Epidemics in small world networks
NASA Astrophysics Data System (ADS)
Telo da Gama, M. M.; Nunes, A.
2006-03-01
For many infectious diseases, a small-world network on an underlying regular lattice is a suitable simplified model for the contact structure of the host population. It is well known that the contact network, described in this setting by a single parameter, the small-world parameter p, plays an important role both in the short term and in the long term dynamics of epidemic spread. We have studied the effect of the network structure on models of immune for life diseases and found that in addition to the reduction of the effective transmission rate, through the screening of infectives, spatial correlations may strongly enhance the stochastic fluctuations. As a consequence, time series of unforced Susceptible-Exposed-Infected-Recovered (SEIR) models provide patterns of recurrent epidemics with realistic amplitudes, suggesting that these models together with complex networks of contacts are the key ingredients to describe the prevaccination dynamical patterns of diseases such as measles and pertussis. We have also studied the role of the host contact strucuture in pathogen antigenic variation, through its effect on the final outcome of an invasion by a viral strain of a population where a very similar virus is endemic. Similar viral strains are modelled by the same infection and reinfection parameters, and by a given degree of cross immunity that represents the antigenic distance between the competing strains. We have found, somewhat surprisingly, that clustering on the network decreases the potential to sustain pathogen diversity.
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.
Collective dynamics of 'small-world' networks.
Watts, D J; Strogatz, S H
1998-06-04
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…
Small-World Brain Networks Revisited
Bassett, Danielle S.; Bullmore, Edward T.
2016-01-01
It is nearly 20 years since the concept of a small-world network was first quantitatively defined, by a combination of high clustering and short path length; and about 10 years since this metric of complex network topology began to be widely applied to analysis of neuroimaging and other neuroscience data as part of the rapid growth of the new field of connectomics. Here, we review briefly the foundational concepts of graph theoretical estimation and generation of small-world networks. We take stock of some of the key developments in the field in the past decade and we consider in some detail the implications of recent studies using high-resolution tract-tracing methods to map the anatomical networks of the macaque and the mouse. In doing so, we draw attention to the important methodological distinction between topological analysis of binary or unweighted graphs, which have provided a popular but simple approach to brain network analysis in the past, and the topology of weighted graphs, which retain more biologically relevant information and are more appropriate to the increasingly sophisticated data on brain connectivity emerging from contemporary tract-tracing and other imaging studies. We conclude by highlighting some possible future trends in the further development of weighted small-worldness as part of a deeper and broader understanding of the topology and the functional value of the strong and weak links between areas of mammalian cortex. PMID:27655008
Blackmail propagation on small-world networks
NASA Astrophysics Data System (ADS)
Shao, Zhi-Gang; Jian-Ping Sang; Zou, Xian-Wu; Tan, Zhi-Jie; Jin, Zhun-Zhi
2005-06-01
The dynamics of the blackmail propagation model based on small-world networks is investigated. It is found that for a given transmitting probability λ the dynamical behavior of blackmail propagation transits from linear growth type to logistical growth one with the network randomness p increases. The transition takes place at the critical network randomness pc=1/N, where N is the total number of nodes in the network. For a given network randomness p the dynamical behavior of blackmail propagation transits from exponential decrease type to logistical growth one with the transmitting probability λ increases. The transition occurs at the critical transmitting probability λc=1/
Social influence in small-world networks
NASA Astrophysics Data System (ADS)
Sun, Kai; Mao, Xiao-Ming; Ouyang, Qi
2002-12-01
We report on our numerical studies of the Axelrod model for social influence in small-world networks. Our simulation results show that the topology of the network has a crucial effect on the evolution of cultures. As the randomness of the network increases, the system undergoes a transition from a highly fragmented phase to a uniform phase. We also find that the power-law distribution at the transition point, reported by Castellano et al, is not a critical phenomenon; it exists not only at the onset of transition but also for almost any control parameters. All these power-law distributions are stable against perturbations. A mean-field theory is developed to explain these phenomena.
Small-World Network Spectra in Mean-Field Theory
NASA Astrophysics Data System (ADS)
Grabow, Carsten; Grosskinsky, Stefan; Timme, Marc
2012-05-01
Collective dynamics on small-world networks emerge in a broad range of systems with their spectra characterizing fundamental asymptotic features. Here we derive analytic mean-field predictions for the spectra of small-world models that systematically interpolate between regular and random topologies by varying their randomness. These theoretical predictions agree well with the actual spectra (obtained by numerical diagonalization) for undirected and directed networks and from fully regular to strongly random topologies. These results may provide analytical insights to empirically found features of dynamics on small-world networks from various research fields, including biology, physics, engineering, and social science.
Geometric Assortative Growth Model for Small-World Networks
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
Network marketing on a small-world network
NASA Astrophysics Data System (ADS)
Kim, Beom Jun; Jun, Tackseung; Kim, Jeong-Yoo; Choi, M. Y.
2006-02-01
We investigate a dynamic model of network marketing in a small-world network structure artificially constructed similarly to the Watts-Strogatz network model. Different from the traditional marketing, consumers can also play the role of the manufacturer's selling agents in network marketing, which is stimulated by the referral fee the manufacturer offers. As the wiring probability α is increased from zero to unity, the network changes from the one-dimensional regular directed network to the star network where all but one player are connected to one consumer. The price p of the product and the referral fee r are used as free parameters to maximize the profit of the manufacturer. It is observed that at α=0 the maximized profit is constant independent of the network size N while at α≠0, it increases linearly with N. This is in parallel to the small-world transition. It is also revealed that while the optimal value of p stays at an almost constant level in a broad range of α, that of r is sensitive to a change in the network structure. The consumer surplus is also studied and discussed.
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.
Characterization and control of small-world networks.
Pandit, S A; Amritkar, R E
1999-08-01
Recently, Watts and Strogatz [Nature (London) 393, 440 (1998)] offered an interesting model of small-world networks. Here we concretize the concept of a "faraway" connection in a network by defining a far edge. Our definition is algorithmic and independent of any external parameters such as topology of the underlying space of the network. We show that it is possible to control the spread of an epidemic by using the knowledge of far edges. We also suggest a model for better product advertisement using the far edges. Our findings indicate that the number of far edges can be a good intrinsic parameter to characterize small-world phenomena.
Characterization and control of small-world networks
NASA Astrophysics Data System (ADS)
Pandit, S. A.; Amritkar, R. E.
1999-08-01
Recently, Watts and Strogatz [Nature (London) 393, 440 (1998)] offered an interesting model of small-world networks. Here we concretize the concept of a ``faraway'' connection in a network by defining a far edge. Our definition is algorithmic and independent of any external parameters such as topology of the underlying space of the network. We show that it is possible to control the spread of an epidemic by using the knowledge of far edges. We also suggest a model for better product advertisement using the far edges. Our findings indicate that the number of far edges can be a good intrinsic parameter to characterize small-world phenomena.
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.
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.
Collective relaxation dynamics of small-world networks
NASA Astrophysics Data System (ADS)
Grabow, Carsten; Grosskinsky, Stefan; Kurths, Jürgen; Timme, Marc
2015-05-01
Complex networks exhibit a wide range of collective dynamic phenomena, including synchronization, diffusion, relaxation, and coordination processes. Their asymptotic dynamics is generically characterized by the local Jacobian, graph Laplacian, or a similar linear operator. The structure of networks with regular, small-world, and random connectivities are reasonably well understood, but their collective dynamical properties remain largely unknown. Here we present a two-stage mean-field theory to derive analytic expressions for network spectra. A single formula covers the spectrum from regular via small-world to strongly randomized topologies in Watts-Strogatz networks, explaining the simultaneous dependencies on network size N , average degree k , and topological randomness q . We present simplified analytic predictions for the second-largest and smallest eigenvalue, and numerical checks confirm our theoretical predictions for zero, small, and moderate topological randomness q , including the entire small-world regime. For large q of the order of one, we apply standard random matrix theory, thereby overarching the full range from regular to randomized network topologies. These results may contribute to our analytic and mechanistic understanding of collective relaxation phenomena of network dynamical systems.
Scaling and percolation in the small-world network model
NASA Astrophysics Data System (ADS)
Newman, M. E. J.; Watts, D. J.
1999-12-01
In this paper we study the small-world network model of Watts and Strogatz, which mimics some aspects of the structure of networks of social interactions. We argue that there is one nontrivial length-scale in the model, analogous to the correlation length in other systems, which is well-defined in the limit of infinite system size and which diverges continuously as the randomness in the network tends to zero, giving a normal critical point in this limit. This length-scale governs the crossover from large- to small-world behavior in the model, as well as the number of vertices in a neighborhood of given radius on the network. We derive the value of the single critical exponent controlling behavior in the critical region and the finite size scaling form for the average vertex-vertex distance on the network, and, using series expansion and Padé approximants, find an approximate analytic form for the scaling function. We calculate the effective dimension of small-world graphs and show that this dimension varies as a function of the length-scale on which it is measured, in a manner reminiscent of multifractals. We also study the problem of site percolation on small-world networks as a simple model of disease propagation, and derive an approximate expression for the percolation probability at which a giant component of connected vertices first forms (in epidemiological terms, the point at which an epidemic occurs). The typical cluster radius satisfies the expected finite size scaling form with a cluster size exponent close to that for a random graph. All our analytic results are confirmed by extensive numerical simulations of the model.
Small-world human brain networks: Perspectives and challenges.
Liao, Xuhong; Vasilakos, Athanasios V; He, Yong
2017-06-01
Modelling the human brain as a complex network has provided a powerful mathematical framework to characterize the structural and functional architectures of the brain. In the past decade, the combination of non-invasive neuroimaging techniques and graph theoretical approaches enable us to map human structural and functional connectivity patterns (i.e., connectome) at the macroscopic level. One of the most influential findings is that human brain networks exhibit prominent small-world organization. Such a network architecture in the human brain facilitates efficient information segregation and integration at low wiring and energy costs, which presumably results from natural selection under the pressure of a cost-efficiency balance. Moreover, the small-world organization undergoes continuous changes during normal development and ageing and exhibits dramatic alterations in neurological and psychiatric disorders. In this review, we survey recent advances regarding the small-world architecture in human brain networks and highlight the potential implications and applications in multidisciplinary fields, including cognitive neuroscience, medicine and engineering. Finally, we highlight several challenging issues and areas for future research in this rapidly growing field. Copyright © 2017 Elsevier Ltd. All rights reserved.
Coordination sequences and information spreading in small-world networks
NASA Astrophysics Data System (ADS)
Herrero, Carlos P.
2002-10-01
We study the spread of information in small-world networks generated from different d-dimensional regular lattices, with d=1, 2, and 3. With this purpose, we analyze by numerical simulations the behavior of the coordination sequence, e.g., the average number of sites C(n) that can be reached from a given node of the network in n steps along its bonds. For sufficiently large networks, we find an asymptotic behavior C(n)~ρn, with a constant ρ that depends on the network dimension d and on the rewiring probability p (which measures the disorder strength of a given network). A simple model of information spreading in these networks is studied, assuming that only a fraction q of the network sites are active. The number of active nodes reached in n steps has an asymptotic form λn, λ being a constant that depends on p and q, as well as on the dimension d of the underlying lattice. The information spreading presents two different regimes depending on the value of λ: For λ>1 the information propagates along the whole system, and for λ<1 the spreading is damped and the information remains confined in a limited region of the network. We discuss the connection of these results with site percolation in small-world networks.
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
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.
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.
Time reversibility of quantum diffusion in small-world networks
NASA Astrophysics Data System (ADS)
Han, Sung-Guk; Kim, Beom Jun
2012-02-01
We study the time-reversal dynamics of a tight-binding electron in the Watts-Strogatz (WS) small-world networks. The localized initial wave packet at time t = 0 diffuses as time proceeds until the time-reversal operation, together with the momentum perturbation of the strength η, is made at the reversal time T. The time irreversibility is measured by I = |Π( t = 2 T) - Π( t = 0)|, where Π is the participation ratio gauging the extendedness of the wavefunction and for convenience, t is measured forward even after the time reversal. When η = 0, the time evolution after T makes the wavefunction at t = 2 T identical to the one at t = 0, and we find I = 0, implying a null irreversibility or a complete reversibility. On the other hand, as η is increased from zero, the reversibility becomes weaker, and we observe enhancement of the irreversibility. We find that I linearly increases with increasing η in the weakly-perturbed region, and that the irreversibility is much stronger in the WS network than in the local regular network.
Small-world networks exhibit pronounced intermittent synchronization
NASA Astrophysics Data System (ADS)
Choudhary, Anshul; Mitra, Chiranjit; Kohar, Vivek; Sinha, Sudeshna; Kurths, Jürgen
2017-11-01
We report the phenomenon of temporally intermittently synchronized and desynchronized dynamics in Watts-Strogatz networks of chaotic Rössler oscillators. We consider topologies for which the master stability function (MSF) predicts stable synchronized behaviour, as the rewiring probability (p) is tuned from 0 to 1. MSF essentially utilizes the largest non-zero Lyapunov exponent transversal to the synchronization manifold in making stability considerations, thereby ignoring the other Lyapunov exponents. However, for an N-node networked dynamical system, we observe that the difference in its Lyapunov spectra (corresponding to the N - 1 directions transversal to the synchronization manifold) is crucial and serves as an indicator of the presence of intermittently synchronized behaviour. In addition to the linear stability-based (MSF) analysis, we further provide global stability estimate in terms of the fraction of state-space volume shared by the intermittently synchronized state, as p is varied from 0 to 1. This fraction becomes appreciably large in the small-world regime, which is surprising, since this limit has been otherwise considered optimal for synchronized dynamics. Finally, we characterize the nature of the observed intermittency and its dominance in state-space as network rewiring probability (p) is varied.
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.
Constructing a Watts-Strogatz network from a small-world network with symmetric degree distribution.
Menezes, Mozart B C; Kim, Seokjin; Huang, Rongbing
2017-01-01
Though the small-world phenomenon is widespread in many real networks, it is still challenging to replicate a large network at the full scale for further study on its structure and dynamics when sufficient data are not readily available. We propose a method to construct a Watts-Strogatz network using a sample from a small-world network with symmetric degree distribution. Our method yields an estimated degree distribution which fits closely with that of a Watts-Strogatz network and leads into accurate estimates of network metrics such as clustering coefficient and degree of separation. We observe that the accuracy of our method increases as network size increases.
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
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.
From brain to earth and climate systems: small-world interaction networks or not?
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).
Infection dynamics on spatial small-world network models
NASA Astrophysics Data System (ADS)
Iotti, Bryan; Antonioni, Alberto; Bullock, Seth; Darabos, Christian; Tomassini, Marco; Giacobini, Mario
2017-11-01
The study of complex networks, and in particular of social networks, has mostly concentrated on relational networks, abstracting the distance between nodes. Spatial networks are, however, extremely relevant in our daily lives, and a large body of research exists to show that the distances between nodes greatly influence the cost and probability of establishing and maintaining a link. A random geometric graph (RGG) is the main type of synthetic network model used to mimic the statistical properties and behavior of many social networks. We propose a model, called REDS, that extends energy-constrained RGGs to account for the synergic effect of sharing the cost of a link with our neighbors, as is observed in real relational networks. We apply both the standard Watts-Strogatz rewiring procedure and another method that conserves the degree distribution of the network. The second technique was developed to eliminate unwanted forms of spatial correlation between the degree of nodes that are affected by rewiring, limiting the effect on other properties such as clustering and assortativity. We analyze both the statistical properties of these two network types and their epidemiological behavior when used as a substrate for a standard susceptible-infected-susceptible compartmental model. We consider and discuss the differences in properties and behavior between RGGs and REDS as rewiring increases and as infection parameters are changed. We report considerable differences both between the network types and, in the case of REDS, between the two rewiring schemes. We conclude that REDS represent, with the application of these rewiring mechanisms, extremely useful and interesting tools in the study of social and epidemiological phenomena in synthetic complex networks.
Right-side-stretched multifractal spectra indicate small-worldness in networks
NASA Astrophysics Data System (ADS)
Oświȩcimka, Paweł; Livi, Lorenzo; Drożdż, Stanisław
2018-04-01
Complex network formalism allows to explain the behavior of systems composed by interacting units. Several prototypical network models have been proposed thus far. The small-world model has been introduced to mimic two important features observed in real-world systems: i) local clustering and ii) the possibility to move across a network by means of long-range links that significantly reduce the characteristic path length. A natural question would be whether there exist several ;types; of small-world architectures, giving rise to a continuum of models with properties (partially) shared with other models belonging to different network families. Here, we take advantage of the interplay between network theory and time series analysis and propose to investigate small-world signatures in complex networks by analyzing multifractal characteristics of time series generated from such networks. In particular, we suggest that the degree of right-sided asymmetry of multifractal spectra is linked with the degree of small-worldness present in networks. This claim is supported by numerical simulations performed on several parametric models, including prototypical small-world networks, scale-free, fractal and also real-world networks describing protein molecules. Our results also indicate that right-sided asymmetry emerges with the presence of the following topological properties: low edge density, low average shortest path, and high clustering coefficient.
Trade-offs between robustness and small-world effect in complex networks
Peng, Guan-Sheng; Tan, Suo-Yi; Wu, Jun; Holme, Petter
2016-01-01
Robustness and small-world effect are two crucial structural features of complex networks and have attracted increasing attention. However, little is known about the relation between them. Here we demonstrate that, there is a conflicting relation between robustness and small-world effect for a given degree sequence. We suggest that the robustness-oriented optimization will weaken the small-world effect and vice versa. Then, we propose a multi-objective trade-off optimization model and develop a heuristic algorithm to obtain the optimal trade-off topology for robustness and small-world effect. We show that the optimal network topology exhibits a pronounced core-periphery structure and investigate the structural properties of the optimized networks in detail. PMID:27853301
Damage spreading in spatial and small-world random Boolean networks
NASA Astrophysics Data System (ADS)
Lu, Qiming; Teuscher, Christof
2014-02-01
The study of the response of complex dynamical social, biological, or technological networks to external perturbations has numerous applications. Random Boolean networks (RBNs) are commonly used as a simple generic model for certain dynamics of complex systems. Traditionally, RBNs are interconnected randomly and without considering any spatial extension and arrangement of the links and nodes. However, most real-world networks are spatially extended and arranged with regular, power-law, small-world, or other nonrandom connections. Here we explore the RBN network topology between extreme local connections, random small-world, and pure random networks, and study the damage spreading with small perturbations. We find that spatially local connections change the scaling of the Hamming distance at very low connectivities (K¯≪1) and that the critical connectivity of stability Ks changes compared to random networks. At higher K¯, this scaling remains unchanged. We also show that the Hamming distance of spatially local networks scales with a power law as the system size N increases, but with a different exponent for local and small-world networks. The scaling arguments for small-world networks are obtained with respect to the system sizes and strength of spatially local connections. We further investigate the wiring cost of the networks. From an engineering perspective, our new findings provide the key design trade-offs between damage spreading (robustness), the network's wiring cost, and the network's communication characteristics.
Temporal efficiency evaluation and small-worldness characterization in temporal networks
NASA Astrophysics Data System (ADS)
Dai, Zhongxiang; Chen, Yu; Li, Junhua; Fam, Johnson; Bezerianos, Anastasios; Sun, Yu
2016-09-01
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.
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
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.
Potts Model in One-Dimension on Directed Small-World Networks
NASA Astrophysics Data System (ADS)
Aquino, Édio O.; Lima, F. W. S.; Araújo, Ascânio D.; Costa Filho, Raimundo N.
2018-06-01
The critical properties of the Potts model with q=3 and 8 states in one-dimension on directed small-world networks are investigated. This disordered system is simulated by updating it with the Monte Carlo heat bath algorithm. The Potts model on these directed small-world networks presents in fact a second-order phase transition with a new set of critical exponents for q=3 considering a rewiring probability p=0.1. For q=8 the system exhibits only a first-order phase transition independent of p.
On the structural properties of small-world networks with range-limited shortcut links
NASA Astrophysics Data System (ADS)
Jia, Tao; Kulkarni, Rahul V.
2013-12-01
We explore a new variant of Small-World Networks (SWNs), in which an additional parameter (r) sets the length scale over which shortcuts are uniformly distributed. When r=0 we have an ordered network, whereas r=1 corresponds to the original Watts-Strogatz SWN model. These limited range SWNs have a similar degree distribution and scaling properties as the original SWN model. We observe the small-world phenomenon for r≪1, indicating that global shortcuts are not necessary for the small-world effect. For limited range SWNs, the average path length changes nonmonotonically with system size, whereas for the original SWN model it increases monotonically. We propose an expression for the average path length for limited range SWNs based on numerical simulations and analytical approximations.
The Conundrum of Functional Brain Networks: Small-World Efficiency or Fractal Modularity
Gallos, Lazaros K.; Sigman, Mariano; Makse, Hernán A.
2012-01-01
The human brain has been studied at multiple scales, from neurons, circuits, areas with well-defined anatomical and functional boundaries, to large-scale functional networks which mediate coherent cognition. In a recent work, we addressed the problem of the hierarchical organization in the brain through network analysis. Our analysis identified functional brain modules of fractal structure that were inter-connected in a small-world topology. Here, we provide more details on the use of network science tools to elaborate on this behavior. We indicate the importance of using percolation theory to highlight the modular character of the functional brain network. These modules present a fractal, self-similar topology, identified through fractal network methods. When we lower the threshold of correlations to include weaker ties, the network as a whole assumes a small-world character. These weak ties are organized precisely as predicted by theory maximizing information transfer with minimal wiring costs. PMID:22586406
Critical behavior of the contact process on small-world networks
NASA Astrophysics Data System (ADS)
Ferreira, Ronan S.; Ferreira, Silvio C.
2013-11-01
We investigate the role of clustering on the critical behavior of the contact process (CP) on small-world networks using the Watts-Strogatz (WS) network model with an edge rewiring probability p. The critical point is well predicted by a homogeneous cluster-approximation for the limit of vanishing clustering ( p → 1). The critical exponents and dimensionless moment ratios of the CP are in agreement with those predicted by the mean-field theory for any p > 0. This independence on the network clustering shows that the small-world property is a sufficient condition for the mean-field theory to correctly predict the universality of the model. Moreover, we compare the CP dynamics on WS networks with rewiring probability p = 1 and random regular networks and show that the weak heterogeneity of the WS network slightly changes the critical point but does not alter other critical quantities of the model.
Emergence of small-world structure in networks of spiking neurons through STDP plasticity.
Basalyga, Gleb; Gleiser, Pablo M; Wennekers, Thomas
2011-01-01
In this work, we use a complex network approach to investigate how a neural network structure changes under synaptic plasticity. In particular, we consider a network of conductance-based, single-compartment integrate-and-fire excitatory and inhibitory neurons. Initially the neurons are connected randomly with uniformly distributed synaptic weights. The weights of excitatory connections can be strengthened or weakened during spiking activity by the mechanism known as spike-timing-dependent plasticity (STDP). We extract a binary directed connection matrix by thresholding the weights of the excitatory connections at every simulation step and calculate its major topological characteristics such as the network clustering coefficient, characteristic path length and small-world index. We numerically demonstrate that, under certain conditions, a nontrivial small-world structure can emerge from a random initial network subject to STDP learning.
NASA Astrophysics Data System (ADS)
Boaretto, B. R. R.; Budzinski, R. C.; Prado, T. L.; Kurths, J.; Lopes, S. R.
2018-05-01
It is known that neural networks under small-world topology can present anomalous synchronization and nonstationary behavior for weak coupling regimes. Here, we propose methods to suppress the anomalous synchronization and also to diminish the nonstationary behavior occurring in weakly coupled neural network under small-world topology. We consider a network of 2000 thermally sensitive identical neurons, based on the model of Hodgkin-Huxley in a small-world topology, with the probability of adding non local connection equal to p = 0 . 001. Based on experimental protocols to suppress anomalous synchronization, as well as nonstationary behavior of the neural network dynamics, we make use of (i) external stimulus (pulsed current); (ii) biologic parameters changing (neuron membrane conductance changes); and (iii) body temperature changes. Quantification analysis to evaluate phase synchronization makes use of the Kuramoto's order parameter, while recurrence quantification analysis, particularly the determinism, computed over the easily accessible mean field of network, the local field potential (LFP), is used to evaluate nonstationary states. We show that the methods proposed can control the anomalous synchronization and nonstationarity occurring for weak coupling parameter without any effect on the individual neuron dynamics, neither in the expected asymptotic synchronized states occurring for large values of the coupling parameter.
Critical behavior and correlations on scale-free small-world networks: Application to network design
NASA Astrophysics Data System (ADS)
Ostilli, M.; Ferreira, A. L.; Mendes, J. F. F.
2011-06-01
We analyze critical phenomena on networks generated as the union of hidden variable models (networks with any desired degree sequence) with arbitrary graphs. The resulting networks are general small worlds similar to those à la Watts and Strogatz, but with a heterogeneous degree distribution. We prove that the critical behavior (thermal or percolative) remains completely unchanged by the presence of finite loops (or finite clustering). Then, we show that, in large but finite networks, correlations of two given spins may be strong, i.e., approximately power-law-like, at any temperature. Quite interestingly, if γ is the exponent for the power-law distribution of the vertex degree, for γ⩽3 and with or without short-range couplings, such strong correlations persist even in the thermodynamic limit, contradicting the common opinion that, in mean-field models, correlations always disappear in this limit. Finally, we provide the optimal choice of rewiring under which percolation phenomena in the rewired network are best performed, a natural criterion to reach best communication features, at least in noncongested regimes.
Driving and driven architectures of directed small-world human brain functional networks.
Yan, Chaogan; He, Yong
2011-01-01
Recently, increasing attention has been focused on the investigation of the human brain connectome that describes the patterns of structural and functional connectivity networks of the human brain. Many studies of the human connectome have demonstrated that the brain network follows a small-world topology with an intrinsically cohesive modular structure and includes several network hubs in the medial parietal regions. However, most of these studies have only focused on undirected connections between regions in which the directions of information flow are not taken into account. How the brain regions causally influence each other and how the directed network of human brain is topologically organized remain largely unknown. Here, we applied linear multivariate Granger causality analysis (GCA) and graph theoretical approaches to a resting-state functional MRI dataset with a large cohort of young healthy participants (n = 86) to explore connectivity patterns of the population-based whole-brain functional directed network. This directed brain network exhibited prominent small-world properties, which obviously improved previous results of functional MRI studies showing weak small-world properties in the directed brain networks in terms of a kernel-based GCA and individual analysis. This brain network also showed significant modular structures associated with 5 well known subsystems: fronto-parietal, visual, paralimbic/limbic, subcortical and primary systems. Importantly, we identified several driving hubs predominantly located in the components of the attentional network (e.g., the inferior frontal gyrus, supplementary motor area, insula and fusiform gyrus) and several driven hubs predominantly located in the components of the default mode network (e.g., the precuneus, posterior cingulate gyrus, medial prefrontal cortex and inferior parietal lobule). Further split-half analyses indicated that our results were highly reproducible between two independent subgroups. The
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.
Phase Transitions of an Epidemic Spreading Model in Small-World Networks
NASA Astrophysics Data System (ADS)
Hua, Da-Yin; Gao, Ke
2011-06-01
We propose a modified susceptible-infected-refractory-susceptible (SIRS) model to investigate the global oscillations of the epidemic spreading in Watts—Strogatz (WS) small-world networks. It is found that when an individual immunity does not change or decays slowly in an immune period, the system can exhibit complex transition from an infecting stationary state to a large amplitude sustained oscillation or an absorbing state with no infection. When the immunity decays rapidly in the immune period, the transition to the global oscillation disappears and there is no oscillation. Furthermore, based on the spatio-temporal evolution patterns and the phase diagram, it is disclosed that a long immunity period takes an important role in the emergence of the global oscillation in small-world networks.
Small-worldness characteristics and its gender relation in specific hemispheric networks.
Miraglia, F; Vecchio, F; Bramanti, P; Rossini, P M
2015-12-03
Aim of this study was to verify whether the topological organization of human brain functional networks is different for males and females in resting state EEGs. Undirected and weighted brain networks were computed by eLORETA lagged linear connectivity in 130 subjects (59 males and 71 females) within each hemisphere and in four resting state networks (Attentional Network (AN), Frontal Network (FN), Sensorimotor Network (SN), Default Mode Network (DMN)). We found that small-world (SW) architecture in the left hemisphere Frontal network presented differences in both delta and alpha band, in particular lower values in delta and higher in alpha 2 in males respect to females while in the right hemisphere differences were found in lower values of SW in males respect to females in gamma Attentional, delta Sensorimotor and delta and gamma DMNs. Gender small-worldness differences in some of resting state networks indicated that there are specific brain differences in the EEG rhythms when the brain is in the resting-state condition. These specific regions could be considered related to the functions of behavior and cognition and should be taken into account both for research on healthy and brain diseased subjects. Copyright © 2015 IBRO. Published by Elsevier Ltd. All rights reserved.
Optimal convergence in naming game with geography-based negotiation on small-world networks
NASA Astrophysics Data System (ADS)
Liu, Run-Ran; Wang, Wen-Xu; Lai, Ying-Cheng; Chen, Guanrong; Wang, Bing-Hong
2011-01-01
We propose a negotiation strategy to address the effect of geography on the dynamics of naming games over small-world networks. Communication and negotiation frequencies between two agents are determined by their geographical distance in terms of a parameter characterizing the correlation between interaction strength and the distance. A finding is that there exists an optimal parameter value leading to fastest convergence to global consensus on naming. Numerical computations and a theoretical analysis are provided to substantiate our findings.
Harmonic stochastic resonance-enhanced signal detecting in NW small-world neural network
NASA Astrophysics Data System (ADS)
Wang, Dao-Guang; Liang, Xiao-Ming; Wang, Jing; Yang, Cheng-Fang; Liu, Kai; Lü, Hua-Ping
2010-11-01
The harmonic stochastic resonance-enhanced signal detecting in Newman-Watts small-world neural network is studied using the Hodgkin-Huxley dynamical equation with noise. If the connection probability p, coupling strength gsyn and noise intensity D matches well, higher order resonance will be found and an optimal signal-to-noise ratio will be obtained. Then, the reasons are given to explain the mechanism of this appearance.
Phase synchronization of bursting neurons in clustered small-world networks
NASA Astrophysics Data System (ADS)
Batista, C. A. S.; Lameu, E. L.; Batista, A. M.; Lopes, S. R.; Pereira, T.; Zamora-López, G.; Kurths, J.; Viana, R. L.
2012-07-01
We investigate the collective dynamics of bursting neurons on clustered networks. The clustered network model is composed of subnetworks, each of them presenting the so-called small-world property. This model can also be regarded as a network of networks. In each subnetwork a neuron is connected to other ones with regular as well as random connections, the latter with a given intracluster probability. Moreover, in a given subnetwork each neuron has an intercluster probability to be connected to the other subnetworks. The local neuron dynamics has two time scales (fast and slow) and is modeled by a two-dimensional map. In such small-world network the neuron parameters are chosen to be slightly different such that, if the coupling strength is large enough, there may be synchronization of the bursting (slow) activity. We give bounds for the critical coupling strength to obtain global burst synchronization in terms of the network structure, that is, the probabilities of intracluster and intercluster connections. We find that, as the heterogeneity in the network is reduced, the network global synchronizability is improved. We show that the transitions to global synchrony may be abrupt or smooth depending on the intercluster probability.
Stochastic resonance enhancement of small-world neural networks by hybrid synapses and time delay
NASA Astrophysics Data System (ADS)
Yu, Haitao; Guo, Xinmeng; Wang, Jiang
2017-01-01
The synergistic effect of hybrid electrical-chemical synapses and information transmission delay on the stochastic response behavior in small-world neuronal networks is investigated. Numerical results show that, the stochastic response behavior can be regulated by moderate noise intensity to track the rhythm of subthreshold pacemaker, indicating the occurrence of stochastic resonance (SR) in the considered neural system. Inheriting the characteristics of two types of synapses-electrical and chemical ones, neural networks with hybrid electrical-chemical synapses are of great improvement in neuron communication. Particularly, chemical synapses are conducive to increase the network detectability by lowering the resonance noise intensity, while the information is better transmitted through the networks via electrical coupling. Moreover, time delay is able to enhance or destroy the periodic stochastic response behavior intermittently. In the time-delayed small-world neuronal networks, the introduction of electrical synapses can significantly improve the signal detection capability by widening the range of optimal noise intensity for the subthreshold signal, and the efficiency of SR is largely amplified in the case of pure chemical couplings. In addition, the stochastic response behavior is also profoundly influenced by the network topology. Increasing the rewiring probability in pure chemically coupled networks can always enhance the effect of SR, which is slightly influenced by information transmission delay. On the other hand, the capacity of information communication is robust to the network topology within the time-delayed neuronal systems including electrical couplings.
Stretched exponential dynamics of coupled logistic maps on a small-world network
NASA Astrophysics Data System (ADS)
Mahajan, Ashwini V.; Gade, Prashant M.
2018-02-01
We investigate the dynamic phase transition from partially or fully arrested state to spatiotemporal chaos in coupled logistic maps on a small-world network. Persistence of local variables in a coarse grained sense acts as an excellent order parameter to study this transition. We investigate the phase diagram by varying coupling strength and small-world rewiring probability p of nonlocal connections. The persistent region is a compact region bounded by two critical lines where band-merging crisis occurs. On one critical line, the persistent sites shows a nonexponential (stretched exponential) decay for all p while for another one, it shows crossover from nonexponential to exponential behavior as p → 1 . With an effectively antiferromagnetic coupling, coupling to two neighbors on either side leads to exchange frustration. Apart from exchange frustration, non-bipartite topology and nonlocal couplings in a small-world network could be a reason for anomalous relaxation. The distribution of trap times in asymptotic regime has a long tail as well. The dependence of temporal evolution of persistence on initial conditions is studied and a scaling form for persistence after waiting time is proposed. We present a simple possible model for this behavior.
Focus-based filtering + clustering technique for power-law networks with small world phenomenon
NASA Astrophysics Data System (ADS)
Boutin, François; Thièvre, Jérôme; Hascoët, Mountaz
2006-01-01
Realistic interaction networks usually present two main properties: a power-law degree distribution and a small world behavior. Few nodes are linked to many nodes and adjacent nodes are likely to share common neighbors. Moreover, graph structure usually presents a dense core that is difficult to explore with classical filtering and clustering techniques. In this paper, we propose a new filtering technique accounting for a user-focus. This technique extracts a tree-like graph with also power-law degree distribution and small world behavior. Resulting structure is easily drawn with classical force-directed drawing algorithms. It is also quickly clustered and displayed into a multi-level silhouette tree (MuSi-Tree) from any user-focus. We built a new graph filtering + clustering + drawing API and report a case study.
The brainstem reticular formation is a small-world, not scale-free, network
Humphries, M.D; Gurney, K; Prescott, T.J
2005-01-01
Recently, it has been demonstrated that several complex systems may have simple graph-theoretic characterizations as so-called ‘small-world’ and ‘scale-free’ networks. These networks have also been applied to the gross neural connectivity between primate cortical areas and the nervous system of Caenorhabditis elegans. Here, we extend this work to a specific neural circuit of the vertebrate brain—the medial reticular formation (RF) of the brainstem—and, in doing so, we have made three key contributions. First, this work constitutes the first model (and quantitative review) of this important brain structure for over three decades. Second, we have developed the first graph-theoretic analysis of vertebrate brain connectivity at the neural network level. Third, we propose simple metrics to quantitatively assess the extent to which the networks studied are small-world or scale-free. We conclude that the medial RF is configured to create small-world (implying coherent rapid-processing capabilities), but not scale-free, type networks under assumptions which are amenable to quantitative measurement. PMID:16615219
Excitement and synchronization of small-world neuronal networks with short-term synaptic plasticity.
Han, Fang; Wiercigroch, Marian; Fang, Jian-An; Wang, Zhijie
2011-10-01
Excitement and synchronization of electrically and chemically coupled Newman-Watts (NW) small-world neuronal networks with a short-term synaptic plasticity described by a modified Oja learning rule are investigated. For each type of neuronal network, the variation properties of synaptic weights are examined first. Then the effects of the learning rate, the coupling strength and the shortcut-adding probability on excitement and synchronization of the neuronal network are studied. It is shown that the synaptic learning suppresses the over-excitement, helps synchronization for the electrically coupled network but impairs synchronization for the chemically coupled one. Both the introduction of shortcuts and the increase of the coupling strength improve synchronization and they are helpful in increasing the excitement for the chemically coupled network, but have little effect on the excitement of the electrically coupled one.
A game-theoretic approach to optimize ad hoc networks inspired by small-world network topology
NASA Astrophysics Data System (ADS)
Tan, Mian; Yang, Tinghong; Chen, Xing; Yang, Gang; Zhu, Guoqing; Holme, Petter; Zhao, Jing
2018-03-01
Nodes in ad hoc networks are connected in a self-organized manner. Limited communication radius makes information transmit in multi-hop mode, and each forwarding needs to consume the energy of nodes. Insufficient communication radius or exhaustion of energy may cause the absence of some relay nodes and links, further breaking network connectivity. On the other hand, nodes in the network may refuse to cooperate due to objective faulty or personal selfish, hindering regular communication in the network. This paper proposes a model called Repeated Game in Small World Networks (RGSWN). In this model, we first construct ad hoc networks with small-world feature by forming "communication shortcuts" between multiple-radio nodes. Small characteristic path length reduces average forwarding times in networks; meanwhile high clustering coefficient enhances network robustness. Such networks still maintain relative low global power consumption, which is beneficial to extend the network survival time. Then we use MTTFT strategy (Mend-Tolerance Tit-for-Tat) for repeated game as a rule for the interactions between neighbors in the small-world networks. Compared with other five strategies of repeated game, this strategy not only punishes the nodes' selfishness more reasonably, but also has the best tolerance to the network failure. This work is insightful for designing an efficient and robust ad hoc network.
NASA Astrophysics Data System (ADS)
Yu, Haitao; Wang, Jiang; Liu, Chen; Deng, Bin; Wei, Xile
2011-12-01
We study the phenomenon of stochastic resonance on a modular neuronal network consisting of several small-world subnetworks with a subthreshold periodic pacemaker. Numerical results show that the correlation between the pacemaker frequency and the dynamical response of the network is resonantly dependent on the intensity of additive spatiotemporal noise. This effect of pacemaker-driven stochastic resonance of the system depends extensively on the local and the global network structure, such as the intra- and inter-coupling strengths, rewiring probability of individual small-world subnetwork, the number of links between different subnetworks, and the number of subnetworks. All these parameters play a key role in determining the ability of the network to enhance the noise-induced outreach of the localized subthreshold pacemaker, and only they bounded to a rather sharp interval of values warrant the emergence of the pronounced stochastic resonance phenomenon. Considering the rather important role of pacemakers in real-life, the presented results could have important implications for many biological processes that rely on an effective pacemaker for their proper functioning.
Lei, Hui; Cui, Yan; Fan, Jie; Zhang, Xiaocui; Zhong, Mingtian; Yi, Jinyao; Cai, Lin; Yao, Dezhong; Zhu, Xiongzhao
2017-09-01
There are limited data on neurobiological correlates of poor insight in obsessive-compulsive disorder (OCD). This study explored whether specific changes occur in small-world network (SWN) properties in the brain functional network of OCD patients with poor insight. Resting-state electroencephalograms (EEGs) were recorded for 12 medication-free OCD patients with poor insight, 50 medication-free OCD patients with good insight, and 36 healthy controls. Both of the OCD groups exhibited topological alterations in the brain functional network characterized by abnormal small-world parameters at the beta band. However, the alterations at the theta band only existed in the OCD patients with poor insight. A relatively small sample size. Subjects were naïve to medications and those with Axis I comorbidity were excluded, perhaps limiting generalizability. Disrupted functional integrity at the beta bands of the brain functional network may be related to OCD, while disrupted functional integrity at the theta band may be associated with poor insight in OCD patients, thus this study might provide novel insight into our understanding of the pathophysiology of OCD. Copyright © 2017 Elsevier B.V. All rights reserved.
Critical behavior of the XY-rotor model on regular and small-world networks
NASA Astrophysics Data System (ADS)
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 Nlinks˜Nγ, 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 ɛ=E/N,ɛc=0.75. Moreover, for γc≃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 pSW∝1/Nγ. Then considering the XY-rotors model on these networks, we find that a second-order phase transition occurs at a critical energy ɛc which logarithmically depends on the topological parameters p and γ. We also define a critical probability pMF, corresponding to the probability beyond which the mean field is quantitatively recovered, and we analyze its dependence on γ.
A family of small-world network models built by complete graph and iteration-function
NASA Astrophysics Data System (ADS)
Ma, Fei; Yao, Bing
2018-02-01
Small-world networks are popular in real-life complex systems. In the past few decades, researchers presented amounts of small-world models, in which some are stochastic and the rest are deterministic. In comparison with random models, it is not only convenient but also interesting to study the topological properties of deterministic models in some fields, such as graph theory, theorem computer sciences and so on. As another concerned darling in current researches, community structure (modular topology) is referred to as an useful statistical parameter to uncover the operating functions of network. So, building and studying such models with community structure and small-world character will be a demanded task. Hence, in this article, we build a family of sparse network space N(t) which is different from those previous deterministic models. Even though, our models are established in the same way as them, iterative generation. By randomly connecting manner in each time step, every resulting member in N(t) has no absolutely self-similar feature widely shared in a large number of previous models. This makes our insight not into discussing a class certain model, but into investigating a group various ones spanning a network space. Somewhat surprisingly, our results prove all members of N(t) to possess some similar characters: (a) sparsity, (b) exponential-scale feature P(k) ∼α-k, and (c) small-world property. Here, we must stress a very screming, but intriguing, phenomenon that the difference of average path length (APL) between any two members in N(t) is quite small, which indicates this random connecting way among members has no great effect on APL. At the end of this article, as a new topological parameter correlated to reliability, synchronization capability and diffusion properties of networks, the number of spanning trees on a representative member NB(t) of N(t) is studied in detail, then an exact analytical solution for its spanning trees entropy is also
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.
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.
Effects of channel noise on firing coherence of small-world Hodgkin-Huxley neuronal networks
NASA Astrophysics Data System (ADS)
Sun, X. J.; Lei, J. Z.; Perc, M.; Lu, Q. S.; Lv, S. J.
2011-01-01
We investigate the effects of channel noise on firing coherence of Watts-Strogatz small-world networks consisting of biophysically realistic HH neurons having a fraction of blocked voltage-gated sodium and potassium ion channels embedded in their neuronal membranes. The intensity of channel noise is determined by the number of non-blocked ion channels, which depends on the fraction of working ion channels and the membrane patch size with the assumption of homogeneous ion channel density. We find that firing coherence of the neuronal network can be either enhanced or reduced depending on the source of channel noise. As shown in this paper, sodium channel noise reduces firing coherence of neuronal networks; in contrast, potassium channel noise enhances it. Furthermore, compared with potassium channel noise, sodium channel noise plays a dominant role in affecting firing coherence of the neuronal network. Moreover, we declare that the observed phenomena are independent of the rewiring probability.
Wu, Qiong; Gao, Yang; Liu, Ai-Shi; Xie, Li-Zhi; Qian, Long; Yang, Xiao-Guang
2018-01-01
To date, the most frequently reported neuroimaging biomarkers in Parkinson's disease (PD) are direct brain imaging measurements focusing on local disrupted regions. However, the notion that PD is related to abnormal functional and structural connectivity has received support in the past few years. Here, we employed graph theory to analyze the structural co-variance networks derived from 50 PD patients and 48 normal controls (NC). Then, the small world properties of brain networks were assessed in the structural networks that were constructed based on cortical volume data. Our results showed that both the PD and NC groups had a small world architecture in brain structural networks. However, the PD patients had a higher characteristic path length and clustering coefficients compared with the NC group. With regard to the nodal centrality, 11 regions, including 3 association cortices, 5 paralimbic cortices, and 3 subcortical regions were identified as hubs in the PD group. In contrast, 10 regions, including 7 association cortical regions, 2 paralimbic cortical regions, and the primary motor cortex region, were identified as hubs. Moreover, the regional centrality was profoundly affected in PD patients, including decreased nodal centrality in the right inferior occipital gyrus and the middle temporal gyrus and increased nodal centrality in the right amygdala, the left caudate and the superior temporal gyrus. In addition, the structural cortical network of PD showed reduced topological stability for targeted attacks. Together, this study shows that the coordinated patterns of cortical volume network are widely altered in PD patients with a decrease in the efficiency of parallel information processing. These changes provide structural evidence to support the concept that the core pathophysiology of PD is associated with disruptive alterations in the coordination of large-scale brain networks that underlie high-level cognition. Copyright © 2017. Published by Elsevier B.V.
Properties of a new small-world network with spatially biased random shortcuts
NASA Astrophysics Data System (ADS)
Matsuzawa, Ryo; Tanimoto, Jun; Fukuda, Eriko
2017-11-01
This paper introduces a small-world (SW) network with a power-law distance distribution that differs from conventional models in that it uses completely random shortcuts. By incorporating spatial constraints, we analyze the divergence of the proposed model from conventional models in terms of fundamental network properties such as clustering coefficient, average path length, and degree distribution. We find that when the spatial constraint more strongly prohibits a long shortcut, the clustering coefficient is improved and the average path length increases. We also analyze the spatial prisoner's dilemma (SPD) games played on our new SW network in order to understand its dynamical characteristics. Depending on the basis graph, i.e., whether it is a one-dimensional ring or a two-dimensional lattice, and the parameter controlling the prohibition of long-distance shortcuts, the emergent results can vastly differ.
Disease transmission in territorial populations: the small-world network of Serengeti lions
Craft, Meggan E.; Volz, Erik; Packer, Craig; Meyers, Lauren Ancel
2011-01-01
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. PMID:21030428
Levodopa modulates small-world architecture of functional brain networks in Parkinson's disease.
Berman, Brian D; Smucny, Jason; Wylie, Korey P; Shelton, Erika; Kronberg, Eugene; Leehey, Maureen; Tregellas, Jason R
2016-11-01
PD is associated with disrupted connectivity to a large number of distributed brain regions. How the disease alters the functional topological organization of the brain, however, remains poorly understood. Furthermore, how levodopa modulates network topology in PD is largely unknown. The objective of this study was to use resting-state functional MRI and graph theory to determine how small-world architecture is altered in PD and affected by levodopa administration. Twenty-one PD patients and 20 controls underwent functional MRI scanning. PD patients were scanned off medication and 1 hour after 200 mg levodopa. Imaging data were analyzed using 226 nodes comprising 10 intrinsic brain networks. Correlation matrices were generated for each subject and converted into cost-thresholded, binarized adjacency matrices. Cost-integrated whole-brain global and local efficiencies were compared across groups and tested for relationships with disease duration and severity. Data from 2 patients and 4 controls were excluded because of excess motion. Patients off medication showed no significant changes in global efficiency and overall local efficiency, but in a subnetwork analysis did show increased local efficiency in executive (P = 0.006) and salience (P = 0.018) networks. Levodopa significantly decreased local efficiency (P = 0.039) in patients except within the subcortical network, in which it significantly increased local efficiency (P = 0.007). Levodopa modulates global and local efficiency measures of small-world topology in PD, suggesting that degeneration of nigrostriatal neurons in PD may be associated with a large-scale network reorganization and that levodopa tends to normalize the disrupted network topology in PD. © 2016 International Parkinson and Movement Disorder Society. © 2016 International Parkinson and Movement Disorder Society.
A review of structural and functional brain networks: small world and atlas.
Yao, Zhijun; Hu, Bin; Xie, Yuanwei; Moore, Philip; Zheng, Jiaxiang
2015-03-01
Brain networks can be divided into two categories: structural and functional networks. Many studies of neuroscience have reported that the complex brain networks are characterized by small-world or scale-free properties. The identification of nodes is the key factor in studying the properties of networks on the macro-, micro- or mesoscale in both structural and functional networks. In the study of brain networks, nodes are always determined by atlases. Therefore, the selection of atlases is critical, and appropriate atlases are helpful to combine the analyses of structural and functional networks. Currently, some problems still exist in the establishment or usage of atlases, which are often caused by the segmentation or the parcellation of the brain. We suggest that quantification of brain networks might be affected by the selection of atlases to a large extent. In the process of building atlases, the influences of single subjects and groups should be balanced. In this article, we focused on the effects of atlases on the analysis of brain networks and the improved divisions based on the tractography or connectivity in the parcellation of atlases.
