Infectious disease control using contact tracing in random and scale-free networks

PubMed Central

Kiss, Istvan Z; Green, Darren M; Kao, Rowland R

2005-01-01

Contact tracing aims to identify and isolate individuals that have been in contact with infectious individuals. The efficacy of contact tracing and the hierarchy of traced nodes—nodes with higher degree traced first—is investigated and compared on random and scale-free (SF) networks with the same number of nodes N and average connection K. For values of the transmission rate larger than a threshold, the final epidemic size on SF networks is smaller than that on corresponding random networks. While in random networks new infectious and traced nodes from all classes have similar average degrees, in SF networks the average degree of nodes that are in more advanced stages of the disease is higher at any given time. On SF networks tracing removes possible sources of infection with high average degree. However a higher tracing effort is required to control the epidemic than on corresponding random networks due to the high initial velocity of spread towards the highly connected nodes. An increased latency period fails to significantly improve contact tracing efficacy. Contact tracing has a limited effect if the removal rate of susceptible nodes is relatively high, due to the fast local depletion of susceptible nodes. PMID:16849217

Node Redeployment Algorithm Based on Stratified Connected Tree for Underwater Sensor Networks

PubMed Central

Liu, Jun; Jiang, Peng; Wu, Feng; Yu, Shanen; Song, Chunyue

2016-01-01

During the underwater sensor networks (UWSNs) operation, node drift with water environment causes network topology changes. Periodic node location examination and adjustment are needed to maintain good network monitoring quality as long as possible. In this paper, a node redeployment algorithm based on stratified connected tree for UWSNs is proposed. At every network adjustment moment, self-examination and adjustment on node locations are performed firstly. If a node is outside the monitored space, it returns to the last location recorded in its memory along straight line. Later, the network topology is stratified into a connected tree that takes the sink node as the root node by broadcasting ready information level by level, which can improve the network connectivity rate. Finally, with synthetically considering network coverage and connectivity rates, and node movement distance, the sink node performs centralized optimization on locations of leaf nodes in the stratified connected tree. Simulation results show that the proposed redeployment algorithm can not only keep the number of nodes in the monitored space as much as possible and maintain good network coverage and connectivity rates during network operation, but also reduce node movement distance during node redeployment and prolong the network lifetime. PMID:28029124

λ-augmented tree for robust data collection in Advanced Metering Infrastructure

DOE PAGES

Kamto, Joseph; Qian, Lijun; Li, Wei; ...

2016-01-01

In this study, tree multicast configuration of smart meters (SMs) can maintain the connectivity and meet the latency requirements for the Advanced Metering Infrastructure (AMI). However, such topology is extremely weak as any single failure suffices to break its connectivity. On the other hand, the impact of a SM node failure can be more or less significant: a noncut SM node will have a limited local impact compared to a cut SM node that will break the network connectivity. In this work, we design a highly connected tree with a set of backup links to minimize the weakness of treemore » topology of SMs. A topology repair scheme is proposed to address the impact of a SM node failure on the connectivity of the augmented tree network. It relies on a loop detection scheme to define the criticality of a SM node and specifically targets cut SM node by selecting backup parent SM to cover its children. Detailed algorithms to create such AMI tree and related theoretical and complexity analysis are provided with insightful simulation results: sufficient redundancy is provided to alleviate data loss at the cost of signaling overhead. It is however observed that biconnected tree provides the best compromise between the two entities.« less

λ-augmented tree for robust data collection in Advanced Metering Infrastructure

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

Kamto, Joseph; Qian, Lijun; Li, Wei

In this study, tree multicast configuration of smart meters (SMs) can maintain the connectivity and meet the latency requirements for the Advanced Metering Infrastructure (AMI). However, such topology is extremely weak as any single failure suffices to break its connectivity. On the other hand, the impact of a SM node failure can be more or less significant: a noncut SM node will have a limited local impact compared to a cut SM node that will break the network connectivity. In this work, we design a highly connected tree with a set of backup links to minimize the weakness of treemore » topology of SMs. A topology repair scheme is proposed to address the impact of a SM node failure on the connectivity of the augmented tree network. It relies on a loop detection scheme to define the criticality of a SM node and specifically targets cut SM node by selecting backup parent SM to cover its children. Detailed algorithms to create such AMI tree and related theoretical and complexity analysis are provided with insightful simulation results: sufficient redundancy is provided to alleviate data loss at the cost of signaling overhead. It is however observed that biconnected tree provides the best compromise between the two entities.« less

SOUNET: Self-Organized Underwater Wireless Sensor Network.

PubMed

Kim, Hee-Won; Cho, Ho-Shin

2017-02-02

In this paper, we propose an underwater wireless sensor network (UWSN) named SOUNET where sensor nodes form and maintain a tree-topological network for data gathering in a self-organized manner. After network topology discovery via packet flooding, the sensor nodes consistently update their parent node to ensure the best connectivity by referring to the timevarying neighbor tables. Such a persistent and self-adaptive method leads to high network connectivity without any centralized control, even when sensor nodes are added or unexpectedly lost. Furthermore, malfunctions that frequently happen in self-organized networks such as node isolation and closed loop are resolved in a simple way. Simulation results show that SOUNET outperforms other conventional schemes in terms of network connectivity, packet delivery ratio (PDR), and energy consumption throughout the network. In addition, we performed an experiment at the Gyeongcheon Lake in Korea using commercial underwater modems to verify that SOUNET works well in a real environment.

SOUNET: Self-Organized Underwater Wireless Sensor Network

PubMed Central

Kim, Hee-won; Cho, Ho-Shin

2017-01-01

In this paper, we propose an underwater wireless sensor network (UWSN) named SOUNET where sensor nodes form and maintain a tree-topological network for data gathering in a self-organized manner. After network topology discovery via packet flooding, the sensor nodes consistently update their parent node to ensure the best connectivity by referring to the time-varying neighbor tables. Such a persistent and self-adaptive method leads to high network connectivity without any centralized control, even when sensor nodes are added or unexpectedly lost. Furthermore, malfunctions that frequently happen in self-organized networks such as node isolation and closed loop are resolved in a simple way. Simulation results show that SOUNET outperforms other conventional schemes in terms of network connectivity, packet delivery ratio (PDR), and energy consumption throughout the network. In addition, we performed an experiment at the Gyeongcheon Lake in Korea using commercial underwater modems to verify that SOUNET works well in a real environment. PMID:28157164

Contextual Hub Analysis Tool (CHAT): A Cytoscape app for identifying contextually relevant hubs in biological networks.

PubMed

Muetze, Tanja; Goenawan, Ivan H; Wiencko, Heather L; Bernal-Llinares, Manuel; Bryan, Kenneth; Lynn, David J

2016-01-01

Highly connected nodes (hubs) in biological networks are topologically important to the structure of the network and have also been shown to be preferentially associated with a range of phenotypes of interest. The relative importance of a hub node, however, can change depending on the biological context. Here, we report a Cytoscape app, the Contextual Hub Analysis Tool (CHAT), which enables users to easily construct and visualize a network of interactions from a gene or protein list of interest, integrate contextual information, such as gene expression or mass spectrometry data, and identify hub nodes that are more highly connected to contextual nodes (e.g. genes or proteins that are differentially expressed) than expected by chance. In a case study, we use CHAT to construct a network of genes that are differentially expressed in Dengue fever, a viral infection. CHAT was used to identify and compare contextual and degree-based hubs in this network. The top 20 degree-based hubs were enriched in pathways related to the cell cycle and cancer, which is likely due to the fact that proteins involved in these processes tend to be highly connected in general. In comparison, the top 20 contextual hubs were enriched in pathways commonly observed in a viral infection including pathways related to the immune response to viral infection. This analysis shows that such contextual hubs are considerably more biologically relevant than degree-based hubs and that analyses which rely on the identification of hubs solely based on their connectivity may be biased towards nodes that are highly connected in general rather than in the specific context of interest. CHAT is available for Cytoscape 3.0+ and can be installed via the Cytoscape App Store ( http://apps.cytoscape.org/apps/chat).

Value of peripheral nodes in controlling multilayer scale-free networks

NASA Astrophysics Data System (ADS)

Zhang, Yan; Garas, Antonios; Schweitzer, Frank

2016-01-01

We analyze the controllability of a two-layer network, where driver nodes can be chosen randomly only from one layer. Each layer contains a scale-free network with directed links and the node dynamics depends on the incoming links from other nodes. We combine the in-degree and out-degree values to assign an importance value w to each node, and distinguish between peripheral nodes with low w and central nodes with high w . Based on numerical simulations, we find that the controllable part of the network is larger when choosing low w nodes to connect the two layers. The control is as efficient when peripheral nodes are driver nodes as it is for the case of more central nodes. However, if we assume a cost to utilize nodes that is proportional to their overall degree, utilizing peripheral nodes to connect the two layers or to act as driver nodes is not only the most cost-efficient solution, it is also the one that performs best in controlling the two-layer network among the different interconnecting strategies we have tested.

Highly designable phenotypes and mutational buffers emerge from a systematic mapping between network topology and dynamic output.

PubMed

Nochomovitz, Yigal D; Li, Hao

2006-03-14

Deciphering the design principles for regulatory networks is fundamental to an understanding of biological systems. We have explored the mapping from the space of network topologies to the space of dynamical phenotypes for small networks. Using exhaustive enumeration of a simple model of three- and four-node networks, we demonstrate that certain dynamical phenotypes can be generated by an atypically broad spectrum of network topologies. Such dynamical outputs are highly designable, much like certain protein structures can be designed by an unusually broad spectrum of sequences. The network topologies that encode a highly designable dynamical phenotype possess two classes of connections: a fully conserved core of dedicated connections that encodes the stable dynamical phenotype and a partially conserved set of variable connections that controls the transient dynamical flow. By comparing the topologies and dynamics of the three- and four-node network ensembles, we observe a large number of instances of the phenomenon of "mutational buffering," whereby addition of a fourth node suppresses phenotypic variation amongst a set of three-node networks.

Chimera-like states in structured heterogeneous networks

NASA Astrophysics Data System (ADS)

Li, Bo; Saad, David

2017-04-01

Chimera-like states are manifested through the coexistence of synchronous and asynchronous dynamics and have been observed in various systems. To analyze the role of network topology in giving rise to chimera-like states, we study a heterogeneous network model comprising two groups of nodes, of high and low degrees of connectivity. The architecture facilitates the analysis of the system, which separates into a densely connected coherent group of nodes, perturbed by their sparsely connected drifting neighbors. It describes a synchronous behavior of the densely connected group and scaling properties of the induced perturbations.

Key-Node-Separated Graph Clustering and Layouts for Human Relationship Graph Visualization.

PubMed

Itoh, Takayuki; Klein, Karsten

2015-01-01

Many graph-drawing methods apply node-clustering techniques based on the density of edges to find tightly connected subgraphs and then hierarchically visualize the clustered graphs. However, users may want to focus on important nodes and their connections to groups of other nodes for some applications. For this purpose, it is effective to separately visualize the key nodes detected based on adjacency and attributes of the nodes. This article presents a graph visualization technique for attribute-embedded graphs that applies a graph-clustering algorithm that accounts for the combination of connections and attributes. The graph clustering step divides the nodes according to the commonality of connected nodes and similarity of feature value vectors. It then calculates the distances between arbitrary pairs of clusters according to the number of connecting edges and the similarity of feature value vectors and finally places the clusters based on the distances. Consequently, the technique separates important nodes that have connections to multiple large clusters and improves the visibility of such nodes' connections. To test this technique, this article presents examples with human relationship graph datasets, including a coauthorship and Twitter communication network dataset.

Protograph LDPC Codes with Node Degrees at Least 3

NASA Technical Reports Server (NTRS)

Divsalar, Dariush; Jones, Christopher

2006-01-01

In this paper we present protograph codes with a small number of degree-3 nodes and one high degree node. The iterative decoding threshold for proposed rate 1/2 codes are lower, by about 0.2 dB, than the best known irregular LDPC codes with degree at least 3. The main motivation is to gain linear minimum distance to achieve low error floor. Also to construct rate-compatible protograph-based LDPC codes for fixed block length that simultaneously achieves low iterative decoding threshold and linear minimum distance. We start with a rate 1/2 protograph LDPC code with degree-3 nodes and one high degree node. Higher rate codes are obtained by connecting check nodes with degree-2 non-transmitted nodes. This is equivalent to constraint combining in the protograph. The condition where all constraints are combined corresponds to the highest rate code. This constraint must be connected to nodes of degree at least three for the graph to have linear minimum distance. Thus having node degree at least 3 for rate 1/2 guarantees linear minimum distance property to be preserved for higher rates. Through examples we show that the iterative decoding threshold as low as 0.544 dB can be achieved for small protographs with node degrees at least three. A family of low- to high-rate codes with minimum distance linearly increasing in block size and with capacity-approaching performance thresholds is presented. FPGA simulation results for a few example codes show that the proposed codes perform as predicted.

Effects of local and global network connectivity on synergistic epidemics

NASA Astrophysics Data System (ADS)

Broder-Rodgers, David; Pérez-Reche, Francisco J.; Taraskin, Sergei N.

2015-12-01

Epidemics in networks can be affected by cooperation in transmission of infection and also connectivity between nodes. An interplay between these two properties and their influence on epidemic spread are addressed in the paper. A particular type of cooperative effects (called synergy effects) is considered, where the transmission rate between a pair of nodes depends on the number of infected neighbors. The connectivity effects are studied by constructing networks of different topology, starting with lattices with only local connectivity and then with networks that have both local and global connectivity obtained by random bond-rewiring to nodes within a certain distance. The susceptible-infected-removed epidemics were found to exhibit several interesting effects: (i) for epidemics with strong constructive synergy spreading in networks with high local connectivity, the bond rewiring has a negative role in epidemic spread, i.e., it reduces invasion probability; (ii) in contrast, for epidemics with destructive or weak constructive synergy spreading on networks of arbitrary local connectivity, rewiring helps epidemics to spread; (iii) and, finally, rewiring always enhances the spread of epidemics, independent of synergy, if the local connectivity is low.

Effects of local and global network connectivity on synergistic epidemics.

PubMed

Broder-Rodgers, David; Pérez-Reche, Francisco J; Taraskin, Sergei N

2015-12-01

Epidemics in networks can be affected by cooperation in transmission of infection and also connectivity between nodes. An interplay between these two properties and their influence on epidemic spread are addressed in the paper. A particular type of cooperative effects (called synergy effects) is considered, where the transmission rate between a pair of nodes depends on the number of infected neighbors. The connectivity effects are studied by constructing networks of different topology, starting with lattices with only local connectivity and then with networks that have both local and global connectivity obtained by random bond-rewiring to nodes within a certain distance. The susceptible-infected-removed epidemics were found to exhibit several interesting effects: (i) for epidemics with strong constructive synergy spreading in networks with high local connectivity, the bond rewiring has a negative role in epidemic spread, i.e., it reduces invasion probability; (ii) in contrast, for epidemics with destructive or weak constructive synergy spreading on networks of arbitrary local connectivity, rewiring helps epidemics to spread; (iii) and, finally, rewiring always enhances the spread of epidemics, independent of synergy, if the local connectivity is low.

Connecting node and method for constructing a connecting node

NASA Technical Reports Server (NTRS)

Johnson, Christopher J. (Inventor); Raboin, Jasen L. (Inventor); Spexarth, Gary R. (Inventor)

2011-01-01

A connecting node comprises a polyhedral structure comprising a plurality of panels joined together at its side edges to form a spherical approximation, wherein at least one of the plurality of panels comprises a faceted surface being constructed with a passage for integrating with one of a plurality of elements comprising a docking port, a hatch, and a window that is attached to the connecting node. A method for manufacturing a connecting node comprises the steps of providing a plurality of panels, connecting the plurality of panels to form a spherical approximation, wherein each edge of each panel of the plurality is joined to another edge of another panel, and constructing at least one of the plurality of panels to include a passage for integrating at least one of a plurality of elements that may be attached to the connecting node.

Announcing Supercomputer Summit

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

Wells, Jack; Bland, Buddy; Nichols, Jeff

Summit is the next leap in leadership-class computing systems for open science. With Summit we will be able to address, with greater complexity and higher fidelity, questions concerning who we are, our place on earth, and in our universe. Summit will deliver more than five times the computational performance of Titan’s 18,688 nodes, using only approximately 3,400 nodes when it arrives in 2017. Like Titan, Summit will have a hybrid architecture, and each node will contain multiple IBM POWER9 CPUs and NVIDIA Volta GPUs all connected together with NVIDIA’s high-speed NVLink. Each node will have over half a terabyte ofmore » coherent memory (high bandwidth memory + DDR4) addressable by all CPUs and GPUs plus 800GB of non-volatile RAM that can be used as a burst buffer or as extended memory. To provide a high rate of I/O throughput, the nodes will be connected in a non-blocking fat-tree using a dual-rail Mellanox EDR InfiniBand interconnect. Upon completion, Summit will allow researchers in all fields of science unprecedented access to solving some of the world’s most pressing challenges.« less

ORA User’s Guide 2013

DTIC Science & Technology

2013-06-03

and a C++ computational backend . The most current version of ORA (3.0.8.5) software is available on the casos website: http://casos.cs.cmu.edu...optimizing a network’s design structure. ORA uses a Java interface for ease of use, and a C++ computational backend . The most current version of ORA...Eigenvector Centrality : Node most connected to other highly connected nodes. Assists in identifying those who can mobilize others Entity Class

Assortativity and leadership emerge from anti-preferential attachment in heterogeneous networks.

PubMed

Sendiña-Nadal, I; Danziger, M M; Wang, Z; Havlin, S; Boccaletti, S

2016-02-18

Real-world networks have distinct topologies, with marked deviations from purely random networks. Many of them exhibit degree-assortativity, with nodes of similar degree more likely to link to one another. Though microscopic mechanisms have been suggested for the emergence of other topological features, assortativity has proven elusive. Assortativity can be artificially implanted in a network via degree-preserving link permutations, however this destroys the graph's hierarchical clustering and does not correspond to any microscopic mechanism. Here, we propose the first generative model which creates heterogeneous networks with scale-free-like properties in degree and clustering distributions and tunable realistic assortativity. Two distinct populations of nodes are incrementally added to an initial network by selecting a subgraph to connect to at random. One population (the followers) follows preferential attachment, while the other population (the potential leaders) connects via anti-preferential attachment: they link to lower degree nodes when added to the network. By selecting the lower degree nodes, the potential leader nodes maintain high visibility during the growth process, eventually growing into hubs. The evolution of links in Facebook empirically validates the connection between the initial anti-preferential attachment and long term high degree. In this way, our work sheds new light on the structure and evolution of social networks.

Assortativity and leadership emerge from anti-preferential attachment in heterogeneous networks

NASA Astrophysics Data System (ADS)

Sendiña-Nadal, I.; Danziger, M. M.; Wang, Z.; Havlin, S.; Boccaletti, S.

2016-02-01

Real-world networks have distinct topologies, with marked deviations from purely random networks. Many of them exhibit degree-assortativity, with nodes of similar degree more likely to link to one another. Though microscopic mechanisms have been suggested for the emergence of other topological features, assortativity has proven elusive. Assortativity can be artificially implanted in a network via degree-preserving link permutations, however this destroys the graph’s hierarchical clustering and does not correspond to any microscopic mechanism. Here, we propose the first generative model which creates heterogeneous networks with scale-free-like properties in degree and clustering distributions and tunable realistic assortativity. Two distinct populations of nodes are incrementally added to an initial network by selecting a subgraph to connect to at random. One population (the followers) follows preferential attachment, while the other population (the potential leaders) connects via anti-preferential attachment: they link to lower degree nodes when added to the network. By selecting the lower degree nodes, the potential leader nodes maintain high visibility during the growth process, eventually growing into hubs. The evolution of links in Facebook empirically validates the connection between the initial anti-preferential attachment and long term high degree. In this way, our work sheds new light on the structure and evolution of social networks.

Multi-scale dynamics and relaxation of a tethered membrane in a solvent by Monte Carlo simulations

NASA Astrophysics Data System (ADS)

Pandey, Ras; Anderson, Kelly; Farmer, Barry

2006-03-01

A tethered membrane modeled by a flexible sheet dissipates entropy as it wrinkles and crumples. Nodes of a coarse grained membrane are connected via multiple pathways for dynamical modes to propagate. We consider a sheet with nodes connected by fluctuating bonds on a cubic lattice. The empty lattice sites constitute an effective solvent medium via node-solvent interaction. Each node execute its stochastic motion with the Metropolis algorithm subject to bond fluctuations, excluded volume constraints, and interaction energy. Dynamics and conformation of the sheet are examined at a low and a high temperature with attractive and repulsive node-node interactions for the contrast in an attractive solvent medium. Variations of the mean square displacement of the center node of the sheet and that of its center of mass with the time steps are examined in detail which show different power-law motion from short to long time regimes. Relaxation of the gyration radius and scaling of its asymptotic value with the molecular weight are examined.

Synchronization and long-time memory in neural networks with inhibitory hubs and synaptic plasticity

NASA Astrophysics Data System (ADS)

Bertolotti, Elena; Burioni, Raffaella; di Volo, Matteo; Vezzani, Alessandro

2017-01-01

We investigate the dynamical role of inhibitory and highly connected nodes (hub) in synchronization and input processing of leaky-integrate-and-fire neural networks with short term synaptic plasticity. We take advantage of a heterogeneous mean-field approximation to encode the role of network structure and we tune the fraction of inhibitory neurons fI and their connectivity level to investigate the cooperation between hub features and inhibition. We show that, depending on fI, highly connected inhibitory nodes strongly drive the synchronization properties of the overall network through dynamical transitions from synchronous to asynchronous regimes. Furthermore, a metastable regime with long memory of external inputs emerges for a specific fraction of hub inhibitory neurons, underlining the role of inhibition and connectivity also for input processing in neural networks.

Small worlds in space: Synchronization, spatial and relational modularity

NASA Astrophysics Data System (ADS)

Brede, M.

2010-06-01

In this letter we investigate networks that have been optimized to realize a trade-off between enhanced synchronization and cost of wire to connect the nodes in space. Analyzing the evolved arrangement of nodes in space and their corresponding network topology, a class of small-world networks characterized by spatial and network modularity is found. More precisely, for low cost of wire optimal configurations are characterized by a division of nodes into two spatial groups with maximum distance from each other, whereas network modularity is low. For high cost of wire, the nodes organize into several distinct groups in space that correspond to network modules connected on a ring. In between, spatially and relationally modular small-world networks are found.

Adaptive Connectivity Restoration from Node Failure(s) in Wireless Sensor Networks

PubMed Central

Wang, Huaiyuan; Ding, Xu; Huang, Cheng; Wu, Xiaobei

2016-01-01

Recently, there is a growing interest in the applications of wireless sensor networks (WSNs). A set of sensor nodes is deployed in order to collectively survey an area of interest and/or perform specific surveillance tasks in some of the applications, such as battlefield reconnaissance. Due to the harsh deployment environments and limited energy supply, nodes may fail, which impacts the connectivity of the whole network. Since a single node failure (cut-vertex) will destroy the connectivity and divide the network into disjoint blocks, most of the existing studies focus on the problem of single node failure. However, the failure of multiple nodes would be a disaster to the whole network and must be repaired effectively. Only few studies are proposed to handle the problem of multiple cut-vertex failures, which is a special case of multiple node failures. Therefore, this paper proposes a comprehensive solution to address the problems of node failure (single and multiple). Collaborative Single Node Failure Restoration algorithm (CSFR) is presented to solve the problem of single node failure only with cooperative communication, but CSFR-M, which is the extension of CSFR, handles the single node failure problem more effectively with node motion. Moreover, Collaborative Connectivity Restoration Algorithm (CCRA) is proposed on the basis of cooperative communication and node maneuverability to restore network connectivity after multiple nodes fail. CSFR-M and CCRA are reactive methods that initiate the connectivity restoration after detecting the node failure(s). In order to further minimize the energy dissipation, CCRA opts to simplify the recovery process by gridding. Moreover, the distance that an individual node needs to travel during recovery is reduced by choosing the nearest suitable candidates. Finally, extensive simulations validate the performance of CSFR, CSFR-M and CCRA. PMID:27690030

Isolation and Connectivity in Random Geometric Graphs with Self-similar Intensity Measures

NASA Astrophysics Data System (ADS)

Dettmann, Carl P.

2018-05-01

Random geometric graphs consist of randomly distributed nodes (points), with pairs of nodes within a given mutual distance linked. In the usual model the distribution of nodes is uniform on a square, and in the limit of infinitely many nodes and shrinking linking range, the number of isolated nodes is Poisson distributed, and the probability of no isolated nodes is equal to the probability the whole graph is connected. Here we examine these properties for several self-similar node distributions, including smooth and fractal, uniform and nonuniform, and finitely ramified or otherwise. We show that nonuniformity can break the Poisson distribution property, but it strengthens the link between isolation and connectivity. It also stretches out the connectivity transition. Finite ramification is another mechanism for lack of connectivity. The same considerations apply to fractal distributions as smooth, with some technical differences in evaluation of the integrals and analytical arguments.

Node Self-Deployment Algorithm Based on Pigeon Swarm Optimization for Underwater Wireless Sensor Networks

PubMed Central

Yu, Shanen; Xu, Yiming; Jiang, Peng; Wu, Feng; Xu, Huan

2017-01-01

At present, free-to-move node self-deployment algorithms aim at event coverage and cannot improve network coverage under the premise of considering network connectivity, network reliability and network deployment energy consumption. Thus, this study proposes pigeon-based self-deployment algorithm (PSA) for underwater wireless sensor networks to overcome the limitations of these existing algorithms. In PSA, the sink node first finds its one-hop nodes and maximizes the network coverage in its one-hop region. The one-hop nodes subsequently divide the network into layers and cluster in each layer. Each cluster head node constructs a connected path to the sink node to guarantee network connectivity. Finally, the cluster head node regards the ratio of the movement distance of the node to the change in the coverage redundancy ratio as the target function and employs pigeon swarm optimization to determine the positions of the nodes. Simulation results show that PSA improves both network connectivity and network reliability, decreases network deployment energy consumption, and increases network coverage. PMID:28338615

Announcing Supercomputer Summit

ScienceCinema

Wells, Jack; Bland, Buddy; Nichols, Jeff; Hack, Jim; Foertter, Fernanda; Hagen, Gaute; Maier, Thomas; Ashfaq, Moetasim; Messer, Bronson; Parete-Koon, Suzanne

2018-01-16

Summit is the next leap in leadership-class computing systems for open science. With Summit we will be able to address, with greater complexity and higher fidelity, questions concerning who we are, our place on earth, and in our universe. Summit will deliver more than five times the computational performance of Titan’s 18,688 nodes, using only approximately 3,400 nodes when it arrives in 2017. Like Titan, Summit will have a hybrid architecture, and each node will contain multiple IBM POWER9 CPUs and NVIDIA Volta GPUs all connected together with NVIDIA’s high-speed NVLink. Each node will have over half a terabyte of coherent memory (high bandwidth memory + DDR4) addressable by all CPUs and GPUs plus 800GB of non-volatile RAM that can be used as a burst buffer or as extended memory. To provide a high rate of I/O throughput, the nodes will be connected in a non-blocking fat-tree using a dual-rail Mellanox EDR InfiniBand interconnect. Upon completion, Summit will allow researchers in all fields of science unprecedented access to solving some of the world’s most pressing challenges.

A Game Theoretic Optimization Method for Energy Efficient Global Connectivity in Hybrid Wireless Sensor Networks

PubMed Central

Lee, JongHyup; Pak, Dohyun

2016-01-01

For practical deployment of wireless sensor networks (WSN), WSNs construct clusters, where a sensor node communicates with other nodes in its cluster, and a cluster head support connectivity between the sensor nodes and a sink node. In hybrid WSNs, cluster heads have cellular network interfaces for global connectivity. However, when WSNs are active and the load of cellular networks is high, the optimal assignment of cluster heads to base stations becomes critical. Therefore, in this paper, we propose a game theoretic model to find the optimal assignment of base stations for hybrid WSNs. Since the communication and energy cost is different according to cellular systems, we devise two game models for TDMA/FDMA and CDMA systems employing power prices to adapt to the varying efficiency of recent wireless technologies. The proposed model is defined on the assumptions of the ideal sensing field, but our evaluation shows that the proposed model is more adaptive and energy efficient than local selections. PMID:27589743

An Autonomous Connectivity Restoration Algorithm Based on Finite State Machine for Wireless Sensor-Actor Networks.

PubMed

Zhang, Ying; Wang, Jun; Hao, Guan

2018-01-08

With the development of autonomous unmanned intelligent systems, such as the unmanned boats, unmanned planes and autonomous underwater vehicles, studies on Wireless Sensor-Actor Networks (WSANs) have attracted more attention. Network connectivity algorithms play an important role in data exchange, collaborative detection and information fusion. Due to the harsh application environment, abnormal nodes often appear, and the network connectivity will be prone to be lost. Network self-healing mechanisms have become critical for these systems. In order to decrease the movement overhead of the sensor-actor nodes, an autonomous connectivity restoration algorithm based on finite state machine is proposed. The idea is to identify whether a node is a critical node by using a finite state machine, and update the connected dominating set in a timely way. If an abnormal node is a critical node, the nearest non-critical node will be relocated to replace the abnormal node. In the case of multiple node abnormality, a regional network restoration algorithm is introduced. It is designed to reduce the overhead of node movements while restoration happens. Simulation results indicate the proposed algorithm has better performance on the total moving distance and the number of total relocated nodes compared with some other representative restoration algorithms.

An Autonomous Connectivity Restoration Algorithm Based on Finite State Machine for Wireless Sensor-Actor Networks

PubMed Central

Zhang, Ying; Wang, Jun; Hao, Guan

2018-01-01

With the development of autonomous unmanned intelligent systems, such as the unmanned boats, unmanned planes and autonomous underwater vehicles, studies on Wireless Sensor-Actor Networks (WSANs) have attracted more attention. Network connectivity algorithms play an important role in data exchange, collaborative detection and information fusion. Due to the harsh application environment, abnormal nodes often appear, and the network connectivity will be prone to be lost. Network self-healing mechanisms have become critical for these systems. In order to decrease the movement overhead of the sensor-actor nodes, an autonomous connectivity restoration algorithm based on finite state machine is proposed. The idea is to identify whether a node is a critical node by using a finite state machine, and update the connected dominating set in a timely way. If an abnormal node is a critical node, the nearest non-critical node will be relocated to replace the abnormal node. In the case of multiple node abnormality, a regional network restoration algorithm is introduced. It is designed to reduce the overhead of node movements while restoration happens. Simulation results indicate the proposed algorithm has better performance on the total moving distance and the number of total relocated nodes compared with some other representative restoration algorithms. PMID:29316702

Method and apparatus for eliminating unsuccessful tries in a search tree

NASA Technical Reports Server (NTRS)

Peterson, John C. (Inventor); Chow, Edward (Inventor); Madan, Herb S. (Inventor)

1991-01-01

A circuit switching system in an M-ary, n-cube connected network completes a best-first path from an originating node to a destination node by latching valid legs of the path as the path is being sought out. Each network node is provided with a routing hyperswitch sub-network, (HSN) connected between that node and bidirectional high capacity communication channels of the n-cube network. The sub-networks are all controlled by routing algorithms which respond to message identification headings (headers) on messages to be routed along one or more routing legs. The header includes information embedded therein which is interpreted by each sub-network to route and historically update the header. A logic circuit, available at every node, implements the algorithm and automatically forwards or back-tracks the header in the network legs of various paths until a completed path is latched.

Towards understanding the behavior of physical systems using information theory

NASA Astrophysics Data System (ADS)

Quax, Rick; Apolloni, Andrea; Sloot, Peter M. A.

2013-09-01

One of the goals of complex network analysis is to identify the most influential nodes, i.e., the nodes that dictate the dynamics of other nodes. In the case of autonomous systems or transportation networks, highly connected hubs play a preeminent role in diffusing the flow of information and viruses; in contrast, in language evolution most linguistic norms come from the peripheral nodes who have only few contacts. Clearly a topological analysis of the interactions alone is not sufficient to identify the nodes that drive the state of the network. Here we show how information theory can be used to quantify how the dynamics of individual nodes propagate through a system. We interpret the state of a node as a storage of information about the state of other nodes, which is quantified in terms of Shannon information. This information is transferred through interactions and lost due to noise, and we calculate how far it can travel through a network. We apply this concept to a model of opinion formation in a complex social network to calculate the impact of each node by measuring how long its opinion is remembered by the network. Counter-intuitively we find that the dynamics of opinions are not determined by the hubs or peripheral nodes, but rather by nodes with an intermediate connectivity.

Brain connectivity aberrations in anabolic-androgenic steroid users.

PubMed

Westlye, Lars T; Kaufmann, Tobias; Alnæs, Dag; Hullstein, Ingunn R; Bjørnebekk, Astrid

2017-01-01

Sustained anabolic-androgenic steroid (AAS) use has adverse behavioral consequences, including aggression, violence and impulsivity. Candidate mechanisms include disruptions of brain networks with high concentrations of androgen receptors and critically involved in emotional and cognitive regulation. Here, we tested the effects of AAS on resting-state functional brain connectivity in the largest sample of AAS-users to date. We collected resting-state functional magnetic resonance imaging (fMRI) data from 151 males engaged in heavy resistance strength training. 50 users tested positive for AAS based on the testosterone to epitestosterone (T/E) ratio and doping substances in urine. 16 previous users and 59 controls tested negative. We estimated brain network nodes and their time-series using ICA and dual regression and defined connectivity matrices as the between-node partial correlations. In line with the emotional and behavioral consequences of AAS, current users exhibited reduced functional connectivity between key nodes involved in emotional and cognitive regulation, in particular reduced connectivity between the amygdala and default-mode network (DMN) and between the dorsal attention network (DAN) and a frontal node encompassing the superior and inferior frontal gyri (SFG/IFG) and the anterior cingulate cortex (ACC), with further reductions as a function of dependency, lifetime exposure, and cycle state (on/off).

Node Self-Deployment Algorithm Based on an Uneven Cluster with Radius Adjusting for Underwater Sensor Networks

PubMed Central

Jiang, Peng; Xu, Yiming; Wu, Feng

2016-01-01

Existing move-restricted node self-deployment algorithms are based on a fixed node communication radius, evaluate the performance based on network coverage or the connectivity rate and do not consider the number of nodes near the sink node and the energy consumption distribution of the network topology, thereby degrading network reliability and the energy consumption balance. Therefore, we propose a distributed underwater node self-deployment algorithm. First, each node begins the uneven clustering based on the distance on the water surface. Each cluster head node selects its next-hop node to synchronously construct a connected path to the sink node. Second, the cluster head node adjusts its depth while maintaining the layout formed by the uneven clustering and then adjusts the positions of in-cluster nodes. The algorithm originally considers the network reliability and energy consumption balance during node deployment and considers the coverage redundancy rate of all positions that a node may reach during the node position adjustment. Simulation results show, compared to the connected dominating set (CDS) based depth computation algorithm, that the proposed algorithm can increase the number of the nodes near the sink node and improve network reliability while guaranteeing the network connectivity rate. Moreover, it can balance energy consumption during network operation, further improve network coverage rate and reduce energy consumption. PMID:26784193

Assembly Mechanism of the Contractile Ring for Cytokinesis by Fission Yeast

NASA Astrophysics Data System (ADS)

Vavylonis, Dimitrios; Wu, Jian-Qiu; Huang, Xiaolei; O'Shaughnessy, Ben; Pollard, Thomas

2008-03-01

Animals and fungi assemble a contractile ring of actin filaments and the motor protein myosin to separate into individual daughter cells during cytokinesis. We studied the mechanism of contractile ring assembly in fission yeast with high time resolution confocal microscopy, computational image analysis methods, and numerical simulations. Approximately 63 nodes containing myosin, broadly distributed around the cell equator, assembled into a ring through stochastic motions, making many starts, stops, and changes of direction as they condense into a ring. Estimates of node friction coefficients from the mean square displacement of stationary nodes imply forces for node movement are greater than ˜ 4 pN, similarly to forces by a few molecular motors. Skeletonization and topology analysis of images of cells expressing fluorescent actin filament markers showed transient linear elements extending in all directions from myosin nodes and establishing connections among them. We propose a model with traction between nodes depending on transient connections established by stochastic search and capture (``search, capture, pull and release''). Numerical simulations of the model using parameter values obtained from experiment succesfully condense nodes into a continuous ring.

A Depth-Adjustment Deployment Algorithm Based on Two-Dimensional Convex Hull and Spanning Tree for Underwater Wireless Sensor Networks.

PubMed

Jiang, Peng; Liu, Shuai; Liu, Jun; Wu, Feng; Zhang, Le

2016-07-14

Most of the existing node depth-adjustment deployment algorithms for underwater wireless sensor networks (UWSNs) just consider how to optimize network coverage and connectivity rate. However, these literatures don't discuss full network connectivity, while optimization of network energy efficiency and network reliability are vital topics for UWSN deployment. Therefore, in this study, a depth-adjustment deployment algorithm based on two-dimensional (2D) convex hull and spanning tree (NDACS) for UWSNs is proposed. First, the proposed algorithm uses the geometric characteristics of a 2D convex hull and empty circle to find the optimal location of a sleep node and activate it, minimizes the network coverage overlaps of the 2D plane, and then increases the coverage rate until the first layer coverage threshold is reached. Second, the sink node acts as a root node of all active nodes on the 2D convex hull and then forms a small spanning tree gradually. Finally, the depth-adjustment strategy based on time marker is used to achieve the three-dimensional overall network deployment. Compared with existing depth-adjustment deployment algorithms, the simulation results show that the NDACS algorithm can maintain full network connectivity with high network coverage rate, as well as improved network average node degree, thus increasing network reliability.

A Depth-Adjustment Deployment Algorithm Based on Two-Dimensional Convex Hull and Spanning Tree for Underwater Wireless Sensor Networks

PubMed Central

Jiang, Peng; Liu, Shuai; Liu, Jun; Wu, Feng; Zhang, Le

2016-01-01

Most of the existing node depth-adjustment deployment algorithms for underwater wireless sensor networks (UWSNs) just consider how to optimize network coverage and connectivity rate. However, these literatures don’t discuss full network connectivity, while optimization of network energy efficiency and network reliability are vital topics for UWSN deployment. Therefore, in this study, a depth-adjustment deployment algorithm based on two-dimensional (2D) convex hull and spanning tree (NDACS) for UWSNs is proposed. First, the proposed algorithm uses the geometric characteristics of a 2D convex hull and empty circle to find the optimal location of a sleep node and activate it, minimizes the network coverage overlaps of the 2D plane, and then increases the coverage rate until the first layer coverage threshold is reached. Second, the sink node acts as a root node of all active nodes on the 2D convex hull and then forms a small spanning tree gradually. Finally, the depth-adjustment strategy based on time marker is used to achieve the three-dimensional overall network deployment. Compared with existing depth-adjustment deployment algorithms, the simulation results show that the NDACS algorithm can maintain full network connectivity with high network coverage rate, as well as improved network average node degree, thus increasing network reliability. PMID:27428970

Graph theoretic analysis of structural connectivity across the spectrum of Alzheimer's disease: The importance of graph creation methods

PubMed Central

Phillips, David J.; McGlaughlin, Alec; Ruth, David; Jager, Leah R.; Soldan, Anja

2015-01-01

Graph theory is increasingly being used to study brain connectivity across the spectrum of Alzheimer's disease (AD), but prior findings have been inconsistent, likely reflecting methodological differences. We systematically investigated how methods of graph creation (i.e., type of correlation matrix and edge weighting) affect structural network properties and group differences. We estimated the structural connectivity of brain networks based on correlation maps of cortical thickness obtained from MRI. Four groups were compared: 126 cognitively normal older adults, 103 individuals with Mild Cognitive Impairment (MCI) who retained MCI status for at least 3 years (stable MCI), 108 individuals with MCI who progressed to AD-dementia within 3 years (progressive MCI), and 105 individuals with AD-dementia. Small-world measures of connectivity (characteristic path length and clustering coefficient) differed across groups, consistent with prior studies. Groups were best discriminated by the Randić index, which measures the degree to which highly connected nodes connect to other highly connected nodes. The Randić index differentiated the stable and progressive MCI groups, suggesting that it might be useful for tracking and predicting the progression of AD. Notably, however, the magnitude and direction of group differences in all three measures were dependent on the method of graph creation, indicating that it is crucial to take into account how graphs are constructed when interpreting differences across diagnostic groups and studies. The algebraic connectivity measures showed few group differences, independent of the method of graph construction, suggesting that global connectivity as it relates to node degree is not altered in early AD. PMID:25984446

A Multi-Hop Clustering Mechanism for Scalable IoT Networks.

PubMed

Sung, Yoonyoung; Lee, Sookyoung; Lee, Meejeong

2018-03-23

It is expected that up to 26 billion Internet of Things (IoT) equipped with sensors and wireless communication capabilities will be connected to the Internet by 2020 for various purposes. With a large scale IoT network, having each node connected to the Internet with an individual connection may face serious scalability issues. The scalability problem of the IoT network may be alleviated by grouping the nodes of the IoT network into clusters and having a representative node in each cluster connect to the Internet on behalf of the other nodes in the cluster instead of having a per-node Internet connection and communication. In this paper, we propose a multi-hop clustering mechanism for IoT networks to minimize the number of required Internet connections. Specifically, the objective of proposed mechanism is to select the minimum number of coordinators, which take the role of a representative node for the cluster, i.e., having the Internet connection on behalf of the rest of the nodes in the cluster and to map a partition of the IoT nodes onto the selected set of coordinators to minimize the total distance between the nodes and their respective coordinator under a certain constraint in terms of maximum hop count between the IoT nodes and their respective coordinator. Since this problem can be mapped into a set cover problem which is known as NP-hard, we pursue a heuristic approach to solve the problem and analyze the complexity of the proposed solution. Through a set of experiments with varying parameters, the proposed scheme shows 63-87.3% reduction of the Internet connections depending on the number of the IoT nodes while that of the optimal solution is 65.6-89.9% in a small scale network. Moreover, it is shown that the performance characteristics of the proposed mechanism coincide with expected performance characteristics of the optimal solution in a large-scale network.

A Multi-Hop Clustering Mechanism for Scalable IoT Networks

PubMed Central

2018-01-01

It is expected that up to 26 billion Internet of Things (IoT) equipped with sensors and wireless communication capabilities will be connected to the Internet by 2020 for various purposes. With a large scale IoT network, having each node connected to the Internet with an individual connection may face serious scalability issues. The scalability problem of the IoT network may be alleviated by grouping the nodes of the IoT network into clusters and having a representative node in each cluster connect to the Internet on behalf of the other nodes in the cluster instead of having a per-node Internet connection and communication. In this paper, we propose a multi-hop clustering mechanism for IoT networks to minimize the number of required Internet connections. Specifically, the objective of proposed mechanism is to select the minimum number of coordinators, which take the role of a representative node for the cluster, i.e., having the Internet connection on behalf of the rest of the nodes in the cluster and to map a partition of the IoT nodes onto the selected set of coordinators to minimize the total distance between the nodes and their respective coordinator under a certain constraint in terms of maximum hop count between the IoT nodes and their respective coordinator. Since this problem can be mapped into a set cover problem which is known as NP-hard, we pursue a heuristic approach to solve the problem and analyze the complexity of the proposed solution. Through a set of experiments with varying parameters, the proposed scheme shows 63–87.3% reduction of the Internet connections depending on the number of the IoT nodes while that of the optimal solution is 65.6–89.9% in a small scale network. Moreover, it is shown that the performance characteristics of the proposed mechanism coincide with expected performance characteristics of the optimal solution in a large-scale network. PMID:29570691

Scalable Wrap-Around Shuffle Exchange Network with Deflection Routing

NASA Technical Reports Server (NTRS)

Monacos, Steve P. (Inventor)

1997-01-01

The invention in one embodiment is a communication network including plural non-blocking crossbar nodes, first apparatus for connecting the nodes in a first layer of connecting links, and second apparatus for connecting links independent of the first layer, whereby each layer is connected to the other layer at each point of the nodes. Preferably, each one of the layers of connecting links corresponds to one recirculating network topology that closes in on itself.

Hyperswitch Network For Hypercube Computer

NASA Technical Reports Server (NTRS)

Chow, Edward; Madan, Herbert; Peterson, John

1989-01-01

Data-driven dynamic switching enables high speed data transfer. Proposed hyperswitch network based on mixed static and dynamic topologies. Routing header modified in response to congestion or faults encountered as path established. Static topology meets requirement if nodes have switching elements that perform necessary routing header revisions dynamically. Hypercube topology now being implemented with switching element in each computer node aimed at designing very-richly-interconnected multicomputer system. Interconnection network connects great number of small computer nodes, using fixed hypercube topology, characterized by point-to-point links between nodes.

Current limiter circuit system

DOEpatents

Witcher, Joseph Brandon; Bredemann, Michael V.

2017-09-05

An apparatus comprising a steady state sensing circuit, a switching circuit, and a detection circuit. The steady state sensing circuit is connected to a first, a second and a third node. The first node is connected to a first device, the second node is connected to a second device, and the steady state sensing circuit causes a scaled current to flow at the third node. The scaled current is proportional to a voltage difference between the first and second node. The switching circuit limits an amount of current that flows between the first and second device. The detection circuit is connected to the third node and the switching circuit. The detection circuit monitors the scaled current at the third node and controls the switching circuit to limit the amount of the current that flows between the first and second device when the scaled current is greater than a desired level.

Adaptive control of structural balance for complex dynamical networks based on dynamic coupling of nodes

NASA Astrophysics Data System (ADS)

Gao, Zilin; Wang, Yinhe; Zhang, Lili

2018-02-01

In the existing research results of the complex dynamical networks controlled, the controllers are mainly used to guarantee the synchronization or stabilization of the nodes’ state, and the terms coupled with connection relationships may affect the behaviors of nodes, this obviously ignores the dynamic common behavior of the connection relationships between the nodes. In fact, from the point of view of large-scale system, a complex dynamical network can be regarded to be composed of two time-varying dynamic subsystems, which can be called the nodes subsystem and the connection relationships subsystem, respectively. Similar to the synchronization or stabilization of the nodes subsystem, some characteristic phenomena can be also emerged in the connection relationships subsystem. For example, the structural balance in the social networks and the synaptic facilitation in the biological neural networks. This paper focuses on the structural balance in dynamic complex networks. Generally speaking, the state of the connection relationships subsystem is difficult to be measured accurately in practical applications, and thus it is not easy to implant the controller directly into the connection relationships subsystem. It is noted that the nodes subsystem and the relationships subsystem are mutually coupled, which implies that the state of the connection relationships subsystem can be affected by the controllable state of nodes subsystem. Inspired by this observation, by using the structural balance theory of triad, the controller with the parameter adaptive law is proposed for the nodes subsystem in this paper, which may ensure the connection relationship matrix to approximate a given structural balance matrix in the sense of the uniformly ultimately bounded (UUB). That is, the structural balance may be obtained by employing the controlling state of the nodes subsystem. Finally, the simulations are used to show the validity of the method in this paper.

Fault tolerant hypercube computer system architecture

NASA Technical Reports Server (NTRS)

Madan, Herb S. (Inventor); Chow, Edward (Inventor)

1989-01-01

A fault-tolerant multiprocessor computer system of the hypercube type comprising a hierarchy of computers of like kind which can be functionally substituted for one another as necessary is disclosed. Communication between the working nodes is via one communications network while communications between the working nodes and watch dog nodes and load balancing nodes higher in the structure is via another communications network separate from the first. A typical branch of the hierarchy reporting to a master node or host computer comprises, a plurality of first computing nodes; a first network of message conducting paths for interconnecting the first computing nodes as a hypercube. The first network provides a path for message transfer between the first computing nodes; a first watch dog node; and a second network of message connecting paths for connecting the first computing nodes to the first watch dog node independent from the first network, the second network provides an independent path for test message and reconfiguration affecting transfers between the first computing nodes and the first switch watch dog node. There is additionally, a plurality of second computing nodes; a third network of message conducting paths for interconnecting the second computing nodes as a hypercube. The third network provides a path for message transfer between the second computing nodes; a fourth network of message conducting paths for connecting the second computing nodes to the first watch dog node independent from the third network. The fourth network provides an independent path for test message and reconfiguration affecting transfers between the second computing nodes and the first watch dog node; and a first multiplexer disposed between the first watch dog node and the second and fourth networks for allowing the first watch dog node to selectively communicate with individual ones of the computing nodes through the second and fourth networks; as well as, a second watch dog node operably connected to the first multiplexer whereby the second watch dog node can selectively communicate with individual ones of the computing nodes through the second and fourth networks. The branch is completed by a first load balancing node; and a second multiplexer connected between the first load balancing node and the first and second watch dog nodes, allowing the first load balancing node to selectively communicate with the first and second watch dog nodes.

Parallel processing data network of master and slave transputers controlled by a serial control network

DOEpatents

Crosetto, D.B.

1996-12-31

The present device provides for a dynamically configurable communication network having a multi-processor parallel processing system having a serial communication network and a high speed parallel communication network. The serial communication network is used to disseminate commands from a master processor to a plurality of slave processors to effect communication protocol, to control transmission of high density data among nodes and to monitor each slave processor`s status. The high speed parallel processing network is used to effect the transmission of high density data among nodes in the parallel processing system. Each node comprises a transputer, a digital signal processor, a parallel transfer controller, and two three-port memory devices. A communication switch within each node connects it to a fast parallel hardware channel through which all high density data arrives or leaves the node. 6 figs.

Parallel processing data network of master and slave transputers controlled by a serial control network

DOEpatents

Crosetto, Dario B.

1996-01-01

The present device provides for a dynamically configurable communication network having a multi-processor parallel processing system having a serial communication network and a high speed parallel communication network. The serial communication network is used to disseminate commands from a master processor (100) to a plurality of slave processors (200) to effect communication protocol, to control transmission of high density data among nodes and to monitor each slave processor's status. The high speed parallel processing network is used to effect the transmission of high density data among nodes in the parallel processing system. Each node comprises a transputer (104), a digital signal processor (114), a parallel transfer controller (106), and two three-port memory devices. A communication switch (108) within each node (100) connects it to a fast parallel hardware channel (70) through which all high density data arrives or leaves the node.

Network modelling methods for FMRI.

PubMed

Smith, Stephen M; Miller, Karla L; Salimi-Khorshidi, Gholamreza; Webster, Matthew; Beckmann, Christian F; Nichols, Thomas E; Ramsey, Joseph D; Woolrich, Mark W

2011-01-15

There is great interest in estimating brain "networks" from FMRI data. This is often attempted by identifying a set of functional "nodes" (e.g., spatial ROIs or ICA maps) and then conducting a connectivity analysis between the nodes, based on the FMRI timeseries associated with the nodes. Analysis methods range from very simple measures that consider just two nodes at a time (e.g., correlation between two nodes' timeseries) to sophisticated approaches that consider all nodes simultaneously and estimate one global network model (e.g., Bayes net models). Many different methods are being used in the literature, but almost none has been carefully validated or compared for use on FMRI timeseries data. In this work we generate rich, realistic simulated FMRI data for a wide range of underlying networks, experimental protocols and problematic confounds in the data, in order to compare different connectivity estimation approaches. Our results show that in general correlation-based approaches can be quite successful, methods based on higher-order statistics are less sensitive, and lag-based approaches perform very poorly. More specifically: there are several methods that can give high sensitivity to network connection detection on good quality FMRI data, in particular, partial correlation, regularised inverse covariance estimation and several Bayes net methods; however, accurate estimation of connection directionality is more difficult to achieve, though Patel's τ can be reasonably successful. With respect to the various confounds added to the data, the most striking result was that the use of functionally inaccurate ROIs (when defining the network nodes and extracting their associated timeseries) is extremely damaging to network estimation; hence, results derived from inappropriate ROI definition (such as via structural atlases) should be regarded with great caution. Copyright © 2010 Elsevier Inc. All rights reserved.

Minimum spanning tree analysis of the human connectome.

PubMed

van Dellen, Edwin; Sommer, Iris E; Bohlken, Marc M; Tewarie, Prejaas; Draaisma, Laurijn; Zalesky, Andrew; Di Biase, Maria; Brown, Jesse A; Douw, Linda; Otte, Willem M; Mandl, René C W; Stam, Cornelis J

2018-06-01

One of the challenges of brain network analysis is to directly compare network organization between subjects, irrespective of the number or strength of connections. In this study, we used minimum spanning tree (MST; a unique, acyclic subnetwork with a fixed number of connections) analysis to characterize the human brain network to create an empirical reference network. Such a reference network could be used as a null model of connections that form the backbone structure of the human brain. We analyzed the MST in three diffusion-weighted imaging datasets of healthy adults. The MST of the group mean connectivity matrix was used as the empirical null-model. The MST of individual subjects matched this reference MST for a mean 58%-88% of connections, depending on the analysis pipeline. Hub nodes in the MST matched with previously reported locations of hub regions, including the so-called rich club nodes (a subset of high-degree, highly interconnected nodes). Although most brain network studies have focused primarily on cortical connections, cortical-subcortical connections were consistently present in the MST across subjects. Brain network efficiency was higher when these connections were included in the analysis, suggesting that these tracts may be utilized as the major neural communication routes. Finally, we confirmed that MST characteristics index the effects of brain aging. We conclude that the MST provides an elegant and straightforward approach to analyze structural brain networks, and to test network topological features of individual subjects in comparison to empirical null models. © 2018 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc.

Communication efficiency and congestion of signal traffic in large-scale brain networks.

PubMed

Mišić, Bratislav; Sporns, Olaf; McIntosh, Anthony R

2014-01-01

The complex connectivity of the cerebral cortex suggests that inter-regional communication is a primary function. Using computational modeling, we show that anatomical connectivity may be a major determinant for global information flow in brain networks. A macaque brain network was implemented as a communication network in which signal units flowed between grey matter nodes along white matter paths. Compared to degree-matched surrogate networks, information flow on the macaque brain network was characterized by higher loss rates, faster transit times and lower throughput, suggesting that neural connectivity may be optimized for speed rather than fidelity. Much of global communication was mediated by a "rich club" of hub regions: a sub-graph comprised of high-degree nodes that are more densely interconnected with each other than predicted by chance. First, macaque communication patterns most closely resembled those observed for a synthetic rich club network, but were less similar to those seen in a synthetic small world network, suggesting that the former is a more fundamental feature of brain network topology. Second, rich club regions attracted the most signal traffic and likewise, connections between rich club regions carried more traffic than connections between non-rich club regions. Third, a number of rich club regions were significantly under-congested, suggesting that macaque connectivity actively shapes information flow, funneling traffic towards some nodes and away from others. Together, our results indicate a critical role of the rich club of hub nodes in dynamic aspects of global brain communication.

Communication Efficiency and Congestion of Signal Traffic in Large-Scale Brain Networks

PubMed Central

Mišić, Bratislav; Sporns, Olaf; McIntosh, Anthony R.

2014-01-01

The complex connectivity of the cerebral cortex suggests that inter-regional communication is a primary function. Using computational modeling, we show that anatomical connectivity may be a major determinant for global information flow in brain networks. A macaque brain network was implemented as a communication network in which signal units flowed between grey matter nodes along white matter paths. Compared to degree-matched surrogate networks, information flow on the macaque brain network was characterized by higher loss rates, faster transit times and lower throughput, suggesting that neural connectivity may be optimized for speed rather than fidelity. Much of global communication was mediated by a “rich club” of hub regions: a sub-graph comprised of high-degree nodes that are more densely interconnected with each other than predicted by chance. First, macaque communication patterns most closely resembled those observed for a synthetic rich club network, but were less similar to those seen in a synthetic small world network, suggesting that the former is a more fundamental feature of brain network topology. Second, rich club regions attracted the most signal traffic and likewise, connections between rich club regions carried more traffic than connections between non-rich club regions. Third, a number of rich club regions were significantly under-congested, suggesting that macaque connectivity actively shapes information flow, funneling traffic towards some nodes and away from others. Together, our results indicate a critical role of the rich club of hub nodes in dynamic aspects of global brain communication. PMID:24415931

Inter-trabecular angle: A parameter of trabecular bone architecture in the human proximal femur that reveals underlying topological motifs.

PubMed

Reznikov, Natalie; Chase, Hila; Ben Zvi, Yehonatan; Tarle, Victoria; Singer, Matthew; Brumfeld, Vlad; Shahar, Ron; Weiner, Steve

2016-10-15

Trabecular bone is an intricate 3D network of struts and plates. Although the structure-function relations in trabecular bone have been studied since the time of Julius Wolff, controversy still exists regarding the architectural parameters responsible for its stability and resilience. We present a parameter that measures the angle between two connected trabeculae - the Inter-Trabecular Angle (ITA). We studied the ITA values derived from μCT scans of different regions of the proximal femora of 5 individuals of different age and sex. We show that the ITA angle distribution of nodes with 3 connecting trabeculae has a mean close to 120°, nodes with 4 connecting trabeculae has a mean close to 109° and nodes of higher connectivity have mean ITA values around 100°. This tendency to spread the ITAs around geometrically symmetrical motifs is highly conserved. The implication is that the ITAs are optimized such that the smallest amount of material spans the maximal 3D volume, and possibly by so doing trabecular bone might be better adapted to multidirectional loading. We also draw a parallel between trabecular bone and tensegrity structures - where lightweight, resilient and stable tetrahedron-based shapes contribute to strain redistribution amongst all the elements and to collective impact dampening. The Inter-Trabecular Angle (ITA) is a new topological parameter of trabecular bone. The ITA characterizes the way trabeculae connect with each other at nodes, regardless of their thickness and shape. The mean ITA value of nodes with 3 trabeculae is close to 120°, of nodes with 4 trabeculae is just below 109°, and the mean ITA of nodes with 5 and more trabeculae is around 100°. Thus the connections of trabeculae trend towards adopting symmetrical shapes. This implies that trabeculae can maximally span 3D space using the minimal amount of material. We draw a parallel between this motif and the concept of tensegrity - an engineering premise to which many living creatures conform at multiple levels of organization. Copyright © 2016 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.

Network theory may explain the vulnerability of medieval human settlements to the Black Death pandemic.

PubMed

Gómez, José M; Verdú, Miguel

2017-03-06

Epidemics can spread across large regions becoming pandemics by flowing along transportation and social networks. Two network attributes, transitivity (when a node is connected to two other nodes that are also directly connected between them) and centrality (the number and intensity of connections with the other nodes in the network), are widely associated with the dynamics of transmission of pathogens. Here we investigate how network centrality and transitivity influence vulnerability to diseases of human populations by examining one of the most devastating pandemic in human history, the fourteenth century plague pandemic called Black Death. We found that, after controlling for the city spatial location and the disease arrival time, cities with higher values of both centrality and transitivity were more severely affected by the plague. A simulation study indicates that this association was due to central cities with high transitivity undergo more exogenous re-infections. Our study provides an easy method to identify hotspots in epidemic networks. Focusing our effort in those vulnerable nodes may save time and resources by improving our ability of controlling deadly epidemics.

Analysis of the Spatial Organization of Pastures as a Contact Network, Implications for Potential Disease Spread and Biosecurity in Livestock, France, 2010.

PubMed

Palisson, Aurore; Courcoul, Aurélie; Durand, Benoit

2017-01-01

The use of pastures is part of common herd management practices for livestock animals, but contagion between animals located on neighbouring pastures is one of the major modes of infectious disease transmission between herds. At the population level, this transmission is strongly constrained by the spatial organization of pastures. The aim of this study was to answer two questions: (i) is the spatial configuration of pastures favourable to the spread of infectious diseases in France? (ii) would biosecurity measures allow decreasing this vulnerability? Based on GIS data, the spatial organization of pastures was represented using networks. Nodes were the 3,159,787 pastures reported in 2010 by the French breeders to claim the Common Agricultural Policy subsidies. Links connected pastures when the distance between them was below a predefined threshold. Premises networks were obtained by aggregating into a single node all the pastures under the same ownership. Although the pastures network was very fragmented when the distance threshold was short (1.5 meters, relevant for a directly-transmitted disease), it was not the case when the distance threshold was larger (500 m, relevant for a vector-borne disease: 97% of the nodes in the largest connected component). The premises network was highly connected as the largest connected component always included more than 83% of the nodes, whatever the distance threshold. Percolation analyses were performed to model the population-level efficacy of biosecurity measures. Percolation thresholds varied according to the modelled biosecurity measures and to the distance threshold. They were globally high (e.g. >17% of nodes had to be removed, mimicking the confinement of animals inside farm buildings, to obtain the disappearance of the large connected component). The network of pastures thus appeared vulnerable to the spread of diseases in France. Only a large acceptance of biosecurity measures by breeders would allow reducing this structural risk.

Analysis of the Spatial Organization of Pastures as a Contact Network, Implications for Potential Disease Spread and Biosecurity in Livestock, France, 2010

PubMed Central

Palisson, Aurore; Courcoul, Aurélie; Durand, Benoit

2017-01-01

The use of pastures is part of common herd management practices for livestock animals, but contagion between animals located on neighbouring pastures is one of the major modes of infectious disease transmission between herds. At the population level, this transmission is strongly constrained by the spatial organization of pastures. The aim of this study was to answer two questions: (i) is the spatial configuration of pastures favourable to the spread of infectious diseases in France? (ii) would biosecurity measures allow decreasing this vulnerability? Based on GIS data, the spatial organization of pastures was represented using networks. Nodes were the 3,159,787 pastures reported in 2010 by the French breeders to claim the Common Agricultural Policy subsidies. Links connected pastures when the distance between them was below a predefined threshold. Premises networks were obtained by aggregating into a single node all the pastures under the same ownership. Although the pastures network was very fragmented when the distance threshold was short (1.5 meters, relevant for a directly-transmitted disease), it was not the case when the distance threshold was larger (500 m, relevant for a vector-borne disease: 97% of the nodes in the largest connected component). The premises network was highly connected as the largest connected component always included more than 83% of the nodes, whatever the distance threshold. Percolation analyses were performed to model the population-level efficacy of biosecurity measures. Percolation thresholds varied according to the modelled biosecurity measures and to the distance threshold. They were globally high (e.g. >17% of nodes had to be removed, mimicking the confinement of animals inside farm buildings, to obtain the disappearance of the large connected component). The network of pastures thus appeared vulnerable to the spread of diseases in France. Only a large acceptance of biosecurity measures by breeders would allow reducing this structural risk. PMID:28060913

Routing Based on Length of Time of Available Connection

NASA Technical Reports Server (NTRS)

Anandappan, Thanga (Inventor); Roy, Aloke (Inventor); Malve, Sharath Babu (Inventor); Toth, Louis T. (Inventor)

2016-01-01

In an embodiment, a method of routing packets at a first node in an ad-hoc network is provided. The method includes receiving, at the first node, a plurality of route-alive messages corresponding to a destination, each of the plurality of route-alive messages including a route time indicating a length of time in which a communicative connection is available between the second node that sent the respective route-alive message and the destination. The method also includes determining an updated route time for each second node. The updated route time corresponds to a length of time in which a communication connection is available between the first node and the destination through the respective second node. A second node is selected for sending a packet to based on the updated route time for each of the second nodes, wherein a node having a longer updated route time is given higher priority for selection.

Prioritizing Urban Habitats for Connectivity Conservation: Integrating Centrality and Ecological Metrics.

PubMed

Poodat, Fatemeh; Arrowsmith, Colin; Fraser, David; Gordon, Ascelin

2015-09-01

Connectivity among fragmented areas of habitat has long been acknowledged as important for the viability of biological conservation, especially within highly modified landscapes. Identifying important habitat patches in ecological connectivity is a priority for many conservation strategies, and the application of 'graph theory' has been shown to provide useful information on connectivity. Despite the large number of metrics for connectivity derived from graph theory, only a small number have been compared in terms of the importance they assign to nodes in a network. This paper presents a study that aims to define a new set of metrics and compares these with traditional graph-based metrics, used in the prioritization of habitat patches for ecological connectivity. The metrics measured consist of "topological" metrics, "ecological metrics," and "integrated metrics," Integrated metrics are a combination of topological and ecological metrics. Eight metrics were applied to the habitat network for the fat-tailed dunnart within Greater Melbourne, Australia. A non-directional network was developed in which nodes were linked to adjacent nodes. These links were then weighted by the effective distance between patches. By applying each of the eight metrics for the study network, nodes were ranked according to their contribution to the overall network connectivity. The structured comparison revealed the similarity and differences in the way the habitat for the fat-tailed dunnart was ranked based on different classes of metrics. Due to the differences in the way the metrics operate, a suitable metric should be chosen that best meets the objectives established by the decision maker.

Going End to End to Deliver High-Speed Data

NASA Technical Reports Server (NTRS)

2005-01-01

By the end of the 1990s, the optical fiber "backbone" of the telecommunication and data-communication networks had evolved from megabits-per-second transmission rates to gigabits-per-second transmission rates. Despite this boom in bandwidth, however, users at the end nodes were still not being reached on a consistent basis. (An end node is any device that does not behave like a router or a managed hub or switch. Examples of end node objects are computers, printers, serial interface processor phones, and unmanaged hubs and switches.) The primary reason that prevents bandwidth from reaching the end nodes is the complex local network topology that exists between the optical backbone and the end nodes. This complex network topology consists of several layers of routing and switch equipment which introduce potential congestion points and network latency. By breaking down the complex network topology, a true optical connection can be achieved. Access Optical Networks, Inc., is making this connection a reality with guidance from NASA s nondestructive evaluation experts.

Consensus between Pipelines in Structural Brain Networks

PubMed Central

Parker, Christopher S.; Deligianni, Fani; Cardoso, M. Jorge; Daga, Pankaj; Modat, Marc; Dayan, Michael; Clark, Chris A.

2014-01-01

Structural brain networks may be reconstructed from diffusion MRI tractography data and have great potential to further our understanding of the topological organisation of brain structure in health and disease. Network reconstruction is complex and involves a series of processesing methods including anatomical parcellation, registration, fiber orientation estimation and whole-brain fiber tractography. Methodological choices at each stage can affect the anatomical accuracy and graph theoretical properties of the reconstructed networks, meaning applying different combinations in a network reconstruction pipeline may produce substantially different networks. Furthermore, the choice of which connections are considered important is unclear. In this study, we assessed the similarity between structural networks obtained using two independent state-of-the-art reconstruction pipelines. We aimed to quantify network similarity and identify the core connections emerging most robustly in both pipelines. Similarity of network connections was compared between pipelines employing different atlases by merging parcels to a common and equivalent node scale. We found a high agreement between the networks across a range of fiber density thresholds. In addition, we identified a robust core of highly connected regions coinciding with a peak in similarity across network density thresholds, and replicated these results with atlases at different node scales. The binary network properties of these core connections were similar between pipelines but showed some differences in atlases across node scales. This study demonstrates the utility of applying multiple structural network reconstrution pipelines to diffusion data in order to identify the most important connections for further study. PMID:25356977

Connecting to HPC VPN | High-Performance Computing | NREL

Science.gov Websites

and password will match your NREL network account login/password. From OS X or Linux, open a terminal finalized. Open a Remote Desktop connection using server name WINHPC02 (this is the login node). Mac Mac

Polyhedral integrated and free space optical interconnection

DOEpatents

Erteza, I.A.

1998-01-06

An optical communication system uses holographic optical elements to provide guided wave and non-guided communication, resulting in high bandwidth, high connectivity optical communications. Holograms within holographic optical elements route optical signals between elements and between nodes connected to elements. Angular and wavelength multiplexing allow the elements to provide high connectivity. The combination of guided and non-guided communication allows compact polyhedral system geometries. Guided wave communications provided by multiplexed substrate-mode holographic optical elements eases system alignment. 7 figs.

Polyhedral integrated and free space optical interconnection

DOEpatents

Erteza, Ireena A.

1998-01-01

An optical communication system uses holographic optical elements to provide guided wave and non-guided communication, resulting in high bandwidth, high connectivity optical communications. Holograms within holographic optical elements route optical signals between elements and between nodes connected to elements. Angular and wavelength multiplexing allow the elements to provide high connectivity. The combination of guided and non-guided communication allows compact polyhedral system geometries. Guided wave communications provided by multiplexed substrate-mode holographic optical elements eases system alignment.

