for bigger network domains. We also analyzed the Fourier spectrum of the whole network membrane potential and verified that noise provokes the reduction of main θ and α peaks before transitioning into chaotic spiking. However, network size does not reproduce a similar phenomena; instead we recorded a reduction in peaks’ amplitude, a better sharpness and definition of Fourier peaks, but not the evident degeneration to chaos observed with increasing external noise. This work aims to contribute to the understanding of the fundamental mechanisms of propagation of spontaneous spiking in neural networks and gives a quantitative assessment of how noise can be used to control and modulate this phenomenon in Hindmarsh‑Rose (H‑R) neural networks.
Uehara, Taira; Yamasaki, Takao; Okamoto, Tsuyoshi; Koike, Takahiko; Kan, Shigeyuki; Miyauchi, Satoru; Kira, Jun-Ichi; Tobimatsu, Shozo
2014-06-01
It has been revealed that spontaneous coherent brain activity during rest, measured by functional magnetic resonance imaging (fMRI), self-organizes a "small-world" network by which the human brain could sustain higher communication efficiency across global brain regions with lower energy consumption. However, the state-dependent dynamics of the network, especially the dependency on the conscious state, remain poorly understood. In this study, we conducted simultaneous electroencephalographic recording with resting-state fMRI to explore whether functional network organization reflects differences in the conscious state between an awake state and stage 1 sleep. We then evaluated whole-brain functional network properties with fine spatial resolution (3781 regions of interest) using graph theoretical analysis. We found that the efficiency of the functional network evaluated by path length decreased not only at the global level, but also in several specific regions depending on the conscious state. Furthermore, almost two-thirds of nodes that showed a significant decrease in nodal efficiency during stage 1 sleep were categorized as the default-mode network. These results suggest that brain functional network organizations are dynamically optimized for a higher level of information integration in the fully conscious awake state, and that the default-mode network plays a pivotal role in information integration for maintaining conscious awareness. PMID:23349223
NASA Astrophysics Data System (ADS)
Qiu, Tian; Hadzibeganovic, Tarik; Chen, Guang; Zhong, Li-Xin; Wu, Xiao-Run
2010-12-01
Cooperation in the evolutionary snowdrift game with a self-questioning updating mechanism is studied on annealed and quenched small-world networks with directed couplings. Around the payoff parameter value r=0.5, we find a size-invariant symmetrical cooperation effect. While generally suppressing cooperation for r>0.5 payoffs, rewired networks facilitated cooperative behavior for r<0.5. Fair amounts of noise were found to break the observed symmetry and further weaken cooperation at relatively large values of r. However, in the absence of noise, the self-questioning mechanism recovers symmetrical behavior and elevates altruism even under large-reward conditions. Our results suggest that an updating mechanism of this type is necessary to stabilize cooperation in a spatially structured environment which is otherwise detrimental to cooperative behavior, especially at high cost-to-benefit ratios. Additionally, we employ component and local stability analyses to better understand the nature of the manifested dynamics.
NASA Astrophysics Data System (ADS)
Rothkegel, A.; Lehnertz, K.
2014-05-01
We study the collective dynamics of excitatory integrate-and-fire-like oscillators interacting via δ-pulses on a small-world network. The oscillators are endowed with refractory periods and time delays. For weak coupling strengths, the network self-organizes into synchronous and asynchronous regions. Such chimera states allow for two separate routes to synchrony/asynchrony. In addition to the loss of stability of either synchronous or asynchronous regions mediated by long-ranged connections, regions may grow or shrink mediated by the lattice structure. The interplay between these behaviors leads to controlled total sizes of asynchronous regions or to an alternation of synchronization and desynchronization phenomena with irregular macroscopic observables.
A Small World of Citations? The Influence of Collaboration Networks on Citation Practices
Wallace, Matthew L.; Larivière, Vincent; Gingras, Yves
2012-01-01
This paper examines the proximity of authors to those they cite using degrees of separation in a co-author network, essentially using collaboration networks to expand on the notion of self-citations. While the proportion of direct self-citations (including co-authors of both citing and cited papers) is relatively constant in time and across specialties in the natural sciences (10% of references) and the social sciences (20%), the same cannot be said for citations to authors who are members of the co-author network. Differences between fields and trends over time lie not only in the degree of co-authorship which defines the large-scale topology of the collaboration network, but also in the referencing practices within a given discipline, computed by defining a propensity to cite at a given distance within the collaboration network. Overall, there is little tendency to cite those nearby in the collaboration network, excluding direct self-citations. These results are interpreted in terms of small-scale structure, field-specific citation practices, and the value of local co-author networks for the production of knowledge and for the accumulation of symbolic capital. Given the various levels of integration between co-authors, our findings shed light on the question of the availability of ‘arm's length’ expert reviewers of grant applications and manuscripts. PMID:22413016
Beyond Scale-Free Small-World Networks: Cortical Columns for Quick Brains
NASA Astrophysics Data System (ADS)
Stoop, Ralph; Saase, Victor; Wagner, Clemens; Stoop, Britta; Stoop, Ruedi
2013-03-01
We study to what extent cortical columns with their particular wiring boost neural computation. Upon a vast survey of columnar networks performing various real-world cognitive tasks, we detect no signs of enhancement. It is on a mesoscopic—intercolumnar—scale that the existence of columns, largely irrespective of their inner organization, enhances the speed of information transfer and minimizes the total wiring length required to bind distributed columnar computations towards spatiotemporally coherent results. We suggest that brain efficiency may be related to a doubly fractal connectivity law, resulting in networks with efficiency properties beyond those by scale-free networks.
Arzouan, Yossi; Solomon, Sorin; Faust, Miriam; Goldstein, Abraham
2011-01-01
Language comprehension is a complex task that involves a wide network of brain regions. We used topological measures to qualify and quantify the functional connectivity of the networks used under various comprehension conditions. To that aim we developed a technique to represent functional networks based on EEG recordings, taking advantage of their excellent time resolution in order to capture the fast processes that occur during language comprehension. Networks were created by searching for a specific causal relation between areas, the negative feedback loop, which is ubiquitous in many systems. This method is a simple way to construct directed graphs using event-related activity, which can then be analyzed topologically. Brain activity was recorded while subjects read expressions of various types and indicated whether they found them meaningful. Slightly different functional networks were obtained for event-related activity evoked by each expression type. The differences reflect the special contribution of specific regions in each condition and the balance of hemispheric activity involved in comprehending different types of expressions and are consistent with the literature in the field. Our results indicate that representing event-related brain activity as a network using a simple temporal relation, such as the negative feedback loop, to indicate directional connectivity is a viable option for investigation which also derives new information about aspects not reflected in the classical methods for investigating brain activity. PMID:21556324
A Hyper-connected but Less Efficient Small-world Network in the Substance-Dependent Brain
Wang, Ze; Suh, Jesse; Li, Zhengjun; Li, Yin; Franklin, Teresa; O’Brien, Charles; Childress, Anna Rose
2015-01-01
Background The functional interconnections of the addicted brain may differ from the non-addicted population in important ways, but prior analytic approaches were usually limited to the study of connections between a few number of selected brain regions. Recent approaches enable examination of the vast functional interactions within the entire brain, the functional connectome (FCM). The purpose of this study was to characterize FCM alterations in addiction using resting state functional Magnetic Resonance Imaging (rsfMRI) and to assess their relations to addiction-related symptoms. Methods rsfMRI data were acquired from 20 chronic polydrug users whose primary diagnosis was cocaine dependence (DRUG) and 19 age-matched non-drug using healthy controls (CTL). FCM was assessed using graph theoretical analysis. Results Among the assessed 90 brain subdivisions, DRUG showed stronger functional connectivity. After controlling functional connectivity difference and the resultant network density, DRUG showed reduced communication efficiency and reduced small-worldness. Conclusions The increased connection strength in drug users’ brain suggests an elevated dynamic resting state that may enable a rapid, semi-automatic, execution of behaviors directed toward drug-related goals. The reduced FCM communication efficiency and reduced small-worldness suggest a loss of normal inter-regional communications and topology features that makes it difficult to inhibit the drug seeking behavior. PMID:25957794
NASA Astrophysics Data System (ADS)
Huang, Xu-Hui; Hu, Gang
2014-10-01
Phase transitions widely exist in nature and occur when some control parameters are changed. In neural systems, their macroscopic states are represented by the activity states of neuron populations, and phase transitions between different activity states are closely related to corresponding functions in the brain. In particular, phase transitions to some rhythmic synchronous firing states play significant roles on diverse brain functions and disfunctions, such as encoding rhythmical external stimuli, epileptic seizure, etc. However, in previous studies, phase transitions in neuronal networks are almost driven by network parameters (e.g., external stimuli), and there has been no investigation about the transitions between typical activity states of neuronal networks in a self-organized way by applying plastic connection weights. In this paper, we discuss phase transitions in electrically coupled and lattice-based small-world neuronal networks (LBSW networks) under spike-timing-dependent plasticity (STDP). By applying STDP on all electrical synapses, various known and novel phase transitions could emerge in LBSW networks, particularly, the phenomenon of self-organized phase transitions (SOPTs): repeated transitions between synchronous and asynchronous firing states. We further explore the mechanics generating SOPTs on the basis of synaptic weight dynamics.
NASA Astrophysics Data System (ADS)
Percha, Bethany; Dzakpasu, Rhonda; Żochowski, Michał; Parent, Jack
2005-09-01
Temporal correlations in the brain are thought to have very dichotomous roles. On one hand they are ubiquitously present in the healthy brain and are thought to underlie feature binding during information processing. On the other hand, large-scale synchronization is an underlying mechanism of epileptic seizures. In this paper we show a potential mechanism for the transition to pathological coherence underlying seizure generation. We show that properties of phase synchronization in a two-dimensional lattice of nonidentical coupled Hindmarsh-Rose neurons change radically depending on the connectivity structure of the network. We modify the connectivity using the small world network paradigm and measure properties of phase synchronization using a previously developed measure based on assessment of the distributions of relative interspike intervals. We show that the temporal ordering undergoes a dramatic change as a function of topology of the network from local coherence strongly dependent on the distance between two neurons, to global coherence exhibiting a larger degree of ordering and spanning the whole network.
Li, Ting; Hong, Jun; Zhang, Jinhua; Guo, Feng
2014-03-15
The improvement of the resolution of brain signal and the ability to control external device has been the most important goal in BMI research field. This paper describes a non-invasive brain-actuated manipulator experiment, which defined a paradigm for the motion control of a serial manipulator based on motor imagery and shared control. The techniques of component selection, spatial filtering and classification of motor imagery were involved. Small-world neural network (SWNN) was used to classify five brain states. To verify the effectiveness of the proposed classifier, we replace the SWNN classifier by a radial basis function (RBF) networks neural network, a standard multi-layered feed-forward backpropagation network (SMN) and a multi-SVM classifier, with the same features for the classification. The results also indicate that the proposed classifier achieves a 3.83% improvement over the best results of other classifiers. We proposed a shared control method consisting of two control patterns to expand the control of BMI from the software angle. The job of path building for reaching the 'end' point was designated as an assessment task. We recorded all paths contributed by subjects and picked up relevant parameters as evaluation coefficients. With the assistance of two control patterns and series of machine learning algorithms, the proposed BMI originally achieved the motion control of a manipulator in the whole workspace. According to experimental results, we confirmed the feasibility of the proposed BMI method for 3D motion control of a manipulator using EEG during motor imagery. PMID:24333753
NASA Astrophysics Data System (ADS)
Aldrich, Preston R.; El-Zabet, Jermeen; Hassan, Seerat; Briguglio, Joseph; Aliaj, Enela; Radcliffe, Maria; Mirza, Taha; Comar, Timothy; Nadolski, Jeremy; Huebner, Cynthia D.
2015-11-01
Several studies have shown that human transportation networks exhibit small-world structure, meaning they have high local clustering and are easily traversed. However, some have concluded this without statistical evaluations, and others have compared observed structure to globally random rather than planar models. Here, we use Monte Carlo randomizations to test US transportation infrastructure data for small-worldness. Coarse-grained network models were generated from GIS data wherein nodes represent the 3105 contiguous US counties and weighted edges represent the number of highway or railroad links between counties; thus, we focus on linkage topologies and not geodesic distances. We compared railroad and highway transportation networks with a simple planar network based on county edge-sharing, and with networks that were globally randomized and those that were randomized while preserving their planarity. We conclude that terrestrial transportation networks have small-world architecture, as it is classically defined relative to global randomizations. However, this topological structure is sufficiently explained by the planarity of the graphs, and in fact the topological patterns established by the transportation links actually serve to reduce the amount of small-world structure.
ERIC Educational Resources Information Center
Sousa, Fernando Cardoso; Monteiro, Ileana Pardal; Pellissier, René
2014-01-01
This article presents the development of a small-world network using an adapted version of the large-group problem-solving method "Future Search." Two management classes in a higher education setting were selected and required to plan a project. The students completed a survey focused on the frequency of communications before and after…
NASA Astrophysics Data System (ADS)
Nunes Amaral, Luis A.
2002-03-01
We study the statistical properties of a variety of diverse real-world networks including the neural network of C. Elegans, food webs for seven distinct environments, transportation and technological networks, and a number of distinct social networks [1-5]. We present evidence of the occurrence of three classes of small-world networks [2]: (a) scale-free networks, characterized by a vertex connectivity distribution that decays as a power law; (b) broad-scale networks, characterized by a connectivity distribution that has a power-law regime followed by a sharp cut-off; (c) single-scale networks, characterized by a connectivity distribution with a fast decaying tail. Moreover, we note for the classes of broad-scale and single-scale networks that there are constraints limiting the addition of new links. Our results suggest that the nature of such constraints may be the controlling factor for the emergence of different classes of networks. [See http://polymer.bu.edu/ amaral/Networks.html for details and htpp://polymer.bu.edu/ amaral/Professional.html for access to PDF files of articles.] 1. M. Barthélémy, L. A. N. Amaral, Phys. Rev. Lett. 82, 3180-3183 (1999). 2. L. A. N. Amaral, A. Scala, M. Barthélémy, H. E. Stanley, Proc. Nat. Acad. Sci. USA 97, 11149-11152 (2000). 3. F. Liljeros, C. R. Edling, L. A. N. Amaral, H. E. Stanley, and Y. Åberg, Nature 411, 907-908 (2001). 4. J. Camacho, R. Guimera, L.A.N. Amaral, Phys. Rev. E RC (to appear). 5. S. Mossa, M. Barthelemy, H.E. Stanley, L.A.N. Amaral (submitted).
Rothkegel, Alexander; Lehnertz, Klaus
2009-03-01
We investigate numerically the collective dynamical behavior of pulse-coupled nonleaky integrate-and-fire neurons that are arranged on a two-dimensional small-world network. To ensure ongoing activity, we impose a probability for spontaneous firing for each neuron. We study network dynamics evolving from different sets of initial conditions in dependence on coupling strength and rewiring probability. Besides a homogeneous equilibrium state for low coupling strength, we observe different local patterns including cyclic waves, spiral waves, and turbulentlike patterns, which-depending on network parameters-interfere with the global collective firing of the neurons. We attribute the various network dynamics to distinct regimes in the parameter space. For the same network parameters different network dynamics can be observed depending on the set of initial conditions only. Such a multistable behavior and the interplay between local pattern formation and global collective firing may be attributable to the spatiotemporal dynamics of biological networks. PMID:19335013
NASA Astrophysics Data System (ADS)
Rothkegel, Alexander; Lehnertz, Klaus
2009-03-01
We investigate numerically the collective dynamical behavior of pulse-coupled nonleaky integrate-and-fire neurons that are arranged on a two-dimensional small-world network. To ensure ongoing activity, we impose a probability for spontaneous firing for each neuron. We study network dynamics evolving from different sets of initial conditions in dependence on coupling strength and rewiring probability. Besides a homogeneous equilibrium state for low coupling strength, we observe different local patterns including cyclic waves, spiral waves, and turbulentlike patterns, which—depending on network parameters—interfere with the global collective firing of the neurons. We attribute the various network dynamics to distinct regimes in the parameter space. For the same network parameters different network dynamics can be observed depending on the set of initial conditions only. Such a multistable behavior and the interplay between local pattern formation and global collective firing may be attributable to the spatiotemporal dynamics of biological networks.
Koelsch, Stefan; Skouras, Stavros
2014-07-01
Current knowledge about small-world networks underlying emotions is sparse, and confined to functional magnetic resonance imaging (fMRI) studies using resting-state paradigms. This fMRI study applied Eigenvector Centrality Mapping (ECM) and functional connectivity analysis to reveal neural small-world networks underlying joy and fear. Joy and fear were evoked using music, presented in 4-min blocks. Results show that the superficial amygdala (SF), laterobasal amygdala (LB), striatum, and hypothalamus function as computational hubs during joy. Out of these computational hubs, the amygdala nuclei showed the highest centrality values. The SF showed functional connectivity during joy with the mediodorsal thalamus (MD) and nucleus accumbens (Nac), suggesting that SF, MD, and Nac modulate approach behavior in response to positive social signals such as joyful music. The striatum was functionally connected during joy with the LB, as well as with premotor cortex, areas 1 and 7a, hippocampus, insula and cingulate cortex, showing that sensorimotor, attentional, and emotional processes converge in the striatum during music perception. The hypothalamus showed functional connectivity during joy with hippocampus and MD, suggesting that hypothalamic endocrine activity is modulated by hippocampal and thalamic activity during sustained periods of music-evoked emotion. Our study indicates high centrality of the amygdala nuclei groups within a functional network underlying joy, suggesting that these nuclei play a central role for the modulation of emotion-specific activity within this network. PMID:25050430
Cluster-size entropy in the Axelrod model of social influence: Small-world networks and mass media
NASA Astrophysics Data System (ADS)
Gandica, Y.; Charmell, A.; Villegas-Febres, J.; Bonalde, I.