Scaling of Directed Dynamical Small-World Networks with Random Responses
NASA Astrophysics Data System (ADS)
Zhu, Chen-Ping; Xiong, Shi-Jie; Tian, Ying-Jie; Li, Nan; Jiang, Ke-Sheng
2004-05-01
A dynamical model of small-world networks, with directed links which describe various correlations in social and natural phenomena, is presented. Random responses of sites to the input message are introduced to simulate real systems. The interplay of these ingredients results in the collective dynamical evolution of a spinlike variable S(t) of the whole network. The global average spreading length
Sparsely-synchronized brain rhythm in a small-world neural network
NASA Astrophysics Data System (ADS)
Kim, Sang-Yoon; Lim, Woochang
2013-07-01
Sparsely-synchronized cortical rhythms, associated with diverse cognitive functions, have been observed in electric recordings of brain activity. At the population level, cortical rhythms exhibit small-amplitude fast oscillations while at the cellular level, individual neurons show stochastic firings sparsely at a much lower rate than the population rate. We study the effect of network architecture on sparse synchronization in an inhibitory population of subthreshold Morris-Lecar neurons (which cannot fire spontaneously without noise). Previously, sparse synchronization was found to occur for cases of both global coupling ( i.e., regular all-to-all coupling) and random coupling. However, a real neural network is known to be non-regular and non-random. Here, we consider sparse Watts-Strogatz small-world networks which interpolate between a regular lattice and a random graph via rewiring. We start from a regular lattice with only short-range connections and then investigate the emergence of sparse synchronization by increasing the rewiring probability p for the short-range connections. For p = 0, the average synaptic path length between pairs of neurons becomes long; hence, only an unsynchronized population state exists because the global efficiency of information transfer is low. However, as p is increased, long-range connections begin to appear, and global effective communication between distant neurons may be available via shorter synaptic paths. Consequently, as p passes a threshold p th (}~ 0.044), sparsely-synchronized population rhythms emerge. However, with increasing p, longer axon wirings become expensive because of their material and energy costs. At an optimal value p* DE (}~ 0.24) of the rewiring probability, the ratio of the synchrony degree to the wiring cost is found to become maximal. In this way, an optimal sparse synchronization is found to occur at a minimal wiring cost in an economic small-world network through trade-off between synchrony and
Promotion of cooperation induced by appropriate payoff aspirations in a small-world networked game
NASA Astrophysics Data System (ADS)
Chen, Xiaojie; Wang, Long
2008-01-01
Based on learning theory, we adopt a stochastic learning updating rule to investigate the evolution of cooperation in the Prisoner’s Dilemma game on Newman-Watts small-world networks with different payoff aspiration levels. Interestingly, simulation results show that the mechanism of intermediate aspiration promoting cooperation resembles a resonancelike behavior, and there exists a ping-pong vibration of cooperation for large payoff aspiration. To explain the nontrivial dependence of the cooperation level on the aspiration level, we investigate the fractions of links, provide analytical results of the cooperation level, and find that the simulation results are in close agreement with analytical ones. Our work may be helpful in understanding the cooperative behavior induced by the aspiration level in society.
Dong, Zhekang; Duan, Shukai; Hu, Xiaofang; Wang, Lidan; Li, Hai
2014-01-01
In this paper, we present an implementation scheme of memristor-based multilayer feedforward small-world neural network (MFSNN) inspirited by the lack of the hardware realization of the MFSNN on account of the need of a large number of electronic neurons and synapses. More specially, a mathematical closed-form charge-governed memristor model is presented with derivation procedures and the corresponding Simulink model is presented, which is an essential block for realizing the memristive synapse and the activation function in electronic neurons. Furthermore, we investigate a more intelligent memristive PID controller by incorporating the proposed MFSNN into intelligent PID control based on the advantages of the memristive MFSNN on computation speed and accuracy. Finally, numerical simulations have demonstrated the effectiveness of the proposed scheme.
Dong, Zhekang; Duan, Shukai; Hu, Xiaofang; Wang, Lidan
2014-01-01
In this paper, we present an implementation scheme of memristor-based multilayer feedforward small-world neural network (MFSNN) inspirited by the lack of the hardware realization of the MFSNN on account of the need of a large number of electronic neurons and synapses. More specially, a mathematical closed-form charge-governed memristor model is presented with derivation procedures and the corresponding Simulink model is presented, which is an essential block for realizing the memristive synapse and the activation function in electronic neurons. Furthermore, we investigate a more intelligent memristive PID controller by incorporating the proposed MFSNN into intelligent PID control based on the advantages of the memristive MFSNN on computation speed and accuracy. Finally, numerical simulations have demonstrated the effectiveness of the proposed scheme. PMID:25202723
A fault-tolerant small world topology control model in ad hoc networks for search and rescue
NASA Astrophysics Data System (ADS)
Tan, Mian; Fang, Ling; Wu, Yue; Zhang, Bo; Chang, Bowen; Holme, Petter; Zhao, Jing
2018-02-01
Due to their self-organized, multi-hop and distributed characteristics, ad hoc networks are useful in search and rescue. Topology control models need to be designed for energy-efficient, robust and fast communication in ad hoc networks. This paper proposes a topology control model which specializes for search and rescue-Compensation Small World-Repeated Game (CSWRG)-which integrates mobility models, constructing small world networks and a game-theoretic approach to the allocation of resources. Simulation results show that our mobility models can enhance the communication performance of the constructed small-world networks. Our strategy, based on repeated game, can suppress selfish behavior and compensate agents that encounter selfish or faulty neighbors. This model could be useful for the design of ad hoc communication networks.
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.
NASA Astrophysics Data System (ADS)
She, Qi; Chen, Guanrong; Chan, Rosa H. M.
2016-02-01
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.
Naming games in two-dimensional and small-world-connected random geometric networks.
Lu, Qiming; Korniss, G; Szymanski, B K
2008-01-01
We investigate a prototypical agent-based model, the naming game, on two-dimensional random geometric networks. The naming game [Baronchelli, J. Stat. Mech.: Theory Exp. (2006) P06014] is a minimal model, employing local communications that captures the emergence of shared communication schemes (languages) in a population of autonomous semiotic agents. Implementing the naming games with local broadcasts on random geometric graphs, serves as a model for agreement dynamics in large-scale, autonomously operating wireless sensor networks. Further, it captures essential features of the scaling properties of the agreement process for spatially embedded autonomous agents. Among the relevant observables capturing the temporal properties of the agreement process, we investigate the cluster-size distribution and the distribution of the agreement times, both exhibiting dynamic scaling. We also present results for the case when a small density of long-range communication links are added on top of the random geometric graph, resulting in a "small-world"-like network and yielding a significantly reduced time to reach global agreement. We construct a finite-size scaling analysis for the agreement times in this case.
Abnormal small-world architecture of top–down control networks in obsessive–compulsive disorder
Zhang, Tijiang; Wang, Jinhui; Yang, Yanchun; Wu, Qizhu; Li, Bin; Chen, Long; Yue, Qiang; Tang, Hehan; Yan, Chaogan; Lui, Su; Huang, Xiaoqi; Chan, Raymond C.K.; Zang, Yufeng; He, Yong; Gong, Qiyong
2011-01-01
Background Obsessive–compulsive disorder (OCD) is a common neuropsychiatric disorder that is characterized by recurrent intrusive thoughts, ideas or images and repetitive ritualistic behaviours. Although focal structural and functional abnormalities in specific brain regions have been widely studied in populations with OCD, changes in the functional relations among them remain poorly understood. This study examined OCD–related alterations in functional connectivity patterns in the brain’s top–down control network. Methods We applied resting-state functional magnetic resonance imaging to investigate the correlation patterns of intrinsic or spontaneous blood oxygen level–dependent signal fluctuations in 18 patients with OCD and 16 healthy controls. The brain control networks were first constructed by thresholding temporal correlation matrices of 39 brain regions associated with top–down control and then analyzed using graph theory-based approaches. Results Compared with healthy controls, the patients with OCD showed decreased functional connectivity in the posterior temporal regions and increased connectivity in various control regions such as the cingulate, precuneus, thalamus and cerebellum. Furthermore, the brain’s control networks in the healthy controls showed small-world architecture (high clustering coefficients and short path lengths), suggesting an optimal balance between modularized and distributed information processing. In contrast, the patients with OCD showed significantly higher local clustering, implying abnormal functional organization in the control network. Further analysis revealed that the changes in network properties occurred in regions of increased functional connectivity strength in patients with OCD. Limitations The patient group in the present study was heterogeneous in terms of symptom clusters, and most of the patients with OCD were medicated. Conclusion Our preliminary results suggest that the organizational patterns of
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.
Finite Memory Walk and Its Application to Small-World Network
NASA Astrophysics Data System (ADS)
Oshima, Hiraku; Odagaki, Takashi
2012-07-01
In order to investigate the effects of cycles on the dynamical process on both regular lattices and complex networks, we introduce a finite memory walk (FMW) as an extension of the simple random walk (SRW), in which a walker is prohibited from moving to sites visited during m steps just before the current position. This walk interpolates the simple random walk (SRW), which has no memory (m = 0), and the self-avoiding walk (SAW), which has an infinite memory (m = ∞). We investigate the FMW on regular lattices and clarify the fundamental characteristics of the walk. We find that (1) the mean-square displacement (MSD) of the FMW shows a crossover from the SAW at a short time step to the SRW at a long time step, and the crossover time is approximately equivalent to the number of steps remembered, and that the MSD can be rescaled in terms of the time step and the size of memory; (2) the mean first-return time (MFRT) of the FMW changes significantly at the number of remembered steps that corresponds to the size of the smallest cycle in the regular lattice, where ``smallest'' indicates that the size of the cycle is the smallest in the network; (3) the relaxation time of the first-return time distribution (FRTD) decreases as the number of cycles increases. We also investigate the FMW on the Watts--Strogatz networks that can generate small-world networks, and show that the clustering coefficient of the Watts--Strogatz network is strongly related to the MFRT of the FMW that can remember two steps.
Zhang, Yue; Jiang, Yin; Glielmi, Christopher B; Li, Longchuan; Hu, Xiaoping; Wang, Xiaoying; Han, Jisheng; Zhang, Jue; Cui, Cailian; Fang, Jing
2013-09-01
Acupuncture, which is recognized as an alternative and complementary treatment in Western medicine, has long shown efficiencies in chronic pain relief, drug addiction treatment, stroke rehabilitation and other clinical practices. The neural mechanism underlying acupuncture, however, is still unclear. Many studies have focused on the sustained effects of acupuncture on healthy subjects, yet there are very few on the topological organization of functional networks in the whole brain in response to long-duration acupuncture (longer than 20 min). This paper presents a novel study on the effects of long-duration transcutaneous electric acupoint stimulation (TEAS) on the small-world properties of brain functional networks. Functional magnetic resonance imaging was used to construct brain functional networks of 18 healthy subjects (9 males and 9 females) during the resting state. All subjects received both TEAS and minimal TEAS (MTEAS) and were scanned before and after each stimulation. An altered functional network was found with lower local efficiency and no significant change in global efficiency for healthy subjects after TEAS, while no significant difference was observed after MTEAS. The experiments also showed that the nodal efficiencies in several paralimbic/limbic regions were altered by TEAS, and those in middle frontal gyrus and other regions by MTEAS. To remove the psychological effects and the baseline, we compared the difference between diffTEAS (difference between after and before TEAS) and diffMTEAS (difference between after and before MTEAS). The results showed that the local efficiency was decreased and that the nodal efficiencies in frontal gyrus, orbitofrontal cortex, anterior cingulate gyrus and hippocampus gyrus were changed. Based on those observations, we conclude that long-duration TEAS may modulate the short-range connections of brain functional networks and also the limbic system. Copyright © 2013 Elsevier Inc. All rights reserved.
Interictal to Ictal Phase Transition in a Small-World Network
NASA Astrophysics Data System (ADS)
Nemzer, Louis; Cravens, Gary; Worth, Robert
Real-time detection and prediction of seizures in patients with epilepsy is essential for rapid intervention. Here, we perform a full Hodgkin-Huxley calculation using n 50 in silico neurons configured in a small-world network topology to generate simulated EEG signals. The connectivity matrix, constructed using a Watts-Strogatz algorithm, admits randomized or deterministic entries. We find that situations corresponding to interictal (non-seizure) and ictal (seizure) states are separated by a phase transition that can be influenced by congenital channelopathies, anticonvulsant drugs, and connectome plasticity. The interictal phase exhibits scale-free phenomena, as characterized by a power law form of the spectral power density, while the ictal state suffers from pathological synchronization. We compare the results with intracranial EEG data and show how these findings may be used to detect or even predict seizure onset. Along with the balance of excitatory and inhibitory factors, the network topology plays a large role in determining the overall characteristics of brain activity. We have developed a new platform for testing the conditions that contribute to the phase transition between non-seizure and seizure states.
Phase Transition for the Maki-Thompson Rumour Model on a Small-World Network
NASA Astrophysics Data System (ADS)
Agliari, Elena; Pachon, Angelica; Rodriguez, Pablo M.; Tavani, Flavia
2017-11-01
We consider the Maki-Thompson model for the stochastic propagation of a rumour within a population. In this model the population is made up of "spreaders", "ignorants" and "stiflers"; any spreader attempts to pass the rumour to the other individuals via pair-wise interactions and in case the other individual is an ignorant, it becomes a spreader, while in the other two cases the initiating spreader turns into a stifler. In a finite population the process will eventually reach an equilibrium situation where individuals are either stiflers or ignorants. We extend the original hypothesis of homogenously mixed population by allowing for a small-world network embedding the model, in such a way that interactions occur only between nearest-neighbours. This structure is realized starting from a k-regular ring and by inserting, in the average, c additional links in such a way that k and c are tuneable parameters for the population architecture. We prove that this system exhibits a transition between regimes of localization (where the final number of stiflers is at most logarithmic in the population size) and propagation (where the final number of stiflers grows algebraically with the population size) at a finite value of the network parameter c. A quantitative estimate for the critical value of c is obtained via extensive numerical simulations.
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.
SmallWorld Behavior of the Worldwide Active Volcanoes Network: Preliminary Results
NASA Astrophysics Data System (ADS)
Spata, A.; Bonforte, A.; Nunnari, G.; Puglisi, G.
2009-12-01
We propose a preliminary complex networks based approach in order to model and characterize volcanoes activity correlation observed on a planetary scale over the last two thousand years. Worldwide volcanic activity is in fact related to the general plate tectonics that locally drives the faults activity, that in turn controls the magma upraise beneath the volcanoes. To find correlations among different volcanoes could indicate a common underlying mechanism driving their activity and could help us interpreting the deeper common dynamics controlling their unrest. All the first evidences found testing the procedure, suggest the suitability of this analysis to investigate global volcanism related to plate tectonics. The first correlations found, in fact, indicate that an underlying common large-scale dynamics seems to drive volcanic activity at least around the Pacific plate, where it collides and subduces beneath American, Eurasian and Australian plates. From this still preliminary analysis, also more complex relationships among volcanoes lying on different tectonic margins have been found, suggesting some more complex interrelationships between different plates. The understanding of eventually detected correlations could be also used to further implement warning systems, relating the unrest probabilities of a specific volcano also to the ongoing activity to the correlated ones. Our preliminary results suggest that, as for other many physical and biological systems, an underlying organizing principle of planetary volcanoes activity might exist and it could be a small-world principle. In fact we found that, from a topological perspective, volcanoes correlations are characterized by the typical features of small-world network: a high clustering coefficient and a low characteristic path length. These features confirm that global volcanoes activity is characterized by both short and long-range correlations. We stress here the fact that numerical simulation carried out in
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.
2016-01-01
Sequential patterns of prefrontal activity are believed to mediate important behaviors, e.g., working memory, but it remains unclear exactly how they are generated. In accordance with previous studies of cortical circuits, we found that prefrontal microcircuits in young adult mice spontaneously generate many more stereotyped sequences of activity than expected by chance. However, the key question of whether these sequences depend on a specific functional organization within the cortical microcircuit, or emerge simply as a by-product of random interactions between neurons, remains unanswered. We observed that correlations between prefrontal neurons do follow a specific functional organization—they have a small-world topology. However, until now it has not been possible to directly link small-world topologies to specific circuit functions, e.g., sequence generation. Therefore, we developed a novel analysis to address this issue. Specifically, we constructed surrogate data sets that have identical levels of network activity at every point in time but nevertheless represent various network topologies. We call this method shuffling activity to rearrange correlations (SHARC). We found that only surrogate data sets based on the actual small-world functional organization of prefrontal microcircuits were able to reproduce the levels of sequences observed in actual data. As expected, small-world data sets contained many more sequences than surrogate data sets with randomly arranged correlations. Surprisingly, small-world data sets also outperformed data sets in which correlations were maximally clustered. Thus the small-world functional organization of cortical microcircuits, which effectively balances the random and maximally clustered regimes, is optimal for producing stereotyped sequential patterns of activity. PMID:26888108
Gallos, Lazaros K; Makse, Hernán A; Sigman, Mariano
2012-02-21
The human brain is organized in functional modules. Such an organization presents a basic conundrum: Modules ought to be sufficiently independent to guarantee functional specialization and sufficiently connected to bind multiple processors for efficient information transfer. It is commonly accepted that small-world architecture of short paths and large local clustering may solve this problem. However, there is intrinsic tension between shortcuts generating small worlds and the persistence of modularity, a global property unrelated to local clustering. Here, we present a possible solution to this puzzle. We first show that a modified percolation theory can define a set of hierarchically organized modules made of strong links in functional brain networks. These modules are "large-world" self-similar structures and, therefore, are far from being small-world. However, incorporating weaker ties to the network converts it into a small world preserving an underlying backbone of well-defined modules. Remarkably, weak ties are precisely organized as predicted by theory maximizing information transfer with minimal wiring cost. This trade-off architecture is reminiscent of the "strength of weak ties" crucial concept of social networks. Such a design suggests a natural solution to the paradox of efficient information flow in the highly modular structure of the brain.
Gallos, Lazaros K.; Makse, Hernán A.; Sigman, Mariano
2012-01-01
The human brain is organized in functional modules. Such an organization presents a basic conundrum: Modules ought to be sufficiently independent to guarantee functional specialization and sufficiently connected to bind multiple processors for efficient information transfer. It is commonly accepted that small-world architecture of short paths and large local clustering may solve this problem. However, there is intrinsic tension between shortcuts generating small worlds and the persistence of modularity, a global property unrelated to local clustering. Here, we present a possible solution to this puzzle. We first show that a modified percolation theory can define a set of hierarchically organized modules made of strong links in functional brain networks. These modules are “large-world” self-similar structures and, therefore, are far from being small-world. However, incorporating weaker ties to the network converts it into a small world preserving an underlying backbone of well-defined modules. Remarkably, weak ties are precisely organized as predicted by theory maximizing information transfer with minimal wiring cost. This trade-off architecture is reminiscent of the “strength of weak ties” crucial concept of social networks. Such a design suggests a natural solution to the paradox of efficient information flow in the highly modular structure of the brain. PMID:22308319
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.
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
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.
Zhang, Jianbao; Ma, Zhongjun, E-mail: mzj1234402@163.com; Chen, Guanrong
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 ormore » 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.« less
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.
NASA Astrophysics Data System (ADS)
Zhang, Jianbao; Ma, Zhongjun; Chen, Guanrong
2014-06-01
All edges in the classical Watts and Strogatz's small-world network model are unweighted and cooperative (positive). By introducing competitive (negative) inter-cluster edges and assigning edge weights to mimic more realistic networks, this paper develops a modified model which possesses co-competitive weighted couplings and cluster structures while maintaining the common small-world network properties of small average shortest path lengths and large clustering coefficients. Based on theoretical analysis, it is proved that the new model with inter-cluster co-competition balance has an important dynamical property of robust cluster synchronous pattern formation. More precisely, clusters will neither merge nor split regardless of adding or deleting nodes and edges, under the condition of inter-cluster co-competition balance. Numerical simulations demonstrate the robustness of the model against the increase of the coupling strength and several topological variations.
Zhang, Jiang; Li, Yuyao; Chen, Huafu; Ding, Jurong; Yuan, Zhen
2016-11-04
In this study, small-world network analysis was performed to identify the similarities and differences between functional brain networks for right- and left-hand motor imageries (MIs). First, Pearson correlation coefficients among the nodes within the functional brain networks from healthy subjects were calculated. Then, small-world network indicators, including the clustering coefficient, the average path length, the global efficiency, the local efficiency, the average node degree, and the small-world index, were generated for the functional brain networks during both right- and left-hand MIs. We identified large differences in the small-world network indicators between the functional networks during MI and in the random networks. More importantly, the functional brain networks underlying the right- and left-hand MIs exhibited similar small-world properties in terms of the clustering coefficient, the average path length, the global efficiency, and the local efficiency. By contrast, the right- and left-hand MI brain networks showed differences in small-world characteristics, including indicators such as the average node degree and the small-world index. Interestingly, our findings also suggested that the differences in the activity intensity and range, the average node degree, and the small-world index of brain networks between the right- and left-hand MIs were associated with the asymmetry of brain functions.
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. © 2013.
Stanton, Neville A; Walker, Guy H; Sorensen, Linda J
2012-01-01
This article presents the rationale behind an important enhancement to a socio-technical model of organisations and teams derived from military research. It combines this with empirical results which take advantage of these enhancements. In Part 1, a new theoretical legacy for the model is developed based on Ergonomics theories and insights. This allows team communications data to be plotted into the model and for it to demonstrate discriminate validity between alternative team structures. Part 2 presents multinational data from the Experimental Laboratory for Investigating Collaboration, Information-sharing, and Trust (ELICIT) community. It was surprising to see that teams in both traditional hierarchical command and control and networked 'peer-to-peer' organisations operate in broadly the same area of the model, a region occupied by networks of communication exhibiting 'small world' properties. Small world networks may be of considerable importance for the Ergonomics analysis of team organisation and performance. This article is themed around macro and systems Ergonomics, and examines the effects of command and control structures. Despite some differences in behaviour and measures of agility, when given the freedom to do so, participants organised themselves into a small world network. This network type has important and interesting implications for the Ergonomics design of teams and organisations.
Yu, Haitao; Guo, Xinmeng; Wang, Jiang, E-mail: jiangwang@tju.edu.cn
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 formore » 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.« less
Qu, Haibo; Lu, Su; Zhang, Wenjing; Xiao, Yuan; Ning, Gang; Sun, Huaiqiang
2016-10-01
We applied resting-state functional magnetic resonance imaging(rfMRI)combined with graph theory to analyze 90 regions of the infantile small world neural network of the whole brain.We tried to get the following two points clear:1 whether the parameters of the node property of the infantile small world neural network are correlated with the level of infantile intelligence development;2 whether the parameters of the infantile small world neural network are correlated with the children’s baseline parameters,i.e.,the demographic parameters such as gender,age,parents’ education level,etc.Twelve cases of healthy infants were included in the investigation(9males and 3females with the average age of 33.42±8.42 months.)We then evaluated the level of infantile intelligence of all the cases and graded by Gesell Development Scale Test.We used a Siemens 3.0T Trio imaging system to perform resting-state(rs)EPI scans,and collected the BOLD functional Magnetic Resonance Imaging(fMRI)data.We performed the data processing with Statistical Parametric Mapping 5(SPM5)based on Matlab environment.Furthermore,we got the attributes of the whole brain small world and node attributes of 90 encephalic regions of templates of Anatomatic Automatic Labeling(ALL).At last,we carried out correlation study between the above-mentioned attitudes,intelligence scale parameters and demographic data.The results showed that many node attributes of small world neural network were closely correlated with intelligence scale parameters.Betweeness was mainly centered in thalamus,superior frontal gyrus,and occipital lobe(negative correlation).The r value of superior occipital gyrus associated with the individual and social intelligent scale was-0.729(P=0.007);degree was mainly centered in amygdaloid nucleus,superior frontal gyrus,and inferior parietal gyrus(positive correlation).The r value of inferior parietal gyrus associated with the gross motor intelligent scale was 0.725(P=0.008);efficiency was mainly
Small-world bias of correlation networks: From brain to climate
NASA Astrophysics Data System (ADS)
Hlinka, Jaroslav; Hartman, David; Jajcay, Nikola; Tomeček, David; Tintěra, Jaroslav; Paluš, Milan
2017-03-01
Complex systems are commonly characterized by the properties of their graph representation. Dynamical complex systems are then typically represented by a graph of temporal dependencies between time series of state variables of their subunits. It has been shown recently that graphs constructed in this way tend to have relatively clustered structure, potentially leading to spurious detection of small-world properties even in the case of systems with no or randomly distributed true interactions. However, the strength of this bias depends heavily on a range of parameters and its relevance for real-world data has not yet been established. In this work, we assess the relevance of the bias using two examples of multivariate time series recorded in natural complex systems. The first is the time series of local brain activity as measured by functional magnetic resonance imaging in resting healthy human subjects, and the second is the time series of average monthly surface air temperature coming from a large reanalysis of climatological data over the period 1948-2012. In both cases, the clustering in the thresholded correlation graph is substantially higher compared with a realization of a density-matched random graph, while the shortest paths are relatively short, showing thus distinguishing features of small-world structure. However, comparable or even stronger small-world properties were reproduced in correlation graphs of model processes with randomly scrambled interconnections. This suggests that the small-world properties of the correlation matrices of these real-world systems indeed do not reflect genuinely the properties of the underlying interaction structure, but rather result from the inherent properties of correlation matrix.
Small-world bias of correlation networks: From brain to climate.
Hlinka, Jaroslav; Hartman, David; Jajcay, Nikola; Tomeček, David; Tintěra, Jaroslav; Paluš, Milan
2017-03-01
Complex systems are commonly characterized by the properties of their graph representation. Dynamical complex systems are then typically represented by a graph of temporal dependencies between time series of state variables of their subunits. It has been shown recently that graphs constructed in this way tend to have relatively clustered structure, potentially leading to spurious detection of small-world properties even in the case of systems with no or randomly distributed true interactions. However, the strength of this bias depends heavily on a range of parameters and its relevance for real-world data has not yet been established. In this work, we assess the relevance of the bias using two examples of multivariate time series recorded in natural complex systems. The first is the time series of local brain activity as measured by functional magnetic resonance imaging in resting healthy human subjects, and the second is the time series of average monthly surface air temperature coming from a large reanalysis of climatological data over the period 1948-2012. In both cases, the clustering in the thresholded correlation graph is substantially higher compared with a realization of a density-matched random graph, while the shortest paths are relatively short, showing thus distinguishing features of small-world structure. However, comparable or even stronger small-world properties were reproduced in correlation graphs of model processes with randomly scrambled interconnections. This suggests that the small-world properties of the correlation matrices of these real-world systems indeed do not reflect genuinely the properties of the underlying interaction structure, but rather result from the inherent properties of correlation matrix.
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.
NASA Astrophysics Data System (ADS)
Wu, Huijun; Wang, Hao; Lü, Linyuan
Applying network science to investigate the complex systems has become a hot topic. In neuroscience, understanding the architectures of complex brain networks was a vital issue. An enormous amount of evidence had supported the brain was cost/efficiency trade-off with small-worldness, hubness and modular organization through the functional MRI and structural MRI investigations. However, the T1-weighted/T2-weighted (T1w/T2w) ratio brain networks were mostly unexplored. Here, we utilized a KL divergence-based method to construct large-scale individual T1w/T2w ratio brain networks and investigated the underlying topological attributes of these networks. Our results supported that the T1w/T2w ratio brain networks were comprised of small-worldness, an exponentially truncated power-law degree distribution, frontal-parietal hubs and modular organization. Besides, there were significant positive correlations between the network metrics and fluid intelligence. Thus, the T1w/T2w ratio brain networks open a new avenue to understand the human brain and are a necessary supplement for future MRI studies.
Impact of Partial Time Delay on Temporal Dynamics of Watts-Strogatz Small-World Neuronal Networks
NASA Astrophysics Data System (ADS)
Yan, Hao; Sun, Xiaojuan
2017-06-01
In this paper, we mainly discuss effects of partial time delay on temporal dynamics of Watts-Strogatz (WS) small-world neuronal networks by controlling two parameters. One is the time delay τ and the other is the probability of partial time delay pdelay. Temporal dynamics of WS small-world neuronal networks are discussed with the aid of temporal coherence and mean firing rate. With the obtained simulation results, it is revealed that for small time delay τ, the probability pdelay could weaken temporal coherence and increase mean firing rate of neuronal networks, which indicates that it could improve neuronal firings of the neuronal networks while destroying firing regularity. For large time delay τ, temporal coherence and mean firing rate do not have great changes with respect to pdelay. Time delay τ always has great influence on both temporal coherence and mean firing rate no matter what is the value of pdelay. Moreover, with the analysis of spike trains and histograms of interspike intervals of neurons inside neuronal networks, it is found that the effects of partial time delays on temporal coherence and mean firing rate could be the result of locking between the period of neuronal firing activities and the value of time delay τ. In brief, partial time delay could have great influence on temporal dynamics of the neuronal networks.
Market-oriented Programming Using Small-world Networks for Controlling Building Environments
NASA Astrophysics Data System (ADS)
Shigei, Noritaka; Miyajima, Hiromi; Osako, Tsukasa
The market model, which is one of the economic activity models, is modeled as an agent system, and applying the model to the resource allocation problem has been studied. For air conditioning control of building, which is one of the resource allocation problems, an effective method based on the agent system using auction has been proposed for traditional PID controller. On the other hand, it has been considered that this method is performed by decentralized control. However, its decentralization is not perfect, and its performace is not enough. In this paper, firstly, we propose a perfectly decentralized agent model and show its performance. Secondly, in order to improve the model, we propose the agent model based on small-world model. The effectiveness of the proposed model is shown by simulation.
Varoquaux, G; Gramfort, A; Poline, J B; Thirion, B
2012-01-01
Correlations in the signal observed via functional Magnetic Resonance Imaging (fMRI), are expected to reveal the interactions in the underlying neural populations through hemodynamic response. In particular, they highlight distributed set of mutually correlated regions that correspond to brain networks related to different cognitive functions. Yet graph-theoretical studies of neural connections give a different picture: that of a highly integrated system with small-world properties: local clustering but with short pathways across the complete structure. We examine the conditional independence properties of the fMRI signal, i.e. its Markov structure, to find realistic assumptions on the connectivity structure that are required to explain the observed functional connectivity. In particular we seek a decomposition of the Markov structure into segregated functional networks using decomposable graphs: a set of strongly-connected and partially overlapping cliques. We introduce a new method to efficiently extract such cliques on a large, strongly-connected graph. We compare methods learning different graph structures from functional connectivity by testing the goodness of fit of the model they learn on new data. We find that summarizing the structure as strongly-connected networks can give a good description only for very large and overlapping networks. These results highlight that Markov models are good tools to identify the structure of brain connectivity from fMRI signals, but for this purpose they must reflect the small-world properties of the underlying neural systems. Copyright © 2012 Elsevier Ltd. All rights reserved.
Yan, Yan; Song, Jian; Xu, Guozheng; Yao, Shun; Cao, Chenglong; Li, Chang; Peng, Guibao; Du, Hao
2017-10-01
This study investigated the characteristics of the small-world brain network architecture of patients with mild traumatic brain injury (MTBI), and a correlation between brain functional connectivity network properties in the resting-state fMRI and Standardized Assessment of Concussion (SAC) parameters. The neurological conditions of 22 MTBI patients and 17 normal control individuals were evaluated according to the SAC. Resting-state fMRI was performed in all subjects 3 and 7days after injury respectively. After preprocessing the fMRI data, cortex functional regions were marked using AAL90 and Dosenbach160 templates. The small-world network parameters and areas under the integral curves were computed in the range of sparsity from 0.01 to 0.5. Independent-sample t-tests were used to compare these parameters between the MTBI and control group. Significantly different parameters were investigated for correlations with SAC scores; those that correlated were chosen for further curve fitting. The clustering coefficient, the communication efficiency across in local networks, and the strength of connectivity were all higher in MTBI patients relative to control individuals. Parameters in 160 brain regions of the MTBI group significantly correlated with total SAC score and score for attention; the network parameters may be a quadratic function of attention scores of SAC and a cubic function of SAC scores. MTBI patients were characterized by elevated communication efficiency across global brain regions, and in local networks, and strength of mean connectivity. These features may be associated with brain function compensation. The network parameters significantly correlated with SAC total and attention scores. Copyright © 2017 Elsevier Ltd. All rights reserved.
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.
Sun, Xiaojuan; Perc, Matjaž; Kurths, Jürgen
2017-05-01
In this paper, we study effects of partial time delays on phase synchronization in Watts-Strogatz small-world neuronal networks. Our focus is on the impact of two parameters, namely the time delay τ and the probability of partial time delay p delay , whereby the latter determines the probability with which a connection between two neurons is delayed. Our research reveals that partial time delays significantly affect phase synchronization in this system. In particular, partial time delays can either enhance or decrease phase synchronization and induce synchronization transitions with changes in the mean firing rate of neurons, as well as induce switching between synchronized neurons with period-1 firing to synchronized neurons with period-2 firing. Moreover, in comparison to a neuronal network where all connections are delayed, we show that small partial time delay probabilities have especially different influences on phase synchronization of neuronal networks.
NASA Astrophysics Data System (ADS)
Sun, Xiaojuan; Perc, Matjaž; Kurths, Jürgen
2017-05-01
In this paper, we study effects of partial time delays on phase synchronization in Watts-Strogatz small-world neuronal networks. Our focus is on the impact of two parameters, namely the time delay τ and the probability of partial time delay pdelay, whereby the latter determines the probability with which a connection between two neurons is delayed. Our research reveals that partial time delays significantly affect phase synchronization in this system. In particular, partial time delays can either enhance or decrease phase synchronization and induce synchronization transitions with changes in the mean firing rate of neurons, as well as induce switching between synchronized neurons with period-1 firing to synchronized neurons with period-2 firing. Moreover, in comparison to a neuronal network where all connections are delayed, we show that small partial time delay probabilities have especially different influences on phase synchronization of neuronal networks.
Quality of Care as an Emergent Phenomenon out of a Small-World Network of Relational Actors.
Fiorini, Rodolfo; De Giacomo, Piero; Marconi, Pier Luigi; L'Abate, Luciano
2014-01-01
In Healthcare Decision Support System, the development and evaluation of effective "Quality of Care" (QOC) indicators, in simulation-based training, are key feature to develop resilient and antifragile organization scenarios. Is it possible to conceive of QOC not only as a result of a voluntary and rational decision, imposed or even not, but also as an overall system "emergent phenomenon" out of a small-world network of relational synthetic actors, endowed with their own personality profiles to simulate human behaviour (for short, called "subjects")? In order to answer this question and to observe the phenomena of real emergence we should use computational models of high complexity, with heavy computational load and extensive computational time. Nevertheless, De Giacomo's Elementary Pragmatic Model (EPM) intrinsic self-reflexive functional logical closure enables to run simulation examples to classify the outcomes grown out of a small-world network of relational subjects fast and effectively. Therefore, it is possible to take note and to learn of how much strategic systemic interventions can induce context conditions of QOC facilitation, which can improve the effectiveness of specific actions, which otherwise might be paradoxically counterproductive also. Early results are so encouraging to use EPM as basic block to start designing more powerful Evolutive Elementary Pragmatic Model (E2PM) for real emergence computational model, to cope with ontological uncertainty at system level.
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.
The small world of osteocytes: connectomics of the lacuno-canalicular network in bone
NASA Astrophysics Data System (ADS)
Kollmannsberger, Philip; Kerschnitzki, Michael; Repp, Felix; Wagermaier, Wolfgang; Weinkamer, Richard; Fratzl, Peter
2017-07-01
Osteocytes and their cell processes reside in a large, interconnected network of voids pervading the mineralized bone matrix of most vertebrates. This osteocyte lacuno-canalicular network (OLCN) is believed to play important roles in mechanosensing, mineral homeostasis, and for the mechanical properties of bone. While the extracellular matrix structure of bone is extensively studied on ultrastructural and macroscopic scales, there is a lack of quantitative knowledge on how the cellular network is organized. Using a recently introduced imaging and quantification approach, we analyze the OLCN in different bone types from mouse and sheep that exhibit different degrees of structural organization not only of the cell network but also of the fibrous matrix deposited by the cells. We define a number of robust, quantitative measures that are derived from the theory of complex networks. These measures enable us to gain insights into how efficient the network is organized with regard to intercellular transport and communication. Our analysis shows that the cell network in regularly organized, slow-growing bone tissue from sheep is less connected, but more efficiently organized compared to irregular and fast-growing bone tissue from mice. On the level of statistical topological properties (edges per node, edge length and degree distribution), both network types are indistinguishable, highlighting that despite pronounced differences at the tissue level, the topological architecture of the osteocyte canalicular network at the subcellular level may be independent of species and bone type. Our results suggest a universal mechanism underlying the self-organization of individual cells into a large, interconnected network during bone formation and mineralization.
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.
Tian, Lixia; Wang, Jinhui; Yan, Chaogan; He, Yong
2011-01-01
We employed resting-state functional MRI (R-fMRI) to investigate hemisphere- and gender-related differences in the topological organization of human brain functional networks. Brain networks were first constructed by measuring inter-regional temporal correlations of R-fMRI data within each hemisphere in 86 young, healthy, right-handed adults (38 males and 48 females) followed by a graph-theory analysis. The hemispheric networks exhibit small-world attributes (high clustering and short paths) that are compatible with previous results in the whole-brain functional networks. Furthermore, we found that compared with females, males have a higher normalized clustering coefficient in the right hemispheric network but a lower clustering coefficient in the left hemispheric network, suggesting a gender-hemisphere interaction. Moreover, we observed significant hemisphere-related differences in the regional nodal characteristics in various brain regions, such as the frontal and occipital regions (leftward asymmetry) and the temporal regions (rightward asymmetry), findings that are consistent with previous studies of brain structural and functional asymmetries. Together, our results suggest that the topological organization of human brain functional networks is associated with gender and hemispheres, and they provide insights into the understanding of functional substrates underlying individual differences in behaviors and cognition. Copyright © 2010 Elsevier Inc. All rights reserved.
Arzouan, Yossi; Solomon, Sorin; Faust, Miriam; Goldstein, Abraham
2011-04-27
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.
Yu, Dongyuan; Xu, Xu; Zhou, Jing; Li, Eric
2017-05-01
This study considers a delayed neural network with excitatory and inhibitory shortcuts. The global stability of the trivial equilibrium is investigated based on Lyapunov's direct method and the delay-dependent criteria are obtained. It is shown that both the excitatory and inhibitory shortcuts decrease the stability interval, but a time delay can be employed as a global stabilizer. In addition, we analyze the bounds of the eigenvalues of the adjacent matrix using matrix perturbation theory and then obtain the generalized sufficient conditions for local stability. The possibility of small inhibitory shortcuts is helpful for maintaining stability. The mechanisms of instability, bifurcation modes, and chaos are also investigated. Compared with methods based on mean-field theory, the proposed method can guarantee the stability of the system in most cases with random events. The proposed method is effective for cases where excitatory and inhibitory shortcuts exist simultaneously in the network. Copyright © 2017 Elsevier Ltd. All rights reserved.
Kleczkowski, Adam; Oleś, Katarzyna; Gudowska-Nowak, Ewa; Gilligan, Christopher A.
2012-01-01
We present a combined epidemiological and economic model for control of diseases spreading on local and small-world networks. The disease is characterized by a pre-symptomatic infectious stage that makes detection and control of cases more difficult. The effectiveness of local (ring-vaccination or culling) and global control strategies is analysed by comparing the net present values of the combined cost of preventive treatment and illness. The optimal strategy is then selected by minimizing the total cost of the epidemic. We show that three main strategies emerge, with treating a large number of individuals (global strategy, GS), treating a small number of individuals in a well-defined neighbourhood of a detected case (local strategy) and allowing the disease to spread unchecked (null strategy, NS). The choice of the optimal strategy is governed mainly by a relative cost of palliative and preventive treatments. If the disease spreads within the well-defined neighbourhood, the local strategy is optimal unless the cost of a single vaccine is much higher than the cost associated with hospitalization. In the latter case, it is most cost-effective to refrain from prevention. Destruction of local correlations, either by long-range (small-world) links or by inclusion of many initial foci, expands the range of costs for which the NS is most cost-effective. The GS emerges for the case when the cost of prevention is much lower than the cost of treatment and there is a substantial non-local component in the disease spread. We also show that local treatment is only desirable if the disease spreads on a small-world network with sufficiently few long-range links; otherwise it is optimal to treat globally. In the mean-field case, there are only two optimal solutions, to treat all if the cost of the vaccine is low and to treat nobody if it is high. The basic reproduction ratio, R0, does not depend on the rate of responsive treatment in this case and the disease always invades (but
Kleczkowski, Adam; Oleś, Katarzyna; Gudowska-Nowak, Ewa; Gilligan, Christopher A
2012-01-07
We present a combined epidemiological and economic model for control of diseases spreading on local and small-world networks. The disease is characterized by a pre-symptomatic infectious stage that makes detection and control of cases more difficult. The effectiveness of local (ring-vaccination or culling) and global control strategies is analysed by comparing the net present values of the combined cost of preventive treatment and illness. The optimal strategy is then selected by minimizing the total cost of the epidemic. We show that three main strategies emerge, with treating a large number of individuals (global strategy, GS), treating a small number of individuals in a well-defined neighbourhood of a detected case (local strategy) and allowing the disease to spread unchecked (null strategy, NS). The choice of the optimal strategy is governed mainly by a relative cost of palliative and preventive treatments. If the disease spreads within the well-defined neighbourhood, the local strategy is optimal unless the cost of a single vaccine is much higher than the cost associated with hospitalization. In the latter case, it is most cost-effective to refrain from prevention. Destruction of local correlations, either by long-range (small-world) links or by inclusion of many initial foci, expands the range of costs for which the NS is most cost-effective. The GS emerges for the case when the cost of prevention is much lower than the cost of treatment and there is a substantial non-local component in the disease spread. We also show that local treatment is only desirable if the disease spreads on a small-world network with sufficiently few long-range links; otherwise it is optimal to treat globally. In the mean-field case, there are only two optimal solutions, to treat all if the cost of the vaccine is low and to treat nobody if it is high. The basic reproduction ratio, R(0), does not depend on the rate of responsive treatment in this case and the disease always invades
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.
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
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. Copyright © 2013 Elsevier B.V. All rights reserved.
NASA Astrophysics Data System (ADS)
Najafi, M. N.; Dashti-Naserabadi, H.
2018-03-01
In many situations we are interested in the propagation of energy in some portions of a three-dimensional system with dilute long-range links. In this paper, a sandpile model is defined on the three-dimensional small-world network with real dissipative boundaries and the energy propagation is studied in three dimensions as well as the two-dimensional cross-sections. Two types of cross-sections are defined in the system, one in the bulk and another in the system boundary. The motivation of this is to make clear how the statistics of the avalanches in the bulk cross-section tend to the statistics of the dissipative avalanches, defined in the boundaries as the concentration of long-range links (α ) increases. This trend is numerically shown to be a power law in a manner described in the paper. Two regimes of α are considered in this work. For sufficiently small α s the dominant behavior of the system is just like that of the regular BTW, whereas for the intermediate values the behavior is nontrivial with some exponents that are reported in the paper. It is shown that the spatial extent up to which the statistics is similar to the regular BTW model scales with α just like the dissipative BTW model with the dissipation factor (mass in the corresponding ghost model) m2˜α for the three-dimensional system as well as its two-dimensional cross-sections.
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…
Hu, Yuxiao; Xu, Qiang; Shen, Junkang; Li, Kai; Zhu, Hong; Zhang, Zhiqiang; Lu, Guangming
2015-02-01
Many studies have demonstrated the small-worldness of the human brain, and have revealed a sexual dimorphism in brain network properties. However, little is known about the gender effects on the topological organization of the brain metabolic covariance networks. To investigate the small-worldness and the gender differences in the topological architectures of human brain metabolic networks. FDG-PET data of 400 healthy right-handed subjects (200 women and 200 age-matched men) were involved in the present study. Metabolic networks of each gender were constructed by calculating the covariance of regional cerebral glucose metabolism (rCMglc) across subjects on the basis of AAL parcellation. Gender differences of network and nodal properties were investigated by using the graph theoretical approaches. Moreover, the gender-related difference of rCMglc in each brain region was tested for investigating the relationships between the hub regions and the brain regions showing significant gender-related differences in rCMglc. We found prominent small-world properties in the domain of metabolic networks in each gender. No significant gender difference in the global characteristics was found. Gender differences of nodal characteristic were observed in a few brain regions. We also found bilateral and lateralized distributions of network hubs in the females and males. Furthermore, we first reported that some hubs of a gender located in the brain regions showing weaker rCMglc in this gender than the other gender. The present study demonstrated that small-worldness was existed in metabolic networks, and revealed gender differences of organizational patterns in metabolic network. These results maybe provided insights into the understanding of the metabolic substrates underlying individual differences in cognition and behaviors. © The Foundation Acta Radiologica 2014 Reprints and permissions: sagepub.co.uk/journalsPermissions.nav.
NASA Astrophysics Data System (ADS)
Nunes Amaral, Luis A.
2002-03-01
We study the statistical properties of a variety of diverse real-world networks including the neural network of C. Elegans, food webs for seven distinct environments, transportation and technological networks, and a number of distinct social networks [1-5]. We present evidence of the occurrence of three classes of small-world networks [2]: (a) scale-free networks, characterized by a vertex connectivity distribution that decays as a power law; (b) broad-scale networks, characterized by a connectivity distribution that has a power-law regime followed by a sharp cut-off; (c) single-scale networks, characterized by a connectivity distribution with a fast decaying tail. Moreover, we note for the classes of broad-scale and single-scale networks that there are constraints limiting the addition of new links. Our results suggest that the nature of such constraints may be the controlling factor for the emergence of different classes of networks. [See http://polymer.bu.edu/ amaral/Networks.html for details and htpp://polymer.bu.edu/ amaral/Professional.html for access to PDF files of articles.] 1. M. Barthélémy, L. A. N. Amaral, Phys. Rev. Lett. 82, 3180-3183 (1999). 2. L. A. N. Amaral, A. Scala, M. Barthélémy, H. E. Stanley, Proc. Nat. Acad. Sci. USA 97, 11149-11152 (2000). 3. F. Liljeros, C. R. Edling, L. A. N. Amaral, H. E. Stanley, and Y. Åberg, Nature 411, 907-908 (2001). 4. J. Camacho, R. Guimera, L.A.N. Amaral, Phys. Rev. E RC (to appear). 5. S. Mossa, M. Barthelemy, H.E. Stanley, L.A.N. Amaral (submitted).
NASA Astrophysics Data System (ADS)
Ma, Fei; Yao, Bing
2017-10-01
It is always an open, demanding and difficult task for generating available model to simulate dynamical functions and reveal inner principles from complex systems and networks. In this article, due to lots of real-life and artificial networks are built from series of simple and small groups (components), we discuss some interesting and helpful network-operation to generate more realistic network models. In view of community structure (modular topology), we present a class of sparse network models N(t , m) . At the moment, we capture the fact the N(t , 4) has not only scale-free feature, which means that the probability that a randomly selected vertex with degree k decays as a power-law, following P(k) ∼k-γ, where γ is the degree exponent, but also small-world property, which indicates that the typical distance between two uniform randomly chosen vertices grows proportionally to logarithm of the order of N(t , 4) , namely, relatively shorter diameter and lower average path length, simultaneously displays higher clustering coefficient. Next, as a new topological parameter correlating to reliability, synchronization capability and diffusion properties of networks, the number of spanning trees over a network is studied in more detail, an exact analytical solution for the number of spanning trees of the N(t , 4) is obtained. Based on the network-operation, part hub-vertex linking with each other will be helpful for structuring various network models and investigating the rules related with real-life networks.