Photonic Quantum Networks formed from NV− centers

PubMed Central

Nemoto, Kae; Trupke, Michael; Devitt, Simon J.; Scharfenberger, Burkhard; Buczak, Kathrin; Schmiedmayer, Jörg; Munro, William J.

2016-01-01

In this article we present a simple repeater scheme based on the negatively-charged nitrogen vacancy centre in diamond. Each repeater node is built from modules comprising an optical cavity containing a single NV−, with one nuclear spin from 15N as quantum memory. The module uses only deterministic processes and interactions to achieve high fidelity operations (>99%), and modules are connected by optical fiber. In the repeater node architecture, the processes between modules by photons can be in principle deterministic, however current limitations on optical components lead the processes to be probabilistic but heralded. Our resource-modest repeater architecture contains two modules at each node, and the repeater nodes are then connected by entangled photon pairs. We discuss the performance of such a quantum repeater network with modest resources and then incorporate more resource-intense strategies step by step. Our architecture should allow large-scale quantum information networks with existing or near future technology. PMID:27215433

Photonic Quantum Networks formed from NV(-) centers.

PubMed

Nemoto, Kae; Trupke, Michael; Devitt, Simon J; Scharfenberger, Burkhard; Buczak, Kathrin; Schmiedmayer, Jörg; Munro, William J

2016-05-24

In this article we present a simple repeater scheme based on the negatively-charged nitrogen vacancy centre in diamond. Each repeater node is built from modules comprising an optical cavity containing a single NV(-), with one nuclear spin from (15)N as quantum memory. The module uses only deterministic processes and interactions to achieve high fidelity operations (>99%), and modules are connected by optical fiber. In the repeater node architecture, the processes between modules by photons can be in principle deterministic, however current limitations on optical components lead the processes to be probabilistic but heralded. Our resource-modest repeater architecture contains two modules at each node, and the repeater nodes are then connected by entangled photon pairs. We discuss the performance of such a quantum repeater network with modest resources and then incorporate more resource-intense strategies step by step. Our architecture should allow large-scale quantum information networks with existing or near future technology.

Coupling effect of nodes popularity and similarity on social network persistence.

PubMed

Jin, Xiaogang; Jin, Cheng; Huang, Jiaxuan; Min, Yong

2017-02-21

Network robustness represents the ability of networks to withstand failures and perturbations. In social networks, maintenance of individual activities, also called persistence, is significant towards understanding robustness. Previous works usually consider persistence on pre-generated network structures; while in social networks, the network structure is growing with the cascading inactivity of existed individuals. Here, we address this challenge through analysis for nodes under a coevolution model, which characterizes individual activity changes under three network growth modes: following the descending order of nodes' popularity, similarity or uniform random. We show that when nodes possess high spontaneous activities, a popularity-first growth mode obtains highly persistent networks; otherwise, with low spontaneous activities, a similarity-first mode does better. Moreover, a compound growth mode, with the consecutive joining of similar nodes in a short period and mixing a few high popularity nodes, obtains the highest persistence. Therefore, nodes similarity is essential for persistent social networks, while properly coupling popularity with similarity further optimizes the persistence. This demonstrates the evolution of nodes activity not only depends on network topology, but also their connective typology.

Power module assembly

DOEpatents

Campbell, Jeremy B [Torrance, CA; Newson, Steve [Redondo Beach, CA

2011-11-15

A power module assembly of the type suitable for deployment in a vehicular power inverter, wherein the power inverter has a grounded chassis, is provided. The power module assembly comprises a conductive base layer electrically coupled to the chassis, an insulating layer disposed on the conductive base layer, a first conductive node disposed on the insulating layer, a second conductive node disposed on the insulating layer, wherein the first and second conductive nodes are electrically isolated from each other. The power module assembly also comprises a first capacitor having a first electrode electrically connected to the conductive base layer, and a second electrode electrically connected to the first conductive node, and further comprises a second capacitor having a first electrode electrically connected to the conductive base layer, and a second electrode electrically connected to the second conductive node.

Interferon-α acutely impairs whole-brain functional connectivity network architecture - A preliminary study.

PubMed

Dipasquale, Ottavia; Cooper, Ella A; Tibble, Jeremy; Voon, Valerie; Baglio, Francesca; Baselli, Giuseppe; Cercignani, Mara; Harrison, Neil A

2016-11-01

Interferon-alpha (IFN-α) is a key mediator of antiviral immune responses used to treat Hepatitis C infection. Though clinically effective, IFN-α rapidly impairs mood, motivation and cognition, effects that can appear indistinguishable from major depression and provide powerful empirical support for the inflammation theory of depression. Though inflammation has been shown to modulate activity within discrete brain regions, how it affects distributed information processing and the architecture of whole brain functional connectivity networks have not previously been investigated. Here we use a graph theoretic analysis of resting state functional magnetic resonance imaging (rfMRI) to investigate acute effects of systemic interferon-alpha (IFN-α) on whole brain functional connectivity architecture and its relationship to IFN-α-induced mood change. Twenty-two patients with Hepatitis-C infection, initiating IFN-α-based therapy were scanned at baseline and 4h after their first IFN-α dose. The whole brain network was parcellated into 110 cortical and sub-cortical nodes based on the Oxford-Harvard Atlas and effects assessed on higher-level graph metrics, including node degree, betweenness centrality, global and local efficiency. IFN-α was associated with a significant reduction in global network connectivity (node degree) (p=0.033) and efficiency (p=0.013), indicating a global reduction of information transfer among the nodes forming the whole brain network. Effects were similar for highly connected (hub) and non-hub nodes, with no effect on betweenness centrality (p>0.1). At a local level, we identified regions with reduced efficiency of information exchange and a sub-network with decreased functional connectivity after IFN-α. Changes in local and particularly global functional connectivity correlated with associated changes in mood measured on the Profile of Mood States (POMS) questionnaire. IFN-α rapidly induced a profound shift in whole brain network structure, impairing global functional connectivity and the efficiency of parallel information exchange. Correlations with multiple indices of mood change support a role for global changes in brain functional connectivity architecture in coordinated behavioral responses to IFN-α. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

High Speed All-Optical Data Distribution Network

NASA Astrophysics Data System (ADS)

Braun, Steve; Hodara, Henri

2017-11-01

This article describes the performance and capabilities of an all-optical network featuring low latency, high speed file transfer between serially connected optical nodes. A basic component of the network is a network interface card (NIC) implemented through a unique planar lightwave circuit (PLC) that performs add/drop data and optical signal amplification. The network uses a linear bus topology with nodes in a "T" configuration, as described in the text. The signal is sent optically (hence, no latency) to all nodes via wavelength division multiplexing (WDM), with each node receiver tuned to wavelength of choice via an optical de-multiplexer. Each "T" node routes a portion of the signal to/from the bus through optical couplers, embedded in the network interface card (NIC), to each of the 1 through n computers.

Fine-Grained Parcellation of Brain Connectivity Improves Differentiation of States of Consciousness During Graded Propofol Sedation.

PubMed

Liu, Xiaolin; Lauer, Kathryn K; Ward, B Douglas; Roberts, Christopher J; Liu, Suyan; Gollapudy, Suneeta; Rohloff, Robert; Gross, William; Xu, Zhan; Chen, Guangyu; Binder, Jeffrey R; Li, Shi-Jiang; Hudetz, Anthony G

2017-08-01

Conscious perception relies on interactions between spatially and functionally distinct modules of the brain at various spatiotemporal scales. These interactions are altered by anesthesia, an intervention that leads to fading consciousness. Relatively little is known about brain functional connectivity and its anesthetic modulation at a fine spatial scale. Here, we used functional imaging to examine propofol-induced changes in functional connectivity in brain networks defined at a fine-grained parcellation based on a combination of anatomical and functional features. Fifteen healthy volunteers underwent resting-state functional imaging in wakeful baseline, mild sedation, deep sedation, and recovery of consciousness. Compared with wakeful baseline, propofol produced widespread, dose-dependent functional connectivity changes that scaled with the extent to which consciousness was altered. The dominant changes in connectivity were associated with the frontal lobes. By examining node pairs that demonstrated a trend of functional connectivity change between wakefulness and deep sedation, quadratic discriminant analysis differentiated the states of consciousness in individual participants more accurately at a fine-grained parcellation (e.g., 2000 nodes) than at a coarse-grained parcellation (e.g., 116 anatomical nodes). Our study suggests that defining brain networks at a high granularity may provide a superior imaging-based distinction of the graded effect of anesthesia on consciousness.

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

Emergence of Rich-Club Topology and Coordinated Dynamics in Development of Hippocampal Functional Networks In Vitro

PubMed Central

Charlesworth, Paul; Kitzbichler, Manfred G.; Paulsen, Ole

2015-01-01

Recent studies demonstrated that the anatomical network of the human brain shows a “rich-club” organization. This complex topological feature implies that highly connected regions, hubs of the large-scale brain network, are more densely interconnected with each other than expected by chance. Rich-club nodes were traversed by a majority of short paths between peripheral regions, underlining their potential importance for efficient global exchange of information between functionally specialized areas of the brain. Network hubs have also been described at the microscale of brain connectivity (so-called “hub neurons”). Their role in shaping synchronous dynamics and forming microcircuit wiring during development, however, is not yet fully understood. The present study aimed to investigate the role of hubs during network development, using multi-electrode arrays and functional connectivity analysis during spontaneous multi-unit activity (MUA) of dissociated primary mouse hippocampal neurons. Over the first 4 weeks in vitro, functional connectivity significantly increased in strength, density, and size, with mature networks demonstrating a robust modular and small-world topology. As expected by a “rich-get-richer” growth rule of network evolution, MUA graphs were found to form rich-clubs at an early stage in development (14 DIV). Later on, rich-club nodes were a consistent topological feature of MUA graphs, demonstrating high nodal strength, efficiency, and centrality. Rich-club nodes were also found to be crucial for MUA dynamics. They often served as broker of spontaneous activity flow, confirming that hub nodes and rich-clubs may play an important role in coordinating functional dynamics at the microcircuit level. PMID:25855164

Low-rank network decomposition reveals structural characteristics of small-world networks

NASA Astrophysics Data System (ADS)

Barranca, Victor J.; Zhou, Douglas; Cai, David

2015-12-01

Small-world networks occur naturally throughout biological, technological, and social systems. With their prevalence, it is particularly important to prudently identify small-world networks and further characterize their unique connection structure with respect to network function. In this work we develop a formalism for classifying networks and identifying small-world structure using a decomposition of network connectivity matrices into low-rank and sparse components, corresponding to connections within clusters of highly connected nodes and sparse interconnections between clusters, respectively. We show that the network decomposition is independent of node indexing and define associated bounded measures of connectivity structure, which provide insight into the clustering and regularity of network connections. While many existing network characterizations rely on constructing benchmark networks for comparison or fail to describe the structural properties of relatively densely connected networks, our classification relies only on the intrinsic network structure and is quite robust with respect to changes in connection density, producing stable results across network realizations. Using this framework, we analyze several real-world networks and reveal new structural properties, which are often indiscernible by previously established characterizations of network connectivity.

Improved targeted immunization strategies based on two rounds of selection

NASA Astrophysics Data System (ADS)

Xia, Ling-Ling; Song, Yu-Rong; Li, Chan-Chan; Jiang, Guo-Ping

2018-04-01

In the case of high degree targeted immunization where the number of vaccine is limited, when more than one node associated with the same degree meets the requirement of high degree centrality, how can we choose a certain number of nodes from those nodes, so that the number of immunized nodes will not exceed the limit? In this paper, we introduce a new idea derived from the selection process of second-round exam to solve this problem and then propose three improved targeted immunization strategies. In these proposed strategies, the immunized nodes are selected through two rounds of selection, where we increase the quotas of first-round selection according the evaluation criterion of degree centrality and then consider another characteristic parameter of node, such as node's clustering coefficient, betweenness and closeness, to help choose targeted nodes in the second-round selection. To validate the effectiveness of the proposed strategies, we compare them with the degree immunizations including the high degree targeted and the high degree adaptive immunizations using two metrics: the size of the largest connected component of immunized network and the number of infected nodes. Simulation results demonstrate that the proposed strategies based on two rounds of sorting are effective for heterogeneous networks and their immunization effects are better than that of the degree immunizations.

Motion video compression system with neural network having winner-take-all function

NASA Technical Reports Server (NTRS)

Fang, Wai-Chi (Inventor); Sheu, Bing J. (Inventor)

1997-01-01

A motion video data system includes a compression system, including an image compressor, an image decompressor correlative to the image compressor having an input connected to an output of the image compressor, a feedback summing node having one input connected to an output of the image decompressor, a picture memory having an input connected to an output of the feedback summing node, apparatus for comparing an image stored in the picture memory with a received input image and deducing therefrom pixels having differences between the stored image and the received image and for retrieving from the picture memory a partial image including the pixels only and applying the partial image to another input of the feedback summing node, whereby to produce at the output of the feedback summing node an updated decompressed image, a subtraction node having one input connected to received the received image and another input connected to receive the partial image so as to generate a difference image, the image compressor having an input connected to receive the difference image whereby to produce a compressed difference image at the output of the image compressor.

An Energy Efficient Simultaneous-Node Repositioning Algorithm for Mobile Sensor Networks

PubMed Central

Hasbullah, Halabi; Nazir, Babar; Khan, Imran Ali

2014-01-01

Recently, wireless sensor network (WSN) applications have seen an increase in interest. In search and rescue, battlefield reconnaissance, and some other such applications, so that a survey of the area of interest can be made collectively, a set of mobile nodes is deployed. Keeping the network nodes connected is vital for WSNs to be effective. The provision of connectivity can be made at the time of startup and can be maintained by carefully coordinating the nodes when they move. However, if a node suddenly fails, the network could be partitioned to cause communication problems. Recently, several methods that use the relocation of nodes for connectivity restoration have been proposed. However, these methods have the tendency to not consider the potential coverage loss in some locations. This paper addresses the concerns of both connectivity and coverage in an integrated way so that this gap can be filled. A novel algorithm for simultaneous-node repositioning is introduced. In this approach, each neighbour of the failed node, one by one, moves in for a certain amount of time to take the place of the failed node, after which it returns to its original location in the network. The effectiveness of this algorithm has been verified by the simulation results. PMID:25152924

Community detection using preference networks

NASA Astrophysics Data System (ADS)

Tasgin, Mursel; Bingol, Haluk O.

2018-04-01

Community detection is the task of identifying clusters or groups of nodes in a network where nodes within the same group are more connected with each other than with nodes in different groups. It has practical uses in identifying similar functions or roles of nodes in many biological, social and computer networks. With the availability of very large networks in recent years, performance and scalability of community detection algorithms become crucial, i.e. if time complexity of an algorithm is high, it cannot run on large networks. In this paper, we propose a new community detection algorithm, which has a local approach and is able to run on large networks. It has a simple and effective method; given a network, algorithm constructs a preference network of nodes where each node has a single outgoing edge showing its preferred node to be in the same community with. In such a preference network, each connected component is a community. Selection of the preferred node is performed using similarity based metrics of nodes. We use two alternatives for this purpose which can be calculated in 1-neighborhood of nodes, i.e. number of common neighbors of selector node and its neighbors and, the spread capability of neighbors around the selector node which is calculated by the gossip algorithm of Lind et.al. Our algorithm is tested on both computer generated LFR networks and real-life networks with ground-truth community structure. It can identify communities accurately in a fast way. It is local, scalable and suitable for distributed execution on large networks.

Petaflops router

DOEpatents

Baker, Zachary Kent; Power, John Fredrick; Tripp, Justin Leonard; Dunham, Mark Edward; Stettler, Matthew W; Jones, John Alexander

2014-10-14

Disclosed is a method and system for performing operations on at least one input data vector in order to produce at least one output vector to permit easy, scalable and fast programming of a petascale equivalent supercomputer. A PetaFlops Router may comprise one or more PetaFlops Nodes, which may be connected to each other and/or external data provider/consumers via a programmable crossbar switch external to the PetaFlops Node. Each PetaFlops Node has a FPGA and a programmable intra-FPGA crossbar switch that permits input and output variables to be configurably connected to various physical operators contained in the FPGA as desired by a user. This allows a user to specify the instruction set of the system on a per-application basis. Further, the intra-FPGA crossbar switch permits the output of one operation to be delivered as an input to a second operation. By configuring the external crossbar switch, the output of a first operation on a first PetaFlops Node may be used as the input for a second operation on a second PetaFlops Node. An embodiment may provide an ability for the system to recognize and generate pipelined functions. Streaming operators may be connected together at run-time and appropriately staged to allow data to flow through a series of functions. This allows the system to provide high throughput and parallelism when possible. The PetaFlops Router may implement the user desired instructions by appropriately configuring the intra-FPGA crossbar switch on each PetaFlops Node and the external crossbar switch.

Popularity versus similarity in growing networks.

PubMed

Papadopoulos, Fragkiskos; Kitsak, Maksim; Serrano, M Ángeles; Boguñá, Marián; Krioukov, Dmitri

2012-09-27

The principle that 'popularity is attractive' underlies preferential attachment, which is a common explanation for the emergence of scaling in growing networks. If new connections are made preferentially to more popular nodes, then the resulting distribution of the number of connections possessed by nodes follows power laws, as observed in many real networks. Preferential attachment has been directly validated for some real networks (including the Internet), and can be a consequence of different underlying processes based on node fitness, ranking, optimization, random walks or duplication. Here we show that popularity is just one dimension of attractiveness; another dimension is similarity. We develop a framework in which new connections optimize certain trade-offs between popularity and similarity, instead of simply preferring popular nodes. The framework has a geometric interpretation in which popularity preference emerges from local optimization. As opposed to preferential attachment, our optimization framework accurately describes the large-scale evolution of technological (the Internet), social (trust relationships between people) and biological (Escherichia coli metabolic) networks, predicting the probability of new links with high precision. The framework that we have developed can thus be used for predicting new links in evolving networks, and provides a different perspective on preferential attachment as an emergent phenomenon.

Coupling effect of nodes popularity and similarity on social network persistence

PubMed Central

Jin, Xiaogang; Jin, Cheng; Huang, Jiaxuan; Min, Yong

2017-01-01

Network robustness represents the ability of networks to withstand failures and perturbations. In social networks, maintenance of individual activities, also called persistence, is significant towards understanding robustness. Previous works usually consider persistence on pre-generated network structures; while in social networks, the network structure is growing with the cascading inactivity of existed individuals. Here, we address this challenge through analysis for nodes under a coevolution model, which characterizes individual activity changes under three network growth modes: following the descending order of nodes’ popularity, similarity or uniform random. We show that when nodes possess high spontaneous activities, a popularity-first growth mode obtains highly persistent networks; otherwise, with low spontaneous activities, a similarity-first mode does better. Moreover, a compound growth mode, with the consecutive joining of similar nodes in a short period and mixing a few high popularity nodes, obtains the highest persistence. Therefore, nodes similarity is essential for persistent social networks, while properly coupling popularity with similarity further optimizes the persistence. This demonstrates the evolution of nodes activity not only depends on network topology, but also their connective typology. PMID:28220840

Coupling effect of nodes popularity and similarity on social network persistence

NASA Astrophysics Data System (ADS)

Jin, Xiaogang; Jin, Cheng; Huang, Jiaxuan; Min, Yong

2017-02-01

Network robustness represents the ability of networks to withstand failures and perturbations. In social networks, maintenance of individual activities, also called persistence, is significant towards understanding robustness. Previous works usually consider persistence on pre-generated network structures; while in social networks, the network structure is growing with the cascading inactivity of existed individuals. Here, we address this challenge through analysis for nodes under a coevolution model, which characterizes individual activity changes under three network growth modes: following the descending order of nodes’ popularity, similarity or uniform random. We show that when nodes possess high spontaneous activities, a popularity-first growth mode obtains highly persistent networks; otherwise, with low spontaneous activities, a similarity-first mode does better. Moreover, a compound growth mode, with the consecutive joining of similar nodes in a short period and mixing a few high popularity nodes, obtains the highest persistence. Therefore, nodes similarity is essential for persistent social networks, while properly coupling popularity with similarity further optimizes the persistence. This demonstrates the evolution of nodes activity not only depends on network topology, but also their connective typology.

Weighted compactness function based label propagation algorithm for community detection

NASA Astrophysics Data System (ADS)

Zhang, Weitong; Zhang, Rui; Shang, Ronghua; Jiao, Licheng

2018-02-01

Community detection in complex networks, is to detect the community structure with the internal structure relatively compact and the external structure relatively sparse, according to the topological relationship among nodes in the network. In this paper, we propose a compactness function which combines the weight of nodes, and use it as the objective function to carry out the node label propagation. Firstly, according to the node degree, we find the sets of core nodes which have great influence on the network. The more the connections between the core nodes and the other nodes are, the larger the amount of the information these kernel nodes receive and transform. Then, according to the similarity of the nodes between the core nodes sets and the nodes degree, we assign weights to the nodes in the network. So the label of the nodes with great influence will be the priority in the label propagation process, which effectively improves the accuracy of the label propagation. The compactness function between nodes and communities in this paper is based on the nodes influence. It combines the connections between nodes and communities with the degree of the node belongs to its neighbor communities based on calculating the node weight. The function effectively uses the information of nodes and connections in the network. The experimental results show that the proposed algorithm can achieve good results in the artificial network and large-scale real networks compared with the 8 contrast algorithms.

Resting-State Network Topology Differentiates Task Signals across the Adult Life Span.

PubMed

Chan, Micaela Y; Alhazmi, Fahd H; Park, Denise C; Savalia, Neil K; Wig, Gagan S

2017-03-08

Brain network connectivity differs across individuals. For example, older adults exhibit less segregated resting-state subnetworks relative to younger adults (Chan et al., 2014). It has been hypothesized that individual differences in network connectivity impact the recruitment of brain areas during task execution. While recent studies have described the spatial overlap between resting-state functional correlation (RSFC) subnetworks and task-evoked activity, it is unclear whether individual variations in the connectivity pattern of a brain area (topology) relates to its activity during task execution. We report data from 238 cognitively normal participants (humans), sampled across the adult life span (20-89 years), to reveal that RSFC-based network organization systematically relates to the recruitment of brain areas across two functionally distinct tasks (visual and semantic). The functional activity of brain areas (network nodes) were characterized according to their patterns of RSFC: nodes with relatively greater connections to nodes in their own functional system ("non-connector" nodes) exhibited greater activity than nodes with relatively greater connections to nodes in other systems ("connector" nodes). This "activation selectivity" was specific to those brain systems that were central to each of the tasks. Increasing age was accompanied by less differentiated network topology and a corresponding reduction in activation selectivity (or differentiation) across relevant network nodes. The results provide evidence that connectional topology of brain areas quantified at rest relates to the functional activity of those areas during task. Based on these findings, we propose a novel network-based theory for previous reports of the "dedifferentiation" in brain activity observed in aging. SIGNIFICANCE STATEMENT Similar to other real-world networks, the organization of brain networks impacts their function. As brain network connectivity patterns differ across individuals, we hypothesized that individual differences in network connectivity would relate to differences in brain activity. Using functional MRI in a group of individuals sampled across the adult life span (20-89 years), we measured correlations at rest and related the functional connectivity patterns to measurements of functional activity during two independent tasks. Brain activity varied in relation to connectivity patterns revealed by large-scale network analysis. This relationship tracked the differences in connectivity patterns accompanied by older age, providing important evidence for a link between the topology of areal connectivity measured at rest and the functional recruitment of these areas during task performance. Copyright © 2017 Chan et al.

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.

Dimensionless, Scale Invariant, Edge Weight Metric for the Study of Complex Structural Networks

PubMed Central

Colon-Perez, Luis M.; Spindler, Caitlin; Goicochea, Shelby; Triplett, William; Parekh, Mansi; Montie, Eric; Carney, Paul R.; Price, Catherine; Mareci, Thomas H.

2015-01-01

High spatial and angular resolution diffusion weighted imaging (DWI) with network analysis provides a unique framework for the study of brain structure in vivo. DWI-derived brain connectivity patterns are best characterized with graph theory using an edge weight to quantify the strength of white matter connections between gray matter nodes. Here a dimensionless, scale-invariant edge weight is introduced to measure node connectivity. This edge weight metric provides reasonable and consistent values over any size scale (e.g. rodents to humans) used to quantify the strength of connection. Firstly, simulations were used to assess the effects of tractography seed point density and random errors in the estimated fiber orientations; with sufficient signal-to-noise ratio (SNR), edge weight estimates improve as the seed density increases. Secondly to evaluate the application of the edge weight in the human brain, ten repeated measures of DWI in the same healthy human subject were analyzed. Mean edge weight values within the cingulum and corpus callosum were consistent and showed low variability. Thirdly, using excised rat brains to study the effects of spatial resolution, the weight of edges connecting major structures in the temporal lobe were used to characterize connectivity in this local network. The results indicate that with adequate resolution and SNR, connections between network nodes are characterized well by this edge weight metric. Therefore this new dimensionless, scale-invariant edge weight metric provides a robust measure of network connectivity that can be applied in any size regime. PMID:26173147

Minimum spanning tree analysis of the human connectome

PubMed Central

Sommer, Iris E.; Bohlken, Marc M.; Tewarie, Prejaas; Draaisma, Laurijn; Zalesky, Andrew; Di Biase, Maria; Brown, Jesse A.; Douw, Linda; Otte, Willem M.; Mandl, René C.W.; Stam, Cornelis J.

2018-01-01

Abstract One of the challenges of brain network analysis is to directly compare network organization between subjects, irrespective of the number or strength of connections. In this study, we used minimum spanning tree (MST; a unique, acyclic subnetwork with a fixed number of connections) analysis to characterize the human brain network to create an empirical reference network. Such a reference network could be used as a null model of connections that form the backbone structure of the human brain. We analyzed the MST in three diffusion‐weighted imaging datasets of healthy adults. The MST of the group mean connectivity matrix was used as the empirical null‐model. The MST of individual subjects matched this reference MST for a mean 58%–88% of connections, depending on the analysis pipeline. Hub nodes in the MST matched with previously reported locations of hub regions, including the so‐called rich club nodes (a subset of high‐degree, highly interconnected nodes). Although most brain network studies have focused primarily on cortical connections, cortical–subcortical connections were consistently present in the MST across subjects. Brain network efficiency was higher when these connections were included in the analysis, suggesting that these tracts may be utilized as the major neural communication routes. Finally, we confirmed that MST characteristics index the effects of brain aging. We conclude that the MST provides an elegant and straightforward approach to analyze structural brain networks, and to test network topological features of individual subjects in comparison to empirical null models. PMID:29468769

Dimensionless, Scale Invariant, Edge Weight Metric for the Study of Complex Structural Networks.

PubMed

Colon-Perez, Luis M; Spindler, Caitlin; Goicochea, Shelby; Triplett, William; Parekh, Mansi; Montie, Eric; Carney, Paul R; Price, Catherine; Mareci, Thomas H

2015-01-01

High spatial and angular resolution diffusion weighted imaging (DWI) with network analysis provides a unique framework for the study of brain structure in vivo. DWI-derived brain connectivity patterns are best characterized with graph theory using an edge weight to quantify the strength of white matter connections between gray matter nodes. Here a dimensionless, scale-invariant edge weight is introduced to measure node connectivity. This edge weight metric provides reasonable and consistent values over any size scale (e.g. rodents to humans) used to quantify the strength of connection. Firstly, simulations were used to assess the effects of tractography seed point density and random errors in the estimated fiber orientations; with sufficient signal-to-noise ratio (SNR), edge weight estimates improve as the seed density increases. Secondly to evaluate the application of the edge weight in the human brain, ten repeated measures of DWI in the same healthy human subject were analyzed. Mean edge weight values within the cingulum and corpus callosum were consistent and showed low variability. Thirdly, using excised rat brains to study the effects of spatial resolution, the weight of edges connecting major structures in the temporal lobe were used to characterize connectivity in this local network. The results indicate that with adequate resolution and SNR, connections between network nodes are characterized well by this edge weight metric. Therefore this new dimensionless, scale-invariant edge weight metric provides a robust measure of network connectivity that can be applied in any size regime.

Implementation of Distributed Services for a Deep Sea Moored Instrument Network

NASA Astrophysics Data System (ADS)

Oreilly, T. C.; Headley, K. L.; Risi, M.; Davis, D.; Edgington, D. R.; Salamy, K. A.; Chaffey, M.

2004-12-01

The Monterey Ocean Observing System (MOOS) is a moored observatory network consisting of interconnected instrument nodes on the sea surface, midwater, and deep sea floor. We describe Software Infrastructure and Applications for MOOS ("SIAM"), which implement the management, control, and data acquisition infrastructure for the moored observatory. Links in the MOOS network include fiber-optic and 10-BaseT copper connections between the at-sea nodes. A Globalstar satellite transceiver or 900 MHz Freewave terrestrial line-of-sight RF modem provides the link to shore. All of these links support Internet protocols, providing TCP/IP connectivity throughout a system that extends from shore to sensor nodes at the air-sea interface, through the oceanic water column to a benthic network of sensor nodes extending across the deep sea floor. Exploiting this TCP/IP infrastructure as well as capabilities provided by MBARI's MOOS mooring controller, we use powerful Internet software technologies to implement a distributed management, control and data acquisition system for the moored observatory. The system design meets the demanding functional requirements specified for MOOS. Nodes and their instruments are represented by Java RMI "services" having well defined software interfaces. Clients anywhere on the network can interact with any node or instrument through its corresponding service. A client may be on the same node as the service, may be on another node, or may reside on shore. Clients may be human, e.g. when a scientist on shore accesses a deployed instrument in real-time through a user interface. Clients may also be software components that interact autonomously with instruments and nodes, e.g. for purposes such as system resource management or autonomous detection and response to scientifically interesting events. All electrical power to the moored network is provided by solar and wind energy, and the RF shore-to-mooring links are intermittent and relatively low-bandwidth connections. Thus power and wireless bandwidth are limited resources that constrain our choice of service technologies and wireless access strategy. We describe and evaluate system performance in light of actual deployment of observatory elements in Monterey Bay, and discuss how the system can be developed further. We also consider management and control strategies for the cable-to-shore observatory known as MARS ("Monterey Accelerated Research System"). The MARS cable will provide high power and continuous high-bandwidth connectivity between seafloor instrument nodes and shore, thus removing key limitations of the moored observatory. Moreover MARS functional requirements may differ significantly from MOOS requirements. In light of these differences, we discuss how elements of our MOOS moored observatory architecture might be adapted to MARS.

Drawing Inspiration from Human Brain Networks: Construction of Interconnected Virtual Networks

PubMed Central

Kominami, Daichi; Leibnitz, Kenji; Murata, Masayuki

2018-01-01

Virtualization of wireless sensor networks (WSN) is widely considered as a foundational block of edge/fog computing, which is a key technology that can help realize next-generation Internet of things (IoT) networks. In such scenarios, multiple IoT devices and service modules will be virtually deployed and interconnected over the Internet. Moreover, application services are expected to be more sophisticated and complex, thereby increasing the number of modifications required for the construction of network topologies. Therefore, it is imperative to establish a method for constructing a virtualized WSN (VWSN) topology that achieves low latency on information transmission and high resilience against network failures, while keeping the topological construction cost low. In this study, we draw inspiration from inter-modular connectivity in human brain networks, which achieves high performance when dealing with large-scale networks composed of a large number of modules (i.e., regions) and nodes (i.e., neurons). We propose a method for assigning inter-modular links based on a connectivity model observed in the cerebral cortex of the brain, known as the exponential distance rule (EDR) model. We then choose endpoint nodes of these links by controlling inter-modular assortativity, which characterizes the topological connectivity of brain networks. We test our proposed methods using simulation experiments. The results show that the proposed method based on the EDR model can construct a VWSN topology with an optimal combination of communication efficiency, robustness, and construction cost. Regarding the selection of endpoint nodes for the inter-modular links, the results also show that high assortativity enhances the robustness and communication efficiency because of the existence of inter-modular links of two high-degree nodes. PMID:29642483

Drawing Inspiration from Human Brain Networks: Construction of Interconnected Virtual Networks.

PubMed

Murakami, Masaya; Kominami, Daichi; Leibnitz, Kenji; Murata, Masayuki

2018-04-08

Virtualization of wireless sensor networks (WSN) is widely considered as a foundational block of edge/fog computing, which is a key technology that can help realize next-generation Internet of things (IoT) networks. In such scenarios, multiple IoT devices and service modules will be virtually deployed and interconnected over the Internet. Moreover, application services are expected to be more sophisticated and complex, thereby increasing the number of modifications required for the construction of network topologies. Therefore, it is imperative to establish a method for constructing a virtualized WSN (VWSN) topology that achieves low latency on information transmission and high resilience against network failures, while keeping the topological construction cost low. In this study, we draw inspiration from inter-modular connectivity in human brain networks, which achieves high performance when dealing with large-scale networks composed of a large number of modules (i.e., regions) and nodes (i.e., neurons). We propose a method for assigning inter-modular links based on a connectivity model observed in the cerebral cortex of the brain, known as the exponential distance rule (EDR) model. We then choose endpoint nodes of these links by controlling inter-modular assortativity, which characterizes the topological connectivity of brain networks. We test our proposed methods using simulation experiments. The results show that the proposed method based on the EDR model can construct a VWSN topology with an optimal combination of communication efficiency, robustness, and construction cost. Regarding the selection of endpoint nodes for the inter-modular links, the results also show that high assortativity enhances the robustness and communication efficiency because of the existence of inter-modular links of two high-degree nodes.

DEVELOPMENT OF THE “RICH CLUB” IN BRAIN CONNECTIVITY NETWORKS FROM 438 ADOLESCENTS & ADULTS AGED 12 TO 30

PubMed Central

Dennis, Emily L.; Jahanshad, Neda; Toga, Arthur W.; McMahon, Katie L.; de Zubicaray, Greig I.; Hickie, Ian; Wright, Margaret J.; Thompson, Paul M.

2014-01-01

The ‘rich club’ coefficient describes a phenomenon where a network's hubs (high-degree nodes) are on average more intensely interconnected than lower-degree nodes. Networks with rich clubs often have an efficient, higher-order organization, but we do not yet know how the rich club emerges in the living brain, or how it changes as our brain networks develop. Here we chart the developmental trajectory of the rich club in anatomical brain networks from 438 subjects aged 12-30. Cortical networks were constructed from 68×68 connectivity matrices of fiber density, using whole-brain tractography in 4-Tesla 105-gradient high angular resolution diffusion images (HARDI). The adult and younger cohorts had rich clubs that included different nodes; the rich club effect intensified with age. Rich-club organization is a sign of a network's efficiency and robustness. These concepts and findings may be advantageous for studying brain maturation and abnormal brain development. PMID:24827471

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

A universal computer control system for motors

NASA Technical Reports Server (NTRS)

Szakaly, Zoltan F. (Inventor)

1991-01-01

A control system for a multi-motor system such as a space telerobot, having a remote computational node and a local computational node interconnected with one another by a high speed data link is described. A Universal Computer Control System (UCCS) for the telerobot is located at each node. Each node is provided with a multibus computer system which is characterized by a plurality of processors with all processors being connected to a common bus, and including at least one command processor. The command processor communicates over the bus with a plurality of joint controller cards. A plurality of direct current torque motors, of the type used in telerobot joints and telerobot hand-held controllers, are connected to the controller cards and responds to digital control signals from the command processor. Essential motor operating parameters are sensed by analog sensing circuits and the sensed analog signals are converted to digital signals for storage at the controller cards where such signals can be read during an address read/write cycle of the command processing processor.

Non-parametric model selection for subject-specific topological organization of resting-state functional connectivity.

PubMed

Ferrarini, Luca; Veer, Ilya M; van Lew, Baldur; Oei, Nicole Y L; van Buchem, Mark A; Reiber, Johan H C; Rombouts, Serge A R B; Milles, J

2011-06-01

In recent years, graph theory has been successfully applied to study functional and anatomical connectivity networks in the human brain. Most of these networks have shown small-world topological characteristics: high efficiency in long distance communication between nodes, combined with highly interconnected local clusters of nodes. Moreover, functional studies performed at high resolutions have presented convincing evidence that resting-state functional connectivity networks exhibits (exponentially truncated) scale-free behavior. Such evidence, however, was mostly presented qualitatively, in terms of linear regressions of the degree distributions on log-log plots. Even when quantitative measures were given, these were usually limited to the r(2) correlation coefficient. However, the r(2) statistic is not an optimal estimator of explained variance, when dealing with (truncated) power-law models. Recent developments in statistics have introduced new non-parametric approaches, based on the Kolmogorov-Smirnov test, for the problem of model selection. In this work, we have built on this idea to statistically tackle the issue of model selection for the degree distribution of functional connectivity at rest. The analysis, performed at voxel level and in a subject-specific fashion, confirmed the superiority of a truncated power-law model, showing high consistency across subjects. Moreover, the most highly connected voxels were found to be consistently part of the default mode network. Our results provide statistically sound support to the evidence previously presented in literature for a truncated power-law model of resting-state functional connectivity. Copyright © 2010 Elsevier Inc. All rights reserved.

The Cabled Component of NSF's Ocean Observatories Initiative: A Distributed, Multi-Sensor, Interactive Telepresence Within Ever-Shifting Marine Ecosystems

NASA Astrophysics Data System (ADS)

Delaney, J. R.; Kelley, D. S.; Proskurowski, G. K.; Kawka, O. E.; Fundis, A.; Mulvihill, M.; Harkins, G.; Harrington, M.; McGuire, C.; Manalang, D.; Light, R.; Stewart, A.; Brand, B.

2013-12-01

Since mid-year 2011, NSF's Ocean Observatories Initiative has made considerable progress in installing its cabled seafloor and water-column component off the Washington-Oregon Coast. The Primary Infrastructure is nearly operational and includes ~900 km of high-power (10 kV) and bandwidth (10 Gbs) submarine electro-optical cable and 7 seafloor power- and communications switching stations (nodes) in a two-cable network spanning tectonically active zones across the Juan de Fuca Plate, with access to the overlying ocean. The system is connected to a shore-landing in Pacific City, Oregon, with a dual-path terrestrial backhaul to Portland where connections to major continent-wide, high-speed networks link via the Internet to the undersea system. During summer 2013 the VISIONS'13 expedition, using the R/V Thompson and the remotely operated vehicle (ROV) ROPOS, placed a number of secondary infrastructure elements on the seafloor, ready to be connected to the Primary Nodes when the system is fully tested and accepted by the Consortium for Ocean Leadership. Secondary infrastructure installed using the ROV ROPOS includes over 23,000 meters of extension cables, which comprise twelve electro-optical and electrical cables that provide links from the Primary Nodes to experimental sites and instrument clusters. Smaller nodes (junction boxes) were also deployed, with three installed on the seafloor. All cables and junction boxes were fully tested, which included powering up and communicating through the nodes and sensors using the ROV ROPOS as a power-communication source, and live data transmission of the resultant engineering and science data to the ship located 3000-1500m above the seafloor. Locations include sites near the base of the continental slope and on Axial Seamount, the most magmatically active volcano on the Juan de Fuca Ridge. Real-time data streamed from instruments connected to extension cables at Axial Volcano via ROPOS revealed a significant local earthquake on the volcano, and a minor signal showing direct tidal measurements from 300 miles offshore. Sensors to be installed and connected in 2014 will provide seismic information, current velocities, inflation and deflation measurements of the volcanic caldera, high-definition video on demand, digital-still imagery, chemical data from methane seeps and vent sites using mass spectrometers, and an array of thermistors in a low-temperature vent field. Six instrumented full water-column moorings with two different types of profilers will be installed and connected to the cable in 2014.

A transmission power optimization with a minimum node degree for energy-efficient wireless sensor networks with full-reachability.

PubMed

Chen, Yi-Ting; Horng, Mong-Fong; Lo, Chih-Cheng; Chu, Shu-Chuan; Pan, Jeng-Shyang; Liao, Bin-Yih

2013-03-20

Transmission power optimization is the most significant factor in prolonging the lifetime and maintaining the connection quality of wireless sensor networks. Un-optimized transmission power of nodes either interferes with or fails to link neighboring nodes. The optimization of transmission power depends on the expected node degree and node distribution. In this study, an optimization approach to an energy-efficient and full reachability wireless sensor network is proposed. In the proposed approach, an adjustment model of the transmission range with a minimum node degree is proposed that focuses on topology control and optimization of the transmission range according to node degree and node density. The model adjusts the tradeoff between energy efficiency and full reachability to obtain an ideal transmission range. In addition, connectivity and reachability are used as performance indices to evaluate the connection quality of a network. The two indices are compared to demonstrate the practicability of framework through simulation results. Furthermore, the relationship between the indices under the conditions of various node degrees is analyzed to generalize the characteristics of node densities. The research results on the reliability and feasibility of the proposed approach will benefit the future real deployments.

A Transmission Power Optimization with a Minimum Node Degree for Energy-Efficient Wireless Sensor Networks with Full-Reachability

PubMed Central

Chen, Yi-Ting; Horng, Mong-Fong; Lo, Chih-Cheng; Chu, Shu-Chuan; Pan, Jeng-Shyang; Liao, Bin-Yih

2013-01-01

Transmission power optimization is the most significant factor in prolonging the lifetime and maintaining the connection quality of wireless sensor networks. Un-optimized transmission power of nodes either interferes with or fails to link neighboring nodes. The optimization of transmission power depends on the expected node degree and node distribution. In this study, an optimization approach to an energy-efficient and full reachability wireless sensor network is proposed. In the proposed approach, an adjustment model of the transmission range with a minimum node degree is proposed that focuses on topology control and optimization of the transmission range according to node degree and node density. The model adjusts the tradeoff between energy efficiency and full reachability to obtain an ideal transmission range. In addition, connectivity and reachability are used as performance indices to evaluate the connection quality of a network. The two indices are compared to demonstrate the practicability of framework through simulation results. Furthermore, the relationship between the indices under the conditions of various node degrees is analyzed to generalize the characteristics of node densities. The research results on the reliability and feasibility of the proposed approach will benefit the future real deployments. PMID:23519351

Self-assembly of the yeast actomyosin contractile ring as an aggregation process: kinetics of formation and instability regimes

NASA Astrophysics Data System (ADS)

Ojkic, Nikola; Vavylonis, Dimitrios

2009-03-01

Fission yeast cells assemble an equatorial contractile ring for cytokinesis, the last step of mitosis. The ring assembles from ˜ 65 membrane-bound ``nodes''' containing myosin motors and other proteins. Actin filaments that grow out from the nodes establish transient connections among the nodes and aid in pulling them together in a process that appears as pair-wise attraction (Vavylonis et al. Science 97:319, 2008). We used scaling arguments, coarse grained stability analysis of homogeneous states, and Monte Carlo simulations of simple models, to explore the conditions that yield fast and efficient ring formation, as opposed to formation of isolated clumps. We described our results as a function of: number of nodes, rate of establishing connections, range of node interaction, distance traveled per node interaction and broad band width, w. Uniform cortical 2d distributions of nodes are stable over short times due to randomness of connections among nodes, but become unstable over long times due to fluctuations in the initial node distribution. Successful condensation of nodes into a ring requires sufficiently small w such that lateral contraction occurs faster then clump formation.

Emergence of rich-club topology and coordinated dynamics in development of hippocampal functional networks in vitro.

PubMed

Schroeter, Manuel S; Charlesworth, Paul; Kitzbichler, Manfred G; Paulsen, Ole; Bullmore, Edward T

2015-04-08

Recent studies demonstrated that the anatomical network of the human brain shows a "rich-club" organization. This complex topological feature implies that highly connected regions, hubs of the large-scale brain network, are more densely interconnected with each other than expected by chance. Rich-club nodes were traversed by a majority of short paths between peripheral regions, underlining their potential importance for efficient global exchange of information between functionally specialized areas of the brain. Network hubs have also been described at the microscale of brain connectivity (so-called "hub neurons"). Their role in shaping synchronous dynamics and forming microcircuit wiring during development, however, is not yet fully understood. The present study aimed to investigate the role of hubs during network development, using multi-electrode arrays and functional connectivity analysis during spontaneous multi-unit activity (MUA) of dissociated primary mouse hippocampal neurons. Over the first 4 weeks in vitro, functional connectivity significantly increased in strength, density, and size, with mature networks demonstrating a robust modular and small-world topology. As expected by a "rich-get-richer" growth rule of network evolution, MUA graphs were found to form rich-clubs at an early stage in development (14 DIV). Later on, rich-club nodes were a consistent topological feature of MUA graphs, demonstrating high nodal strength, efficiency, and centrality. Rich-club nodes were also found to be crucial for MUA dynamics. They often served as broker of spontaneous activity flow, confirming that hub nodes and rich-clubs may play an important role in coordinating functional dynamics at the microcircuit level. Copyright © 2015 the authors 0270-6474/15/355459-12$15.00/0.

Fault-Tolerant Self-Stabilizing Distributed Clock Synchronization Protocol for Arbitrary Digraphs

NASA Technical Reports Server (NTRS)

Malekpour, Mahyar R. (Inventor)

2014-01-01

A self-stabilizing network in the form of an arbitrary, non-partitioned digraph includes K nodes having a synchronizer executing a protocol. K-1 monitors of each node may receive a Sync message transmitted from a directly connected node. When the Sync message is received, the logical clock value for the receiving node is set to between 0 and a communication latency value (gamma) if the clock value is less than a minimum event-response delay (D). A new Sync message is also transmitted to any directly connected nodes if the clock value is greater than or equal to both D and a graph threshold (T(sub S)). When the Sync message is not received the synchronizer increments the clock value if the clock value is less than a resynchronization period (P), and resets the clock value and transmits a new Sync message to all directly connected nodes when the clock value equals or exceeds P.

Discussion on Influence of High Strength Bolt’s Parameters on the Weld Reinforced Combined Connection with Bolts and Welds

NASA Astrophysics Data System (ADS)

Ma, Jiansuo; Wang, Yuanqing; Li, Mingfeng; Bai, Runshan; Ban, Huiyong

2018-03-01

In the process of existing steel structure operation, in order to prevent the bolted joints from being damaged by insufficient carrying capacity, welds can be used for reinforcement. Weld reinforced combined connection with bolts and weld consists with high strength bolts and side fillet weld composition. The parameters and properties of high strength bolts and fillet welds have a direct effect on the connection. Based on the test results, We explore the influence that welding seam reinforcement and the performance of the connection between the number of high strength bolts and specifications changes in this paper. It will provide a theoretical reference for the design of connection nodes of steel structure reinforcement project.

Research on TCP/IP network communication based on Node.js

NASA Astrophysics Data System (ADS)

Huang, Jing; Cai, Lixiong

2018-04-01

In the face of big data, long connection and high synchronization, TCP/IP network communication will cause performance bottlenecks due to its blocking multi-threading service model. This paper presents a method of TCP/IP network communication protocol based on Node.js. On the basis of analyzing the characteristics of Node.js architecture and asynchronous non-blocking I/O model, the principle of its efficiency is discussed, and then compare and analyze the network communication model of TCP/IP protocol to expound the reasons why TCP/IP protocol stack is widely used in network communication. Finally, according to the large data and high concurrency in the large-scale grape growing environment monitoring process, a TCP server design based on Node.js is completed. The results show that the example runs stably and efficiently.

A review of variables of urban street connectivity for spatial connection

NASA Astrophysics Data System (ADS)

Mohamad, W. S. N. W.; Said, I.

2014-02-01

Several studies on street connectivity in cities and towns have been modeled on topology, morphology, technology and psychology of people living in the urban environment. Street connectivity means the connection of streets that offers people alternative routes. However, there emerge difficulties to determine the suitable variables and analysis to be chosen in defining the accurate result for studies street connectivity. The aim of this paper is to identify variables of street connectivity by applying GIS and Space Syntax. This paper reviews the variables of street connectivity from 15 past articles done in 1990s to early 2000s from journals of nine disciplines on Environment and Behavior, Planning and Design, Computers, Environment and Urban Systems, Applied Earth Observation and Geo-information, Environment and Planning, Physica A: Statistical Mechanics and its Applications, Environmental Psychology, Social Science and Medicine and Building and Environment. From the review, there are four variables found for street connectivity: link (streets-streets, street-nodes or node-streets, nodes-nodes), accessibility, least-angle, and centrality. Space syntax and GIS are suitable tools to analyze the four variables relating to systematic street systems for pedestrians. This review implies that planners of the street systems, in the aspect of street connectivity in cities and towns, should consider these four variables.

Lymph node toxoplasmosis. Follow-up of 237 histologically diagnosed and serologically verified cases.

PubMed

Miettinen, M; Saxén, L; Saxén, E

1980-01-01

The clinical features, histology and follow-up of lymph node toxoplasmosis are presented in the light of 237 histologically and serologically verified cases. Lymph node toxoplasmosis is a disease with mild symptoms, and in most patients the enlarged lymph nodes were the only sign. Three fourths of the patients were women and the majority were under 40 years of age. The clinical picture was not specific, but suggestive features included a relatively short history, presence of the nodes in the neck and relative lymphocytosis in peripheral blood. Histological changes in the lymph nodes were characteristic. The most important features were strong hyperplasia but preserved general structure with small groups of epithelioid cells both in the paracortical area and in the germinal centers. Strands of monocytoid cells were usually found. 80% of the cases with typical histology also had high antibody titers, and in more than 85% of the cases with high antibodies, the lymph nodes presented a typical picture of toxoplasmosis. The follow-up revealed that lymph node toxoplasmosis. The follow-up revealed that lymph node toxoplasmosis is a disease without complications, nor is there any connection with malignant lymphomas.

New Scheduling Algorithms for Agile All-Photonic Networks

NASA Astrophysics Data System (ADS)

Mehri, Mohammad Saleh; Ghaffarpour Rahbar, Akbar

2017-12-01

An optical overlaid star network is a class of agile all-photonic networks that consists of one or more core node(s) at the center of the star network and a number of edge nodes around the core node. In this architecture, a core node may use a scheduling algorithm for transmission of traffic through the network. A core node is responsible for scheduling optical packets that arrive from edge nodes and switching them toward their destinations. Nowadays, most edge nodes use virtual output queue (VOQ) architecture for buffering client packets to achieve high throughput. This paper presents two efficient scheduling algorithms called discretionary iterative matching (DIM) and adaptive DIM. These schedulers find maximum matching in a small number of iterations and provide high throughput and incur low delay. The number of arbiters in these schedulers and the number of messages exchanged between inputs and outputs of a core node are reduced. We show that DIM and adaptive DIM can provide better performance in comparison with iterative round-robin matching with SLIP (iSLIP). SLIP means the act of sliding for a short distance to select one of the requested connections based on the scheduling algorithm.

Preferential degradation of cognitive networks differentiates Alzheimer's disease from ageing.

PubMed

Chhatwal, Jasmeer P; Schultz, Aaron P; Johnson, Keith A; Hedden, Trey; Jaimes, Sehily; Benzinger, Tammie L S; Jack, Clifford; Ances, Beau M; Ringman, John M; Marcus, Daniel S; Ghetti, Bernardino; Farlow, Martin R; Danek, Adrian; Levin, Johannes; Yakushev, Igor; Laske, Christoph; Koeppe, Robert A; Galasko, Douglas R; Xiong, Chengjie; Masters, Colin L; Schofield, Peter R; Kinnunen, Kirsi M; Salloway, Stephen; Martins, Ralph N; McDade, Eric; Cairns, Nigel J; Buckles, Virginia D; Morris, John C; Bateman, Randall; Sperling, Reisa A

2018-05-01

Converging evidence from structural, metabolic and functional connectivity MRI suggests that neurodegenerative diseases, such as Alzheimer's disease, target specific neural networks. However, age-related network changes commonly co-occur with neuropathological cascades, limiting efforts to disentangle disease-specific alterations in network function from those associated with normal ageing. Here we elucidate the differential effects of ageing and Alzheimer's disease pathology through simultaneous analyses of two functional connectivity MRI datasets: (i) young participants harbouring highly-penetrant mutations leading to autosomal-dominant Alzheimer's disease from the Dominantly Inherited Alzheimer's Network (DIAN), an Alzheimer's disease cohort in which age-related comorbidities are minimal and likelihood of progression along an Alzheimer's disease trajectory is extremely high; and (ii) young and elderly participants from the Harvard Aging Brain Study, a cohort in which imaging biomarkers of amyloid burden and neurodegeneration can be used to disambiguate ageing alone from preclinical Alzheimer's disease. Consonant with prior reports, we observed the preferential degradation of cognitive (especially the default and dorsal attention networks) over motor and sensory networks in early autosomal-dominant Alzheimer's disease, and found that this distinctive degradation pattern was magnified in more advanced stages of disease. Importantly, a nascent form of the pattern observed across the autosomal-dominant Alzheimer's disease spectrum was also detectable in clinically normal elderly with clear biomarker evidence of Alzheimer's disease pathology (preclinical Alzheimer's disease). At the more granular level of individual connections between node pairs, we observed that connections within cognitive networks were preferentially targeted in Alzheimer's disease (with between network connections relatively spared), and that connections between positively coupled nodes (correlations) were preferentially degraded as compared to connections between negatively coupled nodes (anti-correlations). In contrast, ageing in the absence of Alzheimer's disease biomarkers was characterized by a far less network-specific degradation across cognitive and sensory networks, of between- and within-network connections, and of connections between positively and negatively coupled nodes. We go on to demonstrate that formalizing the differential patterns of network degradation in ageing and Alzheimer's disease may have the practical benefit of yielding connectivity measurements that highlight early Alzheimer's disease-related connectivity changes over those due to age-related processes. Together, the contrasting patterns of connectivity in Alzheimer's disease and ageing add to prior work arguing against Alzheimer's disease as a form of accelerated ageing, and suggest multi-network composite functional connectivity MRI metrics may be useful in the detection of early Alzheimer's disease-specific alterations co-occurring with age-related connectivity changes. More broadly, our findings are consistent with a specific pattern of network degradation associated with the spreading of Alzheimer's disease pathology within targeted neural networks.

A game-theoretic approach to optimize ad hoc networks inspired by small-world network topology

NASA Astrophysics Data System (ADS)

Tan, Mian; Yang, Tinghong; Chen, Xing; Yang, Gang; Zhu, Guoqing; Holme, Petter; Zhao, Jing

2018-03-01

Nodes in ad hoc networks are connected in a self-organized manner. Limited communication radius makes information transmit in multi-hop mode, and each forwarding needs to consume the energy of nodes. Insufficient communication radius or exhaustion of energy may cause the absence of some relay nodes and links, further breaking network connectivity. On the other hand, nodes in the network may refuse to cooperate due to objective faulty or personal selfish, hindering regular communication in the network. This paper proposes a model called Repeated Game in Small World Networks (RGSWN). In this model, we first construct ad hoc networks with small-world feature by forming "communication shortcuts" between multiple-radio nodes. Small characteristic path length reduces average forwarding times in networks; meanwhile high clustering coefficient enhances network robustness. Such networks still maintain relative low global power consumption, which is beneficial to extend the network survival time. Then we use MTTFT strategy (Mend-Tolerance Tit-for-Tat) for repeated game as a rule for the interactions between neighbors in the small-world networks. Compared with other five strategies of repeated game, this strategy not only punishes the nodes' selfishness more reasonably, but also has the best tolerance to the network failure. This work is insightful for designing an efficient and robust ad hoc network.

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

Bradonjic, Milan; Elsasser, Robert; Friedrich, Tobias

A Randon Geometric Graph (RGG) is constructed by distributing n nodes uniformly at random in the unit square and connecting two nodes if their Euclidean distance is at most r, for some prescribed r. They analyze the following randomized broadcast algorithm on RGGs. At the beginning, there is only one informed node. Then in each round, each informed node chooses a neighbor uniformly at random and informs it. They prove that this algorithm informs every node in the largest component of a RGG in {Omicron}({radical}n/r) rounds with high probability. This holds for any value of r larger than the criticalmore » value for the emergence of a giant component. In particular, the result implies that the diameter of the giant component is {Theta}({radical}n/r).« less

Connectivity disruption sparks explosive epidemic spreading.

PubMed

Böttcher, L; Woolley-Meza, O; Goles, E; Helbing, D; Herrmann, H J

2016-04-01

We investigate the spread of an infection or other malfunction of cascading nature when a system component can recover only if it remains reachable from a functioning central component. We consider the susceptible-infected-susceptible model, typical of mathematical epidemiology, on a network. Infection spreads from infected to healthy nodes, with the addition that infected nodes can only recover when they remain connected to a predefined central node, through a path that contains only healthy nodes. In this system, clusters of infected nodes will absorb their noninfected interior because no path exists between the central node and encapsulated nodes. This gives rise to the simultaneous infection of multiple nodes. Interestingly, the system converges to only one of two stationary states: either the whole population is healthy or it becomes completely infected. This simultaneous cluster infection can give rise to discontinuous jumps of different sizes in the number of failed nodes. Larger jumps emerge at lower infection rates. The network topology has an important effect on the nature of the transition: we observed hysteresis for networks with dominating local interactions. Our model shows how local spread can abruptly turn uncontrollable when it disrupts connectivity at a larger spatial scale.

Empirical study on a directed and weighted bus transport network in China

NASA Astrophysics Data System (ADS)

Feng, Shumin; Hu, Baoyu; Nie, Cen; Shen, Xianghao

2016-01-01

Bus transport networks are directed complex networks that consist of routes, stations, and passenger flow. In this study, the concept of duplication factor is introduced to analyze the differences between uplinks and downlinks for the bus transport network of Harbin (BTN-H). Further, a new representation model for BTNs is proposed, named as directed-space P. Two empirical characteristics of BTN-H are reported in this paper. First, the cumulative distributions of weighted degree, degree, number of routes that connect to each station, and node weight (peak-hour trips at a station) uniformly follow the exponential law. Meanwhile, the node weight shows positive correlations with the corresponding weighted degree, degree, and number of routes that connect to a station. Second, a new richness parameter of a node is explored by its node weight and the connectivity, weighted connectivity, average shortest path length and efficiency between rich nodes can be fitted by composite exponential functions to demonstrate the rich-club phenomenon.

Fault current limiter and alternating current circuit breaker

DOEpatents

Boenig, Heinrich J.

1998-01-01

A solid-state circuit breaker and current limiter for a load served by an alternating current source having a source impedance, the solid-state circuit breaker and current limiter comprising a thyristor bridge interposed between the alternating current source and the load, the thyristor bridge having four thyristor legs and four nodes, with a first node connected to the alternating current source, and a second node connected to the load. A coil is connected from a third node to a fourth node, the coil having an impedance of a value calculated to limit the current flowing therethrough to a predetermined value. Control means are connected to the thyristor legs for limiting the alternating current flow to the load under fault conditions to a predetermined level, and for gating the thyristor bridge under fault conditions to quickly reduce alternating current flowing therethrough to zero and thereafter to maintain the thyristor bridge in an electrically open condition preventing the alternating current from flowing therethrough for a predetermined period of time.

Fault current limiter and alternating current circuit breaker

DOEpatents

Boenig, H.J.

1998-03-10

A solid-state circuit breaker and current limiter are disclosed for a load served by an alternating current source having a source impedance, the solid-state circuit breaker and current limiter comprising a thyristor bridge interposed between the alternating current source and the load, the thyristor bridge having four thyristor legs and four nodes, with a first node connected to the alternating current source, and a second node connected to the load. A coil is connected from a third node to a fourth node, the coil having an impedance of a value calculated to limit the current flowing therethrough to a predetermined value. Control means are connected to the thyristor legs for limiting the alternating current flow to the load under fault conditions to a predetermined level, and for gating the thyristor bridge under fault conditions to quickly reduce alternating current flowing therethrough to zero and thereafter to maintain the thyristor bridge in an electrically open condition preventing the alternating current from flowing therethrough for a predetermined period of time. 9 figs.

Influence of Time-Series Normalization, Number of Nodes, Connectivity and Graph Measure Selection on Seizure-Onset Zone Localization from Intracranial EEG.

PubMed

van Mierlo, Pieter; Lie, Octavian; Staljanssens, Willeke; Coito, Ana; Vulliémoz, Serge

2018-04-26

We investigated the influence of processing steps in the estimation of multivariate directed functional connectivity during seizures recorded with intracranial EEG (iEEG) on seizure-onset zone (SOZ) localization. We studied the effect of (i) the number of nodes, (ii) time-series normalization, (iii) the choice of multivariate time-varying connectivity measure: Adaptive Directed Transfer Function (ADTF) or Adaptive Partial Directed Coherence (APDC) and (iv) graph theory measure: outdegree or shortest path length. First, simulations were performed to quantify the influence of the various processing steps on the accuracy to localize the SOZ. Afterwards, the SOZ was estimated from a 113-electrodes iEEG seizure recording and compared with the resection that rendered the patient seizure-free. The simulations revealed that ADTF is preferred over APDC to localize the SOZ from ictal iEEG recordings. Normalizing the time series before analysis resulted in an increase of 25-35% of correctly localized SOZ, while adding more nodes to the connectivity analysis led to a moderate decrease of 10%, when comparing 128 with 32 input nodes. The real-seizure connectivity estimates localized the SOZ inside the resection area using the ADTF coupled to outdegree or shortest path length. Our study showed that normalizing the time-series is an important pre-processing step, while adding nodes to the analysis did only marginally affect the SOZ localization. The study shows that directed multivariate Granger-based connectivity analysis is feasible with many input nodes (> 100) and that normalization of the time-series before connectivity analysis is preferred.

Strength of Structural and Functional Frontostriatal Connectivity Predicts Self-Control in the Healthy Elderly

PubMed Central

Hänggi, Jürgen; Lohrey, Corinna; Drobetz, Reinhard; Baetschmann, Hansruedi; Forstmeier, Simon; Maercker, Andreas; Jäncke, Lutz

2016-01-01

Self-regulation refers to the successful use of executive functions and initiation of top-down processes to control one's thoughts, behavior, and emotions, and it is crucial to perform self-control. Self-control is needed to overcome impulses and can be assessed by delay of gratification (DoG) and delay discounting (DD) paradigms. In children/adolescents, good DoG/DD ability depends on the maturity of frontostriatal connectivity, and its decline in strength with advancing age might adversely affect self-control because prefrontal brain regions are more prone to normal age-related atrophy than other regions. Here, we aimed at highlighting the relationship between frontostriatal connectivity strength and DoG performance in advanced age. We recruited 40 healthy elderly individuals (mean age 74.0 ± 7.7 years) and assessed the DoG ability using the German version of the DoG test for adults in addition to the delay discounting (DD) paradigm. Based on diffusion-weighted and resting-state functional magnetic resonance imaging data, respectively, the structural and functional whole-brain connectome were reconstructed based on 90 different brain regions of interest in addition to a 12-node frontostriatal DoG-specific network and the resulting connectivity matrices were subjected to network-based statistics. The 90-nodes whole-brain connectome analyses revealed subnetworks significantly associated with DoG and DD with a preponderance of frontostriatal nodes involved suggesting a high specificity of the findings. Structural and functional connectivity strengths between the putamen, caudate nucleus, and nucleus accumbens on the one hand and orbitofrontal, dorsal, and ventral lateral prefrontal cortices on the other hand showed strong positive correlations with DoG and negative correlations with DD corrected for age, sex, intracranial volume, and head motion parameters. These associations cannot be explained by differences in impulsivity and executive functioning. This pattern of correlations between structural or functional frontostriatal connectivity strength and self-control suggests that, in addition to the importance of the frontostriatal nodes itself, the structural and functional properties of different connections within the frontostriatal network are crucial for self-controlled behaviors in the healthy elderly. Because high DoG/low DD is a significant predictor of willpower and wellbeing in the elderly population, interventions aiming at strengthening frontostriatal connectivity to strengthen self-controlled behavior are needed in the future. PMID:28105013

On Connected Target k-Coverage in Heterogeneous Wireless Sensor Networks.

PubMed

Yu, Jiguo; Chen, Ying; Ma, Liran; Huang, Baogui; Cheng, Xiuzhen

2016-01-15

Coverage and connectivity are two important performance evaluation indices for wireless sensor networks (WSNs). In this paper, we focus on the connected target k-coverage (CTC k) problem in heterogeneous wireless sensor networks (HWSNs). A centralized connected target k-coverage algorithm (CCTC k) and a distributed connected target k-coverage algorithm (DCTC k) are proposed so as to generate connected cover sets for energy-efficient connectivity and coverage maintenance. To be specific, our proposed algorithms aim at achieving minimum connected target k-coverage, where each target in the monitored region is covered by at least k active sensor nodes. In addition, these two algorithms strive to minimize the total number of active sensor nodes and guarantee that each sensor node is connected to a sink, such that the sensed data can be forwarded to the sink. Our theoretical analysis and simulation results show that our proposed algorithms outperform a state-of-art connected k-coverage protocol for HWSNs.

Metabolic PathFinding: inferring relevant pathways in biochemical networks.

PubMed

Croes, Didier; Couche, Fabian; Wodak, Shoshana J; van Helden, Jacques

2005-07-01

Our knowledge of metabolism can be represented as a network comprising several thousands of nodes (compounds and reactions). Several groups applied graph theory to analyse the topological properties of this network and to infer metabolic pathways by path finding. This is, however, not straightforward, with a major problem caused by traversing irrelevant shortcuts through highly connected nodes, which correspond to pool metabolites and co-factors (e.g. H2O, NADP and H+). In this study, we present a web server implementing two simple approaches, which circumvent this problem, thereby improving the relevance of the inferred pathways. In the simplest approach, the shortest path is computed, while filtering out the selection of highly connected compounds. In the second approach, the shortest path is computed on the weighted metabolic graph where each compound is assigned a weight equal to its connectivity in the network. This approach significantly increases the accuracy of the inferred pathways, enabling the correct inference of relatively long pathways (e.g. with as many as eight intermediate reactions). Available options include the calculation of the k-shortest paths between two specified seed nodes (either compounds or reactions). Multiple requests can be submitted in a queue. Results are returned by email, in textual as well as graphical formats (available in http://www.scmbb.ulb.ac.be/pathfinding/).

High-cost, high-capacity backbone for global brain communication.

PubMed

van den Heuvel, Martijn P; Kahn, René S; Goñi, Joaquín; Sporns, Olaf

2012-07-10

Network studies of human brain structural connectivity have identified a specific set of brain regions that are both highly connected and highly central. Recent analyses have shown that these putative hub regions are mutually and densely interconnected, forming a "rich club" within the human brain. Here we show that the set of pathways linking rich club regions forms a central high-cost, high-capacity backbone for global brain communication. Diffusion tensor imaging (DTI) data of two sets of 40 healthy subjects were used to map structural brain networks. The contributions to network cost and communication capacity of global cortico-cortical connections were assessed through measures of their topology and spatial embedding. Rich club connections were found to be more costly than predicted by their density alone and accounted for 40% of the total communication cost. Furthermore, 69% of all minimally short paths between node pairs were found to travel through the rich club and a large proportion of these communication paths consisted of ordered sequences of edges ("path motifs") that first fed into, then traversed, and finally exited the rich club, while passing through nodes of increasing and then decreasing degree. The prevalence of short paths that follow such ordered degree sequences suggests that neural communication might take advantage of strategies for dynamic routing of information between brain regions, with an important role for a highly central rich club. Taken together, our results show that rich club connections make an important contribution to interregional signal traffic, forming a central high-cost, high-capacity backbone for global brain communication.

The stability of financial market networks

NASA Astrophysics Data System (ADS)

Yan, Xin-Guo; Xie, Chi; Wang, Gang-Jin

2014-08-01

We investigate the stability of a financial market network by measuring its topological robustness, namely the ability of the network to resist structural or topological changes. The closing prices of 710 stocks in the Shanghai Stock Exchange (SSE) from 2005 to 2011 are chosen as the empirical data. We divide the period into three sub-periods: before, during, and after the US sub-prime crisis. By monitoring the size of the clusters which fall apart from the network after removing the nodes (i.e., the listed companies in the SSE), we find that: i) the SSE network is sensitive to the nodes' failure, which implies that the network is unstable. ii) the SSE network before the financial crisis has the strongest robustness against the intentional topological damage; iii) the hubs (i.e., highly connected nodes) connect with each other directly and play a vital important role in maintaining SSE network's stability.

