Neutral evolution of mutational robustness

PubMed Central

van Nimwegen, Erik; Crutchfield, James P.; Huynen, Martijn

1999-01-01

We introduce and analyze a general model of a population evolving over a network of selectively neutral genotypes. We show that the population’s limit distribution on the neutral network is solely determined by the network topology and given by the principal eigenvector of the network’s adjacency matrix. Moreover, the average number of neutral mutant neighbors per individual is given by the matrix spectral radius. These results quantify the extent to which populations evolve mutational robustness—the insensitivity of the phenotype to mutations—and thus reduce genetic load. Because the average neutrality is independent of evolutionary parameters—such as mutation rate, population size, and selective advantage—one can infer global statistics of neutral network topology by using simple population data available from in vitro or in vivo evolution. Populations evolving on neutral networks of RNA secondary structures show excellent agreement with our theoretical predictions. PMID:10449760

Nonlinear signaling on biological networks: The role of stochasticity and spectral clustering

NASA Astrophysics Data System (ADS)

Hernandez-Hernandez, Gonzalo; Myers, Jesse; Alvarez-Lacalle, Enrique; Shiferaw, Yohannes

2017-03-01

Signal transduction within biological cells is governed by networks of interacting proteins. Communication between these proteins is mediated by signaling molecules which bind to receptors and induce stochastic transitions between different conformational states. Signaling is typically a cooperative process which requires the occurrence of multiple binding events so that reaction rates have a nonlinear dependence on the amount of signaling molecule. It is this nonlinearity that endows biological signaling networks with robust switchlike properties which are critical to their biological function. In this study we investigate how the properties of these signaling systems depend on the network architecture. Our main result is that these nonlinear networks exhibit bistability where the network activity can switch between states that correspond to a low and high activity level. We show that this bistable regime emerges at a critical coupling strength that is determined by the spectral structure of the network. In particular, the set of nodes that correspond to large components of the leading eigenvector of the adjacency matrix determines the onset of bistability. Above this transition the eigenvectors of the adjacency matrix determine a hierarchy of clusters, defined by its spectral properties, which are activated sequentially with increasing network activity. We argue further that the onset of bistability occurs either continuously or discontinuously depending upon whether the leading eigenvector is localized or delocalized. Finally, we show that at low network coupling stochastic transitions to the active branch are also driven by the set of nodes that contribute more strongly to the leading eigenvector. However, at high coupling, transitions are insensitive to network structure since the network can be activated by stochastic transitions of a few nodes. Thus this work identifies important features of biological signaling networks that may underlie their biological function.

Role of adjacency-matrix degeneracy in maximum-entropy-weighted network models

NASA Astrophysics Data System (ADS)

Sagarra, O.; Pérez Vicente, C. J.; Díaz-Guilera, A.

2015-11-01

Complex network null models based on entropy maximization are becoming a powerful tool to characterize and analyze data from real systems. However, it is not easy to extract good and unbiased information from these models: A proper understanding of the nature of the underlying events represented in them is crucial. In this paper we emphasize this fact stressing how an accurate counting of configurations compatible with given constraints is fundamental to build good null models for the case of networks with integer-valued adjacency matrices constructed from an aggregation of one or multiple layers. We show how different assumptions about the elements from which the networks are built give rise to distinctively different statistics, even when considering the same observables to match those of real data. We illustrate our findings by applying the formalism to three data sets using an open-source software package accompanying the present work and demonstrate how such differences are clearly seen when measuring network observables.

Visualizing weighted networks: a performance comparison of adjacency matrices versus node-link diagrams

NASA Astrophysics Data System (ADS)

McIntire, John P.; Osesina, O. Isaac; Bartley, Cecilia; Tudoreanu, M. Eduard; Havig, Paul R.; Geiselman, Eric E.

2012-06-01

Ensuring the proper and effective ways to visualize network data is important for many areas of academia, applied sciences, the military, and the public. Fields such as social network analysis, genetics, biochemistry, intelligence, cybersecurity, neural network modeling, transit systems, communications, etc. often deal with large, complex network datasets that can be difficult to interact with, study, and use. There have been surprisingly few human factors performance studies on the relative effectiveness of different graph drawings or network diagram techniques to convey information to a viewer. This is particularly true for weighted networks which include the strength of connections between nodes, not just information about which nodes are linked to other nodes. We describe a human factors study in which participants performed four separate network analysis tasks (finding a direct link between given nodes, finding an interconnected node between given nodes, estimating link strengths, and estimating the most densely interconnected nodes) on two different network visualizations: an adjacency matrix with a heat-map versus a node-link diagram. The results should help shed light on effective methods of visualizing network data for some representative analysis tasks, with the ultimate goal of improving usability and performance for viewers of network data displays.

Adaptive Calcified Matrix Response of Dental Pulp to Bacterial Invasion Is Associated with Establishment of a Network of Glial Fibrillary Acidic Protein+/Glutamine Synthetase+ Cells

PubMed Central

Farahani, Ramin M.; Nguyen, Ky-Anh; Simonian, Mary; Hunter, Neil

2010-01-01

We report evidence for anatomical and functional changes of dental pulp in response to bacterial invasion through dentin that parallel responses to noxious stimuli reported in neural crest-derived sensory tissues. Sections of resin-embedded carious adult molar teeth were prepared for immunohistochemistry, in situ hybridization, ultrastructural analysis, and microdissection to extract mRNA for quantitative analyses. In odontoblasts adjacent to the leading edge of bacterial invasion in carious teeth, expression levels of the gene encoding dentin sialo-protein were 16-fold greater than in odontoblasts of healthy teeth, reducing progressively with distance from this site of the carious lesion. In contrast, gene expression for dentin matrix protein-1 by odontoblasts was completely suppressed in carious teeth relative to healthy teeth. These changes in gene expression were related to a gradient of deposited reactionary dentin that displayed a highly modified structure. In carious teeth, interodontoblastic dentin sialo-protein− cells expressing glutamine synthetase (GS) showed up-regulation of glial fibrillary acidic protein (GFAP). These cells extended processes that associated with odontoblasts. Furthermore, connexin 43 established a linkage between adjacent GFAP+/GS+ cells in carious teeth only. These findings indicate an adaptive pulpal response to encroaching caries that includes the deposition of modified, calcified, dentin matrix associated with networks of GFAP+/GS+ interodontoblastic cells. A regulatory role for the networks of GFAP+/GS+ cells is proposed, mediated by the secretion of glutamate to modulate odontoblastic response. PMID:20802180

The ultra-structural organization of the elastic network in the intra- and inter-lamellar matrix of the intervertebral disc.

PubMed

Tavakoli, J; Elliott, D M; Costi, J J

2017-08-01

The inter-lamellar matrix (ILM)-located between adjacent lamellae of the annulus fibrosus-consists of a complex structure of elastic fibers, while elastic fibers of the intra-lamellar region are aligned predominantly parallel to the collagen fibers. The organization of elastic fibers under low magnification, in both inter- and intra-lamellar regions, was studied by light microscopic analysis of histologically prepared samples; however, little is known about their ultrastructure. An ultrastructural visualization of elastic fibers in the inter-lamellar matrix is crucial for describing their contribution to structural integrity, as well as mechanical properties of the annulus fibrosus. The aims of this study were twofold: first, to present an ultrastructural analysis of the elastic fiber network in the ILM and intra-lamellar region, including cross section (CS) and in-plane (IP) lamellae, of the AF using Scanning Electron Microscopy (SEM) and second, to -compare the elastic fiber orientation between the ILM and intra-lamellar region. Four samples (lumbar sheep discs) from adjacent sections (30μm thickness) of anterior annulus were partially digested by a developed NaOH-sonication method for visualization of elastic fibers by SEM. Elastic fiber orientation and distribution were quantified relative to the tangential to circumferential reference axis. Visualization of the ILM under high magnification revealed a dense network of elastic fibers that has not been previously described. Within the ILM, elastic fibers form a complex network, consisting of different size and shape fibers, which differed to those located in the intra-lamellar region. For both regions, the majority of fibers were oriented near 0° with respect to tangential to circumferential (TCD) direction and two minor symmetrical orientations of approximately±45°. Statistically, the orientation of elastic fibers between the ILM and intra-lamellar region was not different (p=0.171). The present study used extracellular matrix partial digestion to address significant gaps in understanding of disc microstructure and will contribute to multidisciplinary ultrastructure-function studies. Visualization of the intra-lamellar matrix under high magnification revealed a dense network of elastic fibers that has not been previously described. The present study used extracellular matrix partial digestion to address significant gaps in understanding of disc microstructure and will contribute to multidisciplinary ultrastructure-function studies. Copyright © 2017 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.

Controllability of flow-conservation networks

NASA Astrophysics Data System (ADS)

Zhao, Chen; Zeng, An; Jiang, Rui; Yuan, Zhengzhong; Wang, Wen-Xu

2017-07-01

The ultimate goal of exploring complex networks is to control them. As such, controllability of complex networks has been intensively investigated. Despite recent advances in studying the impact of a network's topology on its controllability, a comprehensive understanding of the synergistic impact of network topology and dynamics on controllability is still lacking. Here, we explore the controllability of flow-conservation networks, trying to identify the minimal number of driver nodes that can guide the network to any desirable state. We develop a method to analyze the controllability on flow-conservation networks based on exact controllability theory, transforming the original analysis on adjacency matrix to Laplacian matrix. With this framework, we systematically investigate the impact of some key factors of networks, including link density, link directionality, and link polarity, on the controllability of these networks. We also obtain the analytical equations by investigating the network's structural properties approximatively and design the efficient tools. Finally, we consider some real networks with flow dynamics, finding that their controllability is significantly different from that predicted by only considering the topology. These findings deepen our understanding of network controllability with flow-conservation dynamics and provide a general framework to incorporate real dynamics in the analysis of network controllability.

Characterization of complex networks by higher order neighborhood properties

NASA Astrophysics Data System (ADS)

Andrade, R. F. S.; Miranda, J. G. V.; Pinho, S. T. R.; Lobão, T. P.

2008-01-01

A concept of higher order neighborhood in complex networks, introduced previously [Phys. Rev. E 73, 046101 (2006)], is systematically explored to investigate larger scale structures in complex networks. The basic idea is to consider each higher order neighborhood as a network in itself, represented by a corresponding adjacency matrix, and to settle a plenty of new parameters in order to obtain a best characterization of the whole network. Usual network indices are then used to evaluate the properties of each neighborhood. The identification of high order neighborhoods is also regarded as intermediary step towards the evaluation of global network properties, like the diameter, average shortest path between node, and network fractal dimension. Results for a large number of typical networks are presented and discussed.

Referee Networks and Their Spectral Properties

NASA Astrophysics Data System (ADS)

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

2005-09-01

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

Estimating the Importance of Terrorists in a Terror Network

NASA Astrophysics Data System (ADS)

Elhajj, Ahmed; Elsheikh, Abdallah; Addam, Omar; Alzohbi, Mohamad; Zarour, Omar; Aksaç, Alper; Öztürk, Orkun; Özyer, Tansel; Ridley, Mick; Alhajj, Reda

While criminals may start their activities at individual level, the same is in general not true for terrorists who are mostly organized in well established networks. The effectiveness of a terror network could be realized by watching many factors, including the volume of activities accomplished by its members, the capabilities of its members to hide, and the ability of the network to grow and to maintain its influence even after the loss of some members, even leaders. Social network analysis, data mining and machine learning techniques could play important role in measuring the effectiveness of a network in general and in particular a terror network in support of the work presented in this chapter. We present a framework that employs clustering, frequent pattern mining and some social network analysis measures to determine the effectiveness of a network. The clustering and frequent pattern mining techniques start with the adjacency matrix of the network. For clustering, we utilize entries in the table by considering each row as an object and each column as a feature. Thus features of a network member are his/her direct neighbors. We maintain the weight of links in case of weighted network links. For frequent pattern mining, we consider each row of the adjacency matrix as a transaction and each column as an item. Further, we map entries into a 0/1 scale such that every entry whose value is greater than zero is assigned the value one; entries keep the value zero otherwise. This way we can apply frequent pattern mining algorithms to determine the most influential members in a network as well as the effect of removing some members or even links between members of a network. We also investigate the effect of adding some links between members. The target is to study how the various members in the network change role as the network evolves. This is measured by applying some social network analysis measures on the network at each stage during the development. We report some interesting results related to two benchmark networks: the first is 9/11 and the second is Madrid bombing.

Balanced Centrality of Networks.

PubMed

Debono, Mark; Lauri, Josef; Sciriha, Irene

2014-01-01

There is an age-old question in all branches of network analysis. What makes an actor in a network important, courted, or sought? Both Crossley and Bonacich contend that rather than its intrinsic wealth or value, an actor's status lies in the structures of its interactions with other actors. Since pairwise relation data in a network can be stored in a two-dimensional array or matrix, graph theory and linear algebra lend themselves as great tools to gauge the centrality (interpreted as importance, power, or popularity, depending on the purpose of the network) of each actor. We express known and new centralities in terms of only two matrices associated with the network. We show that derivations of these expressions can be handled exclusively through the main eigenvectors (not orthogonal to the all-one vector) associated with the adjacency matrix. We also propose a centrality vector (SWIPD) which is a linear combination of the square, walk, power, and degree centrality vectors with weightings of the various centralities depending on the purpose of the network. By comparing actors' scores for various weightings, a clear understanding of which actors are most central is obtained. Moreover, for threshold networks, the (SWIPD) measure turns out to be independent of the weightings.

Spectra of Adjacency Matrices in Networks of Extreme Introverts and Extroverts

NASA Astrophysics Data System (ADS)

Bassler, Kevin E.; Ezzatabadipour, Mohammadmehdi; Zia, R. K. P.

Many interesting properties were discovered in recent studies of preferred degree networks, suitable for describing social behavior of individuals who tend to prefer a certain number of contacts. In an extreme version (coined the XIE model), introverts always cut links while extroverts always add them. While the intra-group links are static, the cross-links are dynamic and lead to an ensemble of bipartite graphs, with extraordinary correlations between elements of the incidence matrix: nij In the steady state, this system can be regarded as one in thermal equilibrium with long-ranged interactions between the nij's, and displays an extreme Thouless effect. Here, we report simulation studies of a different perspective of networks, namely, the spectra associated with this ensemble of adjacency matrices {aij } . As a baseline, we first consider the spectra associated with a simple random (Erdős-Rényi) ensemble of bipartite graphs, where simulation results can be understood analytically. Work supported by the NSF through Grant DMR-1507371.

Graph Coarsening for Path Finding in Cybersecurity Graphs

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hogan, Emilie A.; Johnson, John R.; Halappanavar, Mahantesh

2013-01-01

n the pass-the-hash attack, hackers repeatedly steal password hashes and move through a computer network with the goal of reaching a computer with high level administrative privileges. In this paper we apply graph coarsening in network graphs for the purpose of detecting hackers using this attack or assessing the risk level of the network's current state. We repeatedly take graph minors, which preserve the existence of paths in the graph, and take powers of the adjacency matrix to count the paths. This allows us to detect the existence of paths as well as find paths that have high risk ofmore » being used by adversaries.« less

A biological approach to assembling tissue modules through endothelial capillary network formation.

PubMed

Riesberg, Jeremiah J; Shen, Wei

2015-09-01

To create functional tissues having complex structures, bottom-up approaches to assembling small tissue modules into larger constructs have been emerging. Most of these approaches are based on chemical reactions or physical interactions at the interface between tissue modules. Here we report a biological assembly approach to integrate small tissue modules through endothelial capillary network formation. When adjacent tissue modules contain appropriate extracellular matrix materials and cell types that support robust endothelial capillary network formation, capillary tubules form and grow across the interface, resulting in assembly of the modules into a single, larger construct. It was shown that capillary networks formed in modules of dense fibrin gels seeded with human umbilical vein endothelial cells (HUVECs) and mesenchymal stem cells (MSCs); adjacent modules were firmly assembled into an integrated construct having a strain to failure of 117 ± 26%, a tensile strength of 2208 ± 83 Pa and a Young's modulus of 2548 ± 574 Pa. Under the same culture conditions, capillary networks were absent in modules of dense fibrin gels seeded with either HUVECs or MSCs alone; adjacent modules disconnected even when handled gently. This biological assembly approach eliminates the need for chemical reactions or physical interactions and their associated limitations. In addition, the integrated constructs are prevascularized, and therefore this bottom-up assembly approach may also help address the issue of vascularization, another key challenge in tissue engineering. Copyright © 2015 John Wiley & Sons, Ltd.

Network discovery with DCM

PubMed Central

Friston, Karl J.; Li, Baojuan; Daunizeau, Jean; Stephan, Klaas E.

2011-01-01

This paper is about inferring or discovering the functional architecture of distributed systems using Dynamic Causal Modelling (DCM). We describe a scheme that recovers the (dynamic) Bayesian dependency graph (connections in a network) using observed network activity. This network discovery uses Bayesian model selection to identify the sparsity structure (absence of edges or connections) in a graph that best explains observed time-series. The implicit adjacency matrix specifies the form of the network (e.g., cyclic or acyclic) and its graph-theoretical attributes (e.g., degree distribution). The scheme is illustrated using functional magnetic resonance imaging (fMRI) time series to discover functional brain networks. Crucially, it can be applied to experimentally evoked responses (activation studies) or endogenous activity in task-free (resting state) fMRI studies. Unlike conventional approaches to network discovery, DCM permits the analysis of directed and cyclic graphs. Furthermore, it eschews (implausible) Markovian assumptions about the serial independence of random fluctuations. The scheme furnishes a network description of distributed activity in the brain that is optimal in the sense of having the greatest conditional probability, relative to other networks. The networks are characterised in terms of their connectivity or adjacency matrices and conditional distributions over the directed (and reciprocal) effective connectivity between connected nodes or regions. We envisage that this approach will provide a useful complement to current analyses of functional connectivity for both activation and resting-state studies. PMID:21182971

Inferring Time-Varying Network Topologies from Gene Expression Data

PubMed Central

2007-01-01

Most current methods for gene regulatory network identification lead to the inference of steady-state networks, that is, networks prevalent over all times, a hypothesis which has been challenged. There has been a need to infer and represent networks in a dynamic, that is, time-varying fashion, in order to account for different cellular states affecting the interactions amongst genes. In this work, we present an approach, regime-SSM, to understand gene regulatory networks within such a dynamic setting. The approach uses a clustering method based on these underlying dynamics, followed by system identification using a state-space model for each learnt cluster—to infer a network adjacency matrix. We finally indicate our results on the mouse embryonic kidney dataset as well as the T-cell activation-based expression dataset and demonstrate conformity with reported experimental evidence. PMID:18309363

Inferring time-varying network topologies from gene expression data.

PubMed

Rao, Arvind; Hero, Alfred O; States, David J; Engel, James Douglas

2007-01-01

Most current methods for gene regulatory network identification lead to the inference of steady-state networks, that is, networks prevalent over all times, a hypothesis which has been challenged. There has been a need to infer and represent networks in a dynamic, that is, time-varying fashion, in order to account for different cellular states affecting the interactions amongst genes. In this work, we present an approach, regime-SSM, to understand gene regulatory networks within such a dynamic setting. The approach uses a clustering method based on these underlying dynamics, followed by system identification using a state-space model for each learnt cluster--to infer a network adjacency matrix. We finally indicate our results on the mouse embryonic kidney dataset as well as the T-cell activation-based expression dataset and demonstrate conformity with reported experimental evidence.

Stability and instability of a neuron network with excitatory and inhibitory small-world connections.

PubMed

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.

Exploring and Making Sense of Large Graphs

DTIC Science & Technology

2015-08-01

and bold) are n × n ; vectors (lower-case bold) are n × 1 column vectors, and scalars (in lower-case plain font) typically correspond to strength of...graph is often denoted as |V| or n . Edges or Links: A finite set E of lines between objects in a graph. The edges represent relationships between the...Adjacency matrix of a simple, unweighted and undirected graph. Adjacency matrix: The adjacency matrix of a graph G is an n × n matrix A, whose element aij

On the Topologic Properties of River Networks

NASA Astrophysics Data System (ADS)

Sarker, S.; Singh, A.

2017-12-01

River network is an important landscape feature and has been studied extensively from a range of geomorphological and hydrological perspective. However, quantifying topologic dynamics and reorganization of river networks is becoming more and more challenging under changing natural and anthropogenic forcings. Here, we use a graph-theoretical approach to study topologic properties of natural and simulated river networks for a range of climatic and tectonic conditions. Among other metrics, we use betweeness and eigenvector centrality distributions computed using adjacency matrix of river networks and show their dependence on energy exponent γ that characterizes mechanism of erosional processes on a landscape. We further compare these topologic characteristics of landscape to geomorphic features such as slope-area curve and drainage density. Furthermore, we identify locations of critical nodes and links on a network as a function of energy exponent γ to understand network robustness and vulnerability under external attacks.

Myosin phosphatase Fine-tunes Zebrafish Motoneuron Position during Axonogenesis

PubMed Central

Granato, Michael

2016-01-01

During embryogenesis the spinal cord shifts position along the anterior-posterior axis relative to adjacent tissues. How motor neurons whose cell bodies are located in the spinal cord while their axons reside in adjacent tissues compensate for such tissue shift is not well understood. Using live cell imaging in zebrafish, we show that as motor axons exit from the spinal cord and extend through extracellular matrix produced by adjacent notochord cells, these cells shift several cell diameters caudally. Despite this pronounced shift, individual motoneuron cell bodies stay aligned with their extending axons. We find that this alignment requires myosin phosphatase activity within motoneurons, and that mutations in the myosin phosphatase subunit mypt1 increase myosin phosphorylation causing a displacement between motoneuron cell bodies and their axons. Thus, we demonstrate that spinal motoneurons fine-tune their position during axonogenesis and we identify the myosin II regulatory network as a key regulator. PMID:27855159

Relating Topological Determinants of Complex Networks to Their Spectral Properties: Structural and Dynamical Effects

NASA Astrophysics Data System (ADS)

Castellano, Claudio; Pastor-Satorras, Romualdo

2017-10-01

The largest eigenvalue of a network's adjacency matrix and its associated principal eigenvector are key elements for determining the topological structure and the properties of dynamical processes mediated by it. We present a physically grounded expression relating the value of the largest eigenvalue of a given network to the largest eigenvalue of two network subgraphs, considered as isolated: the hub with its immediate neighbors and the densely connected set of nodes with maximum K -core index. We validate this formula by showing that it predicts, with good accuracy, the largest eigenvalue of a large set of synthetic and real-world topologies. We also present evidence of the consequences of these findings for broad classes of dynamics taking place on the networks. As a by-product, we reveal that the spectral properties of heterogeneous networks built according to the linear preferential attachment model are qualitatively different from those of their static counterparts.

Network Dynamics of Innovation Processes.

PubMed

Iacopini, Iacopo; Milojević, Staša; Latora, Vito

2018-01-26

We introduce a model for the emergence of innovations, in which cognitive processes are described as random walks on the network of links among ideas or concepts, and an innovation corresponds to the first visit of a node. The transition matrix of the random walk depends on the network weights, while in turn the weight of an edge is reinforced by the passage of a walker. The presence of the network naturally accounts for the mechanism of the "adjacent possible," and the model reproduces both the rate at which novelties emerge and the correlations among them observed empirically. We show this by using synthetic networks and by studying real data sets on the growth of knowledge in different scientific disciplines. Edge-reinforced random walks on complex topologies offer a new modeling framework for the dynamics of correlated novelties and are another example of coevolution of processes and networks.

Effect of tumor resection on the characteristics of functional brain networks.

PubMed

Wang, H; Douw, L; Hernández, J M; Reijneveld, J C; Stam, C J; Van Mieghem, P

2010-08-01

Brain functioning such as cognitive performance depends on the functional interactions between brain areas, namely, the functional brain networks. The functional brain networks of a group of patients with brain tumors are measured before and after tumor resection. In this work, we perform a weighted network analysis to understand the effect of neurosurgery on the characteristics of functional brain networks. Statistically significant changes in network features have been discovered in the beta (13-30 Hz) band after neurosurgery: the link weight correlation around nodes and within triangles increases which implies improvement in local efficiency of information transfer and robustness; the clustering of high link weights in a subgraph becomes stronger, which enhances the global transport capability; and the decrease in the synchronization or virus spreading threshold, revealed by the increase in the largest eigenvalue of the adjacency matrix, which suggests again the improvement of information dissemination.

Network Dynamics of Innovation Processes

NASA Astrophysics Data System (ADS)

Iacopini, Iacopo; Milojević, Staša; Latora, Vito

2018-01-01

We introduce a model for the emergence of innovations, in which cognitive processes are described as random walks on the network of links among ideas or concepts, and an innovation corresponds to the first visit of a node. The transition matrix of the random walk depends on the network weights, while in turn the weight of an edge is reinforced by the passage of a walker. The presence of the network naturally accounts for the mechanism of the "adjacent possible," and the model reproduces both the rate at which novelties emerge and the correlations among them observed empirically. We show this by using synthetic networks and by studying real data sets on the growth of knowledge in different scientific disciplines. Edge-reinforced random walks on complex topologies offer a new modeling framework for the dynamics of correlated novelties and are another example of coevolution of processes and networks.

An ultra-compact and low loss passive beam-forming network integrated on chip with off chip linear array

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lepkowski, Stefan Mark

2015-05-01

The work here presents a review of beam forming architectures. As an example, the author presents an 8x8 Butler Matrix passive beam forming network including the schematic, design/modeling, operation, and simulated results. The limiting factor in traditional beam formers has been the large size dictated by transmission line based couplers. By replacing these couplers with transformer-based couplers, the matrix size is reduced substantially allowing for on chip compact integration. In the example presented, the core area, including the antenna crossover, measures 0.82mm×0.39mm (0.48% the size of a branch line coupler at the same frequency). The simulated beam forming achieves amore » peak PNR of 17.1 dB and 15dB from 57 to 63GHz. At the 60GHz center frequency the average insertion loss is simulated to be 3.26dB. The 8x8 Butler Matrix feeds into an 8-element antenna array to show the array patterns with single beam and adjacent beam isolation.« less

Understanding the influence of all nodes in a network

PubMed Central

Lawyer, Glenn

2015-01-01

Centrality measures such as the degree, k-shell, or eigenvalue centrality can identify a network's most influential nodes, but are rarely usefully accurate in quantifying the spreading power of the vast majority of nodes which are not highly influential. The spreading power of all network nodes is better explained by considering, from a continuous-time epidemiological perspective, the distribution of the force of infection each node generates. The resulting metric, the expected force, accurately quantifies node spreading power under all primary epidemiological models across a wide range of archetypical human contact networks. When node power is low, influence is a function of neighbor degree. As power increases, a node's own degree becomes more important. The strength of this relationship is modulated by network structure, being more pronounced in narrow, dense networks typical of social networking and weakening in broader, looser association networks such as the Internet. The expected force can be computed independently for individual nodes, making it applicable for networks whose adjacency matrix is dynamic, not well specified, or overwhelmingly large. PMID:25727453

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.

Separating temporal and topological effects in walk-based network centrality.

PubMed

Colman, Ewan R; Charlton, Nathaniel

2016-07-01

The recently introduced concept of dynamic communicability is a valuable tool for ranking the importance of nodes in a temporal network. Two metrics, broadcast score and receive score, were introduced to measure the centrality of a node with respect to a model of contagion based on time-respecting walks. This article examines the temporal and structural factors influencing these metrics by considering a versatile stochastic temporal network model. We analytically derive formulas to accurately predict the expectation of the broadcast and receive scores when one or more columns in a temporal edge-list are shuffled. These methods are then applied to two publicly available data sets and we quantify how much the centrality of each individual depends on structural or temporal influences. From our analysis, we highlight two practical contributions: a way to control for temporal variation when computing dynamic communicability and the conclusion that the broadcast and receive scores can, under a range of circumstances, be replaced by the row and column sums of the matrix exponential of a weighted adjacency matrix given by the data.

Separating temporal and topological effects in walk-based network centrality

NASA Astrophysics Data System (ADS)

Colman, Ewan R.; Charlton, Nathaniel

2016-07-01

The recently introduced concept of dynamic communicability is a valuable tool for ranking the importance of nodes in a temporal network. Two metrics, broadcast score and receive score, were introduced to measure the centrality of a node with respect to a model of contagion based on time-respecting walks. This article examines the temporal and structural factors influencing these metrics by considering a versatile stochastic temporal network model. We analytically derive formulas to accurately predict the expectation of the broadcast and receive scores when one or more columns in a temporal edge-list are shuffled. These methods are then applied to two publicly available data sets and we quantify how much the centrality of each individual depends on structural or temporal influences. From our analysis, we highlight two practical contributions: a way to control for temporal variation when computing dynamic communicability and the conclusion that the broadcast and receive scores can, under a range of circumstances, be replaced by the row and column sums of the matrix exponential of a weighted adjacency matrix given by the data.

"Time-dependent flow-networks"

NASA Astrophysics Data System (ADS)

Tupikina, Liubov; Molkentin, Nora; Lopez, Cristobal; Hernandez-Garcia, Emilio; Marwan, Norbert; Kurths, Jürgen

2015-04-01

Complex networks have been successfully applied to various systems such as society, technology, and recently climate. Links in a climate network are defined between two geographical locations if the correlation between the time series of some climate variable is higher than a threshold. Therefore, network links are considered to imply information or heat exchange. However, the relationship between the oceanic and atmospheric flows and the climate network's structure is still unclear. Recently, a theoretical approach verifying the correlation between ocean currents and surface air temperature networks has been introduced, where the Pearson correlation networks were constructed from advection-diffusion dynamics on an underlying flow. Since the continuous approach has its limitations, i.e. high computational complexity and fixed variety of the flows in the underlying system, we introduce a new, method of flow-networks for changing in time velocity fields including external forcing in the system, noise and temperature-decay. Method of the flow-network construction can be divided into several steps: first we obtain the linear recursive equation for the temperature time-series. Then we compute the correlation matrix for time-series averaging the tensor product over all realizations of the noise, which we interpret as a weighted adjacency matrix of the flow-network and analyze using network measures. We apply the method to different types of moving flows with geographical relevance such as meandering flow. Analyzing the flow-networks using network measures we find that our approach can highlight zones of high velocity by degree and transition zones by betweenness, while the combination of these network measures can uncover how the flow propagates within time. Flow-networks can be powerful tool to understand the connection between system's dynamics and network's topology analyzed using network measures in order to shed light on different climatic phenomena.

Slow-down or speed-up of inter- and intra-cluster diffusion of controversial knowledge in stubborn communities based on a small world network

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.

Social climber attachment in forming networks produces a phase transition in a measure of connectivity

NASA Astrophysics Data System (ADS)

Taylor, Dane; Larremore, Daniel B.

2012-09-01

The formation and fragmentation of networks are typically studied using percolation theory, but most previous research has been restricted to studying a phase transition in cluster size, examining the emergence of a giant component. This approach does not study the effects of evolving network structure on dynamics that occur at the nodes, such as the synchronization of oscillators and the spread of information, epidemics, and neuronal excitations. We introduce and analyze an alternative link-formation rule, called social climber (SC) attachment, that may be combined with arbitrary percolation models to produce a phase transition using the largest eigenvalue of the network adjacency matrix as the order parameter. This eigenvalue is significant in the analyses of many network-coupled dynamical systems in which it measures the quality of global coupling and is hence a natural measure of connectivity. We highlight the important self-organized properties of SC attachment and discuss implications for controlling dynamics on networks.

Enhanced Detectability of Community Structure in Multilayer Networks through Layer Aggregation.

PubMed

Taylor, Dane; Shai, Saray; Stanley, Natalie; Mucha, Peter J

2016-06-03

Many systems are naturally represented by a multilayer network in which edges exist in multiple layers that encode different, but potentially related, types of interactions, and it is important to understand limitations on the detectability of community structure in these networks. Using random matrix theory, we analyze detectability limitations for multilayer (specifically, multiplex) stochastic block models (SBMs) in which L layers are derived from a common SBM. We study the effect of layer aggregation on detectability for several aggregation methods, including summation of the layers' adjacency matrices for which we show the detectability limit vanishes as O(L^{-1/2}) with increasing number of layers, L. Importantly, we find a similar scaling behavior when the summation is thresholded at an optimal value, providing insight into the common-but not well understood-practice of thresholding pairwise-interaction data to obtain sparse network representations.

Detection of core-periphery structure in networks based on 3-tuple motifs

NASA Astrophysics Data System (ADS)

Ma, Chuang; Xiang, Bing-Bing; Chen, Han-Shuang; Small, Michael; Zhang, Hai-Feng

2018-05-01

Detecting mesoscale structure, such as community structure, is of vital importance for analyzing complex networks. Recently, a new mesoscale structure, core-periphery (CP) structure, has been identified in many real-world systems. In this paper, we propose an effective algorithm for detecting CP structure based on a 3-tuple motif. In this algorithm, we first define a 3-tuple motif in terms of the patterns of edges as well as the property of nodes, and then a motif adjacency matrix is constructed based on the 3-tuple motif. Finally, the problem is converted to find a cluster that minimizes the smallest motif conductance. Our algorithm works well in different CP structures: including single or multiple CP structure, and local or global CP structures. Results on the synthetic and the empirical networks validate the high performance of our method.

Toward link predictability of complex networks

PubMed Central

Lü, Linyuan; Pan, Liming; Zhou, Tao; Zhang, Yi-Cheng; Stanley, H. Eugene

2015-01-01

The organization of real networks usually embodies both regularities and irregularities, and, in principle, the former can be modeled. The extent to which the formation of a network can be explained coincides with our ability to predict missing links. To understand network organization, we should be able to estimate link predictability. We assume that the regularity of a network is reflected in the consistency of structural features before and after a random removal of a small set of links. Based on the perturbation of the adjacency matrix, we propose a universal structural consistency index that is free of prior knowledge of network organization. Extensive experiments on disparate real-world networks demonstrate that (i) structural consistency is a good estimation of link predictability and (ii) a derivative algorithm outperforms state-of-the-art link prediction methods in both accuracy and robustness. This analysis has further applications in evaluating link prediction algorithms and monitoring sudden changes in evolving network mechanisms. It will provide unique fundamental insights into the above-mentioned academic research fields, and will foster the development of advanced information filtering technologies of interest to information technology practitioners. PMID:25659742

The topology of geology 1: Topological analysis

NASA Astrophysics Data System (ADS)

Thiele, Samuel T.; Jessell, Mark W.; Lindsay, Mark; Ogarko, Vitaliy; Wellmann, J. Florian; Pakyuz-Charrier, Evren

2016-10-01

Topology has been used to characterise and quantify the properties of complex systems in a diverse range of scientific domains. This study explores the concept and applications of topological analysis in geology. We have developed an automatic system for extracting first order 2D topological information from geological maps, and 3D topological information from models built with the Noddy kinematic modelling system, and equivalent analyses should be possible for other implicit modelling systems. A method is presented for describing the spatial and temporal topology of geological models using a set of adjacency relationships that can be expressed as a topology network, thematic adjacency matrix or hive diagram. We define three types of spatial topology (cellular, structural and lithological) that allow us to analyse different aspects of the geology, and then apply them to investigate the geology of the Hamersley Basin, Western Australia.

Causality and Information Dynamics in Networked Systems with Many Agents

DTIC Science & Technology

2017-05-11

representation, the LSI filter given by A(τ) must be invertible, and a sufficient condition for this invertibility is that there is some c > 0 such that the...linear shift-invariant (LSI) filter B̃ij(z) = ∑p τ=1Bij(τ)z −τ whose coefficients are arranged into a column vector B̃ij = (Bij(1), . . . , Bij(p)). In...to the adjacency matrix of the underlying graph, so that looking “depth-wise” at location ij gives the coefficients B̃ij ∈ IRp of the LSI filter from

Finite plateau in spectral gap of polychromatic constrained random networks

NASA Astrophysics Data System (ADS)

Avetisov, V.; Gorsky, A.; Nechaev, S.; Valba, O.

2017-12-01

We consider critical behavior in the ensemble of polychromatic Erdős-Rényi networks and regular random graphs, where network vertices are painted in different colors. The links can be randomly removed and added to the network subject to the condition of the vertex degree conservation. In these constrained graphs we run the Metropolis procedure, which favors the connected unicolor triads of nodes. Changing the chemical potential, μ , of such triads, for some wide region of μ , we find the formation of a finite plateau in the number of intercolor links, which exactly matches the finite plateau in the network algebraic connectivity (the value of the first nonvanishing eigenvalue of the Laplacian matrix, λ2). We claim that at the plateau the spontaneously broken Z2 symmetry is restored by the mechanism of modes collectivization in clusters of different colors. The phenomena of a finite plateau formation holds also for polychromatic networks with M ≥2 colors. The behavior of polychromatic networks is analyzed via the spectral properties of their adjacency and Laplacian matrices.

Synconset Waves and Chains: Spiking Onsets in Synchronous Populations Predict and Are Predicted by Network Structure

PubMed Central

Raghavan, Mohan; Amrutur, Bharadwaj; Narayanan, Rishikesh; Sikdar, Sujit Kumar

2013-01-01

Synfire waves are propagating spike packets in synfire chains, which are feedforward chains embedded in random networks. Although synfire waves have proved to be effective quantification for network activity with clear relations to network structure, their utilities are largely limited to feedforward networks with low background activity. To overcome these shortcomings, we describe a novel generalisation of synfire waves, and define ‘synconset wave’ as a cascade of first spikes within a synchronisation event. Synconset waves would occur in ‘synconset chains’, which are feedforward chains embedded in possibly heavily recurrent networks with heavy background activity. We probed the utility of synconset waves using simulation of single compartment neuron network models with biophysically realistic conductances, and demonstrated that the spread of synconset waves directly follows from the network connectivity matrix and is modulated by top-down inputs and the resultant oscillations. Such synconset profiles lend intuitive insights into network organisation in terms of connection probabilities between various network regions rather than an adjacency matrix. To test this intuition, we develop a Bayesian likelihood function that quantifies the probability that an observed synfire wave was caused by a given network. Further, we demonstrate it's utility in the inverse problem of identifying the network that caused a given synfire wave. This method was effective even in highly subsampled networks where only a small subset of neurons were accessible, thus showing it's utility in experimental estimation of connectomes in real neuronal-networks. Together, we propose synconset chains/waves as an effective framework for understanding the impact of network structure on function, and as a step towards developing physiology-driven network identification methods. Finally, as synconset chains extend the utilities of synfire chains to arbitrary networks, we suggest utilities of our framework to several aspects of network physiology including cell assemblies, population codes, and oscillatory synchrony. PMID:24116018

Cluster and propensity based approximation of a network

PubMed Central

2013-01-01

Background The models in this article generalize current models for both correlation networks and multigraph networks. Correlation networks are widely applied in genomics research. In contrast to general networks, it is straightforward to test the statistical significance of an edge in a correlation network. It is also easy to decompose the underlying correlation matrix and generate informative network statistics such as the module eigenvector. However, correlation networks only capture the connections between numeric variables. An open question is whether one can find suitable decompositions of the similarity measures employed in constructing general networks. Multigraph networks are attractive because they support likelihood based inference. Unfortunately, it is unclear how to adjust current statistical methods to detect the clusters inherent in many data sets. Results Here we present an intuitive and parsimonious parametrization of a general similarity measure such as a network adjacency matrix. The cluster and propensity based approximation (CPBA) of a network not only generalizes correlation network methods but also multigraph methods. In particular, it gives rise to a novel and more realistic multigraph model that accounts for clustering and provides likelihood based tests for assessing the significance of an edge after controlling for clustering. We present a novel Majorization-Minimization (MM) algorithm for estimating the parameters of the CPBA. To illustrate the practical utility of the CPBA of a network, we apply it to gene expression data and to a bi-partite network model for diseases and disease genes from the Online Mendelian Inheritance in Man (OMIM). Conclusions The CPBA of a network is theoretically appealing since a) it generalizes correlation and multigraph network methods, b) it improves likelihood based significance tests for edge counts, c) it directly models higher-order relationships between clusters, and d) it suggests novel clustering algorithms. The CPBA of a network is implemented in Fortran 95 and bundled in the freely available R package PropClust. PMID:23497424

Deterministic ripple-spreading model for complex networks.

PubMed

Hu, Xiao-Bing; Wang, Ming; Leeson, Mark S; Hines, Evor L; Di Paolo, Ezequiel

2011-04-01

This paper proposes a deterministic complex network model, which is inspired by the natural ripple-spreading phenomenon. The motivations and main advantages of the model are the following: (i) The establishment of many real-world networks is a dynamic process, where it is often observed that the influence of a few local events spreads out through nodes, and then largely determines the final network topology. Obviously, this dynamic process involves many spatial and temporal factors. By simulating the natural ripple-spreading process, this paper reports a very natural way to set up a spatial and temporal model for such complex networks. (ii) Existing relevant network models are all stochastic models, i.e., with a given input, they cannot output a unique topology. Differently, the proposed ripple-spreading model can uniquely determine the final network topology, and at the same time, the stochastic feature of complex networks is captured by randomly initializing ripple-spreading related parameters. (iii) The proposed model can use an easily manageable number of ripple-spreading related parameters to precisely describe a network topology, which is more memory efficient when compared with traditional adjacency matrix or similar memory-expensive data structures. (iv) The ripple-spreading model has a very good potential for both extensions and applications.

Matrix Intensification Alters Avian Functional Group Composition in Adjacent Rainforest Fragments

PubMed Central

Deikumah, Justus P.; McAlpine, Clive A.; Maron, Martine

2013-01-01

Conversion of farmland land-use matrices to surface mining is an increasing threat to the habitat quality of forest remnants and their constituent biota, with consequences for ecosystem functionality. We evaluated the effects of matrix type on bird community composition and the abundance and evenness within avian functional groups in south-west Ghana. We hypothesized that surface mining near remnants may result in a shift in functional composition of avifaunal communities, potentially disrupting ecological processes within tropical forest ecosystems. Matrix intensification and proximity to the remnant edge strongly influenced the abundance of members of several functional guilds. Obligate frugivores, strict terrestrial insectivores, lower and upper strata birds, and insect gleaners were most negatively affected by adjacent mining matrices, suggesting certain ecosystem processes such as seed dispersal may be disrupted by landscape change in this region. Evenness of these functional guilds was also lower in remnants adjacent to surface mining, regardless of the distance from remnant edge, with the exception of strict terrestrial insectivores. These shifts suggest matrix intensification can influence avian functional group composition and related ecosystem-level processes in adjacent forest remnants. The management of matrix habitat quality near and within mine concessions is important for improving efforts to preserveavian biodiversity in landscapes undergoing intensification such as through increased surface mining. PMID:24058634

Matrix intensification alters avian functional group composition in adjacent rainforest fragments.

PubMed

Deikumah, Justus P; McAlpine, Clive A; Maron, Martine

2013-01-01

Conversion of farmland land-use matrices to surface mining is an increasing threat to the habitat quality of forest remnants and their constituent biota, with consequences for ecosystem functionality. We evaluated the effects of matrix type on bird community composition and the abundance and evenness within avian functional groups in south-west Ghana. We hypothesized that surface mining near remnants may result in a shift in functional composition of avifaunal communities, potentially disrupting ecological processes within tropical forest ecosystems. Matrix intensification and proximity to the remnant edge strongly influenced the abundance of members of several functional guilds. Obligate frugivores, strict terrestrial insectivores, lower and upper strata birds, and insect gleaners were most negatively affected by adjacent mining matrices, suggesting certain ecosystem processes such as seed dispersal may be disrupted by landscape change in this region. Evenness of these functional guilds was also lower in remnants adjacent to surface mining, regardless of the distance from remnant edge, with the exception of strict terrestrial insectivores. These shifts suggest matrix intensification can influence avian functional group composition and related ecosystem-level processes in adjacent forest remnants. The management of matrix habitat quality near and within mine concessions is important for improving efforts to preserveavian biodiversity in landscapes undergoing intensification such as through increased surface mining.

Different alterations in brain functional networks according to direct and indirect topological connections in patients with schizophrenia.

PubMed

Park, Chang-Hyun; Lee, Seungyup; Kim, Taewon; Won, Wang Yeon; Lee, Kyoung-Uk

2017-10-01

Schizophrenia displays connectivity deficits in the brain, but the literature has shown inconsistent findings about alterations in global efficiency of brain functional networks. We supposed that such inconsistency at the whole brain level may be due to a mixture of different portions of global efficiency at sub-brain levels. Accordingly, we considered measuring portions of global efficiency in two aspects: spatial portions by considering sub-brain networks and topological portions by considering contributions to global efficiency according to direct and indirect topological connections. We proposed adjacency and indirect adjacency as new network parameters attributable to direct and indirect topological connections, respectively, and applied them to graph-theoretical analysis of brain functional networks constructed from resting state fMRI data of 22 patients with schizophrenia and 22 healthy controls. Group differences in the network parameters were observed not for whole brain and hemispheric networks, but for regional networks. Alterations in adjacency and indirect adjacency were in opposite directions, such that adjacency increased, but indirect adjacency decreased in patients with schizophrenia. Furthermore, over connections in frontal and parietal regions, increased adjacency was associated with more severe negative symptoms, while decreased adjacency was associated with more severe positive symptoms of schizophrenia. This finding indicates that connectivity deficits associated with positive and negative symptoms of schizophrenia may involve topologically different paths in the brain. In patients with schizophrenia, although changes in global efficiency may not be clearly shown, different alterations in brain functional networks according to direct and indirect topological connections could be revealed at the regional level. Copyright © 2017 Elsevier B.V. All rights reserved.

Burst of virus infection and a possibly largest epidemic threshold of non-Markovian susceptible-infected-susceptible processes on networks

NASA Astrophysics Data System (ADS)

Liu, Qiang; Van Mieghem, Piet

2018-02-01

Since a real epidemic process is not necessarily Markovian, the epidemic threshold obtained under the Markovian assumption may be not realistic. To understand general non-Markovian epidemic processes on networks, we study the Weibullian susceptible-infected-susceptible (SIS) process in which the infection process is a renewal process with a Weibull time distribution. We find that, if the infection rate exceeds 1 /ln(λ1+1 ) , where λ1 is the largest eigenvalue of the network's adjacency matrix, then the infection will persist on the network under the mean-field approximation. Thus, 1 /ln(λ1+1 ) is possibly the largest epidemic threshold for a general non-Markovian SIS process with a Poisson curing process under the mean-field approximation. Furthermore, non-Markovian SIS processes may result in a multimodal prevalence. As a byproduct, we show that a limiting Weibullian SIS process has the potential to model bursts of a synchronized infection.

Spectral analysis of Chinese language: Co-occurrence networks from four literary genres

NASA Astrophysics Data System (ADS)

Liang, Wei; Chen, Guanrong

2016-05-01

The eigenvalues and eigenvectors of the adjacency matrix of a network contain essential information about its topology. For each of the Chinese language co-occurrence networks constructed from four literary genres, i.e., essay, popular science article, news report, and novel, it is found that the largest eigenvalue depends on the network size N, the number of edges, the average shortest path length, and the clustering coefficient. Moreover, it is found that their node-degree distributions all follow a power-law. The number of different eigenvalues, Nλ, is found numerically to increase in the manner of Nλ ∝ log N for novel and Nλ ∝ N for the other three literary genres. An ;M; shape or a triangle-like distribution appears in their spectral densities. The eigenvector corresponding to the largest eigenvalue is mostly localized to a node with the largest degree. For the above observed phenomena, mathematical analysis is provided with interpretation from a linguistic perspective.

Influence networks among substance abuse treatment clinics: implications for the dissemination of innovations.

PubMed

Johnson, Kimberly; Quanbeck, Andrew; Maus, Adam; Gustafson, David H; Dearing, James W

2015-09-01

Understanding influence networks among substance abuse treatment clinics may speed the diffusion of innovations. The purpose of this study was to describe influence networks in Massachusetts, Michigan, New York, Oregon, and Washington and test two expectations, using social network analysis: (1) Social network measures can identify influential clinics; and (2) Within a network, some weakly connected clinics access out-of-network sources of innovative evidence-based practices and can spread these innovations through the network. A survey of 201 clinics in a parent study on quality improvement provided the data. Network measures and sociograms were obtained from adjacency matrixes created by UCINet. We used regression analysis to determine whether network status relates to clinics' adopting innovations. Findings suggest that influential clinics can be identified and that loosely linked clinics were likely to join the study sooner than more influential clinics but were not more likely to have improved outcomes than other organizations. Findings identify the structure of influence networks for SUD treatment organizations and have mixed results on how those structures impacted diffusion of the intervention under study. Further study is necessary to test whether use of knowledge of the network structure will have an effect on the pace and breadth of dissemination of innovations.

Spectral analysis and slow spreading dynamics on complex networks.

PubMed

Odor, Géza

2013-09-01

The susceptible-infected-susceptible (SIS) model is one of the simplest memoryless systems for describing information or epidemic spreading phenomena with competing creation and spontaneous annihilation reactions. The effect of quenched disorder on the dynamical behavior has recently been compared to quenched mean-field (QMF) approximations in scale-free networks. QMF can take into account topological heterogeneity and clustering effects of the activity in the steady state by spectral decomposition analysis of the adjacency matrix. Therefore, it can provide predictions on possible rare-region effects, thus on the occurrence of slow dynamics. I compare QMF results of SIS with simulations on various large dimensional graphs. In particular, I show that for Erdős-Rényi graphs this method predicts correctly the occurrence of rare-region effects. It also provides a good estimate for the epidemic threshold in case of percolating graphs. Griffiths Phases emerge if the graph is fragmented or if we apply a strong, exponentially suppressing weighting scheme on the edges. The latter model describes the connection time distributions in the face-to-face experiments. In case of a generalized Barabási-Albert type of network with aging connections, strong rare-region effects and numerical evidence for Griffiths Phase dynamics are shown. The dynamical simulation results agree well with the predictions of the spectral analysis applied for the weighted adjacency matrices.

Treatment of multiple adjacent Miller Class I and II gingival recessions with collagen matrix and the modified coronally advanced tunnel technique.

PubMed

Molnár, Bálint; Aroca, Sofia; Keglevich, Tibor; Gera, István; Windisch, Péter; Stavropoulos, Andreas; Sculean, Anton

2013-01-01

To clinically evaluate the treatment of Miller Class I and II multiple adjacent gingival recessions using the modified coronally advanced tunnel technique combined with a newly developed bioresorbable collagen matrix of porcine origin. Eight healthy patients exhibiting at least three multiple Miller Class I and II multiple adjacent gingival recessions (a total of 42 recessions) were consecutively treated by means of the modified coronally advanced tunnel technique and collagen matrix. The following clinical parameters were assessed at baseline and 12 months postoperatively: full mouth plaque score (FMPS), full mouth bleeding score (FMBS), probing depth (PD), recession depth (RD), recession width (RW), keratinized tissue thickness (KTT), and keratinized tissue width (KTW). The primary outcome variable was complete root coverage. Neither allergic reactions nor soft tissue irritations or matrix exfoliations occurred. Postoperative pain and discomfort were reported to be low, and patient acceptance was generally high. At 12 months, complete root coverage was obtained in 2 out of the 8 patients and 30 of the 42 recessions (71%). Within their limits, the present results indicate that treatment of Miller Class I and II multiple adjacent gingival recessions by means of the modified coronally advanced tunnel technique and collagen matrix may result in statistically and clinically significant complete root coverage. Further studies are warranted to evaluate the performance of collagen matrix compared with connective tissue grafts and other soft tissue grafts.

Two-photon laser-generated microtracks in 3D collagen lattices: principles of MMP-dependent and -independent collective cancer cell invasion

NASA Astrophysics Data System (ADS)

Ilina, Olga; Bakker, Gert-Jan; Vasaturo, Angela; Hoffman, Robert M.; Friedl, Peter

2011-02-01

Cancer invasion into an extracellular matrix (ECM) results from a biophysical reciprocal interplay between the expanding cancer lesion and tissue barriers imposed by the adjacent microenvironment. In vivo, connective tissue provides both densely packed ECM barriers adjacent to channel/track-like spaces and loosely organized zones, both of which may impact cancer invasion mode and efficiency; however little is known about how three-dimensional (3D) spaces and aligned tracks present in interstitial tissue guide cell invasion. We here describe a two-photon laser ablation procedure to generate 3D microtracks in dense 3D collagen matrices that support and guide collective cancer cell invasion. Whereas collective invasion of mammary tumor (MMT) breast cancer cells into randomly organized collagen networks required matrix metalloproteinase (MMP) activity for cell-derived collagen breakdown, re-alignment and track generation, preformed tracks supported MMP-independent collective invasion down to a track caliber of 3 µm. Besides contact guidance along the track of least resistance and initial cell deformation (squeezing), MMP-independent collective cell strands led to secondary track expansion by a pushing mechanism. Thus, two-photon laser ablation is useful to generate barrier-free microtracks in a 3D ECM which guide collective invasion independently of pericellular proteolysis.

Network representation of protein interactions: Theory of graph description and analysis.

PubMed

Kurzbach, Dennis

2016-09-01

A methodological framework is presented for the graph theoretical interpretation of NMR data of protein interactions. The proposed analysis generalizes the idea of network representations of protein structures by expanding it to protein interactions. This approach is based on regularization of residue-resolved NMR relaxation times and chemical shift data and subsequent construction of an adjacency matrix that represents the underlying protein interaction as a graph or network. The network nodes represent protein residues. Two nodes are connected if two residues are functionally correlated during the protein interaction event. The analysis of the resulting network enables the quantification of the importance of each amino acid of a protein for its interactions. Furthermore, the determination of the pattern of correlations between residues yields insights into the functional architecture of an interaction. This is of special interest for intrinsically disordered proteins, since the structural (three-dimensional) architecture of these proteins and their complexes is difficult to determine. The power of the proposed methodology is demonstrated at the example of the interaction between the intrinsically disordered protein osteopontin and its natural ligand heparin. © 2016 The Protein Society.

Epidemic threshold in directed networks.

PubMed

Li, Cong; Wang, Huijuan; Van Mieghem, Piet

2013-12-01

Epidemics have so far been mostly studied in undirected networks. However, many real-world networks, such as the online social network Twitter and the world wide web, on which information, emotion, or malware spreads, are directed networks, composed of both unidirectional links and bidirectional links. We define the directionality ξ as the percentage of unidirectional links. The epidemic threshold τ(c) for the susceptible-infected-susceptible (SIS) epidemic is lower bounded by 1/λ(1) in directed networks, where λ(1), also called the spectral radius, is the largest eigenvalue of the adjacency matrix. In this work, we propose two algorithms to generate directed networks with a given directionality ξ. The effect of ξ on the spectral radius λ(1), principal eigenvector x(1), spectral gap (λ(1)-|λ(2)|), and algebraic connectivity μ(N-1) is studied. Important findings are that the spectral radius λ(1) decreases with the directionality ξ, whereas the spectral gap and the algebraic connectivity increase with the directionality ξ. The extent of the decrease of the spectral radius depends on both the degree distribution and the degree-degree correlation ρ(D). Hence, in directed networks, the epidemic threshold is larger and a random walk converges to its steady state faster than that in undirected networks with the same degree distribution.

Epidemic threshold in directed networks

NASA Astrophysics Data System (ADS)

Li, Cong; Wang, Huijuan; Van Mieghem, Piet

2013-12-01

Epidemics have so far been mostly studied in undirected networks. However, many real-world networks, such as the online social network Twitter and the world wide web, on which information, emotion, or malware spreads, are directed networks, composed of both unidirectional links and bidirectional links. We define the directionality ξ as the percentage of unidirectional links. The epidemic threshold τc for the susceptible-infected-susceptible (SIS) epidemic is lower bounded by 1/λ1 in directed networks, where λ1, also called the spectral radius, is the largest eigenvalue of the adjacency matrix. In this work, we propose two algorithms to generate directed networks with a given directionality ξ. The effect of ξ on the spectral radius λ1, principal eigenvector x1, spectral gap (λ1-λ2), and algebraic connectivity μN-1 is studied. Important findings are that the spectral radius λ1 decreases with the directionality ξ, whereas the spectral gap and the algebraic connectivity increase with the directionality ξ. The extent of the decrease of the spectral radius depends on both the degree distribution and the degree-degree correlation ρD. Hence, in directed networks, the epidemic threshold is larger and a random walk converges to its steady state faster than that in undirected networks with the same degree distribution.

On the Maximum Storage Capacity of the Hopfield Model

PubMed Central

Folli, Viola; Leonetti, Marco; Ruocco, Giancarlo

2017-01-01

Recurrent neural networks (RNN) have traditionally been of great interest for their capacity to store memories. In past years, several works have been devoted to determine the maximum storage capacity of RNN, especially for the case of the Hopfield network, the most popular kind of RNN. Analyzing the thermodynamic limit of the statistical properties of the Hamiltonian corresponding to the Hopfield neural network, it has been shown in the literature that the retrieval errors diverge when the number of stored memory patterns (P) exceeds a fraction (≈ 14%) of the network size N. In this paper, we study the storage performance of a generalized Hopfield model, where the diagonal elements of the connection matrix are allowed to be different from zero. We investigate this model at finite N. We give an analytical expression for the number of retrieval errors and show that, by increasing the number of stored patterns over a certain threshold, the errors start to decrease and reach values below unit for P ≫ N. We demonstrate that the strongest trade-off between efficiency and effectiveness relies on the number of patterns (P) that are stored in the network by appropriately fixing the connection weights. When P≫N and the diagonal elements of the adjacency matrix are not forced to be zero, the optimal storage capacity is obtained with a number of stored memories much larger than previously reported. This theory paves the way to the design of RNN with high storage capacity and able to retrieve the desired pattern without distortions. PMID:28119595

Bounds for percolation thresholds on directed and undirected graphs

NASA Astrophysics Data System (ADS)

Hamilton, Kathleen; Pryadko, Leonid

2015-03-01

Percolation theory is an efficient approach to problems with strong disorder, e.g., in quantum or classical transport, composite materials, and diluted magnets. Recently, the growing role of big data in scientific and industrial applications has led to a renewed interest in graph theory as a tool for describing complex connections in various kinds of networks: social, biological, technological, etc. In particular, percolation on graphs has been used to describe internet stability, spread of contagious diseases and computer viruses; related models describe market crashes and viral spread in social networks. We consider site-dependent percolation on directed and undirected graphs, and present several exact bounds for location of the percolation transition in terms of the eigenvalues of matrices associated with graphs, including the adjacency matrix and the Hashimoto matrix used to enumerate non-backtracking walks. These bounds correspond t0 a mean field approximation and become asymptotically exact for graphs with no short cycles. We illustrate this convergence numerically by simulating percolation on several families of graphs with different cycle lengths. This research was supported in part by the NSF Grant PHY-1416578 and by the ARO Grant W911NF-11-1-0027.

An integrated workflow for stress and flow modelling using outcrop-derived discrete fracture networks

NASA Astrophysics Data System (ADS)

Bisdom, K.; Nick, H. M.; Bertotti, G.

2017-06-01

Fluid flow in naturally fractured reservoirs is often controlled by subseismic-scale fracture networks. Although the fracture network can be partly sampled in the direct vicinity of wells, the inter-well scale network is poorly constrained in fractured reservoir models. Outcrop analogues can provide data for populating domains of the reservoir model where no direct measurements are available. However, extracting relevant statistics from large outcrops representative of inter-well scale fracture networks remains challenging. Recent advances in outcrop imaging provide high-resolution datasets that can cover areas of several hundred by several hundred meters, i.e. the domain between adjacent wells, but even then, data from the high-resolution models is often upscaled to reservoir flow grids, resulting in loss of accuracy. We present a workflow that uses photorealistic georeferenced outcrop models to construct geomechanical and fluid flow models containing thousands of discrete fractures covering sufficiently large areas, that does not require upscaling to model permeability. This workflow seamlessly integrates geomechanical Finite Element models with flow models that take into account stress-sensitive fracture permeability and matrix flow to determine the full permeability tensor. The applicability of this workflow is illustrated using an outcropping carbonate pavement in the Potiguar basin in Brazil, from which 1082 fractures are digitised. The permeability tensor for a range of matrix permeabilities shows that conventional upscaling to effective grid properties leads to potential underestimation of the true permeability and the orientation of principal permeabilities. The presented workflow yields the full permeability tensor model of discrete fracture networks with stress-induced apertures, instead of relying on effective properties as most conventional flow models do.

Semantic graphs and associative memories

NASA Astrophysics Data System (ADS)

Pomi, Andrés; Mizraji, Eduardo

2004-12-01

Graphs have been increasingly utilized in the characterization of complex networks from diverse origins, including different kinds of semantic networks. Human memories are associative and are known to support complex semantic nets; these nets are represented by graphs. However, it is not known how the brain can sustain these semantic graphs. The vision of cognitive brain activities, shown by modern functional imaging techniques, assigns renewed value to classical distributed associative memory models. Here we show that these neural network models, also known as correlation matrix memories, naturally support a graph representation of the stored semantic structure. We demonstrate that the adjacency matrix of this graph of associations is just the memory coded with the standard basis of the concept vector space, and that the spectrum of the graph is a code invariant of the memory. As long as the assumptions of the model remain valid this result provides a practical method to predict and modify the evolution of the cognitive dynamics. Also, it could provide us with a way to comprehend how individual brains that map the external reality, almost surely with different particular vector representations, are nevertheless able to communicate and share a common knowledge of the world. We finish presenting adaptive association graphs, an extension of the model that makes use of the tensor product, which provides a solution to the known problem of branching in semantic nets.

A weighted communicability measure applied to complex brain networks

PubMed Central

Crofts, Jonathan J.; Higham, Desmond J.

2009-01-01

Recent advances in experimental neuroscience allow non-invasive studies of the white matter tracts in the human central nervous system, thus making available cutting-edge brain anatomical data describing these global connectivity patterns. Through magnetic resonance imaging, this non-invasive technique is able to infer a snapshot of the cortical network within the living human brain. Here, we report on the initial success of a new weighted network communicability measure in distinguishing local and global differences between diseased patients and controls. This approach builds on recent advances in network science, where an underlying connectivity structure is used as a means to measure the ease with which information can flow between nodes. One advantage of our method is that it deals directly with the real-valued connectivity data, thereby avoiding the need to discretize the corresponding adjacency matrix, i.e. to round weights up to 1 or down to 0, depending upon some threshold value. Experimental results indicate that the new approach is able to extract biologically relevant features that are not immediately apparent from the raw connectivity data. PMID:19141429

Chemomechanical synchronization in heterogeneous self-oscillating gels

NASA Astrophysics Data System (ADS)

Yashin, Victor V.; Balazs, Anna C.

2008-04-01

Using computational modeling, we introduce patches of self-oscillating gels undergoing the Belousov-Zhabotinsky (BZ) reaction into a nonreactive polymer network and thereby demonstrate how these BZ gels can be harnessed to impart remarkable functionality to the entire system. By first focusing on two adjacent patches of BZ gels, we show that the patches’ oscillations can become synchronized in phase or out of phase, with the oscillation frequency depending on the synchronization mode and the spatial separation between these domains. We then apply these results to an array of five adjacent BZ patches and by varying the distance between these pieces, we dramatically alter the dynamical behavior of the patterned gel. For example, the sample can be made to exhibit a unidirectional traveling wave or display a concerted expansion and contraction, properties that are valuable for creating gel-based devices, such as micropumps and microactuators. The findings point to a “modular” design approach, which can impart different functionality simply by arranging identical pieces of BZ gels into distinct spatial arrangements within a polymer matrix.

Dynamic graph system for a semantic database

DOEpatents

Mizell, David

2016-04-12

A method and system in a computer system for dynamically providing a graphical representation of a data store of entries via a matrix interface is disclosed. A dynamic graph system provides a matrix interface that exposes to an application program a graphical representation of data stored in a data store such as a semantic database storing triples. To the application program, the matrix interface represents the graph as a sparse adjacency matrix that is stored in compressed form. Each entry of the data store is considered to represent a link between nodes of the graph. Each entry has a first field and a second field identifying the nodes connected by the link and a third field with a value for the link that connects the identified nodes. The first, second, and third fields represent the rows, column, and elements of the adjacency matrix.

Dynamic graph system for a semantic database

DOEpatents

Mizell, David

2015-01-27

A method and system in a computer system for dynamically providing a graphical representation of a data store of entries via a matrix interface is disclosed. A dynamic graph system provides a matrix interface that exposes to an application program a graphical representation of data stored in a data store such as a semantic database storing triples. To the application program, the matrix interface represents the graph as a sparse adjacency matrix that is stored in compressed form. Each entry of the data store is considered to represent a link between nodes of the graph. Each entry has a first field and a second field identifying the nodes connected by the link and a third field with a value for the link that connects the identified nodes. The first, second, and third fields represent the rows, column, and elements of the adjacency matrix.

Exact evaluation of the causal spectrum and localization properties of electronic states on a scale-free network

NASA Astrophysics Data System (ADS)

Xie, Pinchen; Yang, Bingjia; Zhang, Zhongzhi; Andrade, Roberto F. S.

2018-07-01

A deterministic network with tree structure is considered, for which the spectrum of its adjacency matrix can be exactly evaluated by a recursive renormalization approach. It amounts to successively increasing number of contributions at any finite step of construction of the tree, resulting in a causal chain. The resulting eigenvalues can be related the full energy spectrum of a nearest-neighbor tight-binding model defined on this structure. Given this association, it turns out that further properties of the eigenvectors can be evaluated, like the degree of quantum localization of the tight-binding eigenstates, expressed by the inverse participation ratio (IPR). It happens that, for the current model, the IPR's are also suitable to be analytically expressed in terms in corresponding eigenvalue chain. The resulting IPR scaling behavior is expressed by the tails of eigenvalue chains as well.

Dynamic fair node spectrum allocation for ad hoc networks using random matrices

NASA Astrophysics Data System (ADS)

Rahmes, Mark; Lemieux, George; Chester, Dave; Sonnenberg, Jerry

2015-05-01

Dynamic Spectrum Access (DSA) is widely seen as a solution to the problem of limited spectrum, because of its ability to adapt the operating frequency of a radio. Mobile Ad Hoc Networks (MANETs) can extend high-capacity mobile communications over large areas where fixed and tethered-mobile systems are not available. In one use case with high potential impact, cognitive radio employs spectrum sensing to facilitate the identification of allocated frequencies not currently accessed by their primary users. Primary users own the rights to radiate at a specific frequency and geographic location, while secondary users opportunistically attempt to radiate at a specific frequency when the primary user is not using it. We populate a spatial radio environment map (REM) database with known information that can be leveraged in an ad hoc network to facilitate fair path use of the DSA-discovered links. Utilization of high-resolution geospatial data layers in RF propagation analysis is directly applicable. Random matrix theory (RMT) is useful in simulating network layer usage in nodes by a Wishart adjacency matrix. We use the Dijkstra algorithm for discovering ad hoc network node connection patterns. We present a method for analysts to dynamically allocate node-node path and link resources using fair division. User allocation of limited resources as a function of time must be dynamic and based on system fairness policies. The context of fair means that first available request for an asset is not envied as long as it is not yet allocated or tasked in order to prevent cycling of the system. This solution may also save money by offering a Pareto efficient repeatable process. We use a water fill queue algorithm to include Shapley value marginal contributions for allocation.

