HRD Motif as the Central Hub of the Signaling Network for Activation Loop Autophosphorylation in Abl Kinase.

PubMed

La Sala, Giuseppina; Riccardi, Laura; Gaspari, Roberto; Cavalli, Andrea; Hantschel, Oliver; De Vivo, Marco

2016-11-08

A number of structural factors modulate the activity of Abelson (Abl) tyrosine kinase, whose deregulation is often related to oncogenic processes. First, only the open conformation of the Abl kinase domain's activation loop (A-loop) favors ATP binding to the catalytic cleft. In this regard, the trans-autophosphorylation of the Y412 residue, which is located along the A-loop, favors the stability of the open conformation, in turn enhancing Abl activity. Another key factor for full Abl activity is the formation of active conformations of the catalytic DFG motif in the Abl kinase domain. Furthermore, binding of the SH2 domain to the N-lobe of the Abl kinase was recently demonstrated to have a long-range allosteric effect on the stabilization of the A-loop open state. Intriguingly, these distinct structural factors imply a complex signal transmission network for controlling the A-loop's flexibility and conformational preference for optimal Abl function. However, the exact dynamical features of this signal transmission network structure remain unclear. Here, we report on microsecond-long molecular dynamics coupled with enhanced sampling simulations of multiple Abl model systems, in the presence or absence of the SH2 domain and with the DFG motif flipped in two ways (in or out conformation). Through comparative analysis, our simulations augment the interpretation of the existing Abl experimental data, revealing a dynamical network of interactions that interconnect SH2 domain binding with A-loop plasticity and Y412 autophosphorylation in Abl. This signaling network engages the DFG motif and, importantly, other conserved structural elements of the kinase domain, namely, the EPK-ELK H-bond network and the HRD motif. Our results show that the signal propagation for modulating the A-loop spatial localization is highly dependent on the HRD motif conformation, which thus acts as the central hub of this (allosteric) signaling network controlling Abl activation and function.

Three-dimensional {Co(3+)-Zn2+} and {Co(3+)-Cd2+} networks originated from carboxylate-rich building blocks: syntheses, structures, and heterogeneous catalysis.

PubMed

Kumar, Girijesh; Gupta, Rajeev

2013-10-07

The present work shows the utilization of Co(3+) complexes appended with either para- or meta-arylcarboxylic acid groups as the molecular building blocks for the construction of three-dimensional {Co(3+)-Zn(2+)} and {Co(3+)-Cd(2+)} heterobimetallic networks. The structural characterizations of these networks show several interesting features including well-defined pores and channels. These networks function as heterogeneous and reusable catalysts for the regio- and stereoselective ring-opening reactions of various epoxides and size-selective cyanation reactions of assorted aldehydes.

Data Architecture in an Open Systems Environment.

ERIC Educational Resources Information Center

Bernbom, Gerald; Cromwell, Dennis

1993-01-01

The conceptual basis for structured data architecture, and its integration with open systems technology at Indiana University, are described. Key strategic goals guiding these efforts are discussed: commitment to improved data access; migration to relational database technology, and deployment of a high-speed, multiprotocol network; and…

Advanced functional network analysis in the geosciences: The pyunicorn package

NASA Astrophysics Data System (ADS)

Donges, Jonathan F.; Heitzig, Jobst; Runge, Jakob; Schultz, Hanna C. H.; Wiedermann, Marc; Zech, Alraune; Feldhoff, Jan; Rheinwalt, Aljoscha; Kutza, Hannes; Radebach, Alexander; Marwan, Norbert; Kurths, Jürgen

2013-04-01

Functional networks are a powerful tool for analyzing large geoscientific datasets such as global fields of climate time series originating from observations or model simulations. pyunicorn (pythonic unified complex network and recurrence analysis toolbox) is an open-source, fully object-oriented and easily parallelizable package written in the language Python. It allows for constructing functional networks (aka climate networks) representing the structure of statistical interrelationships in large datasets and, subsequently, investigating this structure using advanced methods of complex network theory such as measures for networks of interacting networks, node-weighted statistics or network surrogates. Additionally, pyunicorn allows to study the complex dynamics of geoscientific systems as recorded by time series by means of recurrence networks and visibility graphs. The range of possible applications of the package is outlined drawing on several examples from climatology.

Structural controllability of unidirectional bipartite networks

NASA Astrophysics Data System (ADS)

Nacher, Jose C.; Akutsu, Tatsuya

2013-04-01

The interactions between fundamental life molecules, people and social organisations build complex architectures that often result in undesired behaviours. Despite all of the advances made in our understanding of network structures over the past decade, similar progress has not been achieved in the controllability of real-world networks. In particular, an analytical framework to address the controllability of bipartite networks is still absent. Here, we present a dominating set (DS)-based approach to bipartite network controllability that identifies the topologies that are relatively easy to control with the minimum number of driver nodes. Our theoretical calculations, assisted by computer simulations and an evaluation of real-world networks offer a promising framework to control unidirectional bipartite networks. Our analysis should open a new approach to reverting the undesired behaviours in unidirectional bipartite networks at will.

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

PubMed

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

2010-07-01

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

Structure and mechanics of aegagropilae fiber network.

PubMed

Verhille, Gautier; Moulinet, Sébastien; Vandenberghe, Nicolas; Adda-Bedia, Mokhtar; Le Gal, Patrice

2017-05-02

Fiber networks encompass a wide range of natural and manmade materials. The threads or filaments from which they are formed span a wide range of length scales: from nanometers, as in biological tissues and bundles of carbon nanotubes, to millimeters, as in paper and insulation materials. The mechanical and thermal behavior of these complex structures depends on both the individual response of the constituent fibers and the density and degree of entanglement of the network. A question of paramount importance is how to control the formation of a given fiber network to optimize a desired function. The study of fiber clustering of natural flocs could be useful for improving fabrication processes, such as in the paper and textile industries. Here, we use the example of aegagropilae that are the remains of a seagrass ( Posidonia oceanica ) found on Mediterranean beaches. First, we characterize different aspects of their structure and mechanical response, and second, we draw conclusions on their formation process. We show that these natural aggregates are formed in open sea by random aggregation and compaction of fibers held together by friction forces. Although formed in a natural environment, thus under relatively unconstrained conditions, the geometrical and mechanical properties of the resulting fiber aggregates are quite robust. This study opens perspectives for manufacturing complex fiber network materials.

iCAVE: an open source tool for visualizing biomolecular networks in 3D, stereoscopic 3D and immersive 3D

PubMed Central

Liluashvili, Vaja; Kalayci, Selim; Fluder, Eugene; Wilson, Manda; Gabow, Aaron

2017-01-01

Abstract Visualizations of biomolecular networks assist in systems-level data exploration in many cellular processes. Data generated from high-throughput experiments increasingly inform these networks, yet current tools do not adequately scale with concomitant increase in their size and complexity. We present an open source software platform, interactome-CAVE (iCAVE), for visualizing large and complex biomolecular interaction networks in 3D. Users can explore networks (i) in 3D using a desktop, (ii) in stereoscopic 3D using 3D-vision glasses and a desktop, or (iii) in immersive 3D within a CAVE environment. iCAVE introduces 3D extensions of known 2D network layout, clustering, and edge-bundling algorithms, as well as new 3D network layout algorithms. Furthermore, users can simultaneously query several built-in databases within iCAVE for network generation or visualize their own networks (e.g., disease, drug, protein, metabolite). iCAVE has modular structure that allows rapid development by addition of algorithms, datasets, or features without affecting other parts of the code. Overall, iCAVE is the first freely available open source tool that enables 3D (optionally stereoscopic or immersive) visualizations of complex, dense, or multi-layered biomolecular networks. While primarily designed for researchers utilizing biomolecular networks, iCAVE can assist researchers in any field. PMID:28814063

iCAVE: an open source tool for visualizing biomolecular networks in 3D, stereoscopic 3D and immersive 3D.

PubMed

Liluashvili, Vaja; Kalayci, Selim; Fluder, Eugene; Wilson, Manda; Gabow, Aaron; Gümüs, Zeynep H

2017-08-01

Visualizations of biomolecular networks assist in systems-level data exploration in many cellular processes. Data generated from high-throughput experiments increasingly inform these networks, yet current tools do not adequately scale with concomitant increase in their size and complexity. We present an open source software platform, interactome-CAVE (iCAVE), for visualizing large and complex biomolecular interaction networks in 3D. Users can explore networks (i) in 3D using a desktop, (ii) in stereoscopic 3D using 3D-vision glasses and a desktop, or (iii) in immersive 3D within a CAVE environment. iCAVE introduces 3D extensions of known 2D network layout, clustering, and edge-bundling algorithms, as well as new 3D network layout algorithms. Furthermore, users can simultaneously query several built-in databases within iCAVE for network generation or visualize their own networks (e.g., disease, drug, protein, metabolite). iCAVE has modular structure that allows rapid development by addition of algorithms, datasets, or features without affecting other parts of the code. Overall, iCAVE is the first freely available open source tool that enables 3D (optionally stereoscopic or immersive) visualizations of complex, dense, or multi-layered biomolecular networks. While primarily designed for researchers utilizing biomolecular networks, iCAVE can assist researchers in any field. © The Authors 2017. Published by Oxford University Press.

Statistically validated mobile communication networks: the evolution of motifs in European and Chinese data

NASA Astrophysics Data System (ADS)

Li, Ming-Xia; Palchykov, Vasyl; Jiang, Zhi-Qiang; Kaski, Kimmo; Kertész, János; Miccichè, Salvatore; Tumminello, Michele; Zhou, Wei-Xing; Mantegna, Rosario N.

2014-08-01

Big data open up unprecedented opportunities for investigating complex systems, including society. In particular, communication data serve as major sources for computational social sciences, but they have to be cleaned and filtered as they may contain spurious information due to recording errors as well as interactions, like commercial and marketing activities, not directly related to the social network. The network constructed from communication data can only be considered as a proxy for the network of social relationships. Here we apply a systematic method, based on multiple-hypothesis testing, to statistically validate the links and then construct the corresponding Bonferroni network, generalized to the directed case. We study two large datasets of mobile phone records, one from Europe and the other from China. For both datasets we compare the raw data networks with the corresponding Bonferroni networks and point out significant differences in the structures and in the basic network measures. We show evidence that the Bonferroni network provides a better proxy for the network of social interactions than the original one. Using the filtered networks, we investigated the statistics and temporal evolution of small directed 3-motifs and concluded that closed communication triads have a formation time scale, which is quite fast and typically intraday. We also find that open communication triads preferentially evolve into other open triads with a higher fraction of reciprocated calls. These stylized facts were observed for both datasets.

Design of Control Plane Architecture Based on Cloud Platform and Experimental Network Demonstration for Multi-domain SDON

NASA Astrophysics Data System (ADS)

Li, Ming; Yin, Hongxi; Xing, Fangyuan; Wang, Jingchao; Wang, Honghuan

2016-02-01

With the features of network virtualization and resource programming, Software Defined Optical Network (SDON) is considered as the future development trend of optical network, provisioning a more flexible, efficient and open network function, supporting intraconnection and interconnection of data centers. Meanwhile cloud platform can provide powerful computing, storage and management capabilities. In this paper, with the coordination of SDON and cloud platform, a multi-domain SDON architecture based on cloud control plane has been proposed, which is composed of data centers with database (DB), path computation element (PCE), SDON controller and orchestrator. In addition, the structure of the multidomain SDON orchestrator and OpenFlow-enabled optical node are proposed to realize the combination of centralized and distributed effective management and control platform. Finally, the functional verification and demonstration are performed through our optical experiment network.

IM-19: a new flexible microporous gallium based-MOF framework with pressure- and temperature-dependent openings.

PubMed

Chaplais, Gérald; Simon-Masseron, Angélique; Porcher, Florence; Lecomte, Claude; Bazer-Bachi, Delphine; Bats, Nicolas; Patarin, Joël

2009-07-14

Five metal-organic frameworks (MOFs) based on the same three-dimensional gallium terephthalate network (IM-19) are described, and an incommensurate structure (for the as-synthesized form) as well as two remarkable guest-free polymorphs (open and closed) are highlighted.

Gene networks and the evolution of plant morphology.

PubMed

Das Gupta, Mainak; Tsiantis, Miltos

2018-06-06

Elaboration of morphology depends on the precise orchestration of gene expression by key regulatory genes. The hierarchy and relationship among the participating genes is commonly known as gene regulatory network (GRN). Therefore, the evolution of morphology ultimately occurs by the rewiring of gene network structures or by the co-option of gene networks to novel domains. The availability of high-resolution expression data combined with powerful statistical tools have opened up new avenues to formulate and test hypotheses on how diverse gene networks influence trait development and diversity. Here we summarize recent studies based on both big-data and genetics approaches to understand the evolution of plant form and physiology. We also discuss recent genome-wide investigations on how studying open-chromatin regions may help study the evolution of gene expression patterns. Copyright © 2018. Published by Elsevier Ltd.