Methods for operating parallel computing systems employing sequenced communications

DOEpatents

Benner, R.E.; Gustafson, J.L.; Montry, G.R.

1999-08-10

A parallel computing system and method are disclosed having improved performance where a program is concurrently run on a plurality of nodes for reducing total processing time, each node having a processor, a memory, and a predetermined number of communication channels connected to the node and independently connected directly to other nodes. The present invention improves performance of the parallel computing system by providing a system which can provide efficient communication between the processors and between the system and input and output devices. A method is also disclosed which can locate defective nodes with the computing system. 15 figs.

Methods for operating parallel computing systems employing sequenced communications

DOEpatents

Benner, Robert E.; Gustafson, John L.; Montry, Gary R.

1999-01-01

A parallel computing system and method having improved performance where a program is concurrently run on a plurality of nodes for reducing total processing time, each node having a processor, a memory, and a predetermined number of communication channels connected to the node and independently connected directly to other nodes. The present invention improves performance of performance of the parallel computing system by providing a system which can provide efficient communication between the processors and between the system and input and output devices. A method is also disclosed which can locate defective nodes with the computing system.

Method for simultaneous overlapped communications between neighboring processors in a multiple

DOEpatents

Benner, Robert E.; Gustafson, John L.; Montry, Gary R.

1991-01-01

A parallel computing system and method having improved performance where a program is concurrently run on a plurality of nodes for reducing total processing time, each node having a processor, a memory, and a predetermined number of communication channels connected to the node and independently connected directly to other nodes. The present invention improves performance of performance of the parallel computing system by providing a system which can provide efficient communication between the processors and between the system and input and output devices. A method is also disclosed which can locate defective nodes with the computing system.

Multi-directional fault detection system

DOEpatents

Archer, Charles Jens; Pinnow, Kurt Walter; Ratterman, Joseph D.; Smith, Brian Edward

2010-11-23

An apparatus, program product and method checks for nodal faults in a group of nodes comprising a center node and all adjacent nodes. The center node concurrently communicates with the immediately adjacent nodes in three dimensions. The communications are analyzed to determine a presence of a faulty node or connection.

Multi-directional fault detection system

DOEpatents

Archer, Charles Jens [Rochester, MN; Pinnow, Kurt Walter [Rochester, MN; Ratterman, Joseph D [Rochester, MN; Smith, Brian Edward [Rochester, MN

2009-03-17

An apparatus, program product and method checks for nodal faults in a group of nodes comprising a center node and all adjacent nodes. The center node concurrently communicates with the immediately adjacent nodes in three dimensions. The communications are analyzed to determine a presence of a faulty node or connection.

Multi-directional fault detection system

DOEpatents

Archer, Charles Jens; Pinnow, Kurt Walter; Ratterman, Joseph D.; Smith, Brian Edward

2010-06-29

An apparatus, program product and method checks for nodal faults in a group of nodes comprising a center node and all adjacent nodes. The center node concurrently communicates with the immediately adjacent nodes in three dimensions. The communications are analyzed to determine a presence of a faulty node or connection.

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.

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.

Structure, Function, and Propagation of Information across Living Two, Four, and Eight Node Degree Topologies.

PubMed

Alagapan, Sankaraleengam; Franca, Eric; Pan, Liangbin; Leondopulos, Stathis; Wheeler, Bruce C; DeMarse, Thomas B

2016-01-01

In this study, we created four network topologies composed of living cortical neurons and compared resultant structural-functional dynamics including the nature and quality of information transmission. Each living network was composed of living cortical neurons and were created using microstamping of adhesion promoting molecules and each was "designed" with different levels of convergence embedded within each structure. Networks were cultured over a grid of electrodes that permitted detailed measurements of neural activity at each node in the network. Of the topologies we tested, the "Random" networks in which neurons connect based on their own intrinsic properties transmitted information embedded within their spike trains with higher fidelity relative to any other topology we tested. Within our patterned topologies in which we explicitly manipulated structure, the effect of convergence on fidelity was dependent on both topology and time-scale (rate vs. temporal coding). A more detailed examination using tools from network analysis revealed that these changes in fidelity were also associated with a number of other structural properties including a node's degree, degree-degree correlations, path length, and clustering coefficients. Whereas information transmission was apparent among nodes with few connections, the greatest transmission fidelity was achieved among the few nodes possessing the highest number of connections (high degree nodes or putative hubs). These results provide a unique view into the relationship between structure and its affect on transmission fidelity, at least within these small neural populations with defined network topology. They also highlight the potential role of tools such as microstamp printing and microelectrode array recordings to construct and record from arbitrary network topologies to provide a new direction in which to advance the study of structure-function relationships.

An improved spatial contour tree constructed method

NASA Astrophysics Data System (ADS)

Zheng, Yi; Zhang, Ling; Guilbert, Eric; Long, Yi

2018-05-01

Contours are important data to delineate the landform on a map. A contour tree provides an object-oriented description of landforms and can be used to enrich the topological information. The traditional contour tree is used to store topological relationships between contours in a hierarchical structure and allows for the identification of eminences and depressions as sets of nested contours. This research proposes an improved contour tree so-called spatial contour tree that contains not only the topological but also the geometric information. It can be regarded as a terrain skeleton in 3-dimention, and it is established based on the spatial nodes of contours which have the latitude, longitude and elevation information. The spatial contour tree is built by connecting spatial nodes from low to high elevation for a positive landform, and from high to low elevation for a negative landform to form a hierarchical structure. The connection between two spatial nodes can provide the real distance and direction as a Euclidean vector in 3-dimention. In this paper, the construction method is tested in the experiment, and the results are discussed. The proposed hierarchical structure is in 3-demintion and can show the skeleton inside a terrain. The structure, where all nodes have geo-information, can be used to distinguish different landforms and applied for contour generalization with consideration of geographic characteristics.

Quantum connectivity optimization algorithms for entanglement source deployment in a quantum multi-hop network

NASA Astrophysics Data System (ADS)

Zou, Zhen-Zhen; Yu, Xu-Tao; Zhang, Zai-Chen

2018-04-01

At first, the entanglement source deployment problem is studied in a quantum multi-hop network, which has a significant influence on quantum connectivity. Two optimization algorithms are introduced with limited entanglement sources in this paper. A deployment algorithm based on node position (DNP) improves connectivity by guaranteeing that all overlapping areas of the distribution ranges of the entanglement sources contain nodes. In addition, a deployment algorithm based on an improved genetic algorithm (DIGA) is implemented by dividing the region into grids. From the simulation results, DNP and DIGA improve quantum connectivity by 213.73% and 248.83% compared to random deployment, respectively, and the latter performs better in terms of connectivity. However, DNP is more flexible and adaptive to change, as it stops running when all nodes are covered.

Local receptive field constrained stacked sparse autoencoder for classification of hyperspectral images.

PubMed

Wan, Xiaoqing; Zhao, Chunhui

2017-06-01

As a competitive machine learning algorithm, the stacked sparse autoencoder (SSA) has achieved outstanding popularity in exploiting high-level features for classification of hyperspectral images (HSIs). In general, in the SSA architecture, the nodes between adjacent layers are fully connected and need to be iteratively fine-tuned during the pretraining stage; however, the nodes of previous layers further away may be less likely to have a dense correlation to the given node of subsequent layers. Therefore, to reduce the classification error and increase the learning rate, this paper proposes the general framework of locally connected SSA; that is, the biologically inspired local receptive field (LRF) constrained SSA architecture is employed to simultaneously characterize the local correlations of spectral features and extract high-level feature representations of hyperspectral data. In addition, the appropriate receptive field constraint is concurrently updated by measuring the spatial distances from the neighbor nodes to the corresponding node. Finally, the efficient random forest classifier is cascaded to the last hidden layer of the SSA architecture as a benchmark classifier. Experimental results on two real HSI datasets demonstrate that the proposed hierarchical LRF constrained stacked sparse autoencoder and random forest (SSARF) provides encouraging results with respect to other contrastive methods, for instance, the improvements of overall accuracy in a range of 0.72%-10.87% for the Indian Pines dataset and 0.74%-7.90% for the Kennedy Space Center dataset; moreover, it generates lower running time compared with the result provided by similar SSARF based methodology.

Network geometry inference using common neighbors

NASA Astrophysics Data System (ADS)

Papadopoulos, Fragkiskos; Aldecoa, Rodrigo; Krioukov, Dmitri

2015-08-01

We introduce and explore a method for inferring hidden geometric coordinates of nodes in complex networks based on the number of common neighbors between the nodes. We compare this approach to the HyperMap method, which is based only on the connections (and disconnections) between the nodes, i.e., on the links that the nodes have (or do not have). We find that for high degree nodes, the common-neighbors approach yields a more accurate inference than the link-based method, unless heuristic periodic adjustments (or "correction steps") are used in the latter. The common-neighbors approach is computationally intensive, requiring O (t4) running time to map a network of t nodes, versus O (t3) in the link-based method. But we also develop a hybrid method with O (t3) running time, which combines the common-neighbors and link-based approaches, and we explore a heuristic that reduces its running time further to O (t2) , without significant reduction in the mapping accuracy. We apply this method to the autonomous systems (ASs) Internet, and we reveal how soft communities of ASs evolve over time in the similarity space. We further demonstrate the method's predictive power by forecasting future links between ASs. Taken altogether, our results advance our understanding of how to efficiently and accurately map real networks to their latent geometric spaces, which is an important necessary step toward understanding the laws that govern the dynamics of nodes in these spaces, and the fine-grained dynamics of network connections.

Local area network with fault-checking, priorities, and redundant backup

NASA Technical Reports Server (NTRS)

Morales, Sergio (Inventor); Friedman, Gary L. (Inventor)

1989-01-01

This invention is a redundant error detecting and correcting local area networked computer system having a plurality of nodes each including a network connector board within the node for connecting to an interfacing transceiver operably attached to a network cable. There is a first network cable disposed along a path to interconnect the nodes. The first network cable includes a plurality of first interfacing transceivers attached thereto. A second network cable is disposed in parallel with the first cable and, in like manner, includes a plurality of second interfacing transceivers attached thereto. There are a plurality of three position switches each having a signal input, three outputs for individual selective connection to the input, and a control input for receiving signals designating which of the outputs is to be connected to the signal input. Each of the switches includes means for designating a response address for responding to addressed signals appearing at the control input and each of the switches further has its signal input connected to a respective one of the input/output lines from the nodes. Also, one of the three outputs is connected to a repective one of the plurality of first interfacing transceivers. There is master switch control means having an output connected to the control inputs of the plurality of three position switches and an input for receiving directive signals for outputting addressed switch position signals to the three position switches as well as monitor and control computer means having a pair of network connector boards therein connected to respective ones of one of the first interfacing transceivers and one of the second interfacing transceivers and an output connected to the input of the master switch means for monitoring the status of the networked computer system by sending messages to the nodes and receiving and verifying messages therefrom and for sending control signals to the master switch to cause the master switch to cause respective ones of the nodes to use a desired one of the first and second cables for transmitting and receiving messages and for disconnecting desired ones of the nodes from both cables.

Distinguishing manipulated stocks via trading network analysis

NASA Astrophysics Data System (ADS)

Sun, Xiao-Qian; Cheng, Xue-Qi; Shen, Hua-Wei; Wang, Zhao-Yang

2011-10-01

Manipulation is an important issue for both developed and emerging stock markets. For the study of manipulation, it is critical to analyze investor behavior in the stock market. In this paper, an analysis of the full transaction records of over a hundred stocks in a one-year period is conducted. For each stock, a trading network is constructed to characterize the relations among its investors. In trading networks, nodes represent investors and a directed link connects a stock seller to a buyer with the total trade size as the weight of the link, and the node strength is the sum of all edge weights of a node. For all these trading networks, we find that the node degree and node strength both have tails following a power-law distribution. Compared with non-manipulated stocks, manipulated stocks have a high lower bound of the power-law tail, a high average degree of the trading network and a low correlation between the price return and the seller-buyer ratio. These findings may help us to detect manipulated stocks.

Optimal Quantum Spatial Search on Random Temporal Networks

NASA Astrophysics Data System (ADS)

Chakraborty, Shantanav; Novo, Leonardo; Di Giorgio, Serena; Omar, Yasser

2017-12-01

To investigate the performance of quantum information tasks on networks whose topology changes in time, we study the spatial search algorithm by continuous time quantum walk to find a marked node on a random temporal network. We consider a network of n nodes constituted by a time-ordered sequence of Erdös-Rényi random graphs G (n ,p ), where p is the probability that any two given nodes are connected: After every time interval τ , a new graph G (n ,p ) replaces the previous one. We prove analytically that, for any given p , there is always a range of values of τ for which the running time of the algorithm is optimal, i.e., O (√{n }), even when search on the individual static graphs constituting the temporal network is suboptimal. On the other hand, there are regimes of τ where the algorithm is suboptimal even when each of the underlying static graphs are sufficiently connected to perform optimal search on them. From this first study of quantum spatial search on a time-dependent network, it emerges that the nontrivial interplay between temporality and connectivity is key to the algorithmic performance. Moreover, our work can be extended to establish high-fidelity qubit transfer between any two nodes of the network. Overall, our findings show that one can exploit temporality to achieve optimal quantum information tasks on dynamical random networks.

Analysing the connectivity and communication of suicidal users on twitter

PubMed Central

Colombo, Gualtiero B.; Burnap, Pete; Hodorog, Andrei; Scourfield, Jonathan

2016-01-01

In this paper we aim to understand the connectivity and communication characteristics of Twitter users who post content subsequently classified by human annotators as containing possible suicidal intent or thinking, commonly referred to as suicidal ideation. We achieve this understanding by analysing the characteristics of their social networks. Starting from a set of human annotated Tweets we retrieved the authors’ followers and friends lists, and identified users who retweeted the suicidal content. We subsequently built the social network graphs. Our results show a high degree of reciprocal connectivity between the authors of suicidal content when compared to other studies of Twitter users, suggesting a tightly-coupled virtual community. In addition, an analysis of the retweet graph has identified bridge nodes and hub nodes connecting users posting suicidal ideation with users who were not, thus suggesting a potential for information cascade and risk of a possible contagion effect. This is particularly emphasised by considering the combined graph merging friendship and retweeting links. PMID:26973360

Active Nodal Task Seeking for High-Performance, Ultra-Dependable Computing

DTIC Science & Technology

1994-07-01

implementation. Figure 1 shows a hardware organization of ANTS: stand-alone computing nodes inter - connected by buses. 2.1 Run Time Partitioning The...nodes in 14 respond to changing loads [27] or system reconfiguration [26]. Existing techniques are all source-initiated or server-initiated [27]. 5.1...short-running task segments. The task segments must be short-running in order that processors will become avalable often enough to satisfy changing

Action and semantic tool knowledge - Effective connectivity in the underlying neural networks.

PubMed

Kleineberg, Nina N; Dovern, Anna; Binder, Ellen; Grefkes, Christian; Eickhoff, Simon B; Fink, Gereon R; Weiss, Peter H

2018-04-26

Evidence from neuropsychological and imaging studies indicate that action and semantic knowledge about tools draw upon distinct neural substrates, but little is known about the underlying interregional effective connectivity. With fMRI and dynamic causal modeling (DCM) we investigated effective connectivity in the left-hemisphere (LH) while subjects performed (i) a function knowledge and (ii) a value knowledge task, both addressing semantic tool knowledge, and (iii) a manipulation (action) knowledge task. Overall, the results indicate crosstalk between action nodes and semantic nodes. Interestingly, effective connectivity was weakened between semantic nodes and action nodes during the manipulation task. Furthermore, pronounced modulations of effective connectivity within the fronto-parietal action system of the LH (comprising lateral occipito-temporal cortex, intraparietal sulcus, supramarginal gyrus, inferior frontal gyrus) were observed in a bidirectional manner during the processing of action knowledge. In contrast, the function and value knowledge tasks resulted in a significant strengthening of the effective connectivity between visual cortex and fusiform gyrus. Importantly, this modulation was present in both semantic tasks, indicating that processing different aspects of semantic knowledge about tools evokes similar effective connectivity patterns. Data revealed that interregional effective connectivity during the processing of tool knowledge occurred in a bidirectional manner with a weakening of connectivity between areas engaged in action and semantic knowledge about tools during the processing of action knowledge. Moreover, different semantic tool knowledge tasks elicited similar effective connectivity patterns. © 2018 Wiley Periodicals, Inc.

All row, planar fault detection system

DOEpatents

Archer, Charles Jens; Pinnow, Kurt Walter; Ratterman, Joseph D; Smith, Brian Edward

2013-07-23

An apparatus, program product and method for detecting nodal faults may simultaneously cause designated nodes of a cell to communicate with all nodes adjacent to each of the designated nodes. Furthermore, all nodes along the axes of the designated nodes are made to communicate with their adjacent nodes, and the communications are analyzed to determine if a node or connection is faulty.

The genetic network of greater sage-grouse: Range-wide identification of keystone hubs of connectivity

Treesearch

Todd B. Cross; Michael K. Schwartz; David E. Naugle; Brad C. Fedy; Jeffrey R. Row; Sara J. Oyler-McCance

2018-01-01

Genetic networks can characterize complex genetic relationships among groups of individuals, which can be used to rank nodes most important to the overall connectivity of the system. Ranking allows scarce resources to be guided toward nodes integral to connectivity. The greater sage-grouse (Centrocercus urophasianus) is a species of conservation concern that breeds on...

Method and systems for a radiation tolerant bus interface circuit

NASA Technical Reports Server (NTRS)

Kinstler, Gary A. (Inventor)

2007-01-01

A bus management tool that allows communication to be maintained between a group of nodes operatively connected on two busses in the presence of radiation by transmitting periodically a first message from one to another of the nodes on one of the busses, determining whether the first message was received by the other of the nodes on the first bus, and when it is determined that the first message was not received by the other of the nodes, transmitting a recovery command to the other of the nodes on a second of the of busses. Methods, systems, and articles of manufacture consistent with the present invention also provide for a bus recovery tool on the other node that re-initializes a bus interface circuit operatively connecting the other node to the first bus in response to the recovery command.

New Markov-Shannon Entropy models to assess connectivity quality in complex networks: from molecular to cellular pathway, Parasite-Host, Neural, Industry, and Legal-Social networks.

PubMed

Riera-Fernández, Pablo; Munteanu, Cristian R; Escobar, Manuel; Prado-Prado, Francisco; Martín-Romalde, Raquel; Pereira, David; Villalba, Karen; Duardo-Sánchez, Aliuska; González-Díaz, Humberto

2012-01-21

Graph and Complex Network theory is expanding its application to different levels of matter organization such as molecular, biological, technological, and social networks. A network is a set of items, usually called nodes, with connections between them, which are called links or edges. There are many different experimental and/or theoretical methods to assign node-node links depending on the type of network we want to construct. Unfortunately, the use of a method for experimental reevaluation of the entire network is very expensive in terms of time and resources; thus the development of cheaper theoretical methods is of major importance. In addition, different methods to link nodes in the same type of network are not totally accurate in such a way that they do not always coincide. In this sense, the development of computational methods useful to evaluate connectivity quality in complex networks (a posteriori of network assemble) is a goal of major interest. In this work, we report for the first time a new method to calculate numerical quality scores S(L(ij)) for network links L(ij) (connectivity) based on the Markov-Shannon Entropy indices of order k-th (θ(k)) for network nodes. The algorithm may be summarized as follows: (i) first, the θ(k)(j) values are calculated for all j-th nodes in a complex network already constructed; (ii) A Linear Discriminant Analysis (LDA) is used to seek a linear equation that discriminates connected or linked (L(ij)=1) pairs of nodes experimentally confirmed from non-linked ones (L(ij)=0); (iii) the new model is validated with external series of pairs of nodes; (iv) the equation obtained is used to re-evaluate the connectivity quality of the network, connecting/disconnecting nodes based on the quality scores calculated with the new connectivity function. This method was used to study different types of large networks. The linear models obtained produced the following results in terms of overall accuracy for network reconstruction: Metabolic networks (72.3%), Parasite-Host networks (93.3%), CoCoMac brain cortex co-activation network (89.6%), NW Spain fasciolosis spreading network (97.2%), Spanish financial law network (89.9%) and World trade network for Intelligent & Active Food Packaging (92.8%). In order to seek these models, we studied an average of 55,388 pairs of nodes in each model and a total of 332,326 pairs of nodes in all models. Finally, this method was used to solve a more complicated problem. A model was developed to score the connectivity quality in the Drug-Target network of US FDA approved drugs. In this last model the θ(k) values were calculated for three types of molecular networks representing different levels of organization: drug molecular graphs (atom-atom bonds), protein residue networks (amino acid interactions), and drug-target network (compound-protein binding). The overall accuracy of this model was 76.3%. This work opens a new door to the computational reevaluation of network connectivity quality (collation) for complex systems in molecular, biomedical, technological, and legal-social sciences as well as in world trade and industry. Copyright © 2011 Elsevier Ltd. All rights reserved.

Noninvasive Electromagnetic Source Imaging and Granger Causality Analysis: An Electrophysiological Connectome (eConnectome) Approach

PubMed Central

Sohrabpour, Abbas; Ye, Shuai; Worrell, Gregory A.; Zhang, Wenbo

2016-01-01

Objective Combined source imaging techniques and directional connectivity analysis can provide useful information about the underlying brain networks in a non-invasive fashion. Source imaging techniques have been used successfully to either determine the source of activity or to extract source time-courses for Granger causality analysis, previously. In this work, we utilize source imaging algorithms to both find the network nodes (regions of interest) and then extract the activation time series for further Granger causality analysis. The aim of this work is to find network nodes objectively from noninvasive electromagnetic signals, extract activation time-courses and apply Granger analysis on the extracted series to study brain networks under realistic conditions. Methods Source imaging methods are used to identify network nodes and extract time-courses and then Granger causality analysis is applied to delineate the directional functional connectivity of underlying brain networks. Computer simulations studies where the underlying network (nodes and connectivity pattern) is known were performed; additionally, this approach has been evaluated in partial epilepsy patients to study epilepsy networks from inter-ictal and ictal signals recorded by EEG and/or MEG. Results Localization errors of network nodes are less than 5 mm and normalized connectivity errors of ~20% in estimating underlying brain networks in simulation studies. Additionally, two focal epilepsy patients were studied and the identified nodes driving the epileptic network were concordant with clinical findings from intracranial recordings or surgical resection. Conclusion Our study indicates that combined source imaging algorithms with Granger causality analysis can identify underlying networks precisely (both in terms of network nodes location and internodal connectivity). Significance The combined source imaging and Granger analysis technique is an effective tool for studying normal or pathological brain conditions. PMID:27740473

Noninvasive Electromagnetic Source Imaging and Granger Causality Analysis: An Electrophysiological Connectome (eConnectome) Approach.

PubMed

Sohrabpour, Abbas; Ye, Shuai; Worrell, Gregory A; Zhang, Wenbo; He, Bin

2016-12-01

Combined source-imaging techniques and directional connectivity analysis can provide useful information about the underlying brain networks in a noninvasive fashion. Source-imaging techniques have been used successfully to either determine the source of activity or to extract source time-courses for Granger causality analysis, previously. In this work, we utilize source-imaging algorithms to both find the network nodes [regions of interest (ROI)] and then extract the activation time series for further Granger causality analysis. The aim of this work is to find network nodes objectively from noninvasive electromagnetic signals, extract activation time-courses, and apply Granger analysis on the extracted series to study brain networks under realistic conditions. Source-imaging methods are used to identify network nodes and extract time-courses and then Granger causality analysis is applied to delineate the directional functional connectivity of underlying brain networks. Computer simulations studies where the underlying network (nodes and connectivity pattern) is known were performed; additionally, this approach has been evaluated in partial epilepsy patients to study epilepsy networks from interictal and ictal signals recorded by EEG and/or Magnetoencephalography (MEG). Localization errors of network nodes are less than 5 mm and normalized connectivity errors of ∼20% in estimating underlying brain networks in simulation studies. Additionally, two focal epilepsy patients were studied and the identified nodes driving the epileptic network were concordant with clinical findings from intracranial recordings or surgical resection. Our study indicates that combined source-imaging algorithms with Granger causality analysis can identify underlying networks precisely (both in terms of network nodes location and internodal connectivity). The combined source imaging and Granger analysis technique is an effective tool for studying normal or pathological brain conditions.

Constructing fMRI connectivity networks: a whole brain functional parcellation method for node definition.

PubMed

Maggioni, Eleonora; Tana, Maria Gabriella; Arrigoni, Filippo; Zucca, Claudio; Bianchi, Anna Maria

2014-05-15

Functional Magnetic Resonance Imaging (fMRI) is used for exploring brain functionality, and recently it was applied for mapping the brain connection patterns. To give a meaningful neurobiological interpretation to the connectivity network, it is fundamental to properly define the network framework. In particular, the choice of the network nodes may affect the final connectivity results and the consequent interpretation. We introduce a novel method for the intra subject topological characterization of the nodes of fMRI brain networks, based on a whole brain parcellation scheme. The proposed whole brain parcellation algorithm divides the brain into clusters that are homogeneous from the anatomical and functional point of view, each of which constitutes a node. The functional parcellation described is based on the Tononi's cluster index, which measures instantaneous correlation in terms of intrinsic and extrinsic statistical dependencies. The method performance and reliability were first tested on simulated data, then on a real fMRI dataset acquired on healthy subjects during visual stimulation. Finally, the proposed algorithm was applied to epileptic patients' fMRI data recorded during seizures, to verify its usefulness as preparatory step for effective connectivity analysis. For each patient, the nodes of the network involved in ictal activity were defined according to the proposed parcellation scheme and Granger Causality Analysis (GCA) was applied to infer effective connectivity. We showed that the algorithm 1) performed well on simulated data, 2) was able to produce reliable inter subjects results and 3) led to a detailed definition of the effective connectivity pattern. Copyright © 2014 Elsevier B.V. All rights reserved.

Rich club analysis in the Alzheimer's disease connectome reveals a relatively undisturbed structural core network

PubMed Central

Daianu, Madelaine; Jahanshad, Neda; Nir, Talia M.; Jack, Clifford R.; Weiner, Michael W.; Bernstein, Matthew; Thompson, Paul M.

2015-01-01

Diffusion imaging can assess the white matter connections within the brain, revealing how neural pathways break down in Alzheimer's disease (AD). We analyzed 3-Tesla whole-brain diffusion-weighted images from 202 participants scanned by the Alzheimer's Disease Neuroimaging Initiative – 50 healthy controls, 110 with mild cognitive impairment (MCI) and 42 AD patients. From whole-brain tractography, we reconstructed structural brain connectivity networks to map connections between cortical regions. We tested whether AD disrupts the ‘rich-club’ – a network property where high-degree network nodes are more interconnected than expected by chance. We calculated the rich-club properties at a range of degree thresholds, as well as other network topology measures including global degree, clustering coefficient, path length and efficiency. Network disruptions predominated in the low-degree regions of the connectome in patients, relative to controls. The other metrics also showed alterations, suggesting a distinctive pattern of disruption in AD, less pronounced in MCI, targeting global brain connectivity, and focusing on more remotely connected nodes rather than the central core of the network. AD involves severely reduced structural connectivity; our step-wise rich club coefficients analyze points to disruptions predominantly in the peripheral network components; other modalities of data are needed to know if this indicates impaired communication among non rich-club regions. The highly connected core was relatively preserved, offering new evidence on the neural basis of progressive risk for cognitive decline. PMID:26037224

A large-scale photonic node architecture that utilizes interconnected OXC subsystems.

PubMed

Iwai, Yuto; Hasegawa, Hiroshi; Sato, Ken-ichi

2013-01-14

We propose a novel photonic node architecture that is composed of interconnected small-scale optical cross-connect subsystems. We also developed an efficient dynamic network control algorithm that complies with a restriction on the number of intra-node fibers used for subsystem interconnection. Numerical evaluations verify that the proposed architecture offers almost the same performance as the equivalent single large-scale cross-connect switch, while enabling substantial hardware scale reductions.

Design of the SLAC RCE Platform: A General Purpose ATCA Based Data Acquisition System

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

Herbst, R.; Claus, R.; Freytag, M.

2015-01-23

The SLAC RCE platform is a general purpose clustered data acquisition system implemented on a custom ATCA compliant blade, called the Cluster On Board (COB). The core of the system is the Reconfigurable Cluster Element (RCE), which is a system-on-chip design based upon the Xilinx Zynq family of FPGAs, mounted on custom COB daughter-boards. The Zynq architecture couples a dual core ARM Cortex A9 based processor with a high performance 28nm FPGA. The RCE has 12 external general purpose bi-directional high speed links, each supporting serial rates of up to 12Gbps. 8 RCE nodes are included on a COB, eachmore » with a 10Gbps connection to an on-board 24-port Ethernet switch integrated circuit. The COB is designed to be used with a standard full-mesh ATCA backplane allowing multiple RCE nodes to be tightly interconnected with minimal interconnect latency. Multiple shelves can be clustered using the front panel 10-gbps connections. The COB also supports local and inter-blade timing and trigger distribution. An experiment specific Rear Transition Module adapts the 96 high speed serial links to specific experiments and allows an experiment-specific timing and busy feedback connection. This coupling of processors with a high performance FPGA fabric in a low latency, multiple node cluster allows high speed data processing that can be easily adapted to any physics experiment. RTEMS and Linux are both ported to the module. The RCE has been used or is the baseline for several current and proposed experiments (LCLS, HPS, LSST, ATLAS-CSC, LBNE, DarkSide, ILC-SiD, etc).« less

Epidemic dynamics on a risk-based evolving social network

NASA Astrophysics Data System (ADS)

Antwi, Shadrack; Shaw, Leah

2013-03-01

Social network models have been used to study how behavior affects the dynamics of an infection in a population. Motivated by HIV, we consider how a trade-off between benefits and risks of sexual connections determine network structure and disease prevalence. We define a stochastic network model with formation and breaking of links as changes in sexual contacts. Each node has an intrinsic benefit its neighbors derive from connecting to it. Nodes' infection status is not apparent to others, but nodes with more connections (higher degree) are assumed more likely to be infected. The probability to form and break links is determined by a payoff computed from the benefit and degree-dependent risk. The disease is represented by a SI (susceptible-infected) model. We study network and epidemic evolution via Monte Carlo simulation and analytically predict the behavior with a heterogeneous mean field approach. The dependence of network connectivity and infection threshold on parameters is determined, and steady state degree distribution and epidemic levels are obtained. We also study a situation where system-wide infection levels alter perception of risk and cause nodes to adjust their behavior. This is a case of an adaptive network, where node status feeds back to change network geometry.

Row fault detection system

DOEpatents

Archer, Charles Jens [Rochester, MN; Pinnow, Kurt Walter [Rochester, MN; Ratterman, Joseph D [Rochester, MN; Smith, Brian Edward [Rochester, MN

2008-10-14

An apparatus, program product and method checks for nodal faults in a row of nodes by causing each node in the row to concurrently communicate with its adjacent neighbor nodes in the row. The communications are analyzed to determine a presence of a faulty node or connection.

Row fault detection system

DOEpatents

Archer, Charles Jens [Rochester, MN; Pinnow, Kurt Walter [Rochester, MN; Ratterman, Joseph D [Rochester, MN; Smith, Brian Edward [Rochester, MN

2012-02-07

An apparatus, program product and method check for nodal faults in a row of nodes by causing each node in the row to concurrently communicate with its adjacent neighbor nodes in the row. The communications are analyzed to determine a presence of a faulty node or connection.

Row fault detection system

DOEpatents

Archer, Charles Jens; Pinnow, Kurt Walter; Ratterman, Joseph D.; Smith, Brian Edward

2010-02-23

An apparatus and program product check for nodal faults in a row of nodes by causing each node in the row to concurrently communicate with its adjacent neighbor nodes in the row. The communications are analyzed to determine a presence of a faulty node or connection.

Exploring the Epileptic Brain Network Using Time-Variant Effective Connectivity and Graph Theory.

PubMed

Storti, Silvia Francesca; Galazzo, Ilaria Boscolo; Khan, Sehresh; Manganotti, Paolo; Menegaz, Gloria

2017-09-01

The application of time-varying measures of causality between source time series can be very informative to elucidate the direction of communication among the regions of an epileptic brain. The aim of the study was to identify the dynamic patterns of epileptic networks in focal epilepsy by applying multivariate adaptive directed transfer function (ADTF) analysis and graph theory to high-density electroencephalographic recordings. The cortical network was modeled after source reconstruction and topology modulations were detected during interictal spikes. First a distributed linear inverse solution, constrained to the individual grey matter, was applied to the averaged spikes and the mean source activity over 112 regions, as identified by the Harvard-Oxford Atlas, was calculated. Then, the ADTF, a dynamic measure of causality, was used to quantify the connectivity strength between pairs of regions acting as nodes in the graph, and the measure of node centrality was derived. The proposed analysis was effective in detecting the focal regions as well as in characterizing the dynamics of the spike propagation, providing evidence of the fact that the node centrality is a reliable feature for the identification of the epileptogenic zones. Validation was performed by multimodal analysis as well as from surgical outcomes. In conclusion, the time-variant connectivity analysis applied to the epileptic patients can distinguish the generator of the abnormal activity from the propagation spread and identify the connectivity pattern over time.

Wireless Data-Acquisition System for Testing Rocket Engines

NASA Technical Reports Server (NTRS)

Lin, Chujen; Lonske, Ben; Hou, Yalin; Xu, Yingjiu; Gang, Mei

2007-01-01

A prototype wireless data-acquisition system has been developed as a potential replacement for a wired data-acquisition system heretofore used in testing rocket engines. The traditional use of wires to connect sensors, signal-conditioning circuits, and data acquisition circuitry is time-consuming and prone to error, especially when, as is often the case, many sensors are used in a test. The system includes one master and multiple slave nodes. The master node communicates with a computer via an Ethernet connection. The slave nodes are powered by rechargeable batteries and are packaged in weatherproof enclosures. The master unit and each of the slave units are equipped with a time-modulated ultra-wide-band (TMUWB) radio transceiver, which spreads its RF energy over several gigahertz by transmitting extremely low-power and super-narrow pulses. In this prototype system, each slave node can be connected to as many as six sensors: two sensors can be connected directly to analog-to-digital converters (ADCs) in the slave node and four sensors can be connected indirectly to the ADCs via signal conditioners. The maximum sampling rate for streaming data from any given sensor is about 5 kHz. The bandwidth of one channel of the TM-UWB radio communication system is sufficient to accommodate streaming of data from five slave nodes when they are fully loaded with data collected through all possible sensor connections. TM-UWB radios have a much higher spatial capacity than traditional sinusoidal wave-based radios. Hence, this TM-UWB wireless data-acquisition can be scaled to cover denser sensor setups for rocket engine test stands. Another advantage of TM-UWB radios is that it will not interfere with existing wireless transmission. The maximum radio-communication range between the master node and a slave node for this prototype system is about 50 ft (15 m) when the master and slave transceivers are equipped with small dipole antennas. The range can be increased by changing to larger antennas and/or greater transmission power. The battery life of a slave node ranges from about six hours during operation at full capacity to as long as three days when the system is in a "sleep" mode used to conserve battery charge during times between setup and rocket-engine testing. Batteries can be added to prolong operational lifetimes. The radio transceiver dominates the power consumption.

Lipoxygenase mediates invasion of intrametastatic lymphatic vessels and propagates lymph node metastasis of human mammary carcinoma xenografts in mouse

PubMed Central

Kerjaschki, Dontscho; Bago-Horvath, Zsuzsanna; Rudas, Margaretha; Sexl, Veronika; Schneckenleithner, Christine; Wolbank, Susanne; Bartel, Gregor; Krieger, Sigurd; Kalt, Romana; Hantusch, Brigitte; Keller, Thomas; Nagy-Bojarszky, Katalin; Huttary, Nicole; Raab, Ingrid; Lackner, Karin; Krautgasser, Katharina; Schachner, Helga; Kaserer, Klaus; Rezar, Sandra; Madlener, Sybille; Vonach, Caroline; Davidovits, Agnes; Nosaka, Hitonari; Hämmerle, Monika; Viola, Katharina; Dolznig, Helmut; Schreiber, Martin; Nader, Alexander; Mikulits, Wolfgang; Gnant, Michael; Hirakawa, Satoshi; Detmar, Michael; Alitalo, Kari; Nijman, Sebastian; Offner, Felix; Maier, Thorsten J.; Steinhilber, Dieter; Krupitza, Georg

2011-01-01

In individuals with mammary carcinoma, the most relevant prognostic predictor of distant organ metastasis and clinical outcome is the status of axillary lymph node metastasis. Metastases form initially in axillary sentinel lymph nodes and progress via connecting lymphatic vessels into postsentinel lymph nodes. However, the mechanisms of consecutive lymph node colonization are unknown. Through the analysis of human mammary carcinomas and their matching axillary lymph nodes, we show here that intrametastatic lymphatic vessels and bulk tumor cell invasion into these vessels highly correlate with formation of postsentinel metastasis. In an in vitro model of tumor bulk invasion, human mammary carcinoma cells caused circular defects in lymphatic endothelial monolayers. These circular defects were highly reminiscent of defects of the lymphovascular walls at sites of tumor invasion in vivo and were primarily generated by the tumor-derived arachidonic acid metabolite 12S-HETE following 15-lipoxygenase-1 (ALOX15) catalysis. Accordingly, pharmacological inhibition and shRNA knockdown of ALOX15 each repressed formation of circular defects in vitro. Importantly, ALOX15 knockdown antagonized formation of lymph node metastasis in xenografted tumors. Furthermore, expression of lipoxygenase in human sentinel lymph node metastases correlated inversely with metastasis-free survival. These results provide evidence that lipoxygenase serves as a mediator of tumor cell invasion into lymphatic vessels and formation of lymph node metastasis in ductal mammary carcinomas. PMID:21540548

Selection of test paths for solder joint intermittent connection faults under DC stimulus

NASA Astrophysics Data System (ADS)

Huakang, Li; Kehong, Lv; Jing, Qiu; Guanjun, Liu; Bailiang, Chen

2018-06-01

The test path of solder joint intermittent connection faults under direct-current stimulus is examined in this paper. According to the physical structure of the circuit, a network model is established first. A network node is utilised to represent the test node. The path edge refers to the number of intermittent connection faults in the path. Then, the selection criteria of the test path based on the node degree index are proposed and the solder joint intermittent connection faults are covered using fewer test paths. Finally, three circuits are selected to verify the method. To test if the intermittent fault is covered by the test paths, the intermittent fault is simulated by a switch. The results show that the proposed method can detect the solder joint intermittent connection fault using fewer test paths. Additionally, the number of detection steps is greatly reduced without compromising fault coverage.

Evoked itch perception is associated with changes in functional brain connectivity.

PubMed

Desbordes, Gaëlle; Li, Ang; Loggia, Marco L; Kim, Jieun; Schalock, Peter C; Lerner, Ethan; Tran, Thanh N; Ring, Johannes; Rosen, Bruce R; Kaptchuk, Ted J; Pfab, Florian; Napadow, Vitaly

2015-01-01

Chronic itch, a highly debilitating condition, has received relatively little attention in the neuroimaging literature. Recent studies suggest that brain regions supporting itch in chronic itch patients encompass sensorimotor and salience networks, and corticostriatal circuits involved in motor preparation for scratching. However, how these different brain areas interact with one another in the context of itch is still unknown. We acquired BOLD fMRI scans in 14 atopic dermatitis patients to investigate resting-state functional connectivity before and after allergen-induced itch exacerbated the clinical itch perception in these patients. A seed-based analysis revealed decreased functional connectivity from baseline resting state to the evoked-itch state between several itch-related brain regions, particularly the insular and cingulate cortices and basal ganglia, where decreased connectivity was significantly correlated with increased levels of perceived itch. In contrast, evoked itch increased connectivity between key nodes of the frontoparietal control network (superior parietal lobule and dorsolateral prefrontal cortex), where higher increase in connectivity was correlated with a lesser increase in perceived itch, suggesting that greater interaction between nodes of this executive attention network serves to limit itch sensation via enhanced top-down regulation. Overall, our results provide the first evidence of itch-dependent changes in functional connectivity across multiple brain regions.

Bridging the Gap between the Human and Macaque Connectome: A Quantitative Comparison of Global Interspecies Structure-Function Relationships and Network Topology

PubMed Central

Miranda-Dominguez, Oscar; Mills, Brian D.; Grayson, David; Woodall, Andrew; Grant, Kathleen A.; Kroenke, Christopher D.

2014-01-01

Resting state functional connectivity MRI (rs-fcMRI) may provide a powerful and noninvasive “bridge” for comparing brain function between patients and experimental animal models; however, the relationship between human and macaque rs-fcMRI remains poorly understood. Here, using a novel surface deformation process for species comparisons in the same anatomical space (Van Essen, 2004, 2005), we found high correspondence, but also unique hub topology, between human and macaque functional connectomes. The global functional connectivity match between species was moderate to strong (r = 0.41) and increased when considering the top 15% strongest connections (r = 0.54). Analysis of the match between functional connectivity and the underlying anatomical connectivity, derived from a previous retrograde tracer study done in macaques (Markov et al., 2012), showed impressive structure–function correspondence in both the macaque and human. When examining the strongest structural connections, we found a 70–80% match between structural and functional connectivity matrices in both species. Finally, we compare species on two widely used metrics for studying hub topology: degree and betweenness centrality. The data showed topological agreement across the species, with nodes of the posterior cingulate showing high degree and betweenness centrality. In contrast, nodes in medial frontal and parietal cortices were identified as having high degree and betweenness in the human as opposed to the macaque. Our results provide: (1) a thorough examination and validation for a surface-based interspecies deformation process, (2) a strong theoretical foundation for making interspecies comparisons of rs-fcMRI, and (3) a unique look at topological distinctions between the species. PMID:24741045

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).

Generalised power graph compression reveals dominant relationship patterns in complex networks

PubMed Central

Ahnert, Sebastian E.

2014-01-01

We introduce a framework for the discovery of dominant relationship patterns in complex networks, by compressing the networks into power graphs with overlapping power nodes. When paired with enrichment analysis of node classification terms, the most compressible sets of edges provide a highly informative sketch of the dominant relationship patterns that define the network. In addition, this procedure also gives rise to a novel, link-based definition of overlapping node communities in which nodes are defined by their relationships with sets of other nodes, rather than through connections within the community. We show that this completely general approach can be applied to undirected, directed, and bipartite networks, yielding valuable insights into the large-scale structure of real-world networks, including social networks and food webs. Our approach therefore provides a novel way in which network architecture can be studied, defined and classified. PMID:24663099

Interplay Among Psychopathologic Variables, Personal Resources, Context-Related Factors, and Real-life Functioning in Individuals With Schizophrenia: A Network Analysis.

PubMed

Galderisi, Silvana; Rucci, Paola; Kirkpatrick, Brian; Mucci, Armida; Gibertoni, Dino; Rocca, Paola; Rossi, Alessandro; Bertolino, Alessandro; Strauss, Gregory P; Aguglia, Eugenio; Bellomo, Antonello; Murri, Martino Belvederi; Bucci, Paola; Carpiniello, Bernardo; Comparelli, Anna; Cuomo, Alessandro; De Berardis, Domenico; Dell'Osso, Liliana; Di Fabio, Fabio; Gelao, Barbara; Marchesi, Carlo; Monteleone, Palmiero; Montemagni, Cristiana; Orsenigo, Giulia; Pacitti, Francesca; Roncone, Rita; Santonastaso, Paolo; Siracusano, Alberto; Vignapiano, Annarita; Vita, Antonio; Zeppegno, Patrizia; Maj, Mario

2018-04-01

Enhanced understanding of factors associated with symptomatic and functional recovery is instrumental to designing personalized treatment plans for people with schizophrenia. To date, this is the first study using network analysis to investigate the associations among cognitive, psychopathologic, and psychosocial variables in a large sample of community-dwelling individuals with schizophrenia. To assess the interplay among psychopathologic variables, cognitive dysfunctions, functional capacity, personal resources, perceived stigma, and real-life functioning in individuals with schizophrenia, using a data-driven approach. This multicenter, cross-sectional study involved 26 university psychiatric clinics and/or mental health departments. A total of 921 community-dwelling individuals with a DSM-IV diagnosis of schizophrenia who were stabilized on antipsychotic treatment were recruited from those consecutively presenting to the outpatient units of the sites between March 1, 2012, and September 30, 2013. Statistical analysis was conducted between July 1 and September 30, 2017. Measures covered psychopathologic variables, neurocognition, social cognition, functional capacity, real-life functioning, resilience, perceived stigma, incentives, and service engagement. Of 740 patients (221 women and 519 men; mean [SD] age, 40.0 [10.9] years) with complete data on the 27 study measures, 163 (22.0%) were remitted (with a score of mild or better on 8 core symptoms). The network analysis showed that functional capacity and everyday life skills were the most central and highly interconnected nodes in the network. Psychopathologic variables split in 2 domains, with positive symptoms being one of the most peripheral and least connected nodes. Functional capacity bridged cognition with everyday life skills; the everyday life skills node was connected to disorganization and expressive deficits. Interpersonal relationships and work skills were connected to avolition; the interpersonal relationships node was also linked to social competence, and the work skills node was linked to social incentives and engagement with mental health services. A case-dropping bootstrap procedure showed centrality indices correlations of 0.75 or greater between the original and randomly defined samples up to 481 of 740 case-dropping (65.0%). No difference in the network structure was found between men and women. The high centrality of functional capacity and everyday life skills in the network suggests that improving the ability to perform tasks relevant to everyday life is critical for any therapeutic intervention in schizophrenia. The pattern of network node connections supports the implementation of personalized interventions.

A conceptual model for quantifying connectivity using graph theory and cellular (per-pixel) approach

NASA Astrophysics Data System (ADS)

Singh, Manudeo; Sinha, Rajiv; Tandon, Sampat K.

2016-04-01

The concept of connectivity is being increasingly used for understanding hydro-geomorphic processes at all spatio-temporal scales. Connectivity is defined as the potential for energy and material flux (water, sediments, nutrients, heat, etc.) to navigate within or between the landscape systems and has two components, structural connectivity and dynamic connectivity. Structural connectivity is defined by the spatially connected features (physical linkages) through which energy and materials flow. Dynamic connectivity is a process defined connectivity component. These two connectivity components also interact with each other by forming a feedback system. This study attempts to explore a method to quantify structural and dynamic connectivity. In fluvial transport systems, sediment and water can flow in either a diffused manner or in a channelized way. At all the scales, hydrological and sediment fluxes can be tracked using a cellular (per-pixel) approach and can be quantified using graphical approach. The material flux, slope and LULC (Land Use Land Cover) weightage factors of a pixel together determine if it will contribute towards connectivity of the landscape/system. In a graphical approach, all the contributing pixels will form a node at their centroid and this node will be connected to the next 'down-node' via a directed edge with 'least cost path'. The length of the edge will depend on the desired spatial scale and its path direction will depend on the traversed pixel's slope and the LULC (weightage) factors. The weightage factors will lie in-between 0 to 1. This value approaches 1 for the LULC factors which promote connectivity. For example, in terms of sediment connectivity, the weightage could be RUSLE (Revised Universal Soil Loss Equation) C-factors with bare unconsolidated surfaces having values close to 1. This method is best suited for areas with low slopes, where LULC can be a deciding as well as dominating factor. The degree of connectivity and its pathways will show changes under different LULC conditions even if the slope remains the same. The graphical approach provides the statistics of connected and disconnected graph elements (edges, nodes) and graph components, thereby allowing the quantification of structural connectivity. This approach also quantifies the dynamic connectivity by allowing the measurement of the fluxes (e.g. via hydrographs or sedimentographs) at any node as well as at any system outlet. The contribution of any sub-system can be understood by removing the remaining sub-systems which can be conveniently achieved by masking associated graph elements.

Early diagnosis of lymph node metastasis: Importance of intranodal pressures.

PubMed

Miura, Yoshinobu; Mikada, Mamoru; Ouchi, Tomoki; Horie, Sachiko; Takeda, Kazu; Yamaki, Teppei; Sakamoto, Maya; Mori, Shiro; Kodama, Tetsuya

2016-03-01

Regional lymph node status is an important prognostic indicator of tumor aggressiveness. However, early diagnosis of metastasis using intranodal pressure, at a stage when lymph node size has not changed significantly, has not been investigated. Here, we use an MXH10/Mo-lpr/lpr mouse model of lymph node metastasis to show that intranodal pressure increases in both the subiliac lymph node and proper axillary lymph node, which are connected by lymphatic vessels, when tumor cells are injected into the subiliac lymph node to induce metastasis to the proper axillary lymph node. We found that intranodal pressure in the subiliac lymph node increased at the stage when metastasis was detected by in vivo bioluminescence, but when proper axillary lymph node volume (measured by high-frequency ultrasound imaging) had not increased significantly. Intravenously injected liposomes, encapsulating indocyanine green, were detected in solid tumors by in vivo bioluminescence, but not in the proper axillary lymph node. Basic blood vessel and lymphatic channel structures were maintained in the proper axillary lymph node, although sinus histiocytosis was detected. These results show that intranodal pressure in the proper axillary lymph node increases at early stages when metastatic tumor cells have not fully proliferated. Intranodal pressure may be a useful parameter for facilitating early diagnosis of lymph node metastasis. © 2015 The Authors. Cancer Science published by John Wiley & Sons Australia, Ltd on behalf of Japanese Cancer Association.

Automatic Network Fingerprinting through Single-Node Motifs

PubMed Central

Echtermeyer, Christoph; da Fontoura Costa, Luciano; Rodrigues, Francisco A.; Kaiser, Marcus

2011-01-01

Complex networks have been characterised by their specific connectivity patterns (network motifs), but their building blocks can also be identified and described by node-motifs—a combination of local network features. One technique to identify single node-motifs has been presented by Costa et al. (L. D. F. Costa, F. A. Rodrigues, C. C. Hilgetag, and M. Kaiser, Europhys. Lett., 87, 1, 2009). Here, we first suggest improvements to the method including how its parameters can be determined automatically. Such automatic routines make high-throughput studies of many networks feasible. Second, the new routines are validated in different network-series. Third, we provide an example of how the method can be used to analyse network time-series. In conclusion, we provide a robust method for systematically discovering and classifying characteristic nodes of a network. In contrast to classical motif analysis, our approach can identify individual components (here: nodes) that are specific to a network. Such special nodes, as hubs before, might be found to play critical roles in real-world networks. PMID:21297963

Transfer-Efficient Face Routing Using the Planar Graphs of Neighbors in High Density WSNs

PubMed Central

Kim, Sang-Ha

2017-01-01

Face routing has been adopted in wireless sensor networks (WSNs) where topological changes occur frequently or maintaining full network information is difficult. For message forwarding in networks, a planar graph is used to prevent looping, and because long edges are removed by planarization and the resulting planar graph is composed of short edges, and messages are forwarded along multiple nodes connected by them even though they can be forwarded directly. To solve this, face routing using information on all nodes within 2-hop range was adopted to forward messages directly to the farthest node within radio range. However, as the density of the nodes increases, network performance plunges because message transfer nodes receive and process increased node information. To deal with this problem, we propose a new face routing using the planar graphs of neighboring nodes to improve transfer efficiency. It forwards a message directly to the farthest neighbor and reduces loads and processing time by distributing network graph construction and planarization to the neighbors. It also decreases the amount of location information to be transmitted by sending information on the planar graph nodes rather than on all neighboring nodes. Simulation results show that it significantly improves transfer efficiency. PMID:29053623

A simple model of global cascades on random networks

NASA Astrophysics Data System (ADS)

Watts, Duncan J.

2002-04-01

The origin of large but rare cascades that are triggered by small initial shocks is a phenomenon that manifests itself as diversely as cultural fads, collective action, the diffusion of norms and innovations, and cascading failures in infrastructure and organizational networks. This paper presents a possible explanation of this phenomenon in terms of a sparse, random network of interacting agents whose decisions are determined by the actions of their neighbors according to a simple threshold rule. Two regimes are identified in which the network is susceptible to very large cascadesherein called global cascadesthat occur very rarely. When cascade propagation is limited by the connectivity of the network, a power law distribution of cascade sizes is observed, analogous to the cluster size distribution in standard percolation theory and avalanches in self-organized criticality. But when the network is highly connected, cascade propagation is limited instead by the local stability of the nodes themselves, and the size distribution of cascades is bimodal, implying a more extreme kind of instability that is correspondingly harder to anticipate. In the first regime, where the distribution of network neighbors is highly skewed, it is found that the most connected nodes are far more likely than average nodes to trigger cascades, but not in the second regime. Finally, it is shown that heterogeneity plays an ambiguous role in determining a system's stability: increasingly heterogeneous thresholds make the system more vulnerable to global cascades; but an increasingly heterogeneous degree distribution makes it less vulnerable.

Statistics of Weighted Brain Networks Reveal Hierarchical Organization and Gaussian Degree Distribution

PubMed Central

Ivković, Miloš; Kuceyeski, Amy; Raj, Ashish

2012-01-01

Whole brain weighted connectivity networks were extracted from high resolution diffusion MRI data of 14 healthy volunteers. A statistically robust technique was proposed for the removal of questionable connections. Unlike most previous studies our methods are completely adapted for networks with arbitrary weights. Conventional statistics of these weighted networks were computed and found to be comparable to existing reports. After a robust fitting procedure using multiple parametric distributions it was found that the weighted node degree of our networks is best described by the normal distribution, in contrast to previous reports which have proposed heavy tailed distributions. We show that post-processing of the connectivity weights, such as thresholding, can influence the weighted degree asymptotics. The clustering coefficients were found to be distributed either as gamma or power-law distribution, depending on the formula used. We proposed a new hierarchical graph clustering approach, which revealed that the brain network is divided into a regular base-2 hierarchical tree. Connections within and across this hierarchy were found to be uncommonly ordered. The combined weight of our results supports a hierarchically ordered view of the brain, whose connections have heavy tails, but whose weighted node degrees are comparable. PMID:22761649

Statistics of weighted brain networks reveal hierarchical organization and Gaussian degree distribution.

PubMed

Ivković, Miloš; Kuceyeski, Amy; Raj, Ashish

2012-01-01

Whole brain weighted connectivity networks were extracted from high resolution diffusion MRI data of 14 healthy volunteers. A statistically robust technique was proposed for the removal of questionable connections. Unlike most previous studies our methods are completely adapted for networks with arbitrary weights. Conventional statistics of these weighted networks were computed and found to be comparable to existing reports. After a robust fitting procedure using multiple parametric distributions it was found that the weighted node degree of our networks is best described by the normal distribution, in contrast to previous reports which have proposed heavy tailed distributions. We show that post-processing of the connectivity weights, such as thresholding, can influence the weighted degree asymptotics. The clustering coefficients were found to be distributed either as gamma or power-law distribution, depending on the formula used. We proposed a new hierarchical graph clustering approach, which revealed that the brain network is divided into a regular base-2 hierarchical tree. Connections within and across this hierarchy were found to be uncommonly ordered. The combined weight of our results supports a hierarchically ordered view of the brain, whose connections have heavy tails, but whose weighted node degrees are comparable.

Space physics analysis network node directory (The Yellow Pages): Fourth edition

NASA Technical Reports Server (NTRS)

Peters, David J.; Sisson, Patricia L.; Green, James L.; Thomas, Valerie L.

1989-01-01

The Space Physics Analysis Network (SPAN) is a component of the global DECnet Internet, which has over 17,000 host computers. The growth of SPAN from its implementation in 1981 to its present size of well over 2,500 registered SPAN host computers, has created a need for users to acquire timely information about the network through a central source. The SPAN Network Information Center (SPAN-NIC) an online facility managed by the National Space Science Data Center (NSSDC) was developed to meet this need for SPAN-wide information. The remote node descriptive information in this document is not currently contained in the SPAN-NIC database, but will be incorporated in the near future. Access to this information is also available to non-DECnet users over a variety of networks such as Telenet, the NASA Packet Switched System (NPSS), and the TCP/IP Internet. This publication serves as the Yellow Pages for SPAN node information. The document also provides key information concerning other computer networks connected to SPAN, nodes associated with each SPAN routing center, science discipline nodes, contacts for primary SPAN nodes, and SPAN reference information. A section on DECnet Internetworking discusses SPAN connections with other wide-area DECnet networks (many with thousands of nodes each). Another section lists node names and their disciplines, countries, and institutions in the SPAN Network Information Center Online Data Base System. All remote sites connected to US-SPAN and European-SPAN (E-SPAN) are indexed. Also provided is information on the SPAN tail circuits, i.e., those remote nodes connected directly to a SPAN routing center, which is the local point of contact for resolving SPAN-related problems. Reference material is included for those who wish to know more about SPAN. Because of the rapid growth of SPAN, the SPAN Yellow Pages is reissued periodically.

Quantum statistics in complex networks

NASA Astrophysics Data System (ADS)

Bianconi, Ginestra

The Barabasi-Albert (BA) model for a complex network shows a characteristic power law connectivity distribution typical of scale free systems. The Ising model on the BA network shows that the ferromagnetic phase transition temperature depends logarithmically on its size. We have introduced a fitness parameter for the BA network which describes the different abilities of nodes to compete for links. This model predicts the formation of a scale free network where each node increases its connectivity in time as a power-law with an exponent depending on its fitness. This model includes the fact that the node connectivity and growth rate do not depend on the node age alone and it reproduces non trivial correlation properties of the Internet. We have proposed a model of bosonic networks by a generalization of the BA model where the properties of quantum statistics can be applied. We have introduced a fitness eta i = e-bei where the temperature T = 1/ b is determined by the noise in the system and the energy ei accounts for qualitative differences of each node for acquiring links. The results of this work show that a power law network with exponent gamma = 2 can give a Bose condensation where a single node grabs a finite fraction of all the links. In order to address the connection with self-organized processes we have introduced a model for a growing Cayley tree that generalizes the dynamics of invasion percolation. At each node we associate a parameter ei (called energy) such that the probability to grow for each node is given by pii ∝ ebei where T = 1/ b is a statistical parameter of the system determined by the noise called the temperature. This model has been solved analytically with a similar mathematical technique as the bosonic scale-free networks and it shows the self organization of the low energy nodes at the interface. In the thermodynamic limit the Fermi distribution describes the probability of the energy distribution at the interface.

DOW-PR DOlphin and Whale Pods Routing Protocol for Underwater Wireless Sensor Networks (UWSNs).

PubMed

Wadud, Zahid; Ullah, Khadem; Hussain, Sajjad; Yang, Xiaodong; Qazi, Abdul Baseer

2018-05-12

Underwater Wireless Sensor Networks (UWSNs) have intrinsic challenges that include long propagation delays, high mobility of sensor nodes due to water currents, Doppler spread, delay variance, multipath, attenuation and geometric spreading. The existing Weighting Depth and Forwarding Area Division Depth Based Routing (WDFAD-DBR) protocol considers the weighting depth of the two hops in order to select the next Potential Forwarding Node (PFN). To improve the performance of WDFAD-DBR, we propose DOlphin and Whale Pod Routing protocol (DOW-PR). In this scheme, we divide the transmission range into a number of transmission power levels and at the same time select the next PFNs from forwarding and suppressed zones. In contrast to WDFAD-DBR, our scheme not only considers the packet upward advancement, but also takes into account the number of suppressed nodes and number of PFNs at the first and second hops. Consequently, reasonable energy reduction is observed while receiving and transmitting packets. Moreover, our scheme also considers the hops count of the PFNs from the sink. In the absence of PFNs, the proposed scheme will select the node from the suppressed region for broadcasting and thus ensures minimum loss of data. Besides this, we also propose another routing scheme (whale pod) in which multiple sinks are placed at water surface, but one sink is embedded inside the water and is physically connected with the surface sink through high bandwidth connection. Simulation results show that the proposed scheme has high Packet Delivery Ratio (PDR), low energy tax, reduced Accumulated Propagation Distance (APD) and increased the network lifetime.

DOW-PR DOlphin and Whale Pods Routing Protocol for Underwater Wireless Sensor Networks (UWSNs)

PubMed Central

Wadud, Zahid; Ullah, Khadem; Hussain, Sajjad; Yang, Xiaodong; Qazi, Abdul Baseer

2018-01-01

Underwater Wireless Sensor Networks (UWSNs) have intrinsic challenges that include long propagation delays, high mobility of sensor nodes due to water currents, Doppler spread, delay variance, multipath, attenuation and geometric spreading. The existing Weighting Depth and Forwarding Area Division Depth Based Routing (WDFAD-DBR) protocol considers the weighting depth of the two hops in order to select the next Potential Forwarding Node (PFN). To improve the performance of WDFAD-DBR, we propose DOlphin and Whale Pod Routing protocol (DOW-PR). In this scheme, we divide the transmission range into a number of transmission power levels and at the same time select the next PFNs from forwarding and suppressed zones. In contrast to WDFAD-DBR, our scheme not only considers the packet upward advancement, but also takes into account the number of suppressed nodes and number of PFNs at the first and second hops. Consequently, reasonable energy reduction is observed while receiving and transmitting packets. Moreover, our scheme also considers the hops count of the PFNs from the sink. In the absence of PFNs, the proposed scheme will select the node from the suppressed region for broadcasting and thus ensures minimum loss of data. Besides this, we also propose another routing scheme (whale pod) in which multiple sinks are placed at water surface, but one sink is embedded inside the water and is physically connected with the surface sink through high bandwidth connection. Simulation results show that the proposed scheme has high Packet Delivery Ratio (PDR), low energy tax, reduced Accumulated Propagation Distance (APD) and increased the network lifetime. PMID:29757208

Communication Range Dynamics and Performance Analysis for a Self-Adaptive Transmission Power Controller.

PubMed

Lucas Martínez, Néstor; Martínez Ortega, José-Fernán; Hernández Díaz, Vicente; Del Toro Matamoros, Raúl M

2016-05-12

The deployment of the nodes in a Wireless Sensor and Actuator Network (WSAN) is typically restricted by the sensing and acting coverage. This implies that the locations of the nodes may be, and usually are, not optimal from the point of view of the radio communication. Additionally, when the transmission power is tuned for those locations, there are other unpredictable factors that can cause connectivity failures, like interferences, signal fading due to passing objects and, of course, radio irregularities. A control-based self-adaptive system is a typical solution to improve the energy consumption while keeping good connectivity. In this paper, we explore how the communication range for each node evolves along the iterations of an energy saving self-adaptive transmission power controller when using different parameter sets in an outdoor scenario, providing a WSAN that automatically adapts to surrounding changes keeping good connectivity. The results obtained in this paper show how the parameters with the best performance keep a k-connected network, where k is in the range of the desired node degree plus or minus a specified tolerance value.

Communication Range Dynamics and Performance Analysis for a Self-Adaptive Transmission Power Controller †

PubMed Central

Lucas Martínez, Néstor; Martínez Ortega, José-Fernán; Hernández Díaz, Vicente; del Toro Matamoros, Raúl M.

2016-01-01

The deployment of the nodes in a Wireless Sensor and Actuator Network (WSAN) is typically restricted by the sensing and acting coverage. This implies that the locations of the nodes may be, and usually are, not optimal from the point of view of the radio communication. Additionally, when the transmission power is tuned for those locations, there are other unpredictable factors that can cause connectivity failures, like interferences, signal fading due to passing objects and, of course, radio irregularities. A control-based self-adaptive system is a typical solution to improve the energy consumption while keeping good connectivity. In this paper, we explore how the communication range for each node evolves along the iterations of an energy saving self-adaptive transmission power controller when using different parameter sets in an outdoor scenario, providing a WSAN that automatically adapts to surrounding changes keeping good connectivity. The results obtained in this paper show how the parameters with the best performance keep a k-connected network, where k is in the range of the desired node degree plus or minus a specified tolerance value. PMID:27187397

Data-based reconstruction of complex geospatial networks, nodal positioning and detection of hidden nodes

PubMed Central

Su, Ri-Qi; Wang, Wen-Xu; Wang, Xiao; Lai, Ying-Cheng

2016-01-01

Given a complex geospatial network with nodes distributed in a two-dimensional region of physical space, can the locations of the nodes be determined and their connection patterns be uncovered based solely on data? We consider the realistic situation where time series/signals can be collected from a single location. A key challenge is that the signals collected are necessarily time delayed, due to the varying physical distances from the nodes to the data collection centre. To meet this challenge, we develop a compressive-sensing-based approach enabling reconstruction of the full topology of the underlying geospatial network and more importantly, accurate estimate of the time delays. A standard triangularization algorithm can then be employed to find the physical locations of the nodes in the network. We further demonstrate successful detection of a hidden node (or a hidden source or threat), from which no signal can be obtained, through accurate detection of all its neighbouring nodes. As a geospatial network has the feature that a node tends to connect with geophysically nearby nodes, the localized region that contains the hidden node can be identified. PMID:26909187

Bisectional fault detection system

DOEpatents

Archer, Charles Jens [Rochester, MN; Pinnow, Kurt Walter [Rochester, MN; Ratterman, Joseph D [Rochester, MN; Smith, Brian Edward [Rochester, MN

2012-02-14

An apparatus, program product and method logically divide a group of nodes and causes node pairs comprising a node from each section to communicate. Results from the communications may be analyzed to determine performance characteristics, such as bandwidth and proper connectivity.

Bisectional fault detection system

DOEpatents

Archer, Charles Jens [Rochester, MN; Pinnow, Kurt Walter [Rochester, MN; Ratterman, Joseph D [Rochester, MN; Smith, Brian Edward [Rochester, MN

2009-08-04

An apparatus and program product logically divide a group of nodes and causes node pairs comprising a node from each section to communicate. Results from the communications may be analyzed to determine performance characteristics, such as bandwidth and proper connectivity.

Bisectional fault detection system

DOEpatents

Archer, Charles Jens [Rochester, MN; Pinnow, Kurt Walter [Rochester, MN; Ratterman, Joseph D [Rochester, MN; Smith, Brian Edward [Rochester, MN

2008-11-11

An apparatus, program product and method logically divides a group of nodes and causes node pairs comprising a node from each section to communicate. Results from the communications may be analyzed to determine performance characteristics, such as bandwidth and proper connectivity.

Model Checking a Self-Stabilizing Distributed Clock Synchronization Protocol for Arbitrary Digraphs

NASA Technical Reports Server (NTRS)

Malekpour, Mahyar R.

2011-01-01

This report presents the mechanical verification of a self-stabilizing distributed clock synchronization protocol for arbitrary digraphs in the absence of faults. This protocol does not rely on assumptions about the initial state of the system, other than the presence of at least one node, and no central clock or a centrally generated signal, pulse, or message is used. The system under study is an arbitrary, non-partitioned digraph ranging from fully connected to 1-connected networks of nodes while allowing for differences in the network elements. Nodes are anonymous, i.e., they do not have unique identities. There is no theoretical limit on the maximum number of participating nodes. The only constraint on the behavior of the node is that the interactions with other nodes are restricted to defined links and interfaces. This protocol deterministically converges within a time bound that is a linear function of the self-stabilization period.

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.

Evidence of Rentian Scaling of Functional Modules in Diverse Biological Networks.

PubMed

How, Javier J; Navlakha, Saket

2018-06-12

Biological networks have long been known to be modular, containing sets of nodes that are highly connected internally. Less emphasis, however, has been placed on understanding how intermodule connections are distributed within a network. Here, we borrow ideas from engineered circuit design and study Rentian scaling, which states that the number of external connections between nodes in different modules is related to the number of nodes inside the modules by a power-law relationship. We tested this property in a broad class of molecular networks, including protein interaction networks for six species and gene regulatory networks for 41 human and 25 mouse cell types. Using evolutionarily defined modules corresponding to known biological processes in the cell, we found that all networks displayed Rentian scaling with a broad range of exponents. We also found evidence for Rentian scaling in functional modules in the Caenorhabditis elegans neural network, but, interestingly, not in three different social networks, suggesting that this property does not inevitably emerge. To understand how such scaling may have arisen evolutionarily, we derived a new graph model that can generate Rentian networks given a target Rent exponent and a module decomposition as inputs. Overall, our work uncovers a new principle shared by engineered circuits and biological networks.