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.
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.
Rowland, Jared A; Stapleton-Kotloski, Jennifer R; Dobbins, Dorothy L; Rogers, Emily; Godwin, Dwayne W; Taber, Katherine H
2018-05-01
Cross-sectional and longitudinal studies in active duty and veteran cohorts have both demonstrated that deployment-acquired traumatic brain injury (TBI) is an independent risk factor for developing post-traumatic stress disorder (PTSD), beyond confounds such as combat exposure, physical injury, predeployment TBI, and pre-deployment psychiatric symptoms. This study investigated how resting-state brain networks differ between individuals who developed PTSD and those who did not following deployment-acquired TBI. Participants included postdeployment veterans with deployment-acquired TBI history both with and without current PTSD diagnosis. Graph metrics, including small-worldness, clustering coefficient, and modularity, were calculated from individually constructed whole-brain networks based on 5-min eyes-open resting-state magnetoencephalography (MEG) recordings. Analyses were adjusted for age and premorbid IQ. Results demonstrated that participants with current PTSD displayed higher levels of small-worldness, F(1,12) = 5.364, p < 0.039, partial eta squared = 0.309, and Cohen's d = 0.972, and clustering coefficient, F(1, 12) = 12.204, p < 0.004, partial eta squared = 0.504, and Cohen's d = 0.905, than participants without current PTSD. There were no between-group differences in modularity or the number of modules present. These findings are consistent with a hyperconnectivity hypothesis of the effect of TBI history on functional networks rather than a disconnection hypothesis, demonstrating increased levels of clustering coefficient rather than a decrease as might be expected; however, these results do not account for potential changes in brain structure. These results demonstrate the potential pathological sequelae of changes in functional brain networks following deployment-acquired TBI and represent potential neurobiological changes associated with deployment-acquired TBI that may increase the risk of subsequently developing PTSD.
Cluster-size entropy in the Axelrod model of social influence: small-world networks and mass media.
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 S(c), 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 S(c)(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 q(c) 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.
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.
Non-Newtonian fluid flow in 2D fracture networks
NASA Astrophysics Data System (ADS)
Zou, L.; Håkansson, U.; Cvetkovic, V.
2017-12-01
Modeling of non-Newtonian fluid (e.g., drilling fluids and cement grouts) flow in fractured rocks is of interest in many geophysical and industrial practices, such as drilling operations, enhanced oil recovery and rock grouting. In fractured rock masses, the flow paths are dominated by fractures, which are often represented as discrete fracture networks (DFN). In the literature, many studies have been devoted to Newtonian fluid (e.g., groundwater) flow in fractured rock using the DFN concept, but few works are dedicated to non-Newtonian fluids.In this study, a generalized flow equation for common non-Newtonian fluids (such as Bingham, power-law and Herschel-Bulkley) in a single fracture is obtained from the analytical solutions for non-Newtonian fluid discharge between smooth parallel plates. Using Monte Carlo sampling based on site characterization data for the distribution of geometrical features (e.g., density, length, aperture and orientations) in crystalline fractured rock, a two dimensional (2D) DFN model is constructed for generic flow simulations. Due to complex properties of non-Newtonian fluids, the relationship between fluid discharge and the pressure gradient is nonlinear. A Galerkin finite element method solver is developed to iteratively solve the obtained nonlinear governing equations for the 2D DFN model. Using DFN realizations, simulation results for different geometrical distributions of the fracture network and different non-Newtonian fluid properties are presented to illustrate the spatial discharge distributions. The impact of geometrical structures and the fluid properties on the non-Newtonian fluid flow in 2D DFN is examined statistically. The results generally show that modeling non-Newtonian fluid flow in fractured rock as a DFN is feasible, and that the discharge distribution may be significantly affected by the geometrical structures as well as by the fluid constitutive properties.
NASA Astrophysics Data System (ADS)
Ausloos, Marcel
2015-06-01
Diffusion of knowledge is expected to be huge when agents are open minded. The report concerns a more difficult diffusion case when communities are made of stubborn agents. Communities having markedly different opinions are for example the Neocreationist and Intelligent Design Proponents (IDP), on one hand, and the Darwinian Evolution Defenders (DED), on the other hand. The case of knowledge diffusion within such communities is studied here on a network based on an adjacency matrix built from time ordered selected quotations of agents, whence for inter- and intra-communities. The network is intrinsically directed and not necessarily reciprocal. Thus, the adjacency matrices have complex eigenvalues; the eigenvectors present complex components. A quantification of the slow-down or speed-up effects of information diffusion in such temporal networks, with non-Markovian contact sequences, can be made by comparing the real time dependent (directed) network to its counterpart, the time aggregated (undirected) network, - which has real eigenvalues. In order to do so, small world networks which both contain an odd number of nodes are studied and compared to similar networks with an even number of nodes. It is found that (i) the diffusion of knowledge is more difficult on the largest networks; (ii) the network size influences the slowing-down or speeding-up diffusion process. Interestingly, it is observed that (iii) the diffusion of knowledge is slower in IDP and faster in DED communities. It is suggested that the finding can be "rationalized", if some "scientific quality" and "publication habit" is attributed to the agents, as common sense would guess. This finding offers some opening discussion toward tying scientific knowledge to belief.
Li, Wenjun; Douglas Ward, B; Liu, Xiaolin; Chen, Gang; Jones, Jennifer L; Antuono, Piero G; Li, Shi-Jiang; Goveas, Joseph S
2015-10-01
The topological architecture of the whole-brain functional networks in those with and without late-life depression (LLD) and amnestic mild cognitive impairment (aMCI) are unknown. To investigate the differences in the small-world measures and the modular community structure of the functional networks between patients with LLD and aMCI when occurring alone or in combination and cognitively healthy non-depressed controls. 79 elderly participants (LLD (n=23), aMCI (n=18), comorbid LLD and aMCI (n=13), and controls (n=25)) completed neuropsychiatric assessments. Graph theoretical methods were employed on resting-state functional connectivity MRI data. LLD and aMCI comorbidity was associated with the greatest disruptions in functional integration measures (decreased global efficiency and increased path length); both LLD groups showed abnormal functional segregation (reduced local efficiency). The modular network organisation was most variable in the comorbid group, followed by patients with LLD-only. Decreased mean global, local and nodal efficiency metrics were associated with greater depressive symptom severity but not memory performance. Considering the whole brain as a complex network may provide unique insights on the neurobiological underpinnings of LLD with and without cognitive impairment. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.
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.
Frantzidis, Christos A; Vivas, Ana B; Tsolaki, Anthoula; Klados, Manousos A; Tsolaki, Magda; Bamidis, Panagiotis D
2014-01-01
Previous neuroscientific findings have linked Alzheimer's Disease (AD) with less efficient information processing and brain network disorganization. However, pathological alterations of the brain networks during the preclinical phase of amnestic Mild Cognitive Impairment (aMCI) remain largely unknown. The present study aimed at comparing patterns of the detection of functional disorganization in MCI relative to Mild Dementia (MD). Participants consisted of 23 cognitively healthy adults, 17 aMCI and 24 mild AD patients who underwent electroencephalographic (EEG) data acquisition during a resting-state condition. Synchronization analysis through the Orthogonal Discrete Wavelet Transform (ODWT), and directional brain network analysis were applied on the EEG data. This computational model was performed for networks that have the same number of edges (N = 500, 600, 700, 800 edges) across all participants and groups (fixed density values). All groups exhibited a small-world (SW) brain architecture. However, we found a significant reduction in the SW brain architecture in both aMCI and MD patients relative to the group of Healthy controls. This functional disorganization was also correlated with the participant's generic cognitive status. The deterioration of the network's organization was caused mainly by deficient local information processing as quantified by the mean cluster coefficient value. Functional hubs were identified through the normalized betweenness centrality metric. Analysis of the local characteristics showed relative hub preservation even with statistically significant reduced strength. Compensatory phenomena were also evident through the formation of additional hubs on left frontal and parietal regions. Our results indicate a declined functional network organization even during the prodromal phase. Degeneration is evident even in the preclinical phase and coexists with transient network reorganization due to compensation.
The Small World of Psychopathology
Borsboom, Denny; Cramer, Angélique O. J.; Schmittmann, Verena D.; Epskamp, Sacha; Waldorp, Lourens J.
2011-01-01
Background Mental disorders are highly comorbid: people having one disorder are likely to have another as well. We explain empirical comorbidity patterns based on a network model of psychiatric symptoms, derived from an analysis of symptom overlap in the Diagnostic and Statistical Manual of Mental Disorders-IV (DSM-IV). Principal Findings We show that a) half of the symptoms in the DSM-IV network are connected, b) the architecture of these connections conforms to a small world structure, featuring a high degree of clustering but a short average path length, and c) distances between disorders in this structure predict empirical comorbidity rates. Network simulations of Major Depressive Episode and Generalized Anxiety Disorder show that the model faithfully reproduces empirical population statistics for these disorders. Conclusions In the network model, mental disorders are inherently complex. This explains the limited successes of genetic, neuroscientific, and etiological approaches to unravel their causes. We outline a psychosystems approach to investigate the structure and dynamics of mental disorders. PMID:22114671
NASA Astrophysics Data System (ADS)
Ma, Fei; Su, Jing; Hao, Yongxing; Yao, Bing; Yan, Guanghui
2018-02-01
The problem of uncovering the internal operating function of network models is intriguing, demanded and attractive in researches of complex networks. Notice that, in the past two decades, a great number of artificial models are built to try to answer the above mentioned task. Based on the different growth ways, these previous models can be divided into two categories, one type, possessing the preferential attachment, follows a power-law P(k) ∼k-γ, 2 < γ < 3. The other has exponential-scaling feature, P(k) ∼α-k. However, there are no models containing above two kinds of growth ways to be presented, even the study of interconnection between these two growth manners in the same model is lacking. Hence, in this paper, we construct a class of planar and self-similar graphs motivated from a new attachment way, vertex-edge-growth network-operation, more precisely, the couple of both them. We report that this model is sparse, small world and hierarchical. And then, not only is scale-free feature in our model, but also lies the degree parameter γ(≈ 3 . 242) out the typical range. Note that, we suggest that the coexistence of multiple vertex growth ways will have a prominent effect on the power-law parameter γ, and the preferential attachment plays a dominate role on the development of networks over time. At the end of this paper, we obtain an exact analytical expression for the total number of spanning trees of models and also capture spanning trees entropy which we have compared with those of their corresponding component elements.
Yao, Yuangen; Deng, Haiyou; Ma, Chengzhang; Yi, Ming; Ma, Jun
2017-01-01
Spiral waves are observed in the chemical, physical and biological systems, and the emergence of spiral waves in cardiac tissue is linked to some diseases such as heart ventricular fibrillation and epilepsy; thus it has importance in theoretical studies and potential medical applications. Noise is inevitable in neuronal systems and can change the electrical activities of neuron in different ways. Many previous theoretical studies about the impacts of noise on spiral waves focus an unbounded Gaussian noise and even colored noise. In this paper, the impacts of bounded noise and rewiring of network on the formation and instability of spiral waves are discussed in small-world (SW) network of Hodgkin-Huxley (HH) neurons through numerical simulations, and possible statistical analysis will be carried out. Firstly, we present SW network of HH neurons subjected to bounded noise. Then, it is numerically demonstrated that bounded noise with proper intensity σ, amplitude A, or frequency f can facilitate the formation of spiral waves when rewiring probability p is below certain thresholds. In other words, bounded noise-induced resonant behavior can occur in the SW network of neurons. In addition, rewiring probability p always impairs spiral waves, while spiral waves are confirmed to be robust for small p, thus shortcut-induced phase transition of spiral wave with the increase of p is induced. Furthermore, statistical factors of synchronization are calculated to discern the phase transition of spatial pattern, and it is confirmed that larger factor of synchronization is approached with increasing of rewiring probability p, and the stability of spiral wave is destroyed.
NASA Astrophysics Data System (ADS)
Ma, Fei; Su, Jing; Yao, Bing
2018-05-01
The problem of determining and calculating the number of spanning trees of any finite graph (model) is a great challenge, and has been studied in various fields, such as discrete applied mathematics, theoretical computer science, physics, chemistry and the like. In this paper, firstly, thank to lots of real-life systems and artificial networks built by all kinds of functions and combinations among some simpler and smaller elements (components), we discuss some helpful network-operation, including link-operation and merge-operation, to design more realistic and complicated network models. Secondly, we present a method for computing the total number of spanning trees. As an accessible example, we apply this method to space of trees and cycles respectively, and our results suggest that it is indeed a better one for such models. In order to reflect more widely practical applications and potentially theoretical significance, we study the enumerating method in some existing scale-free network models. On the other hand, we set up a class of new models displaying scale-free feature, that is to say, following P(k) k-γ, where γ is the degree exponent. Based on detailed calculation, the degree exponent γ of our deterministic scale-free models satisfies γ > 3. In the rest of our discussions, we not only calculate analytically the solutions of average path length, which indicates our models have small-world property being prevailing in amounts of complex systems, but also derive the number of spanning trees by means of the recursive method described in this paper, which clarifies our method is convenient to research these models.
NASA Astrophysics Data System (ADS)
Marchiori, Massimo; Latora, Vito
2000-10-01
The small-world phenomenon, popularly known as six degrees of separation, has been mathematically formalized by Watts and Strogatz in a study of the topological properties of a network. Small-world networks are defined in terms of two quantities: they have a high clustering coefficient C like regular lattices and a short characteristic path length L typical of random networks. Physical distances are of fundamental importance in applications to real cases; nevertheless, this basic ingredient is missing in the original formulation. Here, we introduce a new concept, the connectivity length D, that gives harmony to the whole theory. D can be evaluated on a global and on a local scale and plays in turn the role of L and 1/ C. Moreover, it can be computed for any metrical network and not only for the topological cases. D has a precise meaning in terms of information propagation and describes in a unified way, both the structural and the dynamical aspects of a network: small-worlds are defined by a small global and local D, i.e., by a high efficiency in propagating information both on a local and global scale. The neural system of the nematode C. elegans, the collaboration graph of film actors, and the oldest US subway system, can now be studied also as metrical networks and are shown to be small-worlds.
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.
Kim, Sang-Yoon; Lim, Woochang
2017-09-01
We consider an inhomogeneous small-world network (SWN) composed of inhibitory short-range (SR) and long-range (LR) interneurons, and investigate the effect of network architecture on emergence of synchronized brain rhythms by varying the fraction of LR interneurons p long . The betweenness centralities of the LR and SR interneurons (characterizing the potentiality in controlling communication between other interneurons) are distinctly different. Hence, in view of the betweenness, SWNs we consider are inhomogeneous, unlike the "canonical" Watts-Strogatz SWN with nearly the same betweenness centralities. For small p long , the load of communication traffic is much concentrated on a few LR interneurons. However, as p long is increased, the number of LR connections (coming from LR interneurons) increases, and then the load of communication traffic is less concentrated on LR interneurons, which leads to better efficiency of global communication between interneurons. Sparsely synchronized rhythms are thus found to emerge when passing a small critical value p long (c) (≃0.16). The population frequency of the sparsely synchronized rhythm is ultrafast (higher than 100 Hz), while the mean firing rate of individual interneurons is much lower (∼30 Hz) due to stochastic and intermittent neural discharges. These dynamical behaviors in the inhomogeneous SWN are also compared with those in the homogeneous Watts-Strogatz SWN, in connection with their network topologies. Particularly, we note that the main difference between the two types of SWNs lies in the distribution of betweenness centralities. Unlike the case of the Watts-Strogatz SWN, dynamical responses to external stimuli vary depending on the type of stimulated interneurons in the inhomogeneous SWN. We consider two cases of external time-periodic stimuli applied to sub-populations of the LR and SR interneurons, respectively. Dynamical responses (such as synchronization suppression and enhancement) to these two cases of
Structure of a randomly grown 2-d network.
Ajazi, Fioralba; Napolitano, George M; Turova, Tatyana; Zaurbek, Izbassar
2015-10-01
We introduce a growing random network on a plane as a model of a growing neuronal network. The properties of the structure of the induced graph are derived. We compare our results with available data. In particular, it is shown that depending on the parameters of the model the system undergoes in time different phases of the structure. We conclude with a possible explanation of some empirical data on the connections between neurons. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.
A Small World of Neuronal Synchrony
Yu, Shan; Huang, Debin; Singer, Wolf
2008-01-01
A small-world network has been suggested to be an efficient solution for achieving both modular and global processing—a property highly desirable for brain computations. Here, we investigated functional networks of cortical neurons using correlation analysis to identify functional connectivity. To reconstruct the interaction network, we applied the Ising model based on the principle of maximum entropy. This allowed us to assess the interactions by measuring pairwise correlations and to assess the strength of coupling from the degree of synchrony. Visual responses were recorded in visual cortex of anesthetized cats, simultaneously from up to 24 neurons. First, pairwise correlations captured most of the patterns in the population's activity and, therefore, provided a reliable basis for the reconstruction of the interaction networks. Second, and most importantly, the resulting networks had small-world properties; the average path lengths were as short as in simulated random networks, but the clustering coefficients were larger. Neurons differed considerably with respect to the number and strength of interactions, suggesting the existence of “hubs” in the network. Notably, there was no evidence for scale-free properties. These results suggest that cortical networks are optimized for the coexistence of local and global computations: feature detection and feature integration or binding. PMID:18400792
NASA Astrophysics Data System (ADS)
Zekri, Nouredine; Clerc, Jean Pierre
We study numerically in this work the statistical and dynamical properties of the clusters in a one dimensional small world model. The parameters chosen correspond to a realistic network of children of school age where a disease like measles can propagate. Extensive results on the statistical behavior of the clusters around the percolation threshold, as well as the evoltion with time, are discussed. To cite this article: N. Zekri, J.P. Clerc, C. R. Physique 3 (2002) 741-747.
Force Network of a 2D Frictionless Emulsion System
NASA Astrophysics Data System (ADS)
Desmond, Kenneth; Weeks, Eric R.
2010-03-01
We use a quasi-two-dimensional emulsion as a new experimental system to measure various jamming transition properties. Our system consist of confining oil-in-water emulsion droplets between two parallel plates, so that the droplets are squeezed into quasi-two dimensional disks, analogous to granular photoelastic disks. By varying the droplet area fraction, we investigate the force network of this system as we cross through the jamming transition. At a critical area fraction, the composition of the system is no longer characterized primarily by circular disks, but by disks deformed to varying degrees. Quantifying the deformation provides information about the forces acting upon each droplet, and ultimately the force network. The probability distribution of forces is similar to that found for photoelastic disks, with the width of the force distribution narrowing with increasing packing fraction.
Magnetic anisotropy of metal functionalized phthalocyanine 2D networks
Zhu, Guojun; Zhang, Yun; Xiao, Huaping, E-mail: hpxiao@xtu.edu.cn
2016-06-15
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 μ{sub B} 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 thatmore » 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. - Graphical abstract: The charge density redistribution (ρ{sub MPc}-ρ{sub M}-ρ{sub Pc}) and spin density of the CoPc molecule, from top- and side-views. Purple and green isosurfaces indicate charge depletion and accumulation, respectively. Display Omitted.« less
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.
Modeling fluid transport in 2d paper networks
NASA Astrophysics Data System (ADS)
Tirapu Azpiroz, Jaione; Fereira Silva, Ademir; Esteves Ferreira, Matheus; Lopez Candela, William Fernando; Bryant, Peter William; Ohta, Ricardo Luis; Engel, Michael; Steiner, Mathias Bernhard
2018-02-01
Paper-based microfluidic devices offer great potential as a low-cost platform to perform chemical and biochemical tests. Commercially available formats such as dipsticks and lateral-flow test devices are widely popular as they are easy to handle and produce fast and unambiguous results. While these simple devices lack precise control over the flow to enable integration of complex functionality for multi-step processes or the ability to multiplex several tests, intense research in this area is rapidly expanding the possibilities. Modeling and simulation is increasingly more instrumental in gaining insight into the underlying physics driving the processes inside the channels, however simulation of flow in paper-based microfluidic devices has barely been explored to aid in the optimum design and prototyping of these devices for precise control of the flow. In this paper, we implement a multiphase fluid flow model through porous media for the simulation of paper imbibition of an incompressible, Newtonian fluid such as when water, urine or serum is employed. The formulation incorporates mass and momentum conservation equations under Stokes flow conditions and results in two coupled Darcy's law equations for the pressures and saturations of the wetting and non-wetting phases, further simplified to the Richard's equation for the saturation of the wetting fluid, which is then solved using a Finite Element solver. The model tracks the wetting fluid front as it displaces the non-wetting fluid by computing the time-dependent saturation of the wetting fluid. We apply this to the study of liquid transport in two-dimensional paper networks and validate against experimental data concerning the wetting dynamics of paper layouts of varying geometries.
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.
Liang, Xia; Wang, Jinhui; Yan, Chaogan; Shu, Ni; Xu, Ke; Gong, Gaolang; He, Yong
2012-01-01
Graph theoretical analysis of brain networks based on resting-state functional MRI (R-fMRI) has attracted a great deal of attention in recent years. These analyses often involve the selection of correlation metrics and specific preprocessing steps. However, the influence of these factors on the topological properties of functional brain networks has not been systematically examined. Here, we investigated the influences of correlation metric choice (Pearson's correlation versus partial correlation), global signal presence (regressed or not) and frequency band selection [slow-5 (0.01-0.027 Hz) versus slow-4 (0.027-0.073 Hz)] on the topological properties of both binary and weighted brain networks derived from them, and we employed test-retest (TRT) analyses for further guidance on how to choose the "best" network modeling strategy from the reliability perspective. Our results show significant differences in global network metrics associated with both correlation metrics and global signals. Analysis of nodal degree revealed differing hub distributions for brain networks derived from Pearson's correlation versus partial correlation. TRT analysis revealed that the reliability of both global and local topological properties are modulated by correlation metrics and the global signal, with the highest reliability observed for Pearson's-correlation-based brain networks without global signal removal (WOGR-PEAR). The nodal reliability exhibited a spatially heterogeneous distribution wherein regions in association and limbic/paralimbic cortices showed moderate TRT reliability in Pearson's-correlation-based brain networks. Moreover, we found that there were significant frequency-related differences in topological properties of WOGR-PEAR networks, and brain networks derived in the 0.027-0.073 Hz band exhibited greater reliability than those in the 0.01-0.027 Hz band. Taken together, our results provide direct evidence regarding the influences of correlation metrics and specific
Liang, Xia; Wang, Jinhui; Yan, Chaogan; Shu, Ni; Xu, Ke; Gong, Gaolang; He, Yong
2012-01-01
Graph theoretical analysis of brain networks based on resting-state functional MRI (R-fMRI) has attracted a great deal of attention in recent years. These analyses often involve the selection of correlation metrics and specific preprocessing steps. However, the influence of these factors on the topological properties of functional brain networks has not been systematically examined. Here, we investigated the influences of correlation metric choice (Pearson's correlation versus partial correlation), global signal presence (regressed or not) and frequency band selection [slow-5 (0.01–0.027 Hz) versus slow-4 (0.027–0.073 Hz)] on the topological properties of both binary and weighted brain networks derived from them, and we employed test-retest (TRT) analyses for further guidance on how to choose the “best” network modeling strategy from the reliability perspective. Our results show significant differences in global network metrics associated with both correlation metrics and global signals. Analysis of nodal degree revealed differing hub distributions for brain networks derived from Pearson's correlation versus partial correlation. TRT analysis revealed that the reliability of both global and local topological properties are modulated by correlation metrics and the global signal, with the highest reliability observed for Pearson's-correlation-based brain networks without global signal removal (WOGR-PEAR). The nodal reliability exhibited a spatially heterogeneous distribution wherein regions in association and limbic/paralimbic cortices showed moderate TRT reliability in Pearson's-correlation-based brain networks. Moreover, we found that there were significant frequency-related differences in topological properties of WOGR-PEAR networks, and brain networks derived in the 0.027–0.073 Hz band exhibited greater reliability than those in the 0.01–0.027 Hz band. Taken together, our results provide direct evidence regarding the influences of correlation metrics
Invariant 2D object recognition using the wavelet transform and structured neural networks
NASA Astrophysics Data System (ADS)
Khalil, Mahmoud I.; Bayoumi, Mohamed M.
1999-03-01
This paper applies the dyadic wavelet transform and the structured neural networks approach to recognize 2D objects under translation, rotation, and scale transformation. Experimental results are presented and compared with traditional methods. The experimental results showed that this refined technique successfully classified the objects and outperformed some traditional methods especially in the presence of noise.
Batalle, Dafnis; Eixarch, Elisenda; Figueras, Francesc; Muñoz-Moreno, Emma; Bargallo, Nuria; Illa, Miriam; Acosta-Rojas, Ruthy; Amat-Roldan, Ivan; Gratacos, Eduard
2012-04-02
Intrauterine growth restriction (IUGR) due to placental insufficiency affects 5-10% of all pregnancies and it is associated with a wide range of short- and long-term neurodevelopmental disorders. Prediction of neurodevelopmental outcomes in IUGR is among the clinical challenges of modern fetal medicine and pediatrics. In recent years several studies have used magnetic resonance imaging (MRI) to demonstrate differences in brain structure in IUGR subjects, but the ability to use MRI for individual predictive purposes in IUGR is limited. Recent research suggests that MRI in vivo access to brain connectivity might have the potential to help understanding cognitive and neurodevelopment processes. Specifically, MRI based connectomics is an emerging approach to extract information from MRI data that exhaustively maps inter-regional connectivity within the brain to build a graph model of its neural circuitry known as brain network. In the present study we used diffusion MRI based connectomics to obtain structural brain networks of a prospective cohort of one year old infants (32 controls and 24 IUGR) and analyze the existence of quantifiable brain reorganization of white matter circuitry in IUGR group by means of global and regional graph theory features of brain networks. Based on global and regional analyses of the brain network topology we demonstrated brain reorganization in IUGR infants at one year of age. Specifically, IUGR infants presented decreased global and local weighted efficiency, and a pattern of altered regional graph theory features. By means of binomial logistic regression, we also demonstrated that connectivity measures were associated with abnormal performance in later neurodevelopmental outcome as measured by Bayley Scale for Infant and Toddler Development, Third edition (BSID-III) at two years of age. These findings show the potential of diffusion MRI based connectomics and graph theory based network characteristics for estimating differences in the
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.
Percolation and epidemics in a two-dimensional small world
NASA Astrophysics Data System (ADS)
Newman, M. E.; Jensen, I.; Ziff, R. M.
2002-02-01
Percolation on two-dimensional small-world networks has been proposed as a model for the spread of plant diseases. In this paper we give an analytic solution of this model using a combination of generating function methods and high-order series expansion. Our solution gives accurate predictions for quantities such as the position of the percolation threshold and the typical size of disease outbreaks as a function of the density of ``shortcuts'' in the small-world network. Our results agree with scaling hypotheses and numerical simulations for the same model.
Small worlds in space: Synchronization, spatial and relational modularity
NASA Astrophysics Data System (ADS)
Brede, M.
2010-06-01
In this letter we investigate networks that have been optimized to realize a trade-off between enhanced synchronization and cost of wire to connect the nodes in space. Analyzing the evolved arrangement of nodes in space and their corresponding network topology, a class of small-world networks characterized by spatial and network modularity is found. More precisely, for low cost of wire optimal configurations are characterized by a division of nodes into two spatial groups with maximum distance from each other, whereas network modularity is low. For high cost of wire, the nodes organize into several distinct groups in space that correspond to network modules connected on a ring. In between, spatially and relationally modular small-world networks are found.
Nikolaisen, Julie; Nilsson, Linn I. H.; Pettersen, Ina K. N.; Willems, Peter H. G. M.; Lorens, James B.; Koopman, Werner J. H.; Tronstad, Karl J.
2014-01-01
Mitochondrial morphology and function are coupled in healthy cells, during pathological conditions and (adaptation to) endogenous and exogenous stress. In this sense mitochondrial shape can range from small globular compartments to complex filamentous networks, even within the same cell. Understanding how mitochondrial morphological changes (i.e. “mitochondrial dynamics”) are linked to cellular (patho) physiology is currently the subject of intense study and requires detailed quantitative information. During the last decade, various computational approaches have been developed for automated 2-dimensional (2D) analysis of mitochondrial morphology and number in microscopy images. Although these strategies are well suited for analysis of adhering cells with a flat morphology they are not applicable for thicker cells, which require a three-dimensional (3D) image acquisition and analysis procedure. Here we developed and validated an automated image analysis algorithm allowing simultaneous 3D quantification of mitochondrial morphology and network properties in human endothelial cells (HUVECs). Cells expressing a mitochondria-targeted green fluorescence protein (mitoGFP) were visualized by 3D confocal microscopy and mitochondrial morphology was quantified using both the established 2D method and the new 3D strategy. We demonstrate that both analyses can be used to characterize and discriminate between various mitochondrial morphologies and network properties. However, the results from 2D and 3D analysis were not equivalent when filamentous mitochondria in normal HUVECs were compared with circular/spherical mitochondria in metabolically stressed HUVECs treated with rotenone (ROT). 2D quantification suggested that metabolic stress induced mitochondrial fragmentation and loss of biomass. In contrast, 3D analysis revealed that the mitochondrial network structure was dissolved without affecting the amount and size of the organelles. Thus, our results demonstrate that 3D
C60-pentacene network formation by 2-D co-crystallization.
Jin, Wei; Dougherty, Daniel B; Cullen, William G; Robey, Steven; Reutt-Robey, Janice E
2009-09-01
We report experiments highlighting the mechanistic role of mobile pentacene precursors in the formation of a network C(60)-pentacene co-crystalline structure on Ag(111). This co-crystalline arrangement was first observed by low temperature scanning tunneling microscopy (STM) by Zhang et al. (Zhang, H. L.; Chen, W.; Huang, H.; Chen, L.; Wee, A. T. S. J. Am. Chem. Soc. 2008, 130, 2720-2721). We now show that this structure forms readily at room temperature from a two-dimensional (2-D) mixture. Pentacene, evaporated onto Ag(111) to coverages of 0.4-1.0 ML, produces a two-dimensional (2-D) gas. Subsequently deposited C(60) molecules combine with the pentacene 2-D gas to generate a network structure, consisting of chains of close-packed C(60) molecules, spaced by individual C(60) linkers and 1 nm x 2.5 nm pores containing individual pentacene molecules. Spontaneous formation of this stoichiometric (C(60))(4)-pentacene network from a range of excess pentacene surface coverage (0.4 to 1.0 ML) indicates a self-limiting assembly process. We refine the structure model for this phase and discuss the generality of this co-crystallization mechanism.
Kim, Byoung Soo; Lee, Kangsuk; Kang, Seulki; Lee, Soyeon; Pyo, Jun Beom; Choi, In Suk; Char, Kookheon; Park, Jong Hyuk; Lee, Sang-Soo; Lee, Jonghwi; Son, Jeong Gon
2017-09-14
Stretchable energy storage systems are essential for the realization of implantable and epidermal electronics. However, high-performance stretchable supercapacitors have received less attention because currently available processing techniques and material structures are too limited to overcome the trade-off relationship among electrical conductivity, ion-accessible surface area, and stretchability of electrodes. Herein, we introduce novel 2D reentrant cellular structures of porous graphene/CNT networks for omnidirectionally stretchable supercapacitor electrodes. Reentrant structures, with inwardly protruded frameworks in porous networks, were fabricated by the radial compression of vertically aligned honeycomb-like rGO/CNT networks, which were prepared by a directional crystallization method. Unlike typical porous graphene structures, the reentrant structure provided structure-assisted stretchability, such as accordion and origami structures, to otherwise unstretchable materials. The 2D reentrant structures of graphene/CNT networks maintained excellent electrical conductivities under biaxial stretching conditions and showed a slightly negative or near-zero Poisson's ratio over a wide strain range because of their structural uniqueness. For practical applications, we fabricated all-solid-state supercapacitors based on 2D auxetic structures. A radial compression process up to 1/10 th densified the electrode, significantly increasing the areal and volumetric capacitances of the electrodes. Additionally, vertically aligned graphene/CNT networks provided a plentiful surface area and induced sufficient ion transport pathways for the electrodes. Therefore, they exhibited high gravimetric and areal capacitance values of 152.4 F g -1 and 2.9 F cm -2 , respectively, and had an excellent retention ratio of 88% under a biaxial strain of 100%. Auxetic cellular and vertically aligned structures provide a new strategy for the preparation of robust platforms for stretchable
Small-world behaviour in a system of mobile elements
NASA Astrophysics Data System (ADS)
Manrubia, S. C.; Delgado, J.; Luque, B.
2001-03-01
We analyze the propagation of activity in a system of mobile automata. A number ρLd of elements move as random walkers on a lattice of dimension d, while with a small probability p they can jump to any empty site in the system. We show that this system behaves as a Dynamic Small World (DSW) and present analytic and numerical results for several quantities. Our analysis shows that the persistence time T* (equivalent to the persistence size L* of small-world networks) scales as T* ~ (ρp)-τ, with τ = 1/(d + 1).
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.
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.
Exploring the story, science, and adventure of small worlds
NASA Astrophysics Data System (ADS)
Swann, J. L.; Elkins-Tanton, L. T.; Anbar, A. D.; Klug Boonstra, S.; Tamer, A. J.; Mead, C.; Hunsley, D.
2017-12-01
Small worlds are a strategic focus at NASA, reflected by missions such as Osiris Rex and Psyche among others. The Infiniscope project, with funding from NASA SMD, is building on this scientific and public interest to teach formal and informal learners about asteroids and other small worlds. The digital learning experience, "Where are the small worlds?", and future Infiniscope experiences, incorporate a design theory that we describe as "education through exploration" (ETX) which is provided through an adaptive e-learning platform. This design ensures that learners actively engage in exploration and discovery, while receiving targeted feedback to push through challenges. To ensure that this and future experiences reach and meet the needs of as many educators as possible, Infiniscope includes a digital teaching network to host the experiences and support the reuse and adaptation of digital resources in new lessons. "Where are the small worlds?" puts learners in an interactive simulation of the solar system and provides a mission structure in which they hunt for "astrocaches" on near earth objects, main belt asteroids, and Kuiper-belt objects. These activities allow the learner to discover the locations of the small worlds in the solar system and develop an intuitive understanding for the relative motion of objects at various distances from the Sun. The experience is NGSS-aligned and accompanied by a lesson plan for integration into the classroom. In testing with more than 500 middle-school students, 83% of participants said they wanted to do more experiences like "Where are the small worlds?" They also found the experience both "fun" and "interesting" while being moderately difficult. "Where are the small worlds?" is one of many visualizations and lessons that is available within the Infiniscope teaching network. The network already has hundreds of members and is expected to grow in both numbers and engagement over time. Currently, educators can search and use pre
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.
Convolution neural networks for real-time needle detection and localization in 2D ultrasound.
Mwikirize, Cosmas; Nosher, John L; Hacihaliloglu, Ilker
2018-05-01
We propose a framework for automatic and accurate detection of steeply inserted needles in 2D ultrasound data using convolution neural networks. We demonstrate its application in needle trajectory estimation and tip localization. Our approach consists of a unified network, comprising a fully convolutional network (FCN) and a fast region-based convolutional neural network (R-CNN). The FCN proposes candidate regions, which are then fed to a fast R-CNN for finer needle detection. We leverage a transfer learning paradigm, where the network weights are initialized by training with non-medical images, and fine-tuned with ex vivo ultrasound scans collected during insertion of a 17G epidural needle into freshly excised porcine and bovine tissue at depth settings up to 9 cm and [Formula: see text]-[Formula: see text] insertion angles. Needle detection results are used to accurately estimate needle trajectory from intensity invariant needle features and perform needle tip localization from an intensity search along the needle trajectory. Our needle detection model was trained and validated on 2500 ex vivo ultrasound scans. The detection system has a frame rate of 25 fps on a GPU and achieves 99.6% precision, 99.78% recall rate and an [Formula: see text] score of 0.99. Validation for needle localization was performed on 400 scans collected using a different imaging platform, over a bovine/porcine lumbosacral spine phantom. Shaft localization error of [Formula: see text], tip localization error of [Formula: see text] mm, and a total processing time of 0.58 s were achieved. The proposed method is fully automatic and provides robust needle localization results in challenging scanning conditions. The accurate and robust results coupled with real-time detection and sub-second total processing make the proposed method promising in applications for needle detection and localization during challenging minimally invasive ultrasound-guided procedures.
Dispersion in 2D network: Effects of mixing rule at nodes and molecular diffusion
NASA Astrophysics Data System (ADS)
Wang, Y.; Tao, Q.; Li, M.
2017-12-01
We simulate solute transport in 2D network backbone characterized by pore connectivity and pore heterogeneity by particle-tracking method. In order to ensure the dispersion coefficient reaching an asymptotic value, we upscale dispersion from pore-scale to meter-scale by using periodic boundary condition. As comparison, two different flow mechanisms without or with dispersion in a capillary tube, namely mean flow and Taylor-Aris dispersion, are introduced to investigate the evolution of solute spreading. The longitudinal dispersion coefficient DLM without dispersion in a pipe can roughly be regarded as a parameter to quantify the impact of microscopic structure of porous media on solute spreading, which is smaller than that value DL of Taylor-Aris dispersion. The difference between them decreases with the enhancement of the disorder. The mixing rule at nodes has a minor effect on longitudinal spreading, but has a significant effect on transverse spreading, especially for the nearly homogeneous media. An increase of the disorder in network achieved by increasing pore size heterogeneity or/and decreasing pore connectivity diminishes the difference between two mixing rules. Besides, the evolution of longitudinal dispersion coefficient over diffusion presents three different patterns at different velocities for homogenous media, such as monotonically increasing trend, decreasing first and then increasing trend and monotonically decreasing trend. But all are replaced by power law for a high disorder. The simulation results also accurately predict the experimental dependence of the longitudinal coefficient on Peclet number Pe.
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.
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.
Dispersive dielectric and conductive effects in 2D resistor-capacitor networks.
Hamou, R F; Macdonald, J R; Tuncer, E
2009-01-14
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 × 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 Ω 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
Traumatic brain injury impairs small-world topology
Pandit, Anand S.; Expert, Paul; Lambiotte, Renaud; Bonnelle, Valerie; Leech, Robert; Turkheimer, Federico E.
2013-01-01
Objective: We test the hypothesis that brain networks associated with cognitive function shift away from a “small-world” organization following traumatic brain injury (TBI). Methods: We investigated 20 TBI patients and 21 age-matched controls. Resting-state functional MRI was used to study functional connectivity. Graph theoretical analysis was then applied to partial correlation matrices derived from these data. The presence of white matter damage was quantified using diffusion tensor imaging. Results: Patients showed characteristic cognitive impairments as well as evidence of damage to white matter tracts. Compared to controls, the graph analysis showed reduced overall connectivity, longer average path lengths, and reduced network efficiency. A particular impact of TBI is seen on a major network hub, the posterior cingulate cortex. Taken together, these results confirm that a network critical to cognitive function shows a shift away from small-world characteristics. Conclusions: We provide evidence that key brain networks involved in supporting cognitive function become less small-world in their organization after TBI. This is likely to be the result of diffuse white matter damage, and may be an important factor in producing cognitive impairment after TBI. PMID:23596068
Ambient-Stable and Durable Conductive Ag-Nanowire-Network 2-D Films Decorated with a Ti Layer.
Kim, Yoon-Mi; Hwang, Bu-Yeon; Lee, Ki-Wook; Kim, Jin-Yeol
2018-05-11
Highly stable and durable conductive silver nanowire (Ag NW) network electrode films were prepared through decoration with a 5-nm-thick Ti layer. The Ag NW network 2-D films showed sheet resistance values as low as 32 ohm/sq at 88% transparency when decorated with Ti. These 2-D films exhibited a 30% increase in electrical conductivity while maintaining good stability of the films through enhanced resistance to moisture and oxygen penetration as a result of the protective effect of the Ti layer.
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.
Wealth redistribution in our small world
NASA Astrophysics Data System (ADS)
Iglesias, J. R.; Gonçalves, S.; Pianegonda, S.; Vega, J. L.; Abramson, G.
2003-09-01
We present a simplified model for the exploitation of resources by interacting agents, in an economy with small-world properties. It is shown that Gaussian distributions of wealth, with some cutoff at a poverty line are present for all values of the parameters, while the frequency of maxima and minima strongly depends on the connectivity and the disorder of the lattice. Finally, we compare a system where the commercial links are frozen with an economy where agents can choose their commercial partners at each time step.
Possible Origin of Efficient Navigation in Small Worlds
NASA Astrophysics Data System (ADS)
Hu, Yanqing; Wang, Yougui; Li, Daqing; Havlin, Shlomo; di, Zengru
2011-03-01
The small-world phenomenon is one of the most important properties found in social networks. It includes both short path lengths and efficient navigation between two individuals. It is found by Kleinberg that navigation is efficient only if the probability density distribution of an individual to have a friend at distance r scales as P(r)˜r-1. Although this spatial scaling is found in many empirical studies, the origin of how this scaling emerges is still missing. In this Letter, we propose the origin of this scaling law using the concept of entropy from statistical physics and show that this scaling is the result of optimization of collecting information in social networks.
On the Relation between the Small World Structure and Scientific Activities
Ebadi, Ashkan; Schiffauerova, Andrea
2015-01-01
The modern science has become more complex and interdisciplinary in its nature which might encourage researchers to be more collaborative and get engaged in larger collaboration networks. Various aspects of collaboration networks have been examined so far to detect the most determinant factors in knowledge creation and scientific production. One of the network structures that recently attracted much theoretical attention is called small world. It has been suggested that small world can improve the information transmission among the network actors. In this paper, using the data on 12 periods of journal publications of Canadian researchers in natural sciences and engineering, the co-authorship networks of the researchers are created. Through measuring small world indicators, the small worldiness of the mentioned network and its relation with researchers’ productivity, quality of their publications, and scientific team size are assessed. Our results show that the examined co-authorship network strictly exhibits the small world properties. In addition, it is suggested that in a small world network researchers expand their team size through getting connected to other experts of the field. This team size expansion may result in higher productivity of the whole team as a result of getting access to new resources, benefitting from the internal referring, and exchanging ideas among the team members. Moreover, although small world network is positively correlated with the quality of the articles in terms of both citation count and journal impact factor, it is negatively related with the average productivity of researchers in terms of the number of their publications. PMID:25780922
Optimal Micropatterns in 2D Transport Networks and Their Relation to Image Inpainting
NASA Astrophysics Data System (ADS)
Brancolini, Alessio; Rossmanith, Carolin; Wirth, Benedikt
2018-04-01
We consider two different variational models of transport networks: the so-called branched transport problem and the urban planning problem. Based on a novel relation to Mumford-Shah image inpainting and techniques developed in that field, we show for a two-dimensional situation that both highly non-convex network optimization tasks can be transformed into a convex variational problem, which may be very useful from analytical and numerical perspectives. As applications of the convex formulation, we use it to perform numerical simulations (to our knowledge this is the first numerical treatment of urban planning), and we prove a lower bound for the network cost that matches a known upper bound (in terms of how the cost scales in the model parameters) which helps better understand optimal networks and their minimal costs.
Trellis Tone Modulation Multiple-Access for Peer Discovery in D2D Networks
Lim, Chiwoo; Kim, Sang-Hyo
2018-01-01
In this paper, a new non-orthogonal multiple-access scheme, trellis tone modulation multiple-access (TTMMA), is proposed for peer discovery of distributed device-to-device (D2D) communication. The range and capacity of discovery are important performance metrics in peer discovery. The proposed trellis tone modulation uses single-tone transmission and achieves a long discovery range due to its low Peak-to-Average Power Ratio (PAPR). The TTMMA also exploits non-orthogonal resource assignment to increase the discovery capacity. For the multi-user detection of superposed multiple-access signals, a message-passing algorithm with supplementary schemes are proposed. With TTMMA and its message-passing demodulation, approximately 1.5 times the number of devices are discovered compared to the conventional frequency division multiple-access (FDMA)-based discovery. PMID:29673167
A Novel Crosstalk Suppression Method of the 2-D Networked Resistive Sensor Array
Wu, Jianfeng; Wang, Lei; Li, Jianqing; Song, Aiguo
2014-01-01
The 2-D resistive sensor array in the row–column fashion suffered from the crosstalk problem for parasitic parallel paths. Firstly, we proposed an Improved Isolated Drive Feedback Circuit with Compensation (IIDFCC) based on the voltage feedback method to suppress the crosstalk. In this method, a compensated resistor was specially used to reduce the crosstalk caused by the column multiplexer resistors and the adjacent row elements. Then, a mathematical equivalent resistance expression of the element being tested (EBT) of this circuit was analytically derived and verified by the circuit simulations. The simulation results show that the measurement method can greatly reduce the influence on the EBT caused by parasitic parallel paths for the multiplexers' channel resistor and the adjacent elements. PMID:25046011
Trellis Tone Modulation Multiple-Access for Peer Discovery in D2D Networks.
Lim, Chiwoo; Jang, Min; Kim, Sang-Hyo
2018-04-17
In this paper, a new non-orthogonal multiple-access scheme, trellis tone modulation multiple-access (TTMMA), is proposed for peer discovery of distributed device-to-device (D2D) communication. The range and capacity of discovery are important performance metrics in peer discovery. The proposed trellis tone modulation uses single-tone transmission and achieves a long discovery range due to its low Peak-to-Average Power Ratio (PAPR). The TTMMA also exploits non-orthogonal resource assignment to increase the discovery capacity. For the multi-user detection of superposed multiple-access signals, a message-passing algorithm with supplementary schemes are proposed. With TTMMA and its message-passing demodulation, approximately 1.5 times the number of devices are discovered compared to the conventional frequency division multiple-access (FDMA)-based discovery.
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.
2D wireless sensor network deployment based on Centroidal Voronoi Tessellation
NASA Astrophysics Data System (ADS)
Iliodromitis, Athanasios; Pantazis, George; Vescoukis, Vasileios
2017-06-01
In recent years, Wireless Sensor Networks (WSNs) have rapidly evolved and now comprise a powerful tool in monitoring and observation of the natural environment, among other fields. The use of WSNs is critical in early warning systems, which are of high importance today. In fact, WSNs are adopted more and more in various applications, e.g. for fire or deformation detection. The optimum deployment of sensors is a multi-dimensional problem, which has two main components; network and positioning approach. Although lots of work has dealt with the issue, most of it emphasizes on mere network approach (communication, energy consumption) and not on the topography (positioning) of the sensors in achieving ideal geometry. In some cases, it is hard or even impossible to achieve perfect geometry in nodes' deployment. The ideal and desirable scenario of nodes arranged in square or hexagonal grid would raise extremely the cost of the network, especially in unfriendly or hostile environments. In such environments the positions of the sensors have to be chosen among a list of possible points, which in most cases are randomly distributed. This constraint has to be taken under consideration during the WSN planning. Full geographical coverage is in some applications of the same, if not of greater, importance than the network coverage. Cost is a crucial factor at network planning and given that resources are often limited, what matters, is to cover the whole area with the minimum number of sensors. This paper suggests a deployment method for nodes, in large scale and high density WSNs, based on Centroidal Voronoi Tessellation (CVT). It approximates the solution through the geometry of the random points and proposes a deployment plan, for the given characteristics of the study area, in order to achieve a deployment as near as possible to the ideal one.
Fast Rotational Diffusion of Water Molecules in a 2D Hydrogen Bond Network at Cryogenic Temperatures
Prisk, Timothy; Hoffmann, Christina; Kolesnikov, Alexander I.