MODFLOW–USG version 1: An unstructured grid version of MODFLOW for simulating groundwater flow and tightly coupled processes using a control volume finite-difference formulation

USGS Publications Warehouse

Panday, Sorab; Langevin, Christian D.; Niswonger, Richard G.; Ibaraki, Motomu; Hughes, Joseph D.

2013-01-01

A new version of MODFLOW, called MODFLOW–USG (for UnStructured Grid), was developed to support a wide variety of structured and unstructured grid types, including nested grids and grids based on prismatic triangles, rectangles, hexagons, and other cell shapes. Flexibility in grid design can be used to focus resolution along rivers and around wells, for example, or to subdiscretize individual layers to better represent hydrostratigraphic units. MODFLOW–USG is based on an underlying control volume finite difference (CVFD) formulation in which a cell can be connected to an arbitrary number of adjacent cells. To improve accuracy of the CVFD formulation for irregular grid-cell geometries or nested grids, a generalized Ghost Node Correction (GNC) Package was developed, which uses interpolated heads in the flow calculation between adjacent connected cells. MODFLOW–USG includes a Groundwater Flow (GWF) Process, based on the GWF Process in MODFLOW–2005, as well as a new Connected Linear Network (CLN) Process to simulate the effects of multi-node wells, karst conduits, and tile drains, for example. The CLN Process is tightly coupled with the GWF Process in that the equations from both processes are formulated into one matrix equation and solved simultaneously. This robustness results from using an unstructured grid with unstructured matrix storage and solution schemes. MODFLOW–USG also contains an optional Newton-Raphson formulation, based on the formulation in MODFLOW–NWT, for improving solution convergence and avoiding problems with the drying and rewetting of cells. Because the existing MODFLOW solvers were developed for structured and symmetric matrices, they were replaced with a new Sparse Matrix Solver (SMS) Package developed specifically for MODFLOW–USG. The SMS Package provides several methods for resolving nonlinearities and multiple symmetric and asymmetric linear solution schemes to solve the matrix arising from the flow equations and the Newton-Raphson formulation, respectively.

BinTree Seeking: A Novel Approach to Mine Both Bi-Sparse and Cohesive Modules in Protein Interaction Networks

PubMed Central

Shen, Hong-Bin

2011-01-01

Modern science of networks has brought significant advances to our understanding of complex systems biology. As a representative model of systems biology, Protein Interaction Networks (PINs) are characterized by a remarkable modular structures, reflecting functional associations between their components. Many methods were proposed to capture cohesive modules so that there is a higher density of edges within modules than those across them. Recent studies reveal that cohesively interacting modules of proteins is not a universal organizing principle in PINs, which has opened up new avenues for revisiting functional modules in PINs. In this paper, functional clusters in PINs are found to be able to form unorthodox structures defined as bi-sparse module. In contrast to the traditional cohesive module, the nodes in the bi-sparse module are sparsely connected internally and densely connected with other bi-sparse or cohesive modules. We present a novel protocol called the BinTree Seeking (BTS) for mining both bi-sparse and cohesive modules in PINs based on Edge Density of Module (EDM) and matrix theory. BTS detects modules by depicting links and nodes rather than nodes alone and its derivation procedure is totally performed on adjacency matrix of networks. The number of modules in a PIN can be automatically determined in the proposed BTS approach. BTS is tested on three real PINs and the results demonstrate that functional modules in PINs are not dominantly cohesive but can be sparse. BTS software and the supporting information are available at: www.csbio.sjtu.edu.cn/bioinf/BTS/. PMID:22140454

XDATA

DTIC Science & Technology

2017-05-01

Parallelizing PINT The main focus of our research into the parallelization of the PINT algorithm has been to find appropriately scalable matrix math algorithms...leading eigenvector of the adjacency matrix of the pairwise affinity graph. We reviewed the matrix math implementation currently being used in PINT and...the new versions support a feature called matrix.distributed, which is some level of support for distributed matrix math ; however our code is not

Providing nearest neighbor point-to-point communications among compute nodes of an operational group in a global combining network of a parallel computer

DOEpatents

Archer, Charles J.; Faraj, Ahmad A.; Inglett, Todd A.; Ratterman, Joseph D.

2012-10-23

Methods, apparatus, and products are disclosed for providing nearest neighbor point-to-point communications among compute nodes of an operational group in a global combining network of a parallel computer, each compute node connected to each adjacent compute node in the global combining network through a link, that include: identifying each link in the global combining network for each compute node of the operational group; designating one of a plurality of point-to-point class routing identifiers for each link such that no compute node in the operational group is connected to two adjacent compute nodes in the operational group with links designated for the same class routing identifiers; and configuring each compute node of the operational group for point-to-point communications with each adjacent compute node in the global combining network through the link between that compute node and that adjacent compute node using that link's designated class routing identifier.

Investigation of Coupled model of Pore network and Continuum in shale gas

NASA Astrophysics Data System (ADS)

Cao, G.; Lin, M.

2016-12-01

Flow in shale spanning over many scales, makes the majority of conventional treatment methods disabled. For effectively simulating, a coupled model of pore-scale and continuum-scale was proposed in this paper. Based on the SEM image, we decompose organic-rich-shale into two subdomains: kerogen and inorganic matrix. In kerogen, the nanoscale pore-network is the main storage space and migration pathway so that the molecular phenomena (slip and diffusive transport) is significant. Whereas, inorganic matrix, with relatively large pores and micro fractures, the flow is approximate to Darcy. We use pore-scale network models (PNM) to represent kerogen and continuum-scale models (FVM or FEM) to represent matrix. Finite element mortars are employed to couple pore- and continuum-scale models by enforcing continuity of pressures and fluxes at shared boundary interfaces. In our method, the process in the coupled model is described by pressure square equation, and uses Dirichlet boundary conditions. We discuss several problems: the optimal element number of mortar faces, two categories boundary faces of pore network, the difference between 2D and 3D models, and the difference between continuum models FVM and FEM in mortars. We conclude that: (1) too coarse mesh in mortars will decrease the accuracy, while too fine mesh will lead to an ill-condition even singular system, the optimal element number is depended on boundary pores and nodes number. (2) pore network models are adjacent to two different mortar faces (PNM to PNM, PNM to continuum model), incidental repeated mortar nodes must be deleted. (3) 3D models can be replaced by 2D models under certain condition. (4) FVM is more convenient than FEM, for its simplicity in assigning interface nodes pressure and calculating interface fluxes. This work is supported by the Strategic Priority Research Program of the Chinese Academy of Sciences (XDB10020302), the 973 Program (2014CB239004), the Key Instrument Developing Project of the CAS (ZDYZ2012-1-08-02), the National Natural Science Foundation of China (41574129).

Completing sparse and disconnected protein-protein network by deep learning.

PubMed

Huang, Lei; Liao, Li; Wu, Cathy H

2018-03-22

Protein-protein interaction (PPI) prediction remains a central task in systems biology to achieve a better and holistic understanding of cellular and intracellular processes. Recently, an increasing number of computational methods have shifted from pair-wise prediction to network level prediction. Many of the existing network level methods predict PPIs under the assumption that the training network should be connected. However, this assumption greatly affects the prediction power and limits the application area because the current golden standard PPI networks are usually very sparse and disconnected. Therefore, how to effectively predict PPIs based on a training network that is sparse and disconnected remains a challenge. In this work, we developed a novel PPI prediction method based on deep learning neural network and regularized Laplacian kernel. We use a neural network with an autoencoder-like architecture to implicitly simulate the evolutionary processes of a PPI network. Neurons of the output layer correspond to proteins and are labeled with values (1 for interaction and 0 for otherwise) from the adjacency matrix of a sparse disconnected training PPI network. Unlike autoencoder, neurons at the input layer are given all zero input, reflecting an assumption of no a priori knowledge about PPIs, and hidden layers of smaller sizes mimic ancient interactome at different times during evolution. After the training step, an evolved PPI network whose rows are outputs of the neural network can be obtained. We then predict PPIs by applying the regularized Laplacian kernel to the transition matrix that is built upon the evolved PPI network. The results from cross-validation experiments show that the PPI prediction accuracies for yeast data and human data measured as AUC are increased by up to 8.4 and 14.9% respectively, as compared to the baseline. Moreover, the evolved PPI network can also help us leverage complementary information from the disconnected training network and multiple heterogeneous data sources. Tested by the yeast data with six heterogeneous feature kernels, the results show our method can further improve the prediction performance by up to 2%, which is very close to an upper bound that is obtained by an Approximate Bayesian Computation based sampling method. The proposed evolution deep neural network, coupled with regularized Laplacian kernel, is an effective tool in completing sparse and disconnected PPI networks and in facilitating integration of heterogeneous data sources.

The stability of cellulose: a statistical perspective from a coarse-grained model of hydrogen-bond networks.

PubMed

Shen, Tongye; Gnanakaran, S

2009-04-22

A critical roadblock to the production of biofuels from lignocellulosic biomass is the efficient degradation of crystalline microfibrils of cellulose to glucose. A microscopic understanding of how different physical conditions affect the overall stability of the crystalline structure of microfibrils could facilitate the design of more effective protocols for their degradation. One of the essential physical interactions that stabilizes microfibrils is a network of hydrogen (H) bonds: both intrachain H-bonds between neighboring monomers of a single cellulose polymer chain and interchain H-bonds between adjacent chains. We construct a statistical mechanical model of cellulose assembly at the resolution of explicit hydrogen-bond networks. Using the transfer matrix method, the partition function and the subsequent statistical properties are evaluated. With the help of this lattice-based model, we capture the plasticity of the H-bond network in cellulose due to frustration and redundancy in the placement of H-bonds. This plasticity is responsible for the stability of cellulose over a wide range of temperatures. Stable intrachain and interchain H-bonds are identified as a function of temperature that could possibly be manipulated toward rational destruction of crystalline cellulose.

Efficiency and robustness of different bus network designs

NASA Astrophysics Data System (ADS)

Pang, John Zhen Fu; Bin Othman, Nasri; Ng, Keng Meng; Monterola, Christopher

2015-07-01

We compare the efficiencies and robustness of four transport networks that can be possibly formed as a result of deliberate city planning. The networks are constructed based on their spatial resemblance to the cities of Manhattan (lattice), Sudan (random), Beijing (single-blob) and Greater Cairo (dual-blob). For a given type, a genetic algorithm is employed to obtain an optimized set of the bus routes. We then simulate how commuter travels using Yen's algorithms for k shortest paths on an adjacency matrix. The cost of traveling such as walking between stations is captured by varying the weighted sums of matrices. We also consider the number of transfers a posteriori by looking at the computed shortest paths. With consideration to distances via radius of gyration, redundancies of travel and number of bus transfers, our simulations indicate that random and dual-blob are more efficient than single-blob and lattice networks. Moreover, dual-blob type is least robust when node removals are targeted but is most resilient when node failures are random. The work hopes to guide and provide technical perspectives on how geospatial distribution of a city limits the optimality of transport designs.

Understanding network concepts in modules

PubMed Central

2007-01-01

Background Network concepts are increasingly used in biology and genetics. For example, the clustering coefficient has been used to understand network architecture; the connectivity (also known as degree) has been used to screen for cancer targets; and the topological overlap matrix has been used to define modules and to annotate genes. Dozens of potentially useful network concepts are known from graph theory. Results Here we study network concepts in special types of networks, which we refer to as approximately factorizable networks. In these networks, the pairwise connection strength (adjacency) between 2 network nodes can be factored into node specific contributions, named node 'conformity'. The node conformity turns out to be highly related to the connectivity. To provide a formalism for relating network concepts to each other, we define three types of network concepts: fundamental-, conformity-based-, and approximate conformity-based concepts. Fundamental concepts include the standard definitions of connectivity, density, centralization, heterogeneity, clustering coefficient, and topological overlap. The approximate conformity-based analogs of fundamental network concepts have several theoretical advantages. First, they allow one to derive simple relationships between seemingly disparate networks concepts. For example, we derive simple relationships between the clustering coefficient, the heterogeneity, the density, the centralization, and the topological overlap. The second advantage of approximate conformity-based network concepts is that they allow one to show that fundamental network concepts can be approximated by simple functions of the connectivity in module networks. Conclusion Using protein-protein interaction, gene co-expression, and simulated data, we show that a) many networks comprised of module nodes are approximately factorizable and b) in these types of networks, simple relationships exist between seemingly disparate network concepts. Our results are implemented in freely available R software code, which can be downloaded from the following webpage: http://www.genetics.ucla.edu/labs/horvath/ModuleConformity/ModuleNetworks PMID:17547772

Construction of phylogenetic trees by kernel-based comparative analysis of metabolic networks.

PubMed

Oh, S June; Joung, Je-Gun; Chang, Jeong-Ho; Zhang, Byoung-Tak

2006-06-06

To infer the tree of life requires knowledge of the common characteristics of each species descended from a common ancestor as the measuring criteria and a method to calculate the distance between the resulting values of each measure. Conventional phylogenetic analysis based on genomic sequences provides information about the genetic relationships between different organisms. In contrast, comparative analysis of metabolic pathways in different organisms can yield insights into their functional relationships under different physiological conditions. However, evaluating the similarities or differences between metabolic networks is a computationally challenging problem, and systematic methods of doing this are desirable. Here we introduce a graph-kernel method for computing the similarity between metabolic networks in polynomial time, and use it to profile metabolic pathways and to construct phylogenetic trees. To compare the structures of metabolic networks in organisms, we adopted the exponential graph kernel, which is a kernel-based approach with a labeled graph that includes a label matrix and an adjacency matrix. To construct the phylogenetic trees, we used an unweighted pair-group method with arithmetic mean, i.e., a hierarchical clustering algorithm. We applied the kernel-based network profiling method in a comparative analysis of nine carbohydrate metabolic networks from 81 biological species encompassing Archaea, Eukaryota, and Eubacteria. The resulting phylogenetic hierarchies generally support the tripartite scheme of three domains rather than the two domains of prokaryotes and eukaryotes. By combining the kernel machines with metabolic information, the method infers the context of biosphere development that covers physiological events required for adaptation by genetic reconstruction. The results show that one may obtain a global view of the tree of life by comparing the metabolic pathway structures using meta-level information rather than sequence information. This method may yield further information about biological evolution, such as the history of horizontal transfer of each gene, by studying the detailed structure of the phylogenetic tree constructed by the kernel-based method.

Covariance, correlation matrix, and the multiscale community structure of networks.

PubMed

Shen, Hua-Wei; Cheng, Xue-Qi; Fang, Bin-Xing

2010-07-01

Empirical studies show that real world networks often exhibit multiple scales of topological descriptions. However, it is still an open problem how to identify the intrinsic multiple scales of networks. In this paper, we consider detecting the multiscale community structure of network from the perspective of dimension reduction. According to this perspective, a covariance matrix of network is defined to uncover the multiscale community structure through the translation and rotation transformations. It is proved that the covariance matrix is the unbiased version of the well-known modularity matrix. We then point out that the translation and rotation transformations fail to deal with the heterogeneous network, which is very common in nature and society. To address this problem, a correlation matrix is proposed through introducing the rescaling transformation into the covariance matrix. Extensive tests on real world and artificial networks demonstrate that the correlation matrix significantly outperforms the covariance matrix, identically the modularity matrix, as regards identifying the multiscale community structure of network. This work provides a novel perspective to the identification of community structure and thus various dimension reduction methods might be used for the identification of community structure. Through introducing the correlation matrix, we further conclude that the rescaling transformation is crucial to identify the multiscale community structure of network, as well as the translation and rotation transformations.

Is My Network Module Preserved and Reproducible?

PubMed Central

Langfelder, Peter; Luo, Rui; Oldham, Michael C.; Horvath, Steve

2011-01-01

In many applications, one is interested in determining which of the properties of a network module change across conditions. For example, to validate the existence of a module, it is desirable to show that it is reproducible (or preserved) in an independent test network. Here we study several types of network preservation statistics that do not require a module assignment in the test network. We distinguish network preservation statistics by the type of the underlying network. Some preservation statistics are defined for a general network (defined by an adjacency matrix) while others are only defined for a correlation network (constructed on the basis of pairwise correlations between numeric variables). Our applications show that the correlation structure facilitates the definition of particularly powerful module preservation statistics. We illustrate that evaluating module preservation is in general different from evaluating cluster preservation. We find that it is advantageous to aggregate multiple preservation statistics into summary preservation statistics. We illustrate the use of these methods in six gene co-expression network applications including 1) preservation of cholesterol biosynthesis pathway in mouse tissues, 2) comparison of human and chimpanzee brain networks, 3) preservation of selected KEGG pathways between human and chimpanzee brain networks, 4) sex differences in human cortical networks, 5) sex differences in mouse liver networks. While we find no evidence for sex specific modules in human cortical networks, we find that several human cortical modules are less preserved in chimpanzees. In particular, apoptosis genes are differentially co-expressed between humans and chimpanzees. Our simulation studies and applications show that module preservation statistics are useful for studying differences between the modular structure of networks. Data, R software and accompanying tutorials can be downloaded from the following webpage: http://www.genetics.ucla.edu/labs/horvath/CoexpressionNetwork/ModulePreservation. PMID:21283776

Uplink Scheduling and Adjacent-Channel Coupling Loss Analysis for TD-LTE Deployment

PubMed Central

Yeo, Woon-Young; Moon, Sung Ho

2014-01-01

TD-LTE, one of the two duplexing modes in LTE, operates in unpaired spectrum and has the advantages of TDD-based technologies. It is expected that TD-LTE will be more rapidly deployed in near future and most of WiMax operators will upgrade their networks to TD-LTE gradually. Before completely upgrading to TD-LTE, WiMax may coexist with TD-LTE in an adjacent frequency band. In addition, multiple TD-LTE operators may deploy their networks in adjacent bands. When more than one TDD network operates in adjacent frequency bands, severe interference may happen due to adjacent channel interference (ACI) and unsynchronized operations. In this paper, coexistence issues between TD-LTE and other systems are analyzed and coexistence requirements are provided. This paper has three research objectives. First, frame synchronization between TD-LTE and WiMax is discussed by investigating possible combinations of TD-LTE and WiMax configurations. Second, an uplink scheduling algorithm is proposed to utilize a leakage pattern of ACI in synchronized operations. Third, minimum requirements for coexistence in unsynchronized operations are analyzed by introducing a concept of adjacent-channel coupling loss. From the analysis and simulation results, we can see that coexistence of TD-LTE with other TDD systems is feasible if the two networks are synchronized. For the unsynchronized case, some special cell-site engineering techniques may be required to reduce the ACI. PMID:24707214

Uplink scheduling and adjacent-channel coupling loss analysis for TD-LTE deployment.

PubMed

Yeo, Woon-Young; Moon, Sung Ho; Kim, Jae-Hoon

2014-01-01

TD-LTE, one of the two duplexing modes in LTE, operates in unpaired spectrum and has the advantages of TDD-based technologies. It is expected that TD-LTE will be more rapidly deployed in near future and most of WiMax operators will upgrade their networks to TD-LTE gradually. Before completely upgrading to TD-LTE, WiMax may coexist with TD-LTE in an adjacent frequency band. In addition, multiple TD-LTE operators may deploy their networks in adjacent bands. When more than one TDD network operates in adjacent frequency bands, severe interference may happen due to adjacent channel interference (ACI) and unsynchronized operations. In this paper, coexistence issues between TD-LTE and other systems are analyzed and coexistence requirements are provided. This paper has three research objectives. First, frame synchronization between TD-LTE and WiMax is discussed by investigating possible combinations of TD-LTE and WiMax configurations. Second, an uplink scheduling algorithm is proposed to utilize a leakage pattern of ACI in synchronized operations. Third, minimum requirements for coexistence in unsynchronized operations are analyzed by introducing a concept of adjacent-channel coupling loss. From the analysis and simulation results, we can see that coexistence of TD-LTE with other TDD systems is feasible if the two networks are synchronized. For the unsynchronized case, some special cell-site engineering techniques may be required to reduce the ACI.

Distributed vasculogenesis from modular agarose-hydroxyapatite-fibrinogen microbeads.

PubMed

Rioja, Ana Y; Daley, Ethan L H; Habif, Julia C; Putnam, Andrew J; Stegemann, Jan P

2017-06-01

Critical limb ischemia impairs circulation to the extremities, causing pain, disrupted wound healing, and potential tissue necrosis. Therapeutic angiogenesis seeks to repair the damaged microvasculature directly to restore blood flow. In this study, we developed modular, micro-scale constructs designed to possess robust handling qualities, allow in vitro pre-culture, and promote microvasculature formation. The microbead matrix consisted of an agarose (AG) base to prevent aggregation, combined with cell-adhesive components of fibrinogen (FGN) and/or hydroxyapatite (HA). Microbeads encapsulating a co-culture of human umbilical vein endothelial cells (HUVEC) and fibroblasts were prepared and characterized. Microbeads were generally 80-100µm in diameter, and the size increased with the addition of FGN and HA. Addition of HA increased the yield of microbeads, as well as the homogeneity of distribution of FGN within the matrix. Cell viability was high in all microbead types. When cell-seeded microbeads were embedded in fibrin hydrogels, HUVEC sprouting and inosculation between neighboring microbeads were observed over seven days. Pre-culture of microbeads for an additional seven days prior to embedding in fibrin resulted in significantly greater HUVEC network length in AG+HA+FGN microbeads, as compared to AG, AG+HA or AG+FGN microbeads. Importantly, composite microbeads resulted in more even and widespread endothelial network formation, relative to control microbeads consisting of pure fibrin. These results demonstrate that AG+HA+FGN microbeads support HUVEC sprouting both within and between adjacent microbeads, and can promote distributed vascularization of an external matrix. Such modular microtissues may have utility in treating ischemic tissue by rapidly re-establishing a microvascular network. Critical limb ischemia (CLI) is a chronic disease that can lead to tissue necrosis, amputation, and death. Cell-based therapies are being explored to restore blood flow and prevent the complications of CLI. In this study, we developed small, non-aggregating agarose-hydroxyapatite-fibrinogen microbeads that contained endothelial cells and fibroblasts. Microbeads were easy to handle and culture, and endothelial sprouts formed within and between microbeads. Our data demonstrates that the composition of the microbead matrix altered the degree of endothelial sprouting, and that the addition of hydroxyapatite and fibrinogen resulted in more distributed sprouting compared to pure fibrin microbeads. The microbead format and control of the matrix formulation may therefore be useful in developing revascularization strategies for the treatment of ischemic disease. Copyright © 2017 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.

Fuel cell having electrolyte

DOEpatents

Wright, Maynard K.

1989-01-01

A fuel cell having an electrolyte control volume includes a pair of porous opposed electrodes. A maxtrix is positioned between the pair of electrodes for containing an electrolyte. A first layer of backing paper is positioned adjacent to one of the electrodes. A portion of the paper is substantially previous to the acceptance of the electrolyte so as to absorb electrolyte when there is an excess in the matrix and to desorb electrolyte when there is a shortage in the matrix. A second layer of backing paper is positioned adjacent to the first layer of paper and is substantially impervious to the acceptance of electrolyte.

Link failure detection in a parallel computer

DOEpatents

Archer, Charles J.; Blocksome, Michael A.; Megerian, Mark G.; Smith, Brian E.

2010-11-09

Methods, apparatus, and products are disclosed for link failure detection in a parallel computer including compute nodes connected in a rectangular mesh network, each pair of adjacent compute nodes in the rectangular mesh network connected together using a pair of links, that includes: assigning each compute node to either a first group or a second group such that adjacent compute nodes in the rectangular mesh network are assigned to different groups; sending, by each of the compute nodes assigned to the first group, a first test message to each adjacent compute node assigned to the second group; determining, by each of the compute nodes assigned to the second group, whether the first test message was received from each adjacent compute node assigned to the first group; and notifying a user, by each of the compute nodes assigned to the second group, whether the first test message was received.

Estimation of a cover-type change matrix from error-prone data

Treesearch

Steen Magnussen

2009-01-01

Coregistration and classification errors seriously compromise per-pixel estimates of land cover change. A more robust estimation of change is proposed in which adjacent pixels are grouped into 3x3 clusters and treated as a unit of observation. A complete change matrix is recovered in a two-step process. The diagonal elements of a change matrix are recovered from...

Mathematical foundations of the GraphBLAS

DOE PAGES

Kepner, Jeremy; Aaltonen, Peter; Bader, David; ...

2016-12-01

The GraphBLAS standard (GraphBlas.org) is being developed to bring the potential of matrix-based graph algorithms to the broadest possible audience. Mathematically, the GraphBLAS defines a core set of matrix-based graph operations that can be used to implement a wide class of graph algorithms in a wide range of programming environments. This study provides an introduction to the mathematics of the GraphBLAS. Graphs represent connections between vertices with edges. Matrices can represent a wide range of graphs using adjacency matrices or incidence matrices. Adjacency matrices are often easier to analyze while incidence matrices are often better for representing data. Fortunately, themore » two are easily connected by matrix multiplication. A key feature of matrix mathematics is that a very small number of matrix operations can be used to manipulate a very wide range of graphs. This composability of a small number of operations is the foundation of the GraphBLAS. A standard such as the GraphBLAS can only be effective if it has low performance overhead. Finally, performance measurements of prototype GraphBLAS implementations indicate that the overhead is low.« less

Inferring Weighted Directed Association Network from Multivariate Time Series with a Synthetic Method of Partial Symbolic Transfer Entropy Spectrum and Granger Causality

PubMed Central

Hu, Yanzhu; Ai, Xinbo

2016-01-01

Complex network methodology is very useful for complex system explorer. However, the relationships among variables in complex system are usually not clear. Therefore, inferring association networks among variables from their observed data has been a popular research topic. We propose a synthetic method, named small-shuffle partial symbolic transfer entropy spectrum (SSPSTES), for inferring association network from multivariate time series. The method synthesizes surrogate data, partial symbolic transfer entropy (PSTE) and Granger causality. A proper threshold selection is crucial for common correlation identification methods and it is not easy for users. The proposed method can not only identify the strong correlation without selecting a threshold but also has the ability of correlation quantification, direction identification and temporal relation identification. The method can be divided into three layers, i.e. data layer, model layer and network layer. In the model layer, the method identifies all the possible pair-wise correlation. In the network layer, we introduce a filter algorithm to remove the indirect weak correlation and retain strong correlation. Finally, we build a weighted adjacency matrix, the value of each entry representing the correlation level between pair-wise variables, and then get the weighted directed association network. Two numerical simulated data from linear system and nonlinear system are illustrated to show the steps and performance of the proposed approach. The ability of the proposed method is approved by an application finally. PMID:27832153

Comparison of co-expression measures: mutual information, correlation, and model based indices.

PubMed

Song, Lin; Langfelder, Peter; Horvath, Steve

2012-12-09

Co-expression measures are often used to define networks among genes. Mutual information (MI) is often used as a generalized correlation measure. It is not clear how much MI adds beyond standard (robust) correlation measures or regression model based association measures. Further, it is important to assess what transformations of these and other co-expression measures lead to biologically meaningful modules (clusters of genes). We provide a comprehensive comparison between mutual information and several correlation measures in 8 empirical data sets and in simulations. We also study different approaches for transforming an adjacency matrix, e.g. using the topological overlap measure. Overall, we confirm close relationships between MI and correlation in all data sets which reflects the fact that most gene pairs satisfy linear or monotonic relationships. We discuss rare situations when the two measures disagree. We also compare correlation and MI based approaches when it comes to defining co-expression network modules. We show that a robust measure of correlation (the biweight midcorrelation transformed via the topological overlap transformation) leads to modules that are superior to MI based modules and maximal information coefficient (MIC) based modules in terms of gene ontology enrichment. We present a function that relates correlation to mutual information which can be used to approximate the mutual information from the corresponding correlation coefficient. We propose the use of polynomial or spline regression models as an alternative to MI for capturing non-linear relationships between quantitative variables. The biweight midcorrelation outperforms MI in terms of elucidating gene pairwise relationships. Coupled with the topological overlap matrix transformation, it often leads to more significantly enriched co-expression modules. Spline and polynomial networks form attractive alternatives to MI in case of non-linear relationships. Our results indicate that MI networks can safely be replaced by correlation networks when it comes to measuring co-expression relationships in stationary data.

A novel multilayer model for missing link prediction and future link forecasting in dynamic complex networks

NASA Astrophysics Data System (ADS)

Yasami, Yasser; Safaei, Farshad

2018-02-01

The traditional complex network theory is particularly focused on network models in which all network constituents are dealt with equivalently, while fail to consider the supplementary information related to the dynamic properties of the network interactions. This is a main constraint leading to incorrect descriptions of some real-world phenomena or incomplete capturing the details of certain real-life problems. To cope with the problem, this paper addresses the multilayer aspects of dynamic complex networks by analyzing the properties of intrinsically multilayered co-authorship networks, DBLP and Astro Physics, and presenting a novel multilayer model of dynamic complex networks. The model examines the layers evolution (layers birth/death process and lifetime) throughout the network evolution. Particularly, this paper models the evolution of each node's membership in different layers by an Infinite Factorial Hidden Markov Model considering feature cascade, and thereby formulates the link generation process for intra-layer and inter-layer links. Although adjacency matrixes are useful to describe the traditional single-layer networks, such a representation is not sufficient to describe and analyze the multilayer dynamic networks. This paper also extends a generalized mathematical infrastructure to address the problems issued by multilayer complex networks. The model inference is performed using some Markov Chain Monte Carlo sampling strategies, given synthetic and real complex networks data. Experimental results indicate a tremendous improvement in the performance of the proposed multilayer model in terms of sensitivity, specificity, positive and negative predictive values, positive and negative likelihood ratios, F1-score, Matthews correlation coefficient, and accuracy for two important applications of missing link prediction and future link forecasting. The experimental results also indicate the strong predictivepower of the proposed model for the application of cascade prediction in terms of accuracy.

Autoradiographic localization of specific (/sup 3/H)dexamethasone binding in fetal lung

DOE Office of Scientific and Technical Information (OSTI.GOV)

Beer, D.G.; Butley, M.S.; Cunha, G.R.

1984-10-01

The cellular and subcellular localization of specific (/sup 3/H)dexamethasone binding was examined in fetal mouse lung at various stages of development and in human fetal lung at 8 weeks of gestation using a rapid in vitro steroid incubation technique followed by thaw-mount autoradiography. Competition studies with unlabeled steroids demonstrate the specificity of (/sup 3/H)dexamethasone labeling, and indicate that fetal lung mesenchyme is a primary glucocorticoid target during lung development. Autoradiographs of (/sup 3/H)dexamethasone binding in lung tissue at early stages of development demonstrate that the mesenchyme directly adjacent to the more proximal portions of the bronchiolar network is heavily labeled.more » In contrast, the epithelium which will later differentiate into bronchi and bronchioles, is relatively unlabeled. Distal portions of the growing epithelium, destined to become alveolar ducts and alveoli, do show nuclear localization of (/sup 3/H)dexamethasone. In addition, by utilizing a technique which allows the simultaneous examination of extracellular matrix components and (/sup 3/H)dexamethasone binding, a relationship is observed between extensive mesenchymal (/sup 3/H)dexamethasone binding and extensive extracellular matrix accumulation. Since glucocorticoids stimulate the synthesis of many extracellular matrix components, these results suggest a role for these hormones in affecting mesenchymal-epithelial interactions during lung morphogenesis.« less

Coronally advanced flap with and without a xenogenic collagen matrix in the treatment of multiple recessions: a randomized controlled clinical study.

PubMed

Cardaropoli, Daniele; Tamagnone, Lorenzo; Roffredo, Alessandro; Gaveglio, Lorena

2014-01-01

Multiple adjacent recession defects were treated in 32 patients using a coronally advanced flap (CAF) with or without a collagen matrix (CM). The percentage of root coverage was 81.49% ± 23.45% (58% complete root coverage) for CAF sites (control) and 93.25% ± 10.01% root coverage (72% complete root coverage) for CM plus CAF sites (test). The results achieved in the test group were significantly greater than in the control group, indicating that CM plus CAF is a suitable option for the treatment of multiple adjacent gingival recessions.

Graph edit distance from spectral seriation.

PubMed

Robles-Kelly, Antonio; Hancock, Edwin R

2005-03-01

This paper is concerned with computing graph edit distance. One of the criticisms that can be leveled at existing methods for computing graph edit distance is that they lack some of the formality and rigor of the computation of string edit distance. Hence, our aim is to convert graphs to string sequences so that string matching techniques can be used. To do this, we use a graph spectral seriation method to convert the adjacency matrix into a string or sequence order. We show how the serial ordering can be established using the leading eigenvector of the graph adjacency matrix. We pose the problem of graph-matching as a maximum a posteriori probability (MAP) alignment of the seriation sequences for pairs of graphs. This treatment leads to an expression in which the edit cost is the negative logarithm of the a posteriori sequence alignment probability. We compute the edit distance by finding the sequence of string edit operations which minimizes the cost of the path traversing the edit lattice. The edit costs are determined by the components of the leading eigenvectors of the adjacency matrix and by the edge densities of the graphs being matched. We demonstrate the utility of the edit distance on a number of graph clustering problems.

A generalized graph-theoretical matrix of heterosystems and its application to the VMV procedure.

PubMed

Mozrzymas, Anna

2011-12-14

The extensions of generalized (molecular) graph-theoretical matrix and vector-matrix-vector procedure are considered. The elements of the generalized matrix are redefined in order to describe molecules containing heteroatoms and multiple bonds. The adjacency, distance, detour and reciprocal distance matrices of heterosystems, and corresponding vectors are derived from newly defined generalized graph matrix. The topological indices, which are most widely used in predicting physicochemical and biological properties/activities of various compounds, can be calculated from the new generalized vector-matrix-vector invariant. Copyright © 2011 Elsevier Ltd. All rights reserved.

The association between patient-therapist MATRIX congruence and treatment outcome.

PubMed

Mendlovic, Shlomo; Saad, Amit; Roll, Uri; Ben Yehuda, Ariel; Tuval-Mashiah, Rivka; Atzil-Slonim, Dana

2018-03-14

The present study aimed to examine the association between patient-therapist micro-level congruence/incongruence ratio and psychotherapeutic outcome. Nine good- and nine poor-outcome psychodynamic treatments (segregated by comparing pre- and post-treatment BDI-II) were analyzed (N = 18) moment by moment using the MATRIX (total number of MATRIX codes analyzed = 11,125). MATRIX congruence was defined as similar adjacent MATRIX codes. the congruence/incongruence ratio tended to increase as the treatment progressed only in good-outcome treatments. Progression of MATRIX codes' congruence/incongruence ratio is associated with good outcome of psychotherapy.

Efficient tree tensor network states (TTNS) for quantum chemistry: Generalizations of the density matrix renormalization group algorithm

NASA Astrophysics Data System (ADS)

Nakatani, Naoki; Chan, Garnet Kin-Lic

2013-04-01

We investigate tree tensor network states for quantum chemistry. Tree tensor network states represent one of the simplest generalizations of matrix product states and the density matrix renormalization group. While matrix product states encode a one-dimensional entanglement structure, tree tensor network states encode a tree entanglement structure, allowing for a more flexible description of general molecules. We describe an optimal tree tensor network state algorithm for quantum chemistry. We introduce the concept of half-renormalization which greatly improves the efficiency of the calculations. Using our efficient formulation we demonstrate the strengths and weaknesses of tree tensor network states versus matrix product states. We carry out benchmark calculations both on tree systems (hydrogen trees and π-conjugated dendrimers) as well as non-tree molecules (hydrogen chains, nitrogen dimer, and chromium dimer). In general, tree tensor network states require much fewer renormalized states to achieve the same accuracy as matrix product states. In non-tree molecules, whether this translates into a computational savings is system dependent, due to the higher prefactor and computational scaling associated with tree algorithms. In tree like molecules, tree network states are easily superior to matrix product states. As an illustration, our largest dendrimer calculation with tree tensor network states correlates 110 electrons in 110 active orbitals.

Communication Optimal Parallel Multiplication of Sparse Random Matrices

DTIC Science & Technology

2013-02-21

Definition 2.1), and (2) the algorithm is sparsity- independent, where the computation is statically partitioned to processors independent of the sparsity...struc- ture of the input matrices (see Definition 2.5). The second assumption applies to nearly all existing al- gorithms for general sparse matrix-matrix...where A and B are n× n ER(d) matrices: Definition 2.1 An ER(d) matrix is an adjacency matrix of an Erdős-Rényi graph with parameters n and d/n. That

Providing full point-to-point communications among compute nodes of an operational group in a global combining network of a parallel computer

DOEpatents

Archer, Charles J; Faraj, Ahmad A; Inglett, Todd A; Ratterman, Joseph D

2013-04-16

Methods, apparatus, and products are disclosed for providing full point-to-point communications among compute nodes of an operational group in a global combining network of a parallel computer, each compute node connected to each adjacent compute node in the global combining network through a link, that include: receiving a network packet in a compute node, the network packet specifying a destination compute node; selecting, in dependence upon the destination compute node, at least one of the links for the compute node along which to forward the network packet toward the destination compute node; and forwarding the network packet along the selected link to the adjacent compute node connected to the compute node through the selected link.

A Method for Using Adjacency Matrices to Analyze the Connections Students Make within and between Concepts: The Case of Linear Algebra

ERIC Educational Resources Information Center

Selinski, Natalie E.; Rasmussen, Chris; Wawro, Megan; Zandieh, Michelle

2014-01-01

The central goals of most introductory linear algebra courses are to develop students' proficiency with matrix techniques, to promote their understanding of key concepts, and to increase their ability to make connections between concepts. In this article, we present an innovative method using adjacency matrices to analyze students' interpretation…

On Connected Diagrams and Cumulants of Erdős-Rényi Matrix Models

NASA Astrophysics Data System (ADS)

Khorunzhiy, O.

2008-08-01

Regarding the adjacency matrices of n-vertex graphs and related graph Laplacian we introduce two families of discrete matrix models constructed both with the help of the Erdős-Rényi ensemble of random graphs. Corresponding matrix sums represent the characteristic functions of the average number of walks and closed walks over the random graph. These sums can be considered as discrete analogues of the matrix integrals of random matrix theory. We study the diagram structure of the cumulant expansions of logarithms of these matrix sums and analyze the limiting expressions as n → ∞ in the cases of constant and vanishing edge probabilities.

NET: a new framework for the vectorization and examination of network data.

PubMed

Lasser, Jana; Katifori, Eleni

2017-01-01

The analysis of complex networks both in general and in particular as pertaining to real biological systems has been the focus of intense scientific attention in the past and present. In this paper we introduce two tools that provide fast and efficient means for the processing and quantification of biological networks like Drosophila tracheoles or leaf venation patterns: the Network Extraction Tool ( NET ) to extract data and the Graph-edit-GUI ( GeGUI ) to visualize and modify networks. NET is especially designed for high-throughput semi-automated analysis of biological datasets containing digital images of networks. The framework starts with the segmentation of the image and then proceeds to vectorization using methodologies from optical character recognition. After a series of steps to clean and improve the quality of the extracted data the framework produces a graph in which the network is represented only by its nodes and neighborhood-relations. The final output contains information about the adjacency matrix of the graph, the width of the edges and the positions of the nodes in space. NET also provides tools for statistical analysis of the network properties, such as the number of nodes or total network length. Other, more complex metrics can be calculated by importing the vectorized network to specialized network analysis packages. GeGUI is designed to facilitate manual correction of non-planar networks as these may contain artifacts or spurious junctions due to branches crossing each other. It is tailored for but not limited to the processing of networks from microscopy images of Drosophila tracheoles. The networks extracted by NET closely approximate the network depicted in the original image. NET is fast, yields reproducible results and is able to capture the full geometry of the network, including curved branches. Additionally GeGUI allows easy handling and visualization of the networks.

Google matrix analysis of directed networks

NASA Astrophysics Data System (ADS)

Ermann, Leonardo; Frahm, Klaus M.; Shepelyansky, Dima L.

2015-10-01

In the past decade modern societies have developed enormous communication and social networks. Their classification and information retrieval processing has become a formidable task for the society. Because of the rapid growth of the World Wide Web, and social and communication networks, new mathematical methods have been invented to characterize the properties of these networks in a more detailed and precise way. Various search engines extensively use such methods. It is highly important to develop new tools to classify and rank a massive amount of network information in a way that is adapted to internal network structures and characteristics. This review describes the Google matrix analysis of directed complex networks demonstrating its efficiency using various examples including the World Wide Web, Wikipedia, software architectures, world trade, social and citation networks, brain neural networks, DNA sequences, and Ulam networks. The analytical and numerical matrix methods used in this analysis originate from the fields of Markov chains, quantum chaos, and random matrix theory.

Three list scheduling temporal partitioning algorithm of time space characteristic analysis and compare for dynamic reconfigurable computing

NASA Astrophysics Data System (ADS)

Chen, Naijin

2013-03-01

Level Based Partitioning (LBP) algorithm, Cluster Based Partitioning (CBP) algorithm and Enhance Static List (ESL) temporal partitioning algorithm based on adjacent matrix and adjacent table are designed and implemented in this paper. Also partitioning time and memory occupation based on three algorithms are compared. Experiment results show LBP partitioning algorithm possesses the least partitioning time and better parallel character, as far as memory occupation and partitioning time are concerned, algorithms based on adjacent table have less partitioning time and less space memory occupation.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Barone, C., E-mail: cbarone@unisa.it; Mauro, C.; Pagano, S.

Carbon nanotubes added to polymer and epoxy matrices are compounds of interest for applications in electronics and aerospace. The realization of high-performance devices based on these materials can profit from the investigation of their electric noise properties, as this gives a more detailed insight of the basic charge carriers transport mechanisms at work. The dc and electrical noise characteristics of different polymer/carbon nanotubes composites have been analyzed from 10 to 300 K. The results suggest that all these systems can be regarded as random resistive networks of tunnel junctions formed by adjacent carbon nanotubes. However, in the high-temperature regime, contributions derivingmore » from other possible mechanisms cannot be separated using dc information alone. A transition from a fluctuation-induced tunneling process to a thermally activated regime is instead revealed by electric noise spectroscopy. In particular, a crossover is found from a two-level tunneling mechanism, operating at low temperatures, to resistance fluctuations of a percolative network, in the high-temperature region. The observed behavior of 1/f noise seems to be a general feature for highly conductive samples, independent on the type of polymer matrix and on the nanotube density.« less

Aberrant gene expression in mucosa adjacent to tumor reveals a molecular crosstalk in colon cancer

PubMed Central

2014-01-01

Background A colorectal tumor is not an isolated entity growing in a restricted location of the body. The patient’s gut environment constitutes the framework where the tumor evolves and this relationship promotes and includes a complex and tight correlation of the tumor with inflammation, blood vessels formation, nutrition, and gut microbiome composition. The tumor influence in the environment could both promote an anti-tumor or a pro-tumor response. Methods A set of 98 paired adjacent mucosa and tumor tissues from colorectal cancer (CRC) patients and 50 colon mucosa from healthy donors (246 samples in total) were included in this work. RNA extracted from each sample was hybridized in Affymetrix chips Human Genome U219. Functional relationships between genes were inferred by means of systems biology using both transcriptional regulation networks (ARACNe algorithm) and protein-protein interaction networks (BIANA software). Results Here we report a transcriptomic analysis revealing a number of genes activated in adjacent mucosa from CRC patients, not activated in mucosa from healthy donors. A functional analysis of these genes suggested that this active reaction of the adjacent mucosa was related to the presence of the tumor. Transcriptional and protein-interaction networks were used to further elucidate this response of normal gut in front of the tumor, revealing a crosstalk between proteins secreted by the tumor and receptors activated in the adjacent colon tissue; and vice versa. Remarkably, Slit family of proteins activated ROBO receptors in tumor whereas tumor-secreted proteins transduced a cellular signal finally activating AP-1 in adjacent tissue. Conclusions The systems-level approach provides new insights into the micro-ecology of colorectal tumorogenesis. Disrupting this intricate molecular network of cell-cell communication and pro-inflammatory microenvironment could be a therapeutic target in CRC patients. PMID:24597571

Optimization of matrix tablets controlled drug release using Elman dynamic neural networks and decision trees.

PubMed

Petrović, Jelena; Ibrić, Svetlana; Betz, Gabriele; Đurić, Zorica

2012-05-30

The main objective of the study was to develop artificial intelligence methods for optimization of drug release from matrix tablets regardless of the matrix type. Static and dynamic artificial neural networks of the same topology were developed to model dissolution profiles of different matrix tablets types (hydrophilic/lipid) using formulation composition, compression force used for tableting and tablets porosity and tensile strength as input data. Potential application of decision trees in discovering knowledge from experimental data was also investigated. Polyethylene oxide polymer and glyceryl palmitostearate were used as matrix forming materials for hydrophilic and lipid matrix tablets, respectively whereas selected model drugs were diclofenac sodium and caffeine. Matrix tablets were prepared by direct compression method and tested for in vitro dissolution profiles. Optimization of static and dynamic neural networks used for modeling of drug release was performed using Monte Carlo simulations or genetic algorithms optimizer. Decision trees were constructed following discretization of data. Calculated difference (f(1)) and similarity (f(2)) factors for predicted and experimentally obtained dissolution profiles of test matrix tablets formulations indicate that Elman dynamic neural networks as well as decision trees are capable of accurate predictions of both hydrophilic and lipid matrix tablets dissolution profiles. Elman neural networks were compared to most frequently used static network, Multi-layered perceptron, and superiority of Elman networks have been demonstrated. Developed methods allow simple, yet very precise way of drug release predictions for both hydrophilic and lipid matrix tablets having controlled drug release. Copyright © 2012 Elsevier B.V. All rights reserved.

Fine-granularity inference and estimations to network traffic for SDN.

PubMed

Jiang, Dingde; Huo, Liuwei; Li, Ya

2018-01-01

An end-to-end network traffic matrix is significantly helpful for network management and for Software Defined Networks (SDN). However, the end-to-end network traffic matrix's inferences and estimations are a challenging problem. Moreover, attaining the traffic matrix in high-speed networks for SDN is a prohibitive challenge. This paper investigates how to estimate and recover the end-to-end network traffic matrix in fine time granularity from the sampled traffic traces, which is a hard inverse problem. Different from previous methods, the fractal interpolation is used to reconstruct the finer-granularity network traffic. Then, the cubic spline interpolation method is used to obtain the smooth reconstruction values. To attain an accurate the end-to-end network traffic in fine time granularity, we perform a weighted-geometric-average process for two interpolation results that are obtained. The simulation results show that our approaches are feasible and effective.

Fine-granularity inference and estimations to network traffic for SDN

PubMed Central

Huo, Liuwei; Li, Ya

2018-01-01

An end-to-end network traffic matrix is significantly helpful for network management and for Software Defined Networks (SDN). However, the end-to-end network traffic matrix's inferences and estimations are a challenging problem. Moreover, attaining the traffic matrix in high-speed networks for SDN is a prohibitive challenge. This paper investigates how to estimate and recover the end-to-end network traffic matrix in fine time granularity from the sampled traffic traces, which is a hard inverse problem. Different from previous methods, the fractal interpolation is used to reconstruct the finer-granularity network traffic. Then, the cubic spline interpolation method is used to obtain the smooth reconstruction values. To attain an accurate the end-to-end network traffic in fine time granularity, we perform a weighted-geometric-average process for two interpolation results that are obtained. The simulation results show that our approaches are feasible and effective. PMID:29718913

Computationally Efficient Modeling and Simulation of Large Scale Systems

NASA Technical Reports Server (NTRS)

Jain, Jitesh (Inventor); Koh, Cheng-Kok (Inventor); Balakrishnan, Vankataramanan (Inventor); Cauley, Stephen F (Inventor); Li, Hong (Inventor)

2014-01-01

A system for simulating operation of a VLSI interconnect structure having capacitive and inductive coupling between nodes thereof, including a processor, and a memory, the processor configured to perform obtaining a matrix X and a matrix Y containing different combinations of passive circuit element values for the interconnect structure, the element values for each matrix including inductance L and inverse capacitance P, obtaining an adjacency matrix A associated with the interconnect structure, storing the matrices X, Y, and A in the memory, and performing numerical integration to solve first and second equations.

Secure and Energy-Efficient Data Transmission System Based on Chaotic Compressive Sensing in Body-to-Body Networks.

PubMed

Peng, Haipeng; Tian, Ye; Kurths, Jurgen; Li, Lixiang; Yang, Yixian; Wang, Daoshun

2017-06-01

Applications of wireless body area networks (WBANs) are extended from remote health care to military, sports, disaster relief, etc. With the network scale expanding, nodes increasing, and links complicated, a WBAN evolves to a body-to-body network. Along with the development, energy saving and data security problems are highlighted. In this paper, chaotic compressive sensing (CCS) is proposed to solve these two crucial problems, simultaneously. Compared with the traditional compressive sensing, CCS can save vast storage space by only storing the matrix generation parameters. Additionally, the sensitivity of chaos can improve the security of data transmission. Aimed at image transmission, modified CCS is proposed, which uses two encryption mechanisms, confusion and mask, and performs a much better encryption quality. Simulation is conducted to verify the feasibility and effectiveness of the proposed methods. The results show that the energy efficiency and security are strongly improved, while the storage space is saved. And the secret key is extremely sensitive, [Formula: see text] perturbation of the secret key could lead to a total different decoding, the relative error is larger than 100%. Particularly for image encryption, the performance of the modified method is excellent. The adjacent pixel correlation is smaller than 0.04 in different directions including horizontal, vertical, and diagonal; the entropy of the cipher image with a 256-level gray value is larger than 7.98.

Providing full point-to-point communications among compute nodes of an operational group in a global combining network of a parallel computer

DOE Office of Scientific and Technical Information (OSTI.GOV)

Archer, Charles J.; Faraj, Daniel A.; Inglett, Todd A.

Methods, apparatus, and products are disclosed for providing full point-to-point communications among compute nodes of an operational group in a global combining network of a parallel computer, each compute node connected to each adjacent compute node in the global combining network through a link, that include: receiving a network packet in a compute node, the network packet specifying a destination compute node; selecting, in dependence upon the destination compute node, at least one of the links for the compute node along which to forward the network packet toward the destination compute node; and forwarding the network packet along the selectedmore » link to the adjacent compute node connected to the compute node through the selected link.« less

Modeling the average shortest-path length in growth of word-adjacency networks

NASA Astrophysics Data System (ADS)

Kulig, Andrzej; DroŻdŻ, Stanisław; Kwapień, Jarosław; OświÈ©cimka, Paweł

2015-03-01

We investigate properties of evolving linguistic networks defined by the word-adjacency relation. Such networks belong to the category of networks with accelerated growth but their shortest-path length appears to reveal the network size dependence of different functional form than the ones known so far. We thus compare the networks created from literary texts with their artificial substitutes based on different variants of the Dorogovtsev-Mendes model and observe that none of them is able to properly simulate the novel asymptotics of the shortest-path length. Then, we identify the local chainlike linear growth induced by grammar and style as a missing element in this model and extend it by incorporating such effects. It is in this way that a satisfactory agreement with the empirical result is obtained.

Crystal structure of an orthomyxovirus matrix protein reveals mechanisms for self-polymerization and membrane association.

PubMed

Zhang, Wenting; Zheng, Wenjie; Toh, Yukimatsu; Betancourt-Solis, Miguel A; Tu, Jiagang; Fan, Yanlin; Vakharia, Vikram N; Liu, Jun; McNew, James A; Jin, Meilin; Tao, Yizhi J

2017-08-08

Many enveloped viruses encode a matrix protein. In the influenza A virus, the matrix protein M1 polymerizes into a rigid protein layer underneath the viral envelope to help enforce the shape and structural integrity of intact viruses. The influenza virus M1 is also known to mediate virus budding as well as the nuclear export of the viral nucleocapsids and their subsequent packaging into nascent viral particles. Despite extensive studies on the influenza A virus M1 (FLUA-M1), only crystal structures of its N-terminal domain are available. Here we report the crystal structure of the full-length M1 from another orthomyxovirus that infects fish, the infectious salmon anemia virus (ISAV). The structure of ISAV-M1 assumes the shape of an elbow, with its N domain closely resembling that of the FLUA-M1. The C domain, which is connected to the N domain through a flexible linker, is made of four α-helices packed as a tight bundle. In the crystal, ISAV-M1 monomers form infinite 2D arrays with a network of interactions involving both the N and C domains. Results from liposome flotation assays indicated that ISAV-M1 binds membrane via electrostatic interactions that are primarily mediated by a positively charged surface loop from the N domain. Cryoelectron tomography reconstruction of intact ISA virions identified a matrix protein layer adjacent to the inner leaflet of the viral membrane. The physical dimensions of the virion-associated matrix layer are consistent with the 2D ISAV-M1 crystal lattice, suggesting that the crystal lattice is a valid model for studying M1-M1, M1-membrane, and M1-RNP interactions in the virion.

Epidemic spreading on preferred degree adaptive networks.

PubMed

Jolad, Shivakumar; Liu, Wenjia; Schmittmann, B; Zia, R K P

2012-01-01

We study the standard SIS model of epidemic spreading on networks where individuals have a fluctuating number of connections around a preferred degree κ. Using very simple rules for forming such preferred degree networks, we find some unusual statistical properties not found in familiar Erdös-Rényi or scale free networks. By letting κ depend on the fraction of infected individuals, we model the behavioral changes in response to how the extent of the epidemic is perceived. In our models, the behavioral adaptations can be either 'blind' or 'selective'--depending on whether a node adapts by cutting or adding links to randomly chosen partners or selectively, based on the state of the partner. For a frozen preferred network, we find that the infection threshold follows the heterogeneous mean field result λ(c)/μ = <κ>/<κ2> and the phase diagram matches the predictions of the annealed adjacency matrix (AAM) approach. With 'blind' adaptations, although the epidemic threshold remains unchanged, the infection level is substantially affected, depending on the details of the adaptation. The 'selective' adaptive SIS models are most interesting. Both the threshold and the level of infection changes, controlled not only by how the adaptations are implemented but also how often the nodes cut/add links (compared to the time scales of the epidemic spreading). A simple mean field theory is presented for the selective adaptations which capture the qualitative and some of the quantitative features of the infection phase diagram.

RAC-multi: reader anti-collision algorithm for multichannel mobile RFID networks.

PubMed

Shin, Kwangcheol; Song, Wonil

2010-01-01

At present, RFID is installed on mobile devices such as mobile phones or PDAs and provides a means to obtain information about objects equipped with an RFID tag over a multi-channeled telecommunication networks. To use mobile RFIDs, reader collision problems should be addressed given that readers are continuously moving. Moreover, in a multichannel environment for mobile RFIDs, interference between adjacent channels should be considered. This work first defines a new concept of a reader collision problem between adjacent channels and then suggests a novel reader anti-collision algorithm for RFID readers that use multiple channels. To avoid interference with adjacent channels, the suggested algorithm separates data channels into odd and even numbered channels and allocates odd-numbered channels first to readers. It also sets an unused channel between the control channel and data channels to ensure that control messages and the signal of the adjacent channel experience no interference. Experimental results show that suggested algorithm shows throughput improvements ranging from 29% to 46% for tag identifications compared to the GENTLE reader anti-collision algorithm for multichannel RFID networks.

RAC-Multi: Reader Anti-Collision Algorithm for Multichannel Mobile RFID Networks

PubMed Central

Shin, Kwangcheol; Song, Wonil

2010-01-01

At present, RFID is installed on mobile devices such as mobile phones or PDAs and provides a means to obtain information about objects equipped with an RFID tag over a multi-channeled telecommunication networks. To use mobile RFIDs, reader collision problems should be addressed given that readers are continuously moving. Moreover, in a multichannel environment for mobile RFIDs, interference between adjacent channels should be considered. This work first defines a new concept of a reader collision problem between adjacent channels and then suggests a novel reader anti-collision algorithm for RFID readers that use multiple channels. To avoid interference with adjacent channels, the suggested algorithm separates data channels into odd and even numbered channels and allocates odd-numbered channels first to readers. It also sets an unused channel between the control channel and data channels to ensure that control messages and the signal of the adjacent channel experience no interference. Experimental results show that suggested algorithm shows throughput improvements ranging from 29% to 46% for tag identifications compared to the GENTLE reader anti-collision algorithm for multichannel RFID networks. PMID:22315528

Use of the tunnel technique and an acellular dermal matrix in the treatment of multiple adjacent teeth with gingival recession in the esthetic zone.

PubMed

Mahn, Douglas H

2010-12-01

The proper management of gingival recession is critical to the establishment of a natural-appearing soft tissue architecture. Subepithelial connective tissue grafts have been considered the "gold standard" but are limited by the availability of palatal donor tissue. Tunnel techniques have improved the esthetic results of connective tissue grafting. Acellular dermal matrices have been successful in the treatment of gingival recession and are not limited by the palatal anatomy. The aim of this report is to describe the application of the tunnel technique, with use of an acellular dermal matrix, in the correction of gingival recession affecting multiple adjacent teeth in the esthetic zone.

Reactive solute transport in an asymmetrical fracture-rock matrix system

NASA Astrophysics Data System (ADS)

Zhou, Renjie; Zhan, Hongbin

2018-02-01

The understanding of reactive solute transport in a single fracture-rock matrix system is the foundation of studying transport behavior in the complex fractured porous media. When transport properties are asymmetrically distributed in the adjacent rock matrixes, reactive solute transport has to be considered as a coupled three-domain problem, which is more complex than the symmetric case with identical transport properties in the adjacent rock matrixes. This study deals with the transport problem in a single fracture-rock matrix system with asymmetrical distribution of transport properties in the rock matrixes. Mathematical models are developed for such a problem under the first-type and the third-type boundary conditions to analyze the spatio-temporal concentration and mass distribution in the fracture and rock matrix with the help of Laplace transform technique and de Hoog numerical inverse Laplace algorithm. The newly acquired solutions are then tested extensively against previous analytical and numerical solutions and are proven to be robust and accurate. Furthermore, a water flushing phase is imposed on the left boundary of system after a certain time. The diffusive mass exchange along the fracture/rock matrixes interfaces and the relative masses stored in each of three domains (fracture, upper rock matrix, and lower rock matrix) after the water flushing provide great insights of transport with asymmetric distribution of transport properties. This study has the following findings: 1) Asymmetric distribution of transport properties imposes greater controls on solute transport in the rock matrixes. However, transport in the fracture is mildly influenced. 2) The mass stored in the fracture responses quickly to water flushing, while the mass stored in the rock matrix is much less sensitive to the water flushing. 3) The diffusive mass exchange during the water flushing phase has similar patterns under symmetric and asymmetric cases. 4) The characteristic distance which refers to the zero diffusion between the fracture and the rock matrix during the water flushing phase is closely associated with dispersive process in the fracture.

Spectrum of walk matrix for Koch network and its application

NASA Astrophysics Data System (ADS)

Xie, Pinchen; Lin, Yuan; Zhang, Zhongzhi

2015-06-01

Various structural and dynamical properties of a network are encoded in the eigenvalues of walk matrix describing random walks on the network. In this paper, we study the spectra of walk matrix of the Koch network, which displays the prominent scale-free and small-world features. Utilizing the particular architecture of the network, we obtain all the eigenvalues and their corresponding multiplicities. Based on the link between the eigenvalues of walk matrix and random target access time defined as the expected time for a walker going from an arbitrary node to another one selected randomly according to the steady-state distribution, we then derive an explicit solution to the random target access time for random walks on the Koch network. Finally, we corroborate our computation for the eigenvalues by enumerating spanning trees in the Koch network, using the connection governing eigenvalues and spanning trees, where a spanning tree of a network is a subgraph of the network, that is, a tree containing all the nodes.

Optimization of the kernel functions in a probabilistic neural network analyzing the local pattern distribution.

PubMed

Galleske, I; Castellanos, J

2002-05-01

This article proposes a procedure for the automatic determination of the elements of the covariance matrix of the gaussian kernel function of probabilistic neural networks. Two matrices, a rotation matrix and a matrix of variances, can be calculated by analyzing the local environment of each training pattern. The combination of them will form the covariance matrix of each training pattern. This automation has two advantages: First, it will free the neural network designer from indicating the complete covariance matrix, and second, it will result in a network with better generalization ability than the original model. A variation of the famous two-spiral problem and real-world examples from the UCI Machine Learning Repository will show a classification rate not only better than the original probabilistic neural network but also that this model can outperform other well-known classification techniques.

Effect of landscape matrix type on nesting ecology of the Northern Cardinal

Treesearch

R.A. Sargent; J.C. Kilgo; B.R. Chapman; K.V. Miller

2015-01-01

Spatial distribution of forests relative to other habitats in a landscape may influence nest success of songbirds. For example, nest predation in mature forests increases as the percentage of clear-cut land in the surrounding matrix increases (Yahner and Scott 1988). Blake and Karr (1987) noted that birds breeding in forest fragments may incorporate adjacent habitats,...

A Basic Test Theory Generalizable to Tailored Testing. Technical Report No. 1.

ERIC Educational Resources Information Center

Cliff, Norman

Measures of consistency and completeness of order relations derived from test-type data are proposed. The measures are generalized to apply to incomplete data such as tailored testing. The measures are based on consideration of the items-plus-persons by items-plus-persons matrix as an adjacency matrix in which a 1 means that the row element…

Computationally efficient modeling and simulation of large scale systems

NASA Technical Reports Server (NTRS)

Jain, Jitesh (Inventor); Cauley, Stephen F. (Inventor); Li, Hong (Inventor); Koh, Cheng-Kok (Inventor); Balakrishnan, Venkataramanan (Inventor)

2010-01-01

A method of simulating operation of a VLSI interconnect structure having capacitive and inductive coupling between nodes thereof. A matrix X and a matrix Y containing different combinations of passive circuit element values for the interconnect structure are obtained where the element values for each matrix include inductance L and inverse capacitance P. An adjacency matrix A associated with the interconnect structure is obtained. Numerical integration is used to solve first and second equations, each including as a factor the product of the inverse matrix X.sup.1 and at least one other matrix, with first equation including X.sup.1Y, X.sup.1A, and X.sup.1P, and the second equation including X.sup.1A and X.sup.1P.

DiffSLC: A graph centrality method to detect essential proteins of a protein-protein interaction network.

PubMed

Mistry, Divya; Wise, Roger P; Dickerson, Julie A

2017-01-01

Identification of central genes and proteins in biomolecular networks provides credible candidates for pathway analysis, functional analysis, and essentiality prediction. The DiffSLC centrality measure predicts central and essential genes and proteins using a protein-protein interaction network. Network centrality measures prioritize nodes and edges based on their importance to the network topology. These measures helped identify critical genes and proteins in biomolecular networks. The proposed centrality measure, DiffSLC, combines the number of interactions of a protein and the gene coexpression values of genes from which those proteins were translated, as a weighting factor to bias the identification of essential proteins in a protein interaction network. Potentially essential proteins with low node degree are promoted through eigenvector centrality. Thus, the gene coexpression values are used in conjunction with the eigenvector of the network's adjacency matrix and edge clustering coefficient to improve essentiality prediction. The outcome of this prediction is shown using three variations: (1) inclusion or exclusion of gene co-expression data, (2) impact of different coexpression measures, and (3) impact of different gene expression data sets. For a total of seven networks, DiffSLC is compared to other centrality measures using Saccharomyces cerevisiae protein interaction networks and gene expression data. Comparisons are also performed for the top ranked proteins against the known essential genes from the Saccharomyces Gene Deletion Project, which show that DiffSLC detects more essential proteins and has a higher area under the ROC curve than other compared methods. This makes DiffSLC a stronger alternative to other centrality methods for detecting essential genes using a protein-protein interaction network that obeys centrality-lethality principle. DiffSLC is implemented using the igraph package in R, and networkx package in Python. The python package can be obtained from git.io/diffslcpy. The R implementation and code to reproduce the analysis is available via git.io/diffslc.

Deconvolution using a neural network

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lehman, S.K.

1990-11-15

Viewing one dimensional deconvolution as a matrix inversion problem, we compare a neural network backpropagation matrix inverse with LMS, and pseudo-inverse. This is a largely an exercise in understanding how our neural network code works. 1 ref.

Nitric oxide regulates tumor cell cross-talk with stromal cells in the tumor microenvironment of the liver.

PubMed

Decker, Ningling Kang; Abdelmoneim, Soha S; Yaqoob, Usman; Hendrickson, Helen; Hormes, Joe; Bentley, Mike; Pitot, Henry; Urrutia, Raul; Gores, Greg J; Shah, Vijay H

2008-10-01

Tumor progression is regulated through paracrine interactions between tumor cells and stromal cells in the microenvironment, including endothelial cells and myofibroblasts. Nitric oxide (NO) is a key molecule in the regulation of tumor-microenvironment interactions, although its precise role is incompletely defined. By using complementary in vitro and in vivo approaches, we studied the effect of endothelial NO synthase (eNOS)-derived NO on liver tumor growth and metastasis in relation to adjacent stromal myofibroblasts and matrix because liver tumors maintain a rich, vascular stromal network enriched with phenotypically heterogeneous myofibroblasts. Mice with an eNOS deficiency developed liver tumors more frequently in response to carcinogens compared with control animals. In a surgical model of pancreatic cancer liver metastasis, eNOS overexpression in the tumor microenvironment attenuated both the number and size of tumor implants. NO promoted anoikis of tumor cells in vitro and limited their invasive capacity. Because tumor cell anoikis and invasion are both regulated by myofibroblast-derived matrix, we explored the effect of NO on tumor cell protease expression. Both microarray and Western blot analysis revealed eNOS-dependent down-regulation of the matrix protease cathepsin B within tumor cells, and silencing of cathepsin B attenuated tumor cell invasive capacity in a similar manner to that observed with eNOS overexpression. Thus, a NO gradient within the tumor microenvironment influences tumor progression through orchestrated molecular interactions between tumor cells and stroma.

