Epidemics in interconnected small-world networks.
Liu, Meng; Li, Daqing; Qin, Pengju; Liu, Chaoran; Wang, Huijuan; Wang, Feilong
2015-01-01
Networks can be used to describe the interconnections among individuals, which play an important role in the spread of disease. Although the small-world effect has been found to have a significant impact on epidemics in single networks, the small-world effect on epidemics in interconnected networks has rarely been considered. Here, we study the susceptible-infected-susceptible (SIS) model of epidemic spreading in a system comprising two interconnected small-world networks. We find that the epidemic threshold in such networks decreases when the rewiring probability of the component small-world networks increases. When the infection rate is low, the rewiring probability affects the global steady-state infection density, whereas when the infection rate is high, the infection density is insensitive to the rewiring probability. Moreover, epidemics in interconnected small-world networks are found to spread at different velocities that depend on the rewiring probability.
The ubiquity of small-world networks.
Telesford, Qawi K; Joyce, Karen E; Hayasaka, Satoru; Burdette, Jonathan H; Laurienti, Paul J
2011-01-01
Small-world networks, according to Watts and Strogatz, are a class of networks that are "highly clustered, like regular lattices, yet have small characteristic path lengths, like random graphs." These characteristics result in networks with unique properties of regional specialization with efficient information transfer. Social networks are intuitive examples of this organization, in which cliques or clusters of friends being interconnected but each person is really only five or six people away from anyone else. Although this qualitative definition has prevailed in network science theory, in application, the standard quantitative application is to compare path length (a surrogate measure of distributed processing) and clustering (a surrogate measure of regional specialization) to an equivalent random network. It is demonstrated here that comparing network clustering to that of a random network can result in aberrant findings and that networks once thought to exhibit small-world properties may not. We propose a new small-world metric, ω (omega), which compares network clustering to an equivalent lattice network and path length to a random network, as Watts and Strogatz originally described. Example networks are presented that would be interpreted as small-world when clustering is compared to a random network but are not small-world according to ω. These findings have important implications in network science because small-world networks have unique topological properties, and it is critical to accurately distinguish them from networks without simultaneous high clustering and short path length. PMID:22432451
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…
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
Bumps in Small-World Networks.
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.
Spatially embedded growing small-world networks
Zitin, Ari; Gorowara, Alexander; Squires, Shane; Herrera, Mark; Antonsen, Thomas M.; Girvan, Michelle; Ott, Edward
2014-01-01
Networks in nature are often formed within a spatial domain in a dynamical manner, gaining links and nodes as they develop over time. Motivated by the growth and development of neuronal networks, we propose a class of spatially-based growing network models and investigate the resulting statistical network properties as a function of the dimension and topology of the space in which the networks are embedded. In particular, we consider two models in which nodes are placed one by one in random locations in space, with each such placement followed by configuration relaxation toward uniform node density, and connection of the new node with spatially nearby nodes. We find that such growth processes naturally result in networks with small-world features, including a short characteristic path length and nonzero clustering. We find no qualitative differences in these properties for two different topologies, and we suggest that results for these properties may not depend strongly on the topology of the embedding space. The results do depend strongly on dimension, and higher-dimensional spaces result in shorter path lengths but less clustering. PMID:25395180
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.
Small-world networks in neuronal populations: a computational perspective.
Zippo, Antonio G; Gelsomino, Giuliana; Van Duin, Pieter; Nencini, Sara; Caramenti, Gian Carlo; Valente, Maurizio; Biella, Gabriele E M
2013-08-01
The analysis of the brain in terms of integrated neural networks may offer insights on the reciprocal relation between structure and information processing. Even with inherent technical limits, many studies acknowledge neuron spatial arrangements and communication modes as key factors. In this perspective, we investigated the functional organization of neuronal networks by explicitly assuming a specific functional topology, the small-world network. We developed two different computational approaches. Firstly, we asked whether neuronal populations actually express small-world properties during a definite task, such as a learning task. For this purpose we developed the Inductive Conceptual Network (ICN), which is a hierarchical bio-inspired spiking network, capable of learning invariant patterns by using variable-order Markov models implemented in its nodes. As a result, we actually observed small-world topologies during learning in the ICN. Speculating that the expression of small-world networks is not solely related to learning tasks, we then built a de facto network assuming that the information processing in the brain may occur through functional small-world topologies. In this de facto network, synchronous spikes reflected functional small-world network dependencies. In order to verify the consistency of the assumption, we tested the null-hypothesis by replacing the small-world networks with random networks. As a result, only small world networks exhibited functional biomimetic characteristics such as timing and rate codes, conventional coding strategies and neuronal avalanches, which are cascades of bursting activities with a power-law distribution. Our results suggest that small-world functional configurations are liable to underpin brain information processing at neuronal level.
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 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.
Muldoon, Sarah Feldt; Bridgeford, Eric W; Bassett, Danielle S
2016-02-25
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.
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
Geometric Assortative Growth Model for Small-World Networks
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
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.
Hodge Decomposition of Information Flow on Small-World Networks
Haruna, Taichi; Fujiki, Yuuya
2016-01-01
We investigate the influence of the small-world topology on the composition of information flow on networks. By appealing to the combinatorial Hodge theory, we decompose information flow generated by random threshold networks on the Watts-Strogatz model into three components: gradient, harmonic and curl flows. The harmonic and curl flows represent globally circular and locally circular components, respectively. The Watts-Strogatz model bridges the two extreme network topologies, a lattice network and a random network, by a single parameter that is the probability of random rewiring. The small-world topology is realized within a certain range between them. By numerical simulation we found that as networks become more random the ratio of harmonic flow to the total magnitude of information flow increases whereas the ratio of curl flow decreases. Furthermore, both quantities are significantly enhanced from the level when only network structure is considered for the network close to a random network and a lattice network, respectively. Finally, the sum of these two ratios takes its maximum value within the small-world region. These findings suggest that the dynamical information counterpart of global integration and that of local segregation are the harmonic flow and the curl flow, respectively, and that a part of the small-world region is dominated by internal circulation of information flow. PMID:27733817
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.
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.
Information dynamics in small-world Boolean networks.
Lizier, Joseph T; Pritam, Siddharth; Prokopenko, Mikhail
2011-01-01
Small-world networks have been one of the most influential concepts in complex systems science, partly due to their prevalence in naturally occurring networks. It is often suggested that this prevalence is due to an inherent capability to store and transfer information efficiently. We perform an ensemble investigation of the computational capabilities of small-world networks as compared to ordered and random topologies. To generate dynamic behavior for this experiment, we imbue the nodes in these networks with random Boolean functions. We find that the ordered phase of the dynamics (low activity in dynamics) and topologies with low randomness are dominated by information storage, while the chaotic phase (high activity in dynamics) and topologies with high randomness are dominated by information transfer. Information storage and information transfer are somewhat balanced (crossed over) near the small-world regime, providing quantitative evidence that small-world networks do indeed have a propensity to combine comparably large information storage and transfer capacity. PMID:21762020
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.
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.
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.
Diffusion Processes on Power-Law Small-World Networks
NASA Astrophysics Data System (ADS)
Kozma, Balazs; Hastings, Matthew B.; Korniss, G.
2005-03-01
We consider diffusion driven processes on power-law small-world networks: a random walk process related to folded polymers and surface growth related to synchronization problems. The random links introduced in small-world networks often lead to mean-field coupling (as if the random links were annealed) but in some systems mean-field predictions break down, like diffusion in one dimension. This break-down can be understood treating the random links perturbatively where the mean field prediction appears as the lowest order term of a naive perturbation expansion. Our results were obtained using self-consistent perturbation theory ootnotetextB. Kozma, M. B. Hastings, and G. Korniss, Phys. Rev. Lett. 92, 108701 (2004). and can also be understood in terms of a scaling theory. We find a rich phase diagram, with different transient and recurrent phases, including a critical line with continuously varying exponents.
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.
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
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
2015-03-13
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
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.
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.
Tracking sinks of atmospheric methane using small world networks.
Lee, Chih-Sheng; Su, Pei-Jen
2014-12-01
The present study uses small world network to highlight the key hubs for CH4 atmospheric pathways without considering rate constant of each reaction and concentrations of each species. The atmospheric methane sources and sinks were formulated into a well-organized network of 49 nodes and 302 links. In the network, reactions (including substrates and products) are considered as nodes and their pathways as links. Using a small world model, we analyzed the weighted and directed network of methane sources and sinks. By analyzing the characteristic path length, clustering coefficient, and degree distribution, we obtained insights into the methane network. The results indicate that only a few key nodes serve as hubs or limiting reactions, such as CH4 + OH → CH3 + H2O; HO2 + NO → NO2 + OH; CH3O2H → CH3O + OH; and CH4 + Cl → CH3 + HCl. The network is highly efficient; when key hub reactions experience interruptions, pathways to other nodes can be accessed to complete the methane degradation process. Additionally, our directed network keeps sources and sinks independent of each other such that changes in the number or type of methane sources does not affect the findings related to sinks. Tracking the structure of methane sources and sinks not only provides valuable, and perhaps universal, information about the network structure, but also can lead to a better understanding of the dynamic processes that generate the network. Finally, this is the first attempt of the network model in analyzing environmental issues and may represent a common blueprint for the interconnected reactions (sources and sinks) of other greenhouse gases.
Effects of Route Guidance Systems on Small-World Networks
NASA Astrophysics Data System (ADS)
Wu, Jian-Jun; Sun, Hui-Jun; Gao, Zi-You; Li, Shu-Bin
The route guidance systems (RGS) are efficient in alleviating traffic congestion and reducing transit time of transportation networks. This paper studies the effects of RGS on performance of variably weighted small-world networks. The properties of the average shortest path length, the maximum degree, and the largest betweenness, as important indices for characterizing the network structure in complex networks, are simulated. Results show that there is an optimal guided rate of RGS to minimize the total system cost and the average shortest path length, and proper RGS can reduce the load of the node with maximum degree or largest betweenness. In addition, we found that the load distribution of nodes guided by RGS decay as the power laws which is very important for us to understand and control traffic congestion feasible.
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.
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.
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.
Structured information in small-world neural networks
NASA Astrophysics Data System (ADS)
Dominguez, David; González, Mario; Serrano, Eduardo; Rodríguez, Francisco B.
2009-02-01
The retrieval abilities of spatially uniform attractor networks can be measured by the global overlap between patterns and neural states. However, we found that nonuniform networks, for instance, small-world networks, can retrieve fragments of patterns (blocks) without performing global retrieval. We propose a way to measure the local retrieval using a parameter that is related to the fluctuation of the block overlaps. Simulation of neural dynamics shows a competition between local and global retrieval. The phase diagram shows a transition from local retrieval to global retrieval when the storage ratio increases and the topology becomes more random. A theoretical approach confirms the simulation results and predicts that the stability of blocks can be improved by dilution.
Structured information in small-world neural networks.
Dominguez, David; González, Mario; Serrano, Eduardo; Rodríguez, Francisco B
2009-02-01
The retrieval abilities of spatially uniform attractor networks can be measured by the global overlap between patterns and neural states. However, we found that nonuniform networks, for instance, small-world networks, can retrieve fragments of patterns (blocks) without performing global retrieval. We propose a way to measure the local retrieval using a parameter that is related to the fluctuation of the block overlaps. Simulation of neural dynamics shows a competition between local and global retrieval. The phase diagram shows a transition from local retrieval to global retrieval when the storage ratio increases and the topology becomes more random. A theoretical approach confirms the simulation results and predicts that the stability of blocks can be improved by dilution.
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.
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
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.
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 P(ij)∼r(ij)(-α), where r(ij) is the Manhattan distance. By assigning each shortcut an activity rate subjected to its geometric distance τ(ij)∼r(ij)(-C), long-range links become active intermittently, leading to the time-varying dynamics. We show that for 0
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
Optimal transport in time-varying small-world networks.
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 P(ij)∼r(ij)(-α), where r(ij) is the Manhattan distance. By assigning each shortcut an activity rate subjected to its geometric distance τ(ij)∼r(ij)(-C), long-range links become active intermittently, leading to the time-varying dynamics. We show that for 0
A weighted small world network measure for assessing functional connectivity.
Bolaños, Marcos; Bernat, Edward M; He, Bin; Aviyente, Selin
2013-01-15
There is a growing need to develop measures that can characterize complex patterns of functional connectivity among brain regions. Graph theoretic measures have emerged as an important way to characterize the multivariate connectivity between nodes in a network, which have been successfully applied to neurophysiologic activity. In this paper, we propose a new small-world measure based on advances in both the bivariate measures underlying the graph theoretic approach, as well as in the definition of the measure for weighted graphs. Specifically, we recently proposed a new bivariate time-frequency phase-synchrony (TFPS) measure, which quantifies the dynamic nature of the interactions between neuronal oscillations with a higher time-frequency resolution than previous approaches and is better at isolating relevant activity. The proposed graph theoretic measures, weighted clustering coefficient and path length, represent a new approach to the calculation of weighted graph measures based on this improved bivariate TFPS measure. The new graph theoretic measures are applied to two datasets. The first is a well-known social network, Zachary's Karate Club. The second application contains event-related potential (ERP) indexing the well-known error-related negativity (ERN) component related to cognitive control. Results indicate that the new measures outperform the previously published weighted graph measures, and produces expectable results for both applications.
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.
Emergence of Small-World and Limitations to Its Maximization in a Macaque Cerebral Cortical Network
NASA Astrophysics Data System (ADS)
Zhao, Qing-Bai; Liao, Meng-Jie; Chen, Qi-Cai
2011-06-01
We study both the emergence of small-world topology in a macaque cerebral cortical network and the limitations to maximization of small-worldness. The results show that the maximization of neural complexity leads to a small-world topology, but it also limits the maximization of small-worldness. It is suggested that the modular organization that corresponds to different functions may be a limitation. Additionally, the need for strong resilience against attacks may be another limitation.
Influence of Choice of Null Network on Small-World Parameters of Structural Correlation Networks
Hosseini, S. M. Hadi; Kesler, Shelli R.
2013-01-01
In recent years, coordinated variations in brain morphology (e.g., volume, thickness) have been employed as a measure of structural association between brain regions to infer large-scale structural correlation networks. Recent evidence suggests that brain networks constructed in this manner are inherently more clustered than random networks of the same size and degree. Thus, null networks constructed by randomizing topology are not a good choice for benchmarking small-world parameters of these networks. In the present report, we investigated the influence of choice of null networks on small-world parameters of gray matter correlation networks in healthy individuals and survivors of acute lymphoblastic leukemia. Three types of null networks were studied: 1) networks constructed by topology randomization (TOP), 2) networks matched to the distributional properties of the observed covariance matrix (HQS), and 3) networks generated from correlation of randomized input data (COR). The results revealed that the choice of null network not only influences the estimated small-world parameters, it also influences the results of between-group differences in small-world parameters. In addition, at higher network densities, the choice of null network influences the direction of group differences in network measures. Our data suggest that the choice of null network is quite crucial for interpretation of group differences in small-world parameters of structural correlation networks. We argue that none of the available null models is perfect for estimation of small-world parameters for correlation networks and the relative strengths and weaknesses of the selected model should be carefully considered with respect to obtained network measures. PMID:23840672
Influence of choice of null network on small-world parameters of structural correlation networks.
Hosseini, S M Hadi; Kesler, Shelli R
2013-01-01
In recent years, coordinated variations in brain morphology (e.g., volume, thickness) have been employed as a measure of structural association between brain regions to infer large-scale structural correlation networks. Recent evidence suggests that brain networks constructed in this manner are inherently more clustered than random networks of the same size and degree. Thus, null networks constructed by randomizing topology are not a good choice for benchmarking small-world parameters of these networks. In the present report, we investigated the influence of choice of null networks on small-world parameters of gray matter correlation networks in healthy individuals and survivors of acute lymphoblastic leukemia. Three types of null networks were studied: 1) networks constructed by topology randomization (TOP), 2) networks matched to the distributional properties of the observed covariance matrix (HQS), and 3) networks generated from correlation of randomized input data (COR). The results revealed that the choice of null network not only influences the estimated small-world parameters, it also influences the results of between-group differences in small-world parameters. In addition, at higher network densities, the choice of null network influences the direction of group differences in network measures. Our data suggest that the choice of null network is quite crucial for interpretation of group differences in small-world parameters of structural correlation networks. We argue that none of the available null models is perfect for estimation of small-world parameters for correlation networks and the relative strengths and weaknesses of the selected model should be carefully considered with respect to obtained network measures.
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.
A multi-community homogeneous small-world network and its fundamental characteristics
NASA Astrophysics Data System (ADS)
Tanimoto, Jun
2016-10-01
We introduce a new small-world network-which we call the multi-community homogeneous-small-world network-that is divided into multiple communities that are relatively isolated, similar to sparsely connected islands. A generating algorithm is presented and its network parameters are explored. To elucidate the fundamental characteristics of the proposed topology, we adopt spatial prisoner's dilemma games as a template for discussion. Comparing with a conventional homogeneous small-world network, more enhanced network reciprocity is observed in games where a stag hunt-type dilemma is large. With intensive analysis, we find how this enhancement is brought about.
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.
Low-rank network decomposition reveals structural characteristics of small-world networks.
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.
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).
Homeostatic structural plasticity increases the efficiency of small-world networks.
Butz, Markus; Steenbuck, Ines D; van Ooyen, Arjen
2014-01-01
In networks with small-world topology, which are characterized by a high clustering coefficient and a short characteristic path length, information can be transmitted efficiently and at relatively low costs. The brain is composed of small-world networks, and evolution may have optimized brain connectivity for efficient information processing. Despite many studies on the impact of topology on information processing in neuronal networks, little is known about the development of network topology and the emergence of efficient small-world networks. We investigated how a simple growth process that favors short-range connections over long-range connections in combination with a synapse formation rule that generates homeostasis in post-synaptic firing rates shapes neuronal network topology. Interestingly, we found that small-world networks benefited from homeostasis by an increase in efficiency, defined as the averaged inverse of the shortest paths through the network. Efficiency particularly increased as small-world networks approached the desired level of electrical activity. Ultimately, homeostatic small-world networks became almost as efficient as random networks. The increase in efficiency was caused by the emergent property of the homeostatic growth process that neurons started forming more long-range connections, albeit at a low rate, when their electrical activity was close to the homeostatic set-point. Although global network topology continued to change when neuronal activities were around the homeostatic equilibrium, the small-world property of the network was maintained over the entire course of development. Our results may help understand how complex systems such as the brain could set up an efficient network topology in a self-organizing manner. Insights from our work may also lead to novel techniques for constructing large-scale neuronal networks by self-organization.
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.
Dynamics of helping behavior and networks in a small world
NASA Astrophysics Data System (ADS)
Jo, Hang-Hyun; Jung, Woo-Sung; Moon, Hie-Tae
2006-08-01
To investigate an effect of social interaction on the bystanders’ intervention in emergency situations a rescue model was introduced which includes the effects of the victim’s acquaintance with bystanders and those among bystanders from a network perspective. This model reproduces the experimental result that the helping rate (success rate in our model) tends to decrease although the number of bystanders k increases. And the interaction among homogeneous bystanders results in the emergence of hubs in a helping network. For more realistic consideration it is assumed that the agents are located on a one-dimensional lattice (ring), then the randomness pɛ[0,1] is introduced: the kp random bystanders are randomly chosen from a whole population and the k-kp near bystanders are chosen in the nearest order to the victim. We find that there appears another peak of the network density in the vicinity of k=9 and p=0.3 due to the cooperative and competitive interaction between the near and random bystanders.
Damage spreading in spatial and small-world random Boolean networks.
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 K(s) 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.
Temporal efficiency evaluation and small-worldness characterization in temporal networks
Dai, Zhongxiang; Chen, Yu; Li, Junhua; Fam, Johnson; Bezerianos, Anastasios; Sun, Yu
2016-01-01
Numerous real-world systems can be modeled as networks. To date, most network studies have been conducted assuming stationary network characteristics. Many systems, however, undergo topological changes over time. Temporal networks, which incorporate time into conventional network models, are therefore more accurate representations of such dynamic systems. Here, we introduce a novel generalized analytical framework for temporal networks, which enables 1) robust evaluation of the efficiency of temporal information exchange using two new network metrics and 2) quantitative inspection of the temporal small-worldness. Specifically, we define new robust temporal network efficiency measures by incorporating the time dependency of temporal distance. We propose a temporal regular network model, and based on this plus the redefined temporal efficiency metrics and widely used temporal random network models, we introduce a quantitative approach for identifying temporal small-world architectures (featuring high temporal network efficiency both globally and locally). In addition, within this framework, we can uncover network-specific dynamic structures. Applications to brain networks, international trade networks, and social networks reveal prominent temporal small-world properties with distinct dynamic network structures. We believe that the framework can provide further insight into dynamic changes in the network topology of various real-world systems and significantly promote research on temporal networks. PMID:27682314
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.
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.
Basin stability for burst synchronization in small-world networks of chaotic slow-fast oscillators.
Maslennikov, Oleg V; Nekorkin, Vladimir I; Kurths, Jürgen
2015-10-01
The impact of connectivity and individual dynamics on the basin stability of the burst synchronization regime in small-world networks consisting of chaotic slow-fast oscillators is studied. It is shown that there are rewiring probabilities corresponding to the largest basin stabilities, which uncovers a reason for finding small-world topologies in real neuronal networks. The impact of coupling density and strength as well as the nodal parameters of relaxation or excitability are studied. Dynamic mechanisms are uncovered that most strongly influence basin stability of the burst synchronization regime.
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.
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
Small worlds and semantic network growth in typical and late talkers.
Beckage, Nicole; Smith, Linda; Hills, Thomas
2011-05-11
Network analysis has demonstrated that systems ranging from social networks to electric power grids often involve a small world structure-with local clustering but global ac cess. Critically, small world structure has also been shown to characterize adult human semantic networks. Moreover, the connectivity pattern of these mature networks is consistent with lexical growth processes in which children add new words to their vocabulary based on the structure of the language-learning environment. However, thus far, there is no direct evidence that a child's individual semantic network structure is associated with their early language learning. Here we show that, while typically developing children's early networks show small world structure as early as 15 months and with as few as 55 words, children with language delay (late talkers) have this structure to a smaller degree. This implicates a maladaptive bias in word acquisition for late talkers, potentially indicating a preference for "oddball" words. The findings provide the first evidence of a link between small-world connectivity and lexical development in individual children.
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.
Noise induced complexity: patterns and collective phenomena in a small-world neuronal network.
Zheng, Yanhong; Wang, Qingyun; Danca, Marius-F
2014-04-01
The effects of noise on patterns and collective phenomena are studied in a small-world neuronal network with the dynamics of each neuron being described by a two-dimensional Rulkov map neuron. It is shown that for intermediate noise levels, noise-induced ordered patterns emerge spatially, which supports the spatiotemporal coherence resonance. However, the inherent long range couplings of small-world networks can effectively disrupt the internal spatial scale of the media at small fraction of long-range couplings. The temporal order, characterized by the autocorrelation of a firing rate function, can be greatly enhanced by the introduction of small-world connectivity. There exists an optimal fraction of randomly rewired links, where the temporal order and synchronization can be optimized.
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.
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.
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.
Health, 'small-worlds', fractals and complex networks: an emerging field.
Mutch, W Alan; Lefevre, Gerald R
2003-05-01
The importance of 'small-worlds', fractals and complex networks to medicine are discussed. The interrelationship between the concepts is highlighted. 'Small-worlds'--where large populations are linked at the level of the individual have considerable importance for understanding disease transmission. Complex networks where linkages are based on the concept 'the rich get richer' are fundamental in the medical sciences--from enzymatic interactions at the subcellular level to social interactions such as sexual liaisons. Mathematically 'the rich get richer' can be modeled as a power law. Fractal architecture and time sequences can also be modeled by power laws and are ubiquitous in nature with many important examples in medicine. The potential of fractal life support--the return of physiological time sequences to devices such as mechanical ventilators and cardiopulmonary bypass pumps--is presented in the context of a failing complex network. Experimental work suggests that using fractal time sequences improves support of failing organs. Medicine, as a science has much to gain by embracing the interrelated concepts of 'small-worlds', fractals and complex networks. By so doing, medicine will move from the historical reductionist approach toward a more holistic one.
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).
Synchronization of the small-world neuronal network with unreliable synapses
NASA Astrophysics Data System (ADS)
Li, Chunguang; Zheng, Qunxian
2010-09-01
As is well known, synchronization phenomena are ubiquitous in neuronal systems. Recently a lot of work concerning the synchronization of the neuronal network has been accomplished. In these works, the synapses are usually considered reliable, but experimental results show that, in biological neuronal networks, synapses are usually unreliable. In our previous work, we have studied the synchronization of the neuronal network with unreliable synapses; however, we have not paid attention to the effect of topology on the synchronization of the neuronal network. Several recent studies have found that biological neuronal networks have typical properties of small-world networks, characterized by a short path length and high clustering coefficient. In this work, mainly based on the small-world neuronal network (SWNN) with inhibitory neurons, we study the effect of network topology on the synchronization of the neuronal network with unreliable synapses. Together with the network topology, the effects of the GABAergic reversal potential, time delay and noise are also considered. Interestingly, we found a counter-intuitive phenomenon for the SWNN with specific shortcut adding probability, that is, the less reliable the synapses, the better the synchronization performance of the SWNN. We also consider the effects of both local noise and global noise in this work. It is shown that these two different types of noise have distinct effects on the synchronization: one is negative and the other is positive.
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.
Chaotic phase synchronization in small-world networks of bursting neurons.
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.
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 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.
Hsu, Tun-Wei; Wu, Changwei W.; Cheng, Yu-Fan; Chen, Hsiu-Ling; Lu, Cheng-Hsien; Cho, Kuan-Hung
2012-01-01
Hepatic encephalopathy (HE) is a complex neuropsychiatric syndrome and a major complication of liver cirrhosis. Dysmetabolism of the brain, related to elevated ammonia levels, interferes with intercortical connectivity and cognitive function. For evaluation of network efficiency, a ‘small-world’ network model can quantify the effectiveness of information transfer within brain networks. This study aimed to use small-world topology to investigate abnormalities of neuronal connectivity among widely distributed brain regions in patients with liver cirrhosis using resting-state functional magnetic resonance imaging (rs-fMRI). Seventeen cirrhotic patients without HE, 9 with minimal HE, 9 with overt HE, and 35 healthy controls were compared. The interregional correlation matrix was obtained by averaging the rs-fMRI time series over all voxels in each of the 90 regions using the automated anatomical labeling model. Cost and correlation threshold values were then applied to construct the functional brain network. The absolute and relative network efficiencies were calculated; quantifying distinct aspects of the local and global topological network organization. Correlations between network topology parameters, ammonia levels, and the severity of HE were determined using linear regression and ANOVA. The local and global topological efficiencies of the functional connectivity network were significantly disrupted in HE patients; showing abnormal small-world properties. Alterations in regional characteristics, including nodal efficiency and nodal strength, occurred predominantly in the association, primary, and limbic/paralimbic regions. The degree of network organization disruption depended on the severity of HE. Ammonia levels were also significantly associated with the alterations in local network properties. Results indicated that alterations in the rs-fMRI network topology of the brain were associated with HE grade; and that focal or diffuse lesions disturbed the
Scale-Free and Small-World Properties of Vaf Fractal Networks
NASA Astrophysics Data System (ADS)
Li, Hao; Huang, Jian; Le, Anbo; Wang, Qin; Xi, Lifeng
2016-06-01
In this paper, we investigate the vertical-affiliation-free (VAF) evolving networks whose node set is the basic squares in the process of generating the Sierpinski carpet and edge exists between any two nodes if and only if the corresponding basic squares intersect just on their boundary. Although the VAF networks gets rid of the hierarchial organizations produced naturally by the self-similar structures of fractals, we still prove that they are scale-free and have the small-world effect.
Emergence of the small-world architecture in neural networks by activity dependent growth
NASA Astrophysics Data System (ADS)
Gafarov, F. M.
2016-11-01
In this paper, we propose a model describing the growth and development of neural networks based on the latest achievements of experimental neuroscience. The model is based on two evolutionary equations. The first equation is for the evolution of the neurons state and the second is for the growth of axon tips. By using the model, we demonstrated the neuronal growth process from disconnected neurons to fully connected three-dimensional networks. For the analysis of the network's connections structure, we used the random graphs theory methods. It is shown that the growth in neural networks results in the formation of a well-known "small-world" network model. The analysis of the connectivity distribution shows the presence of a strictly non-Gaussian but no scale-free degree distribution for the in-degree node distribution. In terms of the graphs theory, this study developed a new model of dynamic graph.
Critical behavior of the XY-rotor model on regular and small-world networks.
De Nigris, Sarah; Leoncini, Xavier
2013-07-01
We study the XY rotors model on small networks whose number of links scales with the system size N(links)~N(γ), where 1≤γ≤2. We first focus on regular one-dimensional rings in the microcanonical ensemble. For γ<1.5 the model behaves like a short-range one and no phase transition occurs. For γ>1.5, the system equilibrium properties are found to be identical to the mean field, which displays a second-order phase transition at a critical energy density ε=E/N,ε(c)=0.75. Moreover, for γ(c)~/=1.5 we find that a nontrivial state emerges, characterized by an infinite susceptibility. We then consider small-world networks, using the Watts-Strogatz mechanism on the regular networks parametrized by γ. We first analyze the topology and find that the small-world regime appears for rewiring probabilities which scale as p(SW)[proportionality]1/N(γ). Then considering the XY-rotors model on these networks, we find that a second-order phase transition occurs at a critical energy ε(c) which logarithmically depends on the topological parameters p and γ. We also define a critical probability p(MF), corresponding to the probability beyond which the mean field is quantitatively recovered, and we analyze its dependence on γ.
Synchronization and stochastic resonance of the small-world neural network based on the CPG.
Lu, Qiang; Tian, Juan
2014-06-01
According to biological knowledge, the central nervous system controls the central pattern generator (CPG) to drive the locomotion. The brain is a complex system consisting of different functions and different interconnections. The topological properties of the brain display features of small-world network. The synchronization and stochastic resonance have important roles in neural information transmission and processing. In order to study the synchronization and stochastic resonance of the brain based on the CPG, we establish the model which shows the relationship between the small-world neural network (SWNN) and the CPG. We analyze the synchronization of the SWNN when the amplitude and frequency of the CPG are changed and the effects on the CPG when the SWNN's parameters are changed. And we also study the stochastic resonance on the SWNN. The main findings include: (1) When the CPG is added into the SWNN, there exists parameters space of the CPG and the SWNN, which can make the synchronization of the SWNN optimum. (2) There exists an optimal noise level at which the resonance factor Q gets its peak value. And the correlation between the pacemaker frequency and the dynamical response of the network is resonantly dependent on the noise intensity. The results could have important implications for biological processes which are about interaction between the neural network and the CPG.
Spreading dynamics on small-world networks with connectivity fluctuations and correlations.
Vazquez, Alexei
2006-11-01
Infectious diseases and computer malwares spread among humans and computers through the network of contacts among them. These networks are characterized by wide connectivity fluctuations, connectivity correlations, and the small-world property. In a previous work [Phys. Rev. Lett. 96, 038702 (2006)] I have shown that the connectivity fluctuations together with the small-world property lead to a spreading law characterized by an initial power law growth with an exponent determined by the average node distance on the network. Here I extend these results to consider the influence of connectivity correlations which are generally observed in real networks. I show that assortative and disassortative connectivity correlations enhance and diminish, respectively, the range of validity of this spreading law. As a corollary I obtain the region of connectivity fluctuations and degree correlations characterized by the absence of an epidemic threshold. These results are relevant for the spreading of infectious diseases, rumors, and information among humans and the spreading of computer viruses, email worms, and hoaxes among computer users. PMID:17279962
Spreading dynamics on small-world networks with connectivity fluctuations and correlations
NASA Astrophysics Data System (ADS)
Vazquez, Alexei
2006-11-01
Infectious diseases and computer malwares spread among humans and computers through the network of contacts among them. These networks are characterized by wide connectivity fluctuations, connectivity correlations, and the small-world property. In a previous work [Phys. Rev. Lett. 96, 038702 (2006)] I have shown that the connectivity fluctuations together with the small-world property lead to a spreading law characterized by an initial power law growth with an exponent determined by the average node distance on the network. Here I extend these results to consider the influence of connectivity correlations which are generally observed in real networks. I show that assortative and disassortative connectivity correlations enhance and diminish, respectively, the range of validity of this spreading law. As a corollary I obtain the region of connectivity fluctuations and degree correlations characterized by the absence of an epidemic threshold. These results are relevant for the spreading of infectious diseases, rumors, and information among humans and the spreading of computer viruses, email worms, and hoaxes among computer users.
Jarman, Nicholas; Trengove, Chris; Steur, Erik; Tyukin, Ivan; van Leeuwen, Cees
2014-12-01
A modular small-world topology in functional and anatomical networks of the cortex is eminently suitable as an information processing architecture. This structure was shown in model studies to arise adaptively; it emerges through rewiring of network connections according to patterns of synchrony in ongoing oscillatory neural activity. However, in order to improve the applicability of such models to the cortex, spatial characteristics of cortical connectivity need to be respected, which were previously neglected. For this purpose we consider networks endowed with a metric by embedding them into a physical space. We provide an adaptive rewiring model with a spatial distance function and a corresponding spatially local rewiring bias. The spatially constrained adaptive rewiring principle is able to steer the evolving network topology to small world status, even more consistently so than without spatial constraints. Locally biased adaptive rewiring results in a spatial layout of the connectivity structure, in which topologically segregated modules correspond to spatially segregated regions, and these regions are linked by long-range connections. The principle of locally biased adaptive rewiring, thus, may explain both the topological connectivity structure and spatial distribution of connections between neuronal units in a large-scale cortical architecture.
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.
Dynamic range in small-world networks of Hodgkin-Huxley neurons with chemical synapses
NASA Astrophysics Data System (ADS)
Batista, C. A. S.; Viana, R. L.; Lopes, S. R.; Batista, A. M.
2014-09-01
According to Stevens' law the relationship between stimulus and response is a power-law within an interval called the dynamic range. The dynamic range of sensory organs is found to be larger than that of a single neuron, suggesting that the network structure plays a key role in the behavior of both the scaling exponent and the dynamic range of neuron assemblies. In order to verify computationally the relationships between stimulus and response for spiking neurons, we investigate small-world networks of neurons described by the Hodgkin-Huxley equations connected by chemical synapses. We found that the dynamic range increases with the network size, suggesting that the enhancement of the dynamic range observed in sensory organs, with respect to single neurons, is an emergent property of complex network dynamics.
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
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.
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.
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
Two-dimensional small-world networks: Navigation with local information
NASA Astrophysics Data System (ADS)
Chen, Jian-Zhen; Liu, Wei; Zhu, Jian-Yang
2006-05-01
A navigation process is studied on a variant of the Watts-Strogatz small-world network model embedded on a square lattice. With probability p , each vertex sends out a long-range link, and the probability of the other end of this link falling on a vertex at lattice distance r away decays as r-α . Vertices on the network have knowledge of only their nearest neighbors. In a navigation process, messages are forwarded to a designated target. For α<3 and α≠2 , a scaling relation is found between the average actual path length and pL , where L is the average length of the additional long range links. Given pL>1 , a dynamic small world effect is observed, and the behavior of the scaling function at large enough pL is obtained. At α=2 and 3, this kind of scaling breaks down, and different functions of the average actual path length are obtained. For α>3 , the average actual path length is nearly linear with network size.
Effects of hybrid synapses on the vibrational resonance in small-world neuronal networks.
Yu, Haitao; Wang, Jiang; Sun, Jianbing; Yu, Haifeng
2012-09-01
We investigate the effect of vibrational resonance in small-world neuronal networks with hybrid chemical and electrical synapses. It is shown that, irrespective of the probability of chemical synapses, an optimal amplitude of high-frequency component of the signal can optimize the dynamical response of neuron populations to the low-frequency component, which encodes the information. This effect of vibrational resonance of neuronal systems depends extensively on the network structure and parameters, which determine the ability of neuronal networks to enhance the outreach of localized subthreshold low-frequency signal. In particular, chemical synaptic coupling is more efficient than the electrical coupling for the transmission of local input signal due to its selective coupling. Moreover, there exists an optimal small-world topology characterized by an optimal value of rewiring probability, warranting the largest peak value of the system response. Considering that two-frequency signals are ubiquity in brain dynamics, we expect the presented results could have important implications for signal processing in neuronal systems. PMID:23020444
Effects of hybrid synapses on the vibrational resonance in small-world neuronal networks.
Yu, Haitao; Wang, Jiang; Sun, Jianbing; Yu, Haifeng
2012-09-01
We investigate the effect of vibrational resonance in small-world neuronal networks with hybrid chemical and electrical synapses. It is shown that, irrespective of the probability of chemical synapses, an optimal amplitude of high-frequency component of the signal can optimize the dynamical response of neuron populations to the low-frequency component, which encodes the information. This effect of vibrational resonance of neuronal systems depends extensively on the network structure and parameters, which determine the ability of neuronal networks to enhance the outreach of localized subthreshold low-frequency signal. In particular, chemical synaptic coupling is more efficient than the electrical coupling for the transmission of local input signal due to its selective coupling. Moreover, there exists an optimal small-world topology characterized by an optimal value of rewiring probability, warranting the largest peak value of the system response. Considering that two-frequency signals are ubiquity in brain dynamics, we expect the presented results could have important implications for signal processing in neuronal systems.
A study on small-world brain functional networks altered by postherpetic neuralgia.
Zhang, Yue; Liu, Jing; Li, Longchuan; Du, Minyi; Fang, Wenxue; Wang, Dongxin; Jiang, Xuexiang; Hu, Xiaoping; Zhang, Jue; Wang, Xiaoying; Fang, Jing
2014-05-01
Understanding the effect of postherpetic neuralgia (PHN) pain on brain activity is important for clinical strategies. This is the first study, to our knowledge, to relate PHN pain to small-world properties of brain functional networks. Functional magnetic resonance imaging (fMRI) was used to construct functional brain networks of the subjects during the resting state. Sixteen patients with PHN pain and 16 (8 males, 8 females for both groups) age-matched controls were studied. The PHN patients exhibited decreased local efficiency along with non-significant changes of global efficiency in comparison with the healthy controls. Moreover, regional nodal efficiency was found to be significantly affected by PHN pain in the areas related to sense (postcentral gyrus, inferior parietal gyrus and thalamus), memory/affective processes (parahippocampal gyrus) and emotional activities (putamen). Significant correlation (p<0.05) was also found between the nodal efficiency of putamen and pain intensity in PHN patients. Our results suggest that PHN modulates the local efficiency, and the small-world properties of brain networks may have potentials to objectively evaluate pain information in clinic.
Relaxation dynamics of small-world degree-distributed treelike polymer networks
NASA Astrophysics Data System (ADS)
Galiceanu, Mircea; Oliveira, Edieliton S.; Dolgushev, Maxim
2016-11-01
Hyperbranched polymers are typically treelike macromolecules with a very disordered structure. Here we construct hyperbranched polymers based on the degree distribution of the small-world networks. This algorithm allows us to study a transition from monodisperse linear chains to structurally-disordered dendritic polymers by varying the parameter p (0 ≤ p ≤ 1), which measures the randomness and the degree of branching of the network. Employing the framework of generalized Gaussian structures, we determine for the obtained structures the relaxation spectra, which are exemplified on the mechanical relaxation moduli (storage and loss moduli). We monitor these physical quantities for networks of different sizes and for various values of the parameter p. In the intermediate frequency domain, we encounter macroscopically distinguishable behaviours.
Disease transmission in territorial populations: the small-world network of Serengeti lions.
Craft, Meggan E; Volz, Erik; Packer, Craig; Meyers, Lauren Ancel
2011-06-01
Territoriality in animal populations creates spatial structure that is thought to naturally buffer disease invasion. Often, however, territorial populations also include highly mobile, non-residential individuals that potentially serve as disease superspreaders. Using long-term data from the Serengeti Lion Project, we characterize the contact network structure of a territorial wildlife population and address the epidemiological impact of nomadic individuals. As expected, pride contacts are dominated by interactions with neighbouring prides and interspersed by encounters with nomads as they wander throughout the ecosystem. Yet the pride-pride network also includes occasional long-range contacts between prides, making it surprisingly small world and vulnerable to epidemics, even without nomads. While nomads increase both the local and global connectivity of the network, their epidemiological impact is marginal, particularly for diseases with short infectious periods like canine distemper virus. Thus, territoriality in Serengeti lions may be less protective and non-residents less important for disease transmission than previously considered.
Latching chains in K-nearest-neighbor and modular small-world networks.
Song, Sanming; Yao, Hongxun; Simonov, Alexander Yurievich
2015-01-01
Latching dynamics retrieve pattern sequences successively by neural adaption and pattern correlation. We have previously proposed a modular latching chain model in Song et al. (2014) to better accommodate the structured transitions in the brain. Different cortical areas have different network structures. To explore how structural parameters like rewiring probability, threshold, noise and feedback connections affect the latching dynamics, two different connection schemes, K-nearest-neighbor network and modular network both having modular structure are considered. Latching chains are measured using two proposed measures characterizing length of intra-modular latching chains and sequential inter-modular association transitions. Our main findings include: (1) With decreasing threshold coefficient and rewiring probability, both the K-nearest-neighbor network and the modular network experience quantitatively similar phase change processes. (2) The modular network exhibits selectively enhanced latching in the small-world range of connectivity. (3) The K-nearest-neighbor network is more robust to changes in rewiring probability, while the modular network is more robust to the presence of noise pattern pairs and to changes in the strength of feedback connections. According to our findings, the relationships between latching chains in K-nearest-neighbor and modular networks and different forms of cognition and information processing emerging in the brain are discussed.
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.
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.
Effects of distance-dependent delay on small-world neuronal networks.
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. PMID:27176338
Effects of distance-dependent delay on small-world neuronal networks.
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.
Synchronization transition of identical phase oscillators in a directed small-world network
NASA Astrophysics Data System (ADS)
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.