2011-10-01
We study the Axelrod's cultural adaptation model using the concept of cluster-size entropy Sc, which gives information on the variability of the cultural cluster size present in the system. Using networks of different topologies, from regular to random, we find that the critical point of the well-known nonequilibrium monocultural-multicultural (order-disorder) transition of the Axelrod model is given by the maximum of the Sc(q) distributions. The width of the cluster entropy distributions can be used to qualitatively determine whether the transition is first or second order. By scaling the cluster entropy distributions we were able to obtain a relationship between the critical cultural trait qc and the number F of cultural features in two-dimensional regular networks. We also analyze the effect of the mass media (external field) on social systems within the Axelrod model in a square network. We find a partially ordered phase whose largest cultural cluster is not aligned with the external field, in contrast with a recent suggestion that this type of phase cannot be formed in regular networks. We draw a q-B phase diagram for the Axelrod model in regular networks.
NASA Astrophysics Data System (ADS)
Ausloos, Marcel
2015-06-01
Diffusion of knowledge is expected to be huge when agents are open minded. The report concerns a more difficult diffusion case when communities are made of stubborn agents. Communities having markedly different opinions are for example the Neocreationist and Intelligent Design Proponents (IDP), on one hand, and the Darwinian Evolution Defenders (DED), on the other hand. The case of knowledge diffusion within such communities is studied here on a network based on an adjacency matrix built from time ordered selected quotations of agents, whence for inter- and intra-communities. The network is intrinsically directed and not necessarily reciprocal. Thus, the adjacency matrices have complex eigenvalues; the eigenvectors present complex components. A quantification of the slow-down or speed-up effects of information diffusion in such temporal networks, with non-Markovian contact sequences, can be made by comparing the real time dependent (directed) network to its counterpart, the time aggregated (undirected) network, - which has real eigenvalues. In order to do so, small world networks which both contain an odd number of nodes are studied and compared to similar networks with an even number of nodes. It is found that (i) the diffusion of knowledge is more difficult on the largest networks; (ii) the network size influences the slowing-down or speeding-up diffusion process. Interestingly, it is observed that (iii) the diffusion of knowledge is slower in IDP and faster in DED communities. It is suggested that the finding can be "rationalized", if some "scientific quality" and "publication habit" is attributed to the agents, as common sense would guess. This finding offers some opening discussion toward tying scientific knowledge to belief.
Siettos, Constantinos I; Anastassopoulou, Cleo; Russo, Lucia; Grigoras, Christos; Mylonakis, Eleftherios
2016-01-01
Objectives As the Ebola virus disease is still sustained in Sierra Leone, we analysed the epidemic for a recent period (21 December 2014 to 17 April 2015) using a small-world networked model and forecasted its evolution. Policy-control scenarios for the containment of the epidemic were also examined. Methods We developed an agent-based model with 6 million individuals (the population of Sierra Leone) interacting through a small-world social network. The model incorporates the main epidemiological factors, including the effect of burial practices to virus transmission. The effective reproductive number (Re) was evaluated directly from the agent-based simulations. Estimates of the epidemiological variables were computed on the basis of the official cases as reported by the Centers for Disease Control and Prevention (CDC). Results From 21 December 2014 to 18 February 2015 the epidemic was in recession compared with previous months, as indicated by the estimated Re of ∼0.77 (95% CI 0.72 to 0.82). From 18 February to 17 April 2015, the Re rose above criticality (∼1.98, 95% CI 1.33 to 2.22), flashing a note of caution for the situation. By projecting in time, we predicted that the epidemic would continue through July 2015. Our predictions were close to the cases reported by CDC by the end of June, verifying the criticality of the situation. In light of these developments, while revising our manuscript, we expanded our analysis to include the most recent data (until 15 August 2015). By mid-August, Re had fallen below criticality and the epidemic was expected to fade out by early December 2015. Conclusions Our results call for the continuation of drastic control measures, which in the absence of an effective vaccine or therapy at present can only translate to isolation of the infected section of the population, to contain the epidemic. PMID:26826143
Analysis of a bio-dynamic model via Lyapunov principle and small-world network for tuberculosis.
Chung, H-Y; Chung, C-Y; Ou, S-C
2012-10-01
The study will apply Lyapunov principle to construct a dynamic model for tuberculosis (TB). The Lyapunov principle is commonly used to examine and determine the stability of a dynamic system. To simulate the transmissions of vector-borne diseases and discuss the related health policies effects on vector-borne diseases, the authors combine the multi-agent-based system, social network and compartmental model to develop an epidemic simulation model. In the identity level, the authors use the multi-agent-based system and the mirror identity concept to describe identities with social network features such as daily visits, long-distance movement, high degree of clustering, low degree of separation and local clustering. The research will analyse the complex dynamic mathematic model of TB epidemic and determine its stability property by using the popular Matlab/Simulink software and relative software packages. Facing the current TB epidemic situation, the development of TB and its developing trend through constructing a dynamic bio-mathematical system model of TB is investigated. After simulating the development of epidemic situation with the solution of the SMIR epidemic model, the authors will come up with a good scheme to control epidemic situation to analyse the parameter values of a model that influence epidemic situation evolved. The authors will try to find the quarantining parameters that are the most important factors to control epidemic situation. The SMIR epidemic model and the results via numerical analysis may offer effective prevention with reference to controlling epidemic situation of TB. PMID:23101874
Duality Between Spin Networks and the 2D Ising Model
NASA Astrophysics Data System (ADS)
Bonzom, Valentin; Costantino, Francesco; Livine, Etera R.
2016-06-01
The goal of this paper is to exhibit a deep relation between the partition function of the Ising model on a planar trivalent graph and the generating series of the spin network evaluations on the same graph. We provide respectively a fermionic and a bosonic Gaussian integral formulation for each of these functions and we show that they are the inverse of each other (up to some explicit constants) by exhibiting a supersymmetry relating the two formulations. We investigate three aspects and applications of this duality. First, we propose higher order supersymmetric theories that couple the geometry of the spin networks to the Ising model and for which supersymmetric localization still holds. Secondly, after interpreting the generating function of spin network evaluations as the projection of a coherent state of loop quantum gravity onto the flat connection state, we find the probability distribution induced by that coherent state on the edge spins and study its stationary phase approximation. It is found that the stationary points correspond to the critical values of the couplings of the 2D Ising model, at least for isoradial graphs. Third, we analyze the mapping of the correlations of the Ising model to spin network observables, and describe the phase transition on those observables on the hexagonal lattice. This opens the door to many new possibilities, especially for the study of the coarse-graining and continuum limit of spin networks in the context of quantum gravity.
NASA Astrophysics Data System (ADS)
Peng, Junhao
2016-03-01
In this paper, we study random walks on a small-world scale-free network, also called as pseudofractal scale-free web (PSFW), and analyze the volatilities of first passage time (FPT) and first return time (FRT) by using the variance and reduced moment as measures. Note that the FRT and FPT are deeply affected by the starting or target site. We do not intend to enumerate all the possible cases and analyze them. We only study the volatilities of FRT for a given hub (i.e. node with highest degree) and the volatilities of the global FPT (GFPT) to a given hub, which is the average of the FPTs for arriving at a given hub from any possible starting site selected randomly according to the equilibrium distribution of the Markov chain. Firstly, we calculate exactly the probability generating function of the GFPT and FRT based on the self-similar structure of the PSFW. Then, we calculate the probability distribution, mean, variance and reduced moment of the GFPT and FRT by using the generating functions as a tool. Results show that: the reduced moment of FRT grows with increasing network order N and tends to infinity while N\\to ∞ ; but for the reduced moments of GFPT, it is almost a constant(≈ 1.1605) for large N. Therefore, on the PSFW of large size, the FRT has huge fluctuations and the estimate provided by MFRT is unreliable, whereas the fluctuations of the GFPT are much smaller and the estimate provided by its mean is more reliable. The method we propose can also be used to analyze the volatilities of FPT and FRT on other networks with self-similar structure, such as (u, v) flowers and recursive scale-free trees.
Sigma-delta cellular neural network for 2D modulation.
Aomori, Hisashi; Otake, Tsuyoshi; Takahashi, Nobuaki; Tanaka, Mamoru
2008-01-01
Although sigma-delta modulation is widely used for analog-to-digital (A/D) converters, sigma-delta concepts are only for 1D signals. Signal processing in the digital domain is extremely useful for 2D signals such as used in image processing, medical imaging, ultrasound imaging, and so on. The intricate task that provides true 2D sigma-delta modulation is feasible in the spatial domain sigma-delta modulation using the discrete-time cellular neural network (DT-CNN) with a C-template. In the proposed architecture, the A-template is used for a digital-to-analog converter (DAC), the C-template works as an integrator, and the nonlinear output function is used for the bilevel output. In addition, due to the cellular neural network (CNN) characteristics, each pixel of an image corresponds to a cell of a CNN, and each cell is connected spatially by the A-template. Therefore, the proposed system can be thought of as a very large-scale and super-parallel sigma-delta modulator. Moreover, the spatio-temporal dynamics is designed to obtain an optimal reconstruction signal. The experimental results show the excellent reconstruction performance and capabilities of the CNN as a sigma-delta modulator. PMID:18215502
NASA Astrophysics Data System (ADS)
Dong, Lin-Rong
2010-09-01
This paper investigates the dynamic evolution with limited learning information on a small-world network. In the system, the information among the interaction players is not very lucid, and the players are not allowed to inspect the profit collected by its neighbors, thus the focal player cannot choose randomly a neighbor or the wealthiest one and compare its payoff to copy its strategy. It is assumed that the information acquainted by the player declines in the form of the exponential with the geographical distance between the players, and a parameter V is introduced to denote the inspect-ability about the players. It is found that under the hospitable conditions, cooperation increases with the randomness and is inhibited by the large connectivity for the prisoner's dilemma; however, cooperation is maximal at the moderate rewiring probability and is chaos with the connectivity for the snowdrift game. For the two games, the acuminous sight is in favor of the cooperation under the hospitable conditions; whereas, the myopic eyes are advantageous to cooperation and cooperation increases with the randomness under the hostile condition.
NASA Astrophysics Data System (ADS)
Zekri, Nouredine; Clerc, Jean Pierre
We study numerically in this work the statistical and dynamical properties of the clusters in a one dimensional small world model. The parameters chosen correspond to a realistic network of children of school age where a disease like measles can propagate. Extensive results on the statistical behavior of the clusters around the percolation threshold, as well as the evoltion with time, are discussed. To cite this article: N. Zekri, J.P. Clerc, C. R. Physique 3 (2002) 741-747.
2D Carbon Nanotube Network: A New material for Electronics
NASA Astrophysics Data System (ADS)
Gruner, George
2006-03-01
This talk will focus on the electronic properties of two dimensional carbon nanotube networks, and on their application potential. Percolation issues, together with the frequency, and temperature dependent activity will be discussed. The network can be tuned from having semiconducting to metallic like behavior, and doping with electron withdrawing and donating species leads to networks with tailor-made electronic properties. The network is also highly transparent in the visible spectral range, this attribute -- together with simple room temperature fab processes -- opens up application opportunities in the area of electronics, opto-electronics, photovoltaics and sensors. Recent results on solar cells, OLEDs and smart windows will be reviewed. Field effect transistors that incorporate nanotube network conducting channels, together with complex functional devices that incorporate networks and functional molecules will also be discussed. Finally a comparison will be made with conventional and emerging materials that compete area of disposable, flexible and printable electronics.
2D pattern evolution constrained by complex network dynamics
NASA Astrophysics Data System (ADS)
da Rocha, L. E. C.; Costa, L. da F.
2007-03-01
Complex networks have established themselves in recent years as being particularly suitable and flexible for representing and modelling several complex natural and artificial systems. In the same time in which the structural intricacies of such networks are being revealed and understood, efforts have also been directed at investigating how such connectivity properties define and constrain the dynamics of systems unfolding on such structures. However, less attention has been focused on hybrid systems, i.e. involving more than one type of network and/or dynamics. Several real systems present such an organization, e.g. the dynamics of a disease coexisting with the dynamics of the immune system. The current paper investigates a specific system involving diffusive (linear and nonlinear) dynamics taking place in a regular network while interacting with a complex network of defensive agents following Erdös Rényi (ER) and Barabási Albert (BA) graph models with moveable nodes. More specifically, the complex network is expected to control, and if possible, to extinguish the diffusion of some given unwanted process (e.g. fire, oil spilling, pest dissemination, and virus or bacteria reproduction during an infection). Two types of pattern evolution are considered: Fick and Gray Scott. The nodes of the defensive network then interact with the diffusing patterns and communicate between themselves in order to control the diffusion. The main findings include the identification of higher efficiency for the BA control networks and the presence of relapses in the case of the ER model.
Ring Correlations in Two-Dimensional (2D) Random Networks
NASA Astrophysics Data System (ADS)
Sadjadi, Mahdi; Thorpe, M. F.
Amorphous materials can be characterized by their ring structure. Recently, two experimental groups imaged bilayers of vitreous silica at atomic resolution which provides a direct access to the ring structure of a 2D glass. It has been shown that experimental samples have various ring statistics, obey Aboav-Weaire law and have a distinct area law. In this work, we study correlations between rings as a function of their size and topological separation. We show that correlation is medium-range and vanishes when the separation is about three rings apart. We also present a generalization of the Aboav-Weaire law.
Structure of a randomly grown 2-d network.
Ajazi, Fioralba; Napolitano, George M; Turova, Tatyana; Zaurbek, Izbassar
2015-10-01
We introduce a growing random network on a plane as a model of a growing neuronal network. The properties of the structure of the induced graph are derived. We compare our results with available data. In particular, it is shown that depending on the parameters of the model the system undergoes in time different phases of the structure. We conclude with a possible explanation of some empirical data on the connections between neurons. PMID:26375356
Magnetic anisotropy of metal functionalized phthalocyanine 2D networks
NASA Astrophysics Data System (ADS)
Zhu, Guojun; Zhang, Yun; Xiao, Huaping; Cao, Juexian
2016-06-01
The magnetic anisotropy of metal including Cr, Mn, Fe, Co, Mo, Tc, Ru, Rh, W, Re, Os, Ir atoms functionalized phthalocyanine networks have been investigated with first-principles calculations. The magnetic moments can be expressed as 8-n μB with n the electronic number of outmost d shell in the transition metals. The huge magnetocrystalline anisotropy energy (MAE) is obtained by torque method. Especially, the MAE of Re functionalized phthalocyanine network is about 20 meV with an easy axis perpendicular to the plane of phthalocyanine network. The MAE is further manipulated by applying the external biaxial strain. It is found that the MAE is linear increasing with the external strain in the range of -2% to 2%. Our results indicate an effective approach to modulate the MAE for practical application.
Small Worldness in Dense and Weighted Connectomes
NASA Astrophysics Data System (ADS)
Colon-Perez, Luis; Couret, Michelle; Triplett, William; Price, Catherine; Mareci, Thomas
2016-05-01
The human brain is a heterogeneous network of connected functional regions; however, most brain network studies assume that all brain connections can be described in a framework of binary connections. The brain is a complex structure of white matter tracts connected by a wide range of tract sizes, which suggests a broad range of connection strengths. Therefore, the assumption that the connections are binary yields an incomplete picture of the brain. Various thresholding methods have been used to remove spurious connections and reduce the graph density in binary networks. But these thresholds are arbitrary and make problematic the comparison of networks created at different thresholds. The heterogeneity of connection strengths can be represented in graph theory by applying weights to the network edges. Using our recently introduced edge weight parameter, we estimated the topological brain network organization using a complimentary weighted connectivity framework to the traditional framework of a binary network. To examine the reproducibility of brain networks in a controlled condition, we studied the topological network organization of a single healthy individual by acquiring 10 repeated diffusion-weighted magnetic resonance image datasets, over a one-month period on the same scanner, and analyzing these networks with deterministic tractography. We applied a threshold to both the binary and weighted networks and determined that the extra degree of freedom that comes with the framework of weighting network connectivity provides a robust result as any threshold level. The proposed weighted connectivity framework provides a stable result and is able to demonstrate the small world property of brain networks in situations where the binary framework is inadequate and unable to demonstrate this network property.
Small Worldness in Dense and Weighted Connectomes
Colon-Perez, Luis M.; Couret, Michelle; Triplett, William; Price, Catherine C.; Mareci, Thomas H.