Network analysis of a financial market based on genuine correlation and threshold method

NASA Astrophysics Data System (ADS)

Namaki, A.; Shirazi, A. H.; Raei, R.; Jafari, G. R.

2011-10-01

A financial market is an example of an adaptive complex network consisting of many interacting units. This network reflects market’s behavior. In this paper, we use Random Matrix Theory (RMT) notion for specifying the largest eigenvector of correlation matrix as the market mode of stock network. For a better risk management, we clean the correlation matrix by removing the market mode from data and then construct this matrix based on the residuals. We show that this technique has an important effect on correlation coefficient distribution by applying it for Dow Jones Industrial Average (DJIA). To study the topological structure of a network we apply the removing market mode technique and the threshold method to Tehran Stock Exchange (TSE) as an example. We show that this network follows a power-law model in certain intervals. We also show the behavior of clustering coefficients and component numbers of this network for different thresholds. These outputs are useful for both theoretical and practical purposes such as asset allocation and risk management.

Complex network analysis of resting-state fMRI of the brain.

PubMed

Anwar, Abdul Rauf; Hashmy, Muhammad Yousaf; Imran, Bilal; Riaz, Muhammad Hussnain; Mehdi, Sabtain Muhammad Muntazir; Muthalib, Makii; Perrey, Stephane; Deuschl, Gunther; Groppa, Sergiu; Muthuraman, Muthuraman

2016-08-01

Due to the fact that the brain activity hardly ever diminishes in healthy individuals, analysis of resting state functionality of the brain seems pertinent. Various resting state networks are active inside the idle brain at any time. Based on various neuro-imaging studies, it is understood that various structurally distant regions of the brain could be functionally connected. Regions of the brain, that are functionally connected, during rest constitutes to the resting state network. In the present study, we employed the complex network measures to estimate the presence of community structures within a network. Such estimate is named as modularity. Instead of using a traditional correlation matrix, we used a coherence matrix taken from the causality measure between different nodes. Our results show that in prolonged resting state the modularity starts to decrease. This decrease was observed in all the resting state networks and on both sides of the brain. Our study highlights the usage of coherence matrix instead of correlation matrix for complex network analysis.

Whitby Mudstone, flow from matrix to fractures

NASA Astrophysics Data System (ADS)

Houben, Maartje; Hardebol, Nico; Barnhoorn, Auke; Boersma, Quinten; Peach, Colin; Bertotti, Giovanni; Drury, Martyn

2016-04-01

Fluid flow from matrix to well in shales would be faster if we account for the duality of the permeable medium considering a high permeable fracture network together with a tight matrix. To investigate how long and how far a gas molecule would have to travel through the matrix until it reaches an open connected fracture we investigated the permeability of the Whitby Mudstone (UK) matrix in combination with mapping the fracture network present in the current outcrops of the Whitby Mudstone at the Yorkshire coast. Matrix permeability was measured perpendicular to the bedding using a pressure step decay method on core samples and permeability values are in the microdarcy range. The natural fracture network present in the pavement shows a connected network with dominant NS and EW strikes, where the NS fractures are the main fracture set with an orthogonal fracture set EW. Fracture spacing relations in the pavements show that the average distance to the nearest fracture varies between 7 cm (EW) and 14 cm (NS), where 90% of the matrix is 30 cm away from the nearest fracture. By making some assumptions like; fracture network at depth is similar to what is exposed in the current pavements and open to flow, fracture network is at hydrostatic pressure at 3 km depth, overpressure between matrix and fractures is 10% and a matrix permeability perpendicular to the bedding of 0.1 microdarcy, we have calculated the time it takes for a gas molecule to travel to the nearest fracture. These input values give travel times up to 8 days for a distance of 14 cm. If the permeability is changed to 1 nanodarcy or 10 microdarcy travel times change to 2.2 years or 2 hours respectively.

Generating probabilistic Boolean networks from a prescribed transition probability matrix.

PubMed

Ching, W-K; Chen, X; Tsing, N-K

2009-11-01

Probabilistic Boolean networks (PBNs) have received much attention in modeling genetic regulatory networks. A PBN can be regarded as a Markov chain process and is characterised by a transition probability matrix. In this study, the authors propose efficient algorithms for constructing a PBN when its transition probability matrix is given. The complexities of the algorithms are also analysed. This is an interesting inverse problem in network inference using steady-state data. The problem is important as most microarray data sets are assumed to be obtained from sampling the steady-state.

A Conceptual Framework for Representing Human Behavior Characteristics in a System of Systems Agent-Based Survivability Simulation

DTIC Science & Technology

2010-11-22

fuzzy matrix converges to a “zero-one” matrix. The values of “0” and “1” simply means that two edges of the network with “1” have a crisp ...fuzzy matrix converges to a “zero-one” matrix. The values of “0” and “1” simply means that two edges of the network with “1” have a crisp connectivity...converges to a “zero-one” matrix. The values of “0” and “1” simply means that two edges of the network with “1” have a crisp connectivity (and

Topological Distances Between Brain Networks

PubMed Central

Lee, Hyekyoung; Solo, Victor; Davidson, Richard J.; Pollak, Seth D.

2018-01-01

Many existing brain network distances are based on matrix norms. The element-wise differences may fail to capture underlying topological differences. Further, matrix norms are sensitive to outliers. A few extreme edge weights may severely affect the distance. Thus it is necessary to develop network distances that recognize topology. In this paper, we introduce Gromov-Hausdorff (GH) and Kolmogorov-Smirnov (KS) distances. GH-distance is often used in persistent homology based brain network models. The superior performance of KS-distance is contrasted against matrix norms and GH-distance in random network simulations with the ground truths. The KS-distance is then applied in characterizing the multimodal MRI and DTI study of maltreated children.

MATLAB Simulation of Gradient-Based Neural Network for Online Matrix Inversion

NASA Astrophysics Data System (ADS)

Zhang, Yunong; Chen, Ke; Ma, Weimu; Li, Xiao-Dong

This paper investigates the simulation of a gradient-based recurrent neural network for online solution of the matrix-inverse problem. Several important techniques are employed as follows to simulate such a neural system. 1) Kronecker product of matrices is introduced to transform a matrix-differential-equation (MDE) to a vector-differential-equation (VDE); i.e., finally, a standard ordinary-differential-equation (ODE) is obtained. 2) MATLAB routine "ode45" is introduced to solve the transformed initial-value ODE problem. 3) In addition to various implementation errors, different kinds of activation functions are simulated to show the characteristics of such a neural network. Simulation results substantiate the theoretical analysis and efficacy of the gradient-based neural network for online constant matrix inversion.

Assessing Anthropogenic Influence and Edge Effect Influence on Forested Riparian Buffer Spatial Configuration and Structure: An Example Using Lidar Remote Sensing Methods

NASA Astrophysics Data System (ADS)

Wasser, L. A.; Chasmer, L. E.

2012-12-01

Forested riparian buffers (FRB) perform numerous critical ecosystem services. However, globally, FRB spatial configuration and structure have been modified by anthropogenic development resulting in widespread ecological degradation as seen in the Gulf of Mexico and the Chesapeake Bay. Riparian corridors within developed areas are particularly vulnerable to disturbance given two edges - the naturally occurring stream edge and the matrix edge. Increased edge length predisposes riparian vegetation to "edge effects", characterized by modified physical and environmental conditions at the interface between the forested buffer and the adjacent landuse, or matrix and forest fragment degradation. The magnitude and distance of edge influence may be further influenced by adjacent landuse type and the width of the buffer corridor at any given location. There is a need to quantify riparian buffer spatial configuration and structure over broad geographic extents and within multiple riparian systems in support of ecologically sound management and landuse decisions. This study thus assesses the influence of varying landuse types (agriculture, suburban development and undeveloped) on forested riparian buffer 3-dimensional structure and spatial configuration using high resolution Light Detection and Ranging (LiDAR) data collected within a headwater watershed. Few studies have assessed riparian buffer structure and width contiguously for an entire watershed, an integral component of watershed planning and restoration efforts such as those conducted throughout the Chesapeake Bay. The objectives of the study are to 1) quantify differences in vegetation structure at the stream and matrix influenced riparian buffer edges, compared to the forested interior and 2) assess continuous patterns of changes in vegetation structure throughout the buffer corridor beginning at the matrix edge and ending at the stream within buffers a) of varying width and b) that are adjacent to varying landuse types. Results suggest that 1) the spatial configuration of riparian forests has a strong influence on forest structure compared to a weaker association with adjacent landuse type 2) developed landuse types are often associated with increased understory vegetation density 3) that riparian vegetation canopy cover is dense regardless of corridor width or adjacent landuse type and 4) the degree to which edge effects propagate into the buffer corridor is most influenced by corridor width. The study further demonstrates the utility of automated algorithms that sample lidar data in watershed-wide ecological analysis. Results suggest that landuse regulations should encourage wider buffers which will in turn support a greater range of ecosystem services including improved wildlife habitat, stream shading and detrital inputs.

Lattice Boltzmann simulation of CO2 reactive transport in network fractured media

NASA Astrophysics Data System (ADS)

Tian, Zhiwei; Wang, Junye

2017-08-01

Carbon dioxide (CO2) geological sequestration plays an important role in mitigating CO2 emissions for climate change. Understanding interactions of the injected CO2 with network fractures and hydrocarbons is key for optimizing and controlling CO2 geological sequestration and evaluating its risks to ground water. However, there is a well-known, difficult process in simulating the dynamic interaction of fracture-matrix, such as dynamic change of matrix porosity, unsaturated processes in rock matrix, and effect of rock mineral properties. In this paper, we develop an explicit model of the fracture-matrix interactions using multilayer bounce-back treatment as a first attempt to simulate CO2 reactive transport in network fractured media through coupling the Dardis's LBM porous model for a new interface treatment. Two kinds of typical fracture networks in porous media are simulated: straight cross network fractures and interleaving network fractures. The reaction rate and porosity distribution are illustrated and well-matched patterns are found. The species concentration distribution and evolution with time steps are also analyzed and compared with different transport properties. The results demonstrate the capability of this model to investigate the complex processes of CO2 geological injection and reactive transport in network fractured media, such as dynamic change of matrix porosity.

Autoscoring Essays Based on Complex Networks

ERIC Educational Resources Information Center

Ke, Xiaohua; Zeng, Yongqiang; Luo, Haijiao

2016-01-01

This article presents a novel method, the Complex Dynamics Essay Scorer (CDES), for automated essay scoring using complex network features. Texts produced by college students in China were represented as scale-free networks (e.g., a word adjacency model) from which typical network features, such as the in-/out-degrees, clustering coefficient (CC),…

Linear matrix inequality approach to exponential synchronization of a class of chaotic neural networks with time-varying delays

NASA Astrophysics Data System (ADS)

Wu, Wei; Cui, Bao-Tong

2007-07-01

In this paper, a synchronization scheme for a class of chaotic neural networks with time-varying delays is presented. This class of chaotic neural networks covers several well-known neural networks, such as Hopfield neural networks, cellular neural networks, and bidirectional associative memory networks. The obtained criteria are expressed in terms of linear matrix inequalities, thus they can be efficiently verified. A comparison between our results and the previous results shows that our results are less restrictive.

Electronic and optical properties of GaN/AlN quantum dots with adjacent threading dislocations

NASA Astrophysics Data System (ADS)

Ye, Han; Lu, Peng-Fei; Yu, Zhong-Yuan; Yao, Wen-Jie; Chen, Zhi-Hui; Jia, Bo-Yong; Liu, Yu-Min

2010-04-01

We present a theory to simulate a coherent GaN QD with an adjacent pure edge threading dislocation by using a finite element method. The piezoelectric effects and the strain modified band edges are investigated in the framework of multi-band k · p theory to calculate the electron and the heavy hole energy levels. The linear optical absorption coefficients corresponding to the interband ground state transition are obtained via the density matrix approach and perturbation expansion method. The results indicate that the strain distribution of the threading dislocation affects the electronic structure. Moreover, the ground state transition behaviour is also influenced by the position of the adjacent threading dislocation.

The method of similar operators in the study of the spectra of the adjacency matrices of graphs

NASA Astrophysics Data System (ADS)

Kozlukov, Serge

2018-03-01

The method of similar operators [1, 2, 3] is used to investigate spectral properties of a certain class of matrices in the context of graphs [4, 5]. Specifically, we consider the adjacency matrix of an “almost-complete graph”. Then we generalize the result to allow the matrices obtained as combinations of the Kronecker products [6, 7] and the small-norm perturbations. We derive the estimates of the spectra and the eigenvectors of such matrices.

Singular Vectors' Subtle Secrets

ERIC Educational Resources Information Center

James, David; Lachance, Michael; Remski, Joan

2011-01-01

Social scientists use adjacency tables to discover influence networks within and among groups. Building on work by Moler and Morrison, we use ordered pairs from the components of the first and second singular vectors of adjacency matrices as tools to distinguish these groups and to identify particularly strong or weak individuals.

Dynamics of VEGF matrix-retention in vascular network patterning

NASA Astrophysics Data System (ADS)

Köhn-Luque, A.; de Back, W.; Yamaguchi, Y.; Yoshimura, K.; Herrero, M. A.; Miura, T.

2013-12-01

Vascular endothelial growth factor (VEGF) is a central regulator of blood vessel morphogenesis, although its role in patterning of endothelial cells into vascular networks is not fully understood. It has been suggested that binding of soluble VEGF to extracellular matrix components causes spatially restricted cues that guide endothelial cells into network patterns. Yet, current evidence for such a mechanism remains indirect. In this study, we quantitatively analyse the dynamics of VEGF retention in a controlled in vitro situation of human umbilical vascular endothelial cells (HUVECs) in Matrigel. We show that fluorescent VEGF accumulates in pericellular areas and colocalizes with VEGF binding molecules. Analysis of fluorescence recovery after photobleaching reveals that binding/unbinding to matrix molecules dominates VEGF dynamics in the pericellular region. Computational simulations using our experimental measurements of kinetic parameters show that matrix retention of chemotactic signals can lead to the formation of reticular cellular networks on a realistic timescale. Taken together, these results show that VEGF binds to matrix molecules in proximity of HUVECs in Matrigel, and suggest that bound VEGF drives vascular network patterning.

Geometric control of capillary architecture via cell-matrix mechanical interactions.

PubMed

Sun, Jian; Jamilpour, Nima; Wang, Fei-Yue; Wong, Pak Kin

2014-03-01

Capillary morphogenesis is a multistage, multicellular activity that plays a pivotal role in various developmental and pathological situations. In-depth understanding of the regulatory mechanism along with the capability of controlling the morphogenic process will have direct implications on tissue engineering and therapeutic angiogenesis. Extensive research has been devoted to elucidate the biochemical factors that regulate capillary morphogenesis. The roles of geometric confinement and cell-matrix mechanical interactions on the capillary architecture, nevertheless, remain largely unknown. Here, we show geometric control of endothelial network topology by creating physical confinements with microfabricated fences and wells. Decreasing the thickness of the matrix also results in comparable modulation of the network architecture, supporting the boundary effect is mediated mechanically. The regulatory role of cell-matrix mechanical interaction on the network topology is further supported by alternating the matrix stiffness by a cell-inert PEG-dextran hydrogel. Furthermore, reducing the cell traction force with a Rho-associated protein kinase inhibitor diminishes the boundary effect. Computational biomechanical analysis delineates the relationship between geometric confinement and cell-matrix mechanical interaction. Collectively, these results reveal a mechanoregulation scheme of endothelial cells to regulate the capillary network architecture via cell-matrix mechanical interactions. Copyright © 2014 Elsevier Ltd. All rights reserved.

Assessment of Matrix Multiplication Learning with a Rule-Based Analytical Model--"A Bayesian Network Representation"

ERIC Educational Resources Information Center

Zhang, Zhidong

2016-01-01

This study explored an alternative assessment procedure to examine learning trajectories of matrix multiplication. It took rule-based analytical and cognitive task analysis methods specifically to break down operation rules for a given matrix multiplication. Based on the analysis results, a hierarchical Bayesian network, an assessment model,…

Electronic implementation of associative memory based on neural network models

NASA Technical Reports Server (NTRS)

Moopenn, A.; Lambe, John; Thakoor, A. P.

1987-01-01

An electronic embodiment of a neural network based associative memory in the form of a binary connection matrix is described. The nature of false memory errors, their effect on the information storage capacity of binary connection matrix memories, and a novel technique to eliminate such errors with the help of asymmetrical extra connections are discussed. The stability of the matrix memory system incorporating a unique local inhibition scheme is analyzed in terms of local minimization of an energy function. The memory's stability, dynamic behavior, and recall capability are investigated using a 32-'neuron' electronic neural network memory with a 1024-programmable binary connection matrix.

8. MACHINERY SHED STORAGE ROOM ADDITION DETAIL SHOWING MATRIX OF ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

8. MACHINERY SHED STORAGE ROOM ADDITION DETAIL SHOWING MATRIX OF NAILS USED TO ADHERE PORTLAND CEMENT PLASTER, SOUTH ADOBE WALL ADJACENT TO WINDOW Note: Photographs Nos. AZ-159-A-9 through AZ-159-A-10 are photocopies of photographs. The original prints and negatives are located in the SCS Tucson Plant Materials Center, Tucson, Arizona. Photographer Ted F. Spaller. - Tucson Plant Material Center, Machinery Shed, 3241 North Romero Road, Tucson, Pima County, AZ

Composites incorporated a conductive polymer nanofiber network

DOEpatents

Pozzo, Lilo Danielle; Newbloom, Gregory

2017-04-11

Methods of forming composites that incorporate networks of conductive polymer nanofibers are provided. Networks of less-than conductive polymers are first formed and then doped with a chemical dopant to provide networks of conductive polymers. The networks of conductive polymers are then incorporated into a matrix in order to improve the conductivity of the matrix. The formed composites are useful as conductive coatings for applications including electromagnetic energy management on exterior surfaces of vehicles.

Discontinuities in effective permeability due to fracture percolation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hyman, Jeffrey De'Haven; Karra, Satish; Carey, James William

Motivated by a triaxial coreflood experiment with a sample of Utica shale where an abrupt jump in permeability was observed, possibly due to the creation of a percolating fracture network through the sample, we perform numerical simulations based on the experiment to characterize how the effective permeability of otherwise low-permeability porous media depends on fracture formation, connectivity, and the contrast between the fracture and matrix permeabilities. While a change in effective permeability due to fracture formation is expected, the dependence of its magnitude upon the contrast between the matrix permeability and fracture permeability and the fracture network structure is poorlymore » characterized. We use two different high-fidelity fracture network models to characterize how effective permeability changes as percolation occurs. The first is a dynamic two-dimensional fracture propagation model designed to mimic the laboratory settings of the experiment. The second is a static three-dimensional discrete fracture network (DFN) model, whose fracture and network statistics are based on the fractured sample of Utica shale. Once the network connects the inflow and outflow boundaries, the effective permeability increases non-linearly with network density. In most networks considered, a jump in the effective permeability was observed when the embedded fracture network percolated. We characterize how the magnitude of the jump, should it occur, depends on the contrast between the fracture and matrix permeabilities. For small contrasts between the matrix and fracture permeabilities the change is insignificant. However, for larger contrasts, there is a substantial jump whose magnitude depends non-linearly on the difference between matrix and fracture permeabilities. A power-law relationship between the size of the jump and the difference between the matrix and fracture permeabilities is observed. In conclusion, the presented results underscore the importance of fracture network topology on the upscaled properties of the porous medium in which it is embedded.« less

Discontinuities in effective permeability due to fracture percolation

DOE PAGES

Hyman, Jeffrey De'Haven; Karra, Satish; Carey, James William; ...

2018-01-31

Motivated by a triaxial coreflood experiment with a sample of Utica shale where an abrupt jump in permeability was observed, possibly due to the creation of a percolating fracture network through the sample, we perform numerical simulations based on the experiment to characterize how the effective permeability of otherwise low-permeability porous media depends on fracture formation, connectivity, and the contrast between the fracture and matrix permeabilities. While a change in effective permeability due to fracture formation is expected, the dependence of its magnitude upon the contrast between the matrix permeability and fracture permeability and the fracture network structure is poorlymore » characterized. We use two different high-fidelity fracture network models to characterize how effective permeability changes as percolation occurs. The first is a dynamic two-dimensional fracture propagation model designed to mimic the laboratory settings of the experiment. The second is a static three-dimensional discrete fracture network (DFN) model, whose fracture and network statistics are based on the fractured sample of Utica shale. Once the network connects the inflow and outflow boundaries, the effective permeability increases non-linearly with network density. In most networks considered, a jump in the effective permeability was observed when the embedded fracture network percolated. We characterize how the magnitude of the jump, should it occur, depends on the contrast between the fracture and matrix permeabilities. For small contrasts between the matrix and fracture permeabilities the change is insignificant. However, for larger contrasts, there is a substantial jump whose magnitude depends non-linearly on the difference between matrix and fracture permeabilities. A power-law relationship between the size of the jump and the difference between the matrix and fracture permeabilities is observed. In conclusion, the presented results underscore the importance of fracture network topology on the upscaled properties of the porous medium in which it is embedded.« less

Structure for HTS composite conductors and the manufacture of same

DOEpatents

Cotton, J.D.; Riley, G.N. Jr.

1999-06-01

A superconducting oxide composite structure including a superconducting oxide member, a metal layer surrounding the superconducting oxide member, and an insulating layer of a complex oxide formed in situ adjacent to the superconducting oxide member and the metal layer is provided together with a method of forming such a superconducting oxide composite structure including encapsulating a superconducting oxide member or precursor within a metal matrix layer from the group of: (1) a reactive metal sheath adjacent to the superconducting oxide member or precursor, the reactive metal sheath surrounded by a second metal layer or (2) an alloy containing a reactive metal; to form an intermediate product, and, heating the intermediate product at temperatures and for time sufficient to form an insulating layer of a complex oxide in situ, the insulating layer to the superconducting oxide member or precursor and the metal matrix layer. 10 figs.

Structure for hts composite conductors and the manufacture of same

DOEpatents

Cotton, James D.; Riley, Jr., Gilbert Neal

1999-01-01

A superconducting oxide composite structure including a superconducting oxide member, a metal layer surrounding the superconducting oxide member, and an insulating layer of a complex oxide formed in situ adjacent to the superconducting oxide member and the metal layer is provided together with a method of forming such a superconducting oxide composite structure including encapsulating a superconducting oxide member or precursor within a metal matrix layer from the group of: (i) a reactive metal sheath adjacent to the superconducting oxide member or precursor, the reactive metal sheath surrounded by a second metal layer or (ii) an alloy containing a reactive metal; to form an intermediate product, and, heating the intermediate product at temperatures and for time sufficient to form an insulating layer of a complex oxide in situ, the insulating layer to the superconducting oxide member or precursor and the metal matrix layer.

Deformation analysis of boron/aluminum specimens by moire interferometry

NASA Technical Reports Server (NTRS)

Post, Daniel; Guo, Yifan; Czarnek, Robert

1989-01-01

Whole-field surface deformations were measured for two slotted tension specimens from multiply laminates, one with 0 deg fiber orientation in the surface ply and the other with 45 deg orientation. Macromechanical and micromechanical details were revealed using high-sensitivity moire interferometry. Although global deformations of all plies were essentially equal, numerous random or anomalous features were observed. Local deformations of adjacent 0 deg and 45 deg plies were very different, both near the slot and remote from it, requiring large interlaminar shear strains for continuity. Shear strains were concentrated in the aluminum matrix. For 45 deg plies, a major portion of the deformation was by shear; large plastic slip of matrix occurred at random locations in 45 deg plies, wherein groups of fibers slipped relative to other groups. Shear strains in the interior, between adjacent fibers, were larger than the measured surface strains.

SENTRE and TREND attenuator field installations

DOT National Transportation Integrated Search

1990-02-01

Arizona's canal network is extensive and necessitates the existence of many short bridges on the highway network. The necessity for maintaining access to adjacent canal roads dictates that any barrier installation intended to shield errant vehicles f...

Extending Topological Approaches to Microseismic-Derived 3D Fracture Networks

NASA Astrophysics Data System (ADS)

Urbancic, T.; Bosman, K.; Baig, A.; Ardakani, E. P.

2017-12-01

Fracture topology is important for determining the fluid-flow characteristics of a fracture network. In most unconventional petroleum applications, flow through subsurface fracture networks is the primary source of production, as matrix permeability is often in the nanodarcy range. Typical models of reservoir discrete fracture networks (DFNs) are constructed using fracture orientation and average spacing, without consideration of how the connectivity of the fracture network aids the percolation of hydrocarbons back to the wellbore. Topological approaches to DFN characterization have been developed and extensively used in analysis of outcrop data and aerial photography. Such study of the surface expression of fracture networks is straight-forward, and the physical form of the observed fractures is directly reflected in the parameters used to describe the topology. However, this analysis largely ignores the three-dimensional nature of natural fracture networks, which is difficult to define accurately in geological studies. SMTI analysis of microseismic event distributions can produce DFNs, where each event is represented by a penny-shaped crack with radius and orientation determined from the frequency content of the waveforms and assessment of the slip instability of the potential fracture planes, respectively. Analysis of the geometric relationships between a set of fractures can provide details of intersections between fractures, and thus the topological characteristics of the fracture network. Extension of existing 2D topology approaches to 3D fracture networks is non-trivial. In the 2D case, a fracture intersection is a single point (node), and branches connect adjacent nodes along fractures. For the 3D case, intersection "nodes" become lines, and connecting nodes to find branches becomes more complicated. There are several parameters defined in 2D topology to quantify the connectivity of the fracture network. Equivalent quantities must be defined and calibrated for the 3D case to provide a meaningful measurement of fracture network connectivity. We have developed an approach to analyze the topology of 3D fracture networks derived from microseismic moment tensors. We illustrate the utility of the approach with applications to example datasets from hydraulic fracturing completions.

Matrix product algorithm for stochastic dynamics on networks applied to nonequilibrium Glauber dynamics

NASA Astrophysics Data System (ADS)

Barthel, Thomas; De Bacco, Caterina; Franz, Silvio

2018-01-01

We introduce and apply an efficient method for the precise simulation of stochastic dynamical processes on locally treelike graphs. Networks with cycles are treated in the framework of the cavity method. Such models correspond, for example, to spin-glass systems, Boolean networks, neural networks, or other technological, biological, and social networks. Building upon ideas from quantum many-body theory, our approach is based on a matrix product approximation of the so-called edge messages—conditional probabilities of vertex variable trajectories. Computation costs and accuracy can be tuned by controlling the matrix dimensions of the matrix product edge messages (MPEM) in truncations. In contrast to Monte Carlo simulations, the algorithm has a better error scaling and works for both single instances as well as the thermodynamic limit. We employ it to examine prototypical nonequilibrium Glauber dynamics in the kinetic Ising model. Because of the absence of cancellation effects, observables with small expectation values can be evaluated accurately, allowing for the study of decay processes and temporal correlations.

Assessment of undiscovered oil and gas resources of the Ordovician Utica Shale of the Appalachian Basin Province, 2012

USGS Publications Warehouse

Kirschbaum, Mark A.; Schenk, Christopher J.; Cook, Troy A.; Ryder, Robert T.; Charpentier, Ronald R.; Klett, Timothy R.; Gaswirth, Stephanie B.; Tennyson, Marilyn E.; Whidden, Katherine J.

2012-01-01

The U.S. Geological Survey assessed unconventional oil and gas resources of the Upper Ordovician Utica Shale and adjacent units in the Appalachian Basin Province. The assessment covers parts of Maryland, New York, Ohio, Pennsylvania, Virginia, and West Virginia. The geologic concept is that black shale of the Utica Shale and adjacent units generated hydrocarbons from Type II organic material in areas that are thermally mature for oil and gas. The source rocks generated petroleum that migrated into adjacent units, but also retained significant hydrocarbons within the matrix and adsorbed to organic matter of the shale. These are potentially technically recoverable resources that can be exploited by using horizontal drilling combined with hydraulic fracturing techniques.

Development of Gis Tool for the Solution of Minimum Spanning Tree Problem using Prim's Algorithm

NASA Astrophysics Data System (ADS)

Dutta, S.; Patra, D.; Shankar, H.; Alok Verma, P.

2014-11-01

minimum spanning tree (MST) of a connected, undirected and weighted network is a tree of that network consisting of all its nodes and the sum of weights of all its edges is minimum among all such possible spanning trees of the same network. In this study, we have developed a new GIS tool using most commonly known rudimentary algorithm called Prim's algorithm to construct the minimum spanning tree of a connected, undirected and weighted road network. This algorithm is based on the weight (adjacency) matrix of a weighted network and helps to solve complex network MST problem easily, efficiently and effectively. The selection of the appropriate algorithm is very essential otherwise it will be very hard to get an optimal result. In case of Road Transportation Network, it is very essential to find the optimal results by considering all the necessary points based on cost factor (time or distance). This paper is based on solving the Minimum Spanning Tree (MST) problem of a road network by finding it's minimum span by considering all the important network junction point. GIS technology is usually used to solve the network related problems like the optimal path problem, travelling salesman problem, vehicle routing problems, location-allocation problems etc. Therefore, in this study we have developed a customized GIS tool using Python script in ArcGIS software for the solution of MST problem for a Road Transportation Network of Dehradun city by considering distance and time as the impedance (cost) factors. It has a number of advantages like the users do not need a greater knowledge of the subject as the tool is user-friendly and that allows to access information varied and adapted the needs of the users. This GIS tool for MST can be applied for a nationwide plan called Prime Minister Gram Sadak Yojana in India to provide optimal all weather road connectivity to unconnected villages (points). This tool is also useful for constructing highways or railways spanning several cities optimally or connecting all cities with minimum total road length.

A new estimation of equivalent matrix block sizes in fractured media with two-phase flow applications in dual porosity models

NASA Astrophysics Data System (ADS)

Jerbi, Chahir; Fourno, André; Noetinger, Benoit; Delay, Frederick

2017-05-01

Single and multiphase flows in fractured porous media at the scale of natural reservoirs are often handled by resorting to homogenized models that avoid the heavy computations associated with a complete discretization of both fractures and matrix blocks. For example, the two overlapping continua (fractures and matrix) of a dual porosity system are coupled by way of fluid flux exchanges that deeply condition flow at the large scale. This characteristic is a key to realistic flow simulations, especially for multiphase flow as capillary forces and contrasts of fluid mobility compete in the extraction of a fluid from a capacitive matrix then conveyed through the fractures. The exchange rate between fractures and matrix is conditioned by the so-called mean matrix block size which can be viewed as the size of a single matrix block neighboring a single fracture within a mesh of a dual porosity model. We propose a new evaluation of this matrix block size based on the analysis of discrete fracture networks. The fundaments rely upon establishing at the scale of a fractured block the equivalence between the actual fracture network and a Warren and Root network only made of three regularly spaced fracture families parallel to the facets of the fractured block. The resulting matrix block sizes are then compared via geometrical considerations and two-phase flow simulations to the few other available methods. It is shown that the new method is stable in the sense it provides accurate sizes irrespective of the type of fracture network investigated. The method also results in two-phase flow simulations from dual porosity models very close to that from references calculated in finely discretized networks. Finally, calculations of matrix block sizes by this new technique reveal very rapid, which opens the way to cumbersome applications such as preconditioning a dual porosity approach applied to regional fractured reservoirs.

Asymptotic stability of delay-difference system of hopfield neural networks via matrix inequalities and application.

PubMed

Ratchagit, Kreangkri

2007-10-01

In this paper, we derive a sufficient condition for asymptotic stability of the zero solution of delay-difference system of Hopfield neural networks in terms of certain matrix inequalities by using a discrete version of the Lyapunov second method. The result is applied to obtain new asymptotic stability condition for some class of delay-difference system such as delay-difference system of Hopfield neural networks with multiple delays in terms of certain matrix inequalities. Our results can be well suited for computational purposes.

Dispersion of cellulose nanofibers in biopolymer based nanocomposites

NASA Astrophysics Data System (ADS)

Wang, Bei

The focus of this work was to understand the fundamental dispersion mechanism of cellulose based nanofibers in bionanocomposites. The cellulose nanofibers were extracted from soybean pod and hemp fibers by chemo-mechanical treatments. These are bundles of cellulose nanofibers with a diameter ranging between 50 to 100 nm and lengths of thousands of nanometers which results in very high aspect ratio. In combination with a suitable matrix polymer, cellulose nanofiber networks show considerable potential as an effective reinforcement for high quality specialty applications of bio-based nanocomposites. Cellulose fibrils have a high density of --OH groups on the surface, which have a tendency to form hydrogen bonds with adjacent fibrils, reducing interaction with the surrounding matrix. The use of nanofibers has been mostly restricted to water soluble polymers. This thesis is focused on synthesizing the nanocomposite using a solid phase matrix polypropylene (PP) or polyethylene (PE) by hot compression and poly (vinyl alcohol) (PVA) in an aqueous phase by film casting. The mechanical properties of nanofiber reinforced PVA film demonstrated a 4-5 fold increase in tensile strength, as compared to the untreated fiber-blend-PVA film. It is necessary to reduce the entanglement of the fibrils and improve their dispersion in the matrix by surface modification of fibers without deteriorating their reinforcing capability. Inverse gas chromatography (IGC) was used to explore how various surface treatments would change the dispersion component of surface energy and acid-base character of cellulose nanofibers and the effect of the incorporation of these modified nanofibers into a biopolymer matrix on the properties of their nano-composites. Poly (lactic acid) (PLA) and polyhydroxybutyrate (PHB) based nanocomposites using cellulose nanofibers were prepared by extrusion, injection molding and hot compression. The IGC results indicated that styrene maleic anhydride coated and ethylene-acrylic acid coated fibers improved their potential to interact with both acidic and basic resins. From transmission electron micrograph, it was shown that the nanofibers were partially dispersed in the polymer matrix. The mechanical properties of the nanocomposites were lower than those predicted by theoretical calculations for both nanofiber reinforced biopolymers.

A quasi steady state method for solving transient Darcy flow in complex 3D fractured networks accounting for matrix to fracture flow

NASA Astrophysics Data System (ADS)

Nœtinger, B.

2015-02-01

Modeling natural Discrete Fracture Networks (DFN) receives more and more attention in applied geosciences, from oil and gas industry, to geothermal recovery and aquifer management. The fractures may be either natural, or artificial in case of well stimulation. Accounting for the flow inside the fracture network, and accounting for the transfers between the matrix and the fractures, with the same level of accuracy is an important issue for calibrating the well architecture and for setting up optimal resources recovery strategies. Recently, we proposed an original method allowing to model transient pressure diffusion in the fracture network only [1]. The matrix was assumed to be impervious. A systematic approximation scheme was built, allowing to model the initial DFN by a set of N unknowns located at each identified intersection between fractures. The higher N, the higher the accuracy of the model. The main assumption was using a quasi steady state hypothesis, that states that the characteristic diffusion time over one single fracture is negligible compared with the characteristic time of the macroscopic problem, e.g. change of boundary conditions. In that context, the lowest order approximation N = 1 has the form of solving a transient problem in a resistor/capacitor network, a so-called pipe network. Its topology is the same as the network of geometrical intersections between fractures. In this paper, we generalize this approach in order to account for fluxes from matrix to fractures. The quasi steady state hypothesis at the fracture level is still kept. Then, we show that in the case of well separated time scales between matrix and fractures, the preceding model needs only to be slightly modified in order to incorporate these fluxes. The additional knowledge of the so-called matrix to fracture transfer function allows to modify the mass matrix that becomes a time convolution operator. This is reminiscent of existing space averaged transient dual porosity models.

Multi Scale Modeling of Continuous Aramid Fiber Reinforced Polymer Matrix Composites Used in Ballistic Protection Applications

DTIC Science & Technology

2014-11-16

related to identification of the type and the extent of data generated at a finer length scale to the adjacent coarser length scale, as well as seamless ...data generated at a finer length scale to the adjacent coarser length scale, as well as seamless integration of different length scales into a unified...composite laminate consisting of 32 laminae and impacted (at a 0° obliquity angle and an incident velocity of 500 m/s) by a 0.30 caliber steel

Regenerating Articular Tissue by Converging Technologies

PubMed Central

Paoluzzi, Luca; Pieper, Jeroen; de Wijn, Joost R.; van Blitterswijk, Clemens A.

2008-01-01

Scaffolds for osteochondral tissue engineering should provide mechanical stability, while offering specific signals for chondral and bone regeneration with a completely interconnected porous network for cell migration, attachment, and proliferation. Composites of polymers and ceramics are often considered to satisfy these requirements. As such methods largely rely on interfacial bonding between the ceramic and polymer phase, they may often compromise the use of the interface as an instrument to direct cell fate. Alternatively, here, we have designed hybrid 3D scaffolds using a novel concept based on biomaterial assembly, thereby omitting the drawbacks of interfacial bonding. Rapid prototyped ceramic particles were integrated into the pores of polymeric 3D fiber-deposited (3DF) matrices and infused with demineralized bone matrix (DBM) to obtain constructs that display the mechanical robustness of ceramics and the flexibility of polymers, mimicking bone tissue properties. Ostechondral scaffolds were then fabricated by directly depositing a 3DF structure optimized for cartilage regeneration adjacent to the bone scaffold. Stem cell seeded scaffolds regenerated both cartilage and bone in vivo. PMID:18716660

Single-phase power distribution system power flow and fault analysis

NASA Technical Reports Server (NTRS)

Halpin, S. M.; Grigsby, L. L.

1992-01-01

Alternative methods for power flow and fault analysis of single-phase distribution systems are presented. The algorithms for both power flow and fault analysis utilize a generalized approach to network modeling. The generalized admittance matrix, formed using elements of linear graph theory, is an accurate network model for all possible single-phase network configurations. Unlike the standard nodal admittance matrix formulation algorithms, the generalized approach uses generalized component models for the transmission line and transformer. The standard assumption of a common node voltage reference point is not required to construct the generalized admittance matrix. Therefore, truly accurate simulation results can be obtained for networks that cannot be modeled using traditional techniques.

Graph regularized nonnegative matrix factorization for temporal link prediction in dynamic networks

NASA Astrophysics Data System (ADS)

Ma, Xiaoke; Sun, Penggang; Wang, Yu

2018-04-01

Many networks derived from society and nature are temporal and incomplete. The temporal link prediction problem in networks is to predict links at time T + 1 based on a given temporal network from time 1 to T, which is essential to important applications. The current algorithms either predict the temporal links by collapsing the dynamic networks or collapsing features derived from each network, which are criticized for ignoring the connection among slices. to overcome the issue, we propose a novel graph regularized nonnegative matrix factorization algorithm (GrNMF) for the temporal link prediction problem without collapsing the dynamic networks. To obtain the feature for each network from 1 to t, GrNMF factorizes the matrix associated with networks by setting the rest networks as regularization, which provides a better way to characterize the topological information of temporal links. Then, the GrNMF algorithm collapses the feature matrices to predict temporal links. Compared with state-of-the-art methods, the proposed algorithm exhibits significantly improved accuracy by avoiding the collapse of temporal networks. Experimental results of a number of artificial and real temporal networks illustrate that the proposed method is not only more accurate but also more robust than state-of-the-art approaches.

Field evaluation of porous asphalt pavement

DOT National Transportation Integrated Search

2004-05-01

This report summarizes the construction and early performance of a field trial of a Porous Friction Course (PFC) in Indiana. The PFC is compared to an adjacent section of Stone Matrix Asphalt (SMA) constructed at the same time using the same binder, ...

Metal/fiber laminate and fabrication using a porous metal/fiber preform

NASA Technical Reports Server (NTRS)

Hales, Stephen J. (Inventor); Alexa, Joel A. (Inventor); Jensen, Brian J. (Inventor); Cano, Roberto J. (Inventor); Weiser, Erik S. (Inventor)

2011-01-01

A metal/fiber laminate has a plurality of adjacent layers. Each layer is porous and includes an arrangement of fibers. At least one of the layers has its fibers coated with a metal. A polymer matrix permeates each such arrangement.

Metal/fiber laminate and fabrication using a porous metal/fiber preform

NASA Technical Reports Server (NTRS)

Hales, Stephen J. (Inventor); Alexa, Joel A. (Inventor); Jensen, Brian J. (Inventor); Cano, Roberto J. (Inventor); Weiser, Erik S. (Inventor)

2010-01-01

A metal/fiber laminate has a plurality of adjacent layers. Each layer is porous and includes an arrangement of fibers. At least one of the layers has its fibers coated with a metal. A polymer matrix permeates each such arrangement.

CUDA Enabled Graph Subset Examiner

DOE Office of Scientific and Technical Information (OSTI.GOV)

Johnston, Jeremy T.

2016-12-22

Finding Godsil-McKay switching sets in graphs is one way to demonstrate that a specific graph is not determined by its spectrum--the eigenvalues of its adjacency matrix. An important area of active research in pure mathematics is determining which graphs are determined by their spectra, i.e. when the spectrum of the adjacency matrix uniquely determines the underlying graph. We are interested in exploring the spectra of graphs in the Johnson scheme and specifically seek to determine which of these graphs are determined by their spectra. Given a graph G, a Godsil-McKay switching set is an induced subgraph H on 2k verticesmore » with the following properties: I) H is regular, ii) every vertex in G/H is adjacent to either 0, k, or 2k vertices of H, and iii) at least one vertex in G/H is adjacent to k vertices in H. The software package examines each subset of a user specified size to determine whether or not it satisfies those 3 conditions. The software makes use of the massive parallel processing power of CUDA enabled GPUs. It also exploits the vertex transitivity of graphs in the Johnson scheme by reasoning that if G has a Godsil-McKay switching set, then it has a switching set which includes vertex 1. While the code (in its current state) is tuned to this specific problem, the method of examining each induced subgraph of G can be easily re-written to check for any user specified conditions on the subgraphs and can therefore be used much more broadly.« less

Integrated Circuit For Simulation Of Neural Network

NASA Technical Reports Server (NTRS)

Thakoor, Anilkumar P.; Moopenn, Alexander W.; Khanna, Satish K.

1988-01-01

Ballast resistors deposited on top of circuit structure. Cascadable, programmable binary connection matrix fabricated in VLSI form as basic building block for assembly of like units into content-addressable electronic memory matrices operating somewhat like networks of neurons. Connections formed during storage of data, and data recalled from memory by prompting matrix with approximate or partly erroneous signals. Redundancy in pattern of connections causes matrix to respond with correct stored data.

Reconstruction of Complex Network based on the Noise via QR Decomposition and Compressed Sensing.

PubMed

Li, Lixiang; Xu, Dafei; Peng, Haipeng; Kurths, Jürgen; Yang, Yixian

2017-11-08

It is generally known that the states of network nodes are stable and have strong correlations in a linear network system. We find that without the control input, the method of compressed sensing can not succeed in reconstructing complex networks in which the states of nodes are generated through the linear network system. However, noise can drive the dynamics between nodes to break the stability of the system state. Therefore, a new method integrating QR decomposition and compressed sensing is proposed to solve the reconstruction problem of complex networks under the assistance of the input noise. The state matrix of the system is decomposed by QR decomposition. We construct the measurement matrix with the aid of Gaussian noise so that the sparse input matrix can be reconstructed by compressed sensing. We also discover that noise can build a bridge between the dynamics and the topological structure. Experiments are presented to show that the proposed method is more accurate and more efficient to reconstruct four model networks and six real networks by the comparisons between the proposed method and only compressed sensing. In addition, the proposed method can reconstruct not only the sparse complex networks, but also the dense complex networks.

Context-Sensitive Detection of Local Community Structure

DTIC Science & Technology

2011-04-01

characters in the Victor Hugo novel Les Miserables (lesmis).[77 vertices, 254 edges] [Knu93]. • The neural network of the nematode C. Elegans (c.elegans...adjectives and nouns in the Novel David Cop- perfield by Charles Dickens.[112 vertices, 425 edges] [New06]. • Les Miserables . Co-appearance network of...exponential distribution. The degree distributions of the Network Science, Les Miserables , and Word Adjacencies networks display a similar heavy tail. By

Carbon black networking in elastomers monitored by simultaneous rheological and dielectric investigations.

PubMed

Steinhauser, Dagmar; Möwes, Markus; Klüppel, Manfred

2016-12-14

The rheo-dielectric response of carbon black filled elastomer melts is investigated by dielectric relaxation spectroscopy in the frequency range from 0.1 Hz up to 10 MHz during oszillatory shearing in a plate-plate rheometer. Various concentrations and types of carbon blacks dispersed in a non-crosslinked EPDM melt are considered. It is demonstrated that during heat treatment at low strain amplitude a pronounced flocculation of filler particles takes place leading to a successive increase of the shear modulus and conductivity. Followed up by a strain sweep, the filler network breaks up and both quantities decrease simultaneously with increasing strain amplitude. Two relaxation times, obtained from a Cole-Cole fit of the dielectric spectra, are identified, which both decrease strongly with increasing flocculation time. This behaviour is analyzed in the frame of fractal network models, describing the effect of structural disorder of the conducting carbon black network on the diffusive charge transport. Significant deviations from the predictions of percolation theory are observed, which are traced back to a superimposed cluster-cluster aggregation process (CCA). During flocculation, a universal scaling behaviour holds between the conductivity and the corresponding high frequency relaxation time, which fits all the measured data. The scaling exponent agrees fairly well with the prediction obtained from CCA. It is demonstrated that the underlying basic mechanism is a change of the correlation length of the filler network, i.e. the size of the fractal heterogeneities. This decreases during flocculation due to the formation of additional conductive paths, making the system more homogeneous. An addition less pronounced effect is found from nanoscopic gaps between adjacent filler particles, which decrease during flocculation. The same universal scaling behaviour, as obtained for flocculation, is found for temperature-dependent dielectric measurements of the cured crosslinked systems, which are heated from room temperature up to 200 °C. Thereby, the conductivity decreases significantly and the relaxation time increases, indicating that the filler network breaks up randomly due to the thermal expansion of the rubber matrix.

Carbon black networking in elastomers monitored by simultaneous rheological and dielectric investigations

NASA Astrophysics Data System (ADS)

Steinhauser, Dagmar; Möwes, Markus; Klüppel, Manfred

2016-12-01

The rheo-dielectric response of carbon black filled elastomer melts is investigated by dielectric relaxation spectroscopy in the frequency range from 0.1 Hz up to 10 MHz during oszillatory shearing in a plate-plate rheometer. Various concentrations and types of carbon blacks dispersed in a non-crosslinked EPDM melt are considered. It is demonstrated that during heat treatment at low strain amplitude a pronounced flocculation of filler particles takes place leading to a successive increase of the shear modulus and conductivity. Followed up by a strain sweep, the filler network breaks up and both quantities decrease simultaneously with increasing strain amplitude. Two relaxation times, obtained from a Cole-Cole fit of the dielectric spectra, are identified, which both decrease strongly with increasing flocculation time. This behaviour is analyzed in the frame of fractal network models, describing the effect of structural disorder of the conducting carbon black network on the diffusive charge transport. Significant deviations from the predictions of percolation theory are observed, which are traced back to a superimposed cluster-cluster aggregation process (CCA). During flocculation, a universal scaling behaviour holds between the conductivity and the corresponding high frequency relaxation time, which fits all the measured data. The scaling exponent agrees fairly well with the prediction obtained from CCA. It is demonstrated that the underlying basic mechanism is a change of the correlation length of the filler network, i.e. the size of the fractal heterogeneities. This decreases during flocculation due to the formation of additional conductive paths, making the system more homogeneous. An addition less pronounced effect is found from nanoscopic gaps between adjacent filler particles, which decrease during flocculation. The same universal scaling behaviour, as obtained for flocculation, is found for temperature-dependent dielectric measurements of the cured crosslinked systems, which are heated from room temperature up to 200 °C. Thereby, the conductivity decreases significantly and the relaxation time increases, indicating that the filler network breaks up randomly due to the thermal expansion of the rubber matrix.

Dynamic characterisation of the specific surface area for fracture networks

NASA Astrophysics Data System (ADS)

Cvetkovic, V.

2017-12-01

One important application of chemical transport is geological disposal of high-level nuclear waste for which crystalline rock is a prime candidate for instance in Scandinavia. Interconnected heterogeneous fractures of sparsely fractured rock such as granite, act as conduits for transport of dissolved tracers. Fluid flow is known to be highly channelized in such rocks. Channels imply narrow flow paths, adjacent to essentially stagnant water in the fracture and/or the rock matrix. Tracers are transported along channelised flow paths and retained by minerals and/or stagnant water, depending on their sorption properties; this mechanism is critical for rocks to act as a barrier and ultimately provide safety for a geological repository. The sorbing tracers are retained by diffusion and sorption on mineral surfaces, whereas non-sorbing tracers can be retained only by diffusion into stagnant water of fractures. The retention and transport properties of a sparsely fractured rock will primarily depend on the specific surface area (SSA) of the fracture network which is determined by the heterogeneous structure and flow. The main challenge when characterising SSA on the field-scale is its dependence on the flow dynamics. We first define SSA as a physical quantity and clarify its importance for chemical transport. A methodology for dynamic characterisation of SSA in fracture networks is proposed that relies on three sets of data: i) Flow rate data as obtained by a flow logging procedure; ii) transmissivity data as obtained by pumping tests; iii) fracture network data as obtained from outcrop and geophysical observations. The proposed methodology utilises these data directly as well as indirectly through flow and particle tracking simulations in three-dimensional discrete fracture networks. The methodology is exemplified using specific data from the Swedish site Laxemar. The potential impact of uncertainties is of particular significance and is illustrated for radionuclide attenuation. Effects of internal fracture heterogeneity vs fracture network heterogeneity, and of rock deformation, on the statistical properties of SSA are briefly discussed.

Spectral properties of Google matrix of Wikipedia and other networks

NASA Astrophysics Data System (ADS)

Ermann, Leonardo; Frahm, Klaus M.; Shepelyansky, Dima L.

2013-05-01

We study the properties of eigenvalues and eigenvectors of the Google matrix of the Wikipedia articles hyperlink network and other real networks. With the help of the Arnoldi method, we analyze the distribution of eigenvalues in the complex plane and show that eigenstates with significant eigenvalue modulus are located on well defined network communities. We also show that the correlator between PageRank and CheiRank vectors distinguishes different organizations of information flow on BBC and Le Monde web sites.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mason, J.

CCHDT constructs and classifies various arrangements of hard disks of a single radius places on the unit square with periodic boundary conditions. Specifially, a given configuration is evolved to the nearest critical point on a smoothed hard disk energy fuction, and is classified by the adjacency matrix of the canonically labelled contact graph.

Analyzing coastal turbidity under complex terrestrial loads characterized by a 'stress connectivity matrix' with an atmosphere-watershed-coastal ocean coupled model

NASA Astrophysics Data System (ADS)

Yamamoto, Takahiro; Nadaoka, Kazuo

2018-04-01

Atmospheric, watershed and coastal ocean models were integrated to provide a holistic analysis approach for coastal ocean simulation. The coupled model was applied to coastal ocean in the Philippines where terrestrial sediment loads provided from several adjacent watersheds play a major role in influencing coastal turbidity and are partly responsible for the coastal ecosystem degradation. The coupled model was validated using weather and hydrologic measurement to examine its potential applicability. The results revealed that the coastal water quality may be governed by the loads not only from the adjacent watershed but also from the distant watershed via coastal currents. This important feature of the multiple linkages can be quantitatively characterized by a "stress connectivity matrix", which indicates the complex underlying structure of environmental stresses in coastal ocean. The multiple stress connectivity concept shows the potential advantage of the integrated modelling approach for coastal ocean assessment, which may also serve for compensating the lack of measured data especially in tropical basins.

Improved passive optical network architectures to support local area network emulation and protection

NASA Astrophysics Data System (ADS)

Wong, Elaine; Nadarajah, Nishaanthan; Chae, Chang-Joon; Nirmalathas, Ampalavanapillai; Attygalle, Sanjeewa M.

2006-01-01

We describe two optical layer schemes which simultaneously facilitate local area network emulation and automatic protection switching against distribution fiber breaks in passive optical networks. One scheme employs a narrowband fiber Bragg grating placed close to the star coupler in the feeder fiber of the passive optical network, while the other uses an additional short length distribution fiber from the star coupler to each customer for the redirection of the customer traffic. Both schemes use RF subcarrier multiplexed transmission for intercommunication between customers in conjunction with upstream access to the central office at baseband. Failure detection and automatic protection switching are performed independently by each optical network unit that is located at the customer premises in a distributed manner. The restoration of traffic transported between the central office and an optical network unit in the event of the distribution fiber break is performed by interconnecting adjacent optical network units and carrying out signal transmissions via an independent but interconnected optical network unit. Such a protection mechanism enables multiple adjacent optical network units to be simultaneously protected by a single optical network unit utilizing its maximum available bandwidth. We experimentally verify the feasibility of both schemes with 1.25 Gb/s upstream baseband transmission to the central office and 155 Mb/s local area network data transmission on a RF subcarrier frequency. The experimental results obtained from both schemes are compared, and the power budgets are calculated to analyze the scalability of each scheme.

Aircraft-Based Satellite Navigation Augmentation to Enable Automated Landing and Movement on the Airport Surface

NASA Astrophysics Data System (ADS)

Obeidat, Qasem Turki

A brain-computer interface (BCI) enables a paralyzed user to interact with an external device through brain signals. A BCI measures identifies patterns within these measured signals, translating such patterns into commands. The P300 is a pattern of a scalp potentials elicited by a luminance increment of an attended target rather than a non-target character of an alphanumeric matrix. The Row-Column Paradigm (RCP) can utilize responses to series of illuminations of matrix target and non-target characters to spell out alphanumeric strings of P300-eliciting target characters, yet this popular RCP speller faces three challenges. Theadjacent problem concerns the proximity of neighboring characters, the crowding problem concerns their number. Both adjacent and crowding problems concern how these factors impede BCI performance. The fatigue problem concerns how RCP use is tiring. This dissertation addressed these challenges for both desktop and mobile platforms. A new P300 speller interface, the Zigzag Paradigm (ZP), reduced the adjacent problem by increasing the distance between adjacent characters, as well as the crowding problem, by reducing the number neighboring characters. In desktop study, the classification accuracy was significantly improved 91% with the ZP VS 80.6% with the RCP. Since the ZP is not suitable for mobile P300 spellers with a small screen size, a new P300 speller interface was developed in this study, the Edges Paradigm (EP). The EP reduced the adjacent and crowding problems by adding flashing squares located upon the outer edges of the character matrix in the EP. The classification accuracy of the EP (i.e., 93.3%) was significantly higher than the RCP (i.e., 82.1%). We further compared three speller paradigms (i.e., RCP, ZP, and EP), and the result indicated that the EP produced the highest accuracy and caused less fatigue. Later, the EP is implemented in a simulator of a Samsung galaxy smart phone on the Microsoft Surface Pro 2. The mobile EP was compared with the RCP under the mobility situation when a user is moving on a wheelchair. The results showed that the EP significantly improved the online classification accuracy and user experience over the RCP.

Correlation between centrality metrics and their application to the opinion model

NASA Astrophysics Data System (ADS)

Li, Cong; Li, Qian; Van Mieghem, Piet; Stanley, H. Eugene; Wang, Huijuan

2015-03-01

In recent decades, a number of centrality metrics describing network properties of nodes have been proposed to rank the importance of nodes. In order to understand the correlations between centrality metrics and to approximate a high-complexity centrality metric by a strongly correlated low-complexity metric, we first study the correlation between centrality metrics in terms of their Pearson correlation coefficient and their similarity in ranking of nodes. In addition to considering the widely used centrality metrics, we introduce a new centrality measure, the degree mass. The mth-order degree mass of a node is the sum of the weighted degree of the node and its neighbors no further than m hops away. We find that the betweenness, the closeness, and the components of the principal eigenvector of the adjacency matrix are strongly correlated with the degree, the 1st-order degree mass and the 2nd-order degree mass, respectively, in both network models and real-world networks. We then theoretically prove that the Pearson correlation coefficient between the principal eigenvector and the 2nd-order degree mass is larger than that between the principal eigenvector and a lower order degree mass. Finally, we investigate the effect of the inflexible contrarians selected based on different centrality metrics in helping one opinion to compete with another in the inflexible contrarian opinion (ICO) model. Interestingly, we find that selecting the inflexible contrarians based on the leverage, the betweenness, or the degree is more effective in opinion-competition than using other centrality metrics in all types of networks. This observation is supported by our previous observations, i.e., that there is a strong linear correlation between the degree and the betweenness, as well as a high centrality similarity between the leverage and the degree.

Mapping the neuropsychological profile of temporal lobe epilepsy using cognitive network topology and graph theory.

PubMed

Kellermann, Tanja S; Bonilha, Leonardo; Eskandari, Ramin; Garcia-Ramos, Camille; Lin, Jack J; Hermann, Bruce P

2016-10-01

Normal cognitive function is defined by harmonious interaction among multiple neuropsychological domains. Epilepsy has a disruptive effect on cognition, but how diverse cognitive abilities differentially interact with one another compared with healthy controls (HC) is unclear. This study used graph theory to analyze the community structure of cognitive networks in adults with temporal lobe epilepsy (TLE) compared with that in HC. Neuropsychological assessment was performed in 100 patients with TLE and 82 HC. For each group, an adjacency matrix was constructed representing pair-wise correlation coefficients between raw scores obtained in each possible test combination. For each cognitive network, each node corresponded to a cognitive test; each link corresponded to the correlation coefficient between tests. Global network structure, community structure, and node-wise graph theory properties were qualitatively assessed. The community structure in patients with TLE was composed of fewer, larger, more mixed modules, characterizing three main modules representing close relationships between the following: 1) aspects of executive function (EF), verbal and visual memory, 2) speed and fluency, and 3) speed, EF, perception, language, intelligence, and nonverbal memory. Conversely, controls exhibited a relative division between cognitive functions, segregating into more numerous, smaller modules consisting of the following: 1) verbal memory, 2) language, perception, and intelligence, 3) speed and fluency, and 4) visual memory and EF. Overall node-wise clustering coefficient and efficiency were increased in TLE. Adults with TLE demonstrate a less clear and poorly structured segregation between multiple cognitive domains. This panorama suggests a higher degree of interdependency across multiple cognitive domains in TLE, possibly indicating compensatory mechanisms to overcome functional impairments. Copyright © 2016 Elsevier Inc. All rights reserved.

Integrated Analysis of Long Noncoding RNA and mRNA Expression Profile in Advanced Laryngeal Squamous Cell Carcinoma.

PubMed

Feng, Ling; Wang, Ru; Lian, Meng; Ma, Hongzhi; He, Ning; Liu, Honggang; Wang, Haizhou; Fang, Jugao

2016-01-01

Long non-coding RNA (lncRNA) plays an important role in tumorigenesis. However, the expression pattern and function of lncRNAs in laryngeal squamous cell carcinoma (LSCC) are still unclear. To investigate the aberrantly expressed lncRNAs and mRNAs in advanced LSCC, we screened lncRNA and mRNA expression profiles in 9 pairs of primary Stage IVA LSCC tissues and adjacent non-neoplastic tissues by lncRNA and mRNA integrated microarrays. Gene Ontology and pathway analysis were performed to find out the significant function and pathway of the differentially expressed mRNAs, gene-gene functional interaction network and ceRNA network were constructed to select core mRNAs, and lncRNA-mRNA expression correlation network was built to identify the interactions between lncRNA and mRNA. qRT-PCR was performed to further validate the expressions of selected lncRNAs and mRNAs in advanced LSCC. We found 1459 differentially expressed lncRNAs and 2381 differentially expressed mRNAs, including 846 up-regulated lncRNAs and 613 down-regulated lncRNAs, 1542 up-regulated mRNAs and 839 down-regulated mRNAs. The mRNAs ITGB1, HIF1A, and DDIT4 were selected as core mRNAs, which are mainly involved in biological processes, such as matrix organization, cell cycle, adhesion, and metabolic pathway. LncRNA-mRNA expression correlation network showed LncRNA NR_027340, MIR31HG were positively correlated with ITGB1, HIF1A respectively. LncRNA SOX2-OT was negatively correlated with DDIT4. qRT-PCR further validated the expression of these lncRNAs and mRNAs. The work provides convincing evidence that the identified lncRNAs and mRNAs are potential biomarkers in advanced LSCC for further future studies.

Google matrix of Twitter

NASA Astrophysics Data System (ADS)

Frahm, K. M.; Shepelyansky, D. L.

2012-10-01

We construct the Google matrix of the entire Twitter network, dated by July 2009, and analyze its spectrum and eigenstate properties including the PageRank and CheiRank vectors and 2DRanking of all nodes. Our studies show much stronger inter-connectivity between top PageRank nodes for the Twitter network compared to the networks of Wikipedia and British Universities studied previously. Our analysis allows to locate the top Twitter users which control the information flow on the network. We argue that this small fraction of the whole number of users, which can be viewed as the social network elite, plays the dominant role in the process of opinion formation on the network.

Determining entire mean first-passage time for Cayley networks

NASA Astrophysics Data System (ADS)

Wang, Xiaoqian; Dai, Meifeng; Chen, Yufei; Zong, Yue; Sun, Yu; Su, Weiyi

In this paper, we consider the entire mean first-passage time (EMFPT) with random walks for Cayley networks. We use Laplacian spectra to calculate the EMFPT. Firstly, we calculate the constant term and monomial coefficient of characteristic polynomial. By using the Vieta theorem, we then obtain the sum of reciprocals of all nonzero eigenvalues of Laplacian matrix. Finally, we obtain the scaling of the EMFPT for Cayley networks by using the relationship between the sum of reciprocals of all nonzero eigenvalues of Laplacian matrix and the EMFPT. We expect that our method can be adapted to other types of self-similar networks, such as vicsek networks, polymer networks.

Enhanced Retention of Chemotactic Bacteria in a Pore Network with Residual NAPL Contamination

NASA Astrophysics Data System (ADS)

Ford, R.; Wang, X.

2013-12-01

Nonaqueous phase liquid (NAPL) contaminants are difficult to eliminate from natural aquifers due, in part, to the heterogeneous structure of the soil matrix. Residual NAPL ganglia remain trapped in regions where the hydraulic conductivity is relatively low. Bioremediation processes depend on adequate mixing of microbial populations and the groundwater contaminants that they degrade. The ability of bacteria to sense a chemical gradient and swim preferentially toward locations of higher concentration, known as chemotaxis, can enhance the mixing of bacteria with contaminant sources that may not be readily accessible by advection and dispersion alone. The impact of chemotaxis on bacterial abundance within a low conductivity NAPL-contaminated region of a well-characterized porous matrix was investigated. A microfluidic device was designed to mimic heterogeneous features of a contaminated groundwater system. NAPL ganglia (toluene) were trapped within a fine pore network, and bacteria were injected into the system through a highly conductive adjacent channel. Chemotactic bacteria (P. putida F1) migrated preferentially towards and accumulated in the vicinity of NAPL contaminant sources. The accumulation of chemotactic bacteria was 15% greater in comparison to a nonchemotactic mutant (P. putida F1 CheA). Bacteria in the microfluidic device were subjected to different flow velocities from 0.25 to 5 m/d encompassing the range of typical groundwater flow rates. Chemotactic bacteria exhibited greater accumulation near the intersection between the macrochannel and the porous network at a flow velocity of 0.5 m/d than both the nonchemotactic mutant control and the chemotactic bacteria at a higher flow velocity of 5 m/d. Breakthrough curves observed at the outlet provided indirect evidence that chemotactic bacteria were retained within the contaminated low permeable region for a longer time than the nonchemotactic bacteria at a flow velocity of 0.25 m/d. This retention was diminished at a higher flow velocity of 5 m/d. Numerical solutions of the governing equations for bacterial transport yielded outcomes that were consistent with the experimental results, and statistical analysis also supported the experimental comparisons. The chemotactic response aided efficient delivery of bacteria to NAPL contaminant sources within the low conductivity pore network. Because toluene is degraded by P. putida F1, the greater accumulation of chemotactic bacteria around the NAPL sources is also expected to increase contaminant consumption and improve the efficiency of bioremediation.

Scale-Dependent Fracture-Matrix Interactions And Their Impact on Radionuclide Transport - Final Report

DOE Office of Scientific and Technical Information (OSTI.GOV)

Detwiler, Russell

Matrix diffusion and adsorption within a rock matrix are widely regarded as important mechanisms for retarding the transport of radionuclides and other solutes in fractured rock (e.g., Neretnieks, 1980; Tang et al., 1981; Maloszewski and Zuber, 1985; Novakowski and Lapcevic, 1994; Jardine et al., 1999; Zhou and Xie, 2003; Reimus et al., 2003a,b). When remediation options are being evaluated for old sources of contamination, where a large fraction of contaminants reside within the rock matrix, slow diffusion out of the matrix greatly increases the difficulty and timeframe of remediation. Estimating the rates of solute exchange between fractures and the adjacentmore » rock matrix is a critical factor in quantifying immobilization and/or remobilization of DOE-relevant contaminants within the subsurface. In principle, the most rigorous approach to modeling solute transport with fracture-matrix interaction would be based on local-scale coupled advection-diffusion/dispersion equations for the rock matrix and in discrete fractures that comprise the fracture network (Discrete Fracture Network and Matrix approach, hereinafter referred to as DFNM approach), fully resolving aperture variability in fractures and matrix property heterogeneity. However, such approaches are computationally demanding, and thus, many predictive models rely upon simplified models. These models typically idealize fracture rock masses as a single fracture or system of parallel fractures interacting with slabs of porous matrix or as a mobile-immobile or multi-rate mass transfer system. These idealizations provide tractable approaches for interpreting tracer tests and predicting contaminant mobility, but rely upon a fitted effective matrix diffusivity or mass-transfer coefficients. However, because these fitted parameters are based upon simplified conceptual models, their effectiveness at predicting long-term transport processes remains uncertain. Evidence of scale dependence of effective matrix diffusion coefficients obtained from tracer tests highlights this point and suggests that the underlying mechanisms and relationship between rock and fracture properties are not fully understood in large complex fracture networks. In this project, we developed a high-resolution DFN model of solute transport in fracture networks to explore and quantify the mechanisms that control transport in complex fracture networks and how these may give rise to observed scale-dependent matrix diffusion coefficients. Results demonstrate that small scale heterogeneity in the flow field caused by local aperture variability within individual fractures can lead to long-tailed breakthrough curves indicative of matrix diffusion, even in the absence of interactions with the fracture matrix. Furthermore, the temporal and spatial scale dependence of these processes highlights the inability of short-term tracer tests to estimate transport parameters that will control long-term fate and transport of contaminants in fractured aquifers.« less

Spatial organization of cellulose microfibrils and matrix polysaccharides in primary plant cell walls as imaged by multichannel atomic force microscopy.