Automated Structure Annotation and Curation for MassBank: Potential and Pitfalls

EPA Science Inventory

The European MassBank server (www.massbank.eu) was founded in 2012 by the NORMAN Network (www.norman-network.net) to provide open access to mass spectra of substances of environmental interest contributed by NORMAN members. The automated workflow RMassBank was developed as a part...

The role of syntax in complex networks: Local and global importance of verbs in a syntactic dependency network

NASA Astrophysics Data System (ADS)

Čech, Radek; Mačutek, Ján; Žabokrtský, Zdeněk

2011-10-01

Syntax of natural language has been the focus of linguistics for decades. The complex network theory, being one of new research tools, opens new perspectives on syntax properties of the language. Despite numerous partial achievements, some fundamental problems remain unsolved. Specifically, although statistical properties typical for complex networks can be observed in all syntactic networks, the impact of syntax itself on these properties is still unclear. The aim of the present study is to shed more light on the role of syntax in the syntactic network structure. In particular, we concentrate on the impact of the syntactic function of a verb in the sentence on the complex network structure. Verbs play the decisive role in the sentence structure (“local” importance). From this fact we hypothesize the importance of verbs in the complex network (“global” importance). The importance of verb in the complex network is assessed by the number of links which are directed from the node representing verb to other nodes in the network. Six languages (Catalan, Czech, Dutch, Hungarian, Italian, Portuguese) were used for testing the hypothesis.

Personality and complex brain networks: The role of openness to experience in default network efficiency

PubMed Central

Kaufman, Scott Barry; Benedek, Mathias; Jung, Rex E.; Kenett, Yoed N.; Jauk, Emanuel; Neubauer, Aljoscha C.; Silvia, Paul J.

2015-01-01

Abstract The brain's default network (DN) has been a topic of considerable empirical interest. In fMRI research, DN activity is associated with spontaneous and self‐generated cognition, such as mind‐wandering, episodic memory retrieval, future thinking, mental simulation, theory of mind reasoning, and creative cognition. Despite large literatures on developmental and disease‐related influences on the DN, surprisingly little is known about the factors that impact normal variation in DN functioning. Using structural equation modeling and graph theoretical analysis of resting‐state fMRI data, we provide evidence that Openness to Experience—a normally distributed personality trait reflecting a tendency to engage in imaginative, creative, and abstract cognitive processes—underlies efficiency of information processing within the DN. Across two studies, Openness predicted the global efficiency of a functional network comprised of DN nodes and corresponding edges. In Study 2, Openness remained a robust predictor—even after controlling for intelligence, age, gender, and other personality variables—explaining 18% of the variance in DN functioning. These findings point to a biological basis of Openness to Experience, and suggest that normally distributed personality traits affect the intrinsic architecture of large‐scale brain systems. Hum Brain Mapp 37:773–779, 2016. © 2015 Wiley Periodicals, Inc. PMID:26610181

The Impact of Large Urban Structural Elements on Traffic Flow   a Case Study of Danwei and Xiaoqu in Shanghai

NASA Astrophysics Data System (ADS)

Lyu, H.; Ding, L.; Fan, H.; Meng, L.

2017-09-01

Danwei (working unit) and Xiaoqu (residential community) are two typical and unique structural urban elements in China. The interior roads of Danwei and Xiaoqu are usually not accessible for the public. Recently, there is a call for opening these interior roads to the public to improve road network structure and optimize traffic flow. In this paper we investigate the impact of Danwei and Xiaoqu on their neighbouring traffic quantitatively. By taking into consideration of origins and destinations (ODs) distributions and route selection behaviours (e.g., shortest paths), we propose an extended betweenness centrality to investigate the traffic flow in two scenarios 1) the interior roads of Danwei and Xiaoqu are excluded from urban road network, 2) the interior roads are integrated into road network. A Danwei and a Xiaoqu in Shanghai are used as the study area. The preliminary results show the feasibility of our extended betweenness centrality in investigating the traffic flow patterns and reveal the quantitative changes of the traffic flow after opening interior roads.

The Magnetic Structure of H-Alpha Macrospicules in Solar Coronal Holes

NASA Technical Reports Server (NTRS)

Yamauchi, Y.; Moore, R. L.; Suess, S. T.; Wang, H.; Sakuri, T.

2003-01-01

Measurements by Ulysses in the high-speed polar solar wind have shown the wind to carry some fine-scale structures in which the magnetic field reverses direction by having a switchback fold in it. The lateral span of these magnetic switchbacks, translated to the Sun, is of the scale of the lanes and cells of the magnetic network in which the open magnetic flux of the polar coronal hole and polar solar wind are rooted. This suggests that the magnetic switchbacks might be formed from network-scale magnetic loops that erupt into the corona and then undergo reconnection with the open field. This possibility motivated us to undertake the study reported here of the structure of H-alpha macrospicules observed at the limb in polar coronal holes, to determine whether a significant fraction of these eruptions appear to be erupting loops. From a search of the polar-coronal holes in 6 days of image-processed full-disk H-alpha movies from Big Bear Solar Observatory, we found a total of 35 macrospicules. Nearly all of these (32) were of one or the other of two different forms: 15 were in the form of an erupting loop, and 17 were in the form of a single-column spiked jet. The erupting-loop macrospicules are appropriate for producing the magnetic switchbacks in the polar wind. The spiked-jet macrospicules show the appropriate structure and evolution to be driven by reconnection between network-scale closed field (a network bipole) and the open field rooted against the closed field. This evidence for reconnection in a large fraction of our macrospicules (1) suggests that many spicules may be generated by similar but smaller reconnection events, and (2) supports the view that coronal heating and solar wind acceleration in coronal holes and in quiet regions and corona are driven by explosive reconnection events in the magnetic network.

The Magnetic Structure of H-alpha Macrospicules in Solar Coronal Holes

NASA Technical Reports Server (NTRS)

Yamauchi, Y.; Moore, R. L.; Suess, S. T.; Wang, H.; Sakurai, T.

2004-01-01

Measurements by Ulysses in the high-speed polar solar wind have shown the wind to carry some fine-scale structures in which the magnetic field reverses direction by having a switchback fold in it. The lateral span of these magnetic switchbacks, translated back to the Sun, is of the scale of the lanes and cells of the magnetic network in which the open magnetic field of the polar coronal hole and polar solar wind are rooted. This suggests that the magnetic switchbacks might be formed from network-scale magnetic loops that erupt into the corona and then undergo reconnection with the open field. This possibility motivated us to undertake the study reported here of the structure of Ha macrospicules observed at the limb in polar coronal holes, to determine whether a significant fraction of these eruptions appear to be erupting loops. From a search of the polar coronal holes in 6 days of image- processed full-disk Ha movies from Big Bear Solar Observatory, we found a total of 35 macrospicules. Nearly all of these (32) were of one or the other of two different forms: 15 were in the form of an erupting loop, and 17 were in the form of a single column spiked jet. The erupting-loop macrospicules are appropriate for producing the magnetic switchbacks in the polar wind. The spiked-jet macrospicules show the appropriate structure and evolution to be driven by reconnection between network-scale closed field (a network bipole) and the open field rooted against the closed field. This evidence for reconnection in a large fraction of our macrospicules (1) suggests that many spicules may be generated by similar but smaller reconnection events and (2) supports the view that coronal heating and solar wind acceleration in coronal holes and in quiet regions are driven by explosive reconnection events in the magnetic network.

Software-defined network abstractions and configuration interfaces for building programmable quantum networks

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

Dasari, Venkat; Sadlier, Ronald J; Geerhart, Mr. Billy

Well-defined and stable quantum networks are essential to realize functional quantum applications. Quantum networks are complex and must use both quantum and classical channels to support quantum applications like QKD, teleportation, and superdense coding. In particular, the no-cloning theorem prevents the reliable copying of quantum signals such that the quantum and classical channels must be highly coordinated using robust and extensible methods. We develop new network abstractions and interfaces for building programmable quantum networks. Our approach leverages new OpenFlow data structures and table type patterns to build programmable quantum networks and to support quantum applications.

Orthogonal Operation of Constitutional Dynamic Networks Consisting of DNA-Tweezer Machines.

PubMed

Yue, Liang; Wang, Shan; Cecconello, Alessandro; Lehn, Jean-Marie; Willner, Itamar

2017-12-26

Overexpression or down-regulation of cellular processes are often controlled by dynamic chemical networks. Bioinspired by nature, we introduce constitutional dynamic networks (CDNs) as systems that emulate the principle of the nature processes. The CDNs comprise dynamically interconvertible equilibrated constituents that respond to external triggers by adapting the composition of the dynamic mixture to the energetic stabilization of the constituents. We introduce a nucleic acid-based CDN that includes four interconvertible and mechanically triggered tweezers, AA', BB', AB' and BA', existing in closed, closed, open, and open configurations, respectively. By subjecting the CDN to auxiliary triggers, the guided stabilization of one of the network constituents dictates the dynamic reconfiguration of the structures of the tweezers constituents. The orthogonal and reversible operations of the CDN DNA tweezers are demonstrated, using T-A·T triplex or K + -stabilized G-quadruplex as structural motifs that control the stabilities of the constituents. The implications of the study rest on the possible applications of input-guided CDN assemblies for sensing, logic gate operations, and programmed activation of molecular machines.

Efficient discovery of overlapping communities in massive networks

PubMed Central

Gopalan, Prem K.; Blei, David M.

2013-01-01

Detecting overlapping communities is essential to analyzing and exploring natural networks such as social networks, biological networks, and citation networks. However, most existing approaches do not scale to the size of networks that we regularly observe in the real world. In this paper, we develop a scalable approach to community detection that discovers overlapping communities in massive real-world networks. Our approach is based on a Bayesian model of networks that allows nodes to participate in multiple communities, and a corresponding algorithm that naturally interleaves subsampling from the network and updating an estimate of its communities. We demonstrate how we can discover the hidden community structure of several real-world networks, including 3.7 million US patents, 575,000 physics articles from the arXiv preprint server, and 875,000 connected Web pages from the Internet. Furthermore, we demonstrate on large simulated networks that our algorithm accurately discovers the true community structure. This paper opens the door to using sophisticated statistical models to analyze massive networks. PMID:23950224

Structural covariance networks across the life span, from 6 to 94 years of age.

PubMed

DuPre, Elizabeth; Spreng, R Nathan

2017-10-01

Structural covariance examines covariation of gray matter morphology between brain regions and across individuals. Despite significant interest in the influence of age on structural covariance patterns, no study to date has provided a complete life span perspective-bridging childhood with early, middle, and late adulthood-on the development of structural covariance networks. Here, we investigate the life span trajectories of structural covariance in six canonical neurocognitive networks: default, dorsal attention, frontoparietal control, somatomotor, ventral attention, and visual. By combining data from five open-access data sources, we examine the structural covariance trajectories of these networks from 6 to 94 years of age in a sample of 1,580 participants. Using partial least squares, we show that structural covariance patterns across the life span exhibit two significant, age-dependent trends. The first trend is a stable pattern whose integrity declines over the life span. The second trend is an inverted-U that differentiates young adulthood from other age groups. Hub regions, including posterior cingulate cortex and anterior insula, appear particularly influential in the expression of this second age-dependent trend. Overall, our results suggest that structural covariance provides a reliable definition of neurocognitive networks across the life span and reveal both shared and network-specific trajectories.

Structural covariance networks across the life span, from 6 to 94 years of age

PubMed Central

DuPre, Elizabeth; Spreng, R. Nathan

2017-01-01

Structural covariance examines covariation of gray matter morphology between brain regions and across individuals. Despite significant interest in the influence of age on structural covariance patterns, no study to date has provided a complete life span perspective—bridging childhood with early, middle, and late adulthood—on the development of structural covariance networks. Here, we investigate the life span trajectories of structural covariance in six canonical neurocognitive networks: default, dorsal attention, frontoparietal control, somatomotor, ventral attention, and visual. By combining data from five open-access data sources, we examine the structural covariance trajectories of these networks from 6 to 94 years of age in a sample of 1,580 participants. Using partial least squares, we show that structural covariance patterns across the life span exhibit two significant, age-dependent trends. The first trend is a stable pattern whose integrity declines over the life span. The second trend is an inverted-U that differentiates young adulthood from other age groups. Hub regions, including posterior cingulate cortex and anterior insula, appear particularly influential in the expression of this second age-dependent trend. Overall, our results suggest that structural covariance provides a reliable definition of neurocognitive networks across the life span and reveal both shared and network-specific trajectories. PMID:29855624

Enabling Controlling Complex Networks with Local Topological Information.