2016-01-01
The human brain is a heterogeneous network of connected functional regions; however, most brain network studies assume that all brain connections can be described in a framework of binary connections. The brain is a complex structure of white matter tracts connected by a wide range of tract sizes, which suggests a broad range of connection strengths. Therefore, the assumption that the connections are binary yields an incomplete picture of the brain. Various thresholding methods have been used to remove spurious connections and reduce the graph density in binary networks. But these thresholds are arbitrary and make problematic the comparison of networks created at different thresholds. The heterogeneity of connection strengths can be represented in graph theory by applying weights to the network edges. Using our recently introduced edge weight parameter, we estimated the topological brain network organization using a complimentary weighted connectivity framework to the traditional framework of a binary network. To examine the reproducibility of brain networks in a controlled condition, we studied the topological network organization of a single healthy individual by acquiring 10 repeated diffusion-weighted magnetic resonance image datasets, over a 1-month period on the same scanner, and analyzing these networks with deterministic tractography. We applied a threshold to both the binary and weighted networks and determined that the extra degree of freedom that comes with the framework of weighting network connectivity provides a robust result as any threshold level. The proposed weighted connectivity framework provides a stable result and is able to demonstrate the small world property of brain networks in situations where the binary framework is inadequate and unable to demonstrate this network property. PMID:27478822
Active transport and cluster formation on 2D networks.
Greulich, P; Santen, L
2010-06-01
We introduce a model for active transport on inhomogeneous networks embedded in a diffusive environment which is motivated by vesicular transport on actin filaments. In the presence of a hard-core interaction, particle clusters are observed that exhibit an algebraically decaying distribution in a large parameter regime, indicating the existence of clusters on all scales. The scale-free behavior can be understood by a mechanism promoting preferential attachment of particles to large clusters. The results are compared with a diffusion-limited aggregation model and active transport on a regular network. For both models we observe aggregation of particles to clusters which are characterized by a finite size scale if the relevant time scales and particle densities are considered. PMID:20556462
2D MIMO Network Coding with Inter-Route Interference Cancellation
NASA Astrophysics Data System (ADS)
Tran, Gia Khanh; Sakaguchi, Kei; Ono, Fumie; Araki, Kiyomichi
Infrastructure wireless mesh network has been attracting much attention due to the wide range of its application such as public wireless access, sensor network, etc. In recent years, researchers have shown that significant network throughput gain can be achieved by employing network coding in a wireless environment. For further improvement of network throughput in one dimensional (1D) topology, Ono et al. proposed to use multiple antenna technique combined with network coding. In this paper, being inspired by MIMO network coding in 1D topology, the authors establish a novel MIMO network coding algorithm for a 2D topology consisting of two crossing routes. In this algorithm, multiple network coded flows are spatially multiplexed. Owing to the efficient usage of radio resource of network coding and co-channel interference cancellation ability of MIMO, the proposed algorithm shows an 8-fold gain in network capacity compared to conventional methods in the best-case scenario.
Optimal design of 2D digital filters based on neural networks
NASA Astrophysics Data System (ADS)
Wang, Xiao-hua; He, Yi-gang; Zheng, Zhe-zhao; Zhang, Xu-hong
2005-02-01
Two-dimensional (2-D) digital filters are widely useful in image processing and other 2-D digital signal processing fields,but designing 2-D filters is much more difficult than designing one-dimensional (1-D) ones.In this paper, a new design approach for designing linear-phase 2-D digital filters is described,which is based on a new neural networks algorithm (NNA).By using the symmetry of the given 2-D magnitude specification,a compact express for the magnitude response of a linear-phase 2-D finite impulse response (FIR) filter is derived.Consequently,the optimal problem of designing linear-phase 2-D FIR digital filters is turned to approximate the desired 2-D magnitude response by using the compact express.To solve the problem,a new NNA is presented based on minimizing the mean-squared error,and the convergence theorem is presented and proved to ensure the designed 2-D filter stable.Three design examples are also given to illustrate the effectiveness of the NNA-based design approach.
Small world picture of worldwide seismic events
NASA Astrophysics Data System (ADS)
Ferreira, Douglas S. R.; Papa, Andrés R. R.; Menezes, Ronaldo
2014-08-01
The understanding of long-distance relations between seismic activities has for long been of interest to seismologists and geologists. In this paper we have used data from the worldwide earthquake catalog for the period between 1972 and 2011 to generate a network of sites around the world for earthquakes with magnitude m≥4.5 in the Richter scale. After the network construction, we have analyzed the results under two viewpoints. First, in contrast to previous works, which have considered just small areas, we showed that the best fitting for networks of seismic events is not a pure power law, but a power law with exponential cutoff; we also have found that the global network presents small-world properties. Second, we have found that the time intervals between successive earthquakes have a cumulative probability distribution well fitted by nontraditional functional forms. The implications of our results are significant because they seem to indicate that seisms around the world are not independent. In this paper we provide evidence to support this argument.
Automatic angle measurement of a 2D object using optical correlator-neural networks hybrid system
NASA Astrophysics Data System (ADS)
Manivannan, N.; Neil, M. A. A.
2011-04-01
In this paper a novel method is proposed and demonstrated for automatic rotation angle measurement of a 2D object using a hybrid architecture, consisting of a 4f optical correlator with a binary phase only multiplexed matched filter and a single layer neural network. The hybrid set-up can be considered as a two-layer perceptron-like neural network; an optical correlator is the first layer and the standard single layer neural network is the second layer. The training scheme used to train the hybrid architecture is a combination of a Direct Binary Search algorithm, to train the optical correlator, and an Error Back Propagation algorithm, to train the neural network. The aim is to perform the major information processing by the optical correlator with a small additional processing by the neural network stage. This allows the system to be used for real-time applications as optics has the inherent ability to process information in a parallel manner at high speed. The neural network stage gives an extra dimension of freedom so that complicated tasks like automatic rotation angle measurement can be achieved. Results of both computer simulation and experimental set-up are presented for rotation angle measurement of an English alphabetic character as a 2D object. The experimental set-up consists of a real optical correlator using two spatial light modulators for both input and frequency plane representations and a PC based model of a single layer network.
Väänänen, Taito; Koskela, Harri; Hiltunen, Yrjö; Ala-Korpela, Mika
2002-01-01
Understanding relationships between the structure and composition of molecular mixtures and their chemical properties is a main industrial aim. One central field of research is oil chemistry where the key question is how the molecular characteristics of composite hydrocarbon mixtures can be associated with the macroscopic properties of the oil products. Apparently these relationships are complex and often nonlinear and therefore call for advanced spectroscopic techniques. An informative and an increasingly used approach is two-dimensional nuclear magnetic resonance (2D NMR) spectroscopy. In the case of composite hydrocarbons the application of 2D NMR methodologies in a quantitative manner pose many technical difficulties, and, in any case, the resulting spectra contain many overlapping resonances that challenge the analytical work. Here, we present a general methodology, based on quantitative artificial neural network (ANN) analysis, to resolve overlapping information in 2D NMR spectra and to simultaneously assess the relative importance of multiple spectral variables on the sample properties. The results in a set of 2D NMR spectra of oil samples illustrate, first, that use of ANN analysis for quantitative purposes is feasible also in 2D and, second, that this methodology offers an intrinsic opportunity to assess the complex and nonlinear relationships between the molecular composition and sample properties. The presented ANN methodology is not limited to the analysis of NMR spectra but can also be applied in a manner similar to other (multidimensional) spectroscopic data. PMID:12444730
Vehicular motion in 2D city traffic network with signals controlled by phase shift
NASA Astrophysics Data System (ADS)
Komada, Kazuhito; Kojima, Kengo; Nagatani, Takashi
2011-03-01
We study the dynamic behavior of vehicular traffic through the series of traffic lights controlled by phase shift in two-dimensional (2D) city traffic network. The nonlinear-map model is presented for the vehicular traffic. The city traffic network is made of one-way perpendicular streets arranged in a square lattice with traffic signals where vertical streets are oriented upwards and horizontal streets are oriented rightwards. There are two traffic lights for the movement to north or that to east at each crossing. The traffic lights are controlled by the cycle time, split, and phase shift. The vehicle moves through the series of signals on a path selected by the driver. The city traffic with a heterogeneous density distribution is also studied. The dependence of the arrival time on cycle time, split, phase shift, selected path, and density is clarified for 2D city traffic. It is shown that the vehicular traffic is efficiently controlled by the phase shift.
Bosi, Susanna; Rauti, Rossana; Laishram, Jummi; Turco, Antonio; Lonardoni, Davide; Nieus, Thierry; Prato, Maurizio; Scaini, Denis; Ballerini, Laura
2015-01-01
To recreate in vitro 3D neuronal circuits will ultimately increase the relevance of results from cultured to whole-brain networks and will promote enabling technologies for neuro-engineering applications. Here we fabricate novel elastomeric scaffolds able to instruct 3D growth of living primary neurons. Such systems allow investigating the emerging activity, in terms of calcium signals, of small clusters of neurons as a function of the interplay between the 2D or 3D architectures and network dynamics. We report the ability of 3D geometry to improve functional organization and synchronization in small neuronal assemblies. We propose a mathematical modelling of network dynamics that supports such a result. Entrapping carbon nanotubes in the scaffolds remarkably boosted synaptic activity, thus allowing for the first time to exploit nanomaterial/cell interfacing in 3D growth support. Our 3D system represents a simple and reliable construct, able to improve the complexity of current tissue culture models. PMID:25910072
2D and 3D Histioid Disclination Networks in Liquid Crystals
NASA Astrophysics Data System (ADS)
Jiang, Miao; Guo, Yubing; Lavrentovich, Oleg; Wei, Qi-Huo
Topological defects and disclination lines are of both fundamental interest and practical importance. In this paper, we will show that periodic/non-periodic 2D/3D networks of disclination lines can be created in nematic liquid crystal cells by setting well-designed alignment patterns at the top and bottom substrate surfaces. The desired complex patterns of liquid crystal molecular alignments at the substrates are obtained using a projection photoalignment technique based on plasmonic metamasks. The designs of alignment patterns and their resulting disclination line networks will be presented. These designable topological networks represent a new kind of artificial materials which could be of useful for directing colloidal and molecular assembly. National Science Foundation CMMI-1436565.
Simulation and analysis of solute transport in 2D fracture/pipe networks: The SOLFRAC program
NASA Astrophysics Data System (ADS)
Bodin, Jacques; Porel, Gilles; Delay, Fred; Ubertosi, Fabrice; Bernard, Stéphane; de Dreuzy, Jean-Raynald
2007-01-01
The Time Domain Random Walk (TDRW) method has been recently developed by Delay and Bodin [Delay, F. and Bodin, J., 2001. Time domain random walk method to simulate transport by advection-dispersion and matrix diffusion in fracture networks. Geophys. Res. Lett., 28(21): 4051-4054.] and Bodin et al. [Bodin, J., Porel, G. and Delay, F., 2003c. Simulation of solute transport in discrete fracture networks using the time domain random walk method. Earth Planet. Sci. Lett., 6566: 1-8.] for simulating solute transport in discrete fracture networks. It is assumed that the fracture network can reasonably be represented by a network of interconnected one-dimensional pipes (i.e. flow channels). Processes accounted for are: (1) advection and hydrodynamic dispersion in the channels, (2) matrix diffusion, (3) diffusion into stagnant zones within the fracture planes, (4) sorption reactions onto the fracture walls and in the matrix, (5) linear decay, and (6) mass sharing at fracture intersections. The TDRW method is handy and very efficient in terms of computation costs since it allows for the one-step calculation of the particle residence time in each bond of the network. This method has been programmed in C++, and efforts have been made to develop an efficient and user-friendly software, called SOLFRAC. This program is freely downloadable at the URL http://labo.univ-poitiers.fr/hydrasa/intranet/telechargement.htm. It calculates solute transport into 2D pipe networks, while considering different types of injections and different concepts of local dispersion within each flow channel. Post-simulation analyses are also available, such as the mean velocity or the macroscopic dispersion at the scale of the entire network. The program may be used to evaluate how a given transport mechanism influences the macroscopic transport behaviour of fracture networks. It may also be used, as is the case, e.g., with analytical solutions, to interpret laboratory or field tracer test experiments
A 2D Polychloride Network Held Together by Halogen-Halogen Interactions.
Brückner, Robin; Haller, Heike; Steinhauer, Simon; Müller, Carsten; Riedel, Sebastian
2015-12-14
In a eutectic mixture of two ionic liquids, we have synthesized and crystallized the new polychloride compound [Et4 N]2 [(Cl3 )2 ⋅Cl2 ] that exhibits a periodic 2D polychloride network acting as an anionic layer. Based on its low melting point and vapor pressure, this compound can be described as a room-temperature ionic liquid. The compound was fully characterized by IR and Raman spectroscopy as well as single-crystal X-ray structure determination. The characterization was complemented by solid-state quantum-chemical calculations confirming the results of the experimental work. PMID:26545703
Confinement properties of 2D porous molecular networks on metal surfaces.
Müller, Kathrin; Enache, Mihaela; Stöhr, Meike
2016-04-20
Quantum effects that arise from confinement of electronic states have been extensively studied for the surface states of noble metals. Utilizing small artificial structures for confinement allows tailoring of the surface properties and offers unique opportunities for applications. So far, examples of surface state confinement include thin films, artificial nanoscale structures, vacancy and adatom islands, self-assembled 1D chains, vicinal surfaces, quantum dots and quantum corrals. In this review we summarize recent achievements in changing the electronic structure of surfaces by adsorption of nanoporous networks whose design principles are based on the concepts of supramolecular chemistry. Already in 1993, it was shown that quantum corrals made from Fe atoms on a Cu(1 1 1) surface using single atom manipulation with a scanning tunnelling microscope confine the Shockley surface state. However, since the atom manipulation technique for the construction of corral structures is a relatively time consuming process, the fabrication of periodic two-dimensional (2D) corral structures is practically impossible. On the other side, by using molecular self-assembly extended 2D porous structures can be achieved in a parallel process, i.e. all pores are formed at the same time. The molecular building blocks are usually held together by non-covalent interactions like hydrogen bonding, metal coordination or dipolar coupling. Due to the reversibility of the bond formation defect-free and long-range ordered networks can be achieved. However, recently also examples of porous networks formed by covalent coupling on the surface have been reported. By the choice of the molecular building blocks, the dimensions of the network (pore size and pore to pore distance) can be controlled. In this way, the confinement properties of the individual pores can be tuned. In addition, the effect of the confined state on the hosting properties of the pores will be discussed in this review article
Confinement properties of 2D porous molecular networks on metal surfaces
NASA Astrophysics Data System (ADS)
Müller, Kathrin; Enache, Mihaela; Stöhr, Meike
2016-04-01
Quantum effects that arise from confinement of electronic states have been extensively studied for the surface states of noble metals. Utilizing small artificial structures for confinement allows tailoring of the surface properties and offers unique opportunities for applications. So far, examples of surface state confinement include thin films, artificial nanoscale structures, vacancy and adatom islands, self-assembled 1D chains, vicinal surfaces, quantum dots and quantum corrals. In this review we summarize recent achievements in changing the electronic structure of surfaces by adsorption of nanoporous networks whose design principles are based on the concepts of supramolecular chemistry. Already in 1993, it was shown that quantum corrals made from Fe atoms on a Cu(1 1 1) surface using single atom manipulation with a scanning tunnelling microscope confine the Shockley surface state. However, since the atom manipulation technique for the construction of corral structures is a relatively time consuming process, the fabrication of periodic two-dimensional (2D) corral structures is practically impossible. On the other side, by using molecular self-assembly extended 2D porous structures can be achieved in a parallel process, i.e. all pores are formed at the same time. The molecular building blocks are usually held together by non-covalent interactions like hydrogen bonding, metal coordination or dipolar coupling. Due to the reversibility of the bond formation defect-free and long-range ordered networks can be achieved. However, recently also examples of porous networks formed by covalent coupling on the surface have been reported. By the choice of the molecular building blocks, the dimensions of the network (pore size and pore to pore distance) can be controlled. In this way, the confinement properties of the individual pores can be tuned. In addition, the effect of the confined state on the hosting properties of the pores will be discussed in this review article.
Traumatic brain injury impairs small-world topology
Pandit, Anand S.; Expert, Paul; Lambiotte, Renaud; Bonnelle, Valerie; Leech, Robert; Turkheimer, Federico E.