PubMed

Zhang, Tian; Zheng, Yunzhen; Cosgrove, Daniel J

2016-01-01

We used atomic force microscopy (AFM), complemented with electron microscopy, to characterize the nanoscale and mesoscale structure of the outer (periclinal) cell wall of onion scale epidermis - a model system for relating wall structure to cell wall mechanics. The epidermal wall contains ~100 lamellae, each ~40 nm thick, containing 3.5-nm wide cellulose microfibrils oriented in a common direction within a lamella but varying by ~30 to 90° between adjacent lamellae. The wall thus has a crossed polylamellate, not helicoidal, wall structure. Montages of high-resolution AFM images of the newly deposited wall surface showed that single microfibrils merge into and out of short regions of microfibril bundles, thereby forming a reticulated network. Microfibril direction within a lamella did not change gradually or abruptly across the whole face of the cell, indicating continuity of the lamella across the outer wall. A layer of pectin at the wall surface obscured the underlying cellulose microfibrils when imaged by FESEM, but not by AFM. The AFM thus preferentially detects cellulose microfibrils by probing through the soft matrix in these hydrated walls. AFM-based nanomechanical maps revealed significant heterogeneity in cell wall stiffness and adhesiveness at the nm scale. By color coding and merging these maps, the spatial distribution of soft and rigid matrix polymers could be visualized in the context of the stiffer microfibrils. Without chemical extraction and dehydration, our results provide multiscale structural details of the primary cell wall in its near-native state, with implications for microfibrils motions in different lamellae during uniaxial and biaxial extensions. © 2015 The Authors The Plant Journal © 2015 John Wiley & Sons Ltd.

R-Matrix Analysis of Structures in Economic Indices: from Nuclear Reactions to High-Frequency Trading

NASA Astrophysics Data System (ADS)

Firk, Frank W. K.

2014-03-01

It is shown that the R-matrix theory of nuclear reactions is a viable mathematical theory for the description of the fine, intermediate and gross structure observed in the time-dependence of economic indices in general, and the daily Dow Jones Industrial Average in particular. A Lorentzian approximation to R-matrix theory is used to analyze the complex structures observed in the Dow Jones Industrial Average on a typical trading day. Resonant structures in excited nuclei are characterized by the values of their fundamental strength function, (average total width of the states)/(average spacing between adjacent states). Here, values of the ratios (average lifetime of individual states of a given component of the daily Dow Jones Industrial Average)/(average interval between the adjacent states) are determined. The ratios for the observed fine and intermediate structure of the index are found to be essentially constant throughout the trading day. These quantitative findings are characteristic of the highly statistical nature of many-body, strongly interacting systems, typified by daily trading. It is therefore proposed that the values of these ratios, determined in the first hour-or-so of trading, be used to provide valuable information concerning the likely performance of the fine and intermediate components of the index for the remainder of the trading day.

Analysis of Delamination Growth from Matrix Cracks in Laminates Subjected to Bending Loads

NASA Technical Reports Server (NTRS)

Murri, G. B.; Guynn, E. G.

1986-01-01

A major source of delamination damage in laminated composite materials is from low-velocity impact. In thin composite laminates under point loads, matrix cracks develop first in the plies, and delaminations then grow from these cracks at the ply interfaces. The purpose of this study was to quantify the combined effects of bending and transverse shear loads on delamination initiation from matrix cracks. Graphite-epoxy laminates with 90 deg. plies on the outside were used to provide a two-dimensional simulation of the damage due to low-velocity impact. Three plate bending problems were considered: a 4-point bending, 3-point bending, and an end-clamped center-loaded plate. Under bending, a matrix crack will form on the tension side of the laminate, through the outer 90 deg. plies and parallel to the fibers. Delaminations will then grow in the interface between the cracked 90 deg. ply and the next adjacent ply. Laminate plate theory was used to derive simple equations relating the total strain energy release rate, G, associated with the delamination growth from a 90 deg. ply crack to the applied bending load and laminate stiffness properties. Three different lay-ups were tested and results compared. Test results verified that the delamination always formed at the interface between the cracked 90 deg. ply and the next adjacent ply. Calculated values for total G sub c from the analysis showed good agreement for all configurations. The analysis was able to predict the delamination onset load for the cases considered. The result indicated that the opening mode component (Mode I) for delamination growth from a matrix crack may be much larger than the component due to interlaminar shear (Mode II).

Corrosion free phosphoric acid fuel cell

DOEpatents

Wright, Maynard K.

1990-01-01

A phosphoric acid fuel cell with an electrolyte fuel system which supplies electrolyte via a wick disposed adjacent a cathode to an absorbent matrix which transports the electrolyte to portions of the cathode and an anode which overlaps the cathode on all sides to prevent corrosion within the cell.

Dense fibrillar collagen is a potent inducer of invadopodia via a specific signaling network

PubMed Central

Swatkoski, Stephen; Matsumoto, Kazue; Campbell, Catherine B.; Petrie, Ryan J.; Dimitriadis, Emilios K.; Li, Xin; Mueller, Susette C.; Bugge, Thomas H.; Gucek, Marjan

2015-01-01

Cell interactions with the extracellular matrix (ECM) can regulate multiple cellular activities and the matrix itself in dynamic, bidirectional processes. One such process is local proteolytic modification of the ECM. Invadopodia of tumor cells are actin-rich proteolytic protrusions that locally degrade matrix molecules and mediate invasion. We report that a novel high-density fibrillar collagen (HDFC) matrix is a potent inducer of invadopodia, both in carcinoma cell lines and in primary human fibroblasts. In carcinoma cells, HDFC matrix induced formation of invadopodia via a specific integrin signaling pathway that did not require growth factors or even altered gene and protein expression. In contrast, phosphoproteomics identified major changes in a complex phosphosignaling network with kindlin2 serine phosphorylation as a key regulatory element. This kindlin2-dependent signal transduction network was required for efficient induction of invadopodia on dense fibrillar collagen and for local degradation of collagen. This novel phosphosignaling mechanism regulates cell surface invadopodia via kindlin2 for local proteolytic remodeling of the ECM. PMID:25646088

The impact of different aperture distribution models and critical stress criteria on equivalent permeability in fractured rocks

NASA Astrophysics Data System (ADS)

Bisdom, Kevin; Bertotti, Giovanni; Nick, Hamidreza M.

2016-05-01

Predicting equivalent permeability in fractured reservoirs requires an understanding of the fracture network geometry and apertures. There are different methods for defining aperture, based on outcrop observations (power law scaling), fundamental mechanics (sublinear length-aperture scaling), and experiments (Barton-Bandis conductive shearing). Each method predicts heterogeneous apertures, even along single fractures (i.e., intrafracture variations), but most fractured reservoir models imply constant apertures for single fractures. We compare the relative differences in aperture and permeability predicted by three aperture methods, where permeability is modeled in explicit fracture networks with coupled fracture-matrix flow. Aperture varies along single fractures, and geomechanical relations are used to identify which fractures are critically stressed. The aperture models are applied to real-world large-scale fracture networks. (Sub)linear length scaling predicts the largest average aperture and equivalent permeability. Barton-Bandis aperture is smaller, predicting on average a sixfold increase compared to matrix permeability. Application of critical stress criteria results in a decrease in the fraction of open fractures. For the applied stress conditions, Coulomb predicts that 50% of the network is critically stressed, compared to 80% for Barton-Bandis peak shear. The impact of the fracture network on equivalent permeability depends on the matrix hydraulic properties, as in a low-permeable matrix, intrafracture connectivity, i.e., the opening along a single fracture, controls equivalent permeability, whereas for a more permeable matrix, absolute apertures have a larger impact. Quantification of fracture flow regimes using only the ratio of fracture versus matrix permeability is insufficient, as these regimes also depend on aperture variations within fractures.

Linear analysis near a steady-state of biochemical networks: control analysis, correlation metrics and circuit theory.

PubMed

Heuett, William J; Beard, Daniel A; Qian, Hong

2008-05-15

Several approaches, including metabolic control analysis (MCA), flux balance analysis (FBA), correlation metric construction (CMC), and biochemical circuit theory (BCT), have been developed for the quantitative analysis of complex biochemical networks. Here, we present a comprehensive theory of linear analysis for nonequilibrium steady-state (NESS) biochemical reaction networks that unites these disparate approaches in a common mathematical framework and thermodynamic basis. In this theory a number of relationships between key matrices are introduced: the matrix A obtained in the standard, linear-dynamic-stability analysis of the steady-state can be decomposed as A = SRT where R and S are directly related to the elasticity-coefficient matrix for the fluxes and chemical potentials in MCA, respectively; the control-coefficients for the fluxes and chemical potentials can be written in terms of RTBS and STBS respectively where matrix B is the inverse of A; the matrix S is precisely the stoichiometric matrix in FBA; and the matrix eAt plays a central role in CMC. One key finding that emerges from this analysis is that the well-known summation theorems in MCA take different forms depending on whether metabolic steady-state is maintained by flux injection or concentration clamping. We demonstrate that if rate-limiting steps exist in a biochemical pathway, they are the steps with smallest biochemical conductances and largest flux control-coefficients. We hypothesize that biochemical networks for cellular signaling have a different strategy for minimizing energy waste and being efficient than do biochemical networks for biosynthesis. We also discuss the intimate relationship between MCA and biochemical systems analysis (BSA).

Concentric network symmetry grasps authors' styles in word adjacency networks

NASA Astrophysics Data System (ADS)

Amancio, Diego R.; Silva, Filipi N.; Costa, Luciano da F.

2015-06-01

Several characteristics of written texts have been inferred from statistical analysis derived from networked models. Even though many network measurements have been adapted to study textual properties at several levels of complexity, some textual aspects have been disregarded. In this paper, we study the symmetry of word adjacency networks, a well-known representation of text as a graph. A statistical analysis of the symmetry distribution performed in several novels showed that most of the words do not display symmetric patterns of connectivity. More specifically, the merged symmetry displayed a distribution similar to the ubiquitous power-law distribution. Our experiments also revealed that the studied metrics do not correlate with other traditional network measurements, such as the degree or the betweenness centrality. The discriminability power of the symmetry measurements was verified in the authorship attribution task. Interestingly, we found that specific authors prefer particular types of symmetric motifs. As a consequence, the authorship of books could be accurately identified in 82.5% of the cases, in a dataset comprising books written by 8 authors. Because the proposed measurements for text analysis are complementary to the traditional approach, they can be used to improve the characterization of text networks, which might be useful for applications based on stylistic classification.

Fabric defect detection based on visual saliency using deep feature and low-rank recovery

NASA Astrophysics Data System (ADS)

Liu, Zhoufeng; Wang, Baorui; Li, Chunlei; Li, Bicao; Dong, Yan

2018-04-01

Fabric defect detection plays an important role in improving the quality of fabric product. In this paper, a novel fabric defect detection method based on visual saliency using deep feature and low-rank recovery was proposed. First, unsupervised training is carried out by the initial network parameters based on MNIST large datasets. The supervised fine-tuning of fabric image library based on Convolutional Neural Networks (CNNs) is implemented, and then more accurate deep neural network model is generated. Second, the fabric images are uniformly divided into the image block with the same size, then we extract their multi-layer deep features using the trained deep network. Thereafter, all the extracted features are concentrated into a feature matrix. Third, low-rank matrix recovery is adopted to divide the feature matrix into the low-rank matrix which indicates the background and the sparse matrix which indicates the salient defect. In the end, the iterative optimal threshold segmentation algorithm is utilized to segment the saliency maps generated by the sparse matrix to locate the fabric defect area. Experimental results demonstrate that the feature extracted by CNN is more suitable for characterizing the fabric texture than the traditional LBP, HOG and other hand-crafted features extraction method, and the proposed method can accurately detect the defect regions of various fabric defects, even for the image with complex texture.

Indicating disturbance content and context for preserved areas

Treesearch

N. Zaccarelli; K.H. Riitters; I. Petrosillo; G. Zurlini

2007-01-01

An accepted goal of conservation is to build a conservation network that is resilient to environmental change. The conceptual patch-corridor-matrix model views individual conservation areas as connected components of a regional network capable of sustaining metapopulations and biodiversity, and assessment of contextual conditions in the matrix surrounding conservation...

Effect of chain rigidity on network architecture and deformation behavior of glassy polymer networks

NASA Astrophysics Data System (ADS)

Knowles, Kyler Reser

Processing carbon fiber composite laminates creates molecular-level strains in the thermoset matrix upon curing and cooling which can lead to failures such as geometry deformations, micro-cracking, and other issues. It is known strain creation is attributed to the significant volume and physical state changes undergone by the polymer matrix throughout the curing process, though storage and relaxation of cure-induced strains remain poorly understood. This dissertation establishes two approaches to address the issue. The first establishes testing methods to simultaneously measure key volumetric properties of a carbon fiber composite laminate and its polymer matrix. The second approach considers the rigidity of the polymer matrix in regards to strain storage and relaxation mechanisms which ultimately control composite performance throughout manufacturing and use. Through the use of a non-contact, full-field strain measurement technique known as digital image correlation (DIC), we describe and implement useful experiments which quantify matrix and composite parameters necessary for simulation efforts and failure models. The methods are compared to more traditional techniques and show excellent correlation. Further, we established relationships which represent matrix-fiber compatibility in regards to critical processing constraints. The second approach involves a systematic study of epoxy-amine networks which are chemically-similar but differ in chain segment rigidity. Prior research has investigated the isomer effect of glassy polymers, showing sizeable differences in thermal, volumetric, physical, and mechanical properties. This work builds on these themes and shows the apparent isomer effect is rather an effect of chain rigidity. Indeed, it was found that structurally-dissimilar polymer networks exhibit very similar properties as a consequence of their shared average network rigidity. Differences in chain packing, as a consequence of chain rigidity, were shown to alter the physical, volumetric, and mechanical properties of the glassy networks. Chain rigidity was found to directly control deformation mechanisms, which were related to the yielding behavior of the epoxy network series. The unique benefit to our approach is the ability to separate the role of rigidity - an intramolecular parameter - from intermolecular phenomena which otherwise influence network properties.

Quantum coordinated multi-point communication based on entanglement swapping

NASA Astrophysics Data System (ADS)

Du, Gang; Shang, Tao; Liu, Jian-wei

2017-05-01

In a quantum network, adjacent nodes can communicate with each other point to point by using pre-shared Einsten-Podolsky-Rosen (EPR) pairs, and furthermore remote nodes can establish entanglement channels by using quantum routing among intermediate nodes. However, with the rapid development of quantum networks, the demand of various message transmission among nodes inevitably emerges. In order to realize this goal and extend quantum networks, we propose a quantum coordinated multi-point communication scheme based on entanglement swapping. The scheme takes full advantage of EPR pairs between adjacent nodes and performs multi-party entanglement swapping to transmit messages. Considering various demands of communication, all nodes work cooperatively to realize different message transmission modes, including one to many, many to one and one to some. Scheme analysis shows that the proposed scheme can flexibly organize a coordinated group and efficiently use EPR resources, while it meets basic security requirement under the condition of coordinated communication.

Topological and kinetic determinants of the modal matrices of dynamic models of metabolism

PubMed Central

2017-01-01

Large-scale kinetic models of metabolism are becoming increasingly comprehensive and accurate. A key challenge is to understand the biochemical basis of the dynamic properties of these models. Linear analysis methods are well-established as useful tools for characterizing the dynamic response of metabolic networks. Central to linear analysis methods are two key matrices: the Jacobian matrix (J) and the modal matrix (M-1) arising from its eigendecomposition. The modal matrix M-1 contains dynamically independent motions of the kinetic model near a reference state, and it is sparse in practice for metabolic networks. However, connecting the structure of M-1 to the kinetic properties of the underlying reactions is non-trivial. In this study, we analyze the relationship between J, M-1, and the kinetic properties of the underlying network for kinetic models of metabolism. Specifically, we describe the origin of mode sparsity structure based on features of the network stoichiometric matrix S and the reaction kinetic gradient matrix G. First, we show that due to the scaling of kinetic parameters in real networks, diagonal dominance occurs in a substantial fraction of the rows of J, resulting in simple modal structures with clear biological interpretations. Then, we show that more complicated modes originate from topologically-connected reactions that have similar reaction elasticities in G. These elasticities represent dynamic equilibrium balances within reactions and are key determinants of modal structure. The work presented should prove useful towards obtaining an understanding of the dynamics of kinetic models of metabolism, which are rooted in the network structure and the kinetic properties of reactions. PMID:29267329

Radionuclide Transport in Fracture-Granite Interface Zones

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hu, Q; Mori, A

In situ radionuclide migration experiments, followed by excavation and sample characterization, were conducted in a water-conducting shear zone at the Grimsel Test Site (GTS) in Switzerland to study diffusion paths of radionuclides in fractured granite. In this work, we employed a micro-scale mapping technique that interfaces laser ablation sampling with inductively coupled plasma-mass spectrometry (LA/ICP-MS) to measure the fine-scale (micron-range) distribution of actinides ({sup 234}U, {sup 235}U, and {sup 237}Np) in the fracture-granite interface zones. Long-lived {sup 234}U, {sup 235}U, and {sup 237}Np were detected in flow channels, as well as in the adjacent rock matrix, using the sensitive, feature-basedmore » mapping of the LA/ICP-MS technique. The injected sorbing actinides are mainly located within the advective flowing fractures and the immediately adjacent regions. The water-conducting fracture studied in this work is bounded on one side by mylonite and the other by granitic matrix regions. These actinides did not penetrate into the mylonite side as much as the relatively higher-porosity granite matrix, most likely due to the low porosity, hydraulic conductivity, and diffusivity of the fracture wall (a thickness of about 0.4 mm separates the mylonite region from the fracture) and the mylonite region itself. Overall, the maximum penetration depth detected with this technique for the more diffusive {sup 237}Np over the field experimental time scale of about 60 days was about 10 mm in the granitic matrix, illustrating the importance of matrix diffusion in retarding radionuclide transport from the advective fractures. Laboratory tests and numerical modeling of radionuclide diffusion into granitic matrix was conducted to complement and help interpret the field results. Measured apparent diffusivity of multiple tracers in granite provided consistent predictions for radionuclide transport in the fractured granitic rock.« less

Bond-based linear indices of the non-stochastic and stochastic edge-adjacency matrix. 1. Theory and modeling of ChemPhys properties of organic molecules.

PubMed

Marrero-Ponce, Yovani; Martínez-Albelo, Eugenio R; Casañola-Martín, Gerardo M; Castillo-Garit, Juan A; Echevería-Díaz, Yunaimy; Zaldivar, Vicente Romero; Tygat, Jan; Borges, José E Rodriguez; García-Domenech, Ramón; Torrens, Francisco; Pérez-Giménez, Facundo

2010-11-01

Novel bond-level molecular descriptors are proposed, based on linear maps similar to the ones defined in algebra theory. The kth edge-adjacency matrix (E(k)) denotes the matrix of bond linear indices (non-stochastic) with regard to canonical basis set. The kth stochastic edge-adjacency matrix, ES(k), is here proposed as a new molecular representation easily calculated from E(k). Then, the kth stochastic bond linear indices are calculated using ES(k) as operators of linear transformations. In both cases, the bond-type formalism is developed. The kth non-stochastic and stochastic total linear indices are calculated by adding the kth non-stochastic and stochastic bond linear indices, respectively, of all bonds in molecule. First, the new bond-based molecular descriptors (MDs) are tested for suitability, for the QSPRs, by analyzing regressions of novel indices for selected physicochemical properties of octane isomers (first round). General performance of the new descriptors in this QSPR studies is evaluated with regard to the well-known sets of 2D/3D MDs. From the analysis, we can conclude that the non-stochastic and stochastic bond-based linear indices have an overall good modeling capability proving their usefulness in QSPR studies. Later, the novel bond-level MDs are also used for the description and prediction of the boiling point of 28 alkyl-alcohols (second round), and to the modeling of the specific rate constant (log k), partition coefficient (log P), as well as the antibacterial activity of 34 derivatives of 2-furylethylenes (third round). The comparison with other approaches (edge- and vertices-based connectivity indices, total and local spectral moments, and quantum chemical descriptors as well as E-state/biomolecular encounter parameters) exposes a good behavior of our method in this QSPR studies. Finally, the approach described in this study appears to be a very promising structural invariant, useful not only for QSPR studies but also for similarity/diversity analysis and drug discovery protocols.

Comment on ``The problem of deficiency indices for discrete Schrödinger operators on locally finite graphs'' [J. Math. Phys. 52, 063512 (2011)

NASA Astrophysics Data System (ADS)

Golénia, Sylvain; Schumacher, Christoph

2013-06-01

In this comment we answer negatively to our conjecture concerning the deficiency indices. More precisely, given any non-negative integer n, there is locally finite graph on which the adjacency matrix has deficiency indices (n, n).

EGFR-Dependent Regulation of Matrix-Independent Epithelial Cell Survival

DTIC Science & Technology

2006-04-01

ultraviolet (UV) irradiation ( Mudgil et al., 2003), decreased adhesive interactions between tumor cells and adjacent epithelia Much remains to be...historical perspective on integrin signal transduction. Nat. Cell Biol. 4, E83-E90. Mudgil , A. V., Segal, N., Andriani, F., Wang, Y., Fusenig, N. E. and

Discovering Implicit Networks from Point Process Data

DTIC Science & Technology

2013-08-03

Standard Form 298 (Rev. 8-98) Prescribed by ANSI Std Z39-18 SOCIAL NETWORK ANALYSIS Szell et al, Nature 2012 Saturday, August 3, 13 (a) Adjacency...processes: ‣ Seismology ‣ Epidemiology ‣ Economics ‣ Modeling dependence is challenging - “beyond Poisson” ‣ Strauss and Gibbs Processes ‣ Determinantal

A Deep Stochastic Model for Detecting Community in Complex Networks

NASA Astrophysics Data System (ADS)

Fu, Jingcheng; Wu, Jianliang

2017-01-01

Discovering community structures is an important step to understanding the structure and dynamics of real-world networks in social science, biology and technology. In this paper, we develop a deep stochastic model based on non-negative matrix factorization to identify communities, in which there are two sets of parameters. One is the community membership matrix, of which the elements in a row correspond to the probabilities of the given node belongs to each of the given number of communities in our model, another is the community-community connection matrix, of which the element in the i-th row and j-th column represents the probability of there being an edge between a randomly chosen node from the i-th community and a randomly chosen node from the j-th community. The parameters can be evaluated by an efficient updating rule, and its convergence can be guaranteed. The community-community connection matrix in our model is more precise than the community-community connection matrix in traditional non-negative matrix factorization methods. Furthermore, the method called symmetric nonnegative matrix factorization, is a special case of our model. Finally, based on the experiments on both synthetic and real-world networks data, it can be demonstrated that our algorithm is highly effective in detecting communities.

A spectral method to detect community structure based on distance modularity matrix

NASA Astrophysics Data System (ADS)

Yang, Jin-Xuan; Zhang, Xiao-Dong

2017-08-01

There are many community organizations in social and biological networks. How to identify these community structure in complex networks has become a hot issue. In this paper, an algorithm to detect community structure of networks is proposed by using spectra of distance modularity matrix. The proposed algorithm focuses on the distance of vertices within communities, rather than the most weakly connected vertex pairs or number of edges between communities. The experimental results show that our method achieves better effectiveness to identify community structure for a variety of real-world networks and computer generated networks with a little more time-consumption.

Evaluation of the applicability of the dual‐domain mass transfer model in porous media containing connected high‐conductivity channels

USGS Publications Warehouse

Liu, Gaisheng; Zheng, Chunmiao; Gorelick, Steven M.

2007-01-01

This paper evaluates the dual‐domain mass transfer (DDMT) model to represent transport processes when small‐scale high‐conductivity (K) preferential flow paths (PFPs) are present in a homogenous porous media matrix. The effects of PFPs upon solute transport were examined through detailed numerical experiments involving different realizations of PFP networks, PFP/matrix conductivity contrasts varying from 10:1 to 200:1, different magnitudes of effective conductivities, and a range of molecular diffusion coefficients. Results suggest that the DDMT model can reproduce both the near‐source peak and the downstream low‐concentration spreading observed in the embedded dendritic network when there are large conductivity contrasts between high‐K PFPs and the low‐K matrix. The accuracy of the DDMT model is also affected by the geometry of PFP networks and by the relative significance of the diffusion process in the network‐matrix system.

Extracellular matrix structure.

PubMed

Theocharis, Achilleas D; Skandalis, Spyros S; Gialeli, Chrysostomi; Karamanos, Nikos K

2016-02-01

Extracellular matrix (ECM) is a non-cellular three-dimensional macromolecular network composed of collagens, proteoglycans/glycosaminoglycans, elastin, fibronectin, laminins, and several other glycoproteins. Matrix components bind each other as well as cell adhesion receptors forming a complex network into which cells reside in all tissues and organs. Cell surface receptors transduce signals into cells from ECM, which regulate diverse cellular functions, such as survival, growth, migration, and differentiation, and are vital for maintaining normal homeostasis. ECM is a highly dynamic structural network that continuously undergoes remodeling mediated by several matrix-degrading enzymes during normal and pathological conditions. Deregulation of ECM composition and structure is associated with the development and progression of several pathologic conditions. This article emphasizes in the complex ECM structure as to provide a better understanding of its dynamic structural and functional multipotency. Where relevant, the implication of the various families of ECM macromolecules in health and disease is also presented. Copyright © 2015 Elsevier B.V. All rights reserved.

A multivariate pattern analysis study of the HIV-related white matter anatomical structural connections alterations

NASA Astrophysics Data System (ADS)

Tang, Zhenchao; Liu, Zhenyu; Li, Ruili; Cui, Xinwei; Li, Hongjun; Dong, Enqing; Tian, Jie

2017-03-01

It's widely known that HIV infection would cause white matter integrity impairments. Nevertheless, it is still unclear that how the white matter anatomical structural connections are affected by HIV infection. In the current study, we employed a multivariate pattern analysis to explore the HIV-related white matter connections alterations. Forty antiretroviraltherapy- naïve HIV patients and thirty healthy controls were enrolled. Firstly, an Automatic Anatomical Label (AAL) atlas based white matter structural network, a 90 × 90 FA-weighted matrix, was constructed for each subject. Then, the white matter connections deprived from the structural network were entered into a lasso-logistic regression model to perform HIV-control group classification. Using leave one out cross validation, a classification accuracy (ACC) of 90% (P=0.002) and areas under the receiver operating characteristic curve (AUC) of 0.96 was obtained by the classification model. This result indicated that the white matter anatomical structural connections contributed greatly to HIV-control group classification, providing solid evidence that the white matter connections were affected by HIV infection. Specially, 11 white matter connections were selected in the classification model, mainly crossing the regions of frontal lobe, Cingulum, Hippocampus, and Thalamus, which were reported to be damaged in previous HIV studies. This might suggest that the white matter connections adjacent to the HIV-related impaired regions were prone to be damaged.

Patterns of patterns of synchronization: Noise induced attractor switching in rings of coupled nonlinear oscillators

DOE Office of Scientific and Technical Information (OSTI.GOV)

Emenheiser, Jeffrey; Department of Physics, University of California, Davis, California 95616; Chapman, Airlie

Following the long-lived qualitative-dynamics tradition of explaining behavior in complex systems via the architecture of their attractors and basins, we investigate the patterns of switching between distinct trajectories in a network of synchronized oscillators. Our system, consisting of nonlinear amplitude-phase oscillators arranged in a ring topology with reactive nearest-neighbor coupling, is simple and connects directly to experimental realizations. We seek to understand how the multiple stable synchronized states connect to each other in state space by applying Gaussian white noise to each of the oscillators' phases. To do this, we first analytically identify a set of locally stable limit cyclesmore » at any given coupling strength. For each of these attracting states, we analyze the effect of weak noise via the covariance matrix of deviations around those attractors. We then explore the noise-induced attractor switching behavior via numerical investigations. For a ring of three oscillators, we find that an attractor-switching event is always accompanied by the crossing of two adjacent oscillators' phases. For larger numbers of oscillators, we find that the distribution of times required to stochastically leave a given state falls off exponentially, and we build an attractor switching network out of the destination states as a coarse-grained description of the high-dimensional attractor-basin architecture.« less

The molecular basis of the solution properties of hyaluronan investigated by confocal fluorescence recovery after photobleaching.

PubMed Central

Gribbon, P; Heng, B C; Hardingham, T E

1999-01-01

Hyaluronan (HA) is a highly hydrated polyanion, which is a network-forming and space-filling component in the extracellular matrix of animal tissues. Confocal fluorescence recovery after photobleaching (confocal-FRAP) was used to investigate intramolecular hydrogen bonding and electrostatic interactions in hyaluronan solutions. Self and tracer lateral diffusion coefficients within hyaluronan solutions were measured over a wide range of concentrations (c), with varying electrolyte and at neutral and alkaline pH. The free diffusion coefficient of fluoresceinamine-labeled HA of 500 kDa in PBS was 7.9 x 10(-8) cm(2) s(-1) and of 830 kDa HA was 5.6 x 10(-8) cm(2) s(-1). Reductions in self- and tracer-diffusion with c followed a stretched exponential model. Electrolyte-induced polyanion coil contraction and destiffening resulted in a 2.8-fold increase in self-diffusion between 0 and 100 mM NaCl. Disruption of hydrogen bonds by strong alkali (0.5 M NaOH) resulted in further larger increases in self- and tracer-diffusion coefficients, consistent with a more dynamic and permeable network. Concentrated hyaluronan solution properties were attributed to hydrodynamic and entanglement interactions between domains. There was no evidence of chain-chain associations. At physiological electrolyte concentration and pH, the greatest contribution to the intrinsic stiffness of hyaluronan appeared to be due to hydrogen bonds between adjacent saccharides. PMID:10512840

Study of montmorillonite nanoparticles and electron beam irradiation interaction of ethylene vinyl acetate (EVA)/de-vulcanized waste rubber thermoplastic composites

NASA Astrophysics Data System (ADS)

Bee, Soo-Tueen; Sin, Lee Tin; Hoe, Tie Teck; Ratnam, C. T.; Bee, Soo Ling; Rahmat, A. R.

2018-05-01

The purpose of this work was to investigate the effects of montmorillonite (MMT) loading level and electron beam irradiation on the physical-mechanical properties and thermal stability of ethylene vinyl acetate (EVA)- devulcanised waste rubber blends. The addition of MMT particles has significantly increased the d-spacing and interchain separation of deflection peak (0 0 2) of MMT particles. This indicates that MMT particles have effectively intercalated in polymer matrix of EVA-devulcanised waste rubber blends. Besides, the application of electron beam irradiation dosages <150 kGy could also significantly induce the effective intercalation effect of MMT particles in polymer matrix by introducing crosslinking networks. The increasing of electron beam irradiation dosages up to 250 kGy has gradually increased the gel content of all EVA-devulcanized rubber blends by inducing the formation of crosslinking networks in polymer matrix. Also, the tensile strength of all EVA-devulcanized waste rubber blends was gradually increased when irradiated up to 150 kGy. This is due to the occurrence of crosslinking networks by irradiation could significantly provide reinforcement effect to polymer matrix by effectively transferring the stress applied on polymer matrix throughout the whole polymer matrix.

Magnostics: Image-Based Search of Interesting Matrix Views for Guided Network Exploration.

PubMed

Behrisch, Michael; Bach, Benjamin; Hund, Michael; Delz, Michael; Von Ruden, Laura; Fekete, Jean-Daniel; Schreck, Tobias

2017-01-01

In this work we address the problem of retrieving potentially interesting matrix views to support the exploration of networks. We introduce Matrix Diagnostics (or Magnostics), following in spirit related approaches for rating and ranking other visualization techniques, such as Scagnostics for scatter plots. Our approach ranks matrix views according to the appearance of specific visual patterns, such as blocks and lines, indicating the existence of topological motifs in the data, such as clusters, bi-graphs, or central nodes. Magnostics can be used to analyze, query, or search for visually similar matrices in large collections, or to assess the quality of matrix reordering algorithms. While many feature descriptors for image analyzes exist, there is no evidence how they perform for detecting patterns in matrices. In order to make an informed choice of feature descriptors for matrix diagnostics, we evaluate 30 feature descriptors-27 existing ones and three new descriptors that we designed specifically for MAGNOSTICS-with respect to four criteria: pattern response, pattern variability, pattern sensibility, and pattern discrimination. We conclude with an informed set of six descriptors as most appropriate for Magnostics and demonstrate their application in two scenarios; exploring a large collection of matrices and analyzing temporal networks.

Interfacial crowding of nanoplatelets in co-continuous polymer blends: assembly, elasticity and structure of the interfacial nanoparticle network.

PubMed

Altobelli, R; Salzano de Luna, M; Filippone, G

2017-09-27

The sequence of events which leads to the interfacial crowding of plate-like nanoparticles in co-continuous polymer blends is investigated through a combination of morphological and rheological analyses. Very low amounts (∼0.2 vol%) of organo-modified clay are sufficient to suppress phase coarsening in a co-continuous polystyrene/poly(methyl methacrylate) blend, while lower particle loading allows for a tuning of the characteristic size of the polymer phases at the μm-scale. In any case, an interfacial network of nanoparticles eventually forms, which is driven by the preferred polymer-polymer interface. The elastic features and stress-bearing ability of this peculiar nanoparticle assembly are studied in detail by means of a descriptive two-phase viscoelastic model, which allows isolation of the contribution of the filler network. The role of the co-continuous matrix in driving the space arrangement of the nanoparticles is emphasized by means of comparative analysis with systems based on the same polymers and nanoparticles, but in which the matrix is either a pure polymer or a blend with drop-in-matrix morphology. The relaxation dynamics of the interfacial network was found not to depend on the matrix microstructure, which instead substantially affects the assembly of the nanoplatelets. When the host medium is co-continuous, the particles align along the preferred polymer-polymer interface, percolating at a very low amount (∼0.17 vol%) and prevalently interacting edge-to-edge. The stress bearing ability of such a network is much higher than that in the case of matrix based on a homogeneous polymer or a drop-in-matrix blend, but its elasticity shows low sensitivity to the filler content.

Linear analysis near a steady-state of biochemical networks: Control analysis, correlation metrics and circuit theory

PubMed Central

Heuett, William J; Beard, Daniel A; Qian, Hong

2008-01-01

Background Several approaches, including metabolic control analysis (MCA), flux balance analysis (FBA), correlation metric construction (CMC), and biochemical circuit theory (BCT), have been developed for the quantitative analysis of complex biochemical networks. Here, we present a comprehensive theory of linear analysis for nonequilibrium steady-state (NESS) biochemical reaction networks that unites these disparate approaches in a common mathematical framework and thermodynamic basis. Results In this theory a number of relationships between key matrices are introduced: the matrix A obtained in the standard, linear-dynamic-stability analysis of the steady-state can be decomposed as A = SRT where R and S are directly related to the elasticity-coefficient matrix for the fluxes and chemical potentials in MCA, respectively; the control-coefficients for the fluxes and chemical potentials can be written in terms of RTBS and STBS respectively where matrix B is the inverse of A; the matrix S is precisely the stoichiometric matrix in FBA; and the matrix eAt plays a central role in CMC. Conclusion One key finding that emerges from this analysis is that the well-known summation theorems in MCA take different forms depending on whether metabolic steady-state is maintained by flux injection or concentration clamping. We demonstrate that if rate-limiting steps exist in a biochemical pathway, they are the steps with smallest biochemical conductances and largest flux control-coefficients. We hypothesize that biochemical networks for cellular signaling have a different strategy for minimizing energy waste and being efficient than do biochemical networks for biosynthesis. We also discuss the intimate relationship between MCA and biochemical systems analysis (BSA). PMID:18482450

Recurrent Neural Network for Computing the Drazin Inverse.

PubMed

Stanimirović, Predrag S; Zivković, Ivan S; Wei, Yimin

2015-11-01

This paper presents a recurrent neural network (RNN) for computing the Drazin inverse of a real matrix in real time. This recurrent neural network (RNN) is composed of n independent parts (subnetworks), where n is the order of the input matrix. These subnetworks can operate concurrently, so parallel and distributed processing can be achieved. In this way, the computational advantages over the existing sequential algorithms can be attained in real-time applications. The RNN defined in this paper is convenient for an implementation in an electronic circuit. The number of neurons in the neural network is the same as the number of elements in the output matrix, which represents the Drazin inverse. The difference between the proposed RNN and the existing ones for the Drazin inverse computation lies in their network architecture and dynamics. The conditions that ensure the stability of the defined RNN as well as its convergence toward the Drazin inverse are considered. In addition, illustrative examples and examples of application to the practical engineering problems are discussed to show the efficacy of the proposed neural network.

Google matrix of the world network of economic activities

NASA Astrophysics Data System (ADS)

Kandiah, Vivek; Escaith, Hubert; Shepelyansky, Dima L.

2015-07-01

Using the new data from the OECD-WTO world network of economic activities we construct the Google matrix G of this directed network and perform its detailed analysis. The network contains 58 countries and 37 activity sectors for years 1995 and 2008. The construction of G, based on Markov chain transitions, treats all countries on equal democratic grounds while the contribution of activity sectors is proportional to their exchange monetary volume. The Google matrix analysis allows to obtain reliable ranking of countries and activity sectors and to determine the sensitivity of CheiRank-PageRank commercial balance of countries in respect to price variations and labor cost in various countries. We demonstrate that the developed approach takes into account multiplicity of network links with economy interactions between countries and activity sectors thus being more efficient compared to the usual export-import analysis. The spectrum and eigenstates of G are also analyzed being related to specific activity communities of countries.

E-beam generated holographic masks for optical vector-matrix multiplication

NASA Technical Reports Server (NTRS)

Arnold, S. M.; Case, S. K.

1981-01-01

An optical vector matrix multiplication scheme that encodes the matrix elements as a holographic mask consisting of linear diffraction gratings is proposed. The binary, chrome on glass masks are fabricated by e-beam lithography. This approach results in a fairly simple optical system that promises both large numerical range and high accuracy. A partitioned computer generated hologram mask was fabricated and tested. This hologram was diagonally separated outputs, compact facets and symmetry about the axis. The resultant diffraction pattern at the output plane is shown. Since the grating fringes are written at 45 deg relative to the facet boundaries, the many on-axis sidelobes from each output are seen to be diagonally separated from the adjacent output signals.

Precision pointing of scientific instruments on space station: The LFGGREC perspective

NASA Technical Reports Server (NTRS)

Blackwell, C. C.; Sirlin, S. W.; Laskin, R. A.

1988-01-01

An application of Lyapunov function-gradient-generated robustness-enhancing control (LFGGREC) is explored. The attention is directed to a reduced-complexity representation of the pointing problem presented by the system composed of the Space Infrared Telescope Facility gimbaled to a space station configuration. Uncertainties include disturbance forces applied in the crew compartment area and control moments applied to adjacent scientific payloads (modeled as disturbance moments). Also included are uncertainties in gimbal friction and in the structural component of the system, as reflected in the inertia matrix, the damping matrix, and the stiffness matrix, and the effect of the ignored vibrational dynamics of the structure. The emphasis is on the adaptation of LFGGREC to this particular configuration and on the robustness analysis.

Derivation of stiffness matrix in constitutive modeling of magnetorheological elastomer

NASA Astrophysics Data System (ADS)

Leng, D.; Sun, L.; Sun, J.; Lin, Y.

2013-02-01

Magnetorheological elastomers (MREs) are a class of smart materials whose mechanical properties change instantly by the application of a magnetic field. Based on the specially orthotropic, transversely isotropic stress-strain relationships and effective permeability model, the stiffness matrix of constitutive equations for deformable chain-like MRE is considered. To valid the components of shear modulus in this stiffness matrix, the magnetic-structural simulations with finite element method (FEM) are presented. An acceptable agreement is illustrated between analytical equations and numerical simulations. For the specified magnetic field, sphere particle radius, distance between adjacent particles in chains and volume fractions of ferrous particles, this constitutive equation is effective to engineering application to estimate the elastic behaviour of chain-like MRE in an external magnetic field.

In-situ formation of nanoparticles within a silicon-based matrix

DOEpatents

Thoma, Steven G [Albuquerque, NM; Wilcoxon, Jess P [Albuquerque, NM; Abrams, Billie L [Albuquerque, NM

2008-06-10

A method for encapsulating nanoparticles with an encapsulating matrix that minimizes aggregation and maintains favorable properties of the nanoparticles. The matrix comprises silicon-based network-forming compounds such as ormosils and polysiloxanes. The nanoparticles are synthesized from precursors directly within the silicon-based matrix.

Whole-brain functional connectivity during acquisition of novel grammar: Distinct functional networks depend on language learning abilities.

PubMed

Kepinska, Olga; de Rover, Mischa; Caspers, Johanneke; Schiller, Niels O

2017-03-01

In an effort to advance the understanding of brain function and organisation accompanying second language learning, we investigate the neural substrates of novel grammar learning in a group of healthy adults, consisting of participants with high and average language analytical abilities (LAA). By means of an Independent Components Analysis, a data-driven approach to functional connectivity of the brain, the fMRI data collected during a grammar-learning task were decomposed into maps representing separate cognitive processes. These included the default mode, task-positive, working memory, visual, cerebellar and emotional networks. We further tested for differences within the components, representing individual differences between the High and Average LAA learners. We found high analytical abilities to be coupled with stronger contributions to the task-positive network from areas adjacent to bilateral Broca's region, stronger connectivity within the working memory network and within the emotional network. Average LAA participants displayed stronger engagement within the task-positive network from areas adjacent to the right-hemisphere homologue of Broca's region and typical to lower level processing (visual word recognition), and increased connectivity within the default mode network. The significance of each of the identified networks for the grammar learning process is presented next to a discussion on the established markers of inter-individual learners' differences. We conclude that in terms of functional connectivity, the engagement of brain's networks during grammar acquisition is coupled with one's language learning abilities. Copyright © 2016 Elsevier B.V. All rights reserved.

Investigating the effects of streamline-based fiber tractography on matrix scaling in brain connective network.

PubMed

Jan, Hengtai; Chao, Yi-Ping; Cho, Kuan-Hung; Kuo, Li-Wei

2013-01-01

Investigating the brain connective network using the modern graph theory has been widely applied in cognitive and clinical neuroscience research. In this study, we aimed to investigate the effects of streamline-based fiber tractography on the change of network properties and established a systematic framework to understand how an adequate network matrix scaling can be determined. The network properties, including degree, efficiency and betweenness centrality, show similar tendency in both left and right hemispheres. By employing the curve-fitting process with exponential law and measuring the residuals, the association between changes of network properties and threshold of track numbers is found and an adequate range of investigating the lateralization of brain network is suggested. The proposed approach can be further applied in clinical applications to improve the diagnostic sensitivity using network analysis with graph theory.

[Network structures in biological systems].

PubMed

Oleskin, A V

2013-01-01

Network structures (networks) that have been extensively studied in the humanities are characterized by cohesion, a lack of a central control unit, and predominantly fractal properties. They are contrasted with structures that contain a single centre (hierarchies) as well as with those whose elements predominantly compete with one another (market-type structures). As far as biological systems are concerned, their network structures can be subdivided into a number of types involving different organizational mechanisms. Network organization is characteristic of various structural levels of biological systems ranging from single cells to integrated societies. These networks can be classified into two main subgroups: (i) flat (leaderless) network structures typical of systems that are composed of uniform elements and represent modular organisms or at least possess manifest integral properties and (ii) three-dimensional, partly hierarchical structures characterized by significant individual and/or intergroup (intercaste) differences between their elements. All network structures include an element that performs structural, protective, and communication-promoting functions. By analogy to cell structures, this element is denoted as the matrix of a network structure. The matrix includes a material and an immaterial component. The material component comprises various structures that belong to the whole structure and not to any of its elements per se. The immaterial (ideal) component of the matrix includes social norms and rules regulating network elements' behavior. These behavioral rules can be described in terms of algorithms. Algorithmization enables modeling the behavior of various network structures, particularly of neuron networks and their artificial analogs.

Nonlinear mechanical response of the extracellular matrix: learning from articular cartilage

NASA Astrophysics Data System (ADS)

Kearns, Sarah; Das, Moumita

2015-03-01

We study the mechanical structure-function relations in the extracellular matrix (ECM) with focus on nonlinear shear and compression response. As a model system, our study focuses on the ECM in articular cartilage tissue which has two major mechanobiological components: a network of the biopolymer collagen that acts as a stiff, reinforcing matrix, and a flexible aggrecan network that facilitates deformability. We model this system as a double network hydrogel made of interpenetrating networks of stiff and flexible biopolymers respectively. We study the linear and nonlinear mechanical response of the model ECM to shear and compression forces using a combination of rigidity percolation theory and energy minimization approaches. Our results may provide useful insights into the design principles of the ECM as well as biomimetic hydrogels that are mechanically robust and can, at the same time, easily adapt to cues in their surroundings.

An Optimal Algorithm towards Successive Location Privacy in Sensor Networks with Dynamic Programming

NASA Astrophysics Data System (ADS)

Zhao, Baokang; Wang, Dan; Shao, Zili; Cao, Jiannong; Chan, Keith C. C.; Su, Jinshu

In wireless sensor networks, preserving location privacy under successive inference attacks is extremely critical. Although this problem is NP-complete in general cases, we propose a dynamic programming based algorithm and prove it is optimal in special cases where the correlation only exists between p immediate adjacent observations.

Similarity-balanced discriminant neighbor embedding and its application to cancer classification based on gene expression data.

PubMed

Zhang, Li; Qian, Liqiang; Ding, Chuntao; Zhou, Weida; Li, Fanzhang

2015-09-01

The family of discriminant neighborhood embedding (DNE) methods is typical graph-based methods for dimension reduction, and has been successfully applied to face recognition. This paper proposes a new variant of DNE, called similarity-balanced discriminant neighborhood embedding (SBDNE) and applies it to cancer classification using gene expression data. By introducing a novel similarity function, SBDNE deals with two data points in the same class and the different classes with different ways. The homogeneous and heterogeneous neighbors are selected according to the new similarity function instead of the Euclidean distance. SBDNE constructs two adjacent graphs, or between-class adjacent graph and within-class adjacent graph, using the new similarity function. According to these two adjacent graphs, we can generate the local between-class scatter and the local within-class scatter, respectively. Thus, SBDNE can maximize the between-class scatter and simultaneously minimize the within-class scatter to find the optimal projection matrix. Experimental results on six microarray datasets show that SBDNE is a promising method for cancer classification. Copyright © 2015 Elsevier Ltd. All rights reserved.

Elevated expression of pleiotrophin in pilocarpine-induced seizures of immature rats and in pentylenetetrazole-induced hippocampal astrocytes in vitro.

PubMed

Zhang, Shuqin; Liang, Feng; Wang, Bing; Le, Yuan; Wang, Hua

2014-03-01

Pleiotrophin (PTN) is a secreted extracellular matrix (ECM)-associated cytokine that has emerged as an important neuromodulator with multiple neuronal functions. In the present study, we detected and compared the dynamic expression of PTN in the hippocampus and adjacent cortex of immature rats with pilocarpine-induced epilepsy. Moreover, we also confirmed the results by examining PTN expression in hippocampal astrocytes cultured in the presence of pentylenetetrazole (PTZ). Immunohistochemistry showed faint immunostaining of PTN in the control hippocampus and adjacent cortex. Notably, PTN immunoreactivity began to increase in relatively small cells in the hippocampus and adjacent cortex at 2h and 3 weeks after seizures, and the labeling intensity reached the maximum level in the hippocampus and adjacent cortex at 8 weeks after seizures. Furthermore, we also found that PTZ treatment significantly reduced astrocytic viability in a dose-dependent manner and time-dependently increased expression levels of PTN in hippocampal astrocytes. In conclusion, our data suggest that increased expression of PTN in the brain tissues may be involved in epileptogenesis. Copyright © 2013 Elsevier GmbH. All rights reserved.

Effective distance adaptation traffic dispatching in software defined IP over optical network

NASA Astrophysics Data System (ADS)

Duan, Zhiwei; Li, Hui; Liu, Yuze; Ji, Yuefeng; Li, Hongfa; Lin, Yi

2017-10-01

The rapid growth of IP traffic has contributed to the wide deployment of optical devices (ROADM/OXC, etc.). Meanwhile, with the emergence and application of high-performance network services such as ultra-high video transmission, people are increasingly becoming more and more particular about the quality of service (QoS) of network. However, the pass-band shape of WSSs which is utilized in the ROADM/OXC is not ideal, causing narrowing of spectrum. Spectral narrowing can lead to signal impairment. Therefore, guard-bands need to be inserted between adjacent paths. In order to minimize the bandwidth waste due to guard bands, we propose an effective distance-adaptation traffic dispatching algorithm in IP over optical network based on SDON architecture. We use virtualization technology to set up virtual resources direct links by extracting part of the resources on paths which meet certain specific constraints. We also assign different bandwidth to each IP request based on path length. There is no need for guard-bands between the adjacent paths on the virtual link, which can effectively reduce the number of guard-bands and save the spectrum.

Statistical mechanics of human resource allocation

NASA Astrophysics Data System (ADS)

Inoue, Jun-Ichi; Chen, He

2014-03-01

We provide a mathematical platform to investigate the network topology of agents, say, university graduates who are looking for their positions in labor markets. The basic model is described by the so-called Potts spin glass which is well-known in the research field of statistical physics. In the model, each Potts spin (a tiny magnet in atomic scale length) represents the action of each student, and it takes a discrete variable corresponding to the company he/she applies for. We construct the energy to include three distinct effects on the students' behavior, namely, collective effect, market history and international ranking of companies. In this model system, the correlations (the adjacent matrix) between students are taken into account through the pairwise spin-spin interactions. We carry out computer simulations to examine the efficiency of the model. We also show that some chiral representation of the Potts spin enables us to obtain some analytical insights into our labor markets. This work was financially supported by Grant-in-Aid for Scientific Research (C) of Japan Society for the Promotion of Science No. 25330278.

Metastasis-suppressing NID2, an epigenetically-silenced gene, in the pathogenesis of nasopharyngeal carcinoma and esophageal squamous cell carcinoma.

PubMed

Chai, Annie Wai Yeeng; Cheung, Arthur Kwok Leung; Dai, Wei; Ko, Josephine Mun Yee; Ip, Joseph Chok Yan; Chan, Kwok Wah; Kwong, Dora Lai-Wan; Ng, Wai Tong; Lee, Anne Wing Mui; Ngan, Roger Kai Cheong; Yau, Chun Chung; Tung, Stewart Yuk; Lee, Victor Ho Fun; Lam, Alfred King-Yin; Pillai, Suja; Law, Simon; Lung, Maria Li

2016-11-29

Nidogen-2 (NID2) is a key component of the basement membrane that stabilizes the extracellular matrix (ECM) network. The aim of the study is to analyze the functional roles of NID2 in the pathogenesis of nasopharyngeal carcinoma (NPC) and esophageal squamous cell carcinoma (ESCC). We performed genome-wide methylation profiling of NPC and ESCC and validated our findings using the methylation-sensitive high-resolution melting (MS-HRM) assay. Results showed that promoter methylation of NID2 was significantly higher in NPC and ESCC samples than in their adjacent non-cancer counterparts. Consistently, down-regulation of NID2 was observed in the clinical samples and cell lines of both NPC and ESCC. Re-expression of NID2 suppresses clonogenic survival and migration abilities of transduced NPC and ESCC cells. We showed that NID2 significantly inhibits liver metastasis. Mechanistic studies of signaling pathways also confirm that NID2 suppresses the EGFR/Akt and integrin/FAK/PLCγ metastasis-related pathways. This study provides novel insights into the crucial tumor metastasis suppression roles of NID2 in cancers.

Metastasis-suppressing NID2, an epigenetically-silenced gene, in the pathogenesis of nasopharyngeal carcinoma and esophageal squamous cell carcinoma

PubMed Central

Chai, Annie Wai Yeeng; Cheung, Arthur Kwok Leung; Dai, Wei; Ko, Josephine Mun Yee; Ip, Joseph Chok Yan; Chan, Kwok Wah; Kwong, Dora Lai-Wan; Ng, Wai Tong; Lee, Anne Wing Mui; Ngan, Roger Kai Cheong; Yau, Chun Chung; Tung, Stewart Yuk; Lee, Victor Ho Fun; Lam, Alfred King-Yin; Pillai, Suja; Law, Simon; Lung, Maria Li

2016-01-01

Nidogen-2 (NID2) is a key component of the basement membrane that stabilizes the extracellular matrix (ECM) network. The aim of the study is to analyze the functional roles of NID2 in the pathogenesis of nasopharyngeal carcinoma (NPC) and esophageal squamous cell carcinoma (ESCC). We performed genome-wide methylation profiling of NPC and ESCC and validated our findings using the methylation-sensitive high-resolution melting (MS-HRM) assay. Results showed that promoter methylation of NID2 was significantly higher in NPC and ESCC samples than in their adjacent non-cancer counterparts. Consistently, down-regulation of NID2 was observed in the clinical samples and cell lines of both NPC and ESCC. Re-expression of NID2 suppresses clonogenic survival and migration abilities of transduced NPC and ESCC cells. We showed that NID2 significantly inhibits liver metastasis. Mechanistic studies of signaling pathways also confirm that NID2 suppresses the EGFR/Akt and integrin/FAK/PLCγ metastasis-related pathways. This study provides novel insights into the crucial tumor metastasis suppression roles of NID2 in cancers. PMID:27793011

Centrality measures in temporal networks with time series analysis

NASA Astrophysics Data System (ADS)

Huang, Qiangjuan; Zhao, Chengli; Zhang, Xue; Wang, Xiaojie; Yi, Dongyun

2017-05-01

The study of identifying important nodes in networks has a wide application in different fields. However, the current researches are mostly based on static or aggregated networks. Recently, the increasing attention to networks with time-varying structure promotes the study of node centrality in temporal networks. In this paper, we define a supra-evolution matrix to depict the temporal network structure. With using of the time series analysis, the relationships between different time layers can be learned automatically. Based on the special form of the supra-evolution matrix, the eigenvector centrality calculating problem is turned into the calculation of eigenvectors of several low-dimensional matrices through iteration, which effectively reduces the computational complexity. Experiments are carried out on two real-world temporal networks, Enron email communication network and DBLP co-authorship network, the results of which show that our method is more efficient at discovering the important nodes than the common aggregating method.

Class network routing

DOEpatents

Bhanot, Gyan [Princeton, NJ; Blumrich, Matthias A [Ridgefield, CT; Chen, Dong [Croton On Hudson, NY; Coteus, Paul W [Yorktown Heights, NY; Gara, Alan G [Mount Kisco, NY; Giampapa, Mark E [Irvington, NY; Heidelberger, Philip [Cortlandt Manor, NY; Steinmacher-Burow, Burkhard D [Mount Kisco, NY; Takken, Todd E [Mount Kisco, NY; Vranas, Pavlos M [Bedford Hills, NY

2009-09-08

Class network routing is implemented in a network such as a computer network comprising a plurality of parallel compute processors at nodes thereof. Class network routing allows a compute processor to broadcast a message to a range (one or more) of other compute processors in the computer network, such as processors in a column or a row. Normally this type of operation requires a separate message to be sent to each processor. With class network routing pursuant to the invention, a single message is sufficient, which generally reduces the total number of messages in the network as well as the latency to do a broadcast. Class network routing is also applied to dense matrix inversion algorithms on distributed memory parallel supercomputers with hardware class function (multicast) capability. This is achieved by exploiting the fact that the communication patterns of dense matrix inversion can be served by hardware class functions, which results in faster execution times.

Robust stability of bidirectional associative memory neural networks with time delays

NASA Astrophysics Data System (ADS)

Park, Ju H.

2006-01-01

Based on the Lyapunov Krasovskii functionals combined with linear matrix inequality approach, a novel stability criterion is proposed for asymptotic stability of bidirectional associative memory neural networks with time delays. A novel delay-dependent stability criterion is given in terms of linear matrix inequalities, which can be solved easily by various optimization algorithms.

Fuel cell separator with compressible sealing flanges

DOEpatents

Mientek, A.P.

1984-03-30

A separator for separating adjacent fuel cells in a stack of such cells includes a flat, rectangular, gas-impermeable plate disposed between adjacent cells and having two opposite side margins thereof folded back over one side of the plate to form two first seal flanges and having the other side margins thereof folded back over the opposite side of the plate to form two second seal flanges, each of the seal flanges cooperating with the plate to define a channel in which is disposed a resiliently compressible stack of thin metal sheets. The two first seal flanges cooperate with the electrolyte matrix of one of the cells to form a gas-impermeable seal between an electrode of the one cell and one of two reactant gas manifolds. The second seal flanges cooperate with the electrolyte matrix of the other cell for forming a gas-impermeable seal between an electrode of the other cell and the other of the two reactant gas manifolds. The seal flanges cooperate with the associated compressible stacks of sheets for maintaining a spacing between the plate and the electrolyte matrices while accommodating variation of that spacing.

Incorporation of Tenascin-C into the Extracellular Matrix by Periostin Underlies an Extracellular Meshwork Architecture*

PubMed Central

Kii, Isao; Nishiyama, Takashi; Li, Minqi; Matsumoto, Ken-ichi; Saito, Mitsuru; Amizuka, Norio; Kudo, Akira

2010-01-01

Extracellular matrix (ECM) underlies a complicated multicellular architecture that is subjected to significant forces from mechanical environment. Although various components of the ECM have been enumerated, mechanisms that evolve the sophisticated ECM architecture remain to be addressed. Here we show that periostin, a matricellular protein, promotes incorporation of tenascin-C into the ECM and organizes a meshwork architecture of the ECM. We found that both periostin null mice and tenascin-C null mice exhibited a similar phenotype, confined tibial periostitis, which possibly corresponds to medial tibial stress syndrome in human sports injuries. Periostin possessed adjacent domains that bind to tenascin-C and the other ECM protein: fibronectin and type I collagen, respectively. These adjacent domains functioned as a bridge between tenascin-C and the ECM, which increased deposition of tenascin-C on the ECM. The deposition of hexabrachions of tenascin-C may stabilize bifurcations of the ECM fibrils, which is integrated into the extracellular meshwork architecture. This study suggests a role for periostin in adaptation of the ECM architecture in the mechanical environment. PMID:19887451

Endothelin-1 stimulates colon cancer adjacent fibroblasts.

PubMed

Knowles, Jonathan P; Shi-Wen, Xu; Haque, Samer-ul; Bhalla, Ashish; Dashwood, Michael R; Yang, Shiyu; Taylor, Irving; Winslet, Marc C; Abraham, David J; Loizidou, Marilena

2012-03-15

Endothelin-1 (ET-1) is produced by and stimulates colorectal cancer cells. Fibroblasts produce tumour stroma required for cancer development. We investigated whether ET-1 stimulated processes involved in tumour stroma production by colonic fibroblasts. Primary human fibroblasts, isolated from normal tissues adjacent to colon cancers, were cultured with or without ET-1 and its antagonists. Cellular proliferation, migration and contraction were measured. Expression of enzymes involved in tumour stroma development and alterations in gene transcription were determined by Western blotting and genome microarrays. ET-1 stimulated proliferation, contraction and migration (p < 0.01 v control) and the expression of matrix degrading enzymes TIMP-1 and MMP-2, but not MMP-3. ET-1 upregulated genes for profibrotic growth factors and receptors, signalling molecules, actin modulators and extracellular matrix components. ET-1 stimulated colonic fibroblast cellular processes in vitro that are involved in developing tumour stroma. Upregulated genes were consistent with these processes. By acting as a strong stimulus for tumour stroma creation, ET-1 is proposed as a target for adjuvant cancer therapy. Copyright © 2011 UICC.

Fuel cell separator with compressible sealing flanges

DOEpatents

Mientek, Anthony P.

1985-04-30

A separator for separating adjacent fuel cells in a stack of such cells includes a flat, rectangular, gas-impermeable plate disposed between adjacent cells and having two opposite side margins thereof folded back over one side of the plate to form two first seal flanges and having the other side margins thereof folded back over the opposite side of the plate to form two second seal flanges, each of the seal flanges cooperating with the plate to define a channel in which is disposed a resiliently compressible stack of thin metal sheets. The two first seal flanges cooperate with the electrolyte matrix of one of the cells to form a gas-impermeable seal between an electrode of the one cell and one of two reactant gas manifolds. The second seal flanges cooperate with the electrolyte matrix of the other cell for forming a gas-impermeable seal between an electrode of the other cell and the other of the two reactant gas manifolds. The seal flanges cooperate with the associated compressible stacks of sheets for maintaining a spacing between the plate and the electrolyte matrices while accommodating variation of that spacing.

Incorporation of tenascin-C into the extracellular matrix by periostin underlies an extracellular meshwork architecture.

PubMed

Kii, Isao; Nishiyama, Takashi; Li, Minqi; Matsumoto, Ken-Ichi; Saito, Mitsuru; Amizuka, Norio; Kudo, Akira

2010-01-15

Extracellular matrix (ECM) underlies a complicated multicellular architecture that is subjected to significant forces from mechanical environment. Although various components of the ECM have been enumerated, mechanisms that evolve the sophisticated ECM architecture remain to be addressed. Here we show that periostin, a matricellular protein, promotes incorporation of tenascin-C into the ECM and organizes a meshwork architecture of the ECM. We found that both periostin null mice and tenascin-C null mice exhibited a similar phenotype, confined tibial periostitis, which possibly corresponds to medial tibial stress syndrome in human sports injuries. Periostin possessed adjacent domains that bind to tenascin-C and the other ECM protein: fibronectin and type I collagen, respectively. These adjacent domains functioned as a bridge between tenascin-C and the ECM, which increased deposition of tenascin-C on the ECM. The deposition of hexabrachions of tenascin-C may stabilize bifurcations of the ECM fibrils, which is integrated into the extracellular meshwork architecture. This study suggests a role for periostin in adaptation of the ECM architecture in the mechanical environment.

Achieving high strength and high ductility in metal matrix composites reinforced with a discontinuous three-dimensional graphene-like network.

PubMed

Zhang, Xiang; Shi, Chunsheng; Liu, Enzuo; He, Fang; Ma, Liying; Li, Qunying; Li, Jiajun; Bacsa, Wolfgang; Zhao, Naiqin; He, Chunnian

2017-08-24

Graphene or graphene-like nanosheets have been emerging as an attractive reinforcement for composites due to their unique mechanical and electrical properties as well as their fascinating two-dimensional structure. It is a great challenge to efficiently and homogeneously disperse them within a metal matrix for achieving metal matrix composites with excellent mechanical and physical performance. In this work, we have developed an innovative in situ processing strategy for the fabrication of metal matrix composites reinforced with a discontinuous 3D graphene-like network (3D GN). The processing route involves the in situ synthesis of the encapsulation structure of 3D GN powders tightly anchored with Cu nanoparticles (NPs) (3D GN@Cu) to ensure mixing at the molecular level between graphene-like nanosheets and metal, coating of Cu on the 3D GN@Cu (3D GN@Cu@Cu), and consolidation of the 3D GN@Cu@Cu powders. This process can produce GN/Cu composites on a large scale, in which the in situ synthesized 3D GN not only maintains the perfect 3D network structure within the composites, but also has robust interfacial bonding with the metal matrix. As a consequence, the as-obtained 3D GN/Cu composites exhibit exceptionally high strength and superior ductility (the uniform and total elongation to failure of the composite are even much higher than the unreinforced Cu matrix). To the best of our knowledge, this work is the first report validating that a discontinuous 3D graphene-like network can simultaneously remarkably enhance the strength and ductility of the metal matrix.

Matrix completion by deep matrix factorization.

PubMed

Fan, Jicong; Cheng, Jieyu

2018-02-01

Conventional methods of matrix completion are linear methods that are not effective in handling data of nonlinear structures. Recently a few researchers attempted to incorporate nonlinear techniques into matrix completion but there still exists considerable limitations. In this paper, a novel method called deep matrix factorization (DMF) is proposed for nonlinear matrix completion. Different from conventional matrix completion methods that are based on linear latent variable models, DMF is on the basis of a nonlinear latent variable model. DMF is formulated as a deep-structure neural network, in which the inputs are the low-dimensional unknown latent variables and the outputs are the partially observed variables. In DMF, the inputs and the parameters of the multilayer neural network are simultaneously optimized to minimize the reconstruction errors for the observed entries. Then the missing entries can be readily recovered by propagating the latent variables to the output layer. DMF is compared with state-of-the-art methods of linear and nonlinear matrix completion in the tasks of toy matrix completion, image inpainting and collaborative filtering. The experimental results verify that DMF is able to provide higher matrix completion accuracy than existing methods do and DMF is applicable to large matrices. Copyright © 2017 Elsevier Ltd. All rights reserved.

Membrane consisting of polyquaternary amine ion exchange polymer network interpenetrating the chains of thermoplastic matrix polymer

NASA Technical Reports Server (NTRS)

Rembaum, A.; Wallace, C. J. (Inventor)

1978-01-01

An ion exchange membrane was formed from a solution containing dissolved matrix polymer and a set of monomers which are capable of reacting to form a polyquaternary ion exchange material; for example vinyl pyride and a dihalo hydrocarbon. After casting solution and evaporation of the volatile component's, a relatively strong ion exchange membrane was obtained which is capable of removing anions, such as nitrate or chromate from water. The ion exchange polymer forms an interpenetrating network with the chains of the matrix polymer.

Reconfigurable Control with Neural Network Augmentation for a Modified F-15 Aircraft

NASA Technical Reports Server (NTRS)

Burken, John J.

2007-01-01

This paper describes the performance of a simplified dynamic inversion controller with neural network supplementation. This 6 DOF (Degree-of-Freedom) simulation study focuses on the results with and without adaptation of neural networks using a simulation of the NASA modified F-15 which has canards. One area of interest is the performance of a simulated surface failure while attempting to minimize the inertial cross coupling effect of a [B] matrix failure (a control derivative anomaly associated with a jammed or missing control surface). Another area of interest and presented is simulated aerodynamic failures ([A] matrix) such as a canard failure. The controller uses explicit models to produce desired angular rate commands. The dynamic inversion calculates the necessary surface commands to achieve the desired rates. The simplified dynamic inversion uses approximate short period and roll axis dynamics. Initial results indicated that the transient response for a [B] matrix failure using a Neural Network (NN) improved the control behavior when compared to not using a neural network for a given failure, However, further evaluation of the controller was comparable, with objections io the cross coupling effects (after changes were made to the controller). This paper describes the methods employed to reduce the cross coupling effect and maintain adequate tracking errors. The IA] matrix failure results show that control of the aircraft without adaptation is more difficult [leas damped) than with active neural networks, Simulation results show Neural Network augmentation of the controller improves performance in terms of backing error and cross coupling reduction and improved performance with aerodynamic-type failures.