Yu, Yongqiang; Zhou, Xia; Wang, Haibao; Hu, Xiaopeng; Zhu, Xiaoqun; Xu, Liyan; Zhang, Chao; Sun, Zhongwu
2015-01-01
To investigate the topological properties of the functional connectivity and their relationships with cognition impairment in subcortical vascular cognitive impairment (SVCI) patients, resting-state fMRI and graph theory approaches were employed in 23 SVCI patients and 20 healthy controls. Functional connectivity between 90 brain regions was estimated using bivariate correlation analysis and thresholded to construct a set of undirected graphs. Moreover, all of them were subjected to a battery of cognitive assessment, and the correlations between graph metrics and cognitive performance were further analyzed. Our results are as follows: functional brain networks of both SVCI patients and controls showed small-world attributes over a range of thresholds(0.15≤sparsity≤0.40). However, global topological organization of the functional brain networks in SVCI was significantly disrupted, as indicated by reduced global and local efficiency, clustering coefficients and increased characteristic path lengths relative to normal subjects. The decreased activity areas in SVCI predominantly targeted in the frontal-temporal lobes, while subcortical regions showed increased topological properties, which are suspected to compensate for the inefficiency of the functional network. We also demonstrated that altered brain network properties in SVCI are closely correlated with general cognitive and praxis dysfunction. The disruption of whole-brain topological organization of the functional connectome provides insight into the functional changes in the human brain in SVCI. PMID:26132397
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.
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
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.
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.
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.
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.
Critical properties of a dissipative sandpile model on small-world networks
NASA Astrophysics Data System (ADS)
Bhaumik, Himangsu; Santra, S. B.
2013-12-01
A dissipative sandpile model is constructed and studied on small-world networks (SWNs). SWNs are generated by adding extra links between two arbitrary sites of a two-dimensional square lattice with different shortcut densities ϕ. Three regimes are identified: regular lattice (RL) for ϕ ≲2-12, SWN for 2-12<ϕ<0.1, and random network (RN) for ϕ ≥0.1. In the RL regime, the sandpile dynamics is characterized by the usual Bak, Tang, and Weisenfeld (BTW)-type correlated scaling, whereas in the RN regime it is characterized by mean-field scaling. On SWNs, both scaling behaviors are found to coexist. Small compact avalanches below a certain characteristic size sc are found to belong to the BTW universality class, whereas large, sparse avalanches above sc are found to belong to the mean-field universality class. A scaling theory for the coexistence of two scaling forms on a SWN is developed and numerically verified. Though finite-size scaling is not valid for the dissipative sandpile model on RLs or on SWNs, it is found to be valid on RNs for the same model. Finite-size scaling on RNs appears to be an outcome of super diffusive sand transport and uncorrelated toppling waves.
Critical properties of a dissipative sandpile model on small-world networks.
Bhaumik, Himangsu; Santra, S B
2013-12-01
A dissipative sandpile model is constructed and studied on small-world networks (SWNs). SWNs are generated by adding extra links between two arbitrary sites of a two-dimensional square lattice with different shortcut densities ϕ. Three regimes are identified: regular lattice (RL) for ϕ≲2(-12), SWN for 2(-12)<ϕ<0.1, and random network (RN) for ϕ≥0.1. In the RL regime, the sandpile dynamics is characterized by the usual Bak, Tang, and Weisenfeld (BTW)-type correlated scaling, whereas in the RN regime it is characterized by mean-field scaling. On SWNs, both scaling behaviors are found to coexist. Small compact avalanches below a certain characteristic size s(c) are found to belong to the BTW universality class, whereas large, sparse avalanches above s(c) are found to belong to the mean-field universality class. A scaling theory for the coexistence of two scaling forms on a SWN is developed and numerically verified. Though finite-size scaling is not valid for the dissipative sandpile model on RLs or on SWNs, it is found to be valid on RNs for the same model. Finite-size scaling on RNs appears to be an outcome of super diffusive sand transport and uncorrelated toppling waves.
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.
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)
Yu, Haitao; Wang, Jiang; Du, Jiwei; Deng, Bin; Wei, Xile; Liu, Chen
2013-05-01
The effects of time delay and rewiring probability on stochastic resonance and spatiotemporal order in small-world neuronal networks are studied in this paper. Numerical results show that, irrespective of the pacemaker introduced to one single neuron or all neurons of the network, the phenomenon of stochastic resonance occurs. The time delay in the coupling process can either enhance or destroy stochastic resonance on small-world neuronal networks. In particular, appropriately tuned delays can induce multiple stochastic resonances, which appear intermittently at integer multiples of the oscillation period of the pacemaker. More importantly, it is found that the small-world topology can significantly affect the stochastic resonance on excitable neuronal networks. For small time delays, increasing the rewiring probability can largely enhance the efficiency of pacemaker-driven stochastic resonance. We argue that the time delay and the rewiring probability both play a key role in determining the ability of the small-world neuronal network to improve the noise-induced outreach of the localized subthreshold pacemaker.
Yu, Haitao; Wang, Jiang; Du, Jiwei; Deng, Bin; Wei, Xile; Liu, Chen
2013-05-01
The effects of time delay and rewiring probability on stochastic resonance and spatiotemporal order in small-world neuronal networks are studied in this paper. Numerical results show that, irrespective of the pacemaker introduced to one single neuron or all neurons of the network, the phenomenon of stochastic resonance occurs. The time delay in the coupling process can either enhance or destroy stochastic resonance on small-world neuronal networks. In particular, appropriately tuned delays can induce multiple stochastic resonances, which appear intermittently at integer multiples of the oscillation period of the pacemaker. More importantly, it is found that the small-world topology can significantly affect the stochastic resonance on excitable neuronal networks. For small time delays, increasing the rewiring probability can largely enhance the efficiency of pacemaker-driven stochastic resonance. We argue that the time delay and the rewiring probability both play a key role in determining the ability of the small-world neuronal network to improve the noise-induced outreach of the localized subthreshold pacemaker.
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.
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.
Shim, Miseon; Kim, Do-Won; Lee, Seung-Hwan; Im, Chang-Hwan
2014-07-01
P300 deficits in patients with schizophrenia have previously been investigated using EEGs recorded during auditory oddball tasks. However, small-world cortical functional networks during auditory oddball tasks and their relationships with symptom severity scores in schizophrenia have not yet been investigated. In this study, the small-world characteristics of source-level functional connectivity networks of EEG responses elicited by an auditory oddball paradigm were evaluated using two representative graph-theoretical measures, clustering coefficient and path length. EEG signals from 34 patients with schizophrenia and 34 healthy controls were recorded while each subject was asked to attend to oddball tones. The results showed reduced clustering coefficients and increased path lengths in patients with schizophrenia, suggesting that the small-world functional network is disrupted in patients with schizophrenia. In addition, the negative and cognitive symptom components of positive and negative symptom scales were negatively correlated with the clustering coefficient and positively correlated with path length, demonstrating that both indices are indicators of symptom severity in patients with schizophrenia. Our study results suggest that disrupted small-world characteristics are potential biomarkers for patients with schizophrenia.
Li, Meiling; Chen, Heng; Wang, Junping; Liu, Feng; Long, Zhiliang; Wang, Yifeng; Iturria-Medina, Yasser; Zhang, Jiang; Yu, Chunshui; Chen, Huafu
2014-03-01
Previous behavioral and scanning studies have suggested that handedness is associated with differences in brain morphology as well as in anatomical and functional lateralization. However, little is known about the topological organization of the white matter (WM) structural networks related to handedness. We employed diffusion tensor imaging tractography to investigate handedness- and hemisphere-related differences in the topological organization of the human cortical anatomical network. After constructing left hemispheric/right hemispheric weighted structural networks in 32 right-handed and 24 left-handed healthy individuals, we analyzed the networks by graph theoretic analysis. We found that both the right and left hemispheric WM structural networks in the two groups possessed small-world attributes (high local clustering and short paths between nodes), findings which are consistent with recent results from whole-brain structural networks. In addition, the right hemisphere tended to be more efficient than the left hemisphere, suggesting a high efficiency of general information processing in the right hemisphere. Finally, we found that the right-handed subjects had significant asymmetries in small-world properties (normalized clustering coefficient γ, normalized path length λ, and small-worldness σ), while left-handed subjects had fewer asymmetries. Our findings from large-scale brain networks aid in understanding the structural substrates underlying handedness-related and hemisphere-related differences in cognition and behavior. PMID:24564422
Song, H Francis; Wang, Xiao-Jing
2014-12-01
Small-world networks-complex networks characterized by a combination of high clustering and short path lengths-are widely studied using the paradigmatic model of Watts and Strogatz (WS). Although the WS model is already quite minimal and intuitive, we describe an alternative formulation of the WS model in terms of a distance-dependent probability of connection that further simplifies, both practically and theoretically, the generation of directed and undirected WS-type small-world networks. In addition to highlighting an essential feature of the WS model that has previously been overlooked, namely the equivalence to a simple distance-dependent model, this alternative formulation makes it possible to derive exact expressions for quantities such as the degree and motif distributions and global clustering coefficient for both directed and undirected networks in terms of model parameters.
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.
Anishchenko, Anastasia; Treves, Alessandro
2006-10-01
The metric structure of synaptic connections is obviously an important factor in shaping the properties of neural networks, in particular the capacity to retrieve memories, with which are endowed autoassociative nets operating via attractor dynamics. Qualitatively, some real networks in the brain could be characterized as 'small worlds', in the sense that the structure of their connections is intermediate between the extremes of an orderly geometric arrangement and of a geometry-independent random mesh. Small worlds can be defined more precisely in terms of their mean path length and clustering coefficient; but is such a precise description useful for a better understanding of how the type of connectivity affects memory retrieval? We have simulated an autoassociative memory network of integrate-and-fire units, positioned on a ring, with the network connectivity varied parametrically between ordered and random. We find that the network retrieves previously stored memory patterns when the connectivity is close to random, and displays the characteristic behavior of ordered nets (localized 'bumps' of activity) when the connectivity is close to ordered. Recent analytical work shows that these two behaviors can coexist in a network of simple threshold-linear units, leading to localized retrieval states. We find that they tend to be mutually exclusive behaviors, however, with our integrate-and-fire units. Moreover, the transition between the two occurs for values of the connectivity parameter which are not simply related to the notion of small worlds.
Kim, Sang-Yoon; Lim, Woochang
2015-01-01
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 J(inter) and the average number of intermodular links per interneuron M(syn)(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 J(inter) seems to play "dual" roles for the pacing between spikes in each subnetwork. For large J(inter), due to strong inhibition it plays a destructive role to "spoil" the pacing between spikes, while for small J(inter) it plays a constructive role to "favor" the pacing between spikes. Through competition between the constructive and the destructive roles of J(inter), there exists an intermediate optimal J(inter) at which the pacing degree between spikes becomes maximal. In contrast, the average number of intermodular links per interneuron M(syn)(inter) seems to play a role just to favor the pacing between spikes. With increasing M(syn)(inter), the pacing degree between spikes increases monotonically thanks to the increase in the degree of effectiveness of global communication between spikes
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
Kim, Sang-Yoon; Lim, Woochang
2015-01-01
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 J(inter) and the average number of intermodular links per interneuron M(syn)(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 J(inter) seems to play "dual" roles for the pacing between spikes in each subnetwork. For large J(inter), due to strong inhibition it plays a destructive role to "spoil" the pacing between spikes, while for small J(inter) it plays a constructive role to "favor" the pacing between spikes. Through competition between the constructive and the destructive roles of J(inter), there exists an intermediate optimal J(inter) at which the pacing degree between spikes becomes maximal. In contrast, the average number of intermodular links per interneuron M(syn)(inter) seems to play a role just to favor the pacing between spikes. With increasing M(syn)(inter), the pacing degree between spikes increases monotonically thanks to the increase in the degree of effectiveness of global communication between spikes
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.
NASA Astrophysics Data System (ADS)
Song, H. Francis; Wang, Xiao-Jing
2014-12-01
Small-world networks—complex networks characterized by a combination of high clustering and short path lengths—are widely studied using the paradigmatic model of Watts and Strogatz (WS). Although the WS model is already quite minimal and intuitive, we describe an alternative formulation of the WS model in terms of a distance-dependent probability of connection that further simplifies, both practically and theoretically, the generation of directed and undirected WS-type small-world networks. In addition to highlighting an essential feature of the WS model that has previously been overlooked, namely the equivalence to a simple distance-dependent model, this alternative formulation makes it possible to derive exact expressions for quantities such as the degree and motif distributions and global clustering coefficient for both directed and undirected networks in terms of model parameters.
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.
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.
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)
Chen, Yong; Qin, Shao-Meng; Yu, Lianchun; Zhang, Shengli
2008-03-01
We studied synchronization between prisoner’s dilemma games with voluntary participation in two Newman-Watts small-world networks. It was found that there are three kinds of synchronization: partial phase synchronization, total phase synchronization, and complete synchronization, for varied coupling factors. Besides, two games can reach complete synchronization for the large enough coupling factor. We also discussed the effect of the coupling factor on the amplitude of oscillation of cooperator density.
Yu, Haitao; Wang, Jiang; Du, Jiwei; Deng, Bin; Wei, Xile
2015-02-01
Effects of time delay on the local and global synchronization in small-world neuronal networks with chemical synapses are investigated in this paper. Numerical results show that, for both excitatory and inhibitory coupling types, the information transmission delay can always induce synchronization transitions of spiking neurons in small-world networks. In particular, regions of in-phase and out-of-phase synchronization of connected neurons emerge intermittently as the synaptic delay increases. For excitatory coupling, all transitions to spiking synchronization occur approximately at integer multiples of the firing period of individual neurons; while for inhibitory coupling, these transitions appear at the odd multiples of the half of the firing period of neurons. More importantly, the local synchronization transition is more profound than the global synchronization transition, depending on the type of coupling synapse. For excitatory synapses, the local in-phase synchronization observed for some values of the delay also occur at a global scale; while for inhibitory ones, this synchronization, observed at the local scale, disappears at a global scale. Furthermore, the small-world structure can also affect the phase synchronization of neuronal networks. It is demonstrated that increasing the rewiring probability can always improve the global synchronization of neuronal activity, but has little effect on the local synchronization of neighboring neurons.
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
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.
Liu, Tian; Chen, Yanni; Lin, Pan; Wang, Jue
2015-07-01
We investigated the topologic properties of human brain attention-related functional networks associated with Multi-Source Interference Task (MSIT) performance using electroencephalography (EEG). Data were obtained from 13 children diagnosed with attention-deficit/hyperactivity disorder (ADHD) and 13 normal control children. Functional connectivity between all pairwise combinations of EEG channels was established by calculating synchronization likelihood (SL). The cluster coefficients and path lengths were computed as a function of degree K. The results showed that brain attention functional networks of normal control subjects had efficient small-world topologic properties, whereas these topologic properties were altered in ADHD. In particular, increased local characteristics combined with decreased global characteristics in ADHD led to a disorder-related shift of the network topologic structure toward ordered networks. These findings are consistent with a hypothesis of dysfunctional segregation and integration of the brain in ADHD, and enhance our understanding of the underlying pathophysiologic mechanism of this illness.
Altered small-world anatomical networks in Apolipoprotein-E4 (ApoE4) carriers using MRI.
Goryawala, Mohammed; Zhou, Qi; Duara, Ranjan; Loewenstein, David; Cabrerizo, Mercedes; Barker, Warren; Adjouadi, Malek
2014-01-01
Apolipoprotein E (ApoE) gene and primarily its allele e4 have been identified as a risk factor for Alzheimer's disease (AD). The prevalence of the gene in 25-30% in the population makes it essential to estimate its role in neuroregulation and its impact on distributed brain networks. In this study, we provide computational neuroanatomy based interpretation of large-scale and small-world cortical networks in cognitive normal (CN) subjects with differing Apolipoprotein-E4 (ApoE4) gene expression. We estimated large-scale anatomical networks from cortical thickness measurements derived from magnetic resonance imaging in 147 CN subjects explored in relation to ApoE4 genotype (e4+ carriers (n=41) versus e4- non-carriers (n=106)). Brain networks were constructed by thresholding cortical thickness correlation matrices of 68 bilateral regions of the brain analyzed using well-established graph theoretical approaches. Compared to ApoE4 non-carriers, carriers showed increased interregional correlation coefficients in regions like precentral, superior frontal and inferior temporal regions. Interestingly most of the altered connections were intra-hemispheric limited primarily to the right hemisphere. Furthermore, ApoE4 carriers demonstrated abnormal small-world architecture in the cortical networks with increased clustering coefficient and path lengths as compared to non-carrier, suggesting a less optimal topological organization. Additionally non-carriers demonstrated higher betweenness in regions such as middle temporal, para-hippocampal gyrus, posterior cingulate and insula of the default mode network (DMN), also seen in subjects with AD and mild cognitive impairment (MCI). The results suggest that the complex morphological cortical connectivity patterns are altered in ApoE4 carriers as compared to non-carriers, providing evidence for disruption of integrity in large-scale anatomical brain networks.
NASA Astrophysics Data System (ADS)
Li, Chunguang; Maini, Philip K.
2005-10-01
The Penna bit-string model successfully encompasses many phenomena of population evolution, including inheritance, mutation, evolution, and aging. If we consider social interactions among individuals in the Penna model, the population will form a complex network. In this paper, we first modify the Verhulst factor to control only the birth rate, and introduce activity-based preferential reproduction of offspring in the Penna model. The social interactions among individuals are generated by both inheritance and activity-based preferential increase. Then we study the properties of the complex network generated by the modified Penna model. We find that the resulting complex network has a small-world effect and the assortative mixing property.
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.
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.
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.
Kim, Sang-Yoon; Lim, Woochang
2015-04-01
We are interested in noise-induced firings of subthreshold neurons which may be used for encoding environmental stimuli. Noise-induced population synchronization was previously studied only for the case of global coupling, unlike the case of subthreshold spiking neurons. Hence, we investigate the effect of complex network architecture on noise-induced synchronization in an inhibitory population of subthreshold bursting Hindmarsh-Rose neurons. For modeling complex synaptic connectivity, we consider the Watts-Strogatz small-world network which interpolates between regular lattice and random network via rewiring, and investigate the effect of small-world connectivity on emergence of noise-induced population synchronization. Thus, noise-induced burst synchronization (synchrony on the slow bursting time scale) and spike synchronization (synchrony on the fast spike time scale) are found to appear in a synchronized region of the [Formula: see text]-[Formula: see text] plane ([Formula: see text]: synaptic inhibition strength and [Formula: see text]: noise intensity). As the rewiring probability [Formula: see text] is decreased from 1 (random network) to 0 (regular lattice), the region of spike synchronization shrinks rapidly in the [Formula: see text]-[Formula: see text] plane, while the region of the burst synchronization decreases slowly. We separate the slow bursting and the fast spiking time scales via frequency filtering, and characterize the noise-induced burst and spike synchronizations by employing realistic order parameters and statistical-mechanical measures introduced in our recent work. Thus, the bursting and spiking thresholds for the burst and spike synchronization transitions are determined in terms of the bursting and spiking order parameters, respectively. Furthermore, we also measure the degrees of burst and spike synchronizations in terms of the statistical-mechanical bursting and spiking measures, respectively.
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
Ribeiro, Tiago L; Ribeiro, Sidarta; Belchior, Hindiael; Caixeta, Fábio; Copelli, Mauro
2014-01-01
The power-law size distributions obtained experimentally for neuronal avalanches are an important evidence of criticality in the brain. This evidence is supported by the fact that a critical branching process exhibits the same exponent [Formula: see text]. Models at criticality have been employed to mimic avalanche propagation and explain the statistics observed experimentally. However, a crucial aspect of neuronal recordings has been almost completely neglected in the models: undersampling. While in a typical multielectrode array hundreds of neurons are recorded, in the same area of neuronal tissue tens of thousands of neurons can be found. Here we investigate the consequences of undersampling in models with three different topologies (two-dimensional, small-world and random network) and three different dynamical regimes (subcritical, critical and supercritical). We found that undersampling modifies avalanche size distributions, extinguishing the power laws observed in critical systems. Distributions from subcritical systems are also modified, but the shape of the undersampled distributions is more similar to that of a fully sampled system. Undersampled supercritical systems can recover the general characteristics of the fully sampled version, provided that enough neurons are measured. Undersampling in two-dimensional and small-world networks leads to similar effects, while the random network is insensitive to sampling density due to the lack of a well-defined neighborhood. We conjecture that neuronal avalanches recorded from local field potentials avoid undersampling effects due to the nature of this signal, but the same does not hold for spike avalanches. We conclude that undersampled branching-process-like models in these topologies fail to reproduce the statistics of spike avalanches.
Nogawa, Tomoaki; Hasegawa, Takehisa; Nemoto, Koji
2012-09-01
We study the Ising model in a hierarchical small-world network by renormalization group analysis and find a phase transition between an ordered phase and a critical phase, which is driven by the coupling strength of the shortcut edges. Unlike ordinary phase transitions, which are related to unstable renormalization fixed points (FPs), the singularity in the ordered phase of the present model is governed by the FP that coincides with the stable FP of the ordered phase. The weak stability of the FP yields peculiar criticalities, including logarithmic behavior. On the other hand, the critical phase is related to a nontrivial FP, which depends on the coupling strength and is continuously connected to the ordered FP at the transition point. We show that this continuity indicates the existence of a finite correlation-length-like quantity inside the critical phase, which diverges upon approaching the transition point.
NASA Astrophysics Data System (ADS)
Zhou, Jing; Xu, Xu; Yu, Dongyuan; Zheng, Zhuoqun
This paper presents a detailed analysis on the stability and instability of a coupled oscillator network with small world connections. This network consists of regular connections, excitatory short-cuts or inhibitory short-cuts. By using the perturbation theory of matrix, we give the upper and lower bounds of maximum and minimum eigenvalues of the coupling strength matrix, and then give the generalized sufficient conditions that guarantee the system complete stability or complete instability. In addition, we analyze the effects of the short-cut possibility, excitatory or inhibitory short-cut strength and time delay on the system stability. We also analyze the instability mechanism and bifurcation modes. In addition, the studies on the robustness stability show that the stability of this network is more robust to change of short-cut connections than the regular network. Compared to the mean-field theory, the stability conditions from the proposed method are more conservational. However, the proposed method can guarantee the complete stability even if the randomness is in the system. They are more useful and adaptive than mean-field theory especially when the excitatory and inhibitory connections exist simultaneously.
Qian, Yu
2014-01-01
The synchronization transitions in Newman-Watts small-world neuronal networks (SWNNs) induced by time delay and long-range connection (LRC) probability have been investigated by synchronization parameter and space-time plots. Four distinct parameter regions, that is, asynchronous region, transition region, synchronous region, and oscillatory region have been discovered at certain LRC probability as time delay is increased. Interestingly, desynchronization is observed in oscillatory region. More importantly, we consider the spatiotemporal patterns obtained in delayed Newman-Watts SWNNs are the competition results between long-range drivings (LRDs) and neighboring interactions. In addition, for moderate time delay, the synchronization of neuronal network can be enhanced remarkably by increasing LRC probability. Furthermore, lag synchronization has been found between weak synchronization and complete synchronization as LRC probability is a little less than 1.0. Finally, the two necessary conditions, moderate time delay and large numbers of LRCs, are exposed explicitly for synchronization in delayed Newman-Watts SWNNs. PMID:24810595
Qian, Yu
2014-01-01
The synchronization transitions in Newman-Watts small-world neuronal networks (SWNNs) induced by time delay τ and long-range connection (LRC) probability P have been investigated by synchronization parameter and space-time plots. Four distinct parameter regions, that is, asynchronous region, transition region, synchronous region, and oscillatory region have been discovered at certain LRC probability P = 1.0 as time delay is increased. Interestingly, desynchronization is observed in oscillatory region. More importantly, we consider the spatiotemporal patterns obtained in delayed Newman-Watts SWNNs are the competition results between long-range drivings (LRDs) and neighboring interactions. In addition, for moderate time delay, the synchronization of neuronal network can be enhanced remarkably by increasing LRC probability. Furthermore, lag synchronization has been found between weak synchronization and complete synchronization as LRC probability P is a little less than 1.0. Finally, the two necessary conditions, moderate time delay and large numbers of LRCs, are exposed explicitly for synchronization in delayed Newman-Watts SWNNs.
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
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…
da Silva, Juliana Angeiras Batista; Moreira, Francisco George Brady; dos Santos, Vivianni Marques Leite; Longo, Ricardo Luiz
2014-09-28
Cluster (or island) statistics and topological statistical mechanics based properties were employed in the analyses of hydrogen bond (H-bond) networks of t-butanol, n-butanol and ammonia aqueous solutions. These networks were generated from equilibrated Monte Carlo simulations at mixture compositions covering the entire range of miscibility and a fine grid of points around the topological transitions. We found that these H-bond networks changed from a percolation regime in water rich mixtures to a non-percolating behavior at non-aqueous component rich compositions. Topological analysis of local (clustering coefficients, average degrees) semi-global (path lengths) and global (spectral densities) properties indicated the presence of small-world patterns for the H-bond networks in mixtures at mole fraction compositions larger than ca. 0.6. These small-world patterns are characterized by highly clustered networks with small path lengths. Spectral densities show high order moment contributions that correlate with small-world patterns, thus corroborating the robustness of these statistical mechanics based topological analyses. The degree distributions of these networks were partially rationalized by the differences in the water-water and solute-solute H-bonds.
Anderson, Ariana; Cohen, Mark S
2013-01-01
Functional network connectivity (FNC) is a method of analyzing the temporal relationship of anatomical brain components, comparing the synchronicity between patient groups or conditions. We use functional-connectivity measures between independent components to classify between Schizophrenia patients and healthy controls during resting-state. Connectivity is measured using a variety of graph-theoretic connectivity measures such as graph density, average path length, and small-worldness. The Schizophrenia patients showed significantly less clustering (transitivity) among components than healthy controls (p < 0.05, corrected) with networks less likely to be connected, and also showed lower small-world connectivity than healthy controls. Using only these connectivity measures, an SVM classifier (without parameter tuning) could discriminate between Schizophrenia patients and healthy controls with 65% accuracy, compared to 51% chance. This implies that the global functional connectivity between resting-state networks is altered in Schizophrenia, with networks more likely to be disconnected and behave dissimilarly for diseased patients. We present this research finding as a tutorial using the publicly available COBRE dataset of 146 Schizophrenia patients and healthy controls, provided as part of the 1000 Functional Connectomes Project. We demonstrate preprocessing, using independent component analysis (ICA) to nominate networks, computing graph-theoretic connectivity measures, and finally using these connectivity measures to either classify between patient groups or assess between-group differences using formal hypothesis testing. All necessary code is provided for both running command-line FSL preprocessing, and for computing all statistical measures and SVM classification within R. Collectively, this work presents not just findings of diminished FNC among resting-state networks in Schizophrenia, but also a practical connectivity tutorial.
van Noort, Vera; Snel, Berend; Huynen, Martijn A
2004-01-01
We investigated the gene coexpression network in Saccharomyces cerevisiae, in which genes are linked when they are coregulated. This network is shown to have a scale-free, small-world architecture. Such architecture is typical of biological networks in which the nodes are connected when they are involved in the same biological process. Current models for the evolution of intracellular networks do not adequately reproduce the features that we observe in the network. We therefore derive a new model for its evolution based on the observation that there is a positive correlation between the sequence similarity of paralogues and their probability of coexpression or sharing of transcription factor binding sites (TFBSs). The simple, neutralist's model consists of (1) coduplication of genes with their TFBSs, (2) deletion and duplication of individual TFBSs and (3) gene loss. A network is constructed by connecting genes that share multiple TFBSs. Our model reproduces the scale-free, small-world architecture of the coregulation network and the homology relations between coregulated genes without the need for selection either at the level of the network structure or at the level of gene regulation. PMID:14968131
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
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
NASA Astrophysics Data System (ADS)
Ma, Jun; Yang, Li-Jian; Wu, Ying; Zhang, Cai-Rong
2010-09-01
The effect of small-world connection and noise on the formation and transition of spiral wave in the networks of Hodgkin-Huxley neurons are investigated in detail. Some interesting results are found in our numerical studies. i) The quiescent neurons are activated to propagate electric signal to others by generating and developing spiral wave from spiral seed in small area. ii) A statistical factor is defined to describe the collective properties and phase transition induced by the topology of networks and noise. iii) Stable rotating spiral wave can be generated and keeps robust when the rewiring probability is below certain threshold, otherwise, spiral wave can not be developed from the spiral seed and spiral wave breakup occurs for a stable rotating spiral wave. iv) Gaussian white noise is introduced on the membrane of neurons to study the noise-induced phase transition on spiral wave in small-world networks of neurons. It is confirmed that Gaussian white noise plays active role in supporting and developing spiral wave in the networks of neurons, and appearance of smaller factor of synchronization indicates high possibility to induce spiral wave.
Tse, A; Verkhivker, G M
2015-07-01
The human protein kinases play a fundamental regulatory role in orchestrating functional processes in complex cellular networks. Understanding how conformational equilibrium between functional kinase states can be modulated by ligand binding or mutations is critical for quantifying molecular basis of allosteric regulation and drug resistance. In this work, molecular dynamics simulations of the Abl kinase complexes with cancer drugs (Imatinib and Dasatinib) were combined with structure-based network modeling to characterize dynamics of the residue interaction networks in these systems. The results have demonstrated that structural architecture of kinase complexes can produce a small-world topology of the interaction networks. Our data have indicated that specific Imatinib binding to a small number of highly connected residues could lead to network-bridging effects and allow for efficient allosteric communication, which is mediated by a dominant pathway sensitive to the unphosphorylated Abl state. In contrast, Dasatinib binding to the active kinase form may activate a broader ensemble of allosteric pathways that are less dependent on the phosphorylation status of Abl and provide a better balance between the efficiency and resilience of signaling routes. Our results have unveiled how differences in the residue interaction networks and allosteric communications of the Abl kinase complexes can be directly related to drug resistance effects. This study offers a plausible perspective on how efficiency and robustness of the residue interaction networks and allosteric pathways in kinase structures may be associated with protein responses to drug binding.
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.
Toppi, J; De Vico Fallani, F; Vecchiato, G; Maglione, A G; Cincotti, F; Mattia, D; Salinari, S; Babiloni, F; Astolfi, L
2012-01-01
The application of Graph Theory to the brain connectivity patterns obtained from the analysis of neuroelectrical signals has provided an important step to the interpretation and statistical analysis of such functional networks. The properties of a network are derived from the adjacency matrix describing a connectivity pattern obtained by one of the available functional connectivity methods. However, no common procedure is currently applied for extracting the adjacency matrix from a connectivity pattern. To understand how the topographical properties of a network inferred by means of graph indices can be affected by this procedure, we compared one of the methods extensively used in Neuroscience applications (i.e. fixing the edge density) with an approach based on the statistical validation of achieved connectivity patterns. The comparison was performed on the basis of simulated data and of signals acquired on a polystyrene head used as a phantom. The results showed (i) the importance of the assessing process in discarding the occurrence of spurious links and in the definition of the real topographical properties of the network, and (ii) a dependence of the small world properties obtained for the phantom networks from the spatial correlation of the neighboring electrodes.
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.
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
Li, Meiling; Wang, Junping; Liu, Feng; Chen, Heng; Lu, Fengmei; Wu, Guorong; Yu, Chunshui; Chen, Huafu
2015-05-01
The human brain has been described as a complex network, which integrates information with high efficiency. However, the relationships between the efficiency of human brain functional networks and handedness and brain size remain unclear. Twenty-one left-handed and 32 right-handed healthy subjects underwent a resting-state functional magnetic resonance imaging scan. The whole brain functional networks were constructed by thresholding Pearson correlation matrices of 90 cortical and subcortical regions. Graph theory-based methods were employed to further analyze their topological properties. As expected, all participants demonstrated small-world topology, suggesting a highly efficient topological structure. Furthermore, we found that smaller brains showed higher local efficiency, whereas larger brains showed higher global efficiency, reflecting a suitable efficiency balance between local specialization and global integration of brain functional activity. Compared with right-handers, significant alterations in nodal efficiency were revealed in left-handers, involving the anterior and median cingulate gyrus, middle temporal gyrus, angular gyrus, and amygdala. Our findings indicated that the functional network organization in the human brain was associated with handedness and brain size.
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.
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.
Adaptation algorithms for 2-D feedforward neural networks.
Kaczorek, T
1995-01-01
The generalized weight adaptation algorithms presented by J.G. Kuschewski et al. (1993) and by S.H. Zak and H.J. Sira-Ramirez (1990) are extended for 2-D madaline and 2-D two-layer feedforward neural nets (FNNs).
NASA Astrophysics Data System (ADS)
Li, Yan-Long; Ma, Jun; Zhang, Wei; Liu, Yan-Jun
2009-10-01
This paper numerically investigates the order parameter and synchronisation in the small world connected FitzHugh-Nagumo excitable systems. The simulations show that the order parameter continuously decreases with increasing D, the quality of the synchronisation worsens for large noise intensity. As the coupling intensity goes up, the quality of the synchronisation worsens, and it finds that the larger rewiring probability becomes the larger order parameter. It obtains the complete phase diagram for a wide range of values of noise intensity D and control parameter g.
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.
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.
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
Construction and repair of highly ordered 2D covalent networks by chemical equilibrium regulation.
Guan, Cui-Zhong; Wang, Dong; Wan, Li-Jun
2012-03-21
The construction of well-ordered 2D covalent networks via the dehydration of di-borate aromatic molecules was successfully realized through introducing a small amount of water into a closed reaction system to regulate the chemical equilibrium.
Properties of interacting 2D chiral tensor network states
NASA Astrophysics Data System (ADS)
Bradlyn, Barry; Dubail, Jerome; Read, Nicholas
2015-03-01
In a recent paper, Dubail and Read gave a construction for free fermion tensor network states(TNSs) in the chiral p + ip and ν = 1 Chern insulator topological phases in two dimensions, and gave a generalization to Laughlin-like states. However, on general principles these free fermion states must be ground states of gapless local Hamiltonians. In this talk, we address the issue of the energy gap in the interacting states, with a particular focus on the ν = 1 / 2 bosonic Laughlin-like TNS. Through a combination of analytic and numerical arguments, we will show that these states too have gapless local parent Hamiltonians. Nevertheless, we will explore to what degree they can be used as numerical approximations to gapped phases.
Properties of 2D Chiral Tensor Network States
NASA Astrophysics Data System (ADS)
Bradlyn, Barry; Dubail, Jerome; Read, Nicholas
2014-03-01
States that can be represented as a sum over local auxiliary degress of freedom are known as tensor network states (TNSs). In a recent paper, Dubail and Read gave a construction for free fermion TNSs in the chiral p + ip and ν = 1 Chern insulator topological phases in two dimensions, and gave a generalization to Laughlin-like states. However, on general principles these free fermion states must be ground states of gapless local Hamiltonians. In this talk, we address the issue of what topological properties persist in these gapless states. We show analytically that the DC Hall conductivity for the ν = 1 Chern insulator TNS is quantized, although the conductivity tensor at finite frequency suffers from non-analytic corrections. Additionally, we investigate the issue of the energy gap for the interacting ν = 1 / 2 Laughlin-like TNS through Monte Carlo simulations.
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
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.
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.
Higher-Order Neural Networks Applied to 2D and 3D Object Recognition
NASA Technical Reports Server (NTRS)
Spirkovska, Lilly; Reid, Max B.
1994-01-01
A Higher-Order Neural Network (HONN) can be designed to be invariant to geometric transformations such as scale, translation, and in-plane rotation. Invariances are built directly into the architecture of a HONN and do not need to be learned. Thus, for 2D object recognition, the network needs to be trained on just one view of each object class, not numerous scaled, translated, and rotated views. Because the 2D object recognition task is a component of the 3D object recognition task, built-in 2D invariance also decreases the size of the training set required for 3D object recognition. We present results for 2D object recognition both in simulation and within a robotic vision experiment and for 3D object recognition in simulation. We also compare our method to other approaches and show that HONNs have distinct advantages for position, scale, and rotation-invariant object recognition. The major drawback of HONNs is that the size of the input field is limited due to the memory required for the large number of interconnections in a fully connected network. We present partial connectivity strategies and a coarse-coding technique for overcoming this limitation and increasing the input field to that required by practical object recognition problems.
The small world of human language.
Ferrer I Cancho, R.; Solé, R. V.
2001-01-01
Words in human language interact in sentences in non-random ways, and allow humans to construct an astronomic variety of sentences from a limited number of discrete units. This construction process is extremely fast and robust. The co-occurrence of words in sentences reflects language organization in a subtle manner that can be described in terms of a graph of word interactions. Here, we show that such graphs display two important features recently found in a disparate number of complex systems. (i) The so called small-world effect. In particular, the average distance between two words, d (i.e. the average minimum number of links to be crossed from an arbitrary word to another), is shown to be d approximately equal to 2-3, even though the human brain can store many thousands. (ii) A scale-free distribution of degrees. The known pronounced effects of disconnecting the most connected vertices in such networks can be identified in some language disorders. These observations indicate some unexpected features of language organization that might reflect the evolutionary and social history of lexicons and the origins of their flexibility and combinatorial nature. PMID:11674874
Adaptive reorganization of 2D molecular nanoporous network induced by coadsorbed guest molecule.
Zheng, Qing-Na; Wang, Lei; Zhong, Yu-Wu; Liu, Xuan-He; Chen, Ting; Yan, Hui-Juan; Wang, Dong; Yao, Jian-Nian; Wan, Li-Jun
2014-03-25
The ordered array of nanovoids in nanoporous networks, such as honeycomb, Kagome, and square, provides a molecular template for the accommodation of "guest molecules". Compared with the commonly studied guest molecules featuring high symmetry evenly incorporated into the template, guest molecules featuring lower symmetry are rare to report. Herein, we report the formation of a distinct patterned superlattice of guest molecules by selective trapping of guest molecules into the honeycomb network of trimesic acid (TMA). Two distinct surface patterns have been achieved by the guest inclusion induced adaptive reconstruction of a 2D molecular nanoporous network. The honeycomb networks can synergetically tune the arrangement upon inclusion of the guest molecules with different core size but similar peripherals groups, resulting in a trihexagonal Kagome or triangular patterns.
Simulation and analysis of solute transport in 2D fracture/pipe networks: the SOLFRAC program.
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 (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 performed
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.
The Academic Life: Small Worlds, Different Worlds
ERIC Educational Resources Information Center
Locke, William
2010-01-01
"The Academic Life: Small Worlds, Different Worlds" represented an impressive investigation of the largest and most complex national academic community in the world, which seriously attempted a detailed representation of the variations in its form. Its ethnographic orientation to understanding the internal academic life through exploratory…
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.
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.
NASA Astrophysics Data System (ADS)
Mendoza-Torres, F.; Diaz-Viera, M. A.
2015-12-01
In many natural fractured porous media, such as aquifers, soils, oil and geothermal reservoirs, fractures play a crucial role in their flow and transport properties. An approach that has recently gained popularity for modeling fracture systems is the Discrete Fracture Network (DFN) model. This approach consists in applying a stochastic boolean simulation method, also known as object simulation method, where fractures are represented as simplified geometric objects (line segments in 2D and polygons in 3D). One of the shortcomings of this approach is that it usually does not consider the dependency relationships that may exist between the geometric properties of fractures (direction, length, aperture, etc), that is, each property is simulated independently. In this work a method for modeling such dependencies by copula theory is introduced. In particular, a nonparametric model using Bernstein copulas for direction-length fracture dependency in 2D is presented. The application of this method is illustrated in a case study for a fractured rock sample from a carbonate reservoir outcrop.
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.
Hierarchical, 4-connected Small-World Graph
NASA Astrophysics Data System (ADS)
Goncalves, Bruno; Boettcher, Stefan
2008-03-01
A new sequences of graphs are introduced that mimic small-world properties. The graphs are recursively constructed but retain a fixed, regular degree. They consist of a one-dimensional lattice backbone overlayed by a hierarchical sequence of long-distance links in a pattern reminiscent of the tower-of-hanoi sequence. These 4-regular graphs are non-planar, have a diameter growing as 2^√2N^2 (or as [2N]^α with α˜√2N^2/22N^2), and a nontrivial phase transition Tc>0, for the Ising ferromagnet. These results suggest that these graphs are similar to small-world graphs with mean-field-like properties.
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
Inversion of 2-D DC resistivity data using rapid optimization and minimal complexity neural network
NASA Astrophysics Data System (ADS)
Singh, U. K.; Tiwari, R. K.; Singh, S. B.
2010-02-01
The backpropagation (BP) artificial neural network (ANN) technique of optimization based on steepest descent algorithm is known to be inept for its poor performance and does not ensure global convergence. Nonlinear and complex DC resistivity data require efficient ANN model and more intensive optimization procedures for better results and interpretations. Improvements in the computational ANN modeling process are described with the goals of enhancing the optimization process and reducing ANN model complexity. Well-established optimization methods, such as Radial basis algorithm (RBA) and Levenberg-Marquardt algorithms (LMA) have frequently been used to deal with complexity and nonlinearity in such complex geophysical records. We examined here the efficiency of trained LMA and RB networks by using 2-D synthetic resistivity data and then finally applied to the actual field vertical electrical resistivity sounding (VES) data collected from the Puga Valley, Jammu and Kashmir, India. The resulting ANN reconstruction resistivity results are compared with the result of existing inversion approaches, which are in good agreement. The depths and resistivity structures obtained by the ANN methods also correlate well with the known drilling results and geologic boundaries. The application of the above ANN algorithms proves to be robust and could be used for fast estimation of resistive structures for other complex earth model also.
Dispersive dielectric and conductive effects in 2D resistor--capacitor networks
Hamou, R F F; Macdonald, Ross J.; Tuncer, Enis
2009-01-01
How to predict and better understand the effective properties of disordered material mixtures has been a long-standing problem in different research fields, especially in condensed matter physics. In order to address this subject and achieve a better understanding of the frequency-dependent properties of these systems, a large 2D L x L square structure of resistors and capacitors was used to calculate the immittance response of a network formed by random filling of binary conductor/insulator phases with 1000 O resistors and 10 nF capacitors. The effects of percolating clusters on the immittance response were studied statistically through the generation of 10 000 different random network samples at the percolation threshold. The scattering of the imaginary part of the immittance near the dc limit shows a clear separation between the responses of percolating and non-percolating samples, with the gap between their distributions dependent on both network size and applied frequency. These results could be used to monitor connectivity in composite materials. The effects of the content and structure of the percolating path on the nature of the observed dispersion were investigated, with special attention paid to the geometrical fractal concept of the backbone and its influence on the behavior of relaxation-time distributions. For three different resistor-capacitor proportions, the appropriateness of many fitting models was investigated for modeling and analyzing individual resistor-capacitor network dispersed frequency responses using complex-nonlinear-least-squares fitting. Several remarkable new features were identified, including a useful duality relationship and the need for composite fitting models rather than either a simple power law or a single Davidson-Cole one. Good fits of data for fully percolating random networks required two dispersive fitting models in parallel or series, with a cutoff at short times of the distribution of relaxation times of one of them
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
Enhanced brain small-worldness after sleep deprivation: a compensatory effect.