2013-01-01
Objective: We test the hypothesis that brain networks associated with cognitive function shift away from a “small-world” organization following traumatic brain injury (TBI). Methods: We investigated 20 TBI patients and 21 age-matched controls. Resting-state functional MRI was used to study functional connectivity. Graph theoretical analysis was then applied to partial correlation matrices derived from these data. The presence of white matter damage was quantified using diffusion tensor imaging. Results: Patients showed characteristic cognitive impairments as well as evidence of damage to white matter tracts. Compared to controls, the graph analysis showed reduced overall connectivity, longer average path lengths, and reduced network efficiency. A particular impact of TBI is seen on a major network hub, the posterior cingulate cortex. Taken together, these results confirm that a network critical to cognitive function shows a shift away from small-world characteristics. Conclusions: We provide evidence that key brain networks involved in supporting cognitive function become less small-world in their organization after TBI. This is likely to be the result of diffuse white matter damage, and may be an important factor in producing cognitive impairment after TBI. PMID:23596068
Smith, Brian J; Overholts, Anna C; Hwang, Nicky; Dichtel, William R
2016-03-01
We explore the crystallization of a high surface area imine-linked two-dimensional covalent organic framework (2D COF). The growth process reveals rapid initial formation of an amorphous network that subsequently crystallizes into the layered 2D network. The metastable amorphous polymer may be isolated and resubjected to growth conditions to form the COF. These experiments provide the first mechanistic insight into the mechanism of imine-linked 2D COF formation, which is distinct from that of boronate-ester linked COFs. PMID:26857035
Assessing small-worldness of dynamic functional brain connectivity during complex tasks.
Shen Ren; Taya, Fumihiko; Yu Sun; deSouza, Joshua; Thakor, Nitish V; Bezerianos, Anastasios
2015-08-01
The development of network theory has introduced new approaches to understand the brain as a complex system. Currently the time-variant functional connectivity of brain networks under complex tasks is still being investigated. To explore connectivity during complex cognitive and motor tasks, this study focused on the relevance of small-worldness to human workloads using EEG signals from a dynamic analytic approach. Experiments were designed to investigate the small-worldness under two types of flight simulation tasks at two levels of difficulty - easy and hard. The results demonstrated a consistent small-world architecture of brain connectivity with time-based variance during complex tasks. We noticed an increased small-world effect especially at the alpha band when performing hard tasks compared to easy tasks, which relate to high and low workload respectively. Our results show the potential of dynamic brain network analysis in exploring time-variant and task-dependent brain connectivity during complex tasks. PMID:26736899
2D image classification for 3D anatomy localization: employing deep convolutional neural networks
NASA Astrophysics Data System (ADS)
de Vos, Bob D.; Wolterink, Jelmer M.; de Jong, Pim A.; Viergever, Max A.; Išgum, Ivana
2016-03-01
Localization of anatomical regions of interest (ROIs) is a preprocessing step in many medical image analysis tasks. While trivial for humans, it is complex for automatic methods. Classic machine learning approaches require the challenge of hand crafting features to describe differences between ROIs and background. Deep convolutional neural networks (CNNs) alleviate this by automatically finding hierarchical feature representations from raw images. We employ this trait to detect anatomical ROIs in 2D image slices in order to localize them in 3D. In 100 low-dose non-contrast enhanced non-ECG synchronized screening chest CT scans, a reference standard was defined by manually delineating rectangular bounding boxes around three anatomical ROIs -- heart, aortic arch, and descending aorta. Every anatomical ROI was automatically identified using a combination of three CNNs, each analyzing one orthogonal image plane. While single CNNs predicted presence or absence of a specific ROI in the given plane, the combination of their results provided a 3D bounding box around it. Classification performance of each CNN, expressed in area under the receiver operating characteristic curve, was >=0.988. Additionally, the performance of ROI localization was evaluated. Median Dice scores for automatically determined bounding boxes around the heart, aortic arch, and descending aorta were 0.89, 0.70, and 0.85 respectively. The results demonstrate that accurate automatic 3D localization of anatomical structures by CNN-based 2D image classification is feasible.
Some tensor-network diagnostics for a class of 2D SPT states with internal symmetry
NASA Astrophysics Data System (ADS)
Prakash, Abhishodh; Wei, Tzu-Chieh
We demonstrate some diagnostic techniques to characterize certain 2D tensor network states with internal symmetries that are classified by the third group cohomology of the symmetry group. We use the discussions of Else et al. [Phys. Rev. B 90, 235137 (2014)] to extract data that determines the phase of matter from the tensors that make up a specific class of wave functions. This is possible because the symmetry transformation at the `physical' level, which is of product form, translates to a symmetry in the `virtual' level which may no longer be of product form. An appropriate analysis of the virtual-space symmetry helps us obtain the topological information (the 3-cocycle twist) that places the wave function in the classification scheme. This reproduces the results of Chen et al. [Phys. Rev. B 87,155114 (2013)] without using projection operators in merging two 'Matrix Product Operators' of the symmetry representation of two group actions.
Surface-Supported Robust 2D Lanthanide-Carboxylate Coordination Networks.
Urgel, José I; Cirera, Borja; Wang, Yang; Auwärter, Willi; Otero, Roberto; Gallego, José M; Alcamí, Manuel; Klyatskaya, Svetlana; Ruben, Mario; Martín, Fernando; Miranda, Rodolfo; Ecija, David; Barth, Johannes V
2015-12-16
Lanthanide-based metal-organic compounds and architectures are promising systems for sensing, heterogeneous catalysis, photoluminescence, and magnetism. Herein, the fabrication of interfacial 2D lanthanide-carboxylate networks is introduced. This study combines low- and variable-temperature scanning tunneling microscopy (STM) and X-ray photoemission spectroscopy (XPS) experiments, and density functional theory (DFT) calculations addressing their design and electronic properties. The bonding of ditopic linear linkers to Gd centers on a Cu(111) surface gives rise to extended nanoporous grids, comprising mononuclear nodes featuring eightfold lateral coordination. XPS and DFT elucidate the nature of the bond, indicating ionic characteristics, which is also manifest in appreciable thermal stability. This study introduces a new generation of robust low-dimensional metallosupramolecular systems incorporating the functionalities of the f-block elements. PMID:26524215
The lesioned brain: still a small-world?
Douw, Linda; van Dellen, Edwin; Baayen, Johannes C; Klein, Martin; Velis, Demetrios N; Alpherts, Willem C J; Heimans, Jan J; Reijneveld, Jaap C; Stam, Cornelis Jan
2010-01-01
The intra-arterial amobarbital procedure (IAP or Wada test) is used to determine language lateralization and contralateral memory functioning in patients eligible for neurosurgery because of pharmaco-resistant epilepsy. During unilateral sedation, functioning of the contralateral hemisphere is assessed by means of neuropsychological tests. We use the IAP as a reversible model for the effect of lesions on brain network topology. Three artifact-free epochs (4096 samples) were selected from each electroencephalogram record before and after amobarbital injection. Functional connectivity was assessed by means of the synchronization likelihood. The resulting functional connectivity matrices were constructed for all six epochs per patient in four frequency bands, and weighted network analysis was performed. The clustering coefficient, average path length, small-world index, and edge weight correlation were calculated. Recordings of 33 patients were available. Network topology changed significantly after amobarbital injection: clustering decreased in all frequency bands, while path length decreased in the theta and lower alpha band, indicating a shift toward a more random network topology. Likewise, the edge weight correlation decreased after injection of amobarbital in the theta and beta bands. Network characteristics after injection of amobarbital were correlated with memory score: higher theta band small-world index and increased upper alpha path length were related to better memory score. The whole-brain network topology in patients eligible for epilepsy surgery becomes more random and less optimally organized after selective sedation of one hemisphere, as has been reported in studies with brain tumor patients. Furthermore, memory functioning after injection seems related to network topology, indicating that functional performance is related to topological network properties of the brain. PMID:21120140
The Lesioned Brain: Still a Small-World?
Douw, Linda; van Dellen, Edwin; Baayen, Johannes C.; Klein, Martin; Velis, Demetrios N.; Alpherts, Willem C. J.; Heimans, Jan J.; Reijneveld, Jaap C.; Stam, Cornelis Jan
2010-01-01
The intra-arterial amobarbital procedure (IAP or Wada test) is used to determine language lateralization and contralateral memory functioning in patients eligible for neurosurgery because of pharmaco-resistant epilepsy. During unilateral sedation, functioning of the contralateral hemisphere is assessed by means of neuropsychological tests. We use the IAP as a reversible model for the effect of lesions on brain network topology. Three artifact-free epochs (4096 samples) were selected from each electroencephalogram record before and after amobarbital injection. Functional connectivity was assessed by means of the synchronization likelihood. The resulting functional connectivity matrices were constructed for all six epochs per patient in four frequency bands, and weighted network analysis was performed. The clustering coefficient, average path length, small-world index, and edge weight correlation were calculated. Recordings of 33 patients were available. Network topology changed significantly after amobarbital injection: clustering decreased in all frequency bands, while path length decreased in the theta and lower alpha band, indicating a shift toward a more random network topology. Likewise, the edge weight correlation decreased after injection of amobarbital in the theta and beta bands. Network characteristics after injection of amobarbital were correlated with memory score: higher theta band small-world index and increased upper alpha path length were related to better memory score. The whole-brain network topology in patients eligible for epilepsy surgery becomes more random and less optimally organized after selective sedation of one hemisphere, as has been reported in studies with brain tumor patients. Furthermore, memory functioning after injection seems related to network topology, indicating that functional performance is related to topological network properties of the brain. PMID:21120140
Toward IMRT 2D dose modeling using artificial neural networks: A feasibility study
Kalantzis, Georgios; Vasquez-Quino, Luis A.; Zalman, Travis; Pratx, Guillem; Lei, Yu
2011-10-15
Purpose: To investigate the feasibility of artificial neural networks (ANN) to reconstruct dose maps for intensity modulated radiation treatment (IMRT) fields compared with those of the treatment planning system (TPS). Methods: An artificial feed forward neural network and the back-propagation learning algorithm have been used to replicate dose calculations of IMRT fields obtained from PINNACLE{sup 3} v9.0. The ANN was trained with fluence and dose maps of IMRT fields for 6 MV x-rays, which were obtained from the amorphous silicon (a-Si) electronic portal imaging device of Novalis TX. Those fluence distributions were imported to the TPS and the dose maps were calculated on the horizontal midpoint plane of a water equivalent homogeneous cylindrical virtual phantom. Each exported 2D dose distribution from the TPS was classified into two clusters of high and low dose regions, respectively, based on the K-means algorithm and the Euclidian metric in the fluence-dose domain. The data of each cluster were divided into two sets for the training and validation phase of the ANN, respectively. After the completion of the ANN training phase, 2D dose maps were reconstructed by the ANN and isodose distributions were created. The dose maps reconstructed by ANN were evaluated and compared with the TPS, where the mean absolute deviation of the dose and the {gamma}-index were used. Results: A good agreement between the doses calculated from the TPS and the trained ANN was achieved. In particular, an average relative dosimetric difference of 4.6% and an average {gamma}-index passing rate of 93% were obtained for low dose regions, and a dosimetric difference of 2.3% and an average {gamma}-index passing rate of 97% for high dose region. Conclusions: An artificial neural network has been developed to convert fluence maps to corresponding dose maps. The feasibility and potential of an artificial neural network to replicate complex convolution kernels in the TPS for IMRT dose calculations
Güell, Aleix G; Ebejer, Neil; Snowden, Michael E; McKelvey, Kim; Macpherson, Julie V; Unwin, Patrick R
2012-07-17
Carbon nanotubes have attracted considerable interest for electrochemical, electrocatalytic, and sensing applications, yet there remains uncertainty concerning the intrinsic electrochemical (EC) activity. In this study, we use scanning electrochemical cell microscopy (SECCM) to determine local heterogeneous electron transfer (HET) kinetics in a random 2D network of single-walled carbon nanotubes (SWNTs) on an Si/SiO(2) substrate. The high spatial resolution of SECCM, which employs a mobile nanoscale EC cell as a probe for imaging, enables us to sample the responses of individual portions of a wide range of SWNTs within this complex arrangement. Using two redox processes, the oxidation of ferrocenylmethyl trimethylammonium and the reduction of ruthenium (III) hexaamine, we have obtained conclusive evidence for the high intrinsic EC activity of the sidewalls of the large majority of SWNTs in networks. Moreover, we show that the ends of SWNTs and the points where two SWNTs cross do not show appreciably different HET kinetics relative to the sidewall. Using finite element method modeling, we deduce standard rate constants for the two redox couples and demonstrate that HET based solely on characteristic defects in the SWNT side wall is highly unlikely. This is further confirmed by the analysis of individual line profiles taken as the SECCM probe scans over an SWNT. More generally, the studies herein demonstrate SECCM to be a powerful and versatile method for activity mapping of complex electrode materials under conditions of high mass transport, where kinetic assignments can be made with confidence. PMID:22635266
Facial Sketch Synthesis Using 2D Direct Combined Model-Based Face-Specific Markov Network.
Tu, Ching-Ting; Chan, Yu-Hsien; Chen, Yi-Chung
2016-08-01
A facial sketch synthesis system is proposed, featuring a 2D direct combined model (2DDCM)-based face-specific Markov network. In contrast to the existing facial sketch synthesis systems, the proposed scheme aims to synthesize sketches, which reproduce the unique drawing style of a particular artist, where this drawing style is learned from a data set consisting of a large number of image/sketch pairwise training samples. The synthesis system comprises three modules, namely, a global module, a local module, and an enhancement module. The global module applies a 2DDCM approach to synthesize the global facial geometry and texture of the input image. The detailed texture is then added to the synthesized sketch in a local patch-based manner using a parametric 2DDCM model and a non-parametric Markov random field (MRF) network. Notably, the MRF approach gives the synthesized results an appearance more consistent with the drawing style of the training samples, while the 2DDCM approach enables the synthesis of outcomes with a more derivative style. As a result, the similarity between the synthesized sketches and the input images is greatly improved. Finally, a post-processing operation is performed to enhance the shadowed regions of the synthesized image by adding strong lines or curves to emphasize the lighting conditions. The experimental results confirm that the synthesized facial images are in good qualitative and quantitative agreement with the input images as well as the ground-truth sketches provided by the same artist. The representing power of the proposed framework is demonstrated by synthesizing facial sketches from input images with a wide variety of facial poses, lighting conditions, and races even when such images are not included in the training data set. Moreover, the practical applicability of the proposed framework is demonstrated by means of automatic facial recognition tests. PMID:27244737
Possible Origin of Efficient Navigation in Small Worlds
NASA Astrophysics Data System (ADS)
Hu, Yanqing; Wang, Yougui; Li, Daqing; Havlin, Shlomo; di, Zengru
2011-03-01
The small-world phenomenon is one of the most important properties found in social networks. It includes both short path lengths and efficient navigation between two individuals. It is found by Kleinberg that navigation is efficient only if the probability density distribution of an individual to have a friend at distance r scales as P(r)˜r-1. Although this spatial scaling is found in many empirical studies, the origin of how this scaling emerges is still missing. In this Letter, we propose the origin of this scaling law using the concept of entropy from statistical physics and show that this scaling is the result of optimization of collecting information in social networks.
On the relation between the small world structure and scientific activities.
Ebadi, Ashkan; Schiffauerova, Andrea
2015-01-01
The modern science has become more complex and interdisciplinary in its nature which might encourage researchers to be more collaborative and get engaged in larger collaboration networks. Various aspects of collaboration networks have been examined so far to detect the most determinant factors in knowledge creation and scientific production. One of the network structures that recently attracted much theoretical attention is called small world. It has been suggested that small world can improve the information transmission among the network actors. In this paper, using the data on 12 periods of journal publications of Canadian researchers in natural sciences and engineering, the co-authorship networks of the researchers are created. Through measuring small world indicators, the small worldiness of the mentioned network and its relation with researchers' productivity, quality of their publications, and scientific team size are assessed. Our results show that the examined co-authorship network strictly exhibits the small world properties. In addition, it is suggested that in a small world network researchers expand their team size through getting connected to other experts of the field. This team size expansion may result in higher productivity of the whole team as a result of getting access to new resources, benefitting from the internal referring, and exchanging ideas among the team members. Moreover, although small world network is positively correlated with the quality of the articles in terms of both citation count and journal impact factor, it is negatively related with the average productivity of researchers in terms of the number of their publications. PMID:25780922
On the Relation between the Small World Structure and Scientific Activities
Ebadi, Ashkan; Schiffauerova, Andrea
2015-01-01
The modern science has become more complex and interdisciplinary in its nature which might encourage researchers to be more collaborative and get engaged in larger collaboration networks. Various aspects of collaboration networks have been examined so far to detect the most determinant factors in knowledge creation and scientific production. One of the network structures that recently attracted much theoretical attention is called small world. It has been suggested that small world can improve the information transmission among the network actors. In this paper, using the data on 12 periods of journal publications of Canadian researchers in natural sciences and engineering, the co-authorship networks of the researchers are created. Through measuring small world indicators, the small worldiness of the mentioned network and its relation with researchers’ productivity, quality of their publications, and scientific team size are assessed. Our results show that the examined co-authorship network strictly exhibits the small world properties. In addition, it is suggested that in a small world network researchers expand their team size through getting connected to other experts of the field. This team size expansion may result in higher productivity of the whole team as a result of getting access to new resources, benefitting from the internal referring, and exchanging ideas among the team members. Moreover, although small world network is positively correlated with the quality of the articles in terms of both citation count and journal impact factor, it is negatively related with the average productivity of researchers in terms of the number of their publications. PMID:25780922
Consensus Problems on Small World Graphs: A Structural Study
NASA Astrophysics Data System (ADS)
Hovareshti, Pedram; Baras, John S.