Individual water molecules or small clusters of water molecules contained within microporous minerals present an extreme case of confinement where the local structure of hydrogen bond networks are dramatically altered from bulk water. In the zinc silicate hemimorphite, the water molecules form a two-dimensional hydrogen bond network with hydroxyl groups in the crystal framework. Here in this paper, we present a combined experimental and theoretical study of the structure and dynamics of water molecules within this network. The water molecules undergo a continuous phase transition in their orientational configuration analogous to a two-dimensional Ising model. The incoherent dynamic structure factormore » reveals two thermally activated relaxation processes, one on a subpicosecond timescale and another on a 10–100 ps timescale, between 70 and 130 K. The slow process is an in-plane reorientation of the water molecule involving the breaking of hydrogen bonds with a framework that, despite the low temperatures involved, is analogous to rotational diffusion of water molecules in the bulk liquid. The fast process is a localized motion of the water molecule with no apparent analogs among known bulk or confined phases of water.« less
Fast Rotational Diffusion of Water Molecules in a 2D Hydrogen Bond Network at Cryogenic Temperatures
NASA Astrophysics Data System (ADS)
Prisk, T. R.; Hoffmann, C.; Kolesnikov, A. I.; Mamontov, E.; Podlesnyak, A. A.; Wang, X.; Kent, P. R. C.; Anovitz, L. M.
2018-05-01
Individual water molecules or small clusters of water molecules contained within microporous minerals present an extreme case of confinement where the local structure of hydrogen bond networks are dramatically altered from bulk water. In the zinc silicate hemimorphite, the water molecules form a two-dimensional hydrogen bond network with hydroxyl groups in the crystal framework. Here, we present a combined experimental and theoretical study of the structure and dynamics of water molecules within this network. The water molecules undergo a continuous phase transition in their orientational configuration analogous to a two-dimensional Ising model. The incoherent dynamic structure factor reveals two thermally activated relaxation processes, one on a subpicosecond timescale and another on a 10-100 ps timescale, between 70 and 130 K. The slow process is an in-plane reorientation of the water molecule involving the breaking of hydrogen bonds with a framework that, despite the low temperatures involved, is analogous to rotational diffusion of water molecules in the bulk liquid. The fast process is a localized motion of the water molecule with no apparent analogs among known bulk or confined phases of water.
Fast Rotational Diffusion of Water Molecules in a 2D Hydrogen Bond Network at Cryogenic Temperatures
Prisk, Timothy; Hoffmann, Christina; Kolesnikov, Alexander I.; ...
2018-05-09
Individual water molecules or small clusters of water molecules contained within microporous minerals present an extreme case of confinement where the local structure of hydrogen bond networks are dramatically altered from bulk water. In the zinc silicate hemimorphite, the water molecules form a two-dimensional hydrogen bond network with hydroxyl groups in the crystal framework. Here in this paper, we present a combined experimental and theoretical study of the structure and dynamics of water molecules within this network. The water molecules undergo a continuous phase transition in their orientational configuration analogous to a two-dimensional Ising model. The incoherent dynamic structure factormore » reveals two thermally activated relaxation processes, one on a subpicosecond timescale and another on a 10–100 ps timescale, between 70 and 130 K. The slow process is an in-plane reorientation of the water molecule involving the breaking of hydrogen bonds with a framework that, despite the low temperatures involved, is analogous to rotational diffusion of water molecules in the bulk liquid. The fast process is a localized motion of the water molecule with no apparent analogs among known bulk or confined phases of water.« less
Architecture of marine food webs: To be or not be a 'small-world'.
Marina, Tomás Ignacio; Saravia, Leonardo A; Cordone, Georgina; Salinas, Vanesa; Doyle, Santiago R; Momo, Fernando R
2018-01-01
The search for general properties in network structure has been a central issue for food web studies in recent years. One such property is the small-world topology that combines a high clustering and a small distance between nodes of the network. This property may increase food web resilience but make them more sensitive to the extinction of connected species. Food web theory has been developed principally from freshwater and terrestrial ecosystems, largely omitting marine habitats. If theory needs to be modified to accommodate observations from marine ecosystems, based on major differences in several topological characteristics is still on debate. Here we investigated if the small-world topology is a common structural pattern in marine food webs. We developed a novel, simple and statistically rigorous method to examine the largest set of complex marine food webs to date. More than half of the analyzed marine networks exhibited a similar or lower characteristic path length than the random expectation, whereas 39% of the webs presented a significantly higher clustering than its random counterpart. Our method proved that 5 out of 28 networks fulfilled both features of the small-world topology: short path length and high clustering. This work represents the first rigorous analysis of the small-world topology and its associated features in high-quality marine networks. We conclude that such topology is a structural pattern that is not maximized in marine food webs; thus it is probably not an effective model to study robustness, stability and feasibility of marine ecosystems.
Coevolutionary dynamics of opinion propagation and social balance: The key role of small-worldness
NASA Astrophysics Data System (ADS)
Chen, Yan; Chen, Lixue; Sun, Xian; Zhang, Kai; Zhang, Jie; Li, Ping
2014-03-01
The propagation of various opinions in social networks, which influences human inter-relationships and even social structure, and hence is a most important part of social life. We have incorporated social balance into opinion propagation in social networks are influenced by social balance. The edges in networks can represent both friendly or hostile relations, and change with the opinions of individual nodes. We introduce a model to characterize the coevolutionary dynamics of these two dynamical processes on Watts-Strogatz (WS) small-world network. We employ two distinct evolution rules (i) opinion renewal; and (ii) relation adjustment. By changing the rewiring probability, and thus the small-worldness of the WS network, we found that the time for the system to reach balanced states depends critically on both the average path length and clustering coefficient of the network, which is different than other networked process like epidemic spreading. In particular, the system equilibrates most quickly when the underlying network demonstrates strong small-worldness, i.e., small average path lengths and large clustering coefficient. We also find that opinion clusters emerge in the process of the network approaching the global equilibrium, and a measure of global contrariety is proposed to quantify the balanced state of a social network.
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.
Experimental implementation of acoustic impedance control by a 2D network of distributed smart cells
NASA Astrophysics Data System (ADS)
David, P.; Collet, M.; Cote, J.-M.
2010-03-01
New miniaturization and integration capabilities available from emerging microelectromechanical system (MEMS) technology will allow silicon-based artificial skins involving thousands of elementary actuators to be developed in the near future. Smart structures combining large arrays of elementary motion pixels are thus being studied so that fundamental properties could be dynamically adjusted. This paper investigates the acoustical capabilities of a network of distributed transducers connected with a suitable controlling strategy. The research aims at designing an integrated active interface for sound attenuation by using suitable changes of acoustical impedance. The control strategy is based on partial differential equations (PDE) and the multiscaled physics of electromechanical elements. Specific techniques based on PDE control theory have provided a simple boundary control equation able to annihilate the reflections of acoustic waves. To experimentally implement the method, the control strategy is discretized as a first order time-space operator. The obtained quasi-collocated architecture, composed of a large number of sensors and actuators, provides high robustness and stability. The experimental results demonstrate how a well controlled active skin can substantially modify sound reflectivity of the acoustical interface and reduce the propagation of acoustic waves.
2D PWV monitoring of a wide and orographically complex area with a low dense GNSS network
NASA Astrophysics Data System (ADS)
Ferrando, Ilaria; Federici, Bianca; Sguerso, Domenico
2018-04-01
This study presents an innovative procedure to monitor the precipitable water vapor (PWV) content of a wide and orographically complex area with low-density networks. The procedure, termed G4M (global navigation satellite system, GNSS, for Meteorology), has been developed in a geographic information system (GIS) environment using the free and open source GRASS GIS software (https://grass.osgeo.org). The G4M input data are zenith total delay estimates obtained from GNSS permanent stations network adjustment and pressure ( P) and temperature ( T) observations using existing infrastructure networks with different geographic distributions in the study area. In spite of the wide sensor distribution, the procedure produces 2D maps with high spatiotemporal resolution (up to 250 m and 6 min) based on a simplified mathematical model including data interpolation, which was conceived by the authors to describe the atmosphere's physics. In addition to PWV maps, the procedure provides ΔPWV and heterogeneity index maps: the former represents PWV variations with respect to a "calm" moment, which are useful for monitoring the PWV evolution; and the latter are promising indicators to localize severe meteorological events in time and space. This innovative procedure is compared with meteorological simulations in this paper; in addition, an application to a severe event that occurred in Genoa (Italy) is presented.[Figure not available: see fulltext.
NASA Astrophysics Data System (ADS)
Ariga, Katsuhiko; Watanabe, Shun; Mori, Taizo; Takeya, Jun
2018-04-01
Nanoarchitectonics is a new paradigm to combine and unify nanotechnology with other sciences and technologies, such as supramolecular chemistry, self-assembly, self-organization, materials technology for manipulation of the size of material objects, and even biotechnology for hybridization with bio-components. The nanoarchitectonic concept leads to the synergistic combination of various methodologies in materials production, including atomic/molecular-level control, self-organization, and field-controlled organization. The focus of this review is on soft 2D nanoarchitectonics. Scientific views on soft 2D nanomaterials are not fully established compared with those on rigid 2D materials. Here, we collect recent examples of 2D nanoarchitectonic constructions of functional materials and systems with soft components. These examples are selected according to the following three categories on the basis of 2D spatial density and motional freedom: (i) well-packed and oriented organic 2D materials with rational design of component molecules and device applications, (ii) well-defined assemblies with 2D porous structures as 2D network materials, and (iii) 2D control of molecular machines and receptors on the basis of certain motional freedom confined in two dimensions.
Coupled 1-D sewer and street networks and 2-D flooding model to rapidly evaluate surface inundation
NASA Astrophysics Data System (ADS)
Kao, Hong-Ming; Hsu, Hao-Ming
2017-04-01
Flash floods have occurred frequently in the urban areas around the world and cause the infrastructure and people living to expose continuously in the high risk level of pluvial flooding. According to historical surveys, the major reasons of severe surface inundations in the urban areas can be attributed to heavy rainfall in the short time and/or drainage system failure. In order to obtain real-time flood forecasting with high accuracy and less uncertainty, an appropriate system for predicting floods is necessary. For the reason, this study coupled 1-D sewer and street networks and 2-D flooding model as an operational modelling system for rapidly evaluating surface inundation. The proposed system is constructed by three significant components: (1) all the rainfall-runoff of a sub-catchment collected via gullies is simulated by the RUNOFF module of the Storm Water Management Model (SWMM); (2) and directly drained to the 1-D sewer and street networks via manholes as inflow discharges to conduct flow routing by using the EXTRAN module of SWMM; (3) after the 1-D simulations, the surcharges from manholes are considered as point sources in 2-D overland flow simulations that are executed by the WASH123D model. It can thus be used for urban flood modelling that reflects the rainfall-runoff processes, and the dynamic flow interactions between the storm sewer system and the ground surface in urban areas. In the present study, we adopted the Huwei Science and Technology Park, located in the south-western part of Taiwan, as the demonstration area because of its high industrial values. The region has an area about 1 km2 with approximately 1 km in both length and width. It is as isolated urban drainage area in which there is a complete sewer system that collects the runoff and drains to the detention pond. Based on the simulated results, the proposed modelling system was found that the simulated floods fit to the survey records because the physical rainfall-runoff phenomena in
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
NASA Astrophysics Data System (ADS)
Liu, Richeng; Li, Bo; Jiang, Yujing; Yu, Liyuan
2018-01-01
Hydro-mechanical properties of rock fractures are core issues for many geoscience and geo-engineering practices. Previous experimental and numerical studies have revealed that shear processes could greatly enhance the permeability of single rock fractures, yet the shear effects on hydraulic properties of fractured rock masses have received little attention. In most previous fracture network models, single fractures are typically presumed to be formed by parallel plates and flow is presumed to obey the cubic law. However, related studies have suggested that the parallel plate model cannot realistically represent the surface characters of natural rock fractures, and the relationship between flow rate and pressure drop will no longer be linear at sufficiently large Reynolds numbers. In the present study, a numerical approach was established to assess the effects of shear on the hydraulic properties of 2-D discrete fracture networks (DFNs) in both linear and nonlinear regimes. DFNs considering fracture surface roughness and variation of aperture in space were generated using an originally developed code DFNGEN. Numerical simulations by solving Navier-Stokes equations were performed to simulate the fluid flow through these DFNs. A fracture that cuts through each model was sheared and by varying the shear and normal displacements, effects of shear on equivalent permeability and nonlinear flow characteristics of DFNs were estimated. The results show that the critical condition of quantifying the transition from a linear flow regime to a nonlinear flow regime is: 10-4 〈 J < 10-3, where J is the hydraulic gradient. When the fluid flow is in a linear regime (i.e., J < 10-4), the relative deviation of equivalent permeability induced by shear, δ2, is linearly correlated with J with small variations, while for fluid flow in the nonlinear regime (J 〉 10-3), δ2 is nonlinearly correlated with J. A shear process would reduce the equivalent permeability significantly in the
Unusual percolation in simple small-world networks.
Cohen, Reuven; Dawid, Daryush Jonathan; Kardar, Mehran; Bar-Yam, Yaneer
2009-06-01
We present an exact solution of percolation in a generalized class of Watts-Strogatz graphs defined on a one-dimensional underlying lattice. We find a nonclassical critical point in the limit of the number of long-range bonds in the system going to zero, with a discontinuity in the percolation probability and a divergence in the mean finite-cluster size. We show that the critical behavior falls into one of three regimes depending on the proportion of occupied long-range to unoccupied nearest-neighbor bonds, with each regime being characterized by different critical exponents. The three regimes can be united by a single scaling function around the critical point. These results can be used to identify the number of long-range links necessary to secure connectivity in a communication or transportation chain. As an example, we can resolve the communication problem in a game of "telephone."
Pichierri, Fabio, E-mail: fabio@che.tohoku.ac.jp
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{sup +}) in the contaminated environment.
Frary, R.; Louie, J.; Pullammanappallil, S.
Roxanna Frary, John N. Louie, Sathish Pullammanappallil, Amy Eisses, 2011, Preliminary 3d depth migration of a network of 2d seismic lines for fault imaging at a Pyramid Lake, Nevada geothermal prospect: presented at American Geophysical Union Fall Meeting, San Francisco, Dec. 5-9, abstract T13G-07.
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.
Bazeley, Peter S; Prithivi, Sridevi; Struble, Craig A; Povinelli, Richard J; Sem, Daniel S
2006-01-01
Cytochrome P450 2D6 (CYP2D6) is used to develop an approach for predicting affinity and relevant binding conformation(s) for highly flexible binding sites. The approach combines the use of docking scores and compound properties as attributes in building a neural network (NN) model. It begins by identifying segments of CYP2D6 that are important for binding specificity, based on structural variability among diverse CYP enzymes. A family of distinct, low-energy conformations of CYP2D6 are generated using simulated annealing (SA) and a collection of 82 compounds with known CYP2D6 affinities are docked. Interestingly, docking poses are observed on the backside of the heme as well as in the known active site. Docking scores for the active site binders, along with compound-specific attributes, are used to train a neural network model to properly bin compounds as strong binders, moderate binders, or nonbinders. Attribute selection is used to preselect the most important scores and compound-specific attributes for the model. A prediction accuracy of 85+/-6% is achieved. Dominant attributes include docking scores for three of the 20 conformations in the ensemble as well as the compound's formal charge, number of aromatic rings, and AlogP. Although compound properties were highly predictive attributes (12% improvement over baseline) in the NN-based prediction of CYP2D6 binders, their combined use with docking score attributes is synergistic (net increase of 23% above baseline). Beyond prediction of affinity, attribute selection provides a way to identify the most relevant protein conformation(s), in terms of binding competence. In the case of CYP2D6, three out of the ensemble of 20 SA-generated structures are found to be the most predictive for binding.
NASA Astrophysics Data System (ADS)
Mei, Hong-Xin; Zhang, Ting; Huang, Hua-Qi; Huang, Rong-Bin; Zheng, Lan-Sun
2016-03-01
Three mix-ligand Ag(I) coordination compounds, namely, {[Ag10(tpyz) 5(L1) 5(H2 O)2].(H2 O)4}n (1, tpyz = 2,3,4,5-tetramethylpyrazine, H2 L1 = phthalic acid), [Ag4(tpyz) 2(L2) 2(H2 O)].(H2 O)5}n (2, H2 L2 = isophthalic acid) {[Ag2(tpyz) 2(L3) (H2 O)4].(H2 O)8}n (3, H2 L3 = terephthalic acid), have been synthesized and characterized by elemental analysis, IR, PXRD and X-ray single-crystal diffraction. 1 exhibits a 2D layer which can be simplified as a (4,4) net. 2 is a 3D network which can be simplified as a (3,3)-connected 2-nodal net with a point symbol of {102.12}{102}. 3 consists of linear [Ag(tpyz) (H2 O)2]n chain. Of particular interest, discrete hexamer water clusters were observed in 1 and 2, while a 2D L10(6) water layer exists in 3. The results suggest that the benzene dicarboxylates play pivotal roles in the formation of the different host architectures as well as different water aggregations. Moreover, thermogravimetric analysis (TGA) and emissive behaviors of these compounds were investigated.
Demirkıran, Gökhan; Kalaycı Demir, Güleser; Güzeliş, Cüneyt
2018-02-01
This study proposes a two-dimensional (2D) oscillator model of p53 network, which is derived via reducing the multidimensional two-phase dynamics model into a model of ataxia telangiectasia mutated (ATM) and Wip1 variables, and studies the impact of p53-regulators on cell fate decision. First, the authors identify a 6D core oscillator module, then reduce this module into a 2D oscillator model while preserving the qualitative behaviours. The introduced 2D model is shown to be an excitable relaxation oscillator. This oscillator provides a mechanism that leads diverse modes underpinning cell fate, each corresponding to a cell state. To investigate the effects of p53 inhibitors and the intrinsic time delay of Wip1 on the characteristics of oscillations, they introduce also a delay differential equation version of the 2D oscillator. They observe that the suppression of p53 inhibitors decreases the amplitudes of p53 oscillation, though the suppression increases the sustained level of p53. They identify Wip1 and P53DINP1 as possible targets for cancer therapies considering their impact on the oscillator, supported by biological findings. They model some mutations as critical changes of the phase space characteristics. Possible cancer therapeutic strategies are then proposed for preventing these mutations' effects using the phase space approach.
NASA Astrophysics Data System (ADS)
Ryu, Minjoo; Lee, Young-A.; Jung, Ok-Sang
2018-01-01
The self-assembly of CuX2 (X- = Cl-, Br-, NO3-, ClO4-, and BF4-) with a new diallylbis(pyridin-3-yl)silane ligand (L) gives rise to the similar 2D coordination networks with composition of Cu(II) and L of 1: 2 irrespective of anions and solvents. The 2D networks of [CuCl2L2]·2H2O, [CuBr2L2]·2H2O, and [Cu(H2O)2L2]·(NO3)2 are packed in a staggered mode while the similar networks of [Cu(BF4)2L2] and [Cu(ClO4)2L2] are arrayed in a eclipsed fashion. These crystals of all 2D networks have been employed as catalysts for 3,5-di-tert-butylcatechol (3,5-DBCat) oxidation, showing the catalytic effects in the order of [CuCl2L2]·2H2O > [CuBr2L2]·2H2O > [Cu(H2O)2L2]·(NO3)2 > [Cu(ClO4)2L2] > [Cu(BF4)2L2] in chloroform and exhibiting the catalytic effects of only [Cu(H2O)2L2]·(NO3)2 in acetone. Thus, the catalytic effect on catechol oxidation is strongly dependent on anions and media.
Predictive protocol of flocks with small-world connection pattern.
Zhang, Hai-Tao; Chen, Michael Z Q; Zhou, Tao
2009-01-01
By introducing a predictive mechanism with small-world connections, we propose a new motion protocol for self-driven flocks. The small-world connections are implemented by randomly adding long-range interactions from the leader to a few distant agents, namely, pseudoleaders. The leader can directly affect the pseudoleaders, thereby influencing all the other agents through them efficiently. Moreover, these pseudoleaders are able to predict the leader's motion several steps ahead and use this information in decision making towards coherent flocking with more stable formation. It is shown that drastic improvement can be achieved in terms of both the consensus performance and the communication cost. From the engineering point of view, the current protocol allows for a significant improvement in the cohesion and rigidity of the formation at a fairly low cost of adding a few long-range links embedded with predictive capabilities. Significantly, this work uncovers an important feature of flocks that predictive capability and long-range links can compensate for the insufficiency of each other. These conclusions are valid for both the attractive and repulsive swarm model and the Vicsek model.
2016-05-31
and included explosives such as TATP, HMTD, RDX, RDX, ammonium nitrate , potassium perchlorate, potassium nitrate , sugar, and TNT. The approach...Distribution Unlimited UU UU UU UU 31-05-2016 15-Apr-2014 14-Jan-2015 Final Report: Technical Topic 3.2.2. d Bayesian and Non- parametric Statistics...of Papers published in non peer-reviewed journals: Final Report: Technical Topic 3.2.2. d Bayesian and Non-parametric Statistics: Integration of Neural
Reduced small world brain connectivity in probands with a family history of epilepsy.
Bharath, R D; Chaitanya, G; Panda, R; Raghavendra, K; Sinha, S; Sahoo, A; Gohel, S; Biswal, B B; Satishchandra, P
2016-12-01
The role of inheritance in ascertaining susceptibility to epilepsy is well established, although the pathogenetic mechanisms are still not very clear. Interviewing for a positive family history is a popular epidemiological tool in the understanding of this susceptibility. Our aim was to visualize and localize network abnormalities that could be associated with a positive family history in a group of patients with hot water epilepsy (HWE) using resting-state functional magnetic resonance imaging (rsfMRI). Graph theory analysis of rsfMRI (clustering coefficient γ; path length λ; small worldness σ) in probands with a positive family history of epilepsy (FHE+, 25) were compared with probands without FHE (FHE-, 33). Whether a closer biological relationship was associated with a higher likelihood of network abnormalities was also ascertained. A positive family history of epilepsy had decreased γ, increased λ and decreased σ in bilateral temporofrontal regions compared to FHE- (false discovery rate corrected P ≤ 0.0062). These changes were more pronounced in probands having first degree relatives and siblings with epilepsy. Probands with multiple types of epilepsy in the family showed decreased σ in comparison to only HWE in the family. Graph theory analysis of the rsfMRI can be used to understand the neurobiology of diseases like genetic susceptibility in HWE. Reduced small worldness, proportional to the degree of relationship, is consistent with the current understanding that disease severity is higher in closer biological relations. © 2016 EAN.
NASA Astrophysics Data System (ADS)
Pezzotti, Simone; Serva, Alessandra; Gaigeot, Marie-Pierre
2018-05-01
Following our previous work where the existence of a special 2-Dimensional H-Bond (2D-HB)-Network was revealed at the air-water interface [S. Pezzotti et al., J. Phys. Chem. Lett. 8, 3133 (2017)], we provide here a full structural and dynamical characterization of this specific arrangement by means of both Density Functional Theory based and Force Field based molecular dynamics simulations. We show in particular that water at the interface with air reconstructs to maximize H-Bonds formed between interfacial molecules, which leads to the formation of an extended and non-interrupted 2-Dimensional H-Bond structure involving on average ˜90% of water molecules at the interface. We also show that the existence of such an extended structure, composed of H-Bonds all oriented parallel to the surface, constrains the reorientional dynamics of water that is hence slower at the interface than in the bulk. The structure and dynamics of the 2D-HB-Network provide new elements to possibly rationalize several specific properties of the air-water interface, such as water surface tension, anisotropic reorientation of interfacial water under an external field, and proton hopping.
Kwon, Yea-Hoon; Shin, Sae-Byuk; Kim, Shin-Dug
2018-04-30
The purpose of this study is to improve human emotional classification accuracy using a convolution neural networks (CNN) model and to suggest an overall method to classify emotion based on multimodal data. We improved classification performance by combining electroencephalogram (EEG) and galvanic skin response (GSR) signals. GSR signals are preprocessed using by the zero-crossing rate. Sufficient EEG feature extraction can be obtained through CNN. Therefore, we propose a suitable CNN model for feature extraction by tuning hyper parameters in convolution filters. The EEG signal is preprocessed prior to convolution by a wavelet transform while considering time and frequency simultaneously. We use a database for emotion analysis using the physiological signals open dataset to verify the proposed process, achieving 73.4% accuracy, showing significant performance improvement over the current best practice models.
NASA Astrophysics Data System (ADS)
Li, S. H.; Xia, X. H.; Wang, Y. D.; Wang, X. L.; Tu, J. P.
2017-02-01
It is a core task to find solutions to suppress the "shuttle effect" of polysulfides and improve high rate capability at the sulfur cathode of lithium sulfur batteries. Herein we first time propose a concept of multileveled blocking "dams" to suppress the diffusion of polysulfides. We report a facile and effective strategy to construct multidimensional conductive carbon hosts for accommodation of active sulfur. Multidimensional ternary carbon networks (MTCNs) with 0D nanospheres, 1D nanotubes and 2D nanoflakes are organically combined together to provide multileveled conductive channels to reserve active sulfur and promote stable sustained reactions. In the light of enhanced conductivity and multileveled blocking "dams" for polysulfides, the designed MTCNs/S cathode has been demonstrated with noticeable improvement in discharge capacity (1472 mAh g-1 at 0.l C) and long-term cycling stability (65% retention at 5.0 C after 500 cycles). Our research may provide a new insight in the gradient blocking of polysulfides with the help of multidimensional carbon networks.
Vecchio, Fabrizio; Miraglia, Francesca; Piludu, Francesca; Granata, Giuseppe; Romanello, Roberto; Caulo, Massimo; Onofrj, Valeria; Bramanti, Placido; Colosimo, Cesare; Rossini, Paolo Maria
2017-04-01
Brain imaging plays an important role in the study of Alzheimer's disease (AD), where atrophy has been found to occur in the hippocampal formation during the very early disease stages and to progress in parallel with the disease's evolution. The aim of the present study was to evaluate a possible correlation between "Small World" characteristics of the brain connectivity architecture-as extracted from EEG recordings-and hippocampal volume in AD patients. A dataset of 144 subjects, including 110 AD (MMSE 21.3) and 34 healthy Nold (MMSE 29.8) individuals, was evaluated. Weighted and undirected networks were built by the eLORETA solutions of the cortical sources' activities moving from EEG recordings. The evaluation of the hippocampal volume was carried out on a subgroup of 60 AD patients who received a high-resolution T1-weighted sequence and underwent processing for surface-based cortex reconstruction and volumetric segmentation using the Freesurfer image analysis software. Results showed that, quantitatively, more correlation was observed in the right hemisphere, but the same trend was seen in both hemispheres. Alpha band connectivity was negatively correlated, while slow (delta) and fast-frequency (beta, gamma) bands positively correlated with hippocampal volume. Namely, the larger the hippocampal volume, the lower the alpha and the higher the delta, beta, and gamma Small World characteristics of connectivity. Accordingly, the Small World connectivity pattern could represent a functional counterpart of structural hippocampal atrophying and related-network disconnection.
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…
Stochastic resonance in the majority vote model on regular and small-world lattices
NASA Astrophysics Data System (ADS)
Krawiecki, A.
2017-11-01
The majority vote model with two states on regular and small-world networks is considered under the influence of periodic driving. Monte Carlo simulations show that the time-dependent magnetization, playing the role of the output signal, exhibits maximum periodicity at nonzero values of the internal noise parameter q, which is manifested as the occurrence of the maximum of the spectral power amplification; the location of the maximum depends in a nontrivial way on the amplitude and frequency of the periodic driving as well as on the network topology. This indicates the appearance of stochastic resonance in the system as a function of the intensity of the internal noise. Besides, for low frequencies and for certain narrow ranges of the amplitudes of the periodic driving double maxima of the spectral power amplification as a function of q occur, i.e., stochastic multiresonance appears. The above-mentioned results quantitatively agree with those obtained from numerical simulations of the mean-field equations for the time-dependent magnetization. In contrast, analytic solutions for the spectral power amplification obtained from the latter equations using the linear response approximation deviate significanlty from the numerical results since the effect of the periodic driving on the system is not small even for vanishing amplitude.
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.
The Structure of Borders in a Small World
Thiemann, Christian; Theis, Fabian; Grady, Daniel; Brune, Rafael; Brockmann, Dirk
2010-01-01
Territorial subdivisions and geographic borders are essential for understanding phenomena in sociology, political science, history, and economics. They influence the interregional flow of information and cross-border trade and affect the diffusion of innovation and technology. However, it is unclear if existing administrative subdivisions that typically evolved decades ago still reflect the most plausible organizational structure of today. The complexity of modern human communication, the ease of long-distance movement, and increased interaction across political borders complicate the operational definition and assessment of geographic borders that optimally reflect the multi-scale nature of today's human connectivity patterns. What border structures emerge directly from the interplay of scales in human interactions is an open question. Based on a massive proxy dataset, we analyze a multi-scale human mobility network and compute effective geographic borders inherent to human mobility patterns in the United States. We propose two computational techniques for extracting these borders and for quantifying their strength. We find that effective borders only partially overlap with existing administrative borders, and show that some of the strongest mobility borders exist in unexpected regions. We show that the observed structures cannot be generated by gravity models for human traffic. Finally, we introduce the concept of link significance that clarifies the observed structure of effective borders. Our approach represents a novel type of quantitative, comparative analysis framework for spatially embedded multi-scale interaction networks in general and may yield important insight into a multitude of spatiotemporal phenomena generated by human activity. PMID:21124970
The structure of borders in a small world.
Thiemann, Christian; Theis, Fabian; Grady, Daniel; Brune, Rafael; Brockmann, Dirk
2010-11-18
Territorial subdivisions and geographic borders are essential for understanding phenomena in sociology, political science, history, and economics. They influence the interregional flow of information and cross-border trade and affect the diffusion of innovation and technology. However, it is unclear if existing administrative subdivisions that typically evolved decades ago still reflect the most plausible organizational structure of today. The complexity of modern human communication, the ease of long-distance movement, and increased interaction across political borders complicate the operational definition and assessment of geographic borders that optimally reflect the multi-scale nature of today's human connectivity patterns. What border structures emerge directly from the interplay of scales in human interactions is an open question. Based on a massive proxy dataset, we analyze a multi-scale human mobility network and compute effective geographic borders inherent to human mobility patterns in the United States. We propose two computational techniques for extracting these borders and for quantifying their strength. We find that effective borders only partially overlap with existing administrative borders, and show that some of the strongest mobility borders exist in unexpected regions. We show that the observed structures cannot be generated by gravity models for human traffic. Finally, we introduce the concept of link significance that clarifies the observed structure of effective borders. Our approach represents a novel type of quantitative, comparative analysis framework for spatially embedded multi-scale interaction networks in general and may yield important insight into a multitude of spatiotemporal phenomena generated by human activity.
NASA Astrophysics Data System (ADS)
Al-karawi, Dhurgham; Sayasneh, A.; Al-Assam, Hisham; Jassim, Sabah; Page, N.; Timmerman, D.; Bourne, T.; Du, Hongbo
2017-05-01
Ovarian cysts are a common pathology in women of all age groups. It is estimated that 5-10% of women have a surgical intervention to remove an ovarian cyst in their lifetime. Given this frequency rate, characterization of ovarian masses is essential for optimal management of patients. Patients with benign ovarian masses can be managed conservatively if they are asymptomatic. Mature teratomas are common benign ovarian cysts that occur, in most cases, in premenopausal women. These ovarian cysts can contain different types of human tissue including bone, cartilage, fat, hair, or other tissue. If they are causing no symptoms, they can be harmless and may not require surgery. Subjective assessment by ultrasound examiners has a high diagnostic accuracy when characterising mature teratomas from other types of tumours. The aim of this study is to develop a computerised technique with the potential to characterise mature teratomas and distinguish them from other types of benign ovarian tumours. Local Binary Pattern (LBP) was applied to extract texture features that are specific in distinguishing teratomas. Neural Networks (NN) was then used as a classifier for recognising mature teratomas. A pilot sample set of 130 B-mode static ovarian ultrasound images (41 mature teratomas tumours and 89 other types of benign tumours) was used to test the effectiveness of the proposed technique. Test results show an average accuracy rate of 99.4% with a sensitivity of 100%, specificity of 98.8% and positive predictive value of 98.9%. This study demonstrates that the NN and LBP techniques can accurately classify static 2D B-mode ultrasound images of benign ovarian masses into mature teratomas and other types of benign tumours.
ERIC Educational Resources Information Center
Jackson, Laura Christion
1997-01-01
Provides advice for small alumni offices on how to sponsor an alumni travel program, focusing on booking a travel agent, deciding where to go, using faculty as tour guides or lecturers, making time for alumni office staff to go along, remembering special touches, visiting local alumni, avoiding overt fund raising, and being prepared for problems.…
NASA Astrophysics Data System (ADS)
Krawiecki, A.
A multi-agent spin model for changes of prices in the stock market based on the Ising-like cellular automaton with interactions between traders randomly varying in time is investigated by means of Monte Carlo simulations. The structure of interactions has topology of a small-world network obtained from regular two-dimensional square lattices with various coordination numbers by randomly cutting and rewiring edges. Simulations of the model on regular lattices do not yield time series of logarithmic price returns with statistical properties comparable with the empirical ones. In contrast, in the case of networks with a certain degree of randomness for a wide range of parameters the time series of the logarithmic price returns exhibit intermittent bursting typical of volatility clustering. Also the tails of distributions of returns obey a power scaling law with exponents comparable to those obtained from the empirical data.
Bharath, Rose D; Panda, Rajanikant; Reddam, Venkateswara Reddy; Bhaskar, M V; Gohel, Suril; Bhardwaj, Sujas; Prajapati, Arvind; Pal, Pramod Kumar
2017-01-01
Background and Purpose : Repetitive transcranial magnetic stimulation (rTMS) induces widespread changes in brain connectivity. As the network topology differences induced by a single session of rTMS are less known we undertook this study to ascertain whether the network alterations had a small-world morphology using multi-modal graph theory analysis of simultaneous EEG-fMRI. Method : Simultaneous EEG-fMRI was acquired in duplicate before (R1) and after (R2) a single session of rTMS in 14 patients with Writer's Cramp (WC). Whole brain neuronal and hemodynamic network connectivity were explored using the graph theory measures and clustering coefficient, path length and small-world index were calculated for EEG and resting state fMRI (rsfMRI). Multi-modal graph theory analysis was used to evaluate the correlation of EEG and fMRI clustering coefficients. Result : A single session of rTMS was found to increase the clustering coefficient and small-worldness significantly in both EEG and fMRI ( p < 0.05). Multi-modal graph theory analysis revealed significant modulations in the fronto-parietal regions immediately after rTMS. The rsfMRI revealed additional modulations in several deep brain regions including cerebellum, insula and medial frontal lobe. Conclusion : Multi-modal graph theory analysis of simultaneous EEG-fMRI can supplement motor physiology methods in understanding the neurobiology of rTMS in vivo . Coinciding evidence from EEG and rsfMRI reports small-world morphology for the acute phase network hyper-connectivity indicating changes ensuing low-frequency rTMS is probably not "noise".
Avoiding the "It's a Small World" Effect: A Lesson Plan to Explore Diversity
ERIC Educational Resources Information Center
Endacott, Jason L.; Bowles, Freddie A.
2013-01-01
Classroom instruction about other cultures all too often resembles the Disney version of "It's a Small World" with Fantasyland-like cultural stereotypes, ceremonial activities, and traditional dress that can lead to serious misunderstandings about the depth and complexity of global societies. Social studies instruction presents the…
Big Policies and a Small World: An Analysis of Policy Problems and Solutions in Physical Education
ERIC Educational Resources Information Center
Penney, Dawn
2017-01-01
This paper uses Ball's [1998. Big policies/small world: An introduction to international perspectives in education policy. "Comparative Education," 34(2), 119-130] policy analysis and Bernstein's [1990. "The structuring of pedagogic discourse. Volume IV class, codes and control". London: Routledge; 2000, "Pedagogy,…
Liu Guocheng; Chen Yongqiang; Wang Xiuli
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. Compoundmore » 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.« less
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.
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.
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.
Yu, Xiao-Yang, E-mail: yangyangyu0103@sohu.com; Jilin Institute of Chemical Technology, Jilin City, Jilin 132022; Cui, Xiao-Bing
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{submore » 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
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
Norman, Berk; Pedoia, Valentina; Majumdar, Sharmila
2018-03-27
Purpose To analyze how automatic segmentation translates in accuracy and precision to morphology and relaxometry compared with manual segmentation and increases the speed and accuracy of the work flow that uses quantitative magnetic resonance (MR) imaging to study knee degenerative diseases such as osteoarthritis (OA). Materials and Methods This retrospective study involved the analysis of 638 MR imaging volumes from two data cohorts acquired at 3.0 T: (a) spoiled gradient-recalled acquisition in the steady state T1 ρ -weighted images and (b) three-dimensional (3D) double-echo steady-state (DESS) images. A deep learning model based on the U-Net convolutional network architecture was developed to perform automatic segmentation. Cartilage and meniscus compartments were manually segmented by skilled technicians and radiologists for comparison. Performance of the automatic segmentation was evaluated on Dice coefficient overlap with the manual segmentation, as well as by the automatic segmentations' ability to quantify, in a longitudinally repeatable way, relaxometry and morphology. Results The models produced strong Dice coefficients, particularly for 3D-DESS images, ranging between 0.770 and 0.878 in the cartilage compartments to 0.809 and 0.753 for the lateral meniscus and medial meniscus, respectively. The models averaged 5 seconds to generate the automatic segmentations. Average correlations between manual and automatic quantification of T1 ρ and T2 values were 0.8233 and 0.8603, respectively, and 0.9349 and 0.9384 for volume and thickness, respectively. Longitudinal precision of the automatic method was comparable with that of the manual one. Conclusion U-Net demonstrates efficacy and precision in quickly generating accurate segmentations that can be used to extract relaxation times and morphologic characterization and values that can be used in the monitoring and diagnosis of OA. © RSNA, 2018 Online supplemental material is available for this article.
NASA Astrophysics Data System (ADS)
Sardina, V.
2017-12-01
The Pacific Tsunami Warning Center's round the clock operations rely on the rapid determination of the source parameters of earthquakes occurring around the world. To rapidly estimate source parameters such as earthquake location and magnitude the PTWC analyzes data streams ingested in near-real time from a global network of more than 700 seismic stations. Both the density of this network and the data latency of its member stations at any given time have a direct impact on the speed at which the PTWC scientists on duty can locate an earthquake and estimate its magnitude. In this context, it turns operationally advantageous to have the ability of assessing how quickly the PTWC operational system can reasonably detect and locate and earthquake, estimate its magnitude, and send the corresponding tsunami message whenever appropriate. For this purpose, we designed and implemented a multithreaded C++ software package to generate detection time grids for both P- and S-waves after taking into consideration the seismic network topology and the data latency of its member stations. We first encapsulate all the parameters of interest at a given geographic point, such as geographic coordinates, P- and S-waves detection time in at least a minimum number of stations, and maximum allowed azimuth gap into a DetectionTimePoint class. Then we apply composition and inheritance to define a DetectionTimeLine class that handles a vector of DetectionTimePoint objects along a given latitude. A DetectionTimesGrid class in turn handles the dynamic allocation of new TravelTimeLine objects and assigning the calculation of the corresponding P- and S-waves' detection times to new threads. Finally, we added a GUI that allows the user to interactively set all initial calculation parameters and output options. Initial testing in an eight core system shows that generation of a global 2D grid at 1 degree resolution setting detection on at least 5 stations and no azimuth gap restriction takes under 25
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
Three-state Potts model on non-local directed small-world lattices
NASA Astrophysics Data System (ADS)
Ferraz, Carlos Handrey Araujo; Lima, José Luiz Sousa
2017-10-01
In this paper, we study the non-local directed Small-World (NLDSW) disorder effects in the three-state Potts model as a form to capture the essential features shared by real complex systems where non-locality effects play a important role in the behavior of these systems. Using Monte Carlo techniques and finite-size scaling analysis, we estimate the infinite lattice critical temperatures and the leading critical exponents in this model. In particular, we investigate the first- to second-order phase transition crossover when NLDSW links are inserted. A cluster-flip algorithm was used to reduce the critical slowing down effect in our simulations. We find that for a NLDSW disorder densities p
Chemically Tunable 2D Materials
new opto-electronic silicon based 2D materials, (ii) new material coatings that can change color from transparent to blue chemically or with heat, and...conduction and transparency . Activities are integrated with in-situ fundamental investigation to synergistically develop a complete understanding in materials research.
E-2D Advanced Hawkeye Aircraft (E-2D AHE)
2015-12-01
and Homeland Defense. As a part of the E-2D AHE radar modernization effort, the Navy also invested in integrating a full glass cockpit and full...Communication Navigation Surveillance/Air Traffic Management capability. The glass cockpit will also provide the capability for the pilot or co-pilot to...hours at a station distance of 200nm Flat Turn Service Ceiling =>25,000 feet above MSL at mission profile =>25,000 feet above MSL at mission
2-D or not 2-D, that is the question: A Northern California test
Mayeda, K; Malagnini, L; Phillips, W S
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 ofmore » 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
Vulnerability of complex networks
NASA Astrophysics Data System (ADS)
Mishkovski, Igor; Biey, Mario; Kocarev, Ljupco
2011-01-01
We consider normalized average edge betweenness of a network as a metric of network vulnerability. We suggest that normalized average edge betweenness together with is relative difference when certain number of nodes and/or edges are removed from the network is a measure of network vulnerability, called vulnerability index. Vulnerability index is calculated for four synthetic networks: Erdős-Rényi (ER) random networks, Barabási-Albert (BA) model of scale-free networks, Watts-Strogatz (WS) model of small-world networks, and geometric random networks. Real-world networks for which vulnerability index is calculated include: two human brain networks, three urban networks, one collaboration network, and two power grid networks. We find that WS model of small-world networks and biological networks (human brain networks) are the most robust networks among all networks studied in the paper.
Energy Efficiency of D2D Multi-User Cooperation.
Zhang, Zufan; Wang, Lu; Zhang, Jie
2017-03-28
The Device-to-Device (D2D) communication system is an important part of heterogeneous networks. It has great potential to improve spectrum efficiency, throughput and energy efficiency cooperation of multiple D2D users with the advantage of direct communication. When cooperating, D2D users expend extraordinary energy to relay data to other D2D users. Hence, the remaining energy of D2D users determines the life of the system. This paper proposes a cooperation scheme for multiple D2D users who reuse the orthogonal spectrum and are interested in the same data by aiming to solve the energy problem of D2D users. Considering both energy availability and the Signal to Noise Ratio (SNR) of each D2D user, the Kuhn-Munkres algorithm is introduced in the cooperation scheme to solve relay selection problems. Thus, the cooperation issue is transformed into a maximum weighted matching (MWM) problem. In order to enhance energy efficiency without the deterioration of Quality of Service (QoS), the link outage probability is derived according to the Shannon Equation by considering the data rate and delay. The simulation studies the relationships among the number of cooperative users, the length of shared data, the number of data packets and energy efficiency.
Quantum coherence selective 2D Raman–2D electronic spectroscopy
Spencer, Austin P.; Hutson, William O.; Harel, Elad
2017-01-01
Electronic and vibrational correlations report on the dynamics and structure of molecular species, yet revealing these correlations experimentally has proved extremely challenging. Here, we demonstrate a method that probes correlations between states within the vibrational and electronic manifold with quantum coherence selectivity. Specifically, we measure a fully coherent four-dimensional spectrum which simultaneously encodes vibrational–vibrational, electronic–vibrational and electronic–electronic interactions. By combining near-impulsive resonant and non-resonant excitation, the desired fifth-order signal of a complex organic molecule in solution is measured free of unwanted lower-order contamination. A critical feature of this method is electronic and vibrational frequency resolution, enabling isolation and assignment of individual quantum coherence pathways. The vibronic structure of the system is then revealed within an otherwise broad and featureless 2D electronic spectrum. This method is suited for studying elusive quantum effects in which electronic transitions strongly couple to phonons and vibrations, such as energy transfer in photosynthetic pigment–protein complexes. PMID:28281541
2D transition metal dichalcogenides
NASA Astrophysics Data System (ADS)
Manzeli, Sajedeh; Ovchinnikov, Dmitry; Pasquier, Diego; Yazyev, Oleg V.; Kis, Andras
2017-08-01
Graphene is very popular because of its many fascinating properties, but its lack of an electronic bandgap has stimulated the search for 2D materials with semiconducting character. Transition metal dichalcogenides (TMDCs), which are semiconductors of the type MX2, where M is a transition metal atom (such as Mo or W) and X is a chalcogen atom (such as S, Se or Te), provide a promising alternative. Because of its robustness, MoS2 is the most studied material in this family. TMDCs exhibit a unique combination of atomic-scale thickness, direct bandgap, strong spin-orbit coupling and favourable electronic and mechanical properties, which make them interesting for fundamental studies and for applications in high-end electronics, spintronics, optoelectronics, energy harvesting, flexible electronics, DNA sequencing and personalized medicine. In this Review, the methods used to synthesize TMDCs are examined and their properties are discussed, with particular attention to their charge density wave, superconductive and topological phases. The use of TMCDs in nanoelectronic devices is also explored, along with strategies to improve charge carrier mobility, high frequency operation and the use of strain engineering to tailor their properties.
Bending Rigidity of 2D Silica.
Büchner, C; Eder, S D; Nesse, T; Kuhness, D; Schlexer, P; Pacchioni, G; Manson, J R; Heyde, M; Holst, B; Freund, H-J
2018-06-01
A chemically stable bilayers of SiO_{2} (2D silica) is a new, wide band gap 2D material. Up till now graphene has been the only 2D material where the bending rigidity has been measured. Here we present inelastic helium atom scattering data from 2D silica on Ru(0001) and extract the first bending rigidity, κ, measurements for a nonmonoatomic 2D material of definable thickness. We find a value of κ=8.8 eV±0.5 eV which is of the same order of magnitude as theoretical values in the literature for freestanding crystalline 2D silica.
NASA Astrophysics Data System (ADS)
Büchner, C.; Eder, S. D.; Nesse, T.; Kuhness, D.; Schlexer, P.; Pacchioni, G.; Manson, J. R.; Heyde, M.; Holst, B.; Freund, H.-J.
2018-06-01
A chemically stable bilayers of SiO2 (2D silica) is a new, wide band gap 2D material. Up till now graphene has been the only 2D material where the bending rigidity has been measured. Here we present inelastic helium atom scattering data from 2D silica on Ru(0001) and extract the first bending rigidity, κ , measurements for a nonmonoatomic 2D material of definable thickness. We find a value of κ =8.8 eV ±0.5 eV which is of the same order of magnitude as theoretical values in the literature for freestanding crystalline 2D silica.
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
2016-05-11
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.
2D Organic Materials for Optoelectronic Applications.
Yang, Fangxu; Cheng, Shanshan; Zhang, Xiaotao; Ren, Xiaochen; Li, Rongjin; Dong, Huanli; Hu, Wenping
2018-01-01
The remarkable merits of 2D materials with atomically thin structures and optoelectronic attributes have inspired great interest in integrating 2D materials into electronics and optoelectronics. Moreover, as an emerging field in the 2D-materials family, assembly of organic nanostructures into 2D forms offers the advantages of molecular diversity, intrinsic flexibility, ease of processing, light weight, and so on, providing an exciting prospect for optoelectronic applications. Herein, the applications of organic 2D materials for optoelectronic devices are a main focus. Material examples include 2D, organic, crystalline, small molecules, polymers, self-assembly monolayers, and covalent organic frameworks. The protocols for 2D-organic-crystal-fabrication and -patterning techniques are briefly discussed, then applications in optoelectronic devices are introduced in detail. Overall, an introduction to what is known and suggestions for the potential of many exciting developments are presented. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
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.
Disordered configurations of the Glauber model in two-dimensional networks
NASA Astrophysics Data System (ADS)
Bačić, Iva; Franović, Igor; Perc, Matjaž
2017-12-01
We analyze the ordering efficiency and the structure of disordered configurations for the zero-temperature Glauber model on Watts-Strogatz networks obtained by rewiring 2D regular square lattices. In the small-world regime, the dynamics fails to reach the ordered state in the thermodynamic limit. Due to the interplay of the perturbed regular topology and the energy neutral stochastic state transitions, the stationary state consists of two intertwined domains, manifested as multiclustered states on the original lattice. Moreover, for intermediate rewiring probabilities, one finds an additional source of disorder due to the low connectivity degree, which gives rise to small isolated droplets of spins. We also examine the ordering process in paradigmatic two-layer networks with heterogeneous rewiring probabilities. Comparing the cases of a multiplex network and the corresponding network with random inter-layer connectivity, we demonstrate that the character of the final state qualitatively depends on the type of inter-layer connections.