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.

Ventral Striatum Functional Connectivity as a Predictor of Adolescent Depressive Disorder in a Longitudinal Community-Based Sample.

PubMed

Pan, Pedro Mario; Sato, João R; Salum, Giovanni A; Rohde, Luis A; Gadelha, Ary; Zugman, Andre; Mari, Jair; Jackowski, Andrea; Picon, Felipe; Miguel, Eurípedes C; Pine, Daniel S; Leibenluft, Ellen; Bressan, Rodrigo A; Stringaris, Argyris

2017-11-01

Previous studies have implicated aberrant reward processing in the pathogenesis of adolescent depression. However, no study has used functional connectivity within a distributed reward network, assessed using resting-state functional MRI (fMRI), to predict the onset of depression in adolescents. This study used reward network-based functional connectivity at baseline to predict depressive disorder at follow-up in a community sample of adolescents. A total of 637 children 6-12 years old underwent resting-state fMRI. Discovery and replication analyses tested intrinsic functional connectivity (iFC) among nodes of a putative reward network. Logistic regression tested whether striatal node strength, a measure of reward-related iFC, predicted onset of a depressive disorder at 3-year follow-up. Further analyses investigated the specificity of this prediction. Increased left ventral striatum node strength predicted increased risk for future depressive disorder (odds ratio=1.54, 95% CI=1.09-2.18), even after excluding participants who had depressive disorders at baseline (odds ratio=1.52, 95% CI=1.05-2.20). Among 11 reward-network nodes, only the left ventral striatum significantly predicted depression. Striatal node strength did not predict other common adolescent psychopathology, such as anxiety, attention deficit hyperactivity disorder, and substance use. Aberrant ventral striatum functional connectivity specifically predicts future risk for depressive disorder. This finding further emphasizes the need to understand how brain reward networks contribute to youth depression.

Critical tipping point distinguishing two types of transitions in modular network structures

NASA Astrophysics Data System (ADS)

Shai, Saray; Kenett, Dror Y.; Kenett, Yoed N.; Faust, Miriam; Dobson, Simon; Havlin, Shlomo

2015-12-01

Modularity is a key organizing principle in real-world large-scale complex networks. The relatively sparse interactions between modules are critical to the functionality of the system and are often the first to fail. We model such failures as site percolation targeting interconnected nodes, those connecting between modules. We find, using percolation theory and simulations, that they lead to a "tipping point" between two distinct regimes. In one regime, removal of interconnected nodes fragments the modules internally and causes the system to collapse. In contrast, in the other regime, while only attacking a small fraction of nodes, the modules remain but become disconnected, breaking the entire system. We show that networks with broader degree distribution might be highly vulnerable to such attacks since only few nodes are needed to interconnect the modules, consequently putting the entire system at high risk. Our model has the potential to shed light on many real-world phenomena, and we briefly consider its implications on recent advances in the understanding of several neurocognitive processes and diseases.

AISIM (Automated Interactive Simulation Modeling System) VAX Version Training Manual.

DTIC Science & Technology

1985-02-01

node to which the link is to run, a-nd-(3) a user-given name of the link. To pi’ace a link called " LINKI " from NODE1 to NODE2, type CON NODE1,NODE2...example, to eliminate the connection between NODEI and NODE2 type DELETE LINKI The result on the screen would be that the link named "LINK1" would...the user should now enter the command: DEFINE PATH,NODE2 ,NODE4, LINKI ,LINK4 not only would the path from NODE2 to NODE4 be established, but the path

Latency Hiding in Dynamic Partitioning and Load Balancing of Grid Computing Applications

NASA Technical Reports Server (NTRS)

Das, Sajal K.; Harvey, Daniel J.; Biswas, Rupak

2001-01-01

The Information Power Grid (IPG) concept developed by NASA is aimed to provide a metacomputing platform for large-scale distributed computations, by hiding the intricacies of highly heterogeneous environment and yet maintaining adequate security. In this paper, we propose a latency-tolerant partitioning scheme that dynamically balances processor workloads on the.IPG, and minimizes data movement and runtime communication. By simulating an unsteady adaptive mesh application on a wide area network, we study the performance of our load balancer under the Globus environment. The number of IPG nodes, the number of processors per node, and the interconnected speeds are parameterized to derive conditions under which the IPG would be suitable for parallel distributed processing of such applications. Experimental results demonstrate that effective solution are achieved when the IPG nodes are connected by a high-speed asynchronous interconnection network.

Behavior of susceptible-infected-susceptible epidemics on heterogeneous networks with saturation

NASA Astrophysics Data System (ADS)

Joo, Jaewook; Lebowitz, Joel L.

2004-06-01

We investigate saturation effects in susceptible-infected-susceptible models of the spread of epidemics in heterogeneous populations. The structure of interactions in the population is represented by networks with connectivity distribution P(k) , including scale-free (SF) networks with power law distributions P(k)˜ k-γ . Considering cases where the transmission of infection between nodes depends on their connectivity, we introduce a saturation function C(k) which reduces the infection transmission rate λ across an edge going from a node with high connectivity k . A mean-field approximation with the neglect of degree-degree correlation then leads to a finite threshold λc >0 for SF networks with 2<γ⩽3 . We also find, in this approximation, the fraction of infected individuals among those with degree k for λ close to λc . We investigate via computer simulation the contact process on a heterogeneous regular lattice and compare the results with those obtained from mean-field theory with and without neglect of degree-degree correlations.

Effect of inlet modelling on surface drainage in coupled urban flood simulation

NASA Astrophysics Data System (ADS)

Jang, Jiun-Huei; Chang, Tien-Hao; Chen, Wei-Bo

2018-07-01

For a highly developed urban area with complete drainage systems, flood simulation is necessary for describing the flow dynamics from rainfall, to surface runoff, and to sewer flow. In this study, a coupled flood model based on diffusion wave equations was proposed to simulate one-dimensional sewer flow and two-dimensional overland flow simultaneously. The overland flow model provides details on the rainfall-runoff process to estimate the excess runoff that enters the sewer system through street inlets for sewer flow routing. Three types of inlet modelling are considered in this study, including the manhole-based approach that ignores the street inlets by draining surface water directly into manholes, the inlet-manhole approach that drains surface water into manholes that are each connected to multiple inlets, and the inlet-node approach that drains surface water into sewer nodes that are connected to individual inlets. The simulation results were compared with a high-intensity rainstorm event that occurred in 2015 in Taipei City. In the verification of the maximum flood extent, the two approaches that considered street inlets performed considerably better than that without street inlets. When considering the aforementioned models in terms of temporal flood variation, using manholes as receivers leads to an overall inefficient draining of the surface water either by the manhole-based approach or by the inlet-manhole approach. Using the inlet-node approach is more reasonable than using the inlet-manhole approach because the inlet-node approach greatly reduces the fluctuation of the sewer water level. The inlet-node approach is more efficient in draining surface water by reducing flood volume by 13% compared with the inlet-manhole approach and by 41% compared with the manhole-based approach. The results show that inlet modeling has a strong influence on drainage efficiency in coupled flood simulation.

Deterministic quantum state transfer and remote entanglement using microwave photons.

PubMed

Kurpiers, P; Magnard, P; Walter, T; Royer, B; Pechal, M; Heinsoo, J; Salathé, Y; Akin, A; Storz, S; Besse, J-C; Gasparinetti, S; Blais, A; Wallraff, A

2018-06-01

Sharing information coherently between nodes of a quantum network is fundamental to distributed quantum information processing. In this scheme, the computation is divided into subroutines and performed on several smaller quantum registers that are connected by classical and quantum channels 1 . A direct quantum channel, which connects nodes deterministically rather than probabilistically, achieves larger entanglement rates between nodes and is advantageous for distributed fault-tolerant quantum computation 2 . Here we implement deterministic state-transfer and entanglement protocols between two superconducting qubits fabricated on separate chips. Superconducting circuits 3 constitute a universal quantum node 4 that is capable of sending, receiving, storing and processing quantum information 5-8 . Our implementation is based on an all-microwave cavity-assisted Raman process 9 , which entangles or transfers the qubit state of a transmon-type artificial atom 10 with a time-symmetric itinerant single photon. We transfer qubit states by absorbing these itinerant photons at the receiving node, with a probability of 98.1 ± 0.1 per cent, achieving a transfer-process fidelity of 80.02 ± 0.07 per cent for a protocol duration of only 180 nanoseconds. We also prepare remote entanglement on demand with a fidelity as high as 78.9 ± 0.1 per cent at a rate of 50 kilohertz. Our results are in excellent agreement with numerical simulations based on a master-equation description of the system. This deterministic protocol has the potential to be used for quantum computing distributed across different nodes of a cryogenic network.

Genetic transformation of carnation (Dianthus caryophylus L.).

PubMed

Nontaswatsri, Chalermsri; Fukai, Seiichi

2010-01-01

This chapter describes a rapid and efficient protocol for explant preparation and genetic transformation of carnation. Node explants from greenhouse-grown plants and leaf explants from in vitro plants are infected with Agrobacterium tumefaciens AGL0 harboring pKT3 plasmid, consisting of GUS and NPTII genes. Explant preparation is an important factor to obtain the transformed plants. The GUS-staining area was located only on the cut end of explants and only explants with a cut end close to the connecting area between node and leaf, produced transformed shoots. The cocultivation medium is also an important factor for the successful genetic transformation of carnation node and leaf explants. High genetic transformation efficiency of node and leaf explants cocultured with Agrobacterium tumefaciens was achieved when the explants were cocultivated on a filter paper soaked with water or water and acetosyringone mixture (AS).

Characterization of topological structure on complex networks.

PubMed

Nakamura, Ikuo

2003-10-01

Characterizing the topological structure of complex networks is a significant problem especially from the viewpoint of data mining on the World Wide Web. "Page rank" used in the commercial search engine Google is such a measure of authority to rank all the nodes matching a given query. We have investigated the page-rank distribution of the real Web and a growing network model, both of which have directed links and exhibit a power law distributions of in-degree (the number of incoming links to the node) and out-degree (the number of outgoing links from the node), respectively. We find a concentration of page rank on a small number of nodes and low page rank on high degree regimes in the real Web, which can be explained by topological properties of the network, e.g., network motifs, and connectivities of nearest neighbors.

Core-periphery structure requires something else in the network

NASA Astrophysics Data System (ADS)

Kojaku, Sadamori; Masuda, Naoki

2018-04-01

A network with core-periphery structure consists of core nodes that are densely interconnected. In contrast to a community structure, which is a different meso-scale structure of networks, core nodes can be connected to peripheral nodes and peripheral nodes are not densely interconnected. Although core-periphery structure sounds reasonable, we argue that it is merely accounted for by heterogeneous degree distributions, if one partitions a network into a single core block and a single periphery block, which the famous Borgatti–Everett algorithm and many succeeding algorithms assume. In other words, there is a strong tendency that high-degree and low-degree nodes are judged to be core and peripheral nodes, respectively. To discuss core-periphery structure beyond the expectation of the node’s degree (as described by the configuration model), we propose that one needs to assume at least one block of nodes apart from the focal core-periphery structure, such as a different core-periphery pair, community or nodes not belonging to any meso-scale structure. We propose a scalable algorithm to detect pairs of core and periphery in networks, controlling for the effect of the node’s degree. We illustrate our algorithm using various empirical networks.

Method and apparatus for connecting finite element meshes and performing simulations therewith

DOEpatents

Dohrmann, Clark R.; Key, Samuel W.; Heinstein, Martin W.

2003-05-06

The present invention provides a method of connecting dissimilar finite element meshes. A first mesh, designated the master mesh, and a second mesh, designated the slave mesh, each have interface surfaces proximal the other. Each interface surface has a corresponding interface mesh comprising a plurality of interface nodes. Each slave interface node is assigned new coordinates locating the interface node on the interface surface of the master mesh. The slave interface surface is further redefined to be the projection of the slave interface mesh onto the master interface surface.

A new measure based on degree distribution that links information theory and network graph analysis

PubMed Central

2012-01-01

Background Detailed connection maps of human and nonhuman brains are being generated with new technologies, and graph metrics have been instrumental in understanding the general organizational features of these structures. Neural networks appear to have small world properties: they have clustered regions, while maintaining integrative features such as short average pathlengths. Results We captured the structural characteristics of clustered networks with short average pathlengths through our own variable, System Difference (SD), which is computationally simple and calculable for larger graph systems. SD is a Jaccardian measure generated by averaging all of the differences in the connection patterns between any two nodes of a system. We calculated SD over large random samples of matrices and found that high SD matrices have a low average pathlength and a larger number of clustered structures. SD is a measure of degree distribution with high SD matrices maximizing entropic properties. Phi (Φ), an information theory metric that assesses a system’s capacity to integrate information, correlated well with SD - with SD explaining over 90% of the variance in systems above 11 nodes (tested for 4 to 13 nodes). However, newer versions of Φ do not correlate well with the SD metric. Conclusions The new network measure, SD, provides a link between high entropic structures and degree distributions as related to small world properties. PMID:22726594

Immunization of complex networks

NASA Astrophysics Data System (ADS)

Pastor-Satorras, Romualdo; Vespignani, Alessandro

2002-03-01

Complex networks such as the sexual partnership web or the Internet often show a high degree of redundancy and heterogeneity in their connectivity properties. This peculiar connectivity provides an ideal environment for the spreading of infective agents. Here we show that the random uniform immunization of individuals does not lead to the eradication of infections in all complex networks. Namely, networks with scale-free properties do not acquire global immunity from major epidemic outbreaks even in the presence of unrealistically high densities of randomly immunized individuals. The absence of any critical immunization threshold is due to the unbounded connectivity fluctuations of scale-free networks. Successful immunization strategies can be developed only by taking into account the inhomogeneous connectivity properties of scale-free networks. In particular, targeted immunization schemes, based on the nodes' connectivity hierarchy, sharply lower the network's vulnerability to epidemic attacks.

Aging and response conflict solution: Behavioural and functional connectivity changes

PubMed Central

Cieslik, Edna C.; Behrwind, Simone D.; Roski, Christian; Caspers, Svenja; Amunts, Katrin; Eickhoff, Simon B.

2014-01-01

Healthy aging has been found associated with less efficient response conflict solution, but the cognitive and neural mechanisms remain elusive. In a two-experiment study, we first examined the behavioural consequences of this putative age-related decline for conflicts induced by spatial stimulus–response incompatibility. We then used resting-state functional magnetic resonance imaging data from a large, independent sample of adults (n = 399; 18–85 years) to investigate age differences in functional connectivity between the nodes of a network previously found associated with incompatibility-induced response conflicts in the very same paradigm. As expected, overcoming interference from conflicting response tendencies took longer in older adults, even after accounting for potential mediator variables (general response speed and accuracy, motor speed, visuomotor coordination ability, and cognitive flexibility). Experiment 2 revealed selective age-related decreases in functional connectivity between bilateral anterior insula, pre-supplementary motor area, and right dorsolateral prefrontal cortex. Importantly, these age effects persisted after controlling for regional gray-matter atrophy assessed by voxel-based morphometry. Meta-analytic functional profiling using the BrainMap database showed these age-sensitive nodes to be more strongly linked to highly abstract cognition, as compared with the remaining network nodes, which in turn were more strongly linked to action-related processing. These findings indicate changes in interregional coupling with age among task-relevant network nodes that are not specifically associated with conflict resolution per se. Rather, our behavioural and neural data jointly suggest that healthy aging is associated with difficulties in properly activating non-dominant but relevant task schemata necessary to exert efficient cognitive control over action. PMID:24718622

Aging and response conflict solution: behavioural and functional connectivity changes.

PubMed

Langner, Robert; Cieslik, Edna C; Behrwind, Simone D; Roski, Christian; Caspers, Svenja; Amunts, Katrin; Eickhoff, Simon B

2015-01-01

Healthy aging has been found associated with less efficient response conflict solution, but the cognitive and neural mechanisms have remained elusive. In a two-experiment study, we first examined the behavioural consequences of this putative age-related decline for conflicts induced by spatial stimulus-response incompatibility. We then used resting-state functional magnetic resonance imaging data from a large, independent sample of adults (n = 399; 18-85 years) to investigate age differences in functional connectivity between the nodes of a network previously found associated with incompatibility-induced response conflicts in the very same paradigm. As expected, overcoming interference from conflicting response tendencies took longer in older adults, even after accounting for potential mediator variables (general response speed and accuracy, motor speed, visuomotor coordination ability, and cognitive flexibility). Experiment 2 revealed selective age-related decreases in functional connectivity between bilateral anterior insula, pre-supplementary motor area, and right dorsolateral prefrontal cortex. Importantly, these age effects persisted after controlling for regional grey-matter atrophy assessed by voxel-based morphometry. Meta-analytic functional profiling using the BrainMap database showed these age-sensitive nodes to be more strongly linked to highly abstract cognition, as compared with the remaining network nodes, which were more strongly linked to action-related processing. These findings indicate changes in interregional coupling with age among task-relevant network nodes that are not specifically associated with conflict resolution per se. Rather, our behavioural and neural data jointly suggest that healthy aging is associated with difficulties in properly activating non-dominant but relevant task schemata necessary to exert efficient cognitive control over action.

Fast computation of voxel-level brain connectivity maps from resting-state functional MRI using l₁-norm as approximation of Pearson's temporal correlation: proof-of-concept and example vector hardware implementation.

PubMed

Minati, Ludovico; Zacà, Domenico; D'Incerti, Ludovico; Jovicich, Jorge

2014-09-01

An outstanding issue in graph-based analysis of resting-state functional MRI is choice of network nodes. Individual consideration of entire brain voxels may represent a less biased approach than parcellating the cortex according to pre-determined atlases, but entails establishing connectedness for 1(9)-1(11) links, with often prohibitive computational cost. Using a representative Human Connectome Project dataset, we show that, following appropriate time-series normalization, it may be possible to accelerate connectivity determination replacing Pearson correlation with l1-norm. Even though the adjacency matrices derived from correlation coefficients and l1-norms are not identical, their similarity is high. Further, we describe and provide in full an example vector hardware implementation of l1-norm on an array of 4096 zero instruction-set processors. Calculation times <1000 s are attainable, removing the major deterrent to voxel-based resting-sate network mapping and revealing fine-grained node degree heterogeneity. L1-norm should be given consideration as a substitute for correlation in very high-density resting-state functional connectivity analyses. Copyright © 2014 IPEM. Published by Elsevier Ltd. All rights reserved.

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.

On the Simulation-Based Reliability of Complex Emergency Logistics Networks in Post-Accident Rescues.

PubMed

Wang, Wei; Huang, Li; Liang, Xuedong

2018-01-06

This paper investigates the reliability of complex emergency logistics networks, as reliability is crucial to reducing environmental and public health losses in post-accident emergency rescues. Such networks' statistical characteristics are analyzed first. After the connected reliability and evaluation indices for complex emergency logistics networks are effectively defined, simulation analyses of network reliability are conducted under two different attack modes using a particular emergency logistics network as an example. The simulation analyses obtain the varying trends in emergency supply times and the ratio of effective nodes and validates the effects of network characteristics and different types of attacks on network reliability. The results demonstrate that this emergency logistics network is both a small-world and a scale-free network. When facing random attacks, the emergency logistics network steadily changes, whereas it is very fragile when facing selective attacks. Therefore, special attention should be paid to the protection of supply nodes and nodes with high connectivity. The simulation method provides a new tool for studying emergency logistics networks and a reference for similar studies.

On the Simulation-Based Reliability of Complex Emergency Logistics Networks in Post-Accident Rescues

PubMed Central

Wang, Wei; Huang, Li; Liang, Xuedong

2018-01-01

This paper investigates the reliability of complex emergency logistics networks, as reliability is crucial to reducing environmental and public health losses in post-accident emergency rescues. Such networks’ statistical characteristics are analyzed first. After the connected reliability and evaluation indices for complex emergency logistics networks are effectively defined, simulation analyses of network reliability are conducted under two different attack modes using a particular emergency logistics network as an example. The simulation analyses obtain the varying trends in emergency supply times and the ratio of effective nodes and validates the effects of network characteristics and different types of attacks on network reliability. The results demonstrate that this emergency logistics network is both a small-world and a scale-free network. When facing random attacks, the emergency logistics network steadily changes, whereas it is very fragile when facing selective attacks. Therefore, special attention should be paid to the protection of supply nodes and nodes with high connectivity. The simulation method provides a new tool for studying emergency logistics networks and a reference for similar studies. PMID:29316614

Frequency of an accessory popliteal efferent lymphatic pathway in dogs.

PubMed

Mayer, Monique N; Sweet, Katherine A; Patsikas, Michael N; Sukut, Sally L; Waldner, Cheryl L

2018-05-01

Staging and therapeutic planning for dogs with malignant disease in the popliteal lymph node are based on the expected patterns of lymphatic drainage from the lymph node. The medial iliac lymph nodes are known to receive efferent lymph from the popliteal lymph node; however, an accessory popliteal efferent pathway with direct connection to the sacral lymph nodes has also been less frequently reported. The primary objective of this prospective, anatomic study was to describe the frequency of various patterns of lymphatic drainage of the popliteal lymph node. With informed client consent, 50 adult dogs with no known disease of the lymphatic system underwent computed tomographic lymphography after ultrasound-guided, percutaneous injection of 350 mg/ml iohexol into a popliteal lymph node. In all 50 dogs, the popliteal lymph node drained directly to the ipsilateral medial iliac lymph node through multiple lymphatic vessels that coursed along the medial thigh. In 26% (13/50) of dogs, efferent vessels also drained from the popliteal lymph node directly to the internal iliac and/or sacral lymph nodes, coursing laterally through the gluteal region and passing over the dorsal aspect of the pelvis. Lymphatic connections between the right and left medial iliac and right and left internal iliac lymph nodes were found. Based on our findings, the internal iliac and sacral lymph nodes should be considered when staging or planning therapy for dogs with malignant disease in the popliteal lymph node. © 2018 American College of Veterinary Radiology.

Design of Low-Noise Output Amplifiers for P-channel Charge-Coupled Devices Fabricated on High-Resistivity Silicon

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

Haque, S; Frost, F Dion R.; Groulx, R

2011-12-22

We describe the design and optimization of low-noise, single-stage output amplifiers for p-channel charge-coupled devices (CCDs) used for scientific applications in astronomy and other fields. The CCDs are fabricated on high-resistivity, 4000–5000 -cm, n-type silicon substrates. Single-stage amplifiers with different output structure designs and technologies have been characterized. The standard output amplifier is designed with an n{sup +} polysilicon gate that has a metal connection to the sense node. In an effort to lower the output amplifier readout noise by minimizing the capacitance seen at the sense node, buried-contact technology has been investigated. In this case, the output transistor hasmore » a p{sup +} polysilicon gate that connects directly to the p{sup +} sense node. Output structures with buried-contact areas as small as 2 μm × 2 μm are characterized. In addition, the geometry of the source-follower transistor was varied, and we report test results on the conversion gain and noise of the various amplifier structures. By use of buried-contact technology, better amplifier geometry, optimization of the amplifier biases and improvements in the test electronics design, we obtain a 45% reduction in noise, corresponding to 1.7 e{sup -} rms at 70 kpixels/sec.« less

Spatio-Temporal Patterns of the International Merger and Acquisition Network.

PubMed

Dueñas, Marco; Mastrandrea, Rossana; Barigozzi, Matteo; Fagiolo, Giorgio

2017-09-07

This paper analyses the world web of mergers and acquisitions (M&As) using a complex network approach. We use data of M&As to build a temporal sequence of binary and weighted-directed networks for the period 1995-2010 and 224 countries (nodes) connected according to their M&As flows (links). We study different geographical and temporal aspects of the international M&A network (IMAN), building sequences of filtered sub-networks whose links belong to specific intervals of distance or time. Given that M&As and trade are complementary ways of reaching foreign markets, we perform our analysis using statistics employed for the study of the international trade network (ITN), highlighting the similarities and differences between the ITN and the IMAN. In contrast to the ITN, the IMAN is a low density network characterized by a persistent giant component with many external nodes and low reciprocity. Clustering patterns are very heterogeneous and dynamic. High-income economies are the main acquirers and are characterized by high connectivity, implying that most countries are targets of a few acquirers. Like in the ITN, geographical distance strongly impacts the structure of the IMAN: link-weights and node degrees have a non-linear relation with distance, and an assortative pattern is present at short distances.

Sediment pathways in a tropical forest: effects of logging roads and skid trails

NASA Astrophysics Data System (ADS)

Sidle, Roy C.; Sasaki, Shozo; Otsuki, Mieko; Noguchi, Shoji; Rahim Nik, Abdul

2004-03-01

Significant erosion occurred from recently constructed forest logging roads and skid trails in a small headwater catchment in Peninsular Malaysia. Soil loss was estimated by measuring dimensions of all significant rills and gullies along the road, as well as by measuring height of preserved soil pedestals in sidecast and fill material and on skid trails. Estimates of surface erosion from logging roads and skid trails were 272 +/- 20 t ha-1 year-1 and 275 +/- 20 t ha-1 year-1 respectively. However, owing to lack of connectivity of skid trails to the stream, much of the sediment mobilized on skid trails was stored either on adjacent hillslopes or the trails themselves, rather than being transported to the stream system, as was the case for the road. Steeper skid trails (>20% gradient) had slightly higher erosion rates (320 +/- 24 t ha-1 year-1) than trails with gentler gradients (245-264 t ha-1 year-1). Some 60% of the soil loss on logging roads comes from erosion of the running surface. Disturbed cut and fill material along the road supplied the remaining 40% of the soil loss from roads. Roads and skid trails had no designed drainage systems; runoff discharged onto the hillslope at 25 major discharge nodes from the logging road (690 m total length) and at 34 nodes from skid trails (2300 m). Sediment pathways were either fully or moderately connected to headwater channels at 64% of the logging road nodes, but at only 26% of the nodes emanating from skid trails. A detailed sediment budget revealed that 78% of the soil loss from the road system (including log landings) was delivered to the stream in the first 16 months after logging began. Most (90%) of the deposition from skid trails occurred below just three discharge nodes. Runoff from and onto skid trails often exacerbated the sediment connectivity to channels. Clearly, sediment discharge from logging roads was more highly connected to the stream than discharge from skid trails. Once in the channel, much of this sediment was temporarily stored in the floodplain and behind woody debris.

Certification of Completion of Level-2 Milestone 464: Complete Phase 1 Integration of Site-Wide Global Parallel File System (SWGPFS)

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

Heidelberg, S T; Fitzgerald, K J; Richmond, G H

2006-01-24

There has been substantial development of the Lustre parallel filesystem prior to the configuration described below for this milestone. The initial Lustre filesystems that were deployed were directly connected to the cluster interconnect, i.e. Quadrics Elan3. That is, the clients (OSSes) and Meta-data Servers (MDS) were all directly connected to the cluster's internal high speed interconnect. This configuration serves a single cluster very well, but does not provide sharing of the filesystem among clusters. LLNL funded the development of high-efficiency ''portals router'' code by CFS (the company that develops Lustre) to enable us to move the Lustre servers to amore » GigE-connected network configuration, thus making it possible to connect to the servers from several clusters. With portals routing available, here is what changes: (1) another storage-only cluster is deployed to front the Lustre storage devices (these become the Lustre OSSes and MDS), (2) this ''Lustre cluster'' is attached via GigE connections to a large GigE switch/router cloud, (3) a small number of compute-cluster nodes are designated as ''gateway'' or ''portal router'' nodes, and (4) the portals router nodes are GigE-connected to the switch/router cloud. The Lustre configuration is then changed to reflect the new network paths. A typical example of this is a compute cluster and a related visualization cluster: the compute cluster produces the data (writes it to the Lustre filesystem), and the visualization cluster consumes some of the data (reads it from the Lustre filesystem). This process can be expanded by aggregating several collections of Lustre backend storage resources into one or more ''centralized'' Lustre filesystems, and then arranging to have several ''client'' clusters mount these centralized filesystems. The ''client clusters'' can be any combination of compute, visualization, archiving, or other types of cluster. This milestone demonstrates the operation and performance of a scaled-down version of such a large, centralized, shared Lustre filesystem concept.« less

Resting connectivity between salience nodes predicts recognition memory.

PubMed

Andreano, Joseph M; Touroutoglou, Alexandra; Dickerson, Bradford C; Barrett, Lisa F

2017-06-01

The resting connectivity of the brain's salience network, particularly the ventral subsystem of the salience network, has been previously associated with various measures of affective reactivity. Numerous studies have demonstrated that increased affective arousal leads to enhanced consolidation of memory. This suggests that individuals with greater ventral salience network connectivity will exhibit greater responses to affective experience, leading to a greater enhancement of memory by affect. To test this hypothesis, resting ventral salience connectivity was measured in 41 young adults, who were then exposed to neutral and negative affect inductions during a paired associate memory test. Memory performance for material learned under both negative and neutral induction was tested for correlation with resting connectivity between major ventral salience nodes. The results showed a significant interaction between mood induction (negative vs neutral) and connectivity between ventral anterior insula and pregenual anterior cingulate cortex, indicating that salience node connectivity predicted memory for material encoded under negative, but not neutral induction. These findings suggest that the network state of the perceiver, measured prior to affective experience, meaningfully influences the extent to which affect modulates memory. Implications of these findings for individuals with affective disorder, who show alterations in both connectivity and memory, are considered. © The Author (2017). Published by Oxford University Press.

Earthquake Complex Network Analysis Before and After the Mw 8.2 Earthquake in Iquique, Chile

NASA Astrophysics Data System (ADS)

Pasten, D.

2017-12-01

The earthquake complex networks have shown that they are abble to find specific features in seismic data set. In space, this networkshave shown a scale-free behavior for the probability distribution of connectivity, in directed networks and theyhave shown a small-world behavior, for the undirected networks.In this work, we present an earthquake complex network analysis for the large earthquake Mw 8.2 in the north ofChile (near to Iquique) in April, 2014. An earthquake complex network is made dividing the three dimensional space intocubic cells, if one of this cells contain an hypocenter, we name this cell like a node. The connections between nodes aregenerated in time. We follow the time sequence of seismic events and we are making the connections betweennodes. Now, we have two different networks: a directed and an undirected network. Thedirected network takes in consideration the time-direction of the connections, that is very important for the connectivityof the network: we are considering the connectivity, ki of the i-th node, like the number of connections going out ofthe node i plus the self-connections (if two seismic events occurred successive in time in the same cubic cell, we havea self-connection). The undirected network is made removing the direction of the connections and the self-connectionsfrom the directed network. For undirected networks, we are considering only if two nodes are or not connected.We have built a directed complex network and an undirected complex network, before and after the large earthquake in Iquique. We have used magnitudes greater than Mw = 1.0 and Mw = 3.0. We found that this method can recognize the influence of thissmall seismic events in the behavior of the network and we found that the size of the cell used to build the network isanother important factor to recognize the influence of the large earthquake in this complex system. This method alsoshows a difference in the values of the critical exponent γ (for the probability distribution of connectivity in the directednetwork) before and after the large earthquake, but this method does not show a change in the clustering behavior ofthe undirected network, before and after the large earthquake, showing a small-world behavior for the network beforeand after of this large seismic event.

Social network analysis for assessment of avian influenza spread and trading patterns of backyard chickens in Nakhon Pathom, Suphan Buri and Ratchaburi, Thailand.

PubMed

Poolkhet, C; Chairatanayuth, P; Thongratsakul, S; Yatbantoong, N; Kasemsuwan, S; Damchoey, D; Rukkwamsuk, T

2013-09-01

The aim of this study is to explain the social networks of the backyard chicken in Ratchaburi, Suphan Buri and Nakhon Pathom Provinces. In this study, we designed the nodes as groups of persons or places involved in activities relating to backyard chickens. The ties are all activities related to the nodes. The study applied a partial network approach to assess the spreading pattern of avian influenza. From 557 questionnaires collected from the nodes, the researchers found that the degree (the numbers of ties that a node has) and closeness (the distance from one node to the others) centralities of Nakhon Pathom were significantly higher than those of the others (P<0.001). The results show that compared with the remaining areas, this area is more quickly connected to many links. If the avian influenza virus subtype H5N1 was released into the network, the disease would spread throughout this province more rapidly than in Ratchaburi and Suphan Buri. The betweenness centrality in each of these provinces showed no differences (P>0.05). In this study, the nodes that play an important role in all networks are farmers who raise consumable chicken, farmers who raise both consumable chicken and fighting cocks, farmers' households that connect with dominant nodes, and the owners and observers of fighting cocks at arenas and training fields. In this study, we did not find cut points or blocks in the network. Moreover, we detected a random network in all provinces. Thus, connectivity between the nodes covers long or short distances, with less predictable behaviour. Finally, this study suggests that activities between the important nodes must receive special attention for disease control during future disease outbreaks. © 2012 Blackwell Verlag GmbH.

Using VirtualGL/TurboVNC Software on the Peregrine System |

Science.gov Websites

High-Performance Computing | NREL VirtualGL/TurboVNC Software on the Peregrine System Using , allowing users to access and share large-memory visualization nodes with high-end graphics processing units may be better than just using X11 forwarding when connecting from a remote site with low bandwidth and

On the connectivity of the cosmic web: theory and implications for cosmology and galaxy formation

NASA Astrophysics Data System (ADS)

Codis, Sandrine; Pogosyan, Dmitri; Pichon, Christophe

2018-06-01

Cosmic connectivity and multiplicity, i.e. the number of filaments globally or locally connected to a given cluster is a natural probe of the growth of structure and in particular of the nature of dark energy. It is also a critical ingredient driving the assembly history of galaxies as it controls mass and angular momentum accretion. The connectivity of the cosmic web is investigated here via the persistent skeleton. This tool identifies topologically the ridges of the cosmic landscape which allows us to investigate how the nodes of the cosmic web are connected together. When applied to Gaussian random fields corresponding to the high redshift universe, it is found that on average the nodes are connected to exactly κ = 4 neighbours in two dimensions and ˜6.1 in three dimensions. Investigating spatial dimensions up to d = 6, typical departures from a cubic lattice κ = 2d are shown to scale like the power 7/4 of the dimension. These numbers strongly depend on the height of the peaks: the higher the peak the larger the connectivity. Predictions from first principles based on peak theory are shown to reproduce well the connectivity and multiplicity of Gaussian random fields and cosmological simulations. As an illustration, connectivity is quantified in galaxy lensing convergence maps and large dark haloes catalogues. As a function of redshift and scale the mean connectivity decreases in a cosmology-dependent way. As a function of halo mass it scales like 10/3 times the log of the mass. Implications on galactic scales are discussed.

Enhancement of large fluctuations to extinction in adaptive networks

NASA Astrophysics Data System (ADS)

Hindes, Jason; Schwartz, Ira B.; Shaw, Leah B.

2018-01-01

During an epidemic, individual nodes in a network may adapt their connections to reduce the chance of infection. A common form of adaption is avoidance rewiring, where a noninfected node breaks a connection to an infected neighbor and forms a new connection to another noninfected node. Here we explore the effects of such adaptivity on stochastic fluctuations in the susceptible-infected-susceptible model, focusing on the largest fluctuations that result in extinction of infection. Using techniques from large-deviation theory, combined with a measurement of heterogeneity in the susceptible degree distribution at the endemic state, we are able to predict and analyze large fluctuations and extinction in adaptive networks. We find that in the limit of small rewiring there is a sharp exponential reduction in mean extinction times compared to the case of zero adaption. Furthermore, we find an exponential enhancement in the probability of large fluctuations with increased rewiring rate, even when holding the average number of infected nodes constant.

Entropy of spatial network ensembles

NASA Astrophysics Data System (ADS)

Coon, Justin P.; Dettmann, Carl P.; Georgiou, Orestis

2018-04-01

We analyze complexity in spatial network ensembles through the lens of graph entropy. Mathematically, we model a spatial network as a soft random geometric graph, i.e., a graph with two sources of randomness, namely nodes located randomly in space and links formed independently between pairs of nodes with probability given by a specified function (the "pair connection function") of their mutual distance. We consider the general case where randomness arises in node positions as well as pairwise connections (i.e., for a given pair distance, the corresponding edge state is a random variable). Classical random geometric graph and exponential graph models can be recovered in certain limits. We derive a simple bound for the entropy of a spatial network ensemble and calculate the conditional entropy of an ensemble given the node location distribution for hard and soft (probabilistic) pair connection functions. Under this formalism, we derive the connection function that yields maximum entropy under general constraints. Finally, we apply our analytical framework to study two practical examples: ad hoc wireless networks and the US flight network. Through the study of these examples, we illustrate that both exhibit properties that are indicative of nearly maximally entropic ensembles.

A Markovian model of evolving world input-output network

PubMed Central

Isacchini, Giulio

2017-01-01

The initial theoretical connections between Leontief input-output models and Markov chains were established back in 1950s. However, considering the wide variety of mathematical properties of Markov chains, so far there has not been a full investigation of evolving world economic networks with Markov chain formalism. In this work, using the recently available world input-output database, we investigated the evolution of the world economic network from 1995 to 2011 through analysis of a time series of finite Markov chains. We assessed different aspects of this evolving system via different known properties of the Markov chains such as mixing time, Kemeny constant, steady state probabilities and perturbation analysis of the transition matrices. First, we showed how the time series of mixing times and Kemeny constants could be used as an aggregate index of globalization. Next, we focused on the steady state probabilities as a measure of structural power of the economies that are comparable to GDP shares of economies as the traditional index of economies welfare. Further, we introduced two measures of systemic risk, called systemic influence and systemic fragility, where the former is the ratio of number of influenced nodes to the total number of nodes, caused by a shock in the activity of a node, and the latter is based on the number of times a specific economic node is affected by a shock in the activity of any of the other nodes. Finally, focusing on Kemeny constant as a global indicator of monetary flow across the network, we showed that there is a paradoxical effect of a change in activity levels of economic nodes on the overall flow of the world economic network. While the economic slowdown of the majority of nodes with high structural power results to a slower average monetary flow over the network, there are some nodes, where their slowdowns improve the overall quality of the network in terms of connectivity and the average flow of the money. PMID:29065145

Opinion formation on adaptive networks with intensive average degree

NASA Astrophysics Data System (ADS)

Schmittmann, B.; Mukhopadhyay, Abhishek

2010-12-01

We study the evolution of binary opinions on a simple adaptive network of N nodes. At each time step, a randomly selected node updates its state (“opinion”) according to the majority opinion of the nodes that it is linked to; subsequently, all links are reassigned with probability p˜ (q˜) if they connect nodes with equal (opposite) opinions. In contrast to earlier work, we ensure that the average connectivity (“degree”) of each node is independent of the system size (“intensive”), by choosing p˜ and q˜ to be of O(1/N) . Using simulations and analytic arguments, we determine the final steady states and the relaxation into these states for different system sizes. We find two absorbing states, characterized by perfect consensus, and one metastable state, characterized by a population split evenly between the two opinions. The relaxation time of this state grows exponentially with the number of nodes, N . A second metastable state, found in the earlier studies, is no longer observed.

Design and Implementation of Secure Area Expansion Scheme for Public Wireless LAN Services

NASA Astrophysics Data System (ADS)

Watanabe, Ryu; Tanaka, Toshiaki

Recently, wireless LAN (WLAN) technology has become a major wireless communication method. The communication bandwidth is increasing and speeds have attained rates exceeding 100 Mbps. Therefore, WLAN technology is regarded as one of the promising communication methods for future networks. In addition, public WLAN connection services can be used in many locations. However, the number of the access points (AP) is insufficient for seamless communication and it cannot be said that users can use the service ubiquitously. An ad-hoc network style connection can be used to expand the coverage area of a public WLAN service. By relaying the user messages among the user nodes, a node can obtain an Internet connection via an AP, even though the node is located outside the AP's direct wireless connection area. Such a coverage area extending technology has many advantages thanks to the feature that no additional infrastructure is required. Therefore, there is a strong demand for this technology as it allows the cost-effective construction of future networks. When a secure ad-hoc routing protocol is used for message exchange in the WLAN service, the message routes are protected from malicious behavior such as route forging and can be maintained appropriately. To do this, however, a new node that wants to join the WLAN service has to obtain information such as the public key certificate and IP address in order to start secure ad-hoc routing. In other words, an initial setup is required for every network node to join the WLAN service properly. Ordinarily, such information should be assigned from the AP. However, new nodes cannot always contact an AP directly. Therefore, there are problems about information delivery in the initial setup of a network node. These problems originate in the multi hop connection based on the ad-hoc routing protocols. In order to realize an expanded area WLAN service, in this paper, the authors propose a secure public key certificate and address provision scheme during the initial setup phase on mobile nodes for the service. The proposed scheme also considers the protection of user privacy. Accordingly, none of the user nodes has to reveal their unique and persistent information to other nodes. Instead of using such information, temporary values are sent by an AP to mobile nodes and used for secure ad-hoc routing operations. Therefore, our proposed scheme prevents tracking by malicious parties by avoiding the use of unique information. Moreover, a test bed was also implemented based on the proposal and an evaluation was carried out in order to confirm performance. In addition, the authors describe a countermeasure against denial of service (DoS) attacks based on the approach to privacy protection described in our proposal.

Functional Brain Networks: Does the Choice of Dependency Estimator and Binarization Method Matter?

NASA Astrophysics Data System (ADS)

Jalili, Mahdi

2016-07-01

The human brain can be modelled as a complex networked structure with brain regions as individual nodes and their anatomical/functional links as edges. Functional brain networks are constructed by first extracting weighted connectivity matrices, and then binarizing them to minimize the noise level. Different methods have been used to estimate the dependency values between the nodes and to obtain a binary network from a weighted connectivity matrix. In this work we study topological properties of EEG-based functional networks in Alzheimer’s Disease (AD). To estimate the connectivity strength between two time series, we use Pearson correlation, coherence, phase order parameter and synchronization likelihood. In order to binarize the weighted connectivity matrices, we use Minimum Spanning Tree (MST), Minimum Connected Component (MCC), uniform threshold and density-preserving methods. We find that the detected AD-related abnormalities highly depend on the methods used for dependency estimation and binarization. Topological properties of networks constructed using coherence method and MCC binarization show more significant differences between AD and healthy subjects than the other methods. These results might explain contradictory results reported in the literature for network properties specific to AD symptoms. The analysis method should be seriously taken into account in the interpretation of network-based analysis of brain signals.

Information transmission on hybrid networks

NASA Astrophysics Data System (ADS)

Chen, Rongbin; Cui, Wei; Pu, Cunlai; Li, Jie; Ji, Bo; Gakis, Konstantinos; Pardalos, Panos M.

2018-01-01

Many real-world communication networks often have hybrid nature with both fixed nodes and moving modes, such as the mobile phone networks mainly composed of fixed base stations and mobile phones. In this paper, we discuss the information transmission process on the hybrid networks with both fixed and mobile nodes. The fixed nodes (base stations) are connected as a spatial lattice on the plane forming the information-carrying backbone, while the mobile nodes (users), which are the sources and destinations of information packets, connect to their current nearest fixed nodes respectively to deliver and receive information packets. We observe the phase transition of traffic load in the hybrid network when the packet generation rate goes from below and then above a critical value, which measures the network capacity of packets delivery. We obtain the optimal speed of moving nodes leading to the maximum network capacity. We further improve the network capacity by rewiring the fixed nodes and by considering the current load of fixed nodes during packets transmission. Our purpose is to optimize the network capacity of hybrid networks from the perspective of network science, and provide some insights for the construction of future communication infrastructures.

Connected component analysis of review-SEM images for sub-10nm node process verification

NASA Astrophysics Data System (ADS)

Halder, Sandip; Leray, Philippe; Sah, Kaushik; Cross, Andrew; Parisi, Paolo

2017-03-01

Analysis of hotspots is becoming more and more critical as we scale from node to node. To define true process windows at sub-14 nm technology nodes, often defect inspections are being included to weed out design weak spots (often referred to as hotspots). Defect inspection sub 28 nm nodes is a two pass process. Defect locations identified by optical inspection tools need to be reviewed by review-SEM's to understand exactly which feature is failing in the region flagged by the optical tool. The images grabbed by the review-SEM tool are used for classification but rarely for quantification. The goal of this paper is to see if the thousands of review-SEM images which are existing can be used for quantification and further analysis. More specifically we address the SEM quantification problem with connected component analysis.

Correctness Proof of a Self-Stabilizing Distributed Clock Synchronization Protocol for Arbitrary Digraphs

NASA Technical Reports Server (NTRS)

Malekpour, Mahyar R.

2011-01-01

This report presents a deductive proof of a self-stabilizing distributed clock synchronization protocol. It is focused on the distributed clock synchronization of an arbitrary, non-partitioned digraph ranging from fully connected to 1-connected networks of nodes while allowing for differences in the network elements. This protocol does not rely on assumptions about the initial state of the system, and no central clock or a centrally generated signal, pulse, or message is used. Nodes are anonymous, i.e., they do not have unique identities. There is no theoretical limit on the maximum number of participating nodes. The only constraint on the behavior of the node is that the interactions with other nodes are restricted to defined links and interfaces. We present a deductive proof of the correctness of the protocol as it applies to the networks with unidirectional and bidirectional links. We also confirm the claims of determinism and linear convergence.

EClerize: A customized force-directed graph drawing algorithm for biological graphs with EC attributes.

PubMed

Danaci, Hasan Fehmi; Cetin-Atalay, Rengul; Atalay, Volkan

2018-03-26

Visualizing large-scale data produced by the high throughput experiments as a biological graph leads to better understanding and analysis. This study describes a customized force-directed layout algorithm, EClerize, for biological graphs that represent pathways in which the nodes are associated with Enzyme Commission (EC) attributes. The nodes with the same EC class numbers are treated as members of the same cluster. Positions of nodes are then determined based on both the biological similarity and the connection structure. EClerize minimizes the intra-cluster distance, that is the distance between the nodes of the same EC cluster and maximizes the inter-cluster distance, that is the distance between two distinct EC clusters. EClerize is tested on a number of biological pathways and the improvement brought in is presented with respect to the original algorithm. EClerize is available as a plug-in to cytoscape ( http://apps.cytoscape.org/apps/eclerize ).

Rutgers University Subcontract B611610 Final Report

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

Soundarajan, Sucheta; Eliassi-Rad, Tina; Gallagher, Brian

Given an incomplete (i.e., partially-observed) network, which nodes should we actively probe in order to achieve the highest accuracy for a given network feature? For example, consider a cyber-network administrator who observes only a portion of the network at time t and wants to accurately identify the most important (e.g., highest PageRank) nodes in the complete network. She has a limited budget for probing the network. Of all the nodes she has observed, which should she probe in order to most accurately identify the important nodes? We propose a novel and scalable algorithm, MaxOutProbe, and evaluate it w.r.t. four networkmore » features (largest connected component, PageRank, core-periphery, and community detection), five network sampling strategies, and seven network datasets from different domains. Across a range of conditions, MaxOutProbe demonstrates consistently high performance relative to several baseline strategies« less

Design and Operation of Inland Ports as Nodes of the Trans-Texas Corridor

DOT National Transportation Integrated Search

2006-08-01

The Trans-Texas Corridor (TTC) will provide relatively few links to by-passed metropolitan areas, and it is highly likely that inland ports or groups of "big box" outlets will be developed close to such connections to promote more efficient freight d...

Role of Graph Architecture in Controlling Dynamical Networks with Applications to Neural Systems.

PubMed

Kim, Jason Z; Soffer, Jonathan M; Kahn, Ari E; Vettel, Jean M; Pasqualetti, Fabio; Bassett, Danielle S

2018-01-01

Networked systems display complex patterns of interactions between components. In physical networks, these interactions often occur along structural connections that link components in a hard-wired connection topology, supporting a variety of system-wide dynamical behaviors such as synchronization. While descriptions of these behaviors are important, they are only a first step towards understanding and harnessing the relationship between network topology and system behavior. Here, we use linear network control theory to derive accurate closed-form expressions that relate the connectivity of a subset of structural connections (those linking driver nodes to non-driver nodes) to the minimum energy required to control networked systems. To illustrate the utility of the mathematics, we apply this approach to high-resolution connectomes recently reconstructed from Drosophila, mouse, and human brains. We use these principles to suggest an advantage of the human brain in supporting diverse network dynamics with small energetic costs while remaining robust to perturbations, and to perform clinically accessible targeted manipulation of the brain's control performance by removing single edges in the network. Generally, our results ground the expectation of a control system's behavior in its network architecture, and directly inspire new directions in network analysis and design via distributed control.

Role of graph architecture in controlling dynamical networks with applications to neural systems

NASA Astrophysics Data System (ADS)

Kim, Jason Z.; Soffer, Jonathan M.; Kahn, Ari E.; Vettel, Jean M.; Pasqualetti, Fabio; Bassett, Danielle S.

2018-01-01

Networked systems display complex patterns of interactions between components. In physical networks, these interactions often occur along structural connections that link components in a hard-wired connection topology, supporting a variety of system-wide dynamical behaviours such as synchronization. Although descriptions of these behaviours are important, they are only a first step towards understanding and harnessing the relationship between network topology and system behaviour. Here, we use linear network control theory to derive accurate closed-form expressions that relate the connectivity of a subset of structural connections (those linking driver nodes to non-driver nodes) to the minimum energy required to control networked systems. To illustrate the utility of the mathematics, we apply this approach to high-resolution connectomes recently reconstructed from Drosophila, mouse, and human brains. We use these principles to suggest an advantage of the human brain in supporting diverse network dynamics with small energetic costs while remaining robust to perturbations, and to perform clinically accessible targeted manipulation of the brain's control performance by removing single edges in the network. Generally, our results ground the expectation of a control system's behaviour in its network architecture, and directly inspire new directions in network analysis and design via distributed control.

Summarisation of weighted networks

NASA Astrophysics Data System (ADS)

Zhou, Fang; Qu, Qiang; Toivonen, Hannu

2017-09-01

Networks often contain implicit structure. We introduce novel problems and methods that look for structure in networks, by grouping nodes into supernodes and edges to superedges, and then make this structure visible to the user in a smaller generalised network. This task of finding generalisations of nodes and edges is formulated as 'network Summarisation'. We propose models and algorithms for networks that have weights on edges, on nodes or on both, and study three new variants of the network summarisation problem. In edge-based weighted network summarisation, the summarised network should preserve edge weights as well as possible. A wider class of settings is considered in path-based weighted network summarisation, where the resulting summarised network should preserve longer range connectivities between nodes. Node-based weighted network summarisation in turn allows weights also on nodes and summarisation aims to preserve more information related to high weight nodes. We study theoretical properties of these problems and show them to be NP-hard. We propose a range of heuristic generalisation algorithms with different trade-offs between complexity and quality of the result. Comprehensive experiments on real data show that weighted networks can be summarised efficiently with relatively little error.

Key node selection in minimum-cost control of complex networks

NASA Astrophysics Data System (ADS)

Ding, Jie; Wen, Changyun; Li, Guoqi

2017-11-01

Finding the key node set that is connected with a given number of external control sources for driving complex networks from initial state to any predefined state with minimum cost, known as minimum-cost control problem, is critically important but remains largely open. By defining an importance index for each node, we propose revisited projected gradient method extension (R-PGME) in Monte-Carlo scenario to determine key node set. It is found that the importance index of a node is strongly correlated to occurrence rate of that node to be selected as a key node in Monte-Carlo realizations for three elementary topologies, Erdős-Rényi and scale-free networks. We also discover the distribution patterns of key nodes when the control cost reaches its minimum. Specifically, the importance indices of all nodes in an elementary stem show a quasi-periodic distribution with high peak values in the beginning and end of a quasi-period while they approach to a uniform distribution in an elementary cycle. We further point out that an elementary dilation can be regarded as two elementary stems whose lengths are the closest, and the importance indices in each stem present similar distribution as in an elementary stem. Our results provide a better understanding and deep insight of locating the key nodes in different topologies with minimum control cost.

Percolation of spatially constrained Erdős-Rényi networks with degree correlations.

PubMed

Schmeltzer, C; Soriano, J; Sokolov, I M; Rüdiger, S

2014-01-01

Motivated by experiments on activity in neuronal cultures [ J. Soriano, M. Rodríguez Martínez, T. Tlusty and E. Moses Proc. Natl. Acad. Sci. 105 13758 (2008)], we investigate the percolation transition and critical exponents of spatially embedded Erdős-Rényi networks with degree correlations. In our model networks, nodes are randomly distributed in a two-dimensional spatial domain, and the connection probability depends on Euclidian link length by a power law as well as on the degrees of linked nodes. Generally, spatial constraints lead to higher percolation thresholds in the sense that more links are needed to achieve global connectivity. However, degree correlations favor or do not favor percolation depending on the connectivity rules. We employ two construction methods to introduce degree correlations. In the first one, nodes stay homogeneously distributed and are connected via a distance- and degree-dependent probability. We observe that assortativity in the resulting network leads to a decrease of the percolation threshold. In the second construction methods, nodes are first spatially segregated depending on their degree and afterwards connected with a distance-dependent probability. In this segregated model, we find a threshold increase that accompanies the rising assortativity. Additionally, when the network is constructed in a disassortative way, we observe that this property has little effect on the percolation transition.

Hidden Connectivity in Networks with Vulnerable Classes of Nodes

NASA Astrophysics Data System (ADS)

Krause, Sebastian M.; Danziger, Michael M.; Zlatić, Vinko

2016-10-01

In many complex systems representable as networks, nodes can be separated into different classes. Often these classes can be linked to a mutually shared vulnerability. Shared vulnerabilities may be due to a shared eavesdropper or correlated failures. In this paper, we show the impact of shared vulnerabilities on robust connectivity and how the heterogeneity of node classes can be exploited to maintain functionality by utilizing multiple paths. Percolation is the field of statistical physics that is generally used to analyze connectivity in complex networks, but in its existing forms, it cannot treat the heterogeneity of multiple vulnerable classes. To analyze the connectivity under these constraints, we describe each class as a color and develop a "color-avoiding" percolation. We present an analytic theory for random networks and a numerical algorithm for all networks, with which we can determine which nodes are color-avoiding connected and whether the maximal set percolates in the system. We find that the interaction of topology and color distribution implies a rich critical behavior, with critical values and critical exponents depending both on the topology and on the color distribution. Applying our physics-based theory to the Internet, we show how color-avoiding percolation can be used as the basis for new topologically aware secure communication protocols. Beyond applications to cybersecurity, our framework reveals a new layer of hidden structure in a wide range of natural and technological systems.

Analyses of the response of a complex weighted network to nodes removal strategies considering links weight: The case of the Beijing urban road system

NASA Astrophysics Data System (ADS)

Bellingeri, Michele; Lu, Zhe-Ming; Cassi, Davide; Scotognella, Francesco

2018-02-01

Complex network response to node loss is a central question in different fields of science ranging from physics, sociology, biology to ecology. Previous studies considered binary networks where the weight of the links is not accounted for. However, in real-world networks the weights of connections can be widely different. Here, we analyzed the response of real-world road traffic complex network of Beijing, the most prosperous city in China. We produced nodes removal attack simulations using classic binary node features and we introduced weighted ranks for node importance. We measured the network functioning during nodes removal with three different parameters: the size of the largest connected cluster (LCC), the binary network efficiency (Bin EFF) and the weighted network efficiency (Weg EFF). We find that removing nodes according to weighted rank, i.e. considering the weight of the links as a number of taxi flows along the roads, produced in general the highest damage in the system. Our results show that: (i) in order to model Beijing road complex networks response to nodes (intersections) failure, it is necessary to consider the weight of the links; (ii) to discover the best attack strategy, it is important to use nodes rank accounting links weight.

Meth math: modeling temperature responses to methamphetamine.

PubMed

Molkov, Yaroslav I; Zaretskaia, Maria V; Zaretsky, Dmitry V

2014-04-15

Methamphetamine (Meth) can evoke extreme hyperthermia, which correlates with neurotoxicity and death in laboratory animals and humans. The objective of this study was to uncover the mechanisms of a complex dose dependence of temperature responses to Meth by mathematical modeling of the neuronal circuitry. On the basis of previous studies, we composed an artificial neural network with the core comprising three sequentially connected nodes: excitatory, medullary, and sympathetic preganglionic neuronal (SPN). Meth directly stimulated the excitatory node, an inhibitory drive targeted the medullary node, and, in high doses, an additional excitatory drive affected the SPN node. All model parameters (weights of connections, sensitivities, and time constants) were subject to fitting experimental time series of temperature responses to 1, 3, 5, and 10 mg/kg Meth. Modeling suggested that the temperature response to the lowest dose of Meth, which caused an immediate and short hyperthermia, involves neuronal excitation at a supramedullary level. The delay in response after the intermediate doses of Meth is a result of neuronal inhibition at the medullary level. Finally, the rapid and robust increase in body temperature induced by the highest dose of Meth involves activation of high-dose excitatory drive. The impairment in the inhibitory mechanism can provoke a life-threatening temperature rise and makes it a plausible cause of fatal hyperthermia in Meth users. We expect that studying putative neuronal sites of Meth action and the neuromediators involved in a detailed model of this system may lead to more effective strategies for prevention and treatment of hyperthermia induced by amphetamine-like stimulants.

Meth math: modeling temperature responses to methamphetamine

PubMed Central

Molkov, Yaroslav I.; Zaretskaia, Maria V.

2014-01-01

Methamphetamine (Meth) can evoke extreme hyperthermia, which correlates with neurotoxicity and death in laboratory animals and humans. The objective of this study was to uncover the mechanisms of a complex dose dependence of temperature responses to Meth by mathematical modeling of the neuronal circuitry. On the basis of previous studies, we composed an artificial neural network with the core comprising three sequentially connected nodes: excitatory, medullary, and sympathetic preganglionic neuronal (SPN). Meth directly stimulated the excitatory node, an inhibitory drive targeted the medullary node, and, in high doses, an additional excitatory drive affected the SPN node. All model parameters (weights of connections, sensitivities, and time constants) were subject to fitting experimental time series of temperature responses to 1, 3, 5, and 10 mg/kg Meth. Modeling suggested that the temperature response to the lowest dose of Meth, which caused an immediate and short hyperthermia, involves neuronal excitation at a supramedullary level. The delay in response after the intermediate doses of Meth is a result of neuronal inhibition at the medullary level. Finally, the rapid and robust increase in body temperature induced by the highest dose of Meth involves activation of high-dose excitatory drive. The impairment in the inhibitory mechanism can provoke a life-threatening temperature rise and makes it a plausible cause of fatal hyperthermia in Meth users. We expect that studying putative neuronal sites of Meth action and the neuromediators involved in a detailed model of this system may lead to more effective strategies for prevention and treatment of hyperthermia induced by amphetamine-like stimulants. PMID:24500434

Connectivity Restoration in Wireless Sensor Networks via Space Network Coding.

PubMed

Uwitonze, Alfred; Huang, Jiaqing; Ye, Yuanqing; Cheng, Wenqing

2017-04-20

The problem of finding the number and optimal positions of relay nodes for restoring the network connectivity in partitioned Wireless Sensor Networks (WSNs) is Non-deterministic Polynomial-time hard (NP-hard) and thus heuristic methods are preferred to solve it. This paper proposes a novel polynomial time heuristic algorithm, namely, Relay Placement using Space Network Coding (RPSNC), to solve this problem, where Space Network Coding, also called Space Information Flow (SIF), is a new research paradigm that studies network coding in Euclidean space, in which extra relay nodes can be introduced to reduce the cost of communication. Unlike contemporary schemes that are often based on Minimum Spanning Tree (MST), Euclidean Steiner Minimal Tree (ESMT) or a combination of MST with ESMT, RPSNC is a new min-cost multicast space network coding approach that combines Delaunay triangulation and non-uniform partitioning techniques for generating a number of candidate relay nodes, and then linear programming is applied for choosing the optimal relay nodes and computing their connection links with terminals. Subsequently, an equilibrium method is used to refine the locations of the optimal relay nodes, by moving them to balanced positions. RPSNC can adapt to any density distribution of relay nodes and terminals, as well as any density distribution of terminals. The performance and complexity of RPSNC are analyzed and its performance is validated through simulation experiments.

The degree-related clustering coefficient and its application to link prediction

NASA Astrophysics Data System (ADS)

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

2016-07-01

Link prediction plays a significant role in explaining the evolution of networks. However it is still a challenging problem that has been addressed only with topological information in recent years. Based on the belief that network nodes with a great number of common neighbors are more likely to be connected, many similarity indices have achieved considerable accuracy and efficiency. Motivated by the natural assumption that the effect of missing links on the estimation of a node's clustering ability could be related to node degree, in this paper, we propose a degree-related clustering coefficient index to quantify the clustering ability of nodes. Unlike the classical clustering coefficient, our new coefficient is highly robust when the observed bias of links is considered. Furthermore, we propose a degree-related clustering ability path (DCP) index, which applies the proposed coefficient to the link prediction problem. Experiments on 12 real-world networks show that our proposed method is highly accurate and robust compared with four common-neighbor-based similarity indices (Common Neighbors(CN), Adamic-Adar(AA), Resource Allocation(RA), and Preferential Attachment(PA)), and the recently introduced clustering ability (CA) index.

Controllability of protein-protein interaction phosphorylation-based networks: Participation of the hub 14-3-3 protein family

PubMed Central

Uhart, Marina; Flores, Gabriel; Bustos, Diego M.

2016-01-01

Posttranslational regulation of protein function is an ubiquitous mechanism in eukaryotic cells. Here, we analyzed biological properties of nodes and edges of a human protein-protein interaction phosphorylation-based network, especially of those nodes critical for the network controllability. We found that the minimal number of critical nodes needed to control the whole network is 29%, which is considerably lower compared to other real networks. These critical nodes are more regulated by posttranslational modifications and contain more binding domains to these modifications than other kinds of nodes in the network, suggesting an intra-group fast regulation. Also, when we analyzed the edges characteristics that connect critical and non-critical nodes, we found that the former are enriched in domain-to-eukaryotic linear motif interactions, whereas the later are enriched in domain-domain interactions. Our findings suggest a possible structure for protein-protein interaction networks with a densely interconnected and self-regulated central core, composed of critical nodes with a high participation in the controllability of the full network, and less regulated peripheral nodes. Our study offers a deeper understanding of complex network control and bridges the controllability theorems for complex networks and biological protein-protein interaction phosphorylation-based networked systems. PMID:27195976

Graph Metrics of Structural Brain Networks in Individuals with Schizophrenia and Healthy Controls: Group Differences, Relationships with Intelligence, and Genetics.

PubMed

Yeo, Ronald A; Ryman, Sephira G; van den Heuvel, Martijn P; de Reus, Marcel A; Jung, Rex E; Pommy, Jessica; Mayer, Andrew R; Ehrlich, Stefan; Schulz, S Charles; Morrow, Eric M; Manoach, Dara; Ho, Beng-Choon; Sponheim, Scott R; Calhoun, Vince D

2016-02-01

One of the most prominent features of schizophrenia is relatively lower general cognitive ability (GCA). An emerging approach to understanding the roots of variation in GCA relies on network properties of the brain. In this multi-center study, we determined global characteristics of brain networks using graph theory and related these to GCA in healthy controls and individuals with schizophrenia. Participants (N=116 controls, 80 patients with schizophrenia) were recruited from four sites. GCA was represented by the first principal component of a large battery of neurocognitive tests. Graph metrics were derived from diffusion-weighted imaging. The global metrics of longer characteristic path length and reduced overall connectivity predicted lower GCA across groups, and group differences were noted for both variables. Measures of clustering, efficiency, and modularity did not differ across groups or predict GCA. Follow-up analyses investigated three topological types of connectivity--connections among high degree "rich club" nodes, "feeder" connections to these rich club nodes, and "local" connections not involving the rich club. Rich club and local connectivity predicted performance across groups. In a subsample (N=101 controls, 56 patients), a genetic measure reflecting mutation load, based on rare copy number deletions, was associated with longer characteristic path length. Results highlight the importance of characteristic path lengths and rich club connectivity for GCA and provide no evidence for group differences in the relationships between graph metrics and GCA.

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.

Mapping higher-order relations between brain structure and function with embedded vector representations of connectomes.

PubMed

Rosenthal, Gideon; Váša, František; Griffa, Alessandra; Hagmann, Patric; Amico, Enrico; Goñi, Joaquín; Avidan, Galia; Sporns, Olaf

2018-06-05

Connectomics generates comprehensive maps of brain networks, represented as nodes and their pairwise connections. The functional roles of nodes are defined by their direct and indirect connectivity with the rest of the network. However, the network context is not directly accessible at the level of individual nodes. Similar problems in language processing have been addressed with algorithms such as word2vec that create embeddings of words and their relations in a meaningful low-dimensional vector space. Here we apply this approach to create embedded vector representations of brain networks or connectome embeddings (CE). CE can characterize correspondence relations among brain regions, and can be used to infer links that are lacking from the original structural diffusion imaging, e.g., inter-hemispheric homotopic connections. Moreover, we construct predictive deep models of functional and structural connectivity, and simulate network-wide lesion effects using the face processing system as our application domain. We suggest that CE offers a novel approach to revealing relations between connectome structure and function.

Connecting Performance Analysis and Visualization to Advance Extreme Scale Computing

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

Bremer, Peer-Timo; Mohr, Bernd; Schulz, Martin

2015-07-29

The characterization, modeling, analysis, and tuning of software performance has been a central topic in High Performance Computing (HPC) since its early beginnings. The overall goal is to make HPC software run faster on particular hardware, either through better scheduling, on-node resource utilization, or more efficient distributed communication.

Disintegration of Sensorimotor Brain Networks in Schizophrenia.

PubMed

Kaufmann, Tobias; Skåtun, Kristina C; Alnæs, Dag; Doan, Nhat Trung; Duff, Eugene P; Tønnesen, Siren; Roussos, Evangelos; Ueland, Torill; Aminoff, Sofie R; Lagerberg, Trine V; Agartz, Ingrid; Melle, Ingrid S; Smith, Stephen M; Andreassen, Ole A; Westlye, Lars T

2015-11-01

Schizophrenia is a severe mental disorder associated with derogated function across various domains, including perception, language, motor, emotional, and social behavior. Due to its complex symptomatology, schizophrenia is often regarded a disorder of cognitive processes. Yet due to the frequent involvement of sensory and perceptual symptoms, it has been hypothesized that functional disintegration between sensory and cognitive processes mediates the heterogeneous and comprehensive schizophrenia symptomatology. Here, using resting-state functional magnetic resonance imaging in 71 patients and 196 healthy controls, we characterized the standard deviation in BOLD (blood-oxygen-level-dependent) signal amplitude and the functional connectivity across a range of functional brain networks. We investigated connectivity on the edge and node level using network modeling based on independent component analysis and utilized the brain network features in cross-validated classification procedures. Both amplitude and connectivity were significantly altered in patients, largely involving sensory networks. Reduced standard deviation in amplitude was observed in a range of visual, sensorimotor, and auditory nodes in patients. The strongest differences in connectivity implicated within-sensorimotor and sensorimotor-thalamic connections. Furthermore, sensory nodes displayed widespread alterations in the connectivity with higher-order nodes. We demonstrated robustness of effects across subjects by significantly classifying diagnostic group on the individual level based on cross-validated multivariate connectivity features. Taken together, the findings support the hypothesis of disintegrated sensory and cognitive processes in schizophrenia, and the foci of effects emphasize that targeting the sensory and perceptual domains may be key to enhance our understanding of schizophrenia pathophysiology. © The Author 2015. Published by Oxford University Press on behalf of the Maryland Psychiatric Research Center. All rights reserved. For permissions, please email: journals.permissions@oup.com.

Zero energy-storage ballast for compact fluorescent lamps

DOEpatents

Schultz, W.N.; Thomas, R.J.

1999-08-31

A CFL ballast includes complementary-type switching devices connected in series with their gates connected together at a control node. The switching devices supply a resonant tank circuit which is tuned to a frequency near, but slightly lower than, the resonant frequency of a resonant control circuit. As a result, the tank circuit restarts oscillations immediately following each zero crossing of the bus voltage. Such rapid restarts avoid undesirable flickering while maintaining the operational advantages and high efficacy of the CFL ballast. 4 figs.