Consensus problems arise in many instances of collaborative control of multi-agent complex systems; where it is important for the agents to act in coordination with the other agents. To reach coordination, agents need to share information. In large groups of agents the information sharing should be local in some sense, due to energy limitations, reliability, and other constraints. A consensus protocol is an iterative method that provides the group with a common coordination variable. However, local information exchange limits the speed of convergence of such protocols. Therefore, in order to achieve high convergence speed, we should be able to design appropriate network topologies. A reasonable conjecture is that the small world graphs should result in good convergence speed for consensus problems because their low average pairwise path length should speed the diffusion of information in the system. In this paper we address this conjecture by simulations and also by studying the spectral properties of a class of matrices corresponding to consensus problems on small world graphs.
Formats and Network Protocols for Browser Access to 2D Raster Data
NASA Astrophysics Data System (ADS)
Plesea, L.
2015-12-01
Tiled web maps in browsers are a major success story, forming the foundation of many current web applications. Enabling tiled data access is the next logical step, and is likely to meet with similar success. Many ad-hoc approaches have already started to appear, and something similar is explored within the Open Geospatial Consortium. One of the main obstacles in making browser data access a reality is the lack of a well-known data format. This obstacle also represents an opportunity to analyze the requirements and possible candidates, applying lessons learned from web tiled image services and protocols. Similar to the image counterpart, a web tile raster data format needs to have good intrinsic compression and be able to handle high byte count data types including floating point. An overview of a possible solution to the format problem, a 2D data raster compression algorithm called Limited Error Raster Compression (LERC) will be presented. In addition to the format, best practices for high request rate HTTP services also need to be followed. In particular, content delivery network (CDN) caching suitability needs to be part of any design, not an after-thought. Last but not least, HTML 5 browsers will certainly be part of any solution since they provide improved access to binary data, as well as more powerful ways to view and interact with the data in the browser. In a simple but relevant application, digital elevation model (DEM) raster data is served as LERC compressed data tiles which are used to generate terrain by a HTML5 scene viewer.
Space missions orbits around small worlds
NASA Astrophysics Data System (ADS)
Cardoso dos Santos, Josué; dos Santos Carvalho, Jean Paulo; Vilhena de Moraes, Rodolpho; Bertachini de Almeida Prado, Antônio Fernando
2015-08-01
Space missions under study to visit icy moons and small worlds in our solar system will requires orbits with low-altitude and high inclinations. These orbits provides a better coverage to map the surface and to analyse the gravitational and magnetic fields. In this context, obtain these orbits has become important in planning of these missions. Celestial bodies like Haumea, Europa, Ganymede, Callisto, Enceladus, Titan and Triton are among the objects under study study to receive missions in a near future. In order to obtain low-altitude and high inclined orbits for future exploration of these bodies, this work aims to present an analytical study to describe and evaluate gravitational disturbances over a spacecraft's orbit around a minor body. An analytical model for the third-body perturbation is presented. Perturbations due to the non-sphericity of the minor body are considered. The effects on spacecraft's orbital elements are analyzed to provide the the more useful and desired orbits. The dynamic of these orbits is explored by numerical simulations. The results present good accordance with the literature.
Shi, Li; Niu, Xiaoke; Wan, Hong
2015-05-01
The biological networks have been widely reported to present small-world properties. However, the effects of small-world network structure on population's encoding performance remain poorly understood. To address this issue, we applied a small world-based framework to quantify and analyze the response dynamics of cell assemblies recorded from rat primary visual cortex, and further established a population encoding model based on small world-based generalized linear model (SW-GLM). The electrophysiological experimental results show that the small world-based population responses to different topological shapes present significant variation (t test, p < 0.01; effect size: Hedge's g > 0.8), while no significant variation was found for control networks without considering their spatial connectivity (t test, p > 0.05; effect size: Hedge's g < 0.5). Furthermore, the numerical experimental results show that the predicted response under SW-GLM is more accurate and reliable compared to the control model without small-world structure, and the decoding performance is also improved about 10 % by taking the small-world structure into account. The above results suggest the important role of the small-world neural structure in encoding visual information for the neural population by providing electrophysiological and theoretical evidence, respectively. The study helps greatly to well understand the population encoding mechanisms of visual cortex. PMID:25764307
NASA Astrophysics Data System (ADS)
Rabbani, Arash; Ayatollahi, Shahab; Kharrat, Riyaz; Dashti, Nader
2016-08-01
In this study, we have utilized 3-D micro-tomography images of real and synthetic rocks to introduce two mathematical correlations which estimate the distribution parameters of 3-D coordination number using a single 2-D cross-sectional image. By applying a watershed segmentation algorithm, it is found that the distribution of 3-D coordination number is acceptably predictable by statistical analysis of the network extracted from 2-D images. In this study, we have utilized 25 volumetric images of rocks in order to propose two mathematical formulas. These formulas aim to approximate the average and standard deviation of coordination number in 3-D pore networks. Then, the formulas are applied for five independent test samples to evaluate the reliability. Finally, pore network flow modeling is used to find the error of absolute permeability prediction using estimated and measured coordination numbers. Results show that the 2-D images are considerably informative about the 3-D network of the rocks and can be utilized to approximate the 3-D connectivity of the porous spaces with determination coefficient of about 0.85 that seems to be acceptable considering the variety of the studied samples.
2D warp-and-woof interwoven networks constructed by helical chains with different chirality.
Feng, Yuhua; Guo, Yang; OuYang, Yan; Liu, Zhanquan; Liao, Daizheng; Cheng, Peng; Yan, Shiping; Jiang, Zonghui
2007-09-21
Two unprecedented 2D entangled layers of warp-and-woof threads interwoven by left- and right-handed helical chains, {[Mn(salen)Au(CN)2]4(H2O)}n (salen = N,N'-ethylenebis(salicylideneaminato)) and {Mn(acacen)Ag(CN)2}n (acacen = N,N'-ethylenebis(acetylacetonylideneiminate)) 2, have been synthesized and characterized. PMID:17728880
Observation of kinetic networks of hydrogen-bond exchange using 2D IR echo spectroscopy
NASA Astrophysics Data System (ADS)
Kim, Yung Sam; Hochstrasser, Robin M.
The ultrafast H-bond motion in acetonitrile/methanol and of methanol and water around a dicarbonyl (piperidone) dominates the mechanism of vibrational coherence transfer in linear and 2D IR echo spectra. Multiple state coherence transfer and energy transfer are seen at and between the two carbonyl groups of the piperidone in both water and methanol.
Coevolutionary dynamics of opinion propagation and social balance: The key role of small-worldness
NASA Astrophysics Data System (ADS)
Chen, Yan; Chen, Lixue; Sun, Xian; Zhang, Kai; Zhang, Jie; Li, Ping
2014-03-01
The propagation of various opinions in social networks, which influences human inter-relationships and even social structure, and hence is a most important part of social life. We have incorporated social balance into opinion propagation in social networks are influenced by social balance. The edges in networks can represent both friendly or hostile relations, and change with the opinions of individual nodes. We introduce a model to characterize the coevolutionary dynamics of these two dynamical processes on Watts-Strogatz (WS) small-world network. We employ two distinct evolution rules (i) opinion renewal; and (ii) relation adjustment. By changing the rewiring probability, and thus the small-worldness of the WS network, we found that the time for the system to reach balanced states depends critically on both the average path length and clustering coefficient of the network, which is different than other networked process like epidemic spreading. In particular, the system equilibrates most quickly when the underlying network demonstrates strong small-worldness, i.e., small average path lengths and large clustering coefficient. We also find that opinion clusters emerge in the process of the network approaching the global equilibrium, and a measure of global contrariety is proposed to quantify the balanced state of a social network.
NASA Astrophysics Data System (ADS)
Zhang, Z.-Z.; Zhou, S.-G.; Zou, T.
2007-04-01
In this paper, firstly, we study analytically the topological features of a family of hierarchical lattices (HLs) from the view point of complex networks. We derive some basic properties of HLs controlled by a parameter q: scale-free degree distribution with exponent γ=2+ln 2/(ln q), null clustering coefficient, power-law behavior of grid coefficient, exponential growth of average path length (non-small-world), fractal scaling with dimension dB=ln (2q)/(ln 2), and disassortativity. Our results show that scale-free networks are not always small-world, and support the conjecture that self-similar scale-free networks are not assortative. Secondly, we define a deterministic family of graphs called small-world hierarchical lattices (SWHLs). Our construction preserves the structure of hierarchical lattices, including its degree distribution, fractal architecture, clustering coefficient, while the small-world phenomenon arises. Finally, the dynamical processes of intentional attacks and collective synchronization are studied and the comparisons between HLs and Barabási-Albert (BA) networks as well as SWHLs are shown. We find that the self-similar property of HLs and SWHLs significantly increases the robustness of such networks against targeted damage on hubs, as compared to the very vulnerable non fractal BA networks, and that HLs have poorer synchronizability than their counterparts SWHLs and BA networks. We show that degree distribution of scale-free networks does not suffice to characterize their synchronizability, and that networks with smaller average path length are not always easier to synchronize.
Tuning the resonance properties of 2D carbon nanotube networks towards a mechanical resonator
NASA Astrophysics Data System (ADS)
Zhan, Haifei; Zhang, Guiyong; Zhang, Baocheng; Bell, John M.; Gu, Yuantong
2015-08-01
The capabilities of the mechanical resonator-based nanosensors in detecting ultra-small mass or force shifts have driven a continuing exploration of the palette of nanomaterials for such application purposes. Based on large-scale molecular dynamics simulations, we have assessed the applicability of a new class of carbon nanomaterials for nanoresonator usage, i.e. the single-wall carbon nanotube (SWNT) network. It is found that SWNT networks inherit excellent mechanical properties from the constituent SWNTs, possessing a high natural frequency. However, although a high quality factor is suggested from the simulation results, it is hard to obtain an unambiguous Q-factor due to the existence of vibration modes in addition to the dominant mode. The nonlinearities resulting from these extra vibration modes are found to exist uniformly under various testing conditions including different initial actuations and temperatures. Further testing shows that these modes can be effectively suppressed through the introduction of axial strain, leading to an extremely high quality factor in the order of 109 estimated from the SWNT network with 2% tensile strain. Additional studies indicate that the carbon rings connecting the SWNTs can also be used to alter the vibrational properties of the resulting network. This study suggests that the SWNT network can be a good candidate for applications as nanoresonators.
Tuning the resonance properties of 2D carbon nanotube networks towards a mechanical resonator.
Zhan, Haifei; Zhang, Guiyong; Zhang, Baocheng; Bell, John M; Gu, Yuantong
2015-08-01
The capabilities of the mechanical resonator-based nanosensors in detecting ultra-small mass or force shifts have driven a continuing exploration of the palette of nanomaterials for such application purposes. Based on large-scale molecular dynamics simulations, we have assessed the applicability of a new class of carbon nanomaterials for nanoresonator usage, i.e. the single-wall carbon nanotube (SWNT) network. It is found that SWNT networks inherit excellent mechanical properties from the constituent SWNTs, possessing a high natural frequency. However, although a high quality factor is suggested from the simulation results, it is hard to obtain an unambiguous Q-factor due to the existence of vibration modes in addition to the dominant mode. The nonlinearities resulting from these extra vibration modes are found to exist uniformly under various testing conditions including different initial actuations and temperatures. Further testing shows that these modes can be effectively suppressed through the introduction of axial strain, leading to an extremely high quality factor in the order of 10(9) estimated from the SWNT network with 2% tensile strain. Additional studies indicate that the carbon rings connecting the SWNTs can also be used to alter the vibrational properties of the resulting network. This study suggests that the SWNT network can be a good candidate for applications as nanoresonators. PMID:26184034
A Novel Crosstalk Suppression Method of the 2-D Networked Resistive Sensor Array
Wu, Jianfeng; Wang, Lei; Li, Jianqing; Song, Aiguo
2014-01-01
The 2-D resistive sensor array in the row–column fashion suffered from the crosstalk problem for parasitic parallel paths. Firstly, we proposed an Improved Isolated Drive Feedback Circuit with Compensation (IIDFCC) based on the voltage feedback method to suppress the crosstalk. In this method, a compensated resistor was specially used to reduce the crosstalk caused by the column multiplexer resistors and the adjacent row elements. Then, a mathematical equivalent resistance expression of the element being tested (EBT) of this circuit was analytically derived and verified by the circuit simulations. The simulation results show that the measurement method can greatly reduce the influence on the EBT caused by parasitic parallel paths for the multiplexers' channel resistor and the adjacent elements. PMID:25046011
A 2D zinc-organic network being easily exfoliated into isolated sheets
NASA Astrophysics Data System (ADS)
Yu, Guihong; Li, Ruiqing; Leng, Zhihua; Gan, Shucai
2016-08-01
A metal-organic aggregate, namely {Zn2Cl2(BBC)}n (BBC = 4,4‧,4‧‧-(benzene-1,3,5-triyl-tris(benzene-4,1-diyl))tribenzoate) was obtained by solvothermal synthesis. Its structure is featured with the Zn2(COO)3 paddle-wheels with two chloride anions on axial positions and hexagonal pores in the layers. The exclusion of water in the precursor and the solvent plays a crucial role in the formation of target compound. This compound can be easily dissolved in alkaline solution and exfoliated into isolated sheets, which shows a novel way for the preparation of 2D materials.
Ferrimagnetism in 2D networks of porphyrin-X and -XO (X=Sc,...,Zn) with acetylene bridges
NASA Astrophysics Data System (ADS)
Wierzbowska, Małgorzata; Sobolewski, Andrzej L.
2016-03-01
Magnetism in 2D networks of the acetylene-bridged transition metal porphyrins M(P)-2(C-C)-2 (denoted P-TM), and oxo-TM-porphyrins OM(P)-2(C-C)-2 (denoted P-TMO), is studied with the density functional theory (DFT) and the self-interaction corrected pseudopotential scheme (pSIC). Addition of oxygen lowers magnetism of P-TMO with respect to the corresponding P-TM for most of the first-half 3d-row TMs. In contrast, binding O with the second-half 3d-row TMs or Sc increases the magnetic moments. Ferrimagnetism is found for the porphyrin networks with the TMs from V to Co and also for these cases with oxygen. This is a long-range effect of the delocalized spin-polarization, extended even to the acetylene bridges.
Dynamic force measurement of rearrangements in a 2D network of droplets
NASA Astrophysics Data System (ADS)
Barkley, Solomon; Backholm, Matilda; Dalnoki-Veress, Kari
2015-03-01
The interaction between two liquid droplets in an immiscible liquid is well understood. However, the emulsions relevant to biological and industrial processes involve high concentrations of these droplets, and multi-body effects cannot be ignored. As droplets rearrange in response to a disturbance, the importance of individual pair-wise interactions between droplets changes with the geometry of neighbours. Here we report on an experimental setup consisting of a two- dimensional network of monodisperse droplets stabilized with a surfactant. The system is studied with micropipette deflection, which permits direct measurement of forces along with simultaneous imaging of the droplet network. One micropipette is used to apply a tensile or compressive force to the droplet cluster, while a second pipette acts as a force-transducing cantilever, deflecting in response to rearrangements of the droplets.
Power Versus Spectrum 2-D Sensing in Energy Harvesting Cognitive Radio Networks
NASA Astrophysics Data System (ADS)
Zhang, Yanyan; Han, Weijia; Li, Di; Zhang, Ping; Cui, Shuguang
2015-12-01
Energy harvester based cognitive radio is a promising solution to address the shortage of both spectrum and energy. Since the spectrum access and power consumption patterns are interdependent, and the power value harvested from certain environmental sources are spatially correlated, the new power dimension could provide additional information to enhance the spectrum sensing accuracy. In this paper, the Markovian behavior of the primary users is considered, based on which we adopt a hidden input Markov model to specify the primary vs. secondary dynamics in the system. Accordingly, we propose a 2-D spectrum and power (harvested) sensing scheme to improve the primary user detection performance, which is also capable of estimating the primary transmit power level. Theoretical and simulated results demonstrate the effectiveness of the proposed scheme, in term of the performance gain achieved by considering the new power dimension. To the best of our knowledge, this is the first work to jointly consider the spectrum and power dimensions for the cognitive primary user detection problem.
Contact transfer length investigation of a 2D nanoparticle network by scanning probe microscopy.