PubMed

Li, Guoqi; Deng, Lei; Xiao, Gaoxi; Tang, Pei; Wen, Changyun; Hu, Wuhua; Pei, Jing; Shi, Luping; Stanley, H Eugene

2018-03-15

Complex networks characterize the nature of internal/external interactions in real-world systems including social, economic, biological, ecological, and technological networks. Two issues keep as obstacles to fulfilling control of large-scale networks: structural controllability which describes the ability to guide a dynamical system from any initial state to any desired final state in finite time, with a suitable choice of inputs; and optimal control, which is a typical control approach to minimize the cost for driving the network to a predefined state with a given number of control inputs. For large complex networks without global information of network topology, both problems remain essentially open. Here we combine graph theory and control theory for tackling the two problems in one go, using only local network topology information. For the structural controllability problem, a distributed local-game matching method is proposed, where every node plays a simple Bayesian game with local information and local interactions with adjacent nodes, ensuring a suboptimal solution at a linear complexity. Starring from any structural controllability solution, a minimizing longest control path method can efficiently reach a good solution for the optimal control in large networks. Our results provide solutions for distributed complex network control and demonstrate a way to link the structural controllability and optimal control together.

Inter-allotropic transformations in the heterogeneous carbon nanotube networks.

PubMed

Jung, Hyun Young; Jung, Sung Mi; Kim, Dong Won; Jung, Yung Joon

2017-01-19

The allotropic transformations of carbon provide an immense technological interest for tailoring the desired molecular structures in the scalable nanoelectronic devices. Herein, we explore the effects of morphology and geometric alignment of the nanotubes for the re-engineering of carbon bonds in the heterogeneous carbon nanotube (CNT) networks. By applying alternating voltage pulses and electrical forces, the single-walled CNTs in networks were predominantly transformed into other predetermined sp 2 carbon structures (multi-walled CNTs and multi-layered graphitic nanoribbons), showing a larger intensity in a coalescence-induced mode of Raman spectra with the increasing channel width. Moreover, the transformed networks have a newly discovered sp 2 -sp 3 hybrid nanostructures in accordance with the alignment. The sp 3 carbon structures at the small channel are controlled, such that they contain up to about 29.4% networks. This study provides a controllable method for specific types of inter-allotropic transformations/hybridizations, which opens up the further possibility for the engineering of nanocarbon allotropes in the robust large-scale network-based devices.

The Open World: Access to Knowledge as a Foundation for an Open World

ERIC Educational Resources Information Center

Rossini, Carolina

2010-01-01

The change brought about in the networked information environment is deep and structural, in a way that has the potential to empower cultures left out of the Industrial Revolution. Thus, the author stresses that it is fundamental for individuals to understand, from a developing nation's perspective, how the Internet changes the capacity of…

From kinetic-structure analysis to engineering crystalline fiber networks in soft materials.

PubMed

Wang, Rong-Yao; Wang, Peng; Li, Jing-Liang; Yuan, Bing; Liu, Yu; Li, Li; Liu, Xiang-Yang

2013-03-07

Understanding the role of kinetics in fiber network microstructure formation is of considerable importance in engineering gel materials to achieve their optimized performances/functionalities. In this work, we present a new approach for kinetic-structure analysis for fibrous gel materials. In this method, kinetic data is acquired using a rheology technique and is analyzed in terms of an extended Dickinson model in which the scaling behaviors of dynamic rheological properties in the gelation process are taken into account. It enables us to extract the structural parameter, i.e. the fractal dimension, of a fibrous gel from the dynamic rheological measurement of the gelation process, and to establish the kinetic-structure relationship suitable for both dilute and concentrated gelling systems. In comparison to the fractal analysis method reported in a previous study, our method is advantageous due to its general validity for a wide range of fractal structures of fibrous gels, from a highly compact network of the spherulitic domains to an open fibrous network structure. With such a kinetic-structure analysis, we can gain a quantitative understanding of the role of kinetic control in engineering the microstructure of the fiber network in gel materials.

Dermoscopy of accessory nipples in authors’ own study

PubMed Central

Szymszal, Jan; Silny, Wojciech

2014-01-01

Introduction The accessory nipple (AN) is characterised by its network-like structures, which may suggest the diagnosis of a melanocytic lesion. The knowledge about additional dermoscopic features of AN may greatly minimise the risk of unnecessary surgical excisions. Aim To analyse and present different clinical and dermoscopic forms, in which the AN may appear. Material and methods Ninety AN with dermoscopic features were evaluated in the study, detected in 14 patients between the years 2008 and 2014. Results The most common dermoscopic features of the AN were central, scar-like areas (15/19) and peripheral network-like structures (12/19). A number of cleft-like appearances (8/19) and central network-like structures (7/19) had also been observed. Moreover, among the dermoscopic features, white cobblestone-like structures (7/19), a central round dimpling with a plug (6/19) and fisheye-like structures resembling comedo-like openings (9/19) have all also been noted. There is a statistical significance in the occurrence of white cobblestone-like structures with central network-like structures (Fisher's exact test p = 0.0449). The presence of peripheral network-like structures with the occurrence of central scar-like areas was statistically highly significant (p = 0.0091). The central round dimpling was never observed alongside any central network-like structures in any of the lesions (p = 0.0436). Conclusions Accessory nipples are most commonly characterised by the occurrence of a peripheral network-like structure accompanied by the presence of a scar-like area. PMID:25097482

Inferring the mesoscale structure of layered, edge-valued, and time-varying networks

NASA Astrophysics Data System (ADS)

Peixoto, Tiago P.

2015-10-01

Many network systems are composed of interdependent but distinct types of interactions, which cannot be fully understood in isolation. These different types of interactions are often represented as layers, attributes on the edges, or as a time dependence of the network structure. Although they are crucial for a more comprehensive scientific understanding, these representations offer substantial challenges. Namely, it is an open problem how to precisely characterize the large or mesoscale structure of network systems in relation to these additional aspects. Furthermore, the direct incorporation of these features invariably increases the effective dimension of the network description, and hence aggravates the problem of overfitting, i.e., the use of overly complex characterizations that mistake purely random fluctuations for actual structure. In this work, we propose a robust and principled method to tackle these problems, by constructing generative models of modular network structure, incorporating layered, attributed and time-varying properties, as well as a nonparametric Bayesian methodology to infer the parameters from data and select the most appropriate model according to statistical evidence. We show that the method is capable of revealing hidden structure in layered, edge-valued, and time-varying networks, and that the most appropriate level of granularity with respect to the additional dimensions can be reliably identified. We illustrate our approach on a variety of empirical systems, including a social network of physicians, the voting correlations of deputies in the Brazilian national congress, the global airport network, and a proximity network of high-school students.

The making of an immigrant niche.

PubMed

Waldinger, R

1994-01-01

"This article speaks to the conceptual and methodological issues in research on the making of an immigrant niche through a case study of immigrant professionals in New York City government." The author argues that "the growth of this immigrant niche resulted from changes in the relative supply of native workers and in the structure of employment, which opened the bureaucracy to immigrants and reduced native/immigrant competition. These shifts opened hiring portals; given the advantages of network hiring for workers and managers, and an immigrant propensity for government employment, network recruitment led to a rapid buildup in immigrant ranks." excerpt

Structure and Topology Dynamics of Hyper-Frequency Networks during Rest and Auditory Oddball Performance.

PubMed

Müller, Viktor; Perdikis, Dionysios; von Oertzen, Timo; Sleimen-Malkoun, Rita; Jirsa, Viktor; Lindenberger, Ulman

2016-01-01

Resting-state and task-related recordings are characterized by oscillatory brain activity and widely distributed networks of synchronized oscillatory circuits. Electroencephalographic recordings (EEG) were used to assess network structure and network dynamics during resting state with eyes open and closed, and auditory oddball performance through phase synchronization between EEG channels. For this assessment, we constructed a hyper-frequency network (HFN) based on within- and cross-frequency coupling (WFC and CFC, respectively) at 10 oscillation frequencies ranging between 2 and 20 Hz. We found that CFC generally differentiates between task conditions better than WFC. CFC was the highest during resting state with eyes open. Using a graph-theoretical approach (GTA), we found that HFNs possess small-world network (SWN) topology with a slight tendency to random network characteristics. Moreover, analysis of the temporal fluctuations of HFNs revealed specific network topology dynamics (NTD), i.e., temporal changes of different graph-theoretical measures such as strength, clustering coefficient, characteristic path length (CPL), local, and global efficiency determined for HFNs at different time windows. The different topology metrics showed significant differences between conditions in the mean and standard deviation of these metrics both across time and nodes. In addition, using an artificial neural network approach, we found stimulus-related dynamics that varied across the different network topology metrics. We conclude that functional connectivity dynamics (FCD), or NTD, which was found using the HFN approach during rest and stimulus processing, reflects temporal and topological changes in the functional organization and reorganization of neuronal cell assemblies.

Structure and Topology Dynamics of Hyper-Frequency Networks during Rest and Auditory Oddball Performance

PubMed Central

Müller, Viktor; Perdikis, Dionysios; von Oertzen, Timo; Sleimen-Malkoun, Rita; Jirsa, Viktor; Lindenberger, Ulman

2016-01-01

Resting-state and task-related recordings are characterized by oscillatory brain activity and widely distributed networks of synchronized oscillatory circuits. Electroencephalographic recordings (EEG) were used to assess network structure and network dynamics during resting state with eyes open and closed, and auditory oddball performance through phase synchronization between EEG channels. For this assessment, we constructed a hyper-frequency network (HFN) based on within- and cross-frequency coupling (WFC and CFC, respectively) at 10 oscillation frequencies ranging between 2 and 20 Hz. We found that CFC generally differentiates between task conditions better than WFC. CFC was the highest during resting state with eyes open. Using a graph-theoretical approach (GTA), we found that HFNs possess small-world network (SWN) topology with a slight tendency to random network characteristics. Moreover, analysis of the temporal fluctuations of HFNs revealed specific network topology dynamics (NTD), i.e., temporal changes of different graph-theoretical measures such as strength, clustering coefficient, characteristic path length (CPL), local, and global efficiency determined for HFNs at different time windows. The different topology metrics showed significant differences between conditions in the mean and standard deviation of these metrics both across time and nodes. In addition, using an artificial neural network approach, we found stimulus-related dynamics that varied across the different network topology metrics. We conclude that functional connectivity dynamics (FCD), or NTD, which was found using the HFN approach during rest and stimulus processing, reflects temporal and topological changes in the functional organization and reorganization of neuronal cell assemblies. PMID:27799906

Software-defined network abstractions and configuration interfaces for building programmable quantum networks

NASA Astrophysics Data System (ADS)

Dasari, Venkat R.; Sadlier, Ronald J.; Geerhart, Billy E.; Snow, Nikolai A.; Williams, Brian P.; Humble, Travis S.

2017-05-01

Well-defined and stable quantum networks are essential to realize functional quantum communication applications. Quantum networks are complex and must use both quantum and classical channels to support quantum applications like QKD, teleportation, and superdense coding. In particular, the no-cloning theorem prevents the reliable copying of quantum signals such that the quantum and classical channels must be highly coordinated using robust and extensible methods. In this paper, we describe new network abstractions and interfaces for building programmable quantum networks. Our approach leverages new OpenFlow data structures and table type patterns to build programmable quantum networks and to support quantum applications.

Model of community emergence in weighted social networks

NASA Astrophysics Data System (ADS)

Kumpula, J. M.; Onnela, J.-P.; Saramäki, J.; Kertész, J.; Kaski, K.

2009-04-01

Over the years network theory has proven to be rapidly expanding methodology to investigate various complex systems and it has turned out to give quite unparalleled insight to their structure, function, and response through data analysis, modeling, and simulation. For social systems in particular the network approach has empirically revealed a modular structure due to interplay between the network topology and link weights between network nodes or individuals. This inspired us to develop a simple network model that could catch some salient features of mesoscopic community and macroscopic topology formation during network evolution. Our model is based on two fundamental mechanisms of network sociology for individuals to find new friends, namely cyclic closure and focal closure, which are mimicked by local search-link-reinforcement and random global attachment mechanisms, respectively. In addition we included to the model a node deletion mechanism by removing all its links simultaneously, which corresponds for an individual to depart from the network. Here we describe in detail the implementation of our model algorithm, which was found to be computationally efficient and produce many empirically observed features of large-scale social networks. Thus this model opens a new perspective for studying such collective social phenomena as spreading, structure formation, and evolutionary processes.

Contagion of Cooperation in Static and Fluid Social Networks.