Matching algorithm of missile tail flame based on back-propagation neural network

NASA Astrophysics Data System (ADS)

Huang, Da; Huang, Shucai; Tang, Yidong; Zhao, Wei; Cao, Wenhuan

2018-02-01

This work presents a spectral matching algorithm of missile plume detection that based on neural network. The radiation value of the characteristic spectrum of the missile tail flame is taken as the input of the network. The network's structure including the number of nodes and layers is determined according to the number of characteristic spectral bands and missile types. We can get the network weight matrixes and threshold vectors through training the network using training samples, and we can determine the performance of the network through testing the network using the test samples. A small amount of data cause the network has the advantages of simple structure and practicality. Network structure composed of weight matrix and threshold vector can complete task of spectrum matching without large database support. Network can achieve real-time requirements with a small quantity of data. Experiment results show that the algorithm has the ability to match the precise spectrum and strong robustness.

Delivering heparin-binding insulin-like growth factor 1 with self-assembling peptide hydrogels.

PubMed

Florine, Emily M; Miller, Rachel E; Liebesny, Paul H; Mroszczyk, Keri A; Lee, Richard T; Patwari, Parth; Grodzinsky, Alan J

2015-02-01

Heparin-binding insulin-like growth factor 1 (HB-IGF-1) is a fusion protein of IGF-1 with the HB domain of heparin-binding epidermal growth factor-like growth factor. A single dose of HB-IGF-1 has been shown to bind specifically to cartilage and to promote sustained upregulation of proteoglycan synthesis in cartilage explants. Achieving strong integration between native cartilage and tissue-engineered cartilage remains challenging. We hypothesize that if a growth factor delivered by the tissue engineering scaffold could stimulate enhanced matrix synthesis by both the cells within the scaffold and the adjacent native cartilage, integration could be enhanced. In this work, we investigated methods for adsorbing HB-IGF-1 to self-assembling peptide hydrogels to deliver the growth factor to encapsulated chondrocytes and cartilage explants cultured with growth factor-loaded hydrogels. We tested multiple methods for adsorbing HB-IGF-1 in self-assembling peptide hydrogels, including adsorption prior to peptide assembly, following peptide assembly, and with/without heparan sulfate (HS, a potential linker between peptide molecules and HB-IGF-1). We found that HB-IGF-1 and HS were retained in the peptide for all tested conditions. A subset of these conditions was then studied for their ability to stimulate increased matrix production by gel-encapsulated chondrocytes and by chondrocytes within adjacent native cartilage. Adsorbing HB-IGF-1 or IGF-1 prior to peptide assembly was found to stimulate increased sulfated glycosaminoglycan per DNA and hydroxyproline content of chondrocyte-seeded hydrogels compared with basal controls at day 10. Cartilage explants cultured adjacent to functionalized hydrogels had increased proteoglycan synthesis at day 10 when HB-IGF-1 was adsorbed, but not IGF-1. We conclude that delivery of HB-IGF-1 to focal defects in cartilage using self-assembling peptide hydrogels is a promising technique that could aid cartilage repair via enhanced matrix production and integration with native tissue.

Robust outer synchronization between two nonlinear complex networks with parametric disturbances and mixed time-varying delays

NASA Astrophysics Data System (ADS)

Zhang, Chuan; Wang, Xingyuan; Luo, Chao; Li, Junqiu; Wang, Chunpeng

2018-03-01

In this paper, we focus on the robust outer synchronization problem between two nonlinear complex networks with parametric disturbances and mixed time-varying delays. Firstly, a general complex network model is proposed. Besides the nonlinear couplings, the network model in this paper can possess parametric disturbances, internal time-varying delay, discrete time-varying delay and distributed time-varying delay. Then, according to the robust control strategy, linear matrix inequality and Lyapunov stability theory, several outer synchronization protocols are strictly derived. Simple linear matrix controllers are designed to driver the response network synchronize to the drive network. Additionally, our results can be applied on the complex networks without parametric disturbances. Finally, by utilizing the delayed Lorenz chaotic system as the dynamics of all nodes, simulation examples are given to demonstrate the effectiveness of our theoretical results.

Crack Opening Displacement Behavior in Ceramic Matrix Composites

NASA Technical Reports Server (NTRS)

Sevener, Kathy; Tracy, Jared; Chen, Zhe; Daly, Sam; Kiser, Doug

2017-01-01

Ceramic Matrix Composites (CMC) modeling and life prediction strongly depend on oxidation, and therefore require a thorough understanding of when matrix cracks occur, the extent of cracking for given conditions (time-temperature-environment-stress), and the interactions of matrix cracks with fibers and interfaces. In this work, the evolution of matrix cracks in a melt-infiltrated Silicon Carbide/Silicon Carbide (SiC/SiC) CMC under uniaxial tension was examined using scanning electron microscopy (SEM) combined with digital image correlation (DIC) and manual crack opening displacement (COD) measurements. Strain relaxation due to matrix cracking, the relationship between COD's and applied stress, and damage evolution at stresses below the proportional limit were assessed. Direct experimental observation of strain relaxation adjacent to regions of matrix cracking is presented and discussed. Additionally, crack openings were found to increase linearly with increasing applied stress, and no crack was found to pass fully through the gage cross-section. This observation is discussed in the context of the assumption of through-cracks for all loading conditions and fiber architectures in oxidation modeling. Finally, the combination of SEM with DIC is demonstrated throughout to be a powerful means for damage identification and quantification in CMC's at stresses well below the proportional limit.

Investigation of a SiC/Ti-24Al-11Nb composite

NASA Technical Reports Server (NTRS)

Brindley, P. K.; Bartolotta, P. A.; Klima, S. J.

1988-01-01

A summary of ongoing research on the characterization of a continuous fiber reinforced SiC/Ti-24Al-11Nb (at percent) composite is presented. The powder metallurgy fabrication technique is described as are the nondestructive evaluation results of the as-fabricated composite plates. Tensile properties of the SiC fiber, the matrix material, and the 0-deg SiC/Ti-24Al-11Nb composite (fibers oriented unidirectionally, parallel to the loading axis) from room temperature to 1100 C are presented and discussed with regard to the resultant fractography. The as-fabricated fiber-matrix interface has been examined by scanning transmission electron microscopy and the compounds present in the reaction zone have been identified. Fiber-matrix interaction and stability of the matrix near the fiber is characterized at 815, 985, and 1200 C from 1 to 500 hr. Measurements of the fiber-matrix reaction, the loss of C-rich coating from the surface of the SiC fiber, and the growth of the Beta depleted zone in the matrix adjacent to the fiber are presented. These data and the difference in coefficient of thermal expansion between the fiber and the matrix are discussed in terms of their likely effects on mechanical properties.

Prediction of U-Mo dispersion nuclear fuels with Al-Si alloy using artificial neural network

DOE Office of Scientific and Technical Information (OSTI.GOV)

Susmikanti, Mike, E-mail: mike@batan.go.id; Sulistyo, Jos, E-mail: soj@batan.go.id

2014-09-30

Dispersion nuclear fuels, consisting of U-Mo particles dispersed in an Al-Si matrix, are being developed as fuel for research reactors. The equilibrium relationship for a mixture component can be expressed in the phase diagram. It is important to analyze whether a mixture component is in equilibrium phase or another phase. The purpose of this research it is needed to built the model of the phase diagram, so the mixture component is in the stable or melting condition. Artificial neural network (ANN) is a modeling tool for processes involving multivariable non-linear relationships. The objective of the present work is to developmore » code based on artificial neural network models of system equilibrium relationship of U-Mo in Al-Si matrix. This model can be used for prediction of type of resulting mixture, and whether the point is on the equilibrium phase or in another phase region. The equilibrium model data for prediction and modeling generated from experimentally data. The artificial neural network with resilient backpropagation method was chosen to predict the dispersion of nuclear fuels U-Mo in Al-Si matrix. This developed code was built with some function in MATLAB. For simulations using ANN, the Levenberg-Marquardt method was also used for optimization. The artificial neural network is able to predict the equilibrium phase or in the phase region. The develop code based on artificial neural network models was built, for analyze equilibrium relationship of U-Mo in Al-Si matrix.« less

A novel protection scheme for a hybrid WDM/TDM PON

NASA Astrophysics Data System (ADS)

Chen, Jiajia; Wosinska, Lena; He, Sailing

2007-11-01

This paper proposes a novel protection scheme based on the cyclic property of an array waveguide grating (AWG) and neighboring connection pattern between two adjacent optical network units (ONUs) for the hybrid WDM/TDM passive optical networks (PONs). Our scheme uses 50% fewer wavelengths while offering one order of magnitude better connection availability than the existing scheme.

Analysis of world terror networks from the reduced Google matrix of Wikipedia

NASA Astrophysics Data System (ADS)

El Zant, Samer; Frahm, Klaus M.; Jaffrès-Runser, Katia; Shepelyansky, Dima L.

2018-01-01

We apply the reduced Google matrix method to analyze interactions between 95 terrorist groups and determine their relationships and influence on 64 world countries. This is done on the basis of the Google matrix of the English Wikipedia (2017) composed of 5 416 537 articles which accumulate a great part of global human knowledge. The reduced Google matrix takes into account the direct and hidden links between a selection of 159 nodes (articles) appearing due to all paths of a random surfer moving over the whole network. As a result we obtain the network structure of terrorist groups and their relations with selected countries including hidden indirect links. Using the sensitivity of PageRank to a weight variation of specific links we determine the geopolitical sensitivity and influence of specific terrorist groups on world countries. The world maps of the sensitivity of various countries to influence of specific terrorist groups are obtained. We argue that this approach can find useful application for more extensive and detailed data bases analysis.

Electronic device aspects of neural network memories

NASA Technical Reports Server (NTRS)

Lambe, J.; Moopenn, A.; Thakoor, A. P.

1985-01-01

The basic issues related to the electronic implementation of the neural network model (NNM) for content addressable memories are examined. A brief introduction to the principles of the NNM is followed by an analysis of the information storage of the neural network in the form of a binary connection matrix and the recall capability of such matrix memories based on a hardware simulation study. In addition, materials and device architecture issues involved in the future realization of such networks in VLSI-compatible ultrahigh-density memories are considered. A possible space application of such devices would be in the area of large-scale information storage without mechanical devices.

Stability and stabilisation of a class of networked dynamic systems

NASA Astrophysics Data System (ADS)

Liu, H. B.; Wang, D. Q.

2018-04-01

We investigate the stability and stabilisation of a linear time invariant networked heterogeneous system with arbitrarily connected subsystems. A new linear matrix inequality based sufficient and necessary condition for the stability is derived, based on which the stabilisation is provided. The obtained conditions efficiently utilise the block-diagonal characteristic of system parameter matrices and the sparseness of subsystem connection matrix. Moreover, a sufficient condition only dependent on each individual subsystem is also presented for the stabilisation of the networked systems with a large scale. Numerical simulations show that these conditions are computationally valid in the analysis and synthesis of a large-scale networked system.

A Network and Visual Quality Aware N-Screen Content Recommender System Using Joint Matrix Factorization

PubMed Central

Ullah, Farman; Sarwar, Ghulam; Lee, Sungchang

2014-01-01

We propose a network and visual quality aware N-Screen content recommender system. N-Screen provides more ways than ever before to access multimedia content through multiple devices and heterogeneous access networks. The heterogeneity of devices and access networks present new questions of QoS (quality of service) in the realm of user experience with content. We propose, a recommender system that ensures a better visual quality on user's N-screen devices and the efficient utilization of available access network bandwidth with user preferences. The proposed system estimates the available bandwidth and visual quality on users N-Screen devices and integrates it with users preferences and contents genre information to personalize his N-Screen content. The objective is to recommend content that the user's N-Screen device and access network are capable of displaying and streaming with the user preferences that have not been supported in existing systems. Furthermore, we suggest a joint matrix factorization approach to jointly factorize the users rating matrix with the users N-Screen device similarity and program genres similarity. Finally, the experimental results show that we also enhance the prediction and recommendation accuracy, sparsity, and cold start issues. PMID:24982999

Social patterns revealed through random matrix theory

NASA Astrophysics Data System (ADS)

Sarkar, Camellia; Jalan, Sarika

2014-11-01

Despite the tremendous advancements in the field of network theory, very few studies have taken weights in the interactions into consideration that emerge naturally in all real-world systems. Using random matrix analysis of a weighted social network, we demonstrate the profound impact of weights in interactions on emerging structural properties. The analysis reveals that randomness existing in particular time frame affects the decisions of individuals rendering them more freedom of choice in situations of financial security. While the structural organization of networks remains the same throughout all datasets, random matrix theory provides insight into the interaction pattern of individuals of the society in situations of crisis. It has also been contemplated that individual accountability in terms of weighted interactions remains as a key to success unless segregation of tasks comes into play.

Geometry in Biomimetic Network: Double Gyroid to Pseudo-Single Gyroid in Nanohybrid Materials

NASA Astrophysics Data System (ADS)

Hsueh, Han-Yu; Ho, Rong-Ming; Hung, Yu-Chueh; Ling, Yi-Chun; Hasegawa, Hirokazu

2013-03-01

Biological systems have developed delicately arranged micro- and architectures to produce striking optical effects since millions of years ago. Inspired by the textures of butterfly wings with single gyroid (SG) structure, herein, we aim to fabricate biocompatible and robust materials with SG-like structure in nanometer size so as to give new materials with unprecedented optical properties for applications. Biommicking from the biological photonic structures of butterfly wings, a double gyroid (DG) structure in nanometer size is obtained from the self-assembly of polystyrene-b-poly(L-lactide) (PS-PLLA). To acquire robust backbone networks, inorganic networks in polymer matrix are fabricated by using the hydrolyzed PS-PLLA with DG structure as a template for sol-gel reaction. Owing to the soft polymer matrix, two co-continuous inorganic networks embedded in the polymer matrix can be rearranged by thermal annealing at temperature above the glass transition of the polymer. Consequently, the rearrangement of these inorganic networks leads the formation of SG-like structure possessing unique nanohybrids with ordered texture. This unique nanomaterials with SG-like structure is referred as a pseudo-SG (p-SG) nanohybrids.

Neural network simulation of the atmospheric point spread function for the adjacency effect research

NASA Astrophysics Data System (ADS)

Ma, Xiaoshan; Wang, Haidong; Li, Ligang; Yang, Zhen; Meng, Xin

2016-10-01

Adjacency effect could be regarded as the convolution of the atmospheric point spread function (PSF) and the surface leaving radiance. Monte Carlo is a common method to simulate the atmospheric PSF. But it can't obtain analytic expression and the meaningful results can be only acquired by statistical analysis of millions of data. A backward Monte Carlo algorithm was employed to simulate photon emitting and propagating in the atmosphere under different conditions. The PSF was determined by recording the photon-receiving numbers in fixed bin at different position. A multilayer feed-forward neural network with a single hidden layer was designed to learn the relationship between the PSF's and the input condition parameters. The neural network used the back-propagation learning rule for training. Its input parameters involved atmosphere condition, spectrum range, observing geometry. The outputs of the network were photon-receiving numbers in the corresponding bin. Because the output units were too many to be allowed by neural network, the large network was divided into a collection of smaller ones. These small networks could be ran simultaneously on many workstations and/or PCs to speed up the training. It is important to note that the simulated PSF's by Monte Carlo technique in non-nadir viewing angles are more complicated than that in nadir conditions which brings difficulties in the design of the neural network. The results obtained show that the neural network approach could be very useful to compute the atmospheric PSF based on the simulated data generated by Monte Carlo method.

Matrix stiffness modulates formation and activity of neuronal networks of controlled architectures.

PubMed

Lantoine, Joséphine; Grevesse, Thomas; Villers, Agnès; Delhaye, Geoffrey; Mestdagh, Camille; Versaevel, Marie; Mohammed, Danahe; Bruyère, Céline; Alaimo, Laura; Lacour, Stéphanie P; Ris, Laurence; Gabriele, Sylvain

2016-05-01

The ability to construct easily in vitro networks of primary neurons organized with imposed topologies is required for neural tissue engineering as well as for the development of neuronal interfaces with desirable characteristics. However, accumulating evidence suggests that the mechanical properties of the culture matrix can modulate important neuronal functions such as growth, extension, branching and activity. Here we designed robust and reproducible laminin-polylysine grid micropatterns on cell culture substrates that have similar biochemical properties but a 100-fold difference in Young's modulus to investigate the role of the matrix rigidity on the formation and activity of cortical neuronal networks. We found that cell bodies of primary cortical neurons gradually accumulate in circular islands, whereas axonal extensions spread on linear tracks to connect circular islands. Our findings indicate that migration of cortical neurons is enhanced on soft substrates, leading to a faster formation of neuronal networks. Furthermore, the pre-synaptic density was two times higher on stiff substrates and consistently the number of action potentials and miniature synaptic currents was enhanced on stiff substrates. Taken together, our results provide compelling evidence to indicate that matrix stiffness is a key parameter to modulate the growth dynamics, synaptic density and electrophysiological activity of cortical neuronal networks, thus providing useful information on scaffold design for neural tissue engineering. Copyright © 2016 Elsevier Ltd. All rights reserved.

Drug release control and system understanding of sucrose esters matrix tablets by artificial neural networks.

PubMed

Chansanroj, Krisanin; Petrović, Jelena; Ibrić, Svetlana; Betz, Gabriele

2011-10-09

Artificial neural networks (ANNs) were applied for system understanding and prediction of drug release properties from direct compacted matrix tablets using sucrose esters (SEs) as matrix-forming agents for controlled release of a highly water soluble drug, metoprolol tartrate. Complexity of the system was presented through the effects of SE concentration and tablet porosity at various hydrophilic-lipophilic balance (HLB) values of SEs ranging from 0 to 16. Both effects contributed to release behaviors especially in the system containing hydrophilic SEs where swelling phenomena occurred. A self-organizing map neural network (SOM) was applied for visualizing interrelation among the variables and multilayer perceptron neural networks (MLPs) were employed to generalize the system and predict the drug release properties based on HLB value and concentration of SEs and tablet properties, i.e., tablet porosity, volume and tensile strength. Accurate prediction was obtained after systematically optimizing network performance based on learning algorithm of MLP. Drug release was mainly attributed to the effects of SEs, tablet volume and tensile strength in multi-dimensional interrelation whereas tablet porosity gave a small impact. Ability of system generalization and accurate prediction of the drug release properties proves the validity of SOM and MLPs for the formulation modeling of direct compacted matrix tablets containing controlled release agents of different material properties. Copyright © 2011 Elsevier B.V. All rights reserved.

Methods for absorbing neutrons

DOEpatents

Guillen, Donna P [Idaho Falls, ID; Longhurst, Glen R [Idaho Falls, ID; Porter, Douglas L [Idaho Falls, ID; Parry, James R [Idaho Falls, ID

2012-07-24

A conduction cooled neutron absorber may include a metal matrix composite that comprises a metal having a thermal neutron cross-section of at least about 50 barns and a metal having a thermal conductivity of at least about 1 W/cmK. Apparatus for providing a neutron flux having a high fast-to-thermal neutron ratio may include a source of neutrons that produces fast neutrons and thermal neutrons. A neutron absorber positioned adjacent the neutron source absorbs at least some of the thermal neutrons so that a region adjacent the neutron absorber has a fast-to-thermal neutron ratio of at least about 15. A coolant in thermal contact with the neutron absorber removes heat from the neutron absorber.

Differentially-charged and sequentially-switched square-wave pulse forming network

DOEpatents

North, George G. [Stockton, CA; Vogilin, George E. [Livermore, CA

1980-04-01

A pulse forming network for delivering a high-energy square-wave pulse to a load, including a series of inductive-capacitive sections wherein the capacitors are differentially charged higher further from the load. Each charged capacitor is isolated from adjacent sections and the load by means of a normally open switch at the output of each section. The switch between the load and the closest section to the load is closed to begin discharge of the capacitor in that section into the load. During discharge of each capacitor, the voltage thereacross falls to a predetermined potential with respect to the potential across the capacitor in the next adjacent section further from the load. When this potential is reached, it is used to close the switch in the adjacent section further from the load and thereby apply the charge in that section to the load through the adjacent section toward the load. Each successive section further from the load is sequentially switched in this manner to continuously and evenly supply energy to the load over the period of the pulse, with the differentially charged capacitors providing higher potentials away from the load to compensate for the voltage drop across the resistance of each inductor. This arrangement is low in cost and yet provides a high-energy pulse in an acceptable square-wave form.

Differentially-charged and sequentially-switched square-wave pulse forming network

DOEpatents

North, G.G.; Vogilin, G.E.

1980-04-01

Disclosed is a pulse forming network for delivering a high-energy square-wave pulse to a load, including a series of inductive-capacitive sections wherein the capacitors are differentially charged higher further from the load. Each charged capacitor is isolated from adjacent sections and the load by means of a normally open switch at the output of each section. The switch between the load and the closest section to the load is closed to begin discharge of the capacitor in that section into the load. During discharge of each capacitor, the voltage thereacross falls to a predetermined potential with respect to the potential across the capacitor in the next adjacent section further from the load. When this potential is reached, it is used to close the switch in the adjacent section further from the load and thereby apply the charge in that section to the load through the adjacent section toward the load. Each successive section further from the load is sequentially switched in this manner to continuously and evenly supply energy to the load over the period of the pulse, with the differentially charged capacitors providing higher potentials away from the load to compensate for the voltage drop across the resistance of each inductor. This arrangement is low in cost and yet provides a high-energy pulse in an acceptable square-wave form. 5 figs.

Association of matrix metalloproteinase inducer (EMMPRIN) with the expression of matrix metalloproteinases-1, -2 and -9 during periapical lesion development.

PubMed

Sousa, Natália Guimarães Kalatzis; Cardoso, Cristina Ribeiro de Barros; Silva, João Satana da; Kuga, Milton Carlos; Tanomaru-Filho, Mário; Faria, Gisele

2014-09-01

To evaluate the expression of matrix metalloproteinase inducer (EMMPRIN) and its correlation with the expression of matrix metalloproteinases (MMPs)-1, -2 and -9 during the development of periapical lesion in mice. Periapical lesions were induced in the lower first molars of mice and after 7, 14, 21 and 42 days the mandibles were removed. The periapical lesions were measured by micro-computed tomography. The expression of EMMPRIN, MMPs-1, -2, and -9 genes were determined by real-time RT-PCR. The location and expression of EMMPRIN and MMPs were evaluated by immunohistochemistry. At 14 days, the periapical lesion area was higher than at 7 days. At 21 and 42 days no statistically significant bone loss was observed in comparison to 14 days. The control group showed discrete and occasional EMMPRIM, MMP-1, -2 and -9 immunostaining in the periodontal ligament fibroblasts. At 7, 14, 21 and 42 days intense immunoexpression was observed for EMMPRIN, MMPs-1, -2 and -9 in the region adjacent to the apical foramen. The EMMPRIN immunoexpression was higher at 7, 14, 21 and 42 days compared with the control. There was a positive correlation between gene expression of EMMPRIN and MMPs in the active phase of periapical lesion development. There is a high expression of EMMPRIM mainly by the inflammatory infiltrate in the region adjacent to the apical foramen during periapical lesion development. Furthermore, the positive correlation with MMP-1, -2, and -9 during the first days after periapical lesion induction indicates that EMMPRIM may be involved in the active phase of periapical lesions development. Copyright © 2014 Elsevier Ltd. All rights reserved.

Internal damping due to dislocation movements induced by thermal expansion mismatch between matrix and particles in metal matrix composites. [Al/SiC

DOE Office of Scientific and Technical Information (OSTI.GOV)

Girand, C.; Lormand, G.; Fougeres, R.

In metal matrix composites (MMCs), the mechanical 1 of the reinforcement-matrix interface is an important parameter because it governs the load transfer from matrix to particles, from which the mechanical properties of these materials are derived. Therefore, it would be useful to set out an experimental method able to characterize the interface and the adjacent matrix behaviors. Thus, a study has been undertaken by means of internal damping (I.D.) measurements, which are well known to be very sensitive for studying irreversible displacements at the atomic scale. More especially, this investigation is based on the fact that, during cooling of MMC's,more » stress concentrations originating from differences in coefficients of thermal expansion (C.T.E.) of matrix and particles should induce dislocation movements in the matrix surrounding the reinforcement; that is, local microplastic strains occur. Therefore, during I.D. measurements vs temperature these movements should contribute to MMCs I.D. in a process similar to those involved around first order phase transitions in solids. The aim of this paper is to present, in the case of Al/SiC particulate composites, new developments of this approach that has previously led to promising results in the case of Al-Si alloys.« less

Distribution of the Red Imported Ant, Solenopsis invicta, in Road and Powerline Habitats

Treesearch

Judith H. Stiles; Robert H. Jones

1998-01-01

For early-successional species, road and powerline cuts through forests provide refugia and source populations for invading adjacent forest gaps. Within an 800 km2 forest matrix in South Carolina, we determined if width disturbance frequency or linear features of road and powerline cuts influenced the mound distribution of the red imported fire...

A reliability analysis tool for SpaceWire network

NASA Astrophysics Data System (ADS)

Zhou, Qiang; Zhu, Longjiang; Fei, Haidong; Wang, Xingyou

2017-04-01

A SpaceWire is a standard for on-board satellite networks as the basis for future data-handling architectures. It is becoming more and more popular in space applications due to its technical advantages, including reliability, low power and fault protection, etc. High reliability is the vital issue for spacecraft. Therefore, it is very important to analyze and improve the reliability performance of the SpaceWire network. This paper deals with the problem of reliability modeling and analysis with SpaceWire network. According to the function division of distributed network, a reliability analysis method based on a task is proposed, the reliability analysis of every task can lead to the system reliability matrix, the reliability result of the network system can be deduced by integrating these entire reliability indexes in the matrix. With the method, we develop a reliability analysis tool for SpaceWire Network based on VC, where the computation schemes for reliability matrix and the multi-path-task reliability are also implemented. By using this tool, we analyze several cases on typical architectures. And the analytic results indicate that redundancy architecture has better reliability performance than basic one. In practical, the dual redundancy scheme has been adopted for some key unit, to improve the reliability index of the system or task. Finally, this reliability analysis tool will has a directive influence on both task division and topology selection in the phase of SpaceWire network system design.

Analytic tools for investigating the structure of network reliability measures with regard to observation correlations

NASA Astrophysics Data System (ADS)

Prószyński, W.; Kwaśniak, M.

2018-03-01

A global measure of observation correlations in a network is proposed, together with the auxiliary indices related to non-diagonal elements of the correlation matrix. Based on the above global measure, a specific representation of the correlation matrix is presented, being the result of rigorously proven theorem formulated within the present research. According to the theorem, each positive definite correlation matrix can be expressed by a scale factor and a so-called internal weight matrix. Such a representation made it possible to investigate the structure of the basic reliability measures with regard to observation correlations. Numerical examples carried out for two test networks illustrate the structure of those measures that proved to be dependent on global correlation index. Also, the levels of global correlation are proposed. It is shown that one can readily find an approximate value of the global correlation index, and hence the correlation level, for the expected values of auxiliary indices being the only knowledge about a correlation matrix of interest. The paper is an extended continuation of the previous study of authors that was confined to the elementary case termed uniform correlation. The extension covers arbitrary correlation matrices and a structure of correlation effect.

Analysis of a Data Communication Network’s Performance under Varying Retransmission Disciplines

DTIC Science & Technology

1990-09-01

The routing table is updated using delay information transmitted via congestion/routing up- date packets ( CRUP ) or through delay measurement...previous delay, plus or minus a threshold value, a CRUP is generated and flooded over the network. Upon receipt of a CRUP the ROUTING function up- dates...DDN topology is very large, accounting for the time delay for the full network to be updated, whereas adjacent PSN’s receive CRUP packets virtually

Biphasic response of cell invasion to matrix stiffness in 3-dimensional biopolymer networks

PubMed Central

Lang, Nadine R.; Skodzek, Kai; Hurst, Sebastian; Mainka, Astrid; Steinwachs, Julian; Schneider, Julia; Aifantis, Katerina E.; Fabry, Ben

2015-01-01

When cells come in contact with an adhesive matrix, they begin to spread and migrate with a speed that depends on the stiffness of the extracellular matrix. On a flat surface, migration speed decreases with matrix stiffness mainly due to an increased stability of focal adhesions. In a 3-dimensional (3D) environment, cell migration is thought to be additionally impaired by the steric hindrance imposed by the surrounding matrix. For porous 3D biopolymer networks such as collagen gels, however, the effect of matrix stiffness on cell migration is difficult to separate from effects of matrix pore size and adhesive ligand density, and is therefore unknown. Here we used glutaraldehyde as a crosslinker to increase the stiffness of self-assembled collagen biopolymer networks independently of collagen concentration or pore size. Breast carcinoma cells were seeded onto the surface of 3D collagen gels, and the invasion depth was measured after 3 days of culture. Cell invasion in gels with pore sizes larger than 5 μm increased with higher gel stiffness, whereas invasion in gels with smaller pores decreased with higher gel stiffness. These data show that 3D cell invasion is enhanced by higher matrix stiffness, opposite to cell behavior in 2D, as long as the pore size does not fall below a critical value where it causes excessive steric hindrance. These findings may be important for optimizing the recellularization of soft tissue implants or for the design of 3D invasion models in cancer research. PMID:25462839

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.

Heat resistant substrates and battery separators made therefrom

NASA Technical Reports Server (NTRS)

Langer, Alois (Inventor); Scala, Luciano C. (Inventor); Ruffing, Charles R. (Inventor)

1976-01-01

A flexible substrate having a caustic resistant support and at least one membrane comprising a solid polymeric matrix containing a network of interconnected pores and interdispersed inorganic filler particles with a ratio of filler: polymer in the polymeric matrix of between about 1:1 to 5:1, is made by coating at least one side of the support with a filler:coating formulation mixture of inorganic filler particles and a caustic resistant, water insoluble polymer dissolved in an organic solvent, and removing the solvent from the mixture to provide a porous network within the polymeric matrix.

Stability and dynamical properties of material flow systems on random networks

NASA Astrophysics Data System (ADS)

Anand, K.; Galla, T.

2009-04-01

The theory of complex networks and of disordered systems is used to study the stability and dynamical properties of a simple model of material flow networks defined on random graphs. In particular we address instabilities that are characteristic of flow networks in economic, ecological and biological systems. Based on results from random matrix theory, we work out the phase diagram of such systems defined on extensively connected random graphs, and study in detail how the choice of control policies and the network structure affects stability. We also present results for more complex topologies of the underlying graph, focussing on finitely connected Erdös-Réyni graphs, Small-World Networks and Barabási-Albert scale-free networks. Results indicate that variability of input-output matrix elements, and random structures of the underlying graph tend to make the system less stable, while fast price dynamics or strong responsiveness to stock accumulation promote stability.

Computing the shape of brain networks using graph filtration and Gromov-Hausdorff metric.

PubMed

Lee, Hyekyoung; Chung, Moo K; Kang, Hyejin; Kim, Boong-Nyun; Lee, Dong Soo

2011-01-01

The difference between networks has been often assessed by the difference of global topological measures such as the clustering coefficient, degree distribution and modularity. In this paper, we introduce a new framework for measuring the network difference using the Gromov-Hausdorff (GH) distance, which is often used in shape analysis. In order to apply the GH distance, we define the shape of the brain network by piecing together the patches of locally connected nearest neighbors using the graph filtration. The shape of the network is then transformed to an algebraic form called the single linkage matrix. The single linkage matrix is subsequently used in measuring network differences using the GH distance. As an illustration, we apply the proposed framework to compare the FDG-PET based functional brain networks out of 24 attention deficit hyperactivity disorder (ADHD) children, 26 autism spectrum disorder (ASD) children and 11 pediatric control subjects.

Functional connectivity analysis in resting state fMRI with echo-state networks and non-metric clustering for network structure recovery

NASA Astrophysics Data System (ADS)

Wismüller, Axel; DSouza, Adora M.; Abidin, Anas Z.; Wang, Xixi; Hobbs, Susan K.; Nagarajan, Mahesh B.

2015-03-01

Echo state networks (ESN) are recurrent neural networks where the hidden layer is replaced with a fixed reservoir of neurons. Unlike feed-forward networks, neuron training in ESN is restricted to the output neurons alone thereby providing a computational advantage. We demonstrate the use of such ESNs in our mutual connectivity analysis (MCA) framework for recovering the primary motor cortex network associated with hand movement from resting state functional MRI (fMRI) data. Such a framework consists of two steps - (1) defining a pair-wise affinity matrix between different pixel time series within the brain to characterize network activity and (2) recovering network components from the affinity matrix with non-metric clustering. Here, ESNs are used to evaluate pair-wise cross-estimation performance between pixel time series to create the affinity matrix, which is subsequently subject to non-metric clustering with the Louvain method. For comparison, the ground truth of the motor cortex network structure is established with a task-based fMRI sequence. Overlap between the primary motor cortex network recovered with our model free MCA approach and the ground truth was measured with the Dice coefficient. Our results show that network recovery with our proposed MCA approach is in close agreement with the ground truth. Such network recovery is achieved without requiring low-pass filtering of the time series ensembles prior to analysis, an fMRI preprocessing step that has courted controversy in recent years. Thus, we conclude our MCA framework can allow recovery and visualization of the underlying functionally connected networks in the brain on resting state fMRI.

How Fast Can Networks Synchronize? A Random Matrix Theory Approach

NASA Astrophysics Data System (ADS)

Timme, Marc; Wolf, Fred; Geisel, Theo

2004-03-01

Pulse-coupled oscillators constitute a paradigmatic class of dynamical systems interacting on networks because they model a variety of biological systems including flashing fireflies and chirping crickets as well as pacemaker cells of the heart and neural networks. Synchronization is one of the most simple and most prevailing kinds of collective dynamics on such networks. Here we study collective synchronization [1] of pulse-coupled oscillators interacting on asymmetric random networks. Using random matrix theory we analytically determine the speed of synchronization in such networks in dependence on the dynamical and network parameters [2]. The speed of synchronization increases with increasing coupling strengths. Surprisingly, however, it stays finite even for infinitely strong interactions. The results indicate that the speed of synchronization is limited by the connectivity of the network. We discuss the relevance of our findings to general equilibration processes on complex networks. [5mm] [1] M. Timme, F. Wolf, T. Geisel, Phys. Rev. Lett. 89:258701 (2002). [2] M. Timme, F. Wolf, T. Geisel, cond-mat/0306512 (2003).

Tracking trade transactions in water resource systems: A node-arc optimization formulation

NASA Astrophysics Data System (ADS)

Erfani, Tohid; Huskova, Ivana; Harou, Julien J.

2013-05-01

We formulate and apply a multicommodity network flow node-arc optimization model capable of tracking trade transactions in complex water resource systems. The model uses a simple node to node network connectivity matrix and does not require preprocessing of all possible flow paths in the network. We compare the proposed node-arc formulation with an existing arc-path (flow path) formulation and explain the advantages and difficulties of both approaches. We verify the proposed formulation model on a hypothetical water distribution network. Results indicate the arc-path model solves the problem with fewer constraints, but the proposed formulation allows using a simple network connectivity matrix which simplifies modeling large or complex networks. The proposed algorithm allows converting existing node-arc hydroeconomic models that broadly represent water trading to ones that also track individual supplier-receiver relationships (trade transactions).

Hazard Monitoring in a Spectrum-Challenged Future: US Department of Transportation Adjacent Band Compatibility Assessment of Interference on High-Precision GNSS Receivers

NASA Astrophysics Data System (ADS)

Blume, F.; Berglund, H. T.

2016-12-01

In 2012 the Federal Communications Commission (FCC) reversed its decision to allow communications company LightSquared to use GPS-adjacent spectrum for a ground based network after testing demonstrated harmful interference to GPS receivers. Now rebranded as Ligado, they have submitted modified application to use a smaller portion of the L-band spectrum at much lower power. Many GPS community stakeholders, including the hazard monitoring and EEW communities remain concerned that Ligado's proposed use could still cause harmful interference, causing signal degradation, real-time positioning errors, and total failure of GNSS hardware in widespread use in hazard monitoring networks. The Department of Transportation (DoT) has conducted hardware tests to determine adjacent-band transmitter power limit criteria that would prevent harmful interference from Ligado's operations. We present preliminary results produced from the data collected by the three UNAVCO receiver types tested: Trimble NetRS, Trimble NetR9, and Septentrio PolaRx5. In the first round of testing, simulated GNSS signals were broadcast in an anechoic chamber (pictured below) while interfering signals are broadcast simultaneously with varying amplitude and frequency. The older GPS-only NetRS receiver showed smaller reductions in SNR at frequencies adjacent to GPS L1 as compared to the other receivers, suggesting narrower L1 filter bandwidth in the RF frontend. The NetR9 showed greater decreases in observed SNR in the 1615 to 1625 MHz range when compared to the other two receivers. This suggests that the NetR9's L1 filter bandwidth has been increased to accommodate GNSS signals. Linearity tests were conducted to better relate SNR measurements between receiver types. The PolaRx5 receiver showed less SNR variation between tracking channels than both Trimble receivers. Our results show the power levels at which adjacent-band interference begins degrading receiver performance and eventually disables tracking. As the demand for spectrum for mobile applications increases, operators of hazard networks may need to consider the impact of RF interference on data quality and continuity. UNAVCO's participation ensures that our high precision GNSS community interests are represented in the future spectrum allocation decisions.

Central Savannah River Area P-16 Professional Development School Network: A Reflective Summary of Four Years of Collaboration.

ERIC Educational Resources Information Center

Cooper, Mary Gendernalik

This article traces the development of the Central Savannah River Area P-16 Professional Development School Network Initiative (PDSNI), which began in 1998 as a collaboration between the Department of Teacher Development at Augusta State University, Georgia, and four adjacent school systems. The collaboration's mission was to cultivate a network…

Random walks with long-range steps generated by functions of Laplacian matrices

NASA Astrophysics Data System (ADS)

Riascos, A. P.; Michelitsch, T. M.; Collet, B. A.; Nowakowski, A. F.; Nicolleau, F. C. G. A.

2018-04-01

In this paper, we explore different Markovian random walk strategies on networks with transition probabilities between nodes defined in terms of functions of the Laplacian matrix. We generalize random walk strategies with local information in the Laplacian matrix, that describes the connections of a network, to a dynamic determined by functions of this matrix. The resulting processes are non-local allowing transitions of the random walker from one node to nodes beyond its nearest neighbors. We find that only two types of Laplacian functions are admissible with distinct behaviors for long-range steps in the infinite network limit: type (i) functions generate Brownian motions, type (ii) functions Lévy flights. For this asymptotic long-range step behavior only the lowest non-vanishing order of the Laplacian function is relevant, namely first order for type (i), and fractional order for type (ii) functions. In the first part, we discuss spectral properties of the Laplacian matrix and a series of relations that are maintained by a particular type of functions that allow to define random walks on any type of undirected connected networks. Once described general properties, we explore characteristics of random walk strategies that emerge from particular cases with functions defined in terms of exponentials, logarithms and powers of the Laplacian as well as relations of these dynamics with non-local strategies like Lévy flights and fractional transport. Finally, we analyze the global capacity of these random walk strategies to explore networks like lattices and trees and different types of random and complex networks.

Random matrix approach to plasmon resonances in the random impedance network model of disordered nanocomposites

NASA Astrophysics Data System (ADS)

Olekhno, N. A.; Beltukov, Y. M.

2018-05-01

Random impedance networks are widely used as a model to describe plasmon resonances in disordered metal-dielectric and other two-component nanocomposites. In the present work, the spectral properties of resonances in random networks are studied within the framework of the random matrix theory. We have shown that the appropriate ensemble of random matrices for the considered problem is the Jacobi ensemble (the MANOVA ensemble). The obtained analytical expressions for the density of states in such resonant networks show a good agreement with the results of numerical simulations in a wide range of metal filling fractions 0

New Measurement for Correlation of Co-evolution Relationship of Subsequences in Protein.

PubMed

Gao, Hongyun; Yu, Xiaoqing; Dou, Yongchao; Wang, Jun

2015-12-01

Many computational tools have been developed to measure the protein residues co-evolution. Most of them only focus on co-evolution for pairwise residues in a protein sequence. However, number of residues participate in co-evolution might be multiple. And some co-evolved residues are clustered in several distinct regions in primary structure. Therefore, the co-evolution among the adjacent residues and the correlation between the distinct regions offer insights into function and evolution of the protein and residues. Subsequence is used to represent the adjacent multiple residues in one distinct region. In the paper, co-evolution relationship in each subsequence is represented by mutual information matrix (MIM). Then, Pearson's correlation coefficient: R value is developed to measure the similarity correlation of two MIMs. MSAs from Catalytic Data Base (Catalytic Site Atlas, CSA) are used for testing. R value characterizes a specific class of residues. In contrast to individual pairwise co-evolved residues, adjacent residues without high individual MI values are found since the co-evolved relationship among them is similar to that among another set of adjacent residues. These subsequences possess some flexibility in the composition of side chains, such as the catalyzed environment.

CD-Based Indices for Link Prediction in Complex Network.

PubMed

Wang, Tao; Wang, Hongjue; Wang, Xiaoxia

2016-01-01

Lots of similarity-based algorithms have been designed to deal with the problem of link prediction in the past decade. In order to improve prediction accuracy, a novel cosine similarity index CD based on distance between nodes and cosine value between vectors is proposed in this paper. Firstly, node coordinate matrix can be obtained by node distances which are different from distance matrix and row vectors of the matrix are regarded as coordinates of nodes. Then, cosine value between node coordinates is used as their similarity index. A local community density index LD is also proposed. Then, a series of CD-based indices include CD-LD-k, CD*LD-k, CD-k and CDI are presented and applied in ten real networks. Experimental results demonstrate the effectiveness of CD-based indices. The effects of network clustering coefficient and assortative coefficient on prediction accuracy of indices are analyzed. CD-LD-k and CD*LD-k can improve prediction accuracy without considering the assortative coefficient of network is negative or positive. According to analysis of relative precision of each method on each network, CD-LD-k and CD*LD-k indices have excellent average performance and robustness. CD and CD-k indices perform better on positive assortative networks than on negative assortative networks. For negative assortative networks, we improve and refine CD index, referred as CDI index, combining the advantages of CD index and evolutionary mechanism of the network model BA. Experimental results reveal that CDI index can increase prediction accuracy of CD on negative assortative networks.

CD-Based Indices for Link Prediction in Complex Network

PubMed Central

Wang, Tao; Wang, Hongjue; Wang, Xiaoxia

2016-01-01

Lots of similarity-based algorithms have been designed to deal with the problem of link prediction in the past decade. In order to improve prediction accuracy, a novel cosine similarity index CD based on distance between nodes and cosine value between vectors is proposed in this paper. Firstly, node coordinate matrix can be obtained by node distances which are different from distance matrix and row vectors of the matrix are regarded as coordinates of nodes. Then, cosine value between node coordinates is used as their similarity index. A local community density index LD is also proposed. Then, a series of CD-based indices include CD-LD-k, CD*LD-k, CD-k and CDI are presented and applied in ten real networks. Experimental results demonstrate the effectiveness of CD-based indices. The effects of network clustering coefficient and assortative coefficient on prediction accuracy of indices are analyzed. CD-LD-k and CD*LD-k can improve prediction accuracy without considering the assortative coefficient of network is negative or positive. According to analysis of relative precision of each method on each network, CD-LD-k and CD*LD-k indices have excellent average performance and robustness. CD and CD-k indices perform better on positive assortative networks than on negative assortative networks. For negative assortative networks, we improve and refine CD index, referred as CDI index, combining the advantages of CD index and evolutionary mechanism of the network model BA. Experimental results reveal that CDI index can increase prediction accuracy of CD on negative assortative networks. PMID:26752405

A general gridding, discretization, and coarsening methodology for modeling flow in porous formations with discrete geological features

NASA Astrophysics Data System (ADS)

Karimi-Fard, M.; Durlofsky, L. J.

2016-10-01

A comprehensive framework for modeling flow in porous media containing thin, discrete features, which could be high-permeability fractures or low-permeability deformation bands, is presented. The key steps of the methodology are mesh generation, fine-grid discretization, upscaling, and coarse-grid discretization. Our specialized gridding technique combines a set of intersecting triangulated surfaces by constructing approximate intersections using existing edges. This procedure creates a conforming mesh of all surfaces, which defines the internal boundaries for the volumetric mesh. The flow equations are discretized on this conforming fine mesh using an optimized two-point flux finite-volume approximation. The resulting discrete model is represented by a list of control-volumes with associated positions and pore-volumes, and a list of cell-to-cell connections with associated transmissibilities. Coarse models are then constructed by the aggregation of fine-grid cells, and the transmissibilities between adjacent coarse cells are obtained using flow-based upscaling procedures. Through appropriate computation of fracture-matrix transmissibilities, a dual-continuum representation is obtained on the coarse scale in regions with connected fracture networks. The fine and coarse discrete models generated within the framework are compatible with any connectivity-based simulator. The applicability of the methodology is illustrated for several two- and three-dimensional examples. In particular, we consider gas production from naturally fractured low-permeability formations, and transport through complex fracture networks. In all cases, highly accurate solutions are obtained with significant model reduction.

Scalable Matrix Algorithms for Interactive Analytics of Very Large Informatics Graphs

DTIC Science & Technology

2017-06-14

information networks. Depending on the situation, these larger networks may not fit on a single machine. Although we considered traditional matrix and graph...collection of information is estimated to average 1 hour per response, including the time for reviewing instructions, searching existing data sources...gathering and maintaining the data needed, and completing and reviewing the collection of information . Send comments regarding this burden estimate or

Fractional quantum mechanics on networks: Long-range dynamics and quantum transport

NASA Astrophysics Data System (ADS)

Riascos, A. P.; Mateos, José L.

2015-11-01

In this paper we study the quantum transport on networks with a temporal evolution governed by the fractional Schrödinger equation. We generalize the dynamics based on continuous-time quantum walks, with transitions to nearest neighbors on the network, to the fractional case that allows long-range displacements. By using the fractional Laplacian matrix of a network, we establish a formalism that combines a long-range dynamics with the quantum superposition of states; this general approach applies to any type of connected undirected networks, including regular, random, and complex networks, and can be implemented from the spectral properties of the Laplacian matrix. We study the fractional dynamics and its capacity to explore the network by means of the transition probability, the average probability of return, and global quantities that characterize the efficiency of this quantum process. As a particular case, we explore analytically these quantities for circulant networks such as rings, interacting cycles, and complete graphs.

Pinning impulsive control algorithms for complex network

NASA Astrophysics Data System (ADS)

Sun, Wen; Lü, Jinhu; Chen, Shihua; Yu, Xinghuo

2014-03-01

In this paper, we further investigate the synchronization of complex dynamical network via pinning control in which a selection of nodes are controlled at discrete times. Different from most existing work, the pinning control algorithms utilize only the impulsive signals at discrete time instants, which may greatly improve the communication channel efficiency and reduce control cost. Two classes of algorithms are designed, one for strongly connected complex network and another for non-strongly connected complex network. It is suggested that in the strongly connected network with suitable coupling strength, a single controller at any one of the network's nodes can always pin the network to its homogeneous solution. In the non-strongly connected case, the location and minimum number of nodes needed to pin the network are determined by the Frobenius normal form of the coupling matrix. In addition, the coupling matrix is not necessarily symmetric or irreducible. Illustrative examples are then given to validate the proposed pinning impulsive control algorithms.

Chaotic, informational and synchronous behaviour of multiplex networks

NASA Astrophysics Data System (ADS)

Baptista, M. S.; Szmoski, R. M.; Pereira, R. F.; Pinto, S. E. De Souza

2016-03-01

The understanding of the relationship between topology and behaviour in interconnected networks would allow to charac- terise and predict behaviour in many real complex networks since both are usually not simultaneously known. Most previous studies have focused on the relationship between topology and synchronisation. In this work, we provide analytical formulas that shows how topology drives complex behaviour: chaos, information, and weak or strong synchronisation; in multiplex net- works with constant Jacobian. We also study this relationship numerically in multiplex networks of Hindmarsh-Rose neurons. Whereas behaviour in the analytically tractable network is a direct but not trivial consequence of the spectra of eigenvalues of the Laplacian matrix, where behaviour may strongly depend on the break of symmetry in the topology of interconnections, in Hindmarsh-Rose neural networks the nonlinear nature of the chemical synapses breaks the elegant mathematical connec- tion between the spectra of eigenvalues of the Laplacian matrix and the behaviour of the network, creating networks whose behaviour strongly depends on the nature (chemical or electrical) of the inter synapses.

Fractional quantum mechanics on networks: Long-range dynamics and quantum transport.

PubMed

Riascos, A P; Mateos, José L

2015-11-01

In this paper we study the quantum transport on networks with a temporal evolution governed by the fractional Schrödinger equation. We generalize the dynamics based on continuous-time quantum walks, with transitions to nearest neighbors on the network, to the fractional case that allows long-range displacements. By using the fractional Laplacian matrix of a network, we establish a formalism that combines a long-range dynamics with the quantum superposition of states; this general approach applies to any type of connected undirected networks, including regular, random, and complex networks, and can be implemented from the spectral properties of the Laplacian matrix. We study the fractional dynamics and its capacity to explore the network by means of the transition probability, the average probability of return, and global quantities that characterize the efficiency of this quantum process. As a particular case, we explore analytically these quantities for circulant networks such as rings, interacting cycles, and complete graphs.

A Random Walk Approach to Query Informative Constraints for Clustering.

PubMed

Abin, Ahmad Ali

2017-08-09

This paper presents a random walk approach to the problem of querying informative constraints for clustering. The proposed method is based on the properties of the commute time, that is the expected time taken for a random walk to travel between two nodes and return, on the adjacency graph of data. Commute time has the nice property of that, the more short paths connect two given nodes in a graph, the more similar those nodes are. Since computing the commute time takes the Laplacian eigenspectrum into account, we use this property in a recursive fashion to query informative constraints for clustering. At each recursion, the proposed method constructs the adjacency graph of data and utilizes the spectral properties of the commute time matrix to bipartition the adjacency graph. Thereafter, the proposed method benefits from the commute times distance on graph to query informative constraints between partitions. This process iterates for each partition until the stop condition becomes true. Experiments on real-world data show the efficiency of the proposed method for constraints selection.

Hydrocarbons in sediments along a tropical estuary-shelf transition area: Sources and spatial distribution.

PubMed

Maciel, Daniele Claudino; de Souza, José Roberto Botelho; Taniguchi, Satie; Bícego, Márcia Caruso; Schettini, Carlos Augusto França; Zanardi-Lamardo, Eliete

2016-12-15

Estuaries generally act as sediment traps and may retain a range of contaminants associated to this matrix. Aliphatic hydrocarbons (AHs) were investigated in Capibaribe Estuarine System and adjacent shelf, Northeast of Brazil, to evaluate the contamination and to better understand its functionality related to the coast. Fourteen sediment samples were analyzed, using gas chromatography with flame ionization detection. Total AHs concentrations ranged from 7.5 to 190.3μgg -1 and n-alkanes ranged from below detection limit (

The effect of rigid fixation on growth of the neurocranium.

PubMed

Wong, L; Dufresne, C R; Richtsmeier, J T; Manson, P N

1991-09-01

The effects on skull growth of plating the coronal suture and frontal bone were studied in New Zealand White rabbits. Three-dimensional coordinate landmarks were digitized and analyzed to determine the differences in form between operated and unoperated animals using Euclidian distance matrix analysis. This method compares sets of interlandmark distances in three dimensions and was used to demonstrate changes induced by plating. We interpret these changes in morphology to be the result of differences in growth between the operated and unoperated groups. Periosteal elevation alone (n = 6) resulted in a minimal local growth increase. Coronal suture plating (n = 8) resulted in local growth restriction with contralateral and adjacent size increases. Frontal bone plating (n = 6) without crossing a suture line also resulted in local growth restriction and adjacent bone size increases. The timing of intervention in relation to the completion of bone growth may explain the magnitude of clinically apparent effects. Changes in bones adjacent to those directly manipulated may be an attempt to maintain a normal skull volume.

Sparse representation of whole-brain fMRI signals for identification of functional networks.

PubMed

Lv, Jinglei; Jiang, Xi; Li, Xiang; Zhu, Dajiang; Chen, Hanbo; Zhang, Tuo; Zhang, Shu; Hu, Xintao; Han, Junwei; Huang, Heng; Zhang, Jing; Guo, Lei; Liu, Tianming

2015-02-01

There have been several recent studies that used sparse representation for fMRI signal analysis and activation detection based on the assumption that each voxel's fMRI signal is linearly composed of sparse components. Previous studies have employed sparse coding to model functional networks in various modalities and scales. These prior contributions inspired the exploration of whether/how sparse representation can be used to identify functional networks in a voxel-wise way and on the whole brain scale. This paper presents a novel, alternative methodology of identifying multiple functional networks via sparse representation of whole-brain task-based fMRI signals. Our basic idea is that all fMRI signals within the whole brain of one subject are aggregated into a big data matrix, which is then factorized into an over-complete dictionary basis matrix and a reference weight matrix via an effective online dictionary learning algorithm. Our extensive experimental results have shown that this novel methodology can uncover multiple functional networks that can be well characterized and interpreted in spatial, temporal and frequency domains based on current brain science knowledge. Importantly, these well-characterized functional network components are quite reproducible in different brains. In general, our methods offer a novel, effective and unified solution to multiple fMRI data analysis tasks including activation detection, de-activation detection, and functional network identification. Copyright © 2014 Elsevier B.V. All rights reserved.

Identification of a Novel TGF-β-Binding Site in the Zona Pellucida C-terminal (ZP-C) Domain of TGF-β-Receptor-3 (TGFR-3)

PubMed Central

Diestel, Uschi; Resch, Marcus; Meinhardt, Kathrin; Weiler, Sigrid; Hellmann, Tina V.; Mueller, Thomas D.; Nickel, Joachim; Eichler, Jutta; Muller, Yves A.

2013-01-01

The zona pellucida (ZP) domain is present in extracellular proteins such as the zona pellucida proteins and tectorins and participates in the formation of polymeric protein networks. However, the ZP domain also occurs in the cytokine signaling co-receptor transforming growth factor β (TGF-β) receptor type 3 (TGFR-3, also known as betaglycan) where it contributes to cytokine ligand recognition. Currently it is unclear how the ZP domain architecture enables this dual functionality. Here, we identify a novel major TGF-β-binding site in the FG loop of the C-terminal subdomain of the murine TGFR-3 ZP domain (ZP-C) using protein crystallography, limited proteolysis experiments, surface plasmon resonance measurements and synthetic peptides. In the murine 2.7 Å crystal structure that we are presenting here, the FG-loop is disordered, however, well-ordered in a recently reported homologous rat ZP-C structure. Surprisingly, the adjacent external hydrophobic patch (EHP) segment is registered differently in the rat and murine structures suggesting that this segment only loosely associates with the remaining ZP-C fold. Such a flexible and temporarily-modulated association of the EHP segment with the ZP domain has been proposed to control the polymerization of ZP domain-containing proteins. Our findings suggest that this flexibility also extends to the ZP domain of TGFR-3 and might facilitate co-receptor ligand interaction and presentation via the adjacent FG-loop. This hints that a similar C-terminal region of the ZP domain architecture possibly regulates both the polymerization of extracellular matrix proteins and cytokine ligand recognition of TGFR-3. PMID:23826237

Evaluation of matrix metalloproteinase-9 expressions in nasopharyngeal carcinoma patients

NASA Astrophysics Data System (ADS)

Farhat; Asnir, R. A.; Yudhistira, A.; Daulay, E. R.; Puspitasari, D.; Yulius, S.

2018-03-01

Nasopharyngeal carcinoma (NPC) is one of head and neck cancer with a poor prognosis because of the position of the tumor adjacent to the skull base and vital structures. Degradation of extracellular matrix that will cause tumor cells to invade surrounding tissues, vascular or lymphatic vessels. One that plays a role in the extracellular matrix degradation process is matrix metalloproteinase-9 (MMP-9). MMP-9 plays a role in tumor invasion process, metastasis and induction of tumor tissue vascularization. To determine the expression of MMP-9 in patients with nasopharyngeal carcinoma, a descriptive study was conducted by examining immunohistochemistry MMP-9 in 30 NPC tissues that had never received radiotherapy, chemotherapy or combination. Frequency distribution of NPC patient mostly in the age group 41-50 years old and 51-60 years were nine people (30.0%); men (73.3%) and non-keratinizing squamous cell carcinoma (53.3%) histopathology type. The overexpression of MMP-9 in patients with nasopharyngeal carcinoma were mostly found in advance stage.

Combined heat and mass transfer device for improving separation process

DOEpatents

Tran, Thanh Nhon

1999-01-01

A two-phase small channel heat exchange matrix simultaneously provides for heat transfer and mass transfer between the liquid and vapor phases of a multi-component mixture at a single, predetermined location within a separation column, significantly improving the thermodynamic efficiency of the separation process. The small channel heat exchange matrix is composed of a series of channels having a hydraulic diameter no greater than 5.0 millimeters for conducting a two-phase coolant. In operation, the matrix provides the liquid-vapor contacting surfaces within the separation column, such that heat and mass are transferred simultaneously between the liquid and vapor phases. The two-phase coolant allows for a uniform heat transfer coefficient to be maintained along the length of the channels and across the surface of the matrix. Preferably, a perforated, concave sheet connects each channel to an adjacent channel to facilitate the flow of the liquid and vapor phases within the column and to increase the liquid-vapor contacting surface area.

Combined heat and mass transfer device for improving separation process

DOEpatents

Tran, T.N.

1999-08-24

A two-phase small channel heat exchange matrix simultaneously provides for heat transfer and mass transfer between the liquid and vapor phases of a multi-component mixture at a single, predetermined location within a separation column, significantly improving the thermodynamic efficiency of the separation process. The small channel heat exchange matrix is composed of a series of channels having a hydraulic diameter no greater than 5.0 millimeters for conducting a two-phase coolant. In operation, the matrix provides the liquid-vapor contacting surfaces within the separation column, such that heat and mass are transferred simultaneously between the liquid and vapor phases. The two-phase coolant allows for a uniform heat transfer coefficient to be maintained along the length of the channels and across the surface of the matrix. Preferably, a perforated, concave sheet connects each channel to an adjacent channel to facilitate the flow of the liquid and vapor phases within the column and to increase the liquid-vapor contacting surface area. 12 figs.

Multi-Target Angle Tracking Algorithm for Bistatic MIMO Radar Based on the Elements of the Covariance Matrix

PubMed Central

Zhang, Zhengyan; Zhang, Jianyun; Zhou, Qingsong; Li, Xiaobo

2018-01-01

In this paper, we consider the problem of tracking the direction of arrivals (DOA) and the direction of departure (DOD) of multiple targets for bistatic multiple-input multiple-output (MIMO) radar. A high-precision tracking algorithm for target angle is proposed. First, the linear relationship between the covariance matrix difference and the angle difference of the adjacent moment was obtained through three approximate relations. Then, the proposed algorithm obtained the relationship between the elements in the covariance matrix difference. On this basis, the performance of the algorithm was improved by averaging the covariance matrix element. Finally, the least square method was used to estimate the DOD and DOA. The algorithm realized the automatic correlation of the angle and provided better performance when compared with the adaptive asymmetric joint diagonalization (AAJD) algorithm. The simulation results demonstrated the effectiveness of the proposed algorithm. The algorithm provides the technical support for the practical application of MIMO radar. PMID:29518957

Multi-Target Angle Tracking Algorithm for Bistatic Multiple-Input Multiple-Output (MIMO) Radar Based on the Elements of the Covariance Matrix.

PubMed

Zhang, Zhengyan; Zhang, Jianyun; Zhou, Qingsong; Li, Xiaobo

2018-03-07

In this paper, we consider the problem of tracking the direction of arrivals (DOA) and the direction of departure (DOD) of multiple targets for bistatic multiple-input multiple-output (MIMO) radar. A high-precision tracking algorithm for target angle is proposed. First, the linear relationship between the covariance matrix difference and the angle difference of the adjacent moment was obtained through three approximate relations. Then, the proposed algorithm obtained the relationship between the elements in the covariance matrix difference. On this basis, the performance of the algorithm was improved by averaging the covariance matrix element. Finally, the least square method was used to estimate the DOD and DOA. The algorithm realized the automatic correlation of the angle and provided better performance when compared with the adaptive asymmetric joint diagonalization (AAJD) algorithm. The simulation results demonstrated the effectiveness of the proposed algorithm. The algorithm provides the technical support for the practical application of MIMO radar.

Observer-Based Discrete-Time Nonnegative Edge Synchronization of Networked Systems.

PubMed

Su, Housheng; Wu, Han; Chen, Xia

2017-10-01

This paper studies the multi-input and multi-output discrete-time nonnegative edge synchronization of networked systems based on neighbors' output information. The communication relationship among the edges of networked systems is modeled by well-known line graph. Two observer-based edge synchronization algorithms are designed, for which some necessary and sufficient synchronization conditions are derived. Moreover, some computable sufficient synchronization conditions are obtained, in which the feedback matrix and the observer matrix are computed by solving the linear programming problems. We finally design several simulation examples to demonstrate the validity of the given nonnegative edge synchronization algorithms.

The Combinatorial Trace Method in Action

ERIC Educational Resources Information Center

Krebs, Mike; Martinez, Natalie C.

2013-01-01

On any finite graph, the number of closed walks of length k is equal to the sum of the kth powers of the eigenvalues of any adjacency matrix. This simple observation is the basis for the combinatorial trace method, wherein we attempt to count (or bound) the number of closed walks of a given length so as to obtain information about the graph's…

Distribution of erlotinib in rash and normal skin in cancer patients receiving erlotinib visualized by matrix assisted laser desorption/ionization mass spectrometry imaging.

PubMed

Nishimura, Meiko; Hayashi, Mitsuhiro; Mizutani, Yu; Takenaka, Kei; Imamura, Yoshinori; Chayahara, Naoko; Toyoda, Masanori; Kiyota, Naomi; Mukohara, Toru; Aikawa, Hiroaki; Fujiwara, Yasuhiro; Hamada, Akinobu; Minami, Hironobu

2018-04-06

The development of skin rashes is the most common adverse event observed in cancer patients treated with epidermal growth factor receptor-tyrosine kinase inhibitors such as erlotinib. However, the pharmacological evidence has not been fully revealed. Erlotinib distribution in the rashes was more heterogeneous than that in the normal skin, and the rashes contained statistically higher concentrations of erlotinib than adjacent normal skin in the superficial skin layer (229 ± 192 vs. 120 ± 103 ions/mm 2 ; P = 0.009 in paired t -test). LC-MS/MS confirmed that the concentration of erlotinib in the skin rashes was higher than that in normal skin in the superficial skin layer (1946 ± 1258 vs. 1174 ± 662 ng/cm 3 ; P = 0.028 in paired t -test). The results of MALDI-MSI and LC-MS/MS were well correlated (coefficient of correlation 0.879, P < 0.0001). Focal distribution of erlotinib in the skin tissue was visualized using non-labeled MALDI-MSI. Erlotinib concentration in the superficial layer of the skin rashes was higher than that in the adjacent normal skin. We examined patients with advanced pancreatic cancer who developed skin rashes after treatment with erlotinib and gemcitabine. We biopsied both the rash and adjacent normal skin tissues, and visualized and compared the distribution of erlotinib within the skin using matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI). The tissue concentration of erlotinib was also measured by liquid chromatography-tandem mass spectrometry (LC-MS/MS) with laser microdissection.

Distribution of erlotinib in rash and normal skin in cancer patients receiving erlotinib visualized by matrix assisted laser desorption/ionization mass spectrometry imaging

PubMed Central

Mizutani, Yu; Takenaka, Kei; Imamura, Yoshinori; Chayahara, Naoko; Toyoda, Masanori; Kiyota, Naomi; Mukohara, Toru; Aikawa, Hiroaki; Fujiwara, Yasuhiro; Hamada, Akinobu; Minami, Hironobu

2018-01-01

Background The development of skin rashes is the most common adverse event observed in cancer patients treated with epidermal growth factor receptor-tyrosine kinase inhibitors such as erlotinib. However, the pharmacological evidence has not been fully revealed. Results Erlotinib distribution in the rashes was more heterogeneous than that in the normal skin, and the rashes contained statistically higher concentrations of erlotinib than adjacent normal skin in the superficial skin layer (229 ± 192 vs. 120 ± 103 ions/mm2; P = 0.009 in paired t-test). LC-MS/MS confirmed that the concentration of erlotinib in the skin rashes was higher than that in normal skin in the superficial skin layer (1946 ± 1258 vs. 1174 ± 662 ng/cm3; P = 0.028 in paired t-test). The results of MALDI-MSI and LC-MS/MS were well correlated (coefficient of correlation 0.879, P < 0.0001). Conclusions Focal distribution of erlotinib in the skin tissue was visualized using non-labeled MALDI-MSI. Erlotinib concentration in the superficial layer of the skin rashes was higher than that in the adjacent normal skin. Methods We examined patients with advanced pancreatic cancer who developed skin rashes after treatment with erlotinib and gemcitabine. We biopsied both the rash and adjacent normal skin tissues, and visualized and compared the distribution of erlotinib within the skin using matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI). The tissue concentration of erlotinib was also measured by liquid chromatography-tandem mass spectrometry (LC–MS/MS) with laser microdissection. PMID:29719624

Lumbar spine intervertebral disc gene delivery: a pilot study in lewis rats.