Zero energy-storage ballast for compact fluorescent lamps

DOEpatents

Schultz, William Newell; Thomas, Robert James

1999-01-01

A CFL ballast includes complementary-type switching devices connected in series with their gates connected together at a control node. The switching devices supply a resonant tank circuit which is tuned to a frequency near, but slightly lower than, the resonant frequency of a resonant control circuit. As a result, the tank circuit restarts oscillations immediately following each zero crossing of the bus voltage. Such rapid restarts avoid undesirable flickering while maintaining the operational advantages and high efficacy of the CFL ballast.

Earthquake Complex Network applied along the Chilean Subduction Zone.

NASA Astrophysics Data System (ADS)

Martin, F.; Pasten, D.; Comte, D.

2017-12-01

In recent years the earthquake complex networks have been used as a useful tool to describe and characterize the behavior of seismicity. The earthquake complex network is built in space, dividing the three dimensional space in cubic cells. If the cubic cell contains a hypocenter, we call this cell like a node. The connections between nodes follows the time sequence of the occurrence of the seismic events. In this sense, we have a spatio-temporal configuration of a specific region using the seismicity in that zone. In this work, we are applying complex networks to characterize the subduction zone along the coast of Chile using two networks: a directed and an undirected network. The directed network takes in consideration the time-direction of the connections, that is very important for the connectivity of the network: we are considering the connectivity, ki of the i-th node, like the number of connections going out from the node i and we add the self-connections (if two seismic events occurred successive in time in the same cubic cell, we have a self-connection). The undirected network is the result of remove the direction of the connections and the self-connections from the directed network. These two networks were building using seismic data events recorded by CSN (Chilean Seismological Center) in Chile. This analysis includes the last largest earthquakes occurred in Iquique (April 2014) and in Illapel (September 2015). The result for the directed network shows a change in the value of the critical exponent along the Chilean coast. The result for the undirected network shows a small-world behavior without important changes in the topology of the network. Therefore, the complex network analysis shows a new form to characterize the Chilean subduction zone with a simple method that could be compared with another methods to obtain more details about the behavior of the seismicity in this region.

Modular sensor network node

DOEpatents

Davis, Jesse Harper Zehring [Berkeley, CA; Stark, Jr., Douglas Paul; Kershaw, Christopher Patrick [Hayward, CA; Kyker, Ronald Dean [Livermore, CA

2008-06-10

A distributed wireless sensor network node is disclosed. The wireless sensor network node includes a plurality of sensor modules coupled to a system bus and configured to sense a parameter. The parameter may be an object, an event or any other parameter. The node collects data representative of the parameter. The node also includes a communication module coupled to the system bus and configured to allow the node to communicate with other nodes. The node also includes a processing module coupled to the system bus and adapted to receive the data from the sensor module and operable to analyze the data. The node also includes a power module connected to the system bus and operable to generate a regulated voltage.

Parameters affecting the resilience of scale-free networks to random failures.

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

Link, Hamilton E.; LaViolette, Randall A.; Lane, Terran

2005-09-01

It is commonly believed that scale-free networks are robust to massive numbers of random node deletions. For example, Cohen et al. in (1) study scale-free networks including some which approximate the measured degree distribution of the Internet. Their results suggest that if each node in this network failed independently with probability 0.99, most of the remaining nodes would still be connected in a giant component. In this paper, we show that a large and important subclass of scale-free networks are not robust to massive numbers of random node deletions. In particular, we study scale-free networks which have minimum node degreemore » of 1 and a power-law degree distribution beginning with nodes of degree 1 (power-law networks). We show that, in a power-law network approximating the Internet's reported distribution, when the probability of deletion of each node is 0.5 only about 25% of the surviving nodes in the network remain connected in a giant component, and the giant component does not persist beyond a critical failure rate of 0.9. The new result is partially due to improved analytical accommodation of the large number of degree-0 nodes that result after node deletions. Our results apply to power-law networks with a wide range of power-law exponents, including Internet-like networks. We give both analytical and empirical evidence that such networks are not generally robust to massive random node deletions.« less

DELTACON: A Principled Massive-Graph Similarity Function with Attribution

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

Koutra, Danai; Shah, Neil; Vogelstein, Joshua T.

How much did a network change since yesterday? How different is the wiring between Bob's brain (a left-handed male) and Alice's brain (a right-handed female)? Graph similarity with known node correspondence, i.e. the detection of changes in the connectivity of graphs, arises in numerous settings. In this work, we formally state the axioms and desired properties of the graph similarity functions, and evaluate when state-of-the-art methods fail to detect crucial connectivity changes in graphs. We propose DeltaCon, a principled, intuitive, and scalable algorithm that assesses the similarity between two graphs on the same nodes (e.g. employees of a company, customersmore » of a mobile carrier). In our experiments on various synthetic and real graphs we showcase the advantages of our method over existing similarity measures. We also employ DeltaCon to real applications: (a) we classify people to groups of high and low creativity based on their brain connectivity graphs, and (b) do temporal anomaly detection in the who-emails-whom Enron graph.« less

DELTACON: A Principled Massive-Graph Similarity Function with Attribution

DOE PAGES

Koutra, Danai; Shah, Neil; Vogelstein, Joshua T.; ...

2014-05-22

How much did a network change since yesterday? How different is the wiring between Bob's brain (a left-handed male) and Alice's brain (a right-handed female)? Graph similarity with known node correspondence, i.e. the detection of changes in the connectivity of graphs, arises in numerous settings. In this work, we formally state the axioms and desired properties of the graph similarity functions, and evaluate when state-of-the-art methods fail to detect crucial connectivity changes in graphs. We propose DeltaCon, a principled, intuitive, and scalable algorithm that assesses the similarity between two graphs on the same nodes (e.g. employees of a company, customersmore » of a mobile carrier). In our experiments on various synthetic and real graphs we showcase the advantages of our method over existing similarity measures. We also employ DeltaCon to real applications: (a) we classify people to groups of high and low creativity based on their brain connectivity graphs, and (b) do temporal anomaly detection in the who-emails-whom Enron graph.« less

Reconfiguration in Robust Distributed Real-Time Systems Based on Global Checkpoints

DTIC Science & Technology

1991-12-01

achieved by utilizing distributed systems in which a single application program executes on multiple processors, connected to a network. The distributed...single application program executes on multiple proces- sors, connected to a network. The distributed nature of such systems make it possible to ...resident at every node. How - ever, the responsibility for execution of a particular function is assigned to only one node in this framework. This function

Viewing socio-affective stimuli increases connectivity within an extended default mode network.

PubMed

Göttlich, Martin; Ye, Zheng; Rodriguez-Fornells, Antoni; Münte, Thomas F; Krämer, Ulrike M

2017-03-01

Empathy is an essential ability for prosocial behavior. Previous imaging studies identified a number of brain regions implicated in affective and cognitive aspects of empathy. In this study, we investigated the neural correlates of empathy from a network perspective using graph theory and beta-series correlations. Two independent data sets were acquired using the same paradigm that elicited empathic responses to socio-affective stimuli. One data set was used to define the network nodes and modular structure, the other data set was used to investigate the effects of emotional versus neutral stimuli on network connectivity. Emotional relative to neutral stimuli increased connectivity between 74 nodes belonging to different networks. Most of these nodes belonged to an extended default mode network (eDMN). The other nodes belonged to a cognitive control network or visual networks. Within the eDMN, posterior STG/TPJ regions were identified as provincial hubs. The eDMN also showed stronger connectivity to the cognitive control network encompassing lateral PFC regions. Connector hubs between the two networks were posterior cingulate cortex and ventrolateral PFC. This stresses the advantage of a network approach as regions similarly modulated by task conditions can be dissociated into distinct networks and regions crucial for network integration can be identified. Copyright © 2017 Elsevier Inc. All rights reserved.

Broadcasting a message in a parallel computer

DOEpatents

Archer, Charles J; Faraj, Ahmad A

2013-04-16

Methods, systems, and products are disclosed for broadcasting a message in a parallel computer that includes: transmitting, by the logical root to all of the nodes directly connected to the logical root, a message; and for each node except the logical root: receiving the message; if that node is the physical root, then transmitting the message to all of the child nodes except the child node from which the message was received; if that node received the message from a parent node and if that node is not a leaf node, then transmitting the message to all of the child nodes; and if that node received the message from a child node and if that node is not the physical root, then transmitting the message to all of the child nodes except the child node from which the message was received and transmitting the message to the parent node.

Broadcasting a message in a parallel computer

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

None

Methods, systems, and products are disclosed for broadcasting a message in a parallel computer that includes: transmitting, by the logical root to all of the nodes directly connected to the logical root, a message; and for each node except the logical root: receiving the message; if that node is the physical root, then transmitting the message to all of the child nodes except the child node from which the message was received; if that node received the message from a parent node and if that node is not a leaf node, then transmitting the message to all of the childmore » nodes; and if that node received the message from a child node and if that node is not the physical root, then transmitting the message to all of the child nodes except the child node from which the message was received and transmitting the message to the parent node.« less

Method and Circuit for Injecting a Precise Amount of Charge onto a Circuit Node

NASA Technical Reports Server (NTRS)

Hancock, Bruce R. (Inventor)

2016-01-01

A method and circuit for injecting charge into a circuit node, comprising (a) resetting a capacitor's voltage through a first transistor; (b) after the resetting, pre-charging the capacitor through the first transistor; and (c) after the pre-charging, further charging the capacitor through a second transistor, wherein the second transistor is connected between the capacitor and a circuit node, and the further charging draws charge through the second transistor from the circuit node, thereby injecting charge into the circuit node.

Large epidemic thresholds emerge in heterogeneous networks of heterogeneous nodes

NASA Astrophysics Data System (ADS)

Yang, Hui; Tang, Ming; Gross, Thilo

2015-08-01

One of the famous results of network science states that networks with heterogeneous connectivity are more susceptible to epidemic spreading than their more homogeneous counterparts. In particular, in networks of identical nodes it has been shown that network heterogeneity, i.e. a broad degree distribution, can lower the epidemic threshold at which epidemics can invade the system. Network heterogeneity can thus allow diseases with lower transmission probabilities to persist and spread. However, it has been pointed out that networks in which the properties of nodes are intrinsically heterogeneous can be very resilient to disease spreading. Heterogeneity in structure can enhance or diminish the resilience of networks with heterogeneous nodes, depending on the correlations between the topological and intrinsic properties. Here, we consider a plausible scenario where people have intrinsic differences in susceptibility and adapt their social network structure to the presence of the disease. We show that the resilience of networks with heterogeneous connectivity can surpass those of networks with homogeneous connectivity. For epidemiology, this implies that network heterogeneity should not be studied in isolation, it is instead the heterogeneity of infection risk that determines the likelihood of outbreaks.

Large epidemic thresholds emerge in heterogeneous networks of heterogeneous nodes.

PubMed

Yang, Hui; Tang, Ming; Gross, Thilo

2015-08-21

One of the famous results of network science states that networks with heterogeneous connectivity are more susceptible to epidemic spreading than their more homogeneous counterparts. In particular, in networks of identical nodes it has been shown that network heterogeneity, i.e. a broad degree distribution, can lower the epidemic threshold at which epidemics can invade the system. Network heterogeneity can thus allow diseases with lower transmission probabilities to persist and spread. However, it has been pointed out that networks in which the properties of nodes are intrinsically heterogeneous can be very resilient to disease spreading. Heterogeneity in structure can enhance or diminish the resilience of networks with heterogeneous nodes, depending on the correlations between the topological and intrinsic properties. Here, we consider a plausible scenario where people have intrinsic differences in susceptibility and adapt their social network structure to the presence of the disease. We show that the resilience of networks with heterogeneous connectivity can surpass those of networks with homogeneous connectivity. For epidemiology, this implies that network heterogeneity should not be studied in isolation, it is instead the heterogeneity of infection risk that determines the likelihood of outbreaks.

Dynamical Response of Networks Under External Perturbations: Exact Results

NASA Astrophysics Data System (ADS)

Chinellato, David D.; Epstein, Irving R.; Braha, Dan; Bar-Yam, Yaneer; de Aguiar, Marcus A. M.

2015-04-01

We give exact statistical distributions for the dynamic response of influence networks subjected to external perturbations. We consider networks whose nodes have two internal states labeled 0 and 1. We let nodes be frozen in state 0, in state 1, and the remaining nodes change by adopting the state of a connected node with a fixed probability per time step. The frozen nodes can be interpreted as external perturbations to the subnetwork of free nodes. Analytically extending and to be smaller than 1 enables modeling the case of weak coupling. We solve the dynamical equations exactly for fully connected networks, obtaining the equilibrium distribution, transition probabilities between any two states and the characteristic time to equilibration. Our exact results are excellent approximations for other topologies, including random, regular lattice, scale-free and small world networks, when the numbers of fixed nodes are adjusted to take account of the effect of topology on coupling to the environment. This model can describe a variety of complex systems, from magnetic spins to social networks to population genetics, and was recently applied as a framework for early warning signals for real-world self-organized economic market crises.

Scaling of Average Weighted Receiving Time on Double-Weighted Koch Networks

NASA Astrophysics Data System (ADS)

Dai, Meifeng; Ye, Dandan; Hou, Jie; Li, Xingyi

2015-03-01

In this paper, we introduce a model of the double-weighted Koch networks based on actual road networks depending on the two weight factors w,r ∈ (0, 1]. The double weights represent the capacity-flowing weight and the cost-traveling weight, respectively. Denote by wFij the capacity-flowing weight connecting the nodes i and j, and denote by wCij the cost-traveling weight connecting the nodes i and j. Let wFij be related to the weight factor w, and let wCij be related to the weight factor r. This paper assumes that the walker, at each step, starting from its current node, moves to any of its neighbors with probability proportional to the capacity-flowing weight of edge linking them. The weighted time for two adjacency nodes is the cost-traveling weight connecting the two nodes. We define the average weighted receiving time (AWRT) on the double-weighted Koch networks. The obtained result displays that in the large network, the AWRT grows as power-law function of the network order with the exponent, represented by θ(w,r) = ½ log2(1 + 3wr). We show that the AWRT exhibits a sublinear or linear dependence on network order. Thus, the double-weighted Koch networks are more efficient than classic Koch networks in receiving information.

Stability of a giant connected component in a complex network

NASA Astrophysics Data System (ADS)

Kitsak, Maksim; Ganin, Alexander A.; Eisenberg, Daniel A.; Krapivsky, Pavel L.; Krioukov, Dmitri; Alderson, David L.; Linkov, Igor

2018-01-01

We analyze the stability of the network's giant connected component under impact of adverse events, which we model through the link percolation. Specifically, we quantify the extent to which the largest connected component of a network consists of the same nodes, regardless of the specific set of deactivated links. Our results are intuitive in the case of single-layered systems: the presence of large degree nodes in a single-layered network ensures both its robustness and stability. In contrast, we find that interdependent networks that are robust to adverse events have unstable connected components. Our results bring novel insights to the design of resilient network topologies and the reinforcement of existing networked systems.

A graph-based evolutionary algorithm: Genetic Network Programming (GNP) and its extension using reinforcement learning.

PubMed

Mabu, Shingo; Hirasawa, Kotaro; Hu, Jinglu

2007-01-01

This paper proposes a graph-based evolutionary algorithm called Genetic Network Programming (GNP). Our goal is to develop GNP, which can deal with dynamic environments efficiently and effectively, based on the distinguished expression ability of the graph (network) structure. The characteristics of GNP are as follows. 1) GNP programs are composed of a number of nodes which execute simple judgment/processing, and these nodes are connected by directed links to each other. 2) The graph structure enables GNP to re-use nodes, thus the structure can be very compact. 3) The node transition of GNP is executed according to its node connections without any terminal nodes, thus the past history of the node transition affects the current node to be used and this characteristic works as an implicit memory function. These structural characteristics are useful for dealing with dynamic environments. Furthermore, we propose an extended algorithm, "GNP with Reinforcement Learning (GNPRL)" which combines evolution and reinforcement learning in order to create effective graph structures and obtain better results in dynamic environments. In this paper, we applied GNP to the problem of determining agents' behavior to evaluate its effectiveness. Tileworld was used as the simulation environment. The results show some advantages for GNP over conventional methods.

The Node Acquisition and Integration Technique: A Node-Link Based Teaching/Learning Strategy.

ERIC Educational Resources Information Center

Diekhoff, George M.

This paper presents the results of three experiments conducted in connection with development of a node-link based teaching/learning strategy. In experiment 1, subjects were instructed to either define concepts selected from a unit of introductory psychology or to describe the relationships existing between pairs of concepts. The cognitive…

Use of Networked Collaborative Concept Mapping To Measure Team Processes and Team Outcomes.

ERIC Educational Resources Information Center

Chung, Gregory K. W. K.; O'Neil, Harold F., Jr.; Herl, Howard E.; Dennis, Robert A.

The feasibility of using a computer-based networked collaborative concept mapping system to measure teamwork skills was studied. A concept map is a node-link-node representation of content, where the nodes represent concepts and links represent relationships between connected concepts. Teamwork processes were examined for a group concept mapping…

Eradicating catastrophic collapse in interdependent networks via reinforced nodes

PubMed Central

Yuan, Xin; Hu, Yanqing; Havlin, Shlomo

2017-01-01

In interdependent networks, it is usually assumed, based on percolation theory, that nodes become nonfunctional if they lose connection to the network giant component. However, in reality, some nodes, equipped with alternative resources, together with their connected neighbors can still be functioning after disconnected from the giant component. Here, we propose and study a generalized percolation model that introduces a fraction of reinforced nodes in the interdependent networks that can function and support their neighborhood. We analyze, both analytically and via simulations, the order parameter—the functioning component—comprising both the giant component and smaller components that include at least one reinforced node. Remarkably, it is found that, for interdependent networks, we need to reinforce only a small fraction of nodes to prevent abrupt catastrophic collapses. Moreover, we find that the universal upper bound of this fraction is 0.1756 for two interdependent Erdős–Rényi (ER) networks: regular random (RR) networks and scale-free (SF) networks with large average degrees. We also generalize our theory to interdependent networks of networks (NONs). These findings might yield insight for designing resilient interdependent infrastructure networks. PMID:28289204

OceanNOMADS: A New Distribution Node for Operational Ocean Model Output

NASA Astrophysics Data System (ADS)

Cross, S.; Vance, T.; Breckenridge, T.

2009-12-01

The NOAA National Operational Model Archive and Distribution System (NOMADS) is a distributed, web-services based project providing real-time and retrospective access to climate and weather model data and related datasets. OceanNOMADS is a new NOMADS node dedicated to ocean model and related data, with an initial focus on operational ocean models from NOAA and the U.S. Navy. The node offers data access through a Thematic Real-time Environmental Distributed Data Services (THREDDS) server via the commonly used OPeNDAP protocol. The primary server is operated by the National Coastal Data Development Center and hosted by the Northern Gulf Institute at Stennis Space Center, MS. In cooperation with the National Marine Fisheries Service and Mississippi State University (MSU), a duplicate server is being installed at MSU with a 1-gigabit connection to the National Lambda Rail. This setup will allow us to begin to quantify the benefit of high-speed data connections to scientists needing remote access to these large datasets. Work is also underway on the next generation of services from OceanNOMADS, including user-requested server-side data reformatting, regridding, and aggregation, as well as tools for model-data comparison.

Design and Analysis of a Data Fusion Scheme in Mobile Wireless Sensor Networks Based on Multi-Protocol Mobile Agents

PubMed Central

Wu, Chunxue; Wu, Wenliang; Wan, Caihua

2017-01-01

Sensors are increasingly used in mobile environments with wireless network connections. Multiple sensor types measure distinct aspects of the same event. Their measurements are then combined to produce integrated, reliable results. As the number of sensors in networks increases, low energy requirements and changing network connections complicate event detection and measurement. We present a data fusion scheme for use in mobile wireless sensor networks with high energy efficiency and low network delays, that still produces reliable results. In the first phase, we used a network simulation where mobile agents dynamically select the next hop migration node based on the stability parameter of the link, and perform the data fusion at the migration node. Agents use the fusion results to decide if it should return the fusion results to the processing center or continue to collect more data. In the second phase. The feasibility of data fusion at the node level is confirmed by an experimental design where fused data from color sensors show near-identical results to actual physical temperatures. These results are potentially important for new large-scale sensor network applications. PMID:29099793

Rich club network analysis shows distinct patterns of disruption in frontotemporal dementia and Alzheimer’s disease

PubMed Central

Daianu, Madelaine; Jahanshad, Neda; Villalon-Reina, Julio E.; Mendez, Mario F.; Bartzokis, George; Jimenez, Elvira E.; Joshi, Aditi; Barsuglia, Joseph; Thompson, Paul M.

2015-01-01

Diffusion imaging and brain connectivity analyses can reveal the underlying organizational patterns of the human brain, described as complex networks of densely interlinked regions. Here, we analyzed 1.5-Tesla whole-brain diffusion-weighted images from 64 participants – 15 patients with behavioral variant frontotemporal (bvFTD) dementia, 19 with early-onset Alzheimer’s disease (EOAD), and 30 healthy elderly controls. Based on whole-brain tractography, we reconstructed structural brain connectivity networks to map connections between cortical regions. We examined how bvFTD and EOAD disrupt the weighted ‘rich club’ – a network property where high-degree network nodes are more interconnected than expected by chance. bvFTD disrupts both the nodal and global organization of the network in both low- and high-degree regions of the brain. EOAD targets the global connectivity of the brain, mainly affecting the fiber density of high-degree (highly connected) regions that form the rich club network. These rich club analyses suggest distinct patterns of disruptions among different forms of dementia. PMID:26161050

Analysis and Tools for Improved Management of Connectionless and Connection-Oriented BLE Devices Coexistence

PubMed Central

Del Campo, Antonio; Cintioni, Lorenzo; Spinsante, Susanna; Gambi, Ennio

2017-01-01

With the introduction of low-power wireless technologies, like Bluetooth Low Energy (BLE), new applications are approaching the home automation, healthcare, fitness, automotive and consumer electronics markets. BLE devices are designed to maximize the battery life, i.e., to run for long time on a single coin-cell battery. In typical application scenarios of home automation and Ambient Assisted Living (AAL), the sensors that monitor relatively unpredictable and rare events should coexist with other sensors that continuously communicate health or environmental parameter measurements. The former usually work in connectionless mode, acting as advertisers, while the latter need a persistent connection, acting as slave nodes. The coexistence of connectionless and connection-oriented networks, that share the same central node, can be required to reduce the number of handling devices, thus keeping the network complexity low and limiting the packet’s traffic congestion. In this paper, the medium access management, operated by the central node, has been modeled, focusing on the scheduling procedure in both connectionless and connection-oriented communication. The models have been merged to provide a tool supporting the configuration design of BLE devices, during the network design phase that precedes the real implementation. The results highlight the suitability of the proposed tool: the ability to set the device parameters to allow us to keep a practical discovery latency for event-driven sensors and avoid undesired overlaps between scheduled scanning and connection phases due to bad management performed by the central node. PMID:28387724

Analysis and Tools for Improved Management of Connectionless and Connection-Oriented BLE Devices Coexistence.

PubMed

Del Campo, Antonio; Cintioni, Lorenzo; Spinsante, Susanna; Gambi, Ennio

2017-04-07

With the introduction of low-power wireless technologies, like Bluetooth Low Energy (BLE), new applications are approaching the home automation, healthcare, fitness, automotive and consumer electronics markets. BLE devices are designed to maximize the battery life, i.e., to run for long time on a single coin-cell battery. In typical application scenarios of home automation and Ambient Assisted Living (AAL), the sensors that monitor relatively unpredictable and rare events should coexist with other sensors that continuously communicate health or environmental parameter measurements. The former usually work in connectionless mode, acting as advertisers, while the latter need a persistent connection, acting as slave nodes. The coexistence of connectionless and connection-oriented networks, that share the same central node, can be required to reduce the number of handling devices, thus keeping the network complexity low and limiting the packet's traffic congestion. In this paper, the medium access management, operated by the central node, has been modeled, focusing on the scheduling procedure in both connectionless and connection-oriented communication. The models have been merged to provide a tool supporting the configuration design of BLE devices, during the network design phase that precedes the real implementation. The results highlight the suitability of the proposed tool: the ability to set the device parameters to allow us to keep a practical discovery latency for event-driven sensors and avoid undesired overlaps between scheduled scanning and connection phases due to bad management performed by the central node.

Exploring anti-community structure in networks with application to incompatibility of traditional Chinese medicine

NASA Astrophysics Data System (ADS)

Zhu, Jiajing; Liu, Yongguo; Zhang, Yun; Liu, Xiaofeng; Xiao, Yonghua; Wang, Shidong; Wu, Xindong

2017-11-01

Community structure is one of the most important properties in networks, in which a node shares its most connections with the others in the same community. On the contrary, the anti-community structure means the nodes in the same group have few or no connections with each other. In Traditional Chinese Medicine (TCM), the incompatibility problem of herbs is a challenge to the clinical medication safety. In this paper, we propose a new anti-community detection algorithm, Random non-nEighboring nOde expansioN (REON), to find anti-communities in networks, in which a new evaluation criterion, anti-modularity, is designed to measure the quality of the obtained anti-community structure. In order to establish anti-communities in REON, we expand the node set by non-neighboring node expansion and regard the node set with the highest anti-modularity as an anti-community. Inspired by the phenomenon that the node with higher degree has greater contribution to the anti-modularity, an improved algorithm called REONI is developed by expanding node set by the non-neighboring node with the maximum degree, which greatly enhances the efficiency of REON. Experiments on synthetic and real-world networks demonstrate the superiority of the proposed algorithms over the existing methods. In addition, by applying REONI to the herb network, we find that it can discover incompatible herb combinations.

Design of Deformation Monitoring System for Volcano Mitigation

NASA Astrophysics Data System (ADS)

Islamy, M. R. F.; Salam, R. A.; Munir, M. M.; Irsyam, M.; Khairurrijal

2016-08-01

Indonesia has many active volcanoes that are potentially disastrous. It needs good mitigation systems to prevent victims and to reduce casualties from potential disaster caused by volcanoes eruption. Therefore, the system to monitor the deformation of volcano was built. This system employed telemetry with the combination of Radio Frequency (RF) communications of XBEE and General Packet Radio Service (GPRS) communication of SIM900. There are two types of modules in this system, first is the coordinator as a parent and second is the node as a child. Each node was connected to coordinator forming a Wireless Sensor Network (WSN) with a star topology and it has an inclinometer based sensor, a Global Positioning System (GPS), and an XBEE module. The coordinator collects data to each node, one a time, to prevent collision data between nodes, save data to SD Card and transmit data to web server via GPRS. Inclinometer was calibrated with self-built in calibrator and tested in high temperature environment to check the durability. The GPS was tested by displaying its position in web server via Google Map Application Protocol Interface (API v.3). It was shown that the coordinator can receive and transmit data from every node to web server very well and the system works well in a high temperature environment.

STS-88 Crew Interview: Nancy Currie

NASA Technical Reports Server (NTRS)

1998-01-01

Nancy Currie discusses the seven-day mission that will be highlighted by the mating of the U.S.-built Node 1 station element to the Functional Energy Block (FGB) which will already be in orbit, and two spacewalks to connect power and data transmission cables between the Node and the FGB. Node 1 will be the first Space Station hardware delivered by the Space Shuttle. He also disscusses the assembly sequence. The crew will conduct a series of rendezvous maneuvers similar to those conducted on other Shuttle missions to reach the orbiting FGB. Once the two elements are docked, Ross and Newman will conduct two scheduled spacewalks to connect power and data cables between the Node, PMAs and the FGB. The day following the spacewalks, Endeavour will undock from the two components, completing the first Space Station assembly mission.

Reconfigureable network node

DOEpatents

Vanderveen, Keith B [Tracy, CA; Talbot, Edward B [Livermore, CA; Mayer, Laurence E [Davis, CA

2008-04-08

Nodes in a network having a plurality of nodes establish communication links with other nodes using available transmission media, as the ability to establish such links becomes available and desirable. The nodes predict when existing communications links will fail, become overloaded or otherwise degrade network effectiveness and act to establish substitute or additional links before the node's ability to communicate with the other nodes on the network is adversely affected. A node stores network topology information and programmed link establishment rules and criteria. The node evaluates characteristics that predict existing links with other nodes becoming unavailable or degraded. The node then determines whether it can form a communication link with a substitute node, in order to maintain connectivity with the network. When changing its communication links, a node broadcasts that information to the network. Other nodes update their stored topology information and consider the updated topology when establishing new communications links for themselves.

A Novel Energy Efficient Topology Control Scheme Based on a Coverage-Preserving and Sleep Scheduling Model for Sensor Networks

PubMed Central

Shi, Binbin; Wei, Wei; Wang, Yihuai; Shu, Wanneng

2016-01-01

In high-density sensor networks, scheduling some sensor nodes to be in the sleep mode while other sensor nodes remain active for monitoring or forwarding packets is an effective control scheme to conserve energy. In this paper, a Coverage-Preserving Control Scheduling Scheme (CPCSS) based on a cloud model and redundancy degree in sensor networks is proposed. Firstly, the normal cloud model is adopted for calculating the similarity degree between the sensor nodes in terms of their historical data, and then all nodes in each grid of the target area can be classified into several categories. Secondly, the redundancy degree of a node is calculated according to its sensing area being covered by the neighboring sensors. Finally, a centralized approximation algorithm based on the partition of the target area is designed to obtain the approximate minimum set of nodes, which can retain the sufficient coverage of the target region and ensure the connectivity of the network at the same time. The simulation results show that the proposed CPCSS can balance the energy consumption and optimize the coverage performance of the sensor network. PMID:27754405

A Novel Energy Efficient Topology Control Scheme Based on a Coverage-Preserving and Sleep Scheduling Model for Sensor Networks.

PubMed

Shi, Binbin; Wei, Wei; Wang, Yihuai; Shu, Wanneng

2016-10-14

In high-density sensor networks, scheduling some sensor nodes to be in the sleep mode while other sensor nodes remain active for monitoring or forwarding packets is an effective control scheme to conserve energy. In this paper, a Coverage-Preserving Control Scheduling Scheme (CPCSS) based on a cloud model and redundancy degree in sensor networks is proposed. Firstly, the normal cloud model is adopted for calculating the similarity degree between the sensor nodes in terms of their historical data, and then all nodes in each grid of the target area can be classified into several categories. Secondly, the redundancy degree of a node is calculated according to its sensing area being covered by the neighboring sensors. Finally, a centralized approximation algorithm based on the partition of the target area is designed to obtain the approximate minimum set of nodes, which can retain the sufficient coverage of the target region and ensure the connectivity of the network at the same time. The simulation results show that the proposed CPCSS can balance the energy consumption and optimize the coverage performance of the sensor network.

Modeling Dynamic Evolution of Online Friendship Network

NASA Astrophysics Data System (ADS)

Wu, Lian-Ren; Yan, Qiang

2012-10-01

In this paper, we study the dynamic evolution of friendship network in SNS (Social Networking Site). Our analysis suggests that an individual joining a community depends not only on the number of friends he or she has within the community, but also on the friendship network generated by those friends. In addition, we propose a model which is based on two processes: first, connecting nearest neighbors; second, strength driven attachment mechanism. The model reflects two facts: first, in the social network it is a universal phenomenon that two nodes are connected when they have at least one common neighbor; second, new nodes connect more likely to nodes which have larger weights and interactions, a phenomenon called strength driven attachment (also called weight driven attachment). From the simulation results, we find that degree distribution P(k), strength distribution P(s), and degree-strength correlation are all consistent with empirical data.

KENNEDY SPACE CENTER, FLA. - An overhead crane in the Space Station Processing Facility lifts the U.S. Node 2 out of its shipping container. The node will be moved to a workstand. The second of three connecting modules on the International Space Station, the Italian-built Node 2 attaches to the end of the U.S. Lab and provides attach locations for the Japanese laboratory, European laboratory, the Centrifuge Accommodation Module and, later, Multipurpose Logistics Modules. It will provide the primary docking location for the Shuttle when a pressurized mating adapter is attached to Node 2. Installation of the module will complete the U.S. Core of the ISS. Node 2 is the designated payload for mission STS-120. No orbiter or launch date has been determined yet.

NASA Image and Video Library

2003-06-03

KENNEDY SPACE CENTER, FLA. - An overhead crane in the Space Station Processing Facility lifts the U.S. Node 2 out of its shipping container. The node will be moved to a workstand. The second of three connecting modules on the International Space Station, the Italian-built Node 2 attaches to the end of the U.S. Lab and provides attach locations for the Japanese laboratory, European laboratory, the Centrifuge Accommodation Module and, later, Multipurpose Logistics Modules. It will provide the primary docking location for the Shuttle when a pressurized mating adapter is attached to Node 2. Installation of the module will complete the U.S. Core of the ISS. Node 2 is the designated payload for mission STS-120. No orbiter or launch date has been determined yet.

Anatomical and neurohistological observations on the heart of the rose ringed parakeet, Psittacula krameri.

PubMed

Qayyum, M A; Shaad, F U

1976-01-01

Anatomy, histology and innervation of the heart of the rose ringed parakeet, Psittacula krameri have been studied in the present investigation. The sinuatrial node is found to be well-developed. It is located towards the right side of the cephalic end of the interatrial septum and composed of a few nucleated cells and a large fibrous mass. The atrioventricular node is poorly defined, present at the caudal end of the interatrial septum. The node is somewhat triangular in shape and is composed of elongated and multinucleated specialized fibres. The node is not covered by any connective tissue sheath. The poor development of the atrio ventricular node and the absence of any sheath around it may be correlated with the fast rate of the heart beat. The atrioventricular bundle is observed at the cephalic end of the interventricular septum. A branch from the right limb of the atrioventricular bundle is noted to pass directly into the right atrioventricular valve. The heart is richly innervated. Ganglion cells along with nerve fibres have been observed at the sulcus terminalis and the atrioventricular junction. A direct nervous connection could be observed between the sinuatrial and atrioventricular nodes. It is argued that the impulse which originates in the sinuatrial node would reach the atrioventricular node through the unspecialized muscle fibres and nerve fibres of the interatrial septum. Nerve cells could not be traced in the substance of the sinuatrial node, atrioventricular node and atrioventricular bundle.

Masked Proportional Routing

NASA Technical Reports Server (NTRS)

Wolpert, David H. (Inventor)

2003-01-01

Distributed approach for determining a path connecting adjacent network nodes, for probabilistically or deterministically transporting an entity, with entity characteristic mu from a source node to a destination node. Each node i is directly connected to an arbitrary number J(mu) of nodes, labeled or numbered j=jl, j2, .... jJ(mu). In a deterministic version, a J(mu)-component baseline proportion vector p(i;mu) is associated with node i. A J(mu)-component applied proportion vector p*(i;mu) is determined from p(i;mu) to preclude an entity visiting a node more than once. Third and fourth J(mu)-component vectors, with components iteratively determined by Target(i;n(mu);mu),=alpha(mu).Target(i;n(mu)-1;mu)j+beta(mu).p* (i;mu)j and Actual(i;n(mu);+a(mu)j. Actual(i;n(mu)-l;mu)j+beta(mu).Sent(i;j'(mu);n(mu)-1;mu)j, are computed, where n(mu) is an entity sequence index and alpha(mu) and beta(mu) are selected numbers. In one embodiment, at each node i, the node j=j'(mu) with the largest vector component difference, Target(i;n(mu);mu)j'- Actual (i;n(mu);mu)j'. is chosen for the next link for entity transport, except in special gap circumstances, where the same link is optionally used for transporting consecutively arriving entities. The network nodes may be computer-controlled routers that switch collections of packets, frames, cells or other information units. Alternatively, the nodes may be waypoints for movement of physical items in a network or for transformation of a physical item. The nodes may be states of an entity undergoing state transitions, where allowed transitions are specified by the network and/or the destination node.

Multimodal investigation of triple network connectivity in patients with 22q11DS and association with executive functions.

PubMed

Padula, Maria C; Schaer, Marie; Scariati, Elisa; Maeder, Johanna; Schneider, Maude; Eliez, Stephan

2017-04-01

Large-scale brain networks play a prominent role in cognitive abilities and their activity is impaired in psychiatric disorders, such as schizophrenia. Patients with 22q11.2 deletion syndrome (22q11DS) are at high risk of developing schizophrenia and present similar cognitive impairments, including executive functions deficits. Thus, 22q11DS represents a model for the study of neural biomarkers associated with schizophrenia. In this study, we investigated structural and functional connectivity within and between the Default Mode (DMN), the Central Executive (CEN), and the Saliency network (SN) in 22q11DS using resting-state fMRI and DTI. Furthermore, we investigated if triple network impairments were related to executive dysfunctions or the presence of psychotic symptoms. Sixty-three patients with 22q11DS and sixty-eighty controls (age 6-33 years) were included in the study. Structural connectivity between main nodes of DMN, CEN, and SN was computed using probabilistic tractography. Functional connectivity was computed as the partial correlation between the time courses extracted from each node. Structural and functional connectivity measures were then correlated to executive functions and psychotic symptom scores. Our results showed mainly reduced structural connectivity within the CEN, DMN, and SN, in patients with 22q11DS compared with controls as well as reduced between-network connectivity. Functional connectivity appeared to be more preserved, with impairments being evident only within the DMN. Structural connectivity impairments were also related to executive dysfunctions. These findings show an association between triple network structural alterations and executive deficits in patients with the microdeletion, suggesting that 22q11DS and schizophrenia share common psychopathological mechanisms. Hum Brain Mapp 38:2177-2189, 2017. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Configuring compute nodes of a parallel computer in an operational group into a plurality of independent non-overlapping collective networks

DOEpatents

Archer, Charles J.; Inglett, Todd A.; Ratterman, Joseph D.; Smith, Brian E.

2010-03-02

Methods, apparatus, and products are disclosed for configuring compute nodes of a parallel computer in an operational group into a plurality of independent non-overlapping collective networks, the compute nodes in the operational group connected together for data communications through a global combining network, that include: partitioning the compute nodes in the operational group into a plurality of non-overlapping subgroups; designating one compute node from each of the non-overlapping subgroups as a master node; and assigning, to the compute nodes in each of the non-overlapping subgroups, class routing instructions that organize the compute nodes in that non-overlapping subgroup as a collective network such that the master node is a physical root.

Adaptive triangular mesh generation

NASA Technical Reports Server (NTRS)

Erlebacher, G.; Eiseman, P. R.

1984-01-01

A general adaptive grid algorithm is developed on triangular grids. The adaptivity is provided by a combination of node addition, dynamic node connectivity and a simple node movement strategy. While the local restructuring process and the node addition mechanism take place in the physical plane, the nodes are displaced on a monitor surface, constructed from the salient features of the physical problem. An approximation to mean curvature detects changes in the direction of the monitor surface, and provides the pulling force on the nodes. Solutions to the axisymmetric Grad-Shafranov equation demonstrate the capturing, by triangles, of the plasma-vacuum interface in a free-boundary equilibrium configuration.

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

Rodenbeck, Christopher T; Girardi, Michael

Internal nodes of a constituent integrated circuit (IC) package of a multichip module (MCM) are protected from excessive charge during plasma cleaning of the MCM. The protected nodes are coupled to an internal common node of the IC package by respectively associated discharge paths. The common node is connected to a bond pad of the IC package. During MCM assembly, and before plasma cleaning, this bond pad receives a wire bond to a ground bond pad on the MCM substrate.

Systematic network assessment of the carcinogenic activities of cadmium

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

Chen, Peizhan; Duan, Xiaohua; Li, Mian

Cadmium has been defined as type I carcinogen for humans, but the underlying mechanisms of its carcinogenic activity and its influence on protein-protein interactions in cells are not fully elucidated. The aim of the current study was to evaluate, systematically, the carcinogenic activity of cadmium with systems biology approaches. From a literature search of 209 studies that performed with cellular models, 208 proteins influenced by cadmium exposure were identified. All of these were assessed by Western blotting and were recognized as key nodes in network analyses. The protein-protein functional interaction networks were constructed with NetBox software and visualized with Cytoscapemore » software. These cadmium-rewired genes were used to construct a scale-free, highly connected biological protein interaction network with 850 nodes and 8770 edges. Of the network, nine key modules were identified and 60 key signaling pathways, including the estrogen, RAS, PI3K-Akt, NF-κB, HIF-1α, Jak-STAT, and TGF-β signaling pathways, were significantly enriched. With breast cancer, colorectal and prostate cancer cellular models, we validated the key node genes in the network that had been previously reported or inferred form the network by Western blotting methods, including STAT3, JNK, p38, SMAD2/3, P65, AKT1, and HIF-1α. These results suggested the established network was robust and provided a systematic view of the carcinogenic activities of cadmium in human. - Highlights: • A cadmium-influenced network with 850 nodes and 8770 edges was established. • The cadmium-rewired gene network was scale-free and highly connected. • Nine modules were identified, and 60 key signaling pathways related to cadmium-induced carcinogenesis were found. • Key mediators in the network were validated in multiple cellular models.« less

Cell boundary fault detection system

DOEpatents

Archer, Charles Jens [Rochester, MN; Pinnow, Kurt Walter [Rochester, MN; Ratterman, Joseph D [Rochester, MN; Smith, Brian Edward [Rochester, MN

2009-05-05

A method determines a nodal fault along the boundary, or face, of a computing cell. Nodes on adjacent cell boundaries communicate with each other, and the communications are analyzed to determine if a node or connection is faulty.

Cascading failures in complex networks with community structure

NASA Astrophysics Data System (ADS)

Lin, Guoqiang; di, Zengru; Fan, Ying

2014-12-01

Much empirical evidence shows that when attacked with cascading failures, scale-free or even random networks tend to collapse more extensively when the initially deleted node has higher betweenness. Meanwhile, in networks with strong community structure, high-betweenness nodes tend to be bridge nodes that link different communities, and the removal of such nodes will reduce only the connections among communities, leaving the networks fairly stable. Understanding what will affect cascading failures and how to protect or attack networks with strong community structure is therefore of interest. In this paper, we have constructed scale-free Community Networks (SFCN) and Random Community Networks (RCN). We applied these networks, along with the Lancichinett-Fortunato-Radicchi (LFR) benchmark, to the cascading-failure scenario to explore their vulnerability to attack and the relationship between cascading failures and the degree distribution and community structure of a network. The numerical results show that when the networks are of a power-law distribution, a stronger community structure will result in the failure of fewer nodes. In addition, the initial removal of the node with the highest betweenness will not lead to the worst cascading, i.e. the largest avalanche size. The Betweenness Overflow (BOF), an index that we developed, is an effective indicator of this tendency. The RCN, however, display a different result. In addition, the avalanche size of each node can be adopted as an index to evaluate the importance of the node.

Efficient Actor Recovery Paradigm for Wireless Sensor and Actor Networks

PubMed Central

Mahjoub, Reem K.; Elleithy, Khaled

2017-01-01

The actor nodes are the spine of wireless sensor and actor networks (WSANs) that collaborate to perform a specific task in an unverified and uneven environment. Thus, there is a possibility of high failure rate in such unfriendly scenarios due to several factors such as power consumption of devices, electronic circuit failure, software errors in nodes or physical impairment of the actor nodes and inter-actor connectivity problem. Therefore, it is extremely important to discover the failure of a cut-vertex actor and network-disjoint in order to improve the Quality-of-Service (QoS). In this paper, we propose an Efficient Actor Recovery (EAR) paradigm to guarantee the contention-free traffic-forwarding capacity. The EAR paradigm consists of a Node Monitoring and Critical Node Detection (NMCND) algorithm that monitors the activities of the nodes to determine the critical node. In addition, it replaces the critical node with backup node prior to complete node-failure which helps balancing the network performance. The packets are handled using Network Integration and Message Forwarding (NIMF) algorithm that determines the source of forwarding the packets; either from actor or sensor. This decision-making capability of the algorithm controls the packet forwarding rate to maintain the network for a longer time. Furthermore, for handling the proper routing strategy, Priority-Based Routing for Node Failure Avoidance (PRNFA) algorithm is deployed to decide the priority of the packets to be forwarded based on the significance of information available in the packet. To validate the effectiveness of the proposed EAR paradigm, the proposed algorithms were tested using OMNET++ simulation. PMID:28420102

Efficient Actor Recovery Paradigm for Wireless Sensor and Actor Networks.

PubMed

Mahjoub, Reem K; Elleithy, Khaled

2017-04-14

The actor nodes are the spine of wireless sensor and actor networks (WSANs) that collaborate to perform a specific task in an unverified and uneven environment. Thus, there is a possibility of high failure rate in such unfriendly scenarios due to several factors such as power consumption of devices, electronic circuit failure, software errors in nodes or physical impairment of the actor nodes and inter-actor connectivity problem. Therefore, it is extremely important to discover the failure of a cut-vertex actor and network-disjoint in order to improve the Quality-of-Service (QoS). In this paper, we propose an Efficient Actor Recovery (EAR) paradigm to guarantee the contention-free traffic-forwarding capacity. The EAR paradigm consists of a Node Monitoring and Critical Node Detection (NMCND) algorithm that monitors the activities of the nodes to determine the critical node. In addition, it replaces the critical node with backup node prior to complete node-failure which helps balancing the network performance. The packets are handled using Network Integration and Message Forwarding (NIMF) algorithm that determines the source of forwarding the packets; either from actor or sensor. This decision-making capability of the algorithm controls the packet forwarding rate to maintain the network for a longer time. Furthermore, for handling the proper routing strategy, Priority-Based Routing for Node Failure Avoidance (PRNFA) algorithm is deployed to decide the priority of the packets to be forwarded based on the significance of information available in the packet. To validate the effectiveness of the proposed EAR paradigm, the proposed algorithms were tested using OMNET++ simulation.

Reliable appropriate topology design for multiple-processor systems

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

Chou, C.P.

1987-01-01

A Shift and Replace Graph which is a very appropriate candidate for the topology of a multiple-processor system is a function of two positive integers r and m, and is denoted as SRF(r,m). Pradhan and Reddy proved that the node connectivity of SRG(r,m) is at least r and also give a routing algorithm which generally requires 2m jumps if the number of node failures is no larger than r - 1. Later, Esfahanian and Hakimi proved that SRG(r,m) has maximum node connectivity 2r - 2 and give routing algorithms which require: (1) at most m + 3 + log/sub r/mmore » jumps if 3 + log/sub r/m does not exceed m and the number of node failures is at most r - 1; (2) at most m + 5 + log/sub r/m jumps if 4 + log/sub r/m less than or equal to m and the number of node failures if less than or equal to 2r - 3; (3) all the other situations require no more than 2m jumps. By modifying the SRG(r,m), it is first proved that node connectivity of SRG(r,m) can be increased to: (1) 2r - 1 when r = 2, m = 2, and (2) 2r when (r = 2, m > 2) or (r > 2, m greater than or equal to 2, m greater than or equal to 2). The routing algorithms are also given for the modified SRG (r,m), which require at most 2m + 3 jumps when the number of node failures is less than or equal to 2r - 1.« less

Intelligent self-organization methods for wireless ad hoc sensor networks based on limited resources

NASA Astrophysics Data System (ADS)

Hortos, William S.

2006-05-01

A wireless ad hoc sensor network (WSN) is a configuration for area surveillance that affords rapid, flexible deployment in arbitrary threat environments. There is no infrastructure support and sensor nodes communicate with each other only when they are in transmission range. To a greater degree than the terminals found in mobile ad hoc networks (MANETs) for communications, sensor nodes are resource-constrained, with limited computational processing, bandwidth, memory, and power, and are typically unattended once in operation. Consequently, the level of information exchange among nodes, to support any complex adaptive algorithms to establish network connectivity and optimize throughput, not only deplete those limited resources and creates high overhead in narrowband communications, but also increase network vulnerability to eavesdropping by malicious nodes. Cooperation among nodes, critical to the mission of sensor networks, can thus be disrupted by the inappropriate choice of the method for self-organization. Recent published contributions to the self-configuration of ad hoc sensor networks, e.g., self-organizing mapping and swarm intelligence techniques, have been based on the adaptive control of the cross-layer interactions found in MANET protocols to achieve one or more performance objectives: connectivity, intrusion resistance, power control, throughput, and delay. However, few studies have examined the performance of these algorithms when implemented with the limited resources of WSNs. In this paper, self-organization algorithms for the initiation, operation and maintenance of a network topology from a collection of wireless sensor nodes are proposed that improve the performance metrics significant to WSNs. The intelligent algorithm approach emphasizes low computational complexity, energy efficiency and robust adaptation to change, allowing distributed implementation with the actual limited resources of the cooperative nodes of the network. Extensions of the algorithms from flat topologies to two-tier hierarchies of sensor nodes are presented. Results from a few simulations of the proposed algorithms are compared to the published results of other approaches to sensor network self-organization in common scenarios. The estimated network lifetime and extent under static resource allocations are computed.

Finding Minimum-Power Broadcast Trees for Wireless Networks

NASA Technical Reports Server (NTRS)

Arabshahi, Payman; Gray, Andrew; Das, Arindam; El-Sharkawi, Mohamed; Marks, Robert, II

2004-01-01

Some algorithms have been devised for use in a method of constructing tree graphs that represent connections among the nodes of a wireless communication network. These algorithms provide for determining the viability of any given candidate connection tree and for generating an initial set of viable trees that can be used in any of a variety of search algorithms (e.g., a genetic algorithm) to find a tree that enables the network to broadcast from a source node to all other nodes while consuming the minimum amount of total power. The method yields solutions better than those of a prior algorithm known as the broadcast incremental power algorithm, albeit at a slightly greater computational cost.

Resilient Wireless Sensor Networks Using Topology Control: A Review

PubMed Central

Huang, Yuanjiang; Martínez, José-Fernán; Sendra, Juana; López, Lourdes

2015-01-01

Wireless sensor networks (WSNs) may be deployed in failure-prone environments, and WSNs nodes easily fail due to unreliable wireless connections, malicious attacks and resource-constrained features. Nevertheless, if WSNs can tolerate at most losing k − 1 nodes while the rest of nodes remain connected, the network is called k − connected. k is one of the most important indicators for WSNs’ self-healing capability. Following a WSN design flow, this paper surveys resilience issues from the topology control and multi-path routing point of view. This paper provides a discussion on transmission and failure models, which have an important impact on research results. Afterwards, this paper reviews theoretical results and representative topology control approaches to guarantee WSNs to be k − connected at three different network deployment stages: pre-deployment, post-deployment and re-deployment. Multi-path routing protocols are discussed, and many NP-complete or NP-hard problems regarding topology control are identified. The challenging open issues are discussed at the end. This paper can serve as a guideline to design resilient WSNs. PMID:26404272

Representation of activity in images using geospatial temporal graphs

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

Brost, Randolph; McLendon, III, William C.; Parekh, Ojas D.

Various technologies pertaining to modeling patterns of activity observed in remote sensing images using geospatial-temporal graphs are described herein. Graphs are constructed by representing objects in remote sensing images as nodes, and connecting nodes with undirected edges representing either distance or adjacency relationships between objects and directed edges representing changes in time. Activity patterns may be discerned from the graphs by coding nodes representing persistent objects like buildings differently from nodes representing ephemeral objects like vehicles, and examining the geospatial-temporal relationships of ephemeral nodes within the graph.

High definition infrared spectroscopic imaging for lymph node histopathology.

PubMed

Leslie, L Suzanne; Wrobel, Tomasz P; Mayerich, David; Bindra, Snehal; Emmadi, Rajyasree; Bhargava, Rohit

2015-01-01

Chemical imaging is a rapidly emerging field in which molecular information within samples can be used to predict biological function and recognize disease without the use of stains or manual identification. In Fourier transform infrared (FT-IR) spectroscopic imaging, molecular absorption contrast provides a large signal relative to noise. Due to the long mid-IR wavelengths and sub-optimal instrument design, however, pixel sizes have historically been much larger than cells. This limits both the accuracy of the technique in identifying small regions, as well as the ability to visualize single cells. Here we obtain data with micron-sized sampling using a tabletop FT-IR instrument, and demonstrate that the high-definition (HD) data lead to accurate identification of multiple cells in lymph nodes that was not previously possible. Highly accurate recognition of eight distinct classes - naïve and memory B cells, T cells, erythrocytes, connective tissue, fibrovascular network, smooth muscle, and light and dark zone activated B cells was achieved in healthy, reactive, and malignant lymph node biopsies using a random forest classifier. The results demonstrate that cells currently identifiable only through immunohistochemical stains and cumbersome manual recognition of optical microscopy images can now be distinguished to a similar level through a single IR spectroscopic image from a lymph node biopsy.

Network biology discovers pathogen contact points in host protein-protein interactomes.

PubMed

Ahmed, Hadia; Howton, T C; Sun, Yali; Weinberger, Natascha; Belkhadir, Youssef; Mukhtar, M Shahid

2018-06-13

In all organisms, major biological processes are controlled by complex protein-protein interactions networks (interactomes), yet their structural complexity presents major analytical challenges. Here, we integrate a compendium of over 4300 phenotypes with Arabidopsis interactome (AI-1 MAIN ). We show that nodes with high connectivity and betweenness are enriched and depleted in conditional and essential phenotypes, respectively. Such nodes are located in the innermost layers of AI-1 MAIN and are preferential targets of pathogen effectors. We extend these network-centric analyses to Cell Surface Interactome (CSI LRR ) and predict its 35 most influential nodes. To determine their biological relevance, we show that these proteins physically interact with pathogen effectors and modulate plant immunity. Overall, our findings contrast with centrality-lethality rule, discover fast information spreading nodes, and highlight the structural properties of pathogen targets in two different interactomes. Finally, this theoretical framework could possibly be applicable to other inter-species interactomes to reveal pathogen contact points.

Mechanical end joint system for structural column elements

NASA Technical Reports Server (NTRS)

Bush, H. G.; Wallsom, R. E. (Inventor)

1982-01-01

A mechanical end joint system, useful for the transverse connection of strut elements to a common node, comprises a node joint half with a semicircular tongue and groove, and a strut joint half with a semicircular tongue and groove. The two joint halves are engaged transversely and the connection is made secure by the inherent physical property characteristics of locking latches and/or by a spring-actioned shaft. A quick release mechanism provides rapid disengagement of the joint halves.

Disruptions of brain structural network in end-stage renal disease patients with long-term hemodialysis and normal-appearing brain tissues.

PubMed

Chou, Ming-Chung; Ko, Chih-Hung; Chang, Jer-Ming; Hsieh, Tsyh-Jyi

2018-05-04

End-stage renal disease (ESRD) patients on hemodialysis were demonstrated to exhibit silent and invisible white-matter alterations which would likely lead to disruptions of brain structural networks. Therefore, the purpose of this study was to investigate the disruptions of brain structural network in ESRD patients. Thiry-three ESRD patients with normal-appearing brain tissues and 29 age- and gender-matched healthy controls were enrolled in this study and underwent both cognitive ability screening instrument (CASI) assessment and diffusion tensor imaging (DTI) acquisition. Brain structural connectivity network was constructed using probabilistic tractography with automatic anatomical labeling template. Graph-theory analysis was performed to detect the alterations of node-strength, node-degree, node-local efficiency, and node-clustering coefficient in ESRD patients. Correlational analysis was performed to understand the relationship between network measures, CASI score, and dialysis duration. Structural connectivity, node-strength, node-degree, and node-local efficiency were significantly decreased, whereas node-clustering coefficient was significantly increased in ESRD patients as compared with healthy controls. The disrupted local structural networks were generally associated with common neurological complications of ESRD patients, but the correlational analysis did not reveal significant correlation between network measures, CASI score, and dialysis duration. Graph-theory analysis was helpful to investigate disruptions of brain structural network in ESRD patients with normal-appearing brain tissues. Copyright © 2018. Published by Elsevier Masson SAS.

Coarse-graining and self-dissimilarity of complex networks

NASA Astrophysics Data System (ADS)

Itzkovitz, Shalev; Levitt, Reuven; Kashtan, Nadav; Milo, Ron; Itzkovitz, Michael; Alon, Uri

2005-01-01

Can complex engineered and biological networks be coarse-grained into smaller and more understandable versions in which each node represents an entire pattern in the original network? To address this, we define coarse-graining units as connectivity patterns which can serve as the nodes of a coarse-grained network and present algorithms to detect them. We use this approach to systematically reverse-engineer electronic circuits, forming understandable high-level maps from incomprehensible transistor wiring: first, a coarse-grained version in which each node is a gate made of several transistors is established. Then the coarse-grained network is itself coarse-grained, resulting in a high-level blueprint in which each node is a circuit module made of many gates. We apply our approach also to a mammalian protein signal-transduction network, to find a simplified coarse-grained network with three main signaling channels that resemble multi-layered perceptrons made of cross-interacting MAP-kinase cascades. We find that both biological and electronic networks are “self-dissimilar,” with different network motifs at each level. The present approach may be used to simplify a variety of directed and nondirected, natural and designed networks.

Random Time Identity Based Firewall In Mobile Ad hoc Networks

NASA Astrophysics Data System (ADS)

Suman, Patel, R. B.; Singh, Parvinder

2010-11-01

A mobile ad hoc network (MANET) is a self-organizing network of mobile routers and associated hosts connected by wireless links. MANETs are highly flexible and adaptable but at the same time are highly prone to security risks due to the open medium, dynamically changing network topology, cooperative algorithms, and lack of centralized control. Firewall is an effective means of protecting a local network from network-based security threats and forms a key component in MANET security architecture. This paper presents a review of firewall implementation techniques in MANETs and their relative merits and demerits. A new approach is proposed to select MANET nodes at random for firewall implementation. This approach randomly select a new node as firewall after fixed time and based on critical value of certain parameters like power backup. This approach effectively balances power and resource utilization of entire MANET because responsibility of implementing firewall is equally shared among all the nodes. At the same time it ensures improved security for MANETs from outside attacks as intruder will not be able to find out the entry point in MANET due to the random selection of nodes for firewall implementation.

KENNEDY SPACE CENTER, FLA. - STS-120 Mission Specialists Piers Sellers and Michael Foreman are in the Space Station Processing Facility for hardware familiarization. The mission will deliver the second of three Station connecting modules, Node 2, which attaches to the end of U.S. Lab. It will provide attach locations for the Japanese laboratory, European laboratory, the Centrifuge Accommodation Module and later Multi-Purpose Logistics Modules. The addition of Node 2 will complete the U.S. core of the International Space Station.

NASA Image and Video Library

2003-07-18

KENNEDY SPACE CENTER, FLA. - STS-120 Mission Specialists Piers Sellers and Michael Foreman are in the Space Station Processing Facility for hardware familiarization. The mission will deliver the second of three Station connecting modules, Node 2, which attaches to the end of U.S. Lab. It will provide attach locations for the Japanese laboratory, European laboratory, the Centrifuge Accommodation Module and later Multi-Purpose Logistics Modules. The addition of Node 2 will complete the U.S. core of the International Space Station.

Multinode reconfigurable pipeline computer

NASA Technical Reports Server (NTRS)

Nosenchuck, Daniel M. (Inventor); Littman, Michael G. (Inventor)

1989-01-01

A multinode parallel-processing computer is made up of a plurality of innerconnected, large capacity nodes each including a reconfigurable pipeline of functional units such as Integer Arithmetic Logic Processors, Floating Point Arithmetic Processors, Special Purpose Processors, etc. The reconfigurable pipeline of each node is connected to a multiplane memory by a Memory-ALU switch NETwork (MASNET). The reconfigurable pipeline includes three (3) basic substructures formed from functional units which have been found to be sufficient to perform the bulk of all calculations. The MASNET controls the flow of signals from the memory planes to the reconfigurable pipeline and vice versa. the nodes are connectable together by an internode data router (hyperspace router) so as to form a hypercube configuration. The capability of the nodes to conditionally configure the pipeline at each tick of the clock, without requiring a pipeline flush, permits many powerful algorithms to be implemented directly.

Analysis of Handoff Mechanisms in Mobile IP

NASA Astrophysics Data System (ADS)

Jayaraj, Maria Nadine Simonel; Issac, Biju; Haldar, Manas Kumar

2011-06-01

One of the most important challenges in mobile Internet Protocol (IP) is to provide service for a mobile node to maintain its connectivity to network when it moves from one domain to another. IP is responsible for routing packets across network. The first major version of IP is the Internet Protocol version 4 (IPv4). It is one of the dominant protocols relevant to wireless network. Later a newer version of IP called the IPv6 was proposed. Mobile IPv6 is mainly introduced for the purpose of mobility. Mobility management enables network to locate roaming nodes in order to deliver packets and maintain connections with them when moving into new domains. Handoff occurs when a mobile node moves from one network to another. It is a key factor of mobility because a mobile node can trigger several handoffs during a session. This paper briefly explains on mobile IP and its handoff issues, along with the drawbacks of mobile IP.

Analysis of Network Vulnerability Under Joint Node and Link Attacks

NASA Astrophysics Data System (ADS)

Li, Yongcheng; Liu, Shumei; Yu, Yao; Cao, Ting

2018-03-01

The security problem of computer network system is becoming more and more serious. The fundamental reason is that there are security vulnerabilities in the network system. Therefore, it’s very important to identify and reduce or eliminate these vulnerabilities before they are attacked. In this paper, we are interested in joint node and link attacks and propose a vulnerability evaluation method based on the overall connectivity of the network to defense this attack. Especially, we analyze the attack cost problem from the attackers’ perspective. The purpose is to find the set of least costs for joint links and nodes, and their deletion will lead to serious network connection damage. The simulation results show that the vulnerable elements obtained from the proposed method are more suitable for the attacking idea of the malicious persons in joint node and link attack. It is easy to find that the proposed method has more realistic protection significance.

Constrained Low-Interference Relay Node Deployment for Underwater Acoustic Wireless Sensor Networks

NASA Astrophysics Data System (ADS)

Li, Deying; Li, Zheng; Ma, Wenkai; Chen, Wenping

An Underwater Acoustic Wireless Sensor Network (UA-WSN) consists of many resource-constrained Underwater Sensor Nodes (USNs), which are deployed to perform collaborative monitoring tasks over a given region. One way to preserve network connectivity while guaranteing other network QoS is to deploy some Relay Nodes (RNs) in the networks, in which RNs' function is more powerful than USNs and their cost is more expensive. This paper addresses Constrained Low-interference Relay Node Deployment (C-LRND) problem for 3-D UA-WSNs in which the RNs are placed at a subset of candidate locations to ensure connectivity between the USNs, under both the number of RNs deployed and the value of total incremental interference constraints. We first prove that it is NP-hard, then present a general approximation algorithm framework and get two polynomial time O(1)-approximation algorithms.

Quantitative methods of identifying the key nodes in the illegal wildlife trade network

PubMed Central

Patel, Nikkita Gunvant; Rorres, Chris; Joly, Damien O.; Brownstein, John S.; Boston, Ray; Levy, Michael Z.; Smith, Gary

2015-01-01

Innovative approaches are needed to combat the illegal trade in wildlife. Here, we used network analysis and a new database, HealthMap Wildlife Trade, to identify the key nodes (countries) that support the illegal wildlife trade. We identified key exporters and importers from the number of shipments a country sent and received and from the number of connections a country had to other countries over a given time period. We used flow betweenness centrality measurements to identify key intermediary countries. We found the set of nodes whose removal from the network would cause the maximum disruption to the network. Selecting six nodes would fragment 89.5% of the network for elephants, 92.3% for rhinoceros, and 98.1% for tigers. We then found sets of nodes that would best disseminate an educational message via direct connections through the network. We would need to select 18 nodes to reach 100% of the elephant trade network, 16 nodes for rhinoceros, and 10 for tigers. Although the choice of locations for interventions should be customized for the animal and the goal of the intervention, China was the most frequently selected country for network fragmentation and information dissemination. Identification of key countries will help strategize illegal wildlife trade interventions. PMID:26080413

KSC-07pd0644

NASA Image and Video Library

2007-03-15

KENNEDY SPACE CENTER, FLA. -- NASA Node 2 module sits inside the Space Station Processing Facility highbay with its new name, Harmony, revealed. The name, Harmony, was chosen from an academic competition involving thousands of students in kindergarten through high school. The Node 2 Challenge required students to learn about the International Space Station, build a scale model of the module, and write an essay explaining their proposed name. This will be the first U.S. piece of the space station named by someone other than a NASA official. Node 2 is a pressurized module that will act as a connecting port and passageway to additional international science labs and supply spacecraft. It also will be a work platform for the station's robotic arm. The module is scheduled to fly on mission STS-120 aboard Space Shuttle Atlantis targeted for later this year. Photo credit: NASA/Jim Grossmann

International Space Station Node 1 is moved for leak test

NASA Technical Reports Server (NTRS)

1998-01-01

Node 1, the first element for the International Space Station, and attached Pressurized Mating Adapter-1 continue with prelaunch preparation activities at KSC's Space Station Processing Facility. Node 1 is a connecting passageway to the living and working areas of the space station. The node is being removed from the element rotation stand, or test stand, where it underwent an interim weight and center of gravity determination. (The final determination is planned to be performed prior to transporting Node 1 to the launch pad.) Now the node is being moved to the Shuttle payload transportation canister, where the doors will be closed for a two-week leak check. Node 1 is scheduled to fly on STS-88.

Suppressing epidemics on networks by exploiting observer nodes.

PubMed

Takaguchi, Taro; Hasegawa, Takehisa; Yoshida, Yuichi

2014-07-01

To control infection spreading on networks, we investigate the effect of observer nodes that recognize infection in a neighboring node and make the rest of the neighbor nodes immune. We numerically show that random placement of observer nodes works better on networks with clustering than on locally treelike networks, implying that our model is promising for realistic social networks. The efficiency of several heuristic schemes for observer placement is also examined for synthetic and empirical networks. In parallel with numerical simulations of epidemic dynamics, we also show that the effect of observer placement can be assessed by the size of the largest connected component of networks remaining after removing observer nodes and links between their neighboring nodes.

Suppressing epidemics on networks by exploiting observer nodes

NASA Astrophysics Data System (ADS)

Takaguchi, Taro; Hasegawa, Takehisa; Yoshida, Yuichi

2014-07-01

To control infection spreading on networks, we investigate the effect of observer nodes that recognize infection in a neighboring node and make the rest of the neighbor nodes immune. We numerically show that random placement of observer nodes works better on networks with clustering than on locally treelike networks, implying that our model is promising for realistic social networks. The efficiency of several heuristic schemes for observer placement is also examined for synthetic and empirical networks. In parallel with numerical simulations of epidemic dynamics, we also show that the effect of observer placement can be assessed by the size of the largest connected component of networks remaining after removing observer nodes and links between their neighboring nodes.

Network analysis of functional brain connectivity in borderline personality disorder using resting-state fMRI

PubMed Central

Xu, Tingting; Cullen, Kathryn R.; Mueller, Bryon; Schreiner, Mindy W.; Lim, Kelvin O.; Schulz, S. Charles; Parhi, Keshab K.

2016-01-01

Borderline personality disorder (BPD) is associated with symptoms such as affect dysregulation, impaired sense of self, and self-harm behaviors. Neuroimaging research on BPD has revealed structural and functional abnormalities in specific brain regions and connections. However, little is known about the topological organizations of brain networks in BPD. We collected resting-state functional magnetic resonance imaging (fMRI) data from 20 patients with BPD and 10 healthy controls, and constructed frequency-specific functional brain networks by correlating wavelet-filtered fMRI signals from 82 cortical and subcortical regions. We employed graph-theory based complex network analysis to investigate the topological properties of the brain networks, and employed network-based statistic to identify functional dysconnections in patients. In the 0.03–0.06 Hz frequency band, compared to controls, patients with BPD showed significantly larger measures of global network topology, including the size of largest connected graph component, clustering coefficient, small-worldness, and local efficiency, indicating increased local cliquishness of the functional brain network. Compared to controls, patients showed lower nodal centrality at several hub nodes but greater centrality at several non-hub nodes in the network. Furthermore, an interconnected subnetwork in 0.03–0.06 Hz frequency band was identified that showed significantly lower connectivity in patients. The links in the subnetwork were mainly long-distance connections between regions located at different lobes; and the mean connectivity of this subnetwork was negatively correlated with the increased global topology measures. Lastly, the key network measures showed high correlations with several clinical symptom scores, and classified BPD patients against healthy controls with high accuracy based on linear discriminant analysis. The abnormal topological properties and connectivity found in this study may add new knowledge to the current understanding of functional brain networks in BPD. However, due to limitation of small sample sizes, the results of the current study should be viewed as exploratory and need to be validated on large samples in future works. PMID:26977400

Network analysis of functional brain connectivity in borderline personality disorder using resting-state fMRI.