PubMed

Jordan, Jillian J; Rand, David G; Arbesman, Samuel; Fowler, James H; Christakis, Nicholas A

2013-01-01

Cooperation is essential for successful human societies. Thus, understanding how cooperative and selfish behaviors spread from person to person is a topic of theoretical and practical importance. Previous laboratory experiments provide clear evidence of social contagion in the domain of cooperation, both in fixed networks and in randomly shuffled networks, but leave open the possibility of asymmetries in the spread of cooperative and selfish behaviors. Additionally, many real human interaction structures are dynamic: we often have control over whom we interact with. Dynamic networks may differ importantly in the goals and strategic considerations they promote, and thus the question of how cooperative and selfish behaviors spread in dynamic networks remains open. Here, we address these questions with data from a social dilemma laboratory experiment. We measure the contagion of both cooperative and selfish behavior over time across three different network structures that vary in the extent to which they afford individuals control over their network ties. We find that in relatively fixed networks, both cooperative and selfish behaviors are contagious. In contrast, in more dynamic networks, selfish behavior is contagious, but cooperative behavior is not: subjects are fairly likely to switch to cooperation regardless of the behavior of their neighbors. We hypothesize that this insensitivity to the behavior of neighbors in dynamic networks is the result of subjects' desire to attract new cooperative partners: even if many of one's current neighbors are defectors, it may still make sense to switch to cooperation. We further hypothesize that selfishness remains contagious in dynamic networks because of the well-documented willingness of cooperators to retaliate against selfishness, even when doing so is costly. These results shed light on the contagion of cooperative behavior in fixed and fluid networks, and have implications for influence-based interventions aiming at increasing cooperative behavior.

DISTRIBUTED RC NETWORKS WITH RATIONAL TRANSFER FUNCTIONS,

DTIC Science & Technology

A distributed RC circuit analogous to a continuously tapped transmission line can be made to have a rational short-circuit transfer admittance and...one rational shortcircuit driving-point admittance. A subcircuit of the same structure has a rational open circuit transfer impedance and one rational ...open circuit driving-point impedance. Hence, rational transfer functions may be obtained while considering either generator impedance or load

Unified functional network and nonlinear time series analysis for complex systems science: The pyunicorn package

NASA Astrophysics Data System (ADS)

Donges, Jonathan F.; Heitzig, Jobst; Beronov, Boyan; Wiedermann, Marc; Runge, Jakob; Feng, Qing Yi; Tupikina, Liubov; Stolbova, Veronika; Donner, Reik V.; Marwan, Norbert; Dijkstra, Henk A.; Kurths, Jürgen

2015-11-01

We introduce the pyunicorn (Pythonic unified complex network and recurrence analysis toolbox) open source software package for applying and combining modern methods of data analysis and modeling from complex network theory and nonlinear time series analysis. pyunicorn is a fully object-oriented and easily parallelizable package written in the language Python. It allows for the construction of functional networks such as climate networks in climatology or functional brain networks in neuroscience representing the structure of statistical interrelationships in large data sets of time series and, subsequently, investigating this structure using advanced methods of complex network theory such as measures and models for spatial networks, networks of interacting networks, node-weighted statistics, or network surrogates. Additionally, pyunicorn provides insights into the nonlinear dynamics of complex systems as recorded in uni- and multivariate time series from a non-traditional perspective by means of recurrence quantification analysis, recurrence networks, visibility graphs, and construction of surrogate time series. The range of possible applications of the library is outlined, drawing on several examples mainly from the field of climatology.

Identifying and characterizing key nodes among communities based on electrical-circuit networks.

PubMed

Zhu, Fenghui; Wang, Wenxu; Di, Zengru; Fan, Ying

2014-01-01

Complex networks with community structures are ubiquitous in the real world. Despite many approaches developed for detecting communities, we continue to lack tools for identifying overlapping and bridging nodes that play crucial roles in the interactions and communications among communities in complex networks. Here we develop an algorithm based on the local flow conservation to effectively and efficiently identify and distinguish the two types of nodes. Our method is applicable in both undirected and directed networks without a priori knowledge of the community structure. Our method bypasses the extremely challenging problem of partitioning communities in the presence of overlapping nodes that may belong to multiple communities. Due to the fact that overlapping and bridging nodes are of paramount importance in maintaining the function of many social and biological networks, our tools open new avenues towards understanding and controlling real complex networks with communities accompanied with the key nodes.

Brain modularity controls the critical behavior of spontaneous activity.

PubMed

Russo, R; Herrmann, H J; de Arcangelis, L

2014-03-13

The human brain exhibits a complex structure made of scale-free highly connected modules loosely interconnected by weaker links to form a small-world network. These features appear in healthy patients whereas neurological diseases often modify this structure. An important open question concerns the role of brain modularity in sustaining the critical behaviour of spontaneous activity. Here we analyse the neuronal activity of a model, successful in reproducing on non-modular networks the scaling behaviour observed in experimental data, on a modular network implementing the main statistical features measured in human brain. We show that on a modular network, regardless the strength of the synaptic connections or the modular size and number, activity is never fully scale-free. Neuronal avalanches can invade different modules which results in an activity depression, hindering further avalanche propagation. Critical behaviour is solely recovered if inter-module connections are added, modifying the modular into a more random structure.

Irreversible thermodynamics of open chemical networks. I. Emergent cycles and broken conservation laws

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

Polettini, Matteo, E-mail: matteo.polettini@uni.lu; Esposito, Massimiliano

In this paper and Paper II, we outline a general framework for the thermodynamic description of open chemical reaction networks, with special regard to metabolic networks regulating cellular physiology and biochemical functions. We first introduce closed networks “in a box”, whose thermodynamics is subjected to strict physical constraints: the mass-action law, elementarity of processes, and detailed balance. We further digress on the role of solvents and on the seemingly unacknowledged property of network independence of free energy landscapes. We then open the system by assuming that the concentrations of certain substrate species (the chemostats) are fixed, whether because promptly regulatedmore » by the environment via contact with reservoirs, or because nearly constant in a time window. As a result, the system is driven out of equilibrium. A rich algebraic and topological structure ensues in the network of internal species: Emergent irreversible cycles are associated with nonvanishing affinities, whose symmetries are dictated by the breakage of conservation laws. These central results are resumed in the relation a + b = s{sup Y} between the number of fundamental affinities a, that of broken conservation laws b and the number of chemostats s{sup Y}. We decompose the steady state entropy production rate in terms of fundamental fluxes and affinities in the spirit of Schnakenberg's theory of network thermodynamics, paving the way for the forthcoming treatment of the linear regime, of efficiency and tight coupling, of free energy transduction, and of thermodynamic constraints for network reconstruction.« less

Irreversible thermodynamics of open chemical networks. I. Emergent cycles and broken conservation laws.

PubMed

Polettini, Matteo; Esposito, Massimiliano

2014-07-14

In this paper and Paper II, we outline a general framework for the thermodynamic description of open chemical reaction networks, with special regard to metabolic networks regulating cellular physiology and biochemical functions. We first introduce closed networks "in a box", whose thermodynamics is subjected to strict physical constraints: the mass-action law, elementarity of processes, and detailed balance. We further digress on the role of solvents and on the seemingly unacknowledged property of network independence of free energy landscapes. We then open the system by assuming that the concentrations of certain substrate species (the chemostats) are fixed, whether because promptly regulated by the environment via contact with reservoirs, or because nearly constant in a time window. As a result, the system is driven out of equilibrium. A rich algebraic and topological structure ensues in the network of internal species: Emergent irreversible cycles are associated with nonvanishing affinities, whose symmetries are dictated by the breakage of conservation laws. These central results are resumed in the relation a + b = s(Y) between the number of fundamental affinities a, that of broken conservation laws b and the number of chemostats s(Y). We decompose the steady state entropy production rate in terms of fundamental fluxes and affinities in the spirit of Schnakenberg's theory of network thermodynamics, paving the way for the forthcoming treatment of the linear regime, of efficiency and tight coupling, of free energy transduction, and of thermodynamic constraints for network reconstruction.

Irreversible thermodynamics of open chemical networks. I. Emergent cycles and broken conservation laws

NASA Astrophysics Data System (ADS)

Polettini, Matteo; Esposito, Massimiliano

2014-07-01

In this paper and Paper II, we outline a general framework for the thermodynamic description of open chemical reaction networks, with special regard to metabolic networks regulating cellular physiology and biochemical functions. We first introduce closed networks "in a box", whose thermodynamics is subjected to strict physical constraints: the mass-action law, elementarity of processes, and detailed balance. We further digress on the role of solvents and on the seemingly unacknowledged property of network independence of free energy landscapes. We then open the system by assuming that the concentrations of certain substrate species (the chemostats) are fixed, whether because promptly regulated by the environment via contact with reservoirs, or because nearly constant in a time window. As a result, the system is driven out of equilibrium. A rich algebraic and topological structure ensues in the network of internal species: Emergent irreversible cycles are associated with nonvanishing affinities, whose symmetries are dictated by the breakage of conservation laws. These central results are resumed in the relation a + b = sY between the number of fundamental affinities a, that of broken conservation laws b and the number of chemostats sY. We decompose the steady state entropy production rate in terms of fundamental fluxes and affinities in the spirit of Schnakenberg's theory of network thermodynamics, paving the way for the forthcoming treatment of the linear regime, of efficiency and tight coupling, of free energy transduction, and of thermodynamic constraints for network reconstruction.

Influence of Applying Additional Forcing Fans for the Air Distribution in Ventilation Network

NASA Astrophysics Data System (ADS)

Szlązak, Nikodem; Obracaj, Dariusz; Korzec, Marek

2016-09-01

Mining progress in underground mines cause the ongoing movement of working areas. Consequently, it becomes necessary to adapt the ventilation network of a mine to direct airflow into newly-opened districts. For economic reasons, opening new fields is often achieved via underground workings. Length of primary intake and return routes increases and also increases the total resistance of a complex ventilation network. The development of a subsurface structure can make it necessary to change the air distribution in a ventilation network. Increasing airflow into newly-opened districts is necessary. In mines where extraction does not entail gas-related hazards, there is possibility of implementing a push-pull ventilation system in order to supplement airflows to newly developed mining fields. This is achieved by installing subsurface fan stations with forcing fans at the bottom of downcast shaft. In push-pull systems with multiple main fans, it is vital to select forcing fans with characteristic curves matching those of the existing exhaust fans to prevent undesirable mutual interaction. In complex ventilation networks it is necessary to calculate distribution of airflow (especially in networks with a large number of installed fans). In the article the influence of applying additional forcing fans for the air distribution in ventilation network for underground mine were considered. There are also analysed the extent of overpressure caused by the additional forcing fan in branches of the ventilation network (the operating range of additional forcing fan). Possibilities of increasing airflow rate in working areas were conducted.

Self-organization of network dynamics into local quantized states.

PubMed

Nicolaides, Christos; Juanes, Ruben; Cueto-Felgueroso, Luis

2016-02-17

Self-organization and pattern formation in network-organized systems emerges from the collective activation and interaction of many interconnected units. A striking feature of these non-equilibrium structures is that they are often localized and robust: only a small subset of the nodes, or cell assembly, is activated. Understanding the role of cell assemblies as basic functional units in neural networks and socio-technical systems emerges as a fundamental challenge in network theory. A key open question is how these elementary building blocks emerge, and how they operate, linking structure and function in complex networks. Here we show that a network analogue of the Swift-Hohenberg continuum model-a minimal-ingredients model of nodal activation and interaction within a complex network-is able to produce a complex suite of localized patterns. Hence, the spontaneous formation of robust operational cell assemblies in complex networks can be explained as the result of self-organization, even in the absence of synaptic reinforcements.

The topology of large Open Connectome networks for the human brain.

PubMed

Gastner, Michael T; Ódor, Géza

2016-06-07

The structural human connectome (i.e. the network of fiber connections in the brain) can be analyzed at ever finer spatial resolution thanks to advances in neuroimaging. Here we analyze several large data sets for the human brain network made available by the Open Connectome Project. We apply statistical model selection to characterize the degree distributions of graphs containing up to nodes and edges. A three-parameter generalized Weibull (also known as a stretched exponential) distribution is a good fit to most of the observed degree distributions. For almost all networks, simple power laws cannot fit the data, but in some cases there is statistical support for power laws with an exponential cutoff. We also calculate the topological (graph) dimension D and the small-world coefficient σ of these networks. While σ suggests a small-world topology, we found that D < 4 showing that long-distance connections provide only a small correction to the topology of the embedding three-dimensional space.

The topology of large Open Connectome networks for the human brain

NASA Astrophysics Data System (ADS)

Gastner, Michael T.; Ódor, Géza

2016-06-01

The structural human connectome (i.e. the network of fiber connections in the brain) can be analyzed at ever finer spatial resolution thanks to advances in neuroimaging. Here we analyze several large data sets for the human brain network made available by the Open Connectome Project. We apply statistical model selection to characterize the degree distributions of graphs containing up to nodes and edges. A three-parameter generalized Weibull (also known as a stretched exponential) distribution is a good fit to most of the observed degree distributions. For almost all networks, simple power laws cannot fit the data, but in some cases there is statistical support for power laws with an exponential cutoff. We also calculate the topological (graph) dimension D and the small-world coefficient σ of these networks. While σ suggests a small-world topology, we found that D < 4 showing that long-distance connections provide only a small correction to the topology of the embedding three-dimensional space.