PubMed

Damle, Sheela R; Rawlins, Bernard A; Boachie-Adjei, Oheneba; Crystal, Ronald G; Hidaka, Chisa; Cunningham, Matthew E

2013-02-01

Basic research toward understanding and treating disc pathology in the spine has utilized numerous animal models, with delivery of small molecules, purified factors, and genes of interest. To date, gene delivery to the rat lumbar spine has only been described utilizing genetically programmed cells in a matrix which has required partial disc excision, and expected limitation of treatment diffusion into the disc. This study was designed to develop and describe a surgical technique for lumbar spine exposure and disc space preparation, and use of a matrix-free method for gene delivery. Naïve or genetically programmed isogeneic bone marrow stromal cells were surgically delivered to adolescent male Lewis rat lumbar discs, and utilizing quantitative biochemical and qualitative immunohistological assessments, the implanted cells were detected 3 days post-procedure. Statistically significant differences were noted for recovery of the β-galactosidase marker gene comparing delivery of naïve or labeled cells (10(5) cells per disc) from the site of implantation, and between delivery of 10(5) or 10(6) labeled cells per disc at the site of implantation and the adjacent vertebral body. Immunohistology confirmed that the β-galactosidase marker was detected in the adjacent vertebra bone in the zone of surgical implantation. The model requires further testing in larger cohorts and with biologically active genes of interest, but the observations from the pilot experiments are very encouraging that this will be a useful comparative model for basic spine research involving gene or cell delivery, or other locally delivered therapies to the intervertebral disc or adjacent vertebral bodies in rats.

Radiative, nonradiative, and mixed-decay transitions of rare-earth ions in dielectric media

NASA Astrophysics Data System (ADS)

Burshtein, Zeev

2010-09-01

We present and discuss in a comprehensive, deductive, and simplified manner, issues of nonradiative transitions involvement in fluorescence of ions embedded in dielectric solid matrices. The semiclassical approach is favored over a full quantum description, and empiric quantities are introduced from the start. One issue is nonradiative single-phonon transitions when the energy gap between the adjacent electronic ion states is smaller than the cutoff matrix phonon energy. Another issue is transitions in a complex energy scheme, where some visible and near-visible transitions are radiative and others are nonradiative. A refined Füchtbauer-Ladenburg recipe for calculation of the stimulated emission spectrum on the basis of measurable absorption and fluorescence emission spectra is worked out. The last issue is multiphonon nonradiative transitions occurring when the energy gap between adjacent electronic ion states is larger than the cutoff matrix phonon energy. Transition probabilities were calculated on the basis of anharmonicity of the effective potential supporting the internal atomic basis vibrations. An expression in a closed form is obtained, similar to the empiric ``energy gap'' law, however, with parameters related to specific host material properties and the actual transition in the ion. Comparison to existing experimental evidence is presented and discussed in detail.

Adaptive P300 based control system

PubMed Central

Jin, Jing; Allison, Brendan Z.; Sellers, Eric W.; Brunner, Clemens; Horki, Petar; Wang, Xingyu; Neuper, Christa

2015-01-01

An adaptive P300 brain-computer interface (BCI) using a 12 × 7 matrix explored new paradigms to improve bit rate and accuracy. During online use, the system adaptively selects the number of flashes to average. Five different flash patterns were tested. The 19-flash paradigm represents the typical row/column presentation (i.e., 12 columns and 7 rows). The 9- and 14-flash A & B paradigms present all items of the 12 × 7 matrix three times using either nine or 14 flashes (instead of 19), decreasing the amount of time to present stimuli. Compared to 9-flash A, 9-flash B decreased the likelihood that neighboring items would flash when the target was not flashing, thereby reducing interference from items adjacent to targets. 14-flash A also reduced adjacent item interference and 14-flash B additionally eliminated successive (double) flashes of the same item. Results showed that accuracy and bit rate of the adaptive system were higher than the non-adaptive system. In addition, 9- and 14-flash B produced significantly higher performance than their respective A conditions. The results also show the trend that the 14-flash B paradigm was better than the 19-flash pattern for naïve users. PMID:21474877

Cell adhesion molecules, the extracellular matrix and oral squamous carcinoma.

PubMed

Lyons, A J; Jones, J

2007-08-01

Carcinomas are characterized by invasion of malignant cells into the underlying connective tissue and migration of malignant cells to form metastases at distant sites. These processes require alterations in cell-cell and cell-extracellular matrix interactions. As cell adhesion molecules play a role in cell-cell and cell-extracellular matrix adhesion and interactions they are involved in the process of tumour invasion and metastases. In epithelial tissues, receptors of the integrin family mediate adhesion to the adjacent matrix whereas cadherins largely mediate intercellular adhesion. These and other cell adhesion molecules such as intercellular adhesion molecule-1, CD44, dystroglycans and selectins, are involved and undergo changes in carcinomas, which provide possible targets for anti-cancer drug treatments. In the extracellular matrix that is associated with tumours, laminin 5, oncofetal fibronectin and tenascin C appear. The degree of expression of some of these moieties indicates prognosis in oral cancer and offer targets for antibody-directed radiotherapy. Metalloproteases which degrade the extracellular matrix are increased in carcinomas, and their activity is necessary for tumour angiogenesis and consequent invasion and metastases. Metalloprotease inhibitors have begun to produce decreases in mortality in clinical trials. This report provides a brief overview of our current understanding of cell adhesion molecules, the extracellular matrix, tumour invasion and metastasis.

Matrix Completion Optimization for Localization in Wireless Sensor Networks for Intelligent IoT

PubMed Central

Nguyen, Thu L. N.; Shin, Yoan

2016-01-01

Localization in wireless sensor networks (WSNs) is one of the primary functions of the intelligent Internet of Things (IoT) that offers automatically discoverable services, while the localization accuracy is a key issue to evaluate the quality of those services. In this paper, we develop a framework to solve the Euclidean distance matrix completion problem, which is an important technical problem for distance-based localization in WSNs. The sensor network localization problem is described as a low-rank dimensional Euclidean distance completion problem with known nodes. The task is to find the sensor locations through recovery of missing entries of a squared distance matrix when the dimension of the data is small compared to the number of data points. We solve a relaxation optimization problem using a modification of Newton’s method, where the cost function depends on the squared distance matrix. The solution obtained in our scheme achieves a lower complexity and can perform better if we use it as an initial guess for an interactive local search of other higher precision localization scheme. Simulation results show the effectiveness of our approach. PMID:27213378

Analysis of double stub tuner control stability in a many element phased array antenna with strong cross-coupling

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wallace, G. M.; Fitzgerald, E.; Johnson, D. K.

2014-02-12

Active stub tuning with a fast ferrite tuner (FFT) allows for the system to respond dynamically to changes in the plasma impedance such as during the L-H transition or edge localized modes (ELMs), and has greatly increased the effectiveness of fusion ion cyclotron range of frequency systems. A high power waveguide double-stub tuner is under development for use with the Alcator C-Mod lower hybrid current drive (LHCD) system. Exact impedance matching with a double-stub is possible for a single radiating element under most load conditions, with the reflection coefficient reduced from Γ to Γ{sup 2} in the “forbidden region.” Themore » relative phase shift between adjacent columns of a LHCD antenna is critical for control of the launched n{sub ∥} spectrum. Adding a double-stub tuning network will perturb the phase of the forward wave particularly if the unmatched reflection coefficient is high. This effect can be compensated by adjusting the phase of the low power microwave drive for each klystron amplifier. Cross-coupling of the reflected power between columns of the launcher must also be considered. The problem is simulated by cascading a scattering matrix for the plasma provided by a linear coupling model with the measured launcher scattering matrix and that of the FFTs. The solution is advanced in an iterative manner similar to the time-dependent behavior of the real system. System performance is presented under a range of edge density conditions from under-dense to over-dense and a range of launched n{sub ∥}.« less

Myocardial matrix-polyethylene glycol hybrid hydrogels for tissue engineering

NASA Astrophysics Data System (ADS)

Grover, Gregory N.; Rao, Nikhil; Christman, Karen L.

2014-01-01

Similar to other protein-based hydrogels, extracellular matrix (ECM) based hydrogels, derived from decellularized tissues, have a narrow range of mechanical properties and are rapidly degraded. These hydrogels contain natural cellular adhesion sites, form nanofibrous networks similar to native ECM, and are biodegradable. In this study, we expand the properties of these types of materials by incorporating poly(ethylene glycol) (PEG) into the ECM network. We use decellularized myocardial matrix as an example of a tissue specific ECM derived hydrogel. Myocardial matrix-PEG hybrids were synthesized by two different methods, cross-linking the proteins with an amine-reactive PEG-star and photo-induced radical polymerization of two different multi-armed PEG-acrylates. We show that both methods allow for conjugation of PEG to the myocardial matrix by gel electrophoresis and infrared spectroscopy. Scanning electron microscopy demonstrated that the hybrid materials still contain a nanofibrous network similar to unmodified myocardial matrix and that the fiber diameter is changed by the method of PEG incorporation and PEG molecular weight. PEG conjugation also decreased the rate of enzymatic degradation in vitro, and increased material stiffness. Hybrids synthesized with amine-reactive PEG had gelation rates of 30 min, similar to the unmodified myocardial matrix, and incorporation of PEG did not prevent cell adhesion and migration through the hydrogels, thus offering the possibility to have an injectable ECM hydrogel that degrades more slowly in vivo. The photo-polymerized radical systems gelled in 4 min upon irradiation, allowing 3D encapsulation and culture of cells, unlike the soft unmodified myocardial matrix. This work demonstrates that PEG incorporation into ECM-based hydrogels can expand material properties, thereby opening up new possibilities for in vitro and in vivo applications.

Stability and synchronization analysis of inertial memristive neural networks with time delays.

PubMed

Rakkiyappan, R; Premalatha, S; Chandrasekar, A; Cao, Jinde

2016-10-01

This paper is concerned with the problem of stability and pinning synchronization of a class of inertial memristive neural networks with time delay. In contrast to general inertial neural networks, inertial memristive neural networks is applied to exhibit the synchronization and stability behaviors due to the physical properties of memristors and the differential inclusion theory. By choosing an appropriate variable transmission, the original system can be transformed into first order differential equations. Then, several sufficient conditions for the stability of inertial memristive neural networks by using matrix measure and Halanay inequality are derived. These obtained criteria are capable of reducing computational burden in the theoretical part. In addition, the evaluation is done on pinning synchronization for an array of linearly coupled inertial memristive neural networks, to derive the condition using matrix measure strategy. Finally, the two numerical simulations are presented to show the effectiveness of acquired theoretical results.

Data Imputation in Epistatic MAPs by Network-Guided Matrix Completion

PubMed Central

Žitnik, Marinka; Zupan, Blaž

2015-01-01

Abstract Epistatic miniarray profile (E-MAP) is a popular large-scale genetic interaction discovery platform. E-MAPs benefit from quantitative output, which makes it possible to detect subtle interactions with greater precision. However, due to the limits of biotechnology, E-MAP studies fail to measure genetic interactions for up to 40% of gene pairs in an assay. Missing measurements can be recovered by computational techniques for data imputation, in this way completing the interaction profiles and enabling downstream analysis algorithms that could otherwise be sensitive to missing data values. We introduce a new interaction data imputation method called network-guided matrix completion (NG-MC). The core part of NG-MC is low-rank probabilistic matrix completion that incorporates prior knowledge presented as a collection of gene networks. NG-MC assumes that interactions are transitive, such that latent gene interaction profiles inferred by NG-MC depend on the profiles of their direct neighbors in gene networks. As the NG-MC inference algorithm progresses, it propagates latent interaction profiles through each of the networks and updates gene network weights toward improved prediction. In a study with four different E-MAP data assays and considered protein–protein interaction and gene ontology similarity networks, NG-MC significantly surpassed existing alternative techniques. Inclusion of information from gene networks also allowed NG-MC to predict interactions for genes that were not included in original E-MAP assays, a task that could not be considered by current imputation approaches. PMID:25658751

Electrophoretic deposition of ultrasonicated and functionalized nanomaterials for multifunctional composites

NASA Astrophysics Data System (ADS)

An, Qi

Recent advances in the synthesis and characterization of nanostructured composite materials have enabled a broad range of opportunities for engineering the properties of polymer-matrix materials. Carbon nanotubes (CNTs) are known to have exceptional mechanical, electrical and thermal properties. Because of their small size, CNTs can occupy regions between traditional micro-scale reinforcements and create a hierarchical micro/nano structure spanning several orders of magnitude. Since CNTs possess critical reinforcement dimensions below 100 nm, new opportunities exist for tailoring the fiber/matrix interphase regions and ultimately the mechanical and electrical performance of advanced fiber-composites with minimal impact on the fiber-dominated properties. This growing interest in nanoscale hybridization with conventional fiber reinforcement has highlighted the need to develop new processing techniques for successful CNT integration. In this work, a novel and industrially scalable approach for producing multi-scale hybrid carbon nanotube/fiber composites using an electrophoretic deposition (EPD) technique has been studied as an alternative to in situ chemical vapor deposition growth (CVD). EPD is a widely used industrial coating process employed in areas ranging from automotive to electronics production. The method has a number of benefits which include low energy use and the ability to homogenously coat complex shapes with well adhered films of controlled thickness and density. A stable aqueous dispersion of multi-walled carbon nanotubes (MWCNTs) was produced using a novel ozonolysis and ultrasonication (USO) technique that results in dispersion and functionalization in a single step. Networks of CNTs span between adjacent fibers and the resulting composites exhibit significant increases in electrical conductivity and considerable improvements in the interlaminar shear strength and fracture toughness. In order to better understand the underlying mechanisms behind the selective reinforcement of CNTs on the glass-epoxy systems, detailed model interphase study and microdroplet debonding test were conducted to investigate the interfacial properties between an epoxy matrix and glass with the electrophoretically coated CNTs.

Internal calibration on adjacent samples (InCAS) with Fourier transform mass spectrometry.

PubMed

O'Connor, P B; Costello, C E

2000-12-15

Using matrix-assisted laser desorption/ionization (MAL DI) on a trapped ion mass spectrometer such as a Fourier transform mass spectrometer (FTMS) allows accumulation of ions in the cell from multiple laser shots prior to detection. If ions from separate MALDI samples are accumulated simultaneously in the cell, ions from one sample can be used to calibrate ions from the other sample. Since the ions are detected simultaneously in the cell, this is, in effect, internal calibration, but there are no selective desorption effects in the MALDI source. This method of internal calibration with adjacent samples is demonstrated here on cesium iodide clusters, peptides, oligosaccharides, poly(propylene glycol), and fullerenes and provides typical FTMS internal calibration mass accuracy of < 1 ppm.

Quantifying 10 years of Improvements in Earthquake and Tsunami Monitoring in the Caribbean and Adjacent Regions

NASA Astrophysics Data System (ADS)

von Hillebrandt-Andrade, C.; Huerfano Moreno, V. A.; McNamara, D. E.; Saurel, J. M.

2014-12-01

The magnitude-9.3 Sumatra-Andaman Islands earthquake of December 26, 2004, increased global awareness to the destructive hazard of earthquakes and tsunamis. Post event assessments of global coastline vulnerability highlighted the Caribbean as a region of high hazard and risk and that it was poorly monitored. Nearly 100 tsunamis have been reported for the Caribbean region and Adjacent Regions in the past 500 years and continue to pose a threat for its nations, coastal areas along the Gulf of Mexico, and the Atlantic seaboard of North and South America. Significant efforts to improve monitoring capabilities have been undertaken since this time including an expansion of the United States Geological Survey (USGS) Global Seismographic Network (GSN) (McNamara et al., 2006) and establishment of the United Nations Educational, Scientific and Cultural Organization (UNESCO) Intergovernmental Coordination Group (ICG) for the Tsunami and other Coastal Hazards Warning System for the Caribbean and Adjacent Regions (CARIBE EWS). The minimum performance standards it recommended for initial earthquake locations include: 1) Earthquake detection within 1 minute, 2) Minimum magnitude threshold = M4.5, and 3) Initial hypocenter error of <30 km. In this study, we assess current compliance with performance standards and model improvements in earthquake and tsunami monitoring capabilities in the Caribbean region since the first meeting of the UNESCO ICG-Caribe EWS in 2006. The three measures of network capability modeled in this study are: 1) minimum Mw detection threshold; 2) P-wave detection time of an automatic processing system and; 3) theoretical earthquake location uncertainty. By modeling three measures of seismic network capability, we can optimize the distribution of ICG-Caribe EWS seismic stations and select an international network that will be contributed from existing real-time broadband national networks in the region. Sea level monitoring improvements both offshore and along the coast will also be addressed. With the support of Member States and other countries and organizations it has been possible to significantly expand the sea level network thus reducing the amount of time it now takes to verify tsunamis.

Robust stability for stochastic bidirectional associative memory neural networks with time delays

NASA Astrophysics Data System (ADS)

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

2008-02-01

In this paper, the asymptotic stability is considered for a class of uncertain stochastic bidirectional associative memory neural networks with time delays and parameter uncertainties. The delays are time-invariant and the uncertainties are norm-bounded that enter into all network parameters. The aim of this paper is to establish easily verifiable conditions under which the delayed neural network is robustly asymptotically stable in the mean square for all admissible parameter uncertainties. By employing a Lyapunov-Krasovskii functional and conducting the stochastic analysis, a linear matrix inequality matrix inequality (LMI) approach is developed to derive the stability criteria. The proposed criteria can be easily checked by the Matlab LMI toolbox. A numerical example is given to demonstrate the usefulness of the proposed criteria.

Global exponential stability of neutral high-order stochastic Hopfield neural networks with Markovian jump parameters and mixed time delays.

PubMed

Huang, Haiying; Du, Qiaosheng; Kang, Xibing

2013-11-01

In this paper, a class of neutral high-order stochastic Hopfield neural networks with Markovian jump parameters and mixed time delays is investigated. The jumping parameters are modeled as a continuous-time finite-state Markov chain. At first, the existence of equilibrium point for the addressed neural networks is studied. By utilizing the Lyapunov stability theory, stochastic analysis theory and linear matrix inequality (LMI) technique, new delay-dependent stability criteria are presented in terms of linear matrix inequalities to guarantee the neural networks to be globally exponentially stable in the mean square. Numerical simulations are carried out to illustrate the main results. © 2013 ISA. Published by ISA. All rights reserved.

Topological Edge Modes in Active Mikado Networks

NASA Astrophysics Data System (ADS)

Zhou, Di; Zhang, Leyou; Mao, Xiaoming

Mechanical properties of disordered fiber networks are not only important in understanding a broad range of natural (such as the cytoskeleton and the extracellular matrix) and manmade materials (such as aerogels and porous media) but also exhibit interesting and rich physics. In this talk, we discuss how topological floppy edge modes can emerge from these fiber networks as a result of active driving. It is known that straight fibers in a network carries a state of self-stress and bears a bulk floppy mode. We find that, interestingly, by driving the network with a tiny perturbation, the bulk modes evolve into edge modes. We introduce a new transfer matrix formulation that can be applied to this strongly disordered system, to characterize the topological edge modes. We also discuss possible implications of these edge modes in biological processes. NSF-DMR-1609051.

Predicting drug-target interactions by dual-network integrated logistic matrix factorization

NASA Astrophysics Data System (ADS)

Hao, Ming; Bryant, Stephen H.; Wang, Yanli

2017-01-01

In this work, we propose a dual-network integrated logistic matrix factorization (DNILMF) algorithm to predict potential drug-target interactions (DTI). The prediction procedure consists of four steps: (1) inferring new drug/target profiles and constructing profile kernel matrix; (2) diffusing drug profile kernel matrix with drug structure kernel matrix; (3) diffusing target profile kernel matrix with target sequence kernel matrix; and (4) building DNILMF model and smoothing new drug/target predictions based on their neighbors. We compare our algorithm with the state-of-the-art method based on the benchmark dataset. Results indicate that the DNILMF algorithm outperforms the previously reported approaches in terms of AUPR (area under precision-recall curve) and AUC (area under curve of receiver operating characteristic) based on the 5 trials of 10-fold cross-validation. We conclude that the performance improvement depends on not only the proposed objective function, but also the used nonlinear diffusion technique which is important but under studied in the DTI prediction field. In addition, we also compile a new DTI dataset for increasing the diversity of currently available benchmark datasets. The top prediction results for the new dataset are confirmed by experimental studies or supported by other computational research.

Massive-scale gene co-expression network construction and robustness testing using random matrix theory.

PubMed

Gibson, Scott M; Ficklin, Stephen P; Isaacson, Sven; Luo, Feng; Feltus, Frank A; Smith, Melissa C

2013-01-01

The study of gene relationships and their effect on biological function and phenotype is a focal point in systems biology. Gene co-expression networks built using microarray expression profiles are one technique for discovering and interpreting gene relationships. A knowledge-independent thresholding technique, such as Random Matrix Theory (RMT), is useful for identifying meaningful relationships. Highly connected genes in the thresholded network are then grouped into modules that provide insight into their collective functionality. While it has been shown that co-expression networks are biologically relevant, it has not been determined to what extent any given network is functionally robust given perturbations in the input sample set. For such a test, hundreds of networks are needed and hence a tool to rapidly construct these networks. To examine functional robustness of networks with varying input, we enhanced an existing RMT implementation for improved scalability and tested functional robustness of human (Homo sapiens), rice (Oryza sativa) and budding yeast (Saccharomyces cerevisiae). We demonstrate dramatic decrease in network construction time and computational requirements and show that despite some variation in global properties between networks, functional similarity remains high. Moreover, the biological function captured by co-expression networks thresholded by RMT is highly robust.

Distribution of collagens type V and VI in the normal human alveolar mucosa: an immunoelectronmicroscopic study using ultrathin frozen sections.

PubMed

Rabanus, J P; Gelderblom, H R; Schuppan, D; Becker, J

1991-05-01

The ultrastructural localization of collagens type V and VI in normal human gingival mucosa was investigated by immunoelectron microscopy. Twenty biopsies were fixed in dimethylsuberimidate and shock-frozen in slush nitrogen. Collagen type V was mainly located to meshworks of uniform nonstriated microfibrils of 12 to 20 nm width, which preferentially appeared in larger spaces between cross-striated major collagen fibrils. Occasionally single microfibrils of collagen type V fanned out from the ends of major collagen fibrils, which may indicate a role as a core fibril. Collagen type V was not found in the subepithelial basement membrane and the immediately adjacent stroma. Collagen type VI was detected in a loose reticular network of unbanded microfilaments that were morphologically distinguishable by knoblike protrusions every 100-110 nm. These microfilaments were found in the vicinity, but not as an intrinsic component, of the subepithelial basement membrane. Single filaments of collagen type VI filaments appeared to form bridges between neighboring cross-striated major collagen fibrils, suggesting an interconnecting role for this collagen type. The method presented appears to be excellently suited to study the normal and pathological supramolecular organization of the oral extracellular matrix.

Active link selection for efficient semi-supervised community detection

NASA Astrophysics Data System (ADS)

Yang, Liang; Jin, Di; Wang, Xiao; Cao, Xiaochun

2015-03-01

Several semi-supervised community detection algorithms have been proposed recently to improve the performance of traditional topology-based methods. However, most of them focus on how to integrate supervised information with topology information; few of them pay attention to which information is critical for performance improvement. This leads to large amounts of demand for supervised information, which is expensive or difficult to obtain in most fields. For this problem we propose an active link selection framework, that is we actively select the most uncertain and informative links for human labeling for the efficient utilization of the supervised information. We also disconnect the most likely inter-community edges to further improve the efficiency. Our main idea is that, by connecting uncertain nodes to their community hubs and disconnecting the inter-community edges, one can sharpen the block structure of adjacency matrix more efficiently than randomly labeling links as the existing methods did. Experiments on both synthetic and real networks demonstrate that our new approach significantly outperforms the existing methods in terms of the efficiency of using supervised information. It needs ~13% of the supervised information to achieve a performance similar to that of the original semi-supervised approaches.

Mitochondrial fusion dynamics is robust in the heart and depends on calcium oscillations and contractile activity

PubMed Central

Eisner, Verónica; Gao, Erhe; Csordás, György; Slovinsky, William S.; Paillard, Melanie; Cheng, Lan; Ibetti, Jessica; Chen, S. R. Wayne; Chuprun, J. Kurt; Hoek, Jan B.; Koch, Walter J.; Hajnóczky, György

2017-01-01

Mitochondrial fusion is thought to be important for supporting cardiac contractility, but is hardly detectable in cultured cardiomyocytes and is difficult to directly evaluate in the heart. We overcame this obstacle through in vivo adenoviral transduction with matrix-targeted photoactivatable GFP and confocal microscopy. Imaging in whole rat hearts indicated mitochondrial network formation and fusion activity in ventricular cardiomyocytes. Promptly after isolation, cardiomyocytes showed extensive mitochondrial connectivity and fusion, which decayed in culture (at 24–48 h). Fusion manifested both as rapid content mixing events between adjacent organelles and slower events between both neighboring and distant mitochondria. Loss of fusion in culture likely results from the decline in calcium oscillations/contractile activity and mitofusin 1 (Mfn1), because (i) verapamil suppressed both contraction and mitochondrial fusion, (ii) after spontaneous contraction or short-term field stimulation fusion activity increased in cardiomyocytes, and (iii) ryanodine receptor-2–mediated calcium oscillations increased fusion activity in HEK293 cells and complementing changes occurred in Mfn1. Weakened cardiac contractility in vivo in alcoholic animals is also associated with depressed mitochondrial fusion. Thus, attenuated mitochondrial fusion might contribute to the pathogenesis of cardiomyopathy. PMID:28096338

Active link selection for efficient semi-supervised community detection

PubMed Central

Yang, Liang; Jin, Di; Wang, Xiao; Cao, Xiaochun

2015-01-01

Several semi-supervised community detection algorithms have been proposed recently to improve the performance of traditional topology-based methods. However, most of them focus on how to integrate supervised information with topology information; few of them pay attention to which information is critical for performance improvement. This leads to large amounts of demand for supervised information, which is expensive or difficult to obtain in most fields. For this problem we propose an active link selection framework, that is we actively select the most uncertain and informative links for human labeling for the efficient utilization of the supervised information. We also disconnect the most likely inter-community edges to further improve the efficiency. Our main idea is that, by connecting uncertain nodes to their community hubs and disconnecting the inter-community edges, one can sharpen the block structure of adjacency matrix more efficiently than randomly labeling links as the existing methods did. Experiments on both synthetic and real networks demonstrate that our new approach significantly outperforms the existing methods in terms of the efficiency of using supervised information. It needs ~13% of the supervised information to achieve a performance similar to that of the original semi-supervised approaches. PMID:25761385

Structure-correlated diffusion anisotropy in nanoporous channel networks by Monte Carlo simulations and percolation theory

NASA Astrophysics Data System (ADS)

Kondrashova, Daria; Valiullin, Rustem; Kärger, Jörg; Bunde, Armin

2017-07-01

Nanoporous silicon consisting of tubular pores imbedded in a silicon matrix has found many technological applications and provides a useful model system for studying phase transitions under confinement. Recently, a model for mass transfer in these materials has been elaborated [Kondrashova et al., Sci. Rep. 7, 40207 (2017)], which assumes that adjacent channels can be connected by "bridges" (with probability pbridge) which allows diffusion perpendicular to the channels. Along the channels, diffusion can be slowed down by "necks" which occur with probability pneck. In this paper we use Monte-Carlo simulations to study diffusion along the channels and perpendicular to them, as a function of pbridge and pneck, and find remarkable correlations between the diffusivities in longitudinal and radial directions. For clarifying the diffusivity in radial direction, which is governed by the concentration of bridges, we applied percolation theory. We determine analytically how the critical concentration of bridges depends on the size of the system and show that it approaches zero in the thermodynamic limit. Our analysis suggests that the critical properties of the model, including the diffusivity in radial direction, are in the universality class of two-dimensional lattice percolation, which is confirmed by our numerical study.

One-dimensional pressure transfer models for acoustic-electric transmission channels

NASA Astrophysics Data System (ADS)

Wilt, K. R.; Lawry, T. J.; Scarton, H. A.; Saulnier, G. J.

2015-09-01

A method for modeling piezoelectric-based ultrasonic acoustic-electric power and data transmission channels is presented. These channels employ piezoelectric disk transducers to convey signals across a series of physical layers using ultrasonic waves. This model decomposes the mechanical pathway of the signal into individual ultrasonic propagation layers which are generally independent of the layer's adjacent domains. Each layer is represented by a two-by-two traveling pressure wave transfer matrix which relates the forward and reverse pressure waves on one side of the layer to the pressure waves on the opposite face, where each face is assumed to be in contact with a domain of arbitrary reference acoustic impedance. A rigorous implementation of ultrasonic beam spreading is introduced and implemented within applicable domains. Compatible pressure-wave models for piezoelectric transducers are given, which relate the electric voltage and current interface of the transducer to the pressure waves on one mechanical interface while also allowing for passive acoustic loading of the secondary mechanical interface. It is also shown that the piezoelectric model's electrical interface is compatible with transmission line parameters (ABCD-parameters), allowing for connection of electronic components and networks. The model is shown to be capable of reproducing the behavior of realistic physical channels.

A New Measure of Wireless Network Connectivity

DTIC Science & Technology

2014-10-31

matrix QG. From Lemma 1, QG is a non-zero nonnegative matrix. Thus from the Perron - Frobenius Theorem, [24], its largest magni- tude eigenvalue, known as...the Perron - Frobenius eigenvalue is real and positive. Further as QG is symmetric, all its eigenval- ues are real, and its largest magnitude...eigenvalue λmax(QG) is also its largest singular value. Also from the Perron - Frobenius Theorem, should the network be connected, i.e. QG is positive as opposed

Toric Networks, Geometric R-Matrices and Generalized Discrete Toda Lattices

NASA Astrophysics Data System (ADS)

Inoue, Rei; Lam, Thomas; Pylyavskyy, Pavlo

2016-11-01

We use the combinatorics of toric networks and the double affine geometric R-matrix to define a three-parameter family of generalizations of the discrete Toda lattice. We construct the integrals of motion and a spectral map for this system. The family of commuting time evolutions arising from the action of the R-matrix is explicitly linearized on the Jacobian of the spectral curve. The solution to the initial value problem is constructed using Riemann theta functions.

A feedforward artificial neural network based on quantum effect vector-matrix multipliers.

PubMed

Levy, H J; McGill, T C

1993-01-01

The vector-matrix multiplier is the engine of many artificial neural network implementations because it can simulate the way in which neurons collect weighted input signals from a dendritic arbor. A new technology for building analog weighting elements that is theoretically capable of densities and speeds far beyond anything that conventional VLSI in silicon could ever offer is presented. To illustrate the feasibility of such a technology, a small three-layer feedforward prototype network with five binary neurons and six tri-state synapses was built and used to perform all of the fundamental logic functions: XOR, AND, OR, and NOT.

Feasibility Study for Casting of High Temperature Refractory Superalloy Composites

NASA Technical Reports Server (NTRS)

Lee, Jonathan A.

1998-01-01

Abstract This study investigated the feasibility of using conventional casting technique to fabricate refractory wires reinforced superalloy composites. These composites were being developed for advanced rocket engine turbine blades and other high temperature applications operating up to 2000 F. Several types of refractory metal wires such as W- Th, W-Re, Mo-Hf-C and W-HF-C reinforced waspaloy were experimentally cast and heat treated at 2000 F up to 48 hrs. Scanning electron microscope analysis was conducted in regions adjacent to the wire-matrix interface to determine the reaction zone and chemical compatibility resulting from material interdiffusion. It was concluded that fabrication using conventional casting may be feasible because the wire-matrix reaction zone thickness was comparable to similar composites produced by arc-sprayed monotape with hot isostatic pressing technique, Moreover, it was also found that the chemical compatibility could be improved significantly through a slight modification of the superalloy matrix compositions.

Fully Decentralized Semi-supervised Learning via Privacy-preserving Matrix Completion.

PubMed

Fierimonte, Roberto; Scardapane, Simone; Uncini, Aurelio; Panella, Massimo

2016-08-26

Distributed learning refers to the problem of inferring a function when the training data are distributed among different nodes. While significant work has been done in the contexts of supervised and unsupervised learning, the intermediate case of Semi-supervised learning in the distributed setting has received less attention. In this paper, we propose an algorithm for this class of problems, by extending the framework of manifold regularization. The main component of the proposed algorithm consists of a fully distributed computation of the adjacency matrix of the training patterns. To this end, we propose a novel algorithm for low-rank distributed matrix completion, based on the framework of diffusion adaptation. Overall, the distributed Semi-supervised algorithm is efficient and scalable, and it can preserve privacy by the inclusion of flexible privacy-preserving mechanisms for similarity computation. The experimental results and comparison on a wide range of standard Semi-supervised benchmarks validate our proposal.

High power x-ray welding of metal-matrix composites

DOEpatents

Rosenberg, Richard A.; Goeppner, George A.; Noonan, John R.; Farrell, William J.; Ma, Qing

1999-01-01

A method for joining metal-matrix composites (MMCs) by using high power x-rays as a volumetric heat source is provided. The method involves directing an x-ray to the weld line between two adjacent MMCs materials to create an irradiated region or melt zone. The x-rays have a power density greater than about 10.sup.4 watts/cm.sup.2 and provide the volumetric heat required to join the MMC materials. Importantly, the reinforcing material of the metal-matrix composites remains uniformly distributed in the melt zone, and the strength of the MMCs are not diminished. In an alternate embodiment, high power x-rays are used to provide the volumetric heat required to weld metal elements, including metal elements comprised of metal alloys. In an alternate embodiment, high power x-rays are used to provide the volumetric heat required to weld metal elements, including metal elements comprised of metal alloys.

Physiological Ranges of Matrix Rigidity Modulate Primary Mouse Hepatocyte Function In Part Through Hepatocyte Nuclear Factor 4 Alpha

PubMed Central

Desai, Seema S.; Tung, Jason C.; Zhou, Vivian X.; Grenert, James P.; Malato, Yann; Rezvani, Milad; Español-Suñer, Regina; Willenbring, Holger; Weaver, Valerie M.; Chang, Tammy T.

2016-01-01

Matrix rigidity has important effects on cell behavior and is increased during liver fibrosis; however, its effect on primary hepatocyte function is unknown. We hypothesized that increased matrix rigidity in fibrotic livers would activate mechanotransduction in hepatocytes and lead to inhibition of hepatic-specific functions. To determine the physiologically relevant ranges of matrix stiffness at the cellular level, we performed detailed atomic force microscopy analysis across liver lobules from normal and fibrotic livers. We determined that normal liver matrix stiffness was around 150Pa and increased to 1–6kPa in areas near fibrillar collagen deposition in fibrotic livers. In vitro culture of primary hepatocytes on collagen matrix of tunable rigidity demonstrated that fibrotic levels of matrix stiffness had profound effects on cytoskeletal tension and significantly inhibited hepatocyte-specific functions. Normal liver stiffness maintained functional gene regulation by hepatocyte nuclear factor 4 alpha (HNF4α) whereas fibrotic matrix stiffness inhibited the HNF4α transcriptional network. Fibrotic levels of matrix stiffness activated mechanotransduction in primary hepatocytes through focal adhesion kinase (FAK). In addition, blockade of the Rho/Rho-associated protein kinase (ROCK) pathway rescued HNF4α expression from hepatocytes cultured on stiff matrix. Conclusion Fibrotic levels of matrix stiffness significantly inhibit hepatocyte-specific functions in part by inhibiting the HNF4α transcriptional network mediated through the Rho/ROCK pathway. Increased appreciation of the role of matrix rigidity in modulating hepatocyte function will advance our understanding of the mechanisms of hepatocyte dysfunction in liver cirrhosis and spur development of novel treatments for chronic liver disease. PMID:26755329

Neural network based feed-forward high density associative memory

NASA Technical Reports Server (NTRS)

Daud, T.; Moopenn, A.; Lamb, J. L.; Ramesham, R.; Thakoor, A. P.

1987-01-01

A novel thin film approach to neural-network-based high-density associative memory is described. The information is stored locally in a memory matrix of passive, nonvolatile, binary connection elements with a potential to achieve a storage density of 10 to the 9th bits/sq cm. Microswitches based on memory switching in thin film hydrogenated amorphous silicon, and alternatively in manganese oxide, have been used as programmable read-only memory elements. Low-energy switching has been ascertained in both these materials. Fabrication and testing of memory matrix is described. High-speed associative recall approaching 10 to the 7th bits/sec and high storage capacity in such a connection matrix memory system is also described.

Mueller-matrix mapping of biological tissues in differential diagnosis of optical anisotropy mechanisms of protein networks

NASA Astrophysics Data System (ADS)

Ushenko, V. A.; Sidor, M. I.; Marchuk, Yu F.; Pashkovskaya, N. V.; Andreichuk, D. R.

2015-03-01

We report a model of Mueller-matrix description of optical anisotropy of protein networks in biological tissues with allowance for the linear birefringence and dichroism. The model is used to construct the reconstruction algorithms of coordinate distributions of phase shifts and the linear dichroism coefficient. In the statistical analysis of such distributions, we have found the objective criteria of differentiation between benign and malignant tissues of the female reproductive system. From the standpoint of evidence-based medicine, we have determined the operating characteristics (sensitivity, specificity and accuracy) of the Mueller-matrix reconstruction method of optical anisotropy parameters and demonstrated its effectiveness in the differentiation of benign and malignant tumours.

Discovering mutated driver genes through a robust and sparse co-regularized matrix factorization framework with prior information from mRNA expression patterns and interaction network.

PubMed

Xi, Jianing; Wang, Minghui; Li, Ao

2018-06-05

Discovery of mutated driver genes is one of the primary objective for studying tumorigenesis. To discover some relatively low frequently mutated driver genes from somatic mutation data, many existing methods incorporate interaction network as prior information. However, the prior information of mRNA expression patterns are not exploited by these existing network-based methods, which is also proven to be highly informative of cancer progressions. To incorporate prior information from both interaction network and mRNA expressions, we propose a robust and sparse co-regularized nonnegative matrix factorization to discover driver genes from mutation data. Furthermore, our framework also conducts Frobenius norm regularization to overcome overfitting issue. Sparsity-inducing penalty is employed to obtain sparse scores in gene representations, of which the top scored genes are selected as driver candidates. Evaluation experiments by known benchmarking genes indicate that the performance of our method benefits from the two type of prior information. Our method also outperforms the existing network-based methods, and detect some driver genes that are not predicted by the competing methods. In summary, our proposed method can improve the performance of driver gene discovery by effectively incorporating prior information from interaction network and mRNA expression patterns into a robust and sparse co-regularized matrix factorization framework.

High speed polling protocol for multiple node network

NASA Technical Reports Server (NTRS)

Kirkham, Harold (Inventor)

1995-01-01

The invention is a multiple interconnected network of intelligent message-repeating remote nodes which employs a remote node polling process performed by a master node by transmitting a polling message generically addressed to all remote nodes associated with the master node. Each remote node responds upon receipt of the generically addressed polling message by transmitting a poll-answering informational message and by relaying the polling message to other adjacent remote nodes.

Research of Ad Hoc Networks Access Algorithm

NASA Astrophysics Data System (ADS)

Xiang, Ma

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

Autonomous distributed self-organization for mobile wireless sensor networks.

PubMed

Wen, Chih-Yu; Tang, Hung-Kai

2009-01-01

This paper presents an adaptive combined-metrics-based clustering scheme for mobile wireless sensor networks, which manages the mobile sensors by utilizing the hierarchical network structure and allocates network resources efficiently A local criteria is used to help mobile sensors form a new cluster or join a current cluster. The messages transmitted during hierarchical clustering are applied to choose distributed gateways such that communication for adjacent clusters and distributed topology control can be achieved. In order to balance the load among clusters and govern the topology change, a cluster reformation scheme using localized criterions is implemented. The proposed scheme is simulated and analyzed to abstract the network behaviors in a number of settings. The experimental results show that the proposed algorithm provides efficient network topology management and achieves high scalability in mobile sensor networks.

Hybrid optoelectronic neural networks using a mutually pumped phase-conjugate mirror

NASA Astrophysics Data System (ADS)

Dunning, G. J.; Owechko, Y.; Soffer, B. H.

1991-06-01

A method is described for interconnecting hybrid optoelectronic neural networks by using a mutually pumped phase conjugate mirror (MP-PCM). In this method, cross talk due to Bragg degeneracies is greatly reduced by storing each weight among many spatially and angularly multiplexed gratings. The effective weight throughput is increased by the parallel updating of weights using outer-product learning. Experiments demonstrated a high degree of interconnectivity between adjacent pixels. A diagram is presented showing the architecture for the optoelectronic neural network using an MP-PCM.

New Passivity Criteria for Fuzzy Bam Neural Networks with Markovian Jumping Parameters and Time-Varying Delays

NASA Astrophysics Data System (ADS)

Vadivel, P.; Sakthivel, R.; Mathiyalagan, K.; Thangaraj, P.

2013-02-01

This paper addresses the problem of passivity analysis issue for a class of fuzzy bidirectional associative memory (BAM) neural networks with Markovian jumping parameters and time varying delays. A set of sufficient conditions for the passiveness of the considered fuzzy BAM neural network model is derived in terms of linear matrix inequalities by using the delay fractioning technique together with the Lyapunov function approach. In addition, the uncertainties are inevitable in neural networks because of the existence of modeling errors and external disturbance. Further, this result is extended to study the robust passivity criteria for uncertain fuzzy BAM neural networks with time varying delays and uncertainties. These criteria are expressed in the form of linear matrix inequalities (LMIs), which can be efficiently solved via standard numerical software. Two numerical examples are provided to demonstrate the effectiveness of the obtained results.

Electrical Properties of an m × n Hammock Network

NASA Astrophysics Data System (ADS)

Tan, Zhen; Tan, Zhi-Zhong; Zhou, Ling

2018-05-01

Electrical property is an important problem in the field of natural science and physics, which usually involves potential, current and resistance in the electric circuit. We investigate the electrical properties of an arbitrary hammock network, which has not been resolved before, and propose the exact potential formula of an arbitrary m × n hammock network by means of the Recursion-Transform method with current parameters (RT-I) pioneered by one of us [Z. Z. Tan, Phys. Rev. E 91 (2015) 052122], and the branch currents and equivalent resistance of the network are derived naturally. Our key technique is to setting up matrix equations and making matrix transformation, the potential formula derived is a meaningful discovery, which deduces many novel applications. The discovery of potential formula of the hammock network provides new theoretical tools and techniques for related scientific research. Supported by the Natural Science Foundation of Jiangsu Province under Grant No. BK20161278

Finite-time mixed outer synchronization of complex networks with coupling time-varying delay.

PubMed

He, Ping; Ma, Shu-Hua; Fan, Tao

2012-12-01

This article is concerned with the problem of finite-time mixed outer synchronization (FMOS) of complex networks with coupling time-varying delay. FMOS is a recently developed generalized synchronization concept, i.e., in which different state variables of the corresponding nodes can evolve into finite-time complete synchronization, finite-time anti-synchronization, and even amplitude finite-time death simultaneously for an appropriate choice of the controller gain matrix. Some novel stability criteria for the synchronization between drive and response complex networks with coupling time-varying delay are derived using the Lyapunov stability theory and linear matrix inequalities. And a simple linear state feedback synchronization controller is designed as a result. Numerical simulations for two coupled networks of modified Chua's circuits are then provided to demonstrate the effectiveness and feasibility of the proposed complex networks control and synchronization schemes and then compared with the proposed results and the previous schemes for accuracy.

Hand-waving and interpretive dance: an introductory course on tensor networks

NASA Astrophysics Data System (ADS)

Bridgeman, Jacob C.; Chubb, Christopher T.

2017-06-01

The curse of dimensionality associated with the Hilbert space of spin systems provides a significant obstruction to the study of condensed matter systems. Tensor networks have proven an important tool in attempting to overcome this difficulty in both the numerical and analytic regimes. These notes form the basis for a seven lecture course, introducing the basics of a range of common tensor networks and algorithms. In particular, we cover: introductory tensor network notation, applications to quantum information, basic properties of matrix product states, a classification of quantum phases using tensor networks, algorithms for finding matrix product states, basic properties of projected entangled pair states, and multiscale entanglement renormalisation ansatz states. The lectures are intended to be generally accessible, although the relevance of many of the examples may be lost on students without a background in many-body physics/quantum information. For each lecture, several problems are given, with worked solutions in an ancillary file.

Multiscale fracture network characterization and impact on flow: A case study on the Latemar carbonate platform

NASA Astrophysics Data System (ADS)

Hardebol, N. J.; Maier, C.; Nick, H.; Geiger, S.; Bertotti, G.; Boro, H.

2015-12-01

A fracture network arrangement is quantified across an isolated carbonate platform from outcrop and aerial imagery to address its impact on fluid flow. The network is described in terms of fracture density, orientation, and length distribution parameters. Of particular interest is the role of fracture cross connections and abutments on the effective permeability. Hence, the flow simulations explicitly account for network topology by adopting Discrete-Fracture-and-Matrix description. The interior of the Latemar carbonate platform (Dolomites, Italy) is taken as outcrop analogue for subsurface reservoirs of isolated carbonate build-ups that exhibit a fracture-dominated permeability. New is our dual strategy to describe the fracture network both as deterministic- and stochastic-based inputs for flow simulations. The fracture geometries are captured explicitly and form a multiscale data set by integration of interpretations from outcrops, airborne imagery, and lidar. The deterministic network descriptions form the basis for descriptive rules that are diagnostic of the complex natural fracture arrangement. The fracture networks exhibit a variable degree of multitier hierarchies with smaller-sized fractures abutting against larger fractures under both right and oblique angles. The influence of network topology on connectivity is quantified using Discrete-Fracture-Single phase fluid flow simulations. The simulation results show that the effective permeability for the fracture and matrix ensemble can be 50 to 400 times higher than the matrix permeability of 1.0 · 10-14 m2. The permeability enhancement is strongly controlled by the connectivity of the fracture network. Therefore, the degree of intersecting and abutting fractures should be captured from outcrops with accuracy to be of value as analogue.

Iterative Neighbour-Information Gathering for Ranking Nodes in Complex Networks

NASA Astrophysics Data System (ADS)

Xu, Shuang; Wang, Pei; Lü, Jinhu

2017-01-01

Designing node influence ranking algorithms can provide insights into network dynamics, functions and structures. Increasingly evidences reveal that node’s spreading ability largely depends on its neighbours. We introduce an iterative neighbourinformation gathering (Ing) process with three parameters, including a transformation matrix, a priori information and an iteration time. The Ing process iteratively combines priori information from neighbours via the transformation matrix, and iteratively assigns an Ing score to each node to evaluate its influence. The algorithm appropriates for any types of networks, and includes some traditional centralities as special cases, such as degree, semi-local, LeaderRank. The Ing process converges in strongly connected networks with speed relying on the first two largest eigenvalues of the transformation matrix. Interestingly, the eigenvector centrality corresponds to a limit case of the algorithm. By comparing with eight renowned centralities, simulations of susceptible-infected-removed (SIR) model on real-world networks reveal that the Ing can offer more exact rankings, even without a priori information. We also observe that an optimal iteration time is always in existence to realize best characterizing of node influence. The proposed algorithms bridge the gaps among some existing measures, and may have potential applications in infectious disease control, designing of optimal information spreading strategies.

Effect of advective flow in fractures and matrix diffusion on natural gas production

DOE PAGES

Karra, Satish; Makedonska, Nataliia; Viswanathan, Hari S.; ...

2015-10-12

Although hydraulic fracturing has been used for natural gas production for the past couple of decades, there are significant uncertainties about the underlying mechanisms behind the production curves that are seen in the field. A discrete fracture network based reservoir-scale work flow is used to identify the relative effect of flow of gas in fractures and matrix diffusion on the production curve. With realistic three dimensional representations of fracture network geometry and aperture variability, simulated production decline curves qualitatively resemble observed production decline curves. The high initial peak of the production curve is controlled by advective fracture flow of freemore » gas within the network and is sensitive to the fracture aperture variability. Matrix diffusion does not significantly affect the production decline curve in the first few years, but contributes to production after approximately 10 years. These results suggest that the initial flushing of gas-filled background fractures combined with highly heterogeneous flow paths to the production well are sufficient to explain observed initial production decline. Lastly, these results also suggest that matrix diffusion may support reduced production over longer time frames.« less

Functionalized gold nanoparticles as additive to form polymer/metal composite matrix for improved DNA sequencing by capillary electrophoresis.

PubMed

Zhou, Dan; Yang, Liping; Yang, Runmiao; Song, Weihua; Peng, Shuhua; Wang, Yanmei

2009-11-15

A new matrix additive, poly (N,N-dimethylacrylamide)-functionalized gold nanoparticle (GNP-PDMA), was prepared by "grafting-to" approach, and then incorporated into quasi-interpenetrating network (quasi-IPN) composed of linear polyacrylamide (LPA, 3.3 MDa) and PDMA to form novel polymer/metal composite sieving matrix (quasi-IPN/GNP-PDMA) for DNA sequencing by capillary electrophoresis. Without complete optimization, quasi-IPN/GNP-PDMA yielded a readlength of 801 bases at 98% accuracy in about 64 min by using the ABI 310 Genetic Analyzer at 50 degrees C and 150 V/cm. Compared with previous quasi-IPN/GNPs, quasi-IPN/GNP-PDMA can further improve DNA sequencing performances. This is because the presence of GNP-PDMA can improve the compatibility of GNPs with the whole sequencing system, enhance the entanglement degree of networks, and increase the GNP concentration in system, which consequently lead to higher restriction and stability, higher apparent molecular weight (MW), and smaller pore size of the total sieving networks. Furthermore, the composite matrix was also compared with quasi-IPN containing higher-MW LPA and commercial POP-6. The results indicate that the composite matrix is a promising one for DNA sequencing to achieve full automation due to the separation provided with high resolution, speediness, excellent reproducibility, and easy loading in the presence of GNP-PDMA.

Sparse matrix-vector multiplication on network-on-chip

NASA Astrophysics Data System (ADS)

Sun, C.-C.; Götze, J.; Jheng, H.-Y.; Ruan, S.-J.

2010-12-01

In this paper, we present an idea for performing matrix-vector multiplication by using Network-on-Chip (NoC) architecture. In traditional IC design on-chip communications have been designed with dedicated point-to-point interconnections. Therefore, regular local data transfer is the major concept of many parallel implementations. However, when dealing with the parallel implementation of sparse matrix-vector multiplication (SMVM), which is the main step of all iterative algorithms for solving systems of linear equation, the required data transfers depend on the sparsity structure of the matrix and can be extremely irregular. Using the NoC architecture makes it possible to deal with arbitrary structure of the data transfers; i.e. with the irregular structure of the sparse matrices. So far, we have already implemented the proposed SMVM-NoC architecture with the size 4×4 and 5×5 in IEEE 754 single float point precision using FPGA.

Nonlinear recurrent neural networks for finite-time solution of general time-varying linear matrix equations.

PubMed

Xiao, Lin; Liao, Bolin; Li, Shuai; Chen, Ke

2018-02-01

In order to solve general time-varying linear matrix equations (LMEs) more efficiently, this paper proposes two nonlinear recurrent neural networks based on two nonlinear activation functions. According to Lyapunov theory, such two nonlinear recurrent neural networks are proved to be convergent within finite-time. Besides, by solving differential equation, the upper bounds of the finite convergence time are determined analytically. Compared with existing recurrent neural networks, the proposed two nonlinear recurrent neural networks have a better convergence property (i.e., the upper bound is lower), and thus the accurate solutions of general time-varying LMEs can be obtained with less time. At last, various different situations have been considered by setting different coefficient matrices of general time-varying LMEs and a great variety of computer simulations (including the application to robot manipulators) have been conducted to validate the better finite-time convergence of the proposed two nonlinear recurrent neural networks. Copyright © 2017 Elsevier Ltd. All rights reserved.

Mergers + acquisitions.

PubMed

Hoppszallern, Suzanna

2002-05-01

The hospital sector in 2001 led the health care field in mergers and acquisitions. Most deals involved a network augmenting its presence within a specific region or in a market adjacent to its primary service area. Analysts expect M&A activity to increase in 2002.

The Oakland Conglomerate: a Hayward Fault Teconite?

NASA Astrophysics Data System (ADS)

Strayer, L. M.; Allen, J. R.

2008-12-01

The Late Cretaceous Oakland Conglomerate (OC), a coarse-grained cobble and sandstone unit of the Great Valley Sequence is a tectonite. Faulted and shattered cobbles and well developed grain-on-grain contact features between clasts are ubiquitous and penetrative throughout conglomeratic lenses. The OC outcrops east of the Hayward fault (HF) and adjacent to the Chabot fault in the East Bay Hills. It overlies the Knoxville Formation and may have been buried beneath 4-6 km of younger units. The OC is a proximal submarine fan deposit with sediment sourced to the ancestral Klamath and Sierra Nevada. Clast types are dominated by volcanics, granitoids, as well as numerous quartzites, perhaps reflecting complex provenance:Klamath and pre-Sierran arc and pre-Cretaceous Basin and Range. And although there was a significant interval between the Late-K deposition of the OC and the inception of San Andreas faulting in the Bay Area, its 1-2 km proximity to the HF in the Oakland Metropolitan area strongly suggests that much of the brittle-plastic deformation within the OC may be due to earthquakes upon the nearby Hayward fault. Clasts with the OC are frequently shattered, fractured or faulted. Most have grain-on-grain contact features on their surfaces regardless of whether they are matrix or grain supported. Faulting in the cobbles ranges from outcrop scale, penetrative and often conjugate shear fracture sets that run through both cobbles and matrix (if present), to closely spaced en-echelon faults that clearly deform cobbles, and radially shattered specimens with nearly conical conjugate shear fractures that are clearly the result of point loading due to grain-on-grain contact. There are at least 3 types of contact structures, ranging from: 1) Type-H, bright circular halos with little or no surface dimpling, likely the result of intense microfracture at the contact; 2) Type-S, shattered, rounded 'firing-pin' structures that have pulverized, depressed contact that is the locus of radial and conjugate shear fractures that offset the surface of the clasts. Cross-cutting relationships suggest that pulverized dimpling and faulting are synchronous. These appear to form both with and without matrix involvement. 3) Type-P, clean, well formed, pressure solution pits, often rimmed by a discrete lip of adjacent matrix, likely cemented by locally available quartz. These are often cut by the faults of Type-S above. Type-S and Type-P contact features can and often do occur in the same specimen. Type-H and some Type-S contacts appear to be products of 'clean' grain-on-grain contact without matrix involvement. Differences between the bright halo and the pressure solution pits may be due to the presence of a thin layer of matrix sand, which appears to facilitate wholesale pressure solution. Faults within the matrix and cobbles are often conjugate, and penetrative at the outcrop scale. Initial structural analysis suggests these faults might lend themselves to stress inversion techniques if enough examples are available. Since many of the cobbles were re-cemented after they were faulted, there may be potential to gain insight into their burial depths during these events by investigating their geochemistry. The OC, given its very close proximity to the HF, may provide a record of the shortening direction and stress orientations directly adjacent to this important plate boundary.

Multi-color incomplete Cholesky conjugate gradient methods for vector computers

DOE Office of Scientific and Technical Information (OSTI.GOV)

Poole, E.L.

1986-01-01

This research is concerned with the solution on vector computers of linear systems of equations. Ax = b, where A is a large, sparse symmetric positive definite matrix with non-zero elements lying only along a few diagonals of the matrix. The system is solved using the incomplete Cholesky conjugate gradient method (ICCG). Multi-color orderings are used of the unknowns in the linear system to obtain p-color matrices for which a no-fill block ICCG method is implemented on the CYBER 205 with O(N/p) length vector operations in both the decomposition of A and, more importantly, in the forward and back solvesmore » necessary at each iteration of the method. (N is the number of unknowns and p is a small constant). A p-colored matrix is a matrix that can be partitioned into a p x p block matrix where the diagonal blocks are diagonal matrices. The matrix is stored by diagonals and matrix multiplication by diagonals is used to carry out the decomposition of A and the forward and back solves. Additionally, if the vectors across adjacent blocks line up, then some of the overhead associated with vector startups can be eliminated in the matrix vector multiplication necessary at each conjugate gradient iteration. Necessary and sufficient conditions are given to determine which multi-color orderings of the unknowns correspond to p-color matrices, and a process is indicated for choosing multi-color orderings.« less

Massive-Scale Gene Co-Expression Network Construction and Robustness Testing Using Random Matrix Theory

PubMed Central

Isaacson, Sven; Luo, Feng; Feltus, Frank A.; Smith, Melissa C.

2013-01-01

The study of gene relationships and their effect on biological function and phenotype is a focal point in systems biology. Gene co-expression networks built using microarray expression profiles are one technique for discovering and interpreting gene relationships. A knowledge-independent thresholding technique, such as Random Matrix Theory (RMT), is useful for identifying meaningful relationships. Highly connected genes in the thresholded network are then grouped into modules that provide insight into their collective functionality. While it has been shown that co-expression networks are biologically relevant, it has not been determined to what extent any given network is functionally robust given perturbations in the input sample set. For such a test, hundreds of networks are needed and hence a tool to rapidly construct these networks. To examine functional robustness of networks with varying input, we enhanced an existing RMT implementation for improved scalability and tested functional robustness of human (Homo sapiens), rice (Oryza sativa) and budding yeast (Saccharomyces cerevisiae). We demonstrate dramatic decrease in network construction time and computational requirements and show that despite some variation in global properties between networks, functional similarity remains high. Moreover, the biological function captured by co-expression networks thresholded by RMT is highly robust. PMID:23409071

Continuous-time quantum walks on star graphs

DOE Office of Scientific and Technical Information (OSTI.GOV)

Salimi, S.

2009-06-15

In this paper, we investigate continuous-time quantum walk on star graphs. It is shown that quantum central limit theorem for a continuous-time quantum walk on star graphs for N-fold star power graph, which are invariant under the quantum component of adjacency matrix, converges to continuous-time quantum walk on K{sub 2} graphs (complete graph with two vertices) and the probability of observing walk tends to the uniform distribution.

Signal Processing for Time-Series Functions on a Graph

DTIC Science & Technology

2018-02-01

as filtering to functions supported on graphs. These methods can be applied to scalar functions with a domain that can be described by a fixed...classical signal processing such as filtering to account for the graph domain. This work essentially divides into 2 basic approaches: graph Laplcian...based filtering and weighted adjacency matrix-based filtering . In Shuman et al.,11 and elaborated in Bronstein et al.,13 filtering operators are

Convex Graph Invariants

DTIC Science & Technology

2010-12-02

Motzkin, T. and Straus, E. (1965). Maxima for graphs and a new proof of a theorem of Turan . Canad. J. Math. 17 533–540. [33] Rendl, F. and Sotirov, R...Convex Graph Invariants Venkat Chandrasekaran, Pablo A . Parrilo, and Alan S. Willsky ∗ Laboratory for Information and Decision Systems Department of...this paper we study convex graph invariants, which are graph invariants that are convex functions of the adjacency matrix of a graph. Some examples

Lung Reference Set A Application: Dawn Coverley- University of York (2011) — EDRN Public Portal

Cancer.gov

A variant of the nuclear matrix factor Ciz1 is prevalent in lung cancer cell lines and tumours, but not in adjacent lung tissue, giving rise to a protein that is stable enough to be detected in just one ul of plasma. This project evaluates the potential of variant Ciz1 as an early detection tool for lung cancer, using variant-selective antibodies.

Histological analysis of the alterations on cortical bone channels network after radiotherapy: A rabbit study.

PubMed

Rabelo, Gustavo Davi; Beletti, Marcelo Emílio; Dechichi, Paula

2010-10-01

The aim of this study was to evaluate the effects of radiotherapy in cortical bone channels network. Fourteen rabbits were divided in two groups and test group received single dose of 15 Gy cobalt-60 radiation in tibia, bilaterally. The animals were sacrificed and a segment of tibia was removed and histologically processed. Histological images were taken and had their bone channels segmented and called regions of interest (ROI). Images were analyzed through developed algorithms using the SCILAB mathematical environment, getting percentage of bone matrix, ROI areas, ROI perimeters, their standard deviations and Lacunarity. The osteocytes and empty lacunae were also counted. Data were evaluated using Kolmogorov-Smirnov, Mann Whitney, and Student's t test (P < 0.05). Significant differences in bone matrix percentage, area and perimeters of the channels, their respective standard deviations and lacunarity were found between groups. In conclusion, the radiotherapy causes reduction of bone matrix and modifies the morphology of bone channels network. © 2010 Wiley-Liss, Inc.

High-Speed Computation of the Kleene Star in Max-Plus Algebraic System Using a Cell Broadband Engine

NASA Astrophysics Data System (ADS)

Goto, Hiroyuki

This research addresses a high-speed computation method for the Kleene star of the weighted adjacency matrix in a max-plus algebraic system. We focus on systems whose precedence constraints are represented by a directed acyclic graph and implement it on a Cell Broadband Engine™ (CBE) processor. Since the resulting matrix gives the longest travel times between two adjacent nodes, it is often utilized in scheduling problem solvers for a class of discrete event systems. This research, in particular, attempts to achieve a speedup by using two approaches: parallelization and SIMDization (Single Instruction, Multiple Data), both of which can be accomplished by a CBE processor. The former refers to a parallel computation using multiple cores, while the latter is a method whereby multiple elements are computed by a single instruction. Using the implementation on a Sony PlayStation 3™ equipped with a CBE processor, we found that the SIMDization is effective regardless of the system's size and the number of processor cores used. We also found that the scalability of using multiple cores is remarkable especially for systems with a large number of nodes. In a numerical experiment where the number of nodes is 2000, we achieved a speedup of 20 times compared with the method without the above techniques.

A Gaussian random field model for similarity-based smoothing in Bayesian disease mapping.

PubMed

Baptista, Helena; Mendes, Jorge M; MacNab, Ying C; Xavier, Miguel; Caldas-de-Almeida, José

2016-08-01

Conditionally specified Gaussian Markov random field (GMRF) models with adjacency-based neighbourhood weight matrix, commonly known as neighbourhood-based GMRF models, have been the mainstream approach to spatial smoothing in Bayesian disease mapping. In the present paper, we propose a conditionally specified Gaussian random field (GRF) model with a similarity-based non-spatial weight matrix to facilitate non-spatial smoothing in Bayesian disease mapping. The model, named similarity-based GRF, is motivated for modelling disease mapping data in situations where the underlying small area relative risks and the associated determinant factors do not vary systematically in space, and the similarity is defined by "similarity" with respect to the associated disease determinant factors. The neighbourhood-based GMRF and the similarity-based GRF are compared and accessed via a simulation study and by two case studies, using new data on alcohol abuse in Portugal collected by the World Mental Health Survey Initiative and the well-known lip cancer data in Scotland. In the presence of disease data with no evidence of positive spatial correlation, the simulation study showed a consistent gain in efficiency from the similarity-based GRF, compared with the adjacency-based GMRF with the determinant risk factors as covariate. This new approach broadens the scope of the existing conditional autocorrelation models. © The Author(s) 2016.

Physiological ranges of matrix rigidity modulate primary mouse hepatocyte function in part through hepatocyte nuclear factor 4 alpha.

PubMed

Desai, Seema S; Tung, Jason C; Zhou, Vivian X; Grenert, James P; Malato, Yann; Rezvani, Milad; Español-Suñer, Regina; Willenbring, Holger; Weaver, Valerie M; Chang, Tammy T

2016-07-01

Matrix rigidity has important effects on cell behavior and is increased during liver fibrosis; however, its effect on primary hepatocyte function is unknown. We hypothesized that increased matrix rigidity in fibrotic livers would activate mechanotransduction in hepatocytes and lead to inhibition of liver-specific functions. To determine the physiologically relevant ranges of matrix stiffness at the cellular level, we performed detailed atomic force microscopy analysis across liver lobules from normal and fibrotic livers. We determined that normal liver matrix stiffness was around 150 Pa and increased to 1-6 kPa in areas near fibrillar collagen deposition in fibrotic livers. In vitro culture of primary hepatocytes on collagen matrix of tunable rigidity demonstrated that fibrotic levels of matrix stiffness had profound effects on cytoskeletal tension and significantly inhibited hepatocyte-specific functions. Normal liver stiffness maintained functional gene regulation by hepatocyte nuclear factor 4 alpha (HNF4α), whereas fibrotic matrix stiffness inhibited the HNF4α transcriptional network. Fibrotic levels of matrix stiffness activated mechanotransduction in primary hepatocytes through focal adhesion kinase. In addition, blockade of the Rho/Rho-associated protein kinase pathway rescued HNF4α expression from hepatocytes cultured on stiff matrix. Fibrotic levels of matrix stiffness significantly inhibit hepatocyte-specific functions in part by inhibiting the HNF4α transcriptional network mediated through the Rho/Rho-associated protein kinase pathway. Increased appreciation of the role of matrix rigidity in modulating hepatocyte function will advance our understanding of the mechanisms of hepatocyte dysfunction in liver cirrhosis and spur development of novel treatments for chronic liver disease. (Hepatology 2016;64:261-275). © 2016 by the American Association for the Study of Liver Diseases.

Cascaded VLSI Chips Help Neural Network To Learn

NASA Technical Reports Server (NTRS)

Duong, Tuan A.; Daud, Taher; Thakoor, Anilkumar P.

1993-01-01

Cascading provides 12-bit resolution needed for learning. Using conventional silicon chip fabrication technology of VLSI, fully connected architecture consisting of 32 wide-range, variable gain, sigmoidal neurons along one diagonal and 7-bit resolution, electrically programmable, synaptic 32 x 31 weight matrix implemented on neuron-synapse chip. To increase weight nominally from 7 to 13 bits, synapses on chip individually cascaded with respective synapses on another 32 x 32 matrix chip with 7-bit resolution synapses only (without neurons). Cascade correlation algorithm varies number of layers effectively connected into network; adds hidden layers one at a time during learning process in such way as to optimize overall number of neurons and complexity and configuration of network.

Optical and mechanical behaviors of glassy silicone networks derived from linear siloxane precursors

NASA Astrophysics Data System (ADS)

Jang, Heejun; Seo, Wooram; Kim, Hyungsun; Lee, Yoonjoo; Kim, Younghee

2016-01-01

Silicon-based inorganic polymers are promising materials as matrix materials for glass fiber composites because of their good process ability, transparency, and thermal property. In this study, for utilization as a matrix precursor for a glass-fiber-reinforced composite, glassy silicone networks were prepared via hydrosilylation of linear/pendant Si-H polysiloxanes and the C=C bonds of viny-lterminated linear/cyclic polysiloxanes. 13C nuclear magnetic resonance spectroscopy was used to determine the structure of the cross-linked states, and a thermal analysis was performed. To assess the mechanical properties of the glassy silicone networks, we performed nanoindentation and 4-point bending tests. Cross-linked networks derived from siloxane polymers are thermally and optically more stable at high temperatures. Different cross-linking agents led to final networks with different properties due to differences in the molecular weights and structures. After stepped postcuring, the Young's modulus and the hardness of the glassy silicone networks increased; however, the brittleness also increased. The characteristics of the cross-linking agent played an important role in the functional glassy silicone networks.

Laplacian normalization and random walk on heterogeneous networks for disease-gene prioritization.