Zhang, He; Lv, Jing-Hua; Yu, Kai; Wang, Chun-mei; Wang, Chun-xiao; Sun, Di; Zhou, Bai-bin
2015-07-28
A series of basket-like heteropoly blues, formulated as (H4bth)[{Cu(H2O)}2{Sr ⊂ P6MoV2MoVI16O73}]·4H2O (1), {H2bih}3[{FeII(H2O)2}{Sr ⊂ P6MoV2MoVI16O73}]·2H2O (2), (H2bih)3[{CoII(H2O)2}{Sr ⊂ P6MoV2MoVI16O73}]·2H2O (3), (H2bih)3[{NiII(H2O)2}{Sr ⊂ P6MoV2MoVI16O73}]·2H2O (4), (H2bih)2(H2bip)[{Zn (H2O)0.5}{Sr ⊂ P6MoV2MoVI16O73}]·5.5H2O (5), (bth = 1,6-bis(triazole)hexane; bih = 1,6-bis(imidazol)hexane; bip = 1,5-bis(imidazol)pentane) have been synthesized hydrothermally and fully characterized. The structural analysis shows that all the compounds contain two electron reduced polyanions [Sr ⊂ P6MoV2MoVI16O73]8− (abbreviated as {P6Mo18O73}), which consists of a tetra vacant γ-Dawson-type{P2Mo14} unit and a “handle”-shaped {P4Mo4} segment encapsulating a Sr2+ cation in the central cavity. Compound 1 is a 6-connected two-dimensional (2D) layer, which represents the first 2D assembly of basket-type polyoxometalates. Compounds 2–4 are isostructural one-dimensional zigzag chains linked by an M(H2O)2 linker (M = iron for 2, cobalt for 3, and nickel for 4). Compound 5 is a dimeric cluster supported by a binuclear {Zn2(H2O)} unit. The optical band gaps of 1–5 reveal their semiconductive natures. The compounds if used as photocatalysts exhibit a universal high efficiency degradation ability for dyes such as methylene blue, Rhodamine B, and Azon phloxine. The lifetime and reaction mechanism of the catalysts were investigated with a series of experiments. The compounds also show good bifunctional electrocatalytic behavior for the oxidation of ascorbic acid (AA) and reduction of nitrite ions.
Staring 2-D hadamard transform spectral imager
Gentry, Stephen M [Albuquerque, NM; Wehlburg, Christine M [Albuquerque, NM; Wehlburg, Joseph C [Albuquerque, NM; Smith, Mark W [Albuquerque, NM; Smith, Jody L [Albuquerque, NM
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.
A distance constrained synaptic plasticity model of C. elegans neuronal network
NASA Astrophysics Data System (ADS)
Badhwar, Rahul; Bagler, Ganesh
2017-03-01
Brain research has been driven by enquiry for principles of brain structure organization and its control mechanisms. The neuronal wiring map of C. elegans, the only complete connectome available till date, presents an incredible opportunity to learn basic governing principles that drive structure and function of its neuronal architecture. Despite its apparently simple nervous system, C. elegans is known to possess complex functions. The nervous system forms an important underlying framework which specifies phenotypic features associated to sensation, movement, conditioning and memory. In this study, with the help of graph theoretical models, we investigated the C. elegans neuronal network to identify network features that are critical for its control. The 'driver neurons' are associated with important biological functions such as reproduction, signalling processes and anatomical structural development. We created 1D and 2D network models of C. elegans neuronal system to probe the role of features that confer controllability and small world nature. The simple 1D ring model is critically poised for the number of feed forward motifs, neuronal clustering and characteristic path-length in response to synaptic rewiring, indicating optimal rewiring. Using empirically observed distance constraint in the neuronal network as a guiding principle, we created a distance constrained synaptic plasticity model that simultaneously explains small world nature, saturation of feed forward motifs as well as observed number of driver neurons. The distance constrained model suggests optimum long distance synaptic connections as a key feature specifying control of the network.
Fernández de Luis, Roberto; Larrea, Edurne S; Orive, Joseba; Lezama, Luis; Arriortua, María I
2016-11-21
The average and commensurate superstructures of the one-dimensional coordination polymer {Cu(NO 3 )(H 2 O)}(HTae)(Bpy) (H 2 Tae = 1,1,2,2-tetraacetylethane, Bpy = 4,4'-bipyridine) were determined by single-crystal X-ray diffraction, and the possible symmetry relations between the space group of the average structure and the superstructure were checked. The crystal structure consists in parallel and oblique {Cu(HTae)(Bpy)} zigzag metal-organic chains stacked along the [100] crystallographic direction. The origin of the fivefold c axis in the commensurate superstructure is ascribed to a commensurate modulation of the coordination environment of the copper atoms. The commensurately ordered nitrate groups and coordinated water molecules establish a two-dimensional hydrogen-bonding network. Moreover, the crystal structure shows a commensurate to incommensurate transition at room temperature. The release of the coordination water molecules destabilizes the crystal framework, and the compound shows an irreversible structure transformation above 100 °C. Despite the loss of crystallinity, the spectroscopic studies indicate that the main building blocks of the crystal framework are retained after the transformation. The hydrogen-bonding network not only plays a crucial role stabilizing the crystal structure but also is an important pathway for magnetic exchange transmission. In fact, the magnetic susceptibility curves indicate that after the loss of coordinated water molecules, and hence the collapse of the hydrogen-bonding network, the weak anti-ferromagnetic coupling observed in the initial compound is broken. The electron paramagnetic resonance spectra are the consequence of the average signals from Cu(II) with different orientations, indicating that the magnetic coupling is effective between them. In fact, X- and Q-band data are reflecting different situations; the X-band spectra show the characteristics of an exchange g-tensor, while the Q-band signals are coming from
Lessons Learned, Headquarters, 2d Infantry Division
responsibilities under the Armistice Agreement of 1953 in sector; (2) conduct anti-infiltration, anti-raiding, counter-espionage, and counter-sabotage activities; and (3) implement 2d Infantry Division portion of EUSA Cold War program.
Perspective: 2D for beyond CMOS
NASA Astrophysics Data System (ADS)
Robinson, Joshua A.
2018-05-01
Two-Dimensional (2D) materials have been a "beyond CMOS" focus for more than a decade now, and we are on the verge of a variety of breakthroughs in the science to enable their incorporation into next generation electronics. This perspective discusses some of the challenges that must be overcome, as well as various opportunities that await us in the world of 2D for beyond CMOS.
Davis, Elizabeth; Sloan, Tyler; Aurelius, Krista; Barbour, Angela; Bodey, Elijah; Clark, Brigette; Dennis, Celeste; Drown, Rachel; Fleming, Megan; Humbert, Allison; Glasgo, Elizabeth; Kerns, Trent; Lingro, Kelly; McMillin, MacKenzie; Meyer, Aaron; Pope, Breanna; Stalevicz, April; Steffen, Brittney; Steindl, Austin; Williams, Carolyn; Wimberley, Carmen; Zenas, Robert; Butela, Kristen; Wildschutte, Hans
2017-06-01
The emergence of bacterial pathogens resistant to all known antibiotics is a global health crisis. Adding to this problem is that major pharmaceutical companies have shifted away from antibiotic discovery due to low profitability. As a result, the pipeline of new antibiotics is essentially dry and many bacteria now resist the effects of most commonly used drugs. To address this global health concern, citizen science through the Small World Initiative (SWI) was formed in 2012. As part of SWI, students isolate bacteria from their local environments, characterize the strains, and assay for antibiotic production. During the 2015 fall semester at Bowling Green State University, students isolated 77 soil-derived bacteria and genetically characterized strains using the 16S rRNA gene, identified strains exhibiting antagonistic activity, and performed an expanded SWI workflow using transposon mutagenesis to identify a biosynthetic gene cluster involved in toxigenic compound production. We identified one mutant with loss of antagonistic activity and through subsequent whole-genome sequencing and linker-mediated PCR identified a 24.9 kb biosynthetic gene locus likely involved in inhibitory activity in that mutant. Further assessment against human pathogens demonstrated the inhibition of Bacillus cereus, Listeria monocytogenes, and methicillin-resistant Staphylococcus aureus in the presence of this compound, thus supporting our molecular strategy as an effective research pipeline for SWI antibiotic discovery and genetic characterization. © 2017 The Authors. MicrobiologyOpen published by John Wiley & Sons Ltd.
Towards Macroscopic Crystalline 2D Polymers.
Feng, Xinliang; Schlüter, Dieter
2018-05-29
Periodic and nanoporous monolayer polymers, whose structures can be viewed as molecular fisherman's nets, have been classified as 2D polymers. They have been previously synthesized under mild photoirradiation conditions in the interior of layered single crystals of well-designed monomers, followed by a liquid-phase exfoliation. While these mild conditions allow for full structure control, the size of 2D polymers obtained cannot exceed that of the crystals from which they are prepared. In this Review, we discuss different concepts currently pursued to prepare macroscopically sized 2D polymers, focusing on syntheses at the air/water and liquid/liquid interfaces. While these interfaces are larger reaction loci than single crystals, sheet-like polymers obtained at them pose complex and time-consuming analytical challenges. Some of these challenges are concretely discussed and indicators are provided for identifying the promising cases enabling to concentrate on them in the future research. This Review also particularly discusses three representative examples of 2D polymers to provide a state-of-the-art picture of this emerging field of polymer and materials science. Finally, we discuss the range of applications, such as nanomembranes, electronics, optoelectronics and electrocatalysts for water splitting, that are relevant for these novel organic 2D materials. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
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; Tobias, B J; Luhmann, N C
2014-11-01
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.
Pasquali, Matias; Serchi, Tommaso; Planchon, Sebastien; Renaut, Jenny
2017-01-01
The two-dimensional difference gel electrophoresis method is a valuable approach for proteomics. The method, using cyanine fluorescent dyes, allows the co-migration of multiple protein samples in the same gel and their simultaneous detection, thus reducing experimental and analytical time. 2D-DIGE, compared to traditional post-staining 2D-PAGE protocols (e.g., colloidal Coomassie or silver nitrate), provides faster and more reliable gel matching, limiting the impact of gel to gel variation, and allows also a good dynamic range for quantitative comparisons. By the use of internal standards, it is possible to normalize for experimental variations in spot intensities and gel patterns. Here we describe the experimental steps we follow in our routine 2D-DIGE procedure that we then apply to multiple biological questions.
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. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
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. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
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…
Synthesis and Characterization of 2-D Materials
NASA Astrophysics Data System (ADS)
Pazos, S.; Sahoo, P.; Afaneh, T.; Rodriguez Gutierrez, H.
Atomically thin transition-metal dichacogenides (TMD), graphene, and boron nitride (BN) are two-dimensional materials where the charge carriers (electrons and holes) are confined to move in a plane. They exhibit distinctive optoelectronic properties compared to their bulk layered counterparts. When combined into heterostructures, these materials open more possibilities in terms of new properties and device functionality. In this work, WSe2 and graphene were grown using Chemical Vapor Deposition (CVD) and Physical Vapor Deposition (PVD) techniques. The quality and morphology of each material was checked using Raman, Photoluminescence Spectroscopy, and Scanning Electron Microscopy. Graphene had been successfully grown homogenously, characterized, and transferred from copper to silicon dioxide substrates; these films will be used in future studies to build 2-D devices. Different morphologies of WSe2 2-D islands were successfully grown on SiO2 substrates. Depending on the synthesis conditions, the material on each sample had single layer, double layer, and multi-layer areas. A variety of 2-D morphologies were also observed in the 2-D islands. This project is supported by the NSF REU Grant #1560090 and NSF Grant #DMR-1557434.
Parallel stitching of 2D materials
Ling, Xi; Wu, Lijun; Lin, Yuxuan; ...
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.
Phase velocity in 2D TTI media
NASA Astrophysics Data System (ADS)
Xuan, Yihua; He, Qiaodeng; Lin, Yan
2007-03-01
We derive an expression for phase velocity in 2D tilted transverse isotropy (TTI) media. Snapshots of phase velocity in TTI and transverse isotropy (TI) model media are simulated and analyzed using the derived expression. In addition, the x-component character differences between the modeled phase velocities of the two media models are compared and analyzed.
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
2016-02-06
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, itmore » 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
Extrinsic Cation Selectivity of 2D Membranes
2017-01-01
From a systematic study of the concentration driven diffusion of positive and negative ions across porous 2D membranes of graphene and hexagonal boron nitride (h-BN), we prove their cation selectivity. Using the current–voltage characteristics of graphene and h-BN monolayers separating reservoirs of different salt concentrations, we calculate the reversal potential as a measure of selectivity. We tune the Debye screening length by exchanging the salt concentrations and demonstrate that negative surface charge gives rise to cation selectivity. Surprisingly, h-BN and graphene membranes show similar characteristics, strongly suggesting a common origin of selectivity in aqueous solvents. For the first time, we demonstrate that the cation flux can be increased by using ozone to create additional pores in graphene while maintaining excellent selectivity. We discuss opportunities to exploit our scalable method to use 2D membranes for applications including osmotic power conversion. PMID:28157333
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 highmore » 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
NASA Astrophysics Data System (ADS)
Smith, Greg; Lankshear, Allan
1998-07-01
2dF is a multi-object instrument mounted at prime focus at the AAT capable of spectroscopic analysis of 400 objects in a single 2 degree field. It also prepares a second 2 degree 400 object field while the first field is being observed. At its heart is a high precision robotic positioner that places individual fiber end magnetic buttons on one of two field plates. The button gripper is carried on orthogonal gantries powered by linear synchronous motors and contains a TV camera which precisely locates backlit buttons to allow placement in user defined locations to 10 (mu) accuracy. Fiducial points on both plates can also be observed by the camera to allow repeated checks on positioning accuracy. Field plates rotate to follow apparent sky rotation. The spectrographs both analyze light from the 200 observing fibers each and back- illuminate the 400 fibers being re-positioned during the observing run. The 2dF fiber position and spectrograph system is a large and complex instrument located at the prime focus of the Anglo Australian Telescope. The mechanical design has departed somewhat from the earlier concepts of Gray et al, but still reflects the audacity of those first ideas. The positioner is capable of positioning 400 fibers on a field plate while another 400 fibers on another plate are observing at the focus of the telescope and feeding the twin spectrographs. When first proposed it must have seemed like ingenuity unfettered by caution. Yet now it works, and works wonderfully well. 2dF is a system which functions as the result of the combined and coordinated efforts of the astronomers, the mechanical designers and tradespeople, the electronic designers, the programmers, the support staff at the telescope, and the manufacturing subcontractors. The mechanical design of the 2dF positioner and spectrographs was carried out by the mechanical engineering staff of the AAO and the majority of the manufacture was carried out in the AAO workshops.
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.
Simulation of 2D Granular Hopper Flow
NASA Astrophysics Data System (ADS)
Li, Zhusong; Shattuck, Mark
2012-02-01
Jamming and intermittent granular flow are big problems in industry, and the vertical hopper is a canonical example of these difficulties. We simulate gravity driven flow and jamming of 2D disks in a vertical hopper and compare with identical companion experiments presented in this session. We measure and compare the flow rate and probability for jamming as a function of particle properties and geometry. We evaluate the ability of standard Hertz-Mindlin contact mode to quantitatively predict the experimental flow.
Quasiparticle interference in unconventional 2D systems.
Chen, Lan; Cheng, Peng; Wu, Kehui
2017-03-15
At present, research of 2D systems mainly focuses on two kinds of materials: graphene-like materials and transition-metal dichalcogenides (TMDs). Both of them host unconventional 2D electronic properties: pseudospin and the associated chirality of electrons in graphene-like materials, and spin-valley-coupled electronic structures in the TMDs. These exotic electronic properties have attracted tremendous interest for possible applications in nanodevices in the future. Investigation on the quasiparticle interference (QPI) in 2D systems is an effective way to uncover these properties. In this review, we will begin with a brief introduction to 2D systems, including their atomic structures and electronic bands. Then, we will discuss the formation of Friedel oscillation due to QPI in constant energy contours of electron bands, and show the basic concept of Fourier-transform scanning tunneling microscopy/spectroscopy (FT-STM/STS), which can resolve Friedel oscillation patterns in real space and consequently obtain the QPI patterns in reciprocal space. In the next two parts, we will summarize some pivotal results in the investigation of QPI in graphene and silicene, in which systems the low-energy quasiparticles are described by the massless Dirac equation. The FT-STM experiments show there are two different interference channels (intervalley and intravalley scattering) and backscattering suppression, which associate with the Dirac cones and the chirality of quasiparticles. The monolayer and bilayer graphene on different substrates (SiC and metal surfaces), and the monolayer and multilayer silicene on a Ag(1 1 1) surface will be addressed. The fifth part will introduce the FT-STM research on QPI in TMDs (monolayer and bilayer of WSe 2 ), which allow us to infer the spin texture of both conduction and valence bands, and present spin-valley coupling by tracking allowed and forbidden scattering channels.
2D materials: Graphene and others
Bansal, Suneev Anil, E-mail: suneev@gmail.com; Singh, Amrinder Pal; Kumar, Suresh
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.
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.
Melting of 2D colloidal crystals
NASA Astrophysics Data System (ADS)
Maret, G.; Eisenmann, C.; Gasser, U.; Vongruenberg, H. H.; Keim, P.; Zahn, K.
2004-11-01
We study melting of 2D crystals of super-paramagnetic colloidal particles confined by gravity to a flat air-water interface. The effective system temperature is given by the strength of the dipolar inter-particle interaction controlled by an external magnetic field B. Particle positions are obtained by video-microscopy. In vertical B-field crystals are hexagonal and we find all features of the 2-step melting scenario predicted by KTHNY-theory. In particular, quantitative agreement is found for the translational and orientational order parameters related to bound and isolated dislocations and disclinations. From particle position fluctuations wave-vector (q) dependent normal-mode spring constants are obtained in agreement with phonon band structure calculations. The elastic constants (q=0 limit) soften near melting in quantitative agreement with KTHNY. By tilting B away from vertical anisotropic 2D crystals are generated; at small tilting angles they melt through a quasi-hexatic phase, while at higher tilts a centered rectangular phase is found which melts into a 2D smectic-like phase through orientation-dependent dislocations.
Cell Migration in 1D and 2D Nanofiber Microenvironments.
Estabridis, Horacio M; Jana, Aniket; Nain, Amrinder; Odde, David J
2018-03-01
Understanding how cells migrate in fibrous environments is important in wound healing, immune function, and cancer progression. A key question is how fiber orientation and network geometry influence cell movement. Here we describe a quantitative, modeling-based approach toward identifying the mechanisms by which cells migrate in fibrous geometries having well controlled orientation. Specifically, U251 glioblastoma cells were seeded onto non-electrospinning Spinneret based tunable engineering parameters fiber substrates that consist of networks of suspended 400 nm diameter nanofibers. Cells were classified based on the local fiber geometry and cell migration dynamics observed by light microscopy. Cells were found in three distinct geometries: adhering two a single fiber, adhering to two parallel fibers, and adhering to a network of orthogonal fibers. Cells adhering to a single fiber or two parallel fibers can only move in one dimension along the fiber axis, whereas cells on a network of orthogonal fibers can move in two dimensions. We found that cells move faster and more persistently in 1D geometries than in 2D, with cell migration being faster on parallel fibers than on single fibers. To explain these behaviors mechanistically, we simulated cell migration in the three different geometries using a motor-clutch based model for cell traction forces. Using nearly identical parameter sets for each of the three cases, we found that the simulated cells naturally replicated the reduced migration in 2D relative to 1D geometries. In addition, the modestly faster 1D migration on parallel fibers relative to single fibers was captured using a correspondingly modest increase in the number of clutches to reflect increased surface area of adhesion on parallel fibers. Overall, the integrated modeling and experimental analysis shows that cell migration in response to varying fibrous geometries can be explained by a simple mechanical readout of geometry via a motor-clutch mechanism.
DNN-state identification of 2D distributed parameter systems
NASA Astrophysics Data System (ADS)
Chairez, I.; Fuentes, R.; Poznyak, A.; Poznyak, T.; Escudero, M.; Viana, L.
2012-02-01
There are many examples in science and engineering which are reduced to a set of partial differential equations (PDEs) through a process of mathematical modelling. Nevertheless there exist many sources of uncertainties around the aforementioned mathematical representation. Moreover, to find exact solutions of those PDEs is not a trivial task especially if the PDE is described in two or more dimensions. It is well known that neural networks can approximate a large set of continuous functions defined on a compact set to an arbitrary accuracy. In this article, a strategy based on the differential neural network (DNN) for the non-parametric identification of a mathematical model described by a class of two-dimensional (2D) PDEs is proposed. The adaptive laws for weights ensure the 'practical stability' of the DNN-trajectories to the parabolic 2D-PDE states. To verify the qualitative behaviour of the suggested methodology, here a non-parametric modelling problem for a distributed parameter plant is analysed.
2D non-separable linear canonical transform (2D-NS-LCT) based cryptography
NASA Astrophysics Data System (ADS)
Zhao, Liang; Muniraj, Inbarasan; Healy, John J.; Malallah, Ra'ed; Cui, Xiao-Guang; Ryle, James P.; Sheridan, John T.
2017-05-01
The 2D non-separable linear canonical transform (2D-NS-LCT) can describe a variety of paraxial optical systems. Digital algorithms to numerically evaluate the 2D-NS-LCTs are not only important in modeling the light field propagations but also of interest in various signal processing based applications, for instance optical encryption. Therefore, in this paper, for the first time, a 2D-NS-LCT based optical Double-random- Phase-Encryption (DRPE) system is proposed which offers encrypting information in multiple degrees of freedom. Compared with the traditional systems, i.e. (i) Fourier transform (FT); (ii) Fresnel transform (FST); (iii) Fractional Fourier transform (FRT); and (iv) Linear Canonical transform (LCT), based DRPE systems, the proposed system is more secure and robust as it encrypts the data with more degrees of freedom with an augmented key-space.
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.
2D stepping drive for hyperspectral systems
NASA Astrophysics Data System (ADS)
Endrödy, Csaba; Mehner, Hannes; Grewe, Adrian; Sinzinger, Stefan; Hoffmann, Martin
2015-07-01
We present the design, fabrication and characterization of a compact 2D stepping microdrive for pinhole array positioning. The miniaturized solution enables a highly integrated compact hyperspectral imaging system. Based on the geometry of the pinhole array, an inch-worm drive with electrostatic actuators was designed resulting in a compact (1 cm2) positioning system featuring a step size of about 15 µm in a 170 µm displacement range. The high payload (20 mg) as required for the pinhole array and the compact system design exceed the known electrostatic inch-worm-based microdrives.
Gluon amplitudes as 2 d conformal correlators
NASA Astrophysics Data System (ADS)
Pasterski, Sabrina; Shao, Shu-Heng; Strominger, Andrew
2017-10-01
Recently, spin-one wave functions in four dimensions that are conformal primaries of the Lorentz group S L (2 ,C ) were constructed. We compute low-point, tree-level gluon scattering amplitudes in the space of these conformal primary wave functions. The answers have the same conformal covariance as correlators of spin-one primaries in a 2 d CFT. The Britto-Cachazo-Feng-Witten (BCFW) recursion relation between three- and four-point gluon amplitudes is recast into this conformal basis.
Periodically sheared 2D Yukawa systems
Kovács, Anikó Zsuzsa; Hartmann, Peter; Center for Astrophysics, Space Physics and Engineering Research
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.
NASA Astrophysics Data System (ADS)
Yang, Shengxue; Jiang, Chengbao; Wei, Su-huai
2017-06-01
Two-dimensional (2D) layered inorganic nanomaterials have attracted huge attention due to their unique electronic structures, as well as extraordinary physical and chemical properties for use in electronics, optoelectronics, spintronics, catalysts, energy generation and storage, and chemical sensors. Graphene and related layered inorganic analogues have shown great potential for gas-sensing applications because of their large specific surface areas and strong surface activities. This review aims to discuss the latest advancements in the 2D layered inorganic materials for gas sensors. We first elaborate the gas-sensing mechanisms and introduce various types of gas-sensing devices. Then, we describe the basic parameters and influence factors of the gas sensors to further enhance their performance. Moreover, we systematically present the current gas-sensing applications based on graphene, graphene oxide (GO), reduced graphene oxide (rGO), functionalized GO or rGO, transition metal dichalcogenides, layered III-VI semiconductors, layered metal oxides, phosphorene, hexagonal boron nitride, etc. Finally, we conclude the future prospects of these layered inorganic materials in gas-sensing applications.
Remarks on thermalization in 2D CFT
NASA Astrophysics Data System (ADS)
de Boer, Jan; Engelhardt, Dalit
2016-12-01
We revisit certain aspects of thermalization in 2D conformal field theory (CFT). In particular, we consider similarities and differences between the time dependence of correlation functions in various states in rational and non-rational CFTs. We also consider the distinction between global and local thermalization and explain how states obtained by acting with a diffeomorphism on the ground state can appear locally thermal, and we review why the time-dependent expectation value of the energy-momentum tensor is generally a poor diagnostic of global thermalization. Since all 2D CFTs have an infinite set of commuting conserved charges, generic initial states might be expected to give rise to a generalized Gibbs ensemble rather than a pure thermal ensemble at late times. We construct the holographic dual of the generalized Gibbs ensemble and show that, to leading order, it is still described by a Banados-Teitelboim-Zanelli black hole. The extra conserved charges, while rendering c <1 theories essentially integrable, therefore seem to have little effect on large-c conformal field theories.
Intermittency in 2D soap film turbulence
NASA Astrophysics Data System (ADS)
Cerbus, R. T.; Goldburg, W. I.
2013-10-01
The Reynolds number dependency of intermittency for 2D turbulence is studied in a flowing soap film. The Reynolds number used here is the Taylor microscale Reynolds number Rλ, which ranges from 20 to 800. Strong intermittency is found for both the inverse energy and direct enstrophy cascades as measured by (a) the pdf of velocity differences P(δu(r)) at inertial scales r, (b) the kurtosis of P(∂xu), and (c) the scaling of the so-called intermittency exponent μ, which is zero if intermittency is absent. Measures (b) and (c) are quantitative, while (a) is qualitative. These measurements are in disagreement with some previous results but not all. The velocity derivatives are nongaussian at all Rλ but show signs of becoming gaussian as Rλ increases beyond the largest values that could be reached. The kurtosis of P(δu(r)) at various r indicates that the intermittency is scale dependent. The structure function scaling exponents also deviate strongly from the Kraichnan prediction. For the enstrophy cascade, the intermittency decreases as a power law in Rλ. This study suggests the need for a new look at the statistics of 2D turbulence.
Cheng, Hongfei; Zhou, Yi; Feng, Yaping; Geng, Wenxiao; Liu, Qinfu; Guo, Wei; Jiang, Lei
2017-06-01
Inspired by the microstructure of nacre, material design, and large-scale integration of artificial nanofluidic devices step into a completely new stage, termed 2D nanofluidics, in which mass and charge transportation are confined in the interstitial space between reconstructed 2D nanomaterials. However, all the existing 2D nanofluidic systems are reconstituted from homogeneous nanobuilding blocks. Herein, this paper reports the bottom-up construction of 2D nanofluidic materials with kaolinite-based Janus nanobuilding blocks, and demonstrates two types of electrokinetic energy conversion through the network of 2D nanochannels. Being different from previous 2D nanofluidic systems, two distinct types of sub-nanometer- and nanometer-wide fluidic channels of about 6.8 and 13.8 Å are identified in the reconstructed kaolinite membranes (RKM), showing prominent surface-governed ion transport behaviors and nearly perfect cation-selectivity. The RKMs exhibit superior capability in osmotic and hydraulic energy conversion, compared to graphene-based membranes. The mineral-based 2D nanofluidic system opens up a new avenue to self-assemble asymmetric 2D nanomaterials for energy, environmental, and healthcare applications. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
Update on 2-D OMEGA Capsule Implosions
NASA Astrophysics Data System (ADS)
Bradley, Paul
2017-10-01
We have an upgraded laser energy deposition package in our AMR-Eulerian radiation-hydrodynamic code called RAGE. As part of our validation effort, we ran 2-D simulations for a series of OMEGA direct drive implosion capsules that have shell thickness ranging from 7.2 to 29.3 μm and different gas fills. These simulations include the effect of surface roughness, laser spot non-uniformity, the mounting stalk, and the glue spot. We examined the sensitivity of our simulated results to mesh resolution and mix model. Our simulated results compare well to the experimental yield, ion temperature, burn width, and x-ray size data. Work performed by Los Alamos National Laboratory under contract DE-AC52-06NA25396 for the National Nuclear Security Administration of the U.S. Department of Energy.
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.
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.
Nonlinear Optics with 2D Layered Materials.
Autere, Anton; Jussila, Henri; Dai, Yunyun; Wang, Yadong; Lipsanen, Harri; Sun, Zhipei
2018-06-01
2D layered materials (2DLMs) are a subject of intense research for a wide variety of applications (e.g., electronics, photonics, and optoelectronics) due to their unique physical properties. Most recently, increasing research efforts on 2DLMs are projected toward the nonlinear optical properties of 2DLMs, which are not only fascinating from the fundamental science point of view but also intriguing for various potential applications. Here, the current state of the art in the field of nonlinear optics based on 2DLMs and their hybrid structures (e.g., mixed-dimensional heterostructures, plasmonic structures, and silicon/fiber integrated structures) is reviewed. Several potential perspectives and possible future research directions of these promising nanomaterials for nonlinear optics are also presented. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
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.
Simulation of Yeast Cooperation in 2D.
Wang, M; Huang, Y; Wu, Z
2016-03-01
Evolution of cooperation has been an active research area in evolutionary biology in decades. An important type of cooperation is developed from group selection, when individuals form spatial groups to prevent them from foreign invasions. In this paper, we study the evolution of cooperation in a mixed population of cooperating and cheating yeast strains in 2D with the interactions among the yeast cells restricted to their small neighborhoods. We conduct a computer simulation based on a game theoretic model and show that cooperation is increased when the interactions are spatially restricted, whether the game is of a prisoner's dilemma, snow drifting, or mutual benefit type. We study the evolution of homogeneous groups of cooperators or cheaters and describe the conditions for them to sustain or expand in an opponent population. We show that under certain spatial restrictions, cooperator groups are able to sustain and expand as group sizes become large, while cheater groups fail to expand and keep them from collapse.
Predicting 2D target velocity cannot help 2D motion integration for smooth pursuit initiation.
Montagnini, Anna; Spering, Miriam; Masson, Guillaume S
2006-12-01
Smooth pursuit eye movements reflect the temporal dynamics of bidimensional (2D) visual motion integration. When tracking a single, tilted line, initial pursuit direction is biased toward unidimensional (1D) edge motion signals, which are orthogonal to the line orientation. Over 200 ms, tracking direction is slowly corrected to finally match the 2D object motion during steady-state pursuit. We now show that repetition of line orientation and/or motion direction does not eliminate the transient tracking direction error nor change the time course of pursuit correction. Nonetheless, multiple successive presentations of a single orientation/direction condition elicit robust anticipatory pursuit eye movements that always go in the 2D object motion direction not the 1D edge motion direction. These results demonstrate that predictive signals about target motion cannot be used for an efficient integration of ambiguous velocity signals at pursuit initiation.
Vaccination intervention on epidemic dynamics in networks
NASA Astrophysics Data System (ADS)
Peng, Xiao-Long; Xu, Xin-Jian; Fu, Xinchu; Zhou, Tao
2013-02-01
Vaccination is an important measure available for preventing or reducing the spread of infectious diseases. In this paper, an epidemic model including susceptible, infected, and imperfectly vaccinated compartments is studied on Watts-Strogatz small-world, Barabási-Albert scale-free, and random scale-free networks. The epidemic threshold and prevalence are analyzed. For small-world networks, the effective vaccination intervention is suggested and its influence on the threshold and prevalence is analyzed. For scale-free networks, the threshold is found to be strongly dependent both on the effective vaccination rate and on the connectivity distribution. Moreover, so long as vaccination is effective, it can linearly decrease the epidemic prevalence in small-world networks, whereas for scale-free networks it acts exponentially. These results can help in adopting pragmatic treatment upon diseases in structured populations.
Local 2D-2D tunneling in high mobility electron systems
NASA Astrophysics Data System (ADS)
Pelliccione, Matthew; Sciambi, Adam; Bartel, John; Goldhaber-Gordon, David; Pfeiffer, Loren; West, Ken; Lilly, Michael; Bank, Seth; Gossard, Arthur
2012-02-01
Many scanning probe techniques have been utilized in recent years to measure local properties of high mobility two-dimensional (2D) electron systems in GaAs. However, most techniques lack the ability to tunnel into the buried 2D system and measure local spectroscopic information. We report scanning gate measurements on a bilayer GaAs/AlGaAs heterostructure that allows for a local modulation of tunneling between two 2D electron layers. We call this technique Virtual Scanning Tunneling Microscopy (VSTM) [1,2] as the influence of the scanning gate is analogous to an STM tip, except at a GaAs/AlGaAs interface instead of a surface. We will discuss the spectroscopic capabilities of the technique, and show preliminary results of measurements on a high mobility 2D electron system.[1] A. Sciambi, M. Pelliccione et al., Appl. Phys. Lett. 97, 132103 (2010).[2] A. Sciambi, M. Pelliccione et al., Phys. Rev. B 84, 085301 (2011).
2D Radiative Processes Near Cloud Edges
NASA Technical Reports Server (NTRS)
Varnai, T.
2012-01-01
Because of the importance and complexity of dynamical, microphysical, and radiative processes taking place near cloud edges, the transition zone between clouds and cloud free air has been the subject of intense research both in the ASR program and in the wider community. One challenge in this research is that the one-dimensional (1D) radiative models widely used in both remote sensing and dynamical simulations become less accurate near cloud edges: The large horizontal gradients in particle concentrations imply that accurate radiative calculations need to consider multi-dimensional radiative interactions among areas that have widely different optical properties. This study examines the way the importance of multidimensional shortwave radiative interactions changes as we approach cloud edges. For this, the study relies on radiative simulations performed for a multiyear dataset of clouds observed over the NSA, SGP, and TWP sites. This dataset is based on Microbase cloud profiles as well as wind measurements and ARM cloud classification products. The study analyzes the way the difference between 1D and 2D simulation results increases near cloud edges. It considers both monochromatic radiances and broadband radiative heating, and it also examines the influence of factors such as cloud type and height, and solar elevation. The results provide insights into the workings of radiative processes and may help better interpret radiance measurements and better estimate the radiative impacts of this critical region.
2D/3D facial feature extraction
NASA Astrophysics Data System (ADS)
Çinar Akakin, Hatice; Ali Salah, Albert; Akarun, Lale; Sankur, Bülent
2006-02-01
We propose and compare three different automatic landmarking methods for near-frontal faces. The face information is provided as 480x640 gray-level images in addition to the corresponding 3D scene depth information. All three methods follow a coarse-to-fine suite and use the 3D information in an assist role. The first method employs a combination of principal component analysis (PCA) and independent component analysis (ICA) features to analyze the Gabor feature set. The second method uses a subset of DCT coefficients for template-based matching. These two methods employ SVM classifiers with polynomial kernel functions. The third method uses a mixture of factor analyzers to learn Gabor filter outputs. We contrast the localization performance separately with 2D texture and 3D depth information. Although the 3D depth information per se does not perform as well as texture images in landmark localization, the 3D information has still a beneficial role in eliminating the background and the false alarms.
Multimodal 2D Brain Computer Interface.
Almajidy, Rand K; Boudria, Yacine; Hofmann, Ulrich G; Besio, Walter; Mankodiya, Kunal
2015-08-01
In this work we used multimodal, non-invasive brain signal recording systems, namely Near Infrared Spectroscopy (NIRS), disc electrode electroencephalography (EEG) and tripolar concentric ring electrodes (TCRE) electroencephalography (tEEG). 7 healthy subjects participated in our experiments to control a 2-D Brain Computer Interface (BCI). Four motor imagery task were performed, imagery motion of the left hand, the right hand, both hands and both feet. The signal slope (SS) of the change in oxygenated hemoglobin concentration measured by NIRS was used for feature extraction while the power spectrum density (PSD) of both EEG and tEEG in the frequency band 8-30Hz was used for feature extraction. Linear Discriminant Analysis (LDA) was used to classify different combinations of the aforementioned features. The highest classification accuracy (85.2%) was achieved by using features from all the three brain signals recording modules. The improvement in classification accuracy was highly significant (p = 0.0033) when using the multimodal signals features as compared to pure EEG features.
Restoring 2D content from distorted documents.
Brown, Michael S; Sun, Mingxuan; Yang, Ruigang; Yun, Lin; Seales, W Brent
2007-11-01
This paper presents a framework to restore the 2D content printed on documents in the presence of geometric distortion and non-uniform illumination. Compared with textbased document imaging approaches that correct distortion to a level necessary to obtain sufficiently readable text or to facilitate optical character recognition (OCR), our work targets nontextual documents where the original printed content is desired. To achieve this goal, our framework acquires a 3D scan of the document's surface together with a high-resolution image. Conformal mapping is used to rectify geometric distortion by mapping the 3D surface back to a plane while minimizing angular distortion. This conformal "deskewing" assumes no parametric model of the document's surface and is suitable for arbitrary distortions. Illumination correction is performed by using the 3D shape to distinguish content gradient edges from illumination gradient edges in the high-resolution image. Integration is performed using only the content edges to obtain a reflectance image with significantly less illumination artifacts. This approach makes no assumptions about light sources and their positions. The results from the geometric and photometric correction are combined to produce the final output.
2D Geodynamic models of Microcontinent Formation
NASA Astrophysics Data System (ADS)
Tetreault, Joya; Buiter, Susanne
2013-04-01
Continental fragments (microcontinents and continental ribbons) are rifted-off blocks of relatively unthinned continental crust situated among the severely thinned crust of passive margins. The existence of these large crustal blocks would suggest that the passive margin containing them either underwent simultaneous differential rifting or multi-stage rifting in order to produce continental breakup and seafloor spreading in more than one location in the span of approximately 100 km. Also, because continental fragments do not occur on every passive margin, there must be something particular about the crust and/or lithosphere that led to the production of these features. Some proposed mechanisms for microcontinent and continental ribbon formation include (1) structural inheritance, (2) strain localization by serpentinized mantle or magmatic underplating, and (3) plume interaction with an active rift. Pre-existing weakness and inherited structural fabrics in typical continental crust from past tectonic events, such as varying rheology of accreted terranes and collisional suture zones, could be reactivated and serve as foci for deformation. The second theory is that strain is localized in certain regions by large amounts of weakened material that are either serpentinized mantle or mafic bodies underplating the thinned crust. Another possible process that could lead to continental fragment formation is magmatic influence of hot plume material that focuses in various regions, producing rifts in separate areas. The Jan Mayen and Seychelles microcontinents both have geological and plate reconstruction evidence to support the plume interaction theory. We use 2-D geodynamic experiments to assess the importance of structural inheritance, strain localization by regions of weakened mantle material, and contributions to rifting from plume material on producing crustal blocks surrounded by seafloor or thinned/hyperextended crust. Our preliminary results suggest that each of these
Microscopic Origins of Shear Jamming for 2D Frictional Grains
NASA Astrophysics Data System (ADS)
Wang, Dong; Ren, Jie; Dijksman, Joshua A.; Zheng, Hu; Behringer, Robert P.
2018-05-01
Shear jamming (SJ) occurs for frictional granular materials with packing fractions ϕ in ϕS<ϕ <ϕJ0, when the material is subject to shear strain γ starting from a force-free state. Here, ϕJμ is the isotropic jamming point for particles with a friction coefficient μ . SJ states have mechanically stable anisotropic force networks, e.g., force chains. Here, we investigate the origins of SJ by considering small-scale structures—trimers and branches—whose response to shear leads to SJ. Trimers are any three grains where the two outer grains contact a center one. Branches occur where three or more quasilinear force chain segments intersect. Certain trimers respond to shear by compressing and bending; bending is a nonlinear symmetry-breaking process that can push particles in the dilation direction faster than the affine dilation. We identify these structures in physical experiments on systems of two-dimensional frictional discs, and verify their role in SJ. Trimer bending and branch creation both increase Z above Ziso≃3 needed for jamming 2D frictional grains, and grow the strong force network, leading to SJ.
Superconductivity in 2D and nearly 2D: A Conserving Description
NASA Astrophysics Data System (ADS)
Deisz, John; Hess, Daryl; Serene, Joe
1998-03-01
In a previous work,(J.J. Deisz, D.W. Hess, and J.W. Serene, Phys. Rev. Lett., to appear.) we used a 2D Hubbard model with an attractive interaction to explicitly show that a superconducting state in the fluctuation exchange approximation (FEA) could be detected from self-consistent calculations of the internal energy and free energy as a function of a threaded flux. The FEA is a conserving approximation beyond mean field theory that includes the exchange of Cooper pair, density, and spin fluctuations. Here, we present extensions of our previous calculations and show a phase diagram as a function of interaction strength and density. We discuss the nature of the FEA phase transition in 2D and focus on how it changes with increasing coupling between planes.
Urbankowski, Patrick; Anasori, Babak; Hantanasirisakul, Kanit; ...
2017-11-08
MXenes are a rapidly growing class of 2D transition metal carbides and nitrides, finding applications in fields ranging from energy storage to electromagnetic interference shielding and transparent conductive coatings. However, while more than 20 carbide MXenes have already been synthesized, Ti 4N 3 and Ti 2N are the only nitride MXenes reported so far. Here by ammoniation of Mo 2CT x and V 2CT x MXenes at 600 °C, we report on their transformation to 2D metal nitrides. Carbon atoms in the precursor MXenes are replaced with N atoms, resulting from the decomposition of ammonia molecules. The crystal structures ofmore » the resulting Mo 2N and V 2N were determined with transmission electron microscopy and X-ray pair distribution function analysis. Our results indicate that Mo 2N retains the MXene structure and V 2C transforms to a mixed layered structure of trigonal V 2N and cubic VN. Temperature-dependent resistivity measurements of the nitrides reveal that they exhibit metallic conductivity, as opposed to semiconductor-like behavior of their parent carbides. As important, room-temperature electrical conductivity values of Mo2N and V2N are three and one order of magnitude larger than those of the Mo 2CT x and V 2CT x precursors, respectively. In conclusion, this study shows how gas treatment synthesis such as ammoniation can transform carbide MXenes into 2D nitrides with higher electrical conductivities and metallic behavior, opening a new avenue in 2D materials synthesis.« less
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)
Network rewiring dynamics with convergence towards a star network
Dick, G.; Parry, M.
2016-01-01
Network rewiring as a method for producing a range of structures was first introduced in 1998 by Watts & Strogatz (Nature 393, 440–442. (doi:10.1038/30918)). This approach allowed a transition from regular through small-world to a random network. The subsequent interest in scale-free networks motivated a number of methods for developing rewiring approaches that converged to scale-free networks. This paper presents a rewiring algorithm (RtoS) for undirected, non-degenerate, fixed size networks that transitions from regular, through small-world and scale-free to star-like networks. Applications of the approach to models for the spread of infectious disease and fixation time for a simple genetics model are used to demonstrate the efficacy and application of the approach. PMID:27843396
Network rewiring dynamics with convergence towards a star network.
Whigham, P A; Dick, G; Parry, M
2016-10-01
Network rewiring as a method for producing a range of structures was first introduced in 1998 by Watts & Strogatz ( Nature 393 , 440-442. (doi:10.1038/30918)). This approach allowed a transition from regular through small-world to a random network. The subsequent interest in scale-free networks motivated a number of methods for developing rewiring approaches that converged to scale-free networks. This paper presents a rewiring algorithm (RtoS) for undirected, non-degenerate, fixed size networks that transitions from regular, through small-world and scale-free to star-like networks. Applications of the approach to models for the spread of infectious disease and fixation time for a simple genetics model are used to demonstrate the efficacy and application of the approach.
NKG2D and its ligands in cancer.
Dhar, Payal; Wu, Jennifer D
2018-04-01
NKG2D is an activating immune receptor expressed by NK and effector T cells. Induced expression of NKG2D ligand on tumor cell surface during oncogenic insults renders cancer cells susceptible to immune destruction. In advanced human cancers, tumor cells shed NKG2D ligand to produce an immune soluble form as a means of immune evasion. Soluble NKG2D ligands have been associated with poor clinical prognosis in cancer patients. Harnessing NKG2D pathway is considered a viable avenue in cancer immunotherapy over recent years. In this review, we will discuss the progress and perspectives. Copyright © 2018. Published by Elsevier Ltd.
Transcriptional Regulation of CYP2D6 Expression
Pan, Xian; Ning, Miaoran
2017-01-01
CYP2D6-mediated drug metabolism exhibits large interindividual variability. Although genetic variations in the CYP2D6 gene are well known contributors to the variability, the sources of CYP2D6 variability in individuals of the same genotype remain unexplained. Accumulating data indicate that transcriptional regulation of CYP2D6 may account for part of CYP2D6 variability. Yet, our understanding of factors governing transcriptional regulation of CYP2D6 is limited. Recently, mechanistic studies of increased CYP2D6-mediated drug metabolism in pregnancy revealed two transcription factors, small heterodimer partner (SHP) and Krüppel-like factor 9, as a transcriptional repressor and an activator, respectively, of CYP2D6. Chemicals that increase SHP expression (e.g., retinoids and activators of farnesoid X receptor) were shown to downregulate CYP2D6 expression in the humanized mice as well as in human hepatocytes. This review summarizes the series of studies on the transcriptional regulation of CYP2D6 expression, potentially providing a basis to better understand the large interindividual variability in CYP2D6-mediated drug metabolism. PMID:27698228
Cytochrome P450 2D6 polymorphism and character traits.
Suzuki, Eiji; Kitao, Yoshie; Ono, Yutaka; Iijima, Yoshimi; Inada, Toshiya
2003-06-01
It has been suggested that cytochrome P450 2D6 (CYP2D6) is involved in dopamine metabolism within the brain. The dopamine system is suggested to play a role in determining normal character. The purpose of this study was to examine whether character traits are dependent on cytochrome P450 2D6 activity. We investigated the association between temperament and CYP2D6 gene polymorphism. The subjects were all Japanese and the polymorphism genotyped in the present study was CYP2D6*10. Character traits were assessed using the Temperament and Character Inventory. There was no overall or specific association between personality traits and the CYP2D6*10 allele and genotype frequencies. The present results do not support the hypothesis that CYP2D6 activity affects temperament and character.
Pairwise domain adaptation module for CNN-based 2-D/3-D registration.
Zheng, Jiannan; Miao, Shun; Jane Wang, Z; Liao, Rui
2018-04-01
Accurate two-dimensional to three-dimensional (2-D/3-D) registration of preoperative 3-D data and intraoperative 2-D x-ray images is a key enabler for image-guided therapy. Recent advances in 2-D/3-D registration formulate the problem as a learning-based approach and exploit the modeling power of convolutional neural networks (CNN) to significantly improve the accuracy and efficiency of 2-D/3-D registration. However, for surgery-related applications, collecting a large clinical dataset with accurate annotations for training can be very challenging or impractical. Therefore, deep learning-based 2-D/3-D registration methods are often trained with synthetically generated data, and a performance gap is often observed when testing the trained model on clinical data. We propose a pairwise domain adaptation (PDA) module to adapt the model trained on source domain (i.e., synthetic data) to target domain (i.e., clinical data) by learning domain invariant features with only a few paired real and synthetic data. The PDA module is designed to be flexible for different deep learning-based 2-D/3-D registration frameworks, and it can be plugged into any pretrained CNN model such as a simple Batch-Norm layer. The proposed PDA module has been quantitatively evaluated on two clinical applications using different frameworks of deep networks, demonstrating its significant advantages of generalizability and flexibility for 2-D/3-D medical image registration when a small number of paired real-synthetic data can be obtained.