Liu, Huan; Li, Hong; Wang, Yulin; Lei, Xu
2014-10-01
Sleep deprivation has a variable impact on extrinsic activities during multiple cognitive tasks, especially on mood and emotion processing. There is also a trait-like individual vulnerability or compensatory effect in cognition. Previous studies have elucidated the altered functional connectivity after sleep deprivation. However, it remains unclear whether the small-world properties of resting-state network are sensitive to sleep deprivation. A small-world network is a type of graph that combines a high local connectivity as well as a few long-range connections, which ensures a higher information-processing efficiency at a low cost. The complex network of the brain can be described as a small-world network, in which a node is a brain region and an edge is present when there is a functional correlation between two nodes. Here, we investigated the topological properties of the human brain networks of 22 healthy subjects under sufficient sleep and sleep-deprived conditions. Specifically, small-worldness is utilized to quantify the small-world property, by comparing the clustering coefficient and path length of a given network to an equivalent random network with same degree distribution. After sufficient sleep, the brain networks showed the property of small-worldness. Compared with the resting state under sufficient sleep, the small-world property was significantly enhanced in the sleep deprivation condition, suggesting a possible compensatory adaptation of the human brain. Specifically, the altered measurements were correlated with the neuroticism of subjects, indicating that individuals with low-levels of neuroticism are more resilient to sleep deprivation.
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.
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
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.
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.
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.
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
Bayro-Corrochano, Eduardo; Vazquez-Santacruz, Eduardo; Moya-Sanchez, Eduardo; Castillo-Munis, Efrain
2016-10-01
This paper presents the design of radial basis function geometric bioinspired networks and their applications. Until now, the design of neural networks has been inspired by the biological models of neural networks but mostly using vector calculus and linear algebra. However, these designs have never shown the role of geometric computing. The question is how biological neural networks handle complex geometric representations involving Lie group operations like rotations. Even though the actual artificial neural networks are biologically inspired, they are just models which cannot reproduce a plausible biological process. Until now researchers have not shown how, using these models, one can incorporate them into the processing of geometric computing. Here, for the first time in the artificial neural networks domain, we address this issue by designing a kind of geometric RBF using the geometric algebra framework. As a result, using our artificial networks, we show how geometric computing can be carried out by the artificial neural networks. Such geometric neural networks have a great potential in robot vision. This is the most important aspect of this contribution to propose artificial geometric neural networks for challenging tasks in perception and action. In our experimental analysis, we show the applicability of our geometric designs, and present interesting experiments using 2-D data of real images and 3-D screw axis data. In general, our models should be used to process different types of inputs, such as visual cues, touch (texture, elasticity, temperature), taste, and sound. One important task of a perception-action system is to fuse a variety of cues coming from the environment and relate them via a sensor-motor manifold with motor modules to carry out diverse reasoned actions. PMID:26340785
Bayro-Corrochano, Eduardo; Vazquez-Santacruz, Eduardo; Moya-Sanchez, Eduardo; Castillo-Munis, Efrain
2016-10-01
This paper presents the design of radial basis function geometric bioinspired networks and their applications. Until now, the design of neural networks has been inspired by the biological models of neural networks but mostly using vector calculus and linear algebra. However, these designs have never shown the role of geometric computing. The question is how biological neural networks handle complex geometric representations involving Lie group operations like rotations. Even though the actual artificial neural networks are biologically inspired, they are just models which cannot reproduce a plausible biological process. Until now researchers have not shown how, using these models, one can incorporate them into the processing of geometric computing. Here, for the first time in the artificial neural networks domain, we address this issue by designing a kind of geometric RBF using the geometric algebra framework. As a result, using our artificial networks, we show how geometric computing can be carried out by the artificial neural networks. Such geometric neural networks have a great potential in robot vision. This is the most important aspect of this contribution to propose artificial geometric neural networks for challenging tasks in perception and action. In our experimental analysis, we show the applicability of our geometric designs, and present interesting experiments using 2-D data of real images and 3-D screw axis data. In general, our models should be used to process different types of inputs, such as visual cues, touch (texture, elasticity, temperature), taste, and sound. One important task of a perception-action system is to fuse a variety of cues coming from the environment and relate them via a sensor-motor manifold with motor modules to carry out diverse reasoned actions.
Small World Lives: Implications for the Public Library.
ERIC Educational Resources Information Center
Pendleton, Victoria EM; Chatman, Elfreda A.
1998-01-01
Addresses ways to reexamine the world of information from small world perspectives and suggests implications for public libraries. Highlights include a conceptual scheme to examine small world lives, including social norms, world views, social types, and information behavior; and ethnographic inquiries to illustrate how qualitative methodology can…
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.
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.
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.
NASA Astrophysics Data System (ADS)
Hamerly, Ryan; Inaba, Kensuke; Inagaki, Takahiro; Takesue, Hiroki; Yamamoto, Yoshihisa; Mabuchi, Hideo
2016-09-01
A network of optical parametric oscillators (OPOs) is used to simulate classical Ising and XY spin chains. The collective nonlinear dynamics of this network, driven by quantum noise rather than thermal fluctuations, seeks out the Ising/XY ground state as the system transitions from below to above the lasing threshold. We study the behavior of this “Ising machine” for three canonical problems: a 1D ferromagnetic spin chain, a 2D square lattice and problems where next-nearest-neighbor couplings give rise to frustration. If the pump turn-on time is finite, topological defects form (domain walls for the Ising model, winding number and vortices for XY) and their density can be predicted from a numerical model involving a linear “growth stage” and a nonlinear “saturation stage”. These predictions are compared against recent data for a 10,000-spin 1D Ising machine.
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.
Tahara, Kazukuni; Okuhata, Satoshi; Adisoejoso, Jinne; Lei, Shengbin; Fujita, Takumi; De Feyter, Steven; Tobe, Yoshito
2009-12-01
A series of alkyl- and alkoxy-substituted rhombic-shaped bisDBA derivatives 1a-d, 2a, and 2b were synthesized for the purpose of the formation of porous networks at the 1,2,4-trichlorobenzene (TCB)/graphite interface. Depending on the alkyl-chain length and the solute concentration, bisDBAs exhibit five network structures, three porous structures (porous A, B, and C), and two nonporous structures (nonporous D and E), which are attributed to their rhombic core shape and the position of the substituents. BisDBAs 1a and 1b with the shorter alkyl chains favorably form a porous structure, whereas bisDBAs 1c and 1d with the longer alkyl chains are prone to form nonporous structures. However, upon dilution, nonporous structures are typically transformed into porous ones, a trend that can be understood by the effect of surface coverage, molecular density, and intermolecular interactions on the system's enthalpy. Furthermore, porous structures are stabilized by the coadsorption of solvent molecules. The most intriguing porous structure, the Kagome pattern, was formed for all compounds at least to some extent, and the size of its triangular and hexagonal pores could be tuned by the alkyl-chain length. The present study proves that the concentration control is a powerful and general tool for the construction of porous networks at the liquid-solid interface.
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
Probing Magnetism in 2D Molecular Networks after in Situ Metalation by Transition Metal Atoms.
Schouteden, K; Ivanova, Ts; Li, Z; Iancu, V; Janssens, E; Van Haesendonck, C
2015-03-19
Metalated molecules are the ideal building blocks for the bottom-up fabrication of, e.g., two-dimensional arrays of magnetic particles for spintronics applications. Compared to chemical synthesis, metalation after network formation by an atom beam can yield a higher degree of control and flexibility and allows for mixing of different types of magnetic atoms. We report on successful metalation of tetrapyridyl-porphyrins (TPyP) by Co and Cr atoms, as demonstrated by scanning tunneling microscopy experiments. For the metalation, large periodic networks formed by the TPyP molecules on a Ag(111) substrate are exposed in situ to an atom beam. Voltage-induced dehydrogenation experiments support the conclusion that the porphyrin macrocycle of the TPyP molecule incorporates one transition metal atom. The newly synthesized Co-TPyP and Cr-TPyP complexes exhibit striking differences in their electronic behavior, leading to a magnetic character for Cr-TPyP only as evidenced by Kondo resonance measurements.
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.
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
Nonequilibrium phase transition in directed small-world-Voronoi-Delaunay random lattices
NASA Astrophysics Data System (ADS)
Lima, F. W. S.
2016-01-01
On directed small-world-Voronoi-Delaunay random lattices in two dimensions with quenched connectivity disorder we study the critical properties of the dynamics evolution of public opinion in social influence networks using a simple spin-like model. The system is treated by applying Monte Carlo simulations. We show that directed links on these random lattices may lead to phase diagram with first- and second-order social phase transitions out of equilibrium.
Allain, Ariane; Chauvot de Beauchêne, Isaure; Langenfeld, Florent; Guarracino, Yann; Laine, Elodie; Tchertanov, Luba
2014-01-01
Allostery is a universal phenomenon that couples the information induced by a local perturbation (effector) in a protein to spatially distant regulated sites. Such an event can be described in terms of a large scale transmission of information (communication) through a dynamic coupling between structurally rigid (minimally frustrated) and plastic (locally frustrated) clusters of residues. To elaborate a rational description of allosteric coupling, we propose an original approach - MOdular NETwork Analysis (MONETA) - based on the analysis of inter-residue dynamical correlations to localize the propagation of both structural and dynamical effects of a perturbation throughout a protein structure. MONETA uses inter-residue cross-correlations and commute times computed from molecular dynamics simulations and a topological description of a protein to build a modular network representation composed of clusters of residues (dynamic segments) linked together by chains of residues (communication pathways). MONETA provides a brand new direct and simple visualization of protein allosteric communication. A GEPHI module implemented in the MONETA package allows the generation of 2D graphs of the communication network. An interactive PyMOL plugin permits drawing of the communication pathways between chosen protein fragments or residues on a 3D representation. MONETA is a powerful tool for on-the-fly display of communication networks in proteins. We applied MONETA for the analysis of communication pathways (i) between the main regulatory fragments of receptors tyrosine kinases (RTKs), KIT and CSF-1R, in the native and mutated states and (ii) in proteins STAT5 (STAT5a and STAT5b) in the phosphorylated and the unphosphorylated forms. The description of the physical support for allosteric coupling by MONETA allowed a comparison of the mechanisms of (a) constitutive activation induced by equivalent mutations in two RTKs and (b) allosteric regulation in the activated and non
Piot, Luc; Silly, Fabien; Tortech, Ludovic; Nicolas, Yohann; Blanchard, Philippe; Roncali, Jean; Fichou, Denis
2009-09-16
We show by means of STM that C(60) molecules can be trapped into specific sites of a 2D double-cavity open network, thus forming long-range alignments of single molecules. Since only one of the two cavities has the right size to host C(60), the smallest cavity remains empty and is thus available to trap additional species of smaller size. This novel 2D supramolecular network opens new perspectives in the design of multicomponent guest-host architectures with electronic functionalities. PMID:19462948
NASA Astrophysics Data System (ADS)
Mirabella, S.; Oliveri, I. P.; Ruffino, F.; Maccarrone, G.; Di Bella, S.
2016-10-01
A marked chemiresistive behavior is revealed in a nanostructured material obtained by spin-coating a solution of a bis(salycilaldiminato)Zn(II) Schiff-base (ZnSB) complex. The resulting submicron 2D network exhibits reversible changes in absorbance and resistance under the cycles of absorption and desorption of a volatile amine. These results are explained in terms of a Lewis donor-acceptor interaction between the ZnSB (acceptor) and the chemisorbed amine (donor). The 2D network of ZnSB was employed as a sensing element to fabricate a low-cost device for the volatile amines detection, showing promising results for food spoilage detection.
Walking and Talking Geography: A Small-World Approach
ERIC Educational Resources Information Center
Fertig, Gary; Silverman, Rick
2007-01-01
When teaching geography to students in the primary grades, teachers should provide firsthand experiences that young children need to make meaningful sense of their world. David Sobel, author of "Mapmaking with Children: Sense of Place Education for the Elementary Years," suggests that teachers in the early grades adopt a small-world approach to…
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.
Liu, Yen-Hsiang; Lee, Szu-Hsuan; Chiang, Jung-Chun; Chen, Po-Chen; Chien, Po-Hsiu; Yang, Chen-I
2013-12-28
The synthesis of two homochiral l-tartrate-copper(II) coordination polymers, [Cu2(C4H4O6)2(H2O)2·xH2O]n (1), and [Cu(C4H4O6)]n (2), under hydrothermal conditions, is reported. Compound 1 adopts a 2D layered network structure with a space group of P21, while compound 2 features a 3D network structure with a space group P21212. Interestingly, the 2D layered structure of compound 1 can undergo a crystal-to-crystal network reassembly, with the formation of the 3D network structure of compound 2 under dehydration conditions. Variable temperature and field magnetic studies reveal the existence of a distinct ferromagnetic interaction between Cu(2+) ions as the result of distinct syn-anti carboxylate bridging coordination modes.
NASA Astrophysics Data System (ADS)
Pichierri, Fabio
2016-08-01
Using computational quantum chemistry methods we design novel 2D and 3D soft materials made of cucurbituril macrocycles covalently connected with each other via rigid linkers. Such covalent cucurbituril networks might be useful for the capture of radioactive Cs-137 (present as Cs+) in the contaminated environment.
NASA Astrophysics Data System (ADS)
Gvozdik, L.; Polak, M.; Zaruba, J.; Vanecek, M.
2010-12-01
A geological environment labeled as a Granite massif represents in terms of groundwater flow and transport a distinct hydrogeological environment from that of sedimentary basins, the characterisation of which is generally more complex and uncertain. Massifs are composed of hard crystalline rocks with the very low effective porosity. Due to their rheological properties such rocks are predisposed to brittle deformation resulting from changes in stress conditions. Our specific research project (Research on the influence of intergrangular porosity on deep geological disposal: geological formations, methodology and the development of measurement apparatus) is focussed on the problem of permeable zones within apparently undisturbed granitic rock matrix. The project including the both laboratory and in-situ tracer tests study migration along and through mineral grains in fresh and altered granite. The objective of the project is to assess whether intergranular porosity is a general characteristic of the granitic rock matrix or subject to significant evolution resulting from geochemical and/or hydrogeochemical processes, geotechnical and/or mechanical processes. Moreover, the research is focussed on evaluating methods quantifying intergranular porosity by both physical testing and mathematical modelling using verified standard hydrological software tools. Groundwater flow in microfractures and intergranular pores in granite rock matrix were simulated in three standard hydrogeological modeling programs with completely different conceptual approaches: MODFLOW (Equivalent Continuum concept), FEFLOW (Discrete Fracture and Equivalent Continuum concepts) and NAPSAC (Discrete Fracture Network concept). Specialized random fracture generators were used for creation of several 2D and 3D models in each of the chosen program. Percolation characteristics of these models were tested and analyzed. Several scenarios of laboratory tests of the rock samples permeability made in triaxial
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
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.
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.
Covalent Titanium(IV)-Aryloxide Network Materials: 4,4‧-Biphenoxide 3D and Polyphenolic 2D Motifs
NASA Astrophysics Data System (ADS)
Tanski, Joseph M.; Lobkovsky, Emil B.; Wolczanski, Peter
2000-06-01
The three- and two-dimensional covalent metal-organic network (CMON) compounds {[Ti(μ1,6:η2,η1-4,4‧-OC12H8O)0.5(μ1,6:η2,η1-4,4‧-OC12H8O)(OiPr)(HOiPr)]2·THF}n (1) and {[Ti(μ1,3-1,3-OC6H4O)(μ-1,3-OC6H4OH)(1,3-OC6H4OH) (HOiPr)]2}n (2) were synthesized by treatment of Ti(OiPr)4 with 4,4‧-dihydroxybiphenyl in THF and resorcinol in CS2, respectively, at 100°C. Diffraction data was collected at the Cornell High Energy Synchrotron Source (CHESS) because of the small, weakly diffracting nature of the crystals. 1 (C26H31O5.5Ti, monoclinic, P21, a=10.137(2), b=15.988(3), c=15.745(3), β=107.76(3)°, Z=4, R=0.0858) and 2 (C21H22O7Ti, monoclinic, P21/c, a=11.955(2), b=16.275(3), c=11.028(2), β=113.25(3)°, Z=4, R=0.0550) are both based upon similar edge-sharing bioctahedral dititanium building blocks, (i.e., Ti2(μ-OAr)2). Six connections per dititanium unit constrain the structural motif of 1 to be base-centered. Four μ1,3-diphenoxides per dititanium core in 2 connect to provide a rectangular net, but the regiochemistry of resorcinol ultimately restricts its dimensionality. The structures suggest design elements based on the number and geometry of connecting organic linkages.
Roughness Scaling for the Edwards-Wilkinson Model on Small-World Substrates
NASA Astrophysics Data System (ADS)
Kozma, B.; Hastings, M. B.; Korniss, G.
2004-03-01
We studied the generalization of the Edwards-Wilkinson model to substrates with small-world topology(B. Kozma, M.B. Hastings, and G. Korniss, cond-mat/0309196 (2003).). We considered two implementations of this topology, the ``hard'' version of the network, where each site has exactly one random link of strength p, and the ``soft'' one, where each site on average has p random links of unit strength. Both versions are embedded in one dimension. The research is motivated in part by a recent general criterion for mean-field behavior(M.B. Hastings, Physical Review Letters 91), 098701 (2003). predicting the model to exhibit anomalous scaling on the soft network, and also by synchronization problems in scalable parallel computing(G. Korniss et al., Science 299), 677 (2003). We used impurity averaged perturbation technique to calculate the width in both the weak- and sparse-coupling limits, for the hard and soft network, respectively. The width remains finite in both cases in the infinite system-size limit, but scales differently as p tends to zero. We verified our analytic results by comparing them to those of exact numerical diagonalization.
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…
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
Excitation waves on a minimal small-world model
NASA Astrophysics Data System (ADS)
Isele, Thomas; Hartung, Benedikt; Hövel, Philipp; Schöll, Eckehard
2015-04-01
We examine traveling-wave solutions on a regular ring network with one additional long-range link that spans a distance d. The nodes obey the FitzHugh-Nagumo kinetics in the excitable regime. The additional shortcut induces a plethora of spatio-temporal behavior that is not present without it. We describe the underlying mechanisms for different types of patterns: propagation failure, period decreasing, bistability, shortcut blocking and period multiplication. For this purpose, we investigate the dependence on d, the network size, the coupling range in the original ring and the global coupling strength and present a phase diagram summarizing the different scenarios. Furthermore, we discuss the scaling behavior of the critical distance by analytical means and address the connection to spatially continuous excitable media.
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)
Wang, Xiaonan; Lu, Ying; Jiang, Minxi; Ouyang, Qi
2004-05-01
Trapping and untrapping of spiral tips in a two-dimensional homogeneous excitable medium with local small-world connections are studied by numerical simulation. In a homogeneous medium which can be simulated with a lattice of regular neighborhood connections, the spiral wave is in the meandering regime. When changing the topology of a small region from regular connections to small-world connections, the tip of the spiral waves is attracted by the small-world region, where the average path length declines with the introduction of long distant connections. The “trapped” phenomenon also occurs in regular lattices where the diffusion coefficient of the small region is increased. The above results can be explained by the eikonal equation, the Luther equation, and the relation between the core radius and the diffusion coefficient.
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).
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
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.
NASA Astrophysics Data System (ADS)
Jang, Hyun-Sook; Yu, Changqian; Hayes, Robert; Granick, Steve
2015-03-01
Polymer vesicles (``polymersomes'') are an intriguing class of soft materials, commonly used to encapsulate small molecules or particles. Here we reveal they can also effectively incorporate nanoparticles inside their polymer membrane, leading to novel ``2D nanocomposites.'' The embedded nanoparticles alter the capacity of the polymersomes to bend and to stretch upon external stimuli.
Hybrid graphs as a framework for the small-world effect
NASA Astrophysics Data System (ADS)
Lehmann, Katharina A.; Post, Hendrik D.; Kaufmann, Michael
2006-05-01
In this paper we formalize the small-world effect which describes the surprising fact that a hybrid graph composed of a local graph component and a very sparse random graph has a diameter of O(lnn) whereby the diameter of both components alone is much higher. We show that a large family of these hybrid graphs shows this effect and that this generalized family also includes classic small-world models proposed by various authors although not all of them are captured by the small-world definition given by Watts and Strogatz. Furthermore, we give a detailed upper bound of the hybrid’s graph diameter for different choices of the expected number of random edges by applying a new kind of proof pattern that is applicable to a large number of hybrid graphs. The focus in this paper is on presenting a flexible family of hybrid graphs showing the small-world effect that can be tuned closely to real-world systems.
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
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
Opinion evolution based on cellular automata rules in small world networks
NASA Astrophysics Data System (ADS)
Shi, Xiao-Ming; Shi, Lun; Zhang, Jie-Fang
2010-03-01
In this paper, we apply cellular automata rules, which can be given by a truth table, to human memory. We design each memory as a tracking survey mode that keeps the most recent three opinions. Each cellular automata rule, as a personal mechanism, gives the final ruling in one time period based on the data stored in one's memory. The key focus of the paper is to research the evolution of people's attitudes to the same question. Based on a great deal of empirical observations from computer simulations, all the rules can be classified into 20 groups. We highlight the fact that the phenomenon shown by some rules belonging to the same group will be altered within several steps by other rules in different groups. It is truly amazing that, compared with the last hundreds of presidential voting in America, the eras of important events in America's history coincide with the simulation results obtained by our model.
NASA Astrophysics Data System (ADS)
Liu, Guocheng; Chen, Yongqiang; Wang, Xiuli; Chen, Baokuan; Lin, Hongyan
2009-03-01
Three novel Cd(II) coordination polymers, namely, [Cd(Dpq)(1,8-NDC)(H 2O) 2][Cd(Dpq)(1,8-NDC)]·2H 2O ( 1), [Cd(Dpq)(1,4-NDC)(H 2O)] ( 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 2NDC), 1,4-naphthalene-dicarboxylic acid (1,4-H 2NDC), and 2,6-naphthalene-dicarboxylic acid (2,6-H 2NDC)]. 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 π- π 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 π- π 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.
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.
Lee, Eunjoo; Sung, Jungwoo; An, Taechang; Shin, Heungjoo; Nam, Hong Gil; Lim, Geunbae
2015-05-01
The application of nanomaterials for biosensors and fuel cells is becoming more common, but it requires an understanding of the relationship between the structure and electrochemical characteristics of the materials at the nanoscale. Herein, we report the development of scanning electrochemical microscopy-atomic force microscopy (SECM-AFM) nanoprobes for collecting spatially resolved data regarding the electrochemical activity of nanomaterials such as carbon nanotube (CNT) networks. The fabrication of the nanoprobe begins with the integration of a CNT-bundle wire into a conventional AFM probe followed by the deposition of an insulating layer and cutting of the probe end. In addition, a protrusive insulating tip is integrated at the end of the insulated CNT-bundle wire to maintain a constant distance between the nanoelectrode and the substrate; this yields an L-shaped nanoprobe. The resulting nanoprobes produced well-fitted maps of faradaic current data with less than 300 nm spatial resolution and topographical images of CNT networks owing to the small effective distance (of the order of tens of nanometers) between the electrode and the substrate. Electrochemical imaging using the L-shaped nanoprobe revealed that the electrochemical activity of the CNT network is not homogeneous and provided further understanding of the relationship between the topography and electrochemical characteristics of CNT networks.
Prado-Prado, Francisco; García-Mera, Xerardo; Escobar, Manuel; Sobarzo-Sánchez, Eduardo; Yañez, Matilde; Riera-Fernandez, Pablo; González-Díaz, Humberto
2011-12-01
There are many pairs of possible Drug-Proteins Interactions that may take place or not (DPIs/nDPIs) between drugs with high affinity/non-affinity for different proteins. This fact makes expensive in terms of time and resources, for instance, the determination of all possible ligands-protein interactions for a single drug. In this sense, we can use Quantitative Structure-Activity Relationships (QSAR) models to carry out rational DPIs prediction. Unfortunately, almost all QSAR models predict activity against only one target. To solve this problem we can develop multi-target QSAR (mt-QSAR) models. In this work, we introduce the technique 2D MI-DRAGON a new predictor for DPIs based on two different well-known software. We use the software MARCH-INSIDE (MI) to calculate 3D structural parameters for targets and the software DRAGON was used to calculated 2D molecular descriptors all drugs showing known DPIs present in the Drug Bank (US FDA benchmark dataset). Both classes of parameters were used as input of different Artificial Neural Network (ANN) algorithms to seek an accurate non-linear mt-QSAR predictor. The best ANN model found is a Multi-Layer Perceptron (MLP) with profile MLP 21:21-31-1:1. This MLP classifies correctly 303 out of 339 DPIs (Sensitivity = 89.38%) and 480 out of 510 nDPIs (Specificity = 94.12%), corresponding to training Accuracy = 92.23%. The validation of the model was carried out by means of external predicting series with Sensitivity = 92.18% (625/678 DPIs; Specificity = 90.12% (730/780 nDPIs) and Accuracy = 91.06%. 2D MI-DRAGON offers a good opportunity for fast-track calculation of all possible DPIs of one drug enabling us to re-construct large drug-target or DPIs Complex Networks (CNs). For instance, we reconstructed the CN of the US FDA benchmark dataset with 855 nodes 519 drugs+336 targets). We predicted CN with similar topology (observed and predicted values of average distance are equal to 6.7 vs. 6.6). These CNs can be used to explore
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)
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.
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.
Network models for 2D disordered superconductors
NASA Astrophysics Data System (ADS)
Kagalovsky, Victor; Horovitz, Baruch; Avishai, Yshai
2004-04-01
We study new random matrix symmetry classes which arise in models of non-interacting quasi-particles in disordered superconductors. Within the Altland-Zirnbauer classification scheme these are class C (with time-reversal symmetry broken and spin-rotaion invariance intact), and class D where both symmetries are broken. Preliminary studies of the two remaining symmetry classes CI and DIII are briefly mentioned. New results are presented pertaining to the 3d realization of class C, which, physically, corresponds to a layered superconductor.
Baiz, Carlos R.; Schach, Denise; Tokmakoff, Andrei
2014-01-01
We describe a microscope for measuring two-dimensional infrared (2D IR) spectra of heterogeneous samples with μm-scale spatial resolution, sub-picosecond time resolution, and the molecular structure information of 2D IR, enabling the measurement of vibrational dynamics through correlations in frequency, time, and space. The setup is based on a fully collinear “one beam” geometry in which all pulses propagate along the same optics. Polarization, chopping, and phase cycling are used to isolate the 2D IR signals of interest. In addition, we demonstrate the use of vibrational lifetime as a contrast agent for imaging microscopic variations in molecular environments. PMID:25089490
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.
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.
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
DYNA2D96. Explicit 2-D Hydrodynamic FEM Program
Whirley, R.G.
1992-04-01
DYNA2D is a vectorized, explicit, two-dimensional, axisymmetric and plane strain finite element program for analyzing the large deformation dynamic and hydrodynamic response of inelastic solids. DYNA2D contains 13 material models and 9 equations of state (EOS) to cover a wide range of material behavior. The material models implemented in all machine versions are: elastic, orthotropic elastic, kinematic/isotropic elastic plasticity, thermoelastoplastic, soil and crushable foam, linear viscoelastic, rubber, high explosive burn, isotropic elastic-plastic, temperature-dependent elastic-plastic. The isotropic and temperature-dependent elastic-plastic models determine only the deviatoric stresses. Pressure is determined by one of 9 equations of state including linear polynomial, JWL high explosive, Sack Tuesday high explosive, Gruneisen, ratio of polynomials, linear polynomial with energy deposition, ignition and growth of reaction in HE, tabulated compaction, and tabulated.
2-D or not 2-D, that is the question: A Northern California test
Mayeda, K; Malagnini, L; Phillips, W S; Walter, W R; Dreger, D
2005-06-06
Reliable estimates of the seismic source spectrum are necessary for accurate magnitude, yield, and energy estimation. In particular, how seismic radiated energy scales with increasing earthquake size has been the focus of recent debate within the community and has direct implications on earthquake source physics studies as well as hazard mitigation. The 1-D coda methodology of Mayeda et al. has provided the lowest variance estimate of the source spectrum when compared against traditional approaches that use direct S-waves, thus making it ideal for networks that have sparse station distribution. The 1-D coda methodology has been mostly confined to regions of approximately uniform complexity. For larger, more geophysically complicated regions, 2-D path corrections may be required. The complicated tectonics of the northern California region coupled with high quality broadband seismic data provides for an ideal ''apples-to-apples'' test of 1-D and 2-D path assumptions on direct waves and their coda. Using the same station and event distribution, we compared 1-D and 2-D path corrections and observed the following results: (1) 1-D coda results reduced the amplitude variance relative to direct S-waves by roughly a factor of 8 (800%); (2) Applying a 2-D correction to the coda resulted in up to 40% variance reduction from the 1-D coda results; (3) 2-D direct S-wave results, though better than 1-D direct waves, were significantly worse than the 1-D coda. We found that coda-based moment-rate source spectra derived from the 2-D approach were essentially identical to those from the 1-D approach for frequencies less than {approx}0.7-Hz, however for the high frequencies (0.7{le} f {le} 8.0-Hz), the 2-D approach resulted in inter-station scatter that was generally 10-30% smaller. For complex regions where data are plentiful, a 2-D approach can significantly improve upon the simple 1-D assumption. In regions where only 1-D coda correction is available it is still preferable over 2
2001-01-31
This software reduces the data from two-dimensional kSA MOS program, k-Space Associates, Ann Arbor, MI. Initial MOS data is recorded without headers in 38 columns, with one row of data per acquisition per lase beam tracked. The final MOSS 2d data file is reduced, graphed, and saved in a tab-delimited column format with headers that can be plotted in any graphing software.
Competing coexisting phases in 2D water
Zanotti, Jean-Marc; Judeinstein, Patrick; Dalla-Bernardina, Simona; Creff, Gaëlle; Brubach, Jean-Blaise; Roy, Pascale; Bonetti, Marco; Ollivier, Jacques; Sakellariou, Dimitrios; Bellissent-Funel, Marie-Claire
2016-01-01
The properties of bulk water come from a delicate balance of interactions on length scales encompassing several orders of magnitudes: i) the Hydrogen Bond (HBond) at the molecular scale and ii) the extension of this HBond network up to the macroscopic level. Here, we address the physics of water when the three dimensional extension of the HBond network is frustrated, so that the water molecules are forced to organize in only two dimensions. We account for the large scale fluctuating HBond network by an analytical mean-field percolation model. This approach provides a coherent interpretation of the different events experimentally (calorimetry, neutron, NMR, near and far infra-red spectroscopies) detected in interfacial water at 160, 220 and 250 K. Starting from an amorphous state of water at low temperature, these transitions are respectively interpreted as the onset of creation of transient low density patches of 4-HBonded molecules at 160 K, the percolation of these domains at 220 K and finally the total invasion of the surface by them at 250 K. The source of this surprising behaviour in 2D is the frustration of the natural bulk tetrahedral local geometry and the underlying very significant increase in entropy of the interfacial water molecules. PMID:27185018
Competing coexisting phases in 2D water
NASA Astrophysics Data System (ADS)
Zanotti, Jean-Marc; Judeinstein, Patrick; Dalla-Bernardina, Simona; Creff, Gaëlle; Brubach, Jean-Blaise; Roy, Pascale; Bonetti, Marco; Ollivier, Jacques; Sakellariou, Dimitrios; Bellissent-Funel, Marie-Claire
2016-05-01
The properties of bulk water come from a delicate balance of interactions on length scales encompassing several orders of magnitudes: i) the Hydrogen Bond (HBond) at the molecular scale and ii) the extension of this HBond network up to the macroscopic level. Here, we address the physics of water when the three dimensional extension of the HBond network is frustrated, so that the water molecules are forced to organize in only two dimensions. We account for the large scale fluctuating HBond network by an analytical mean-field percolation model. This approach provides a coherent interpretation of the different events experimentally (calorimetry, neutron, NMR, near and far infra-red spectroscopies) detected in interfacial water at 160, 220 and 250 K. Starting from an amorphous state of water at low temperature, these transitions are respectively interpreted as the onset of creation of transient low density patches of 4-HBonded molecules at 160 K, the percolation of these domains at 220 K and finally the total invasion of the surface by them at 250 K. The source of this surprising behaviour in 2D is the frustration of the natural bulk tetrahedral local geometry and the underlying very significant increase in entropy of the interfacial water molecules.
Georgi, Howard; Kats, Yevgeny
2008-09-26
We discuss what can be learned about unparticle physics by studying simple quantum field theories in one space and one time dimension. We argue that the exactly soluble 2D theory of a massless fermion coupled to a massive vector boson, the Sommerfield model, is an interesting analog of a Banks-Zaks model, approaching a free theory at high energies and a scale-invariant theory with nontrivial anomalous dimensions at low energies. We construct a toy standard model coupling to the fermions in the Sommerfield model and study how the transition from unparticle behavior at low energies to free particle behavior at high energies manifests itself in interactions with the toy standard model particles.
Parademo: e-Democracy Based on a Delegated Expert Selection Process in a Small-World Network
NASA Astrophysics Data System (ADS)
Siebes, Ronny
Many countries have a representative democracy where their governments consist of a relatively small group of politicians that represent the values and beliefs of the majority of the voters. Unfortunately, many citizens are un- satisfied with their rather limited influence on politics especially regarding governments on national level or even higher like the EU or the UN. On the other side, referenda or direct democracies seem to be a too risky way of letting un- knowledgeable or uninterested individuals decide over complex issues. We mainly have these extreme opposites in our democracies due to the limitations of our manually maintained ballot system. Initiatives like Vivarto propose an alternative, called 'Delegated voting' where parts of a vote can be delegated to people with more knowledge on a certain topic. This leads to a convenient position in the middle between both mentioned extremes. We want to use the vast amount of expertise of many online citizens in our societies in selecting the right politicians and solutions. In this paper we propose the design of system called Parademo, that enables a fine-grained e-democracy. Next to this we briefly describe how we can achieve more transparency and third-party functionality by allowing listeners to subscribe to specific information-streams within communities that are formalized in a Semantic-Web language.
Label-based routing for a family of small-world Farey graphs
Zhai, Yinhu; Wang, Yinhe
2016-01-01
We introduce an informative labelling method for vertices in a family of Farey graphs, and deduce a routing algorithm on all the shortest paths between any two vertices in Farey graphs. The label of a vertex is composed of the precise locating position in graphs and the exact time linking to graphs. All the shortest paths routing between any pair of vertices, which number is exactly the product of two Fibonacci numbers, are determined only by their labels, and the time complexity of the algorithm is O(n). It is the first algorithm to figure out all the shortest paths between any pair of vertices in a kind of deterministic graphs. For Farey networks, the existence of an efficient routing protocol is of interest to design practical communication algorithms in relation to dynamical processes (including synchronization and structural controllability) and also to understand the underlying mechanisms that have shaped their particular structure. PMID:27167605
Label-based routing for a family of small-world Farey graphs
NASA Astrophysics Data System (ADS)
Zhai, Yinhu; Wang, Yinhe
2016-05-01
We introduce an informative labelling method for vertices in a family of Farey graphs, and deduce a routing algorithm on all the shortest paths between any two vertices in Farey graphs. The label of a vertex is composed of the precise locating position in graphs and the exact time linking to graphs. All the shortest paths routing between any pair of vertices, which number is exactly the product of two Fibonacci numbers, are determined only by their labels, and the time complexity of the algorithm is O(n). It is the first algorithm to figure out all the shortest paths between any pair of vertices in a kind of deterministic graphs. For Farey networks, the existence of an efficient routing protocol is of interest to design practical communication algorithms in relation to dynamical processes (including synchronization and structural controllability) and also to understand the underlying mechanisms that have shaped their particular structure.
Label-based routing for a family of small-world Farey graphs.
Zhai, Yinhu; Wang, Yinhe
2016-01-01
We introduce an informative labelling method for vertices in a family of Farey graphs, and deduce a routing algorithm on all the shortest paths between any two vertices in Farey graphs. The label of a vertex is composed of the precise locating position in graphs and the exact time linking to graphs. All the shortest paths routing between any pair of vertices, which number is exactly the product of two Fibonacci numbers, are determined only by their labels, and the time complexity of the algorithm is O(n). It is the first algorithm to figure out all the shortest paths between any pair of vertices in a kind of deterministic graphs. For Farey networks, the existence of an efficient routing protocol is of interest to design practical communication algorithms in relation to dynamical processes (including synchronization and structural controllability) and also to understand the underlying mechanisms that have shaped their particular structure. PMID:27167605
Label-based routing for a family of small-world Farey graphs.
Zhai, Yinhu; Wang, Yinhe
2016-01-01
We introduce an informative labelling method for vertices in a family of Farey graphs, and deduce a routing algorithm on all the shortest paths between any two vertices in Farey graphs. The label of a vertex is composed of the precise locating position in graphs and the exact time linking to graphs. All the shortest paths routing between any pair of vertices, which number is exactly the product of two Fibonacci numbers, are determined only by their labels, and the time complexity of the algorithm is O(n). It is the first algorithm to figure out all the shortest paths between any pair of vertices in a kind of deterministic graphs. For Farey networks, the existence of an efficient routing protocol is of interest to design practical communication algorithms in relation to dynamical processes (including synchronization and structural controllability) and also to understand the underlying mechanisms that have shaped their particular structure.
Cappon, Giacomo; Pedersen, Morten Gram
2016-05-01
Many multicellular systems consist of coupled cells that work as a syncytium. The pancreatic islet of Langerhans is a well-studied example of such a microorgan. The islets are responsible for secretion of glucose-regulating hormones, mainly glucagon and insulin, which are released in distinct pulses. In order to observe pulsatile insulin secretion from the β-cells within the islets, the cellular responses must be synchronized. It is now well established that gap junctions provide the electrical nearest-neighbor coupling that allows excitation waves to spread across islets to synchronize the β-cell population. Surprisingly, functional coupling analysis of calcium responses in β-cells shows small-world properties, i.e., a high degree of local coupling with a few long-range "short-cut" connections that reduce the average path-length greatly. Here, we investigate how such long-range functional coupling can appear as a result of heterogeneity, nearest-neighbor coupling, and wave propagation. Heterogeneity is also able to explain a set of experimentally observed synchronization and wave properties without introducing all-or-none cell coupling and percolation theory. Our theoretical results highlight how local biological coupling can give rise to functional small-world properties via heterogeneity and wave propagation. PMID:27249943
NASA Astrophysics Data System (ADS)
Cappon, Giacomo; Pedersen, Morten Gram
2016-05-01
Many multicellular systems consist of coupled cells that work as a syncytium. The pancreatic islet of Langerhans is a well-studied example of such a microorgan. The islets are responsible for secretion of glucose-regulating hormones, mainly glucagon and insulin, which are released in distinct pulses. In order to observe pulsatile insulin secretion from the β-cells within the islets, the cellular responses must be synchronized. It is now well established that gap junctions provide the electrical nearest-neighbor coupling that allows excitation waves to spread across islets to synchronize the β-cell population. Surprisingly, functional coupling analysis of calcium responses in β-cells shows small-world properties, i.e., a high degree of local coupling with a few long-range "short-cut" connections that reduce the average path-length greatly. Here, we investigate how such long-range functional coupling can appear as a result of heterogeneity, nearest-neighbor coupling, and wave propagation. Heterogeneity is also able to explain a set of experimentally observed synchronization and wave properties without introducing all-or-none cell coupling and percolation theory. Our theoretical results highlight how local biological coupling can give rise to functional small-world properties via heterogeneity and wave propagation.
Chen, Jun; Zhang, Qing; Liu, Zhi-Fa; Wang, Shuai-Hua; Xiao, Yu; Li, Rong; Xu, Jian-Gang; Zhao, Ya-Ping; Zheng, Fa-Kun; Guo, Guo-Cong
2015-06-01
Two new lead(II) coordination polymers, [Pb(NO3)(tzib)]n (1) and [Pb(tzib)2]n (2), were successfully synthesized from the reaction of a rigid ligand 1-tetrazole-4-imidazole-benzene (Htzib) and lead(II) nitrate in different solvents. The obtained polymers have been characterized by single-crystal X-ray diffraction analyses, which show that both polymers feature 2D layer structures. The inorganic anion nitrate in 1 shows a μ2-κO3:κO3 bridging mode to connect adjacent lead ions into a zigzag chain, and then the organic ligands tzib(-) join the neighboring chains into a 2D layer by a μ3-κN1:κN2:κN6 connection mode. In 2, there are two different bridging modes of the tzib(-) ligand: μ3-κN1:κN2:κN6 and μ3-κN1:κN6 to coordinate the lead ions into a 2D layer structure. Interestingly, both polymers displayed broadband emissions covering the entire visible spectra, which could be tunable to near white-light emission by varying excitation wavelengths. PMID:25952460
Yang, Zhenzhong; Yang, Jihong; Liu, Wei; Wu, Leihong; Xing, Li; Wang, Yi; Fan, Xiaohui; Cheng, Yiyu
2013-01-01
Type 2 diabetes mellitus (T2D), affecting >90% of the diabetic patients, is one of the major threats to human health. A comprehensive understanding of the mechanisms of T2D at molecular level is essential to facilitate the related translational research. Here, we introduce a comprehensive and up-to-date knowledgebase for T2D, i.e. T2D@ZJU. T2D@ZJU contains three levels of heterogeneous connections associated with T2D, which is retrieved from pathway databases, protein-protein interaction databases and literature, respectively. In current release, T2D@ZJU contains 1078 T2D related entities such as proteins, protein complexes, drugs and others together with their corresponding relationships, which include 3069 manually curated connections, 14,893 protein-protein interactions and 26,716 relationships identified by text-mining technology. Moreover, T2D@ZJU provides a user-friendly web interface for users to browse and search data. A Cytoscape Web-based interactive network browser is available to visualize the corresponding network relationships between T2D-related entities. The functionality of T2D@ZJU is shown by means of several case studies. Database URL: http://tcm.zju.edu.cn/t2d.
ERIC Educational Resources Information Center
Crane, Willow Soltow
1987-01-01
Contains a set of learning activities which deal with the accelerated loss of the earth's tropical rain forests. Includes four lessons that take 15 minutes or less to teach, background information for the teacher, and a longer lesson which provides an in-depth look at the issues that affect this topic. (TW)
Perspectives for spintronics in 2D materials
NASA Astrophysics Data System (ADS)
Han, Wei
2016-03-01
The past decade has been especially creative for spintronics since the (re)discovery of various two dimensional (2D) materials. Due to the unusual physical characteristics, 2D materials have provided new platforms to probe the spin interaction with other degrees of freedom for electrons, as well as to be used for novel spintronics applications. This review briefly presents the most important recent and ongoing research for spintronics in 2D materials.
Quantitative 2D liquid-state NMR.