PubMed

Xu, Tingting; Cullen, Kathryn R; Mueller, Bryon; Schreiner, Mindy W; Lim, Kelvin O; Schulz, S Charles; Parhi, Keshab K

2016-01-01

Borderline personality disorder (BPD) is associated with symptoms such as affect dysregulation, impaired sense of self, and self-harm behaviors. Neuroimaging research on BPD has revealed structural and functional abnormalities in specific brain regions and connections. However, little is known about the topological organizations of brain networks in BPD. We collected resting-state functional magnetic resonance imaging (fMRI) data from 20 patients with BPD and 10 healthy controls, and constructed frequency-specific functional brain networks by correlating wavelet-filtered fMRI signals from 82 cortical and subcortical regions. We employed graph-theory based complex network analysis to investigate the topological properties of the brain networks, and employed network-based statistic to identify functional dysconnections in patients. In the 0.03-0.06 Hz frequency band, compared to controls, patients with BPD showed significantly larger measures of global network topology, including the size of largest connected graph component, clustering coefficient, small-worldness, and local efficiency, indicating increased local cliquishness of the functional brain network. Compared to controls, patients showed lower nodal centrality at several hub nodes but greater centrality at several non-hub nodes in the network. Furthermore, an interconnected subnetwork in 0.03-0.06 Hz frequency band was identified that showed significantly lower connectivity in patients. The links in the subnetwork were mainly long-distance connections between regions located at different lobes; and the mean connectivity of this subnetwork was negatively correlated with the increased global topology measures. Lastly, the key network measures showed high correlations with several clinical symptom scores, and classified BPD patients against healthy controls with high accuracy based on linear discriminant analysis. The abnormal topological properties and connectivity found in this study may add new knowledge to the current understanding of functional brain networks in BPD. However, due to limitation of small sample sizes, the results of the current study should be viewed as exploratory and need to be validated on large samples in future works.

Morphogenetic events in the perinodal connective tissue in a metastatic cancer model.

PubMed

Conti, G; Minicozzi, A; Merigo, F; Marzola, P; Osculati, F; Cordiano, C; Sbarbati, A

2013-02-01

The modifications of connective tissue surrounding metastatic lymph nodes in a murine model of rectal cancer are described. Athymic nude mice (n=36) were inoculated with 10×10(5) ht-29 cancer cells into the submucosal layer of the rectum. Control mice (n=5) were treated with a sterile buffer. Tumor and the involved lymph nodes were visualized in vivo by magnetic resonance imaging at 1 to 4 weeks after cell injection. After the sacrifice, the excised samples were processed for histology. After one week from cell injection all treated animals developed rectal cancer. Since the first week, neoplastic cells were visible in the nodes. In the surrounding connective tissue, the diameter of the adipocytes was reduced and a mesenchymal-like pattern with stellate cells embedded in an oedematous environment was visible. Since the second week, in the perinodal connective an enlargement of the stroma was present. The tissue was organized in cords and areas with extracellular accumulation of lipids were found. At the fourth week, we observed an enlargement of multilocular areas and lobules of elongated elements almost devoid of lipid droplets. In control animals, in absence of neoplastic masses, pelvic nodes were surrounded by a typical connective tissue characterized by unilocular adipocytes with groups of multilocular adipocytes. We have developed a model of rectal cancer with nodal metastases. Using this model, the work demonstrates that around secondary lesions, the morphogenetic events follow a standard evolution characterized by an early phase with lipolysis and mesenchymalization and later phases with a brown-like phenotype acquisition. Copyright © 2012. Published by Elsevier SAS.

Network robustness assessed within a dual connectivity framework: joint dynamics of the Active and Idle Networks.

PubMed

Tejedor, Alejandro; Longjas, Anthony; Zaliapin, Ilya; Ambroj, Samuel; Foufoula-Georgiou, Efi

2017-08-17

Network robustness against attacks has been widely studied in fields as diverse as the Internet, power grids and human societies. But current definition of robustness is only accounting for half of the story: the connectivity of the nodes unaffected by the attack. Here we propose a new framework to assess network robustness, wherein the connectivity of the affected nodes is also taken into consideration, acknowledging that it plays a crucial role in properly evaluating the overall network robustness in terms of its future recovery from the attack. Specifically, we propose a dual perspective approach wherein at any instant in the network evolution under attack, two distinct networks are defined: (i) the Active Network (AN) composed of the unaffected nodes and (ii) the Idle Network (IN) composed of the affected nodes. The proposed robustness metric considers both the efficiency of destroying the AN and that of building-up the IN. We show, via analysis of well-known prototype networks and real world data, that trade-offs between the efficiency of Active and Idle Network dynamics give rise to surprising robustness crossovers and re-rankings, which can have significant implications for decision making.

An agile high-capacity FDMA digital satellite network

NASA Astrophysics Data System (ADS)

Hawkins, R. B.; Johannes, V. I.; Lowell, R.

A centrally controlled digital transmission satellite network has been designed for High Speed Switched Digital Service (HSSDS), which uses both satellite and earth transmission facilities to provide point-to-point digital trunks on a reservation basis. HSSDS customers connect via 1.544 Mb/s loops to the nodes where switches are located, and the FDMA system employed offers 24 one-way 1.544 Mb/s trunks per satellite transponder.

Topological identification of the first uninodal 8-connected lsz MOF built from 2,2'-difluorobiphenyl-4,4'-dicarboxylate pillars and cadmium(II)-triazolate layers.

PubMed

Zhang, Yuchi; Wu, Yuanhua; He, Xin; Ma, Junhan; Shen, Xuan; Zhu, Dunru

2018-03-01

Using polynuclear metal clusters as nodes, many high-symmetry high-connectivity nets, like 8-connnected bcu and 12-connected fcu, have been attained in metal-organic frameworks (MOFs). However, construction of low-symmetry high-connected MOFs with a novel topology still remains a big challenge. For example, a uninodal 8-connected lsz network, observed in inorganic ZrSiO 4 , has not been topologically identified in MOFs. Using 2,2'-difluorobiphenyl-4,4'-dicarboxylic acid (H 2 L) as a new linker and 1,2,4-triazole (Htrz) as a coligand, a novel three-dimensional Cd II -MOF, namely poly[tetrakis(μ 4 -2,2'-difluorobiphenyl-4,4'-dicarboxylato-κ 5 O 1 ,O 1' :O 1' :O 4 :O 4' )tetrakis(N,N-dimethylformamide-κO)tetrakis(μ 3 -1,2,4-triazolato-κ 3 N 1 :N 2 :N 4 )hexacadmium(II)], [Cd 6 (C 14 H 6 F 2 O 4 ) 4 (C 2 H 2 N 3 ) 4 (C 3 H 7 NO) 4 ] n , (I), has been prepared. Single-crystal structure analysis indicates that six different Cd II ions co-exist in (I) and each Cd II ion displays a distorted [CdO 4 N 2 ] octahedral geometry with four equatorial O atoms and two axial N atoms. Three Cd II ions are connected by four carboxylate groups and four trz - ligands to form a linear trinuclear [Cd 3 (COO) 4 (trz) 4 ] cluster, as do the other three Cd II ions. Two Cd 3 clusters are linked by trz - ligands in a μ 1,2,4 -bridging mode to produce a two-dimensional Cd II -triazolate layer with (6,3) topology in the ab plane. These two-dimensional layers are further pillared by the L 2- ligands along the c axis to generate a complicated three-dimensional framework. Topologically, regarding the Cd 3 cluster as an 8-connected node, the whole architecture of (I) is a uninodal 8-connected lsz framework with the Schläfli symbol (4 22 ·6 6 ). Complex (I) was further characterized by elemental analysis, IR spectroscopy, powder X-ray diffraction, thermogravimetric analysis and a photoluminescence study. MOF (I) has a high thermal and water stability.

Progressive Bidirectional Age-Related Changes in Default Mode Network Effective Connectivity across Six Decades

PubMed Central

Li, Karl; Laird, Angela R.; Price, Larry R.; McKay, D. Reese; Blangero, John; Glahn, David C.; Fox, Peter T.

2016-01-01

The default mode network (DMN) is a set of regions that is tonically engaged during the resting state and exhibits task-related deactivation that is readily reproducible across a wide range of paradigms and modalities. The DMN has been implicated in numerous disorders of cognition and, in particular, in disorders exhibiting age-related cognitive decline. Despite these observations, investigations of the DMN in normal aging are scant. Here, we used blood oxygen level dependent (BOLD) functional magnetic resonance imaging (fMRI) acquired during rest to investigate age-related changes in functional connectivity of the DMN in 120 healthy normal volunteers comprising six, 20-subject, decade cohorts (from 20–29 to 70–79). Structural equation modeling (SEM) was used to assess age-related changes in inter-regional connectivity within the DMN. SEM was applied both using a previously published, meta-analytically derived, node-and-edge model, and using exploratory modeling searching for connections that optimized model fit improvement. Although the two models were highly similar (only 3 of 13 paths differed), the sample demonstrated significantly better fit with the exploratory model. For this reason, the exploratory model was used to assess age-related changes across the decade cohorts. Progressive, highly significant changes in path weights were found in 8 (of 13) paths: four rising, and four falling (most changes were significant by the third or fourth decade). In all cases, rising paths and falling paths projected in pairs onto the same nodes, suggesting compensatory increases associated with age-related decreases. This study demonstrates that age-related changes in DMN physiology (inter-regional connectivity) are bidirectional, progressive, of early onset and part of normal aging. PMID:27378909

Progressive Bidirectional Age-Related Changes in Default Mode Network Effective Connectivity across Six Decades.

PubMed

Li, Karl; Laird, Angela R; Price, Larry R; McKay, D Reese; Blangero, John; Glahn, David C; Fox, Peter T

2016-01-01

The default mode network (DMN) is a set of regions that is tonically engaged during the resting state and exhibits task-related deactivation that is readily reproducible across a wide range of paradigms and modalities. The DMN has been implicated in numerous disorders of cognition and, in particular, in disorders exhibiting age-related cognitive decline. Despite these observations, investigations of the DMN in normal aging are scant. Here, we used blood oxygen level dependent (BOLD) functional magnetic resonance imaging (fMRI) acquired during rest to investigate age-related changes in functional connectivity of the DMN in 120 healthy normal volunteers comprising six, 20-subject, decade cohorts (from 20-29 to 70-79). Structural equation modeling (SEM) was used to assess age-related changes in inter-regional connectivity within the DMN. SEM was applied both using a previously published, meta-analytically derived, node-and-edge model, and using exploratory modeling searching for connections that optimized model fit improvement. Although the two models were highly similar (only 3 of 13 paths differed), the sample demonstrated significantly better fit with the exploratory model. For this reason, the exploratory model was used to assess age-related changes across the decade cohorts. Progressive, highly significant changes in path weights were found in 8 (of 13) paths: four rising, and four falling (most changes were significant by the third or fourth decade). In all cases, rising paths and falling paths projected in pairs onto the same nodes, suggesting compensatory increases associated with age-related decreases. This study demonstrates that age-related changes in DMN physiology (inter-regional connectivity) are bidirectional, progressive, of early onset and part of normal aging.

KENNEDY SPACE CENTER, FLA. - An overhead crane in the Space Station Processing Facility is attached to the U.S. Node 2 to lift it out of its shipping container. The node will be moved to a workstand. The second of three connecting modules on the International Space Station, the Italian-built Node 2 attaches to the end of the U.S. Lab and provides attach locations for the Japanese laboratory, European laboratory, the Centrifuge Accommodation Module and, later, Multipurpose Logistics Modules. It will provide the primary docking location for the Shuttle when a pressurized mating adapter is attached to Node 2. Installation of the module will complete the U.S. Core of the ISS. Node 2 is the designated payload for mission STS-120. No orbiter or launch date has been determined yet.

NASA Image and Video Library

2003-06-03

KENNEDY SPACE CENTER, FLA. - An overhead crane in the Space Station Processing Facility is attached to the U.S. Node 2 to lift it out of its shipping container. The node will be moved to a workstand. The second of three connecting modules on the International Space Station, the Italian-built Node 2 attaches to the end of the U.S. Lab and provides attach locations for the Japanese laboratory, European laboratory, the Centrifuge Accommodation Module and, later, Multipurpose Logistics Modules. It will provide the primary docking location for the Shuttle when a pressurized mating adapter is attached to Node 2. Installation of the module will complete the U.S. Core of the ISS. Node 2 is the designated payload for mission STS-120. No orbiter or launch date has been determined yet.

Node 1 and PMA-1 are moved for weight and center of gravity determination

NASA Technical Reports Server (NTRS)

1998-01-01

Node 1, the first U.S. element for the International Space Station, and Pressurized Mating Adapter-1 (PMA-1) continue with prelaunch preparation activities at KSC's Space Station Processing Facility. Node 1 is a connecting passageway to the living and working areas of the space station. The node and PMA-1 are being moved to an element rotation stand, or test stand, where they will undergo an interim weight and center of gravity determination. The final determination is planned to be performed prior to transporting Node 1 to the launch pad. Node 1 is scheduled to fly on STS-88.

Modeling complex metabolic reactions, ecological systems, and financial and legal networks with MIANN models based on Markov-Wiener node descriptors.

PubMed

Duardo-Sánchez, Aliuska; Munteanu, Cristian R; Riera-Fernández, Pablo; López-Díaz, Antonio; Pazos, Alejandro; González-Díaz, Humberto

2014-01-27

The use of numerical parameters in Complex Network analysis is expanding to new fields of application. At a molecular level, we can use them to describe the molecular structure of chemical entities, protein interactions, or metabolic networks. However, the applications are not restricted to the world of molecules and can be extended to the study of macroscopic nonliving systems, organisms, or even legal or social networks. On the other hand, the development of the field of Artificial Intelligence has led to the formulation of computational algorithms whose design is based on the structure and functioning of networks of biological neurons. These algorithms, called Artificial Neural Networks (ANNs), can be useful for the study of complex networks, since the numerical parameters that encode information of the network (for example centralities/node descriptors) can be used as inputs for the ANNs. The Wiener index (W) is a graph invariant widely used in chemoinformatics to quantify the molecular structure of drugs and to study complex networks. In this work, we explore for the first time the possibility of using Markov chains to calculate analogues of node distance numbers/W to describe complex networks from the point of view of their nodes. These parameters are called Markov-Wiener node descriptors of order k(th) (W(k)). Please, note that these descriptors are not related to Markov-Wiener stochastic processes. Here, we calculated the W(k)(i) values for a very high number of nodes (>100,000) in more than 100 different complex networks using the software MI-NODES. These networks were grouped according to the field of application. Molecular networks include the Metabolic Reaction Networks (MRNs) of 40 different organisms. In addition, we analyzed other biological and legal and social networks. These include the Interaction Web Database Biological Networks (IWDBNs), with 75 food webs or ecological systems and the Spanish Financial Law Network (SFLN). The calculated W(k)(i) values were used as inputs for different ANNs in order to discriminate correct node connectivity patterns from incorrect random patterns. The MIANN models obtained present good values of Sensitivity/Specificity (%): MRNs (78/78), IWDBNs (90/88), and SFLN (86/84). These preliminary results are very promising from the point of view of a first exploratory study and suggest that the use of these models could be extended to the high-throughput re-evaluation of connectivity in known complex networks (collation).

Locating hardware faults in a data communications network of a parallel computer

DOEpatents

Archer, Charles J.; Megerian, Mark G.; Ratterman, Joseph D.; Smith, Brian E.

2010-01-12

Hardware faults location in a data communications network of a parallel computer. Such a parallel computer includes a plurality of compute nodes and a data communications network that couples the compute nodes for data communications and organizes the compute node as a tree. Locating hardware faults includes identifying a next compute node as a parent node and a root of a parent test tree, identifying for each child compute node of the parent node a child test tree having the child compute node as root, running a same test suite on the parent test tree and each child test tree, and identifying the parent compute node as having a defective link connected from the parent compute node to a child compute node if the test suite fails on the parent test tree and succeeds on all the child test trees.

Role of local network oscillations in resting-state functional connectivity.

PubMed

Cabral, Joana; Hugues, Etienne; Sporns, Olaf; Deco, Gustavo

2011-07-01

Spatio-temporally organized low-frequency fluctuations (<0.1 Hz), observed in BOLD fMRI signal during rest, suggest the existence of underlying network dynamics that emerge spontaneously from intrinsic brain processes. Furthermore, significant correlations between distinct anatomical regions-or functional connectivity (FC)-have led to the identification of several widely distributed resting-state networks (RSNs). This slow dynamics seems to be highly structured by anatomical connectivity but the mechanism behind it and its relationship with neural activity, particularly in the gamma frequency range, remains largely unknown. Indeed, direct measurements of neuronal activity have revealed similar large-scale correlations, particularly in slow power fluctuations of local field potential gamma frequency range oscillations. To address these questions, we investigated neural dynamics in a large-scale model of the human brain's neural activity. A key ingredient of the model was a structural brain network defined by empirically derived long-range brain connectivity together with the corresponding conduction delays. A neural population, assumed to spontaneously oscillate in the gamma frequency range, was placed at each network node. When these oscillatory units are integrated in the network, they behave as weakly coupled oscillators. The time-delayed interaction between nodes is described by the Kuramoto model of phase oscillators, a biologically-based model of coupled oscillatory systems. For a realistic setting of axonal conduction speed, we show that time-delayed network interaction leads to the emergence of slow neural activity fluctuations, whose patterns correlate significantly with the empirically measured FC. The best agreement of the simulated FC with the empirically measured FC is found for a set of parameters where subsets of nodes tend to synchronize although the network is not globally synchronized. Inside such clusters, the simulated BOLD signal between nodes is found to be correlated, instantiating the empirically observed RSNs. Between clusters, patterns of positive and negative correlations are observed, as described in experimental studies. These results are found to be robust with respect to a biologically plausible range of model parameters. In conclusion, our model suggests how resting-state neural activity can originate from the interplay between the local neural dynamics and the large-scale structure of the brain. Copyright © 2011 Elsevier Inc. All rights reserved.

Fiber-connected position localization sensor networks

NASA Astrophysics Data System (ADS)

Pan, Shilong; Zhu, Dan; Fu, Jianbin; Yao, Tingfeng

2014-11-01

Position localization has drawn great attention due to its wide applications in radars, sonars, electronic warfare, wireless communications and so on. Photonic approaches to realize position localization can achieve high-resolution, which also provides the possibility to move the signal processing from each sensor node to the central station, thanks to the low loss, immunity to electromagnetic interference (EMI) and broad bandwidth brought by the photonic technologies. In this paper, we present a review on the recent works of position localization based on photonic technologies. A fiber-connected ultra-wideband (UWB) sensor network using optical time-division multiplexing (OTDM) is proposed to realize high-resolution localization and moving the signal processing to the central station. A 3.9-cm high spatial resolution is achieved. A wavelength-division multiplexed (WDM) fiber-connected sensor network is also demonstrated to realize location which is independent of the received signal format.

Morphological analysis of lymph nodes in Odontocetes from north and northeast coast of Brazil.

PubMed

De Oliveira e Silva, Fernanda Menezes; Guimarães, Juliana Plácido; Vergara-Parente, Jociery Einhardt; Carvalho, Vitor Luz; De Meirelles, Ana Carolina Oliveira; Marmontel, Miriam; Ferrão, Juliana Shimara Pires; Miglino, Maria Angelica

2014-05-01

The morphology and location of lymph nodes from seven species of Odontocetes, of both sexes and different age groups, were described. All animals were derived from stranding events along the North and Northeastern coasts of Brazil. After the identification of lymph nodes in situ, tissue samples were analyzed for light and electron microscopy. Vascular volume density (VVD) and vascular length density (VLD) were evaluated in the mesenteric lymph nodes. Lymph nodes occurred as solitary nodules or in groups, varying in shape and size. In addition to using the nomenclature recommended by Nomina Anatomica Veterinaria, new nomenclatures were suggested based on the lymph nodes topography. Lymph nodes were covered by a highly vascularized and innervated capsule of dense connective tissue, below which muscle fibers were observed, inconsistently, in all studied species. There was no difference in VLD among different age groups. However, VVD was higher in adults. Lymph nodes parenchyma was divided into an outer cortex, containing lymph nodules and germinal centers; a paracortical region, transition zone with dense lymphoid tissue; and an inner medulla, composed of small irregular cords of lymphatic tissue, blood vessels, and diffuse lymphoid tissue. Abundant collagen fibers were observed around arteries and arterioles. Germinal centers were more evident and developed in calves and young animals, being more discrete and sparse in adults. The morphology of lymph nodes in Odontocetes was typical of that observed in other terrestrial mammals. However, new groups of lymph nodes were described for seven species occurring in the Brazilian coast. Copyright © 2014 Wiley Periodicals, Inc.

Cell boundary fault detection system

DOEpatents

Archer, Charles Jens [Rochester, MN; Pinnow, Kurt Walter [Rochester, MN; Ratterman, Joseph D [Rochester, MN; Smith, Brian Edward [Rochester, MN

2011-04-19

An apparatus and program product determine a nodal fault along the boundary, or face, of a computing cell. Nodes on adjacent cell boundaries communicate with each other, and the communications are analyzed to determine if a node or connection is faulty.

Circuit-Switched Memory Access in Photonic Interconnection Networks for High-Performance Embedded Computing

DTIC Science & Technology

2010-07-22

dependent , providing a natural bandwidth match between compute cores and the memory subsystem. • High Bandwidth Dcnsity. Waveguides crossing the chip...simulate this memory access architecture on a 2S6-core chip with a concentrated 64-node network lIsing detailed traces of high-performance embedded...memory modulcs, wc placc memory access poi nts (MAPs) around the pcriphery of the chip connected to thc nctwork. These MAPs, shown in Figure 4, contain

Connectivity, Coverage and Placement in Wireless Sensor Networks

PubMed Central

Li, Ji; Andrew, Lachlan L.H.; Foh, Chuan Heng; Zukerman, Moshe; Chen, Hsiao-Hwa

2009-01-01

Wireless communication between sensors allows the formation of flexible sensor networks, which can be deployed rapidly over wide or inaccessible areas. However, the need to gather data from all sensors in the network imposes constraints on the distances between sensors. This survey describes the state of the art in techniques for determining the minimum density and optimal locations of relay nodes and ordinary sensors to ensure connectivity, subject to various degrees of uncertainty in the locations of the nodes. PMID:22408474

A multi-hop teleportation protocol of arbitrary four-qubit states through intermediate nodes

NASA Astrophysics Data System (ADS)

Choudhury, Binayak S.; Samanta, Soumen

Teleportation processes over long distances become affected by the almost inevitable existence of noise which interferes with the entangled quantum channels. In view of this, intermediate nodes are introduced in the scheme. These nodes are connected in series through quantum entanglement. In this paper, we present a protocol for transferring an entangled four-particle cluster-type state in an integrated manner through the intermediate nodes. Its efficiency and advantage over the corresponding part by part teleportation process is discussed.

Towards Optimal Connectivity on Multi-layered Networks.

PubMed

Chen, Chen; He, Jingrui; Bliss, Nadya; Tong, Hanghang

2017-10-01

Networks are prevalent in many high impact domains. Moreover, cross-domain interactions are frequently observed in many applications, which naturally form the dependencies between different networks. Such kind of highly coupled network systems are referred to as multi-layered networks , and have been used to characterize various complex systems, including critical infrastructure networks, cyber-physical systems, collaboration platforms, biological systems and many more. Different from single-layered networks where the functionality of their nodes is mainly affected by within-layer connections, multi-layered networks are more vulnerable to disturbance as the impact can be amplified through cross-layer dependencies, leading to the cascade failure to the entire system. To manipulate the connectivity in multi-layered networks, some recent methods have been proposed based on two-layered networks with specific types of connectivity measures. In this paper, we address the above challenges in multiple dimensions. First, we propose a family of connectivity measures (SUBLINE) that unifies a wide range of classic network connectivity measures. Third, we reveal that the connectivity measures in SUBLINE family enjoy diminishing returns property , which guarantees a near-optimal solution with linear complexity for the connectivity optimization problem. Finally, we evaluate our proposed algorithm on real data sets to demonstrate its effectiveness and efficiency.

A framework for detecting communities of unbalanced sizes in networks

NASA Astrophysics Data System (ADS)

Žalik, Krista Rizman; Žalik, Borut

2018-01-01

Community detection in large networks has been a focus of recent research in many of fields, including biology, physics, social sciences, and computer science. Most community detection methods partition the entire network into communities, groups of nodes that have many connections within communities and few connections between them and do not identify different roles that nodes can have in communities. We propose a community detection model that integrates more different measures that can fast identify communities of different sizes and densities. We use node degree centrality, strong similarity with one node from community, maximal similarity of node to community, compactness of communities and separation between communities. Each measure has its own strength and weakness. Thus, combining different measures can benefit from the strengths of each one and eliminate encountered problems of using an individual measure. We present a fast local expansion algorithm for uncovering communities of different sizes and densities and reveals rich information on input networks. Experimental results show that the proposed algorithm is better or as effective as the other community detection algorithms for both real-world and synthetic networks while it requires less time.

Growth and structure of the World Wide Web: Towards realistic modeling

NASA Astrophysics Data System (ADS)

Tadić, Bosiljka

2002-08-01

We simulate evolution of the World Wide Web from the dynamic rules incorporating growth, bias attachment, and rewiring. We show that the emergent double-hierarchical structure with distinct distributions of out- and in-links is comparable with the observed empirical data when the control parameter (average graph flexibility β) is kept in the range β=3-4. We then explore the Web graph by simulating (a) Web crawling to determine size and depth of connected components, and (b) a random walker that discovers the structure of connected subgraphs with dominant attractor and promoter nodes. A random walker that adapts its move strategy to mimic local node linking preferences is shown to have a short access time to "important" nodes on the Web graph.

An unusual 2p-3d-4f heterometallic coordination polymer featuring Ln8Na and Cu8I clusters as nodes

NASA Astrophysics Data System (ADS)

Zhao, Mingjuan; Chen, Shimin; Huang, Yutian; Dan, Youmeng

2017-01-01

A new cluster-based three-dimensional 2p-3d-4f heterometallic framework {[Ho8Na(OH)6Cu16I2(CPT)24](NO3)9(H2O)6(CH3CN)18}n (1, HCPT = 4-(4-carboxyphenyl)-1,2,4 triazole) has been prepared under solvothermal condition by using a custom-designed bifunctional organic ligand. The single-crystal structure analysis reveals that this framework features novel Ln8Na and Cu8I clusters as nodes, these nodes are further connected by the CPT ligands to give rise to a (6,14)-connected network. The magnetic property of this framework has also been investigated.

KSC-04pd1676

NASA Image and Video Library

2004-08-24

KENNEDY SPACE CENTER, FLA. - In the Space Station Processing Facility, a worker observes data from the Traveled Work Systems Test (TWST) conducted on the Node 2. The TWST executes open work that traveled with the Node 2 from Italy and simulates the on-orbit activation sequence. Node 2 was powered up Aug. 19 for the testing. The second of three Space Station connecting modules, the Node 2 attaches to the end of the U.S. Lab and provides attach locations for several other elements. Node 2 is scheduled to launch on mission STS-120, assembly flight 10A to the International Space Station.

Field test of a practical secure communication network with decoy-state quantum cryptography.

PubMed

Chen, Teng-Yun; Liang, Hao; Liu, Yang; Cai, Wen-Qi; Ju, Lei; Liu, Wei-Yue; Wang, Jian; Yin, Hao; Chen, Kai; Chen, Zeng-Bing; Peng, Cheng-Zhi; Pan, Jian-Wei

2009-04-13

We present a secure network communication system that operated with decoy-state quantum cryptography in a real-world application scenario. The full key exchange and application protocols were performed in real time among three nodes, in which two adjacent nodes were connected by approximate 20 km of commercial telecom optical fiber. The generated quantum keys were immediately employed and demonstrated for communication applications, including unbreakable real-time voice telephone between any two of the three communication nodes, or a broadcast from one node to the other two nodes by using one-time pad encryption.

The network property of the thalamus in the default mode network is correlated with trait mindfulness.

PubMed

Wang, X; Xu, M; Song, Y; Li, X; Zhen, Z; Yang, Z; Liu, J

2014-10-10

Mindfulness is typically defined as nonjudgmental awareness of experiences in the present moment, which is beneficial for mental and physical well-being. Previous studies have identified multiple regions in the default mode network (DMN) that are involved in mindfulness, but little is known about how these regions work collaboratively as a network. Here, we used resting-state functional magnetic resonance imaging to investigate the role of the DMN in trait mindfulness by correlating spontaneous functional connectivity among DMN nodes with self-reported trait mindfulness in a large population of young human adults. Among all pairs of the DMN nodes, we found that individuals with weaker functional connectivity between the thalamus and posterior cingulate cortex (PCC) were more mindful of the present. Post-hoc analyses of these two nodes further revealed that graph-based nodal properties of the thalamus, not the PCC, were negatively correlated with trait mindfulness, suggesting that a low involvement of the thalamus in the DMN is relevant for high trait mindfulness. Our findings not only suggest the thalamus as a switch between mind-wandering and mindfulness, but also invite future studies on mechanisms of how mindfulness produces beneficial effects by modulating the thalamus. Copyright © 2014 IBRO. Published by Elsevier Ltd. All rights reserved.

Optimal cube-connected cube multiprocessors

NASA Technical Reports Server (NTRS)

Sun, Xian-He; Wu, Jie

1993-01-01

Many CFD (computational fluid dynamics) and other scientific applications can be partitioned into subproblems. However, in general the partitioned subproblems are very large. They demand high performance computing power themselves, and the solutions of the subproblems have to be combined at each time step. The cube-connect cube (CCCube) architecture is studied. The CCCube architecture is an extended hypercube structure with each node represented as a cube. It requires fewer physical links between nodes than the hypercube, and provides the same communication support as the hypercube does on many applications. The reduced physical links can be used to enhance the bandwidth of the remaining links and, therefore, enhance the overall performance. The concept and the method to obtain optimal CCCubes, which are the CCCubes with a minimum number of links under a given total number of nodes, are proposed. The superiority of optimal CCCubes over standard hypercubes was also shown in terms of the link usage in the embedding of a binomial tree. A useful computation structure based on a semi-binomial tree for divide-and-conquer type of parallel algorithms was identified. It was shown that this structure can be implemented in optimal CCCubes without performance degradation compared with regular hypercubes. The result presented should provide a useful approach to design of scientific parallel computers.

Surname complex network for Brazil and Portugal

NASA Astrophysics Data System (ADS)

Ferreira, G. D.; Viswanathan, G. M.; da Silva, L. R.; Herrmann, H. J.

2018-06-01

We present a study of social networks based on the analysis of Brazilian and Portuguese family names (surnames). We construct networks whose nodes are names of families and whose edges represent parental relations between two families. From these networks we extract the connectivity distribution, clustering coefficient, shortest path and centrality. We find that the connectivity distribution follows an approximate power law. We associate the number of hubs, centrality and entropy to the degree of miscegenation in the societies in both countries. Our results show that Portuguese society has a higher miscegenation degree than Brazilian society. All networks analyzed lead to approximate inverse square power laws in the degree distribution. We conclude that the thermodynamic limit is reached for small networks (3 or 4 thousand nodes). The assortative mixing of all networks is negative, showing that the more connected vertices are connected to vertices with lower connectivity. Finally, the network of surnames presents some small world characteristics.

Broadcasting collective operation contributions throughout a parallel computer

DOEpatents

Faraj, Ahmad [Rochester, MN

2012-02-21

Methods, systems, and products are disclosed for broadcasting collective operation contributions throughout a parallel computer. The parallel computer includes a plurality of compute nodes connected together through a data communications network. Each compute node has a plurality of processors for use in collective parallel operations on the parallel computer. Broadcasting collective operation contributions throughout a parallel computer according to embodiments of the present invention includes: transmitting, by each processor on each compute node, that processor's collective operation contribution to the other processors on that compute node using intra-node communications; and transmitting on a designated network link, by each processor on each compute node according to a serial processor transmission sequence, that processor's collective operation contribution to the other processors on the other compute nodes using inter-node communications.

Node similarity within subgraphs of protein interaction networks

NASA Astrophysics Data System (ADS)

Penner, Orion; Sood, Vishal; Musso, Gabriel; Baskerville, Kim; Grassberger, Peter; Paczuski, Maya

2008-06-01

We propose a biologically motivated quantity, twinness, to evaluate local similarity between nodes in a network. The twinness of a pair of nodes is the number of connected, labeled subgraphs of size n in which the two nodes possess identical neighbours. The graph animal algorithm is used to estimate twinness for each pair of nodes (for subgraph sizes n=4 to n=12) in four different protein interaction networks (PINs). These include an Escherichia coli PIN and three Saccharomyces cerevisiae PINs - each obtained using state-of-the-art high-throughput methods. In almost all cases, the average twinness of node pairs is vastly higher than that expected from a null model obtained by switching links. For all n, we observe a difference in the ratio of type A twins (which are unlinked pairs) to type B twins (which are linked pairs) distinguishing the prokaryote E. coli from the eukaryote S. cerevisiae. Interaction similarity is expected due to gene duplication, and whole genome duplication paralogues in S. cerevisiae have been reported to co-cluster into the same complexes. Indeed, we find that these paralogous proteins are over-represented as twins compared to pairs chosen at random. These results indicate that twinness can detect ancestral relationships from currently available PIN data.

Localization Algorithm Based on a Spring Model (LASM) for Large Scale Wireless Sensor Networks.

PubMed

Chen, Wanming; Mei, Tao; Meng, Max Q-H; Liang, Huawei; Liu, Yumei; Li, Yangming; Li, Shuai

2008-03-15

A navigation method for a lunar rover based on large scale wireless sensornetworks is proposed. To obtain high navigation accuracy and large exploration area, highnode localization accuracy and large network scale are required. However, thecomputational and communication complexity and time consumption are greatly increasedwith the increase of the network scales. A localization algorithm based on a spring model(LASM) method is proposed to reduce the computational complexity, while maintainingthe localization accuracy in large scale sensor networks. The algorithm simulates thedynamics of physical spring system to estimate the positions of nodes. The sensor nodesare set as particles with masses and connected with neighbor nodes by virtual springs. Thevirtual springs will force the particles move to the original positions, the node positionscorrespondingly, from the randomly set positions. Therefore, a blind node position can bedetermined from the LASM algorithm by calculating the related forces with the neighbornodes. The computational and communication complexity are O(1) for each node, since thenumber of the neighbor nodes does not increase proportionally with the network scale size.Three patches are proposed to avoid local optimization, kick out bad nodes and deal withnode variation. Simulation results show that the computational and communicationcomplexity are almost constant despite of the increase of the network scale size. The time consumption has also been proven to remain almost constant since the calculation steps arealmost unrelated with the network scale size.

Information Selection in Intelligence Processing

DTIC Science & Technology

2011-12-01

given. Edges connecting nodes representing irrelevant persons with either relevant or irrelevant persons are added randomly, as in an Erdos- Renyi ...graph (Erdos at Renyi , 1959): For each irrelevant node i , and another node j (either relevant or irrelevant) there is a predetermined probability that...statistics for engineering and the sciences (7th ed.). Boston: Duxbury Press. Erdos, P., & Renyi , A. (1959). “On Random Graphs,” Publicationes

Reduced structural connectivity within a prefrontal-motor-subcortical network in amyotrophic lateral sclerosis.

PubMed

Buchanan, Colin R; Pettit, Lewis D; Storkey, Amos J; Abrahams, Sharon; Bastin, Mark E

2015-05-01

To investigate white matter structural connectivity changes associated with amyotrophic lateral sclerosis (ALS) using network analysis and compare the results with those obtained using standard voxel-based methods, specifically Tract-based Spatial Statistics (TBSS). MRI data were acquired from 30 patients with ALS and 30 age-matched healthy controls. For each subject, 85 grey matter regions (network nodes) were identified from high resolution structural MRI, and network connections formed from the white matter tracts generated by diffusion MRI and probabilistic tractography. Whole-brain networks were constructed using strong constraints on anatomical plausibility and a weighting reflecting tract-averaged fractional anisotropy (FA). Analysis using Network-based Statistics (NBS), without a priori selected regions, identified an impaired motor-frontal-subcortical subnetwork (10 nodes and 12 bidirectional connections), consistent with upper motor neuron pathology, in the ALS group compared with the controls (P = 0.020). Reduced FA in three of the impaired network connections, which involved fibers of the corticospinal tract, correlated with rate of disease progression (P ≤ 0.024). A novel network-tract comparison revealed that the connections involved in the affected network had a strong correspondence (mean overlap of 86.2%) with white matter tracts identified as having reduced FA compared with the control group using TBSS. These findings suggest that white matter degeneration in ALS is strongly linked to the motor cortex, and that impaired structural networks identified using NBS have a strong correspondence to affected white matter tracts identified using more conventional voxel-based methods. © 2014 Wiley Periodicals, Inc.

Methods and apparatus for controlling respective load currents of multiple series-connected loads

DOEpatents

Datta, Michael; Lys, Ihor

2014-05-27

A lighting apparatus (100) includes one or more first LEDs (202) for generating a first spectrum of radiation (503), and one or more second LEDs (204) for generating a second different spectrum radiation (505). The first and second LEDs are electrically connected in series between a first node (516A) and a second node (516B), between which a series current (550) flows with the application of an operating voltage (516) across the nodes. A controllable current path (518) is connected in parallel with one or both of the first and second LEDs so as to at least partially divert the series current, such that a first current (552) through the first LED(s) and a second current (554) through the second LED(s) are different. Such current diversion techniques may be employed to compensate for shifts in color or color temperature of generated light during thermal transients, due to different temperature-dependent current-to-flux relationships for different types of LEDs.

International Space Station Node 1 is moved for leak test

NASA Technical Reports Server (NTRS)

1998-01-01

Node 1, the first element for the International Space Station, and attached Pressurized Mating Adapter-1 continue with prelaunch preparation activities at KSC's Space Station Processing Facility. Node 1 is a connecting passageway to the living and working areas of the space station. The node is seen here being moved into the Shuttle payload transportation canister, where the doors will be closed for a two-week leak check. The node was moved to the canister from the element rotation stand, or test stand, where it underwent an interim weight and center of gravity determination. The final determination is planned to be performed prior to transporting Node 1 to the launch pad. Node 1 is scheduled to fly on STS-88.

International Space Station Node 1 is moved for leak test

NASA Technical Reports Server (NTRS)

1998-01-01

Node 1, the first U.S. element for the International Space Station, and attached Pressurized Mating Adapter-1 continue with prelaunch preparation activities at KSC's Space Station Processing Facility. Node 1 is a connecting passageway to the living and working areas of the space station. The node and PMA-1 are being removed from the element rotation stand, or test stand, where they underwent an interim weight and center of gravity determination. (The final determination is planned to be performed prior to transporting Node 1 to the launch pad.) Now the node is being moved to the Shuttle payload transportation canister, where the doors will be closed for a two-week leak check. Node 1 is scheduled to fly on STS-88.

Bad data packet capture device

DOEpatents

Chen, Dong; Gara, Alan; Heidelberger, Philip; Vranas, Pavlos

2010-04-20

An apparatus and method for capturing data packets for analysis on a network computing system includes a sending node and a receiving node connected by a bi-directional communication link. The sending node sends a data transmission to the receiving node on the bi-directional communication link, and the receiving node receives the data transmission and verifies the data transmission to determine valid data and invalid data and verify retransmissions of invalid data as corresponding valid data. A memory device communicates with the receiving node for storing the invalid data and the corresponding valid data. A computing node communicates with the memory device and receives and performs an analysis of the invalid data and the corresponding valid data received from the memory device.

Penalized likelihood and multi-objective spatial scans for the detection and inference of irregular clusters

PubMed Central

2010-01-01

Background Irregularly shaped spatial clusters are difficult to delineate. A cluster found by an algorithm often spreads through large portions of the map, impacting its geographical meaning. Penalized likelihood methods for Kulldorff's spatial scan statistics have been used to control the excessive freedom of the shape of clusters. Penalty functions based on cluster geometry and non-connectivity have been proposed recently. Another approach involves the use of a multi-objective algorithm to maximize two objectives: the spatial scan statistics and the geometric penalty function. Results & Discussion We present a novel scan statistic algorithm employing a function based on the graph topology to penalize the presence of under-populated disconnection nodes in candidate clusters, the disconnection nodes cohesion function. A disconnection node is defined as a region within a cluster, such that its removal disconnects the cluster. By applying this function, the most geographically meaningful clusters are sifted through the immense set of possible irregularly shaped candidate cluster solutions. To evaluate the statistical significance of solutions for multi-objective scans, a statistical approach based on the concept of attainment function is used. In this paper we compared different penalized likelihoods employing the geometric and non-connectivity regularity functions and the novel disconnection nodes cohesion function. We also build multi-objective scans using those three functions and compare them with the previous penalized likelihood scans. An application is presented using comprehensive state-wide data for Chagas' disease in puerperal women in Minas Gerais state, Brazil. Conclusions We show that, compared to the other single-objective algorithms, multi-objective scans present better performance, regarding power, sensitivity and positive predicted value. The multi-objective non-connectivity scan is faster and better suited for the detection of moderately irregularly shaped clusters. The multi-objective cohesion scan is most effective for the detection of highly irregularly shaped clusters. PMID:21034451

Trade-off between Multiple Constraints Enables Simultaneous Formation of Modules and Hubs in Neural Systems

PubMed Central

Chen, Yuhan; Wang, Shengjun; Hilgetag, Claus C.; Zhou, Changsong

2013-01-01

The formation of the complex network architecture of neural systems is subject to multiple structural and functional constraints. Two obvious but apparently contradictory constraints are low wiring cost and high processing efficiency, characterized by short overall wiring length and a small average number of processing steps, respectively. Growing evidence shows that neural networks are results from a trade-off between physical cost and functional value of the topology. However, the relationship between these competing constraints and complex topology is not well understood quantitatively. We explored this relationship systematically by reconstructing two known neural networks, Macaque cortical connectivity and C. elegans neuronal connections, from combinatory optimization of wiring cost and processing efficiency constraints, using a control parameter , and comparing the reconstructed networks to the real networks. We found that in both neural systems, the reconstructed networks derived from the two constraints can reveal some important relations between the spatial layout of nodes and the topological connectivity, and match several properties of the real networks. The reconstructed and real networks had a similar modular organization in a broad range of , resulting from spatial clustering of network nodes. Hubs emerged due to the competition of the two constraints, and their positions were close to, and partly coincided, with the real hubs in a range of values. The degree of nodes was correlated with the density of nodes in their spatial neighborhood in both reconstructed and real networks. Generally, the rebuilt network matched a significant portion of real links, especially short-distant ones. These findings provide clear evidence to support the hypothesis of trade-off between multiple constraints on brain networks. The two constraints of wiring cost and processing efficiency, however, cannot explain all salient features in the real networks. The discrepancy suggests that there are further relevant factors that are not yet captured here. PMID:23505352

Development of a Computing Cluster At the University of Richmond

NASA Astrophysics Data System (ADS)

Carbonneau, J.; Gilfoyle, G. P.; Bunn, E. F.

2010-11-01

The University of Richmond has developed a computing cluster to support the massive simulation and data analysis requirements for programs in intermediate-energy nuclear physics, and cosmology. It is a 20-node, 240-core system running Red Hat Enterprise Linux 5. We have built and installed the physics software packages (Geant4, gemc, MADmap...) and developed shell and Perl scripts for running those programs on the remote nodes. The system has a theoretical processing peak of about 2500 GFLOPS. Testing with the High Performance Linpack (HPL) benchmarking program (one of the standard benchmarks used by the TOP500 list of fastest supercomputers) resulted in speeds of over 900 GFLOPS. The difference between the maximum and measured speeds is due to limitations in the communication speed among the nodes; creating a bottleneck for large memory problems. As HPL sends data between nodes, the gigabit Ethernet connection cannot keep up with the processing power. We will show how both the theoretical and actual performance of the cluster compares with other current and past clusters, as well as the cost per GFLOP. We will also examine the scaling of the performance when distributed to increasing numbers of nodes.

Sampling networks with prescribed degree correlations

NASA Astrophysics Data System (ADS)

Del Genio, Charo; Bassler, Kevin; Erdos, Péter; Miklos, István; Toroczkai, Zoltán

2014-03-01

A feature of a network known to affect its structural and dynamical properties is the presence of correlations amongst the node degrees. Degree correlations are a measure of how much the connectivity of a node influences the connectivity of its neighbours, and they are fundamental in the study of processes such as the spreading of information or epidemics, the cascading failures of damaged systems and the evolution of social relations. We introduce a method, based on novel mathematical results, that allows the exact sampling of networks where the number of connections between nodes of any given connectivity is specified. Our algorithm provides a weight associated to each sample, thereby allowing network observables to be measured according to any desired distribution, and it is guaranteed to always terminate successfully in polynomial time. Thus, our new approach provides a preferred tool for scientists to model complex systems of current relevance, and enables researchers to precisely study correlated networks with broad societal importance. CIDG acknowledges support by the European Commission's FP7 through grant No. 288021. KEB acknowledges support from the NSF through grant DMR?1206839. KEB, PE, IM and ZT acknowledge support from AFSOR and DARPA through grant FA?9550-12-1-0405.

Graph Theory-Based Analysis of the Lymph Node Fibroblastic Reticular Cell Network.

PubMed

Novkovic, Mario; Onder, Lucas; Bocharov, Gennady; Ludewig, Burkhard

2017-01-01

Secondary lymphoid organs have developed segregated niches that are able to initiate and maintain effective immune responses. Such global organization requires tight control of diverse cellular components, specifically those that regulate lymphocyte trafficking. Fibroblastic reticular cells (FRCs) form a densely interconnected network in lymph nodes and provide key factors necessary for T cell migration and retention, and foster subsequent interactions between T cells and dendritic cells. Development of integrative systems biology approaches has made it possible to elucidate this multilevel complexity of the immune system. Here, we present a graph theory-based analysis of the FRC network in murine lymph nodes, where generation of the network topology is performed using high-resolution confocal microscopy and 3D reconstruction. This approach facilitates the analysis of physical cell-to-cell connectivity, and estimation of topological robustness and global behavior of the network when it is subjected to perturbation in silico.

Selective pinning control of the average disease transmissibility in an HIV contact network

NASA Astrophysics Data System (ADS)

du Toit, E. F.; Craig, I. K.

2015-07-01

Medication is applied to the HIV-infected nodes of high-risk contact networks with the aim of controlling the spread of disease to a predetermined maximum level. This intervention, known as pinning control, is performed both selectively and randomly in the network. These strategies are applied to 300 independent realizations per reference level of incidence on connected undirectional networks without isolated components and varying in size from 100 to 10 000 nodes per network. It is shown that a selective on-off pinning control strategy can control the networks studied with limited steady-state error and, comparing the medians of the doses from both strategies, uses 51.3% less medication than random pinning of all infected nodes. Selective pinning could possibly be used by public health specialists to identify the maximum level of HIV incidence in a population that can be achieved in a constrained funding environment.

KSC-07pd0641

NASA Image and Video Library

2007-03-15

KENNEDY SPACE CENTER, FLA. -- In the Space Station Processing Facility, Mission STS-120 Pilot George Zamka (left) and Commander Pam Melroy stand in front of the Node 2 module with it's new name, Harmony, unveiled. The name, Harmony, was chosen from an academic competition involving thousands of students in kindergarten through high school. The Node 2 Challenge required students to learn about the International Space Station, build a scale model of the module, and write an essay explaining their proposed name. This will be the first U.S. piece of the space station named by someone other than a NASA official. Node 2 is a pressurized module that will act as a connecting port and passageway to additional international science labs and supply spacecraft. It also will be a work platform for the station's robotic arm. The module is scheduled to fly on mission STS-120 aboard Space Shuttle Atlantis targeted for later this year. Photo credit: NASA/Jim Grossmann

KSC-07pd0643

NASA Image and Video Library

2007-03-15

KENNEDY SPACE CENTER, FLA. -- Inside the Space Station Processing Facility, William Gerstenmaier, NASA's associate administrator for Space Operations, talks to members of the media during a ceremony to unveil the Node 2 module's new name, Harmony. The name, Harmony, was chosen from an academic competition involving thousands of students in kindergarten through high school. The Node 2 Challenge required students to learn about the International Space Station, build a scale model of the module, and write an essay explaining their proposed name. This will be the first U.S. piece of the space station named by someone other than a NASA official. Node 2 is a pressurized module that will act as a connecting port and passageway to additional international science labs and supply spacecraft. It also will be a work platform for the station's robotic arm. The module is scheduled to fly on mission STS-120 aboard Space Shuttle Atlantis targeted for later this year. Photo credit: NASA/Jim Grossmann

KSC-07pd0640

NASA Image and Video Library

2007-03-15

KENNEDY SPACE CENTER, FLA. -- In the Space Station Processing Facility, Mission STS-120 Commander Pam Melroy speaks to members of the press and guests during a ceremony to unveil the new name of NASA's Node 2 module, Harmony. The name, Harmony, was chosen from an academic competition involving thousands of students in kindergarten through high school. The Node 2 Challenge required students to learn about the International Space Station, build a scale model of the module, and write an essay explaining their proposed name. This will be the first U.S. piece of the space station named by someone other than a NASA official. Node 2 is a pressurized module that will act as a connecting port and passageway to additional international science labs and supply spacecraft. It also will be a work platform for the station's robotic arm. The module is scheduled to fly on mission STS-120 aboard Space Shuttle Atlantis targeted for later this year. Photo credit: NASA/Jim Grossmann

Reconfigurable routing protocol for free space optical sensor networks.

PubMed

Xie, Rong; Yang, Won-Hyuk; Kim, Young-Chon

2012-01-01

Recently, free space optical sensor networks (FSOSNs), which are based on free space optics (FSO) instead of radio frequency (RF), have gained increasing visibility over traditional wireless sensor networks (WSNs) due to their advantages such as larger capacity, higher security, and lower cost. However, the performance of FSOSNs is restricted to the requirement of a direct line-of-sight (LOS) path between a sender and a receiver pair. Once a node dies of energy depletion, the network would probably suffer from a dramatic decrease of connectivity, resulting in a huge loss of data packets. Thus, this paper proposes a reconfigurable routing protocol (RRP) to overcome this problem by dynamically reconfiguring the network virtual topology. The RRP works in three phases: (1) virtual topology construction, (2) routing establishment, and (3) reconfigurable routing. When data transmission begins, the data packets are first routed through the shortest hop paths. Then a reconfiguration is initiated by the node whose residual energy falls below a threshold. Nodes affected by this dying node are classified into two types, namely maintenance nodes and adjustment nodes, and they are reconfigured according to the types. An energy model is designed to evaluate the performance of RRP through OPNET simulation. Our simulation results indicate that the RRP achieves better performance compared with the simple-link protocol and a direct reconfiguration scheme in terms of connectivity, network lifetime, packet delivery ratio and the number of living nodes.

PeerShield: determining control and resilience criticality of collaborative cyber assets in networks

NASA Astrophysics Data System (ADS)

Cam, Hasan

2012-06-01

As attackers get more coordinated and advanced in cyber attacks, cyber assets are required to have much more resilience, control effectiveness, and collaboration in networks. Such a requirement makes it essential to take a comprehensive and objective approach for measuring the individual and relative performances of cyber security assets in network nodes. To this end, this paper presents four techniques as to how the relative importance of cyber assets can be measured more comprehensively and objectively by considering together the main variables of risk assessment (e.g., threats, vulnerabilities), multiple attributes (e.g., resilience, control, and influence), network connectivity and controllability among collaborative cyber assets in networks. In the first technique, a Bayesian network is used to include the random variables for control, recovery, and resilience attributes of nodes, in addition to the random variables of threats, vulnerabilities, and risk. The second technique shows how graph matching and coloring can be utilized to form collaborative pairs of nodes to shield together against threats and vulnerabilities. The third technique ranks the security assets of nodes by incorporating multiple weights and thresholds of attributes into a decision-making algorithm. In the fourth technique, the hierarchically well-separated tree is enhanced to first identify critical nodes of a network with respect to their attributes and network connectivity, and then selecting some nodes as driver nodes for network controllability.

Adaption of the temporal correlation coefficient calculation for temporal networks (applied to a real-world pig trade network).

PubMed

Büttner, Kathrin; Salau, Jennifer; Krieter, Joachim

2016-01-01

The average topological overlap of two graphs of two consecutive time steps measures the amount of changes in the edge configuration between the two snapshots. This value has to be zero if the edge configuration changes completely and one if the two consecutive graphs are identical. Current methods depend on the number of nodes in the network or on the maximal number of connected nodes in the consecutive time steps. In the first case, this methodology breaks down if there are nodes with no edges. In the second case, it fails if the maximal number of active nodes is larger than the maximal number of connected nodes. In the following, an adaption of the calculation of the temporal correlation coefficient and of the topological overlap of the graph between two consecutive time steps is presented, which shows the expected behaviour mentioned above. The newly proposed adaption uses the maximal number of active nodes, i.e. the number of nodes with at least one edge, for the calculation of the topological overlap. The three methods were compared with the help of vivid example networks to reveal the differences between the proposed notations. Furthermore, these three calculation methods were applied to a real-world network of animal movements in order to detect influences of the network structure on the outcome of the different methods.

Limited-path-length entanglement percolation in quantum complex networks

NASA Astrophysics Data System (ADS)

Cuquet, Martí; Calsamiglia, John

2011-03-01

We study entanglement distribution in quantum complex networks where nodes are connected by bipartite entangled states. These networks are characterized by a complex structure, which dramatically affects how information is transmitted through them. For pure quantum state links, quantum networks exhibit a remarkable feature absent in classical networks: it is possible to effectively rewire the network by performing local operations on the nodes. We propose a family of such quantum operations that decrease the entanglement percolation threshold of the network and increase the size of the giant connected component. We provide analytic results for complex networks with an arbitrary (uncorrelated) degree distribution. These results are in good agreement with numerical simulations, which also show enhancement in correlated and real-world networks. The proposed quantum preprocessing strategies are not robust in the presence of noise. However, even when the links consist of (noisy) mixed-state links, one can send quantum information through a connecting path with a fidelity that decreases with the path length. In this noisy scenario, complex networks offer a clear advantage over regular lattices, namely, the fact that two arbitrary nodes can be connected through a relatively small number of steps, known as the small-world effect. We calculate the probability that two arbitrary nodes in the network can successfully communicate with a fidelity above a given threshold. This amounts to working out the classical problem of percolation with a limited path length. We find that this probability can be significant even for paths limited to few connections and that the results for standard (unlimited) percolation are soon recovered if the path length exceeds by a finite amount the average path length, which in complex networks generally scales logarithmically with the size of the network.

Network Robustness: the whole story

NASA Astrophysics Data System (ADS)

Longjas, A.; Tejedor, A.; Zaliapin, I. V.; Ambroj, S.; Foufoula-Georgiou, E.

2014-12-01

A multitude of actual processes operating on hydrological networks may exhibit binary outcomes such as clean streams in a river network that may become contaminated. These binary outcomes can be modeled by node removal processes (attacks) acting in a network. Network robustness against attacks has been widely studied in fields as diverse as the Internet, power grids and human societies. However, the current definition of robustness is only accounting for the connectivity of the nodes unaffected by the attack. Here, we put forward the idea that the connectivity of the affected nodes can play a crucial role in proper evaluation of the overall network robustness and its future recovery from the attack. Specifically, we propose a dual perspective approach wherein at any instant in the network evolution under attack, two distinct networks are defined: (i) the Active Network (AN) composed of the unaffected nodes and (ii) the Idle Network (IN) composed of the affected nodes. The proposed robustness metric considers both the efficiency of destroying the AN and the efficiency of building-up the IN. This approach is motivated by concrete applied problems, since, for example, if we study the dynamics of contamination in river systems, it is necessary to know both the connectivity of the healthy and contaminated parts of the river to assess its ecological functionality. We show that trade-offs between the efficiency of the Active and Idle network dynamics give rise to surprising crossovers and re-ranking of different attack strategies, pointing to significant implications for decision making.

A Component-Based Diffusion Model With Structural Diversity for Social Networks.

PubMed

Qing Bao; Cheung, William K; Yu Zhang; Jiming Liu

2017-04-01

Diffusion on social networks refers to the process where opinions are spread via the connected nodes. Given a set of observed information cascades, one can infer the underlying diffusion process for social network analysis. The independent cascade model (IC model) is a widely adopted diffusion model where a node is assumed to be activated independently by any one of its neighbors. In reality, how a node will be activated also depends on how its neighbors are connected and activated. For instance, the opinions from the neighbors of the same social group are often similar and thus redundant. In this paper, we extend the IC model by considering that: 1) the information coming from the connected neighbors are similar and 2) the underlying redundancy can be modeled using a dynamic structural diversity measure of the neighbors. Our proposed model assumes each node to be activated independently by different communities (or components) of its parent nodes, each weighted by its effective size. An expectation maximization algorithm is derived to infer the model parameters. We compare the performance of the proposed model with the basic IC model and its variants using both synthetic data sets and a real-world data set containing news stories and Web blogs. Our empirical results show that incorporating the community structure of neighbors and the structural diversity measure into the diffusion model significantly improves the accuracy of the model, at the expense of only a reasonable increase in run-time.

Vulnerability of animal trade networks to the spread of infectious diseases: a methodological approach applied to evaluation and emergency control strategies in cattle, France, 2005.

PubMed

Rautureau, S; Dufour, B; Durand, B

2011-04-01

Besides farming, trade of livestock is a major component of agricultural economy. However, the networks generated by live animal movements are the major support for the propagation of infectious agents between farms, and their structure strongly affects how fast a disease may spread. Structural characteristics may thus be indicators of network vulnerability to the spread of infectious disease. The method proposed here is based upon the analysis of specific subnetworks: the giant strongly connected components (GSCs). Their existence, size and geographic extent are used to assess network vulnerability. Their disappearance when targeted nodes are removed allows studying how network vulnerability may be controlled under emergency conditions. The method was applied to the cattle trade network in France, 2005. Giant strongly connected components were present and widely spread all over the country in yearly, monthly and weekly networks. Among several tested approaches, the most efficient way to make GSCs disappear was based on the ranking of nodes by decreasing betweenness centrality (the proportion of shortest paths between nodes on which a specific node lies). Giant strongly connected components disappearance was obtained after removal of <1% of network nodes. Under emergency conditions, suspending animal trade activities in a small subset of holdings may thus allow to control the spread of an infectious disease through the animal trade network. Nodes representing markets and dealers were widely affected by these simulated control measures. This confirms their importance as 'hubs' for infectious diseases spread. Besides emergency conditions, specific sensitization and preventive measures should be dedicated to this population. © 2010 Blackwell Verlag GmbH.

Qualities and Inequalities in Online Social Networks through the Lens of the Generalized Friendship Paradox.

PubMed

Momeni, Naghmeh; Rabbat, Michael

2016-01-01

The friendship paradox is the phenomenon that in social networks, people on average have fewer friends than their friends do. The generalized friendship paradox is an extension to attributes other than the number of friends. The friendship paradox and its generalized version have gathered recent attention due to the information they provide about network structure and local inequalities. In this paper, we propose several measures of nodal qualities which capture different aspects of their activities and influence in online social networks. Using these measures we analyse the prevalence of the generalized friendship paradox over Twitter and we report high levels of prevalence (up to over 90% of nodes). We contend that this prevalence of the friendship paradox and its generalized version arise because of the hierarchical nature of the connections in the network. This hierarchy is nested as opposed to being star-like. We conclude that these paradoxes are collective phenomena not created merely by a minority of well-connected or high-attribute nodes. Moreover, our results show that a large fraction of individuals can experience the generalized friendship paradox even in the absence of a significant correlation between degrees and attributes.

Three faces of node importance in network epidemiology: Exact results for small graphs

NASA Astrophysics Data System (ADS)

Holme, Petter

2017-12-01

We investigate three aspects of the importance of nodes with respect to susceptible-infectious-removed (SIR) disease dynamics: influence maximization (the expected outbreak size given a set of seed nodes), the effect of vaccination (how much deleting nodes would reduce the expected outbreak size), and sentinel surveillance (how early an outbreak could be detected with sensors at a set of nodes). We calculate the exact expressions of these quantities, as functions of the SIR parameters, for all connected graphs of three to seven nodes. We obtain the smallest graphs where the optimal node sets are not overlapping. We find that (i) node separation is more important than centrality for more than one active node, (ii) vaccination and influence maximization are the most different aspects of importance, and (iii) the three aspects are more similar when the infection rate is low.

Experimental tests and numerical analyses of steel truss bridge gusset connections.

DOT National Transportation Integrated Search

2012-11-01

Gusset plates connect individual steel truss bridge members together at a node. In 10% of the 200,000 steel bridges in US in 2008, failure of a : single truss or connection could lead to collapse. Regular inspection and load rating are essential for ...

KENNEDY SPACE CENTER, FLA. - Astronaut Tim Kopra aids in Intravehicular Activity (IVA) constraints testing on the Italian-built Node 2, a future element of the International Space Station. The second of three Station connecting modules, the Node 2 attaches to the end of the U.S. Lab and provides attach locations for several other elements. Kopra is currently assigned technical duties in the Space Station Branch of the Astronaut Office, where his primary focus involves the testing of crew interfaces for two future ISS modules as well as the implementation of support computers and operational Local Area Network on ISS. Node 2 is scheduled to launch on mission STS-120, Station assembly flight 10A.

NASA Image and Video Library

2004-02-03

KENNEDY SPACE CENTER, FLA. - Astronaut Tim Kopra aids in Intravehicular Activity (IVA) constraints testing on the Italian-built Node 2, a future element of the International Space Station. The second of three Station connecting modules, the Node 2 attaches to the end of the U.S. Lab and provides attach locations for several other elements. Kopra is currently assigned technical duties in the Space Station Branch of the Astronaut Office, where his primary focus involves the testing of crew interfaces for two future ISS modules as well as the implementation of support computers and operational Local Area Network on ISS. Node 2 is scheduled to launch on mission STS-120, Station assembly flight 10A.

KENNEDY SPACE CENTER, FLA. - In the Space Station Processing Facility, workers check over the Italian-built Node 2, a future element of the International Space Station. The second of three Station connecting modules, the Node 2 attaches to the end of the U.S. Lab and provides attach locations for several other elements. Kopra is currently assigned technical duties in the Space Station Branch of the Astronaut Office, where his primary focus involves the testing of crew interfaces for two future ISS modules as well as the implementation of support computers and operational Local Area Network on ISS. Node 2 is scheduled to launch on mission STS-120, Station assembly flight 10A.

NASA Image and Video Library

2004-02-03

KENNEDY SPACE CENTER, FLA. - In the Space Station Processing Facility, workers check over the Italian-built Node 2, a future element of the International Space Station. The second of three Station connecting modules, the Node 2 attaches to the end of the U.S. Lab and provides attach locations for several other elements. Kopra is currently assigned technical duties in the Space Station Branch of the Astronaut Office, where his primary focus involves the testing of crew interfaces for two future ISS modules as well as the implementation of support computers and operational Local Area Network on ISS. Node 2 is scheduled to launch on mission STS-120, Station assembly flight 10A.

Model Checking A Self-Stabilizing Synchronization Protocol for Arbitrary Digraphs

NASA Technical Reports Server (NTRS)

Malekpour, Mahyar R.

2012-01-01

This report presents the mechanical verification of a self-stabilizing distributed clock synchronization protocol for arbitrary digraphs in the absence of faults. This protocol does not rely on assumptions about the initial state of the system, other than the presence of at least one node, and no central clock or a centrally generated signal, pulse, or message is used. The system under study is an arbitrary, non-partitioned digraph ranging from fully connected to 1-connected networks of nodes while allowing for differences in the network elements. Nodes are anonymous, i.e., they do not have unique identities. There is no theoretical limit on the maximum number of participating nodes. The only constraint on the behavior of the node is that the interactions with other nodes are restricted to defined links and interfaces. This protocol deterministically converges within a time bound that is a linear function of the self-stabilization period. A bounded model of the protocol is verified using the Symbolic Model Verifier (SMV) for a subset of digraphs. Modeling challenges of the protocol and the system are addressed. The model checking effort is focused on verifying correctness of the bounded model of the protocol as well as confirmation of claims of determinism and linear convergence with respect to the self-stabilization period.

A novel topology control approach to maintain the node degree in dynamic wireless sensor networks.

PubMed

Huang, Yuanjiang; Martínez, José-Fernán; Díaz, Vicente Hernández; Sendra, Juana

2014-03-07

Topology control is an important technique to improve the connectivity and the reliability of Wireless Sensor Networks (WSNs) by means of adjusting the communication range of wireless sensor nodes. In this paper, a novel Fuzzy-logic Topology Control (FTC) is proposed to achieve any desired average node degree by adaptively changing communication range, thus improving the network connectivity, which is the main target of FTC. FTC is a fully localized control algorithm, and does not rely on location information of neighbors. Instead of designing membership functions and if-then rules for fuzzy-logic controller, FTC is constructed from the training data set to facilitate the design process. FTC is proved to be accurate, stable and has short settling time. In order to compare it with other representative localized algorithms (NONE, FLSS, k-Neighbor and LTRT), FTC is evaluated through extensive simulations. The simulation results show that: firstly, similar to k-Neighbor algorithm, FTC is the best to achieve the desired average node degree as node density varies; secondly, FTC is comparable to FLSS and k-Neighbor in terms of energy-efficiency, but is better than LTRT and NONE; thirdly, FTC has the lowest average maximum communication range than other algorithms, which indicates that the most energy-consuming node in the network consumes the lowest power.

In/Out Status Monitoring in Mobile Asset Tracking with Wireless Sensor Networks

PubMed Central

Kim, Kwangsoo; Chung, Chin-Wan

2010-01-01

A mobile asset with a sensor node in a mobile asset tracking system moves around a monitoring area, leaves it, and then returns to the region repeatedly. The system monitors the in/out status of the mobile asset. Due to the continuous movement of the mobile asset, the system may generate an error for the in/out status of the mobile asset. When the mobile asset is inside the region, the system might determine that it is outside, or vice versa. In this paper, we propose a method to detect and correct the incorrect in/out status of the mobile asset. To solve this problem, our approach uses data about the connection state transition and the battery lifetime of the mobile node attached to the mobile asset. The connection state transition is used to classify the mobile node as normal or abnormal. The battery lifetime is used to predict a valid working period for the mobile node. We evaluate our method using real data generated by a medical asset tracking system. The experimental results show that our method, by using the estimated battery life time or by using the invalid connection state, can detect and correct most cases of incorrect in/out statuses generated by the conventional approach. PMID:22319268

In/out status monitoring in mobile asset tracking with wireless sensor networks.

PubMed

Kim, Kwangsoo; Chung, Chin-Wan

2010-01-01

A mobile asset with a sensor node in a mobile asset tracking system moves around a monitoring area, leaves it, and then returns to the region repeatedly. The system monitors the in/out status of the mobile asset. Due to the continuous movement of the mobile asset, the system may generate an error for the in/out status of the mobile asset. When the mobile asset is inside the region, the system might determine that it is outside, or vice versa. In this paper, we propose a method to detect and correct the incorrect in/out status of the mobile asset. To solve this problem, our approach uses data about the connection state transition and the battery lifetime of the mobile node attached to the mobile asset. The connection state transition is used to classify the mobile node as normal or abnormal. The battery lifetime is used to predict a valid working period for the mobile node. We evaluate our method using real data generated by a medical asset tracking system. The experimental results show that our method, by using the estimated battery life time or by using the invalid connection state, can detect and correct most cases of incorrect in/out statuses generated by the conventional approach.

Locality preserving non-negative basis learning with graph embedding.