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.
The future of 2D metrology for display manufacturing
NASA Astrophysics Data System (ADS)
Sandstrom, Tor; Wahlsten, Mikael; Park, Youngjin
2016-10-01
The race to 800 PPI and higher in mobile devices and the transition to OLED displays are driving a dramatic development of mask quality: resolution, CDU, registration, and complexity. 2D metrology for large area masks is necessary and must follow the roadmap. Driving forces in the market place point to continued development of even more dense displays. State-of-the-art metrology has proven itself capable of overlay below 40 nm and registration below 65 nm for G6 masks. Future developments include incoming and recurrent measurements of pellicalized masks at the panel maker's factory site. Standardization of coordinate systems across supplier networks is feasible. This will enable better yield and production economy for both mask and panel maker. Better distortion correction methods will give better registration on the panels and relax the flatness requirements of the mask blanks. If panels are measured together with masks and the results are used to characterize the aligners, further quality and yield improvements are possible. Possible future developments include in-cell metrology and integration with other instruments in the same platform.
A 2D Model of Hydraulic Fracturing, Damage and Microseismicity
NASA Astrophysics Data System (ADS)
Wangen, Magnus
2018-03-01
We present a model for hydraulic fracturing and damage of low-permeable rock. It computes the intermittent propagation of rock damage, microseismic event locations, microseismic frequency-magnitude distributions, stimulated rock volume and the injection pressure. The model uses a regular 2D grid and is based on ideas from invasion percolation. All damaged and connected cells during a time step constitute a microseismic event, where the size of the event is the number of cells in the cluster. The magnitude of the event is the log _{10} of the event size. The model produces events with a magnitude-frequency distribution having a b value that is approximately 0.8. The model is studied with respect to the physical parameters: permeability of damaged rock and the rock strength. "High" permeabilities of the damaged rock give the same b value ≈ 0.8, but "moderate" permeabilities give higher b values. Another difference is that "high" permeabilities produce a percolation-like fracture network, while "moderate" permeabilities result in damage zones that expand circularly away from the injection point. In the latter case of "moderate" permeabilities, the injection pressure increases substantially beyond the fracturing level. The rock strength and the time step do not change the observed b value of the model for moderate changes.
Modified Brewster angle on conducting 2D materials
NASA Astrophysics Data System (ADS)
Majérus, Bruno; Cormann, Mirko; Reckinger, Nicolas; Paillet, Matthieu; Henrard, Luc; Lambin, Philippe; Lobet, Michaël
2018-04-01
Insertion of two-dimensional (2D) materials in optical systems modifies their electrodynamical response. In particular, the Brewster angle undergoes an up-shift if a substrate is covered with a conducting 2D material. This work theoretically and experimentally investigates this effect related to the 2D induced current at the interface. The shift is predicted for all conducting 2D materials and tunability with respect to the Fermi level of graphene is evidenced. Analytical approximations for high and low 2D conductivities are proposed and avoid cumbersome numerical analysis of experimental data. Experimental demonstration using spectroscopic ellipsometry has been performed in the UV to NIR range on mono-, bi- and trilayer graphene samples. The non-contact measurement of this modified Brewster angle allows to deduce the optical conductivity of 2D materials. Applications to telecommunication technologies can be considered thanks to the tunability of the shift at 1.55 μm.
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.
Differential cytochrome P450 2D metabolism alters tafenoquine pharmacokinetics.
Vuong, Chau; Xie, Lisa H; Potter, Brittney M J; Zhang, Jing; Zhang, Ping; Duan, Dehui; Nolan, Christina K; Sciotti, Richard J; Zottig, Victor E; Nanayakkara, N P Dhammika; Tekwani, Babu L; Walker, Larry A; Smith, Philip L; Paris, Robert M; Read, Lisa T; Li, Qigui; Pybus, Brandon S; Sousa, Jason C; Reichard, Gregory A; Smith, Bryan; Marcsisin, Sean R
2015-07-01
Cytochrome P450 (CYP) 2D metabolism is required for the liver-stage antimalarial efficacy of the 8-aminoquinoline molecule tafenoquine in mice. This could be problematic for Plasmodium vivax radical cure, as the human CYP 2D ortholog (2D6) is highly polymorphic. Diminished CYP 2D6 enzyme activity, as in the poor-metabolizer phenotype, could compromise radical curative efficacy in humans. Despite the importance of CYP 2D metabolism for tafenoquine liver-stage efficacy, the exact role that CYP 2D metabolism plays in the metabolism and pharmacokinetics of tafenoquine and other 8-aminoquinoline molecules has not been extensively studied. In this study, a series of tafenoquine pharmacokinetic experiments were conducted in mice with different CYP 2D metabolism statuses, including wild-type (WT) (reflecting extensive metabolizers for CYP 2D6 substrates) and CYPmouse 2D knockout (KO) (reflecting poor metabolizers for CYP 2D6 substrates) mice. Plasma and liver pharmacokinetic profiles from a single 20-mg/kg of body weight dose of tafenoquine differed between the strains; however, the differences were less striking than previous results obtained for primaquine in the same model. Additionally, the presence of a 5,6-ortho-quinone tafenoquine metabolite was examined in both mouse strains. The 5,6-ortho-quinone species of tafenoquine was observed, and concentrations of the metabolite were highest in the WT extensive-metabolizer phenotype. Altogether, this study indicates that CYP 2D metabolism in mice affects tafenoquine pharmacokinetics and could have implications for human tafenoquine pharmacokinetics in polymorphic CYP 2D6 human populations. Copyright © 2015, American Society for Microbiology. All Rights Reserved.
Differential Cytochrome P450 2D Metabolism Alters Tafenoquine Pharmacokinetics
Vuong, Chau; Xie, Lisa H.; Potter, Brittney M. J.; Zhang, Jing; Zhang, Ping; Duan, Dehui; Nolan, Christina K.; Sciotti, Richard J.; Zottig, Victor E.; Nanayakkara, N. P. Dhammika; Tekwani, Babu L.; Walker, Larry A.; Smith, Philip L.; Paris, Robert M.; Read, Lisa T.; Li, Qigui; Pybus, Brandon S.; Sousa, Jason C.; Reichard, Gregory A.; Smith, Bryan
2015-01-01
Cytochrome P450 (CYP) 2D metabolism is required for the liver-stage antimalarial efficacy of the 8-aminoquinoline molecule tafenoquine in mice. This could be problematic for Plasmodium vivax radical cure, as the human CYP 2D ortholog (2D6) is highly polymorphic. Diminished CYP 2D6 enzyme activity, as in the poor-metabolizer phenotype, could compromise radical curative efficacy in humans. Despite the importance of CYP 2D metabolism for tafenoquine liver-stage efficacy, the exact role that CYP 2D metabolism plays in the metabolism and pharmacokinetics of tafenoquine and other 8-aminoquinoline molecules has not been extensively studied. In this study, a series of tafenoquine pharmacokinetic experiments were conducted in mice with different CYP 2D metabolism statuses, including wild-type (WT) (reflecting extensive metabolizers for CYP 2D6 substrates) and CYPmouse 2D knockout (KO) (reflecting poor metabolizers for CYP 2D6 substrates) mice. Plasma and liver pharmacokinetic profiles from a single 20-mg/kg of body weight dose of tafenoquine differed between the strains; however, the differences were less striking than previous results obtained for primaquine in the same model. Additionally, the presence of a 5,6-ortho-quinone tafenoquine metabolite was examined in both mouse strains. The 5,6-ortho-quinone species of tafenoquine was observed, and concentrations of the metabolite were highest in the WT extensive-metabolizer phenotype. Altogether, this study indicates that CYP 2D metabolism in mice affects tafenoquine pharmacokinetics and could have implications for human tafenoquine pharmacokinetics in polymorphic CYP 2D6 human populations. PMID:25870069
Buser, Thaddaeus J; Sidlauskas, Brian L; Summers, Adam P
2018-05-01
We contrast 2D vs. 3D landmark-based geometric morphometrics in the fish subfamily Oligocottinae by using 3D landmarks from CT-generated models and comparing the morphospace of the 3D landmarks to one based on 2D landmarks from images. The 2D and 3D shape variables capture common patterns across taxa, such that the pairwise Procrustes distances among taxa correspond and the trends captured by principal component analysis are similar in the xy plane. We use the two sets of landmarks to test several ecomorphological hypotheses from the literature. Both 2D and 3D data reject the hypothesis that head shape correlates significantly with the depth at which a species is commonly found. However, in taxa where shape variation in the z-axis is high, the 2D shape variables show sufficiently strong distortion to influence the outcome of the hypothesis tests regarding the relationship between mouth size and feeding ecology. Only the 3D data support previous studies which showed that large mouth sizes correlate positively with high percentages of elusive prey in the diet. When used to test for morphological divergence, 3D data show no evidence of divergence, while 2D data show that one clade of oligocottines has diverged from all others. This clade shows the greatest degree of z-axis body depth within Oligocottinae, and we conclude that the inability of the 2D approach to capture this lateral body depth causes the incongruence between 2D and 3D analyses. Anat Rec, 301:806-818, 2018. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.
Resilience of networks to environmental stress: From regular to random networks
NASA Astrophysics Data System (ADS)
Eom, Young-Ho
2018-04-01
Despite the huge interest in network resilience to stress, most of the studies have concentrated on internal stress damaging network structure (e.g., node removals). Here we study how networks respond to environmental stress deteriorating their external conditions. We show that, when regular networks gradually disintegrate as environmental stress increases, disordered networks can suddenly collapse at critical stress with hysteresis and vulnerability to perturbations. We demonstrate that this difference results from a trade-off between node resilience and network resilience to environmental stress. The nodes in the disordered networks can suppress their collapses due to the small-world topology of the networks but eventually collapse all together in return. Our findings indicate that some real networks can be highly resilient against environmental stress to a threshold yet extremely vulnerable to the stress above the threshold because of their small-world topology.
NASA Astrophysics Data System (ADS)
Liben-Nowell, David
With the recent explosion of popularity of commercial social-networking sites like Facebook and MySpace, the size of social networks that can be studied scientifically has passed from the scale traditionally studied by sociologists and anthropologists to the scale of networks more typically studied by computer scientists. In this chapter, I will highlight a recent line of computational research into the modeling and analysis of the small-world phenomenon - the observation that typical pairs of people in a social network are connected by very short chains of intermediate friends - and the ability of members of a large social network to collectively find efficient routes to reach individuals in the network. I will survey several recent mathematical models of social networks that account for these phenomena, with an emphasis on both the provable properties of these social-network models and the empirical validation of the models against real large-scale social-network data.
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
NASA Astrophysics Data System (ADS)
Mu, Mulan; Wan, Chaoying; McNally, Tony
2017-12-01
The outstanding thermal conductivity (λ) of graphene and its derivatives offers a potential route to enhance the thermal conductivity of epoxy resins. Key challenges still need to be overcome to ensure effective dispersion and distribution of 2D graphitic fillers throughout the epoxy matrix. 2D filler type, morphology, surface chemistry and dimensions are all important factors in determining filler thermal conductivity and de facto the thermal conductivity of the composite material. To achieve significant enhancement in the thermal conductivity of epoxy composites, different strategies are required to minimise phonon scattering at the interface between the nano-filler and epoxy matrix, including chemical functionalisation of the filler surfaces such that interactions between filler and matrix are promoted and interfacial thermal resistance (ITR) reduced. The combination of graphitic fillers with dimensions on different length scales can potentially form an interconnected multi-dimensional filler network and, thus contribute to enhanced thermal conduction. In this review, we describe the relevant properties of different 2D nano-structured graphitic materials and the factors which determine the translation of the intrinsic thermal conductivity of these 2D materials to epoxy resins. The key challenges and perspectives with regard achieving epoxy composites with significantly enhanced thermal conductivity on addition of 2D graphitic materials are presented.
2-D Path Corrections for Local and Regional Coda Waves: A Test of Transportability
Mayeda, K M; Malagnini, L; Phillips, W S
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 regionsmore » 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
1998-05-01
Mission Research Corporation MRC/WDC-R-424 COMPARISON OF HELIX TWT SIMULATION USING 2-D PIC ( MAGIC ), 2-D MODAL (GATOR), AND 1-D MODAL (CHRISTINE...BRILLOUIN RUN 9 3.4 OUTLIER ELECTRON EFFECT IN GATOR 12 3.5 EMISSION CONDITION AND NONLAMINAR FLOW IN MAGIC 12 3.6 RADIAL SHEAR 13 SECTION 4. PPM B...Simulation using 2-D PIC ( MAGIC ), 2-D Modal (GATOR) and 1-D Modal (CHRISTINE) methods * D.N. Smithe(a), H. Freund(b), T. M. Antonsen Jr.,(b)’(c), E
Graph theoretical analysis of complex networks in the brain
Stam, Cornelis J; Reijneveld, Jaap C
2007-01-01
Since the discovery of small-world and scale-free networks the study of complex systems from a network perspective has taken an enormous flight. In recent years many important properties of complex networks have been delineated. In particular, significant progress has been made in understanding the relationship between the structural properties of networks and the nature of dynamics taking place on these networks. For instance, the 'synchronizability' of complex networks of coupled oscillators can be determined by graph spectral analysis. These developments in the theory of complex networks have inspired new applications in the field of neuroscience. Graph analysis has been used in the study of models of neural networks, anatomical connectivity, and functional connectivity based upon fMRI, EEG and MEG. These studies suggest that the human brain can be modelled as a complex network, and may have a small-world structure both at the level of anatomical as well as functional connectivity. This small-world structure is hypothesized to reflect an optimal situation associated with rapid synchronization and information transfer, minimal wiring costs, as well as a balance between local processing and global integration. The topological structure of functional networks is probably restrained by genetic and anatomical factors, but can be modified during tasks. There is also increasing evidence that various types of brain disease such as Alzheimer's disease, schizophrenia, brain tumours and epilepsy may be associated with deviations of the functional network topology from the optimal small-world pattern. PMID:17908336
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…
2D:4D, Lateralization and Strength in Handball Players
ERIC Educational Resources Information Center
Eler, Nebahat; Eler, Serdar
2018-01-01
Lateralization, which is also known as hand preference, and 2D:4D finger ratio is a sign of prenatal testosterone and known to be associated with strength. The aim of this study is to investigate the relationship between 2D:4D, lateralization and hand grip strength in relation to hand and forearm that are thought to be effective in handball in…
2D Ruddlesden-Popper Perovskites for Optoelectronics.
Chen, Yani; Sun, Yong; Peng, Jiajun; Tang, Junhui; Zheng, Kaibo; Liang, Ziqi
2018-01-01
Conventional 3D organic-inorganic halide perovskites have recently undergone unprecedented rapid development. Yet, their inherent instabilities over moisture, light, and heat remain a crucial challenge prior to the realization of commercialization. By contrast, the emerging 2D Ruddlesden-Popper-type perovskites have recently attracted increasing attention owing to their great environmental stability. However, the research of 2D perovskites is just in their infancy. In comparison to 3D analogues, they are natural quantum wells with a much larger exciton binding energy. Moreover, their inner structural, dielectric, optical, and excitonic properties remain to be largely explored, limiting further applications. This review begins with an introduction to 2D perovskites, along with a detailed comparison to 3D counterparts. Then, a discussion of the organic spacer cation engineering of 2D perovskites is presented. Next, quasi-2D perovskites that fall between 3D and 2D perovskites are reviewed and compared. The unique excitonic properties, electron-phonon coupling, and polarons of 2D perovskites are then be revealed. A range of their (opto)electronic applications is highlighted in each section. Finally, a summary is given, and the strategies toward structural design, growth control, and photophysics studies of 2D perovskites for high-performance electronic devices are rationalized. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
Interactions of DNA coated upconversion nanoparticles with 2D materials
NASA Astrophysics Data System (ADS)
Giust, Davide; Lucío, María. Isabel; Muskens, Otto L.; Kanaras, Antonios G.
2018-02-01
In this work we investigated the nature of quenching between different types of 2D materials (WS2, MoS2 and graphene oxide) and oligonucleotide coated-upconversion nanoparticles. This study contributes towards the efficient design of biosensors based on 2D materials and DNA-coated upconversion nanoparticles.
Simulation of Rio Grande floodplain inundation Using FLO-2D
J. S. O' Brien; W. T. Fullerton
1999-01-01
Spring floodplain inundation is important to the natural functions of the Rio Grande bosque biological community including cottonwood tree germination and recruitment. To predict floodplain inundation, a two-dimensional flood routing model FLO-2D will be applied to various reaches of the Rio Grande. FLO-2D will assess overbank flooding in terms of the area of...
2D nanomaterials assembled from sequence-defined molecules
Mu, Peng; Zhou, Guangwen; Chen, Chun-Long
Two dimensional (2D) nanomaterials have attracted broad interest owing to their unique physical and chemical properties with potential applications in electronics, chemistry, biology, medicine and pharmaceutics. Due to the current limitations of traditional 2D nanomaterials (e.g., graphene and graphene oxide) in tuning surface chemistry and compositions, 2D nanomaterials assembled from sequence-defined molecules (e.g., DNAs, proteins, peptides and peptoids) have recently been developed. They represent an emerging class of 2D nanomaterials with attractive physical and chemical properties. In this mini-review, we summarize the recent progress in the synthesis and applications of this type of sequence-defined 2D nanomaterials. The challenges and opportunitiesmore » in this new field are also discussed.« less
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. Copyright © 2016, American Association for the Advancement of Science.
Plasmonics of 2D Nanomaterials: Properties and Applications
Li, Yu; Li, Ziwei; Chi, Cheng; Shan, Hangyong; Zheng, Liheng
2017-01-01
Plasmonics has developed for decades in the field of condensed matter physics and optics. Based on the classical Maxwell theory, collective excitations exhibit profound light‐matter interaction properties beyond classical physics in lots of material systems. With the development of nanofabrication and characterization technology, ultra‐thin two‐dimensional (2D) nanomaterials attract tremendous interest and show exceptional plasmonic properties. Here, we elaborate the advanced optical properties of 2D materials especially graphene and monolayer molybdenum disulfide (MoS2), review the plasmonic properties of graphene, and discuss the coupling effect in hybrid 2D nanomaterials. Then, the plasmonic tuning methods of 2D nanomaterials are presented from theoretical models to experimental investigations. Furthermore, we reveal the potential applications in photocatalysis, photovoltaics and photodetections, based on the development of 2D nanomaterials, we make a prospect for the future theoretical physics and practical applications. PMID:28852608
Synthesis and chemistry of elemental 2D materials
Mannix, Andrew J.; Kiraly, Brian; Hersam, Mark C.
2017-01-25
2D materials have attracted considerable attention in the past decade for their superlative physical properties. These materials consist of atomically thin sheets exhibiting covalent in-plane bonding and weak interlayer and layer-substrate bonding. Following the example of graphene, most emerging 2D materials are derived from structures that can be isolated from bulk phases of layered materials, which form a limited library for new materials discovery. Entirely synthetic 2D materials provide access to a greater range of properties through the choice of constituent elements and substrates. Of particular interest are elemental 2D materials, because they provide the most chemically tractable case formore » synthetic exploration. In this Review, we explore the progress made in the synthesis and chemistry of synthetic elemental 2D materials, and offer perspectives and challenges for the future of this emerging field.« less
2D nanomaterials assembled from sequence-defined molecules
Mu, Peng; Zhou, Guangwen; Chen, Chun-Long
2017-10-21
Two dimensional (2D) nanomaterials have attracted broad interest owing to their unique physical and chemical properties with potential applications in electronics, chemistry, biology, medicine and pharmaceutics. Due to the current limitations of traditional 2D nanomaterials (e.g., graphene and graphene oxide) in tuning surface chemistry and compositions, 2D nanomaterials assembled from sequence-defined molecules (e.g., DNAs, proteins, peptides and peptoids) have recently been developed. They represent an emerging class of 2D nanomaterials with attractive physical and chemical properties. Here, we summarize the recent progress in the synthesis and applications of this type of sequence-defined 2D nanomaterials. We also discuss the challenges andmore » opportunities in this new field.« less
2D nanomaterials assembled from sequence-defined molecules
Mu, Peng; Zhou, Guangwen; Chen, Chun-Long
Two dimensional (2D) nanomaterials have attracted broad interest owing to their unique physical and chemical properties with potential applications in electronics, chemistry, biology, medicine and pharmaceutics. Due to the current limitations of traditional 2D nanomaterials (e.g., graphene and graphene oxide) in tuning surface chemistry and compositions, 2D nanomaterials assembled from sequence-defined molecules (e.g., DNAs, proteins, peptides and peptoids) have recently been developed. They represent an emerging class of 2D nanomaterials with attractive physical and chemical properties. Here, we summarize the recent progress in the synthesis and applications of this type of sequence-defined 2D nanomaterials. We also discuss the challenges andmore » opportunities in this new field.« less
ERIC Educational Resources Information Center
Maughan, George R.; Petitto, Karen R.; McLaughlin, Don
2001-01-01
Describes the connectivity features and options of modern campus communication and information system networks, including signal transmission (wire-based and wireless), signal switching, convergence of networks, and network assessment variables, to enable campus leaders to make sound future-oriented decisions. (EV)
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.
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.
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.
From 3 d duality to 2 d duality
NASA Astrophysics Data System (ADS)
Aharony, Ofer; Razamat, Shlomo S.; Willett, Brian
2017-11-01
In this paper we discuss 3 d N = 2 supersymmetric gauge theories and their IR dualities when they are compactified on a circle of radius r, and when we take the 2 d limit in which r → 0. The 2 d limit depends on how the mass parameters are scaled as r → 0, and often vacua become infinitely distant in the 2 d limit, leading to a direct sum of different 2 d theories. For generic mass parameters, when we take the same limit on both sides of a duality, we obtain 2 d dualities (between gauge theories and/or Landau-Ginzburg theories) that pass all the usual tests. However, when there are non-compact branches the discussion is subtle because the metric on the moduli space, which is not controlled by supersymmetry, plays an important role in the low-energy dynamics after compactification. Generally speaking, for IR dualities of gauge theories, we conjecture that dualities involving non-compact Higgs branches survive. On the other hand when there is a non-compact Coulomb branch on at least one side of the duality, the duality fails already when the 3 d theories are compactified on a circle. Using the valid reductions we reproduce many known 2 d IR dualities, giving further evidence for their validity, and we also find new 2 d dualities.
Decoding 2D-PAGE complex maps: relevance to proteomics.
Pietrogrande, Maria Chiara; Marchetti, Nicola; Dondi, Francesco; Righetti, Pier Giorgio
2006-03-20
This review describes two mathematical approaches useful for decoding the complex signal of 2D-PAGE maps of protein mixtures. These methods are helpful for interpreting the large amount of data of each 2D-PAGE map by extracting all the analytical information hidden therein by spot overlapping. Here the basic theory and application to 2D-PAGE maps are reviewed: the means for extracting information from the experimental data and their relevance to proteomics are discussed. One method is based on the quantitative theory of statistical model of peak overlapping (SMO) using the spot experimental data (intensity and spatial coordinates). The second method is based on the study of the 2D-autocovariance function (2D-ACVF) computed on the experimental digitised map. They are two independent methods that are able to extract equal and complementary information from the 2D-PAGE map. Both methods permit to obtain fundamental information on the sample complexity and the separation performance and to single out ordered patterns present in spot positions: the availability of two independent procedures to compute the same separation parameters is a powerful tool to estimate the reliability of the obtained results. The SMO procedure is an unique tool to quantitatively estimate the degree of spot overlapping present in the map, while the 2D-ACVF method is particularly powerful in simply singling out the presence of order in the spot position from the complexity of the whole 2D map, i.e., spot trains. The procedures were validated by extensive numerical computation on computer-generated maps describing experimental 2D-PAGE gels of protein mixtures. Their applicability to real samples was tested on reference maps obtained from literature sources. The review describes the most relevant information for proteomics: sample complexity, separation performance, overlapping extent, identification of spot trains related to post-translational modifications (PTMs).
Wearable energy sources based on 2D materials.
Yi, Fang; Ren, Huaying; Shan, Jingyuan; Sun, Xiao; Wei, Di; Liu, Zhongfan
2018-05-08
Wearable energy sources are in urgent demand due to the rapid development of wearable electronics. Besides flexibility and ultrathin thickness, emerging 2D materials present certain extraordinary properties that surpass the properties of conventional materials, which make them advantageous for high-performance wearable energy sources. Here, we provide a comprehensive review of recent advances in 2D material based wearable energy sources including wearable batteries, supercapacitors, and different types of energy harvesters. The crucial roles of 2D materials in the wearable energy sources are highlighted. Based on the current progress, the existing challenges and future prospects are outlined and discussed.
Recent advances in 2D materials for photocatalysis.
Luo, Bin; Liu, Gang; Wang, Lianzhou
2016-04-07
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.
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. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
2D constant-loss taper for mode conversion
NASA Astrophysics Data System (ADS)
Horth, Alexandre; Kashyap, Raman; Quitoriano, Nathaniel J.
2015-03-01
Proposed in this manuscript is a novel taper geometry, the constant-loss taper (CLT). This geometry is derived with 1D slabs of silicon embedded in silicon dioxide using coupled-mode theory (CMT). The efficiency of the CLT is compared to both linear and parabolic tapers using CMT and 2D finite-difference time-domain simulations. It is shown that over a short 2D, 4.45 μm long taper the CLT's mode conversion efficiency is ~90% which is 10% and 18% more efficient than a 2D parabolic or linear taper, respectively.
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.
CC2D1A and CC2D1B regulate degradation and signaling of EGFR and TLR4.
Deshar, Rakesh; Cho, Eun-Bee; Yoon, Sungjoo Kim; Yoon, Jong-Bok
2016-11-11
Signaling through many transmembrane receptors is terminated by their sorting to the intraluminal vesicles (ILVs) of multivescular bodies (MVBs) and subsequent lysosomal degradation. ILV formation requires the endosomal sorting complex required for transport (ESCRT) machinery. CC2D1A and CC2D1B interact with the CHMP4 family of proteins, the major subunit of the ESCRT-III complex, however, their roles in receptor degradation and signaling are poorly defined. Here, we report that CC2D1A binds to CHMP4B polymers formed on endosomes to regulate the endosomal sorting pathway. We show that depletion of CC2D1A and B accelerates degradation of EGFR and elicits rapid termination of its downstream signaling through ERK1 and 2. Depletion of CC2D1A and B promotes sorting of EGFR to ILV leading to its rapid lysosomal degradation. In addition, we show that knockdown of CC2D1A and B has similar effects on degradation and downstream signaling of another membrane receptor, TLR4. Thus, these findings suggest that CC2D1A and B may have broad effects on transmembrane receptors by preventing premature ILV sorting and termination of signaling. Copyright © 2016 Elsevier Inc. All rights reserved.
Recovering 3D particle size distributions from 2D sections
NASA Astrophysics Data System (ADS)
Cuzzi, Jeffrey N.; Olson, Daniel M.
2017-03-01
We discuss different ways to convert observed, apparent particle size distributions from 2D sections (thin sections, SEM maps on planar surfaces, etc.) into true 3D particle size distributions. We give a simple, flexible, and practical method to do this; show which of these techniques gives the most faithful conversions; and provide (online) short computer codes to calculate both 2D-3D recoveries and simulations of 2D observations by random sectioning. The most important systematic bias of 2D sectioning, from the standpoint of most chondrite studies, is an overestimate of the abundance of the larger particles. We show that fairly good recoveries can be achieved from observed size distributions containing 100-300 individual measurements of apparent particle diameter.
Soluble NKG2D ligands: prevalence, release, and functional impact.
Salih, Helmut Rainer; Holdenrieder, Stefan; Steinle, Alexander
2008-05-01
Natural Killer (NK) cells are capable to recognize and eliminate malignant cells. Anti-tumor responses of NK cells are promoted by the tumor-associated expression of cell stress-inducible ligands of the activating NK receptor NKG2D. Current evidence suggests that established tumors subvert NKG2D-mediated tumor immunosurveillance by releasing NKG2D ligands (NKG2DL). Release of NKG2DL has been observed in a broad variety of human tumor entities and is thought to interfere with NKG2D-mediated tumor immunity in several ways. Further, levels of soluble NKG2DL (sNKG2DL) were also found to be elevated under various non-malignant conditions, although the functional implications remain largely unclear. Here we review and discuss the available data on the prevalence, release, functional impact, and potential clinical value of sNKG2DL.
Excitons in atomically thin 2D semiconductors and their applications
Xiao, Jun; Zhao, Mervin; Wang, Yuan; ...
2017-01-01
The research on emerging layered two-dimensional (2D) semiconductors, such as molybdenum disulfide (MoS 2), reveals unique optical properties generating significant interest. Experimentally, these materials were observed to host extremely strong light-matter interactions as a result of the enhanced excitonic effect in two dimensions. Thus, understanding and manipulating the excitons are crucial to unlocking the potential of 2D materials for future photonic and optoelectronic devices. Here in this review, we unravel the physical origin of the strong excitonic effect and unique optical selection rules in 2D semiconductors. In addition, control of these excitons by optical, electrical, as well as mechanical meansmore » is examined. Finally, the resultant devices such as excitonic light emitting diodes, lasers, optical modulators, and coupling in an optical cavity are overviewed, demonstrating how excitons can shape future 2D optoelectronics.« less
Vortex unbinding in 2D classical JJ arrays
Minnhagen, Petter
1998-05-15
Vortices for 2D superfluids are introduced and are described in terms of a 2D Coulomb gas. The 2D classical JJ array is modeled by a 2D XY-model and a mapping between the XY-model and the Coulomb gas is given. The physical properties of a JJ array are then given in terms of the corresponding Coulomb gas properties. First aspects of the Kosterlitz-Thouless vortex unbinding transitions are reviewed. Consequences for the resistance as well as the frequency dependent conductivity are described. Next the vortex unbinding induced by an external current is considered with Consequencies for the non-linear IV-characteristics. Finally some somemore » effects of a perpendicular magnetic field are discussed in terms of an interplay between free vortices and bound vortex pairs.« less
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.
32 CFR 1639.4 - Exclusion from Class 2-D.
Code of Federal Regulations, 2010 CFR
2010-07-01
... recognized; or (c) He ceases to be a full-time student; or (d) He fails to maintain satisfactory academic... Class 2-D when: (a) He fails to establish that the theological or divinity school is a recognized school...
2. D Street facade and rear (east) blank wall of ...
2. D Street facade and rear (east) blank wall of parking garage. Farther east is 408 8th Street (National Art And Frame Company). - PMI Parking Garage, 403-407 Ninth Street, Northwest, Washington, District of Columbia, DC
Optical identification using imperfections in 2D materials
NASA Astrophysics Data System (ADS)
Cao, Yameng; Robson, Alexander J.; Alharbi, Abdullah; Roberts, Jonathan; Woodhead, Christopher S.; Noori, Yasir J.; Bernardo-Gavito, Ramón; Shahrjerdi, Davood; Roedig, Utz; Fal'ko, Vladimir I.; Young, Robert J.
2017-12-01
The ability to uniquely identify an object or device is important for authentication. Imperfections, locked into structures during fabrication, can be used to provide a fingerprint that is challenging to reproduce. In this paper, we propose a simple optical technique to read unique information from nanometer-scale defects in 2D materials. Imperfections created during crystal growth or fabrication lead to spatial variations in the bandgap of 2D materials that can be characterized through photoluminescence measurements. We show a simple setup involving an angle-adjustable transmission filter, simple optics and a CCD camera can capture spatially-dependent photoluminescence to produce complex maps of unique information from 2D monolayers. Atomic force microscopy is used to verify the origin of the optical signature measured, demonstrating that it results from nanometer-scale imperfections. This solution to optical identification with 2D materials could be employed as a robust security measure to prevent counterfeiting.
Phonon thermal conduction in novel 2D materials.
Xu, Xiangfan; Chen, Jie; Li, Baowen
2016-12-07
Recently, there has been increasing interest in phonon thermal transport in low-dimensional materials, due to the crucial importance of dissipating and managing heat in micro- and nano-electronic devices. Significant progress has been achieved for one-dimensional (1D) systems, both theoretically and experimentally. However, the study of heat conduction in two-dimensional (2D) systems is still in its infancy due to the limited availability of 2D materials and the technical challenges of fabricating suspended samples that are suitable for thermal measurements. In this review, we outline different experimental techniques and theoretical approaches for phonon thermal transport in 2D materials, discuss the problems and challenges of phonon thermal transport measurements and provide a comparison between existing experimental data. Special attention will be given to the effects of size, dimensionality, anisotropy and mode contributions in novel 2D systems, including graphene, boron nitride, MoS 2 , black phosphorous and silicene.
Studying Zeolite Catalysts with a 2D Model System
Boscoboinik, Anibal
2016-12-07
Anibal Boscoboinik, a materials scientist at Brookhaven’s Center for Functional Nanomaterials, discusses the surface-science tools and 2D model system he uses to study catalysis in nanoporous zeolites, which catalyze reactions in many industrial processes.
Negative terahertz photoconductivity in 2D layered materials.
Lu, Junpeng; Liu, Hongwei; Sun, Jing
2017-11-17
The remarkable qualities of 2D layered materials such as wide spectral coverage, high strength and great flexibility mean that ultrathin 2D layered materials have the potential to meet the criteria of next-generation optoelectronic devices. Photoconductivity is one of the critical parameters of materials applied to optoelectronics. In contrast to traditional semiconductors, specific ultrathin 2D layers present anomalous negative photoconductivity. This opens a new avenue for designing novel optoelectronic devices. It is important to have a deep understanding of the fundamentals of this anomalous response, in order to design and optimize such devices. In this review, we provide an overview of the observation of negative photoconductivity in 2D layered materials including graphene, topological insulators and transitional metal dichalcogenides. We also summarize recent reports on investigations into the fundamental mechanism using ultrafast terahertz (THz) spectroscopies. Finally, we conclude the review by discussing the existing challenges and proposing the possible prospects of this direction of research.
Excitons in atomically thin 2D semiconductors and their applications
NASA Astrophysics Data System (ADS)
Xiao, Jun; Zhao, Mervin; Wang, Yuan; Zhang, Xiang
2017-06-01
The research on emerging layered two-dimensional (2D) semiconductors, such as molybdenum disulfide (MoS2), reveals unique optical properties generating significant interest. Experimentally, these materials were observed to host extremely strong light-matter interactions as a result of the enhanced excitonic effect in two dimensions. Thus, understanding and manipulating the excitons are crucial to unlocking the potential of 2D materials for future photonic and optoelectronic devices. In this review, we unravel the physical origin of the strong excitonic effect and unique optical selection rules in 2D semiconductors. In addition, control of these excitons by optical, electrical, as well as mechanical means is examined. Finally, the resultant devices such as excitonic light emitting diodes, lasers, optical modulators, and coupling in an optical cavity are overviewed, demonstrating how excitons can shape future 2D optoelectronics.
Photonics of 2D gold nanolayers on sapphire surface
Muslimov, A. E., E-mail: amuslimov@mail.ru; Butashin, A. V.; Nabatov, B. V.
Gold layers with thicknesses of up to several nanometers, including ordered and disordered 2D nanostructures of gold particles, have been formed on sapphire substrates; their morphology is described; and optical investigations are carried out. The possibility of increasing the accuracy of predicting the optical properties of gold layers and 2D nanostructures using quantum-mechanical models based on functional density theory calculation techniques is considered. The application potential of the obtained materials in photonics is estimated.
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.
CYP2D6 variability in populations from Venezuela.
Moreno, Nancy; Flores-Angulo, Carlos; Villegas, Cecilia; Mora, Yuselin
2016-12-01
CYP2D6 is an important cytochrome P450 enzyme that plays an important role in the metabolism of about 25% of currently prescribed drugs. The presence of polymorphisms in the CYP2D6 gene may modulate enzyme level and activity, thereby affecting individual responses to pharmacological treatments. The most prevalent diseases in the admixed population from Venezuela are cardiovascular and cancer, whereas viral, bacterial and parasitic diseases, particularly malaria, are prevalent in Amerindian populations; in the treatment of these diseases, several drugs that are metabolized by CYP2D6 are used. In this work, we reviewed the data on CYP2D6 variability and predicted metabolizer phenotypes, in healthy volunteers of two admixed and five Amerindian populations from Venezuela. The Venezuelan population is very heterogeneous as a result of the genetic admixture of three major ethnical components: Europeans, Africans and Amerindians. There are noticeable inter-regional and inter-population differences in the process of mixing of this population. Hitherto, there are few published studies in Venezuela on CYP2D6; therefore, it is necessary to increase research in this regard, in particular to develop studies with a larger sample size. There is a considerable amount of work remaining before CYP2D6 is integrated into clinical practice in Venezuela.
A 2D spiral turbo-spin-echo technique.
Li, Zhiqiang; Karis, John P; Pipe, James G
2018-03-09
2D turbo-spin-echo (TSE) is widely used in the clinic for neuroimaging. However, the long refocusing radiofrequency pulse train leads to high specific absorption rate (SAR) and alters the contrast compared to conventional spin-echo. The purpose of this work is to develop a robust 2D spiral TSE technique for fast T 2 -weighted imaging with low SAR and improved contrast. A spiral-in/out readout is incorporated into 2D TSE to fully take advantage of the acquisition efficiency of spiral sampling while avoiding potential off-resonance-related artifacts compared to a typical spiral-out readout. A double encoding strategy and a signal demodulation method are proposed to mitigate the artifacts because of the T 2 -decay-induced signal variation. An adapted prescan phase correction as well as a concomitant phase compensation technique are implemented to minimize the phase errors. Phantom data demonstrate the efficacy of the proposed double encoding/signal demodulation, as well as the prescan phase correction and concomitant phase compensation. Volunteer data show that the proposed 2D spiral TSE achieves fast scan speed with high SNR, low SAR, and improved contrast compared to conventional Cartesian TSE. A robust 2D spiral TSE technique is feasible and provides a potential alternative to conventional 2D Cartesian TSE for T 2 -weighted neuroimaging. © 2018 International Society for Magnetic Resonance in Medicine.
Dirac Magnon Nodal Loops in Quasi-2D Quantum Magnets.
Owerre, S A
2017-07-31
In this report, we propose a new concept of one-dimensional (1D) closed lines of Dirac magnon nodes in two-dimensional (2D) momentum space of quasi-2D quantum magnetic systems. They are termed "2D Dirac magnon nodal-line loops". We utilize the bilayer honeycomb ferromagnets with intralayer coupling J and interlayer coupling J L , which is realizable in the honeycomb chromium compounds CrX 3 (X ≡ Br, Cl, and I). However, our results can also exist in other layered quasi-2D quantum magnetic systems. Here, we show that the magnon bands of the bilayer honeycomb ferromagnets overlap for J L ≠ 0 and form 1D closed lines of Dirac magnon nodes in 2D momentum space. The 2D Dirac magnon nodal-line loops are topologically protected by inversion and time-reversal symmetry. Furthermore, we show that they are robust against weak Dzyaloshinskii-Moriya interaction Δ DM < J L and possess chiral magnon edge modes.
Borophene as a prototype for synthetic 2D materials development
NASA Astrophysics Data System (ADS)
Mannix, Andrew J.; Zhang, Zhuhua; Guisinger, Nathan P.; Yakobson, Boris I.; Hersam, Mark C.
2018-06-01
The synthesis of 2D materials with no analogous bulk layered allotropes promises a substantial breadth of physical and chemical properties through the diverse structural options afforded by substrate-dependent epitaxy. However, despite the joint theoretical and experimental efforts to guide materials discovery, successful demonstrations of synthetic 2D materials have been rare. The recent synthesis of 2D boron polymorphs (that is, borophene) provides a notable example of such success. In this Perspective, we discuss recent progress and future opportunities for borophene research. Borophene combines unique mechanical properties with anisotropic metallicity, which complements the canon of conventional 2D materials. The multi-centre characteristics of boron-boron bonding lead to the formation of configurationally varied, vacancy-mediated structural motifs, providing unprecedented diversity in a mono-elemental 2D system with potential for electronic applications, chemical functionalization, materials synthesis and complex heterostructures. With its foundations in computationally guided synthesis, borophene can serve as a prototype for ongoing efforts to discover and exploit synthetic 2D materials.
2D Ruddlesden-Popper Perovskites Microring Laser Array.
Zhang, Haihua; Liao, Qing; Wu, Yishi; Zhang, Zhaoyi; Gao, Qinggang; Liu, Peng; Li, Meili; Yao, Jiannian; Fu, Hongbing
2018-04-01
3D organic-inorganic hybrid perovskites have featured high gain coefficients through the electron-hole plasma stimulated emission mechanism, while their 2D counterparts of Ruddlesden-Popper perovskites (RPPs) exhibit strongly bound electron-hole pairs (excitons) at room temperature. High-performance solar cells and light-emitting diodes (LEDs) are reported based on 2D RPPs, whereas light-amplification devices remain largely unexplored. Here, it is demonstrated that ultrafast energy transfer along cascade quantum well (QW) structures in 2D RPPs concentrates photogenerated carriers on the lowest-bandgap QW state, at which population inversion can be readily established enabling room-temperature amplified spontaneous emission and lasing. Gain coefficients measured for 2D RPP thin-films (≈100 nm in thickness) are found about at least four times larger than those for their 3D counterparts. High-density large-area microring arrays of 2D RPPs are fabricated as whispering-gallery-mode lasers, which exhibit high quality factor (Q ≈ 2600), identical optical modes, and similarly low lasing thresholds, allowing them to be ignited simultaneously as a laser array. The findings reveal that 2D RPPs are excellent solution-processed gain materials potentially for achieving electrically driven lasers and ideally for on-chip integration of nanophotonics. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
Borophene as a prototype for synthetic 2D materials development.
Mannix, Andrew J; Zhang, Zhuhua; Guisinger, Nathan P; Yakobson, Boris I; Hersam, Mark C
2018-06-01
The synthesis of 2D materials with no analogous bulk layered allotropes promises a substantial breadth of physical and chemical properties through the diverse structural options afforded by substrate-dependent epitaxy. However, despite the joint theoretical and experimental efforts to guide materials discovery, successful demonstrations of synthetic 2D materials have been rare. The recent synthesis of 2D boron polymorphs (that is, borophene) provides a notable example of such success. In this Perspective, we discuss recent progress and future opportunities for borophene research. Borophene combines unique mechanical properties with anisotropic metallicity, which complements the canon of conventional 2D materials. The multi-centre characteristics of boron-boron bonding lead to the formation of configurationally varied, vacancy-mediated structural motifs, providing unprecedented diversity in a mono-elemental 2D system with potential for electronic applications, chemical functionalization, materials synthesis and complex heterostructures. With its foundations in computationally guided synthesis, borophene can serve as a prototype for ongoing efforts to discover and exploit synthetic 2D materials.
Boundary element method for 2D materials and thin films.
Hrtoň, M; Křápek, V; Šikola, T
2017-10-02
2D materials emerge as a viable platform for the control of light at the nanoscale. In this context the need has arisen for a fast and reliable tool capable of capturing their strictly 2D nature in 3D light scattering simulations. So far, 2D materials and their patterned structures (ribbons, discs, etc.) have been mostly treated as very thin films of subnanometer thickness with an effective dielectric function derived from their 2D optical conductivity. In this study an extension to the existing framework of the boundary element method (BEM) with 2D materials treated as a conductive interface between two media is presented. The testing of our enhanced method on problems with known analytical solutions reveals that for certain types of tasks the new modification is faster than the original BEM algorithm. Furthermore, the representation of 2D materials as an interface allows us to simulate problems in which their optical properties depend on spatial coordinates. Such spatial dependence can occur naturally or can be tailored artificially to attain new functional properties.
NASA Astrophysics Data System (ADS)
Harman, Philip V.; Flack, Julien; Fox, Simon; Dowley, Mark
2002-05-01
The conversion of existing 2D images to 3D is proving commercially viable and fulfills the growing need for high quality stereoscopic images. This approach is particularly effective when creating content for the new generation of autostereoscopic displays that require multiple stereo images. The dominant technique for such content conversion is to develop a depth map for each frame of 2D material. The use of a depth map as part of the 2D to 3D conversion process has a number of desirable characteristics: 1. The resolution of the depth may be lower than that of the associated 2D image. 2. It can be highly compressed. 3. 2D compatibility is maintained. 4. Real time generation of stereo, or multiple stereo pairs, is possible. The main disadvantage has been the laborious nature of the manual conversion techniques used to create depth maps from existing 2D images, which results in a slow and costly process. An alternative, highly productive technique has been developed based upon the use of Machine Leaning Algorithm (MLAs). This paper describes the application of MLAs to the generation of depth maps and presents the results of the commercial application of this approach.
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.
Spatially Controlled Noncovalent Functionalization of 2D Materials Based on Molecular Architecture.
Bang, Jae Jin; Porter, Ashlin G; Davis, Tyson C; Hayes, Tyler R; Claridge, Shelley A
2018-05-15
Polymerizable amphiphiles can be assembled into lying-down phases on 2D materials such as graphite and graphene to create chemically orthogonal surface patterns at 5-10 nm scales, locally modulating functionality of the 2D basal plane. Functionalization can be carried out through Langmuir-Schaefer conversion, in which a subset of molecules is transferred out of a standing phase film on water onto the 2D substrate. Here, we leverage differences in molecular structure to spatially control transfer at both nanoscopic and microscopic scales. We compare transfer properties of five different single- and dual-chain amphiphiles, demonstrating that those with strong lateral interactions (e.g., hydrogen-bonding networks) exhibit the lowest transfer efficiencies. Since molecular structures also influence microscopic domain morphologies in Langmuir films, we show that it is possible to transfer such microscale patterns, taking advantage of variations in the local transfer rates based on the structural heterogeneity in Langmuir films. Nanoscale domain morphologies also vary in ways that are consistent with predicted relative transfer and diffusion rates. These results suggest strategies to tailor noncovalent functionalization of 2D substrates through controlled LS transfer.
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
2D Hexagonal Boron Nitride (2D-hBN) Explored for the Electrochemical Sensing of Dopamine.
Khan, Aamar F; Brownson, Dale A C; Randviir, Edward P; Smith, Graham C; Banks, Craig E
2016-10-04
Crystalline 2D hexagonal boron nitride (2D-hBN) nanosheets are explored as a potential electrocatalyst toward the electroanalytical sensing of dopamine (DA). The 2D-hBN nanosheets are electrically wired via a drop-casting modification process onto a range of commercially available carbon supporting electrodes, including glassy carbon (GC), boron-doped diamond (BDD), and screen-printed graphitic electrodes (SPEs). 2D-hBN has not previously been explored toward the electrochemical detection/electrochemical sensing of DA. We critically evaluate the potential electrocatalytic performance of 2D-hBN modified electrodes, the effect of supporting carbon electrode platforms, and the effect of "mass coverage" (which is commonly neglected in the 2D material literature) toward the detection of DA. The response of 2D-hBN modified electrodes is found to be largely dependent upon the interaction between 2D-hBN and the underlying supporting electrode material. For example, in the case of SPEs, modification with 2D-hBN (324 ng) improves the electrochemical response, decreasing the electrochemical oxidation potential of DA by ∼90 mV compared to an unmodified SPE. Conversely, modification of a GC electrode with 2D-hBN (324 ng) resulted in an increased oxidation potential of DA by ∼80 mV when compared to the unmodified electrode. We explore the underlying mechanisms of the aforementioned examples and infer that electrode surface interactions and roughness factors are critical considerations. 2D-hBN is utilized toward the sensing of DA in the presence of the common interferents ascorbic acid (AA) and uric acid (UA). 2D-hBN is found to be an effective electrocatalyst in the simultaneous detection of DA and UA at both pH 5.0 and 7.4. The peak separations/resolution between DA and UA increases by ∼70 and 50 mV (at pH 5.0 and 7.4, respectively, when utilizing 108 ng of 2D-hBN) compared to unmodified SPEs, with a particularly favorable response evident in pH 5.0, giving rise to a
Digit ratio (2D:4D) and postoperative pain perception.