Giraudeau, Patrick
2014-06-01
Two-dimensional (2D) liquid-state NMR has a very high potential to simultaneously determine the absolute concentration of small molecules in complex mixtures, thanks to its capacity to separate overlapping resonances. However, it suffers from two main drawbacks that probably explain its relatively late development. First, the 2D NMR signal is strongly molecule-dependent and site-dependent; second, the long duration of 2D NMR experiments prevents its general use for high-throughput quantitative applications and affects its quantitative performance. Fortunately, the last 10 years has witnessed an increasing number of contributions where quantitative approaches based on 2D NMR were developed and applied to solve real analytical issues. This review aims at presenting these recent efforts to reach a high trueness and precision in quantitative measurements by 2D NMR. After highlighting the interest of 2D NMR for quantitative analysis, the different strategies to determine the absolute concentrations from 2D NMR spectra are described and illustrated by recent applications. The last part of the manuscript concerns the recent development of fast quantitative 2D NMR approaches, aiming at reducing the experiment duration while preserving - or even increasing - the analytical performance. We hope that this comprehensive review will help readers to apprehend the current landscape of quantitative 2D NMR, as well as the perspectives that may arise from it.
Staring 2-D hadamard transform spectral imager
Gentry, Stephen M.; Wehlburg, Christine M.; Wehlburg, Joseph C.; Smith, Mark W.; Smith, Jody L.
2006-02-07
A staring imaging system inputs a 2D spatial image containing multi-frequency spectral information. This image is encoded in one dimension of the image with a cyclic Hadamarid S-matrix. The resulting image is detecting with a spatial 2D detector; and a computer applies a Hadamard transform to recover the encoded image.
NASA Astrophysics Data System (ADS)
Liu, Shi Xin; Li, Jian Hui; Wang, You You; Wu, Xiang Xia; Huo, Jian Zhong; Ding, Bin; Wang, Xiu Guang; Zhu, Zhao Zhou; Xia, Jun
2015-05-01
Using the 4-substituted-1,2,4-triazole derivate ligand 4-p-tolyl-1,2,4-triazole (L), two novel luminescent Cadmium(II) frameworks, namely {[Cd(μ2-L)3]·(NO3)2·L}n (1) and [Cd1.5(μ2-L)(μ2-Br)2(μ3-Br)]n (2) have been isolated under hydrothermal conditions. The structural analysis reveals that 1 presents a one-dimensional (1D) chain structural motif containing novel infinite triple Cd-(trz)-Cd bridges (triply trz-bridged M-M species). While 2 presents a rare I2O0 type framework, in which the infinite 2D Cd-Br-Cd inorganic connectivity with a 4-connected Kagome topology can be observed. The FT-IR, PXRD and thermal stabilities of 1-2 have investigated. The solid-state photo-luminescent spectra of organic ligand L and 1-2 also have been measured indicating strong emission bands.
2D materials for nanophotonic devices
NASA Astrophysics Data System (ADS)
Xu, Renjing; Yang, Jiong; Zhang, Shuang; Pei, Jiajie; Lu, Yuerui
2015-12-01
Two-dimensional (2D) materials have become very important building blocks for electronic, photonic, and phononic devices. The 2D material family has four key members, including the metallic graphene, transition metal dichalcogenide (TMD) layered semiconductors, semiconducting black phosphorous, and the insulating h-BN. Owing to the strong quantum confinements and defect-free surfaces, these atomically thin layers have offered us perfect platforms to investigate the interactions among photons, electrons and phonons. The unique interactions in these 2D materials are very important for both scientific research and application engineering. In this talk, I would like to briefly summarize and highlight the key findings, opportunities and challenges in this field. Next, I will introduce/highlight our recent achievements. We demonstrated atomically thin micro-lens and gratings using 2D MoS2, which is the thinnest optical component around the world. These devices are based on our discovery that the elastic light-matter interactions in highindex 2D materials is very strong. Also, I would like to introduce a new two-dimensional material phosphorene. Phosphorene has strongly anisotropic optical response, which creates 1D excitons in a 2D system. The strong confinement in phosphorene also enables the ultra-high trion (charged exciton) binding energies, which have been successfully measured in our experiments. Finally, I will briefly talk about the potential applications of 2D materials in energy harvesting.
Internal Photoemission Spectroscopy of 2-D Materials
NASA Astrophysics Data System (ADS)
Nguyen, Nhan; Li, Mingda; Vishwanath, Suresh; Yan, Rusen; Xiao, Shudong; Xing, Huili; Cheng, Guangjun; Hight Walker, Angela; Zhang, Qin
Recent research has shown the great benefits of using 2-D materials in the tunnel field-effect transistor (TFET), which is considered a promising candidate for the beyond-CMOS technology. The on-state current of TFET can be enhanced by engineering the band alignment of different 2D-2D or 2D-3D heterostructures. Here we present the internal photoemission spectroscopy (IPE) approach to determine the band alignments of various 2-D materials, in particular SnSe2 and WSe2, which have been proposed for new TFET designs. The metal-oxide-2-D semiconductor test structures are fabricated and characterized by IPE, where the band offsets from the 2-D semiconductor to the oxide conduction band minimum are determined by the threshold of the cube root of IPE yields as a function of photon energy. In particular, we find that SnSe2 has a larger electron affinity than most semiconductors and can be combined with other semiconductors to form near broken-gap heterojunctions with low barrier heights which can produce a higher on-state current. The details of data analysis of IPE and the results from Raman spectroscopy and spectroscopic ellipsometry measurements will also be presented and discussed.
2D materials: to graphene and beyond.
Mas-Ballesté, Rubén; Gómez-Navarro, Cristina; Gómez-Herrero, Julio; Zamora, Félix
2011-01-01
This review is an attempt to illustrate the different alternatives in the field of 2D materials. Graphene seems to be just the tip of the iceberg and we show how the discovery of alternative 2D materials is starting to show the rest of this iceberg. The review comprises the current state-of-the-art of the vast literature in concepts and methods already known for isolation and characterization of graphene, and rationalizes the quite disperse literature in other 2D materials such as metal oxides, hydroxides and chalcogenides, and metal-organic frameworks.
2-d Finite Element Code Postprocessor
1996-07-15
ORION is an interactive program that serves as a postprocessor for the analysis programs NIKE2D, DYNA2D, TOPAZ2D, and CHEMICAL TOPAZ2D. ORION reads binary plot files generated by the two-dimensional finite element codes currently used by the Methods Development Group at LLNL. Contour and color fringe plots of a large number of quantities may be displayed on meshes consisting of triangular and quadrilateral elements. ORION can compute strain measures, interface pressures along slide lines, reaction forcesmore » along constrained boundaries, and momentum. ORION has been applied to study the response of two-dimensional solids and structures undergoing finite deformations under a wide variety of large deformation transient dynamic and static problems and heat transfer analyses.« less
Ginsparg, P.
1991-01-01
These are introductory lectures for a general audience that give an overview of the subject of matrix models and their application to random surfaces, 2d gravity, and string theory. They are intentionally 1.5 years out of date.
Ginsparg, P.
1991-12-31
These are introductory lectures for a general audience that give an overview of the subject of matrix models and their application to random surfaces, 2d gravity, and string theory. They are intentionally 1.5 years out of date.
Brittle damage models in DYNA2D
Faux, D.R.
1997-09-01
DYNA2D is an explicit Lagrangian finite element code used to model dynamic events where stress wave interactions influence the overall response of the system. DYNA2D is often used to model penetration problems involving ductile-to-ductile impacts; however, with the advent of the use of ceramics in the armor-anti-armor community and the need to model damage to laser optics components, good brittle damage models are now needed in DYNA2D. This report will detail the implementation of four brittle damage models in DYNA2D, three scalar damage models and one tensor damage model. These new brittle damage models are then used to predict experimental results from three distinctly different glass damage problems.
ERIC Educational Resources Information Center
Burnett, Gary; Jaeger, Paul T.
2008-01-01
Introduction: This paper attempts to build bridges between two sets of theoretical concepts related to information behaviour: the macro-level concepts of Jurgen Habermas related to lifeworlds and the micro-level concepts of Elfreda Chatman related to small worlds. Argument: Habermas and Chatman explored similar issues of information behaviour at…
Chemical Approaches to 2D Materials.
Samorì, Paolo; Palermo, Vincenzo; Feng, Xinliang
2016-08-01
Chemistry plays an ever-increasing role in the production, functionalization, processing and applications of graphene and other 2D materials. This special issue highlights a selection of enlightening chemical approaches to 2D materials, which nicely reflect the breadth of the field and convey the excitement of the individuals involved in it, who are trying to translate graphene and related materials from the laboratory into a real, high-impact technology. PMID:27478083
Chemical Approaches to 2D Materials.
Samorì, Paolo; Palermo, Vincenzo; Feng, Xinliang
2016-08-01
Chemistry plays an ever-increasing role in the production, functionalization, processing and applications of graphene and other 2D materials. This special issue highlights a selection of enlightening chemical approaches to 2D materials, which nicely reflect the breadth of the field and convey the excitement of the individuals involved in it, who are trying to translate graphene and related materials from the laboratory into a real, high-impact technology.
Yang, Li-Ming; Dornfeld, Matthew; Frauenheim, Thomas; Ganz, Eric
2015-10-21
We predict a highly stable and robust atomically thin gold monolayer with a hexagonal close packed lattice stabilized by metallic bonding with contributions from strong relativistic effects and aurophilic interactions. We have shown that the framework of the Au monolayer can survive 10 ps MD annealing simulations up to 1400 K. The framework is also able to survive large motions out of the plane. Due to the smaller number of bonds per atom in the 2D layer compared to the 3D bulk we observe significantly enhanced energy per bond (0.94 vs. 0.52 eV per bond). This is similar to the increase in bond strength going from 3D diamond to 2D graphene. It is a non-magnetic metal, and was found to be the global minima in the 2D space. Phonon dispersion calculations demonstrate high kinetic stability with no negative modes. This 2D gold monolayer corresponds to the top monolayer of the bulk Au(111) face-centered cubic lattice. The close-packed lattice maximizes the aurophilic interactions. We find that the electrons are completely delocalized in the plane and behave as 2D nearly free electron gas. We hope that the present work can inspire the experimental fabrication of novel free standing 2D metal systems.
2d index and surface operators
NASA Astrophysics Data System (ADS)
Gadde, Abhijit; Gukov, Sergei
2014-03-01
In this paper we compute the superconformal index of 2d (2, 2) supersymmetric gauge theories. The 2d superconformal index, a.k.a. flavored elliptic genus, is computed by a unitary matrix integral much like the matrix integral that computes the 4d superconformal index. We compute the 2d index explicitly for a number of examples. In the case of abelian gauge theories we see that the index is invariant under flop transition and under CY-LG correspondence. The index also provides a powerful check of the Seiberg-type duality for non-abelian gauge theories discovered by Hori and Tong. In the later half of the paper, we study half-BPS surface operators in = 2 super-conformal gauge theories. They are engineered by coupling the 2d (2, 2) supersymmetric gauge theory living on the support of the surface operator to the 4d = 2 theory, so that different realizations of the same surface operator with a given Levi type are related by a 2d analogue of the Seiberg duality. The index of this coupled system is computed by using the tools developed in the first half of the paper. The superconformal index in the presence of surface defect is expected to be invariant under generalized S-duality. We demonstrate that it is indeed the case. In doing so the Seiberg-type duality of the 2d theory plays an important role.
Orthotropic Piezoelectricity in 2D Nanocellulose
NASA Astrophysics Data System (ADS)
García, Y.; Ruiz-Blanco, Yasser B.; Marrero-Ponce, Yovani; Sotomayor-Torres, C. M.
2016-10-01
The control of electromechanical responses within bonding regions is essential to face frontier challenges in nanotechnologies, such as molecular electronics and biotechnology. Here, we present Iβ-nanocellulose as a potentially new orthotropic 2D piezoelectric crystal. The predicted in-layer piezoelectricity is originated on a sui-generis hydrogen bonds pattern. Upon this fact and by using a combination of ab-initio and ad-hoc models, we introduce a description of electrical profiles along chemical bonds. Such developments lead to obtain a rationale for modelling the extended piezoelectric effect originated within bond scales. The order of magnitude estimated for the 2D Iβ-nanocellulose piezoelectric response, ~pm V‑1, ranks this material at the level of currently used piezoelectric energy generators and new artificial 2D designs. Such finding would be crucial for developing alternative materials to drive emerging nanotechnologies.
Orthotropic Piezoelectricity in 2D Nanocellulose
García, Y.; Ruiz-Blanco, Yasser B.; Marrero-Ponce, Yovani; Sotomayor-Torres, C. M.
2016-01-01
The control of electromechanical responses within bonding regions is essential to face frontier challenges in nanotechnologies, such as molecular electronics and biotechnology. Here, we present Iβ-nanocellulose as a potentially new orthotropic 2D piezoelectric crystal. The predicted in-layer piezoelectricity is originated on a sui-generis hydrogen bonds pattern. Upon this fact and by using a combination of ab-initio and ad-hoc models, we introduce a description of electrical profiles along chemical bonds. Such developments lead to obtain a rationale for modelling the extended piezoelectric effect originated within bond scales. The order of magnitude estimated for the 2D Iβ-nanocellulose piezoelectric response, ~pm V−1, ranks this material at the level of currently used piezoelectric energy generators and new artificial 2D designs. Such finding would be crucial for developing alternative materials to drive emerging nanotechnologies. PMID:27708364
2D microwave imaging reflectometer electronics
Spear, A. G.; Domier, C. W. Hu, X.; Muscatello, C. M.; Ren, X.; Luhmann, N. C.; Tobias, B. J.
2014-11-15
A 2D microwave imaging reflectometer system has been developed to visualize electron density fluctuations on the DIII-D tokamak. Simultaneously illuminated at four probe frequencies, large aperture optics image reflections from four density-dependent cutoff surfaces in the plasma over an extended region of the DIII-D plasma. Localized density fluctuations in the vicinity of the plasma cutoff surfaces modulate the plasma reflections, yielding a 2D image of electron density fluctuations. Details are presented of the receiver down conversion electronics that generate the in-phase (I) and quadrature (Q) reflectometer signals from which 2D density fluctuation data are obtained. Also presented are details on the control system and backplane used to manage the electronics as well as an introduction to the computer based control program.
Optical modulators with 2D layered materials
NASA Astrophysics Data System (ADS)
Sun, Zhipei; Martinez, Amos; Wang, Feng
2016-04-01
Light modulation is an essential operation in photonics and optoelectronics. With existing and emerging technologies increasingly demanding compact, efficient, fast and broadband optical modulators, high-performance light modulation solutions are becoming indispensable. The recent realization that 2D layered materials could modulate light with superior performance has prompted intense research and significant advances, paving the way for realistic applications. In this Review, we cover the state of the art of optical modulators based on 2D materials, including graphene, transition metal dichalcogenides and black phosphorus. We discuss recent advances employing hybrid structures, such as 2D heterostructures, plasmonic structures, and silicon and fibre integrated structures. We also take a look at the future perspectives and discuss the potential of yet relatively unexplored mechanisms, such as magneto-optic and acousto-optic modulation.
Inkjet printing of 2D layered materials.
Li, Jiantong; Lemme, Max C; Östling, Mikael
2014-11-10
Inkjet printing of 2D layered materials, such as graphene and MoS2, has attracted great interests for emerging electronics. However, incompatible rheology, low concentration, severe aggregation and toxicity of solvents constitute critical challenges which hamper the manufacturing efficiency and product quality. Here, we introduce a simple and general technology concept (distillation-assisted solvent exchange) to efficiently overcome these challenges. By implementing the concept, we have demonstrated excellent jetting performance, ideal printing patterns and a variety of promising applications for inkjet printing of 2D layered materials. PMID:25169938
Inkjet printing of 2D layered materials.
Li, Jiantong; Lemme, Max C; Östling, Mikael
2014-11-10
Inkjet printing of 2D layered materials, such as graphene and MoS2, has attracted great interests for emerging electronics. However, incompatible rheology, low concentration, severe aggregation and toxicity of solvents constitute critical challenges which hamper the manufacturing efficiency and product quality. Here, we introduce a simple and general technology concept (distillation-assisted solvent exchange) to efficiently overcome these challenges. By implementing the concept, we have demonstrated excellent jetting performance, ideal printing patterns and a variety of promising applications for inkjet printing of 2D layered materials.
Caruso, Joseph P; Israel, Natalie; Rowland, Kimberly; Lovelace, Matthew J; Saunders, Mary Jane
2016-03-01
Course-based undergraduate research is known to improve science, technology, engineering, and mathematics student achievement. We tested "The Small World Initiative, a Citizen-Science Project to Crowdsource Novel Antibiotic Discovery" to see if it also improved student performance and the critical thinking of non-science majors in Introductory Biology at Florida Atlantic University (a large, public, minority-dominant institution) in academic year 2014-15. California Critical Thinking Skills Test pre- and posttests were offered to both Small World Initiative (SWI) and control lab students for formative amounts of extra credit. SWI lab students earned significantly higher lecture grades than control lab students, had significantly fewer lecture grades of D+ or lower, and had significantly higher critical thinking posttest total scores than control students. Lastly, more SWI students were engaged while taking critical thinking tests. These results support the hypothesis that utilizing independent course-based undergraduate science research improves student achievement even in nonscience students. PMID:27047613
Caruso, Joseph P; Israel, Natalie; Rowland, Kimberly; Lovelace, Matthew J; Saunders, Mary Jane
2016-03-01
Course-based undergraduate research is known to improve science, technology, engineering, and mathematics student achievement. We tested "The Small World Initiative, a Citizen-Science Project to Crowdsource Novel Antibiotic Discovery" to see if it also improved student performance and the critical thinking of non-science majors in Introductory Biology at Florida Atlantic University (a large, public, minority-dominant institution) in academic year 2014-15. California Critical Thinking Skills Test pre- and posttests were offered to both Small World Initiative (SWI) and control lab students for formative amounts of extra credit. SWI lab students earned significantly higher lecture grades than control lab students, had significantly fewer lecture grades of D+ or lower, and had significantly higher critical thinking posttest total scores than control students. Lastly, more SWI students were engaged while taking critical thinking tests. These results support the hypothesis that utilizing independent course-based undergraduate science research improves student achievement even in nonscience students.
Parallel stitching of 2D materials
Ling, Xi; Wu, Lijun; Lin, Yuxuan; Ma, Qiong; Wang, Ziqiang; Song, Yi; Yu, Lili; Huang, Shengxi; Fang, Wenjing; Zhang, Xu; et al
2016-01-27
Diverse parallel stitched 2D heterostructures, including metal–semiconductor, semiconductor–semiconductor, and insulator–semiconductor, are synthesized directly through selective “sowing” of aromatic molecules as the seeds in the chemical vapor deposition (CVD) method. Lastly, the methodology enables the large-scale fabrication of lateral heterostructures, which offers tremendous potential for its application in integrated circuits.
Parallel Stitching of 2D Materials.
Ling, Xi; Lin, Yuxuan; Ma, Qiong; Wang, Ziqiang; Song, Yi; Yu, Lili; Huang, Shengxi; Fang, Wenjing; Zhang, Xu; Hsu, Allen L; Bie, Yaqing; Lee, Yi-Hsien; Zhu, Yimei; Wu, Lijun; Li, Ju; Jarillo-Herrero, Pablo; Dresselhaus, Mildred; Palacios, Tomás; Kong, Jing
2016-03-23
Diverse parallel stitched 2D heterostructures, including metal-semiconductor, semiconductor-semiconductor, and insulator-semiconductor, are synthesized directly through selective "sowing" of aromatic molecules as the seeds in the chemical vapor deposition (CVD) method. The methodology enables the large-scale fabrication of lateral heterostructures, which offers tremendous potential for its application in integrated circuits.
Application of 2D Non-Graphene Materials and 2D Oxide Nanostructures for Biosensing Technology
Shavanova, Kateryna; Bakakina, Yulia; Burkova, Inna; Shtepliuk, Ivan; Viter, Roman; Ubelis, Arnolds; Beni, Valerio; Starodub, Nickolaj; Yakimova, Rositsa; Khranovskyy, Volodymyr
2016-01-01
The discovery of graphene and its unique properties has inspired researchers to try to invent other two-dimensional (2D) materials. After considerable research effort, a distinct “beyond graphene” domain has been established, comprising the library of non-graphene 2D materials. It is significant that some 2D non-graphene materials possess solid advantages over their predecessor, such as having a direct band gap, and therefore are highly promising for a number of applications. These applications are not limited to nano- and opto-electronics, but have a strong potential in biosensing technologies, as one example. However, since most of the 2D non-graphene materials have been newly discovered, most of the research efforts are concentrated on material synthesis and the investigation of the properties of the material. Applications of 2D non-graphene materials are still at the embryonic stage, and the integration of 2D non-graphene materials into devices is scarcely reported. However, in recent years, numerous reports have blossomed about 2D material-based biosensors, evidencing the growing potential of 2D non-graphene materials for biosensing applications. This review highlights the recent progress in research on the potential of using 2D non-graphene materials and similar oxide nanostructures for different types of biosensors (optical and electrochemical). A wide range of biological targets, such as glucose, dopamine, cortisol, DNA, IgG, bisphenol, ascorbic acid, cytochrome and estradiol, has been reported to be successfully detected by biosensors with transducers made of 2D non-graphene materials. PMID:26861346
Application of 2D Non-Graphene Materials and 2D Oxide Nanostructures for Biosensing Technology.
Shavanova, Kateryna; Bakakina, Yulia; Burkova, Inna; Shtepliuk, Ivan; Viter, Roman; Ubelis, Arnolds; Beni, Valerio; Starodub, Nickolaj; Yakimova, Rositsa; Khranovskyy, Volodymyr
2016-01-01
The discovery of graphene and its unique properties has inspired researchers to try to invent other two-dimensional (2D) materials. After considerable research effort, a distinct "beyond graphene" domain has been established, comprising the library of non-graphene 2D materials. It is significant that some 2D non-graphene materials possess solid advantages over their predecessor, such as having a direct band gap, and therefore are highly promising for a number of applications. These applications are not limited to nano- and opto-electronics, but have a strong potential in biosensing technologies, as one example. However, since most of the 2D non-graphene materials have been newly discovered, most of the research efforts are concentrated on material synthesis and the investigation of the properties of the material. Applications of 2D non-graphene materials are still at the embryonic stage, and the integration of 2D non-graphene materials into devices is scarcely reported. However, in recent years, numerous reports have blossomed about 2D material-based biosensors, evidencing the growing potential of 2D non-graphene materials for biosensing applications. This review highlights the recent progress in research on the potential of using 2D non-graphene materials and similar oxide nanostructures for different types of biosensors (optical and electrochemical). A wide range of biological targets, such as glucose, dopamine, cortisol, DNA, IgG, bisphenol, ascorbic acid, cytochrome and estradiol, has been reported to be successfully detected by biosensors with transducers made of 2D non-graphene materials.
Stochastic Inversion of 2D Magnetotelluric Data
Chen, Jinsong
2010-07-01
The algorithm is developed to invert 2D magnetotelluric (MT) data based on sharp boundary parametrization using a Bayesian framework. Within the algorithm, we consider the locations and the resistivity of regions formed by the interfaces are as unknowns. We use a parallel, adaptive finite-element algorithm to forward simulate frequency-domain MT responses of 2D conductivity structure. Those unknown parameters are spatially correlated and are described by a geostatistical model. The joint posterior probability distribution function is explored by Markov Chain Monte Carlo (MCMC) sampling methods. The developed stochastic model is effective for estimating the interface locations and resistivity. Most importantly, it provides details uncertainty information on each unknown parameter. Hardware requirements: PC, Supercomputer, Multi-platform, Workstation; Software requirements C and Fortan; Operation Systems/version is Linux/Unix or Windows
Explicit 2-D Hydrodynamic FEM Program
1996-08-07
DYNA2D* is a vectorized, explicit, two-dimensional, axisymmetric and plane strain finite element program for analyzing the large deformation dynamic and hydrodynamic response of inelastic solids. DYNA2D* contains 13 material models and 9 equations of state (EOS) to cover a wide range of material behavior. The material models implemented in all machine versions are: elastic, orthotropic elastic, kinematic/isotropic elastic plasticity, thermoelastoplastic, soil and crushable foam, linear viscoelastic, rubber, high explosive burn, isotropic elastic-plastic, temperature-dependent elastic-plastic. Themore » isotropic and temperature-dependent elastic-plastic models determine only the deviatoric stresses. Pressure is determined by one of 9 equations of state including linear polynomial, JWL high explosive, Sack Tuesday high explosive, Gruneisen, ratio of polynomials, linear polynomial with energy deposition, ignition and growth of reaction in HE, tabulated compaction, and tabulated.« less
Stochastic Inversion of 2D Magnetotelluric Data
2010-07-01
The algorithm is developed to invert 2D magnetotelluric (MT) data based on sharp boundary parametrization using a Bayesian framework. Within the algorithm, we consider the locations and the resistivity of regions formed by the interfaces are as unknowns. We use a parallel, adaptive finite-element algorithm to forward simulate frequency-domain MT responses of 2D conductivity structure. Those unknown parameters are spatially correlated and are described by a geostatistical model. The joint posterior probability distribution function ismore » explored by Markov Chain Monte Carlo (MCMC) sampling methods. The developed stochastic model is effective for estimating the interface locations and resistivity. Most importantly, it provides details uncertainty information on each unknown parameter. Hardware requirements: PC, Supercomputer, Multi-platform, Workstation; Software requirements C and Fortan; Operation Systems/version is Linux/Unix or Windows« less
Static & Dynamic Response of 2D Solids
1996-07-15
NIKE2D is an implicit finite-element code for analyzing the finite deformation, static and dynamic response of two-dimensional, axisymmetric, plane strain, and plane stress solids. The code is fully vectorized and available on several computing platforms. A number of material models are incorporated to simulate a wide range of material behavior including elasto-placicity, anisotropy, creep, thermal effects, and rate dependence. Slideline algorithms model gaps and sliding along material interfaces, including interface friction, penetration and single surfacemore » contact. Interactive-graphics and rezoning is included for analyses with large mesh distortions. In addition to quasi-Newton and arc-length procedures, adaptive algorithms can be defined to solve the implicit equations using the solution language ISLAND. Each of these capabilities and more make NIKE2D a robust analysis tool.« less
Static & Dynamic Response of 2D Solids
Lin, Jerry
1996-07-15
NIKE2D is an implicit finite-element code for analyzing the finite deformation, static and dynamic response of two-dimensional, axisymmetric, plane strain, and plane stress solids. The code is fully vectorized and available on several computing platforms. A number of material models are incorporated to simulate a wide range of material behavior including elasto-placicity, anisotropy, creep, thermal effects, and rate dependence. Slideline algorithms model gaps and sliding along material interfaces, including interface friction, penetration and single surface contact. Interactive-graphics and rezoning is included for analyses with large mesh distortions. In addition to quasi-Newton and arc-length procedures, adaptive algorithms can be defined to solve the implicit equations using the solution language ISLAND. Each of these capabilities and more make NIKE2D a robust analysis tool.
Explicit 2-D Hydrodynamic FEM Program
Lin, Jerry
1996-08-07
DYNA2D* is a vectorized, explicit, two-dimensional, axisymmetric and plane strain finite element program for analyzing the large deformation dynamic and hydrodynamic response of inelastic solids. DYNA2D* contains 13 material models and 9 equations of state (EOS) to cover a wide range of material behavior. The material models implemented in all machine versions are: elastic, orthotropic elastic, kinematic/isotropic elastic plasticity, thermoelastoplastic, soil and crushable foam, linear viscoelastic, rubber, high explosive burn, isotropic elastic-plastic, temperature-dependent elastic-plastic. The isotropic and temperature-dependent elastic-plastic models determine only the deviatoric stresses. Pressure is determined by one of 9 equations of state including linear polynomial, JWL high explosive, Sack Tuesday high explosive, Gruneisen, ratio of polynomials, linear polynomial with energy deposition, ignition and growth of reaction in HE, tabulated compaction, and tabulated.
2D photonic-crystal optomechanical nanoresonator.
Makles, K; Antoni, T; Kuhn, A G; Deléglise, S; Briant, T; Cohadon, P-F; Braive, R; Beaudoin, G; Pinard, L; Michel, C; Dolique, V; Flaminio, R; Cagnoli, G; Robert-Philip, I; Heidmann, A
2015-01-15
We present the optical optimization of an optomechanical device based on a suspended InP membrane patterned with a 2D near-wavelength grating (NWG) based on a 2D photonic-crystal geometry. We first identify by numerical simulation a set of geometrical parameters providing a reflectivity higher than 99.8% over a 50-nm span. We then study the limitations induced by the finite value of the optical waist and lateral size of the NWG pattern using different numerical approaches. The NWG grating, pierced in a suspended InP 265-nm thick membrane, is used to form a compact microcavity involving the suspended nanomembrane as an end mirror. The resulting cavity has a waist size smaller than 10 μm and a finesse in the 200 range. It is used to probe the Brownian motion of the mechanical modes of the nanomembrane. PMID:25679837
Compact 2-D graphical representation of DNA
NASA Astrophysics Data System (ADS)
Randić, Milan; Vračko, Marjan; Zupan, Jure; Novič, Marjana
2003-05-01
We present a novel 2-D graphical representation for DNA sequences which has an important advantage over the existing graphical representations of DNA in being very compact. It is based on: (1) use of binary labels for the four nucleic acid bases, and (2) use of the 'worm' curve as template on which binary codes are placed. The approach is illustrated on DNA sequences of the first exon of human β-globin and gorilla β-globin.
2D materials: Graphene and others
NASA Astrophysics Data System (ADS)
Bansal, Suneev Anil; Singh, Amrinder Pal; Kumar, Suresh
2016-05-01
Present report reviews the recent advancements in new atomically thick 2D materials. Materials covered in this review are Graphene, Silicene, Germanene, Boron Nitride (BN) and Transition metal chalcogenides (TMC). These materials show extraordinary mechanical, electronic and optical properties which make them suitable candidates for future applications. Apart from unique properties, tune-ability of highly desirable properties of these materials is also an important area to be emphasized on.
Layer Engineering of 2D Semiconductor Junctions.
He, Yongmin; Sobhani, Ali; Lei, Sidong; Zhang, Zhuhua; Gong, Yongji; Jin, Zehua; Zhou, Wu; Yang, Yingchao; Zhang, Yuan; Wang, Xifan; Yakobson, Boris; Vajtai, Robert; Halas, Naomi J; Li, Bo; Xie, Erqing; Ajayan, Pulickel
2016-07-01
A new concept for junction fabrication by connecting multiple regions with varying layer thicknesses, based on the thickness dependence, is demonstrated. This type of junction is only possible in super-thin-layered 2D materials, and exhibits similar characteristics as p-n junctions. Rectification and photovoltaic effects are observed in chemically homogeneous MoSe2 junctions between domains of different thicknesses. PMID:27136275
Realistic and efficient 2D crack simulation
NASA Astrophysics Data System (ADS)
Yadegar, Jacob; Liu, Xiaoqing; Singh, Abhishek
2010-04-01
Although numerical algorithms for 2D crack simulation have been studied in Modeling and Simulation (M&S) and computer graphics for decades, realism and computational efficiency are still major challenges. In this paper, we introduce a high-fidelity, scalable, adaptive and efficient/runtime 2D crack/fracture simulation system by applying the mathematically elegant Peano-Cesaro triangular meshing/remeshing technique to model the generation of shards/fragments. The recursive fractal sweep associated with the Peano-Cesaro triangulation provides efficient local multi-resolution refinement to any level-of-detail. The generated binary decomposition tree also provides efficient neighbor retrieval mechanism used for mesh element splitting and merging with minimal memory requirements essential for realistic 2D fragment formation. Upon load impact/contact/penetration, a number of factors including impact angle, impact energy, and material properties are all taken into account to produce the criteria of crack initialization, propagation, and termination leading to realistic fractal-like rubble/fragments formation. The aforementioned parameters are used as variables of probabilistic models of cracks/shards formation, making the proposed solution highly adaptive by allowing machine learning mechanisms learn the optimal values for the variables/parameters based on prior benchmark data generated by off-line physics based simulation solutions that produce accurate fractures/shards though at highly non-real time paste. Crack/fracture simulation has been conducted on various load impacts with different initial locations at various impulse scales. The simulation results demonstrate that the proposed system has the capability to realistically and efficiently simulate 2D crack phenomena (such as window shattering and shards generation) with diverse potentials in military and civil M&S applications such as training and mission planning.
2D Spinodal Decomposition in Forced Turbulence
NASA Astrophysics Data System (ADS)
Fan, Xiang; Diamond, Patrick; Chacon, Luis; Li, Hui
2015-11-01
Spinodal decomposition is a second order phase transition for binary fluid mixture, from one thermodynamic phase to form two coexisting phases. The governing equation for this coarsening process below critical temperature, Cahn-Hilliard Equation, is very similar to 2D MHD Equation, especially the conserved quantities have a close correspondence between each other, so theories for MHD turbulence are used to study spinodal decomposition in forced turbulence. Domain size is increased with time along with the inverse cascade, and the length scale can be arrested by a forced turbulence with direct cascade. The two competing mechanisms lead to a stabilized domain size length scale, which can be characterized by Hinze Scale. The 2D spinodal decomposition in forced turbulence is studied by both theory and simulation with ``pixie2d.'' This work focuses on the relation between Hinze scale and spectra and cascades. Similarities and differences between spinodal decomposition and MHD are investigated. Also some transport properties are studied following MHD theories. This work is supported by the Department of Energy under Award Number DE-FG02-04ER54738.
MAGNUM-2D computer code: user's guide
England, R.L.; Kline, N.W.; Ekblad, K.J.; Baca, R.G.
1985-01-01
Information relevant to the general use of the MAGNUM-2D computer code is presented. This computer code was developed for the purpose of modeling (i.e., simulating) the thermal and hydraulic conditions in the vicinity of a waste package emplaced in a deep geologic repository. The MAGNUM-2D computer computes (1) the temperature field surrounding the waste package as a function of the heat generation rate of the nuclear waste and thermal properties of the basalt and (2) the hydraulic head distribution and associated groundwater flow fields as a function of the temperature gradients and hydraulic properties of the basalt. MAGNUM-2D is a two-dimensional numerical model for transient or steady-state analysis of coupled heat transfer and groundwater flow in a fractured porous medium. The governing equations consist of a set of coupled, quasi-linear partial differential equations that are solved using a Galerkin finite-element technique. A Newton-Raphson algorithm is embedded in the Galerkin functional to formulate the problem in terms of the incremental changes in the dependent variables. Both triangular and quadrilateral finite elements are used to represent the continuum portions of the spatial domain. Line elements may be used to represent discrete conduits. 18 refs., 4 figs., 1 tab.
Engineering light outcoupling in 2D materials.
Lien, Der-Hsien; Kang, Jeong Seuk; Amani, Matin; Chen, Kevin; Tosun, Mahmut; Wang, Hsin-Ping; Roy, Tania; Eggleston, Michael S; Wu, Ming C; Dubey, Madan; Lee, Si-Chen; He, Jr-Hau; Javey, Ali
2015-02-11
When light is incident on 2D transition metal dichalcogenides (TMDCs), it engages in multiple reflections within underlying substrates, producing interferences that lead to enhancement or attenuation of the incoming and outgoing strength of light. Here, we report a simple method to engineer the light outcoupling in semiconducting TMDCs by modulating their dielectric surroundings. We show that by modulating the thicknesses of underlying substrates and capping layers, the interference caused by substrate can significantly enhance the light absorption and emission of WSe2, resulting in a ∼11 times increase in Raman signal and a ∼30 times increase in the photoluminescence (PL) intensity of WSe2. On the basis of the interference model, we also propose a strategy to control the photonic and optoelectronic properties of thin-layer WSe2. This work demonstrates the utilization of outcoupling engineering in 2D materials and offers a new route toward the realization of novel optoelectronic devices, such as 2D LEDs and solar cells.
Deterministic hierarchical networks
NASA Astrophysics Data System (ADS)
Barrière, L.; Comellas, F.; Dalfó, C.; Fiol, M. A.
2016-06-01
It has been shown that many networks associated with complex systems are small-world (they have both a large local clustering coefficient and a small diameter) and also scale-free (the degrees are distributed according to a power law). Moreover, these networks are very often hierarchical, as they describe the modularity of the systems that are modeled. Most of the studies for complex networks are based on stochastic methods. However, a deterministic method, with an exact determination of the main relevant parameters of the networks, has proven useful. Indeed, this approach complements and enhances the probabilistic and simulation techniques and, therefore, it provides a better understanding of the modeled systems. In this paper we find the radius, diameter, clustering coefficient and degree distribution of a generic family of deterministic hierarchical small-world scale-free networks that has been considered for modeling real-life complex systems.
NASA Astrophysics Data System (ADS)
Lacava, C.; Carrol, L.; Bozzola, A.; Marchetti, R.; Minzioni, P.; Cristiani, I.; Fournier, M.; Bernabe, S.; Gerace, D.; Andreani, L. C.
2016-03-01
We present the characterization of Silicon-on-insulator (SOI) photonic-crystal based 2D grating-couplers (2D-GCs) fabricated by CEA-Leti in the frame of the FP7 Fabulous project, which is dedicated to the realization of devices and systems for low-cost and high-performance passives-optical-networks. On the analyzed samples different test structures are present, including 2D-GC connected to another 2D-GC by different waveguides (in a Mach-Zehnder like configuration), and 2D-GC connected to two separate 2D-GCs, so as to allow a complete assessment of different parameters. Measurements were carried out using a tunable laser source operating in the extended telecom bandwidth and a fiber-based polarization controlling system at the input of device-under-test. The measured data yielded an overall fiber-to-fiber loss of 7.5 dB for the structure composed by an input 2D-GC connected to two identical 2D-GCs. This value was obtained at the peak wavelength of the grating, and the 3-dB bandwidth of the 2D-GC was assessed to be 43 nm. Assuming that the waveguide losses are negligible, so as to make a worst-case analysis, the coupling efficiency of the single 2D-GC results to be equal to -3.75 dB, constituting, to the best of our knowledge, the lowest value ever reported for a fully CMOS compatible 2D-GC. It is worth noting that both the obtained values are in good agreement with those expected by the numerical simulations performed using full 3D analysis by Lumerical FDTD-solutions.
GBL-2D Version 1.0: a 2D geometry boolean library.
McBride, Cory L. (Elemental Technologies, American Fort, UT); Schmidt, Rodney Cannon; Yarberry, Victor R.; Meyers, Ray J.
2006-11-01
This report describes version 1.0 of GBL-2D, a geometric Boolean library for 2D objects. The library is written in C++ and consists of a set of classes and routines. The classes primarily represent geometric data and relationships. Classes are provided for 2D points, lines, arcs, edge uses, loops, surfaces and mask sets. The routines contain algorithms for geometric Boolean operations and utility functions. Routines are provided that incorporate the Boolean operations: Union(OR), XOR, Intersection and Difference. A variety of additional analytical geometry routines and routines for importing and exporting the data in various file formats are also provided. The GBL-2D library was originally developed as a geometric modeling engine for use with a separate software tool, called SummitView [1], that manipulates the 2D mask sets created by designers of Micro-Electro-Mechanical Systems (MEMS). However, many other practical applications for this type of software can be envisioned because the need to perform 2D Boolean operations can arise in many contexts.
Periodically sheared 2D Yukawa systems
Kovács, Anikó Zsuzsa; Hartmann, Peter; Donkó, Zoltán
2015-10-15
We present non-equilibrium molecular dynamics simulation studies on the dynamic (complex) shear viscosity of a 2D Yukawa system. We have identified a non-monotonic frequency dependence of the viscosity at high frequencies and shear rates, an energy absorption maximum (local resonance) at the Einstein frequency of the system at medium shear rates, an enhanced collective wave activity, when the excitation is near the plateau frequency of the longitudinal wave dispersion, and the emergence of significant configurational anisotropy at small frequencies and high shear rates.
ENERGY LANDSCAPE OF 2D FLUID FORMS
Y. JIANG; ET AL
2000-04-01
The equilibrium states of 2D non-coarsening fluid foams, which consist of bubbles with fixed areas, correspond to local minima of the total perimeter. (1) The authors find an approximate value of the global minimum, and determine directly from an image how far a foam is from its ground state. (2) For (small) area disorder, small bubbles tend to sort inwards and large bubbles outwards. (3) Topological charges of the same sign repel while charges of opposite sign attract. (4) They discuss boundary conditions and the uniqueness of the pattern for fixed topology.
Formation and properties of a terpyridine-based 2D MOF on the surface of water
NASA Astrophysics Data System (ADS)
Koitz, Ralph; Hutter, Jürg; Iannuzzi, Marcella
2016-06-01
Two-dimensional networks inspired by graphene are of prime importance in nanoscience. We present a computational study of an infinite molecular sheet confined on a water surface to assess its properties and formation mechanism. Terpyridine-based ligand molecules are interlinked by Zn ions to form an extended 2D metal-organic framework. We show that the network is stable on the water surface, and that the substrate affects the dynamic properties of the sheet, exhibiting a confining effect and flattening the sheet by 30%. We use metadynamics to characterize the process of network formation and breaking and determine an intra-network binding energy of 143 kJ mol‑1. Based on this mechanistic insight we propose that the 2D network strength can be tuned by varying the rigidity of the ligand through its chemical structure.
WFR-2D: an analytical model for PWAS-generated 2D ultrasonic guided wave propagation
NASA Astrophysics Data System (ADS)
Shen, Yanfeng; Giurgiutiu, Victor
2014-03-01
This paper presents WaveFormRevealer 2-D (WFR-2D), an analytical predictive tool for the simulation of 2-D ultrasonic guided wave propagation and interaction with damage. The design of structural health monitoring (SHM) systems and self-aware smart structures requires the exploration of a wide range of parameters to achieve best detection and quantification of certain types of damage. Such need for parameter exploration on sensor dimension, location, guided wave characteristics (mode type, frequency, wavelength, etc.) can be best satisfied with analytical models which are fast and efficient. The analytical model was constructed based on the exact 2-D Lamb wave solution using Bessel and Hankel functions. Damage effects were inserted in the model by considering the damage as a secondary wave source with complex-valued directivity scattering coefficients containing both amplitude and phase information from wave-damage interaction. The analytical procedure was coded with MATLAB, and a predictive simulation tool called WaveFormRevealer 2-D was developed. The wave-damage interaction coefficients (WDICs) were extracted from harmonic analysis of local finite element model (FEM) with artificial non-reflective boundaries (NRB). The WFR-2D analytical simulation results were compared and verified with full scale multiphysics finite element models and experiments with scanning laser vibrometer. First, Lamb wave propagation in a pristine aluminum plate was simulated with WFR-2D, compared with finite element results, and verified by experiments. Then, an inhomogeneity was machined into the plate to represent damage. Analytical modeling was carried out, and verified by finite element simulation and experiments. This paper finishes with conclusions and suggestions for future work.