PubMed

Ghanbari, Yasser; Herrington, John; Gur, Ruben C; Schultz, Robert T; Verma, Ragini

2013-01-01

The high dimensionality of connectivity networks necessitates the development of methods identifying the connectivity building blocks that not only characterize the patterns of brain pathology but also reveal representative population patterns. In this paper, we present a non-negative component analysis framework for learning localized and sparse sub-network patterns of connectivity matrices by decomposing them into two sets of discriminative and reconstructive bases. In order to obtain components that are designed towards extracting population differences, we exploit the geometry of the population by using a graphtheoretical scheme that imposes locality-preserving properties as well as maintaining the underlying distance between distant nodes in the original and the projected space. The effectiveness of the proposed framework is demonstrated by applying it to two clinical studies using connectivity matrices derived from DTI to study a population of subjects with ASD, as well as a developmental study of structural brain connectivity that extracts gender differences.

Measures for brain connectivity analysis: nodes centrality and their invariant patterns

NASA Astrophysics Data System (ADS)

da Silva, Laysa Mayra Uchôa; Baltazar, Carlos Arruda; Silva, Camila Aquemi; Ribeiro, Mauricio Watanabe; de Aratanha, Maria Adelia Albano; Deolindo, Camila Sardeto; Rodrigues, Abner Cardoso; Machado, Birajara Soares

2017-07-01

The high dynamical complexity of the brain is related to its small-world topology, which enable both segregated and integrated information processing capabilities. Several measures of connectivity estimation have already been employed to characterize functional brain networks from multivariate electrophysiological data. However, understanding the properties of each measure that lead to a better description of the real topology and capture the complex phenomena present in the brain remains challenging. In this work we compared four nonlinear connectivity measures and show that each method characterizes distinct features of brain interactions. The results suggest an invariance of global network parameters from different behavioral states and that more complete description may be reached considering local features, independently of the connectivity measure employed. Our findings also point to future perspectives in connectivity studies that combine distinct and complementary dependence measures in assembling higher dimensions manifolds.

The Analysis of Alpha Beta Pruning and MTD(f) Algorithm to Determine the Best Algorithm to be Implemented at Connect Four Prototype

NASA Astrophysics Data System (ADS)

Tommy, Lukas; Hardjianto, Mardi; Agani, Nazori

2017-04-01

Connect Four is a two-player game which the players take turns dropping discs into a grid to connect 4 of one’s own discs next to each other vertically, horizontally, or diagonally. At Connect Four, Computer requires artificial intelligence (AI) in order to play properly like human. There are many AI algorithms that can be implemented to Connect Four, but the suitable algorithms are unknown. The suitable algorithm means optimal in choosing move and its execution time is not slow at search depth which is deep enough. In this research, analysis and comparison between standard alpha beta (AB) Pruning and MTD(f) will be carried out at the prototype of Connect Four in terms of optimality (win percentage) and speed (execution time and the number of leaf nodes). Experiments are carried out by running computer versus computer mode with 12 different conditions, i.e. varied search depth (5 through 10) and who moves first. The percentage achieved by MTD(f) based on experiments is win 45,83%, lose 37,5% and draw 16,67%. In the experiments with search depth 8, MTD(f) execution time is 35, 19% faster and evaluate 56,27% fewer leaf nodes than AB Pruning. The results of this research are MTD(f) is as optimal as AB Pruning at Connect Four prototype, but MTD(f) on average is faster and evaluates fewer leaf nodes than AB Pruning. The execution time of MTD(f) is not slow and much faster than AB Pruning at search depth which is deep enough.

Large-Scale Hypoconnectivity Between Resting-State Functional Networks in Unmedicated Adolescent Major Depressive Disorder.

PubMed

Sacchet, Matthew D; Ho, Tiffany C; Connolly, Colm G; Tymofiyeva, Olga; Lewinn, Kaja Z; Han, Laura Km; Blom, Eva H; Tapert, Susan F; Max, Jeffrey E; Frank, Guido Kw; Paulus, Martin P; Simmons, Alan N; Gotlib, Ian H; Yang, Tony T

2016-11-01

Major depressive disorder (MDD) often emerges during adolescence, a critical period of brain development. Recent resting-state fMRI studies of adults suggest that MDD is associated with abnormalities within and between resting-state networks (RSNs). Here we tested whether adolescent MDD is characterized by abnormalities in interactions among RSNs. Participants were 55 unmedicated adolescents diagnosed with MDD and 56 matched healthy controls. Functional connectivity was mapped using resting-state fMRI. We used the network-based statistic (NBS) to compare large-scale connectivity between groups and also compared the groups on graph metrics. We further assessed whether group differences identified using nodes defined from functionally defined RSNs were also evident when using anatomically defined nodes. In addition, we examined relations between network abnormalities and depression severity and duration. Finally, we compared intranetwork connectivity between groups and assessed the replication of previously reported MDD-related abnormalities in connectivity. The NBS indicated that, compared with controls, depressed adolescents exhibited reduced connectivity (p<0.024, corrected) between a specific set of RSNs, including components of the attention, central executive, salience, and default mode networks. The NBS did not identify group differences in network connectivity when using anatomically defined nodes. Longer duration of depression was significantly correlated with reduced connectivity in this set of network interactions (p=0.020, corrected), specifically with reduced connectivity between components of the dorsal attention network. The dorsal attention network was also characterized by reduced intranetwork connectivity in the MDD group. Finally, we replicated previously reported abnormal connectivity in individuals with MDD. In summary, adolescents with MDD show hypoconnectivity between large-scale brain networks compared with healthy controls. Given that connectivity among these networks typically increases during adolescent neurodevelopment, these results suggest that adolescent depression is associated with abnormalities in neural systems that are still developing during this critical period.

Large-Scale Hypoconnectivity Between Resting-State Functional Networks in Unmedicated Adolescent Major Depressive Disorder

PubMed Central

Sacchet, Matthew D; Ho, Tiffany C; Connolly, Colm G; Tymofiyeva, Olga; Lewinn, Kaja Z; Han, Laura KM; Blom, Eva H; Tapert, Susan F; Max, Jeffrey E; Frank, Guido KW; Paulus, Martin P; Simmons, Alan N; Gotlib, Ian H; Yang, Tony T

2016-01-01

Major depressive disorder (MDD) often emerges during adolescence, a critical period of brain development. Recent resting-state fMRI studies of adults suggest that MDD is associated with abnormalities within and between resting-state networks (RSNs). Here we tested whether adolescent MDD is characterized by abnormalities in interactions among RSNs. Participants were 55 unmedicated adolescents diagnosed with MDD and 56 matched healthy controls. Functional connectivity was mapped using resting-state fMRI. We used the network-based statistic (NBS) to compare large-scale connectivity between groups and also compared the groups on graph metrics. We further assessed whether group differences identified using nodes defined from functionally defined RSNs were also evident when using anatomically defined nodes. In addition, we examined relations between network abnormalities and depression severity and duration. Finally, we compared intranetwork connectivity between groups and assessed the replication of previously reported MDD-related abnormalities in connectivity. The NBS indicated that, compared with controls, depressed adolescents exhibited reduced connectivity (p<0.024, corrected) between a specific set of RSNs, including components of the attention, central executive, salience, and default mode networks. The NBS did not identify group differences in network connectivity when using anatomically defined nodes. Longer duration of depression was significantly correlated with reduced connectivity in this set of network interactions (p=0.020, corrected), specifically with reduced connectivity between components of the dorsal attention network. The dorsal attention network was also characterized by reduced intranetwork connectivity in the MDD group. Finally, we replicated previously reported abnormal connectivity in individuals with MDD. In summary, adolescents with MDD show hypoconnectivity between large-scale brain networks compared with healthy controls. Given that connectivity among these networks typically increases during adolescent neurodevelopment, these results suggest that adolescent depression is associated with abnormalities in neural systems that are still developing during this critical period. PMID:27238621

Corticocortical evoked potentials reveal projectors and integrators in human brain networks.

PubMed

Keller, Corey J; Honey, Christopher J; Entz, Laszlo; Bickel, Stephan; Groppe, David M; Toth, Emilia; Ulbert, Istvan; Lado, Fred A; Mehta, Ashesh D

2014-07-02

The cerebral cortex is composed of subregions whose functional specialization is largely determined by their incoming and outgoing connections with each other. In the present study, we asked which cortical regions can exert the greatest influence over other regions and the cortical network as a whole. Previous research on this question has relied on coarse anatomy (mapping large fiber pathways) or functional connectivity (mapping inter-regional statistical dependencies in ongoing activity). Here we combined direct electrical stimulation with recordings from the cortical surface to provide a novel insight into directed, inter-regional influence within the cerebral cortex of awake humans. These networks of directed interaction were reproducible across strength thresholds and across subjects. Directed network properties included (1) a decrease in the reciprocity of connections with distance; (2) major projector nodes (sources of influence) were found in peri-Rolandic cortex and posterior, basal and polar regions of the temporal lobe; and (3) major receiver nodes (receivers of influence) were found in anterolateral frontal, superior parietal, and superior temporal regions. Connectivity maps derived from electrical stimulation and from resting electrocorticography (ECoG) correlations showed similar spatial distributions for the same source node. However, higher-level network topology analysis revealed differences between electrical stimulation and ECoG that were partially related to the reciprocity of connections. Together, these findings inform our understanding of large-scale corticocortical influence as well as the interpretation of functional connectivity networks. Copyright © 2014 the authors 0270-6474/14/349152-12$15.00/0.

Tyurin works on a CPA in the hatch between the MPLM and Node 1

NASA Image and Video Library

2001-08-01

ISS003-E-5136 (August 2001) --- Mikhail Tyurin of Rosaviakosmos, Expedition Three flight engineer, secures a connection on a Controller Power Assembly (CPA) in a hatchway on Unity Node 1. This image was taken with a digital still camera.

Wide-area-distributed storage system for a multimedia database

NASA Astrophysics Data System (ADS)

Ueno, Masahiro; Kinoshita, Shigechika; Kuriki, Makato; Murata, Setsuko; Iwatsu, Shigetaro

1998-12-01

We have developed a wide-area-distribution storage system for multimedia databases, which minimizes the possibility of simultaneous failure of multiple disks in the event of a major disaster. It features a RAID system, whose member disks are spatially distributed over a wide area. Each node has a device, which includes the controller of the RAID and the controller of the member disks controlled by other nodes. The devices in the node are connected to a computer, using fiber optic cables and communicate using fiber-channel technology. Any computer at a node can utilize multiple devices connected by optical fibers as a single 'virtual disk.' The advantage of this system structure is that devices and fiber optic cables are shared by the computers. In this report, we first described our proposed system, and a prototype was used for testing. We then discussed its performance; i.e., how to read and write throughputs are affected by data-access delay, the RAID level, and queuing.

Hopping in the Crowd to Unveil Network Topology.

PubMed

Asllani, Malbor; Carletti, Timoteo; Di Patti, Francesca; Fanelli, Duccio; Piazza, Francesco

2018-04-13

We introduce a nonlinear operator to model diffusion on a complex undirected network under crowded conditions. We show that the asymptotic distribution of diffusing agents is a nonlinear function of the nodes' degree and saturates to a constant value for sufficiently large connectivities, at variance with standard diffusion in the absence of excluded-volume effects. Building on this observation, we define and solve an inverse problem, aimed at reconstructing the a priori unknown connectivity distribution. The method gathers all the necessary information by repeating a limited number of independent measurements of the asymptotic density at a single node, which can be chosen randomly. The technique is successfully tested against both synthetic and real data and is also shown to estimate with great accuracy the total number of nodes.

Hopping in the Crowd to Unveil Network Topology

NASA Astrophysics Data System (ADS)

Asllani, Malbor; Carletti, Timoteo; Di Patti, Francesca; Fanelli, Duccio; Piazza, Francesco

2018-04-01

We introduce a nonlinear operator to model diffusion on a complex undirected network under crowded conditions. We show that the asymptotic distribution of diffusing agents is a nonlinear function of the nodes' degree and saturates to a constant value for sufficiently large connectivities, at variance with standard diffusion in the absence of excluded-volume effects. Building on this observation, we define and solve an inverse problem, aimed at reconstructing the a priori unknown connectivity distribution. The method gathers all the necessary information by repeating a limited number of independent measurements of the asymptotic density at a single node, which can be chosen randomly. The technique is successfully tested against both synthetic and real data and is also shown to estimate with great accuracy the total number of nodes.

GFSSP Training Course Lectures

NASA Technical Reports Server (NTRS)

Majumdar, Alok K.

2008-01-01

GFSSP has been extended to model conjugate heat transfer Fluid Solid Network Elements include: a) Fluid nodes and Flow Branches; b) Solid Nodes and Ambient Nodes; c) Conductors connecting Fluid-Solid, Solid-Solid and Solid-Ambient Nodes. Heat Conduction Equations are solved simultaneously with Fluid Conservation Equations for Mass, Momentum, Energy and Equation of State. The extended code was verified by comparing with analytical solution for simple conduction-convection problem The code was applied to model: a) Pressurization of Cryogenic Tank; b) Freezing and Thawing of Metal; c) Chilldown of Cryogenic Transfer Line; d) Boil-off from Cryogenic Tank.

Fighting for resources: Two leaders in the money addicted social hierarchies

NASA Astrophysics Data System (ADS)

Dybiec, Bartłomiej

Building of hierarchy is inevitably associated with the constant competition for resources and attention. Here, we show how presence of two favored (leading) nodes affects properties of the network connecting individuals. In particular, we study how nodes characteristics depend on relative asymmetry between two leading nodes. It is shown that without strong and rigorous avoidance mechanism, individuals can support both dominating nodes. Slow redistribution of resources enhances this effect. Moreover, slow redistribution of resources results in development of social networks with a very limited number of layers.

Integrated Social and QoS Trust-Based Routing in Mobile Ad Hoc Delay Tolerant Networks

DTIC Science & Technology

2010-11-15

d-connectivity, honesty, or unselfishness) with: encounter*,. , A ^// m = / (3) {•p ounter,x r. , . .-, ( Ti x m (t), ifm =j ^indirect. X, T...take into account node »’ s belief in node m in the calculation ofT(jreet’ x(t + At). This models the decay of trust as trust is derived from a distant...directly based on node /’ s past experiences with node m up to time t + At, including the current encounter. Taking the fact that /? a + /?2 = 1, we obtain

Person-Locator System Based On Wristband Radio Transponders

NASA Technical Reports Server (NTRS)

Mintz, Frederick W.; Blaes, Brent R.; Chandler, Charles W.

1995-01-01

Computerized system based on wristband radio frequency (RF), passive transponders is being developed for use in real-time tracking of individuals in custodial institutions like prisons and mental hospitals. Includes monitoring system that contains central computer connected to low-power, high-frequency central transceiver. Transceiver connected to miniature transceiver nodes mounted unobtrusively at known locations throughout the institution. Wristband transponders embedded in common hospital wristbands. Wristbands tamperproof: each contains embedded wire loop which, when broken or torn off and discarded, causes wristband to disappear from system, thus causing alarm. Individuals could be located in a timely fashion at relatively low cost.

Polarity-specific high-level information propagation in neural networks.

PubMed

Lin, Yen-Nan; Chang, Po-Yen; Hsiao, Pao-Yueh; Lo, Chung-Chuan

2014-01-01

Analyzing the connectome of a nervous system provides valuable information about the functions of its subsystems. Although much has been learned about the architectures of neural networks in various organisms by applying analytical tools developed for general networks, two distinct and functionally important properties of neural networks are often overlooked. First, neural networks are endowed with polarity at the circuit level: Information enters a neural network at input neurons, propagates through interneurons, and leaves via output neurons. Second, many functions of nervous systems are implemented by signal propagation through high-level pathways involving multiple and often recurrent connections rather than by the shortest paths between nodes. In the present study, we analyzed two neural networks: the somatic nervous system of Caenorhabditis elegans (C. elegans) and the partial central complex network of Drosophila, in light of these properties. Specifically, we quantified high-level propagation in the vertical and horizontal directions: the former characterizes how signals propagate from specific input nodes to specific output nodes and the latter characterizes how a signal from a specific input node is shared by all output nodes. We found that the two neural networks are characterized by very efficient vertical and horizontal propagation. In comparison, classic small-world networks show a trade-off between vertical and horizontal propagation; increasing the rewiring probability improves the efficiency of horizontal propagation but worsens the efficiency of vertical propagation. Our result provides insights into how the complex functions of natural neural networks may arise from a design that allows them to efficiently transform and combine input signals.

Polarity-specific high-level information propagation in neural networks

PubMed Central

Lin, Yen-Nan; Chang, Po-Yen; Hsiao, Pao-Yueh; Lo, Chung-Chuan

2014-01-01

Analyzing the connectome of a nervous system provides valuable information about the functions of its subsystems. Although much has been learned about the architectures of neural networks in various organisms by applying analytical tools developed for general networks, two distinct and functionally important properties of neural networks are often overlooked. First, neural networks are endowed with polarity at the circuit level: Information enters a neural network at input neurons, propagates through interneurons, and leaves via output neurons. Second, many functions of nervous systems are implemented by signal propagation through high-level pathways involving multiple and often recurrent connections rather than by the shortest paths between nodes. In the present study, we analyzed two neural networks: the somatic nervous system of Caenorhabditis elegans (C. elegans) and the partial central complex network of Drosophila, in light of these properties. Specifically, we quantified high-level propagation in the vertical and horizontal directions: the former characterizes how signals propagate from specific input nodes to specific output nodes and the latter characterizes how a signal from a specific input node is shared by all output nodes. We found that the two neural networks are characterized by very efficient vertical and horizontal propagation. In comparison, classic small-world networks show a trade-off between vertical and horizontal propagation; increasing the rewiring probability improves the efficiency of horizontal propagation but worsens the efficiency of vertical propagation. Our result provides insights into how the complex functions of natural neural networks may arise from a design that allows them to efficiently transform and combine input signals. PMID:24672472

Functional and Topological Conditions for Explosive Synchronization Develop in Human Brain Networks with the Onset of Anesthetic-Induced Unconsciousness

PubMed Central

Kim, Minkyung; Mashour, George A.; Moraes, Stefanie-Blain; Vanini, Giancarlo; Tarnal, Vijay; Janke, Ellen; Hudetz, Anthony G.; Lee, Uncheol

2016-01-01

Sleep, anesthesia, and coma share a number of neural features but the recovery profiles are radically different. To understand the mechanisms of reversibility of unconsciousness at the network level, we studied the conditions for gradual and abrupt transitions in conscious and anesthetized states. We hypothesized that the conditions for explosive synchronization (ES) in human brain networks would be present in the anesthetized brain just over the threshold of unconsciousness. To test this hypothesis, functional brain networks were constructed from multi-channel electroencephalogram (EEG) recordings in seven healthy subjects across conscious, unconscious, and recovery states. We analyzed four variables that are involved in facilitating ES in generic, non-biological networks: (1) correlation between node degree and frequency, (2) disassortativity (i.e., the tendency of highly-connected nodes to link with less-connected nodes, or vice versa), (3) frequency difference of coupled nodes, and (4) an inequality relationship between local and global network properties, which is referred to as the suppressive rule. We observed that the four network conditions for ES were satisfied in the unconscious state. Conditions for ES in the human brain suggest a potential mechanism for rapid recovery from the lightly-anesthetized state. This study demonstrates for the first time that the network conditions for ES, formerly shown in generic networks only, are present in empirically-derived functional brain networks. Further investigations with deep anesthesia, sleep, and coma could provide insight into the underlying causes of variability in recovery profiles of these unconscious states. PMID:26834616

Functional and Topological Conditions for Explosive Synchronization Develop in Human Brain Networks with the Onset of Anesthetic-Induced Unconsciousness.

PubMed

Kim, Minkyung; Mashour, George A; Moraes, Stefanie-Blain; Vanini, Giancarlo; Tarnal, Vijay; Janke, Ellen; Hudetz, Anthony G; Lee, Uncheol

2016-01-01

Sleep, anesthesia, and coma share a number of neural features but the recovery profiles are radically different. To understand the mechanisms of reversibility of unconsciousness at the network level, we studied the conditions for gradual and abrupt transitions in conscious and anesthetized states. We hypothesized that the conditions for explosive synchronization (ES) in human brain networks would be present in the anesthetized brain just over the threshold of unconsciousness. To test this hypothesis, functional brain networks were constructed from multi-channel electroencephalogram (EEG) recordings in seven healthy subjects across conscious, unconscious, and recovery states. We analyzed four variables that are involved in facilitating ES in generic, non-biological networks: (1) correlation between node degree and frequency, (2) disassortativity (i.e., the tendency of highly-connected nodes to link with less-connected nodes, or vice versa), (3) frequency difference of coupled nodes, and (4) an inequality relationship between local and global network properties, which is referred to as the suppressive rule. We observed that the four network conditions for ES were satisfied in the unconscious state. Conditions for ES in the human brain suggest a potential mechanism for rapid recovery from the lightly-anesthetized state. This study demonstrates for the first time that the network conditions for ES, formerly shown in generic networks only, are present in empirically-derived functional brain networks. Further investigations with deep anesthesia, sleep, and coma could provide insight into the underlying causes of variability in recovery profiles of these unconscious states.

Communities and classes in symmetric fractals

NASA Astrophysics Data System (ADS)

Krawczyk, Małgorzata J.

2015-07-01

Two aspects of fractal networks are considered: the community structure and the class structure, where classes of nodes appear as a consequence of a local symmetry of nodes. The analyzed systems are the networks constructed for two selected symmetric fractals: the Sierpinski triangle and the Koch curve. Communities are searched for by means of a set of differential equations. Overlapping nodes which belong to two different communities are identified by adding some noise to the initial connectivity matrix. Then, a node can be characterized by a spectrum of probabilities of belonging to different communities. Our main goal is that the overlapping nodes with the same spectra belong to the same class.

Smart sensing surveillance system

NASA Astrophysics Data System (ADS)

Hsu, Charles; Chu, Kai-Dee; O'Looney, James; Blake, Michael; Rutar, Colleen

2010-04-01

Unattended ground sensor (UGS) networks have been widely used in remote battlefield and other tactical applications over the last few decades due to the advances of the digital signal processing. The UGS network can be applied in a variety of areas including border surveillance, special force operations, perimeter and building protection, target acquisition, situational awareness, and force protection. In this paper, a highly-distributed, fault-tolerant, and energyefficient Smart Sensing Surveillance System (S4) is presented to efficiently provide 24/7 and all weather security operation in a situation management environment. The S4 is composed of a number of distributed nodes to collect, process, and disseminate heterogeneous sensor data. Nearly all S4 nodes have passive sensors to provide rapid omnidirectional detection. In addition, Pan- Tilt- Zoom- (PTZ) Electro-Optics EO/IR cameras are integrated to selected nodes to track the objects and capture associated imagery. These S4 camera-connected nodes will provide applicable advanced on-board digital image processing capabilities to detect and track the specific objects. The imaging detection operations include unattended object detection, human feature and behavior detection, and configurable alert triggers, etc. In the S4, all the nodes are connected with a robust, reconfigurable, LPI/LPD (Low Probability of Intercept/ Low Probability of Detect) wireless mesh network using Ultra-wide band (UWB) RF technology, which can provide an ad-hoc, secure mesh network and capability to relay network information, communicate and pass situational awareness and messages. The S4 utilizes a Service Oriented Architecture such that remote applications can interact with the S4 network and use the specific presentation methods. The S4 capabilities and technologies have great potential for both military and civilian applications, enabling highly effective security support tools for improving surveillance activities in densely crowded environments and near perimeters and borders. The S4 is compliant with Open Geospatial Consortium - Sensor Web Enablement (OGC-SWE®) standards. It would be directly applicable to solutions for emergency response personnel, law enforcement, and other homeland security missions, as well as in applications requiring the interoperation of sensor networks with handheld or body-worn interface devices.

Constructing networks from a dynamical system perspective for multivariate nonlinear time series.

PubMed

Nakamura, Tomomichi; Tanizawa, Toshihiro; Small, Michael

2016-03-01

We describe a method for constructing networks for multivariate nonlinear time series. We approach the interaction between the various scalar time series from a deterministic dynamical system perspective and provide a generic and algorithmic test for whether the interaction between two measured time series is statistically significant. The method can be applied even when the data exhibit no obvious qualitative similarity: a situation in which the naive method utilizing the cross correlation function directly cannot correctly identify connectivity. To establish the connectivity between nodes we apply the previously proposed small-shuffle surrogate (SSS) method, which can investigate whether there are correlation structures in short-term variabilities (irregular fluctuations) between two data sets from the viewpoint of deterministic dynamical systems. The procedure to construct networks based on this idea is composed of three steps: (i) each time series is considered as a basic node of a network, (ii) the SSS method is applied to verify the connectivity between each pair of time series taken from the whole multivariate time series, and (iii) the pair of nodes is connected with an undirected edge when the null hypothesis cannot be rejected. The network constructed by the proposed method indicates the intrinsic (essential) connectivity of the elements included in the system or the underlying (assumed) system. The method is demonstrated for numerical data sets generated by known systems and applied to several experimental time series.

Metropolitan all-pass and inter-city quantum communication network.

PubMed

Chen, Teng-Yun; Wang, Jian; Liang, Hao; Liu, Wei-Yue; Liu, Yang; Jiang, Xiao; Wang, Yuan; Wan, Xu; Cai, Wei-Qi; Ju, Lei; Chen, Luo-Kan; Wang, Liu-Jun; Gao, Yuan; Chen, Kai; Peng, Cheng-Zhi; Chen, Zeng-Bing; Pan, Jian-Wei

2010-12-20

We have demonstrated a metropolitan all-pass quantum communication network in field fiber for four nodes. Any two nodes of them can be connected in the network to perform quantum key distribution (QKD). An optical switching module is presented that enables arbitrary 2-connectivity among output ports. Integrated QKD terminals are worked out, which can operate either as a transmitter, a receiver, or even both at the same time. Furthermore, an additional link in another city of 60 km fiber (up to 130 km) is seamless integrated into this network based on a trusted relay architecture. On all the links, we have implemented protocol of decoy state scheme. All of necessary electrical hardware, synchronization, feedback control, network software, execution of QKD protocols are made by tailored designing, which allow a completely automatical and stable running. Our system has been put into operation in Hefei in August 2009, and publicly demonstrated during an evaluation conference on quantum network organized by the Chinese Academy of Sciences on August 29, 2009. Real-time voice telephone with one-time pad encoding between any two of the five nodes (four all-pass nodes plus one additional node through relay) is successfully established in the network within 60 km.

Integration of Mesh Optimization with 3D All-Hex Mesh Generation, LDRD Subcase 3504340000, Final Report

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

KNUPP,PATRICK; MITCHELL,SCOTT A.

1999-11-01

In an attempt to automatically produce high-quality all-hex meshes, we investigated a mesh improvement strategy: given an initial poor-quality all-hex mesh, we iteratively changed the element connectivity, adding and deleting elements and nodes, and optimized the node positions. We found a set of hex reconnection primitives. We improved the optimization algorithms so they can untangle a negative-Jacobian mesh, even considering Jacobians on the boundary, and subsequently optimize the condition number of elements in an untangled mesh. However, even after applying both the primitives and optimization we were unable to produce high-quality meshes in certain regions. Our experiences suggest that manymore » boundary configurations of quadrilaterals admit no hexahedral mesh with positive Jacobians, although we have no proof of this.« less

Dynamic Evolution Model Based on Social Network Services

NASA Astrophysics Data System (ADS)

Xiong, Xi; Gou, Zhi-Jian; Zhang, Shi-Bin; Zhao, Wen

2013-11-01

Based on the analysis of evolutionary characteristics of public opinion in social networking services (SNS), in the paper we propose a dynamic evolution model, in which opinions are coupled with topology. This model shows the clustering phenomenon of opinions in dynamic network evolution. The simulation results show that the model can fit the data from a social network site. The dynamic evolution of networks accelerates the opinion, separation and aggregation. The scale and the number of clusters are influenced by confidence limit and rewiring probability. Dynamic changes of the topology reduce the number of isolated nodes, while the increased confidence limit allows nodes to communicate more sufficiently. The two effects make the distribution of opinion more neutral. The dynamic evolution of networks generates central clusters with high connectivity and high betweenness, which make it difficult to control public opinions in SNS.

Coevolution of dynamical states and interactions in dynamic networks

NASA Astrophysics Data System (ADS)

Zimmermann, Martín G.; Eguíluz, Víctor M.; San Miguel, Maxi

2004-06-01

We explore the coupled dynamics of the internal states of a set of interacting elements and the network of interactions among them. Interactions are modeled by a spatial game and the network of interaction links evolves adapting to the outcome of the game. As an example, we consider a model of cooperation in which the adaptation is shown to facilitate the formation of a hierarchical interaction network that sustains a highly cooperative stationary state. The resulting network has the characteristics of a small world network when a mechanism of local neighbor selection is introduced in the adaptive network dynamics. The highly connected nodes in the hierarchical structure of the network play a leading role in the stability of the network. Perturbations acting on the state of these special nodes trigger global avalanches leading to complete network reorganization.

Theoretical Manual for Analysis of Arch Dams

DTIC Science & Technology

1993-07-01

eight nodes lying on the midsurface , half-way between the corresponding surface nodes (Pawsey 1970). Each node on the midsurface has five DOF’s, three...translations in the global directions, and two rotations about two axes perpendicular to the midsurface normal (Figure 5-4). The sixth DOF, associated...Figure 5-3). The coordinates of any point within the element are described in terms of the midsurface coordinates and a vector connecting the two upper

Convergence and divergence across construction methods for human brain white matter networks: an assessment based on individual differences.

PubMed

Zhong, Suyu; He, Yong; Gong, Gaolang

2015-05-01

Using diffusion MRI, a number of studies have investigated the properties of whole-brain white matter (WM) networks with differing network construction methods (node/edge definition). However, how the construction methods affect individual differences of WM networks and, particularly, if distinct methods can provide convergent or divergent patterns of individual differences remain largely unknown. Here, we applied 10 frequently used methods to construct whole-brain WM networks in a healthy young adult population (57 subjects), which involves two node definitions (low-resolution and high-resolution) and five edge definitions (binary, FA weighted, fiber-density weighted, length-corrected fiber-density weighted, and connectivity-probability weighted). For these WM networks, individual differences were systematically analyzed in three network aspects: (1) a spatial pattern of WM connections, (2) a spatial pattern of nodal efficiency, and (3) network global and local efficiencies. Intriguingly, we found that some of the network construction methods converged in terms of individual difference patterns, but diverged with other methods. Furthermore, the convergence/divergence between methods differed among network properties that were adopted to assess individual differences. Particularly, high-resolution WM networks with differing edge definitions showed convergent individual differences in the spatial pattern of both WM connections and nodal efficiency. For the network global and local efficiencies, low-resolution and high-resolution WM networks for most edge definitions consistently exhibited a highly convergent pattern in individual differences. Finally, the test-retest analysis revealed a decent temporal reproducibility for the patterns of between-method convergence/divergence. Together, the results of the present study demonstrated a measure-dependent effect of network construction methods on the individual difference of WM network properties. © 2015 Wiley Periodicals, Inc.

Employing linear tetranuclear [Zn4(COO)4(OH)2] clusters as building subunits to construct a new Zn(II) coordination polymer with tunable luminescent properties

NASA Astrophysics Data System (ADS)

Li, Wu-Wu; Zhang, Zun-Ting

2016-02-01

A new Zn(II) coordination polymer, [Zn2(btc) (biimpy) (OH)]n (1 H3btc = 1,3,5-benzenetricarboxylic acid, biimpy = 2,6-bis(1-imdazoly)pyridine) has been successfully synthesized and characterized by elemental analysis, powder single crystal X-ray diffraction analyses. Compound 1 features a 3D framework employing linear tetranuclear [Zn4(COO)4(OH)2] cluster as building subunits. Topological analysis reveals it represents a (3,10)-connected structural topology by viewing btc3-, linear tetranuclear clusters and biimpy as 3-connected nodes, 10-connected nodes, linear linkers, respectively. Moreover, the thermal stability and luminescent property of compound 1 have been well investigated.

Using the OASES-A to illustrate how network analysis can be applied to understand the experience of stuttering.

PubMed

Siew, Cynthia S Q; Pelczarski, Kristin M; Yaruss, J Scott; Vitevitch, Michael S

Network science uses mathematical and computational techniques to examine how individual entities in a system, represented by nodes, interact, as represented by connections between nodes. This approach has been used by Cramer et al. (2010) to make "symptom networks" to examine various psychological disorders. In the present analysis we examined a network created from the items in the Overall Assessment of the Speaker's Experience of Stuttering-Adult (OASES-A), a commonly used measure for evaluating adverse impact in the lives of people who stutter. The items of the OASES-A were represented as nodes in the network. Connections between nodes were placed if responses to those two items in the OASES-A had a correlation coefficient greater than ±0.5. Several network analyses revealed which nodes were "important" in the network. Several centrally located nodes and "key players" in the network were identified. A community detection analysis found groupings of nodes that differed slightly from the subheadings of the OASES-A. Centrally located nodes and "key players" in the network may help clinicians prioritize treatment. The different community structure found for people who stutter suggests that the way people who stutter view stuttering may differ from the way that scientists and clinicians view stuttering. Finally, the present analyses illustrate how the network approach might be applied to other speech, language, and hearing disorders to better understand how those disorders are experienced and to provide insights for their treatment. Copyright © 2016 Elsevier Inc. All rights reserved.

Network of dedicated processors for finding lowest-cost map path

NASA Technical Reports Server (NTRS)

Eberhardt, Silvio P. (Inventor)

1991-01-01

A method and associated apparatus are disclosed for finding the lowest cost path of several variable paths. The paths are comprised of a plurality of linked cost-incurring areas existing between an origin point and a destination point. The method comprises the steps of connecting a purality of nodes together in the manner of the cost-incurring areas; programming each node to have a cost associated therewith corresponding to one of the cost-incurring areas; injecting a signal into one of the nodes representing the origin point; propagating the signal through the plurality of nodes from inputs to outputs; reducing the signal in magnitude at each node as a function of the respective cost of the node; and, starting at one of the nodes representing the destination point and following a path having the least reduction in magnitude of the signal from node to node back to one of the nodes representing the origin point whereby the lowest cost path from the origin point to the destination point is found.

Robustness of a network formed by n interdependent networks with a one-to-one correspondence of dependent nodes.

PubMed

Gao, Jianxi; Buldyrev, S V; Havlin, S; Stanley, H E

2012-06-01

Many real-world networks interact with and depend upon other networks. We develop an analytical framework for studying a network formed by n fully interdependent randomly connected networks, each composed of the same number of nodes N. The dependency links connecting nodes from different networks establish a unique one-to-one correspondence between the nodes of one network and the nodes of the other network. We study the dynamics of the cascades of failures in such a network of networks (NON) caused by a random initial attack on one of the networks, after which a fraction p of its nodes survives. We find for the fully interdependent loopless NON that the final state of the NON does not depend on the dynamics of the cascades but is determined by a uniquely defined mutual giant component of the NON, which generalizes both the giant component of regular percolation of a single network (n=1) and the recently studied case of the mutual giant component of two interdependent networks (n=2). We also find that the mutual giant component does not depend on the topology of the NON and express it in terms of generating functions of the degree distributions of the network. Our results show that, for any n≥2 there exists a critical p=p(c)>0 below which the mutual giant component abruptly collapses from a finite nonzero value for p≥p(c) to zero for p2, a RR NON is stable for any n with p(c)<1). This results arises from the critical role played by singly connected nodes which exist in an ER NON and enhance the cascading failures, but do not exist in a RR NON.

Modelling highly variable environmental factors to assess potential microbial respiration in complex floodplain landscapes

PubMed Central

Tritthart, Michael; Welti, Nina; Bondar-Kunze, Elisabeth; Pinay, Gilles; Hein, Thomas; Habersack, Helmut

2011-01-01

The hydrological exchange conditions strongly determine the biogeochemical dynamics in river systems. More specifically, the connectivity of surface waters between main channels and floodplains is directly controlling the delivery of organic matter and nutrients into the floodplains, where biogeochemical processes recycle them with high rates of activity. Hence, an in-depth understanding of the connectivity patterns between main channel and floodplains is important for the modelling of potential gas emissions in floodplain landscapes. A modelling framework that combines steady-state hydrodynamic simulations with long-term discharge hydrographs was developed to calculate water depths as well as statistical probabilities and event durations for every node of a computation mesh being connected to the main river. The modelling framework was applied to two study sites in the floodplains of the Austrian Danube River, East of Vienna. Validation of modelled flood events showed good agreement with gauge readings. Together with measured sediment properties, results of the validated connectivity model were used as basis for a predictive model yielding patterns of potential microbial respiration based on the best fit between characteristics of a number of sampling sites and the corresponding modelled parameters. Hot spots of potential microbial respiration were found in areas of lower connectivity if connected during higher discharges and areas of high water depths. PMID:27667961

Molecular organization of cytokinesis nodes and contractile rings by super-resolution fluorescence microscopy of live fission yeast

PubMed Central

Laplante, Caroline; Huang, Fang; Tebbs, Irene R.; Bewersdorf, Joerg; Pollard, Thomas D.

2016-01-01

Cytokinesis in animals, fungi, and amoebas depends on the constriction of a contractile ring built from a common set of conserved proteins. Many fundamental questions remain about how these proteins organize to generate the necessary tension for cytokinesis. Using quantitative high-speed fluorescence photoactivation localization microscopy (FPALM), we probed this question in live fission yeast cells at unprecedented resolution. We show that nodes, protein assembly precursors to the contractile ring, are discrete structural units with stoichiometric ratios and distinct distributions of constituent proteins. Anillin Mid1p, Fes/CIP4 homology-Bin/amphiphysin/Rvs (F-BAR) Cdc15p, IQ motif containing GTPase-activating protein (IQGAP) Rng2p, and formin Cdc12p form the base of the node that anchors the ends of myosin II tails to the plasma membrane, with myosin II heads extending into the cytoplasm. This general node organization persists in the contractile ring where nodes move bidirectionally during constriction. We observed the dynamics of the actin network during cytokinesis, starting with the extension of short actin strands from nodes, which sometimes connected neighboring nodes. Later in cytokinesis, a broad network of thick bundles coalesced into a tight ring around the equator of the cell. The actin ring was ∼125 nm wide and ∼125 nm thick. These observations establish the organization of the proteins in the functional units of a cytokinetic contractile ring. PMID:27647921

Improvement of the SEP protocol based on community structure of node degree

NASA Astrophysics Data System (ADS)

Li, Donglin; Wei, Suyuan

2017-05-01

Analyzing the Stable election protocol (SEP) in wireless sensor networks and aiming at the problem of inhomogeneous cluster-heads distribution and unreasonable cluster-heads selectivity and single hop transmission in the SEP, a SEP Protocol based on community structure of node degree (SEP-CSND) is proposed. In this algorithm, network node deployed by using grid deployment model, and the connection between nodes established by setting up the communication threshold. The community structure constructed by node degree, then cluster head is elected in the community structure. On the basis of SEP, the node's residual energy and node degree is added in cluster-heads election. The information is transmitted with mode of multiple hops between network nodes. The simulation experiments showed that compared to the classical LEACH and SEP, this algorithm balances the energy consumption of the entire network and significantly prolongs network lifetime.

Default Mode Network Interference in Mild Traumatic Brain Injury – A Pilot Resting State Study

PubMed Central

Sours, Chandler; Zhuo, Jiachen; Janowich, Jacqueline; Aarabi, Bizhan; Shanmuganathan, Kathirkamanthan; Gullapalli, Rao P

2013-01-01

In this study we investigated the functional connectivity in 23 Mild TBI (mTBI) patients with and without memory complaints using resting state fMRI in the sub-acute stage of injury as well as a group of control participants. Results indicate that mTBI patients with memory complaints performed significantly worse than patients without memory complaints on tests assessing memory from the Automated Neuropsychological Assessment Metrics (ANAM). Altered functional connectivity was observed between the three groups between the default mode network (DMN) and the nodes of the task positive network (TPN). Altered functional connectivity was also observed between both the TPN and DMN and nodes associated with the Salience Network (SN). Following mTBI there is a reduction in anti-correlated networks for both those with and without memory complaints for the DMN, but only a reduction in the anti-correlated network in mTBI patients with memory complaints for the TPN. Furthermore, an increased functional connectivity between the TPN and SN appears to be associated with reduced performance on memory assessments. Overall the results suggest that a disruption in the segregation of the DMN and the TPN at rest may be mediated through both a direct pathway of increased FC between various nodes of the TPN and DMN, and through an indirect pathway that links the TPN and DMN through nodes of the SN. This disruption between networks may cause a detrimental impact on memory functioning following mTBI, supporting the Default Mode Interference Hypothesis in the context of mTBI related memory deficits. PMID:23994210

Default mode network interference in mild traumatic brain injury - a pilot resting state study.

PubMed

Sours, Chandler; Zhuo, Jiachen; Janowich, Jacqueline; Aarabi, Bizhan; Shanmuganathan, Kathirkamanthan; Gullapalli, Rao P

2013-11-06

In this study we investigated the functional connectivity in 23 Mild TBI (mTBI) patients with and without memory complaints using resting state fMRI in the sub-acute stage of injury as well as a group of control participants. Results indicate that mTBI patients with memory complaints performed significantly worse than patients without memory complaints on tests assessing memory from the Automated Neuropsychological Assessment Metrics (ANAM). Altered functional connectivity was observed between the three groups between the default mode network (DMN) and the nodes of the task positive network (TPN). Altered functional connectivity was also observed between both the TPN and DMN and nodes associated with the Salience Network (SN). Following mTBI there is a reduction in anti-correlated networks for both those with and without memory complaints for the DMN, but only a reduction in the anti-correlated network in mTBI patients with memory complaints for the TPN. Furthermore, an increased functional connectivity between the TPN and SN appears to be associated with reduced performance on memory assessments. Overall the results suggest that a disruption in the segregation of the DMN and the TPN at rest may be mediated through both a direct pathway of increased FC between various nodes of the TPN and DMN, and through an indirect pathway that links the TPN and DMN through nodes of the SN. This disruption between networks may cause a detrimental impact on memory functioning following mTBI, supporting the Default Mode Interference Hypothesis in the context of mTBI related memory deficits. © 2013 Elsevier B.V. All rights reserved.

A Family of Algorithms for Computing Consensus about Node State from Network Data

PubMed Central

Brush, Eleanor R.; Krakauer, David C.; Flack, Jessica C.

2013-01-01

Biological and social networks are composed of heterogeneous nodes that contribute differentially to network structure and function. A number of algorithms have been developed to measure this variation. These algorithms have proven useful for applications that require assigning scores to individual nodes–from ranking websites to determining critical species in ecosystems–yet the mechanistic basis for why they produce good rankings remains poorly understood. We show that a unifying property of these algorithms is that they quantify consensus in the network about a node's state or capacity to perform a function. The algorithms capture consensus by either taking into account the number of a target node's direct connections, and, when the edges are weighted, the uniformity of its weighted in-degree distribution (breadth), or by measuring net flow into a target node (depth). Using data from communication, social, and biological networks we find that that how an algorithm measures consensus–through breadth or depth– impacts its ability to correctly score nodes. We also observe variation in sensitivity to source biases in interaction/adjacency matrices: errors arising from systematic error at the node level or direct manipulation of network connectivity by nodes. Our results indicate that the breadth algorithms, which are derived from information theory, correctly score nodes (assessed using independent data) and are robust to errors. However, in cases where nodes “form opinions” about other nodes using indirect information, like reputation, depth algorithms, like Eigenvector Centrality, are required. One caveat is that Eigenvector Centrality is not robust to error unless the network is transitive or assortative. In these cases the network structure allows the depth algorithms to effectively capture breadth as well as depth. Finally, we discuss the algorithms' cognitive and computational demands. This is an important consideration in systems in which individuals use the collective opinions of others to make decisions. PMID:23874167

Dynamical Signatures of Structural Connectivity Damage to a Model of the Brain Posed at Criticality.

PubMed

Haimovici, Ariel; Balenzuela, Pablo; Tagliazucchi, Enzo

2016-12-01

Synchronization of brain activity fluctuations is believed to represent communication between spatially distant neural processes. These interareal functional interactions develop in the background of a complex network of axonal connections linking cortical and subcortical neurons, termed the human "structural connectome." Theoretical considerations and experimental evidence support the view that the human brain can be modeled as a system operating at a critical point between ordered (subcritical) and disordered (supercritical) phases. Here, we explore the hypothesis that pathologies resulting from brain injury of different etiologies are related to this model of a critical brain. For this purpose, we investigate how damage to the integrity of the structural connectome impacts on the signatures of critical dynamics. Adopting a hybrid modeling approach combining an empirical weighted network of human structural connections with a conceptual model of critical dynamics, we show that lesions located at highly transited connections progressively displace the model toward the subcritical regime. The topological properties of the nodes and links are of less importance when considered independently of their weight in the network. We observe that damage to midline hubs such as the middle and posterior cingulate cortex is most crucial for the disruption of criticality in the model. However, a similar effect can be achieved by targeting less transited nodes and links whose connection weights add up to an equivalent amount. This implies that brain pathology does not necessarily arise due to insult targeted at well-connected areas and that intersubject variability could obscure lesions located at nonhub regions. Finally, we discuss the predictions of our model in the context of clinical studies of traumatic brain injury and neurodegenerative disorders.

The Role of Energy Reservoirs in Distributed Computing: Manufacturing, Implementing, and Optimizing Energy Storage in Energy-Autonomous Sensor Nodes

NASA Astrophysics Data System (ADS)

Cowell, Martin Andrew

The world already hosts more internet connected devices than people, and that ratio is only increasing. These devices seamlessly integrate with peoples lives to collect rich data and give immediate feedback about complex systems from business, health care, transportation, and security. As every aspect of global economies integrate distributed computing into their industrial systems and these systems benefit from rich datasets. Managing the power demands of these distributed computers will be paramount to ensure the continued operation of these networks, and is elegantly addressed by including local energy harvesting and storage on a per-node basis. By replacing non-rechargeable batteries with energy harvesting, wireless sensor nodes will increase their lifetimes by an order of magnitude. This work investigates the coupling of high power energy storage with energy harvesting technologies to power wireless sensor nodes; with sections covering device manufacturing, system integration, and mathematical modeling. First we consider the energy storage mechanism of supercapacitors and batteries, and identify favorable characteristics in both reservoir types. We then discuss experimental methods used to manufacture high power supercapacitors in our labs. We go on to detail the integration of our fabricated devices with collaborating labs to create functional sensor node demonstrations. With the practical knowledge gained through in-lab manufacturing and system integration, we build mathematical models to aid in device and system design. First, we model the mechanism of energy storage in porous graphene supercapacitors to aid in component architecture optimization. We then model the operation of entire sensor nodes for the purpose of optimally sizing the energy harvesting and energy reservoir components. In consideration of deploying these sensor nodes in real-world environments, we model the operation of our energy harvesting and power management systems subject to spatially and temporally varying energy availability in order to understand sensor node reliability. Looking to the future, we see an opportunity for further research to implement machine learning algorithms to control the energy resources of distributed computing networks.

Using Link Disconnection Entropy Disorder to Detect Fast Moving Nodes in MANETs.

PubMed

Alvarez, Carlos F; Palafox, Luis E; Aguilar, Leocundo; Sanchez, Mauricio A; Martinez, Luis G

2016-01-01

Mobile ad-hoc networks (MANETs) are dynamic by nature; this dynamism comes from node mobility, traffic congestion, and other transmission conditions. Metrics to evaluate the effects of those conditions shine a light on node's behavior in an ad-hoc network, helping to identify the node or nodes with better conditions of connection. In this paper, we propose a relative index to evaluate a single node reliability, based on the link disconnection entropy disorder using neighboring nodes as reference. Link disconnection entropy disorder is best used to identify fast moving nodes or nodes with unstable communications, this without the need of specialized sensors such as GPS. Several scenarios were studied to verify the index, measuring the effects of Speed and traffic density on the link disconnection entropy disorder. Packet delivery ratio is associated to the metric detecting a strong relationship, enabling the use of the link disconnection entropy disorder to evaluate the stability of a node to communicate with other nodes. To expand the utilization of the link entropy disorder, we identified nodes with higher speeds in network simulations just by using the link entropy disorder.

Network topology and functional connectivity disturbances precede the onset of Huntington’s disease

PubMed Central

Harrington, Deborah L.; Rubinov, Mikail; Durgerian, Sally; Mourany, Lyla; Reece, Christine; Koenig, Katherine; Bullmore, Ed; Long, Jeffrey D.; Paulsen, Jane S.

2015-01-01

Cognitive, motor and psychiatric changes in prodromal Huntington’s disease have nurtured the emergent need for early interventions. Preventive clinical trials for Huntington’s disease, however, are limited by a shortage of suitable measures that could serve as surrogate outcomes. Measures of intrinsic functional connectivity from resting-state functional magnetic resonance imaging are of keen interest. Yet recent studies suggest circumscribed abnormalities in resting-state functional magnetic resonance imaging connectivity in prodromal Huntington’s disease, despite the spectrum of behavioural changes preceding a manifest diagnosis. The present study used two complementary analytical approaches to examine whole-brain resting-state functional magnetic resonance imaging connectivity in prodromal Huntington’s disease. Network topology was studied using graph theory and simple functional connectivity amongst brain regions was explored using the network-based statistic. Participants consisted of gene-negative controls (n = 16) and prodromal Huntington’s disease individuals (n = 48) with various stages of disease progression to examine the influence of disease burden on intrinsic connectivity. Graph theory analyses showed that global network interconnectivity approximated a random network topology as proximity to diagnosis neared and this was associated with decreased connectivity amongst highly-connected rich-club network hubs, which integrate processing from diverse brain regions. However, functional segregation within the global network (average clustering) was preserved. Functional segregation was also largely maintained at the local level, except for the notable decrease in the diversity of anterior insula intermodular-interconnections (participation coefficient), irrespective of disease burden. In contrast, network-based statistic analyses revealed patterns of weakened frontostriatal connections and strengthened frontal-posterior connections that evolved as disease burden increased. These disturbances were often related to long-range connections involving peripheral nodes and interhemispheric connections. A strong association was found between weaker connectivity and decreased rich-club organization, indicating that whole-brain simple connectivity partially expressed disturbances in the communication of highly-connected hubs. However, network topology and network-based statistic connectivity metrics did not correlate with key markers of executive dysfunction (Stroop Test, Trail Making Test) in prodromal Huntington’s disease, which instead were related to whole-brain connectivity disturbances in nodes (right inferior parietal, right thalamus, left anterior cingulate) that exhibited multiple aberrant connections and that mediate executive control. Altogether, our results show for the first time a largely disease burden-dependent functional reorganization of whole-brain networks in prodromal Huntington’s disease. Both analytic approaches provided a unique window into brain reorganization that was not related to brain atrophy or motor symptoms. Longitudinal studies currently in progress will chart the course of functional changes to determine the most sensitive markers of disease progression. PMID:26059655

Network topology and functional connectivity disturbances precede the onset of Huntington's disease.

PubMed

Harrington, Deborah L; Rubinov, Mikail; Durgerian, Sally; Mourany, Lyla; Reece, Christine; Koenig, Katherine; Bullmore, Ed; Long, Jeffrey D; Paulsen, Jane S; Rao, Stephen M

2015-08-01

Cognitive, motor and psychiatric changes in prodromal Huntington's disease have nurtured the emergent need for early interventions. Preventive clinical trials for Huntington's disease, however, are limited by a shortage of suitable measures that could serve as surrogate outcomes. Measures of intrinsic functional connectivity from resting-state functional magnetic resonance imaging are of keen interest. Yet recent studies suggest circumscribed abnormalities in resting-state functional magnetic resonance imaging connectivity in prodromal Huntington's disease, despite the spectrum of behavioural changes preceding a manifest diagnosis. The present study used two complementary analytical approaches to examine whole-brain resting-state functional magnetic resonance imaging connectivity in prodromal Huntington's disease. Network topology was studied using graph theory and simple functional connectivity amongst brain regions was explored using the network-based statistic. Participants consisted of gene-negative controls (n = 16) and prodromal Huntington's disease individuals (n = 48) with various stages of disease progression to examine the influence of disease burden on intrinsic connectivity. Graph theory analyses showed that global network interconnectivity approximated a random network topology as proximity to diagnosis neared and this was associated with decreased connectivity amongst highly-connected rich-club network hubs, which integrate processing from diverse brain regions. However, functional segregation within the global network (average clustering) was preserved. Functional segregation was also largely maintained at the local level, except for the notable decrease in the diversity of anterior insula intermodular-interconnections (participation coefficient), irrespective of disease burden. In contrast, network-based statistic analyses revealed patterns of weakened frontostriatal connections and strengthened frontal-posterior connections that evolved as disease burden increased. These disturbances were often related to long-range connections involving peripheral nodes and interhemispheric connections. A strong association was found between weaker connectivity and decreased rich-club organization, indicating that whole-brain simple connectivity partially expressed disturbances in the communication of highly-connected hubs. However, network topology and network-based statistic connectivity metrics did not correlate with key markers of executive dysfunction (Stroop Test, Trail Making Test) in prodromal Huntington's disease, which instead were related to whole-brain connectivity disturbances in nodes (right inferior parietal, right thalamus, left anterior cingulate) that exhibited multiple aberrant connections and that mediate executive control. Altogether, our results show for the first time a largely disease burden-dependent functional reorganization of whole-brain networks in prodromal Huntington's disease. Both analytic approaches provided a unique window into brain reorganization that was not related to brain atrophy or motor symptoms. Longitudinal studies currently in progress will chart the course of functional changes to determine the most sensitive markers of disease progression. © The Author (2015). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Noise-induced relations between network connectivity and dynamics

NASA Astrophysics Data System (ADS)

Ching, Emily Sc

Many biological systems of interest can be represented as networks of many nodes that are interacting with one another. Often these systems are subject to external influence or noise. One of the central issues is to understand the relation between dynamics and the interaction pattern of the system or the connectivity structure of the network. In particular, a challenging problem is to infer the network connectivity structure from the dynamics. In this talk, we show that for stochastic dynamical systems subjected to noise, the presence of noise gives rise to mathematical relations between the network connectivity structure and quantities that can be calculated using solely the time-series measurements of the dynamics of the nodes. We present these relations for both undirected networks with bidirectional coupling and directed networks with directional coupling and discuss how such relations can be utilized to infer the network connectivity structure of the systems. Work supported by the Hong Kong Research Grants Council under Grant No. CUHK 14300914.

PRP: peripheral routing protocol for WSN realistic marginal mobility model

NASA Astrophysics Data System (ADS)

Tudorache, I. G.; Popescu, A. M.; Kemp, A. H.

2017-02-01

This article proposes a new routing protocol called Peripheral Routing Protocol (PRP) for the scenario where the mobile destination (D) moves at the wireless sensor network (WSN) periphery for gathering data. From a connectivity point of view, when D follows the marginal mobility model (MMM), the WSN becomes a hybrid network: a sparse network, because of the interrupted connectivity between D and the rest of the nodes and a well-connected network, because of the connectivity between all the other nodes of the WSN except D. It will be proven through MATLAB simulations that, for a military application scenario where D's connectivity to the WSN varies between 10% and 95%, compared with the 100% case, PRP outperforms routing protocols recommended for Mobile Ad-hoc Networks (MANET) in three ways: it maintains an average Packet Delivery Ratio (PDR) over 90%, a below 10% and 5% increase for the Average End to End Delay (AETED) and energy per transmitted packet.

A Novel Characterization of Amalgamated Networks in Natural Systems

PubMed Central

Barranca, Victor J.; Zhou, Douglas; Cai, David

2015-01-01

Densely-connected networks are prominent among natural systems, exhibiting structural characteristics often optimized for biological function. To reveal such features in highly-connected networks, we introduce a new network characterization determined by a decomposition of network-connectivity into low-rank and sparse components. Based on these components, we discover a new class of networks we define as amalgamated networks, which exhibit large functional groups and dense connectivity. Analyzing recent experimental findings on cerebral cortex, food-web, and gene regulatory networks, we establish the unique importance of amalgamated networks in fostering biologically advantageous properties, including rapid communication among nodes, structural stability under attacks, and separation of network activity into distinct functional modules. We further observe that our network characterization is scalable with network size and connectivity, thereby identifying robust features significant to diverse physical systems, which are typically undetectable by conventional characterizations of connectivity. We expect that studying the amalgamation properties of biological networks may offer new insights into understanding their structure-function relationships. PMID:26035066

Functional connectivity in the developing brain: A longitudinal study from 4 to 9 months of age

PubMed Central

Damaraju, E.; Caprihan, A.; Lowe, J.R.; Allen, E.A.; Calhoun, V.D.; Phillips, J.P.

2013-01-01

We characterize the development of intrinsic connectivity networks (ICNs) from 4 to 9 months of age with resting state magnetic resonance imaging performed on sleeping infants without sedative medication. Data is analyzed with independent component analysis (ICA). Using both low (30 components) and high (100 components) ICA model order decompositions, we find that the functional network connectivity (FNC) map is largely similar at both 4 and 9 months. However at 9 months the connectivity strength decreases within local networks and increases between more distant networks. The connectivity within the default-mode network, which contains both local and more distant nodes, also increases in strength with age. The low frequency power spectrum increases with age only in the posterior cingulate cortex and posterior default mode network. These findings are consistent with a general developmental pattern of increasing longer distance functional connectivity over the first year of life and raise questions regarding the developmental importance of the posterior cingulate at this age. PMID:23994454

Functional connectivity in the developing brain: a longitudinal study from 4 to 9months of age.

PubMed

Damaraju, E; Caprihan, A; Lowe, J R; Allen, E A; Calhoun, V D; Phillips, J P

2014-01-01

We characterize the development of intrinsic connectivity networks (ICNs) from 4 to 9months of age with resting state magnetic resonance imaging performed on sleeping infants without sedative medication. Data is analyzed with independent component analysis (ICA). Using both low (30 components) and high (100 components) ICA model order decompositions, we find that the functional network connectivity (FNC) map is largely similar at both 4 and 9months. However at 9months the connectivity strength decreases within local networks and increases between more distant networks. The connectivity within the default-mode network, which contains both local and more distant nodes, also increases in strength with age. The low frequency power spectrum increases with age only in the posterior cingulate cortex and posterior default mode network. These findings are consistent with a general developmental pattern of increasing longer distance functional connectivity over the first year of life and raise questions regarding the developmental importance of the posterior cingulate at this age. © 2013.

Differential brain network activity across mood states in bipolar disorder.

PubMed

Brady, Roscoe O; Tandon, Neeraj; Masters, Grace A; Margolis, Allison; Cohen, Bruce M; Keshavan, Matcheri; Öngür, Dost

2017-01-01

This study aimed to identify how the activity of large-scale brain networks differs between mood states in bipolar disorder. The authors measured spontaneous brain activity in subjects with bipolar disorder in mania and euthymia and compared these states to a healthy comparison population. 23 subjects with bipolar disorder type I in a manic episode, 24 euthymic bipolar I subjects, and 23 matched healthy comparison (HC) subjects underwent resting state fMRI scans. Using an existing parcellation of the whole brain, we measured functional connectivity between brain regions and identified significant differences between groups. In unbiased whole-brain analyses, functional connectivity between parietal, occipital, and frontal nodes within the dorsal attention network (DAN) were significantly greater in mania than euthymia or HC subjects. In the default mode network (DMN), connectivity between dorsal frontal nodes and the rest of the DMN differentiated both mood state and diagnosis. The bipolar groups were separate cohorts rather than subjects imaged longitudinally across mood states. Bipolar mood states are associated with highly significant alterations in connectivity in two large-scale brain networks. These same networks also differentiate bipolar mania and euthymia from a HC population. State related changes in DAN and DMN connectivity suggest a circuit based pathology underlying cognitive dysfunction as well as activity/reactivity in bipolar mania. Altered activities in neural networks may be biomarkers of bipolar disorder diagnosis and mood state that are accessible to neuromodulation and are promising novel targets for scientific investigation and possible clinical intervention. Copyright © 2016 Elsevier B.V. All rights reserved.

The impact of land use change and hydroclimatic variability on landscape connectivity dynamics across surface water networks at subcontinental scale

NASA Astrophysics Data System (ADS)

Tulbure, M. G.; Bishop-Taylor, R.; Broich, M.

2017-12-01

Land use (LU) change and hydroclimatic variability affect spatiotemporal landscape connectivity dynamics, important for species movement and dispersal. Despite the fact that LU change can strongly influence dispersal potential over time, prior research has only focused on the impacts of dynamic changes in the distribution of potential habitats. We used 8 time-steps of historical LU together with a Landsat-derived time-series of surface water habitat dynamics (1986-2011) over the Murray-Darling Basin (MDB), a region with extreme hydroclimatic variability, impacted by LU changes. To assess how changing LU and hydroclimatic variability affect landscape connectivity across time, we compared 4 scenarios, namely one where both climate and LU are dynamic over time, one where climate is kept steady (i.e. a median surface water extent layer), and two scenarios where LU is kept steady (i.e. resistance values associated with the most recent or the first LU layer). We used circuit theory to assign landscape features with `resistance' costs and graph theory network analysis, with surface water habitats as `nodes' connected by dispersal paths or `edges' Findings comparing a dry and an average season show high differences in number of nodes (14581 vs 21544) and resistance distances. The combined effect of LU change and landscape wetness was lower than expected, likely a function of the large, MDB-wide, aggregation scale. Spatially explicit analyses are expected to identify areas where the synergistic effect of LU change and landscape wetness greatly reduce or increase landscape connectivity, as well as areas where the two effects cancel each other out.

Circuit theory and model-based inference for landscape connectivity

USGS Publications Warehouse

Hanks, Ephraim M.; Hooten, Mevin B.

2013-01-01

Circuit theory has seen extensive recent use in the field of ecology, where it is often applied to study functional connectivity. The landscape is typically represented by a network of nodes and resistors, with the resistance between nodes a function of landscape characteristics. The effective distance between two locations on a landscape is represented by the resistance distance between the nodes in the network. Circuit theory has been applied to many other scientific fields for exploratory analyses, but parametric models for circuits are not common in the scientific literature. To model circuits explicitly, we demonstrate a link between Gaussian Markov random fields and contemporary circuit theory using a covariance structure that induces the necessary resistance distance. This provides a parametric model for second-order observations from such a system. In the landscape ecology setting, the proposed model provides a simple framework where inference can be obtained for effects that landscape features have on functional connectivity. We illustrate the approach through a landscape genetics study linking gene flow in alpine chamois (Rupicapra rupicapra) to the underlying landscape.

Topological relationships between brain and social networks.

PubMed

Sakata, Shuzo; Yamamori, Tetsuo

2007-01-01

Brains are complex networks. Previously, we revealed that specific connected structures are either significantly abundant or rare in cortical networks. However, it remains unknown whether systems from other disciplines have similar architectures to brains. By applying network-theoretical methods, here we show topological similarities between brain and social networks. We found that the statistical relevance of specific tied structures differs between social "friendship" and "disliking" networks, suggesting relation-type-specific topology of social networks. Surprisingly, overrepresented connected structures in brain networks are more similar to those in the friendship networks than to those in other networks. We found that balanced and imbalanced reciprocal connections between nodes are significantly abundant and rare, respectively, whereas these results are unpredictable by simply counting mutual connections. We interpret these results as evidence of positive selection of balanced mutuality between nodes. These results also imply the existence of underlying common principles behind the organization of brain and social networks.

Mobile Router Developed and Tested

NASA Technical Reports Server (NTRS)

Ivancic, William D.

2002-01-01

The NASA Glenn Research Center, under a NASA Space Act Agreement with Cisco Systems, has been performing joint networking research to apply Internet-based technologies and protocols to space-based communications. As a result of this research, NASA performed stringent performance testing of the mobile router, including the interaction of routing and the transport-level protocol. In addition, Cisco Systems developed the mobile router for both commercial and Government markets. The code has become part of the Cisco Systems Internetworking Operating System (IOS) as of release 12.2 (4) T--which will make this capability available to the community at large. The mobile router is software code that resides in a network router and enables entire networks to roam while maintaining connectivity to the Internet. This router code is pertinent to a myriad of applications for both Government and commercial sectors, including the "wireless battlefield." NASA and the Department of Defense will utilize this technology for near-planetary observation and sensing spacecraft. It is also a key enabling technology for aviation-based information applications. Mobile routing will make it possible for information such as weather, air traffic control, voice, and video to be transmitted to aircraft using Internet-based protocols. This technology shows great promise in reducing congested airways and mitigating aviation disasters due to bad weather. The mobile router can also be incorporated into emergency vehicles (such as ambulances and life-flight aircraft) to provide real-time connectivity back to the hospital and health-care experts, enabling the timely application of emergency care. Commercial applications include entertainment services, Internet protocol (IP) telephone, and Internet connectivity for cruise ships, commercial shipping, tour buses, aircraft, and eventually cars. A mobile router, which is based on mobile IP, allows hosts (mobile nodes) to seamlessly "roam" among various IP subnetworks. This is essential in many wireless networks. A mobile router, unlike a mobile IP node, allows entire networks to roam. Hence, a device connected to the mobile router does not need to be a mobile node because the mobile router provides the roaming capabilities. There are three basic elements in the mobile IP: the home agent, the foreign agent, and the mobile node. The home agent is a router on a mobile node's home network that tunnels datagrams for delivery to the mobile node when it is away from home. The foreign agent is a router on a remote network that provides routing services to a registered mobile node. The mobile node is a host or router that changes its point of attachment from one network or subnetwork to another. In mobile routing, virtual communications are maintained by the home agent, which forwards all packets for the mobile networks to the foreign agent. The foreign agent passes the packets to the mobile router, which then forwards the packets to the devices on its networks. As the mobile router moves, it will register with its home agent on its whereabouts via the foreign agent to assure continuous connectivity.

Neighboring and connectivity-aware routing in VANETs.

PubMed

Ghafoor, Huma; Koo, Insoo; Gohar, Nasir-ud-Din

2014-01-01

A novel position-based routing protocol anchor-based connectivity-aware routing (ACAR) for vehicular ad hoc networks (VANETs) is proposed in this paper to ensure connectivity of routes with more successfully delivered packets. Both buses and cars are considered as vehicular nodes running in both clockwise and anticlockwise directions in a city scenario. Both directions are taken into account for faster communication. ACAR is a hybrid protocol, using both the greedy forwarding approach and the store-carry-and-forward approach to minimize the packet drop rate on the basis of certain assumptions. Our solution to situations that occur when the network is sparse and when any (source or intermediate) node has left its initial position makes this protocol different from those existing in the literature. We consider only vehicle-to-vehicle (V2V) communication in which both the source and destination nodes are moving vehicles. Also, no road-side units are considered. Finally, we compare our protocol with A-STAR (a plausible connectivity-aware routing protocol for city environments), and simulation results in NS-2 show improvement in the number of packets delivered to the destination using fewer hops. Also, we show that ACAR has more successfully-delivered long-distance packets with reasonable packet delay than A-STAR.

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.

Degree-based statistic and center persistency for brain connectivity analysis.

PubMed

Yoo, Kwangsun; Lee, Peter; Chung, Moo K; Sohn, William S; Chung, Sun Ju; Na, Duk L; Ju, Daheen; Jeong, Yong

2017-01-01

Brain connectivity analyses have been widely performed to investigate the organization and functioning of the brain, or to observe changes in neurological or psychiatric conditions. However, connectivity analysis inevitably introduces the problem of mass-univariate hypothesis testing. Although, several cluster-wise correction methods have been suggested to address this problem and shown to provide high sensitivity, these approaches fundamentally have two drawbacks: the lack of spatial specificity (localization power) and the arbitrariness of an initial cluster-forming threshold. In this study, we propose a novel method, degree-based statistic (DBS), performing cluster-wise inference. DBS is designed to overcome the above-mentioned two shortcomings. From a network perspective, a few brain regions are of critical importance and considered to play pivotal roles in network integration. Regarding this notion, DBS defines a cluster as a set of edges of which one ending node is shared. This definition enables the efficient detection of clusters and their center nodes. Furthermore, a new measure of a cluster, center persistency (CP) was introduced. The efficiency of DBS with a known "ground truth" simulation was demonstrated. Then they applied DBS to two experimental datasets and showed that DBS successfully detects the persistent clusters. In conclusion, by adopting a graph theoretical concept of degrees and borrowing the concept of persistence from algebraic topology, DBS could sensitively identify clusters with centric nodes that would play pivotal roles in an effect of interest. DBS is potentially widely applicable to variable cognitive or clinical situations and allows us to obtain statistically reliable and easily interpretable results. Hum Brain Mapp 38:165-181, 2017. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

KENNEDY SPACE CENTER, FLA. - Astronaut Tim Kopra (facing camera) aids in Intravehicular Activity (IVA) constraints testing on the Italian-built Node 2, a future element of the International Space Station. The second of three Station connecting modules, the Node 2 attaches to the end of the U.S. Lab and provides attach locations for several other elements. Kopra is currently assigned technical duties in the Space Station Branch of the Astronaut Office, where his primary focus involves the testing of crew interfaces for two future ISS modules as well as the implementation of support computers and operational Local Area Network on ISS. Node 2 is scheduled to launch on mission STS-120, Station assembly flight 10A.