PubMed

Zhao, Zhi-Qin; Han, Guo-Sheng; Yu, Zu-Guo; Li, Jinyan

2015-08-01

Random walk on heterogeneous networks is a recently emerging approach to effective disease gene prioritization. Laplacian normalization is a technique capable of normalizing the weight of edges in a network. We use this technique to normalize the gene matrix and the phenotype matrix before the construction of the heterogeneous network, and also use this idea to define the transition matrices of the heterogeneous network. Our method has remarkably better performance than the existing methods for recovering known gene-phenotype relationships. The Shannon information entropy of the distribution of the transition probabilities in our networks is found to be smaller than the networks constructed by the existing methods, implying that a higher number of top-ranked genes can be verified as disease genes. In fact, the most probable gene-phenotype relationships ranked within top 3 or top 5 in our gene lists can be confirmed by the OMIM database for many cases. Our algorithms have shown remarkably superior performance over the state-of-the-art algorithms for recovering gene-phenotype relationships. All Matlab codes can be available upon email request. Copyright © 2015 Elsevier Ltd. All rights reserved.

Phylogeny of metabolic networks: a spectral graph theoretical approach.

PubMed

Deyasi, Krishanu; Banerjee, Anirban; Deb, Bony

2015-10-01

Many methods have been developed for finding the commonalities between different organisms in order to study their phylogeny. The structure of metabolic networks also reveals valuable insights into metabolic capacity of species as well as into the habitats where they have evolved. We constructed metabolic networks of 79 fully sequenced organisms and compared their architectures. We used spectral density of normalized Laplacian matrix for comparing the structure of networks. The eigenvalues of this matrix reflect not only the global architecture of a network but also the local topologies that are produced by different graph evolutionary processes like motif duplication or joining. A divergence measure on spectral densities is used to quantify the distances between various metabolic networks, and a split network is constructed to analyse the phylogeny from these distances. In our analysis, we focused on the species that belong to different classes, but appear more related to each other in the phylogeny. We tried to explore whether they have evolved under similar environmental conditions or have similar life histories. With this focus, we have obtained interesting insights into the phylogenetic commonality between different organisms.

National Wildlife Refuge System: Ecological context and integrity

USGS Publications Warehouse

Scott, J.M.; Loveland, T.; Gergely, K.; Strittholt, J.; Staus, N.

2004-01-01

The Refuge Improvement Act of 1997 established a statutory mission and management standards for the National Wildlife Refuge system. The U.S. Fish and Wildlife Service subsequently issued a policy for ensuring the biological integrity, diversity, and environmental health of the system. This policy requires understanding the management objectives of each refuge in a local, regional, and national context. An assessment of the refuge system in a national and regional context reveals that refuges are typically smaller than many conservation holdings and are unevenly distributed across the conterminous U.S. Western rangelands, coastal wetlands, and northern grasslands; wetlands are the best-represented ecosystems, while temperate forests have the poorest representation. In contrast to other agency holdings or management designations in the national protected areas network (e.g., national parks, national forests, wilderness areas), refuges tend to occupy sites at lower elevations and that have higher productivity and soil quality. This difference points to the important contribution of the refuges in providing much needed ecological balance within the national protected areas network. However, the ecological integrity of the refuge system is challenged by the proximity of individual refuges to development. Overall, the refuges are becoming islands in a landscape matrix of urban and agricultural development. This creates future challenges for meeting management objectives to ensure the biological integrity, diversity, and environmental health of the system. If the policy to ensure biological integrity, diversity, and environmental health of the refuge system is to be successful, it may be more important to address issues about what happens on adjacent lands than uses within refuges.

Liquid bridges at the root-soil interface

NASA Astrophysics Data System (ADS)

Carminati, Andrea; Benard, Pascal; Ahmed, Mutez; Zarebanadkouki, Mohsen

2017-04-01

The role of the root-soil interface on soil-plant water relations is unclear. Despite many experimental studies proved that the soil close to the root surface, the rhizosphere, has different properties compared to the adjacent bulk soil, the mechanisms underlying such differences are poorly understood and the implications for plant-water relations remain largely speculative. The objective of this contribution is to discuss the key elements affecting water dynamics in the rhizosphere. Special attention is dedicated to the role of mucilage exuded by roots in shaping the hydraulic properties of the rhizosphere. We identified three key properties: 1) mucilage adsorbs water decreasing its water potential; 2) mucilage decreases the surface tension of the soil solution; 3) mucilage increases the viscosity of the soil solution. These three properties determine the retention and spatial configuration of the liquid phase in porous media. The increase in viscosity and the decrease in surface tension (quantified by the Ohnesorge number) allow the persistence of long liquid filaments even at very negative water potentials. At high mucilage concentrations these filaments form a network that creates an additional matric potential and maintains the continuity of the liquid phase during drying. The biophysical interactions between mucilage and the pore space determine the physical properties of the rhizosphere. Mucilage forms a network that provides mechanical stability to soils upon drying and that maintains the continuity of the liquid phase across the soil-root interface. Such biophysical properties are functional to create an interconnected matrix that maintains the roots in contact with the soil, which is of particular importance when the soil is drying and the transpiration rate is high.

A model for compression-weakening materials and the elastic fields due to contractile cells

NASA Astrophysics Data System (ADS)

Rosakis, Phoebus; Notbohm, Jacob; Ravichandran, Guruswami

2015-12-01

We construct a homogeneous, nonlinear elastic constitutive law that models aspects of the mechanical behavior of inhomogeneous fibrin networks. Fibers in such networks buckle when in compression. We model this as a loss of stiffness in compression in the stress-strain relations of the homogeneous constitutive model. Problems that model a contracting biological cell in a finite matrix are solved. It is found that matrix displacements and stresses induced by cell contraction decay slower (with distance from the cell) in a compression weakening material than linear elasticity would predict. This points toward a mechanism for long-range cell mechanosensing. In contrast, an expanding cell would induce displacements that decay faster than in a linear elastic matrix.

Synchronization in networks with heterogeneous coupling delays

NASA Astrophysics Data System (ADS)

Otto, Andreas; Radons, Günter; Bachrathy, Dániel; Orosz, Gábor

2018-01-01

Synchronization in networks of identical oscillators with heterogeneous coupling delays is studied. A decomposition of the network dynamics is obtained by block diagonalizing a newly introduced adjacency lag operator which contains the topology of the network as well as the corresponding coupling delays. This generalizes the master stability function approach, which was developed for homogenous delays. As a result the network dynamics can be analyzed by delay differential equations with distributed delay, where different delay distributions emerge for different network modes. Frequency domain methods are used for the stability analysis of synchronized equilibria and synchronized periodic orbits. As an example, the synchronization behavior in a system of delay-coupled Hodgkin-Huxley neurons is investigated. It is shown that the parameter regions where synchronized periodic spiking is unstable expand when increasing the delay heterogeneity.

Electronic Neural Networks

NASA Technical Reports Server (NTRS)

Thakoor, Anil

1990-01-01

Viewgraphs on electronic neural networks for space station are presented. Topics covered include: electronic neural networks; electronic implementations; VLSI/thin film hybrid hardware for neurocomputing; computations with analog parallel processing; features of neuroprocessors; applications of neuroprocessors; neural network hardware for terrain trafficability determination; a dedicated processor for path planning; neural network system interface; neural network for robotic control; error backpropagation algorithm for learning; resource allocation matrix; global optimization neuroprocessor; and electrically programmable read only thin-film synaptic array.

Functional characterization of two distinct xyoglucanases from rumenal microbes

USDA-ARS?s Scientific Manuscript database

Xyloglucans are known to function by binding to cellulose microfibrils, crosslinking adjacent fibers forming cellulose-XG networks important for modulation of rigidity and extensibility of the primary cell wall of plants. Enzymatic hydrolysis and modification of xyloglucans has received considerabl...

Gateway to Complexity: The Adjacent Possible of Beginning Writing

ERIC Educational Resources Information Center

Yood, Jessica

2014-01-01

Writing studies' "recent enthusiasm" (Roderick "CF 25") for complexity theory has morphed into higher education's rabid embrace of reform. New curricula claim commitment to an "advanced," "networked," and "global" culture by erasing introductory composition, thereby dismissing the…

Unifying model for random matrix theory in arbitrary space dimensions

NASA Astrophysics Data System (ADS)

Cicuta, Giovanni M.; Krausser, Johannes; Milkus, Rico; Zaccone, Alessio

2018-03-01

A sparse random block matrix model suggested by the Hessian matrix used in the study of elastic vibrational modes of amorphous solids is presented and analyzed. By evaluating some moments, benchmarked against numerics, differences in the eigenvalue spectrum of this model in different limits of space dimension d , and for arbitrary values of the lattice coordination number Z , are shown and discussed. As a function of these two parameters (and their ratio Z /d ), the most studied models in random matrix theory (Erdos-Renyi graphs, effective medium, and replicas) can be reproduced in the various limits of block dimensionality d . Remarkably, the Marchenko-Pastur spectral density (which is recovered by replica calculations for the Laplacian matrix) is reproduced exactly in the limit of infinite size of the blocks, or d →∞ , which clarifies the physical meaning of space dimension in these models. We feel that the approximate results for d =3 provided by our method may have many potential applications in the future, from the vibrational spectrum of glasses and elastic networks to wave localization, disordered conductors, random resistor networks, and random walks.

Ex Situ Investigation of Anisotropic Interconnection in Silicon-Titanium-Nickel Alloy Anode Material

DOE PAGES

Cho, Jong -Soo; Alaboina, Pankaj Kumar; Kang, Chan -Soon; ...

2017-03-10

Herein we investigate the nanostructural evolution of Silicon-Titanium-Nickel (Si-Ti-Ni) ternary alloy material synthesized by melt spinning process for advanced lithium-ion battery anode. The synthesized material was found to have nano-Silicon particles dispersed in the Ti 4Ni 4Si 7 (STN) alloy buffering matrix and was characterized by X-ray diffraction (XRD), High resolution- transmission electron microscope (HR-TEM), Scanning transmission electron microscopes - energy dispersive X-ray spectrometer (STEM-EDS), and electrochemical performance test. The role of STN matrix is to accommodate the volume expansion stresses of the dispersed Si nanoparticles. However, an interesting behavior was observed during cycling. The Si nanoparticles were observed tomore » form interconnection channels growing through the weak STN matrix cracks and evolving to a network isolating the STN matrix into small puddles. In conclusion, this unique nanostructural evolution of Si particles and isolation of the STN matrix failing to offer significant buffering effect to the grown Si network eventually accelerates more volume expansions during cycling due to less mechanical confinement and leads to performance degradation and poor cycle stability.« less

Permitted and forbidden sets in symmetric threshold-linear networks.

PubMed

Hahnloser, Richard H R; Seung, H Sebastian; Slotine, Jean-Jacques

2003-03-01

The richness and complexity of recurrent cortical circuits is an inexhaustible source of inspiration for thinking about high-level biological computation. In past theoretical studies, constraints on the synaptic connection patterns of threshold-linear networks were found that guaranteed bounded network dynamics, convergence to attractive fixed points, and multistability, all fundamental aspects of cortical information processing. However, these conditions were only sufficient, and it remained unclear which were the minimal (necessary) conditions for convergence and multistability. We show that symmetric threshold-linear networks converge to a set of attractive fixed points if and only if the network matrix is copositive. Furthermore, the set of attractive fixed points is nonconnected (the network is multiattractive) if and only if the network matrix is not positive semidefinite. There are permitted sets of neurons that can be coactive at a stable steady state and forbidden sets that cannot. Permitted sets are clustered in the sense that subsets of permitted sets are permitted and supersets of forbidden sets are forbidden. By viewing permitted sets as memories stored in the synaptic connections, we provide a formulation of long-term memory that is more general than the traditional perspective of fixed-point attractor networks. There is a close correspondence between threshold-linear networks and networks defined by the generalized Lotka-Volterra equations.

Method and system for monitoring environmental conditions

DOEpatents

Kulesz, James J [Oak Ridge, TN; Lee, Ronald W [Oak Ridge, TN

2010-11-16

A system for detecting the occurrence of anomalies includes a plurality of spaced apart nodes, with each node having adjacent nodes, each of the nodes having one or more sensors associated with the node and capable of detecting anomalies, and each of the nodes having a controller connected to the sensors associated with the node. The system also includes communication links between adjacent nodes, whereby the nodes form a network. At least one software agent is capable of changing the operation of at least one of the controllers in response to the detection of an anomaly by a sensor.

Exploring methods of cGPS transient detections for the Chilean cGPS network in conjunction with displacement predictions from seismic catalogues: To what extent can we detect seismic and aseismic motion in the cGPS network?

NASA Astrophysics Data System (ADS)

Bedford, J. R.; Moreno, M.; Oncken, O.; Li, S.; Schurr, B.; Metzger, S.; Baez, J. C.; Deng, Z.; Melnick, D.

2016-12-01

Various algorithms for the detection of transient deformation in cGPS networks are under currently being developed to relieve us of by-eye detection, which is an error prone and time-expensive activity. Such algorithms aim to separate the time series into secular, seasonal, and transient components. Additional white and coloured noise, as well as common-mode (network correlated) noise, may remain in the separated transient component of the signal, depending on the processing flow before the separation step. The a-priori knowledge of regional seismicity can assist in the recognition of steps in the data, which are generally corrected for if they are above the noise-floor. Sometimes, the cumulative displacement caused by small earthquakes can create a seemingly continuous transient signal in the cGPS leading to confusion as to whether to attribute this transient motion as seismic or aseismic. Here we demonstrate the efficacy of various transient detection algorithms for subsets of the Chilean cGPS network and present the optimal processing flow for teasing out the transients. We present a step-detection and removal algorithm and estimate the seismic efficiency of any detected transient signals by forward modelling the surface displacements of the earthquakes and comparing to the recovered transient signals. A major challenge in separating signals in the Chilean cGPS network is the overlapping of postseismic effects at adjacent segments: For example, a Mw 9 earthquake will produce a postseismic viscoelastic relaxation that is sustained over decades and several hundreds of kilometres. Additionally, it has been observed in Chile and Japan that following moderately large earthquakes (e.g. Mw > 8) the secular velocities of adjacent segments in the subduction margin suddenly change and remain changed: this effect may be related to a change in speed of slab subduction rather than viscoelastic relaxation, and therefore the signal separation algorithms that assume a time-independent secular velocity at each station may need to be revised to account for this effect. Accordingly, we categorize the recovered separated secular and transient signals of a particular station in terms of the seismic cycle in both its own and adjacent segments and discuss the appropriate modelling strategy for this station given its category.

Unified pipe network method for simulation of water flow in fractured porous rock

NASA Astrophysics Data System (ADS)

Ren, Feng; Ma, Guowei; Wang, Yang; Li, Tuo; Zhu, Hehua

2017-04-01

Rock masses are often conceptualized as dual-permeability media containing fractures or fracture networks with high permeability and porous matrix that is less permeable. In order to overcome the difficulties in simulating fluid flow in a highly discontinuous dual-permeability medium, an effective unified pipe network method is developed, which discretizes the dual-permeability rock mass into a virtual pipe network system. It includes fracture pipe networks and matrix pipe networks. They are constructed separately based on equivalent flow models in a representative area or volume by taking the advantage of the orthogonality of the mesh partition. Numerical examples of fluid flow in 2-D and 3-D domain including porous media and fractured porous media are presented to demonstrate the accuracy, robustness, and effectiveness of the proposed unified pipe network method. Results show that the developed method has good performance even with highly distorted mesh. Water recharge into the fractured rock mass with complex fracture network is studied. It has been found in this case that the effect of aperture change on the water recharge rate is more significant in the early stage compared to the fracture density change.

Vertices cannot be hidden from quantum spatial search for almost all random graphs

NASA Astrophysics Data System (ADS)

Glos, Adam; Krawiec, Aleksandra; Kukulski, Ryszard; Puchała, Zbigniew

2018-04-01

In this paper, we show that all nodes can be found optimally for almost all random Erdős-Rényi G(n,p) graphs using continuous-time quantum spatial search procedure. This works for both adjacency and Laplacian matrices, though under different conditions. The first one requires p=ω (log ^8(n)/n), while the second requires p≥ (1+ɛ )log (n)/n, where ɛ >0. The proof was made by analyzing the convergence of eigenvectors corresponding to outlying eigenvalues in the \\Vert \\cdot \\Vert _∞ norm. At the same time for p<(1-ɛ )log (n)/n, the property does not hold for any matrix, due to the connectivity issues. Hence, our derivation concerning Laplacian matrix is tight.

[Vital traits of woody species in High Andean forest edges of the Cogua Forest Reserve (Colombia)].

PubMed

Montenegro, Alba Lucía; Vargas, Orlando

2008-06-01

The Cogua Forest Reserve was studied throughout eight months to detect the existence of functional species-groups associated with edge wood forest. A second goal was to determine which species were the most successful in edge areas and their particular vital traits. The regeneration and growth of the forest patches to the adjacent matrix depends on the establishment of these species and their tolerance to both habitats. Three types of High Andean edge forest were studied. Two forest patches were chosen for each of the three edge types: Chusquea scandens edge, "paramune" and old-edge; the name of the latter was given because of its advanced successional state. In each patch, the vegetation was evaluated in two 60 m transects perpendicular to the edge and along the matrix-edge-interior gradient of the forest. All woody species were identified and counted to determine their abundance. A total of nine species were chosen as representative of High Andean forest edges in the reserve, because of their high abundance in this environment, their presence in both patches of each edge type and their ability to colonize the adjacent matrix. Each species was evaluated using 20 vital attributes of individual, leaf, and reproductive traits. Six species groups were found through a Correspondence Analysis. However, all nine species have high variation and plasticity levels for the attributes, even inside the groups. This trend suggests that while they are not clearly differentiated functional groups, they probably are representing different strategies within a single functional group of great plasticity. Tibouchina grossa and Pentacalia Pulchella are found in all edge and matrix types; the other species are found in all edge types, except by Gaiadendron punctatum and Weinmannia tomentosa, absent in the Chusquea scandens edge. All nine species are important elements in the restoration of forest edges, mainly where they are more abundant, evidencing their success in the particular conditions of an edge type. Miconia ligustrina and M. squamulosa are the most relevant species in the Chusquea scandens edge and matrix; while G. punctatum, P. pulchella, W. tomentosa, W. balbisiana and especially Macleania rupestris, are more important in the paramune edge and matrix; Hedyosmum bonplandianum is more important in the edge than in the matrix regeneration, while T. grossa is the most successful edge and matrix regeneration species, because it is the most abundant and has high levels of tolerance, vegetative reproduction and litter production. These features are related with a high rate of tissue replacement, as well as a persistent seed bank with smaller and more numerous seeds, evidence of its high fecundity.

A network view on psychiatric disorders: network clusters of symptoms as elementary syndromes of psychopathology.

PubMed

Goekoop, Rutger; Goekoop, Jaap G

2014-01-01

The vast number of psychopathological syndromes that can be observed in clinical practice can be described in terms of a limited number of elementary syndromes that are differentially expressed. Previous attempts to identify elementary syndromes have shown limitations that have slowed progress in the taxonomy of psychiatric disorders. To examine the ability of network community detection (NCD) to identify elementary syndromes of psychopathology and move beyond the limitations of current classification methods in psychiatry. 192 patients with unselected mental disorders were tested on the Comprehensive Psychopathological Rating Scale (CPRS). Principal component analysis (PCA) was performed on the bootstrapped correlation matrix of symptom scores to extract the principal component structure (PCS). An undirected and weighted network graph was constructed from the same matrix. Network community structure (NCS) was optimized using a previously published technique. In the optimal network structure, network clusters showed a 89% match with principal components of psychopathology. Some 6 network clusters were found, including "Depression", "Mania", "Anxiety", "Psychosis", "Retardation", and "Behavioral Disorganization". Network metrics were used to quantify the continuities between the elementary syndromes. We present the first comprehensive network graph of psychopathology that is free from the biases of previous classifications: a 'Psychopathology Web'. Clusters within this network represent elementary syndromes that are connected via a limited number of bridge symptoms. Many problems of previous classifications can be overcome by using a network approach to psychopathology.

Research in Wireless Networks and Communications

DTIC Science & Technology

2008-05-01

TESTBED SETUP AND INITIAL MULTI-HOP EXPERIENCE As a proof of concept, we assembled a testbed platform of nodes based on 400MHz AMD Geode single-board...experi- ments on a testbed network consisting of 400MHz AMD Geode single-board computers made by Thecus Inc. We equipped each of these nodes with two...ground nodes were placed on a line, with about 3 feet of separation between adjacent nodes. The nodes were powered by 400MHz AMD Geode single-board

Distributed Network Protocols

DTIC Science & Technology

1980-07-01

MONITORING AGENCY NAME & ADDRESS(II different from Controlting Office) IS. SECURITY CLASS. (of this report) S Office of Naval Research Unclassified...All protocols are extended to networks with changing. topology. S80 8 4 246 DD0I iA 1473 EDITION OF INOV 65 IS OBSOLETE 8 0 24 SECURITY CLASSIFICATION...to the netowrk . f) Each node knows its adjacent links, but not necessarily the identity of its neighbors, i.e. the nodes at the other end of the links

3D H-bonding networks self-assembly from pyridinium derivatives and bis(maleonitriledithiolato)zincate(II)

NASA Astrophysics Data System (ADS)

Ren, Xiaoming; Xie, Jingli; Chen, Youcun; Kremer, Reinhard Karl

2003-11-01

The two ion-pair complexes, [pyH] 2[Zn(mnt) 2] ( 1) and [4,4'-bipyH 2]-[Zn(mnt) 2] ( 2), were synthesized, where mnt 2- denotes maleonitriledithiolate, and [pyH] +, [4,4'-bipyH 2] 2+ represent pyridinium and diprotonated 4,4'-bipyridinium, respectively. Their single crystal structures show that there are strong bifurcated H-bonding interactions between the cations of the pyridinium derivative and the [Zn(mnt) 2] 2- anions in both 1 and 2. The bifurcated H-bonding interactions between the N-H of the pyridiniums and the CN groups of the mnt 2- ligands give rise to a 2D layered H-bonding network, the adjacent layers come together in such way as mutual embrace to give a tight pack, thus 2D hydrogen-bonding sheets further develop into 3D H-bonding networks through weak C-H⋯S and π⋯π stacking interactions in 1. As for 2, the cations and anions connect into several types of H-bonding macrorings ([2+2], [3+3] and [4+4]), these H-bonding macrorings fuse to extend into 2D layered structure, the interpenetration between [3+3] and [4+4] type H-bonding macrorings in the adjacent layers give further rise to novel 3D extended H-bonding networks, in which there are clearly parallel stacks of cations and the chelate rings of anions.

Algorithm for optimizing bipolar interconnection weights with applications in associative memories and multitarget classification.

PubMed

Chang, S; Wong, K W; Zhang, W; Zhang, Y

1999-08-10

An algorithm for optimizing a bipolar interconnection weight matrix with the Hopfield network is proposed. The effectiveness of this algorithm is demonstrated by computer simulation and optical implementation. In the optical implementation of the neural network the interconnection weights are biased to yield a nonnegative weight matrix. Moreover, a threshold subchannel is added so that the system can realize, in real time, the bipolar weighted summation in a single channel. Preliminary experimental results obtained from the applications in associative memories and multitarget classification with rotation invariance are shown.

Algorithm for Optimizing Bipolar Interconnection Weights with Applications in Associative Memories and Multitarget Classification

NASA Astrophysics Data System (ADS)

Chang, Shengjiang; Wong, Kwok-Wo; Zhang, Wenwei; Zhang, Yanxin

1999-08-01

An algorithm for optimizing a bipolar interconnection weight matrix with the Hopfield network is proposed. The effectiveness of this algorithm is demonstrated by computer simulation and optical implementation. In the optical implementation of the neural network the interconnection weights are biased to yield a nonnegative weight matrix. Moreover, a threshold subchannel is added so that the system can realize, in real time, the bipolar weighted summation in a single channel. Preliminary experimental results obtained from the applications in associative memories and multitarget classification with rotation invariance are shown.

Exponentially convergent state estimation for delayed switched recurrent neural networks.

PubMed

Ahn, Choon Ki

2011-11-01

This paper deals with the delay-dependent exponentially convergent state estimation problem for delayed switched neural networks. A set of delay-dependent criteria is derived under which the resulting estimation error system is exponentially stable. It is shown that the gain matrix of the proposed state estimator is characterised in terms of the solution to a set of linear matrix inequalities (LMIs), which can be checked readily by using some standard numerical packages. An illustrative example is given to demonstrate the effectiveness of the proposed state estimator.

Detecting Seismic Activity with a Covariance Matrix Analysis of Data Recorded on Seismic Arrays

NASA Astrophysics Data System (ADS)

Seydoux, L.; Shapiro, N.; de Rosny, J.; Brenguier, F.

2014-12-01

Modern seismic networks are recording the ground motion continuously all around the word, with very broadband and high-sensitivity sensors. The aim of our study is to apply statistical array-based approaches to processing of these records. We use the methods mainly brought from the random matrix theory in order to give a statistical description of seismic wavefields recorded at the Earth's surface. We estimate the array covariance matrix and explore the distribution of its eigenvalues that contains information about the coherency of the sources that generated the studied wavefields. With this approach, we can make distinctions between the signals generated by isolated deterministic sources and the "random" ambient noise. We design an algorithm that uses the distribution of the array covariance matrix eigenvalues to detect signals corresponding to coherent seismic events. We investigate the detection capacity of our methods at different scales and in different frequency ranges by applying it to the records of two networks: (1) the seismic monitoring network operating on the Piton de la Fournaise volcano at La Réunion island composed of 21 receivers and with an aperture of ~15 km, and (2) the transportable component of the USArray composed of ~400 receivers with ~70 km inter-station spacing.

Nogo-66 Receptor Antagonist Peptide (NEP1-40) Administration Promotes Functional Recovery and Axonal Growth After Lateral Funiculus Injury in the Adult Rat

PubMed Central

Cao, Y.; Shumsky, J. S.; Sabol, M. A.; Kushner, R. A.; Strittmatter, S.; Hamers, F. P. T.; Lee, D. H. S.; Rabacchi, S. A.; Murray, M.

2010-01-01

Objective The myelin protein Nogo inhibits axon regeneration by binding to its receptor (NgR) on axons. Intrathecal delivery of an NgR antagonist (NEP1-40) promotes growth of injured corticospinal axons and recovery of motor function following a dorsal hemisection. The authors used a similar design to examine recovery and repair after a lesion that interrupts the rubrospinal tract (RST). Methods Rats received a lateral funiculotomy at C4 and NEP1-40 or vehicle was delivered to the cervical spinal cord for 4 weeks. Outcome measures included motor and sensory tests and immunohistochemistry. Results Gait analysis showed recovery in the NEP1-40-treated group compared to operated controls, and a test of forelimb usage also showed a beneficial effect. The density of labeled RST axons increased ipsilaterally in the NEP1-40 group in the lateral funiculus rostral to the lesion and contralaterally in both gray and white matter. Thus, rubrospinal axons exhibited diminished dieback and/or growth up to the lesion site. This was accompanied by greater density of 5 HT and calcitonin gene-related peptide axons adjacent to and into the lesion/matrix site in the NEP1-40 group. Conclusions NgR blockade after RST injury is associated with axonal growth and/or diminished dieback of severed RST axons up to but not into or beyond the lesion/matrix site, and growth of serotonergic and dorsal root axons adjacent to and into the lesion/matrix site. NgR blockade also supported partial recovery of function. The authors’ results indicate that severed rubrospinal axons respond to NEP1-40 treatment but less robustly than corticospinal, raphe-spinal, or dorsal root axons. PMID:18056009

Mass Spectrometry Imaging and GC-MS Profiling of the Mammalian Peripheral Sensory-Motor Circuit

NASA Astrophysics Data System (ADS)

Rubakhin, Stanislav S.; Ulanov, Alexander; Sweedler, Jonathan V.

2015-06-01

Matrix-assisted laser desorption/ionization (MALDI) mass spectrometry imaging (MSI) has evolved to become an effective discovery tool in science and clinical diagnostics. Here, chemical imaging approaches are applied to well-defined regions of the mammalian peripheral sensory-motor system, including the dorsal root ganglia (DRG) and adjacent nerves. By combining several MSI approaches, analyte coverage is increased and 195 distinct molecular features are observed. Principal component analysis suggests three chemically different regions within the sensory-motor system, with the DRG and adjacent nerve regions being the most distinct. Investigation of these regions using gas chromatography-mass spectrometry corroborate these findings and reveal important metabolic markers related to the observed differences. The heterogeneity of the structurally, physiologically, and functionally connected regions demonstrates the intricate chemical and spatial regulation of their chemical composition.

Mechanical response of biopolymer double networks

NASA Astrophysics Data System (ADS)

Carroll, Joshua; Das, Moumita

We investigate a double network model of articular cartilage (AC) and characterize its equilibrium mechanical response. AC has very few cells and the extracellular matrix mainly determines its mechanical response. This matrix can be thought of as a double polymer network made of collagen and aggrecan. The collagen fibers are stiff and resist tension and compression forces, while aggrecans are flexible and control swelling and hydration. We construct a microscopic model made of two interconnected disordered polymer networks, with fiber elasticity chosen to qualitatively mimic the experimental system. We study the collective mechanical response of this double network as a function of the concentration and stiffness of the individual components as well as the strength of the connection between them using rigidity percolation theory. Our results may provide a better understanding of mechanisms underlying the mechanical resilience of AC, and more broadly may also lead to new perspectives on the mechanical response of multicomponent soft materials. This work was partially supported by a Cottrell College Science Award.

A fast identification algorithm for Box-Cox transformation based radial basis function neural network.

PubMed

Hong, Xia

2006-07-01

In this letter, a Box-Cox transformation-based radial basis function (RBF) neural network is introduced using the RBF neural network to represent the transformed system output. Initially a fixed and moderate sized RBF model base is derived based on a rank revealing orthogonal matrix triangularization (QR decomposition). Then a new fast identification algorithm is introduced using Gauss-Newton algorithm to derive the required Box-Cox transformation, based on a maximum likelihood estimator. The main contribution of this letter is to explore the special structure of the proposed RBF neural network for computational efficiency by utilizing the inverse of matrix block decomposition lemma. Finally, the Box-Cox transformation-based RBF neural network, with good generalization and sparsity, is identified based on the derived optimal Box-Cox transformation and a D-optimality-based orthogonal forward regression algorithm. The proposed algorithm and its efficacy are demonstrated with an illustrative example in comparison with support vector machine regression.

A practical introduction to tensor networks: Matrix product states and projected entangled pair states

DOE Office of Scientific and Technical Information (OSTI.GOV)

Orús, Román, E-mail: roman.orus@uni-mainz.de

This is a partly non-technical introduction to selected topics on tensor network methods, based on several lectures and introductory seminars given on the subject. It should be a good place for newcomers to get familiarized with some of the key ideas in the field, specially regarding the numerics. After a very general introduction we motivate the concept of tensor network and provide several examples. We then move on to explain some basics about Matrix Product States (MPS) and Projected Entangled Pair States (PEPS). Selected details on some of the associated numerical methods for 1d and 2d quantum lattice systems aremore » also discussed. - Highlights: • A practical introduction to selected aspects of tensor network methods is presented. • We provide analytical examples of MPS and 2d PEPS. • We provide basic aspects on several numerical methods for MPS and 2d PEPS. • We discuss a number of applications of tensor network methods from a broad perspective.« less

Synchronization and desynchronization in a network of locally coupled Wilson-Cowan oscillators.

PubMed

Campbell, S; Wang, D

1996-01-01

A network of Wilson-Cowan (WC) oscillators is constructed, and its emergent properties of synchronization and desynchronization are investigated by both computer simulation and formal analysis. The network is a 2D matrix, where each oscillator is coupled only to its neighbors. We show analytically that a chain of locally coupled oscillators (the piecewise linear approximation to the WC oscillator) synchronizes, and we present a technique to rapidly entrain finite numbers of oscillators. The coupling strengths change on a fast time scale based on a Hebbian rule. A global separator is introduced which receives input from and sends feedback to each oscillator in the matrix. The global separator is used to desynchronize different oscillator groups. Unlike many other models, the properties of this network emerge from local connections that preserve spatial relationships among components and are critical for encoding Gestalt principles of feature grouping. The ability to synchronize and desynchronize oscillator groups within this network offers a promising approach for pattern segmentation and figure/ground segregation based on oscillatory correlation.

Alternative construction of graceful symmetric trees

NASA Astrophysics Data System (ADS)

Sandy, I. P.; Rizal, A.; Manurung, E. N.; Sugeng, K. A.

2018-04-01

Graceful labeling is one of the interesting topics in graph theory. Let G = (V, E) be a tree. The injective mapping f:V\\to \\{0,1,\\ldots,|E|\\} is called graceful if the weight of edge w(xy)=|f(x)-f(y)| are all different for every edge xy. The famous conjecture in this area is all trees are graceful. In this paper we give alternative construction of graceful labeling on symmetric tree using adjacency matrix.

Application of neural networks in the acousto-ultrasonic evaluation of metal-matrix composite specimens

NASA Technical Reports Server (NTRS)

Cios, Krzysztof J.; Tjia, Robert E.; Vary, Alex; Kautz, Harold E.

1992-01-01

Acousto-ultrasonics (AU) is a nondestructive evaluation (NDE) technique that was devised for the testing of various types of composite materials. A study has been done to determine how effectively the AU technique may be applied to metal-matrix composites (MMCs). The authors use the results and data obtained from that study and apply neural networks to them, particularly in the assessment of mechanical property variations of a specimen from AU measurements. It is assumed that there is no information concerning the important features of the AU signal which relate to the mechanical properties of the specimen. Minimally processed AU measurements are used while relying on the network's ability to extract the significant features of the signal.

Finite-time stability of neutral-type neural networks with random time-varying delays

NASA Astrophysics Data System (ADS)

Ali, M. Syed; Saravanan, S.; Zhu, Quanxin

2017-11-01

This paper is devoted to the finite-time stability analysis of neutral-type neural networks with random time-varying delays. The randomly time-varying delays are characterised by Bernoulli stochastic variable. This result can be extended to analysis and design for neutral-type neural networks with random time-varying delays. On the basis of this paper, we constructed suitable Lyapunov-Krasovskii functional together and established a set of sufficient linear matrix inequalities approach to guarantee the finite-time stability of the system concerned. By employing the Jensen's inequality, free-weighting matrix method and Wirtinger's double integral inequality, the proposed conditions are derived and two numerical examples are addressed for the effectiveness of the developed techniques.

Cellular growth in plants requires regulation of cell wall biochemistry.

PubMed

Chebli, Youssef; Geitmann, Anja

2017-02-01

Cell and organ morphogenesis in plants are regulated by the chemical structure and mechanical properties of the extracellular matrix, the cell wall. The two primary load bearing components in the plant cell wall, the pectin matrix and the cellulose/xyloglucan network, are constantly remodelled to generate the morphological changes required during plant development. This remodelling is regulated by a plethora of loosening and stiffening agents such as pectin methyl-esterases, calcium ions, expansins, and glucanases. The tight spatio-temporal regulation of the activities of these agents is a sine qua non condition for proper morphogenesis at cell and tissue levels. The pectin matrix and the cellulose-xyloglucan network operate in concert and their behaviour is mutually dependent on their chemical, structural and mechanical modifications. Copyright © 2017 Elsevier Ltd. All rights reserved.

General transfer matrix formalism to calculate DNA-protein-drug binding in gene regulation: application to OR operator of phage lambda.

PubMed

Teif, Vladimir B

2007-01-01

The transfer matrix methodology is proposed as a systematic tool for the statistical-mechanical description of DNA-protein-drug binding involved in gene regulation. We show that a genetic system of several cis-regulatory modules is calculable using this method, considering explicitly the site-overlapping, competitive, cooperative binding of regulatory proteins, their multilayer assembly and DNA looping. In the methodological section, the matrix models are solved for the basic types of short- and long-range interactions between DNA-bound proteins, drugs and nucleosomes. We apply the matrix method to gene regulation at the O(R) operator of phage lambda. The transfer matrix formalism allowed the description of the lambda-switch at a single-nucleotide resolution, taking into account the effects of a range of inter-protein distances. Our calculations confirm previously established roles of the contact CI-Cro-RNAP interactions. Concerning long-range interactions, we show that while the DNA loop between the O(R) and O(L) operators is important at the lysogenic CI concentrations, the interference between the adjacent promoters P(R) and P(RM) becomes more important at small CI concentrations. A large change in the expression pattern may arise in this regime due to anticooperative interactions between DNA-bound RNA polymerases. The applicability of the matrix method to more complex systems is discussed.

General transfer matrix formalism to calculate DNA–protein–drug binding in gene regulation: application to OR operator of phage λ

PubMed Central

Teif, Vladimir B.

2007-01-01

The transfer matrix methodology is proposed as a systematic tool for the statistical–mechanical description of DNA–protein–drug binding involved in gene regulation. We show that a genetic system of several cis-regulatory modules is calculable using this method, considering explicitly the site-overlapping, competitive, cooperative binding of regulatory proteins, their multilayer assembly and DNA looping. In the methodological section, the matrix models are solved for the basic types of short- and long-range interactions between DNA-bound proteins, drugs and nucleosomes. We apply the matrix method to gene regulation at the OR operator of phage λ. The transfer matrix formalism allowed the description of the λ-switch at a single-nucleotide resolution, taking into account the effects of a range of inter-protein distances. Our calculations confirm previously established roles of the contact CI–Cro–RNAP interactions. Concerning long-range interactions, we show that while the DNA loop between the OR and OL operators is important at the lysogenic CI concentrations, the interference between the adjacent promoters PR and PRM becomes more important at small CI concentrations. A large change in the expression pattern may arise in this regime due to anticooperative interactions between DNA-bound RNA polymerases. The applicability of the matrix method to more complex systems is discussed. PMID:17526526

Immunolocalization of matrix metalloproteinase-13 on bone surface under osteoclasts in rat tibia.

PubMed

Nakamura, Hiroaki; Sato, Ginga; Hirata, Azumi; Yamamoto, Toshio

2004-01-01

Matrix metalloproteinase (MMP)-13 (an interstitial collagenase also called collagenase 3) is involved in degradation of extracellular matrix in various tissues. Using immunohistochemistry and Western blotting, we investigated localization of MMP-13 in rat tibia, to clarify the role of MMP-13 in bone resorption. MMP-13 reactivity was mainly seen on bone surfaces under osteoclasts, and in some osteocytes and their lacunae near osteoclasts. However, immunoreactivity was not seen in chondrocytes or osteoclasts. MMP-13 was also localized on cement lines in the epiphysis. In the growth plate erosion zone, perivascular cells showed MMP-13 reactivity. Immunoelectron microscopy revealed that MMP-13 was localized on the bone surfaces, under the ruffled borders and some clear zones of osteoclasts. Gold-labeled MMP-13 was closely associated with collagen fibrils. Gold labeling was also detected in Golgi apparatus of osteocytes adjacent to osteoclasts and bone lining cells. Western blotting showed that MMP-13 was mainly associated with mineralized bone matrix. These findings suggest that MMP-13 synthesized and secreted by osteoblast-lineage cells is localized under the ruffled borders of osteoclasts. MMP-13 may play an important role in degradation of type I collagen in bone matrix, acting in concert with cathepsin K and MMP-9 produced by osteoclasts. MMP-13 in perivascular cells may be involved in removal of cartilage matrix proteins such as type II collagen and aggrecan.

Similarity-based Regularized Latent Feature Model for Link Prediction in Bipartite Networks.

PubMed

Wang, Wenjun; Chen, Xue; Jiao, Pengfei; Jin, Di

2017-12-05

Link prediction is an attractive research topic in the field of data mining and has significant applications in improving performance of recommendation system and exploring evolving mechanisms of the complex networks. A variety of complex systems in real world should be abstractly represented as bipartite networks, in which there are two types of nodes and no links connect nodes of the same type. In this paper, we propose a framework for link prediction in bipartite networks by combining the similarity based structure and the latent feature model from a new perspective. The framework is called Similarity Regularized Nonnegative Matrix Factorization (SRNMF), which explicitly takes the local characteristics into consideration and encodes the geometrical information of the networks by constructing a similarity based matrix. We also develop an iterative scheme to solve the objective function based on gradient descent. Extensive experiments on a variety of real world bipartite networks show that the proposed framework of link prediction has a more competitive, preferable and stable performance in comparison with the state-of-art methods.

Deformation-induced changes in hydraulic head during ground-water withdrawal

USGS Publications Warehouse

Hsieh, Paul A.

1996-01-01

Ground-water withdrawal from a confined or semiconfined aquifer causes three-dimensional deformation in the pumped aquifer and in adjacent layers (overlying and underlying aquifers and aquitards). In response to the deformation, hydraulic head in the adjacent layers could rise or fall almost immediately after the start of pumping. This deformation-induced effect suggest that an adjacent layer undergoes horizontal compression and vertical extension when pumping begins. Hydraulic head initially drops in a region near the well and close to the pumped aquifer, but rises outside this region. Magnitude of head change varies from a few centimeters to more than 10 centimeters. Factors that influence the development of deformation-induced effects includes matrix rigidity (shear modulus), the arrangement of aquifer and aquitards, their thicknesses, and proximity to land surface. Induced rise in hydraulic head is prominent in an aquitard that extends from land surface to a shallow pumped aquifer. Induced drop in hydraulic head is likely observed close to the well in an aquifer that is separated from the pumped aquifer by a relatively thin aquitard. Induced effects might last for hours in an aquifer, but could persist for many days in an aquitard. Induced effects are eventually dissipated by fluid flow from regions of higher head to regions of lower head, and by propagation of drawdown from the pumped aquifer into adjacent layers.

The extracellular matrix: Structure, composition, age-related differences, tools for analysis and applications for tissue engineering.

PubMed

Kular, Jaspreet K; Basu, Shouvik; Sharma, Ram I

2014-01-01

The extracellular matrix is a structural support network made up of diverse proteins, sugars and other components. It influences a wide number of cellular processes including migration, wound healing and differentiation, all of which is of particular interest to researchers in the field of tissue engineering. Understanding the composition and structure of the extracellular matrix will aid in exploring the ways the extracellular matrix can be utilised in tissue engineering applications especially as a scaffold. This review summarises the current knowledge of the composition, structure and functions of the extracellular matrix and introduces the effect of ageing on extracellular matrix remodelling and its contribution to cellular functions. Additionally, the current analytical technologies to study the extracellular matrix and extracellular matrix-related cellular processes are also reviewed.

Modified multiblock partial least squares path modeling algorithm with backpropagation neural networks approach

NASA Astrophysics Data System (ADS)

Yuniarto, Budi; Kurniawan, Robert

2017-03-01

PLS Path Modeling (PLS-PM) is different from covariance based SEM, where PLS-PM use an approach based on variance or component, therefore, PLS-PM is also known as a component based SEM. Multiblock Partial Least Squares (MBPLS) is a method in PLS regression which can be used in PLS Path Modeling which known as Multiblock PLS Path Modeling (MBPLS-PM). This method uses an iterative procedure in its algorithm. This research aims to modify MBPLS-PM with Back Propagation Neural Network approach. The result is MBPLS-PM algorithm can be modified using the Back Propagation Neural Network approach to replace the iterative process in backward and forward step to get the matrix t and the matrix u in the algorithm. By modifying the MBPLS-PM algorithm using Back Propagation Neural Network approach, the model parameters obtained are relatively not significantly different compared to model parameters obtained by original MBPLS-PM algorithm.

Consensus Algorithms for Networks of Systems with Second- and Higher-Order Dynamics

NASA Astrophysics Data System (ADS)

Fruhnert, Michael

This thesis considers homogeneous networks of linear systems. We consider linear feedback controllers and require that the directed graph associated with the network contains a spanning tree and systems are stabilizable. We show that, in continuous-time, consensus with a guaranteed rate of convergence can always be achieved using linear state feedback. For networks of continuous-time second-order systems, we provide a new and simple derivation of the conditions for a second-order polynomials with complex coefficients to be Hurwitz. We apply this result to obtain necessary and sufficient conditions to achieve consensus with networks whose graph Laplacian matrix may have complex eigenvalues. Based on the conditions found, methods to compute feedback gains are proposed. We show that gains can be chosen such that consensus is achieved robustly over a variety of communication structures and system dynamics. We also consider the use of static output feedback. For networks of discrete-time second-order systems, we provide a new and simple derivation of the conditions for a second-order polynomials with complex coefficients to be Schur. We apply this result to obtain necessary and sufficient conditions to achieve consensus with networks whose graph Laplacian matrix may have complex eigenvalues. We show that consensus can always be achieved for marginally stable systems and discretized systems. Simple conditions for consensus achieving controllers are obtained when the Laplacian eigenvalues are all real. For networks of continuous-time time-variant higher-order systems, we show that uniform consensus can always be achieved if systems are quadratically stabilizable. In this case, we provide a simple condition to obtain a linear feedback control. For networks of discrete-time higher-order systems, we show that constant gains can be chosen such that consensus is achieved for a variety of network topologies. First, we develop simple results for networks of time-invariant systems and networks of time-variant systems that are given in controllable canonical form. Second, we formulate the problem in terms of Linear Matrix Inequalities (LMIs). The condition found simplifies the design process and avoids the parallel solution of multiple LMIs. The result yields a modified Algebraic Riccati Equation (ARE) for which we present an equivalent LMI condition.

Carbon nanotubes/fluorinated polymers nanocomposite thin films for electrical contacts lubrication

NASA Astrophysics Data System (ADS)

Benedetto, A.; Viel, P.; Noël, S.; Izard, N.; Chenevier, P.; Palacin, S.

2007-09-01

The need to operate in extreme environmental conditions (ultra high vacuum, high temperatures, aerospatial environment, …) and the miniaturization toward micro electromechanical systems is demanding new materials in the field of low-level electrical contacts lubrication. Dry and chemically immobilized lubrication is expected to be an alternative to the traditional wet lubricants oils. With the goal to conciliate electrical conductivity and lubricant properties we designed nanocomposite thin films composed of a 2D carbon nanotubes network embedded in an organic matrix. The nanotubes networks were deposited on gold surfaces modified by electrochemical cathodic grafting of poly(acrylonitrile). The same substrate served for covalently bonding the low-friction organic matrix. Three different matrixes were tested: a perfluorinated oligomer chemically grafted and two different polyfluorinated acrylates electrochemically grafted. The nanocomposite thin films have been characterized by ATR FT-IR, XPS and Raman spectroscopy. We measured the effects of the different matrixes and the nanotubes addition on the tribological properties and on the contact resistances of the films.

A Complex Network Approach to Distributional Semantic Models

PubMed Central

Utsumi, Akira

2015-01-01

A number of studies on network analysis have focused on language networks based on free word association, which reflects human lexical knowledge, and have demonstrated the small-world and scale-free properties in the word association network. Nevertheless, there have been very few attempts at applying network analysis to distributional semantic models, despite the fact that these models have been studied extensively as computational or cognitive models of human lexical knowledge. In this paper, we analyze three network properties, namely, small-world, scale-free, and hierarchical properties, of semantic networks created by distributional semantic models. We demonstrate that the created networks generally exhibit the same properties as word association networks. In particular, we show that the distribution of the number of connections in these networks follows the truncated power law, which is also observed in an association network. This indicates that distributional semantic models can provide a plausible model of lexical knowledge. Additionally, the observed differences in the network properties of various implementations of distributional semantic models are consistently explained or predicted by considering the intrinsic semantic features of a word-context matrix and the functions of matrix weighting and smoothing. Furthermore, to simulate a semantic network with the observed network properties, we propose a new growing network model based on the model of Steyvers and Tenenbaum. The idea underlying the proposed model is that both preferential and random attachments are required to reflect different types of semantic relations in network growth process. We demonstrate that this model provides a better explanation of network behaviors generated by distributional semantic models. PMID:26295940

A black carbon air quality network

NASA Astrophysics Data System (ADS)

Kirchstetter, T.; Caubel, J.; Cados, T.; Preble, C.; Rosen, A.

2016-12-01

We developed a portable, power efficient black carbon sensor for deployment in an air quality network in West Oakland, California. West Oakland is a San Francisco Bay Area residential/industrial community adjacent to regional port and rail yard facilities, and is surrounded by major freeways. As such, the community is affected by diesel particulate matter emissions from heavy-duty diesel trucks, locomotives, and ships associated with freight movement. In partnership with Environmental Defense Fund, the Bay Area Air Quality Management District, and the West Oakland Environmental Indicators Project, we are collaborating with community members to build and operate a 100-sensor black carbon measurement network for a period of several months. The sensor employs the filter-based light transmission method to measure black carbon. Each sensor node in the network transmits data hourly via SMS text messages. Cost, power consumption, and performance are considered in choosing components (e.g., pump) and operating conditions (e.g., sample flow rate). In field evaluation trials over several weeks at three monitoring locations, the sensor nodes provided black carbon concentrations comparable to commercial instruments and ran autonomously for a week before sample filters and rechargeable batteries needed to be replaced. Buildup to the 100-sensor network is taking place during Fall 2016 and will overlap with other ongoing air monitoring projects and monitoring platforms in West Oakland. Sensors will be placed along commercial corridors, adjacent to freeways, upwind of and within the Port, and throughout the residential community. Spatial and temporal black carbon concentration patterns will help characterize pollution sources and demonstrate the value of sensing networks for characterizing intra-urban air pollution concentrations and exposure to air pollution.

Synchronization between uncertain nonidentical networks with quantum chaotic behavior

NASA Astrophysics Data System (ADS)

Li, Wenlin; Li, Chong; Song, Heshan

2016-11-01

Synchronization between uncertain nonidentical networks with quantum chaotic behavior is researched. The identification laws of unknown parameters in state equations of network nodes, the adaptive laws of configuration matrix elements and outer coupling strengths are determined based on Lyapunov theorem. The conditions of realizing synchronization between uncertain nonidentical networks are discussed and obtained. Further, Jaynes-Cummings model in physics are taken as the nodes of two networks and simulation results show that the synchronization performance between networks is very stable.

The dynamical modeling and simulation analysis of the recommendation on the user-movie network

NASA Astrophysics Data System (ADS)

Zhang, Shujuan; Jin, Zhen; Zhang, Juan

2016-12-01

At present, most research about the recommender system is based on graph theory and algebraic methods, but these methods cannot predict the evolution of the system with time under the recommendation method, and cannot dynamically analyze the long-term utility of the recommendation method. However, these two aspects can be studied by the dynamical method, which essentially investigates the intrinsic evolution mechanism of things, and is widely used to study a variety of actual problems. So, in this paper, network dynamics is used to study the recommendation on the user-movie network, which consists of users and movies, and the movies are watched either by the personal search or through the recommendation. Firstly, dynamical models are established to characterize the personal search and the system recommendation mechanism: the personal search model, the random recommendation model, the preference recommendation model, the degree recommendation model and the hybrid recommendation model. The rationality of the models established is verified by comparing the stochastic simulation with the numerical simulation. Moreover, the validity of the recommendation methods is evaluated by studying the movie degree, which is defined as the number of the movie that has been watched. Finally, we combine the personal search and the recommendation to establish a more general model. The change of the average degree of all the movies is given with the strength of the recommendation. Results show that for each recommendation method, the change of the movie degree is different, and is related to the initial degree of movies, the adjacency matrix A representing the relation between users and movies, the time t. Additionally, we find that in a long time, the degree recommendation is not as good as that in a short time, which fully demonstrates the advantage of the dynamical method. For the whole user-movie system, the preference recommendation is the best.

Long-term Behavior of Hydrocarbon Production Curves

NASA Astrophysics Data System (ADS)

Lovell, A.; Karra, S.; O'Malley, D.; Viswanathan, H. S.; Srinivasan, G.

2017-12-01

Recovering hydrocarbons (such as natural gas) from naturally-occurring formations with low permeability has had a huge impact on the energy sector, however, recovery rates are low due to poor understanding of recovery and transport mechanisms [1]. The physical mechanisms that control the production of hydrocarbon are only partially understood. Calculations have shown that the short-term behavior in the peak of the production curve is understood to come from the free hydrocarbons in the fracture networks, but the long-term behavior of these curves is often underpredicted [2]. This behavior is thought to be due to small scale processes - such as matrix diffusion, desorption, and connectivity in the damage region around the large fracture network. In this work, we explore some of these small-scale processes using discrete fracture networks (DFN) and the toolkit dfnWorks [3], the matrix diffusion, size of the damage region, and distribution of free gas between the fracture networks and rock matrix. Individual and combined parameter spaces are explored, and comparisons of the resulting production curves are made to experimental site data from the Haynesville formation [4]. We find that matrix diffusion significantly controls the shape of the tail of the production curve, while the distribution of free gas impacts the relative magnitude of the peak to the tail. The height of the damage region has no effect on the shape of the tail. Understanding the constrains of the parameter space based on site data is the first step in rigorously quantifying the uncertainties coming from these types of systems, which can in turn optimize and improve hydrocarbon recovery. [1] C. McGlade, et. al., (2013) Methods of estimating shale gas resources - comparison, evaluation, and implications, Energy, 59, 116-125 [2] S. Karra, et. al., (2015) Effect of advective flow in fractures and matrix diffusion on natural gas production, Water Resources Research, 51(10), 8646-8657 [3] J.D. Hyman, et. al., (2015) dfnworks: A discrete fracture network framework for modeling subsurface flow and transport, Computers & Geosciences, 84, 10-19 [4] E.J. Moniz, et. al., (2011) The future of natural gas, Cambridge, MA, Massachusetts Institute of Technology

A broadband 8-18GHz 4-input 4-output Butler matrix

NASA Astrophysics Data System (ADS)

Milner, Leigh; Parker, Michael

2007-01-01

Butler matrices can be used in antenna beam-forming networks to provide a linear phase distribution across the elements of an array. The development of an 8 to 18GHz micro-strip implementation of a 4-input 4-ouput Butler matrix is described. The designed Butler matrix uses March hybrids, Schiffman phase shifters and wire-bond crossovers integrated on a single 60mm x 70mm alumina substrate.

The feasibility and stability of large complex biological networks: a random matrix approach.

PubMed

Stone, Lewi

2018-05-29

In the 70's, Robert May demonstrated that complexity creates instability in generic models of ecological networks having random interaction matrices A. Similar random matrix models have since been applied in many disciplines. Central to assessing stability is the "circular law" since it describes the eigenvalue distribution for an important class of random matrices A. However, despite widespread adoption, the "circular law" does not apply for ecological systems in which density-dependence operates (i.e., where a species growth is determined by its density). Instead one needs to study the far more complicated eigenvalue distribution of the community matrix S = DA, where D is a diagonal matrix of population equilibrium values. Here we obtain this eigenvalue distribution. We show that if the random matrix A is locally stable, the community matrix S = DA will also be locally stable, providing the system is feasible (i.e., all species have positive equilibria D > 0). This helps explain why, unusually, nearly all feasible systems studied here are locally stable. Large complex systems may thus be even more fragile than May predicted, given the difficulty of assembling a feasible system. It was also found that the degree of stability, or resilience of a system, depended on the minimum equilibrium population.

Developmental tumors and adjacent cortical dysplasia: single or dual pathology?

PubMed

Palmini, André; Paglioli, Eliseu; Silva, Vinicius Duval

2013-12-01

Developmental tumors often lead to refractory partial seizures and constitute a well-defined, surgically remediable epilepsy syndrome. Dysplastic features are often associated with these tumors, and their significance carries both practical and conceptual relevance. If associated focal cortical dysplasia (FCD) relates to the extent of the epileptogenic tissue, then presurgical evaluation and surgical strategies should target both the tumor and the surrounding dyslaminated cortex. Furthermore, the association has been included in the recently revised classification of FCD and the epileptogenicity of this associated dysplastic tissue is crucial to validate such revision. In addition to the possibility of representing dual pathology, the association of developmental tumors and adjacent dysplasia may instead represent a single developmental lesion with distinct parts distributed along a histopathologic continuum. Moreover, the possibility that this adjacent dyslamination is of minor epileptogenic relevance should also be entertained. Surgical data show that complete resection of the solid tumors and immediately adjacent tissue harboring satellites may disrupt epileptogenic networks and lead to high rates of seizure freedom, challenging the epileptogenic relevance of more extensive adjacent dyslaminated cortex. Whether the latter is a primary or secondary abnormality and whether dyslaminated cortex in the context of a second lesion may produce seizures after complete resection of the main lesion is still to be proven. Wiley Periodicals, Inc. © 2013 International League Against Epilepsy.

Endothelial network formed with human dermal microvascular endothelial cells in autologous multicellular skin substitutes.

PubMed

Ponec, Maria; El Ghalbzouri, Abdoelwaheb; Dijkman, Remco; Kempenaar, Johanna; van der Pluijm, Gabri; Koolwijk, Pieter

2004-01-01

A human skin equivalent from a single skin biopsy harboring keratinocytes and melanocytes in the epidermal compartment, and fibroblasts and microvascular dermal endothelial cells in the dermal compartment was developed. The results of the study revealed that the nature of the extracellular matrix of the dermal compartments plays an important role in establishment of endothelial network in vitro. With rat-tail type I collagen matrices only lateral but not vertical expansion of endothelial networks was observed. In contrast, the presence of extracellular matrix of entirely human origin facilitated proper spatial organization of the endothelial network. Namely, when human dermal fibroblasts and microvascular endothelial cells were seeded on the bottom of an inert filter and subsequently epidermal cells were seeded on top of it, fibroblasts produced extracellular matrix throughout which numerous branched tubes were spreading three-dimensionally. Fibroblasts also facilitated the formation of basement membrane at the epidermal/matrix interface. Under all culture conditions, fully differentiated epidermis was formed with numerous melanocytes present in the basal epidermal cell layer. The results of the competitive RT-PCR revealed that both keratinocytes and fibroblasts expressed VEGF-A, -B, -C, aFGF and bFGF mRNA, whereas fibroblasts also expressed VEGF-D mRNA. At protein level, keratinocytes produced 10 times higher amounts of VEGF-A than fibroblasts did. The generation of multicellular skin equivalent from a single human skin biopsy will stimulate further developments for its application in the treatment of full-thickness skin defects. The potential development of biodegradable, biocompatible material suitable for these purposes is a great challenge for future research.

Mean Green operators of deformable fiber networks embedded in a compliant matrix and property estimates

NASA Astrophysics Data System (ADS)

Franciosi, Patrick; Spagnuolo, Mario; Salman, Oguz Umut

2018-04-01

Composites comprising included phases in a continuous matrix constitute a huge class of meta-materials, whose effective properties, whether they be mechanical, physical or coupled, can be selectively optimized by using appropriate phase arrangements and architectures. An important subclass is represented by "network-reinforced matrices," say those materials in which one or more of the embedded phases are co-continuous with the matrix in one or more directions. In this article, we present a method to study effective properties of simple such structures from which more complex ones can be accessible. Effective properties are shown, in the framework of linear elasticity, estimable by using the global mean Green operator for the entire embedded fiber network which is by definition through sample spanning. This network operator is obtained from one of infinite planar alignments of infinite fibers, which the network can be seen as an interpenetrated set of, with the fiber interactions being fully accounted for in the alignments. The mean operator of such alignments is given in exact closed form for isotropic elastic-like or dielectric-like matrices. We first exemplify how these operators relevantly provide, from classic homogenization frameworks, effective properties in the case of 1D fiber bundles embedded in an isotropic elastic-like medium. It is also shown that using infinite patterns with fully interacting elements over their whole influence range at any element concentration suppresses the dilute approximation limit of these frameworks. We finally present a construction method for a global operator of fiber networks described as interpenetrated such bundles.

Parallel protein secondary structure prediction based on neural networks.

PubMed

Zhong, Wei; Altun, Gulsah; Tian, Xinmin; Harrison, Robert; Tai, Phang C; Pan, Yi

2004-01-01

Protein secondary structure prediction has a fundamental influence on today's bioinformatics research. In this work, binary and tertiary classifiers of protein secondary structure prediction are implemented on Denoeux belief neural network (DBNN) architecture. Hydrophobicity matrix, orthogonal matrix, BLOSUM62 and PSSM (position specific scoring matrix) are experimented separately as the encoding schemes for DBNN. The experimental results contribute to the design of new encoding schemes. New binary classifier for Helix versus not Helix ( approximately H) for DBNN produces prediction accuracy of 87% when PSSM is used for the input profile. The performance of DBNN binary classifier is comparable to other best prediction methods. The good test results for binary classifiers open a new approach for protein structure prediction with neural networks. Due to the time consuming task of training the neural networks, Pthread and OpenMP are employed to parallelize DBNN in the hyperthreading enabled Intel architecture. Speedup for 16 Pthreads is 4.9 and speedup for 16 OpenMP threads is 4 in the 4 processors shared memory architecture. Both speedup performance of OpenMP and Pthread is superior to that of other research. With the new parallel training algorithm, thousands of amino acids can be processed in reasonable amount of time. Our research also shows that hyperthreading technology for Intel architecture is efficient for parallel biological algorithms.

MUFOLD-SS: New deep inception-inside-inception networks for protein secondary structure prediction.

PubMed

Fang, Chao; Shang, Yi; Xu, Dong

2018-05-01

Protein secondary structure prediction can provide important information for protein 3D structure prediction and protein functions. Deep learning offers a new opportunity to significantly improve prediction accuracy. In this article, a new deep neural network architecture, named the Deep inception-inside-inception (Deep3I) network, is proposed for protein secondary structure prediction and implemented as a software tool MUFOLD-SS. The input to MUFOLD-SS is a carefully designed feature matrix corresponding to the primary amino acid sequence of a protein, which consists of a rich set of information derived from individual amino acid, as well as the context of the protein sequence. Specifically, the feature matrix is a composition of physio-chemical properties of amino acids, PSI-BLAST profile, and HHBlits profile. MUFOLD-SS is composed of a sequence of nested inception modules and maps the input matrix to either eight states or three states of secondary structures. The architecture of MUFOLD-SS enables effective processing of local and global interactions between amino acids in making accurate prediction. In extensive experiments on multiple datasets, MUFOLD-SS outperformed the best existing methods and other deep neural networks significantly. MUFold-SS can be downloaded from http://dslsrv8.cs.missouri.edu/~cf797/MUFoldSS/download.html. © 2018 Wiley Periodicals, Inc.

Fetal brain extracellular matrix boosts neuronal network formation in 3D bioengineered model of cortical brain tissue.

PubMed

Sood, Disha; Chwalek, Karolina; Stuntz, Emily; Pouli, Dimitra; Du, Chuang; Tang-Schomer, Min; Georgakoudi, Irene; Black, Lauren D; Kaplan, David L

2016-01-01

The extracellular matrix (ECM) constituting up to 20% of the organ volume is a significant component of the brain due to its instructive role in the compartmentalization of functional microdomains in every brain structure. The composition, quantity and structure of ECM changes dramatically during the development of an organism greatly contributing to the remarkably sophisticated architecture and function of the brain. Since fetal brain is highly plastic, we hypothesize that the fetal brain ECM may contain cues promoting neural growth and differentiation, highly desired in regenerative medicine. Thus, we studied the effect of brain-derived fetal and adult ECM complemented with matricellular proteins on cortical neurons using in vitro 3D bioengineered model of cortical brain tissue. The tested parameters included neuronal network density, cell viability, calcium signaling and electrophysiology. Both, adult and fetal brain ECM as well as matricellular proteins significantly improved neural network formation as compared to single component, collagen I matrix. Additionally, the brain ECM improved cell viability and lowered glutamate release. The fetal brain ECM induced superior neural network formation, calcium signaling and spontaneous spiking activity over adult brain ECM. This study highlights the difference in the neuroinductive properties of fetal and adult brain ECM and suggests that delineating the basis for this divergence may have implications for regenerative medicine.

Connectivity and propagule sources composition drive ditch plant metacommunity structure

NASA Astrophysics Data System (ADS)

Favre-Bac, Lisa; Ernoult, Aude; Mony, Cendrine; Rantier, Yann; Nabucet, Jean; Burel, Françoise

2014-11-01

The fragmentation of agricultural landscapes has a major impact on biodiversity. In addition to habitat loss, dispersal limitation increasingly appears as a significant driver of biodiversity decline. Landscape linear elements, like ditches, may reduce the negative impacts of fragmentation by enhancing connectivity for many organisms, in addition to providing refuge habitats. To characterize these effects, we investigated the respective roles of propagule source composition and connectivity at the landscape scale on hydrochorous and non-hydrochorous ditch bank plant metacommunities. Twenty-seven square sites (0.5 km2 each) were selected in an agricultural lowland of northern France. At each site, plant communities were sampled on nine ditch banks (totaling 243 ditches). Variables characterizing propagule sources composition and connectivity were calculated for landscape mosaic and ditch network models. The landscape mosaic influenced only non-hydrochorous species, while the ditch network impacted both hydrochorous and non-hydrochorous species. Non-hydrochorous metacommunities were dependent on a large set of land-use elements, either within the landscape mosaic or adjacent to the ditch network, whereas hydrochorous plant metacommunities were only impacted by the presence of ditches adjacent to crops and roads. Ditch network connectivity also influenced both hydrochorous and non-hydrochorous ditch bank plant metacommunity structure, suggesting that beyond favoring hydrochory, ditches may also enhance plant dispersal by acting on other dispersal vectors. Increasing propagule sources heterogeneity and connectivity appeared to decrease within-metacommunity similarity within landscapes. Altogether, our results suggest that the ditch network's composition and configuration impacts plant metacommunity structure by affecting propagule dispersal possibilities, with contrasted consequences depending on species' dispersal vectors.

Cost-effective optical switch matrix for microwave phased-array

NASA Technical Reports Server (NTRS)

Pan, J. J.; Chia, S. L.; Li, W. Z.; Grove, C. H.

1991-01-01

An all-fiber (6x6) optical shutter switch matrix with the control system for microwave phased array has been demonstrated. The device offers the advantages of integrated configuration, low cost, low power consumption, small size, and light weight. The maximum extinction ratio (among 36 individual pixel) of this switch matrix at 840 nm is 24.2 dB, and the switching time is less than 120 microsec. In addition to phased array application, this low cost switch matrix is extremely attractive for fiber optic switching networks.