Microwave Assisted 2D Materials Exfoliation
NASA Astrophysics Data System (ADS)
Wang, Yanbin
Two-dimensional materials have emerged as extremely important materials with applications ranging from energy and environmental science to electronics and biology. Here we report our discovery of a universal, ultrafast, green, solvo-thermal technology for producing excellent-quality, few-layered nanosheets in liquid phase from well-known 2D materials such as such hexagonal boron nitride (h-BN), graphite, and MoS2. We start by mixing the uniform bulk-layered material with a common organic solvent that matches its surface energy to reduce the van der Waals attractive interactions between the layers; next, the solutions are heated in a commercial microwave oven to overcome the energy barrier between bulk and few-layers states. We discovered the minutes-long rapid exfoliation process is highly temperature dependent, which requires precise thermal management to obtain high-quality inks. We hypothesize a possible mechanism of this proposed solvo-thermal process; our theory confirms the basis of this novel technique for exfoliation of high-quality, layered 2D materials by using an as yet unknown role of the solvent.
Multienzyme Inkjet Printed 2D Arrays.
Gdor, Efrat; Shemesh, Shay; Magdassi, Shlomo; Mandler, Daniel
2015-08-19
The use of printing to produce 2D arrays is well established, and should be relatively facile to adapt for the purpose of printing biomaterials; however, very few studies have been published using enzyme solutions as inks. Among the printing technologies, inkjet printing is highly suitable for printing biomaterials and specifically enzymes, as it offers many advantages. Formulation of the inkjet inks is relatively simple and can be adjusted to a variety of biomaterials, while providing nonharmful environment to the enzymes. Here we demonstrate the applicability of inkjet printing for patterning multiple enzymes in a predefined array in a very straightforward, noncontact method. Specifically, various arrays of the enzymes glucose oxidase (GOx), invertase (INV) and horseradish peroxidase (HP) were printed on aminated glass surfaces, followed by immobilization using glutardialdehyde after printing. Scanning electrochemical microscopy (SECM) was used for imaging the printed patterns and to ascertain the enzyme activity. The successful formation of 2D arrays consisting of enzymes was explored as a means of developing the first surface confined enzyme based logic gates. Principally, XOR and AND gates, each consisting of two enzymes as the Boolean operators, were assembled, and their operation was studied by SECM. PMID:26214072
Caruso, Joseph P.; Israel, Natalie; Rowland, Kimberly; Lovelace, Matthew J.; Saunders, Mary Jane
2016-01-01
Course-based undergraduate research is known to improve science, technology, engineering, and mathematics student achievement. We tested “The Small World Initiative, a Citizen-Science Project to Crowdsource Novel Antibiotic Discovery” to see if it also improved student performance and the critical thinking of non-science majors in Introductory Biology at Florida Atlantic University (a large, public, minority-dominant institution) in academic year 2014–15. California Critical Thinking Skills Test pre- and posttests were offered to both Small World Initiative (SWI) and control lab students for formative amounts of extra credit. SWI lab students earned significantly higher lecture grades than control lab students, had significantly fewer lecture grades of D+ or lower, and had significantly higher critical thinking posttest total scores than control students. Lastly, more SWI students were engaged while taking critical thinking tests. These results support the hypothesis that utilizing independent course-based undergraduate science research improves student achievement even in nonscience students. PMID:27047613
Brane brick models and 2 d (0 , 2) triality
NASA Astrophysics Data System (ADS)
Franco, Sebastián; Lee, Sangmin; Seong, Rak-Kyeong
2016-05-01
We provide a brane realization of 2 d (0 , 2) Gadde-Gukov-Putrov triality in terms of brane brick models. These are Type IIA brane configurations that are T-dual to D1-branes over singular toric Calabi-Yau 4-folds. Triality translates into a local transformation of brane brick models, whose simplest representative is a cube move. We present explicit examples and construct their triality networks. We also argue that the classical mesonic moduli space of brane brick model theories, which corresponds to the probed Calabi-Yau 4-fold, is invariant under triality. Finally, we discuss triality in terms of phase boundaries, which play a central role in connecting Calabi-Yau 4-folds to brane brick models.
Social network structures and bank runs
NASA Astrophysics Data System (ADS)
Li, Shouwei; Li, Jiaheng
2016-05-01
This paper investigates the impact of social network structures of depositors on bank runs. The analyzed network structures include random networks, small-world networks and scale-free networks. Simulation results show that the probability of bank run occurrence in random networks is larger than that in small-world networks, but the probability of bank run occurrence in scale-free networks drops from the highest to the lowest among the three types of network structures with the increase of the proportion of impatient depositors. The average degree of depositor networks has a significant impact on bank runs, but this impact is related to the proportion of impatient depositors and the confidence levels of depositors in banks.
Canard configured aircraft with 2-D nozzle
NASA Technical Reports Server (NTRS)
Child, R. D.; Henderson, W. P.
1978-01-01
A closely-coupled canard fighter with vectorable two-dimensional nozzle was designed for enhanced transonic maneuvering. The HiMAT maneuver goal of a sustained 8g turn at a free-stream Mach number of 0.9 and 30,000 feet was the primary design consideration. The aerodynamic design process was initiated with a linear theory optimization minimizing the zero percent suction drag including jet effects and refined with three-dimensional nonlinear potential flow techniques. Allowances were made for mutual interference and viscous effects. The design process to arrive at the resultant configuration is described, and the design of a powered 2-D nozzle model to be tested in the LRC 16-foot Propulsion Wind Tunnel is shown.
2D Electrostatic Actuation of Microshutter Arrays
NASA Technical Reports Server (NTRS)
Burns, Devin E.; Oh, Lance H.; Li, Mary J.; Kelly, Daniel P.; Kutyrev, Alexander S.; Moseley, Samuel H.
2015-01-01
Electrostatically actuated microshutter arrays consisting of rotational microshutters (shutters that rotate about a torsion bar) were designed and fabricated through the use of models and experiments. Design iterations focused on minimizing the torsional stiffness of the microshutters, while maintaining their structural integrity. Mechanical and electromechanical test systems were constructed to measure the static and dynamic behavior of the microshutters. The torsional stiffness was reduced by a factor of four over initial designs without sacrificing durability. Analysis of the resonant behavior of the microshutters demonstrates that the first resonant mode is a torsional mode occurring around 3000 Hz. At low vacuum pressures, this resonant mode can be used to significantly reduce the drive voltage necessary for actuation requiring as little as 25V. 2D electrostatic latching and addressing was demonstrated using both a resonant and pulsed addressing scheme.
2D Electrostatic Actuation of Microshutter Arrays
NASA Technical Reports Server (NTRS)
Burns, Devin E.; Oh, Lance H.; Li, Mary J.; Jones, Justin S.; Kelly, Daniel P.; Zheng, Yun; Kutyrev, Alexander S.; Moseley, Samuel H.
2015-01-01
An electrostatically actuated microshutter array consisting of rotational microshutters (shutters that rotate about a torsion bar) were designed and fabricated through the use of models and experiments. Design iterations focused on minimizing the torsional stiffness of the microshutters, while maintaining their structural integrity. Mechanical and electromechanical test systems were constructed to measure the static and dynamic behavior of the microshutters. The torsional stiffness was reduced by a factor of four over initial designs without sacrificing durability. Analysis of the resonant behavior of the microshutter arrays demonstrates that the first resonant mode is a torsional mode occurring around 3000 Hz. At low vacuum pressures, this resonant mode can be used to significantly reduce the drive voltage necessary for actuation requiring as little as 25V. 2D electrostatic latching and addressing was demonstrated using both a resonant and pulsed addressing scheme.
2D quantum gravity from quantum entanglement.
Gliozzi, F
2011-01-21
In quantum systems with many degrees of freedom the replica method is a useful tool to study the entanglement of arbitrary spatial regions. We apply it in a way that allows them to backreact. As a consequence, they become dynamical subsystems whose position, form, and extension are determined by their interaction with the whole system. We analyze, in particular, quantum spin chains described at criticality by a conformal field theory. Its coupling to the Gibbs' ensemble of all possible subsystems is relevant and drives the system into a new fixed point which is argued to be that of the 2D quantum gravity coupled to this system. Numerical experiments on the critical Ising model show that the new critical exponents agree with those predicted by the formula of Knizhnik, Polyakov, and Zamolodchikov.
Graphene suspensions for 2D printing
NASA Astrophysics Data System (ADS)
Soots, R. A.; Yakimchuk, E. A.; Nebogatikova, N. A.; Kotin, I. A.; Antonova, I. V.
2016-04-01
It is shown that, by processing a graphite suspension in ethanol or water by ultrasound and centrifuging, it is possible to obtain particles with thicknesses within 1-6 nm and, in the most interesting cases, 1-1.5 nm. Analogous treatment of a graphite suspension in organic solvent yields eventually thicker particles (up to 6-10 nm thick) even upon long-term treatment. Using the proposed ink based on graphene and aqueous ethanol with ethylcellulose and terpineol additives for 2D printing, thin (~5 nm thick) films with sheet resistance upon annealing ~30 MΩ/□ were obtained. With the ink based on aqueous graphene suspension, the sheet resistance was ~5-12 kΩ/□ for 6- to 15-nm-thick layers with a carrier mobility of ~30-50 cm2/(V s).
Metrology for graphene and 2D materials
NASA Astrophysics Data System (ADS)
Pollard, Andrew J.
2016-09-01
The application of graphene, a one atom-thick honeycomb lattice of carbon atoms with superlative properties, such as electrical conductivity, thermal conductivity and strength, has already shown that it can be used to benefit metrology itself as a new quantum standard for resistance. However, there are many application areas where graphene and other 2D materials, such as molybdenum disulphide (MoS2) and hexagonal boron nitride (h-BN), may be disruptive, areas such as flexible electronics, nanocomposites, sensing and energy storage. Applying metrology to the area of graphene is now critical to enable the new, emerging global graphene commercial world and bridge the gap between academia and industry. Measurement capabilities and expertise in a wide range of scientific areas are required to address this challenge. The combined and complementary approach of varied characterisation methods for structural, chemical, electrical and other properties, will allow the real-world issues of commercialising graphene and other 2D materials to be addressed. Here, examples of metrology challenges that have been overcome through a multi-technique or new approach are discussed. Firstly, the structural characterisation of defects in both graphene and MoS2 via Raman spectroscopy is described, and how nanoscale mapping of vacancy defects in graphene is also possible using tip-enhanced Raman spectroscopy (TERS). Furthermore, the chemical characterisation and removal of polymer residue on chemical vapour deposition (CVD) grown graphene via secondary ion mass spectrometry (SIMS) is detailed, as well as the chemical characterisation of iron films used to grow large domain single-layer h-BN through CVD growth, revealing how contamination of the substrate itself plays a role in the resulting h-BN layer. In addition, the role of international standardisation in this area is described, outlining the current work ongoing in both the International Organization of Standardization (ISO) and the
Gaedigk, Andrea; Bradford, L Dianne; Alander, Sarah W; Leeder, J Steven
2006-04-01
Unexplained cases of CYP2D6 genotype/phenotype discordance continue to be discovered. In previous studies, several African Americans with a poor metabolizer phenotype carried the reduced function CYP2D6*10 allele in combination with a nonfunctional allele. We pursued the possibility that these alleles harbor either a known sequence variation (i.e., CYP2D6*36 carrying a gene conversion in exon 9 along the CYP2D6*10-defining 100C>T single-nucleotide polymorphism) or novel sequences variation(s). Discordant cases were evaluated by long-range polymerase chain reaction (PCR) to test for gene rearrangement events, and a 6.6-kilobase pair PCR product encompassing the CYP2D6 gene was cloned and entirely sequenced. Thereafter, allele frequencies were determined in different study populations comprising whites, African Americans, and Asians. Analyses covering the CYP2D7 to 2D6 gene region established that CYP2D6*36 did not only exist as a gene duplication (CYP2D6*36x2) or in tandem with *10 (CYP2D6*36+*10), as previously reported, but also by itself. This "single" CYP2D6*36 allele was found in nine African Americans and one Asian, but was absent in the whites tested. Ultimately, the presence of CYP2D6*36 resolved genotype/phenotype discordance in three cases. We also discovered an exon 9 conversion-positive CYP2D6*4 gene in a duplication arrangement (CYP2D6*4Nx2) and a CYP2D6*4 allele lacking 100C>T (CYP2D6*4M) in two white subjects. The discovery of an allele that carries only one CYP2D6*36 gene copy provides unequivocal evidence that both CYP2D6*36 and *36x2 are associated with a poor metabolizer phenotype. Given a combined frequency of between 0.5 and 3% in African Americans and Asians, genotyping for CYP2D6*36 should improve the accuracy of genotype-based phenotype prediction in these populations.
A new inversion method for (T2, D) 2D NMR logging and fluid typing
NASA Astrophysics Data System (ADS)
Tan, Maojin; Zou, Youlong; Zhou, Cancan
2013-02-01
One-dimensional nuclear magnetic resonance (1D NMR) logging technology has some significant limitations in fluid typing. However, not only can two-dimensional nuclear magnetic resonance (2D NMR) provide some accurate porosity parameters, but it can also identify fluids more accurately than 1D NMR. In this paper, based on the relaxation mechanism of (T2, D) 2D NMR in a gradient magnetic field, a hybrid inversion method that combines least-squares-based QR decomposition (LSQR) and truncated singular value decomposition (TSVD) is examined in the 2D NMR inversion of various fluid models. The forward modeling and inversion tests are performed in detail with different acquisition parameters, such as magnetic field gradients (G) and echo spacing (TE) groups. The simulated results are discussed and described in detail, the influence of the above-mentioned observation parameters on the inversion accuracy is investigated and analyzed, and the observation parameters in multi-TE activation are optimized. Furthermore, the hybrid inversion can be applied to quantitatively determine the fluid saturation. To study the effects of noise level on the hybrid method and inversion results, the numerical simulation experiments are performed using different signal-to-noise-ratios (SNRs), and the effect of different SNRs on fluid typing using three fluid models are discussed and analyzed in detail.
Characteristics on hub networks of urban rail transit networks
NASA Astrophysics Data System (ADS)
Zhang, Jianhua; Wang, Shuliang; Zhang, Zhaojun; Zou, Kuansheng; Shu, Zhan
2016-04-01
This paper proposes an approach to extract the hub networks from urban rail transit networks, and analyzes the characteristics of the hub networks. Minsk metro and Shanghai metro networks are given to illustrate the feasibility and effectiveness of the presented method in this paper. By simulations, we discover that the hub networks of urban rail transit networks possess small-world property and scale-free property. Meanwhile, this paper shows that the hub networks are completely different from the corresponding metro networks. Moreover, we find that the hub network is a hierarchical network, and the root of hub network corresponds to the transfer station of metro network which is passed by the most lines in metro network, and the root controls the main characteristics of hub network. In other words, the transfer station corresponding to this root plays the most important role in the urban rail transit networks.
NASA Astrophysics Data System (ADS)
Cheng, Chingyun; Kangara, Jayampathi; Arakelyan, Ilya; Thomas, John
2016-05-01
We tune the dimensionality of a strongly interacting degenerate 6 Li Fermi gas from 2D to quasi-2D, by adjusting the radial confinement of pancake-shaped clouds to control the radial chemical potential. In the 2D regime with weak radial confinement, the measured pair binding energies are in agreement with 2D-BCS mean field theory, which predicts dimer pairing energies in the many-body regime. In the qausi-2D regime obtained with increased radial confinement, the measured pairing energy deviates significantly from 2D-BCS theory. In contrast to the pairing energy, the measured radii of the cloud profiles are not fit by 2D-BCS theory in either the 2D or quasi-2D regimes, but are fit in both regimes by a beyond mean field polaron-model of the free energy. Supported by DOE, ARO, NSF, and AFOSR.
Phase Engineering of 2D Tin Sulfides.
Mutlu, Zafer; Wu, Ryan J; Wickramaratne, Darshana; Shahrezaei, Sina; Liu, Chueh; Temiz, Selcuk; Patalano, Andrew; Ozkan, Mihrimah; Lake, Roger K; Mkhoyan, K A; Ozkan, Cengiz S
2016-06-01
Tin sulfides can exist in a variety of phases and polytypes due to the different oxidation states of Sn. A subset of these phases and polytypes take the form of layered 2D structures that give rise to a wide host of electronic and optical properties. Hence, achieving control over the phase, polytype, and thickness of tin sulfides is necessary to utilize this wide range of properties exhibited by the compound. This study reports on phase-selective growth of both hexagonal tin (IV) sulfide SnS2 and orthorhombic tin (II) sulfide SnS crystals with diameters of over tens of microns on SiO2 substrates through atmospheric pressure vapor-phase method in a conventional horizontal quartz tube furnace with SnO2 and S powders as the source materials. Detailed characterization of each phase of tin sulfide crystals is performed using various microscopy and spectroscopy methods, and the results are corroborated by ab initio density functional theory calculations. PMID:27099950
Phase Engineering of 2D Tin Sulfides.
Mutlu, Zafer; Wu, Ryan J; Wickramaratne, Darshana; Shahrezaei, Sina; Liu, Chueh; Temiz, Selcuk; Patalano, Andrew; Ozkan, Mihrimah; Lake, Roger K; Mkhoyan, K A; Ozkan, Cengiz S
2016-06-01
Tin sulfides can exist in a variety of phases and polytypes due to the different oxidation states of Sn. A subset of these phases and polytypes take the form of layered 2D structures that give rise to a wide host of electronic and optical properties. Hence, achieving control over the phase, polytype, and thickness of tin sulfides is necessary to utilize this wide range of properties exhibited by the compound. This study reports on phase-selective growth of both hexagonal tin (IV) sulfide SnS2 and orthorhombic tin (II) sulfide SnS crystals with diameters of over tens of microns on SiO2 substrates through atmospheric pressure vapor-phase method in a conventional horizontal quartz tube furnace with SnO2 and S powders as the source materials. Detailed characterization of each phase of tin sulfide crystals is performed using various microscopy and spectroscopy methods, and the results are corroborated by ab initio density functional theory calculations.
The dynamic correlation between degree and betweenness of complex network under attack
NASA Astrophysics Data System (ADS)
Nie, Tingyuan; Guo, Zheng; Zhao, Kun; Lu, Zhe-Ming
2016-09-01
Complex networks are often subjected to failure and attack. Recent work has addressed the resilience of complex networks to either random or intentional deletion of nodes or links. Here we simulate the breakdown of the small-world network and the scale-free network under node failure or attacks. We analyze and discuss the dynamic correlation between degree and betweenness in the process of attack. The simulation results show that the correlation for scale-free network obeys a power law distribution until the network collapses, while it represents irregularly for small-world network.
2-D Animation's Not Just for Mickey Mouse.
ERIC Educational Resources Information Center
Weinman, Lynda
1995-01-01
Discusses characteristics of two-dimensional (2-D) animation; highlights include character animation, painting issues, and motion graphics. Sidebars present Silicon Graphics animations tools and 2-D animation programs for the desktop computer. (DGM)
Generates 2D Input for DYNA NIKE & TOPAZ
Hallquist, J. O.; Sanford, Larry
1996-07-15
MAZE is an interactive program that serves as an input and two-dimensional mesh generator for DYNA2D, NIKE2D, TOPAZ2D, and CHEMICAL TOPAZ2D. MAZE also generates a basic template for ISLAND input. MAZE has been applied to the generation of input data to study the response of two-dimensional solids and structures undergoing finite deformations under a wide variety of large deformation transient dynamic and static problems and heat transfer analyses.
MAZE96. Generates 2D Input for DYNA NIKE & TOPAZ
Sanford, L.; Hallquist, J.O.
1992-02-24
MAZE is an interactive program that serves as an input and two-dimensional mesh generator for DYNA2D, NIKE2D, TOPAZ2D, and CHEMICAL TOPAZ2D. MAZE also generates a basic template for ISLAND input. MAZE has been applied to the generation of input data to study the response of two-dimensional solids and structures undergoing finite deformations under a wide variety of large deformation transient dynamic and static problems and heat transfer analyses.
2d PDE Linear Symmetric Matrix Solver
1983-10-01
ICCG2 (Incomplete Cholesky factorized Conjugate Gradient algorithm for 2d symmetric problems) was developed to solve a linear symmetric matrix system arising from a 9-point discretization of two-dimensional elliptic and parabolic partial differential equations found in plasma physics applications, such as resistive MHD, spatial diffusive transport, and phase space transport (Fokker-Planck equation) problems. These problems share the common feature of being stiff and requiring implicit solution techniques. When these parabolic or elliptic PDE''s are discretized withmore » finite-difference or finite-element methods,the resulting matrix system is frequently of block-tridiagonal form. To use ICCG2, the discretization of the two-dimensional partial differential equation and its boundary conditions must result in a block-tridiagonal supermatrix composed of elementary tridiagonal matrices. The incomplete Cholesky conjugate gradient algorithm is used to solve the linear symmetric matrix equation. Loops are arranged to vectorize on the Cray1 with the CFT compiler, wherever possible. Recursive loops, which cannot be vectorized, are written for optimum scalar speed. For matrices lacking symmetry, ILUCG2 should be used. Similar methods in three dimensions are available in ICCG3 and ILUCG3. A general source containing extensions and macros, which must be processed by a pre-compiler to obtain the standard FORTRAN source, is provided along with the standard FORTRAN source because it is believed to be more readable. The pre-compiler is not included, but pre-compilation may be performed by a text editor as described in the UCRL-88746 Preprint.« less
2d PDE Linear Asymmetric Matrix Solver
1983-10-01
ILUCG2 (Incomplete LU factorized Conjugate Gradient algorithm for 2d problems) was developed to solve a linear asymmetric matrix system arising from a 9-point discretization of two-dimensional elliptic and parabolic partial differential equations found in plasma physics applications, such as plasma diffusion, equilibria, and phase space transport (Fokker-Planck equation) problems. These equations share the common feature of being stiff and requiring implicit solution techniques. When these parabolic or elliptic PDE''s are discretized with finite-difference or finite-elementmore » methods, the resulting matrix system is frequently of block-tridiagonal form. To use ILUCG2, the discretization of the two-dimensional partial differential equation and its boundary conditions must result in a block-tridiagonal supermatrix composed of elementary tridiagonal matrices. A generalization of the incomplete Cholesky conjugate gradient algorithm is used to solve the matrix equation. Loops are arranged to vectorize on the Cray1 with the CFT compiler, wherever possible. Recursive loops, which cannot be vectorized, are written for optimum scalar speed. For problems having a symmetric matrix ICCG2 should be used since it runs up to four times faster and uses approximately 30% less storage. Similar methods in three dimensions are available in ICCG3 and ILUCG3. A general source, containing extensions and macros, which must be processed by a pre-compiler to obtain the standard FORTRAN source, is provided along with the standard FORTRAN source because it is believed to be more readable. The pre-compiler is not included, but pre-compilation may be performed by a text editor as described in the UCRL-88746 Preprint.« less
Position control using 2D-to-2D feature correspondences in vision guided cell micromanipulation.
Zhang, Yanliang; Han, Mingli; Shee, Cheng Yap; Ang, Wei Tech
2007-01-01
Conventional camera calibration that utilizes the extrinsic and intrinsic parameters of the camera and the objects has certain limitations for micro-level cell operations due to the presence of hardware deviations and external disturbances during the experimental process, thereby invalidating the extrinsic parameters. This invalidation is often neglected in macro-world visual servoing and affects the visual image processing quality, causing deviation from the desired position in micro-level cell operations. To increase the success rate of vision guided biological micromanipulations, a novel algorithm monitoring the changing image pattern of the manipulators including the injection micropipette and cell holder is designed and implemented based on 2 dimensional (2D)-to 2D feature correspondences and can adjust the manipulator and perform position control simultaneously. When any deviation is found, the manipulator is retracted to the initial focusing plane before continuing the operation.
A Planar Quantum Transistor Based on 2D-2D Tunneling in Double Quantum Well Heterostructures
Baca, W.E.; Blount, M.A.; Hafich, M.J.; Lyo, S.K.; Moon, J.S.; Reno, J.L.; Simmons, J.A.; Wendt, J.R.
1998-12-14
We report on our work on the double electron layer tunneling transistor (DELTT), based on the gate-control of two-dimensional -- two-dimensional (2D-2D) tunneling in a double quantum well heterostructure. While previous quantum transistors have typically required tiny laterally-defined features, by contrast the DELTT is entirely planar and can be reliably fabricated in large numbers. We use a novel epoxy-bond-and-stop-etch (EBASE) flip-chip process, whereby submicron gating on opposite sides of semiconductor epitaxial layers as thin as 0.24 microns can be achieved. Because both electron layers in the DELTT are 2D, the resonant tunneling features are unusually sharp, and can be easily modulated with one or more surface gates. We demonstrate DELTTs with peak-to-valley ratios in the source-drain I-V curve of order 20:1 below 1 K. Both the height and position of the resonant current peak can be controlled by gate voltage over a wide range. DELTTs with larger subband energy offsets ({approximately} 21 meV) exhibit characteristics that are nearly as good at 77 K, in good agreement with our theoretical calculations. Using these devices, we also demonstrate bistable memories operating at 77 K. Finally, we briefly discuss the prospects for room temperature operation, increases in gain, and high-speed.
'Brukin2D': a 2D visualization and comparison tool for LC-MS data
Tsagkrasoulis, Dimosthenis; Zerefos, Panagiotis; Loudos, George; Vlahou, Antonia; Baumann, Marc; Kossida, Sophia
2009-01-01
Background Liquid Chromatography-Mass Spectrometry (LC-MS) is a commonly used technique to resolve complex protein mixtures. Visualization of large data sets produced from LC-MS, namely the chromatogram and the mass spectra that correspond to its compounds is the focus of this work. Results The in-house developed 'Brukin2D' software, built in Matlab 7.4, which is presented here, uses the compound data that are exported from the Bruker 'DataAnalysis' program, and depicts the mean mass spectra of all the chromatogram compounds from one LC-MS run, in one 2D contour/density plot. Two contour plots from different chromatograph runs can then be viewed in the same window and automatically compared, in order to find their similarities and differences. The results of the comparison can be examined through detailed mass quantification tables, while chromatogram compound statistics are also calculated during the procedure. Conclusion 'Brukin2D' provides a user-friendly platform for quick, easy and integrated view of complex LC-MS data. The software is available at . PMID:19534737
Inhibition of human cytochrome P450 2D6 (CYP2D6) by methadone.
Wu, D; Otton, S V; Sproule, B A; Busto, U; Inaba, T; Kalow, W; Sellers, E M
1993-01-01
1. In microsomes prepared from three human livers, methadone competitively inhibited the O-demethylation of dextromethorphan, a marker substrate for CYP2D6. The apparent Ki value of methadone ranged from 2.5 to 5 microM. 2. Two hundred and fifty-two (252) white Caucasians, including 210 unrelated healthy volunteers and 42 opiate abusers undergoing treatment with methadone were phenotyped using dextromethorphan as the marker drug. Although the frequency of poor metabolizers was similar in both groups, the extensive metabolizers among the opiate abusers tended to have higher O-demethylation metabolic ratios and to excrete less of the dose as dextromethorphan metabolites than control extensive metabolizer subjects. These data suggest inhibition of CYP2D6 by methadone in vivo as well. 3. Because methadone is widely used in the treatment of opiate abuse, inhibition of CYP2D6 activity in these patients might contribute to exaggerated response or unexpected toxicity from drugs that are substrates of this enzyme. PMID:8448065
Correlated Electron Phenomena in 2D Materials
NASA Astrophysics Data System (ADS)
Lambert, Joseph G.
In this thesis, I present experimental results on coherent electron phenomena in layered two-dimensional materials: single layer graphene and van der Waals coupled 2D TiSe2. Graphene is a two-dimensional single-atom thick sheet of carbon atoms first derived from bulk graphite by the mechanical exfoliation technique in 2004. Low-energy charge carriers in graphene behave like massless Dirac fermions, and their density can be easily tuned between electron-rich and hole-rich quasiparticles with electrostatic gating techniques. The sharp interfaces between regions of different carrier densities form barriers with selective transmission, making them behave as partially reflecting mirrors. When two of these interfaces are set at a separation distance within the phase coherence length of the carriers, they form an electronic version of a Fabry-Perot cavity. I present measurements and analysis of multiple Fabry-Perot modes in graphene with parallel electrodes spaced a few hundred nanometers apart. Transition metal dichalcogenide (TMD) TiSe2 is part of the family of materials that coined the term "materials beyond graphene". It contains van der Waals coupled trilayer stacks of Se-Ti-Se. Many TMD materials exhibit a host of interesting correlated electronic phases. In particular, TiSe2 exhibits chiral charge density waves (CDW) below TCDW ˜ 200 K. Upon doping with copper, the CDW state gets suppressed with Cu concentration, and CuxTiSe2 becomes superconducting with critical temperature of T c = 4.15 K. There is still much debate over the mechanisms governing the coexistence of the two correlated electronic phases---CDW and superconductivity. I will present some of the first conductance spectroscopy measurements of proximity coupled superconductor-CDW systems. Measurements reveal a proximity-induced critical current at the Nb-TiSe2 interfaces, suggesting pair correlations in the pure TiSe2. The results indicate that superconducting order is present concurrently with CDW in
CYP2D7 Sequence Variation Interferes with TaqMan CYP2D6*15 and *35 Genotyping
Riffel, Amanda K.; Dehghani, Mehdi; Hartshorne, Toinette; Floyd, Kristen C.; Leeder, J. Steven; Rosenblatt, Kevin P.; Gaedigk, Andrea
2016-01-01
TaqMan™ genotyping assays are widely used to genotype CYP2D6, which encodes a major drug metabolizing enzyme. Assay design for CYP2D6 can be challenging owing to the presence of two pseudogenes, CYP2D7 and CYP2D8, structural and copy number variation and numerous single nucleotide polymorphisms (SNPs) some of which reflect the wild-type sequence of the CYP2D7 pseudogene. The aim of this study was to identify the mechanism causing false-positive CYP2D6*15 calls and remediate those by redesigning and validating alternative TaqMan genotype assays. Among 13,866 DNA samples genotyped by the CompanionDx® lab on the OpenArray platform, 70 samples were identified as heterozygotes for 137Tins, the key SNP of CYP2D6*15. However, only 15 samples were confirmed when tested with the Luminex xTAG CYP2D6 Kit and sequencing of CYP2D6-specific long range (XL)-PCR products. Genotype and gene resequencing of CYP2D6 and CYP2D7-specific XL-PCR products revealed a CC>GT dinucleotide SNP in exon 1 of CYP2D7 that reverts the sequence to CYP2D6 and allows a TaqMan assay PCR primer to bind. Because CYP2D7 also carries a Tins, a false-positive mutation signal is generated. This CYP2D7 SNP was also responsible for generating false-positive signals for rs769258 (CYP2D6*35) which is also located in exon 1. Although alternative CYP2D6*15 and *35 assays resolved the issue, we discovered a novel CYP2D6*15 subvariant in one sample that carries additional SNPs preventing detection with the alternate assay. The frequency of CYP2D6*15 was 0.1% in this ethnically diverse U.S. population sample. In addition, we also discovered linkage between the CYP2D7 CC>GT dinucleotide SNP and the 77G>A (rs28371696) SNP of CYP2D6*43. The frequency of this tentatively functional allele was 0.2%. Taken together, these findings emphasize that regardless of how careful genotyping assays are designed and evaluated before being commercially marketed, rare or unknown SNPs underneath primer and/or probe regions can impact
CYP2D7 Sequence Variation Interferes with TaqMan CYP2D6 (*) 15 and (*) 35 Genotyping.
Riffel, Amanda K; Dehghani, Mehdi; Hartshorne, Toinette; Floyd, Kristen C; Leeder, J Steven; Rosenblatt, Kevin P; Gaedigk, Andrea
2015-01-01
TaqMan™ genotyping assays are widely used to genotype CYP2D6, which encodes a major drug metabolizing enzyme. Assay design for CYP2D6 can be challenging owing to the presence of two pseudogenes, CYP2D7 and CYP2D8, structural and copy number variation and numerous single nucleotide polymorphisms (SNPs) some of which reflect the wild-type sequence of the CYP2D7 pseudogene. The aim of this study was to identify the mechanism causing false-positive CYP2D6 (*) 15 calls and remediate those by redesigning and validating alternative TaqMan genotype assays. Among 13,866 DNA samples genotyped by the CompanionDx® lab on the OpenArray platform, 70 samples were identified as heterozygotes for 137Tins, the key SNP of CYP2D6 (*) 15. However, only 15 samples were confirmed when tested with the Luminex xTAG CYP2D6 Kit and sequencing of CYP2D6-specific long range (XL)-PCR products. Genotype and gene resequencing of CYP2D6 and CYP2D7-specific XL-PCR products revealed a CC>GT dinucleotide SNP in exon 1 of CYP2D7 that reverts the sequence to CYP2D6 and allows a TaqMan assay PCR primer to bind. Because CYP2D7 also carries a Tins, a false-positive mutation signal is generated. This CYP2D7 SNP was also responsible for generating false-positive signals for rs769258 (CYP2D6 (*) 35) which is also located in exon 1. Although alternative CYP2D6 (*) 15 and (*) 35 assays resolved the issue, we discovered a novel CYP2D6 (*) 15 subvariant in one sample that carries additional SNPs preventing detection with the alternate assay. The frequency of CYP2D6 (*) 15 was 0.1% in this ethnically diverse U.S. population sample. In addition, we also discovered linkage between the CYP2D7 CC>GT dinucleotide SNP and the 77G>A (rs28371696) SNP of CYP2D6 (*) 43. The frequency of this tentatively functional allele was 0.2%. Taken together, these findings emphasize that regardless of how careful genotyping assays are designed and evaluated before being commercially marketed, rare or unknown SNPs underneath primer
A Model for Improving the Learning Curves of Artificial Neural Networks
2016-01-01
In this article, the performance of a hybrid artificial neural network (i.e. scale-free and small-world) was analyzed and its learning curve compared to three other topologies: random, scale-free and small-world, as well as to the chemotaxis neural network of the nematode Caenorhabditis Elegans. One hundred equivalent networks (same number of vertices and average degree) for each topology were generated and each was trained for one thousand epochs. After comparing the mean learning curves of each network topology with the C. elegans neural network, we found that the networks that exhibited preferential attachment exhibited the best learning curves. PMID:26901646
Mechanical characterization of 2D, 2D stitched, and 3D braided/RTM materials
NASA Technical Reports Server (NTRS)
Deaton, Jerry W.; Kullerd, Susan M.; Portanova, Marc A.
1993-01-01
Braided composite materials have potential for application in aircraft structures. Fuselage frames, floor beams, wing spars, and stiffeners are examples where braided composites could find application if cost effective processing and damage tolerance requirements are met. Another important consideration for braided composites relates to their mechanical properties and how they compare to the properties of composites produced by other textile composite processes being proposed for these applications. Unfortunately, mechanical property data for braided composites do not appear extensively in the literature. Data are presented in this paper on the mechanical characterization of 2D triaxial braid, 2D triaxial braid plus stitching, and 3D (through-the-thickness) braid composite materials. The braided preforms all had the same graphite tow size and the same nominal braid architectures, (+/- 30 deg/0 deg), and were resin transfer molded (RTM) using the same mold for each of two different resin systems. Static data are presented for notched and unnotched tension, notched and unnotched compression, and compression after impact strengths at room temperature. In addition, some static results, after environmental conditioning, are included. Baseline tension and compression fatigue results are also presented, but only for the 3D braided composite material with one of the resin systems.
Gravitational Wave Signals from 2D and 3D Core Collapse Supernova Explosions
NASA Astrophysics Data System (ADS)
Yakunin, Konstantin; Mezzacappa, Anthony; Marronetti, Pedro; Bruenn, Stephen; Hix, W. Raphael; Lentz, Eric J.; Messer, O. E. Bronson; Harris, J. Austin; Endeve, Eirik; Blondin, John
2016-03-01
We study two- and three-dimensional (2D and 3D) core-collapse supernovae (CCSN) using our first-principles CCSN simulations performed with the neutrino hydrodynamics code CHIMERA. The following physics is included: Newtonian hydrodynamics with a nuclear equation of state capable of describing matter in both NSE and non-NSE, MGFLD neutrino transport with realistic neutrino interactions, an effective GR gravitational potential, and a nuclear reaction network. Both our 2D and 3D models achieve explosion, which in turn enables us to determine their complete gravitational wave signals. In this talk, we present them, and we analyze the similarities and differences between the 2D and 3D signals.
Networks model of the East Turkistan terrorism
NASA Astrophysics Data System (ADS)
Li, Ben-xian; Zhu, Jun-fang; Wang, Shun-guo
2015-02-01
The presence of the East Turkistan terrorist network in China can be traced back to the rebellions on the BAREN region in Xinjiang in April 1990. This article intends to research the East Turkistan networks in China and offer a panoramic view. The events, terrorists and their relationship are described using matrices. Then social network analysis is adopted to reveal the network type and the network structure characteristics. We also find the crucial terrorist leader. Ultimately, some results show that the East Turkistan network has big hub nodes and small shortest path, and that the network follows a pattern of small world network with hierarchical structure.
Computational Screening of 2D Materials for Photocatalysis.
Singh, Arunima K; Mathew, Kiran; Zhuang, Houlong L; Hennig, Richard G
2015-03-19
Two-dimensional (2D) materials exhibit a range of extraordinary electronic, optical, and mechanical properties different from their bulk counterparts with potential applications for 2D materials emerging in energy storage and conversion technologies. In this Perspective, we summarize the recent developments in the field of solar water splitting using 2D materials and review a computational screening approach to rapidly and efficiently discover more 2D materials that possess properties suitable for solar water splitting. Computational tools based on density-functional theory can predict the intrinsic properties of potential photocatalyst such as their electronic properties, optical absorbance, and solubility in aqueous solutions. Computational tools enable the exploration of possible routes to enhance the photocatalytic activity of 2D materials by use of mechanical strain, bias potential, doping, and pH. We discuss future research directions and needed method developments for the computational design and optimization of 2D materials for photocatalysis.
NASA Astrophysics Data System (ADS)
Ribeiro, André S.; Almeida, Miguel
2006-10-01
We propose a model of structural organization and intercommunication between all elements of every team involved in the development of a space probe to improve efficiency. Such structure is built to minimize path between any two elements, allowing fast information flow in the structure. Structures are usually very clustered inside each task team but only the heads of departments, or occasional meetings, usually assure the links between team elements. This is responsible for a lack of information exchange between staff members of each team. We propose the establishment of permanent small working groups of staff elements from different teams, in a random but permanent basis. The elements chosen for such connections establishment can be chosen on a temporary basis, but the connections must exist permanently because only with permanent connections can information flow when needed. A few of such random connections between staff members will diminish the average path length, between any two elements of any team, for information exchange. A small world structure will emerge with low internal energy costs, which is the structure used by biological neuronal systems.
NASA Astrophysics Data System (ADS)
Ribeiro, André S.; Almeida, Miguel
2003-11-01
We propose a model of structural organization and intercommunication between all elements of every team involved in the development of a space probe to improve efficiency. Such structure is built to minimize path between any two elements, allowing fast information flow in the structure. Structures are usually very clustered inside each task team but only the heads of departments, or occasional meetings, usually assure the links between team elements. This is responsible for a lack of information exchange between staff members of each team. We propose the establishment of permanent small working groups of staff elements from different teams, in a random but permanent basis. The elements chosen for such connections establishment can be chosen in a temporary basis, but the connections must exist permanently because only with permanent connections can information flow when needed. A few of such random connections between staff members will diminish the average path length, between any two elements of any team, for information exchange. A small world structure will emerge with low internal energy costs, which is the structure used by biological neuronal systems.
Synthetic Covalent and Non-Covalent 2D Materials.
Boott, Charlotte E; Nazemi, Ali; Manners, Ian
2015-11-16
The creation of synthetic 2D materials represents an attractive challenge that is ultimately driven by their prospective uses in, for example, electronics, biomedicine, catalysis, sensing, and as membranes for separation and filtration. This Review illustrates some recent advances in this diverse field with a focus on covalent and non-covalent 2D polymers and frameworks, and self-assembled 2D materials derived from nanoparticles, homopolymers, and block copolymers.
A Geometric Boolean Library for 2D Objects
2006-01-05
The 2D Boolean Library is a collection of C++ classes -- which primarily represent 2D geometric data and relationships, and routines -- which contain algorithms for 2D geometric Boolean operations and utility functions. Classes are provided for 2D points, lines, arcs, edgeuses, loops, surfaces and mask sets. Routines are provided that incorporate the Boolean operations Union(OR), XOR, Intersection and Difference. Various analytical geometry routines and routines for importing and exporting the data in various filemore » formats, are also provided in the library.« less
VizieR Online Data Catalog: The 2dF Galaxy Redshift Survey (2dFGRS) (2dFGRS Team, 1998-2003)
NASA Astrophysics Data System (ADS)
Colless, M.; Dalton, G.; Maddox, S.; Sutherland, W.; Norberg, P.; Cole, S.; Bland-Hawthorn, J.; Bridges, T.; Cannon, R.; Collins, C.; Couch, W.; Cross, N.; Deeley, K.; de Propris, R.; Driver, S. P.; Efstathiou, G.; Ellis, R. S.; Frenk, C. S.; Glazebrook, K.; Jackson, C.; Lahav, O.; Lewis, I.; Lumsden, S.; Madgwick, D.; Peacock, J. A.; Peterson, B. A.; Price, I.; Seaborne, M.; Taylor, K.
2007-11-01
The 2dF Galaxy Redshift Survey (2dFGRS) is a major spectroscopic survey taking full advantage of the unique capabilities of the 2dF facility built by the Anglo-Australian Observatory. The 2dFGRS is integrated with the 2dF QSO survey (2QZ, Cat. VII/241). The 2dFGRS obtained spectra for 245591 objects, mainly galaxies, brighter than a nominal extinction-corrected magnitude limit of bJ=19.45. Reliable (quality>=3) redshifts were obtained for 221414 galaxies. The galaxies cover an area of approximately 1500 square degrees selected from the extended APM Galaxy Survey in three regions: a North Galactic Pole (NGP) strip, a South Galactic Pole (SGP) strip, and random fields scattered around the SGP strip. Redshifts are measured from spectra covering 3600-8000 Angstroms at a two-pixel resolution of 9.0 Angstrom and a median S/N of 13 per pixel. All redshift identifications are visually checked and assigned a quality parameter Q in the range 1-5; Q>=3 redshifts are 98.4% reliable and have an rms uncertainty of 85 km/s. The overall redshift completeness for Q>=3 redshifts is 91.8% but this varies with magnitude from 99% for the brightest galaxies to 90% for objects at the survey limit. The 2dFGRS data base is available on the World Wide Web at http://www.mso.anu.edu.au/2dFGRS/. (6 data files).