Kasielska-Trojan, Anna; Stabryła, Piotr; Antoszewski, Bogusław
2017-07-01
It has not been established whether sex differences in pain perception are influenced by prenatal sex hormones. Digit ratio as an indicator of prenatal hormone exposure can be used as a simple measure of the influence of prenatal hormones on pain sensitivity or perception in adulthood. The aim of this study was to determine a correlation between the 2D:4D ratio and pain perception in the postoperative period after rhinoplasty. A prospective cohort study of 100 patients (50 women of the mean age of 30.74±8.09years and 50 men of the mean age of 30.98±10.86years) who underwent posttraumatic rhinoplasty due to the nose trauma in Plastic, Reconstructive and Aesthetic Surgery Clinic. The following measurements were taken the day before a surgery: body height, waist and hip circumference, II and IV digits' lengths and body weight. All subjects filled in a questionnaire including 0-10-point VAS scales to assess postoperative pain 1h after an operation (AO), 6h AO, 12h AO, 24h AO and 48h AO. Women with low 2D:4D reported significantly more pain 1h after an operation than women with high 2D:4D. Similar correlation was observed for low 2D:4D in women 48h AO. In men, low 2D:4D was associated with lower postoperative pain 12h AO (p=0.029). In conclusion, we showed that low 2D:4D in women was associated with high postoperative pain, and low right 2D:4D in men was associated with low postoperative pain. This may suggest that intrauterine estrogen exposure makes women more resistant to pain. Copyright © 2017 Elsevier B.V. All rights reserved.
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.
Recent mathematical developments in 2D correlation spectroscopy
NASA Astrophysics Data System (ADS)
Noda, I.
2000-03-01
Recent mathematical developments in the field of 2D correlation spectroscopy, especially those related to the statistical theory, are reported. The notion of correlation phase angle is introduced. The significance of correlation phase angle between dynamic fluctuations of signals measured at two different spectral variables may be linked to more commonly known statistical concepts, such as coherence and correlation coefficient. This treatment provides the direct mathematical connection between the synchronous 2D correlation spectrum with a continuous form of the variance-covariance matrix. Moreover, it gives the background for the formal definition of the disrelation spectrum, which may be used as a heuristic substitution for the asynchronous 2D spectrum. The 2D correlation intensity may be separated into two independent factors representing the normalized extent of signal fluctuation coherence (i.e., correlation coefficient) and the magnitude of spectral intensity changes (i.e., variance). Such separation offers a convenient way to artificially enhance the discriminating power of 2D correlation spectra.
Mermin-Wagner fluctuations in 2D amorphous solids.
Illing, Bernd; Fritschi, Sebastian; Kaiser, Herbert; Klix, Christian L; Maret, Georg; Keim, Peter
2017-02-21
In a recent commentary, J. M. Kosterlitz described how D. Thouless and he got motivated to investigate melting and suprafluidity in two dimensions [Kosterlitz JM (2016) J Phys Condens Matter 28:481001]. It was due to the lack of broken translational symmetry in two dimensions-doubting the existence of 2D crystals-and the first computer simulations foretelling 2D crystals (at least in tiny systems). The lack of broken symmetries proposed by D. Mermin and H. Wagner is caused by long wavelength density fluctuations. Those fluctuations do not only have structural impact, but additionally a dynamical one: They cause the Lindemann criterion to fail in 2D in the sense that the mean squared displacement of atoms is not limited. Comparing experimental data from 3D and 2D amorphous solids with 2D crystals, we disentangle Mermin-Wagner fluctuations from glassy structural relaxations. Furthermore, we demonstrate with computer simulations the logarithmic increase of displacements with system size: Periodicity is not a requirement for Mermin-Wagner fluctuations, which conserve the homogeneity of space on long scales.
Mermin-Wagner fluctuations in 2D amorphous solids
NASA Astrophysics Data System (ADS)
Illing, Bernd; Fritschi, Sebastian; Kaiser, Herbert; Klix, Christian L.; Maret, Georg; Keim, Peter
2017-02-01
In a recent commentary, J. M. Kosterlitz described how D. Thouless and he got motivated to investigate melting and suprafluidity in two dimensions [Kosterlitz JM (2016) J Phys Condens Matter 28:481001]. It was due to the lack of broken translational symmetry in two dimensions—doubting the existence of 2D crystals—and the first computer simulations foretelling 2D crystals (at least in tiny systems). The lack of broken symmetries proposed by D. Mermin and H. Wagner is caused by long wavelength density fluctuations. Those fluctuations do not only have structural impact, but additionally a dynamical one: They cause the Lindemann criterion to fail in 2D in the sense that the mean squared displacement of atoms is not limited. Comparing experimental data from 3D and 2D amorphous solids with 2D crystals, we disentangle Mermin-Wagner fluctuations from glassy structural relaxations. Furthermore, we demonstrate with computer simulations the logarithmic increase of displacements with system size: Periodicity is not a requirement for Mermin-Wagner fluctuations, which conserve the homogeneity of space on long scales.
2-D Clinostat for Simulated Microgravity Experiments with Arabidopsis Seedlings
NASA Astrophysics Data System (ADS)
Wang, Hui; Li, Xugang; Krause, Lars; Görög, Mark; Schüler, Oliver; Hauslage, Jens; Hemmersbach, Ruth; Kircher, Stefan; Lasok, Hanna; Haser, Thomas; Rapp, Katja; Schmidt, Jürgen; Yu, Xin; Pasternak, Taras; Aubry-Hivet, Dorothée; Tietz, Olaf; Dovzhenko, Alexander; Palme, Klaus; Ditengou, Franck Anicet
2016-04-01
Ground-based simulators of microgravity such as fast rotating 2-D clinostats are valuable tools to study gravity related processes. We describe here a versatile g-value-adjustable 2-D clinostat that is suitable for plant analysis. To avoid seedling adaptation to 1 g after clinorotation, we designed chambers that allow rapid fixation. A detailed protocol for fixation, RNA isolation and the analysis of selected genes is described. Using this clinostat we show that mRNA levels of LONG HYPOCOTYL 5 (HY5), MIZU-KUSSEI 1 (MIZ1) and microRNA MIR163 are down-regulated in 5-day-old Arabidopsis thaliana roots after 3 min and 6 min of clinorotation using a maximal reduced g-force of 0.02 g, hence demonstrating that this 2-D clinostat enables the characterization of early transcriptomic events during root response to microgravity. We further show that this 2-D clinostat is able to compensate the action of gravitational force as both gravitropic-dependent statolith sedimentation and subsequent auxin redistribution (monitoring D R5 r e v :: G F P reporter) are abolished when plants are clinorotated. Our results demonstrate that 2-D clinostats equipped with interchangeable growth chambers and tunable rotation velocity are suitable for studying how plants perceive and respond to simulated microgravity.
Perspective: Echoes in 2D-Raman-THz spectroscopy.
Hamm, Peter; Shalit, Andrey
2017-04-07
Recently, various spectroscopic techniques have been developed, which can measure the 2D response of the inter-molecular degrees of freedom of liquids in the THz regime. By employing hybrid Raman-THz pulse sequences, the inherent experimental problems of 2D-Raman spectroscopy are circumvented completely, culminating in the recent measurement of the 2D-Raman-THz responses of water and aqueous salt solutions. This review article focuses on the possibility to observe echoes in such experiments, which would directly reveal the inhomogeneity of the typically extremely blurred THz bands of liquids, and hence the heterogeneity of local structures that are transiently formed, in particular, in a hydrogen-bonding liquid such as water. The generation mechanisms of echoes in 2D-Raman-THz spectroscopy are explained, which differ from those in "conventional" 2D-IR spectroscopy in a subtle but important manner. Subsequently, the circumstances are discussed, under which echoes are expected, revealing a physical picture of the information content of an echo. That is, the echo decay reflects the lifetime of local structures in the liquid on a length scale that equals the delocalization length of the intermolecular modes. Finally, recent experimental results are reviewed from an echo perspective.
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.
Contact engineering for 2D materials and devices.
Schulman, Daniel S; Arnold, Andrew J; Das, Saptarshi
2018-05-08
Over the past decade, the field of two-dimensional (2D) layered materials has surged, promising a new platform for studying diverse physical phenomena that are scientifically intriguing and technologically relevant. Contacts are the communication links between these 2D materials and the three-dimensional world for probing and harnessing their exquisite electronic properties. However, fundamental challenges related to contacts often limit the ultimate performance and potential of 2D materials and devices. This article provides a comprehensive overview of the basic understanding and importance of contacts to 2D materials and various strategies for engineering and improving them. In particular, we elucidate the phenomenon of Fermi level pinning at the metal/2D contact interface, the Schottky versus Ohmic nature of the contacts and various contact engineering approaches including interlayer contacts, phase engineered contacts, and basal versus edge plane contacts, among others. Finally, we also discuss some of the relatively under-addressed and unresolved issues, such as contact scaling, and conclude with a future outlook.
Mermin–Wagner fluctuations in 2D amorphous solids
Illing, Bernd; Fritschi, Sebastian; Kaiser, Herbert; Klix, Christian L.; Maret, Georg; Keim, Peter
2017-01-01
In a recent commentary, J. M. Kosterlitz described how D. Thouless and he got motivated to investigate melting and suprafluidity in two dimensions [Kosterlitz JM (2016) J Phys Condens Matter 28:481001]. It was due to the lack of broken translational symmetry in two dimensions—doubting the existence of 2D crystals—and the first computer simulations foretelling 2D crystals (at least in tiny systems). The lack of broken symmetries proposed by D. Mermin and H. Wagner is caused by long wavelength density fluctuations. Those fluctuations do not only have structural impact, but additionally a dynamical one: They cause the Lindemann criterion to fail in 2D in the sense that the mean squared displacement of atoms is not limited. Comparing experimental data from 3D and 2D amorphous solids with 2D crystals, we disentangle Mermin–Wagner fluctuations from glassy structural relaxations. Furthermore, we demonstrate with computer simulations the logarithmic increase of displacements with system size: Periodicity is not a requirement for Mermin–Wagner fluctuations, which conserve the homogeneity of space on long scales. PMID:28137872
2D Materials for Optical Modulation: Challenges and Opportunities.
Yu, Shaoliang; Wu, Xiaoqin; Wang, Yipei; Guo, Xin; Tong, Limin
2017-04-01
Owing to their atomic layer thickness, strong light-material interaction, high nonlinearity, broadband optical response, fast relaxation, controllable optoelectronic properties, and high compatibility with other photonic structures, 2D materials, including graphene, transition metal dichalcogenides and black phosphorus, have been attracting increasing attention for photonic applications. By tuning the carrier density via electrical or optical means that modifies their physical properties (e.g., Fermi level or nonlinear absorption), optical response of the 2D materials can be instantly changed, making them versatile nanostructures for optical modulation. Here, up-to-date 2D material-based optical modulation in three categories is reviewed: free-space, fiber-based, and on-chip configurations. By analysing cons and pros of different modulation approaches from material and mechanism aspects, the challenges faced by using these materials for device applications are presented. In addition, thermal effects (e.g., laser induced damage) in 2D materials, which are critical to practical applications, are also discussed. Finally, the outlook for future opportunities of these 2D materials for optical modulation is given. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
Simulating synchronization in neuronal networks
NASA Astrophysics Data System (ADS)
Fink, Christian G.
2016-06-01
We discuss several techniques used in simulating neuronal networks by exploring how a network's connectivity structure affects its propensity for synchronous spiking. Network connectivity is generated using the Watts-Strogatz small-world algorithm, and two key measures of network structure are described. These measures quantify structural characteristics that influence collective neuronal spiking, which is simulated using the leaky integrate-and-fire model. Simulations show that adding a small number of random connections to an otherwise lattice-like connectivity structure leads to a dramatic increase in neuronal synchronization.
NASA Astrophysics Data System (ADS)
Shimada, Yutaka; Ikeguchi, Tohru; Shigehara, Takaomi
2012-10-01
In this Letter, we propose a framework to transform a complex network to a time series. The transformation from complex networks to time series is realized by the classical multidimensional scaling. Applying the transformation method to a model proposed by Watts and Strogatz [Nature (London) 393, 440 (1998)], we show that ring lattices are transformed to periodic time series, small-world networks to noisy periodic time series, and random networks to random time series. We also show that these relationships are analytically held by using the circulant-matrix theory and the perturbation theory of linear operators. The results are generalized to several high-dimensional lattices.
Combining 2D angiogenesis and 3D osteosarcoma microtissues to improve vascularization.
Chaddad, Hassan; Kuchler-Bopp, Sabine; Fuhrmann, Guy; Gegout, Hervé; Ubeaud-Sequier, Geneviève; Schwinté, Pascale; Bornert, Fabien; Benkirane-Jessel, Nadia; Idoux-Gillet, Ysia
2017-11-15
Angiogenesis is now well known for being involved in tumor progression, aggressiveness, emergence of metastases, and also resistance to cancer therapies. In this study, to better mimic tumor angiogenesis encountered in vivo, we used 3D culture of osteosarcoma cells (MG-63) that we deposited on 2D endothelial cells (HUVEC) grown in monolayer. We report that endothelial cells combined with tumor cells were able to form a well-organized network, and that tubule-like structures corresponding to new vessels infiltrate tumor spheroids. These vessels presented a lumen and expressed specific markers as CD31 and collagen IV. The combination of 2D endothelial cells and 3D microtissues of tumor cells also increased expression of angiogenic factors as VEGF, CXCR4 and ICAM1. The cell environment is the key point to develop tumor vascularization in vitro and to be closer to tumor encountered in vivo. Copyright © 2017 Elsevier Inc. All rights reserved.
Rapid and Efficient Redox Processes within 2D Covalent Organic Framework Thin Films
DeBlase, Catherine R.; Hernández-Burgos, Kenneth; Silberstein, Katharine E.
2015-03-24
Two-dimensional covalent organic frameworks (2D COFs) are ideally suited for organizing redox-active subunits into periodic, permanently porous polymer networks of interest for pseudocapacitive energy storage. Here we describe a method for synthesizing crystalline, oriented thin films of a redox-active 2D COF on Au working electrodes. The thickness of the COF film was controlled by varying the initial monomer concentration. A large percentage (80–99%) of the anthraquinone groups are electrochemically accessible in films thinner than 200 nm, an order of magnitude improvement over the same COF prepared as a randomly oriented microcrystalline powder. As a result, electrodes functionalized with oriented COFmore » films exhibit a 400% increase in capacitance scaled to electrode area as compared to those functionalized with the randomly oriented COF powder. These results demonstrate the promise of redox-active COFs for electrical energy storage and highlight the importance of controlling morphology for optimal performance.« less
Rapid and Efficient Redox Processes within 2D Covalent Organic Framework Thin Films
DeBlase, Catherine R.; Hernández-Burgos, Kenneth; Silberstein, Katharine E.
2015-02-17
Two-dimensional covalent organic frameworks (2D COFs) are ideally suited for organizing redox-active subunits into periodic, permanently porous polymer networks of interest for pseudocapacitive energy storage. Here we describe a method for synthesizing crystalline, oriented thin films of a redox-active 2D COF on Au working electrodes. The thickness of the COF film was controlled by varying the initial monomer concentration. A large percentage (80–99%) of the anthraquinone groups are electrochemically accessible in films thinner than 200 nm, an order of magnitude improvement over the same COF prepared as a randomly oriented microcrystalline powder. As a result, electrodes functionalized with oriented COFmore » films exhibit a 400% increase in capacitance scaled to electrode area as compared to those functionalized with the randomly oriented COF powder. These results demonstrate the promise of redox-active COFs for electrical energy storage and highlight the importance of controlling morphology for optimal performance.« less
3D hydrogel scaffold doped with 2D graphene materials for biosensors and bioelectronics.
Song, Hyun Seok; Kwon, Oh Seok; Kim, Jae-Hong; Conde, João; Artzi, Natalie
2017-03-15
Hydrogels consisting of three-dimensional (3D) polymeric networks have found a wide range of applications in biotechnology due to their large water capacity, high biocompatibility, and facile functional versatility. The hydrogels with stimulus-responsive swelling properties have been particularly instrumental to realizing signal transduction in biosensors and bioelectronics. Graphenes are two-dimensional (2D) nanomaterials with unprecedented physical, optical, and electronic properties and have also found many applications in biosensors and bioelectronics. These two classes of materials present complementary strengths and limitations which, when effectively coupled, can result in significant synergism in their electrical, mechanical, and biocompatible properties. This report reviews recent advances made with hydrogel and graphene materials for the development of high-performance bioelectronics devices. The report focuses on the interesting intersection of these materials wherein 2D graphenes are hybridized with 3D hydrogels to develop the next generation biosensors and bioelectronics. Copyright © 2016 Elsevier B.V. All rights reserved.
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.
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.
Packing of flexible 2D materials in vesicles
NASA Astrophysics Data System (ADS)
Zou, Guijin; Yi, Xin; Zhu, Wenpeng; Gao, Huajian
2018-06-01
To understand the mechanics of cellular packing of two-dimensional (2D) materials, we perform systematic molecular dynamics simulations and theoretical analysis to investigate the packing of a flexible circular sheet in a spherical vesicle and the 2D packing problem of a strip in a cylindrical vesicle. Depending on the system dimensions and the bending rigidity ratio between the confined sheet and the vesicle membrane, a variety of packing morphologies are observed, including a conical shape, a shape of three-fold symmetry, a cylindrically curved shape, an axisymmetrically buckled shape, as well as the initial circular shape. A set of buckling analyses lead to phase diagrams of the packing morphologies of the encapsulated sheets. These results may have important implications on the mechanism of intracellular packing and toxicity of 2D materials.
Chemical vapour deposition: Transition metal carbides go 2D
Gogotsi, Yury
2015-08-17
Here, the research community has been steadily expanding the family of few-atom-thick crystals beyond graphene, discovering new materials or producing known materials in a 2D state and demonstrating their unique properties 1, 2. Recently, nanometre-thin 2D transition metal carbides have also joined this family 3. Writing in Nature Materials, Chuan Xu and colleagues now report a significant advance in the field, showing the synthesis of large-area, high-quality, nanometre-thin crystals of molybdenum carbide that demonstrate low-temperature 2D superconductivity 4. Moreover, they also show that other ultrathin carbide crystals, such as tungsten and tantalum carbides, can be grown by chemical vapour depositionmore » with a high crystallinity and very low defect concentration.« less
The Wigner distribution and 2D classical maps
NASA Astrophysics Data System (ADS)
Sakhr, Jamal
2017-07-01
The Wigner spacing distribution has a long and illustrious history in nuclear physics and in the quantum mechanics of classically chaotic systems. In this paper, a novel connection between the Wigner distribution and 2D classical mechanics is introduced. Based on a well-known correspondence between the Wigner distribution and the 2D Poisson point process, the hypothesis that typical pseudo-trajectories of a 2D ergodic map have a Wignerian nearest-neighbor spacing distribution (NNSD) is put forward and numerically tested. The standard Euclidean metric is used to compute the interpoint spacings. In all test cases, the hypothesis is upheld, and the range of validity of the hypothesis appears to be robust in the sense that it is not affected by the presence or absence of: (i) mixing; (ii) time-reversal symmetry; and/or (iii) dissipation.
MESH2D Grid generator design and use
Flach, G. P.
Mesh2d is a Fortran90 program originally 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). x-coordinates depending only on index i implies strictly vertical x-grid lines, whereas the y-grid lines can undulate. Mesh2d also assigns an integer material type to each grid cell, mtyp(i,j), in a user-specified manner. The complete grid is specified through three separate input files defining the x(i), y(i,j), and mtyp(i,j) variations. Since the original development effort, Mesh2d has been extended to more general two-dimensional structured grids of the form [x(i,j),(i,j)].
Splashing transients of 2D plasmons launched by swift electrons
Lin, Xiao; Kaminer, Ido; Shi, Xihang; Gao, Fei; Yang, Zhaoju; Gao, Zhen; Buljan, Hrvoje; Joannopoulos, John D.; Soljačić, Marin; Chen, Hongsheng; Zhang, Baile
2017-01-01
Launching of plasmons by swift electrons has long been used in electron energy–loss spectroscopy (EELS) to investigate the plasmonic properties of ultrathin, or two-dimensional (2D), electron systems. However, the question of how a swift electron generates plasmons in space and time has never been answered. We address this issue by calculating and demonstrating the spatial-temporal dynamics of 2D plasmon generation in graphene. We predict a jet-like rise of excessive charge concentration that delays the generation of 2D plasmons in EELS, exhibiting an analog to the hydrodynamic Rayleigh jet in a splashing phenomenon before the launching of ripples. The photon radiation, analogous to the splashing sound, accompanies the plasmon emission and can be understood as being shaken off by the Rayleigh jet–like charge concentration. Considering this newly revealed process, we argue that previous estimates on the yields of graphene plasmons in EELS need to be reevaluated. PMID:28138546
Dynamical heterogeneities of cold 2D Yukawa liquids
NASA Astrophysics Data System (ADS)
Wang, Kang; Huang, Dong; Feng, Yan
2018-06-01
Dynamical heterogeneities of 2D liquid dusty plasmas at different temperatures are investigated systematically using Langevin dynamical simulations. From the simulated trajectories, various heterogeneity measures have been calculated, such as the distance matrix, the averaged squared displacement, the non-Gaussian parameter, and the four-point susceptibility. It is found that, for 2D Yukawa liquids, both spatial and temporal heterogeneities in dynamics are more severe at a lower temperature near the melting point. For various temperatures, the calculated non-Gaussian parameter of 2D Yukawa liquids contains two peaks at different times, indicating the most heterogeneous dynamics, which are attributed to the transition of different motions and the α relaxation time, respectively. In the diffusive motion, the most heterogeneous dynamics for a colder Yukawa liquid happen more slowly, as indicated by both the non-Gaussian parameter and the four-point susceptibility.
Determination of slope failure using 2-D resistivity method
NASA Astrophysics Data System (ADS)
Muztaza, Nordiana Mohd; Saad, Rosli; Ismail, Nur Azwin; Bery, Andy Anderson
2017-07-01
Landslides and slope failure may give negative economic effects including the cost to repair structures, loss of property value and medical costs in the event of injury. To avoid landslide, slope failure and disturbance of the ecosystem, good and detailed planning must be done when developing hilly area. Slope failure classification and various factors contributing to the instability using 2-D resistivity survey conducted in Selangor, Malaysia are described. The study on landslide and slope failure was conducted at Site A and Site B, Selangor using 2-D resistivity method. The implications of the anticipated ground conditions as well as the field observation of the actual conditions are discussed. Nine 2-D resistivity survey lines were conducted in Site A and six 2-D resistivity survey lines with 5 m minimum electrode spacing using Pole-dipole array were performed in Site B. The data were processed using Res2Dinv and Surfer10 software to evaluate the subsurface characteristics. 2-D resistivity results from both locations show that the study areas consist of two main zones. The first zone is alluvium or highly weathered with the resistivity of 100-1000 Ωm at 20-70 m depth. This zone consists of saturated area (1-100 Ωm) and boulders with resistivity value of 1200-3000 Ωm. The second zone with resistivity values of > 3000 Ωm was interpreted as granitic bedrock. The study area was characterized by saturated zones, highly weathered zone, highly contain of sand and boulders that will trigger slope failure in the survey area. Based on the results obtained from the study findings, it can be concluded that 2-D resistivity method is useful method in determination of slope failure.
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.
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.
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.
Radiative heat transfer in 2D Dirac materials
NASA Astrophysics Data System (ADS)
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.
Recording 2-D Nutation NQR Spectra by Random Sampling Method
Sinyavsky, Nikolaj; Jadzyn, Maciej; Ostafin, Michal; Nogaj, Boleslaw
2010-01-01
The method of random sampling was introduced for the first time in the nutation nuclear quadrupole resonance (NQR) spectroscopy where the nutation spectra show characteristic singularities in the form of shoulders. The analytic formulae for complex two-dimensional (2-D) nutation NQR spectra (I = 3/2) were obtained and the condition for resolving the spectral singularities for small values of an asymmetry parameter η was determined. Our results show that the method of random sampling of a nutation interferogram allows significant reduction of time required to perform a 2-D nutation experiment and does not worsen the spectral resolution. PMID:20949121
Thermodynamics of an Attractive 2D Fermi Gas
NASA Astrophysics Data System (ADS)
Fenech, K.; Dyke, P.; Peppler, T.; Lingham, M. G.; Hoinka, S.; Hu, H.; Vale, C. J.
2016-01-01
Thermodynamic properties of matter are conveniently expressed as functional relations between variables known as equations of state. Here we experimentally determine the compressibility, density, and pressure equations of state for an attractive 2D Fermi gas in the normal phase as a function of temperature and interaction strength. In 2D, interacting gases exhibit qualitatively different features to those found in 3D. This is evident in the normalized density equation of state, which peaks at intermediate densities corresponding to the crossover from classical to quantum behavior.
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.
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.
Transmission properties of 2D metamaterial photonic crystals
NASA Astrophysics Data System (ADS)
Mejía-Salazar, Jorge; Porras-Montenegro, Nelson
2014-03-01
By using the finite difference time domain technique, we have performed a theoretical study of the transmission properties in 2D photonic crystals composed by circular cilyndrical metamaterial rods. Numerical transmission spectra was compared with its corresponding photonic band structure in the case of an infinite periodic 2D array obtaining a very good agreement. On the other hand, we have characterized the corresponding symmetries for this system and the results were compared with its corresponding conventional plasmonic metamaterial counterpart. J.R. M-S is funded by the Colombian Agency COLCIENCIAS.
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
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
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.
Optimal Topology Control and Power Allocation for Minimum Energy Consumption in Consensus Networks
2011-12-16
network topologies, such as small world graphs, can greatly increase the convergence rate. In [9], the authors show that nonbipartite Ramanujan graphs...unclassified c . THIS PAGE unclassified Standard Form 298 (Rev. 8-98) Prescribed by ANSI Std Z39-18 23384 IEEE TRANSACTIONS ON SIGNAL PROCESSING, VOL. 60...of iterations necessary to achieve consensus. From this perspec- tive, enforcing a small world, scale-free, or Ramanujan graph topology may not be the
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…
ENVIRONMENTAL EFFECTS OF DREDGING AND DISPOSAL (E2-D2)
US Army Corps of Engineers public web site for the "Environmental Effects of Dredging and Disposal" ("E2-D2") searchable database of published reports and studies about environmental impacts associated with dredging and disposal operations. Many of the reports and studies are ava...
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.
Studying Zeolite Catalysts with a 2D Model System
Boscoboinik, Anibal
2018-06-13
Anibal Boscoboinik, a materials scientist at Brookhavenâs Center for Functional Nanomaterials, discusses the surface-science tools and 2D model system he uses to study catalysis in nanoporous zeolites, which catalyze reactions in many industrial processes.
Wall-crossing in coupled 2d-4d systems
NASA Astrophysics Data System (ADS)
Gaiotto, Davide; Moore, Gregory W.; Neitzke, Andrew
2012-12-01
We introduce a new wall-crossing formula which combines and generalizes the Cecotti-Vafa and Kontsevich-Soibelman formulas for supersymmetric 2d and 4d systems respectively. This 2d-4d wall-crossing formula governs the wall-crossing of BPS states in an {N}=2 supersymmetric 4d gauge theory coupled to a supersymmetric surface defect. When the theory and defect are compactified on a circle, we get a 3d theory with a supersymmetric line operator, corresponding to a hyperholomorphic connection on a vector bundle over a hyperkähler space. The 2d-4d wall-crossing formula can be interpreted as a smoothness condition for this hyperholomorphic connection. We explain how the 2d-4d BPS spectrum can be determined for 4d theories of class {S} , that is, for those theories obtained by compactifying the six-dimensional (0, 2) theory with a partial topological twist on a punctured Riemann surface C. For such theories there are canonical surface defects. We illustrate with several examples in the case of A 1 theories of class {S} . Finally, we indicate how our results can be used to produce solutions to the A 1 Hitchin equations on the Riemann surface C.
Optoelectronics of supported and suspended 2D semiconductors
NASA Astrophysics Data System (ADS)
Bolotin, Kirill
2014-03-01
Two-dimensional semiconductors, materials such monolayer molybdenum disulfide (MoS2) are characterized by strong spin-orbit and electron-electron interactions. However, both electronic and optoelectronic properties of these materials are dominated by disorder-related scattering. In this talk, we investigate approaches to reduce scattering and explore physical phenomena arising in intrinsic 2D semiconductors. First, we discuss fabrication of pristine suspended monolayer MoS2 and use photocurrent spectroscopy measurements to study excitons in this material. We observe band-edge and van Hove singularity excitons and estimate their binding energies. Furthermore, we study dissociation of these excitons and uncover the mechanism of their contribution to photoresponse of MoS2. Second, we study strain-induced modification of bandstructures of 2D semiconductors. With increasing strain, we find large and controllable band gap reduction of both single- and bi-layer MoS2. We also detect experimental signatures consistent with strain-induced transition from direct to indirect band gap in monolayer MoS2. Finally, we fabricate heterostructures of dissimilar 2D semiconductors and study their photoresponse. For closely spaced 2D semiconductors we detect charge transfer, while for separation larger than 10nm we observe Forster-like energy transfer between excitations in different layers.
Promising Thermoelectric Bulk Materials with 2D Structures.
Zhou, Yiming; Zhao, Li-Dong
2017-12-01
Given that more than two thirds of all energy is lost, mostly as waste heat, in utilization processes worldwide, thermoelectric materials, which can directly convert waste heat to electricity, provide an alternative option for optimizing energy utilization processes. After the prediction that superlattices may show high thermoelectric performance, various methods based on quantum effects and superlattice theory have been adopted to analyze bulk materials, leading to the rapid development of thermoelectric materials. Bulk materials with two-dimensional (2D) structures show outstanding properties, and their high performance originates from both their low thermal conductivity and high Seebeck coefficient due to their strong anisotropic features. Here, the advantages of superlattices for enhancing the thermoelectric performance, the transport mechanism in bulk materials with 2D structures, and optimization methods are discussed. The phenomenological transport mechanism in these materials indicates that thermal conductivities are reduced in 2D materials with intrinsically short mean free paths. Recent progress in the transport mechanisms of Bi 2 Te 3 -, SnSe-, and BiCuSeO-based systems is summarized. Finally, possible research directions to enhance the thermoelectric performance of bulk materials with 2D structures are briefly considered. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
2D Materials with Nanoconfined Fluids for Electrochemical Energy Storage
Augustyn, Veronica; Gogotsi, Yury
2017-10-11
In the quest to develop energy storage with both high power and high energy densities, and while maintaining high volumetric capacity, recent results show that a variety of 2D and layered materials exhibit rapid kinetics of ion transport by the incorporation of nanoconfined fluids.
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.
2D nanomaterials based electrochemical biosensors for cancer diagnosis.
Wang, Lu; Xiong, Qirong; Xiao, Fei; Duan, Hongwei
2017-03-15
Cancer is a leading cause of death in the world. Increasing evidence has demonstrated that early diagnosis holds the key towards effective treatment outcome. Cancer biomarkers are extensively used in oncology for cancer diagnosis and prognosis. Electrochemical sensors play key roles in current laboratory and clinical analysis of diverse chemical and biological targets. Recent development of functional nanomaterials offers new possibilities of improving the performance of electrochemical sensors. In particular, 2D nanomaterials have stimulated intense research due to their unique array of structural and chemical properties. The 2D materials of interest cover broadly across graphene, graphene derivatives (i.e., graphene oxide and reduced graphene oxide), and graphene-like nanomaterials (i.e., 2D layered transition metal dichalcogenides, graphite carbon nitride and boron nitride nanomaterials). In this review, we summarize recent advances in the synthesis of 2D nanomaterials and their applications in electrochemical biosensing of cancer biomarkers (nucleic acids, proteins and some small molecules), and present a personal perspective on the future direction of this area. Copyright © 2016 Elsevier B.V. All rights reserved.
Effective Mass Theory of 2D Excitons Revisited
NASA Astrophysics Data System (ADS)
Gonzalez, Joseph; Oleynik, Ivan
Two-dimensional (2D) semiconducting materials possess an exceptionally unique set of electronic and excitonic properties due to the combined effects of quantum and dielectric confinement. Reliable determination of exciton binding energies from both first-principles many-body perturbation theory (GW/BSE) and experiment is very challenging due to the enormous computational expense as well as the tremendous technical difficulties in experiment.. Very recently, effective mass theories of 2D excitons have been developed as an attractive alternative for inexpensive and accurate evaluation of the exciton binding energies. In this presentation, we evaluate two effective mass theory approaches by Velizhanin et al and Olsen et al in predicting exciton binding energies across a wide range of 2D materials. We specifically analyze the trends related to the varying screening lengths and exciton effective masses. We also extended the effective mass theory of 2D excitons to include effects of electron and hole mass anisotropies (mx ≠ my) , the latter showing a substantial influence on exciton binding energies. The recent predictions of exciton binding energies being independent of the exciton effective mass and a linear correlation with the band gap of a specific material are also critically reexamined.
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
Flood hazard assessment using 1D and 2D approaches
NASA Astrophysics Data System (ADS)
Petaccia, Gabriella; Costabile, Pierfranco; Macchione, Francesco; Natale, Luigi
2013-04-01
The EU flood risk Directive (Directive 2007/60/EC) prescribes risk assessment and mapping to develop flood risk management plans. Flood hazard mapping may be carried out with mathematical models able to determine flood-prone areas once realistic conditions (in terms of discharge or water levels) are imposed at the boundaries of the case study. The deterministic models are mainly based on shallow water equations expressed in their 1D or 2D formulation. The 1D approach is widely used, especially in technical studies, due to its relative simplicity, its computational efficiency and also because it requires topographical data not as expensive as the ones needed by 2D models. Even if in a great number of practical situations, such as modeling in-channel flows and not too wide floodplains, the 1D approach may provide results close to the prediction of a more sophisticated 2D model, it must be pointed out that the correct use of a 1D model in practical situations is more complex than it may seem. The main issues to be correctly modeled in a 1D approach are the definition of hydraulic structures such as bridges and buildings interacting with the flow and the treatment of the tributaries. Clearly all these aspects have to be taken into account also in the 2D modeling, but with fewer difficulties. The purpose of this paper is to show how the above cited issues can be described using a 1D or 2D unsteady flow modeling. In particular the Authors will show the devices that have to be implemented in 1D modeling to get reliable predictions of water levels and discharges comparable to the ones obtained using a 2D model. Attention will be focused on an actual river (Crati river) located in the South of Italy. This case study is quite complicated since it deals with the simulation of channeled flows, overbank flows, interactions with buildings, bridges and tributaries. Accurate techniques, intentionally developed by the Authors to take into account all these peculiarities in 1D and 2
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.
The role of topology in microstructure-property relations: a 2D DEM based study
NASA Astrophysics Data System (ADS)
Saleme Ruiz, Katerine; Emelianenko, Maria
2018-01-01
We compare Rényi entropy-based mesoscale approaches for characterizing 2D polycrystalline network topology and geometry, based on the grain number of sides and grain areas, respectively. We study the effect of microstructure disorder on mechanical properties such as elastic and damage response by performing simulations of quasi-static uniaxial compression loading tests on an idealized material using grain-level micro-mechanical discrete element model. While not comprehensive enough to make general conclusions, this study allows us to make observations about the sensitivity of mechanical parameters such as Young's modulus, proportional limit, first yield stress, toughness and amount of microstructure damage to different entropy measures.
Recovering 3D Particle Size Distributions from 2D Sections
NASA Technical Reports Server (NTRS)
Cuzzi, Jeffrey N.; Olson, Daniel A.
2017-01-01
We discuss different ways to convert observed, apparent particle size distributions from 2D sections (thin sections, SEM maps on planar surfaces, etc.) into true 3D particle size distributions. We give a simple, flexible and practical method to do this, show which of these techniques gives the most faithful conversions, and provide (online) short computer codes to calculate both 2D- 3D recoveries and simulations of 2D observations by random sectioning. The most important systematic bias of 2D sectioning, from the standpoint of most chondrite studies, is an overestimate of the abundance of the larger particles. We show that fairly good recoveries can be achieved from observed size distributions containing 100-300 individual measurements of apparent particle diameter. Proper determination of particle size distributions in chondrites - for chondrules, CAIs, and metalgrains - is of basic importance for assessing the processes of formation and/or of accretion of theseparticles into their parent bodies. To date, most information of this sort is gathered from 2D samplescut from a rock such as in microscopic analysis of thin sections, or SEM maps of planar surfaces(Dodd 1976, Hughes 1978a,b; Rubin and Keil 1984, Rubin and Grossman 1987, Grossman et al1988, Rubin 1989, Metzler et al 1992, Kuebler et al 1999, Nelson and Rubin 2002, Schneider et al 2003, Hezel et al 2008; Fisher et al 2014; for an exhaustive review with numerous references seeFriedrich et al 2014). While qualitative discrimination between chondrite types can readily be doneusing data of this sort, any deeper exploration of the processes by which chondrite constituents werecreated or emplaced into their parent requires a more quantitative approach.
2d-LCA - an alternative to x-wires
NASA Astrophysics Data System (ADS)
Puczylowski, Jaroslaw; Hölling, Michael; Peinke, Joachim
2014-11-01
The 2d-Laser Cantilever Anemometer (2d-LCA) is an innovative sensor for two-dimensional velocity measurements in fluids. It uses a micostructured cantilever made of silicon and SU-8 as a sensing element and is capable of performing mesurements with extremly high temporal resolutions up to 150 kHz. The size of the cantilever defines its spatial resolution, which is in the order of 150 μm only. Another big feature is a large angular range of 180° in total. The 2d-LCA has been developed as an alternative measurement method to x-wires with the motivation to create a sensor that can operate in areas where the use of hot-wire anemometry is difficult. These areas include measurements in liquids and in near-wall or particle-laden flows. Unlike hot-wires, the resolution power of the 2d-LCA does not decrease with increasing flow velocity, making it particularly suitable for measurements in high speed flows. Comparative measurements with the 2d-LCA and hot-wires have been carried out in order to assess the performance of the new anemometer. The data of both measurement techniques were analyzed using the same stochastic methods including a spectral analysis as well as an inspection of increment statistics and structure functions. Furthermore, key parameters, such as mean values of both velocity components, angles of attack and the characteristic length scales were determined from both data sets. The analysis reveals a great agreement between both anemometers and thus confirms the new approach.
2D-pattern matching image and video compression: theory, algorithms, and experiments.
Alzina, Marc; Szpankowski, Wojciech; Grama, Ananth
2002-01-01
In this paper, we propose a lossy data compression framework based on an approximate two-dimensional (2D) pattern matching (2D-PMC) extension of the Lempel-Ziv (1977, 1978) lossless scheme. This framework forms the basis upon which higher level schemes relying on differential coding, frequency domain techniques, prediction, and other methods can be built. We apply our pattern matching framework to image and video compression and report on theoretical and experimental results. Theoretically, we show that the fixed database model used for video compression leads to suboptimal but computationally efficient performance. The compression ratio of this model is shown to tend to the generalized entropy. For image compression, we use a growing database model for which we provide an approximate analysis. The implementation of 2D-PMC is a challenging problem from the algorithmic point of view. We use a range of techniques and data structures such as k-d trees, generalized run length coding, adaptive arithmetic coding, and variable and adaptive maximum distortion level to achieve good compression ratios at high compression speeds. We demonstrate bit rates in the range of 0.25-0.5 bpp for high-quality images and data rates in the range of 0.15-0.5 Mbps for a baseline video compression scheme that does not use any prediction or interpolation. We also demonstrate that this asymmetric compression scheme is capable of extremely fast decompression making it particularly suitable for networked multimedia applications.
Advances in research on 2D and 3D graphene-based supercapacitors
NASA Astrophysics Data System (ADS)
Mensing, Johannes Ph.; Poochai, Chatwarin; Kerdpocha, Sadanan; Sriprachuabwong, Chakrit; Wisitsoraat, Anurat; Tuantranont, Adisorn
2017-09-01
Graphene-based materials in two-dimensional (2D) and three-dimensional (3D) configurations are promising as electrode materials for supercapacitors due to their large surface area, excellent electrical conductivity, high electrochemical activity and high stability. In this article recent advances in research on 2D and 3D graphene-based materials for supercapacitor electrodes are reviewed extensively in aspects of fabrication methods and electrochemical performances. From the survey, the performance of 2D and 3D graphene-based materials could be significantly enhanced by employing nanostructures of metal oxides, metals and polymers as well as doping graphene with hetero atoms such as nitrogen and boron. In addition, the charge storage performances were found to depend greatly on materials, preparation method and structural configuration. With similar material components, 3D graphene-based networks tended to exhibit superior supercapacitive performances. Therefore, future research should be focusing on further development of 3D graphene-based materials for supercapacitor applications. Invited talk at 5th Thailand International Nanotechnology Conference (Nano Thailand-2016), 27-29 November 2016, Nakhon Ratchasima, Thailand.
Study on Development of 1D-2D Coupled Real-time Urban Inundation Prediction model
NASA Astrophysics Data System (ADS)
Lee, Seungsoo
2017-04-01
In recent years, we are suffering abnormal weather condition due to climate change around the world. Therefore, countermeasures for flood defense are urgent task. In this research, study on development of 1D-2D coupled real-time urban inundation prediction model using predicted precipitation data based on remote sensing technology is conducted. 1 dimensional (1D) sewerage system analysis model which was introduced by Lee et al. (2015) is used to simulate inlet and overflow phenomena by interacting with surface flown as well as flows in conduits. 2 dimensional (2D) grid mesh refinement method is applied to depict road networks for effective calculation time. 2D surface model is coupled with 1D sewerage analysis model in order to consider bi-directional flow between both. Also parallel computing method, OpenMP, is applied to reduce calculation time. The model is estimated by applying to 25 August 2014 extreme rainfall event which caused severe inundation damages in Busan, Korea. Oncheoncheon basin is selected for study basin and observed radar data are assumed as predicted rainfall data. The model shows acceptable calculation speed with accuracy. Therefore it is expected that the model can be used for real-time urban inundation forecasting system to minimize damages.
Chen, Ting; Li, Shu-Ying; Wang, Dong; Wan, Li-Jun
2017-11-01
Noncovalently introducing stereogenic information is a promising approach to embed chirality in achiral molecular systems. However, the interplay of the noncovalently introduced chirality with the intrinsic chirality of molecules or molecular aggregations has rarely been addressed. We report a competitive chiral expression of the noncovalent interaction-mediated chirality induction and the intrinsic stereogenic center-controlled chirality induction in a two-dimensional (2D) molecular assembly at the liquid/solid interface. Two enantiomorphous honeycomb networks are formed by the coassembly of an achiral 5-(benzyloxy)isophthalic acid (BIC) derivative and 1-octanol at the liquid/solid interface. The preferential formation of the globally homochiral assembly can be achieved either by using the chiral analog of 1-octanol, ( S )-6-methyl-1-octanol, as a chiral coadsorber to induce chirality to the BIC assembly via noncovalent hydrogen bonding or by covalently linking a chiral center in the side chain of BIC. Both the chiral coadsorber and the intrinsically chiral BIC derivative can act as a chiral seeds to induce a preferred handedness in the assembly of the achiral BIC derivatives. Furthermore, the noncovalent interaction-mediated chirality induction can restrain or even overrule the manifestation of the intrinsic chirality of the BIC molecule and dominate the handedness of the 2D molecular coassembly. This study provides insight into the interplay of intrinsically chiral centers and external chiral coadsorbers in the chiral induction, transfer, and amplification processes of 2D molecular assembly.
Chen, Ting; Li, Shu-Ying; Wang, Dong; Wan, Li-Jun
2017-01-01
Noncovalently introducing stereogenic information is a promising approach to embed chirality in achiral molecular systems. However, the interplay of the noncovalently introduced chirality with the intrinsic chirality of molecules or molecular aggregations has rarely been addressed. We report a competitive chiral expression of the noncovalent interaction–mediated chirality induction and the intrinsic stereogenic center–controlled chirality induction in a two-dimensional (2D) molecular assembly at the liquid/solid interface. Two enantiomorphous honeycomb networks are formed by the coassembly of an achiral 5-(benzyloxy)isophthalic acid (BIC) derivative and 1-octanol at the liquid/solid interface. The preferential formation of the globally homochiral assembly can be achieved either by using the chiral analog of 1-octanol, (S)-6-methyl-1-octanol, as a chiral coadsorber to induce chirality to the BIC assembly via noncovalent hydrogen bonding or by covalently linking a chiral center in the side chain of BIC. Both the chiral coadsorber and the intrinsically chiral BIC derivative can act as a chiral seeds to induce a preferred handedness in the assembly of the achiral BIC derivatives. Furthermore, the noncovalent interaction–mediated chirality induction can restrain or even overrule the manifestation of the intrinsic chirality of the BIC molecule and dominate the handedness of the 2D molecular coassembly. This study provides insight into the interplay of intrinsically chiral centers and external chiral coadsorbers in the chiral induction, transfer, and amplification processes of 2D molecular assembly. PMID:29119137
Estimation of Anonymous Email Network Characteristics through Statistical Disclosure Attacks
Portela, Javier; García Villalba, Luis Javier; Silva Trujillo, Alejandra Guadalupe; Sandoval Orozco, Ana Lucila; Kim, Tai-Hoon
2016-01-01
Social network analysis aims to obtain relational data from social systems to identify leaders, roles, and communities in order to model profiles or predict a specific behavior in users’ network. Preserving anonymity in social networks is a subject of major concern. Anonymity can be compromised by disclosing senders’ or receivers’ identity, message content, or sender-receiver relationships. Under strongly incomplete information, a statistical disclosure attack is used to estimate the network and node characteristics such as centrality and clustering measures, degree distribution, and small-world-ness. A database of email networks in 29 university faculties is used to study the method. A research on the small-world-ness and Power law characteristics of these email networks is also developed, helping to understand the behavior of small email networks. PMID:27809275
Estimation of Anonymous Email Network Characteristics through Statistical Disclosure Attacks.
Portela, Javier; García Villalba, Luis Javier; Silva Trujillo, Alejandra Guadalupe; Sandoval Orozco, Ana Lucila; Kim, Tai-Hoon
2016-11-01
Social network analysis aims to obtain relational data from social systems to identify leaders, roles, and communities in order to model profiles or predict a specific behavior in users' network. Preserving anonymity in social networks is a subject of major concern. Anonymity can be compromised by disclosing senders' or receivers' identity, message content, or sender-receiver relationships. Under strongly incomplete information, a statistical disclosure attack is used to estimate the network and node characteristics such as centrality and clustering measures, degree distribution, and small-world-ness. A database of email networks in 29 university faculties is used to study the method. A research on the small-world-ness and Power law characteristics of these email networks is also developed, helping to understand the behavior of small email networks.
A simple model clarifies the complicated relationships of complex networks
Zheng, Bojin; Wu, Hongrun; Kuang, Li; Qin, Jun; Du, Wenhua; Wang, Jianmin; Li, Deyi
2014-01-01
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. PMID:25160506
Emergence of cooperation in non-scale-free networks
NASA Astrophysics Data System (ADS)
Zhang, Yichao; Aziz-Alaoui, M. A.; Bertelle, Cyrille; Zhou, Shi; Wang, Wenting
2014-06-01
Evolutionary game theory is one of the key paradigms behind many scientific disciplines from science to engineering. Previous studies proposed a strategy updating mechanism, which successfully demonstrated that the scale-free network can provide a framework for the emergence of cooperation. Instead, individuals in random graphs and small-world networks do not favor cooperation under this updating rule. However, a recent empirical result shows the heterogeneous networks do not promote cooperation when humans play a prisoner’s dilemma. In this paper, we propose a strategy updating rule with payoff memory. We observe that the random graphs and small-world networks can provide even better frameworks for cooperation than the scale-free networks in this scenario. Our observations suggest that the degree heterogeneity may be neither a sufficient condition nor a necessary condition for the widespread cooperation in complex networks. Also, the topological structures are not sufficed to determine the level of cooperation in complex networks.