In vivo Quantification of the Structural Changes of Collagens in a Melanoma Microenvironment with Second and Third Harmonic Generation Microscopy

NASA Astrophysics Data System (ADS)

Wu, Pei-Chun; Hsieh, Tsung-Yuan; Tsai, Zen-Uong; Liu, Tzu-Ming

2015-03-01

Using in vivo second harmonic generation (SHG) and third harmonic generation (THG) microscopies, we tracked the course of collagen remodeling over time in the same melanoma microenvironment within an individual mouse. The corresponding structural and morphological changes were quantitatively analyzed without labeling using an orientation index (OI), the gray level co-occurrence matrix (GLCM) method, and the intensity ratio of THG to SHG (RTHG/SHG). In the early stage of melanoma development, we found that collagen fibers adjacent to a melanoma have increased OI values and SHG intensities. In the late stages, these collagen networks have more directionality and less homogeneity. The corresponding GLCM traces showed oscillation features and the sum of squared fluctuation VarGLCM increased with the tumor sizes. In addition, the THG intensities of the extracellular matrices increased, indicating an enhanced optical inhomogeneity. Multiplying OI, VarGLCM, and RTHG/SHG together, the combinational collagen remodeling (CR) index at 4 weeks post melanoma implantation showed a 400-times higher value than normal ones. These results validate that our quantitative indices of SHG and THG microscopies are sensitive enough to diagnose the collagen remodeling in vivo. We believe these indices have the potential to help the diagnosis of skin cancers in clinical practice.

In vivo Quantification of the Structural Changes of Collagens in a Melanoma Microenvironment with Second and Third Harmonic Generation Microscopy

PubMed Central

Wu, Pei-Chun; Hsieh, Tsung-Yuan; Tsai, Zen-Uong; Liu, Tzu-Ming

2015-01-01

Using in vivo second harmonic generation (SHG) and third harmonic generation (THG) microscopies, we tracked the course of collagen remodeling over time in the same melanoma microenvironment within an individual mouse. The corresponding structural and morphological changes were quantitatively analyzed without labeling using an orientation index (OI), the gray level co-occurrence matrix (GLCM) method, and the intensity ratio of THG to SHG (RTHG/SHG). In the early stage of melanoma development, we found that collagen fibers adjacent to a melanoma have increased OI values and SHG intensities. In the late stages, these collagen networks have more directionality and less homogeneity. The corresponding GLCM traces showed oscillation features and the sum of squared fluctuation VarGLCM increased with the tumor sizes. In addition, the THG intensities of the extracellular matrices increased, indicating an enhanced optical inhomogeneity. Multiplying OI, VarGLCM, and RTHG/SHG together, the combinational collagen remodeling (CR) index at 4 weeks post melanoma implantation showed a 400-times higher value than normal ones. These results validate that our quantitative indices of SHG and THG microscopies are sensitive enough to diagnose the collagen remodeling in vivo. We believe these indices have the potential to help the diagnosis of skin cancers in clinical practice. PMID:25748390

Industrial entrepreneurial network: Structural and functional analysis

NASA Astrophysics Data System (ADS)

Medvedeva, M. A.; Davletbaev, R. H.; Berg, D. B.; Nazarova, J. J.; Parusheva, S. S.

2016-12-01

Structure and functioning of two model industrial entrepreneurial networks are investigated in the present paper. One of these networks is forming when implementing an integrated project and consists of eight agents, which interact with each other and external environment. The other one is obtained from the municipal economy and is based on the set of the 12 real business entities. Analysis of the networks is carried out on the basis of the matrix of mutual payments aggregated over the certain time period. The matrix is created by the methods of experimental economics. Social Network Analysis (SNA) methods and instruments were used in the present research. The set of basic structural characteristics was investigated: set of quantitative parameters such as density, diameter, clustering coefficient, different kinds of centrality, and etc. They were compared with the random Bernoulli graphs of the corresponding size and density. Discovered variations of random and entrepreneurial networks structure are explained by the peculiarities of agents functioning in production network. Separately, were identified the closed exchange circuits (cyclically closed contours of graph) forming an autopoietic (self-replicating) network pattern. The purpose of the functional analysis was to identify the contribution of the autopoietic network pattern in its gross product. It was found that the magnitude of this contribution is more than 20%. Such value allows using of the complementary currency in order to stimulate economic activity of network agents.

State feedback control design for Boolean networks.

PubMed

Liu, Rongjie; Qian, Chunjiang; Liu, Shuqian; Jin, Yu-Fang

2016-08-26

Driving Boolean networks to desired states is of paramount significance toward our ultimate goal of controlling the progression of biological pathways and regulatory networks. Despite recent computational development of controllability of general complex networks and structural controllability of Boolean networks, there is still a lack of bridging the mathematical condition on controllability to real boolean operations in a network. Further, no realtime control strategy has been proposed to drive a Boolean network. In this study, we applied semi-tensor product to represent boolean functions in a network and explored controllability of a boolean network based on the transition matrix and time transition diagram. We determined the necessary and sufficient condition for a controllable Boolean network and mapped this requirement in transition matrix to real boolean functions and structure property of a network. An efficient tool is offered to assess controllability of an arbitrary Boolean network and to determine all reachable and non-reachable states. We found six simplest forms of controllable 2-node Boolean networks and explored the consistency of transition matrices while extending these six forms to controllable networks with more nodes. Importantly, we proposed the first state feedback control strategy to drive the network based on the status of all nodes in the network. Finally, we applied our reachability condition to the major switch of P53 pathway to predict the progression of the pathway and validate the prediction with published experimental results. This control strategy allowed us to apply realtime control to drive Boolean networks, which could not be achieved by the current control strategy for Boolean networks. Our results enabled a more comprehensive understanding of the evolution of Boolean networks and might be extended to output feedback control design.

Modelling the initial phase of an epidemic using incidence and infection network data: 2009 H1N1 pandemic in Israel as a case study

PubMed Central

Katriel, G.; Yaari, R.; Huppert, A.; Roll, U.; Stone, L.

2011-01-01

This paper presents new computational and modelling tools for studying the dynamics of an epidemic in its initial stages that use both available incidence time series and data describing the population's infection network structure. The work is motivated by data collected at the beginning of the H1N1 pandemic outbreak in Israel in the summer of 2009. We formulated a new discrete-time stochastic epidemic SIR (susceptible-infected-recovered) model that explicitly takes into account the disease's specific generation-time distribution and the intrinsic demographic stochasticity inherent to the infection process. Moreover, in contrast with many other modelling approaches, the model allows direct analytical derivation of estimates for the effective reproductive number (Re) and of their credible intervals, by maximum likelihood and Bayesian methods. The basic model can be extended to include age–class structure, and a maximum likelihood methodology allows us to estimate the model's next-generation matrix by combining two types of data: (i) the incidence series of each age group, and (ii) infection network data that provide partial information of ‘who-infected-who’. Unlike other approaches for estimating the next-generation matrix, the method developed here does not require making a priori assumptions about the structure of the next-generation matrix. We show, using a simulation study, that even a relatively small amount of information about the infection network greatly improves the accuracy of estimation of the next-generation matrix. The method is applied in practice to estimate the next-generation matrix from the Israeli H1N1 pandemic data. The tools developed here should be of practical importance for future investigations of epidemics during their initial stages. However, they require the availability of data which represent a random sample of the real epidemic process. We discuss the conditions under which reporting rates may or may not influence our estimated quantities and the effects of bias. PMID:21247949

A Network View on Psychiatric Disorders: Network Clusters of Symptoms as Elementary Syndromes of Psychopathology

PubMed Central

Goekoop, Rutger; Goekoop, Jaap G.

2014-01-01

Introduction The vast number of psychopathological syndromes that can be observed in clinical practice can be described in terms of a limited number of elementary syndromes that are differentially expressed. Previous attempts to identify elementary syndromes have shown limitations that have slowed progress in the taxonomy of psychiatric disorders. Aim To examine the ability of network community detection (NCD) to identify elementary syndromes of psychopathology and move beyond the limitations of current classification methods in psychiatry. Methods 192 patients with unselected mental disorders were tested on the Comprehensive Psychopathological Rating Scale (CPRS). Principal component analysis (PCA) was performed on the bootstrapped correlation matrix of symptom scores to extract the principal component structure (PCS). An undirected and weighted network graph was constructed from the same matrix. Network community structure (NCS) was optimized using a previously published technique. Results In the optimal network structure, network clusters showed a 89% match with principal components of psychopathology. Some 6 network clusters were found, including "DEPRESSION", "MANIA", “ANXIETY”, "PSYCHOSIS", "RETARDATION", and "BEHAVIORAL DISORGANIZATION". Network metrics were used to quantify the continuities between the elementary syndromes. Conclusion We present the first comprehensive network graph of psychopathology that is free from the biases of previous classifications: a ‘Psychopathology Web’. Clusters within this network represent elementary syndromes that are connected via a limited number of bridge symptoms. Many problems of previous classifications can be overcome by using a network approach to psychopathology. PMID:25427156

Local interconnection neural networks

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhang Jiajun; Zhang Li; Yan Dapen

1993-06-01

The idea of a local interconnection neural network (LINN) is presentd and compared with the globally interconnected Hopfield model. Under the storage limit requirement, LINN is shown to offer the same associative memory capability as the global interconnection neural network while having a much smaller interconnection matrix. LINN can be readily implemented optically using the currently available spatial light modulators. 15 refs.

Identifying group discriminative and age regressive sub-networks from DTI-based connectivity via a unified framework of non-negative matrix factorization and graph embedding

PubMed Central

Ghanbari, Yasser; Smith, Alex R.; Schultz, Robert T.; Verma, Ragini

2014-01-01

Diffusion tensor imaging (DTI) offers rich insights into the physical characteristics of white matter (WM) fiber tracts and their development in the brain, facilitating a network representation of brain’s traffic pathways. Such a network representation of brain connectivity has provided a novel means of investigating brain changes arising from pathology, development or aging. The high dimensionality of these connectivity networks necessitates the development of methods that identify the connectivity building blocks or sub-network components that characterize the underlying variation in the population. In addition, the projection of the subject networks into the basis set provides a low dimensional representation of it, that teases apart different sources of variation in the sample, facilitating variation-specific statistical analysis. We propose a unified framework of non-negative matrix factorization and graph embedding for learning sub-network patterns of connectivity by their projective non-negative decomposition into a reconstructive basis set, as well as, additional basis sets representing variational sources in the population like age and pathology. The proposed framework is applied to a study of diffusion-based connectivity in subjects with autism that shows localized sparse sub-networks which mostly capture the changes related to pathology and developmental variations. PMID:25037933

Modeling the Chinese language as an evolving network

NASA Astrophysics Data System (ADS)

Liang, Wei; Shi, Yuming; Huang, Qiuling

2014-01-01

The evolution of Chinese language has three main features: the total number of characters is gradually increasing, new words are generated in the existing characters, and some old words are no longer used in daily-life language. Based on the features, we propose an evolving language network model. Finally, we use this model to simulate the character co-occurrence networks (nodes are characters, and two characters are connected by an edge if they are adjacent to each other) constructed from essays in 11 different periods of China, and find that characters that appear with high frequency in old words are likely to be reused when new words are formed.

Inter-wall bridging induced peeling of multi-walled carbon nanotubes during tensile failure in aluminum matrix composites.

PubMed

Chen, Biao; Li, Shufeng; Imai, Hisashi; Umeda, Junko; Takahashi, Makoto; Kondoh, Katsuyoshi

2015-02-01

In situ scanning electron microscopy (SEM) observation of a tensile test was performed to investigate the fracturing behavior of multi-walled carbon nanotubes (MWCNTs) in powder metallurgy Al matrix composites. A multiple peeling phenomenon during MWCNT fracturing was clearly observed. Its formation mechanism and resultant effect on the composite strength were examined. Through transition electron microscopy characterizations, it was observed that defective structures like inter-wall bridges cross-linked adjacent walls of MWCNTs. This structure was helpful to improve the inter-wall bonding conditions, leading to the effective load transfer between walls and resultant peeling behaviors of MWCNTs. These results might provide new understandings of the fracturing mechanisms of carbon nanotube reinforcements for designing high-performance nanocomposites. Copyright © 2014 Elsevier Ltd. All rights reserved.

Interfacial stress state present in a 'thin-slice' fibre push-out test

NASA Technical Reports Server (NTRS)

Kallas, M. N.; Koss, D. A.; Hahn, H. T.; Hellmann, J. R.

1992-01-01

An analysis of the stress distributions along the fiber-matrix interface in a 'thin-slice' fiber push-out test is presented for selected test geometries. For the small specimen thicknesses often required to displace large-diameter fibers with high interfacial shear strengths, finite element analysis indicates that large bending stresses may be present. The magnitude of these stresses and their spatial distribution can be very sensitive to the test configuration. For certain test geometries, the specimen configuration itself may alter the interfacial failure process from one which initiates due to a maximum in shear stress near the top surface adjacent to the indentor, to one which involves mixed mode crack growth up from the bottom surface and/or yielding within the matrix near the interface.

Analysis of harmonic spline gravity models for Venus and Mars

NASA Technical Reports Server (NTRS)

Bowin, Carl

1986-01-01

Methodology utilizing harmonic splines for determining the true gravity field from Line-Of-Sight (LOS) acceleration data from planetary spacecraft missions was tested. As is well known, the LOS data incorporate errors in the zero reference level that appear to be inherent in the processing procedure used to obtain the LOS vectors. The proposed method offers a solution to this problem. The harmonic spline program was converted from the VAX 11/780 to the Ridge 32C computer. The problem with the matrix inversion routine that improved inversion of the data matrices used in the Optimum Estimate program for global Earth studies was solved. The problem of obtaining a successful matrix inversion for a single rev supplemented by data for the two adjacent revs still remains.

Thin film photovoltaic device and process of manufacture

DOEpatents

Albright, S.P.; Chamberlin, R.

1997-10-07

Provided is a thin film photovoltaic device and a method of manufacturing the device. The thin film photovoltaic device comprises a film layer having particles which are smaller than about 30 microns in size held in an electrically insulating matrix material to reduce the potential for electrical shorting through the film layer. The film layer may be provided by depositing preformed particles onto a surrogate substrate and binding the particles in a film-forming matrix material to form a flexible sheet with the film layer. The flexible sheet may be separated from the surrogate substrate and cut into flexible strips. A plurality of the flexible strips may be located adjacent to and supported by a common supporting substrate to form a photovoltaic module having a plurality of electrically interconnected photovoltaic cells. 13 figs.

Thin film photovoltaic device and process of manufacture

DOEpatents

Albright, Scot P.; Chamberlin, Rhodes

1999-02-09

Provided is a thin film photovoltaic device and a method of manufacturing the device. The thin film photovoltaic device comprises a film layer having particles which are smaller than about 30 microns in size held in an electrically insulating matrix material to reduce the potential for electrical shorting through the film layer. The film layer may be provided by depositing preformed particles onto a surrogate substrate and binding the particles in a film-forming matrix material to form a flexible sheet with the film layer. The flexible sheet may be separated from the surrogate substrate and cut into flexible strips. A plurality of the flexible strips may be located adjacent to and supported by a common supporting substrate to form a photovoltaic module having a plurality of electrically interconnected photovoltaic cells.

Thin film photovoltaic device and process of manufacture

DOEpatents

Albright, S.P.; Chamberlin, R.

1999-02-09

Provided is a thin film photovoltaic device and a method of manufacturing the device. The thin film photovoltaic device comprises a film layer having particles which are smaller than about 30 microns in size held in an electrically insulating matrix material to reduce the potential for electrical shorting through the film layer. The film layer may be provided by depositing preformed particles onto a surrogate substrate and binding the particles in a film-forming matrix material to form a flexible sheet with the film layer. The flexible sheet may be separated from the surrogate substrate and cut into flexible strips. A plurality of the flexible strips may be located adjacent to and supported by a common supporting substrate to form a photovoltaic module having a plurality of electrically interconnected photovoltaic cells. 13 figs.

Thin film photovoltaic device and process of manufacture

DOEpatents

Albright, Scot P.; Chamberlin, Rhodes

1997-10-07

Provided is a thin film photovoltaic device and a method of manufacturing the device. The thin film photovoltaic device comprises a film layer having particles which are smaller than about 30 microns in size held in an electrically insulating matrix material to reduce the potential for electrical shorting through the film layer. The film layer may be provided by depositing preformed particles onto a surrogate substrate and binding the particles in a film-forming matrix material to form a flexible sheet with the film layer. The flexible sheet may be separated from the surrogate substrate and cut into flexible strips. A plurality of the flexible strips may be located adjacent to and supported by a common supporting substrate to form a photovoltaic module having a plurality of electrically interconnected photovoltaic cells.

A parametric study of variables that affect fiber microbuckling initiation in composite laminates. I - Analyses. II - Experiments

NASA Technical Reports Server (NTRS)

Guynn, E. G.; Ochoa, Ozden O.; Bradley, Walter L.

1992-01-01

The effects of the stacking sequence (orientation of plies adjacent to the 0-deg plies), free surfaces, fiber/matrix interfacial bond strength, initial fiber waviness, resin-rich regions, and nonlinear shear constitutive behavior of the resin on the initiation of fiber microbuckling in thermoplastic composites were investigated using nonlinear geometric and nonlinear 2D finite-element analyses. Results show that reductions in the resin shear tangent modulus, large amplitudes of the initial fiber waviness, and debonds each cause increases in the localized matrix shear strains; these increases lead in turn to premature initiation of fiber microbuckling. The numerical results are compared to experimental data obtained using three thermoplastic composite material systems: (1) commercial APC-2, (2) QUADRAX Unidirectional Interlaced Tape, and AU4U/PEEK.

The influence of passenger flow on the topology characteristics of urban rail transit networks

NASA Astrophysics Data System (ADS)

Hu, Yingyue; Chen, Feng; Chen, Peiwen; Tan, Yurong

2017-05-01

Current researches on the network characteristics of metro networks are generally carried out on topology networks without passenger flows running on it, thus more complex features of the networks with ridership loaded on it cannot be captured. In this study, we incorporated the load of metro networks, passenger volume, into the exploration of network features. Thus, the network can be examined in the context of operation, which is the ultimate purpose of the existence of a metro network. To this end, section load was selected as an edge weight to demonstrate the influence of ridership on the network, and a weighted calculation method for complex network indicators and robustness were proposed to capture the unique behaviors of a metro network with passengers flowing in it. The proposed method was applied on Beijing Subway. Firstly, the passenger volume in terms of daily origin and destination matrix was extracted from exhausted transit smart card data. Using the established approach and the matrix as weighting, common indicators of complex network including clustering coefficient, betweenness and degree were calculated, and network robustness were evaluated under potential attacks. The results were further compared to that of unweighted networks, and it suggests indicators of the network with consideration of passenger volumes differ from that without ridership to some extent, and networks tend to be more vulnerable than that without load on it. The significance sequence for the stations can be changed. By introducing passenger flow weighting, actual operation status of the network can be reflected more accurately. It is beneficial to determine the crucial stations and make precautionary measures for the entire network’s operation security.

An Efficient Scheme of Quantum Wireless Multi-hop Communication using Coefficient Matrix

NASA Astrophysics Data System (ADS)

Zhao, Bei; Zha, Xin-Wei; Duan, Ya-Jun; Sun, Xin-Mei

2015-08-01

By defining the coefficient matrix, a new quantum teleportation scheme in quantum wireless multi-hop network is proposed. With the help of intermediate nodes, an unknown qubit state can be teleported between two distant nodes which do not share entanglement in advance. Arbitrary Bell pairs and entanglement swapping are utilized for establishing quantum channel among intermediate nodes. Using collapsed matrix, the initial quantum state can be perfectly recovered at the destination.

Immunocytochemical characterization of ectopic enamel deposits and cementicles in human teeth.

PubMed

Bosshardt, Dieter D; Nanci, Antonio

2003-02-01

Despite the relative frequency and clinical relevance of radicular enamel deposits and cementicles, their etiology and nature are unknown. The purpose of the present study was therefore to evaluate the presence and distribution of mineralization-associated non-collagenous matrix proteins (NCPs) in various types of root-associated ectopic mineralizations. Human teeth were processed for embedding in epoxy or acrylic resins. Tissue sections were incubated with antibodies to amelogenins (AMEL), bone sialoprotein (BSP), and osteopontin (OPN). Radicular enamel deposits contained residual organic matrix that labeled for AMEL. In contrast, BSP and OPN were not detected in the residual enamel matrix, they were found in the cementum deposited on its surface as well as in collagen-free cementicle-like structures in the adjacent periodontal ligament. True cementicles consisted of a collagenous matrix intermixed with a non-collagenous ground substance. Labeling for BSP and OPN was mainly associated with the interfibrillar ground substance. No immunoreactivity for AMEL was detected in cementicles. These data indicate that ectopic enamel deposits on the root retain a high amount of AMEL, whereas cementicles contain BSP and OPN, two NCPs typically found in bone and cementum. These NCPs may, like in their normal tissue counterparts, play a role in the mineralization process.

Hidden secrets of deformation: Impact-induced compaction within a CV chondrite

NASA Astrophysics Data System (ADS)

Forman, L. V.; Bland, P. A.; Timms, N. E.; Collins, G. S.; Davison, T. M.; Ciesla, F. J.; Benedix, G. K.; Daly, L.; Trimby, P. W.; Yang, L.; Ringer, S. P.

2016-10-01

The CV3 Allende is one of the most extensively studied meteorites in worldwide collections. It is currently classified as S1-essentially unshocked-using the classification scheme of Stöffler et al. (1991), however recent modelling suggests the low porosity observed in Allende indicates the body should have undergone compaction-related deformation. In this study, we detail previously undetected evidence of impact through use of Electron Backscatter Diffraction mapping to identify deformation microstructures in chondrules, AOAs and matrix grains. Our results demonstrate that forsterite-rich chondrules commonly preserve crystal-plastic microstructures (particularly at their margins); that low-angle boundaries in deformed matrix grains of olivine have a preferred orientation; and that disparities in deformation occur between chondrules, surrounding and non-adjacent matrix grains. We find heterogeneous compaction effects present throughout the matrix, consistent with a highly porous initial material. Given the spatial distribution of these crystal-plastic deformation microstructures, we suggest that this is evidence that Allende has undergone impact-induced compaction from an initially heterogeneous and porous parent body. We suggest that current shock classifications (Stöffler et al., 1991) relying upon data from chondrule interiors do not constrain the complete shock history of a sample.

Fast mean and variance computation of the diffuse sound transmission through finite-sized thick and layered wall and floor systems

NASA Astrophysics Data System (ADS)

Decraene, Carolina; Dijckmans, Arne; Reynders, Edwin P. B.

2018-05-01

A method is developed for computing the mean and variance of the diffuse field sound transmission loss of finite-sized layered wall and floor systems that consist of solid, fluid and/or poroelastic layers. This is achieved by coupling a transfer matrix model of the wall or floor to statistical energy analysis subsystem models of the adjacent room volumes. The modal behavior of the wall is approximately accounted for by projecting the wall displacement onto a set of sinusoidal lateral basis functions. This hybrid modal transfer matrix-statistical energy analysis method is validated on multiple wall systems: a thin steel plate, a polymethyl methacrylate panel, a thick brick wall, a sandwich panel, a double-leaf wall with poro-elastic material in the cavity, and a double glazing. The predictions are compared with experimental data and with results obtained using alternative prediction methods such as the transfer matrix method with spatial windowing, the hybrid wave based-transfer matrix method, and the hybrid finite element-statistical energy analysis method. These comparisons confirm the prediction accuracy of the proposed method and the computational efficiency against the conventional hybrid finite element-statistical energy analysis method.

On structure-exploiting trust-region regularized nonlinear least squares algorithms for neural-network learning.

PubMed

Mizutani, Eiji; Demmel, James W

2003-01-01

This paper briefly introduces our numerical linear algebra approaches for solving structured nonlinear least squares problems arising from 'multiple-output' neural-network (NN) models. Our algorithms feature trust-region regularization, and exploit sparsity of either the 'block-angular' residual Jacobian matrix or the 'block-arrow' Gauss-Newton Hessian (or Fisher information matrix in statistical sense) depending on problem scale so as to render a large class of NN-learning algorithms 'efficient' in both memory and operation costs. Using a relatively large real-world nonlinear regression application, we shall explain algorithmic strengths and weaknesses, analyzing simulation results obtained by both direct and iterative trust-region algorithms with two distinct NN models: 'multilayer perceptrons' (MLP) and 'complementary mixtures of MLP-experts' (or neuro-fuzzy modular networks).

Shift-phase code multiplexing technique for holographic memories and optical interconnection

NASA Astrophysics Data System (ADS)

Honma, Satoshi; Muto, Shinzo; Okamoto, Atsushi

2008-03-01

Holographic technologies for optical memories and interconnection devices have been studied actively because of high storage capacity, many wiring patterns and high transmission rate. Among multiplexing techniques such as angular, phase code and wavelength-multiplexing, speckle multiplexing technique have gotten attention due to the simple optical setup having an adjustable random phase filter in only one direction. To keep simple construction and to suppress crosstalk among adjacent page data or wiring patterns for efficient holographic memories and interconnection, we have to consider about optimum randomness of the phase filter. The high randomness causes expanding an illumination area of reference beam on holographic media. On the other hands, the small randomness causes the crosstalk between adjacent hologram data. We have proposed the method of holographic multiplexing, shift-phase code multiplexing with a two-dimensional orthogonal matrix phase filter. A lot of orthogonal phase codes can be produced by shifting the phase filter in one direction. It is able to read and record the individual holograms with low crosstalk. We give the basic experimental result on holographic data multiplexing and consider the phase pattern of the filter to suppress the crosstalk between adjacent holograms sufficiently.

Computing the structural influence matrix for biological systems.

PubMed

Giordano, Giulia; Cuba Samaniego, Christian; Franco, Elisa; Blanchini, Franco

2016-06-01

We consider the problem of identifying structural influences of external inputs on steady-state outputs in a biological network model. We speak of a structural influence if, upon a perturbation due to a constant input, the ensuing variation of the steady-state output value has the same sign as the input (positive influence), the opposite sign (negative influence), or is zero (perfect adaptation), for any feasible choice of the model parameters. All these signs and zeros can constitute a structural influence matrix, whose (i, j) entry indicates the sign of steady-state influence of the jth system variable on the ith variable (the output caused by an external persistent input applied to the jth variable). Each entry is structurally determinate if the sign does not depend on the choice of the parameters, but is indeterminate otherwise. In principle, determining the influence matrix requires exhaustive testing of the system steady-state behaviour in the widest range of parameter values. Here we show that, in a broad class of biological networks, the influence matrix can be evaluated with an algorithm that tests the system steady-state behaviour only at a finite number of points. This algorithm also allows us to assess the structural effect of any perturbation, such as variations of relevant parameters. Our method is applied to nontrivial models of biochemical reaction networks and population dynamics drawn from the literature, providing a parameter-free insight into the system dynamics.

Collagen and mineral deposition in rabbit cortical bone during maturation and growth: effects on tissue properties.

PubMed

Isaksson, Hanna; Harjula, Terhi; Koistinen, Arto; Iivarinen, Jarkko; Seppänen, Kari; Arokoski, Jari P A; Brama, Pieter A; Jurvelin, Jukka S; Helminen, Heikki J

2010-12-01

We characterized the composition and mechanical properties of cortical bone during maturation and growth and in adult life in the rabbit. We hypothesized that the collagen network develops earlier than the mineralized matrix. Growth was monitored, and the rabbits were euthanized at birth (newborn), and at 1, 3, 6, 9, and 18 months of age. The collagen network was assessed biochemically (collagen content, enzymatic and non-enzymatic cross-links) in specimens from the mid-diaphysis of the tibia and femur and biomechanically (tensile testing) from decalcified whole tibia specimens. The mineralized matrix was analyzed using pQCT and 3-point bend tests from intact femur specimens. The collagen content and the Young's modulus of the collagen matrix increased significantly until the rabbits were 3 months old, and thereafter remained stable. The amount of HP and LP collagen cross-links increased continuously from newborn to 18 months of age, whereas PEN cross-links increased after 6 months of age. Bone mineral density and the Young's modulus of the mineralized bone increased until the rabbits were at least 6 months old. We concluded that substantial changes take place during the normal process of development in both the biochemical and biomechanical properties of rabbit cortical bone. In cortical bone, the collagen network reaches its mature composition and mechanical strength prior to the mineralized matrix. © 2010 Orthopaedic Research Society. Published by Wiley Periodicals, Inc.

Genome-wide mRNA and miRNA expression profiling reveal multiple regulatory networks in colorectal cancer

PubMed Central

Vishnubalaji, R; Hamam, R; Abdulla, M-H; Mohammed, M A V; Kassem, M; Al-Obeed, O; Aldahmash, A; Alajez, N M

2015-01-01

Despite recent advances in cancer management, colorectal cancer (CRC) remains the third most common cancer and a major health-care problem worldwide. MicroRNAs have recently emerged as key regulators of cancer development and progression by targeting multiple cancer-related genes; however, such regulatory networks are not well characterized in CRC. Thus, the aim of this study was to perform global messenger RNA (mRNA) and microRNA expression profiling in the same CRC samples and adjacent normal tissues and to identify potential miRNA-mRNA regulatory networks. Our data revealed 1273 significantly upregulated and 1902 downregulated genes in CRC. Pathway analysis revealed significant enrichment in cell cycle, integrated cancer, Wnt (wingless-type MMTV integration site family member), matrix metalloproteinase, and TGF-β pathways in CRC. Pharmacological inhibition of Wnt (using XAV939 or IWP-2) or TGF-β (using SB-431542) pathways led to dose- and time-dependent inhibition of CRC cell growth. Similarly, our data revealed up- (42) and downregulated (61) microRNAs in the same matched samples. Using target prediction and bioinformatics, ~77% of the upregulated genes were predicted to be targeted by microRNAs found to be downregulated in CRC. We subsequently focused on EZH2 (enhancer of zeste homolog 2 ), which was found to be regulated by hsa-miR-26a-5p and several members of the let-7 (lethal-7) family in CRC. Significant inverse correlation between EZH2 and hsa-miR-26a-5p (R2=0.56, P=0.0001) and hsa-let-7b-5p (R2=0.19, P=0.02) expression was observed in the same samples, corroborating the belief of EZH2 being a bona fide target for these two miRNAs in CRC. Pharmacological inhibition of EZH2 led to significant reduction in trimethylated histone H3 on lysine 27 (H3K27) methylation, marked reduction in cell proliferation, and migration in vitro. Concordantly, small interfering RNA-mediated knockdown of EZH2 led to similar effects on CRC cell growth in vitro. Therefore, our data have revealed several hundred potential miRNA-mRNA regulatory networks in CRC and suggest targeting relevant networks as potential therapeutic strategy for CRC. PMID:25611389

Genome-wide mRNA and miRNA expression profiling reveal multiple regulatory networks in colorectal cancer.

PubMed

Vishnubalaji, R; Hamam, R; Abdulla, M-H; Mohammed, M A V; Kassem, M; Al-Obeed, O; Aldahmash, A; Alajez, N M

2015-01-22

Despite recent advances in cancer management, colorectal cancer (CRC) remains the third most common cancer and a major health-care problem worldwide. MicroRNAs have recently emerged as key regulators of cancer development and progression by targeting multiple cancer-related genes; however, such regulatory networks are not well characterized in CRC. Thus, the aim of this study was to perform global messenger RNA (mRNA) and microRNA expression profiling in the same CRC samples and adjacent normal tissues and to identify potential miRNA-mRNA regulatory networks. Our data revealed 1273 significantly upregulated and 1902 downregulated genes in CRC. Pathway analysis revealed significant enrichment in cell cycle, integrated cancer, Wnt (wingless-type MMTV integration site family member), matrix metalloproteinase, and TGF-β pathways in CRC. Pharmacological inhibition of Wnt (using XAV939 or IWP-2) or TGF-β (using SB-431542) pathways led to dose- and time-dependent inhibition of CRC cell growth. Similarly, our data revealed up- (42) and downregulated (61) microRNAs in the same matched samples. Using target prediction and bioinformatics, ~77% of the upregulated genes were predicted to be targeted by microRNAs found to be downregulated in CRC. We subsequently focused on EZH2 (enhancer of zeste homolog 2 ), which was found to be regulated by hsa-miR-26a-5p and several members of the let-7 (lethal-7) family in CRC. Significant inverse correlation between EZH2 and hsa-miR-26a-5p (R(2)=0.56, P=0.0001) and hsa-let-7b-5p (R(2)=0.19, P=0.02) expression was observed in the same samples, corroborating the belief of EZH2 being a bona fide target for these two miRNAs in CRC. Pharmacological inhibition of EZH2 led to significant reduction in trimethylated histone H3 on lysine 27 (H3K27) methylation, marked reduction in cell proliferation, and migration in vitro. Concordantly, small interfering RNA-mediated knockdown of EZH2 led to similar effects on CRC cell growth in vitro. Therefore, our data have revealed several hundred potential miRNA-mRNA regulatory networks in CRC and suggest targeting relevant networks as potential therapeutic strategy for CRC.

Novel permutation measures for image encryption algorithms

NASA Astrophysics Data System (ADS)

Abd-El-Hafiz, Salwa K.; AbdElHaleem, Sherif H.; Radwan, Ahmed G.

2016-10-01

This paper proposes two measures for the evaluation of permutation techniques used in image encryption. First, a general mathematical framework for describing the permutation phase used in image encryption is presented. Using this framework, six different permutation techniques, based on chaotic and non-chaotic generators, are described. The two new measures are, then, introduced to evaluate the effectiveness of permutation techniques. These measures are (1) Percentage of Adjacent Pixels Count (PAPC) and (2) Distance Between Adjacent Pixels (DBAP). The proposed measures are used to evaluate and compare the six permutation techniques in different scenarios. The permutation techniques are applied on several standard images and the resulting scrambled images are analyzed. Moreover, the new measures are used to compare the permutation algorithms on different matrix sizes irrespective of the actual parameters used in each algorithm. The analysis results show that the proposed measures are good indicators of the effectiveness of the permutation technique.

An External Matrix-Assisted Laser Desorption Ionization Source for Flexible FT-ICR Mass Spectrometry Imaging with Internal Calibration on Adjacent Samples

NASA Astrophysics Data System (ADS)

Smith, Donald F.; Aizikov, Konstantin; Duursma, Marc C.; Giskes, Frans; Spaanderman, Dirk-Jan; McDonnell, Liam A.; O'Connor, Peter B.; Heeren, Ron M. A.

2011-01-01

We describe the construction and application of a new MALDI source for FT-ICR mass spectrometry imaging. The source includes a translational X-Y positioning stage with a 10 × 10 cm range of motion for analysis of large sample areas, a quadrupole for mass selection, and an external octopole ion trap with electrodes for the application of an axial potential gradient for controlled ion ejection. An off-line LC MALDI MS/MS run demonstrates the utility of the new source for data- and position-dependent experiments. A FT-ICR MS imaging experiment of a coronal rat brain section yields ˜200 unique peaks from m/z 400-1100 with corresponding mass-selected images. Mass spectra from every pixel are internally calibrated with respect to polymer calibrants collected from an adjacent slide.

40Ar/39Ar Data for White Mica, Biotite, and K-Feldspar Samples from Low-Grade Metamorphic Rocks in the Westminster Terrane and Adjacent Rocks, Maryland

USGS Publications Warehouse

Kunk, Michael J.; McAleer, Ryan J.

2008-01-01

This report contains reduced 40Ar/39Ar data of white mica and K-feldspar mineral separates and matrix of a whole rock phyllite, all from low-grade metamorphic rocks of the Westminster terrane and adjacent strata in central Maryland. This report presents these data in a preliminary form, but in more detail than can be accommodated in todays professional journals. Also included in this report is information on the location of the samples and a brief description of the samples. The data contained herein are not interpreted in a geological context, and care should be taken by readers unfamiliar with argon isotopic data in the use of these results; many of the individual apparent ages are not geologically meaningful. This report is primarily a detailed source document for subsequent publications that will integrate these data into a geological context.

Structural identifiability of cyclic graphical models of biological networks with latent variables.

PubMed

Wang, Yulin; Lu, Na; Miao, Hongyu

2016-06-13

Graphical models have long been used to describe biological networks for a variety of important tasks such as the determination of key biological parameters, and the structure of graphical model ultimately determines whether such unknown parameters can be unambiguously obtained from experimental observations (i.e., the identifiability problem). Limited by resources or technical capacities, complex biological networks are usually partially observed in experiment, which thus introduces latent variables into the corresponding graphical models. A number of previous studies have tackled the parameter identifiability problem for graphical models such as linear structural equation models (SEMs) with or without latent variables. However, the limited resolution and efficiency of existing approaches necessarily calls for further development of novel structural identifiability analysis algorithms. An efficient structural identifiability analysis algorithm is developed in this study for a broad range of network structures. The proposed method adopts the Wright's path coefficient method to generate identifiability equations in forms of symbolic polynomials, and then converts these symbolic equations to binary matrices (called identifiability matrix). Several matrix operations are introduced for identifiability matrix reduction with system equivalency maintained. Based on the reduced identifiability matrices, the structural identifiability of each parameter is determined. A number of benchmark models are used to verify the validity of the proposed approach. Finally, the network module for influenza A virus replication is employed as a real example to illustrate the application of the proposed approach in practice. The proposed approach can deal with cyclic networks with latent variables. The key advantage is that it intentionally avoids symbolic computation and is thus highly efficient. Also, this method is capable of determining the identifiability of each single parameter and is thus of higher resolution in comparison with many existing approaches. Overall, this study provides a basis for systematic examination and refinement of graphical models of biological networks from the identifiability point of view, and it has a significant potential to be extended to more complex network structures or high-dimensional systems.

Water in the presence of inert Lennard-Jones obstacles

NASA Astrophysics Data System (ADS)

Kurtjak, Mario; Urbic, Tomaz

2014-04-01

Water confined by the presence of a 'sea' of inert obstacles was examined. In the article, freely mobile two-dimensional Mercedes-Benz (MB) water put to a disordered, but fixed, matrix of Lennard-Jones disks was studied by the Monte Carlo computer simulations. For the MB water molecules in the matrix of Lennard-Jones disks, we explored the structures, hydrogen-bond-network formation and thermodynamics as a function of temperature and size and density of matrix particles. We found that the structure of model water is perturbed by the presence of the obstacles. Density of confined water, which was in equilibrium with the bulk water, was smaller than the density of the bulk water and the temperature dependence of the density of absorbed water did not show the density anomaly in the studied temperature range. The behaviour observed as a consequence of confinement is similar to that of increasing temperature, which can for a matrix lead to a process similar to capillary evaporation. At the same occupancy of space, smaller matrix molecules cause higher destruction effect on the absorbed water molecules than the bigger ones. We have also tested the hypothesis that at low matrix densities the obstacles induce an increased ordering and 'hydrogen bonding' of the MB model molecules, relative to pure fluid, while at high densities the obstacles reduce MB water structuring, as they prevent the fluid to form good 'hydrogen-bonding' networks. However, for the size of matrix molecules similar to that of water, we did not observe this effect.

INFLUENCE OF REMOTE SENSING IMAGERY SOURCE ON QUANTIFICATION OF RIPARIAN LAND COVER/LAND USE

EPA Science Inventory

This paper compares approaches to quantifying land cover/land use (LCLU) in riparian corridors of 23 watersheds in Oregon's Willamette Valley using aerial photography (AP) and Thematic Mapper (TM) imagery. For each imagery source, we quantified LCLU adjacent to stream networks ac...

Assessing impacts of land-applied manure from concentrated animal feeding operations on fish populations and communities

EPA Science Inventory

Concentrated animal feeding operation (CAFO) waste is a cost effective fertilizer. In the Midwest, networks of subsurface tile-drains expedite transport of animal hormones and nutrients from land-applied CAFO waste to adjacent waterways. The objective of this study was to evaluat...

Concentrations of hormones, pharmaceuticals and other micropollutants in groundwater affected by septic systems in New England and New York.

PubMed

Phillips, P J; Schubert, C; Argue, D; Fisher, I; Furlong, E T; Foreman, W; Gray, J; Chalmers, A

2015-04-15

Septic-system discharges can be an important source of micropollutants (including pharmaceuticals and endocrine active compounds) to adjacent groundwater and surface water systems. Groundwater samples were collected from well networks tapping glacial till in New England (NE) and sandy surficial aquifer New York (NY) during one sampling round in 2011. The NE network assesses the effect of a single large septic system that receives discharge from an extended health care facility for the elderly. The NY network assesses the effect of many small septic systems used seasonally on a densely populated portion of Fire Island. The data collected from these two networks indicate that hydrogeologic and demographic factors affect micropollutant concentrations in these systems. The highest micropollutant concentrations from the NE network were present in samples collected from below the leach beds and in a well downgradient of the leach beds. Total concentrations for personal care/domestic use compounds, pharmaceutical compounds and plasticizer compounds generally ranged from 1 to over 20 μg/L in the NE network samples. High tris(2-butoxyethyl phosphate) plasticizer concentrations in wells beneath and downgradient of the leach beds (>20 μg/L) may reflect the presence of this compound in cleaning agents at the extended health-care facility. The highest micropollutant concentrations for the NY network were present in the shoreline wells and reflect groundwater that is most affected by septic system discharges. One of the shoreline wells had personal care/domestic use, pharmaceutical, and plasticizer concentrations ranging from 0.4 to 5.7 μg/L. Estradiol equivalency quotient concentrations were also highest in a shoreline well sample (3.1 ng/L). Most micropollutant concentrations increase with increasing specific conductance and total nitrogen concentrations for shoreline well samples. These findings suggest that septic systems serving institutional settings and densely populated areas in coastal settings may be locally important sources of micropollutants to adjacent aquifer and marine systems. Published by Elsevier B.V.

TRANSMISSION NETWORK PLANNING METHOD FOR COMPARATIVE STUDIES (JOURNAL VERSION)

EPA Science Inventory

An automated transmission network planning method for comparative studies is presented. This method employs logical steps that may closely parallel those taken in practice by the planning engineers. Use is made of a sensitivity matrix to simulate the engineers' experience in sele...

Requirements management: A CSR's perspective

NASA Technical Reports Server (NTRS)

Thompson, Joanie

1991-01-01

The following subject areas are covered: customer service overview of network service request processing; Customer Service Representative (CSR) responsibility matrix; extract from a sample Memorandum of Understanding; Network Service Request Form and its instructions sample notification of receipt; and requirements management in the NASA Science Internet.

Multilayer neural networks for reduced-rank approximation.

PubMed

Diamantaras, K I; Kung, S Y

1994-01-01

This paper is developed in two parts. First, the authors formulate the solution to the general reduced-rank linear approximation problem relaxing the invertibility assumption of the input autocorrelation matrix used by previous authors. The authors' treatment unifies linear regression, Wiener filtering, full rank approximation, auto-association networks, SVD and principal component analysis (PCA) as special cases. The authors' analysis also shows that two-layer linear neural networks with reduced number of hidden units, trained with the least-squares error criterion, produce weights that correspond to the generalized singular value decomposition of the input-teacher cross-correlation matrix and the input data matrix. As a corollary the linear two-layer backpropagation model with reduced hidden layer extracts an arbitrary linear combination of the generalized singular vector components. Second, the authors investigate artificial neural network models for the solution of the related generalized eigenvalue problem. By introducing and utilizing the extended concept of deflation (originally proposed for the standard eigenvalue problem) the authors are able to find that a sequential version of linear BP can extract the exact generalized eigenvector components. The advantage of this approach is that it's easier to update the model structure by adding one more unit or pruning one or more units when the application requires it. An alternative approach for extracting the exact components is to use a set of lateral connections among the hidden units trained in such a way as to enforce orthogonality among the upper- and lower-layer weights. The authors call this the lateral orthogonalization network (LON) and show via theoretical analysis-and verify via simulation-that the network extracts the desired components. The advantage of the LON-based model is that it can be applied in a parallel fashion so that the components are extracted concurrently. Finally, the authors show the application of their results to the solution of the identification problem of systems whose excitation has a non-invertible autocorrelation matrix. Previous identification methods usually rely on the invertibility assumption of the input autocorrelation, therefore they can not be applied to this case.

Exact sampling of graphs with prescribed degree correlations

NASA Astrophysics Data System (ADS)

Bassler, Kevin E.; Del Genio, Charo I.; Erdős, Péter L.; Miklós, István; Toroczkai, Zoltán

2015-08-01

Many real-world networks exhibit correlations between the node degrees. For instance, in social networks nodes tend to connect to nodes of similar degree and conversely, in biological and technological networks, high-degree nodes tend to be linked with low-degree nodes. Degree correlations also affect the dynamics of processes supported by a network structure, such as the spread of opinions or epidemics. The proper modelling of these systems, i.e., without uncontrolled biases, requires the sampling of networks with a specified set of constraints. We present a solution to the sampling problem when the constraints imposed are the degree correlations. In particular, we develop an exact method to construct and sample graphs with a specified joint-degree matrix, which is a matrix providing the number of edges between all the sets of nodes of a given degree, for all degrees, thus completely specifying all pairwise degree correlations, and additionally, the degree sequence itself. Our algorithm always produces independent samples without backtracking. The complexity of the graph construction algorithm is {O}({NM}) where N is the number of nodes and M is the number of edges.

A network of discrete events for the representation and analysis of diffusion dynamics.

PubMed

Pintus, Alberto M; Pazzona, Federico G; Demontis, Pierfranco; Suffritti, Giuseppe B

2015-11-14

We developed a coarse-grained description of the phenomenology of diffusive processes, in terms of a space of discrete events and its representation as a network. Once a proper classification of the discrete events underlying the diffusive process is carried out, their transition matrix is calculated on the basis of molecular dynamics data. This matrix can be represented as a directed, weighted network where nodes represent discrete events, and the weight of edges is given by the probability that one follows the other. The structure of this network reflects dynamical properties of the process of interest in such features as its modularity and the entropy rate of nodes. As an example of the applicability of this conceptual framework, we discuss here the physics of diffusion of small non-polar molecules in a microporous material, in terms of the structure of the corresponding network of events, and explain on this basis the diffusivity trends observed. A quantitative account of these trends is obtained by considering the contribution of the various events to the displacement autocorrelation function.

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

NASA Astrophysics Data System (ADS)

Meng, Deyuan

2018-04-01

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

Molecular dynamics study on the evolution of interfacial dislocation network and mechanical properties of Ni-based single crystal superalloys

NASA Astrophysics Data System (ADS)

Li, Nan-Lin; Wu, Wen-Ping; Nie, Kai

2018-05-01

The evolution of misfit dislocation network at γ /γ‧ phase interface and tensile mechanical properties of Ni-based single crystal superalloys at various temperatures and strain rates are studied by using molecular dynamics (MD) simulations. From the simulations, it is found that with the increase of loading, the dislocation network effectively inhibits dislocations emitted in the γ matrix cutting into the γ‧ phase and absorbs the matrix dislocations to strengthen itself which increases the stability of structure. Under the influence of the temperature, the initial mosaic structure of dislocation network gradually becomes irregular, and the initial misfit stress and the elastic modulus slowly decline as temperature increasing. On the other hand, with the increase of the strain rate, it almost has no effect on the elastic modulus and the way of evolution of dislocation network, but contributes to the increases of the yield stress and tensile strength. Moreover, tension-compression asymmetry of Ni-based single crystal superalloys is also presented based on MD simulations.

Stress reduction in phase-separated, cross-linked networks: influence of phase structure and kinetics of reaction

PubMed Central

Szczepanski, Caroline R.; Stansbury, Jeffrey W.

2014-01-01

A mechanism for polymerization shrinkage and stress reduction was developed for heterogeneous networks formed via ambient, photo-initiated polymerization-induced phase separation (PIPS). The material system used consists of a bulk homopolymer matrix of triethylene glycol dimethacrylate (TEGDMA) modified with one of three non-reactive, linear prepolymers (poly-methyl, ethyl and butyl methacrylate). At higher prepolymer loading levels (10–20 wt%) an enhanced reduction in both shrinkage and polymerization stress is observed. The onset of gelation in these materials is delayed to a higher degree of methacrylate conversion (~15–25%), providing more time for phase structure evolution by thermodynamically driven monomer diffusion between immiscible phases prior to network macro-gelation. The resulting phase structure was probed by introducing a fluorescently tagged prepolymer into the matrix. The phase structure evolves from a dispersion of prepolymer at low loading levels to a fully co-continuous heterogeneous network at higher loadings. The bulk modulus in phase separated networks is equivalent or greater than that of poly(TEGDMA), despite a reduced polymerization rate and cross-link density in the prepolymer-rich domains. PMID:25418999

Application of the clinical matrix to the diagnosis of leukemia

NASA Astrophysics Data System (ADS)

Pakkala, Sampath Y.; Lin, Frank C.

1992-07-01

A system for diagnosing leukemia subtypes has been formulated using neural networks. The statistical data of the symptoms collected by hematologists is fed into a single training set using a neural network, where the network is trained by using fast backpropagation algorithm, which when done can help the general practitioners for making diagnoses on the basis of signs and symptoms alone.

Locating an imaging radar in Canada for identifying spaceborne objects

NASA Astrophysics Data System (ADS)

Schick, William G.

1992-12-01

This research presents a study of the maximal coverage p-median facility location problem as applied to the location of an imaging radar in Canada for imaging spaceborne objects. The classical mathematical formulation of the maximal coverage p-median problem is converted into network-flow with side constraint formulations that are developed using a scaled down version of the imaging radar location problem. Two types of network-flow with side constraint formulations are developed: a network using side constraints that simulates the gains in a generalized network; and a network resembling a multi-commodity flow problem that uses side constraints to force flow along identical arcs. These small formulations are expanded to encompass a case study using 12 candidate radar sites, and 48 satellites divided into three states. SAS/OR PROC NETFLOW was used to solve the network-flow with side constraint formulations. The case study show that potential for both formulations, although the simulated gains formulation encountered singular matrix computational difficulties as a result of the very organized nature of its side constraint matrix. The multi-commodity flow formulation, when combined with equi-distribution of flow constraints, provided solutions for various values of p, the number of facilities to be selected.

Pore-Scale Simulation and Sensitivity Analysis of Apparent Gas Permeability in Shale Matrix

PubMed Central

Zhang, Pengwei; Hu, Liming; Meegoda, Jay N.

2017-01-01

Extremely low permeability due to nano-scale pores is a distinctive feature of gas transport in a shale matrix. The permeability of shale depends on pore pressure, porosity, pore throat size and gas type. The pore network model is a practical way to explain the macro flow behavior of porous media from a microscopic point of view. In this research, gas flow in a shale matrix is simulated using a previously developed three-dimensional pore network model that includes typical bimodal pore size distribution, anisotropy and low connectivity of the pore structure in shale. The apparent gas permeability of shale matrix was calculated under different reservoir pressures corresponding to different gas exploitation stages. Results indicate that gas permeability is strongly related to reservoir gas pressure, and hence the apparent permeability is not a unique value during the shale gas exploitation, and simulations suggested that a constant permeability for continuum-scale simulation is not accurate. Hence, the reservoir pressures of different shale gas exploitations should be considered. In addition, a sensitivity analysis was also performed to determine the contributions to apparent permeability of a shale matrix from petro-physical properties of shale such as pore throat size and porosity. Finally, the impact of connectivity of nano-scale pores on shale gas flux was analyzed. These results would provide an insight into understanding nano/micro scale flows of shale gas in the shale matrix. PMID:28772465

Pore-Scale Simulation and Sensitivity Analysis of Apparent Gas Permeability in Shale Matrix.

PubMed

Zhang, Pengwei; Hu, Liming; Meegoda, Jay N

2017-01-25

Extremely low permeability due to nano-scale pores is a distinctive feature of gas transport in a shale matrix. The permeability of shale depends on pore pressure, porosity, pore throat size and gas type. The pore network model is a practical way to explain the macro flow behavior of porous media from a microscopic point of view. In this research, gas flow in a shale matrix is simulated using a previously developed three-dimensional pore network model that includes typical bimodal pore size distribution, anisotropy and low connectivity of the pore structure in shale. The apparent gas permeability of shale matrix was calculated under different reservoir pressures corresponding to different gas exploitation stages. Results indicate that gas permeability is strongly related to reservoir gas pressure, and hence the apparent permeability is not a unique value during the shale gas exploitation, and simulations suggested that a constant permeability for continuum-scale simulation is not accurate. Hence, the reservoir pressures of different shale gas exploitations should be considered. In addition, a sensitivity analysis was also performed to determine the contributions to apparent permeability of a shale matrix from petro-physical properties of shale such as pore throat size and porosity. Finally, the impact of connectivity of nano-scale pores on shale gas flux was analyzed. These results would provide an insight into understanding nano/micro scale flows of shale gas in the shale matrix.

Percolation in real interdependent networks

NASA Astrophysics Data System (ADS)

Radicchi, Filippo

2015-07-01

The function of a real network depends not only on the reliability of its own components, but is affected also by the simultaneous operation of other real networks coupled with it. Whereas theoretical methods of direct applicability to real isolated networks exist, the frameworks developed so far in percolation theory for interdependent network layers are of little help in practical contexts, as they are suited only for special models in the limit of infinite size. Here, we introduce a set of heuristic equations that takes as inputs the adjacency matrices of the layers to draw the entire phase diagram for the interconnected network. We demonstrate that percolation transitions in interdependent networks can be understood by decomposing these systems into uncoupled graphs: the intersection among the layers, and the remainders of the layers. When the intersection dominates the remainders, an interconnected network undergoes a smooth percolation transition. Conversely, if the intersection is dominated by the contribution of the remainders, the transition becomes abrupt even in small networks. We provide examples of real systems that have developed interdependent networks sharing cores of `high quality’ edges to prevent catastrophic failures.

Polarization-interference Jones-matrix mapping of biological crystal networks

NASA Astrophysics Data System (ADS)

Ushenko, O. G.; Dubolazov, O. V.; Pidkamin, L. Y.; Sidor, M. I.; Pavlyukovich, N.; Pavlyukovich, O.

2018-01-01

The paper consists of two parts. The first part presents short theoretical basics of the method of Jones-matrix mapping with the help of reference wave. It was provided experimentally measured coordinate distributions of modulus of Jones-matrix elements of polycrystalline film of bile. It was defined the values and ranges of changing of statistic moments, which characterize such distributions. The second part presents the data of statistic analysis of the distributions of matrix elements of polycrystalline film of urine of donors and patients with albuminuria. It was defined the objective criteria of differentiation of albuminuria.

A network dynamics approach to chemical reaction networks

NASA Astrophysics Data System (ADS)

van der Schaft, A. J.; Rao, S.; Jayawardhana, B.

2016-04-01

A treatment of a chemical reaction network theory is given from the perspective of nonlinear network dynamics, in particular of consensus dynamics. By starting from the complex-balanced assumption, the reaction dynamics governed by mass action kinetics can be rewritten into a form which allows for a very simple derivation of a number of key results in the chemical reaction network theory, and which directly relates to the thermodynamics and port-Hamiltonian formulation of the system. Central in this formulation is the definition of a balanced Laplacian matrix on the graph of chemical complexes together with a resulting fundamental inequality. This immediately leads to the characterisation of the set of equilibria and their stability. Furthermore, the assumption of complex balancedness is revisited from the point of view of Kirchhoff's matrix tree theorem. Both the form of the dynamics and the deduced behaviour are very similar to consensus dynamics, and provide additional perspectives to the latter. Finally, using the classical idea of extending the graph of chemical complexes by a 'zero' complex, a complete steady-state stability analysis of mass action kinetics reaction networks with constant inflows and mass action kinetics outflows is given, and a unified framework is provided for structure-preserving model reduction of this important class of open reaction networks.

Hydraulic tomography of discrete networks of conduits and fractures in a karstic aquifer by using a deterministic inversion algorithm

NASA Astrophysics Data System (ADS)

Fischer, P.; Jardani, A.; Lecoq, N.

2018-02-01

In this paper, we present a novel inverse modeling method called Discrete Network Deterministic Inversion (DNDI) for mapping the geometry and property of the discrete network of conduits and fractures in the karstified aquifers. The DNDI algorithm is based on a coupled discrete-continuum concept to simulate numerically water flows in a model and a deterministic optimization algorithm to invert a set of observed piezometric data recorded during multiple pumping tests. In this method, the model is partioned in subspaces piloted by a set of parameters (matrix transmissivity, and geometry and equivalent transmissivity of the conduits) that are considered as unknown. In this way, the deterministic optimization process can iteratively correct the geometry of the network and the values of the properties, until it converges to a global network geometry in a solution model able to reproduce the set of data. An uncertainty analysis of this result can be performed from the maps of posterior uncertainties on the network geometry or on the property values. This method has been successfully tested for three different theoretical and simplified study cases with hydraulic responses data generated from hypothetical karstic models with an increasing complexity of the network geometry, and of the matrix heterogeneity.

Biomechanical cell regulatory networks as complex adaptive systems in relation to cancer.

PubMed

Feller, Liviu; Khammissa, Razia Abdool Gafaar; Lemmer, Johan

2017-01-01

Physiological structure and function of cells are maintained by ongoing complex dynamic adaptive processes in the intracellular molecular pathways controlling the overall profile of gene expression, and by genes in cellular gene regulatory circuits. Cytogenetic mutations and non-genetic factors such as chronic inflammation or repetitive trauma, intrinsic mechanical stresses within extracellular matrix may induce redirection of gene regulatory circuits with abnormal reactivation of embryonic developmental programmes which can now drive cell transformation and cancer initiation, and later cancer progression and metastasis. Some of the non-genetic factors that may also favour cancerization are dysregulation in epithelial-mesenchymal interactions, in cell-to-cell communication, in extracellular matrix turnover, in extracellular matrix-to-cell interactions and in mechanotransduction pathways. Persistent increase in extracellular matrix stiffness, for whatever reason, has been shown to play an important role in cell transformation, and later in cancer cell invasion. In this article we review certain cell regulatory networks driving carcinogenesis, focussing on the role of mechanical stresses modulating structure and function of cells and their extracellular matrices.

Solute transport in a single fracture involving an arbitrary length decay chain with rock matrix comprising different geological layers.

PubMed

Mahmoudzadeh, Batoul; Liu, Longcheng; Moreno, Luis; Neretnieks, Ivars

2014-08-01

A model is developed to describe solute transport and retention in fractured rocks. It accounts for advection along the fracture, molecular diffusion from the fracture to the rock matrix composed of several geological layers, adsorption on the fracture surface, adsorption in the rock matrix layers and radioactive decay-chains. The analytical solution, obtained for the Laplace-transformed concentration at the outlet of the flowing channel, can conveniently be transformed back to the time domain by the use of the de Hoog algorithm. This allows one to readily include it into a fracture network model or a channel network model to predict nuclide transport through channels in heterogeneous fractured media consisting of an arbitrary number of rock units with piecewise constant properties. More importantly, the simulations made in this study recommend that it is necessary to account for decay-chains and also rock matrix comprising at least two different geological layers, if justified, in safety and performance assessment of the repositories for spent nuclear fuel. Copyright © 2014 Elsevier B.V. All rights reserved.

Matrix Interdiction Problem

NASA Astrophysics Data System (ADS)

Kasiviswanathan, Shiva Prasad; Pan, Feng

In the matrix interdiction problem, a real-valued matrix and an integer k is given. The objective is to remove a set of k matrix columns that minimizes in the residual matrix the sum of the row values, where the value of a row is defined to be the largest entry in that row. This combinatorial problem is closely related to bipartite network interdiction problem that can be applied to minimize the probability that an adversary can successfully smuggle weapons. After introducing the matrix interdiction problem, we study the computational complexity of this problem. We show that the matrix interdiction problem is NP-hard and that there exists a constant γ such that it is even NP-hard to approximate this problem within an n γ additive factor. We also present an algorithm for this problem that achieves an (n - k) multiplicative approximation ratio.

Identification of Conserved Moieties in Metabolic Networks by Graph Theoretical Analysis of Atom Transition Networks

DOE Office of Scientific and Technical Information (OSTI.GOV)

Haraldsdóttir, Hulda S.; Fleming, Ronan M. T.

Conserved moieties are groups of atoms that remain intact in all reactions of a metabolic network. Identification of conserved moieties gives insight into the structure and function of metabolic networks and facilitates metabolic modelling. All moiety conservation relations can be represented as nonnegative integer vectors in the left null space of the stoichiometric matrix corresponding to a biochemical network. Algorithms exist to compute such vectors based only on reaction stoichiometry but their computational complexity has limited their application to relatively small metabolic networks. Moreover, the vectors returned by existing algorithms do not, in general, represent conservation of a specific moietymore » with a defined atomic structure. Here, we show that identification of conserved moieties requires data on reaction atom mappings in addition to stoichiometry. We present a novel method to identify conserved moieties in metabolic networks by graph theoretical analysis of their underlying atom transition networks. Our method returns the exact group of atoms belonging to each conserved moiety as well as the corresponding vector in the left null space of the stoichiometric matrix. It can be implemented as a pipeline of polynomial time algorithms. Our implementation completes in under five minutes on a metabolic network with more than 4,000 mass balanced reactions. The scalability of the method enables extension of existing applications for moiety conservation relations to genome-scale metabolic networks. Finally, we also give examples of new applications made possible by elucidating the atomic structure of conserved moieties.« less

Identification of Conserved Moieties in Metabolic Networks by Graph Theoretical Analysis of Atom Transition Networks

PubMed Central

Haraldsdóttir, Hulda S.; Fleming, Ronan M. T.

2016-01-01

Conserved moieties are groups of atoms that remain intact in all reactions of a metabolic network. Identification of conserved moieties gives insight into the structure and function of metabolic networks and facilitates metabolic modelling. All moiety conservation relations can be represented as nonnegative integer vectors in the left null space of the stoichiometric matrix corresponding to a biochemical network. Algorithms exist to compute such vectors based only on reaction stoichiometry but their computational complexity has limited their application to relatively small metabolic networks. Moreover, the vectors returned by existing algorithms do not, in general, represent conservation of a specific moiety with a defined atomic structure. Here, we show that identification of conserved moieties requires data on reaction atom mappings in addition to stoichiometry. We present a novel method to identify conserved moieties in metabolic networks by graph theoretical analysis of their underlying atom transition networks. Our method returns the exact group of atoms belonging to each conserved moiety as well as the corresponding vector in the left null space of the stoichiometric matrix. It can be implemented as a pipeline of polynomial time algorithms. Our implementation completes in under five minutes on a metabolic network with more than 4,000 mass balanced reactions. The scalability of the method enables extension of existing applications for moiety conservation relations to genome-scale metabolic networks. We also give examples of new applications made possible by elucidating the atomic structure of conserved moieties. PMID:27870845

Identification of Conserved Moieties in Metabolic Networks by Graph Theoretical Analysis of Atom Transition Networks

DOE PAGES

Haraldsdóttir, Hulda S.; Fleming, Ronan M. T.

2016-11-21

Conserved moieties are groups of atoms that remain intact in all reactions of a metabolic network. Identification of conserved moieties gives insight into the structure and function of metabolic networks and facilitates metabolic modelling. All moiety conservation relations can be represented as nonnegative integer vectors in the left null space of the stoichiometric matrix corresponding to a biochemical network. Algorithms exist to compute such vectors based only on reaction stoichiometry but their computational complexity has limited their application to relatively small metabolic networks. Moreover, the vectors returned by existing algorithms do not, in general, represent conservation of a specific moietymore » with a defined atomic structure. Here, we show that identification of conserved moieties requires data on reaction atom mappings in addition to stoichiometry. We present a novel method to identify conserved moieties in metabolic networks by graph theoretical analysis of their underlying atom transition networks. Our method returns the exact group of atoms belonging to each conserved moiety as well as the corresponding vector in the left null space of the stoichiometric matrix. It can be implemented as a pipeline of polynomial time algorithms. Our implementation completes in under five minutes on a metabolic network with more than 4,000 mass balanced reactions. The scalability of the method enables extension of existing applications for moiety conservation relations to genome-scale metabolic networks. Finally, we also give examples of new applications made possible by elucidating the atomic structure of conserved moieties.« less

Identification of Conserved Moieties in Metabolic Networks by Graph Theoretical Analysis of Atom Transition Networks.

PubMed

Haraldsdóttir, Hulda S; Fleming, Ronan M T

2016-11-01

Conserved moieties are groups of atoms that remain intact in all reactions of a metabolic network. Identification of conserved moieties gives insight into the structure and function of metabolic networks and facilitates metabolic modelling. All moiety conservation relations can be represented as nonnegative integer vectors in the left null space of the stoichiometric matrix corresponding to a biochemical network. Algorithms exist to compute such vectors based only on reaction stoichiometry but their computational complexity has limited their application to relatively small metabolic networks. Moreover, the vectors returned by existing algorithms do not, in general, represent conservation of a specific moiety with a defined atomic structure. Here, we show that identification of conserved moieties requires data on reaction atom mappings in addition to stoichiometry. We present a novel method to identify conserved moieties in metabolic networks by graph theoretical analysis of their underlying atom transition networks. Our method returns the exact group of atoms belonging to each conserved moiety as well as the corresponding vector in the left null space of the stoichiometric matrix. It can be implemented as a pipeline of polynomial time algorithms. Our implementation completes in under five minutes on a metabolic network with more than 4,000 mass balanced reactions. The scalability of the method enables extension of existing applications for moiety conservation relations to genome-scale metabolic networks. We also give examples of new applications made possible by elucidating the atomic structure of conserved moieties.

Multi-Scale Multi-Physics Modeling of Matrix Transport Properties in Fractured Shale Reservoirs

NASA Astrophysics Data System (ADS)

Mehmani, A.; Prodanovic, M.

2014-12-01

Understanding the shale matrix flow behavior is imperative in successful reservoir development for hydrocarbon production and carbon storage. Without a predictive model, significant uncertainties in flowback from the formation, the communication between the fracture and matrix as well as proper fracturing practice will ensue. Informed by SEM images, we develop deterministic network models that couple pores from multiple scales and their respective fluid physics. The models are used to investigate sorption hysteresis as an affordable way of inferring the nanoscale pore structure in core scale. In addition, restricted diffusion as a function of pore shape, pore-throat size ratios and network connectivity is computed to make correct interpretation of the 2D NMR maps possible. Our novel pore network models have the ability to match sorption hysteresis measurements without any tuning parameters. The results clarify a common misconception of linking type 3 nitrogen hysteresis curves to only the shale pore shape and show promising sensitivty for nanopore structre inference in core scale. The results on restricted diffusion shed light on the importance of including shape factors in 2D NMR interpretations. A priori "weighting factors" as a function of pore-throat and throat-length ratio are presented and the effect of network connectivity on diffusion is quantitatively assessed. We are currently working on verifying our models with experimental data gathered from the Eagleford formation.