Simulation of Cardiac Arrhythmias Using a 2D Heterogeneous Whole Heart Model.
Balakrishnan, Minimol; Chakravarthy, V Srinivasa; Guhathakurta, Soma
2015-01-01
Simulation studies of cardiac arrhythmias at the whole heart level with electrocardiogram (ECG) gives an understanding of how the underlying cell and tissue level changes manifest as rhythm disturbances in the ECG. We present a 2D whole heart model (WHM2D) which can accommodate variations at the cellular level and can generate the ECG waveform. It is shown that, by varying cellular-level parameters like the gap junction conductance (GJC), excitability, action potential duration (APD) and frequency of oscillations of the auto-rhythmic cell in WHM2D a large variety of cardiac arrhythmias can be generated including sinus tachycardia, sinus bradycardia, sinus arrhythmia, sinus pause, junctional rhythm, Wolf Parkinson White syndrome and all types of AV conduction blocks. WHM2D includes key components of the electrical conduction system of the heart like the SA (Sino atrial) node cells, fast conducting intranodal pathways, slow conducting atriovenctricular (AV) node, bundle of His cells, Purkinje network, atrial, and ventricular myocardial cells. SA nodal cells, AV nodal cells, bundle of His cells, and Purkinje cells are represented by the Fitzhugh-Nagumo (FN) model which is a reduced model of the Hodgkin-Huxley neuron model. The atrial and ventricular myocardial cells are modeled by the Aliev-Panfilov (AP) two-variable model proposed for cardiac excitation. WHM2D can prove to be a valuable clinical tool for understanding cardiac arrhythmias.
Simulation of Cardiac Arrhythmias Using a 2D Heterogeneous Whole Heart Model
Balakrishnan, Minimol; Chakravarthy, V. Srinivasa; Guhathakurta, Soma
2015-01-01
Simulation studies of cardiac arrhythmias at the whole heart level with electrocardiogram (ECG) gives an understanding of how the underlying cell and tissue level changes manifest as rhythm disturbances in the ECG. We present a 2D whole heart model (WHM2D) which can accommodate variations at the cellular level and can generate the ECG waveform. It is shown that, by varying cellular-level parameters like the gap junction conductance (GJC), excitability, action potential duration (APD) and frequency of oscillations of the auto-rhythmic cell in WHM2D a large variety of cardiac arrhythmias can be generated including sinus tachycardia, sinus bradycardia, sinus arrhythmia, sinus pause, junctional rhythm, Wolf Parkinson White syndrome and all types of AV conduction blocks. WHM2D includes key components of the electrical conduction system of the heart like the SA (Sino atrial) node cells, fast conducting intranodal pathways, slow conducting atriovenctricular (AV) node, bundle of His cells, Purkinje network, atrial, and ventricular myocardial cells. SA nodal cells, AV nodal cells, bundle of His cells, and Purkinje cells are represented by the Fitzhugh-Nagumo (FN) model which is a reduced model of the Hodgkin-Huxley neuron model. The atrial and ventricular myocardial cells are modeled by the Aliev-Panfilov (AP) two-variable model proposed for cardiac excitation. WHM2D can prove to be a valuable clinical tool for understanding cardiac arrhythmias. PMID:26733873
2-D Path Corrections for Local and Regional Coda Waves: A Test of Transportability
Mayeda, K M; Malagnini, L; Phillips, W S; Walter, W R; Dreger, D S; Morasca, P
2005-07-13
Reliable estimates of the seismic source spectrum are necessary for accurate magnitude, yield, and energy estimation. In particular, how seismic radiated energy scales with increasing earthquake size has been the focus of recent debate within the community and has direct implications on earthquake source physics studies as well as hazard mitigation. The 1-D coda methodology of Mayeda et al. [2003] has provided the lowest variance estimate of the source spectrum when compared against traditional approaches that use direct S-waves, thus making it ideal for networks that have sparse station distribution. The 1-D coda methodology has been mostly confined to regions of approximately uniform complexity. For larger, more geophysically complicated regions, 2-D path corrections may be required. We will compare performance of 1-D versus 2-D path corrections in a variety of regions. First, the complicated tectonics of the northern California region coupled with high quality broadband seismic data provides for an ideal ''apples-to-apples'' test of 1-D and 2-D path assumptions on direct waves and their coda. Next, we will compare results for the Italian Alps using high frequency data from the University of Genoa. For Northern California, we used the same station and event distribution and compared 1-D and 2-D path corrections and observed the following results: (1) 1-D coda results reduced the amplitude variance relative to direct S-waves by roughly a factor of 8 (800%); (2) Applying a 2-D correction to the coda resulted in up to 40% variance reduction from the 1-D coda results; (3) 2-D direct S-wave results, though better than 1-D direct waves, were significantly worse than the 1-D coda. We found that coda-based moment-rate source spectra derived from the 2-D approach were essentially identical to those from the 1-D approach for frequencies less than {approx}0.7-Hz, however for the high frequencies (0.7 {le} f {le} 8.0-Hz), the 2-D approach resulted in inter-station scatter
Responsive ionic liquid-polymer 2D photonic crystal gas sensors.
Smith, Natasha L; Hong, Zhenmin; Asher, Sanford A
2014-12-21
We developed novel air-stable 2D polymerized photonic crystal (2DPC) sensing materials for visual detection of gas phase analytes such as water and ammonia by utilizing a new ionic liquid, ethylguanidine perchlorate (EGP) as the mobile phase. Because of the negligible ionic liquid vapor pressure these 2DPC sensors are indefinitely air stable and, therefore, can be used to sense atmospheric analytes. 2D arrays of ~640 nm polystyrene nanospheres were attached to the surface of crosslinked poly(hydroxyethyl methacrylate) (pHEMA)-based polymer networks dispersed in EGP. The wavelength of the bright 2D photonic crystal diffraction depends sensitively on the 2D array particle spacing. The volume phase transition response of the EGP-pHEMA system to water vapor or gaseous ammonia changes the 2DPC particle spacing, enabling the visual determination of the analyte concentration. Water absorbed by EGP increases the Flory-Huggins interaction parameter, which shrinks the polymer network and causes a blue shift in the diffracted light. Ammonia absorbed by the EGP deprotonates the pHEMA-co-acrylic acid carboxyl groups, swelling the polymer which red shifts the diffracted light.
KPLS-RWBFNN model for MFL 2D defect profile reconstruction
NASA Astrophysics Data System (ADS)
Xu, Chao; Wang, Changlong; Ji, Fengzhu
2013-03-01
Kernel partial least squares (KPLS) is normally very efficient for tackling nonlinear systems by mapping an original input space into a high-dimensional feature space and creating a linear PLS model in the feature space. Unlike other nonlinear PLS techniques, KPLS does not entail any nonlinear optimisation procedures. However, due to the linear inner model of PLS, KPLS is still inappropriate for describing the significant nonlinear characteristic data structure while dealing with complex physical systems in practical situations. Under this circumstance, radial wavelet basic function neural network (RWBFNN) can replace the linear inner model of PLS in the nonlinear kernel-based algorithm. Thus, KPLS-RWBFNN model is proposed in this paper and applied to multi-resolution approximation reconstruction of 2D defect profiles in magnetic flux leakage testing. The reconstructions of 2D defect profiles by this method are implemented, and the comparisons among reconstructions by KPLS, RWBFNN and the proposed approach are also undertaken. Meanwhile, the reconstructions of 2D defects by RWBFNN and the proposed approach at different SNR are also executed. The results indicate that KPLS-RWBFNN model could simplify the structure of the network while holding well-behaved generalisation and multi-resolution approximation and predict the 2D defect profiles accurately and rapidly with good robustness.
Photo-electroactive ternary chalcogenido-indate-stannates with a unique 2-D porous structure.
Wu, Jing; Pu, Ya-Yang; Zhao, Xiao-Wei; Qian, Li-Wen; Bian, Guo-Qing; Zhu, Qin-Yu; Dai, Jie
2015-03-14
A lot of ternary In-Sb-Q (Q = S, Se) chalcogenido-metalates with amines or complex cations have been recently reported for their diverse structures, however, such a type of In-Sn-Q chalcogenido-metalate has been rarely announced. Herein, we report a series of 2-D In-Sn-Q compounds prepared using a metal-phenanthroline cationic template, [M(Phen)3](In2Sn2Q8)·(amine)·nH2O (M = Ni(II), Fe(II) or Co(II); amine = cyclohexylamine (Cha) or 1,6-diaminohexane (Dah); Q = S or Se). Their anions are isostructural and a 2-D porous network with large 16-tetrahedron-rings. The 2-D network joint of In-Sn-Q is a (In/Sn)3Q3 six-membered ring, which is different from the Sn3Q4 pseudosemicube of most 2-D Sn-Q binary compounds. The materials exhibit photocurrent response properties measured using a photo-electrochemical cell. The result shows that (1) the selenides exhibit more intense photocurrents than the sulfides and (2) the current intensity is related to the metal-phenanthroline cations. PMID:25653182
Klassifikation von Standardebenen in der 2D-Echokardiographie mittels 2D-3D-Bildregistrierung
NASA Astrophysics Data System (ADS)
Bergmeir, Christoph; Subramanian, Navneeth
Zum Zweck der Entwicklung eines Systems, das einen unerfahrenen Anwender von Ultraschall (US) zur Aufnahme relevanter anatomischer Strukturen leitet, untersuchen wir die Machbarkeit von 2D-US zu 3D-CT Registrierung. Wir verwenden US-Aufnahmen von Standardebenen des Herzens, welche zu einem 3D-CT-Modell registriert werden. Unser Algorithmus unterzieht sowohl die US-Bilder als auch den CT-Datensatz Vorverarbeitungsschritten, welche die Daten durch Segmentierung auf wesentliche Informationen in Form von Labein für Muskel und Blut reduzieren. Anschließend werden diese Label zur Registrierung mittels der Match-Cardinality-Metrik genutzt. Durch mehrmaliges Registrieren mit verschiedenen Initialisierungen ermitteln wir die im US-Bild sichtbare Standardebene. Wir evaluierten die Methode auf sieben US-Bildern von Standardebenen. Fünf davon wurden korrekt zugeordnet.
Epitaxial 2D SnSe2/ 2D WSe2 van der Waals Heterostructures.
Aretouli, Kleopatra Emmanouil; Tsoutsou, Dimitra; Tsipas, Polychronis; Marquez-Velasco, Jose; Aminalragia Giamini, Sigiava; Kelaidis, Nicolaos; Psycharis, Vassilis; Dimoulas, Athanasios
2016-09-01
van der Waals heterostructures of 2D semiconductor materials can be used to realize a number of (opto)electronic devices including tunneling field effect devices (TFETs). It is shown in this work that high quality SnSe2/WSe2 vdW heterostructure can be grown by molecular beam epitaxy on AlN(0001)/Si(111) substrates using a Bi2Se3 buffer layer. A valence band offset of 0.8 eV matches the energy gap of SnSe2 in such a way that the VB edge of WSe2 and the CB edge of SnSe2 are lined up, making this materials combination suitable for (nearly) broken gap TFETs. PMID:27537619
CVMAC 2D Program: A method of converting 3D to 2D
Lown, J.
1990-06-20
This paper presents the user with a method of converting a three- dimensional wire frame model into a technical illustration, detail, or assembly drawing. By using the 2D Program, entities can be mapped from three-dimensional model space into two-dimensional model space, as if they are being traced. Selected entities to be mapped can include circles, arcs, lines, and points. This program prompts the user to digitize the view to be mapped, specify the layers in which the new two-dimensional entities will reside, and select the entities, either by digitizing or windowing. The new two-dimensional entities are displayed in a small view which the program creates in the lower left corner of the drawing. 9 figs.
2D Four-Channel Perfect Reconstruction Filter Bank Realized with the 2D Lattice Filter Structure
NASA Astrophysics Data System (ADS)
Sezen, S.; Ertüzün, A.
2006-12-01
A novel orthogonal 2D lattice structure is incorporated into the design of a nonseparable 2D four-channel perfect reconstruction filter bank. The proposed filter bank is obtained by using the polyphase decomposition technique which requires the design of an orthogonal 2D lattice filter. Due to constraint of perfect reconstruction, each stage of this lattice filter bank is simply parameterized by two coefficients. The perfect reconstruction property is satisfied regardless of the actual values of these parameters and of the number of the lattice stages. It is also shown that a separable 2D four-channel perfect reconstruction lattice filter bank can be constructed from the 1D lattice filter and that this is a special case of the proposed 2D lattice filter bank under certain conditions. The perfect reconstruction property of the proposed 2D lattice filter approach is verified by computer simulations.
Functional characterization of CYP2D6 enhancer polymorphisms
Wang, Danxin; Papp, Audrey C.; Sun, Xiaochun
2015-01-01
CYP2D6 metabolizes nearly 25% of clinically used drugs. Genetic polymorphisms cause large inter-individual variability in CYP2D6 enzyme activity and are currently used as biomarker to predict CYP2D6 metabolizer phenotype. Previously, we had identified a region 115 kb downstream of CYP2D6 as enhancer for CYP2D6, containing two completely linked single nucleotide polymorphisms (SNPs), rs133333 and rs5758550, associated with enhanced transcription. However, the enhancer effect on CYP2D6 expression, and the causative variant, remained to be ascertained. To characterize the CYP2D6 enhancer element, we applied chromatin conformation capture combined with the next-generation sequencing (4C assays) and chromatin immunoprecipitation with P300 antibody, in HepG2 and human primary culture hepatocytes. The results confirmed the role of the previously identified enhancer region in CYP2D6 expression, expanding the number of candidate variants to three highly linked SNPs (rs133333, rs5758550 and rs4822082). Among these, only rs5758550 demonstrated regulating enhancer activity in a reporter gene assay. Use of clustered regularly interspaced short palindromic repeats mediated genome editing in HepG2 cells targeting suspected enhancer regions decreased CYP2D6 mRNA expression by 70%, only upon deletion of the rs5758550 region. These results demonstrate robust effects of both the enhancer element and SNP rs5758550 on CYP2D6 expression, supporting consideration of rs5758550 for CYP2D6 genotyping panels to yield more accurate phenotype prediction. PMID:25381333
NASA Astrophysics Data System (ADS)
Chae, Dongho; Constantin, Peter; Wu, Jiahong
2014-09-01
We give an example of a well posed, finite energy, 2D incompressible active scalar equation with the same scaling as the surface quasi-geostrophic equation and prove that it can produce finite time singularities. In spite of its simplicity, this seems to be the first such example. Further, we construct explicit solutions of the 2D Boussinesq equations whose gradients grow exponentially in time for all time. In addition, we introduce a variant of the 2D Boussinesq equations which is perhaps a more faithful companion of the 3D axisymmetric Euler equations than the usual 2D Boussinesq equations.
Integrating Mobile Multimedia into Textbooks: 2D Barcodes
ERIC Educational Resources Information Center
Uluyol, Celebi; Agca, R. Kagan
2012-01-01
The major goal of this study was to empirically compare text-plus-mobile phone learning using an integrated 2D barcode tag in a printed text with three other conditions described in multimedia learning theory. The method examined in the study involved modifications of the instructional material such that: a 2D barcode was used near the text, the…
Efficient Visible Quasi-2D Perovskite Light-Emitting Diodes.
Byun, Jinwoo; Cho, Himchan; Wolf, Christoph; Jang, Mi; Sadhanala, Aditya; Friend, Richard H; Yang, Hoichang; Lee, Tae-Woo
2016-09-01
Efficient quasi-2D-structure perovskite light-emitting diodes (4.90 cd A(-1) ) are demonstrated by mixing a 3D-structured perovskite material (methyl ammonium lead bromide) and a 2D-structured perovskite material (phenylethyl ammonium lead bromide), which can be ascribed to better film uniformity, enhanced exciton confinement, and reduced trap density. PMID:27334788
CYP2D6: novel genomic structures and alleles
Kramer, Whitney E.; Walker, Denise L.; O’Kane, Dennis J.; Mrazek, David A.; Fisher, Pamela K.; Dukek, Brian A.; Bruflat, Jamie K.; Black, John L.
2010-01-01
Objective CYP2D6 is a polymorphic gene. It has been observed to be deleted, to be duplicated and to undergo recombination events involving the CYP2D7 pseudogene and surrounding sequences. The objective of this study was to discover the genomic structure of CYP2D6 recombinants that interfere with clinical genotyping platforms that are available today. Methods Clinical samples containing rare homozygous CYP2D6 alleles, ambiguous readouts, and those with duplication signals and two different alleles were analyzed by long-range PCR amplification of individual genes, PCR fragment analysis, allele-specific primer extension assay, and DNA sequencing to characterize alleles and genomic structure. Results Novel alleles, genomic structures, and the DNA sequence of these structures are described. Interestingly, in 49 of 50 DNA samples that had CYP2D6 gene duplications or multiplications where two alleles were detected, the chromosome containing the duplication or multiplication had identical tandem alleles. Conclusion Several new CYP2D6 alleles and genomic structures are described which will be useful for CYP2D6 genotyping. The findings suggest that the recombination events responsible for CYP2D6 duplications and multiplications are because of mechanisms other than interchromosomal crossover during meiosis. PMID:19741566
Efficient Visible Quasi-2D Perovskite Light-Emitting Diodes.
Byun, Jinwoo; Cho, Himchan; Wolf, Christoph; Jang, Mi; Sadhanala, Aditya; Friend, Richard H; Yang, Hoichang; Lee, Tae-Woo
2016-09-01
Efficient quasi-2D-structure perovskite light-emitting diodes (4.90 cd A(-1) ) are demonstrated by mixing a 3D-structured perovskite material (methyl ammonium lead bromide) and a 2D-structured perovskite material (phenylethyl ammonium lead bromide), which can be ascribed to better film uniformity, enhanced exciton confinement, and reduced trap density.
2D materials and van der Waals heterostructures.
Novoselov, K S; Mishchenko, A; Carvalho, A; Castro Neto, A H
2016-07-29
The physics of two-dimensional (2D) materials and heterostructures based on such crystals has been developing extremely fast. With these new materials, truly 2D physics has begun to appear (for instance, the absence of long-range order, 2D excitons, commensurate-incommensurate transition, etc.). Novel heterostructure devices--such as tunneling transistors, resonant tunneling diodes, and light-emitting diodes--are also starting to emerge. Composed from individual 2D crystals, such devices use the properties of those materials to create functionalities that are not accessible in other heterostructures. Here we review the properties of novel 2D crystals and examine how their properties are used in new heterostructure devices.
Van der Waals stacked 2D layered materials for optoelectronics
NASA Astrophysics Data System (ADS)
Zhang, Wenjing; Wang, Qixing; Chen, Yu; Wang, Zhuo; Wee, Andrew T. S.
2016-06-01
The band gaps of many atomically thin 2D layered materials such as graphene, black phosphorus, monolayer semiconducting transition metal dichalcogenides and hBN range from 0 to 6 eV. These isolated atomic planes can be reassembled into hybrid heterostructures made layer by layer in a precisely chosen sequence. Thus, the electronic properties of 2D materials can be engineered by van der Waals stacking, and the interlayer coupling can be tuned, which opens up avenues for creating new material systems with rich functionalities and novel physical properties. Early studies suggest that van der Waals stacked 2D materials work exceptionally well, dramatically enriching the optoelectronics applications of 2D materials. Here we review recent progress in van der Waals stacked 2D materials, and discuss their potential applications in optoelectronics.
Estrogen-Induced Cholestasis Leads to Repressed CYP2D6 Expression in CYP2D6-Humanized Mice
Pan, Xian
2015-01-01
Cholestasis activates bile acid receptor farnesoid X receptor (FXR) and subsequently enhances hepatic expression of small heterodimer partner (SHP). We previously demonstrated that SHP represses the transactivation of cytochrome P450 2D6 (CYP2D6) promoter by hepatocyte nuclear factor (HNF) 4α. In this study, we investigated the effects of estrogen-induced cholestasis on CYP2D6 expression. Estrogen-induced cholestasis occurs in subjects receiving estrogen for contraception or hormone replacement, or in susceptible women during pregnancy. In CYP2D6-humanized transgenic (Tg-CYP2D6) mice, cholestasis triggered by administration of 17α-ethinylestradiol (EE2) at a high dose led to 2- to 3-fold decreases in CYP2D6 expression. This was accompanied by increased hepatic SHP expression and subsequent decreases in the recruitment of HNF4α to CYP2D6 promoter. Interestingly, estrogen-induced cholestasis also led to increased recruitment of estrogen receptor (ER) α, but not that of FXR, to Shp promoter, suggesting a predominant role of ERα in transcriptional regulation of SHP in estrogen-induced cholestasis. EE2 at a low dose (that does not cause cholestasis) also increased SHP (by ∼50%) and decreased CYP2D6 expression (by 1.5-fold) in Tg-CYP2D6 mice, the magnitude of differences being much smaller than that shown in EE2-induced cholestasis. Taken together, our data indicate that EE2-induced cholestasis increases SHP and represses CYP2D6 expression in Tg-CYP2D6 mice in part through ERα transactivation of Shp promoter. PMID:25943116
Disrupted cortical network as a vulnerability marker for obsessive-compulsive disorder.
Peng, Ziwen; Shi, Feng; Shi, Changzheng; Yang, Qiong; Chan, Raymond C K; Shen, Dinggang
2014-09-01
Morphological alterations of brain structure are generally assumed to be involved in the pathophysiology of obsessive–compulsive disorder (OCD). Yet, little is known about the morphological connectivity properties of structural brain networks in OCD or about the heritability of those morphological connectivity properties. To better understand these properties, we conducted a study that defined three different groups: OCD group with 30 subjects, siblings group with 19 subjects, and matched controls group with 30 subjects. A structural brain network was constructed using 68 cortical regions of each subject within their respective group (i.e., one brain network for each group). Both small-worldness and modularity were measured to reflect the morphological connectivity properties of each constructed structural brain network. When compared to the matched controls, the structural brain networks of patients with OCD indeed exhibited atypical small-worldness and modularity. Specifically, small-worldness showed decreased local efficiency, and modularity showed reduced intra-connectivity in Module III (default mode network) and increased interconnectivity between Module I (executive function) and Module II (cognitive control/spatial). Intriguingly, the structured brain networks of the unaffected siblings showed similar small-worldness and modularity as OCD patients. Based on the atypical structural brain networks observed in OCD patients and their unaffected siblings, abnormal small-worldness and modularity may indicate a candidate endophenotype for OCD.
Monomer-dimer problem on some networks
NASA Astrophysics Data System (ADS)
Wu, Ruijuan; Yan, Weigen
2016-09-01
Zhang et al. (2012) obtained the exact formula for the number of all possible monomer-dimer arrangements and the asymptotic growth constant on a scale-free small-world network. In this note, we generalize this result and obtain the exact solution on the monomer-dimer model on many networks. Particularly, we prove that these networks have the same asymptotic growth constant of the number of monomer-dimer arrangements.
Xie, Donghao; Ji, Ding-Kun; Zhang, Yue; Cao, Jun; Zheng, Hu; Liu, Lin; Zang, Yi; Li, Jia; Chen, Guo-Rong; James, Tony D; He, Xiao-Peng
2016-08-01
Here we demonstrate that 2D MoS2 can enhance the receptor-targeting and imaging ability of a fluorophore-labelled ligand. The 2D MoS2 has an enhanced working concentration range when compared with graphene oxide, resulting in the improved imaging of both cell and tissue samples.
A comparison of 1D and 2D LSTM architectures for the recognition of handwritten Arabic
NASA Astrophysics Data System (ADS)
Yousefi, Mohammad Reza; Soheili, Mohammad Reza; Breuel, Thomas M.; Stricker, Didier
2015-01-01
In this paper, we present an Arabic handwriting recognition method based on recurrent neural network. We use the Long Short Term Memory (LSTM) architecture, that have proven successful in different printed and handwritten OCR tasks. Applications of LSTM for handwriting recognition employ the two-dimensional architecture to deal with the variations in both vertical and horizontal axis. However, we show that using a simple pre-processing step that normalizes the position and baseline of letters, we can make use of 1D LSTM, which is faster in learning and convergence, and yet achieve superior performance. In a series of experiments on IFN/ENIT database for Arabic handwriting recognition, we demonstrate that our proposed pipeline can outperform 2D LSTM networks. Furthermore, we provide comparisons with 1D LSTM networks trained with manually crafted features to show that the automatically learned features in a globally trained 1D LSTM network with our normalization step can even outperform such systems.
Efficient 2D MRI relaxometry using compressed sensing
NASA Astrophysics Data System (ADS)
Bai, Ruiliang; Cloninger, Alexander; Czaja, Wojciech; Basser, Peter J.
2015-06-01
Potential applications of 2D relaxation spectrum NMR and MRI to characterize complex water dynamics (e.g., compartmental exchange) in biology and other disciplines have increased in recent years. However, the large amount of data and long MR acquisition times required for conventional 2D MR relaxometry limits its applicability for in vivo preclinical and clinical MRI. We present a new MR pipeline for 2D relaxometry that incorporates compressed sensing (CS) as a means to vastly reduce the amount of 2D relaxation data needed for material and tissue characterization without compromising data quality. Unlike the conventional CS reconstruction in the Fourier space (k-space), the proposed CS algorithm is directly applied onto the Laplace space (the joint 2D relaxation data) without compressing k-space to reduce the amount of data required for 2D relaxation spectra. This framework is validated using synthetic data, with NMR data acquired in a well-characterized urea/water phantom, and on fixed porcine spinal cord tissue. The quality of the CS-reconstructed spectra was comparable to that of the conventional 2D relaxation spectra, as assessed using global correlation, local contrast between peaks, peak amplitude and relaxation parameters, etc. This result brings this important type of contrast closer to being realized in preclinical, clinical, and other applications.
Practical Algorithm For Computing The 2-D Arithmetic Fourier Transform
NASA Astrophysics Data System (ADS)
Reed, Irving S.; Choi, Y. Y.; Yu, Xiaoli
1989-05-01
Recently, Tufts and Sadasiv [10] exposed a method for computing the coefficients of a Fourier series of a periodic function using the Mobius inversion of series. They called this method of analysis the Arithmetic Fourier Transform(AFT). The advantage of the AFT over the FN 1' is that this method of Fourier analysis needs only addition operations except for multiplications by scale factors at one stage of the computation. The disadvantage of the AFT as they expressed it originally is that it could be used effectively only to compute finite Fourier coefficients of a real even function. To remedy this the AFT developed in [10] is extended in [11] to compute the Fourier coefficients of both the even and odd components of a periodic function. In this paper, the improved AFT [11] is extended to a two-dimensional(2-D) Arithmetic Fourier Transform for calculating the Fourier Transform of two-dimensional discrete signals. This new algorithm is based on both the number-theoretic method of Mobius inversion of double series and the complex conjugate property of Fourier coefficients. The advantage of this algorithm over the conventional 2-D FFT is that the corner-turning problem needed in a conventional 2-D Discrete Fourier Transform(DFT) can be avoided. Therefore, this new 2-D algorithm is readily suitable for VLSI implementation as a parallel architecture. Comparing the operations of 2-D AFT of a MxM 2-D data array with the conventional 2-D FFT, the number of multiplications is significantly reduced from (2log2M)M2 to (9/4)M2. Hence, this new algorithm is faster than the FFT algorithm. Finally, two simulation results of this new 2-D AFT algorithm for 2-D artificial and real images are given in this paper.
Statistical mechanics of complex networks
NASA Astrophysics Data System (ADS)
Albert, Réka; Barabási, Albert-László
2002-01-01
Complex networks describe a wide range of systems in nature and society. Frequently cited examples include the cell, a network of chemicals linked by chemical reactions, and the Internet, a network of routers and computers connected by physical links. While traditionally these systems have been modeled as random graphs, it is increasingly recognized that the topology and evolution of real networks are governed by robust organizing principles. This article reviews the recent advances in the field of complex networks, focusing on the statistical mechanics of network topology and dynamics. After reviewing the empirical data that motivated the recent interest in networks, the authors discuss the main models and analytical tools, covering random graphs, small-world and scale-free networks, the emerging theory of evolving networks, and the interplay between topology and the network's robustness against failures and attacks.
2D electron cyclotron emission imaging at ASDEX Upgrade (invited)
Classen, I. G. J.; Boom, J. E.; Vries, P. C. de; Suttrop, W.; Schmid, E.; Garcia-Munoz, M.; Schneider, P. A.; Tobias, B.; Domier, C. W.; Luhmann, N. C. Jr.; Donne, A. J. H.; Jaspers, R. J. E.; Park, H. K.; Munsat, T.
2010-10-15
The newly installed electron cyclotron emission imaging diagnostic on ASDEX Upgrade provides measurements of the 2D electron temperature dynamics with high spatial and temporal resolution. An overview of the technical and experimental properties of the system is presented. These properties are illustrated by the measurements of the edge localized mode and the reversed shear Alfven eigenmode, showing both the advantage of having a two-dimensional (2D) measurement, as well as some of the limitations of electron cyclotron emission measurements. Furthermore, the application of singular value decomposition as a powerful tool for analyzing and filtering 2D data is presented.
Comparison of 2D and 3D gamma analyses
Pulliam, Kiley B.; Huang, Jessie Y.; Howell, Rebecca M.; Followill, David; Kry, Stephen F.; Bosca, Ryan; O’Daniel, Jennifer
2014-02-15
Purpose: As clinics begin to use 3D metrics for intensity-modulated radiation therapy (IMRT) quality assurance, it must be noted that these metrics will often produce results different from those produced by their 2D counterparts. 3D and 2D gamma analyses would be expected to produce different values, in part because of the different search space available. In the present investigation, the authors compared the results of 2D and 3D gamma analysis (where both datasets were generated in the same manner) for clinical treatment plans. Methods: Fifty IMRT plans were selected from the authors’ clinical database, and recalculated using Monte Carlo. Treatment planning system-calculated (“evaluated dose distributions”) and Monte Carlo-recalculated (“reference dose distributions”) dose distributions were compared using 2D and 3D gamma analysis. This analysis was performed using a variety of dose-difference (5%, 3%, 2%, and 1%) and distance-to-agreement (5, 3, 2, and 1 mm) acceptance criteria, low-dose thresholds (5%, 10%, and 15% of the prescription dose), and data grid sizes (1.0, 1.5, and 3.0 mm). Each comparison was evaluated to determine the average 2D and 3D gamma, lower 95th percentile gamma value, and percentage of pixels passing gamma. Results: The average gamma, lower 95th percentile gamma value, and percentage of passing pixels for each acceptance criterion demonstrated better agreement for 3D than for 2D analysis for every plan comparison. The average difference in the percentage of passing pixels between the 2D and 3D analyses with no low-dose threshold ranged from 0.9% to 2.1%. Similarly, using a low-dose threshold resulted in a difference between the mean 2D and 3D results, ranging from 0.8% to 1.5%. The authors observed no appreciable differences in gamma with changes in the data density (constant difference: 0.8% for 2D vs 3D). Conclusions: The authors found that 3D gamma analysis resulted in up to 2.9% more pixels passing than 2D analysis. It must
Recent advances in 2D materials for photocatalysis.
Luo, Bin; Liu, Gang; Wang, Lianzhou
2016-04-01
Two-dimensional (2D) materials have attracted increasing attention for photocatalytic applications because of their unique thickness dependent physical and chemical properties. This review gives a brief overview of the recent developments concerning the chemical synthesis and structural design of 2D materials at the nanoscale and their applications in photocatalytic areas. In particular, recent progress on the emerging strategies for tailoring 2D material-based photocatalysts to improve their photo-activity including elemental doping, heterostructure design and functional architecture assembly is discussed.
NASA Astrophysics Data System (ADS)
Liu, Fu-Jing; Sun, Di; Li, Yun-Hua; Hao, Hong-Jun; Huang, Rong-Bin; Zheng, Lan-Sun
2011-07-01
Two isomers of the aminobenzonitrile were reacted with Ag 2O and phthalic acid under ultrasonic condition, yielding two coordination polymers (CPs) of the formula [Ag 2( o-abn)(pa)] n ( 1) and [Ag 4( m-abn)(pa) 2] n ( 2). They have been characterized by elemental analysis, IR spectrum and single crystal X-ray diffraction. Both complexes 1 and 2 are 2D sheet structures which contain two different Ag(I) aggregates, 1D silver helical chain and 2D silver sheet for 1 and 2, respectively. The o-abn in 1 adopts a rare tridentate μ 3- N, N' N' mode to bridge the neighboring 1D silver chains to form a 2D coordination network, while the m-abn ligand just acts as a monodentate N-donor in 2 and does not contribute to the extension of the 2D silver sheet to the higher dimensionality. As the change of the relative position of amino and cyano groups of the aminobenzonitrile ligand, the dimensionality of the Ag(I) aggregates in 1 and 2 increases from 1D to 2D, which indicates that the relative positions of amino and cyano groups of aminobenzonitrile play an important role in the formation of the diverse Ag(I) aggregates, as a consequence, different 2D coordination networks are produced. Additionally, results about emissive behaviors and thermal stabilities of them are discussed.
Shin, Keun-Young; Kim, Minkyu; Lee, James S; Jang, Jyongsik
2015-01-01
Highly omnidirectional and frequency controllable carbon/polyaniline (C/PANI)-based, two- (2D) and three-dimensional (3D) monopole antennas were fabricated using screen-printing and a one-step, dimensionally confined hydrothermal strategy, respectively. Solvated C/PANI was synthesized by low-temperature interfacial polymerization, during which strong π-π interactions between graphene and the quinoid rings of PANI resulted in an expanded PANI conformation with enhanced crystallinity and improved mechanical and electrical properties. Compared to antennas composed of pristine carbon or PANI-based 2D monopole structures, 2D monopole antennas composed of this enhanced hybrid material were highly efficient and amenable to high-frequency, omnidirectional electromagnetic waves. The mean frequency of C/PANI fiber-based 3D monopole antennas could be controlled by simply cutting and stretching the antenna. These antennas attained high peak gain (3.60 dBi), high directivity (3.91 dBi) and radiation efficiency (92.12%) relative to 2D monopole antenna. These improvements were attributed the high packing density and aspect ratios of C/PANI fibers and the removal of the flexible substrate. This approach offers a valuable and promising tool for producing highly omnidirectional and frequency-controllable, carbon-based monopole antennas for use in wireless networking communications on industrial, scientific, and medical (ISM) bands. PMID:26338090
Shin, Keun-Young; Kim, Minkyu; Lee, James S.; Jang, Jyongsik
2015-01-01
Highly omnidirectional and frequency controllable carbon/polyaniline (C/PANI)-based, two- (2D) and three-dimensional (3D) monopole antennas were fabricated using screen-printing and a one-step, dimensionally confined hydrothermal strategy, respectively. Solvated C/PANI was synthesized by low-temperature interfacial polymerization, during which strong π–π interactions between graphene and the quinoid rings of PANI resulted in an expanded PANI conformation with enhanced crystallinity and improved mechanical and electrical properties. Compared to antennas composed of pristine carbon or PANI-based 2D monopole structures, 2D monopole antennas composed of this enhanced hybrid material were highly efficient and amenable to high-frequency, omnidirectional electromagnetic waves. The mean frequency of C/PANI fiber-based 3D monopole antennas could be controlled by simply cutting and stretching the antenna. These antennas attained high peak gain (3.60 dBi), high directivity (3.91 dBi) and radiation efficiency (92.12%) relative to 2D monopole antenna. These improvements were attributed the high packing density and aspect ratios of C/PANI fibers and the removal of the flexible substrate. This approach offers a valuable and promising tool for producing highly omnidirectional and frequency-controllable, carbon-based monopole antennas for use in wireless networking communications on industrial, scientific, and medical (ISM) bands. PMID:26338090
NASA Astrophysics Data System (ADS)
Shin, Keun-Young; Kim, Minkyu; Lee, James S.; Jang, Jyongsik
2015-09-01
Highly omnidirectional and frequency controllable carbon/polyaniline (C/PANI)-based, two- (2D) and three-dimensional (3D) monopole antennas were fabricated using screen-printing and a one-step, dimensionally confined hydrothermal strategy, respectively. Solvated C/PANI was synthesized by low-temperature interfacial polymerization, during which strong π-π interactions between graphene and the quinoid rings of PANI resulted in an expanded PANI conformation with enhanced crystallinity and improved mechanical and electrical properties. Compared to antennas composed of pristine carbon or PANI-based 2D monopole structures, 2D monopole antennas composed of this enhanced hybrid material were highly efficient and amenable to high-frequency, omnidirectional electromagnetic waves. The mean frequency of C/PANI fiber-based 3D monopole antennas could be controlled by simply cutting and stretching the antenna. These antennas attained high peak gain (3.60 dBi), high directivity (3.91 dBi) and radiation efficiency (92.12%) relative to 2D monopole antenna. These improvements were attributed the high packing density and aspect ratios of C/PANI fibers and the removal of the flexible substrate. This approach offers a valuable and promising tool for producing highly omnidirectional and frequency-controllable, carbon-based monopole antennas for use in wireless networking communications on industrial, scientific, and medical (ISM) bands.
Alloyed 2D Metal-Semiconductor Atomic Layer Junctions.
Kim, Ah Ra; Kim, Yonghun; Nam, Jaewook; Chung, Hee-Suk; Kim, Dong Jae; Kwon, Jung-Dae; Park, Sang Won; Park, Jucheol; Choi, Sun Young; Lee, Byoung Hun; Park, Ji Hyeon; Lee, Kyu Hwan; Kim, Dong-Ho; Choi, Sung Mook; Ajayan, Pulickel M; Hahm, Myung Gwan; Cho, Byungjin
2016-03-01
Heterostructures of compositionally and electronically variant two-dimensional (2D) atomic layers are viable building blocks for ultrathin optoelectronic devices. We show that the composition of interfacial transition region between semiconducting WSe2 atomic layer channels and metallic NbSe2 contact layers can be engineered through interfacial doping with Nb atoms. WxNb1-xSe2 interfacial regions considerably lower the potential barrier height of the junction, significantly improving the performance of the corresponding WSe2-based field-effect transistor devices. The creation of such alloyed 2D junctions between dissimilar atomic layer domains could be the most important factor in controlling the electronic properties of 2D junctions and the design and fabrication of 2D atomic layer devices.
Emerging and potential opportunities for 2D flexible nanoelectronics
NASA Astrophysics Data System (ADS)
Zhu, Weinan; Park, Saungeun; Akinwande, Deji
2016-05-01
The last 10 years have seen the emergence of two-dimensional (2D) nanomaterials such as graphene, transition metal dichalcogenides (TMDs), and black phosphorus (BP) among the growing portfolio of layered van der Waals thin films. Graphene, the prototypical 2D material has advanced rapidly in device, circuit and system studies that has resulted in commercial large-area applications. In this work, we provide a perspective of the emerging and potential translational applications of 2D materials including semiconductors, semimetals, and insulators that comprise the basic material set for diverse nanosystems. Applications include RF transceivers, smart systems, the so-called internet of things, and neurotechnology. We will review the DC and RF electronic performance of graphene and BP thin film transistors. 2D materials at sub-um channel length have so far enabled cut-off frequencies from baseband to 100GHz suitable for low-power RF and sub-THz concepts.
2D hexagonal quaternion Fourier transform in color image processing
NASA Astrophysics Data System (ADS)
Grigoryan, Artyom M.; Agaian, Sos S.
2016-05-01
In this paper, we present a novel concept of the quaternion discrete Fourier transform on the two-dimensional hexagonal lattice, which we call the two-dimensional hexagonal quaternion discrete Fourier transform (2-D HQDFT). The concept of the right-side 2D HQDFT is described and the left-side 2-D HQDFT is similarly considered. To calculate the transform, the image on the hexagonal lattice is described in the tensor representation when the image is presented by a set of 1-D signals, or splitting-signals which can be separately processed in the frequency domain. The 2-D HQDFT can be calculated by a set of 1-D quaternion discrete Fourier transforms (QDFT) of the splitting-signals.
Technical Review of the UNET2D Hydraulic Model
Perkins, William A.; Richmond, Marshall C.
2009-05-18
The Kansas City District of the US Army Corps of Engineers is engaged in a broad range of river management projects that require knowledge of spatially-varied hydraulic conditions such as velocities and water surface elevations. This information is needed to design new structures, improve existing operations, and assess aquatic habitat. Two-dimensional (2D) depth-averaged numerical hydraulic models are a common tool that can be used to provide velocity and depth information. Kansas City District is currently using a specific 2D model, UNET2D, that has been developed to meet the needs of their river engineering applications. This report documents a tech- nical review of UNET2D.
Double resonance rotational spectroscopy of CH2D+
NASA Astrophysics Data System (ADS)
Töpfer, Matthias; Jusko, Pavol; Schlemmer, Stephan; Asvany, Oskar
2016-09-01
Context. Deuterated forms of CH are thought to be responsible for deuterium enrichment in lukewarm astronomical environments. There is no unambiguous detection of CH2D+ in space to date. Aims: Four submillimetre rotational lines of CH2D+ are documented in the literature. Our aim is to present a complete dataset of highly resolved rotational lines, including millimetre (mm) lines needed for a potential detection. Methods: We used a low-temperature ion trap and applied a novel IR-mm-wave double resonance method to measure the rotational lines of CH2D+. Results: We measured 21 low-lying (J ≤ 4) rotational transitions of CH2D+ between 23 GHz and 1.1 THz with accuracies close to 2 ppb.
Alloyed 2D Metal-Semiconductor Atomic Layer Junctions.
Kim, Ah Ra; Kim, Yonghun; Nam, Jaewook; Chung, Hee-Suk; Kim, Dong Jae; Kwon, Jung-Dae; Park, Sang Won; Park, Jucheol; Choi, Sun Young; Lee, Byoung Hun; Park, Ji Hyeon; Lee, Kyu Hwan; Kim, Dong-Ho; Choi, Sung Mook; Ajayan, Pulickel M; Hahm, Myung Gwan; Cho, Byungjin
2016-03-01
Heterostructures of compositionally and electronically variant two-dimensional (2D) atomic layers are viable building blocks for ultrathin optoelectronic devices. We show that the composition of interfacial transition region between semiconducting WSe2 atomic layer channels and metallic NbSe2 contact layers can be engineered through interfacial doping with Nb atoms. WxNb1-xSe2 interfacial regions considerably lower the potential barrier height of the junction, significantly improving the performance of the corresponding WSe2-based field-effect transistor devices. The creation of such alloyed 2D junctions between dissimilar atomic layer domains could be the most important factor in controlling the electronic properties of 2D junctions and the design and fabrication of 2D atomic layer devices. PMID:26839956
ORION96. 2-d Finite Element Code Postprocessor
Sanford, L.A.; Hallquist, J.O.