Network Analysis on Attitudes: A Brief Tutorial.

PubMed

Dalege, Jonas; Borsboom, Denny; van Harreveld, Frenk; van der Maas, Han L J

2017-07-01

In this article, we provide a brief tutorial on the estimation, analysis, and simulation on attitude networks using the programming language R. We first discuss what a network is and subsequently show how one can estimate a regularized network on typical attitude data. For this, we use open-access data on the attitudes toward Barack Obama during the 2012 American presidential election. Second, we show how one can calculate standard network measures such as community structure, centrality, and connectivity on this estimated attitude network. Third, we show how one can simulate from an estimated attitude network to derive predictions from attitude networks. By this, we highlight that network theory provides a framework for both testing and developing formalized hypotheses on attitudes and related core social psychological constructs.

Network Analysis on Attitudes

PubMed Central

Borsboom, Denny; van Harreveld, Frenk; van der Maas, Han L. J.

2017-01-01

In this article, we provide a brief tutorial on the estimation, analysis, and simulation on attitude networks using the programming language R. We first discuss what a network is and subsequently show how one can estimate a regularized network on typical attitude data. For this, we use open-access data on the attitudes toward Barack Obama during the 2012 American presidential election. Second, we show how one can calculate standard network measures such as community structure, centrality, and connectivity on this estimated attitude network. Third, we show how one can simulate from an estimated attitude network to derive predictions from attitude networks. By this, we highlight that network theory provides a framework for both testing and developing formalized hypotheses on attitudes and related core social psychological constructs. PMID:28919944

Network community structure and loop coefficient method

NASA Astrophysics Data System (ADS)

Vragović, I.; Louis, E.

2006-07-01

A modular structure, in which groups of tightly connected nodes could be resolved as separate entities, is a property that can be found in many complex networks. In this paper, we propose a algorithm for identifying communities in networks. It is based on a local measure, so-called loop coefficient that is a generalization of the clustering coefficient. Nodes with a large loop coefficient tend to be core inner community nodes, while other vertices are usually peripheral sites at the borders of communities. Our method gives satisfactory results for both artificial and real-world graphs, if they have a relatively pronounced modular structure. This type of algorithm could open a way of interpreting the role of nodes in communities in terms of the local loop coefficient, and could be used as a complement to other methods.

Structure and organization of Stratocumulus fields: A network approach

NASA Astrophysics Data System (ADS)

Glassmeier, Franziska; Feingold, Graham

2017-04-01

The representation of Stratocumulus (Sc) clouds and their radiative impact is one of the large challenges for global climate models. Aerosol-cloud-precipitation interactions greatly contribute to this challenge by influencing the morphology of Sc fields: In the absence of rain, Sc are arranged in a relatively regular pattern of cloudy cells separated by cloud-free rings of down welling air ('closed cells'). Raining cloud fields, in contrast, exhibit an oscillating pattern of cloudy rings surrounding cloud free cells of negatively buoyant air caused by sedimentation and evaporation of rain ('open cells'). Surprisingly, these regular structures of open and closed cellular Sc fields and their potential for the development of new parameterizations have hardly been explored. In this contribution, we approach the organization of Sc from the perspective of a 2-dimensional random network. We find that cellular networks derived from LES simulations of open- and closed-cell Sc cases are almost indistinguishable and share the following features: (i) The distributions of nearest neighbors, or cell degree, are centered at six. This corresponds to approximately hexagonal cloud cells and is a direct mathematical consequence (Euler formula) of the triple junctions featured by Sc organization. (ii) The degree of individual cells is found to be proportional to the normalized size of the cells. This means that cell arrangement is independent of the typical cell size. (iii) Reflecting the continuously renewing dynamics of Sc fields, large (high-degree) cells tend to be neighbored by small (low-degree) cells and vice versa. These macroscopic network properties emerge independent of the state of the Sc field because the different processes governing the evolution of closed as compared to open cells correspond to topologically equivalent network dynamics. By developing a heuristic model, we show that open and closed cell dynamics can both be mimicked by versions of cell division and cell disappearance and are biased towards the expansion of smaller cells. As a conclusion of our network analysis, Sc organization can be characterized by a typical length scale and a scale-independent cell arrangement. While the typical length scale emerges from the full complexity of aerosol-cloud-precipitation-radiation interactions, cell arrangement is independent of cloud processes and its evolution could be parameterized based on our heuristic model.

A Dialogic Action Perspective on Open Collective Inquiry in Online Forums

ERIC Educational Resources Information Center

Jung, Yusun

2012-01-01

In today's networked environment, online forums emerge as a popular form of social structures that have greater opportunities for learning in various organizational contexts. A plethora of studies have investigated the phenomenon to identify antecedent of its success, such as individual characteristics and organizational structure. However,…

Effects of contact network structure on epidemic transmission trees: implications for data required to estimate network structure.

PubMed

Carnegie, Nicole Bohme

2018-01-30

Understanding the dynamics of disease spread is key to developing effective interventions to control or prevent an epidemic. The structure of the network of contacts over which the disease spreads has been shown to have a strong influence on the outcome of the epidemic, but an open question remains as to whether it is possible to estimate contact network features from data collected in an epidemic. The approach taken in this paper is to examine the distributions of epidemic outcomes arising from epidemics on networks with particular structural features to assess whether that structure could be measured from epidemic data and what other constraints might be needed to make the problem identifiable. To this end, we vary the network size, mean degree, and transmissibility of the pathogen, as well as the network feature of interest: clustering, degree assortativity, or attribute-based preferential mixing. We record several standard measures of the size and spread of the epidemic, as well as measures that describe the shape of the transmission tree in order to ascertain whether there are detectable signals in the final data from the outbreak. The results suggest that there is potential to estimate contact network features from transmission trees or pure epidemic data, particularly for diseases with high transmissibility or for which the relevant contact network is of low mean degree. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

A mismatch between supply and demand of social support in dementia care: a qualitative study on the perspectives of spousal caregivers and their social network members.

PubMed

Dam, Alieske E H; Boots, Lizzy M M; van Boxtel, Martin P J; Verhey, Frans R J; de Vugt, Marjolein E

2017-06-13

Access to social support contributes to feelings of independence and better social health. This qualitative study aims to investigate multi-informant perspectives on informal social support in dementia care networks. Ten spousal caregivers of people with dementia (PwD) completed an ecogram, a social network card and a semi-structured interview. The ecogram aimed to trigger subjective experiences regarding social support. Subsequently, 17 network members were interviewed. The qualitative analyses identified codes, categories, and themes. Sixth themes emerged: (1) barriers to ask for support; (2) facilitators to ask for support; (3) barriers to offer support; (4) facilitators to offer support; (5) a mismatch between supply and demand of social support; and (6) openness in communication to repair the imbalance. Integrating social network perspectives resulted in a novel model identifying a mismatch between the supply and demand of social support, strengthened by a cognitive bias: caregivers reported to think for other social network members and vice versa. Openness in communication in formal and informal care systems might repair this mismatch.

A generalized theory of preferential linking

NASA Astrophysics Data System (ADS)

Hu, Haibo; Guo, Jinli; Liu, Xuan; Wang, Xiaofan

2014-12-01

There are diverse mechanisms driving the evolution of social networks. A key open question dealing with understanding their evolution is: How do various preferential linking mechanisms produce networks with different features? In this paper we first empirically study preferential linking phenomena in an evolving online social network, find and validate the linear preference. We propose an analyzable model which captures the real growth process of the network and reveals the underlying mechanism dominating its evolution. Furthermore based on preferential linking we propose a generalized model reproducing the evolution of online social networks, and present unified analytical results describing network characteristics for 27 preference scenarios. We study the mathematical structure of degree distributions and find that within the framework of preferential linking analytical degree distributions can only be the combinations of finite kinds of functions which are related to rational, logarithmic and inverse tangent functions, and extremely complex network structure will emerge even for very simple sublinear preferential linking. This work not only provides a verifiable origin for the emergence of various network characteristics in social networks, but bridges the micro individuals' behaviors and the global organization of social networks.

Self-organization of network dynamics into local quantized states

DOE PAGES

Nicolaides, Christos; Juanes, Ruben; Cueto-Felgueroso, Luis

2016-02-17

Self-organization and pattern formation in network-organized systems emerges from the collective activation and interaction of many interconnected units. A striking feature of these non-equilibrium structures is that they are often localized and robust: only a small subset of the nodes, or cell assembly, is activated. Understanding the role of cell assemblies as basic functional units in neural networks and socio-technical systems emerges as a fundamental challenge in network theory. A key open question is how these elementary building blocks emerge, and how they operate, linking structure and function in complex networks. Here we show that a network analogue of themore » Swift-Hohenberg continuum model—a minimal-ingredients model of nodal activation and interaction within a complex network—is able to produce a complex suite of localized patterns. Thus, the spontaneous formation of robust operational cell assemblies in complex networks can be explained as the result of self-organization, even in the absence of synaptic reinforcements.« less

Self-organization of network dynamics into local quantized states

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

Nicolaides, Christos; Juanes, Ruben; Cueto-Felgueroso, Luis

Self-organization and pattern formation in network-organized systems emerges from the collective activation and interaction of many interconnected units. A striking feature of these non-equilibrium structures is that they are often localized and robust: only a small subset of the nodes, or cell assembly, is activated. Understanding the role of cell assemblies as basic functional units in neural networks and socio-technical systems emerges as a fundamental challenge in network theory. A key open question is how these elementary building blocks emerge, and how they operate, linking structure and function in complex networks. Here we show that a network analogue of themore » Swift-Hohenberg continuum model—a minimal-ingredients model of nodal activation and interaction within a complex network—is able to produce a complex suite of localized patterns. Thus, the spontaneous formation of robust operational cell assemblies in complex networks can be explained as the result of self-organization, even in the absence of synaptic reinforcements.« less

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

Nigro, Valentina, E-mail: nigro@fis.uniroma3.it; Bruni, Fabio; Ricci, Maria Antonietta

The temperature dependence of the local intra-particle structure of colloidal microgel particles, composed of interpenetrated polymer networks, has been investigated by small-angle neutron scattering at different pH and concentrations, in the range (299÷315) K, where a volume phase transition from a swollen to a shrunken state takes place. Data are well described by a theoretical model that takes into account the presence of both interpenetrated polymer networks and cross-linkers. Two different behaviors are found across the volume phase transition. At neutral pH and T ≈ 307 K, a sharp change of the local structure from a water rich open inhomogeneousmore » interpenetrated polymer network to a homogeneous porous solid-like structure after expelling water is observed. Differently, at acidic pH, the local structure changes almost continuously. These findings demonstrate that a fine control of the pH of the system allows to tune the sharpness of the volume-phase transition.« less

Structural reducibility of multilayer networks

NASA Astrophysics Data System (ADS)

de Domenico, Manlio; Nicosia, Vincenzo; Arenas, Alexandre; Latora, Vito

2015-04-01

Many complex systems can be represented as networks consisting of distinct types of interactions, which can be categorized as links belonging to different layers. For example, a good description of the full protein-protein interactome requires, for some organisms, up to seven distinct network layers, accounting for different genetic and physical interactions, each containing thousands of protein-protein relationships. A fundamental open question is then how many layers are indeed necessary to accurately represent the structure of a multilayered complex system. Here we introduce a method based on quantum theory to reduce the number of layers to a minimum while maximizing the distinguishability between the multilayer network and the corresponding aggregated graph. We validate our approach on synthetic benchmarks and we show that the number of informative layers in some real multilayer networks of protein-genetic interactions, social, economical and transportation systems can be reduced by up to 75%.

The Network Structure of Human Personality According to the NEO-PI-R: Matching Network Community Structure to Factor Structure

PubMed Central

Goekoop, Rutger; Goekoop, Jaap G.; Scholte, H. Steven

2012-01-01

Introduction Human personality is described preferentially in terms of factors (dimensions) found using factor analysis. An alternative and highly related method is network analysis, which may have several advantages over factor analytic methods. Aim To directly compare the ability of network community detection (NCD) and principal component factor analysis (PCA) to examine modularity in multidimensional datasets such as the neuroticism-extraversion-openness personality inventory revised (NEO-PI-R). Methods 434 healthy subjects were tested on the NEO-PI-R. PCA was performed to extract factor structures (FS) of the current dataset using both item scores and facet scores. Correlational network graphs were constructed from univariate correlation matrices of interactions between both items and facets. These networks were pruned in a link-by-link fashion while calculating the network community structure (NCS) of each resulting network using the Wakita Tsurumi clustering algorithm. NCSs were matched against FS and networks of best matches were kept for further analysis. Results At facet level, NCS showed a best match (96.2%) with a ‘confirmatory’ 5-FS. At item level, NCS showed a best match (80%) with the standard 5-FS and involved a total of 6 network clusters. Lesser matches were found with ‘confirmatory’ 5-FS and ‘exploratory’ 6-FS of the current dataset. Network analysis did not identify facets as a separate level of organization in between items and clusters. A small-world network structure was found in both item- and facet level networks. Conclusion We present the first optimized network graph of personality traits according to the NEO-PI-R: a ‘Personality Web’. Such a web may represent the possible routes that subjects can take during personality development. NCD outperforms PCA by producing plausible modularity at item level in non-standard datasets, and can identify the key roles of individual items and clusters in the network. PMID:23284713

The network structure of human personality according to the NEO-PI-R: matching network community structure to factor structure.