Ruiz-Vargas, Carlos S; Reissner, Patrick A; Wagner, Tino; Wyss, Roman M; Park, Hyung Gyu; Stemmer, Andreas
2015-09-11
Nanoparticle network devices find growing application in sensing and electronics. One recurring challenge in the design and fabrication of this class of devices is ensuring a stable interface via robust yet unobstructive electrodes. A figure of merit which dictates the minimum electrode overlap required for optimal charge injection into the network is the contact transfer length. However, we find that traditional contact characterization using the transmission line model, an indirect method which requires extrapolation, is insufficient for network devices. Instead, we apply Kelvin probe force microscopy to characterize the contact resistance by imaging the surface potential with nanometer resolution. We then use scanning probe lithography to directly investigate the contact transfer length. We have determined the transfer length in graphene contacted devices to be 200-400 nm, thus apt for further device reduction which is often necessary for on-site sensing applications. Simulations from a two-dimensional resistor model support our observations and are expected to be an important tool for further optimizing the design of nanoparticle-based devices. PMID:26291069
Fracture network evaluation program (FraNEP): A software for analyzing 2D fracture trace-line maps
NASA Astrophysics Data System (ADS)
Zeeb, Conny; Gomez-Rivas, Enrique; Bons, Paul D.; Virgo, Simon; Blum, Philipp
2013-10-01
Fractures, such as joints, faults and veins, strongly influence the transport of fluids through rocks by either enhancing or inhibiting flow. Techniques used for the automatic detection of lineaments from satellite images and aerial photographs, LIDAR technologies and borehole televiewers significantly enhanced data acquisition. The analysis of such data is often performed manually or with different analysis software. Here we present a novel program for the analysis of 2D fracture networks called FraNEP (Fracture Network Evaluation Program). The program was developed using Visual Basic for Applications in Microsoft Excel™ and combines features from different existing software and characterization techniques. The main novelty of FraNEP is the possibility to analyse trace-line maps of fracture networks applying the (1) scanline sampling, (2) window sampling or (3) circular scanline and window method, without the need of switching programs. Additionally, binning problems are avoided by using cumulative distributions, rather than probability density functions. FraNEP is a time-efficient tool for the characterisation of fracture network parameters, such as density, intensity and mean length. Furthermore, fracture strikes can be visualized using rose diagrams and a fitting routine evaluates the distribution of fracture lengths. As an example of its application, we use FraNEP to analyse a case study of lineament data from a satellite image of the Oman Mountains.
Detecting 2D symmetry-protected topological phases with the tensor-network method
NASA Astrophysics Data System (ADS)
Huang, Ching-Yu; Wei, Tzu-Chieh
Symmetry-protected topological (SPT) phases exhibit nontrivial order if symmetry is respected but are adiabatically connected to the trivial product phase if symmetry is not respected. However, unlike the symmetry breaking phase, there is no local order parameter for SPT phases. Here we employ a tensor-network method to compute the topological invariants characterized by the simulated modular S and T matrices proposed by Hung and Wen to study a transition in a one-parameter family of wavefunctions which are Z2 symmetric. The studied wavefunctions are in some sense the SPT analog of Z2 topological states under a string tension. The numerically obtained S and T matrices are able to characterize the two different phases and identify the transition point.
A small-world-based population encoding model of the primary visual cortex.
Shi, Li; Niu, Xiaoke; Wan, Hong; Shang, Zhigang; Wang, Zhizhong
2015-06-01
A wide range of evidence has shown that information encoding performed by the visual cortex involves complex activities of neuronal populations. However, the effects of the neuronal connectivity structure on the population's encoding performance remain poorly understood. In this paper, a small-world-based population encoding model of the primary visual cortex (V1) is established on the basis of the generalized linear model (GLM) to describe the computation of the neuronal population. The model mainly consists of three sets of filters, including a spatiotemporal stimulus filter, a post-spike history filter, and a set of coupled filters with the coupling neurons organizing as a small-world network. The parameters of the model were fitted with neuronal data of the rat V1 recorded with a micro-electrode array. Compared to the traditional GLM, without considering the small-world structure of the neuronal population, the proposed model was proved to produce more accurate spiking response to grating stimuli and enhance the capability of the neuronal population to carry information. The comparison results proved the validity of the proposed model and further suggest the role of small-world structure in the encoding performance of local populations in V1, which provides new insights for understanding encoding mechanisms of a small scale population in visual system. PMID:25753903
Nanophotonic Filters and Integrated Networks in Flexible 2D Polymer Photonic Crystals
Gan, Xuetao; Clevenson, Hannah; Tsai, Cheng-Chia; Li, Luozhou; Englund, Dirk
2013-01-01
Polymers have appealing optical, biochemical, and mechanical qualities, including broadband transparency, ease of functionalization, and biocompatibility. However, their low refractive indices have precluded wavelength-scale optical confinement and nanophotonic applications in polymers. Here, we introduce a suspended polymer photonic crystal (SPPC) architecture that enables the implementation of nanophotonic structures typically limited to high-index materials. Using the SPPC platform, we demonstrate nanophotonic band-edge filters, waveguides, and nanocavities featuring quality (Q) factors exceeding 2, 300 and mode volumes (Vmode) below 1.7(λ/n)3. The unprecedentedly high Q/Vmode ratio results in a spectrally selective enhancement of radiative transitions of embedded emitters via the cavity Purcell effect with an enhancement factor exceeding 100. Moreover, the SPPC architecture allows straightforward integration of nanophotonic networks, shown here by a waveguide-coupled cavity drop filter with sub-nanometer spectral resolution. The nanoscale optical confinement in polymer promises new applications ranging from optical communications to organic opto-electronics, and nanophotonic polymer sensors. PMID:23828320
Gállego, Isaac; Oncins, Gerard; Sisquella, Xavier; Fernàndez-Busquets, Xavier; Daban, Joan-Ramon
2010-01-01
In a previous study, we found that metaphase chromosomes are formed by thin plates, and here we have applied atomic force microscopy (AFM) and friction force measurements at the nanoscale (nanotribology) to analyze the properties of these planar structures in aqueous media at room temperature. Our results show that high concentrations of NaCl and EDTA and extensive digestion with protease and nuclease enzymes cause plate denaturation. Nanotribology studies show that native plates under structuring conditions (5 mM Mg2+) have a relatively high friction coefficient (μ ≈ 0.3), which is markedly reduced when high concentrations of NaCl or EDTA are added (μ ≈ 0.1). This lubricant effect can be interpreted considering the electrostatic repulsion between DNA phosphate groups and the AFM tip. Protease digestion increases the friction coefficient (μ ≈ 0.5), but the highest friction is observed when DNA is cleaved by micrococcal nuclease (μ ≈ 0.9), indicating that DNA is the main structural element of plates. Whereas nuclease-digested plates are irreversibly damaged after the friction measurement, native plates can absorb kinetic energy from the AFM tip without suffering any damage. These results suggest that plates are formed by a flexible and mechanically resistant two-dimensional network which allows the safe storage of DNA during mitosis. PMID:21156137
Small Worlds Week: Raising Curiosity and Contributing to STEM
NASA Astrophysics Data System (ADS)
Ng, C.; Mayo, L.; Stephenson, B. E.; Keck, A.; Cline, T. D.; Lewis, E. M.
2015-12-01
Dwarf planets, comets, asteroids, and icy moons took center stage in the years 2014-2015 as multiple spacecraft (New Horizons, Dawn, Rosetta, Cassini) and ground-based observing campaigns observed these small and yet amazing celestial bodies. Just prior to the historic New Horizons encounter with the Pluto system, NASA celebrated Small Worlds Week (July 6-10) as a fully online program to highlight small worlds mission discoveries. Small Worlds Week leveraged the infrastructure of Sun-Earth Days that included a robust web design, exemplary education materials, hands-on fun activities, multimedia resources, science and career highlights, and a culminating event. Each day from July 6-9, a new class of solar system small worlds was featured on the website: Monday-comets, Tuesday-asteroids, Wednesday-icy moons, and Thursday-dwarf planets. Then on Friday, July 10, nine scientists from Goddard Space Flight Center, Jet Propulsion Laboratory, Naval Research Laboratory, and Lunar and Planetary Institute gathered online for four hours to answer questions from the public via Facebook and Twitter. Throughout the afternoon the scientists worked closely with a social media expert and several summer interns to reply to inquirers and to archive their chats. By all accounts, Small Worlds Week was a huge success. The group plans to improve and replicate the program during the school year with a more classroom focus, and then to build and extend the program to be held every year. For more information, visit http:// sunearthday.nasa.gov or catch us on Twitter, #nasasww.
Recursive graphs with small-world scale-free properties
NASA Astrophysics Data System (ADS)
Comellas, Francesc; Fertin, Guillaume; Raspaud, André
2004-03-01
We discuss a category of graphs, recursive clique trees, which have small-world and scale-free properties and allow a fine tuning of the clustering and the power-law exponent of their discrete degree distribution. We determine relevant characteristics of those graphs: the diameter, degree distribution, and clustering parameter. The graphs have also an interesting recursive property, and generalize recent constructions with fixed degree distributions.
NASA Astrophysics Data System (ADS)
Mei, Hong-Xin; Zhang, Ting; Huang, Hua-Qi; Huang, Rong-Bin; Zheng, Lan-Sun
2016-03-01
Three mix-ligand Ag(I) coordination compounds, namely, {[Ag10(tpyz) 5(L1) 5(H2 O)2].(H2 O)4}n (1, tpyz = 2,3,4,5-tetramethylpyrazine, H2 L1 = phthalic acid), [Ag4(tpyz) 2(L2) 2(H2 O)].(H2 O)5}n (2, H2 L2 = isophthalic acid) {[Ag2(tpyz) 2(L3) (H2 O)4].(H2 O)8}n (3, H2 L3 = terephthalic acid), have been synthesized and characterized by elemental analysis, IR, PXRD and X-ray single-crystal diffraction. 1 exhibits a 2D layer which can be simplified as a (4,4) net. 2 is a 3D network which can be simplified as a (3,3)-connected 2-nodal net with a point symbol of {102.12}{102}. 3 consists of linear [Ag(tpyz) (H2 O)2]n chain. Of particular interest, discrete hexamer water clusters were observed in 1 and 2, while a 2D L10(6) water layer exists in 3. The results suggest that the benzene dicarboxylates play pivotal roles in the formation of the different host architectures as well as different water aggregations. Moreover, thermogravimetric analysis (TGA) and emissive behaviors of these compounds were investigated.
Geographical threshold graphs with small-world and scale-free properties.
Masuda, Naoki; Miwa, Hiroyoshi; Konno, Norio
2005-03-01
Many real networks are equipped with short diameters, high clustering, and power-law degree distributions. With preferential attachment and network growth, the model by Barabási and Albert simultaneously reproduces these properties, and geographical versions of growing networks have also been analyzed. However, nongrowing networks with intrinsic vertex weights often explain these features more plausibly, since not all networks are really growing. We propose a geographical nongrowing network model with vertex weights. Edges are assumed to form when a pair of vertices are spatially close and/or have large summed weights. Our model generalizes a variety of models as well as the original nongeographical counterpart, such as the unit disk graph, the Boolean model, and the gravity model, which appear in the contexts of percolation, wire communication, mechanical and solid physics, sociology, economy, and marketing. In appropriate configurations, our model produces small-world networks with power-law degree distributions. We also discuss the relation between geography, power laws in networks, and power laws in general quantities serving as vertex weights. PMID:15903494
Ciompi, Francesco; de Hoop, Bartjan; van Riel, Sarah J; Chung, Kaman; Scholten, Ernst Th; Oudkerk, Matthijs; de Jong, Pim A; Prokop, Mathias; van Ginneken, Bram
2015-12-01
In this paper, we tackle the problem of automatic classification of pulmonary peri-fissural nodules (PFNs). The classification problem is formulated as a machine learning approach, where detected nodule candidates are classified as PFNs or non-PFNs. Supervised learning is used, where a classifier is trained to label the detected nodule. The classification of the nodule in 3D is formulated as an ensemble of classifiers trained to recognize PFNs based on 2D views of the nodule. In order to describe nodule morphology in 2D views, we use the output of a pre-trained convolutional neural network known as OverFeat. We compare our approach with a recently presented descriptor of pulmonary nodule morphology, namely Bag of Frequencies, and illustrate the advantages offered by the two strategies, achieving performance of AUC = 0.868, which is close to the one of human experts. PMID:26458112
A 2-D Pore-Network Model of the Drying of Single-Component Liquids in Porous Media
Yortsos, Yanic C.; Yiotis, A.G.; Stubos, A.K.; Boundovis, A.G.
2000-01-20
The drying of liquid-saturated porous media is typically approaching using macroscopic continuum models involving phenomenological coefficients. Insight on these coefficients can be obtained by a more fundamental study at the pore- and pore-network levels. In this report, a model based on pore-network representation of porous media that accounts for various process at the pore-scale is presented. These include mass transfer by advection and diffusion in the gas phase, viscous flow in liquid and gas phases and capillary effects at the gas-liquid menisci in the pore throats.
NASA Astrophysics Data System (ADS)
Villalobos, Gabriel; Linero, Dorian L.; Muñoz, José D.
2011-01-01
A 2D, hexagonal in geometry, statistical model of fracture is proposed. The model is based on the drying fracture process of the bamboo Guadua angustifolia. A network of flexible cells are joined by brittle junctures of fixed Young moduli that break at a certain thresholds in tensile force. The system is solved by means of the Finite Element Method (FEM). The distribution of avalanche breakings exhibits a power law with exponent -2.93(9), in agreement with the random fuse model (Bhattacharyya and Chakrabarti, 2006) [1].
Thuéry, Pierre; Harrowfield, Jack
2015-08-17
4,4'-Biphenyldicarboxylic acid (H2L) was reacted with uranyl ions under solvo-hydrothermal conditions with variations in the experimental procedure (organic cosolvent, presence of additional 3d-block metal cations, and N-donor species), thus giving six complexes of the fully deprotonated acid that were characterized by their crystal structure and, in most cases, their emission spectrum. The three complexes [UO2(L)(DMA)] (1), [UO2(L)(NMP)] (2), and [UO2(L)(NMP)] (3) include the cosolvent as a coligand, and they crystallize as two-dimensional (2D) assemblies, with different combinations of the chelating and bridging-bidentate carboxylate coordination modes, resulting in two different topologies. Complex 4, [Ni(bipy)3][(UO2)2(L)2(C2O4)]·H2O, includes oxalate coligands generated in situ and contains an anionic planar two-dimensional (2D) assembly with a {6(3)} honeycomb topology. The same hexagonal geometry is found in the homoleptic complexes [Ni(bipy)3][(UO2)2(L)3]·6H2O (5) and [Ni(phen)3][(UO2)2(L)3]·4H2O (6), but the large size of the hexagonal rings in these cases (∼27 Å in the longest dimension) allows 2D → three-dimensional (3D) inclined polycatenation to occur, with the two families of networks either orthogonal in tetragonal complex 5 or at an angle of 73.4° in orthorhombic complex 6. The parallel networks are arranged in closely spaced groups of two, with possible π···π stacking interactions, and as many as four rods from four parallel nets pass through each ring of the inclined family of nets, an unusually high degree of catenation. These are the second cases only of 2D → 3D inclined polycatenation in uranyl-organic species. Emission spectra measured in the solid state show the usual vibronic fine structure, with variations in intensity and positions of maxima that are not simply connected with the number of equatorial donors and the presence of additional metal cations. PMID:26241368
Six Degrees of Information Seeking: Stanley Milgram and the Small World of the Library
ERIC Educational Resources Information Center
James, Kathryn
2006-01-01
Stanley Milgram's 1967 "small world" social connectivity study is used to analyze information connectivity, or patron information-seeking behavior. The "small world" study, upon examination, offers a clear example of the failure of social connectivity. This failure is used to highlight the importance of the subjectivities of patron experience of…
Unimodular lattice triangulations as small-world and scale-free random graphs
NASA Astrophysics Data System (ADS)
Krüger, B.; Schmidt, E. M.; Mecke, K.
2015-02-01
Real-world networks, e.g., the social relations or world-wide-web graphs, exhibit both small-world and scale-free behaviour. We interpret lattice triangulations as planar graphs by identifying triangulation vertices with graph nodes and one-dimensional simplices with edges. Since these triangulations are ergodic with respect to a certain Pachner flip, applying different Monte Carlo simulations enables us to calculate average properties of random triangulations, as well as canonical ensemble averages, using an energy functional that is approximately the variance of the degree distribution. All considered triangulations have clustering coefficients comparable with real-world graphs; for the canonical ensemble there are inverse temperatures with small shortest path length independent of system size. Tuning the inverse temperature to a quasi-critical value leads to an indication of scale-free behaviour for degrees k≥slant 5. Using triangulations as a random graph model can improve the understanding of real-world networks, especially if the actual distance of the embedded nodes becomes important.
NASA Astrophysics Data System (ADS)
Gravalos, I.; Moshou, D.; Loutridis, S.; Gialamas, Th.; Kateris, D.; Bompolas, E.; Tsiropoulos, Z.; Xyradakis, P.; Fountas, S.
2013-08-01
In this study a prototype sensor-based platform moving inside a subsurface network of pipes with the task of monitoring the soil moisture content is presented. It comprises of a mobile platform, a modified commercial soil moisture sensor (Diviner 2000), a network of subsurface polyvinylchloride (PVC) access pipes, driving hardware and image processing software. The software allows the composition of two-dimensional (2D) or three-dimensional (3D) images with high accuracy and at a large scale. The 3D soil moisture images are created by using 2D slices for better illustration of the soil moisture variability. Three case studies of varying soil moisture content using an experimental soil tank were examined. In the first case study, the irrigation water was applied uniformly on the entire tank surface. In second and third case studies, the irrigation water was applied uniformly only on the surface of the intermediate and last part of the soil tank respectively. The processed images give a detailed description of the soil moisture distribution of a layer at 15 cm depth under the soil surface in the tank. In all case studies that have been investigated, the distribution of soil moisture was characterized by a significant variability (difference between poorly and well-drained regions) of the soil tank. A very poorly-drained region was located in the middle of the soil tank, while well-drained soil areas were located southwest and northeast. The knowledge of the spatial and temporal distribution of soil moisture is a valuable tool for proper management of crop irrigation.