1992-02-02
ORION is an interactive program that serves as a postprocessor for the analysis programs NIKE2D, DYNA2D, TOPAZ2D, and CHEMICAL TOPAZ2D. ORION reads binary plot files generated by the two-dimensional finite element codes currently used by the Methods Development Group at LLNL. Contour and color fringe plots of a large number of quantities may be displayed on meshes consisting of triangular and quadrilateral elements. ORION can compute strain measures, interface pressures along slide lines, reaction forces along constrained boundaries, and momentum. ORION has been applied to study the response of two-dimensional solids and structures undergoing finite deformations under a wide variety of large deformation transient dynamic and static problems and heat transfer analyses.
Phylogenetic tree construction based on 2D graphical representation
NASA Astrophysics Data System (ADS)
Liao, Bo; Shan, Xinzhou; Zhu, Wen; Li, Renfa
2006-04-01
A new approach based on the two-dimensional (2D) graphical representation of the whole genome sequence [Bo Liao, Chem. Phys. Lett., 401(2005) 196.] is proposed to analyze the phylogenetic relationships of genomes. The evolutionary distances are obtained through measuring the differences among the 2D curves. The fuzzy theory is used to construct phylogenetic tree. The phylogenetic relationships of H5N1 avian influenza virus illustrate the utility of our approach.
Generating a 2D Representation of a Complex Data Structure
NASA Technical Reports Server (NTRS)
James, Mark
2006-01-01
A computer program, designed to assist in the development and debugging of other software, generates a two-dimensional (2D) representation of a possibly complex n-dimensional (where n is an integer >2) data structure or abstract rank-n object in that other software. The nature of the 2D representation is such that it can be displayed on a non-graphical output device and distributed by non-graphical means.
Anisotropic 2D Materials for Tunable Hyperbolic Plasmonics.
Nemilentsau, Andrei; Low, Tony; Hanson, George
2016-02-12
Motivated by the recent emergence of a new class of anisotropic 2D materials, we examine their electromagnetic modes and demonstrate that a broad class of the materials can host highly directional hyperbolic plasmons. Their propagation direction can be manipulated on the spot by gate doping, enabling hyperbolic beam reflection, refraction, and bending. The realization of these natural 2D hyperbolic media opens up a new avenue in dynamic control of hyperbolic plasmons not possible in the 3D version.
A simultaneous 2D/3D autostereo workstation
NASA Astrophysics Data System (ADS)
Chau, Dennis; McGinnis, Bradley; Talandis, Jonas; Leigh, Jason; Peterka, Tom; Knoll, Aaron; Sumer, Aslihan; Papka, Michael; Jellinek, Julius
2012-03-01
We present a novel immersive workstation environment that scientists can use for 3D data exploration and as their everyday 2D computer monitor. Our implementation is based on an autostereoscopic dynamic parallax barrier 2D/3D display, interactive input devices, and a software infrastructure that allows client/server software modules to couple the workstation to scientists' visualization applications. This paper describes the hardware construction and calibration, software components, and a demonstration of our system in nanoscale materials science exploration.
QUENCH2D. Two-Dimensional IHCP Code
Osman, A.; Beck, J.V.
1995-01-01
QUENCH2D* is developed for the solution of general, non-linear, two-dimensional inverse heat transfer problems. This program provides estimates for the surface heat flux distribution and/or heat transfer coefficient as a function of time and space by using transient temperature measurements at appropriate interior points inside the quenched body. Two-dimensional planar and axisymmetric geometries such as turnbine disks and blades, clutch packs, and many other problems can be analyzed using QUENCH2D*.
Designing 2D arrays for SHM of planar structures: a review
NASA Astrophysics Data System (ADS)
Stepinski, Tadeusz; Ambrozinski, Lukasz; Uhl, Tadeusz
2013-04-01
Monitoring structural integrity of large planar structures that aims at detecting and localizing impact or damage at any point of the structure requires normally a relatively dense network of uniformly distributed ultrasonic sensors. 2-D ultrasonic phased arrays, due to their beam-steering capability and all azimuth angle coverage are a very promising tool for structural health monitoring (SHM) of plate-like structures using Lamb waves (LW). Linear phased arrays that have been proposed for that purpose, produce mirrored image characterized by azimuth dependent resolution, which prevents unequivocal damage localization. 2D arrays do not have this drawback and they are even capable of mode selectivity when generating and receiving LWs. Performance of 2D arrays depends on their topology as well as the number of elements (transducers) used and their spacing in terms of wavelength. In this paper we propose a consistent methodology for three-step: theoretical, numerical and experimental investigation of a diversity of 2D array topologies in SHM applications. In the first step, the theoretical evaluation is performed using frequency-dependent structure transfer function (STF). STF that defines linear propagation of different LWs modes through the dispersive medium enables theoretical investigation of the particular array performance for a predefined tone-burst excitation signal. A dedicated software tool has been developed for the numerical evaluation of 2D array directional characteristics (beampattern) in a specific structure. The simulations are performed using local interaction simulation approach (LISA), implemented using NVIDIA CUDA graphical computation unit (GPU), which enables time-efficient 3D simulations of LWs propagation. Beampatterns of a 2D array can be to some extend evaluated analytically and using numerical simulations; in most cases, however, they require experimental verification. Using scanning laser vibrometer is proposed for that purpose, in a setup
Simulating MEMS Chevron Actuator for Strain Engineering 2D Materials
NASA Astrophysics Data System (ADS)
Vutukuru, Mounika; Christopher, Jason; Bishop, David; Swan, Anna
2D materials pose an exciting paradigm shift in the world of electronics. These crystalline materials have demonstrated high electric and thermal conductivities and tensile strength, showing great potential as the new building blocks of basic electronic circuits. However, strain engineering 2D materials for novel devices remains a difficult experimental feat. We propose the integration of 2D materials with MEMS devices to investigate the strain dependence on material properties such as electrical and thermal conductivity, refractive index, mechanical elasticity, and band gap. MEMS Chevron actuators, provides the most accessible framework to study strain in 2D materials due to their high output force displacements for low input power. Here, we simulate Chevron actuators on COMSOL to optimize actuator design parameters and accurately capture the behavior of the devices while under the external force of a 2D material. Through stationary state analysis, we analyze the response of the device through IV characteristics, displacement and temperature curves. We conclude that the simulation precisely models the real-world device through experimental confirmation, proving that the integration of 2D materials with MEMS is a viable option for constructing novel strain engineered devices. The authors acknowledge support from NSF DMR1411008.
A scale-free neural network for modelling neurogenesis
NASA Astrophysics Data System (ADS)
Perotti, Juan I.; Tamarit, Francisco A.; Cannas, Sergio A.
2006-11-01
In this work we introduce a neural network model for associative memory based on a diluted Hopfield model, which grows through a neurogenesis algorithm that guarantees that the final network is a small-world and scale-free one. We also analyze the storage capacity of the network and prove that its performance is larger than that measured in a randomly dilute network with the same connectivity.
Use of the 'Precessions' process for prepolishing and correcting 2D & 2(1/2)D form.
Walker, David D; Freeman, Richard; Morton, Roger; McCavana, Gerry; Beaucamp, Anthony
2006-11-27
The Precessions process polishes complex surfaces from the ground state preserving the ground-in form, and subsequently rectifies measured form errors. Our first paper introduced the technology and focused on the novel tooling. In this paper we describe the unique CNC machine tools and how they operate in polishing and correcting form. Experimental results demonstrate both the '2D' and '2(1/2)D' form-correction modes, as applied to aspheres with rotationally-symmetric target-form.
Electrochemical fabrication of 2D and 3D nickel nanowires using porous anodic alumina templates
NASA Astrophysics Data System (ADS)
Mebed, A. M.; Abd-Elnaiem, Alaa M.; Al-Hosiny, Najm M.
2016-06-01
Mechanically stable nickel (Ni) nanowires array and nanowires network were synthesized by pulse electrochemical deposition using 2D and 3D porous anodic alumina (PAA) templates. The structures and morphologies of as-prepared films were characterized by X-ray diffraction and scanning electron microscopy, respectively. The grown Ni nanowire using 3D PAA revealed more strength and larger surface area than has grown Ni use 2D PAA template. The prepared nanowires have a face-centered cubic crystal structure with average grain size 15 nm, and the preferred orientation of the nucleation of the nanowires is (111). The diameter of the nanowires is about 50-70 nm with length 3 µm. The resulting 3D Ni nanowire lattice, which provides enhanced mechanical stability and an increased surface area, benefits energy storage and many other applications which utilize the large surface area.
Singh, Pramod Kumar; Shrivastava, Nidhi; Chaturvedi, Krishna; Sharma, Bechan; Bhagyawant, Sameer S
2016-01-01
Proteomic analysis was employed to map the seed storage protein network in landrace and cultivated chickpea accessions. Protein extracts were separated by two-dimensional gel electrophoresis (2D-GE) across a broad range 3.0-10.0 immobilized pH gradient (IPG) strips. Comparative elucidation of differentially expressed proteins between two diverse geographically originated chickpea accessions was carried out using 2D-GE coupled with mass spectrometry. A total of 600 protein spots were detected in these accessions. In-gel protein expression patterns revealed three protein spots as upregulated and three other as downregulated. Using trypsin in-gel digestion, these differentially expressed proteins were identified by matrix-assisted laser desorption ionization time of flight mass spectrometry (MALDI-TOF-MS) which showed 45% amino acid homology of chickpea seed storage proteins with Arabidopsis thaliana. PMID:27144024
A Neural-FEM tool for the 2-D magnetic hysteresis modeling
NASA Astrophysics Data System (ADS)
Cardelli, E.; Faba, A.; Laudani, A.; Lozito, G. M.; Riganti Fulginei, F.; Salvini, A.
2016-04-01
The aim of this work is to present a new tool for the analysis of magnetic field problems considering 2-D magnetic hysteresis. In particular, this tool makes use of the Finite Element Method to solve the magnetic field problem in real device, and fruitfully exploits a neural network (NN) for the modeling of 2-D magnetic hysteresis of materials. The NS has as input the magnetic inductions components B at the k-th simulation step and returns as output the corresponding values of the magnetic field H corresponding to the input pattern. It is trained by vector measurements performed on the magnetic material to be modeled. This input/output scheme is directly implemented in a FEM code employing the magnetic potential vector A formulation. Validations through measurements on a real device have been performed.
A simple model clarifies the complicated relationships of complex networks
NASA Astrophysics Data System (ADS)
Zheng, Bojin; Wu, Hongrun; Kuang, Li; Qin, Jun; Du, Wenhua; Wang, Jianmin; Li, Deyi
2014-08-01
Real-world networks such as the Internet and WWW have many common traits. Until now, hundreds of models were proposed to characterize these traits for understanding the networks. Because different models used very different mechanisms, it is widely believed that these traits origin from different causes. However, we find that a simple model based on optimisation can produce many traits, including scale-free, small-world, ultra small-world, Delta-distribution, compact, fractal, regular and random networks. Moreover, by revising the proposed model, the community-structure networks are generated. By this model and the revised versions, the complicated relationships of complex networks are illustrated. The model brings a new universal perspective to the understanding of complex networks and provide a universal method to model complex networks from the viewpoint of optimisation.
2D nanostructures for water purification: graphene and beyond.
Dervin, Saoirse; Dionysiou, Dionysios D; Pillai, Suresh C
2016-08-18
Owing to their atomically thin structure, large surface area and mechanical strength, 2D nanoporous materials are considered to be suitable alternatives for existing desalination and water purification membrane materials. Recent progress in the development of nanoporous graphene based materials has generated enormous potential for water purification technologies. Progress in the development of nanoporous graphene and graphene oxide (GO) membranes, the mechanism of graphene molecular sieve action, structural design, hydrophilic nature, mechanical strength and antifouling properties and the principal challenges associated with nanopore generation are discussed in detail. Subsequently, the recent applications and performance of newly developed 2D materials such as 2D boron nitride (BN) nanosheets, graphyne, molybdenum disulfide (MoS2), tungsten chalcogenides (WS2) and titanium carbide (Ti3C2Tx) are highlighted. In addition, the challenges affecting 2D nanostructures for water purification are highlighted and their applications in the water purification industry are discussed. Though only a few 2D materials have been explored so far for water treatment applications, this emerging field of research is set to attract a great deal of attention in the near future.
Ultrafast 2D-IR spectroelectrochemistry of flavin mononucleotide
NASA Astrophysics Data System (ADS)
El Khoury, Youssef; Van Wilderen, Luuk J. G. W.; Bredenbeck, Jens
2015-06-01
We demonstrate the coupling of ultrafast two-dimensional infrared (2D-IR) spectroscopy to electrochemistry in solution and apply it to flavin mononucleotide, an important cofactor of redox proteins. For this purpose, we designed a spectroelectrochemical cell optimized for 2D-IR measurements in reflection and measured the time-dependent 2D-IR spectra of the oxidized and reduced forms of flavin mononucleotide. The data show anharmonic coupling and vibrational energy transfer between different vibrational modes in the two redox species. Such information is inaccessible with redox-controlled steady-state FTIR spectroscopy. The wide range of applications offered by 2D-IR spectroscopy, such as sub-picosecond structure determination, IR band assignment via energy transfer, disentangling reaction mixtures through band connectivity in the 2D spectra, and the measurement of solvation dynamics and chemical exchange can now be explored under controlled redox potential. The development of this technique furthermore opens new horizons for studying the dynamics of redox proteins.
Ultrafast 2D-IR spectroelectrochemistry of flavin mononucleotide.
El Khoury, Youssef; Van Wilderen, Luuk J G W; Bredenbeck, Jens
2015-06-01
We demonstrate the coupling of ultrafast two-dimensional infrared (2D-IR) spectroscopy to electrochemistry in solution and apply it to flavin mononucleotide, an important cofactor of redox proteins. For this purpose, we designed a spectroelectrochemical cell optimized for 2D-IR measurements in reflection and measured the time-dependent 2D-IR spectra of the oxidized and reduced forms of flavin mononucleotide. The data show anharmonic coupling and vibrational energy transfer between different vibrational modes in the two redox species. Such information is inaccessible with redox-controlled steady-state FTIR spectroscopy. The wide range of applications offered by 2D-IR spectroscopy, such as sub-picosecond structure determination, IR band assignment via energy transfer, disentangling reaction mixtures through band connectivity in the 2D spectra, and the measurement of solvation dynamics and chemical exchange can now be explored under controlled redox potential. The development of this technique furthermore opens new horizons for studying the dynamics of redox proteins.
Mean flow and anisotropic cascades in decaying 2D turbulence
NASA Astrophysics Data System (ADS)
Liu, Chien-Chia; Cerbus, Rory; Gioia, Gustavo; Chakraborty, Pinaki
2015-11-01
Many large-scale atmospheric and oceanic flows are decaying 2D turbulent flows embedded in a non-uniform mean flow. Despite its importance for large-scale weather systems, the affect of non-uniform mean flows on decaying 2D turbulence remains unknown. In the absence of mean flow it is well known that decaying 2D turbulent flows exhibit the enstrophy cascade. More generally, for any 2D turbulent flow, all computational, experimental and field data amassed to date indicate that the spectrum of longitudinal and transverse velocity fluctuations correspond to the same cascade, signifying isotropy of cascades. Here we report experiments on decaying 2D turbulence in soap films with a non-uniform mean flow. We find that the flow transitions from the usual isotropic enstrophy cascade to a series of unusual and, to our knowledge, never before observed or predicted, anisotropic cascades where the longitudinal and transverse spectra are mutually independent. We discuss implications of our results for decaying geophysical turbulence.
Sparse radar imaging using 2D compressed sensing
NASA Astrophysics Data System (ADS)
Hou, Qingkai; Liu, Yang; Chen, Zengping; Su, Shaoying
2014-10-01
Radar imaging is an ill-posed linear inverse problem and compressed sensing (CS) has been proved to have tremendous potential in this field. This paper surveys the theory of radar imaging and a conclusion is drawn that the processing of ISAR imaging can be denoted mathematically as a problem of 2D sparse decomposition. Based on CS, we propose a novel measuring strategy for ISAR imaging radar and utilize random sub-sampling in both range and azimuth dimensions, which will reduce the amount of sampling data tremendously. In order to handle 2D reconstructing problem, the ordinary solution is converting the 2D problem into 1D by Kronecker product, which will increase the size of dictionary and computational cost sharply. In this paper, we introduce the 2D-SL0 algorithm into the reconstruction of imaging. It is proved that 2D-SL0 can achieve equivalent result as other 1D reconstructing methods, but the computational complexity and memory usage is reduced significantly. Moreover, we will state the results of simulating experiments and prove the effectiveness and feasibility of our method.
Ultrafast 2D NMR: an emerging tool in analytical spectroscopy.
Giraudeau, Patrick; Frydman, Lucio
2014-01-01
Two-dimensional nuclear magnetic resonance (2D NMR) spectroscopy is widely used in chemical and biochemical analyses. Multidimensional NMR is also witnessing increased use in quantitative and metabolic screening applications. Conventional 2D NMR experiments, however, are affected by inherently long acquisition durations, arising from their need to sample the frequencies involved along their indirect domains in an incremented, scan-by-scan nature. A decade ago, a so-called ultrafast (UF) approach was proposed, capable of delivering arbitrary 2D NMR spectra involving any kind of homo- or heteronuclear correlation, in a single scan. During the intervening years, the performance of this subsecond 2D NMR methodology has been greatly improved, and UF 2D NMR is rapidly becoming a powerful analytical tool experiencing an expanded scope of applications. This review summarizes the principles and main developments that have contributed to the success of this approach and focuses on applications that have been recently demonstrated in various areas of analytical chemistry--from the real-time monitoring of chemical and biochemical processes, to extensions in hyphenated techniques and in quantitative applications. PMID:25014342
2D nanostructures for water purification: graphene and beyond.
Dervin, Saoirse; Dionysiou, Dionysios D; Pillai, Suresh C
2016-08-18
Owing to their atomically thin structure, large surface area and mechanical strength, 2D nanoporous materials are considered to be suitable alternatives for existing desalination and water purification membrane materials. Recent progress in the development of nanoporous graphene based materials has generated enormous potential for water purification technologies. Progress in the development of nanoporous graphene and graphene oxide (GO) membranes, the mechanism of graphene molecular sieve action, structural design, hydrophilic nature, mechanical strength and antifouling properties and the principal challenges associated with nanopore generation are discussed in detail. Subsequently, the recent applications and performance of newly developed 2D materials such as 2D boron nitride (BN) nanosheets, graphyne, molybdenum disulfide (MoS2), tungsten chalcogenides (WS2) and titanium carbide (Ti3C2Tx) are highlighted. In addition, the challenges affecting 2D nanostructures for water purification are highlighted and their applications in the water purification industry are discussed. Though only a few 2D materials have been explored so far for water treatment applications, this emerging field of research is set to attract a great deal of attention in the near future. PMID:27506268
Sporns, Olaf; Kötter, Rolf
2004-11-01
Complex brains have evolved a highly efficient network architecture whose structural connectivity is capable of generating a large repertoire of functional states. We detect characteristic network building blocks (structural and functional motifs) in neuroanatomical data sets and identify a small set of structural motifs that occur in significantly increased numbers. Our analysis suggests the hypothesis that brain networks maximize both the number and the diversity of functional motifs, while the repertoire of structural motifs remains small. Using functional motif number as a cost function in an optimization algorithm, we obtain network topologies that resemble real brain networks across a broad spectrum of structural measures, including small-world attributes. These results are consistent with the hypothesis that highly evolved neural architectures are organized to maximize functional repertoires and to support highly efficient integration of information.
2004-01-01
Complex brains have evolved a highly efficient network architecture whose structural connectivity is capable of generating a large repertoire of functional states. We detect characteristic network building blocks (structural and functional motifs) in neuroanatomical data sets and identify a small set of structural motifs that occur in significantly increased numbers. Our analysis suggests the hypothesis that brain networks maximize both the number and the diversity of functional motifs, while the repertoire of structural motifs remains small. Using functional motif number as a cost function in an optimization algorithm, we obtain network topologies that resemble real brain networks across a broad spectrum of structural measures, including small-world attributes. These results are consistent with the hypothesis that highly evolved neural architectures are organized to maximize functional repertoires and to support highly efficient integration of information. PMID:15510229
Graphene based 2D-materials for supercapacitors
NASA Astrophysics Data System (ADS)
Palaniselvam, Thangavelu; Baek, Jong-Beom
2015-09-01
Ever-increasing energy demands and the depletion of fossil fuels are compelling humanity toward the development of suitable electrochemical energy conversion and storage devices to attain a more sustainable society with adequate renewable energy and zero environmental pollution. In this regard, supercapacitors are being contemplated as potential energy storage devices to afford cleaner, environmentally friendly energy. Recently, a great deal of attention has been paid to two-dimensional (2D) nanomaterials, including 2D graphene and its inorganic analogues (transition metal double layer hydroxides, chalcogenides, etc), as potential electrodes for the development of supercapacitors with high electrochemical performance. This review provides an overview of the recent progress in using these graphene-based 2D materials as potential electrodes for supercapacitors. In addition, future research trends including notable challenges and opportunities are also discussed.
Perception-based reversible watermarking for 2D vector maps
NASA Astrophysics Data System (ADS)
Men, Chaoguang; Cao, Liujuan; Li, Xiang
2010-07-01
This paper presents an effective and reversible watermarking approach for digital copyright protection of 2D-vector maps. To ensure that the embedded watermark is insensitive for human perception, we only select the noise non-sensitive regions for watermark embedding by estimating vertex density within each polyline. To ensure the exact recovery of original 2D-vector map after watermark extraction, we introduce a new reversible watermarking scheme based on reversible high-frequency wavelet coefficients modification. Within the former-selected non-sensitive regions, our watermarking operates on the lower-order vertex coordinate decimals with integer wavelet transform. Such operation further reduces the visual distortion caused by watermark embedding. We have validated the effectiveness of our scheme on our real-world city river/building 2D-vector maps. We give extensive experimental comparisons with state-of-the-art methods, including embedding capability, invisibility, and robustness over watermark attacking.
Secretory pathways generating immunosuppressive NKG2D ligands
Baragaño Raneros, Aroa; Suarez-Álvarez, Beatriz; López-Larrea, Carlos
2014-01-01
Natural Killer Group 2 member D (NKG2D) activating receptor, present on the surface of various immune cells, plays an important role in activating the anticancer immune response by their interaction with stress-inducible NKG2D ligands (NKG2DL) on transformed cells. However, cancer cells have developed numerous mechanisms to evade the immune system via the downregulation of NKG2DL from the cell surface, including the release of NKG2DL from the cell surface in a soluble form. Here, we review the mechanisms involved in the production of soluble NKG2DL (sNKG2DL) and the potential therapeutic strategies aiming to block the release of these immunosuppressive ligands. Therapeutically enabling the NKG2D-NKG2DL interaction would promote immunorecognition of malignant cells, thus abrogating disease progression. PMID:25050215
2D bifurcations and Newtonian properties of memristive Chua's circuits
NASA Astrophysics Data System (ADS)
Marszalek, W.; Podhaisky, H.
2016-01-01
Two interesting properties of Chua's circuits are presented. First, two-parameter bifurcation diagrams of Chua's oscillatory circuits with memristors are presented. To obtain various 2D bifurcation images a substantial numerical effort, possibly with parallel computations, is needed. The numerical algorithm is described first and its numerical code for 2D bifurcation image creation is available for free downloading. Several color 2D images and the corresponding 1D greyscale bifurcation diagrams are included. Secondly, Chua's circuits are linked to Newton's law φ ''= F(t,φ,φ')/m with φ=\\text{flux} , constant m > 0, and the force term F(t,φ,φ') containing memory terms. Finally, the jounce scalar equations for Chua's circuits are also discussed.
Focusing surface wave imaging with flexible 2D array
NASA Astrophysics Data System (ADS)
Zhou, Shiyuan; Fu, Junqiang; Li, Zhe; Xu, Chunguang; Xiao, Dingguo; Wang, Shaohan
2016-04-01
Curved surface is widely exist in key parts of energy and power equipment, such as, turbine blade cylinder block and so on. Cycling loading and harsh working condition of enable fatigue cracks appear on the surface. The crack should be found in time to avoid catastrophic damage to the equipment. A flexible 2D array transducer was developed. 2D Phased Array focusing method (2DPA), Mode-Spatial Double Phased focusing method (MSDPF) and the imaging method using the flexible 2D array probe are studied. Experiments using these focusing and imaging method are carried out. Surface crack image is obtained with both 2DPA and MSDPF focusing method. It have been proved that MSDPF can be more adaptable for curved surface and more calculate efficient than 2DPA.
Electric field enhancement in a self-assembled 2D array of silver nanospheres
El-Khoury, Patrick Z. E-mail: wayne.hess@pnnl.gov; Gong, Yu; Joly, Alan G.; Abellan, Patricia; Browning, Nigel D.; Hess, Wayne P. E-mail: wayne.hess@pnnl.gov; Khon, Elena; Hu, Dehong; Zamkov, Mikhail; Evans, James E.
2014-12-07
We investigate the plasmonic properties of a self-assembled 2D array of Ag nanospheres (average particle diameter/inter-particle separation distance of 9/3.7 nm). The structures of the individual particles and their assemblies are characterized using high-resolution transmission electron microscopy (HR-TEM). The plasmonic response of the nanoparticle network is probed using two-photon photoemission electron microscopy (TP-PEEM). HR-TEM and TP-PEEM statistics reveal the structure and plasmonic response of the network to be homogeneous on average. This translates into a relatively uniform surface-enhanced Raman scattering (SERS) response from biphenyl,4-4{sup ′}-dithiol (BPDT) molecules adsorbed onto different sites of the network. Reproducible, bright, and low-background SERS spectra are recorded and assigned on the basis of density functional theory calculations in which BPDT is chemisorbed onto the vertex of a finite tetrahedral Ag cluster consisting of 20 Ag atoms. A notable agreement between experiment and theory allows us to rigorously account for the observable vibrational states of BPDT in the ∼200–2200 cm{sup −1} region of the spectrum. Finite difference time domain simulations further reveal that physical enhancement factors on the order of 10{sup 6} are attainable at the nanogaps formed between the silver nanospheres in the 2D array. Combined with modest chemical enhancement factors, this study paves the way for reproducible single molecule signals from an easily self-assembled SERS substrate.
Electric Field Enhancement in a Self-Assembled 2D Array of Silver Nanospheres
El-Khoury, Patrick Z.; Khon, Elena; Gong, Yu; Joly, Alan G.; Abellan, Patricia; Evans, James E.; Browning, Nigel D.; Hu, Dehong; Zamkov, Mikhail; Hess, Wayne P.
2014-12-07
We investigate the plasmonic properties of a self-assembled 2D array of Ag nanospheres (average particle diameter/inter-particle separation distance of ~9/~4 nm). The structures of the individual particles and their assemblies are characterized using high-resolution transmission electron microscopy (HR-TEM). The plasmonic response of the nanoparticle network is probed using two-photon photoemission electron microscopy (TP-PEEM). HR-TEM and TP-PEEM statistics reveal the structure and plasmonic response of the network to be homogeneous on average. This translates into a relatively uniform surface-enhanced Raman scattering (SERS) response from biphenyl,4-4’-dithiol (BPDT) molecules adsorbed onto different sites of the network. Bright and background free SERS spectra are recorded, assigned on the basis of density 2 functional theory calculations in which BPDT is chemisorbed onto the vertex of a finitie tetrahedral Ag cluster consisting of 20 Ag atoms. A remarkable agreement between experiment and theory allows us to rigorously account for the observable vibrational states of BPDT in the ~200-2200 cm-1 region of the spectrum. Finite difference time domain simulations further reveal that physical enhancement factors on the order of 106 are attainable at the nanogaps formed between the silver nanospheres in the 2D array. Combined with modest chemical enhancement factors, this study paves the way for reproducible single molecule signals from an easily self-assembled SERS substrate.
González-Padilla, Jazmin E; Rosales-Hernández, Martha C; Padilla-Martínez, Itzia I; García-Báez, Efren V; Rojas-Lima, Susana; Salazar-Pereda, Veronica
2014-01-01
Molecules of 1,2-bis(4-bromophenyl)-1H-benzimidazole, C19H12Br2N2, (I), and 2-(4-bromophenyl)-1-(4-nitrophenyl)-1H-benzimidazole, C19H12BrN3O2, (II), are arranged in dimeric units through C-H...N and parallel-displaced π-stacking interactions favoured by the appropriate disposition of N- and C-bonded phenyl rings with respect to the mean benzimidazole plane. The molecular packing of the dimers of (I) and (II) arises by the concurrence of a diverse set of weak intermolecular C-X...D (X = H, NO2; D = O, π) interactions.
Radiative heat transfer in 2D Dirac materials.
Rodriguez-López, Pablo; Tse, Wang-Kong; Dalvit, Diego A R
2015-06-01
We compute the radiative heat transfer between two sheets of 2D Dirac materials, including topological Chern insulators and graphene, within the framework of the local approximation for the optical response of these materials. In this approximation, which neglects spatial dispersion, we derive both numerically and analytically the short-distance asymptotic of the near-field heat transfer in these systems, and show that it scales as the inverse of the distance between the two sheets. Finally, we discuss the limitations to the validity of this scaling law imposed by spatial dispersion in 2D Dirac materials. PMID:25965703
Quantum process tomography by 2D fluorescence spectroscopy
Pachón, Leonardo A.; Marcus, Andrew H.; Aspuru-Guzik, Alán
2015-06-07
Reconstruction of the dynamics (quantum process tomography) of the single-exciton manifold in energy transfer systems is proposed here on the basis of two-dimensional fluorescence spectroscopy (2D-FS) with phase-modulation. The quantum-process-tomography protocol introduced here benefits from, e.g., the sensitivity enhancement ascribed to 2D-FS. Although the isotropically averaged spectroscopic signals depend on the quantum yield parameter Γ of the doubly excited-exciton manifold, it is shown that the reconstruction of the dynamics is insensitive to this parameter. Applications to foundational and applied problems, as well as further extensions, are discussed.
On 2D bisection method for double eigenvalue problems
Ji, X.
1996-06-01
The two-dimensional bisection method presented in (SIAM J. Matrix Anal. Appl. 13(4), 1085 (1992)) is efficient for solving a class of double eigenvalue problems. This paper further extends the 2D bisection method of full matrix cases and analyses its stability. As in a single parameter case, the 2D bisection method is very stable for the tridiagonal matrix triples satisfying the symmetric-definite condition. Since the double eigenvalue problems arise from two-parameter boundary value problems, an estimate of the discretization error in eigenpairs is also given. Some numerical examples are included. 42 refs., 1 tab.
Design of the LRP airfoil series using 2D CFD
NASA Astrophysics Data System (ADS)
Zahle, Frederik; Bak, Christian; Sørensen, Niels N.; Vronsky, Tomas; Gaudern, Nicholas
2014-06-01
This paper describes the design and wind tunnel testing of a high-Reynolds number, high lift airfoil series designed for wind turbines. The airfoils were designed using direct gradient- based numerical multi-point optimization based on a Bezier parameterization of the shape, coupled to the 2D Navier-Stokes flow solver EllipSys2D. The resulting airfoils, the LRP2-30 and LRP2-36, achieve both higher operational lift coefficients and higher lift to drag ratios compared to the equivalent FFA-W3 airfoils.
Laboratory Experiments On Continually Forced 2d Turbulence
NASA Astrophysics Data System (ADS)
Wells, M. G.; Clercx, H. J. H.; Van Heijst, G. J. F.
There has been much recent interest in the advection of tracers by 2D turbulence in geophysical flows. While there is a large body of literature on decaying 2D turbulence or forced 2D turbulence in unbounded domains, there have been very few studies of forced turbulence in bounded domains. In this study we present new experimental results from a continuously forced quasi 2D turbulent field. The experiments are performed in a square Perspex tank filled with water. The flow is made quasi 2D by a steady background rotation. The rotation rate of the tank has a small (<8 %) sinusoidal perturbation which leads to the periodic formation of eddies in the corners of the tank. When the oscillation period of the perturbation is greater than an eddy roll-up time-scale, dipole structures are observed to form. The dipoles can migrate away from the walls, and the interior of the tank is continually filled with vortexs. From experimental visualizations the length scale of the vortexs appears to be largely controlled by the initial formation mechanism and large scale structures are not observed to form at large times. Thus the experiments provide a simple way of cre- ating a continuously forced 2D turbulent field. The resulting structures are in contrast with most previous laboratory experiments on 2D turbulence which have investigated decaying turbulence and have observed the formations of large scale structure. In these experiments, decaying turbulence had been produced by a variety of methods such as the decaying turbulence in the wake of a comb of rods (Massen et al 1999), organiza- tion of vortices in thin conducting liquids (Cardoso et al 1994) or in rotating systems where there are sudden changes in angular rotation rate (Konijnenberg et al 1998). Results of dye visualizations, particle tracking experiments and a direct numerical simulation will be presented and discussed in terms of their oceanographic application. Bibliography Cardoso,O. Marteau, D. &Tabeling, P
2012-01-05
Code is for a layered electric medium with 2d structure. Includes air-earth interface at node z=2.. The electric ex and ez fields are calculated on edges of elemental grid and magnetic field hy is calculated on the face of the elemental grid. The code allows for a layered earth with 2d structures. Solutions of coupled first order Maxwell's equations are solved in the two dimensional environment using a finite- difference scheme on a staggered spationamore » and temporal grid.« less
Noninvasive deep Raman detection with 2D correlation analysis
NASA Astrophysics Data System (ADS)
Kim, Hyung Min; Park, Hyo Sun; Cho, Youngho; Jin, Seung Min; Lee, Kang Taek; Jung, Young Mee; Suh, Yung Doug
2014-07-01
The detection of poisonous chemicals enclosed in daily necessaries is prerequisite essential for homeland security with the increasing threat of terrorism. For the detection of toxic chemicals, we combined a sensitive deep Raman spectroscopic method with 2D correlation analysis. We obtained the Raman spectra from concealed chemicals employing spatially offset Raman spectroscopy in which incident line-shaped light experiences multiple scatterings before being delivered to inner component and yielding deep Raman signal. Furthermore, we restored the pure Raman spectrum of each component using 2D correlation spectroscopic analysis with chemical inspection. Using this method, we could elucidate subsurface component under thick powder and packed contents in a bottle.
NASA Astrophysics Data System (ADS)
Hosomichi, Kazuo; Lee, Sungjay
2015-01-01
We study the system of M2-branes suspended between parallel M5-branes using ABJM model with a natural half-BPS boundary condition. For small separation between M5-branes, the worldvolume theory is shown to reduce to a 2D super Yang-Mills theory with some similarity to q-deformed Yang-Mills theory. The gauge coupling is related to the position of the branes in an interesting manner. The theory is considerably different from the 2D theory proposed for multiple "M-strings". We make a detailed comparison of elliptic genus of the two descriptions and find only a partial agreement.
Finite temperature corrections in 2d integrable models
NASA Astrophysics Data System (ADS)
Caselle, M.; Hasenbusch, M.
2002-09-01
We study the finite size corrections for the magnetization and the internal energy of the 2d Ising model in a magnetic field by using transfer matrix techniques. We compare these corrections with the functional form recently proposed by Delfino and LeClair-Mussardo for the finite temperature behaviour of one-point functions in integrable 2d quantum field theories. We find a perfect agreement between theoretical expectations and numerical results. Assuming the proposed functional form as an input in our analysis we obtain a relevant improvement in the precision of the continuum limit estimates of both quantities.
2dF grows up: Echidna for the AAT
NASA Astrophysics Data System (ADS)
McGrath, Andrew; Barden, Sam; Miziarski, Stan; Rambold, William; Smith, Greg
2008-07-01
We present the concept design of a new fibre positioner and spectrograph system for the Anglo-Australian Telescope, as a proposed enhancement to the Anglo-Australian Observatory's well-known 2dF facility. A four-fold multiplex enhancement is accomplished by replacing the 400-fibre 2dF fibre positioning robot with a 1600-fibre Echidna unit, feeding three clones of the AAOmega optical spectrograph. Such a facility has the capability of a redshift 1 survey of a large fraction of the southern sky, collecting five to ten thousand spectra per night for a million-galaxy survey.
Radiative heat transfer in 2D Dirac materials
Rodriguez-López, Pablo; Tse, Wang -Kong; Dalvit, Diego A. R.
2015-05-12
We compute the radiative heat transfer between two sheets of 2D Dirac materials, including topological Chern insulators and graphene, within the framework of the local approximation for the optical response of these materials. In this approximation, which neglects spatial dispersion, we derive both numerically and analytically the short-distance asymptotic of the near-field heat transfer in these systems, and show that it scales as the inverse of the distance between the two sheets. In conclusion, we discuss the limitations to the validity of this scaling law imposed by spatial dispersion in 2D Dirac materials.
Nomenclature for human CYP2D6 alleles.
Daly, A K; Brockmöller, J; Broly, F; Eichelbaum, M; Evans, W E; Gonzalez, F J; Huang, J D; Idle, J R; Ingelman-Sundberg, M; Ishizaki, T; Jacqz-Aigrain, E; Meyer, U A; Nebert, D W; Steen, V M; Wolf, C R; Zanger, U M
1996-06-01
To standardize CYP2D6 allele nomenclature, and to conform with international human gene nomenclature guidelines, an alternative to the current arbitrary system is described. Based on recommendations for human genome nomenclature, we propose that alleles be designated by CYP2D6 followed by an asterisk and a combination of roman letters and arabic numerals distinct for each allele with the number specifying the key mutation and, where appropriate, a letter specifying additional mutations. Criteria for classification as a separate allele and protein nomenclature are also presented. PMID:8807658
Spreading dynamics of 2D dipolar Langmuir monolayer phases.
Heinig, P; Wurlitzer, S; Fischer, Th M
2004-07-01
We study the spreading of a liquid 2D dipolar droplet in a Langmuir monolayer. Interfacial tensions (line tensions) and microscopic contact angles depend on the scale on which they are probed and obey a scaling law. Assuming rapid equilibration of the microscopic contact angle and ideal slippage of the 2D solid/liquid and solid/gas boundary, the driving force of spreading is merely expressed by the shape-dependent long-range interaction integrals. We obtain good agreement between experiment and numerical simulations using this theory. PMID:15278693
Evaluation of 2D ceramic matrix composites in aeroconvective environments
NASA Technical Reports Server (NTRS)
Riccitiello, Salvatore R.; Love, Wendell L.; Balter-Peterson, Aliza
1992-01-01
An evaluation is conducted of a novel ceramic-matrix composite (CMC) material system for use in the aeroconvective-heating environments encountered by the nose caps and wing leading edges of such aerospace vehicles as the Space Shuttle, during orbit-insertion and reentry from LEO. These CMCs are composed of an SiC matrix that is reinforced with Nicalon, Nextel, or carbon refractory fibers in a 2D architecture. The test program conducted for the 2D CMCs gave attention to their subsurface oxidation.
Quantum process tomography by 2D fluorescence spectroscopy
NASA Astrophysics Data System (ADS)
Pachón, Leonardo A.; Marcus, Andrew H.; Aspuru-Guzik, Alán
2015-06-01
Reconstruction of the dynamics (quantum process tomography) of the single-exciton manifold in energy transfer systems is proposed here on the basis of two-dimensional fluorescence spectroscopy (2D-FS) with phase-modulation. The quantum-process-tomography protocol introduced here benefits from, e.g., the sensitivity enhancement ascribed to 2D-FS. Although the isotropically averaged spectroscopic signals depend on the quantum yield parameter Γ of the doubly excited-exciton manifold, it is shown that the reconstruction of the dynamics is insensitive to this parameter. Applications to foundational and applied problems, as well as further extensions, are discussed.