PubMed

Goekoop, Rutger; Goekoop, Jaap G; Scholte, H Steven

2012-01-01

Human personality is described preferentially in terms of factors (dimensions) found using factor analysis. An alternative and highly related method is network analysis, which may have several advantages over factor analytic methods. To directly compare the ability of network community detection (NCD) and principal component factor analysis (PCA) to examine modularity in multidimensional datasets such as the neuroticism-extraversion-openness personality inventory revised (NEO-PI-R). 434 healthy subjects were tested on the NEO-PI-R. PCA was performed to extract factor structures (FS) of the current dataset using both item scores and facet scores. Correlational network graphs were constructed from univariate correlation matrices of interactions between both items and facets. These networks were pruned in a link-by-link fashion while calculating the network community structure (NCS) of each resulting network using the Wakita Tsurumi clustering algorithm. NCSs were matched against FS and networks of best matches were kept for further analysis. At facet level, NCS showed a best match (96.2%) with a 'confirmatory' 5-FS. At item level, NCS showed a best match (80%) with the standard 5-FS and involved a total of 6 network clusters. Lesser matches were found with 'confirmatory' 5-FS and 'exploratory' 6-FS of the current dataset. Network analysis did not identify facets as a separate level of organization in between items and clusters. A small-world network structure was found in both item- and facet level networks. We present the first optimized network graph of personality traits according to the NEO-PI-R: a 'Personality Web'. Such a web may represent the possible routes that subjects can take during personality development. NCD outperforms PCA by producing plausible modularity at item level in non-standard datasets, and can identify the key roles of individual items and clusters in the network.

NEFI: Network Extraction From Images

PubMed Central

Dirnberger, M.; Kehl, T.; Neumann, A.

2015-01-01

Networks are amongst the central building blocks of many systems. Given a graph of a network, methods from graph theory enable a precise investigation of its properties. Software for the analysis of graphs is widely available and has been applied to study various types of networks. In some applications, graph acquisition is relatively simple. However, for many networks data collection relies on images where graph extraction requires domain-specific solutions. Here we introduce NEFI, a tool that extracts graphs from images of networks originating in various domains. Regarding previous work on graph extraction, theoretical results are fully accessible only to an expert audience and ready-to-use implementations for non-experts are rarely available or insufficiently documented. NEFI provides a novel platform allowing practitioners to easily extract graphs from images by combining basic tools from image processing, computer vision and graph theory. Thus, NEFI constitutes an alternative to tedious manual graph extraction and special purpose tools. We anticipate NEFI to enable time-efficient collection of large datasets. The analysis of these novel datasets may open up the possibility to gain new insights into the structure and function of various networks. NEFI is open source and available at http://nefi.mpi-inf.mpg.de. PMID:26521675

3D Filament Network Segmentation with Multiple Active Contours

NASA Astrophysics Data System (ADS)

Xu, Ting; Vavylonis, Dimitrios; Huang, Xiaolei

2014-03-01

Fluorescence microscopy is frequently used to study two and three dimensional network structures formed by cytoskeletal polymer fibers such as actin filaments and microtubules. While these cytoskeletal structures are often dilute enough to allow imaging of individual filaments or bundles of them, quantitative analysis of these images is challenging. To facilitate quantitative, reproducible and objective analysis of the image data, we developed a semi-automated method to extract actin networks and retrieve their topology in 3D. Our method uses multiple Stretching Open Active Contours (SOACs) that are automatically initialized at image intensity ridges and then evolve along the centerlines of filaments in the network. SOACs can merge, stop at junctions, and reconfigure with others to allow smooth crossing at junctions of filaments. The proposed approach is generally applicable to images of curvilinear networks with low SNR. We demonstrate its potential by extracting the centerlines of synthetic meshwork images, actin networks in 2D TIRF Microscopy images, and 3D actin cable meshworks of live fission yeast cells imaged by spinning disk confocal microscopy.

Dynamical gauge effects in an open quantum network

NASA Astrophysics Data System (ADS)

Zhao, Jianshi; Price, Craig; Liu, Qi; Gemelke, Nathan

2016-05-01

We describe new experimental techniques for simulation of high-energy field theories based on an analogy between open thermodynamic systems and effective dynamical gauge-fields following SU(2) × U(1) Yang-Mills models. By coupling near-resonant laser-modes to atoms moving in a disordered optical environment, we create an open system which exhibits a non-equilibrium phase transition between two steady-state behaviors, exhibiting scale-invariant behavior near the transition. By measuring transport of atoms through the disordered network, we observe two distinct scaling behaviors, corresponding to the classical and quantum limits for the dynamical gauge field. This behavior is loosely analogous to dynamical gauge effects in quantum chromodynamics, and can mapped onto generalized open problems in theoretical understanding of quantized non-Abelian gauge theories. Additional, the scaling behavior can be understood from the geometric structure of the gauge potential and linked to the measure of information in the local disordered potential, reflecting an underlying holographic principle. We acknowledge support from NSF Award No.1068570, and the Charles E. Kaufman Foundation.

Metric projection for dynamic multiplex networks.

PubMed

Jurman, Giuseppe

2016-08-01

Evolving multiplex networks are a powerful model for representing the dynamics along time of different phenomena, such as social networks, power grids, biological pathways. However, exploring the structure of the multiplex network time series is still an open problem. Here we propose a two-step strategy to tackle this problem based on the concept of distance (metric) between networks. Given a multiplex graph, first a network of networks is built for each time step, and then a real valued time series is obtained by the sequence of (simple) networks by evaluating the distance from the first element of the series. The effectiveness of this approach in detecting the occurring changes along the original time series is shown on a synthetic example first, and then on the Gulf dataset of political events.

Open source system OpenVPN in a function of Virtual Private Network

NASA Astrophysics Data System (ADS)

Skendzic, A.; Kovacic, B.

2017-05-01

Using of Virtual Private Networks (VPN) can establish high security level in network communication. VPN technology enables high security networking using distributed or public network infrastructure. VPN uses different security and managing rules inside networks. It can be set up using different communication channels like Internet or separate ISP communication infrastructure. VPN private network makes security communication channel over public network between two endpoints (computers). OpenVPN is an open source software product under GNU General Public License (GPL) that can be used to establish VPN communication between two computers inside business local network over public communication infrastructure. It uses special security protocols and 256-bit Encryption and it is capable of traversing network address translators (NATs) and firewalls. It allows computers to authenticate each other using a pre-shared secret key, certificates or username and password. This work gives review of VPN technology with a special accent on OpenVPN. This paper will also give comparison and financial benefits of using open source VPN software in business environment.

Programming of a Mn-coordinated 4-4‧-biphenyl dicarboxylic acid nanosystem on Au(1 1 1) and investigation of the non-covalent binding of C60 molecules

NASA Astrophysics Data System (ADS)

Zhang, Yan-Feng; Zhu, Na; Komeda, T.

The fabrication of Mn-based coordination networks on a Au(1 1 1) substrate with 4-4 '-biphenyl dicarboxylic acid (BDA) as the linker molecule was investigated by scanning tunneling microscopy. Intriguing structures of ladder and rectangular-shaped networks were obtained by controlling the ratios of deposited amount of BDA molecules and Mn atoms. These structures are well explained by models in which BDA molecules occupy the perimeter of the rectangles and a pair of two Mn atoms are placed at the lattice points. For the rectangular structure, further two phases of a rectangular and a square networks were identified in which the paired Mn atoms were directing an identical direction and 90° rotated in an alternate manner, respectively. In addition, it was revealed that the open space surrounded by rectangle BDA molecules could capture a dimer of C60 molecules which were deposited on the Mn-based BDA networks.

Linking structure and activity in nonlinear spiking networks

PubMed Central

Josić, Krešimir; Shea-Brown, Eric

2017-01-01

Recent experimental advances are producing an avalanche of data on both neural connectivity and neural activity. To take full advantage of these two emerging datasets we need a framework that links them, revealing how collective neural activity arises from the structure of neural connectivity and intrinsic neural dynamics. This problem of structure-driven activity has drawn major interest in computational neuroscience. Existing methods for relating activity and architecture in spiking networks rely on linearizing activity around a central operating point and thus fail to capture the nonlinear responses of individual neurons that are the hallmark of neural information processing. Here, we overcome this limitation and present a new relationship between connectivity and activity in networks of nonlinear spiking neurons by developing a diagrammatic fluctuation expansion based on statistical field theory. We explicitly show how recurrent network structure produces pairwise and higher-order correlated activity, and how nonlinearities impact the networks’ spiking activity. Our findings open new avenues to investigating how single-neuron nonlinearities—including those of different cell types—combine with connectivity to shape population activity and function. PMID:28644840

An Interactive, Mobile-Based Tool for Personal Social Network Data Collection and Visualization Among a Geographically Isolated and Socioeconomically Disadvantaged Population: Early-Stage Feasibility Study With Qualitative User Feedback.

PubMed

Eddens, Katherine S; Fagan, Jesse M; Collins, Tom

2017-06-22

Personal social networks have a profound impact on our health, yet collecting personal network data for use in health communication, behavior change, or translation and dissemination interventions has proved challenging. Recent advances in social network data collection software have reduced the burden of network studies on researchers and respondents alike, yet little testing has occurred to discover whether these methods are: (1) acceptable to a variety of target populations, including those who may have limited experience with technology or limited literacy; and (2) practical in the field, specifically in areas that are geographically and technologically disconnected, such as rural Appalachian Kentucky. We explored the early-stage feasibility (Acceptability, Demand, Implementation, and Practicality) of using innovative, interactive, tablet-based network data collection and visualization software (OpenEddi) in field collection of personal network data in Appalachian Kentucky. A total of 168 rural Appalachian women who had previously participated in a study on the use of a self-collected vaginal swab (SCVS) for human papillomavirus testing were recruited by community-based nurse interviewers between September 2013 and August 2014. Participants completed egocentric network surveys via OpenEddi, which captured social and communication network influences on participation in, and recruitment to, the SCVS study. After study completion, we conducted a qualitative group interview with four nurse interviewers and two participants in the network study. Using this qualitative data, and quantitative data from the network study, we applied guidelines from Bowen et al to assess feasibility in four areas of early-stage development of OpenEddi: Acceptability, Demand, Implementation, and Practicality. Basic descriptive network statistics (size, edges, density) were analyzed using RStudio. OpenEddi was perceived as fun, novel, and superior to other data collection methods or tools. Respondents enjoyed the social network survey component, and visualizing social networks produced thoughtful responses from participants about leveraging or changing network content and structure for specific health-promoting purposes. Areas for improved literacy and functionality of the tool were identified. However, technical issues led to substantial (50%) data loss, limiting the success of its implementation from a researcher's perspective, and hindering practicality in the field. OpenEddi is a promising data collection tool for use in geographically isolated and socioeconomically disadvantaged populations. Future development will mitigate technical problems, improve usability and literacy, and test new methods of data collection. These changes will support goals for use of this tool in the delivery of network-based health communication and social support interventions to socioeconomically disadvantaged populations. ©Katherine S Eddens, Jesse M Fagan, Tom Collins. Originally published in JMIR Research Protocols (http://www.researchprotocols.org), 22.06.2017.