Small-world characteristics of EEG patterns in post-anoxic encephalopathy.
Beudel, Martijn; Tjepkema-Cloostermans, Marleen C; Boersma, Jochem H; van Putten, Michel J A M
2014-01-01
Post-anoxic encephalopathy (PAE) has a heterogenous outcome which is difficult to predict. At present, it is possible to predict poor outcome using somatosensory evoked potentials in only a minority of the patients at an early stage. In addition, it remains difficult to predict good outcome at an early stage. Network architecture, as can be quantified with continuous electroencephalography (cEEG), may serve as a candidate measure for predicting neurological outcome. Here, we explore whether cEEG monitoring can be used to detect the integrity of neural network architecture in patients with PAE after cardiac arrest. From 56 patients with PAE treated with mild therapeutic hypothermia, 19-channel cEEG data were recorded starting as soon as possible after cardiac arrest. Adjacency matrices of shared frequencies between 1 and 25 Hz of the EEG channels were obtained using Fourier transformations. Number of network nodes and connections, clustering coefficient (C), average path length (L), and small-world index (SWI) were derived. Outcome was quantified by the best cerebral performance category (CPC)-score within 6 months. Compared to non-survivors, survivors showed significantly more nodes and connections. L was significantly higher and C and SWI were significantly lower in the survivor group than in the non-survivor group. The number of nodes, connections, and the L were negatively correlated with the CPC-score. C and SWI correlated positively with the CPC-score. The combination of number of nodes, connections, C, and L showed the most significant difference and correlation between survivors and non-survivors and CPC-score. Our data might implicate that non-survivors have insufficient distribution and differentiation of neural activity for regaining normal brain function. These network differences, already present during hypothermia, might be further developed as early prognostic markers. The predictive values are however still inferior to current practice parameters
The structure of borders in a small world.
Thiemann, Christian; Theis, Fabian; Grady, Daniel; Brune, Rafael; Brockmann, Dirk
2010-01-01
Territorial subdivisions and geographic borders are essential for understanding phenomena in sociology, political science, history, and economics. They influence the interregional flow of information and cross-border trade and affect the diffusion of innovation and technology. However, it is unclear if existing administrative subdivisions that typically evolved decades ago still reflect the most plausible organizational structure of today. The complexity of modern human communication, the ease of long-distance movement, and increased interaction across political borders complicate the operational definition and assessment of geographic borders that optimally reflect the multi-scale nature of today's human connectivity patterns. What border structures emerge directly from the interplay of scales in human interactions is an open question. Based on a massive proxy dataset, we analyze a multi-scale human mobility network and compute effective geographic borders inherent to human mobility patterns in the United States. We propose two computational techniques for extracting these borders and for quantifying their strength. We find that effective borders only partially overlap with existing administrative borders, and show that some of the strongest mobility borders exist in unexpected regions. We show that the observed structures cannot be generated by gravity models for human traffic. Finally, we introduce the concept of link significance that clarifies the observed structure of effective borders. Our approach represents a novel type of quantitative, comparative analysis framework for spatially embedded multi-scale interaction networks in general and may yield important insight into a multitude of spatiotemporal phenomena generated by human activity. PMID:21124970
Brosch, Tom; Tam, Roger
2015-01-01
Deep learning has traditionally been computationally expensive, and advances in training methods have been the prerequisite for improving its efficiency in order to expand its application to a variety of image classification problems. In this letter, we address the problem of efficient training of convolutional deep belief networks by learning the weights in the frequency domain, which eliminates the time-consuming calculation of convolutions. An essential consideration in the design of the algorithm is to minimize the number of transformations to and from frequency space. We have evaluated the running time improvements using two standard benchmark data sets, showing a speed-up of up to 8 times on 2D images and up to 200 times on 3D volumes. Our training algorithm makes training of convolutional deep belief networks on 3D medical images with a resolution of up to 128×128×128 voxels practical, which opens new directions for using deep learning for medical image analysis. PMID:25380341
Leandro, Jorge; Martins, Ricardo
2016-01-01
Pluvial flooding in urban areas is characterized by a gradually varying inundation process caused by surcharge of the sewer manholes. Therefore urban flood models need to simulate the interaction between the sewer network and the overland flow in order to accurately predict the flood inundation extents. In this work we present a methodology for linking 2D overland flow models with the storm sewer model SWMM 5. SWMM 5 is a well-known free open-source code originally developed in 1971. The latest major release saw its structure re-written in C ++ allowing it to be compiled as a command line executable or through a series of calls made to function inside a dynamic link library (DLL). The methodology developed herein is written inside the same DLL in C + +, and is able to simulate the bi-directional interaction between both models during simulation. Validation is done in a real case study with an existing urban flood coupled model. The novelty herein is that the new methodology can be added to SWMM without the need for editing SWMM's original code. Furthermore, it is directly applicable to other coupled overland flow models aiming to use SWMM 5 as the sewer network model. PMID:27332848
van Winden, Wouter A; van Gulik, Walter M; Schipper, Dick; Verheijen, Peter J T; Krabben, Preben; Vinke, Jacobus L; Heijnen, Joseph J
2003-07-01
At present two alternative methods are available for analyzing the fluxes in a metabolic network: (1) combining measurements of net conversion rates with a set of metabolite balances including the cofactor balances, or (2) leaving out the cofactor balances and fitting the resulting free fluxes to measured (13)C-labeling data. In this study these two approaches are applied to the fluxes in the glycolysis and pentose phosphate pathway of Penicillium chrysogenum growing on either ammonia or nitrate as the nitrogen source, which is expected to give different pentose phosphate pathway fluxes. The presented flux analyses are based on extensive sets of 2D [(13)C, (1)H] COSY data. A new concept is applied for simulation of this type of (13)C-labeling data: cumulative bondomer modeling. The outcomes of the (13)C-labeling based flux analysis substantially differ from those of the pure metabolite balancing approach. The fluxes that are determined using (13)C-labeling data are shown to be highly dependent on the chosen metabolic network. Extending the traditional nonoxidative pentose phosphate pathway with additional transketolase and transaldolase reactions, extending the glycolysis with a fructose 6-phosphate aldolase/dihydroxyacetone kinase reaction sequence or adding a phosphoenolpyruvate carboxykinase reaction to the model considerably improves the fit of the measured and the simulated NMR data. The results obtained using the extended version of the nonoxidative pentose phosphate pathway model show that the transketolase and transaldolase reactions need not be assumed reversible to get a good fit of the (13)C-labeling data. Strict statistical testing of the outcomes of (13)C-labeling based flux analysis using realistic measurement errors is demonstrated to be of prime importance for verifying the assumed metabolic model. PMID:12740935
Potts model on directed small-world Voronoi-Delaunay lattices
NASA Astrophysics Data System (ADS)
Marques, R. M.; Lima, F. W. S.; Costa Filho, Raimundo N.
2016-06-01
The critical properties of the Potts model with q = 3 and 4 states in two-dimensions on directed small-world Voronoi-Delaunay random lattices with quenched connectivity disorder are investigated. This disordered system is simulated by applying the Monte Carlo update heat bath algorithm. The Potts model on these directed small-world random lattices presents in fact a second-order phase transition with new critical exponents for q = 3 and value of the rewiring probability p = 0.01, but for q = 4 the system exhibits only a first-order phase transition independent of p (0 < p < 1).
NASA Astrophysics Data System (ADS)
Zeng, Hong-Li; Zhu, Chen-Ping; Guo, Yan-Dong; Teng, Ao; Jia, Jing; Kong, Hui; Zhou, Rui; Yang, Juan-Ping; Li, Su-Quan
2015-04-01
A co-evolutionary neuronal network model based on previous ones is proposed, and both functional and structural properties are numerically calculated. Recent experiments have revealed power-law behavior in electrocorticogram (ECoG) spectrum related with synaptic plasticity and reorganization. In the present neuronal network model, the network starts its evolution from the initial configuration of random network which is the least biased and without special structure, and the interaction rules among neurons are modified from both models by Bornholdt's and Arcangelis' groups to simulate the process of synaptic development and maturation. The system exhibits dynamic small-world structure which is the result of evolution instead of the assumption beforehand. Meanwhile, the power spectrum of electrical signals reproduces the power-law behavior with the exponent 2.0 just as what is experimentally measured in ECoG spectrum. Moreover, the power spectrum of the average degree per neuron over time also exhibits power-law behavior, with the exponent 2.0 again over more than 5 orders of magnitude. Different from previous results, our network exhibits assortative degree-degree correlation which is expected to be checked by experiments.
Sassen, D. S.; Peterson, J. E.
2010-03-15
.g. Bautu et al., 2006). In the technique of algebraic reconstruction tomography (ART), which is used herein for the travel time inversion (Peterson et al., 1985), a small relaxation parameter will smooth imaging artifacts caused by data errors at the expense of resolution and contrast (Figure 2). However, large data errors such as unaccounted well deviations cannot be adequately suppressed through inversion weighting schemes. Previously, problems with tomograms were treated manually. However, in large data sets and/or networks of data sets, trial and error changes to well geometries become increasingly difficult and ineffective. Mislocation of the transmitter and receiver stations of GPR cross-well tomography data sets can lead to serious imaging artifacts if not accounted for prior to inversion. Previously, problems with tomograms have been treated manually prior to inversion. In large data sets and/or networks of tomographic data sets, trial and error changes to well geometries become increasingly difficult and ineffective. Our approach is to use cross-well data quality checks and a simplified model of borehole deviation with particle swarm optimization (PSO) to automatically correct for source and receiver locations prior to tomographic inversion. We present a simple model of well deviation, which is designed to minimize potential corruption of actual data trends. We also provide quantitative quality control measures based on minimizing correlations between take-off angle and apparent velocity, and a quality check on the continuity of velocity between adjacent wells. This methodology is shown to be accurate and robust for simple 2-D synthetic test cases. Plus, we demonstrate the method on actual field data where it is compared to deviation logs. This study shows the promise for automatic correction of well deviations in GPR tomographic data. Analysis of synthetic data shows that very precise estimates of well deviation can be made for small deviations, even in the
Energy Science and Technology Software Center (ESTSC)
2005-07-01
Aniso2d is a two-dimensional seismic forward modeling code. The earth is parameterized by an X-Z plane in which the seismic properties Can have monoclinic with x-z plane symmetry. The program uses a user define time-domain wavelet to produce synthetic seismograms anrwhere within the two-dimensional media.
Small Worlds Week: An online celebration of planetary science using social media to reach millions
NASA Astrophysics Data System (ADS)
Mayo, Louis
2015-11-01
In celebration of the many recent discoveries from New Horizons, Dawn, Rosetta, and Cassini, NASA launched Small Worlds Week, an online, social media driven outreach program leveraging the infrastructure of Sun-Earth Days that included a robust web design, exemplary education materials, hands-on fun activities, multimedia resources, science and career highlights, and a culminating social media event. Each day from July 6-9, a new class of solar system small worlds was featured on the website: Monday-comets, Tuesday-asteroids, Wednesday-icy moons, and Thursday-dwarf planets. Then on Friday, July 10, nine scientists from Goddard Space Flight Center, Jet Propulsion Laboratory, Naval Research Laboratory, and Lunar and Planetary Institute gathered online for four hours to answer questions from the public via Facebook and Twitter. Throughout the afternoon the scientists worked closely with a social media expert and several summer interns to reply to inquirers and to archive their chats. By all accounts, Small Worlds Week was a huge success with 37 million potential views of the social media Q&A posts. The group plans to improve and replicate the program during the school year with a more classroom focus, and then to build and extend the program to be held every year. For more information, visit http:// sunearthday.nasa.gov or catch us on Twitter, #nasasww.
The role of dimensionality in neuronal network dynamics.
Ulloa Severino, Francesco Paolo; Ban, Jelena; Song, Qin; Tang, Mingliang; Bianconi, Ginestra; Cheng, Guosheng; Torre, Vincent
2016-01-01
Recent results from network theory show that complexity affects several dynamical properties of networks that favor synchronization. Here we show that synchronization in 2D and 3D neuronal networks is significantly different. Using dissociated hippocampal neurons we compared properties of cultures grown on a flat 2D substrates with those formed on 3D graphene foam scaffolds. Both 2D and 3D cultures had comparable glia to neuron ratio and the percentage of GABAergic inhibitory neurons. 3D cultures because of their dimension have many connections among distant neurons leading to small-world networks and their characteristic dynamics. After one week, calcium imaging revealed moderately synchronous activity in 2D networks, but the degree of synchrony of 3D networks was higher and had two regimes: a highly synchronized (HS) and a moderately synchronized (MS) regime. The HS regime was never observed in 2D networks. During the MS regime, neuronal assemblies in synchrony changed with time as observed in mammalian brains. After two weeks, the degree of synchrony in 3D networks decreased, as observed in vivo. These results show that dimensionality determines properties of neuronal networks and that several features of brain dynamics are a consequence of its 3D topology. PMID:27404281
The role of dimensionality in neuronal network dynamics
Ulloa Severino, Francesco Paolo; Ban, Jelena; Song, Qin; Tang, Mingliang; Bianconi, Ginestra; Cheng, Guosheng; Torre, Vincent
2016-01-01
Recent results from network theory show that complexity affects several dynamical properties of networks that favor synchronization. Here we show that synchronization in 2D and 3D neuronal networks is significantly different. Using dissociated hippocampal neurons we compared properties of cultures grown on a flat 2D substrates with those formed on 3D graphene foam scaffolds. Both 2D and 3D cultures had comparable glia to neuron ratio and the percentage of GABAergic inhibitory neurons. 3D cultures because of their dimension have many connections among distant neurons leading to small-world networks and their characteristic dynamics. After one week, calcium imaging revealed moderately synchronous activity in 2D networks, but the degree of synchrony of 3D networks was higher and had two regimes: a highly synchronized (HS) and a moderately synchronized (MS) regime. The HS regime was never observed in 2D networks. During the MS regime, neuronal assemblies in synchrony changed with time as observed in mammalian brains. After two weeks, the degree of synchrony in 3D networks decreased, as observed in vivo. These results show that dimensionality determines properties of neuronal networks and that several features of brain dynamics are a consequence of its 3D topology. PMID:27404281
Greg Flach, Frank Smith
2011-12-31
Mesh2d is a Fortran90 program designed to generate two-dimensional structured grids of the form [x(i),y(i,j)] where [x,y] are grid coordinates identified by indices (i,j). The x(i) coordinates alone can be used to specify a one-dimensional grid. Because the x-coordinates vary only with the i index, a two-dimensional grid is composed in part of straight vertical lines. However, the nominally horizontal y(i,j0) coordinates along index i are permitted to undulate or otherwise vary. Mesh2d also assigns an integer material type to each grid cell, mtyp(i,j), in a user-specified manner. The complete grid is specified through three separate input files defining the x(i), y(i,j), and mtyp(i,j) variations.
Energy Science and Technology Software Center (ESTSC)
2011-12-31
Mesh2d is a Fortran90 program designed to generate two-dimensional structured grids of the form [x(i),y(i,j)] where [x,y] are grid coordinates identified by indices (i,j). The x(i) coordinates alone can be used to specify a one-dimensional grid. Because the x-coordinates vary only with the i index, a two-dimensional grid is composed in part of straight vertical lines. However, the nominally horizontal y(i,j0) coordinates along index i are permitted to undulate or otherwise vary. Mesh2d also assignsmore » an integer material type to each grid cell, mtyp(i,j), in a user-specified manner. The complete grid is specified through three separate input files defining the x(i), y(i,j), and mtyp(i,j) variations.« less
NASA Astrophysics Data System (ADS)
Lotsch, Bettina V.
2015-07-01
Graphene's legacy has become an integral part of today's condensed matter science and has equipped a whole generation of scientists with an armory of concepts and techniques that open up new perspectives for the postgraphene area. In particular, the judicious combination of 2D building blocks into vertical heterostructures has recently been identified as a promising route to rationally engineer complex multilayer systems and artificial solids with intriguing properties. The present review highlights recent developments in the rapidly emerging field of 2D nanoarchitectonics from a materials chemistry perspective, with a focus on the types of heterostructures available, their assembly strategies, and their emerging properties. This overview is intended to bridge the gap between two major—yet largely disjunct—developments in 2D heterostructures, which are firmly rooted in solid-state chemistry or physics. Although the underlying types of heterostructures differ with respect to their dimensions, layer alignment, and interfacial quality, there is common ground, and future synergies between the various assembly strategies are to be expected.