BiPACE 2D--graph-based multiple alignment for comprehensive 2D gas chromatography-mass spectrometry.
Hoffmann, Nils; Wilhelm, Mathias; Doebbe, Anja; Niehaus, Karsten; Stoye, Jens
2014-04-01
Comprehensive 2D gas chromatography-mass spectrometry is an established method for the analysis of complex mixtures in analytical chemistry and metabolomics. It produces large amounts of data that require semiautomatic, but preferably automatic handling. This involves the location of significant signals (peaks) and their matching and alignment across different measurements. To date, there exist only a few openly available algorithms for the retention time alignment of peaks originating from such experiments that scale well with increasing sample and peak numbers, while providing reliable alignment results. We describe BiPACE 2D, an automated algorithm for retention time alignment of peaks from 2D gas chromatography-mass spectrometry experiments and evaluate it on three previously published datasets against the mSPA, SWPA and Guineu algorithms. We also provide a fourth dataset from an experiment studying the H2 production of two different strains of Chlamydomonas reinhardtii that is available from the MetaboLights database together with the experimental protocol, peak-detection results and manually curated multiple peak alignment for future comparability with newly developed algorithms. BiPACE 2D is contained in the freely available Maltcms framework, version 1.3, hosted at http://maltcms.sf.net, under the terms of the L-GPL v3 or Eclipse Open Source licenses. The software used for the evaluation along with the underlying datasets is available at the same location. The C.reinhardtii dataset is freely available at http://www.ebi.ac.uk/metabolights/MTBLS37.
Farber, Nuri B; Nemmers, Brian; Noguchi, Kevin K
2006-09-15
Antagonists of the N-methyl-D-aspartate (NMDA) glutamate receptor, most likely by producing disinhibtion in complex circuits, acutely produce psychosis and cognitive disturbances in humans, and neurotoxicity in rodents. Studies examining NMDA Receptor Hypofunction (NRHypo) neurotoxicity in animals, therefore, may provide insights into the pathophysiology of psychotic disorders. Dopaminergic D2 and/or D3 agents can modify psychosis over days to weeks, suggesting involvement of these transmitter system(s). We studied the ability of D2/D3 agonists and antagonists to modify NRHypo neurotoxicity both after a one-time acute exposure and after chronic daily exposure. Here we report that D2/D3 dopamine agonists, probably via D3 receptors, prevent NRHypo neurotoxicity when given acutely. The protective effect with D2/D3 agonists is not seen after chronic daily dosing. In contrast, the antipsychotic haloperidol does not affect NRHypo neurotoxicity when given acutely at D2/D3 doses. However, after chronic daily dosing of 1, 3, or 5 weeks, haloperidol does prevent NRHypo neurotoxicity with longer durations producing greater protection. Understanding the changes that occur in the NRHypo circuit after chronic exposure to dopaminergic agents could provide important clues into the pathophysiology of psychotic disorders.
Brain anatomical networks in early human brain development.
Fan, Yong; Shi, Feng; Smith, Jeffrey Keith; Lin, Weili; Gilmore, John H; Shen, Dinggang
2011-02-01
Recent neuroimaging studies have demonstrated that human brain networks have economic small-world topology and modular organization, enabling efficient information transfer among brain regions. However, it remains largely unknown how the small-world topology and modular organization of human brain networks emerge and develop. Using longitudinal MRI data of 28 healthy pediatric subjects, collected at their ages of 1 month, 1 year, and 2 years, we analyzed development patterns of brain anatomical networks derived from morphological correlations of brain regional volumes. The results show that the brain network of 1-month-olds has the characteristically economic small-world topology and nonrandom modular organization. The network's cost efficiency increases with the brain development to 1 year and 2 years, so does the modularity, providing supportive evidence for the hypothesis that the small-world topology and the modular organization of brain networks are established during early brain development to support rapid synchronization and information transfer with minimal rewiring cost, as well as to balance between local processing and global integration of information. Copyright © 2010. Published by Elsevier Inc.
Giaddui, T; Yu, J; Xiao, Y
Purpose: 2D-2D kV image guided radiation therapy (IGRT) credentialing evaluation for clinical trial qualification was historically qualitative through submitting screen captures of the fusion process. However, as quantitative DICOM 2D-2D and 2D-3D image registration tools are implemented in clinical practice for better precision, especially in centers that treat patients with protons, better IGRT credentialing techniques are needed. The aim of this work is to establish methodologies for quantitatively reviewing IGRT submissions based on DICOM 2D-2D and 2D-3D image registration and to test the methodologies in reviewing 2D-2D and 2D-3D IGRT submissions for RTOG/NRG Oncology clinical trials qualifications. Methods: DICOM 2D-2Dmore » and 2D-3D automated and manual image registration have been tested using the Harmony tool in MIM software. 2D kV orthogonal portal images are fused with the reference digital reconstructed radiographs (DRR) in the 2D-2D registration while the 2D portal images are fused with DICOM planning CT image in the 2D-3D registration. The Harmony tool allows alignment of the two images used in the registration process and also calculates the required shifts. Shifts calculated using MIM are compared with those submitted by institutions for IGRT credentialing. Reported shifts are considered to be acceptable if differences are less than 3mm. Results: Several tests have been performed on the 2D-2D and 2D-3D registration. The results indicated good agreement between submitted and calculated shifts. A workflow for reviewing these IGRT submissions has been developed and will eventually be used to review IGRT submissions. Conclusion: The IROC Philadelphia RTQA center has developed and tested a new workflow for reviewing DICOM 2D-2D and 2D-3D IGRT credentialing submissions made by different cancer clinical centers, especially proton centers. NRG Center for Innovation in Radiation Oncology (CIRO) and IROC RTQA center continue their collaborative efforts to
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
Smooth 2D manifold extraction from 3D image stack
Shihavuddin, Asm; Basu, Sreetama; Rexhepaj, Elton; Delestro, Felipe; Menezes, Nikita; Sigoillot, Séverine M; Del Nery, Elaine; Selimi, Fekrije; Spassky, Nathalie; Genovesio, Auguste
2017-01-01
Three-dimensional fluorescence microscopy followed by image processing is routinely used to study biological objects at various scales such as cells and tissue. However, maximum intensity projection, the most broadly used rendering tool, extracts a discontinuous layer of voxels, obliviously creating important artifacts and possibly misleading interpretation. Here we propose smooth manifold extraction, an algorithm that produces a continuous focused 2D extraction from a 3D volume, hence preserving local spatial relationships. We demonstrate the usefulness of our approach by applying it to various biological applications using confocal and wide-field microscopy 3D image stacks. We provide a parameter-free ImageJ/Fiji plugin that allows 2D visualization and interpretation of 3D image stacks with maximum accuracy. PMID:28561033
Transition to chaos in an open unforced 2D flow
NASA Technical Reports Server (NTRS)
Pulliam, Thomas H.; Vastano, John A.
1993-01-01
The present numerical study of unsteady, low Reynolds number flow past a 2D airfoil attempts to ascertain the bifurcation sequence leading from simple periodic to complex aperiodic flow with rising Reynolds number, as well as to characterize the degree of chaos present in the aperiodic flow and assess the role of numerics in the modification and control of the observed bifurcation scenario. The ARC2D Navier-Stokes code is used in an unsteady time-accurate mode for most of these computations. The system undergoes a period-doubling bifurcation to chaos as the Reynolds number is increased from 800 to 1600; its chaotic attractors are characterized by estimates of the fractal dimension and partial Liapunov exponent spectra.
Enhanced automated platform for 2D characterization of RFID communications
NASA Astrophysics Data System (ADS)
Vuza, Dan Tudor; Vlǎdescu, Marian
2016-12-01
The characterization of the quality of communication between an RFID reader and a transponder at all expected positions of the latter on the reader antenna is of primal importance for the evaluation of performance of an RFID system. Continuing the line of instruments developed for this purpose by the authors, the present work proposes an enhanced version of a previously introduced automated platform for 2D evaluation. By featuring higher performance in terms of mechanical speed, the new version allows to obtain 2D maps of communication with a higher resolution that would have been prohibitive in terms of test duration with the previous version. The list of measurement procedures that can be executed with the platform is now enlarged with additional ones, such as the determination of the variation of the magnetic coupling between transponder and antenna across the antenna surface and the utilization of transponder simulators for evaluation of the quality of communication.
The Ising model coupled to 2d orders
NASA Astrophysics Data System (ADS)
Glaser, Lisa
2018-04-01
In this article we make first steps in coupling matter to causal set theory in the path integral. We explore the case of the Ising model coupled to the 2d discrete Einstein Hilbert action, restricted to the 2d orders. We probe the phase diagram in terms of the Wick rotation parameter β and the Ising coupling j and find that the matter and the causal sets together give rise to an interesting phase structure. The couplings give rise to five different phases. The causal sets take on random or crystalline characteristics as described in Surya (2012 Class. Quantum Grav. 29 132001) and the Ising model can be correlated or uncorrelated on the random orders and correlated, uncorrelated or anti-correlated on the crystalline orders. We find that at least one new phase transition arises, in which the Ising spins push the causal set into the crystalline phase.
2-D Magnetohydrodynamic Modeling of A Pulsed Plasma Thruster
NASA Technical Reports Server (NTRS)
Thio, Y. C. Francis; Cassibry, J. T.; Wu, S. T.; Rodgers, Stephen L. (Technical Monitor)
2002-01-01
Experiments are being performed on the NASA Marshall Space Flight Center (MSFC) MK-1 pulsed plasma thruster. Data produced from the experiments provide an opportunity to further understand the plasma dynamics in these thrusters via detailed computational modeling. The detailed and accurate understanding of the plasma dynamics in these devices holds the key towards extending their capabilities in a number of applications, including their applications as high power (greater than 1 MW) thrusters, and their use for producing high-velocity, uniform plasma jets for experimental purposes. For this study, the 2-D MHD modeling code, MACH2, is used to provide detailed interpretation of the experimental data. At the same time, a 0-D physics model of the plasma initial phase is developed to guide our 2-D modeling studies.
Metastability and nucleation in the 2D-Potts ferromagnet
NASA Astrophysics Data System (ADS)
de Berganza, Miguel Ibáñez
2009-01-01
The nature of the temperature-driven transition of the 2D q>4-Potts model, and the associated metastability, are studied. The problem was firstly investigated by Binder [1,2] in 1981, who discussed the existence of metastable states in a temperature interval below the critical point, which is first-order for q>4. Starting from the droplet expansion theory for the 2D Potts condensation point (Meunier & Morel, 2000 [3]), we compare the metastability derived from the theory with the dynamic metastability found with a local updating rule dynamics. The results are interpreted in terms of the microscopic mechanisms of nucleation, and compared to those described by Classical Nucleation Theory for the Ising model in an external field, which result to be different in several aspects.
FPCAS2D user's guide, version 1.0
NASA Technical Reports Server (NTRS)
Bakhle, Milind A.
1994-01-01
The FPCAS2D computer code has been developed for aeroelastic stability analysis of bladed disks such as those in fans, compressors, turbines, propellers, or propfans. The aerodynamic analysis used in this code is based on the unsteady two-dimensional full potential equation which is solved for a cascade of blades. The structural analysis is based on a two degree-of-freedom rigid typical section model for each blade. Detailed explanations of the aerodynamic analysis, the numerical algorithms, and the aeroelastic analysis are not given in this report. This guide can be used to assist in the preparation of the input data required by the FPCAS2D code. A complete description of the input data is provided in this report. In addition, four test cases, including inputs and outputs, are provided.
Calculation of wakefields in 2D rectangular structures
Zagorodnov, I.; Bane, K. L. F.; Stupakov, G.
2015-10-19
We consider the calculation of electromagnetic fields generated by an electron bunch passing through a vacuum chamber structure that, in general, consists of an entry pipe, followed by some kind of transition or cavity, and ending in an exit pipe. We limit our study to structures having rectangular cross section, where the height can vary as function of longitudinal coordinate but the width and side walls remain fixed. For such structures, we derive a Fourier representation of the wake potentials through one-dimensional functions. A new numerical approach for calculating the wakes in such structures is proposed and implemented in themore » computer code echo(2d). The computation resource requirements for this approach are moderate and comparable to those for finding the wakes in 2D rotationally symmetric structures. Finally, we present numerical examples obtained with the new numerical code.« less
MPEG-4-based 2D facial animation for mobile devices
NASA Astrophysics Data System (ADS)
Riegel, Thomas B.
2005-03-01
The enormous spread of mobile computing devices (e.g. PDA, cellular phone, palmtop, etc.) emphasizes scalable applications, since users like to run their favorite programs on the terminal they operate at that moment. Therefore appliances are of interest, which can be adapted to the hardware realities without loosing a lot of their functionalities. A good example for this is "Facial Animation," which offers an interesting way to achieve such "scalability." By employing MPEG-4, which provides an own profile for facial animation, a solution for low power terminals including mobile phones is demonstrated. From the generic 3D MPEG-4 face a specific 2D head model is derived, which consists primarily of a portrait image superposed by a suited warping mesh and adapted 2D animation rules. Thus the animation process of MPEG-4 need not be changed and standard compliant facial animation parameters can be used to displace the vertices of the mesh and warp the underlying image accordingly.
TRO-2D - A code for rational transonic aerodynamic optimization
NASA Technical Reports Server (NTRS)
Davis, W. H., Jr.
1985-01-01
Features and sample applications of the transonic rational optimization (TRO-2D) code are outlined. TRO-2D includes the airfoil analysis code FLO-36, the CONMIN optimization code and a rational approach to defining aero-function shapes for geometry modification. The program is part of an effort to develop an aerodynamically smart optimizer that will simplify and shorten the design process. The user has a selection of drag minimization and associated minimum lift, moment, and the pressure distribution, a choice among 14 resident aero-function shapes, and options on aerodynamic and geometric constraints. Design variables such as the angle of attack, leading edge radius and camber, shock strength and movement, supersonic pressure plateau control, etc., are discussed. The results of calculations of a reduced leading edge camber transonic airfoil and an airfoil with a natural laminar flow are provided, showing that only four design variables need be specified to obtain satisfactory results.
The 2-D lattice theory of Flower Constellations
NASA Astrophysics Data System (ADS)
Avendaño, Martín E.; Davis, Jeremy J.; Mortari, Daniele
2013-08-01
The 2-D lattice theory of Flower Constellations, generalizing Harmonic Flower Constellations (the symmetric subset of Flower Constellations) as well as the Walker/ Mozhaev constellations, is presented here. This theory is a new general framework to design symmetric constellations using a 2× 2 lattice matrix of integers or by its minimal representation, the Hermite normal form. From a geometrical point of view, the phasing of satellites is represented by a regular pattern (lattice) on a two-Dimensional torus. The 2-D lattice theory of Flower Constellations does not require any compatibility condition and uses a minimum set of integer parameters whose meaning are explored throughout the paper. This general minimum-parametrization framework allows us to obtain all symmetric distribution of satellites. Due to the J_2 effect this design framework is meant for circular orbits and for elliptical orbits at critical inclination, or to design elliptical constellations for the unperturbed Keplerian case.
Two-particle microrheology of quasi-2D viscous systems.
Prasad, V; Koehler, S A; Weeks, Eric R
2006-10-27
We study the spatially correlated motions of colloidal particles in a quasi-2D system (human serum albumin protein molecules at an air-water interface) for different surface viscosities eta s. We observe a transition in the behavior of the correlated motion, from 2D interface dominated at high eta s to bulk fluid dependent at low eta s. The correlated motions can be scaled onto a master curve which captures the features of this transition. This master curve also characterizes the spatial dependence of the flow field of a viscous interface in response to a force. The scale factors used for the master curve allow for the calculation of the surface viscosity eta s that can be compared to one-particle measurements.
Statistical analysis of quiet stance sway in 2-D
DiZio, Paul; Lackner, James R.
2014-01-01
Subjects exposed to a rotating environment that perturbs their postural sway show adaptive changes in their voluntary spatially directed postural motion to restore accurate movement paths but do not exhibit any obvious learning during passive stance. We have found, however, that a variable known to characterize the degree of stochasticity in quiet stance can also reveal subtle learning phenomena in passive stance. We extended Chow and Collins (Phys Rev E 52(1):909–912, 1995) one-dimensional pinned-polymer model (PPM) to two dimensions (2-D) and then evaluated the model’s ability to make analytical predictions for 2-D quiet stance. To test the model, we tracked center of mass and centers of foot pressures, and compared and contrasted stance sway for the anterior–posterior versus medio-lateral directions before, during, and after exposure to rotation at 10 rpm. Sway of the body during rotation generated Coriolis forces that acted perpendicular to the direction of sway. We found significant adaptive changes for three characteristic features of the mean square displacement (MSD) function: the exponent of the power law defined at short time scales, the proportionality constant of the power law, and the saturation plateau value defined at longer time scales. The exponent of the power law of MSD at a short time scale lies within the bounds predicted by the 2-D PPM. The change in MSD during exposure to rotation also had a power-law exponent in the range predicted by the theoretical model. We discuss the Coriolis force paradigm for studying postural and movement control and the applicability of the PPM model in 2-D for studying postural adaptation. PMID:24477760
2D Variations in Coda Amplitudes in the Middle East
Pasyanos, Michael E.; Gok, Rengin; Walter, William R.
2016-08-16
Here, coda amplitudes have proven to be a stable feature of seismograms, allowing one to reliably measure magnitudes for moderate to large-sized (M≥3) earthquakes over broad regions. Since smaller (M<3) earthquakes are only recorded at higher frequencies where we find larger interstation scatter, amplitude and magnitude estimates for these events are more variable, regional, and path dependent. In this study, we investigate coda amplitude measurements in the Middle East for 2-D variations in attenuation structure.
Topological Thouless pumping in graphene and 2D Dirac materials
NASA Astrophysics Data System (ADS)
Abergel, David; Pertsova, Anna
We present a comprehensive analysis of strain-induced topological Thouless pumping of charge and valley currents in graphene and 2D Dirac materials. We analyze the role of strain deformations with all possible symmetries and classify the charge and valley currents that are adiabatically pumped in response. These manifest as transport without an applied bias. The production of valley currents implies that strained Dirac materials are a candidate platform for valleytronic applications. Supported by ERC project DM-321031.
Consistency between 2D-3D Sediment Transport models
NASA Astrophysics Data System (ADS)
Villaret, Catherine; Jodeau, Magali
2017-04-01
Sediment transport models have been developed and applied by the engineering community to estimate transport rates and morphodynamic bed evolutions in river flows, coastal and estuarine conditions. Environmental modelling systems like the open-source Telemac modelling system include a hierarchy of models from 1D (Mascaret), 2D (Telemac-2D/Sisyphe) and 3D (Telemac-3D/Sedi-3D) and include a wide range of processes to represent sediment flow interactions under more and more complex situations (cohesive, non-cohesive and mixed sediment). Despite some tremendous progresses in the numerical techniques and computing resources, the quality/accuracy of model results mainly depend on the numerous choices and skills of the modeler. In complex situations involving stratification effects, complex geometry, recirculating flows… 2D model assumptions are no longer valid. A full 3D turbulent flow model is then required in order to capture the vertical mixing processes and to represent accurately the coupled flow/sediment distribution. However a number of theoretical and numerical difficulties arise when dealing with sediment transport modelling in 3D which will be high-lighted : (1) Dependency of model results to the vertical grid refinement and choice of boundary conditions and numerical scheme (2) The choice of turbulence model determines also the sediment vertical distribution which is governed by a balance between the downward settling term and upward turbulent diffusion. (3) The use of different numerical schemes for both hydrodynamics (mean and turbulent flow) and sediment transport modelling can lead to some inconsistency including a mismatch in the definition of numerical cells and definition of boundary conditions. We discuss here those present issues and present some detailed comparison between 2D and 3D simulations on a set of validation test cases which are available in the Telemac 7.2 release using both cohesive and non-cohesive sediments.
Energy transfer mechanisms in layered 2D perovskites.
Williams, Olivia F; Guo, Zhenkun; Hu, Jun; Yan, Liang; You, Wei; Moran, Andrew M
2018-04-07
Two-dimensional (2D) perovskite quantum wells are generating broad scientific interest because of their potential for use in optoelectronic devices. Recently, it has been shown that layers of 2D perovskites can be grown in which the average thicknesses of the quantum wells increase from the back to the front of the film. This geometry carries implications for light harvesting applications because the bandgap of a quantum well decreases as its thickness increases. The general structural formula for the 2D perovskite systems under investigation in this work is (PEA) 2 (MA) n-1 [Pb n I 3n+1 ] (PEA = phenethyl ammonium, MA = methyl ammonium). Here, we examine two layered 2D perovskites with different distributions of quantum well thicknesses. Spectroscopic measurements and model calculations suggest that both systems funnel electronic excitations from the back to the front of the film through energy transfer mechanisms on the time scales of 100's of ps (i.e., energy transfer from thinner to thicker quantum wells). In addition, the model calculations demonstrate that the transient absorption spectra are composed of a progression of single exciton and biexciton resonances associated with the individual quantum wells. We find that exciton dissociation and/or charge transport dynamics make only minor contributions to the transient absorption spectra within the first 1 ns after photo-excitation. An analysis of the energy transfer kinetics indicates that the transitions occur primarily between quantum wells with values of n that differ by 1 because of the spectral overlap factor that governs the energy transfer rate. Two-dimensional transient absorption spectra reveal a pattern of resonances consistent with the dominance of sequential energy transfer dynamics.
Energy transfer mechanisms in layered 2D perovskites
NASA Astrophysics Data System (ADS)
Williams, Olivia F.; Guo, Zhenkun; Hu, Jun; Yan, Liang; You, Wei; Moran, Andrew M.
2018-04-01
Two-dimensional (2D) perovskite quantum wells are generating broad scientific interest because of their potential for use in optoelectronic devices. Recently, it has been shown that layers of 2D perovskites can be grown in which the average thicknesses of the quantum wells increase from the back to the front of the film. This geometry carries implications for light harvesting applications because the bandgap of a quantum well decreases as its thickness increases. The general structural formula for the 2D perovskite systems under investigation in this work is (PEA)2(MA)n-1[PbnI3n+1] (PEA = phenethyl ammonium, MA = methyl ammonium). Here, we examine two layered 2D perovskites with different distributions of quantum well thicknesses. Spectroscopic measurements and model calculations suggest that both systems funnel electronic excitations from the back to the front of the film through energy transfer mechanisms on the time scales of 100's of ps (i.e., energy transfer from thinner to thicker quantum wells). In addition, the model calculations demonstrate that the transient absorption spectra are composed of a progression of single exciton and biexciton resonances associated with the individual quantum wells. We find that exciton dissociation and/or charge transport dynamics make only minor contributions to the transient absorption spectra within the first 1 ns after photo-excitation. An analysis of the energy transfer kinetics indicates that the transitions occur primarily between quantum wells with values of n that differ by 1 because of the spectral overlap factor that governs the energy transfer rate. Two-dimensional transient absorption spectra reveal a pattern of resonances consistent with the dominance of sequential energy transfer dynamics.
Report of the 1988 2-D Intercomparison Workshop, chapter 3
NASA Technical Reports Server (NTRS)
Jackman, Charles H.; Brasseur, Guy; Soloman, Susan; Guthrie, Paul D.; Garcia, Rolando; Yung, Yuk L.; Gray, Lesley J.; Tung, K. K.; Ko, Malcolm K. W.; Isaken, Ivar
1989-01-01
Several factors contribute to the errors encountered. With the exception of the line-by-line model, all of the models employ simplifying assumptions that place fundamental limits on their accuracy and range of validity. For example, all 2-D modeling groups use the diffusivity factor approximation. This approximation produces little error in tropospheric H2O and CO2 cooling rates, but can produce significant errors in CO2 and O3 cooling rates at the stratopause. All models suffer from fundamental uncertainties in shapes and strengths of spectral lines. Thermal flux algorithms being used in 2-D tracer tranport models produce cooling rates that differ by as much as 40 percent for the same input model atmosphere. Disagreements of this magnitude are important since the thermal cooling rates must be subtracted from the almost-equal solar heating rates to derive the net radiative heating rates and the 2-D model diabatic circulation. For much of the annual cycle, the net radiative heating rates are comparable in magnitude to the cooling rate differences described. Many of the models underestimate the cooling rates in the middle and lower stratosphere. The consequences of these errors for the net heating rates and the diabatic circulation will depend on their meridional structure, which was not tested here. Other models underestimate the cooling near 1 mbar. Suchs errors pose potential problems for future interactive ozone assessment studies, since they could produce artificially-high temperatures and increased O3 destruction at these levels. These concerns suggest that a great deal of work is needed to improve the performance of thermal cooling rate algorithms used in the 2-D tracer transport models.
2D/ 3D Quantitative Ultrasound of the Breast
NASA Astrophysics Data System (ADS)
Nasief, Haidy Gerges
Breast cancer is the second leading cause of cancer death of women in the United States, so breast cancer screening for early detection is common. The purpose of this dissertation is to optimize quantitative ultrasound (QUS) methods to improve the specificity and objectivity of breast ultrasound. To pursue this goal, the dissertation is divided into two parts: 1) to optimize 2D QUS, and 2) to introduce and validate 3D QUS. Previous studies had validated these methods in phantoms. Applying our QUS analysis on subcutaneous breast fat demonstrated that QUS parameter estimates for subcutaneous fat were consistent among different human subjects. This validated our in vivo data acquisition methods and supported the use of breast fat as a clinical reference tissue for ultrasound BI-RADSRTM assessments. Although current QUS methods perform well for straightforward cases when assumptions of stationarity and diffuse scattering are well-founded, these conditions often are not present due to the complicated nature of in vivo breast tissue. Key improvements in QUS algorithms to address these challenges were: 1) applying a "modified least squares method (MLSM)" to account for the heterogeneous tissue path between the transducer and the region of interest, ROI; 2) detecting anisotropy in acoustic parameters; and 3) detecting and removing the echo sources that depart from diffuse and stationary scattering conditions. The results showed that a Bayesian classifier combining three QUS parameters in a biased pool of high-quality breast ultrasound data successfully differentiated all fibroadenomas from all carcinomas. Given promising initial results in 2D, extension to 3D acquisitions in QUS provided a unique capability to test QUS for the entire breast volume. QUS parameter estimates using 3D data were consistent with those found in 2D for phantoms and in vivo data. Extensions of QUS technology from 2D to 3D can improve the specificity of breast ultrasound, and thus, could lead to
2D Vertical Heterostructures for Novel Tunneling Device Applications
2017-03-01
controlled by a combination of the drain-source voltage bias (VDS) and the top and bottom gate biases (VTG and VBG, respectively). The drain-source...properties that can potentially overcome some of the limitations of epitaxial 3D semiconductor heterostructures. Simulations of 2D...interlayer barrier, such as h-BN, a high-k dielectric material, or a van der Waal gap. Under appropriate bias conditions, charge carriers can tunnel
NASA High-Speed 2D Photogrammetric Measurement System
NASA Technical Reports Server (NTRS)
Dismond, Harriett R.
2012-01-01
The object of this report is to provide users of the NASA high-speed 2D photogrammetric measurement system with procedures required to obtain drop-model trajectory and impact data for full-scale and sub-scale models. This guide focuses on use of the system for vertical drop testing at the NASA Langley Landing and Impact Research (LandIR) Facility.
The Kubo-Greenwood expression and 2d MIT transport
NASA Astrophysics Data System (ADS)
Castner, Theodore
2010-03-01
The 2d MIT in GaAs heterostructures (p- and n-type)features a mobility that drops continuously as the reduced density x= n/nc-1 is decreased. The Kubo-Greenwood result [1] predicts μ = (eɛh/hnc)α^2(x) where α is a normalized DOS. α(x)is obtained from the data [p-type, Gao et al. [2]; n-type Lilly et al. [3
Growth of 2D heterostructures of graphene/BN
NASA Astrophysics Data System (ADS)
Hwang, Jeonghyun; Calderon, Brian R.; Alsalman, Hussain A.; Kwak, Joon Young; Kim, Moonkyung; Spencer, Michael G.
2014-06-01
Metal free direct growth of graphene on h-BN using a high temperature (~1550°C) chemical vapor deposition technique was done under Ar environment. Growth temperature, methane partial pressure, hydrogen/methane flow ratio, and growth time were varied and optimized. Raman spectroscopy clearly showed the signature of graphene with G- (~1580cm-1) and 2D-mode (~2700cm-1). The smallest width of G- and 2D-peak was 30 and 55cm-1, respectively, and the Raman I2D/IG ratio varied between 0.7 and 1.8. Raman D-peak (~1350cm-1) shows a strong dependence on growth temperature with the smallest ID/IG value of 0.15 at 1550°C. In the case of long growth, nitrogen and boron doping were detected by x-ray photoelectron spectroscopy with a small Raman D'-peak. A continuous graphene film with the rms roughness (1×1 μm2 area) of 0.32nm was shown by atomic force microscopy. Early stage of growth revealed circular shaped nucleation islands, the density and heights of which are ~15/μm2 and 1-2 graphene monolayer (ML), respectively. The hydrogen/methane flow ratio was found to be a critical parameter to obtain smooth 2D growth. Growth of h-BN is performed with ammonia borane, hydrogen and Ar. The growth is found to be critically dependent on the conditions of the ammonia boran precursor. Reproducible continuous films of h-BN are reported.
2D Variations in Coda Amplitudes in the Middle East
Pasyanos, Michael E.; Gok, Rengin; Walter, William R.
Here, coda amplitudes have proven to be a stable feature of seismograms, allowing one to reliably measure magnitudes for moderate to large-sized (M≥3) earthquakes over broad regions. Since smaller (M<3) earthquakes are only recorded at higher frequencies where we find larger interstation scatter, amplitude and magnitude estimates for these events are more variable, regional, and path dependent. In this study, we investigate coda amplitude measurements in the Middle East for 2-D variations in attenuation structure.
2D and 3D Traveling Salesman Problem
ERIC Educational Resources Information Center
Haxhimusa, Yll; Carpenter, Edward; Catrambone, Joseph; Foldes, David; Stefanov, Emil; Arns, Laura; Pizlo, Zygmunt
2011-01-01
When a two-dimensional (2D) traveling salesman problem (TSP) is presented on a computer screen, human subjects can produce near-optimal tours in linear time. In this study we tested human performance on a real and virtual floor, as well as in a three-dimensional (3D) virtual space. Human performance on the real floor is as good as that on a…
Exciton Dynamics of 2D Hybrid Perovskite Nanocrystal
NASA Astrophysics Data System (ADS)
Guo, Rui; Zhu, Zhuan; Boulesbaa, Abdelaziz; Venkatesan, Swaminathan; Xiao, Kai; Bao, Jiming; Yao, Yan; Li, Wenzhi
Organic-inorganic hybrid perovskites have emerged as promising materials for applications in photovoltaic and optoelectronic devices. Among the perovskites, two dimensional (2D) perovskites are of great interests due to their remarkable optical and electrical properties as well as the flexibility of material selection for the organic and inorganic moieties. In this study, we demonstrate the solution-phase growth of large square-shaped single-crystalline 2D hybrid perovskites of (C6H5C2H4 NH3) 2 PbBr4 with a few unit cells thickness. Compared to the bulk crystal, a band gap shift and new photoluminescence (PL) peak are observed from the hybrid perovskite sheets. Color of the 2D crystals can be tuned by adjusting the sheet thickness. Pump-probe spectroscopy is used to investigate the exciton dynamics and exhibits a biexponential decay with an amplitude-weighted lifetime of 16.7 ps. Such high-quality (C6H5C2H4 NH3) 2 PbBr4 sheets are expected to have high PL quantum efficiency which can be adopted for light-emitting devices. National Science Foundation (Grant No. CMMI-1334417 and DMR-1506640).
Hybrid 3D-2D printing for bone scaffolds fabrication
NASA Astrophysics Data System (ADS)
Seleznev, V. A.; Prinz, V. Ya
2017-02-01
It is a well-known fact that bone scaffold topography on micro- and nanometer scale influences the cellular behavior. Nano-scale surface modification of scaffolds allows the modulation of biological activity for enhanced cell differentiation. To date, there has been only a limited success in printing scaffolds with micro- and nano-scale features exposed on the surface. To improve on the currently available imperfect technologies, in our paper we introduce new hybrid technologies based on a combination of 2D (nano imprint) and 3D printing methods. The first method is based on using light projection 3D printing and simultaneous 2D nanostructuring of each of the layers during the formation of the 3D structure. The second method is based on the sequential integration of preliminarily created 2D nanostructured films into a 3D printed structure. The capabilities of the developed hybrid technologies are demonstrated with the example of forming 3D bone scaffolds. The proposed technologies can be used to fabricate complex 3D micro- and nanostructured products for various fields.
A novel point cloud registration using 2D image features
NASA Astrophysics Data System (ADS)
Lin, Chien-Chou; Tai, Yen-Chou; Lee, Jhong-Jin; Chen, Yong-Sheng
2017-01-01
Since a 3D scanner only captures a scene of a 3D object at a time, a 3D registration for multi-scene is the key issue of 3D modeling. This paper presents a novel and an efficient 3D registration method based on 2D local feature matching. The proposed method transforms the point clouds into 2D bearing angle images and then uses the 2D feature based matching method, SURF, to find matching pixel pairs between two images. The corresponding points of 3D point clouds can be obtained by those pixel pairs. Since the corresponding pairs are sorted by their distance between matching features, only the top half of the corresponding pairs are used to find the optimal rotation matrix by the least squares approximation. In this paper, the optimal rotation matrix is derived by orthogonal Procrustes method (SVD-based approach). Therefore, the 3D model of an object can be reconstructed by aligning those point clouds with the optimal transformation matrix. Experimental results show that the accuracy of the proposed method is close to the ICP, but the computation cost is reduced significantly. The performance is six times faster than the generalized-ICP algorithm. Furthermore, while the ICP requires high alignment similarity of two scenes, the proposed method is robust to a larger difference of viewing angle.
Cross-correlating 2D and 3D galaxy surveys
Passaglia, Samuel; Manzotti, Alessandro; Dodelson, Scott
2017-06-08
Galaxy surveys probe both structure formation and the expansion rate, making them promising avenues for understanding the dark universe. Photometric surveys accurately map the 2D distribution of galaxy positions and shapes in a given redshift range, while spectroscopic surveys provide sparser 3D maps of the galaxy distribution. We present a way to analyse overlapping 2D and 3D maps jointly and without loss of information. We represent 3D maps using spherical Fourier-Bessel (sFB) modes, which preserve radial coverage while accounting for the spherical sky geometry, and we decompose 2D maps in a spherical harmonic basis. In these bases, a simple expression exists for the cross-correlation of the two fields. One very powerful application is the ability to simultaneously constrain the redshift distribution of the photometric sample, the sample biases, and cosmological parameters. We use our framework to show that combined analysis of DESI and LSST can improve cosmological constraints by factors ofmore » $${\\sim}1.2$$ to $${\\sim}1.8$$ on the region where they overlap relative to identically sized disjoint regions. We also show that in the overlap of DES and SDSS-III in Stripe 82, cross-correlating improves photo-$z$ parameter constraints by factors of $${\\sim}2$$ to $${\\sim}12$$ over internal photo-$z$ reconstructions.« less
2D DOST based local phase pattern for face recognition
NASA Astrophysics Data System (ADS)
Moniruzzaman, Md.; Alam, Mohammad S.
2017-05-01
A new two dimensional (2-D) Discrete Orthogonal Stcokwell Transform (DOST) based Local Phase Pattern (LPP) technique has been proposed for efficient face recognition. The proposed technique uses 2-D DOST as preliminary preprocessing and local phase pattern to form robust feature signature which can effectively accommodate various 3D facial distortions and illumination variations. The S-transform, is an extension of the ideas of the continuous wavelet transform (CWT), is also known for its local spectral phase properties in time-frequency representation (TFR). It provides a frequency dependent resolution of the time-frequency space and absolutely referenced local phase information while maintaining a direct relationship with the Fourier spectrum which is unique in TFR. After utilizing 2-D Stransform as the preprocessing and build local phase pattern from extracted phase information yield fast and efficient technique for face recognition. The proposed technique shows better correlation discrimination compared to alternate pattern recognition techniques such as wavelet or Gabor based face recognition. The performance of the proposed method has been tested using the Yale and extended Yale facial database under different environments such as illumination variation and 3D changes in facial expressions. Test results show that the proposed technique yields better performance compared to alternate time-frequency representation (TFR) based face recognition techniques.
Design Application Translates 2-D Graphics to 3-D Surfaces
NASA Technical Reports Server (NTRS)
2007-01-01
Fabric Images Inc., specializing in the printing and manufacturing of fabric tension architecture for the retail, museum, and exhibit/tradeshow communities, designed software to translate 2-D graphics for 3-D surfaces prior to print production. Fabric Images' fabric-flattening design process models a 3-D surface based on computer-aided design (CAD) specifications. The surface geometry of the model is used to form a 2-D template, similar to a flattening process developed by NASA's Glenn Research Center. This template or pattern is then applied in the development of a 2-D graphic layout. Benefits of this process include 11.5 percent time savings per project, less material wasted, and the ability to improve upon graphic techniques and offer new design services. Partners include Exhibitgroup/Giltspur (end-user client: TAC Air, a division of Truman Arnold Companies Inc.), Jack Morton Worldwide (end-user client: Nickelodeon), as well as 3D Exhibits Inc., and MG Design Associates Corp.
An Intercomparison of 2-D Models Within a Common Framework
NASA Technical Reports Server (NTRS)
Weisenstein, Debra K.; Ko, Malcolm K. W.; Scott, Courtney J.; Jackman, Charles H.; Fleming, Eric L.; Considine, David B.; Kinnison, Douglas E.; Connell, Peter S.; Rotman, Douglas A.; Bhartia, P. K. (Technical Monitor)
2002-01-01
A model intercomparison among the Atmospheric and Environmental Research (AER) 2-D model, the Goddard Space Flight Center (GSFC) 2-D model, and the Lawrence Livermore National Laboratory 2-D model allows us to separate differences due to model transport from those due to the model's chemical formulation. This is accomplished by constructing two hybrid models incorporating the transport parameters of the GSFC and LLNL models within the AER model framework. By comparing the results from the native models (AER and e.g. GSFC) with those from the hybrid model (e.g. AER chemistry with GSFC transport), differences due to chemistry and transport can be identified. For the analysis, we examined an inert tracer whose emission pattern is based on emission from a High Speed Civil Transport (HSCT) fleet; distributions of trace species in the 2015 atmosphere; and the response of stratospheric ozone to an HSCT fleet. Differences in NO(y) in the upper stratosphere are found between models with identical transport, implying different model representations of atmospheric chemical processes. The response of O3 concentration to HSCT aircraft emissions differs in the models from both transport-dominated differences in the HSCT-induced perturbations of H2O and NO(y) as well as from differences in the model represent at ions of O3 chemical processes. The model formulations of cold polar processes are found to be the most significant factor in creating large differences in the calculated ozone perturbations
Splashing transients of 2D plasmons launched by swift electrons
Lin, Xiao; Kaminer, Ido; Shi, Xihang; ...
2017-01-27
Launching of plasmons by swift electrons has long been used in electron energy–loss spectroscopy (EELS) to investigate the plasmonic properties of ultrathin, or two-dimensional (2D), electron systems. However, the question of how a swift electron generates plasmons in space and time has never been answered. We address this issue by calculating and demonstrating the spatial-temporal dynamics of 2D plasmon generation in graphene. We predict a jet-like rise of excessive charge concentration that delays the generation of 2D plasmons in EELS, exhibiting an analog to the hydrodynamic Rayleigh jet in a splashing phenomenon before the launching of ripples. The photon radiation,more » analogous to the splashing sound, accompanies the plasmon emission and can be understood as being shaken off by the Rayleigh jet–like charge concentration. Considering this newly revealed process, we argue that previous estimates on the yields of graphene plasmons in EELS need to be reevaluated.« less
Cross-correlating 2D and 3D galaxy surveys
Passaglia, Samuel; Manzotti, Alessandro; Dodelson, Scott
Galaxy surveys probe both structure formation and the expansion rate, making them promising avenues for understanding the dark universe. Photometric surveys accurately map the 2D distribution of galaxy positions and shapes in a given redshift range, while spectroscopic surveys provide sparser 3D maps of the galaxy distribution. We present a way to analyse overlapping 2D and 3D maps jointly and without loss of information. We represent 3D maps using spherical Fourier-Bessel (sFB) modes, which preserve radial coverage while accounting for the spherical sky geometry, and we decompose 2D maps in a spherical harmonic basis. In these bases, a simple expression exists for the cross-correlation of the two fields. One very powerful application is the ability to simultaneously constrain the redshift distribution of the photometric sample, the sample biases, and cosmological parameters. We use our framework to show that combined analysis of DESI and LSST can improve cosmological constraints by factors ofmore » $${\\sim}1.2$$ to $${\\sim}1.8$$ on the region where they overlap relative to identically sized disjoint regions. We also show that in the overlap of DES and SDSS-III in Stripe 82, cross-correlating improves photo-$z$ parameter constraints by factors of $${\\sim}2$$ to $${\\sim}12$$ over internal photo-$z$ reconstructions.« less
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
Zhang, Na; Wang, Taisheng; Wu, Xing; Jiang, Chen; Zhang, Taiming; Jin, Bangkun; Ji, Hengxing; Bai, Wei; Bai, Ruke
2017-07-25
Recently, investigation on two-dimensional (2D) organic polymers has made great progress, and conjugated 2D polymers already play a dynamic role in both academic and practical applications. However, a convenient, noninterfacial approach to obtain single-layer 2D polymers in solution, especially in aqueous media, remains challenging. Herein, we present a facile, highly efficient, and versatile "1D to 2D" strategy for preparation of free-standing single-monomer-thick conjugated 2D polymers in water without any aid. The 2D structure was achieved by taking advantage of the side-by-side self-assembly of a rigid amphiphilic 1D polymer and following topochemical photopolymerization in water. The spontaneous formation of single-layer polymer sheets was driven by synergetic association of the hydrophobic interactions, π-π stacking interactions, and electrostatic repulsion. Both the supramolecular sheets and the covalent sheets were confirmed by spectroscopic analyses and electron microscope techniques. Moreover, in comparison of the supramolecular 2D polymer, the covalent 2D polymer sheets exhibited not only higher mechanical strength but also higher conductivity, which can be ascribed to the conjugated network within the covalent 2D polymer sheets.
Rhodopsin Photointermediates in 2D Crystals at Physiological Temperatures
Szundi, Istvan; Ruprecht, Jonathan J.; Epps, Jacqueline; Villa, Claudio; Swartz, Trevor E.; Lewis, James W.; Schertler, Gebhard F.X.; Kliger, David S.
2008-01-01
Bovine rhodopsin photointermediates formed in 2D rhodopsin crystal suspensions were studied by measuring the time dependent absorbance changes produced after excitation with 7 nanosecond laser pulses at 15, 25 and 35 °C. The crystalline environment favored the Meta I480 photointermediate, with its formation from Lumi beginning faster than it does in rhodopsin membrane suspensions at 35 °C and its decay to a 380 nm absorbing species being less complete than it is in the native membrane at all temperatures. Measurements performed at pH 5.5 in 2D crystals showed that the 380 nm absorbing product of Meta I480 decay did not display the anomalous pH dependence characteristic of classical Meta II in the native disk membrane. Crystal suspensions bleached at 35 °C and quenched to 19 °C showed that a rapid equilibrium existed on the ∼1 second time scale which suggests that the unprotonated predecessor of Meta II in the native membrane environment (sometimes called MIIa), forms in 2D rhodopsin crystals, but that the non-Schiff base proton uptake completing classical Meta II formation is blocked there. Thus, the 380 nm absorbance arises from an on-pathway intermediate in GPCR activation and does not result from early Schiff base hydrolysis. Kinetic modeling of the time-resolved absorbance data of the 2D crystals was generally consistent with such a mechanism, but details of kinetic spectral changes and the fact that the residuals of exponential fits were not as good as are obtained for rhodopsin in the native membrane suggested the photoexcited samples were heterogeneous. Variable fractional bleach due to the random orientation of linearly dichroic crystals relative to the linearly polarized laser was explored as a cause of heterogeneity but was found unlikely to fully account for it. The fact that the 380 nm product of photoexcitation of rhodopsin 2D crystals is on the physiological pathway of receptor activation suggests that determination of its structure would be of
Advancing Nucleosynthesis in Core-Collapse Supernovae Models Using 2D CHIMERA Simulations
NASA Astrophysics Data System (ADS)
Harris, J. A.; Hix, W. R.; Chertkow, M. A.; Bruenn, S. W.; Lentz, E. J.; Messer, O. B.; Mezzacappa, A.; Blondin, J. M.; Marronetti, P.; Yakunin, K.
2014-01-01
The deaths of massive stars as core-collapse supernovae (CCSN) serve as a crucial link in understanding galactic chemical evolution since the birth of the universe via the Big Bang. We investigate CCSN in polar axisymmetric simulations using the multidimensional radiation hydrodynamics code CHIMERA. Computational costs have traditionally constrained the evolution of the nuclear composition in CCSN models to, at best, a 14-species α-network. However, the limited capacity of the α-network to accurately evolve detailed composition, the neutronization and the nuclear energy generation rate has fettered the ability of prior CCSN simulations to accurately reproduce the chemical abundances and energy distributions as known from observations. These deficits can be partially ameliorated by "post-processing" with a more realistic network. Lagrangian tracer particles placed throughout the star record the temporal evolution of the initial simulation and enable the extension of the nuclear network evolution by incorporating larger systems in post-processing nucleosynthesis calculations. We present post-processing results of the four ab initio axisymmetric CCSN 2D models of Bruenn et al. (2013) evolved with the smaller α-network, and initiated from stellar metallicity, non-rotating progenitors of mass 12, 15, 20, and 25 M⊙ from Woosley & Heger (2007). As a test of the limitations of post-processing, we provide preliminary results from an ongoing simulation of the 15 M⊙ model evolved with a realistic 150 species nuclear reaction network in situ. With more accurate energy generation rates and an improved determination of the thermodynamic trajectories of the tracer particles, we can better unravel the complicated multidimensional "mass-cut" in CCSN simulations and probe for less energetically significant nuclear processes like the νp-process and the r-process, which require still larger networks.
A Nonrigid Kernel-Based Framework for 2D-3D Pose Estimation and 2D Image Segmentation
Sandhu, Romeil; Dambreville, Samuel; Yezzi, Anthony; Tannenbaum, Allen
2013-01-01
In this work, we present a nonrigid approach to jointly solving the tasks of 2D-3D pose estimation and 2D image segmentation. In general, most frameworks that couple both pose estimation and segmentation assume that one has exact knowledge of the 3D object. However, under nonideal conditions, this assumption may be violated if only a general class to which a given shape belongs is given (e.g., cars, boats, or planes). Thus, we propose to solve the 2D-3D pose estimation and 2D image segmentation via nonlinear manifold learning of 3D embedded shapes for a general class of objects or deformations for which one may not be able to associate a skeleton model. Thus, the novelty of our method is threefold: First, we present and derive a gradient flow for the task of nonrigid pose estimation and segmentation. Second, due to the possible nonlinear structures of one’s training set, we evolve the preimage obtained through kernel PCA for the task of shape analysis. Third, we show that the derivation for shape weights is general. This allows us to use various kernels, as well as other statistical learning methodologies, with only minimal changes needing to be made to the overall shape evolution scheme. In contrast with other techniques, we approach the nonrigid problem, which is an infinite-dimensional task, with a finite-dimensional optimization scheme. More importantly, we do not explicitly need to know the interaction between various shapes such as that needed for skeleton models as this is done implicitly through shape learning. We provide experimental results on several challenging pose estimation and segmentation scenarios. PMID:20733218
Cytochrome P450-2D6 Screening Among Elderly Using Antidepressants (CYSCE)
2017-08-15
Depression; Depressive Disorder; Poor Metabolizer Due to Cytochrome P450 CYP2D6 Variant; Intermediate Metabolizer Due to Cytochrome P450 CYP2D6 Variant; Ultrarapid Metabolizer Due to Cytochrome P450 CYP2D6 Variant