NASA Image and Video Library

2004-02-03

KENNEDY SPACE CENTER, FLA. - Astronaut Tim Kopra (facing camera) aids in Intravehicular Activity (IVA) constraints testing on the Italian-built Node 2, a future element of the International Space Station. The second of three Station connecting modules, the Node 2 attaches to the end of the U.S. Lab and provides attach locations for several other elements. Kopra is currently assigned technical duties in the Space Station Branch of the Astronaut Office, where his primary focus involves the testing of crew interfaces for two future ISS modules as well as the implementation of support computers and operational Local Area Network on ISS. Node 2 is scheduled to launch on mission STS-120, Station assembly flight 10A.

KENNEDY SPACE CENTER, FLA. - Astronaut Tim Kopra talks to a technician (off-camera) during Intravehicular Activity (IVA) constraints testing on the Italian-built Node 2, a future element of the International Space Station. The second of three Station connecting modules, the Node 2 attaches to the end of the U.S. Lab and provides attach locations for several other elements. Kopra is currently assigned technical duties in the Space Station Branch of the Astronaut Office, where his primary focus involves the testing of crew interfaces for two future ISS modules as well as the implementation of support computers and operational Local Area Network on ISS. Node 2 is scheduled to launch on mission STS-120, Station assembly flight 10A.

NASA Image and Video Library

2004-02-03

KENNEDY SPACE CENTER, FLA. - Astronaut Tim Kopra talks to a technician (off-camera) during Intravehicular Activity (IVA) constraints testing on the Italian-built Node 2, a future element of the International Space Station. The second of three Station connecting modules, the Node 2 attaches to the end of the U.S. Lab and provides attach locations for several other elements. Kopra is currently assigned technical duties in the Space Station Branch of the Astronaut Office, where his primary focus involves the testing of crew interfaces for two future ISS modules as well as the implementation of support computers and operational Local Area Network on ISS. Node 2 is scheduled to launch on mission STS-120, Station assembly flight 10A.

A Novel Topology Control Approach to Maintain the Node Degree in Dynamic Wireless Sensor Networks

PubMed Central

Huang, Yuanjiang; Martínez, José-Fernán; Díaz, Vicente Hernández; Sendra, Juana

2014-01-01

Topology control is an important technique to improve the connectivity and the reliability of Wireless Sensor Networks (WSNs) by means of adjusting the communication range of wireless sensor nodes. In this paper, a novel Fuzzy-logic Topology Control (FTC) is proposed to achieve any desired average node degree by adaptively changing communication range, thus improving the network connectivity, which is the main target of FTC. FTC is a fully localized control algorithm, and does not rely on location information of neighbors. Instead of designing membership functions and if-then rules for fuzzy-logic controller, FTC is constructed from the training data set to facilitate the design process. FTC is proved to be accurate, stable and has short settling time. In order to compare it with other representative localized algorithms (NONE, FLSS, k-Neighbor and LTRT), FTC is evaluated through extensive simulations. The simulation results show that: firstly, similar to k-Neighbor algorithm, FTC is the best to achieve the desired average node degree as node density varies; secondly, FTC is comparable to FLSS and k-Neighbor in terms of energy-efficiency, but is better than LTRT and NONE; thirdly, FTC has the lowest average maximum communication range than other algorithms, which indicates that the most energy-consuming node in the network consumes the lowest power. PMID:24608008

Multi-species genetic connectivity in a terrestrial habitat network.

PubMed

Marrotte, Robby R; Bowman, Jeff; Brown, Michael G C; Cordes, Chad; Morris, Kimberley Y; Prentice, Melanie B; Wilson, Paul J

2017-01-01

Habitat fragmentation reduces genetic connectivity for multiple species, yet conservation efforts tend to rely heavily on single-species connectivity estimates to inform land-use planning. Such conservation activities may benefit from multi-species connectivity estimates, which provide a simple and practical means to mitigate the effects of habitat fragmentation for a larger number of species. To test the validity of a multi-species connectivity model, we used neutral microsatellite genetic datasets of Canada lynx ( Lynx canadensis ), American marten ( Martes americana ), fisher ( Pekania pennanti ), and southern flying squirrel ( Glaucomys volans ) to evaluate multi-species genetic connectivity across Ontario, Canada. We used linear models to compare node-based estimates of genetic connectivity for each species to point-based estimates of landscape connectivity (current density) derived from circuit theory. To our knowledge, we are the first to evaluate current density as a measure of genetic connectivity. Our results depended on landscape context: habitat amount was more important than current density in explaining multi-species genetic connectivity in the northern part of our study area, where habitat was abundant and fragmentation was low. In the south however, where fragmentation was prevalent, genetic connectivity was correlated with current density. Contrary to our expectations however, locations with a high probability of movement as reflected by high current density were negatively associated with gene flow. Subsequent analyses of circuit theory outputs showed that high current density was also associated with high effective resistance, underscoring that the presence of pinch points is not necessarily indicative of gene flow. Overall, our study appears to provide support for the hypothesis that landscape pattern is important when habitat amount is low. We also conclude that while current density is proportional to the probability of movement per unit area, this does not imply increased gene flow, since high current density tends to be a result of neighbouring pixels with high cost of movement (e.g., low habitat amount). In other words, pinch points with high current density appear to constrict gene flow.

Performance Evaluation of AODV with Blackhole Attack

NASA Astrophysics Data System (ADS)

Dara, Karuna

2010-11-01

A Mobile Ad Hoc Network (MANET) is a temporary network set up by a wireless mobile computers moving arbitrary in the places that have no network infrastructure. These nodes maintain connectivity in a decentralized manner. Since the nodes communicate with each other, they cooperate by forwarding data packets to other nodes in the network. Thus the nodes find a path to the destination node using routing protocols. However, due to security vulnerabilities of the routing protocols, mobile ad-hoc networks are unprotected to attacks of the malicious nodes. One of these attacks is the Black Hole Attack against network integrity absorbing all data packets in the network. Since the data packets do not reach the destination node on account of this attack, data loss will occur. In this paper, we simulated the black hole attack in various mobile ad-hoc network scenarios using AODV routing protocol of MANET and have tried to find a effect if number of nodes are increased with increase in malicious nodes.

Tau burden and the functional connectome in Alzheimer's disease and progressive supranuclear palsy.

PubMed

Cope, Thomas E; Rittman, Timothy; Borchert, Robin J; Jones, P Simon; Vatansever, Deniz; Allinson, Kieren; Passamonti, Luca; Vazquez Rodriguez, Patricia; Bevan-Jones, W Richard; O'Brien, John T; Rowe, James B

2018-02-01

Alzheimer's disease and progressive supranuclear palsy (PSP) represent neurodegenerative tauopathies with predominantly cortical versus subcortical disease burden. In Alzheimer's disease, neuropathology and atrophy preferentially affect 'hub' brain regions that are densely connected. It was unclear whether hubs are differentially affected by neurodegeneration because they are more likely to receive pathological proteins that propagate trans-neuronally, in a prion-like manner, or whether they are selectively vulnerable due to a lack of local trophic factors, higher metabolic demands, or differential gene expression. We assessed the relationship between tau burden and brain functional connectivity, by combining in vivo PET imaging using the ligand AV-1451, and graph theoretic measures of resting state functional MRI in 17 patients with Alzheimer's disease, 17 patients with PSP, and 12 controls. Strongly connected nodes displayed more tau pathology in Alzheimer's disease, independently of intrinsic connectivity network, validating the predictions of theories of trans-neuronal spread but not supporting a role for metabolic demands or deficient trophic support in tau accumulation. This was not a compensatory phenomenon, as the functional consequence of increasing tau burden in Alzheimer's disease was a progressive weakening of the connectivity of these same nodes, reducing weighted degree and local efficiency and resulting in weaker 'small-world' properties. Conversely, in PSP, unlike in Alzheimer's disease, those nodes that accrued pathological tau were those that displayed graph metric properties associated with increased metabolic demand and a lack of trophic support rather than strong functional connectivity. Together, these findings go some way towards explaining why Alzheimer's disease affects large scale connectivity networks throughout cortex while neuropathology in PSP is concentrated in a small number of subcortical structures. Further, we demonstrate that in PSP increasing tau burden in midbrain and deep nuclei was associated with strengthened cortico-cortical functional connectivity. Disrupted cortico-subcortical and cortico-brainstem interactions meant that information transfer took less direct paths, passing through a larger number of cortical nodes, reducing closeness centrality and eigenvector centrality in PSP, while increasing weighted degree, clustering, betweenness centrality and local efficiency. Our results have wide-ranging implications, from the validation of models of tau trafficking in humans to understanding the relationship between regional tau burden and brain functional reorganization. © The Author(s) (2018). Published by Oxford University Press on behalf of the Guarantors of Brain.

Axonal Membranes and Their Domains: Assembly and Function of the Axon Initial Segment and Node of Ranvier

PubMed Central

Nelson, Andrew D.; Jenkins, Paul M.

2017-01-01

Neurons are highly specialized cells of the nervous system that receive, process and transmit electrical signals critical for normal brain function. Here, we review the intricate organization of axonal membrane domains that facilitate rapid action potential conduction underlying communication between complex neuronal circuits. Two critical excitable domains of vertebrate axons are the axon initial segment (AIS) and the nodes of Ranvier, which are characterized by the high concentrations of voltage-gated ion channels, cell adhesion molecules and specialized cytoskeletal networks. The AIS is located at the proximal region of the axon and serves as the site of action potential initiation, while nodes of Ranvier, gaps between adjacent myelin sheaths, allow rapid propagation of the action potential through saltatory conduction. The AIS and nodes of Ranvier are assembled by ankyrins, spectrins and their associated binding partners through the clustering of membrane proteins and connection to the underlying cytoskeleton network. Although the AIS and nodes of Ranvier share similar protein composition, their mechanisms of assembly are strikingly different. Here we will cover the mechanisms of formation and maintenance of these axonal excitable membrane domains, specifically highlighting the similarities and differences between them. We will also discuss recent advances in super resolution fluorescence imaging which have elucidated the arrangement of the submembranous axonal cytoskeleton revealing a surprising structural organization necessary to maintain axonal organization and function. Finally, human mutations in axonal domain components have been associated with a growing number of neurological disorders including severe cognitive dysfunction, epilepsy, autism, neurodegenerative diseases and psychiatric disorders. Overall, this review highlights the assembly, maintenance and function of axonal excitable domains, particularly the AIS and nodes of Ranvier, and how abnormalities in these processes may contribute to disease. PMID:28536506

Laterality effects in functional connectivity of the angular gyrus during rest and episodic retrieval.

PubMed

Bellana, Buddhika; Liu, Zhongxu; Anderson, John A E; Moscovitch, Morris; Grady, Cheryl L

2016-01-08

The angular gyrus (AG) is consistently reported in neuroimaging studies of episodic memory retrieval and is a fundamental node within the default mode network (DMN). Its specific contribution to episodic memory is debated, with some suggesting it is important for the subjective experience of episodic recollection, rather than retrieval of objective episodic details. Across studies of episodic retrieval, the left AG is recruited more reliably than the right. We explored functional connectivity of the right and left AG with the DMN during rest and retrieval to assess whether connectivity could provide insight into the nature of this laterality effect. Using data from the publically available 1000 Functional Connectome Project, 8min of resting fMRI data from 180 healthy young adults were analysed. Whole-brain functional connectivity at rest was measured using a seed-based Partial Least Squares (seed-PLS) approach (McIntosh and Lobaugh, 2004) with bilateral AG seeds. A subsequent analysis used 6-min of rest and 6-min of unconstrained, silent retrieval of autobiographical events from a new sample of 20 younger adults. Analysis of this dataset took a more targeted approach to functional connectivity analysis, consisting of univariate pairwise correlations restricted to nodes of the DMN. The seed-PLS analysis resulted in two Latent Variables that together explained ~86% of the shared cross-block covariance. The first LV revealed a common network consistent with the DMN and engaging the AG bilaterally, whereas the second LV revealed a less robust, yet significant, laterality effect in connectivity - the left AG was more strongly connected to the DMN. Univariate analyses of the second sample again revealed better connectivity between the left AG and the DMN at rest. However, during retrieval the left AG was more strongly connected than the right to non-medial temporal (MTL) nodes of the DMN, and MTL nodes were more strongly connected to the right AG. The multivariate analysis of resting connectivity revealed that the left and right AG show similar connectivity with the DMN. Only after accounting for this commonality were we able to detect a left laterality effect in DMN connectivity. Further probing with univariate connectivity analyses during retrieval demonstrates that the left preference we observe is restricted to the non-MTL regions of the DMN, whereas the right AG shows significantly better connectivity with the MTL. These data suggest bilateral involvement of the AG during retrieval, despite the focus on the left AG in the literature. Furthermore, the results suggest that the contribution of the left AG to retrieval may be separable from that of the MTL, consistent with a role for the left AG in the subjective aspects of recollection in memory, whereas the MTL and the right AG may contribute to objective recollection of specific memory details. Copyright © 2015 Elsevier Ltd. All rights reserved.

Statistical mechanics of scale-free gene expression networks

NASA Astrophysics Data System (ADS)

Gross, Eitan

2012-12-01

The gene co-expression networks of many organisms including bacteria, mice and man exhibit scale-free distribution. This heterogeneous distribution of connections decreases the vulnerability of the network to random attacks and thus may confer the genetic replication machinery an intrinsic resilience to such attacks, triggered by changing environmental conditions that the organism may be subject to during evolution. This resilience to random attacks comes at an energetic cost, however, reflected by the lower entropy of the scale-free distribution compared to the more homogenous, random network. In this study we found that the cell cycle-regulated gene expression pattern of the yeast Saccharomyces cerevisiae obeys a power-law distribution with an exponent α = 2.1 and an entropy of 1.58. The latter is very close to the maximal value of 1.65 obtained from linear optimization of the entropy function under the constraint of a constant cost function, determined by the average degree connectivity . We further show that the yeast's gene expression network can achieve scale-free distribution in a process that does not involve growth but rather via re-wiring of the connections between nodes of an ordered network. Our results support the idea of an evolutionary selection, which acts at the level of the protein sequence, and is compatible with the notion of greater biological importance of highly connected nodes in the protein interaction network. Our constrained re-wiring model provides a theoretical framework for a putative thermodynamically driven evolutionary selection process.

A scale-free systems theory of motivation and addiction.

PubMed

Chambers, R Andrew; Bickel, Warren K; Potenza, Marc N

2007-01-01

Scale-free organizations, characterized by uneven distributions of linkages between nodal elements, describe the structure and function of many life-based complex systems developing under evolutionary pressures. We explore motivated behavior as a scale-free map toward a comprehensive translational theory of addiction. Motivational and behavioral repertoires are reframed as link and nodal element sets, respectively, comprising a scale-free structure. These sets are generated by semi-independent information-processing streams within cortical-striatal circuits that cooperatively provide decision-making and sequential processing functions necessary for traversing maps of motivational links connecting behavioral nodes. Dopamine modulation of cortical-striatal plasticity serves a central-hierarchical mechanism for survival-adaptive sculpting and development of motivational-behavioral repertoires by guiding a scale-free design. Drug-induced dopamine activity promotes drug taking as a highly connected behavioral hub at the expense of natural-adaptive motivational links and behavioral nodes. Conceptualizing addiction as pathological alteration of scale-free motivational-behavioral repertoires unifies neurobiological, neurocomputational and behavioral research while addressing addiction vulnerability in adolescence and psychiatric illness. This model may inform integrative research in defining more effective prevention and treatment strategies for addiction.

A Scale-Free Systems Theory of Motivation and Addiction

PubMed Central

Bickel, Warren K.; Potenza, Marc N.

2007-01-01

Scale-free organizations, characterized by uneven distributions of linkages between nodal elements, describe the structure and function of many life-based complex systems developing under evolutionary pressures. We explore motivated behavior as a scale-free map toward a comprehensive translational theory of addiction. Motivational and behavioral repertoires are reframed as link and nodal element sets, respectively, comprising a scale-free structure. These sets are generated by semi-independent information-processing streams within cortical-striatal circuits that cooperatively provide decision-making and sequential processing functions necessary for traversing maps of motivational links connecting behavioral nodes. Dopamine modulation of cortical-striatal plasticity serves a central-hierarchical mechanism for survival-adaptive sculpting and development of motivational-behavioral repertoires by guiding a scale-free design. Drug-induced dopamine activity promotes drug-taking as a highly connected behavioral hub at the expense of natural-adaptive motivational links and behavioral nodes. Conceptualizing addiction as pathological alteration of scale-free motivational-behavioral repertoires unifies neurobiological, neurocomputational and behavioral research while addressing addiction vulnerability in adolescence and psychiatric illness. This model may inform integrative research in defining more effective prevention and treatment strategies for addiction. PMID:17574673

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.

A Network-Based Method to Assess the Statistical Significance of Mild Co-Regulation Effects

PubMed Central

Horvát, Emőke-Ágnes; Zhang, Jitao David; Uhlmann, Stefan; Sahin, Özgür; Zweig, Katharina Anna

2013-01-01

Recent development of high-throughput, multiplexing technology has initiated projects that systematically investigate interactions between two types of components in biological networks, for instance transcription factors and promoter sequences, or microRNAs (miRNAs) and mRNAs. In terms of network biology, such screening approaches primarily attempt to elucidate relations between biological components of two distinct types, which can be represented as edges between nodes in a bipartite graph. However, it is often desirable not only to determine regulatory relationships between nodes of different types, but also to understand the connection patterns of nodes of the same type. Especially interesting is the co-occurrence of two nodes of the same type, i.e., the number of their common neighbours, which current high-throughput screening analysis fails to address. The co-occurrence gives the number of circumstances under which both of the biological components are influenced in the same way. Here we present SICORE, a novel network-based method to detect pairs of nodes with a statistically significant co-occurrence. We first show the stability of the proposed method on artificial data sets: when randomly adding and deleting observations we obtain reliable results even with noise exceeding the expected level in large-scale experiments. Subsequently, we illustrate the viability of the method based on the analysis of a proteomic screening data set to reveal regulatory patterns of human microRNAs targeting proteins in the EGFR-driven cell cycle signalling system. Since statistically significant co-occurrence may indicate functional synergy and the mechanisms underlying canalization, and thus hold promise in drug target identification and therapeutic development, we provide a platform-independent implementation of SICORE with a graphical user interface as a novel tool in the arsenal of high-throughput screening analysis. PMID:24039936

Towards designing robust coupled networks

NASA Astrophysics Data System (ADS)

Schneider, Christian M.; Yazdani, Nuri; Araújo, Nuno A. M.; Havlin, Shlomo; Herrmann, Hans J.

2013-06-01

Natural and technological interdependent systems have been shown to be highly vulnerable due to cascading failures and an abrupt collapse of global connectivity under initial failure. Mitigating the risk by partial disconnection endangers their functionality. Here we propose a systematic strategy of selecting a minimum number of autonomous nodes that guarantee a smooth transition in robustness. Our method which is based on betweenness is tested on various examples including the famous 2003 electrical blackout of Italy. We show that, with this strategy, the necessary number of autonomous nodes can be reduced by a factor of five compared to a random choice. We also find that the transition to abrupt collapse follows tricritical scaling characterized by a set of exponents which is independent on the protection strategy.

The BlueGene/L supercomputer

NASA Astrophysics Data System (ADS)

Bhanota, Gyan; Chen, Dong; Gara, Alan; Vranas, Pavlos

2003-05-01

The architecture of the BlueGene/L massively parallel supercomputer is described. Each computing node consists of a single compute ASIC plus 256 MB of external memory. The compute ASIC integrates two 700 MHz PowerPC 440 integer CPU cores, two 2.8 Gflops floating point units, 4 MB of embedded DRAM as cache, a memory controller for external memory, six 1.4 Gbit/s bi-directional ports for a 3-dimensional torus network connection, three 2.8 Gbit/s bi-directional ports for connecting to a global tree network and a Gigabit Ethernet for I/O. 65,536 of such nodes are connected into a 3-d torus with a geometry of 32×32×64. The total peak performance of the system is 360 Teraflops and the total amount of memory is 16 TeraBytes.

Indentations and Starting Points in Traveling Sales Tour Problems: Implications for Theory

ERIC Educational Resources Information Center

MacGregor, James N.

2012-01-01

A complete, non-trivial, traveling sales tour problem contains at least one "indentation", where nodes in the interior of the point set are connected between two adjacent nodes on the boundary. Early research reported that human tours exhibited fewer such indentations than expected. A subsequent explanation proposed that this was because…

Effect of resource constraints on intersimilar coupled networks.

PubMed

Shai, S; Dobson, S

2012-12-01

Most real-world networks do not live in isolation but are often coupled together within a larger system. Recent studies have shown that intersimilarity between coupled networks increases the connectivity of the overall system. However, unlike connected nodes in a single network, coupled nodes often share resources, like time, energy, and memory, which can impede flow processes through contention when intersimilarly coupled. We study a model of a constrained susceptible-infected-recovered (SIR) process on a system consisting of two random networks sharing the same set of nodes, where nodes are limited to interact with (and therefore infect) a maximum number of neighbors at each epidemic time step. We obtain that, in agreement with previous studies, when no limit exists (regular SIR model), positively correlated (intersimilar) coupling results in a lower epidemic threshold than negatively correlated (interdissimilar) coupling. However, in the case of the constrained SIR model, the obtained epidemic threshold is lower with negatively correlated coupling. The latter finding differentiates our work from previous studies and provides another step towards revealing the qualitative differences between single and coupled networks.

EdgeMaps: visualizing explicit and implicit relations

NASA Astrophysics Data System (ADS)

Dörk, Marian; Carpendale, Sheelagh; Williamson, Carey

2011-01-01

In this work, we introduce EdgeMaps as a new method for integrating the visualization of explicit and implicit data relations. Explicit relations are specific connections between entities already present in a given dataset, while implicit relations are derived from multidimensional data based on shared properties and similarity measures. Many datasets include both types of relations, which are often difficult to represent together in information visualizations. Node-link diagrams typically focus on explicit data connections, while not incorporating implicit similarities between entities. Multi-dimensional scaling considers similarities between items, however, explicit links between nodes are not displayed. In contrast, EdgeMaps visualize both implicit and explicit relations by combining and complementing spatialization and graph drawing techniques. As a case study for this approach we chose a dataset of philosophers, their interests, influences, and birthdates. By introducing the limitation of activating only one node at a time, interesting visual patterns emerge that resemble the aesthetics of fireworks and waves. We argue that the interactive exploration of these patterns may allow the viewer to grasp the structure of a graph better than complex node-link visualizations.

Information spreading on mobile communication networks: A new model that incorporates human behaviors

NASA Astrophysics Data System (ADS)

Ren, Fei; Li, Sai-Ping; Liu, Chuang

2017-03-01

Recently, there is a growing interest in the modeling and simulation based on real social networks among researchers in multi-disciplines. Using an empirical social network constructed from the calling records of a Chinese mobile service provider, we here propose a new model to simulate the information spreading process. This model takes into account two important ingredients that exist in real human behaviors: information prevalence and preferential spreading. The fraction of informed nodes when the system reaches an asymptotically stable state is primarily determined by information prevalence, and the heterogeneity of link weights would slow down the information diffusion. Moreover, the sizes of blind clusters which consist of connected uninformed nodes show a power-law distribution, and these uninformed nodes correspond to a particular portion of nodes which are located at special positions in the network, namely at the edges of large clusters or inside the clusters connected through weak links. Since the simulations are performed on a real world network, the results should be useful in the understanding of the influences of social network structures and human behaviors on information propagation.

Effect of resource constraints on intersimilar coupled networks

NASA Astrophysics Data System (ADS)

Shai, S.; Dobson, S.

2012-12-01

Most real-world networks do not live in isolation but are often coupled together within a larger system. Recent studies have shown that intersimilarity between coupled networks increases the connectivity of the overall system. However, unlike connected nodes in a single network, coupled nodes often share resources, like time, energy, and memory, which can impede flow processes through contention when intersimilarly coupled. We study a model of a constrained susceptible-infected-recovered (SIR) process on a system consisting of two random networks sharing the same set of nodes, where nodes are limited to interact with (and therefore infect) a maximum number of neighbors at each epidemic time step. We obtain that, in agreement with previous studies, when no limit exists (regular SIR model), positively correlated (intersimilar) coupling results in a lower epidemic threshold than negatively correlated (interdissimilar) coupling. However, in the case of the constrained SIR model, the obtained epidemic threshold is lower with negatively correlated coupling. The latter finding differentiates our work from previous studies and provides another step towards revealing the qualitative differences between single and coupled networks.

A convex optimization method for self-organization in dynamic (FSO/RF) wireless networks

NASA Astrophysics Data System (ADS)

Llorca, Jaime; Davis, Christopher C.; Milner, Stuart D.

2008-08-01

Next generation communication networks are becoming increasingly complex systems. Previously, we presented a novel physics-based approach to model dynamic wireless networks as physical systems which react to local forces exerted on network nodes. We showed that under clear atmospheric conditions the network communication energy can be modeled as the potential energy of an analogous spring system and presented a distributed mobility control algorithm where nodes react to local forces driving the network to energy minimizing configurations. This paper extends our previous work by including the effects of atmospheric attenuation and transmitted power constraints in the optimization problem. We show how our new formulation still results in a convex energy minimization problem. Accordingly, an updated force-driven mobility control algorithm is presented. Forces on mobile backbone nodes are computed as the negative gradient of the new energy function. Results show how in the presence of atmospheric obscuration stronger forces are exerted on network nodes that make them move closer to each other, avoiding loss of connectivity. We show results in terms of network coverage and backbone connectivity and compare the developed algorithms for different scenarios.

Network testbed creation and validation

DOEpatents

Thai, Tan Q.; Urias, Vincent; Van Leeuwen, Brian P.; Watts, Kristopher K.; Sweeney, Andrew John

2017-03-21

Embodiments of network testbed creation and validation processes are described herein. A "network testbed" is a replicated environment used to validate a target network or an aspect of its design. Embodiments describe a network testbed that comprises virtual testbed nodes executed via a plurality of physical infrastructure nodes. The virtual testbed nodes utilize these hardware resources as a network "fabric," thereby enabling rapid configuration and reconfiguration of the virtual testbed nodes without requiring reconfiguration of the physical infrastructure nodes. Thus, in contrast to prior art solutions which require a tester manually build an emulated environment of physically connected network devices, embodiments receive or derive a target network description and build out a replica of this description using virtual testbed nodes executed via the physical infrastructure nodes. This process allows for the creation of very large (e.g., tens of thousands of network elements) and/or very topologically complex test networks.

Global epidemic invasion thresholds in directed cattle subpopulation networks having source, sink, and transit nodes.

PubMed

Schumm, Phillip; Scoglio, Caterina; Zhang, Qian; Balcan, Duygu

2015-02-21

Through the characterization of a metapopulation cattle disease model on a directed network having source, transit, and sink nodes, we derive two global epidemic invasion thresholds. The first threshold defines the conditions necessary for an epidemic to successfully spread at the global scale. The second threshold defines the criteria that permit an epidemic to move out of the giant strongly connected component and to invade the populations of the sink nodes. As each sink node represents a final waypoint for cattle before slaughter, the existence of an epidemic among the sink nodes is a serious threat to food security. We find that the relationship between these two thresholds depends on the relative proportions of transit and sink nodes in the system and the distributions of the in-degrees of both node types. These analytic results are verified through numerical realizations of the metapopulation cattle model. Published by Elsevier Ltd.

Line-plane broadcasting in a data communications network of a parallel computer

DOEpatents

Archer, Charles J.; Berg, Jeremy E.; Blocksome, Michael A.; Smith, Brian E.

2010-06-08

Methods, apparatus, and products are disclosed for line-plane broadcasting in a data communications network of a parallel computer, the parallel computer comprising a plurality of compute nodes connected together through the network, the network optimized for point to point data communications and characterized by at least a first dimension, a second dimension, and a third dimension, that include: initiating, by a broadcasting compute node, a broadcast operation, including sending a message to all of the compute nodes along an axis of the first dimension for the network; sending, by each compute node along the axis of the first dimension, the message to all of the compute nodes along an axis of the second dimension for the network; and sending, by each compute node along the axis of the second dimension, the message to all of the compute nodes along an axis of the third dimension for the network.

Line-plane broadcasting in a data communications network of a parallel computer

DOEpatents

Archer, Charles J.; Berg, Jeremy E.; Blocksome, Michael A.; Smith, Brian E.

2010-11-23

Methods, apparatus, and products are disclosed for line-plane broadcasting in a data communications network of a parallel computer, the parallel computer comprising a plurality of compute nodes connected together through the network, the network optimized for point to point data communications and characterized by at least a first dimension, a second dimension, and a third dimension, that include: initiating, by a broadcasting compute node, a broadcast operation, including sending a message to all of the compute nodes along an axis of the first dimension for the network; sending, by each compute node along the axis of the first dimension, the message to all of the compute nodes along an axis of the second dimension for the network; and sending, by each compute node along the axis of the second dimension, the message to all of the compute nodes along an axis of the third dimension for the network.

Network testbed creation and validation

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

Thai, Tan Q.; Urias, Vincent; Van Leeuwen, Brian P.

Embodiments of network testbed creation and validation processes are described herein. A "network testbed" is a replicated environment used to validate a target network or an aspect of its design. Embodiments describe a network testbed that comprises virtual testbed nodes executed via a plurality of physical infrastructure nodes. The virtual testbed nodes utilize these hardware resources as a network "fabric," thereby enabling rapid configuration and reconfiguration of the virtual testbed nodes without requiring reconfiguration of the physical infrastructure nodes. Thus, in contrast to prior art solutions which require a tester manually build an emulated environment of physically connected network devices,more » embodiments receive or derive a target network description and build out a replica of this description using virtual testbed nodes executed via the physical infrastructure nodes. This process allows for the creation of very large (e.g., tens of thousands of network elements) and/or very topologically complex test networks.« less

Learning and robustness to catch-and-release fishing in a shark social network

PubMed Central

Brown, Culum; Planes, Serge

2017-01-01

Individuals can play different roles in maintaining connectivity and social cohesion in animal populations and thereby influence population robustness to perturbations. We performed a social network analysis in a reef shark population to assess the vulnerability of the global network to node removal under different scenarios. We found that the network was generally robust to the removal of nodes with high centrality. The network appeared also highly robust to experimental fishing. Individual shark catchability decreased as a function of experience, as revealed by comparing capture frequency and site presence. Altogether, these features suggest that individuals learnt to avoid capture, which ultimately increased network robustness to experimental catch-and-release. Our results also suggest that some caution must be taken when using capture–recapture models often used to assess population size as assumptions (such as equal probabilities of capture and recapture) may be violated by individual learning to escape recapture. PMID:28298593

Joint Information Theoretic and Differential Geometrical Approach for Robust Automated Target Recognition

DTIC Science & Technology

2012-02-29

surface and Swiss roll) and real-world data sets (UCI Machine Learning Repository [12] and USPS digit handwriting data). In our experiments, we use...less than µn ( say µ = 0.8), we can first use screening technique to select µn candidate nodes, and then apply BIPS on them for further selection and...identified from node j to node i. So we can say the probability for the existence of this connection is approximately 82%. Given the probability matrix

Community Detection in Complex Networks via Clique Conductance.

PubMed

Lu, Zhenqi; Wahlström, Johan; Nehorai, Arye

2018-04-13

Network science plays a central role in understanding and modeling complex systems in many areas including physics, sociology, biology, computer science, economics, politics, and neuroscience. One of the most important features of networks is community structure, i.e., clustering of nodes that are locally densely interconnected. Communities reveal the hierarchical organization of nodes, and detecting communities is of great importance in the study of complex systems. Most existing community-detection methods consider low-order connection patterns at the level of individual links. But high-order connection patterns, at the level of small subnetworks, are generally not considered. In this paper, we develop a novel community-detection method based on cliques, i.e., local complete subnetworks. The proposed method overcomes the deficiencies of previous similar community-detection methods by considering the mathematical properties of cliques. We apply the proposed method to computer-generated graphs and real-world network datasets. When applied to networks with known community structure, the proposed method detects the structure with high fidelity and sensitivity. When applied to networks with no a priori information regarding community structure, the proposed method yields insightful results revealing the organization of these complex networks. We also show that the proposed method is guaranteed to detect near-optimal clusters in the bipartition case.

Visualizing Ecosystem Energy Flow in Complex Food Web Networks: A Comparison of Three Alaskan Large Marine Ecosystems

NASA Astrophysics Data System (ADS)

Kearney, K.; Aydin, K.

2016-02-01

Oceanic food webs are often depicted as network graphs, with the major organisms or functional groups displayed as nodes and the fluxes of between them as the edges. However, the large number of nodes and edges and high connectance of many management-oriented food webs coupled with graph layout algorithms poorly-suited to certain desired characteristics of food web visualizations often lead to hopelessly tangled diagrams that convey little information other than, "It's complex." Here, I combine several new graph visualization techniques- including a new node layout alorithm based on a trophic similarity (quantification of shared predator and prey) and trophic level, divided edge bundling for edge routing, and intelligent automated placement of labels- to create a much clearer visualization of the important fluxes through a food web. The technique will be used to highlight the differences in energy flow within three Alaskan Large Marine Ecosystems (the Bering Sea, Gulf of Alaska, and Aleutian Islands) that include very similar functional groups but unique energy pathways.

KSC-07pd0642

NASA Image and Video Library

2007-03-15

KENNEDY SPACE CENTER, FLA. -- In the Space Station Processing Facility, Mission STS-120 Pilot George Zamka (left, partially hidden) and Commander Pam Melroy (second from right in group), talk with members of the media and guests after a ceremony to unveil NASA's Node 2 module's new name, Harmony. The name, Harmony, was chosen from an academic competition involving thousands of students in kindergarten through high school. The Node 2 Challenge required students to learn about the International Space Station, build a scale model of the module, and write an essay explaining their proposed name. This will be the first U.S. piece of the space station named by someone other than a NASA official. Node 2 is a pressurized module that will act as a connecting port and passageway to additional international science labs and supply spacecraft. It also will be a work platform for the station's robotic arm. The module is scheduled to fly on mission STS-120 aboard Space Shuttle Atlantis targeted for later this year. Photo credit: NASA/Jim Grossmann

KSC-07pd0637

NASA Image and Video Library

2007-03-15

KENNEDY SPACE CENTER, FLA. -- In the Space Station Processing Facility, Mission STS-120 Pilot George Zamka (left) and Commander Pam Melroy begin to unveil the Node 2 module's new name, Harmony, as Russ Romanella, director of International Space Station and Spacecraft Processing presides over the ceremony. The name, Harmony, was chosen from an academic competition involving thousands of students in kindergarten through high school. The Node 2 Challenge required students to learn about the International Space Station, build a scale model of the module, and write an essay explaining their proposed name. This will be the first U.S. piece of the space station named by someone other than a NASA official. Node 2 is a pressurized module that will act as a connecting port and passageway to additional international science labs and supply spacecraft. It also will be a work platform for the station's robotic arm. The module is scheduled to fly on mission STS-120 aboard Space Shuttle Atlantis targeted for later this year. Photo credit: NASA/Jim Grossmann

Sensor node for remote monitoring of waterborne disease-causing bacteria.

PubMed

Kim, Kyukwang; Myung, Hyun

2015-05-05

A sensor node for sampling water and checking for the presence of harmful bacteria such as E. coli in water sources was developed in this research. A chromogenic enzyme substrate assay method was used to easily detect coliform bacteria by monitoring the color change of the sampled water mixed with a reagent. Live webcam image streaming to the web browser of the end user with a Wi-Fi connected sensor node shows the water color changes in real time. The liquid can be manipulated on the web-based user interface, and also can be observed by webcam feeds. Image streaming and web console servers run on an embedded processor with an expansion board. The UART channel of the expansion board is connected to an external Arduino board and a motor driver to control self-priming water pumps to sample the water, mix the reagent, and remove the water sample after the test is completed. The sensor node can repeat water testing until the test reagent is depleted. The authors anticipate that the use of the sensor node developed in this research can decrease the cost and required labor for testing samples in a factory environment and checking the water quality of local water sources in developing countries.

The raw disk i/o performance of compaq storage works RAID arrays under tru64 unix

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

Uselton, A C

2000-10-19

We report on the raw disk i/o performance of a set of Compaq StorageWorks RAID arrays connected to our cluster of Compaq ES40 computers via Fibre Channel. The best cumulative peak sustained data rate is l17MB/s per node for reads and 77MB/s per node for writes. This value occurs for a configuration in which a node has two Fibre Channel interfaces to a switch, which in turn has two connections to each of two Compaq StorageWorks RAID arrays. Each RAID array has two HSG80 RAID controllers controlling (together) two 5+p RAID chains. A 10% more space efficient arrangement using amore » single 1l+p RAID chain in place of the two 5+P chains is 25% slower for reads and 40% slower for writes.« less

A new centrality measure for identifying influential nodes in social networks

NASA Astrophysics Data System (ADS)

Rhouma, Delel; Ben Romdhane, Lotfi

2018-04-01

The identification of central nodes has been a key problem in the field of social network analysis. In fact, it is a measure that accounts the popularity or the visibility of an actor within a network. In order to capture this concept, various measures, either sample or more elaborate, has been developed. Nevertheless, many of "traditional" measures are not designed to be applicable to huge data. This paper sets out a new node centrality index suitable for large social network. It uses the amount of the neighbors of a node and connections between them to characterize a "pivot" node in the graph. We presented experimental results on real data sets which show the efficiency of our proposal.

T2AR: trust-aware ad-hoc routing protocol for MANET.

PubMed

Dhananjayan, Gayathri; Subbiah, Janakiraman

2016-01-01

Secure data transfer against the malicious attacks is an important issue in an infrastructure-less independent network called mobile ad-hoc network (MANET). Trust assurance between MANET nodes is the key parameter in the high-security provision under dynamic topology variations and open wireless constraints. But, the malicious behavior of nodes reduces the trust level of the nodes that leads to an insecure data delivery. The increase in malicious attacks causes the excessive energy consumption that leads to a reduction of network lifetime. The lack of positional information update of the nodes in ad-hoc on-demand vector (AODV) protocol during the connection establishment offers less trust level between the nodes. Hence, the trust rate computation using energy and mobility models and its update are the essential tasks for secure data delivery. This paper proposes a trust-aware ad-hoc routing (T2AR) protocol to improve the trust level between the nodes in MANET. The proposed method modifies the traditional AODV routing protocol with the constraints of trust rate, energy, mobility based malicious behavior prediction. The packet sequence ID matching from the log reports of neighbor nodes determine the trust rate that avoids the malicious report generation. Besides, the direct and indirect trust observation schemes utilization increases the trust level. Besides, the received signal strength indicator utilization determines the trusted node is within the communication range or not. The comparative analysis between the proposed T2AR with the existing methods such as TRUNCMAN, RBT, GR, FBR and DICOTIDS regarding the average end-to-end delay, throughput, false positives, packet delivery ratio shows the effectiveness of T2AR in the secure MANET environment design.

Organization of complex networks

NASA Astrophysics Data System (ADS)

Kitsak, Maksim

Many large complex systems can be successfully analyzed using the language of graphs and networks. Interactions between the objects in a network are treated as links connecting nodes. This approach to understanding the structure of networks is an important step toward understanding the way corresponding complex systems function. Using the tools of statistical physics, we analyze the structure of networks as they are found in complex systems such as the Internet, the World Wide Web, and numerous industrial and social networks. In the first chapter we apply the concept of self-similarity to the study of transport properties in complex networks. Self-similar or fractal networks, unlike non-fractal networks, exhibit similarity on a range of scales. We find that these fractal networks have transport properties that differ from those of non-fractal networks. In non-fractal networks, transport flows primarily through the hubs. In fractal networks, the self-similar structure requires any transport to also flow through nodes that have only a few connections. We also study, in models and in real networks, the crossover from fractal to non-fractal networks that occurs when a small number of random interactions are added by means of scaling techniques. In the second chapter we use k-core techniques to study dynamic processes in networks. The k-core of a network is the network's largest component that, within itself, exhibits all nodes with at least k connections. We use this k-core analysis to estimate the relative leadership positions of firms in the Life Science (LS) and Information and Communication Technology (ICT) sectors of industry. We study the differences in the k-core structure between the LS and the ICT sectors. We find that the lead segment (highest k-core) of the LS sector, unlike that of the ICT sector, is remarkably stable over time: once a particular firm enters the lead segment, it is likely to remain there for many years. In the third chapter we study how epidemics spread though networks. Our results indicate that a virus is more likely to infect a large area of a network if it originates at a node contained within k-core of high index k.

Reconstruction of the experimentally supported human protein interactome: what can we learn?

PubMed

Klapa, Maria I; Tsafou, Kalliopi; Theodoridis, Evangelos; Tsakalidis, Athanasios; Moschonas, Nicholas K

2013-10-02

Understanding the topology and dynamics of the human protein-protein interaction (PPI) network will significantly contribute to biomedical research, therefore its systematic reconstruction is required. Several meta-databases integrate source PPI datasets, but the protein node sets of their networks vary depending on the PPI data combined. Due to this inherent heterogeneity, the way in which the human PPI network expands via multiple dataset integration has not been comprehensively analyzed. We aim at assembling the human interactome in a global structured way and exploring it to gain insights of biological relevance. First, we defined the UniProtKB manually reviewed human "complete" proteome as the reference protein-node set and then we mined five major source PPI datasets for direct PPIs exclusively between the reference proteins. We updated the protein and publication identifiers and normalized all PPIs to the UniProt identifier level. The reconstructed interactome covers approximately 60% of the human proteome and has a scale-free structure. No apparent differentiating gene functional classification characteristics were identified for the unrepresented proteins. The source dataset integration augments the network mainly in PPIs. Polyubiquitin emerged as the highest-degree node, but the inclusion of most of its identified PPIs may be reconsidered. The high number (>300) of connections of the subsequent fifteen proteins correlates well with their essential biological role. According to the power-law network structure, the unrepresented proteins should mainly have up to four connections with equally poorly-connected interactors. Reconstructing the human interactome based on the a priori definition of the protein nodes enabled us to identify the currently included part of the human "complete" proteome, and discuss the role of the proteins within the network topology with respect to their function. As the network expansion has to comply with the scale-free theory, we suggest that the core of the human interactome has essentially emerged. Thus, it could be employed in systems biology and biomedical research, despite the considerable number of currently unrepresented proteins. The latter are probably involved in specialized physiological conditions, justifying the scarcity of related PPI information, and their identification can assist in designing relevant functional experiments and targeted text mining algorithms.

Broadcasting a message in a parallel computer

DOEpatents

Berg, Jeremy E [Rochester, MN; Faraj, Ahmad A [Rochester, MN

2011-08-02

Methods, systems, and products are disclosed for broadcasting a message in a parallel computer. The parallel computer includes a plurality of compute nodes connected together using a data communications network. The data communications network optimized for point to point data communications and is characterized by at least two dimensions. The compute nodes are organized into at least one operational group of compute nodes for collective parallel operations of the parallel computer. One compute node of the operational group assigned to be a logical root. Broadcasting a message in a parallel computer includes: establishing a Hamiltonian path along all of the compute nodes in at least one plane of the data communications network and in the operational group; and broadcasting, by the logical root to the remaining compute nodes, the logical root's message along the established Hamiltonian path.

Distributed Multihoming Routing Method by Crossing Control MIPv6 with SCTP

NASA Astrophysics Data System (ADS)

Shi, Hongbo; Hamagami, Tomoki

There are various wireless communication technologies, such as 3G, WiFi, used widely in the world. Recently, not only the laptop but also the smart phones can be equipped with multiple wireless devices. The communication terminals which are implemented with multiple interfaces are usually called multi-homed nodes. Meanwhile, a multi-homed node with multiple interfaces can also be regarded as multiple single-homed nodes. For example, when a person who is using smart phone and laptop to connect to the Internet concurrently, we may regard the person as a multi-homed node in the Internet. This paper proposes a new routing method, Multi-homed Mobile Cross-layer Control to handle multi-homed mobile nodes. Our suggestion can provide a distributed end-to-end routing method for handling the communications among multi-homed nodes at the fundamental network layer.

A comprehensive comparison of network similarities for link prediction and spurious link elimination

NASA Astrophysics Data System (ADS)

Zhang, Peng; Qiu, Dan; Zeng, An; Xiao, Jinghua

2018-06-01

Identifying missing interactions in complex networks, known as link prediction, is realized by estimating the likelihood of the existence of a link between two nodes according to the observed links and nodes' attributes. Similar approaches have also been employed to identify and remove spurious links in networks which is crucial for improving the reliability of network data. In network science, the likelihood for two nodes having a connection strongly depends on their structural similarity. The key to address these two problems thus becomes how to objectively measure the similarity between nodes in networks. In the literature, numerous network similarity metrics have been proposed and their accuracy has been discussed independently in previous works. In this paper, we systematically compare the accuracy of 18 similarity metrics in both link prediction and spurious link elimination when the observed networks are very sparse or consist of inaccurate linking information. Interestingly, some methods have high prediction accuracy, they tend to perform low accuracy in identification spurious interaction. We further find that methods can be classified into several cluster according to their behaviors. This work is useful for guiding future use of these similarity metrics for different purposes.

Design and Application of a Field Sensing System for Ground Anchors in Slopes

PubMed Central

Choi, Se Woon; Lee, Jihoon; Kim, Jong Moon; Park, Hyo Seon

2013-01-01

In a ground anchor system, cables or tendons connected to a bearing plate are used for stabilization of slopes. Then, the stability of a slope is dependent on maintaining the tension levels in the cables. So far, no research on a strain-based field sensing system for ground anchors has been reported. Therefore, in this study, a practical monitoring system for long-term sensing of tension levels in tendons for anchor-reinforced slopes is proposed. The system for anchor-reinforced slopes is composed of: (1) load cells based on vibrating wire strain gauges (VWSGs), (2) wireless sensor nodes which receive and process the signals from load cells and then transmit the result to a master node through local area communication, (3) master nodes which transmit the data sent from sensor nodes to the server through mobile communication, and (4) a server located at the base station. The system was applied to field sensing of ground anchors in the 62 m-long and 26 m-high slope at the side of the highway. Based on the long-term monitoring, the safety of the anchor-reinforced slope can be secured by the timely applications of re-tensioning processes in tendons. PMID:23507820

MEMS tracking mirror system for a bidirectional free-space optical link.

PubMed

Jeon, Sungho; Toshiyoshi, Hiroshi

2017-08-20

We report on a bidirectional free-space optical system that is capable of automatic connection and tracking of an optical link between two nodes. A piezoelectric micro-electro-mechanical systems (MEMS) optical scanner is used to steer a laser beam of two wavelengths superposed to visually present a communication zone, to search for the position of the remote node by means of the retro-reflector optics, and to transmit the data between the nodes. A feedback system is developed to control the MEMS scanner to dynamically establish the optical link within a 10-ms transition time and to keep track of the moving node.

IT product competition Network

NASA Astrophysics Data System (ADS)

Xu, Xiu-Lian; Zhou, Lei; Shi, Jian-Jun; Wang, Yong-Li; Feng, Ai-Xia; He, Da-Ren

2008-03-01

Along with the technical development, the IT product competition becomes increasingly fierce in recent years. The factories, which produce the same IT product, have to improve continuously their own product quality for taking a large piece of cake in the product sale market. We suggest using a complex network description for the IT product competition. In the network the factories are defined as nodes, and two nodes are connected by a link if they produce a common IT product. The edge represents the sale competition relationship. 2121 factories and 265 products have been investigated. Some statistical properties, such as the degree distribution, node strength distribution, assortativity, and node degree correlation have been empirically obtained.

The connectivity structure, giant strong component and centrality of metabolic networks.

PubMed

Ma, Hong-Wu; Zeng, An-Ping

2003-07-22

Structural and functional analysis of genome-based large-scale metabolic networks is important for understanding the design principles and regulation of the metabolism at a system level. The metabolic network is conventionally considered to be highly integrated and very complex. A rational reduction of the metabolic network to its core structure and a deeper understanding of its functional modules are important. In this work, we show that the metabolites in a metabolic network are far from fully connected. A connectivity structure consisting of four major subsets of metabolites and reactions, i.e. a fully connected sub-network, a substrate subset, a product subset and an isolated subset is found to exist in metabolic networks of 65 fully sequenced organisms. The largest fully connected part of a metabolic network, called 'the giant strong component (GSC)', represents the most complicated part and the core of the network and has the feature of scale-free networks. The average path length of the whole network is primarily determined by that of the GSC. For most of the organisms, GSC normally contains less than one-third of the nodes of the network. This connectivity structure is very similar to the 'bow-tie' structure of World Wide Web. Our results indicate that the bow-tie structure may be common for large-scale directed networks. More importantly, the uncovered structure feature makes a structural and functional analysis of large-scale metabolic network more amenable. As shown in this work, comparing the closeness centrality of the nodes in the GSC can identify the most central metabolites of a metabolic network. To quantitatively characterize the overall connection structure of the GSC we introduced the term 'overall closeness centralization index (OCCI)'. OCCI correlates well with the average path length of the GSC and is a useful parameter for a system-level comparison of metabolic networks of different organisms. http://genome.gbf.de/bioinformatics/

Expression of connective tissue growth factor in tumor tissues is an independent predictor of poor prognosis in patients with gastric cancer.

PubMed

Liu, Lu-Ying; Han, Yan-Chun; Wu, Shu-Hua; Lv, Zeng-Hua

2008-04-07

To examine the expression of connective tissue growth factor (CTGF), also known as CCN2, in gastric carcinoma (GC), and the correlation between the expression of CTGF, clinicopathologic features and clinical outcomes of patients with GC. One hundred and twenty-two GC patients were included in the present study. All patients were followed up for at least 5 years. Proteins of CTGF were detected using the Powervision two-step immunostaining method. Of the specimens from 122 GC patients analyzed for CTGF expression, 58 (58/122, 47.5%) had a high CTGF expression in cytoplasm of gastric carcinoma cells and 64 (64/122, 52.5%) had a low CTGF expression. Patients with a high CTGF expression showed a higher incidence of lymph node metastasis than those with a low CTGF expression (P = 0.032). Patients with a high CTGF expression had significantly lower 5-year survival rate than those with a low CTGF expression (27.6% vs 46.9%, P = 0.0178), especially those staging I + II + III (35.7% vs 65.2%, P = 0.0027). GC patients with an elevated CTGF expression have more lymph node metastases and a shorter survival time. CTGF seems to be an independent prognostic factor for the successful differentiation of high-risk GC patients staging I + II + III. Over-expression of CTGF in human GC cells results in an increased aggressive ability.

Identification of hub subnetwork based on topological features of genes in breast cancer

PubMed Central

ZHUANG, DA-YONG; JIANG, LI; HE, QING-QING; ZHOU, PENG; YUE, TAO

2015-01-01

The aim of this study was to provide functional insight into the identification of hub subnetworks by aggregating the behavior of genes connected in a protein-protein interaction (PPI) network. We applied a protein network-based approach to identify subnetworks which may provide new insight into the functions of pathways involved in breast cancer rather than individual genes. Five groups of breast cancer data were downloaded and analyzed from the Gene Expression Omnibus (GEO) database of high-throughput gene expression data to identify gene signatures using the genome-wide global significance (GWGS) method. A PPI network was constructed using Cytoscape and clusters that focused on highly connected nodes were obtained using the molecular complex detection (MCODE) clustering algorithm. Pathway analysis was performed to assess the functional relevance of selected gene signatures based on the Kyoto Encyclopedia of Genes and Genomes (KEGG) database. Topological centrality was used to characterize the biological importance of gene signatures, pathways and clusters. The results revealed that, cluster1, as well as the cell cycle and oocyte meiosis pathways were significant subnetworks in the analysis of degree and other centralities, in which hub nodes mostly distributed. The most important hub nodes, with top ranked centrality, were also similar with the common genes from the above three subnetwork intersections, which was viewed as a hub subnetwork with more reproducible than individual critical genes selected without network information. This hub subnetwork attributed to the same biological process which was essential in the function of cell growth and death. This increased the accuracy of identifying gene interactions that took place within the same functional process and was potentially useful for the development of biomarkers and networks for breast cancer. PMID:25573623

Network analysis of translocated Takahe populations to identify disease surveillance targets.

PubMed

Grange, Zoë L; VAN Andel, Mary; French, Nigel P; Gartrell, Brett D

2014-04-01

Social network analysis is being increasingly used in epidemiology and disease modeling in humans, domestic animals, and wildlife. We investigated this tool in describing a translocation network (area that allows movement of animals between geographically isolated locations) used for the conservation of an endangered flightless rail, the Takahe (Porphyrio hochstetteri). We collated records of Takahe translocations within New Zealand and used social network principles to describe the connectivity of the translocation network. That is, networks were constructed and analyzed using adjacency matrices with values based on the tie weights between nodes. Five annual network matrices were created using the Takahe data set, each incremental year included records of previous years. Weights of movements between connected locations were assigned by the number of Takahe moved. We calculated the number of nodes (i(total)) and the number of ties (t(total)) between the nodes. To quantify the small-world character of the networks, we compared the real networks to random graphs of the equivalent size, weighting, and node strength. Descriptive analysis of cumulative annual Takahe movement networks involved determination of node-level characteristics, including centrality descriptors of relevance to disease modeling such as weighted measures of in degree (k(i)(in)), out degree (k(i)(out)), and betweenness (B(i)). Key players were assigned according to the highest node measure of k(i)(in), k(i)(out), and B(i) per network. Networks increased in size throughout the time frame considered. The network had some degree small-world characteristics. Nodes with the highest cumulative tie weights connecting them were the captive breeding center, the Murchison Mountains and 2 offshore islands. The key player fluctuated between the captive breeding center and the Murchison Mountains. The cumulative networks identified the captive breeding center every year as the hub of the network until the final network in 2011. Likewise, the wild Murchison Mountains population was consistently the sink of the network. Other nodes, such as the offshore islands and the wildlife hospital, varied in importance over time. Common network descriptors and measures of centrality identified key locations for targeting disease surveillance. The visual representation of movements of animals in a population that this technique provides can aid decision makers when they evaluate translocation proposals or attempt to control a disease outbreak. © 2014 Society for Conservation Biology.

Experimental demonstration of the optical multi-mesh hypercube: scaleable interconnection network for multiprocessors and multicomputers.

PubMed

Louri, A; Furlonge, S; Neocleous, C

1996-12-10

A prototype of a novel topology for scaleable optical interconnection networks called the optical multi-mesh hypercube (OMMH) is experimentally demonstrated to as high as a 150-Mbit/s data rate (2(7) - 1 nonreturn-to-zero pseudo-random data pattern) at a bit error rate of 10(-13)/link by the use of commercially available devices. OMMH is a scaleable network [Appl. Opt. 33, 7558 (1994); J. Lightwave Technol. 12, 704 (1994)] architecture that combines the positive features of the hypercube (small diameter, connectivity, symmetry, simple routing, and fault tolerance) and the mesh (constant node degree and size scaleability). The optical implementation method is divided into two levels: high-density local connections for the hypercube modules, and high-bit-rate, low-density, long connections for the mesh links connecting the hypercube modules. Free-space imaging systems utilizing vertical-cavity surface-emitting laser (VCSEL) arrays, lenslet arrays, space-invariant holographic techniques, and photodiode arrays are demonstrated for the local connections. Optobus fiber interconnects from Motorola are used for the long-distance connections. The OMMH was optimized to operate at the data rate of Motorola's Optobus (10-bit-wide, VCSEL-based bidirectional data interconnects at 150 Mbits/s). Difficulties encountered included the varying fan-out efficiencies of the different orders of the hologram, misalignment sensitivity of the free-space links, low power (1 mW) of the individual VCSEL's, and noise.

Ablation as targeted perturbation to rewire communication network of persistent atrial fibrillation

PubMed Central

Tao, Susumu; Way, Samuel F.; Garland, Joshua; Chrispin, Jonathan; Ciuffo, Luisa A.; Balouch, Muhammad A.; Nazarian, Saman; Spragg, David D.; Marine, Joseph E.; Berger, Ronald D.; Calkins, Hugh

2017-01-01

Persistent atrial fibrillation (AF) can be viewed as disintegrated patterns of information transmission by action potential across the communication network consisting of nodes linked by functional connectivity. To test the hypothesis that ablation of persistent AF is associated with improvement in both local and global connectivity within the communication networks, we analyzed multi-electrode basket catheter electrograms of 22 consecutive patients (63.5 ± 9.7 years, 78% male) during persistent AF before and after the focal impulse and rotor modulation-guided ablation. Eight patients (36%) developed recurrence within 6 months after ablation. We defined communication networks of AF by nodes (cardiac tissue adjacent to each electrode) and edges (mutual information between pairs of nodes). To evaluate patient-specific parameters of communication, thresholds of mutual information were applied to preserve 10% to 30% of the strongest edges. There was no significant difference in network parameters between both atria at baseline. Ablation effectively rewired the communication network of persistent AF to improve the overall connectivity. In addition, successful ablation improved local connectivity by increasing the average clustering coefficient, and also improved global connectivity by decreasing the characteristic path length. As a result, successful ablation improved the efficiency and robustness of the communication network by increasing the small-world index. These changes were not observed in patients with AF recurrence. Furthermore, a significant increase in the small-world index after ablation was associated with synchronization of the rhythm by acute AF termination. In conclusion, successful ablation rewires communication networks during persistent AF, making it more robust, efficient, and easier to synchronize. Quantitative analysis of communication networks provides not only a mechanistic insight that AF may be sustained by spatially localized sources and global connectivity, but also patient-specific metrics that could serve as a valid endpoint for therapeutic interventions. PMID:28678805

Intercluster Connection in Cognitive Wireless Mesh Networks Based on Intelligent Network Coding

NASA Astrophysics Data System (ADS)

Chen, Xianfu; Zhao, Zhifeng; Jiang, Tao; Grace, David; Zhang, Honggang

2009-12-01

Cognitive wireless mesh networks have great flexibility to improve spectrum resource utilization, within which secondary users (SUs) can opportunistically access the authorized frequency bands while being complying with the interference constraint as well as the QoS (Quality-of-Service) requirement of primary users (PUs). In this paper, we consider intercluster connection between the neighboring clusters under the framework of cognitive wireless mesh networks. Corresponding to the collocated clusters, data flow which includes the exchanging of control channel messages usually needs four time slots in traditional relaying schemes since all involved nodes operate in half-duplex mode, resulting in significant bandwidth efficiency loss. The situation is even worse at the gateway node connecting the two colocated clusters. A novel scheme based on network coding is proposed in this paper, which needs only two time slots to exchange the same amount of information mentioned above. Our simulation shows that the network coding-based intercluster connection has the advantage of higher bandwidth efficiency compared with the traditional strategy. Furthermore, how to choose an optimal relaying transmission power level at the gateway node in an environment of coexisting primary and secondary users is discussed. We present intelligent approaches based on reinforcement learning to solve the problem. Theoretical analysis and simulation results both show that the intelligent approaches can achieve optimal throughput for the intercluster relaying in the long run.

Stochastic blockmodeling of the modules and core of the Caenorhabditis elegans connectome.

PubMed

Pavlovic, Dragana M; Vértes, Petra E; Bullmore, Edward T; Schafer, William R; Nichols, Thomas E

2014-01-01

Recently, there has been much interest in the community structure or mesoscale organization of complex networks. This structure is characterised either as a set of sparsely inter-connected modules or as a highly connected core with a sparsely connected periphery. However, it is often difficult to disambiguate these two types of mesoscale structure or, indeed, to summarise the full network in terms of the relationships between its mesoscale constituents. Here, we estimate a community structure with a stochastic blockmodel approach, the Erdős-Rényi Mixture Model, and compare it to the much more widely used deterministic methods, such as the Louvain and Spectral algorithms. We used the Caenorhabditis elegans (C. elegans) nervous system (connectome) as a model system in which biological knowledge about each node or neuron can be used to validate the functional relevance of the communities obtained. The deterministic algorithms derived communities with 4-5 modules, defined by sparse inter-connectivity between all modules. In contrast, the stochastic Erdős-Rényi Mixture Model estimated a community with 9 blocks or groups which comprised a similar set of modules but also included a clearly defined core, made of 2 small groups. We show that the "core-in-modules" decomposition of the worm brain network, estimated by the Erdős-Rényi Mixture Model, is more compatible with prior biological knowledge about the C. elegans nervous system than the purely modular decomposition defined deterministically. We also show that the blockmodel can be used both to generate stochastic realisations (simulations) of the biological connectome, and to compress network into a small number of super-nodes and their connectivity. We expect that the Erdős-Rényi Mixture Model may be useful for investigating the complex community structures in other (nervous) systems.

Is Vocabulary Growth Influenced by the Relations among Words in a Language Learner's Vocabulary?

ERIC Educational Resources Information Center

Sailor, Kevin M.

2013-01-01

Several recent studies have explored the applicability of the preferential attachment principle to account for vocabulary growth. According to this principle, network growth can be described by a process in which existing nodes recruit new nodes with a probability that is an increasing function of their connectivity within the existing network.…

Countering the Hidden Hand: A Study of Iranian Influence in Iraq

DTIC Science & Technology

2015-12-01

6. Communication and Colleagues Network, K-Core Analysis ....................64 Figure 7. Communication and Colleagues Network, Node Color = Newman ...Groups. Nodes in the Same Newman Group as IRGC Gen. Soleimani are Enlarged...email. Kinship ties are defined as any family connection through blood or marriage, such as children, parents , siblings, mothers- and fathers-in-law

KENNEDY SPACE CENTER, FLA. - Astronaut Tim Kopra (second from right) talks with workers in the Space Station Processing Facility about the Intravehicular Activity (IVA) constraints testing on the Italian-built Node 2, a future element of the International Space Station. . The second of three Station connecting modules, the Node 2 attaches to the end of the U.S. Lab and provides attach locations for several other elements. Kopra is currently assigned technical duties in the Space Station Branch of the Astronaut Office, where his primary focus involves the testing of crew interfaces for two future ISS modules as well as the implementation of support computers and operational Local Area Network on ISS. Node 2 is scheduled to launch on mission STS-120, Station assembly flight 10A.

NASA Image and Video Library

2004-02-03

KENNEDY SPACE CENTER, FLA. - Astronaut Tim Kopra (second from right) talks with workers in the Space Station Processing Facility about the Intravehicular Activity (IVA) constraints testing on the Italian-built Node 2, a future element of the International Space Station. . The second of three Station connecting modules, the Node 2 attaches to the end of the U.S. Lab and provides attach locations for several other elements. Kopra is currently assigned technical duties in the Space Station Branch of the Astronaut Office, where his primary focus involves the testing of crew interfaces for two future ISS modules as well as the implementation of support computers and operational Local Area Network on ISS. Node 2 is scheduled to launch on mission STS-120, Station assembly flight 10A.

A Self-Stabilizing Distributed Clock Synchronization Protocol for Arbitrary Digraphs

NASA Technical Reports Server (NTRS)

Malekpour, Mahyar R.

2011-01-01

This report presents a self-stabilizing distributed clock synchronization protocol in the absence of faults in the system. It is focused on the distributed clock synchronization of an arbitrary, non-partitioned digraph ranging from fully connected to 1-connected networks of nodes while allowing for differences in the network elements. This protocol does not rely on assumptions about the initial state of the system, other than the presence of at least one node, and no central clock or a centrally generated signal, pulse, or message is used. Nodes are anonymous, i.e., they do not have unique identities. There is no theoretical limit on the maximum number of participating nodes. The only constraint on the behavior of the node is that the interactions with other nodes are restricted to defined links and interfaces. We present an outline of a deductive proof of the correctness of the protocol. A model of the protocol was mechanically verified using the Symbolic Model Verifier (SMV) for a variety of topologies. Results of the mechanical proof of the correctness of the protocol are provided. The model checking results have verified the correctness of the protocol as they apply to the networks with unidirectional and bidirectional links. In addition, the results confirm the claims of determinism and linear convergence. As a result, we conjecture that the protocol solves the general case of this problem. We also present several variations of the protocol and discuss that this synchronization protocol is indeed an emergent system.

Overview on In-Space Internet Node Testbed (ISINT)

NASA Technical Reports Server (NTRS)

Richard, Alan M.; Kachmar, Brian A.; Fabian, Theodore; Kerczewski, Robert J.

2000-01-01

The Satellite Networks and Architecture Branch has developed the In-Space Internet Node Technology testbed (ISINT) for investigating the use of commercial Internet products for NASA missions. The testbed connects two closed subnets over a tabletop Ka-band transponder by using commercial routers and modems. Since many NASA assets are in low Earth orbits (LEO's), the testbed simulates the varying signal strength, changing propagation delay, and varying connection times that are normally experienced when communicating to the Earth via a geosynchronous orbiting (GEO) communications satellite. Research results from using this testbed will be used to determine which Internet technologies are appropriate for NASA's future communication needs.

Fault-Tolerant Algorithms for Connectivity Restoration in Wireless Sensor Networks.

PubMed

Zeng, Yali; Xu, Li; Chen, Zhide

2015-12-22

As wireless sensor network (WSN) is often deployed in a hostile environment, nodes in the networks are prone to large-scale failures, resulting in the network not working normally. In this case, an effective restoration scheme is needed to restore the faulty network timely. Most of existing restoration schemes consider more about the number of deployed nodes or fault tolerance alone, but fail to take into account the fact that network coverage and topology quality are also important to a network. To address this issue, we present two algorithms named Full 2-Connectivity Restoration Algorithm (F2CRA) and Partial 3-Connectivity Restoration Algorithm (P3CRA), which restore a faulty WSN in different aspects. F2CRA constructs the fan-shaped topology structure to reduce the number of deployed nodes, while P3CRA constructs the dual-ring topology structure to improve the fault tolerance of the network. F2CRA is suitable when the restoration cost is given the priority, and P3CRA is suitable when the network quality is considered first. Compared with other algorithms, these two algorithms ensure that the network has stronger fault-tolerant function, larger coverage area and better balanced load after the restoration.

Using Link Disconnection Entropy Disorder to Detect Fast Moving Nodes in MANETs

PubMed Central

Palafox, Luis E.; Aguilar, Leocundo; Sanchez, Mauricio A.; Martinez, Luis G.

2016-01-01

Mobile ad-hoc networks (MANETs) are dynamic by nature; this dynamism comes from node mobility, traffic congestion, and other transmission conditions. Metrics to evaluate the effects of those conditions shine a light on node’s behavior in an ad-hoc network, helping to identify the node or nodes with better conditions of connection. In this paper, we propose a relative index to evaluate a single node reliability, based on the link disconnection entropy disorder using neighboring nodes as reference. Link disconnection entropy disorder is best used to identify fast moving nodes or nodes with unstable communications, this without the need of specialized sensors such as GPS. Several scenarios were studied to verify the index, measuring the effects of Speed and traffic density on the link disconnection entropy disorder. Packet delivery ratio is associated to the metric detecting a strong relationship, enabling the use of the link disconnection entropy disorder to evaluate the stability of a node to communicate with other nodes. To expand the utilization of the link entropy disorder, we identified nodes with higher speeds in network simulations just by using the link entropy disorder. PMID:27219671