Liu Guocheng; Chen Yongqiang; Wang Xiuli Chen Baokuan; Lin Hongyan
2009-03-15
Three novel Cd(II) coordination polymers, namely, [Cd(Dpq)(1,8-NDC)(H{sub 2}O){sub 2}][Cd(Dpq)(1,8-NDC)].2H{sub 2}O (1), [Cd(Dpq)(1,4-NDC)(H{sub 2}O)] (2), and [Cd(Dpq)(2,6-NDC)] (3) have been obtained from hydrothermal reactions of cadmium(II) nitrate with the mixed ligands dipyrido [3,2-d:2',3'-f]quinoxaline (Dpq) and three structurally related naphthalene-dicarboxylate ligands [1,8-naphthalene-dicarboxylic acid (1,8-H{sub 2}NDC), 1,4-naphthalene-dicarboxylic acid (1,4-H{sub 2}NDC), and 2,6-naphthalene-dicarboxylic acid (2,6-H{sub 2}NDC)]. Single-crystal X-ray diffraction analysis reveals that the three polymers exhibit novel structures due to different naphthalene-dicarboxylic acid. Compound 1 is a novel cocrystal of left- and right-handed helical chains and binuclear complexes and ultimately packed into a 3D supramolecular structure through hydrogen bonds and {pi}-{pi} stacking interactions. Compound 2 shows a 2D rectangular network (4,4) bridged by 1,4-NDC with two kinds of coordination modes and ultimately packed into a 3D supramolecular structure through inter-layer {pi}-{pi} stacking interactions. Compound 3 is a new 3D coordination polymer with distorted PtS-type network. In addition, the title compounds exhibit blue/green emission in solid state at room temperature. - Graphical abstract: Three novel Cd(II) compounds have been synthesized under hydrothermal conditions exhibiting a systematic variation of architecture by the employment of three structurally related naphthalene-dicarboxylate ligands.
Roy, Nabarun; Tomović, Željko; Buhler, Eric; Lehn, Jean-Marie
2016-09-12
Self-healing polymers hold great promise for the future, enhancing in particular the longevity of polymeric materials. We describe a self-healing covalent polymer, presenting an extensive array of hydrogen-bonding sites based on the combination of urea, urethane, and bis-acyl-hydrazine units. Solvent-cast thin-films prepared by polycondensation of a commercially available dihydrazide and a diisocyanate prepolymer exhibited excellent room temperature autonomous healing with almost full recovery of mechanical properties when two parts of a cut film were overlapped and gently pressed together. This autonomous healing upon damage may be attributed to the supramolecular dynamics of multiple lateral inter-chain hydrogen-bonding interactions between the polymer chains. The solid-state structure of a model compound incorporating the same structural backbone corroborates the existence of an extensive two-dimensional supramolecular hydrogen-bonding network. PMID:27226034
Yu, Xiao-Yang; Cui, Xiao-Bing; Lu, Jing; Luo, Yu-Hui; Zhang, Hong; Gao, Wei-Ping
2014-01-15
Five new inorganic–organic hybrids based on 4,4′-bipyridine and Keggin-type polyoxometalate [SiMo{sub 12}O{sub 40}]{sup 4−}, (SiMo{sub 12}O{sub 40})(H{sub 2}bipy){sub 2}·2H{sub 2}O (1), [Cu(Hbipy){sub 4}(HSiMo{sub 12}O{sub 40})(SiMo{sub 12}O{sub 40})](H{sub 2}bipy){sub 0.5}·7H{sub 2}O (2), [Cu{sub 2}(Hbipy){sub 6}(bipy)(SiMo{sub 12}O{sub 40}){sub 3}](Hbipy){sub 2}·6H{sub 2}O (3), [Cu(bipy){sub 2}(SiMo{sub 12}O{sub 40})](H{sub 2}bipy)·2H{sub 2}O (4) and [Cu{sub 2}(bipy){sub 4}(H{sub 2}O){sub 4}](SiMo{sub 12}O{sub 40})·13H{sub 2}O (5) (bipy=4,4′-bipyridine), have been hydrothermally synthesized. 1 consists of H{sub 2}bipy{sup 2+} and [SiMo{sub 12}O{sub 40}]{sup 4−} units. In 2, two [SiMo{sub 12}O{sub 40}]{sup 4−} are bridged by [Cu(Hbipy){sub 4}]{sup 6+} to form a [Cu(Hbipy){sub 4}(SiMo{sub 12}O{sub 40}){sub 2}]{sup 2−} dimmer. In 3, [SiMo{sub 12}O{sub 40}]{sup 4−} polyanions acting as bidentated bridging ligands and monodentated auxiliary ligands connect [Cu{sub 2}(Hbipy){sub 6}(bipy)]{sup 8+} units into a 1D zigzag chain. In 4, [SiMo{sub 12}O{sub 40}]{sup 4−} polyanions bridge neighboring 1D [Cu(bipy){sub 2}]{sup 2+} double chains into a 2D extended layer. In 5, [SiMo{sub 12}O{sub 40}]{sup 4−} polyanions acting as templates site alternately upon the grids from both sides of the square grid [Cu{sub 2}(bipy){sub 4}(H{sub 2}O){sub 4}]{sup 4+} layer. In addition, the electrochemical behaviors of 1, 3 and 4 and the photocatalysis property of 1 have been investigated. - Graphical abstract: Five new compounds based on [SiMo{sub 12}O{sub 40}]{sup 4−} have been successfully generated. [SiMo{sub 12}O{sub 40}]{sup 4−} anions play different roles in the structures of the five compounds. Display Omitted - Highlights: • Five new compounds based on [SiMo{sub 12}O{sub 40}]{sup 4−} have been generated. • [SiMo{sub 12}O{sub 40}]{sup 4−} anions play different roles in the five structures. • The electrochemical behaviors of 1, 3 and 4 have been
NASA Astrophysics Data System (ADS)
Han, Zhong-Xi; Wang, Ji-Jiang; Hu, Huai-Ming; Chen, Xiao-Li; Wu, Qing-Ran; Li, Dong-Sheng; Shi, Qi-Zhen
2008-11-01
Four new mixed-ligand complexes, namely [Zn 2(pam) 2(2,2'-bpy) 2] ( 1), [Cd(pam)(2,2'-bpy) 2] n ( 2), [Zn(pam)(phen)] n ( 3) and [Cd (pam)(phen)] n · 0.5 n CH 3CH 2OH · 0.5 nH 2O ( 4) (H 2pam = pamoic acid, 2,2'-bpy = 2,2'-bipyridine, phen = 1,10-phenanthroline) have been synthesized under hydro(solvo)thermal conditions. Complex 1 possesses a discrete dinuclear metallamacrocyclic structure. Complex 2 is a 1D homochiral helical coordination polymer that is built from achiral components, whereas 3 displays a 1D helical chain structure. 4 is an unusual 2D double-layered structure generated by π ⋯ π interactions of two 2D networks. The structural differences of these complexes are mainly due to the differences of the size of the rigid aromatic chelate ligands and d 10 metal ions. It appears that the chelate ligands and metal ions of the larger size favor the formation of high-dimensional structures, whereas those of the smaller size favor the formation of low-dimensional structures in the present system. The photoluminescence and thermal stability of these complexes were investigated.
Ugale, Bharat; Singh, Divyendu; Nagaraja, C.M.
2015-03-15
Two new Zn(II)–organic compounds, [Zn(muco)(dbds){sub 2}(H{sub 2}O){sub 2}] (1) and [Zn(muco)(dbs)] (2) (where, muco=trans, trans-muconate dianion, dbds=4,4′-dipyridyldisulfide and dbs=4,4′-dipyridylsulfide) have been synthesized from same precursors but at two different temperatures. Both the compounds have been characterized by single-crystal X-ray diffraction, powder X-ray diffraction, elemental analysis, IR spectroscopy, thermal analysis and photoluminescence studies. Compound 1 prepared at room temperature possesses a molecular structure extended to 2D supramolecular network through (H–O…H) hydrogen-bonding interactions. Compound 2, obtained at high temperature (100 °C) shows a 3-fold interpenetrating 3D framework constituted by an in situ generated dbs linker by the cleavage of S–S and C–S bonds of dbds linker. Thus, the influence of reaction temperature on the formation of two structural phases has been demonstrated. Both 1 and 2 exhibit ligand based luminescence emission owing to n→π⁎ and π→π⁎ transitions and also high thermal stabilities. - Graphical abstract: The influence of temperature on the formation of two structural phases, a 2D supramolecular network and a 3D 3-fold interpenetrating framework has been demonstrated and their luminescence emission is measured. - Highlights: • Two new Zn(II)–organic compounds were synthesized by tuning reaction temperatures. • Temperature induced in situ generation of dbs linker has been observed. • The compounds exhibit high thermal stability and luminescence emission properties. • The effect of temperature on structure, dimension and topology has been presented.
NASA Astrophysics Data System (ADS)
Wang, Jin; Ma, Jianyong; Zhou, Changhe
2014-11-01
A 3×3 high divergent 2D-grating with period of 3.842μm at wavelength of 850nm under normal incidence is designed and fabricated in this paper. This high divergent 2D-grating is designed by the vector theory. The Rigorous Coupled Wave Analysis (RCWA) in association with the simulated annealing (SA) is adopted to calculate and optimize this 2D-grating.The properties of this grating are also investigated by the RCWA. The diffraction angles are more than 10 degrees in the whole wavelength band, which are bigger than the traditional 2D-grating. In addition, the small period of grating increases the difficulties of fabrication. So we fabricate the 2D-gratings by direct laser writing (DLW) instead of traditional manufacturing method. Then the method of ICP etching is used to obtain the high divergent 2D-grating.
A Space-Filling Visualization Technique for Multivariate Small World Graphs
Wong, Pak C.; Foote, Harlan P.; Mackey, Patrick S.; Chin, George; Huang, Zhenyu; Thomas, James J.
2012-03-15
We introduce an information visualization technique, known as GreenCurve, for large sparse graphs that exhibit small world properties. Our fractal-based design approach uses spatial cues to approximate the node connections and thus eliminates the links between the nodes in the visualization. The paper describes a sophisticated algorithm to order the neighboring nodes of a large sparse graph by solving the Fiedler vector of its graph Laplacian, and then fold the graph nodes into a space-filling fractal curve based on the Fiedler vector. The result is a highly compact visualization that gives a succinct overview of the graph with guaranteed visibility of every graph node. We show in the paper that the GreenCurve technology is (1) theoretically sustainable by introducing an error estimation metric to measure the fidelity of the new graph representation, (2) empirically rigorous by conducting a usability study to investigate its strengths and weaknesses against the traditional graph layout, and (3) pragmatically feasible by applying it to analyze stressed conditions of the large scale electric power grid on the west coast.
Analysis of epileptic seizures with complex network.
Ni, Yan; Wang, Yinghua; Yu, Tao; Li, Xiaoli
2014-01-01
Epilepsy is a disease of abnormal neural activities involving large area of brain networks. Until now the nature of functional brain network associated with epilepsy is still unclear. Recent researches indicate that the small world or scale-free attributes and the occurrence of highly clustered connection patterns could represent a general organizational principle in the human brain functional network. In this paper, we seek to find whether the small world or scale-free property of brain network is correlated with epilepsy seizure formation. A mass neural model was adopted to generate multiple channel EEG recordings based on regular, small world, random, and scale-free network models. Whether the connection patterns of cortical networks are directly associated with the epileptic seizures was investigated. The results showed that small world and scale-free cortical networks are highly correlated with the occurrence of epileptic seizures. In particular, the property of small world network is more significant during the epileptic seizures. PMID:25147576
Addressing head motion dependencies for small-world topologies in functional connectomics
Yan, Chao-Gan; Craddock, R. Cameron; He, Yong; Milham, Michael P.
2013-01-01
Graph theoretical explorations of functional interactions within the human connectome, are rapidly advancing our understanding of brain architecture. In particular, global and regional topological parameters are increasingly being employed to quantify and characterize inter-individual differences in human brain function. Head motion remains a significant concern in the accurate determination of resting-state fMRI based assessments of the connectome, including those based on graph theoretical analysis (e.g., motion can increase local efficiency, while decreasing global efficiency and small-worldness). This study provides a comprehensive examination of motion correction strategies on the relationship between motion and commonly used topological parameters. At the individual-level, we evaluated different models of head motion regression and scrubbing, as well as the potential benefits of using partial correlation (estimated via graphical lasso) instead of full correlation. At the group-level, we investigated the utility of regression of motion and mean intrinsic functional connectivity before topological parameters calculation and/or after. Consistent with prior findings, none of the explicit motion-correction approaches at individual-level were able to remove motion relationships for topological parameters. Global signal regression (GSR) emerged as an effective means of mitigating relationships between motion and topological parameters; though at the risk of altering the connectivity structure and topological hub distributions when higher density graphs are employed (e.g., >6%). Group-level analysis correction for motion was once again found to be a crucial step. Finally, similar to recent work, we found a constellation of findings suggestive of the possibility that some of the motion-relationships detected may reflect neural or trait signatures of motion, rather than simply motion-induced artifact. PMID:24421764
Addressing head motion dependencies for small-world topologies in functional connectomics.
Yan, Chao-Gan; Craddock, R Cameron; He, Yong; Milham, Michael P
2013-01-01
Graph theoretical explorations of functional interactions within the human connectome, are rapidly advancing our understanding of brain architecture. In particular, global and regional topological parameters are increasingly being employed to quantify and characterize inter-individual differences in human brain function. Head motion remains a significant concern in the accurate determination of resting-state fMRI based assessments of the connectome, including those based on graph theoretical analysis (e.g., motion can increase local efficiency, while decreasing global efficiency and small-worldness). This study provides a comprehensive examination of motion correction strategies on the relationship between motion and commonly used topological parameters. At the individual-level, we evaluated different models of head motion regression and scrubbing, as well as the potential benefits of using partial correlation (estimated via graphical lasso) instead of full correlation. At the group-level, we investigated the utility of regression of motion and mean intrinsic functional connectivity before topological parameters calculation and/or after. Consistent with prior findings, none of the explicit motion-correction approaches at individual-level were able to remove motion relationships for topological parameters. Global signal regression (GSR) emerged as an effective means of mitigating relationships between motion and topological parameters; though at the risk of altering the connectivity structure and topological hub distributions when higher density graphs are employed (e.g., >6%). Group-level analysis correction for motion was once again found to be a crucial step. Finally, similar to recent work, we found a constellation of findings suggestive of the possibility that some of the motion-relationships detected may reflect neural or trait signatures of motion, rather than simply motion-induced artifact. PMID:24421764
Energy Science and Technology Software Center (ESTSC)
2004-08-01
AnisWave2D is a 2D finite-difference code for a simulating seismic wave propagation in fully anisotropic materials. The code is implemented to run in parallel over multiple processors and is fully portable. A mesh refinement algorithm has been utilized to allow the grid-spacing to be tailored to the velocity model, avoiding the over-sampling of high-velocity materials that usually occurs in fixed-grid schemes.
Structural properties of spatially embedded networks
NASA Astrophysics Data System (ADS)
Kosmidis, K.; Havlin, S.; Bunde, A.
2008-05-01
We study the effects of spatial constraints on the structural properties of networks embedded in one- or two-dimensional space. When nodes are embedded in space, they have a well-defined Euclidean distance r between any pair. We assume that nodes at distance r have a link with probability p(r)~r-δ. We study the mean topological distance l and the clustering coefficient C of these networks and find that they both exhibit phase transitions for some critical value of the control parameter δ depending on the dimensionality d of the embedding space. We have identified three regimes. When δ
NASA Astrophysics Data System (ADS)
Thurai, M.; Bringi, V. N.; Tolstoy, L.; Petersen, W. A.
2012-12-01
On two days during the MC3E campaign in northern Oklahoma, NASA's S-band polarimetric radar (NPOL) performed repeated PPI scans over a network of six 2D video disdrometer (2DVD) sites, located 20 to 30 km from the radar. The scans were repeated approximately every 40 seconds. We consider here the two cases, one a rapidly evolving multi-cell rain event (with large drops) on 24 April 2011 and the second a somewhat more uniform rain event on 11 May 2011. For both events, the external calibration offsets for radar reflectivity and differential reflectivity were determined by comparing the radar data extracted over the disdrometer sites with those determined from scattering simulations using the 2DVD data. Time series comparisons show excellent agreement for all six sites, and a technique was developed to determine the offsets for the NPOL data quantitatively from the comparisons. The radar data were then used to determine the rain rates over the six sites and compared with those derived from the 2DVD measurements. Once again, excellent agreement was obtained for all six sites, both in terms of rain fall rates and rain accumulations (see Fig. 1). Comparisons have also been made over many rain gauges located within ground validation network area. The repeated PPI scans were also used to determine the spatial correlations of two of the main rain drop-size distribution (DSD) parameters (Do and log Nw) as well as rainfall rate (R). The correlations were determined along the radial over the whole azimuthal range of the PPI scans. The spatial correlation of R shows azimuthal dependence particularly for the first event. However, the 50 percentile levels are similar between the two events, at least up to 4 km. For the DSD parameters, reasonable agreement with 2DVD-based spatial correlations were obtained As part of the abovementioned scan sequence, the NPOL had also made repeated RHI scans along one azimuth. These scans were used to determine the vertical correlations of the