Rowley-Neale, Samuel J; Fearn, Jamie M; Brownson, Dale A C; Smith, Graham C; Ji, Xiaobo; Banks, Craig E
2016-08-21
Two-dimensional molybdenum disulphide nanosheets (2D-MoS2) have proven to be an effective electrocatalyst, with particular attention being focused on their use towards increasing the efficiency of the reactions associated with hydrogen fuel cells. Whilst the majority of research has focused on the Hydrogen Evolution Reaction (HER), herein we explore the use of 2D-MoS2 as a potential electrocatalyst for the much less researched Oxygen Reduction Reaction (ORR). We stray from literature conventions and perform experiments in 0.1 M H2SO4 acidic electrolyte for the first time, evaluating the electrochemical performance of the ORR with 2D-MoS2 electrically wired/immobilised upon several carbon based electrodes (namely; Boron Doped Diamond (BDD), Edge Plane Pyrolytic Graphite (EPPG), Glassy Carbon (GC) and Screen-Printed Electrodes (SPE)) whilst exploring a range of 2D-MoS2 coverages/masses. Consequently, the findings of this study are highly applicable to real world fuel cell applications. We show that significant improvements in ORR activity can be achieved through the careful selection of the underlying/supporting carbon materials that electrically wire the 2D-MoS2 and utilisation of an optimal mass of 2D-MoS2. The ORR onset is observed to be reduced to ca. +0.10 V for EPPG, GC and SPEs at 2D-MoS2 (1524 ng cm(-2) modification), which is far closer to Pt at +0.46 V compared to bare/unmodified EPPG, GC and SPE counterparts. This report is the first to demonstrate such beneficial electrochemical responses in acidic conditions using a 2D-MoS2 based electrocatalyst material on a carbon-based substrate (SPEs in this case). Investigation of the beneficial reaction mechanism reveals the ORR to occur via a 4 electron process in specific conditions; elsewhere a 2 electron process is observed. This work offers valuable insights for those wishing to design, fabricate and/or electrochemically test 2D-nanosheet materials towards the ORR. PMID:27448174
Tønning, Erik; Polders, Daniel; Callaghan, Paul T; Engelsen, Søren B
2007-09-01
This paper demonstrates how the multi-linear PARAFAC model can with advantage be used to decompose 2D diffusion-relaxation correlation NMR spectra prior to 2D-Laplace inversion to the T(2)-D domain. The decomposition is advantageous for better interpretation of the complex correlation maps as well as for the quantification of extracted T(2)-D components. To demonstrate the new method seventeen mixtures of wheat flour, starch, gluten, oil and water were prepared and measured with a 300 MHz nuclear magnetic resonance (NMR) spectrometer using a pulsed gradient stimulated echo (PGSTE) pulse sequence followed by a Carr-Purcell-Meiboom-Gill (CPMG) pulse echo train. By varying the gradient strength, 2D diffusion-relaxation data were recorded for each sample. From these double exponentially decaying relaxation data the PARAFAC algorithm extracted two unique diffusion-relaxation components, explaining 99.8% of the variation in the data set. These two components were subsequently transformed to the T(2)-D domain using 2D-inverse Laplace transformation and quantitatively assigned to the oil and water components of the samples. The oil component was one distinct distribution with peak intensity at D=3 x 10(-12) m(2) s(-1) and T(2)=180 ms. The water component consisted of two broad populations of water molecules with diffusion coefficients and relaxation times centered around correlation pairs: D=10(-9) m(2) s(-1), T(2)=10 ms and D=3 x 10(-13) m(2) s(-1), T(2)=13 ms. Small spurious peaks observed in the inverse Laplace transformation of original complex data were effectively filtered by the PARAFAC decomposition and thus considered artefacts from the complex Laplace transformation. The oil-to-water ratio determined by PARAFAC followed by 2D-Laplace inversion was perfectly correlated with known oil-to-water ratio of the samples. The new method of using PARAFAC prior to the 2D-Laplace inversion proved to have superior potential in analysis of diffusion-relaxation spectra, as it
Rowley-Neale, Samuel J; Fearn, Jamie M; Brownson, Dale A C; Smith, Graham C; Ji, Xiaobo; Banks, Craig E
2016-08-21
Two-dimensional molybdenum disulphide nanosheets (2D-MoS2) have proven to be an effective electrocatalyst, with particular attention being focused on their use towards increasing the efficiency of the reactions associated with hydrogen fuel cells. Whilst the majority of research has focused on the Hydrogen Evolution Reaction (HER), herein we explore the use of 2D-MoS2 as a potential electrocatalyst for the much less researched Oxygen Reduction Reaction (ORR). We stray from literature conventions and perform experiments in 0.1 M H2SO4 acidic electrolyte for the first time, evaluating the electrochemical performance of the ORR with 2D-MoS2 electrically wired/immobilised upon several carbon based electrodes (namely; Boron Doped Diamond (BDD), Edge Plane Pyrolytic Graphite (EPPG), Glassy Carbon (GC) and Screen-Printed Electrodes (SPE)) whilst exploring a range of 2D-MoS2 coverages/masses. Consequently, the findings of this study are highly applicable to real world fuel cell applications. We show that significant improvements in ORR activity can be achieved through the careful selection of the underlying/supporting carbon materials that electrically wire the 2D-MoS2 and utilisation of an optimal mass of 2D-MoS2. The ORR onset is observed to be reduced to ca. +0.10 V for EPPG, GC and SPEs at 2D-MoS2 (1524 ng cm(-2) modification), which is far closer to Pt at +0.46 V compared to bare/unmodified EPPG, GC and SPE counterparts. This report is the first to demonstrate such beneficial electrochemical responses in acidic conditions using a 2D-MoS2 based electrocatalyst material on a carbon-based substrate (SPEs in this case). Investigation of the beneficial reaction mechanism reveals the ORR to occur via a 4 electron process in specific conditions; elsewhere a 2 electron process is observed. This work offers valuable insights for those wishing to design, fabricate and/or electrochemically test 2D-nanosheet materials towards the ORR.
NASA Astrophysics Data System (ADS)
Tønning, Erik; Polders, Daniel; Callaghan, Paul T.; Engelsen, Søren B.
2007-09-01
This paper demonstrates how the multi-linear PARAFAC model can with advantage be used to decompose 2D diffusion-relaxation correlation NMR spectra prior to 2D-Laplace inversion to the T2- D domain. The decomposition is advantageous for better interpretation of the complex correlation maps as well as for the quantification of extracted T2- D components. To demonstrate the new method seventeen mixtures of wheat flour, starch, gluten, oil and water were prepared and measured with a 300 MHz nuclear magnetic resonance (NMR) spectrometer using a pulsed gradient stimulated echo (PGSTE) pulse sequence followed by a Carr-Purcell-Meiboom-Gill (CPMG) pulse echo train. By varying the gradient strength, 2D diffusion-relaxation data were recorded for each sample. From these double exponentially decaying relaxation data the PARAFAC algorithm extracted two unique diffusion-relaxation components, explaining 99.8% of the variation in the data set. These two components were subsequently transformed to the T2- D domain using 2D-inverse Laplace transformation and quantitatively assigned to the oil and water components of the samples. The oil component was one distinct distribution with peak intensity at D = 3 × 10 -12 m 2 s -1 and T2 = 180 ms. The water component consisted of two broad populations of water molecules with diffusion coefficients and relaxation times centered around correlation pairs: D = 10 -9 m 2 s -1, T2 = 10 ms and D = 3 × 10 -13 m 2 s -1, T2 = 13 ms. Small spurious peaks observed in the inverse Laplace transformation of original complex data were effectively filtered by the PARAFAC decomposition and thus considered artefacts from the complex Laplace transformation. The oil-to-water ratio determined by PARAFAC followed by 2D-Laplace inversion was perfectly correlated with known oil-to-water ratio of the samples. The new method of using PARAFAC prior to the 2D-Laplace inversion proved to have superior potential in analysis of diffusion-relaxation spectra, as it
ERIC Educational Resources Information Center
Cerf, Vinton G.
1991-01-01
The demands placed on the networks transporting the information and knowledge generated by the increased diversity and sophistication of computational machinery are described. What is needed to support this increased flow, the structures already in place, and what must be built are topics of discussion. (KR)
Scale-Free Brain Functional Networks
NASA Astrophysics Data System (ADS)
Eguíluz, Victor M.; Chialvo, Dante R.; Cecchi, Guillermo A.; Baliki, Marwan; Apkarian, A. Vania
2005-01-01
Functional magnetic resonance imaging is used to extract functional networks connecting correlated human brain sites. Analysis of the resulting networks in different tasks shows that (a)the distribution of functional connections, and the probability of finding a link versus distance are both scale-free, (b)the characteristic path length is small and comparable with those of equivalent random networks, and (c)the clustering coefficient is orders of magnitude larger than those of equivalent random networks. All these properties, typical of scale-free small-world networks, reflect important functional information about brain states.
2D-CELL: image processing software for extraction and analysis of 2-dimensional cellular structures
NASA Astrophysics Data System (ADS)
Righetti, F.; Telley, H.; Leibling, Th. M.; Mocellin, A.
1992-01-01
2D-CELL is a software package for the processing and analyzing of photographic images of cellular structures in a largely interactive way. Starting from a binary digitized image, the programs extract the line network (skeleton) of the structure and determine the graph representation that best models it. Provision is made for manually correcting defects such as incorrect node positions or dangling bonds. Then a suitable algorithm retrieves polygonal contours which define individual cells — local boundary curvatures are neglected for simplicity. Using elementary analytical geometry relations, a range of metric and topological parameters describing the population are then computed, organized into statistical distributions and graphically displayed.
Orbit computation of the TELECOM-2D satellite with a Genetic Algorithm
NASA Astrophysics Data System (ADS)
Deleflie, Florent; Coulot, David; Vienne, Alain; Decosta, Romain; Richard, Pascal; Lasri, Mohammed Amjad
2014-07-01
In order to test a preliminary orbit determination method, we fit an orbit of the geostationary satellite TELECOM-2D, as if we did not know any a priori information on its trajectory. The method is based on a genetic algorithm coupled to an analytical propagator of the trajectory, that is used over a couple of days, and that uses a whole set of altazimutal data that are acquired by the tracking network made up of the two TAROT telescopes. The adjusted orbit is then compared to a numerical reference. The method is described, and the results are analyzed, as a step towards an operational method of preliminary orbit determination for uncatalogued objects.
Discrepant Results in a 2-D Marble Collision
ERIC Educational Resources Information Center
Kalajian, Peter
2013-01-01
Video analysis of 2-D collisions is an excellent way to investigate conservation of linear momentum. The often-desired experimental design goal is to minimize the momentum loss in order to demonstrate the conservation law. An air table with colliding pucks is an ideal medium for this experiment, but such equipment is beyond the budget of many…
THz devices based on 2D electron systems
NASA Astrophysics Data System (ADS)
Xing, Huili Grace; Yan, Rusen; Song, Bo; Encomendero, Jimy; Jena, Debdeep
2015-05-01
In two-dimensional electron systems with mobility on the order of 1,000 - 10,000 cm2/Vs, the electron scattering time is about 1 ps. For the THz window of 0.3 - 3 THz, the THz photon energy is in the neighborhood of 1 meV, substantially smaller than the optical phonon energy of solids where these 2D electron systems resides. These properties make the 2D electron systems interesting as a platform to realize THz devices. In this paper, I will review 3 approaches investigated in the past few years in my group toward THz devices. The first approach is the conventional high electron mobility transistor based on GaN toward THz amplifiers. The second approach is to employ the tunable intraband absorption in 2D electron systems to realize THz modulators, where I will use graphene as a model material system. The third approach is to exploit plasma wave in these 2D electron systems that can be coupled with a negative differential conductance element for THz amplifiers/sources/detectors.
ELLIPT2D: A Flexible Finite Element Code Written Python
Pletzer, A.; Mollis, J.C.
2001-03-22
The use of the Python scripting language for scientific applications and in particular to solve partial differential equations is explored. It is shown that Python's rich data structure and object-oriented features can be exploited to write programs that are not only significantly more concise than their counter parts written in Fortran, C or C++, but are also numerically efficient. To illustrate this, a two-dimensional finite element code (ELLIPT2D) has been written. ELLIPT2D provides a flexible and easy-to-use framework for solving a large class of second-order elliptic problems. The program allows for structured or unstructured meshes. All functions defining the elliptic operator are user supplied and so are the boundary conditions, which can be of Dirichlet, Neumann or Robbins type. ELLIPT2D makes extensive use of dictionaries (hash tables) as a way to represent sparse matrices.Other key features of the Python language that have been widely used include: operator over loading, error handling, array slicing, and the Tkinter module for building graphical use interfaces. As an example of the utility of ELLIPT2D, a nonlinear solution of the Grad-Shafranov equation is computed using a Newton iterative scheme. A second application focuses on a solution of the toroidal Laplace equation coupled to a magnetohydrodynamic stability code, a problem arising in the context of magnetic fusion research.
NKG2D ligands mediate immunosurveillance of senescent cells.
Sagiv, Adi; Burton, Dominick G A; Moshayev, Zhana; Vadai, Ezra; Wensveen, Felix; Ben-Dor, Shifra; Golani, Ofra; Polic, Bojan; Krizhanovsky, Valery
2016-02-01
Cellular senescence is a stress response mechanism that limits tumorigenesis and tissue damage. Induction of cellular senescence commonly coincides with an immunogenic phenotype that promotes self-elimination by components of the immune system, thereby facilitating tumor suppression and limiting excess fibrosis during wound repair. The mechanisms by which senescent cells regulate their immune surveillance are not completely understood. Here we show that ligands of an activating Natural Killer (NK) cell receptor (NKG2D), MICA and ULBP2 are consistently up-regulated following induction of replicative senescence, oncogene-induced senescence and DNA damage - induced senescence. MICA and ULBP2 proteins are necessary for efficient NK-mediated cytotoxicity towards senescent fibroblasts. The mechanisms regulating the initial expression of NKG2D ligands in senescent cells are dependent on a DNA damage response, whilst continuous expression of these ligands is regulated by the ERK signaling pathway. In liver fibrosis, the accumulation of senescent activated stellate cells is increased in mice lacking NKG2D receptor leading to increased fibrosis. Overall, our results provide new insights into the mechanisms regulating the expression of immune ligands in senescent cells and reveal the importance of NKG2D receptor-ligand interaction in protecting against liver fibrosis. PMID:26878797
Proteomic Profiling of Macrophages by 2D Electrophoresis
Bouvet, Marion; Turkieh, Annie; Acosta-Martin, Adelina E.; Chwastyniak, Maggy; Beseme, Olivia; Amouyel, Philippe; Pinet, Florence
2014-01-01
The goal of the two-dimensional (2D) electrophoresis protocol described here is to show how to analyse the phenotype of human cultured macrophages. The key role of macrophages has been shown in various pathological disorders such as inflammatory, immunological, and infectious diseases. In this protocol, we use primary cultures of human monocyte-derived macrophages that can be differentiated into the M1 (pro-inflammatory) or the M2 (anti-inflammatory) phenotype. This in vitro model is reliable for studying the biological activities of M1 and M2 macrophages and also for a proteomic approach. Proteomic techniques are useful for comparing the phenotype and behaviour of M1 and M2 macrophages during host pathogenicity. 2D gel electrophoresis is a powerful proteomic technique for mapping large numbers of proteins or polypeptides simultaneously. We describe the protocol of 2D electrophoresis using fluorescent dyes, named 2D Differential Gel Electrophoresis (DIGE). The M1 and M2 macrophages proteins are labelled with cyanine dyes before separation by isoelectric focusing, according to their isoelectric point in the first dimension, and their molecular mass, in the second dimension. Separated protein or polypeptidic spots are then used to detect differences in protein or polypeptide expression levels. The proteomic approaches described here allows the investigation of the macrophage protein changes associated with various disorders like host pathogenicity or microbial toxins. PMID:25408153
2D signature for detection and identification of drugs
NASA Astrophysics Data System (ADS)
Trofimov, Vyacheslav A.; Varentsova, Svetlana A.; Shen, Jingling; Zhang, Cunlin; Zhou, Qingli; Shi, Yulei
2011-06-01
The method of spectral dynamics analysis (SDA-method) is used for obtaining the2D THz signature of drugs. This signature is used for the detection and identification of drugs with similar Fourier spectra by transmitted THz signal. We discuss the efficiency of SDA method for the identification problem of pure methamphetamine (MA), methylenedioxyamphetamine (MDA), 3, 4-methylenedioxymethamphetamine (MDMA) and Ketamine.
2-D Imaging of Electron Temperature in Tokamak Plasmas
T. Munsat; E. Mazzucato; H. Park; C.W. Domier; M. Johnson; N.C. Luhmann Jr.; J. Wang; Z. Xia; I.G.J. Classen; A.J.H. Donne; M.J. van de Pol
2004-07-08
By taking advantage of recent developments in millimeter wave imaging technology, an Electron Cyclotron Emission Imaging (ECEI) instrument, capable of simultaneously measuring 128 channels of localized electron temperature over a 2-D map in the poloidal plane, has been developed for the TEXTOR tokamak. Data from the new instrument, detailing the MHD activity associated with a sawtooth crash, is presented.
On the sensitivity of the 2D electromagnetic invisibility cloak
NASA Astrophysics Data System (ADS)
Kaproulias, S.; Sigalas, M. M.
2012-10-01
A computational study of the sensitivity of the two dimensional (2D) electromagnetic invisibility cloaks is performed with the finite element method. A circular metallic object is covered with the cloak and the effects of absorption, gain and disorder are examined. Also the effect of covering the cloak with a thin dielectric layer is studied.
Rheological Properties of Quasi-2D Fluids in Microgravity
NASA Technical Reports Server (NTRS)
Stannarius, Ralf; Trittel, Torsten; Eremin, Alexey; Harth, Kirsten; Clark, Noel; Maclennan, Joseph; Glaser, Matthew; Park, Cheol; Hall, Nancy; Tin, Padetha
2015-01-01
In recent years, research on complex fluids and fluids in restricted geometries has attracted much attention in the scientific community. This can be attributed not only to the development of novel materials based on complex fluids but also to a variety of important physical phenomena which have barely been explored. One example is the behavior of membranes and thin fluid films, which can be described by two-dimensional (2D) rheology behavior that is quite different from 3D fluids. In this study, we have investigated the rheological properties of freely suspended films of a thermotropic liquid crystal in microgravity experiments. This model system mimics isotropic and anisotropic quasi 2D fluids [46]. We use inkjet printing technology to dispense small droplets (inclusions) onto the film surface. The motion of these inclusions provides information on the rheological properties of the films and allows the study of a variety of flow instabilities. Flat films have been investigated on a sub-orbital rocket flight and curved films (bubbles) have been studied in the ISS project OASIS. Microgravity is essential when the films are curved in order to avoid sedimentation. The experiments yield the mobility of the droplets in the films as well as the mutual mobility of pairs of particles. Experimental results will be presented for 2D-isotropic (smectic-A) and 2D-nematic (smectic-C) phases.
NASA Astrophysics Data System (ADS)
Rowley-Neale, Samuel J.; Fearn, Jamie M.; Brownson, Dale A. C.; Smith, Graham C.; Ji, Xiaobo; Banks, Craig E.
2016-08-01
Two-dimensional molybdenum disulphide nanosheets (2D-MoS2) have proven to be an effective electrocatalyst, with particular attention being focused on their use towards increasing the efficiency of the reactions associated with hydrogen fuel cells. Whilst the majority of research has focused on the Hydrogen Evolution Reaction (HER), herein we explore the use of 2D-MoS2 as a potential electrocatalyst for the much less researched Oxygen Reduction Reaction (ORR). We stray from literature conventions and perform experiments in 0.1 M H2SO4 acidic electrolyte for the first time, evaluating the electrochemical performance of the ORR with 2D-MoS2 electrically wired/immobilised upon several carbon based electrodes (namely; Boron Doped Diamond (BDD), Edge Plane Pyrolytic Graphite (EPPG), Glassy Carbon (GC) and Screen-Printed Electrodes (SPE)) whilst exploring a range of 2D-MoS2 coverages/masses. Consequently, the findings of this study are highly applicable to real world fuel cell applications. We show that significant improvements in ORR activity can be achieved through the careful selection of the underlying/supporting carbon materials that electrically wire the 2D-MoS2 and utilisation of an optimal mass of 2D-MoS2. The ORR onset is observed to be reduced to ca. +0.10 V for EPPG, GC and SPEs at 2D-MoS2 (1524 ng cm-2 modification), which is far closer to Pt at +0.46 V compared to bare/unmodified EPPG, GC and SPE counterparts. This report is the first to demonstrate such beneficial electrochemical responses in acidic conditions using a 2D-MoS2 based electrocatalyst material on a carbon-based substrate (SPEs in this case). Investigation of the beneficial reaction mechanism reveals the ORR to occur via a 4 electron process in specific conditions; elsewhere a 2 electron process is observed. This work offers valuable insights for those wishing to design, fabricate and/or electrochemically test 2D-nanosheet materials towards the ORR.Two-dimensional molybdenum disulphide nanosheets
The NH2D hyperfine structure revealed by astrophysical observations
NASA Astrophysics Data System (ADS)
Daniel, F.; Coudert, L. H.; Punanova, A.; Harju, J.; Faure, A.; Roueff, E.; Sipilä, O.; Caselli, P.; Güsten, R.; Pon, A.; Pineda, J. E.
2016-02-01
Context. The 111-101 lines of ortho- and para-NH2D (o/p-NH2D) at 86 and 110 GHz, respectively, are commonly observed to provide constraints on the deuterium fractionation in the interstellar medium. In cold regions, the hyperfine structure that is due to the nitrogen (14N) nucleus is resolved. To date, this splitting is the only one that is taken into account in the NH2D column density estimates. Aims: We investigate how including the hyperfine splitting caused by the deuterium (D) nucleus affects the analysis of the rotational lines of NH2D. Methods: We present 30 m IRAM observations of the above mentioned lines and APEX o/p-NH2D observations of the 101-000 lines at 333 GHz. The hyperfine patterns of the observed lines were calculated taking into account the splitting induced by the D nucleus. The analysis then relies on line lists that either neglect or include the splitting induced by the D nucleus. Results: The hyperfine spectra are first analyzed with a line list that only includes the hyperfine splitting that is due to the 14N nucleus. We find inconsistencies between the line widths of the 101-000 and 111-101 lines, the latter being larger by a factor of ~1.6 ± 0.3. Such a large difference is unexpected because the two sets of lines probably originate from the same region. We next employed a newly computed line list for the o/p-NH2D transitions where the hyperfine structure induced by both nitrogen and deuterium nuclei was included. With this new line list, the analysis of the previous spectra leads to compatible line widths. Conclusions: Neglecting the hyperfine structure caused by D leads to overestimating the line widths of the o/p-NH2D lines at 3 mm. The error for a cold molecular core is about 50%. This error propagates directly to the column density estimate. We therefore recommend to take the hyperfine splittings caused by both the 14N and D nuclei into account in any analysis that relies on these lines. Based on observations carried out with the IRAM
Half-metallicity in 2D organometallic honeycomb frameworks
NASA Astrophysics Data System (ADS)
Sun, Hao; Li, Bin; Zhao, Jin
2016-10-01
Half-metallic materials with a high Curie temperature (T C) have many potential applications in spintronics. Magnetic metal free two-dimensional (2D) half-metallic materials with a honeycomb structure contain graphene-like Dirac bands with π orbitals and show excellent aspects in transport properties. In this article, by investigating a series of 2D organometallic frameworks with a honeycomb structure using first principles calculations, we study the origin of forming half-metallicity in this kind of 2D organometallic framework. Our analysis shows that charge transfer and covalent bonding are two crucial factors in the formation of half-metallicity in organometallic frameworks. (i) Sufficient charge transfer from metal atoms to the molecules is essential to form the magnetic centers. (ii) These magnetic centers need to be connected through covalent bonding, which guarantee the strong ferromagnetic (FM) coupling. As examples, the organometallic frameworks composed by (1,3,5)-benzenetricarbonitrile (TCB) molecules with noble metals (Au, Ag, Cu) show half-metallic properties with T C as high as 325 K. In these organometallic frameworks, the strong electronegative cyano-groups (CN groups) drive the charge transfer from metal atoms to the TCB molecules, forming the local magnetic centers. These magnetic centers experience strong FM coupling through the d-p covalent bonding. We propose that most of the 2D organometallic frameworks composed by molecule—CN—noble metal honeycomb structures contain similar half metallicity. This is verified by replacing TCB molecules with other organic molecules. Although the TCB-noble metal organometallic framework has not yet been synthesized, we believe the development of synthesizing techniques and facility will enable the realization of them. Our study provides new insight into the 2D half-metallic material design for the potential applications in nanotechnology.
Half-metallicity in 2D organometallic honeycomb frameworks.
Sun, Hao; Li, Bin; Zhao, Jin
2016-10-26
Half-metallic materials with a high Curie temperature (T C) have many potential applications in spintronics. Magnetic metal free two-dimensional (2D) half-metallic materials with a honeycomb structure contain graphene-like Dirac bands with π orbitals and show excellent aspects in transport properties. In this article, by investigating a series of 2D organometallic frameworks with a honeycomb structure using first principles calculations, we study the origin of forming half-metallicity in this kind of 2D organometallic framework. Our analysis shows that charge transfer and covalent bonding are two crucial factors in the formation of half-metallicity in organometallic frameworks. (i) Sufficient charge transfer from metal atoms to the molecules is essential to form the magnetic centers. (ii) These magnetic centers need to be connected through covalent bonding, which guarantee the strong ferromagnetic (FM) coupling. As examples, the organometallic frameworks composed by (1,3,5)-benzenetricarbonitrile (TCB) molecules with noble metals (Au, Ag, Cu) show half-metallic properties with T C as high as 325 K. In these organometallic frameworks, the strong electronegative cyano-groups (CN groups) drive the charge transfer from metal atoms to the TCB molecules, forming the local magnetic centers. These magnetic centers experience strong FM coupling through the d-p covalent bonding. We propose that most of the 2D organometallic frameworks composed by molecule-CN-noble metal honeycomb structures contain similar half metallicity. This is verified by replacing TCB molecules with other organic molecules. Although the TCB-noble metal organometallic framework has not yet been synthesized, we believe the development of synthesizing techniques and facility will enable the realization of them. Our study provides new insight into the 2D half-metallic material design for the potential applications in nanotechnology.
Half-metallicity in 2D organometallic honeycomb frameworks.
Sun, Hao; Li, Bin; Zhao, Jin
2016-10-26
Half-metallic materials with a high Curie temperature (T C) have many potential applications in spintronics. Magnetic metal free two-dimensional (2D) half-metallic materials with a honeycomb structure contain graphene-like Dirac bands with π orbitals and show excellent aspects in transport properties. In this article, by investigating a series of 2D organometallic frameworks with a honeycomb structure using first principles calculations, we study the origin of forming half-metallicity in this kind of 2D organometallic framework. Our analysis shows that charge transfer and covalent bonding are two crucial factors in the formation of half-metallicity in organometallic frameworks. (i) Sufficient charge transfer from metal atoms to the molecules is essential to form the magnetic centers. (ii) These magnetic centers need to be connected through covalent bonding, which guarantee the strong ferromagnetic (FM) coupling. As examples, the organometallic frameworks composed by (1,3,5)-benzenetricarbonitrile (TCB) molecules with noble metals (Au, Ag, Cu) show half-metallic properties with T C as high as 325 K. In these organometallic frameworks, the strong electronegative cyano-groups (CN groups) drive the charge transfer from metal atoms to the TCB molecules, forming the local magnetic centers. These magnetic centers experience strong FM coupling through the d-p covalent bonding. We propose that most of the 2D organometallic frameworks composed by molecule-CN-noble metal honeycomb structures contain similar half metallicity. This is verified by replacing TCB molecules with other organic molecules. Although the TCB-noble metal organometallic framework has not yet been synthesized, we believe the development of synthesizing techniques and facility will enable the realization of them. Our study provides new insight into the 2D half-metallic material design for the potential applications in nanotechnology. PMID:27541575
A 2D simulation model for urban flood management
NASA Astrophysics Data System (ADS)
Price, Roland; van der Wielen, Jonathan; Velickov, Slavco; Galvao, Diogo
2014-05-01
The European Floods Directive, which came into force on 26 November 2007, requires member states to assess all their water courses and coast lines for risk of flooding, to map flood extents and assets and humans at risk, and to take adequate and coordinated measures to reduce the flood risk in consultation with the public. Flood Risk Management Plans are to be in place by 2015. There are a number of reasons for the promotion of this Directive, not least because there has been much urban and other infrastructural development in flood plains, which puts many at risk of flooding along with vital societal assets. In addition there is growing awareness that the changing climate appears to be inducing more frequent extremes of rainfall with a consequent increases in the frequency of flooding. Thirdly, the growing urban populations in Europe, and especially in the developing countries, means that more people are being put at risk from a greater frequency of urban flooding in particular. There are urgent needs therefore to assess flood risk accurately and consistently, to reduce this risk where it is important to do so or where the benefit is greater than the damage cost, to improve flood forecasting and warning, to provide where necessary (and possible) flood insurance cover, and to involve all stakeholders in decision making affecting flood protection and flood risk management plans. Key data for assessing risk are water levels achieved or forecasted during a flood. Such levels should of course be monitored, but they also need to be predicted, whether for design or simulation. A 2D simulation model (PriceXD) solving the shallow water wave equations is presented specifically for determining flood risk, assessing flood defense schemes and generating flood forecasts and warnings. The simulation model is required to have a number of important properties: -Solve the full shallow water wave equations using a range of possible solutions; -Automatically adjust the time step and
Spatially embedded random networks.
Barnett, L; Di Paolo, E; Bullock, S
2007-11-01
Many real-world networks analyzed in modern network theory have a natural spatial element; e.g., the Internet, social networks, neural networks, etc. Yet, aside from a comparatively small number of somewhat specialized and domain-specific studies, the spatial element is mostly ignored and, in particular, its relation to network structure disregarded. In this paper we introduce a model framework to analyze the mediation of network structure by spatial embedding; specifically, we model connectivity as dependent on the distance between network nodes. Our spatially embedded random networks construction is not primarily intended as an accurate model of any specific class of real-world networks, but rather to gain intuition for the effects of spatial embedding on network structure; nevertheless we are able to demonstrate, in a quite general setting, some constraints of spatial embedding on connectivity such as the effects of spatial symmetry, conditions for scale free degree distributions and the existence of small-world spatial networks. We also derive some standard structural statistics for spatially embedded networks and illustrate the application of our model framework with concrete examples. PMID:18233726
Spatially embedded random networks
NASA Astrophysics Data System (ADS)
Barnett, L.; di Paolo, E.; Bullock, S.
2007-11-01
Many real-world networks analyzed in modern network theory have a natural spatial element; e.g., the Internet, social networks, neural networks, etc. Yet, aside from a comparatively small number of somewhat specialized and domain-specific studies, the spatial element is mostly ignored and, in particular, its relation to network structure disregarded. In this paper we introduce a model framework to analyze the mediation of network structure by spatial embedding; specifically, we model connectivity as dependent on the distance between network nodes. Our spatially embedded random networks construction is not primarily intended as an accurate model of any specific class of real-world networks, but rather to gain intuition for the effects of spatial embedding on network structure; nevertheless we are able to demonstrate, in a quite general setting, some constraints of spatial embedding on connectivity such as the effects of spatial symmetry, conditions for scale free degree distributions and the existence of small-world spatial networks. We also derive some standard structural statistics for spatially embedded networks and illustrate the application of our model framework with concrete examples.
Alizadeh, M.H. Mirzaei, M.; Razavi, H.
2008-03-04
A new inorganic-organic hybrid material based on polyoxometallate, [L-C{sub 2}H{sub 6}NO{sub 2}]{sub 3}[(PO{sub 4})Mo{sub 12}O{sub 36}].5H{sub 2}O, has been successfully synthesized and characterized by single-crystal X-ray analysis, elemental analysis, infrared and ultraviolet spectroscopy, proton nuclear magnetic resonance and differential thermal analysis techniques. The title compound crystallizes in the monoclinic space group, P2{sub 1}/c{sub ,} with a = 12.4938 (8) A, b = 19.9326 (12) A, c = 17.9270 (11) A, {beta} = 102.129 (1){sup o}, V = 4364.8 (5) A{sup 3}, Z = 4 and R{sub 1}(wR{sub 2}) = 0.0513, 0.0877. The most remarkable structural feature of this hybrid can be described as two-dimensional inorganic infinite plane-like (2D/{infinity} [(PO{sub 4})Mo{sub 12}O{sub 36}]{sup 3-}) which forming via weak Van der Waals interactions along the z axis. The characteristic band of the Keggin anion [(PO{sub 4})Mo{sub 12}O{sub 36}]{sup 3-} appears at 210 nm in the UV spectrum. Thermal analysis indicates that the Keggin anion skeleton begins to decompose at 520 deg. C.
Improved community model for social networks based on social mobility
NASA Astrophysics Data System (ADS)
Lu, Zhe-Ming; Wu, Zhen; Luo, Hao; Wang, Hao-Xian
2015-07-01
This paper proposes an improved community model for social networks based on social mobility. The relationship between the group distribution and the community size is investigated in terms of communication rate and turnover rate. The degree distributions, clustering coefficients, average distances and diameters of networks are analyzed. Experimental results demonstrate that the proposed model possesses the small-world property and can reproduce social networks effectively and efficiently.
2D-2D tunneling field-effect transistors using WSe2/SnSe2 heterostructures
NASA Astrophysics Data System (ADS)
Roy, Tania; Tosun, Mahmut; Hettick, Mark; Ahn, Geun Ho; Hu, Chenming; Javey, Ali
2016-02-01
Two-dimensional materials present a versatile platform for developing steep transistors due to their uniform thickness and sharp band edges. We demonstrate 2D-2D tunneling in a WSe2/SnSe2 van der Waals vertical heterojunction device, where WSe2 is used as the gate controlled p-layer and SnSe2 is the degenerately n-type layer. The van der Waals gap facilitates the regulation of band alignment at the heterojunction, without the necessity of a tunneling barrier. ZrO2 is used as the gate dielectric, allowing the scaling of gate oxide to improve device subthreshold swing. Efficient gate control and clean interfaces yield a subthreshold swing of ˜100 mV/dec for >2 decades of drain current at room temperature, hitherto unobserved in 2D-2D tunneling devices. The subthreshold swing is independent of temperature, which is a clear signature of band-to-band tunneling at the heterojunction. A maximum switching ratio ION/IOFF of 107 is obtained. Negative differential resistance in the forward bias characteristics is observed at 77 K. This work bodes well for the possibilities of two-dimensional materials for the realization of energy-efficient future-generation electronics.
NASA Astrophysics Data System (ADS)
Movassaghi, Babak; Rasche, Volker; Viergever, Max A.; Niessen, Wiro J.
2004-05-01
For the diagnosis of ischemic heart disease, accurate quantitative analysis of the coronary arteries is important. In coronary angiography, a number of projections is acquired from which 3D models of the coronaries can be reconstructed. A signifcant limitation of the current 3D modeling procedures is the required user interaction for defining the centerlines of the vessel structures in the 2D projections. Currently, the 3D centerlines of the coronary tree structure are calculated based on the interactively determined centerlines in two projections. For every interactively selected centerline point in a first projection the corresponding point in a second projection has to be determined interactively by the user. The correspondence is obtained based on the epipolar-geometry. In this paper a method is proposed to retrieve all the information required for the modeling procedure, by the interactive determination of the 2D centerline-points in only one projection. For every determined 2D centerline-point the corresponding 3D centerline-point is calculated by the analysis of the 1D gray value functions of the corresponding epipolarlines in space for all available 2D projections. This information is then used to build a 3D representation of the coronary arteries using coronary modeling techniques. The approach is illustrated on the analysis of calibrated phantom and calibrated coronary projection data.
Self-Healing Networks: Redundancy and Structure
Quattrociocchi, Walter; Caldarelli, Guido; Scala, Antonio
2014-01-01
We introduce the concept of self-healing in the field of complex networks modelling; in particular, self-healing capabilities are implemented through distributed communication protocols that exploit redundant links to recover the connectivity of the system. We then analyze the effect of the level of redundancy on the resilience to multiple failures; in particular, we measure the fraction of nodes still served for increasing levels of network damages. Finally, we study the effects of redundancy under different connectivity patterns—from planar grids, to small-world, up to scale-free networks—on healing performances. Small-world topologies show that introducing some long-range connections in planar grids greatly enhances the resilience to multiple failures with performances comparable to the case of the most resilient (and least realistic) scale-free structures. Obvious applications of self-healing are in the important field of infrastructural networks like gas, power, water, oil distribution systems. PMID:24533065
Measuring JHH values with a selective constant-time 2D NMR protocol
NASA Astrophysics Data System (ADS)
Lin, Liangjie; Wei, Zhiliang; Lin, Yanqin; Chen, Zhong
2016-11-01
Proton-proton scalar couplings play important roles in molecule structure elucidation. However, measurements of JHH values in complex coupled spin systems remain challenging. In this study, we develop a selective constant-time (SECT) 2D NMR protocol with which scalar coupling networks involving chosen protons can be revealed, and corresponding JHH values can be measured through doublets along the F1 dimension. All JHH values within a network of n fully coupled protons can be separately determined with (n - 1) SECT experiments. Additionally, the proposed pulse sequence possesses satisfactory sensitivity and handy implementation. Therefore, it will interest scientists who intend to address structural analyzes of molecules with overcrowded spectra, and may greatly facilitate the applications of scalar-coupling constants in molecule structure studies.
A novel class of strain gauges based on layered percolative films of 2D materials.
Hempel, Marek; Nezich, Daniel; Kong, Jing; Hofmann, Mario
2012-11-14
Here we report on the fabrication and characterization of a novel type of strain gauge based on percolative networks of 2D materials. The high sensitivity of the percolative carrier transport to strain induced morphology changes was exploited in strain sensors that can be produced from a wide variety of materials. Highly reliable and sensitive graphene-based thin film strain gauges were produced from solution processed graphene flakes by spray deposition. Control of the gauge sensitivity could be exerted through deposition-induced changes to the film morphology. This exceptional property was explained through modeling of the strain induced changes to the flake-flake overlap for different percolation networks. The ability to directly deposit strain gauges on complex-shaped and transparent surfaces was presented. The demonstrated scalable fabrication, superior sensitivity over conventional sensors, and unique properties of the described strain gauges have the potential to improve existing technology and open up new fields of applications for strain sensors.
NASA Astrophysics Data System (ADS)
Mitra, Bivas
is organized as follows. Section 2 presents an introduction to the Internet and different protocols related to it. This section also specifies the socio-technological properties of the Internet, like scale invariance, the small-world property, network resilience, etc. Section 3 describes the P2P networks, their categorization, and other related issues like search, stability, etc. Section 4 concludes the chapter.
Modeling floods in a dense urban area using 2D shallow water equations
NASA Astrophysics Data System (ADS)
Mignot, E.; Paquier, A.; Haider, S.
2006-07-01
SummaryA code solving the 2D shallow water equations by an explicit second-order scheme is used to simulate the severe October 1988 flood in the Richelieu urban locality of the French city of Nîmes. A reference calculation using a detailed description of the street network and of the cross-sections of the streets, considering impervious residence blocks and neglecting the flow interaction with the sewer network provides a mean peak water elevation 0.13 m lower than the measured flood marks with a standard deviation between the measured and computed water depths of 0.53 m. Sensitivity analysis of various topographical and numerical parameters shows that globally, the results keep the same level of accuracy, which reflects both the stability of the calculation method and the smoothening of results. However, the local flow modifications due to change of parameter values can drastically modify the local water depths, especially when the local flow regime is modified. Furthermore, the flow distribution to the downstream parts of the city can be altered depending on the set of parameters used. Finally, a second event, the 2002 flood, was simulated with the calibrated model providing results similar to 1988 flood calculation. Thus, the article shows that, after calibration, a 2D model can be used to help planning mitigation measures in a dense urban area.
A facile route for 3D aerogels from nanostructured 1D and 2D materials
Jung, Sung Mi; Jung, Hyun Young; Dresselhaus, Mildred S.; Jung, Yung Joon; Kong, Jing
2012-01-01
Aerogels have numerous applications due to their high surface area and low densities. However, creating aerogels from a large variety of materials has remained an outstanding challenge. Here, we report a new methodology to enable aerogel production with a wide range of materials. The method is based on the assembly of anisotropic nano-objects (one-dimensional (1D) nanotubes, nanowires, or two-dimensional (2D) nanosheets) into a cross-linking network from their colloidal suspensions at the transition from the semi-dilute to the isotropic concentrated regime. The resultant aerogels have highly porous and ultrafine three-dimensional (3D) networks consisting of 1D (Ag, Si, MnO2, single-walled carbon nanotubes (SWNTs)) and 2D materials (MoS2, graphene, h-BN) with high surface areas, low densities, and high electrical conductivities. This method opens up a facile route for aerogel production with a wide variety of materials and tremendous opportunities for bio-scaffold, energy storage, thermoelectric, catalysis, and hydrogen storage applications. PMID:23152940
CHARACTERIZATION BY SEM OF THE PYROCARBON FIBER COATING IN 2D-SIC/CVI-SIC
Youngblood, Gerald E.
2011-03-23
The previous report examined electrical conductivity (EC) data from RT to 800°C for several forms of two-dimensional silicon carbide composite made with a chemical vapor infiltration (CVI) matrix (2D-SiC/CVI-SiC), an important quantity needed for the design of an FCI. We found that both in-plane and transverse EC-values for 2D-SiC/CVI-SiC strongly depended on the total thickness of the highly conductive pyrocarbon (PyC) fiber coating and the alignment of the carbon coating network. Furthermore, the transverse EC depended on the degree of interconnectivity of this network. For our EC-modeling efforts we used either “nominal” coating thickness values provided by the composite fabricator or we made thickness estimates based on a limited number of fiber cross-section examinations using SEM. Because of the importance of using a truly representative coating thickness value in our analysis, we examined numerous new SEM cross-sectional views to reassess the reliability of our limited number of original coating thickness measurements as well as to obtain an estimate of the variation in thickness values for different composite configurations.
RGB-D SLAM Based on Extended Bundle Adjustment with 2D and 3D Information
Di, Kaichang; Zhao, Qiang; Wan, Wenhui; Wang, Yexin; Gao, Yunjun
2016-01-01
In the study of SLAM problem using an RGB-D camera, depth information and visual information as two types of primary measurement data are rarely tightly coupled during refinement of camera pose estimation. In this paper, a new method of RGB-D camera SLAM is proposed based on extended bundle adjustment with integrated 2D and 3D information on the basis of a new projection model. First, the geometric relationship between the image plane coordinates and the depth values is constructed through RGB-D camera calibration. Then, 2D and 3D feature points are automatically extracted and matched between consecutive frames to build a continuous image network. Finally, extended bundle adjustment based on the new projection model, which takes both image and depth measurements into consideration, is applied to the image network for high-precision pose estimation. Field experiments show that the proposed method has a notably better performance than the traditional method, and the experimental results demonstrate the effectiveness of the proposed method in improving localization accuracy. PMID:27529256
RGB-D SLAM Based on Extended Bundle Adjustment with 2D and 3D Information.
Di, Kaichang; Zhao, Qiang; Wan, Wenhui; Wang, Yexin; Gao, Yunjun
2016-08-13
In the study of SLAM problem using an RGB-D camera, depth information and visual information as two types of primary measurement data are rarely tightly coupled during refinement of camera pose estimation. In this paper, a new method of RGB-D camera SLAM is proposed based on extended bundle adjustment with integrated 2D and 3D information on the basis of a new projection model. First, the geometric relationship between the image plane coordinates and the depth values is constructed through RGB-D camera calibration. Then, 2D and 3D feature points are automatically extracted and matched between consecutive frames to build a continuous image network. Finally, extended bundle adjustment based on the new projection model, which takes both image and depth measurements into consideration, is applied to the image network for high-precision pose estimation. Field experiments show that the proposed method has a notably better performance than the traditional method, and the experimental results demonstrate the effectiveness of the proposed method in improving localization accuracy.
RGB-D SLAM Based on Extended Bundle Adjustment with 2D and 3D Information.
Di, Kaichang; Zhao, Qiang; Wan, Wenhui; Wang, Yexin; Gao, Yunjun
2016-01-01
In the study of SLAM problem using an RGB-D camera, depth information and visual information as two types of primary measurement data are rarely tightly coupled during refinement of camera pose estimation. In this paper, a new method of RGB-D camera SLAM is proposed based on extended bundle adjustment with integrated 2D and 3D information on the basis of a new projection model. First, the geometric relationship between the image plane coordinates and the depth values is constructed through RGB-D camera calibration. Then, 2D and 3D feature points are automatically extracted and matched between consecutive frames to build a continuous image network. Finally, extended bundle adjustment based on the new projection model, which takes both image and depth measurements into consideration, is applied to the image network for high-precision pose estimation. Field experiments show that the proposed method has a notably better performance than the traditional method, and the experimental results demonstrate the effectiveness of the proposed method in improving localization accuracy. PMID:27529256