An Interactive, Mobile-Based Tool for Personal Social Network Data Collection and Visualization Among a Geographically Isolated and Socioeconomically Disadvantaged Population: Early-Stage Feasibility Study With Qualitative User Feedback

PubMed Central

Fagan, Jesse M; Collins, Tom

2017-01-01

Background Personal social networks have a profound impact on our health, yet collecting personal network data for use in health communication, behavior change, or translation and dissemination interventions has proved challenging. Recent advances in social network data collection software have reduced the burden of network studies on researchers and respondents alike, yet little testing has occurred to discover whether these methods are: (1) acceptable to a variety of target populations, including those who may have limited experience with technology or limited literacy; and (2) practical in the field, specifically in areas that are geographically and technologically disconnected, such as rural Appalachian Kentucky. Objective We explored the early-stage feasibility (Acceptability, Demand, Implementation, and Practicality) of using innovative, interactive, tablet-based network data collection and visualization software (OpenEddi) in field collection of personal network data in Appalachian Kentucky. Methods A total of 168 rural Appalachian women who had previously participated in a study on the use of a self-collected vaginal swab (SCVS) for human papillomavirus testing were recruited by community-based nurse interviewers between September 2013 and August 2014. Participants completed egocentric network surveys via OpenEddi, which captured social and communication network influences on participation in, and recruitment to, the SCVS study. After study completion, we conducted a qualitative group interview with four nurse interviewers and two participants in the network study. Using this qualitative data, and quantitative data from the network study, we applied guidelines from Bowen et al to assess feasibility in four areas of early-stage development of OpenEddi: Acceptability, Demand, Implementation, and Practicality. Basic descriptive network statistics (size, edges, density) were analyzed using RStudio. Results OpenEddi was perceived as fun, novel, and superior to other data collection methods or tools. Respondents enjoyed the social network survey component, and visualizing social networks produced thoughtful responses from participants about leveraging or changing network content and structure for specific health-promoting purposes. Areas for improved literacy and functionality of the tool were identified. However, technical issues led to substantial (50%) data loss, limiting the success of its implementation from a researcher’s perspective, and hindering practicality in the field. Conclusions OpenEddi is a promising data collection tool for use in geographically isolated and socioeconomically disadvantaged populations. Future development will mitigate technical problems, improve usability and literacy, and test new methods of data collection. These changes will support goals for use of this tool in the delivery of network-based health communication and social support interventions to socioeconomically disadvantaged populations. PMID:28642217

Playing distributed two-party quantum games on quantum networks

NASA Astrophysics Data System (ADS)

Liu, Bo-Yang; Dai, Hong-Yi; Zhang, Ming

2017-12-01

This paper investigates quantum games between two remote players on quantum networks. We propose two schemes for distributed remote quantum games: the client-server scheme based on states transmission between nodes of the network and the peer-to-peer scheme devised upon remote quantum operations. Following these schemes, we construct two designs of the distributed prisoners' dilemma game on quantum entangling networks, where concrete methods are employed for teleportation and nonlocal two-qubits unitary gates, respectively. It seems to us that the requirement for playing distributed quantum games on networks is still an open problem. We explore this problem by comparing and characterizing the two schemes from the viewpoints of network structures, quantum and classical operations, experimental realization and simplification.

An operational open-end file transfer protocol for mobile satellite communications

NASA Technical Reports Server (NTRS)

Wang, Charles; Cheng, Unjeng; Yan, Tsun-Yee

1988-01-01

This paper describes an operational open-end file transfer protocol which includes the connecting procedure, data transfer, and relinquishment procedure for mobile satellite communications. The protocol makes use of the frame level and packet level formats of the X.25 standard for the data link layer and network layer, respectively. The structure of a testbed for experimental simulation of this protocol over a mobile fading channel is also introduced.

Architecture Design and Experimental Platform Demonstration of Optical Network based on OpenFlow Protocol

NASA Astrophysics Data System (ADS)

Xing, Fangyuan; Wang, Honghuan; Yin, Hongxi; Li, Ming; Luo, Shenzi; Wu, Chenguang

2016-02-01

With the extensive application of cloud computing and data centres, as well as the constantly emerging services, the big data with the burst characteristic has brought huge challenges to optical networks. Consequently, the software defined optical network (SDON) that combines optical networks with software defined network (SDN), has attracted much attention. In this paper, an OpenFlow-enabled optical node employed in optical cross-connect (OXC) and reconfigurable optical add/drop multiplexer (ROADM), is proposed. An open source OpenFlow controller is extended on routing strategies. In addition, the experiment platform based on OpenFlow protocol for software defined optical network, is designed. The feasibility and availability of the OpenFlow-enabled optical nodes and the extended OpenFlow controller are validated by the connectivity test, protection switching and load balancing experiments in this test platform.

Social Cohesion, Structural Holes, and a Tale of Two Measures

NASA Astrophysics Data System (ADS)

Latora, V.; Nicosia, V.; Panzarasa, P.

2013-05-01

In the social sciences, the debate over the structural foundations of social capital has long vacillated between two positions on the relative benefits associated with two types of social structures: closed structures, rich in third-party relationships, and open structures, rich in structural holes and brokerage opportunities. In this paper, we engage with this debate by focusing on the measures typically used for formalising the two conceptions of social capital: clustering and effective size. We show that these two measures are simply two sides of the same coin, as they can be expressed one in terms of the other through a simple functional relation. Building on this relation, we then attempt to reconcile closed and open structures by proposing a new measure, Simmelian brokerage, that captures opportunities of brokerage between otherwise disconnected cohesive groups of contacts. Implications of our findings for research on social capital and complex networks are discussed.

The relations between network-operation and topological-property in a scale-free and small-world network with community structure

NASA Astrophysics Data System (ADS)

Ma, Fei; Yao, Bing

2017-10-01

It is always an open, demanding and difficult task for generating available model to simulate dynamical functions and reveal inner principles from complex systems and networks. In this article, due to lots of real-life and artificial networks are built from series of simple and small groups (components), we discuss some interesting and helpful network-operation to generate more realistic network models. In view of community structure (modular topology), we present a class of sparse network models N(t , m) . At the moment, we capture the fact the N(t , 4) has not only scale-free feature, which means that the probability that a randomly selected vertex with degree k decays as a power-law, following P(k) ∼k-γ, where γ is the degree exponent, but also small-world property, which indicates that the typical distance between two uniform randomly chosen vertices grows proportionally to logarithm of the order of N(t , 4) , namely, relatively shorter diameter and lower average path length, simultaneously displays higher clustering coefficient. Next, as a new topological parameter correlating to reliability, synchronization capability and diffusion properties of networks, the number of spanning trees over a network is studied in more detail, an exact analytical solution for the number of spanning trees of the N(t , 4) is obtained. Based on the network-operation, part hub-vertex linking with each other will be helpful for structuring various network models and investigating the rules related with real-life networks.

φ-evo: A program to evolve phenotypic models of biological networks.

PubMed

Henry, Adrien; Hemery, Mathieu; François, Paul

2018-06-01

Molecular networks are at the core of most cellular decisions, but are often difficult to comprehend. Reverse engineering of network architecture from their functions has proved fruitful to classify and predict the structure and function of molecular networks, suggesting new experimental tests and biological predictions. We present φ-evo, an open-source program to evolve in silico phenotypic networks performing a given biological function. We include implementations for evolution of biochemical adaptation, adaptive sorting for immune recognition, metazoan development (somitogenesis, hox patterning), as well as Pareto evolution. We detail the program architecture based on C, Python 3, and a Jupyter interface for project configuration and network analysis. We illustrate the predictive power of φ-evo by first recovering the asymmetrical structure of the lac operon regulation from an objective function with symmetrical constraints. Second, we use the problem of hox-like embryonic patterning to show how a single effective fitness can emerge from multi-objective (Pareto) evolution. φ-evo provides an efficient approach and user-friendly interface for the phenotypic prediction of networks and the numerical study of evolution itself.

Correlations between Community Structure and Link Formation in Complex Networks

PubMed Central

Liu, Zhen; He, Jia-Lin; Kapoor, Komal; Srivastava, Jaideep

2013-01-01

Background Links in complex networks commonly represent specific ties between pairs of nodes, such as protein-protein interactions in biological networks or friendships in social networks. However, understanding the mechanism of link formation in complex networks is a long standing challenge for network analysis and data mining. Methodology/Principal Findings Links in complex networks have a tendency to cluster locally and form so-called communities. This widely existed phenomenon reflects some underlying mechanism of link formation. To study the correlations between community structure and link formation, we present a general computational framework including a theory for network partitioning and link probability estimation. Our approach enables us to accurately identify missing links in partially observed networks in an efficient way. The links having high connection likelihoods in the communities reveal that links are formed preferentially to create cliques and accordingly promote the clustering level of the communities. The experimental results verify that such a mechanism can be well captured by our approach. Conclusions/Significance Our findings provide a new insight into understanding how links are created in the communities. The computational framework opens a wide range of possibilities to develop new approaches and applications, such as community detection and missing link prediction. PMID:24039818

Combinatorial explosion in model gene networks

NASA Astrophysics Data System (ADS)

Edwards, R.; Glass, L.

2000-09-01

The explosive growth in knowledge of the genome of humans and other organisms leaves open the question of how the functioning of genes in interacting networks is coordinated for orderly activity. One approach to this problem is to study mathematical properties of abstract network models that capture the logical structures of gene networks. The principal issue is to understand how particular patterns of activity can result from particular network structures, and what types of behavior are possible. We study idealized models in which the logical structure of the network is explicitly represented by Boolean functions that can be represented by directed graphs on n-cubes, but which are continuous in time and described by differential equations, rather than being updated synchronously via a discrete clock. The equations are piecewise linear, which allows significant analysis and facilitates rapid integration along trajectories. We first give a combinatorial solution to the question of how many distinct logical structures exist for n-dimensional networks, showing that the number increases very rapidly with n. We then outline analytic methods that can be used to establish the existence, stability and periods of periodic orbits corresponding to particular cycles on the n-cube. We use these methods to confirm the existence of limit cycles discovered in a sample of a million randomly generated structures of networks of 4 genes. Even with only 4 genes, at least several hundred different patterns of stable periodic behavior are possible, many of them surprisingly complex. We discuss ways of further classifying these periodic behaviors, showing that small mutations (reversal of one or a few edges on the n-cube) need not destroy the stability of a limit cycle. Although these networks are very simple as models of gene networks, their mathematical transparency reveals relationships between structure and behavior, they suggest that the possibilities for orderly dynamics in such networks are extremely rich and they offer novel ways to think about how mutations can alter dynamics.

Combinatorial explosion in model gene networks.

PubMed

Edwards, R.; Glass, L.

2000-09-01

The explosive growth in knowledge of the genome of humans and other organisms leaves open the question of how the functioning of genes in interacting networks is coordinated for orderly activity. One approach to this problem is to study mathematical properties of abstract network models that capture the logical structures of gene networks. The principal issue is to understand how particular patterns of activity can result from particular network structures, and what types of behavior are possible. We study idealized models in which the logical structure of the network is explicitly represented by Boolean functions that can be represented by directed graphs on n-cubes, but which are continuous in time and described by differential equations, rather than being updated synchronously via a discrete clock. The equations are piecewise linear, which allows significant analysis and facilitates rapid integration along trajectories. We first give a combinatorial solution to the question of how many distinct logical structures exist for n-dimensional networks, showing that the number increases very rapidly with n. We then outline analytic methods that can be used to establish the existence, stability and periods of periodic orbits corresponding to particular cycles on the n-cube. We use these methods to confirm the existence of limit cycles discovered in a sample of a million randomly generated structures of networks of 4 genes. Even with only 4 genes, at least several hundred different patterns of stable periodic behavior are possible, many of them surprisingly complex. We discuss ways of further classifying these periodic behaviors, showing that small mutations (reversal of one or a few edges on the n-cube) need not destroy the stability of a limit cycle. Although these networks are very simple as models of gene networks, their mathematical transparency reveals relationships between structure and behavior, they suggest that the possibilities for orderly dynamics in such networks are extremely rich and they offer novel ways to think about how mutations can alter dynamics. (c) 2000 American Institute of Physics.

Determining the Ages and Distances of 4 Open Clusters

NASA Astrophysics Data System (ADS)

Sawczynec, Erica A.; James D. Armstrong, Joe M. Ritter, Jeff Kuhn

2018-01-01

The study of nearby young open clusters can give insight into star formation and potentially the local rate of metal enrichment. Presented is a BVRI photometric analysis of 4 open clusters; NGC 2509, NGC 2483, NGC 2482, and NGC 6705, in order to reevaluate previously published ages and distances using modern CCD photometry, and newer stellar models. Observations were obtained from the Cerro Tololo node of the Las Cumbres Observatory 1.0 meter network. Color magnitude diagrams were compared to modeled isochrones and the updated ages and distances determined. An interesting stellar association was found in the color magnitude diagram of NGC 6705. The structure is suggestive of two epochs of stellar formation. Members of this structure were evaluated using the Gaia Archive in order to explore the possibility of a heterogeneous population. The status of NGC 2483 as an open cluster has been debated; however, it has been noted that there is a high concentration of Be stars found in the region. It is concluded that NGC 2483 is an open cluster.

Transcription initiation complex structures elucidate DNA opening.

PubMed

Plaschka, C; Hantsche, M; Dienemann, C; Burzinski, C; Plitzko, J; Cramer, P

2016-05-19

Transcription of eukaryotic protein-coding genes begins with assembly of the RNA polymerase (Pol) II initiation complex and promoter DNA opening. Here we report cryo-electron microscopy (cryo-EM) structures of yeast initiation complexes containing closed and open DNA at resolutions of 8.8 Å and 3.6 Å, respectively. DNA is positioned and retained over the Pol II cleft by a network of interactions between the TATA-box-binding protein TBP and transcription factors TFIIA, TFIIB, TFIIE, and TFIIF. DNA opening occurs around the tip of the Pol II clamp and the TFIIE 'extended winged helix' domain, and can occur in the absence of TFIIH. Loading of the DNA template strand into the active centre may be facilitated by movements of obstructing protein elements triggered by allosteric binding of the TFIIE 'E-ribbon' domain. The results suggest a unified model for transcription initiation with a key event, the trapping of open promoter DNA by extended protein-protein and protein-DNA contacts.

Value Co-creation and Co-innovation: Linking Networked Organisations and Customer Communities

NASA Astrophysics Data System (ADS)

Romero, David; Molina, Arturo

Strategic networks such as Collaborative Networked Organisations (CNOs) and Virtual Customer Communities (VCCs) show a high potential as drivers of value co-creation and collaborative innovation in today’s Networking Era. Both look at the network structures as a source of jointly value creation and open innovation through access to new skills, knowledge, markets and technologies by sharing risk and integrating complementary competencies. This collaborative endeavour has proven to be able to enhance the adaptability and flexibility of CNOs and VCCs value creating systems in order to react in response to external drivers such as collaborative (business) opportunities. This paper presents a reference framework for creating interface networks, also known as ‘experience-centric networks’, as enablers for linking networked organisations and customer communities in order to support the establishment of user-driven and collaborative innovation networks.

Centrality in earthquake multiplex networks

NASA Astrophysics Data System (ADS)

Lotfi, Nastaran; Darooneh, Amir Hossein; Rodrigues, Francisco A.

2018-06-01

Seismic time series has been mapped as a complex network, where a geographical region is divided into square cells that represent the nodes and connections are defined according to the sequence of earthquakes. In this paper, we map a seismic time series to a temporal network, described by a multiplex network, and characterize the evolution of the network structure in terms of the eigenvector centrality measure. We generalize previous works that considered the single layer representation of earthquake networks. Our results suggest that the multiplex representation captures better earthquake activity than methods based on single layer networks. We also verify that the regions with highest seismological activities in Iran and California can be identified from the network centrality analysis. The temporal modeling of seismic data provided here may open new possibilities for a better comprehension of the physics of earthquakes.

Computational neural networks in chemistry: Model free mapping devices for predicting chemical reactivity from molecular structure

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

Elrod, D.W.

1992-01-01

Computational neural networks (CNNs) are a computational paradigm inspired by the brain's massively parallel network of highly interconnected neurons. The power of computational neural networks derives not so much from their ability to model the brain as from their ability to learn by example and to map highly complex, nonlinear functions, without the need to explicitly specify the functional relationship. Two central questions about CNNs were investigated in the context of predicting chemical reactions: (1) the mapping properties of neural networks and (2) the representation of chemical information for use in CNNs. Chemical reactivity is here considered an example ofmore » a complex, nonlinear function of molecular structure. CNN's were trained using modifications of the back propagation learning rule to map a three dimensional response surface similar to those typically observed in quantitative structure-activity and structure-property relationships. The computational neural network's mapping of the response surface was found to be robust to the effects of training sample size, noisy data and intercorrelated input variables. The investigation of chemical structure representation led to the development of a molecular structure-based connection-table representation suitable for neural network training. An extension of this work led to a BE-matrix structure representation that was found to be general for several classes of reactions. The CNN prediction of chemical reactivity and regiochemistry was investigated for electrophilic aromatic substitution reactions, Markovnikov addition to alkenes, Saytzeff elimination from haloalkanes, Diels-Alder cycloaddition, and retro Diels-Alder ring opening reactions using these connectivity-matrix derived representations. The reaction predictions made by the CNNs were more accurate than those of an expert system and were comparable to predictions made by chemists.« less

CMsearch: simultaneous exploration of protein sequence space and structure space improves not only protein homology detection but also protein structure prediction.

PubMed

Cui, Xuefeng; Lu, Zhiwu; Wang, Sheng; Jing-Yan Wang, Jim; Gao, Xin

2016-06-15

Protein homology detection, a fundamental problem in computational biology, is an indispensable step toward predicting protein structures and understanding protein functions. Despite the advances in recent decades on sequence alignment, threading and alignment-free methods, protein homology detection remains a challenging open problem. Recently, network methods that try to find transitive paths in the protein structure space demonstrate the importance of incorporating network information of the structure space. Yet, current methods merge the sequence space and the structure space into a single space, and thus introduce inconsistency in combining different sources of information. We present a novel network-based protein homology detection method, CMsearch, based on cross-modal learning. Instead of exploring a single network built from the mixture of sequence and structure space information, CMsearch builds two separate networks to represent the sequence space and the structure space. It then learns sequence-structure correlation by simultaneously taking sequence information, structure information, sequence space information and structure space information into consideration. We tested CMsearch on two challenging tasks, protein homology detection and protein structure prediction, by querying all 8332 PDB40 proteins. Our results demonstrate that CMsearch is insensitive to the similarity metrics used to define the sequence and the structure spaces. By using HMM-HMM alignment as the sequence similarity metric, CMsearch clearly outperforms state-of-the-art homology detection methods and the CASP-winning template-based protein structure prediction methods. Our program is freely available for download from http://sfb.kaust.edu.sa/Pages/Software.aspx : xin.gao@kaust.edu.sa Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press.

Extracting Message Inter-Departure Time Distributions from the Human Electroencephalogram

PubMed Central

Mišić, Bratislav; Vakorin, Vasily A.; Kovačević, Nataša; Paus, Tomáš; McIntosh, Anthony R.

2011-01-01

The complex connectivity of the cerebral cortex is a topic of much study, yet the link between structure and function is still unclear. The processing capacity and throughput of information at individual brain regions remains an open question and one that could potentially bridge these two aspects of neural organization. The rate at which information is emitted from different nodes in the network and how this output process changes under different external conditions are general questions that are not unique to neuroscience, but are of interest in multiple classes of telecommunication networks. In the present study we show how some of these questions may be addressed using tools from telecommunications research. An important system statistic for modeling and performance evaluation of distributed communication systems is the time between successive departures of units of information at each node in the network. We describe a method to extract and fully characterize the distribution of such inter-departure times from the resting-state electroencephalogram (EEG). We show that inter-departure times are well fitted by the two-parameter Gamma distribution. Moreover, they are not spatially or neurophysiologically trivial and instead are regionally specific and sensitive to the presence of sensory input. In both the eyes-closed and eyes-open conditions, inter-departure time distributions were more dispersed over posterior parietal channels, close to regions which are known to have the most dense structural connectivity. The biggest differences between the two conditions were observed at occipital sites, where inter-departure times were significantly more variable in the eyes-open condition. Together, these results suggest that message departure times are indicative of network traffic and capture a novel facet of neural activity. PMID:21673866

Analysis of Cisco Open Network Environment (ONE) OpenFlow Controller Implementation

DTIC Science & Technology

2014-08-01

Software - Defined Networking ( SDN ), when fully realized, offer many improvements over the current rigid and...functionalities like handshake, connection setup, switch management, and security. 15. SUBJECT TERMS OpenFlow, software - defined networking , Cisco ONE, SDN ...innovating packet-forwarding technologies. Network device roles are strictly defined with little or no flexibility. In Software - Defined Networks ( SDNs ),

Initial stage of physical ageing in network glasses

NASA Astrophysics Data System (ADS)

Golovchak, R.; Ingram, A.; Kozdras, A.; Vlcek, M.; Roiland, C.; Bureau, B.; Shpotyuk, O.

2012-11-01

An atomistic view on Johari-Goldstein secondary β-relaxation processes responsible for structural relaxation far below the glass transition temperature (Tg ) in network glasses is developed for the archetypal chalcogenide glass, As20Se80, using positron annihilation lifetime, differential scanning calorimetry, Raman scattering and nuclear magnetic resonance techniques. Increased density fluctuations are shown to be responsible for the initial stage of physical ageing in these materials at the temperatures below Tg . They are correlated with changes in thermodynamic parameters of structural relaxation through the glass-to-supercooled liquid transition interval. General shrinkage, occurred during the next stage of physical ageing, is shown to be determined by the ability of system to release these redundant open volumes from the glass bulk through the densification process of glass network.

Structural limitations of learning in a crowd: communication vulnerability and information diffusion in MOOCs.

PubMed

Gillani, Nabeel; Yasseri, Taha; Eynon, Rebecca; Hjorth, Isis

2014-09-23

Massive Open Online Courses (MOOCs) bring together a global crowd of thousands of learners for several weeks or months. In theory, the openness and scale of MOOCs can promote iterative dialogue that facilitates group cognition and knowledge construction. Using data from two successive instances of a popular business strategy MOOC, we filter observed communication patterns to arrive at the "significant" interaction networks between learners and use complex network analysis to explore the vulnerability and information diffusion potential of the discussion forums. We find that different discussion topics and pedagogical practices promote varying levels of 1) "significant" peer-to-peer engagement, 2) participant inclusiveness in dialogue, and ultimately, 3) modularity, which impacts information diffusion to prevent a truly "global" exchange of knowledge and learning. These results indicate the structural limitations of large-scale crowd-based learning and highlight the different ways that learners in MOOCs leverage, and learn within, social contexts. We conclude by exploring how these insights may inspire new developments in online education.

Structural limitations of learning in a crowd: communication vulnerability and information diffusion in MOOCs

PubMed Central

Gillani, Nabeel; Yasseri, Taha; Eynon, Rebecca; Hjorth, Isis

2014-01-01

Massive Open Online Courses (MOOCs) bring together a global crowd of thousands of learners for several weeks or months. In theory, the openness and scale of MOOCs can promote iterative dialogue that facilitates group cognition and knowledge construction. Using data from two successive instances of a popular business strategy MOOC, we filter observed communication patterns to arrive at the “significant” interaction networks between learners and use complex network analysis to explore the vulnerability and information diffusion potential of the discussion forums. We find that different discussion topics and pedagogical practices promote varying levels of 1) “significant” peer-to-peer engagement, 2) participant inclusiveness in dialogue, and ultimately, 3) modularity, which impacts information diffusion to prevent a truly “global” exchange of knowledge and learning. These results indicate the structural limitations of large-scale crowd-based learning and highlight the different ways that learners in MOOCs leverage, and learn within, social contexts. We conclude by exploring how these insights may inspire new developments in online education. PMID:25244925

Structural limitations of learning in a crowd: communication vulnerability and information diffusion in MOOCs

NASA Astrophysics Data System (ADS)

Gillani, Nabeel; Yasseri, Taha; Eynon, Rebecca; Hjorth, Isis

2014-09-01

Massive Open Online Courses (MOOCs) bring together a global crowd of thousands of learners for several weeks or months. In theory, the openness and scale of MOOCs can promote iterative dialogue that facilitates group cognition and knowledge construction. Using data from two successive instances of a popular business strategy MOOC, we filter observed communication patterns to arrive at the ``significant'' interaction networks between learners and use complex network analysis to explore the vulnerability and information diffusion potential of the discussion forums. We find that different discussion topics and pedagogical practices promote varying levels of 1) ``significant'' peer-to-peer engagement, 2) participant inclusiveness in dialogue, and ultimately, 3) modularity, which impacts information diffusion to prevent a truly ``global'' exchange of knowledge and learning. These results indicate the structural limitations of large-scale crowd-based learning and highlight the different ways that learners in MOOCs leverage, and learn within, social contexts. We conclude by exploring how these insights may inspire new developments in online education.

Formation of crystal-like structures and branched networks from nonionic spherical micelles

NASA Astrophysics Data System (ADS)

Cardiel, Joshua J.; Furusho, Hirotoshi; Skoglund, Ulf; Shen, Amy Q.

2015-12-01

Crystal-like structures at nano and micron scales have promise for purification and confined reactions, and as starting points for fabricating highly ordered crystals for protein engineering and drug discovery applications. However, developing controlled crystallization techniques from batch processes remain challenging. We show that neutrally charged nanoscale spherical micelles from biocompatible nonionic surfactant solutions can evolve into nano- and micro-sized branched networks and crystal-like structures. This occurs under simple combinations of temperature and flow conditions. Our findings not only suggest new opportunities for developing controlled universal crystallization and encapsulation procedures that are sensitive to ionic environments and high temperatures, but also open up new pathways for accelerating drug discovery processes, which are of tremendous interest to pharmaceutical and biotechnological industries.

Toward quantum plasmonic networks

DOE PAGES

Holtfrerich, M. W.; Dowran, M.; Davidson, R.; ...

2016-08-30

Here, we demonstrate the transduction of macroscopic quantum entanglement by independent, distant plasmonic structures embedded in separate thin silver films. In particular, we show that the plasmon-mediated transmission through each film conserves spatially dependent, entangled quantum images, opening the door for the implementation of parallel quantum protocols, super-resolution imaging, and quantum plasmonic sensing geometries at the nanoscale level. The conservation of quantum information by the transduction process shows that continuous variable multi-mode entanglement is momentarily transferred from entangled beams of light to the space-like separated, completely independent plasmonic structures, thus providing a first important step toward establishing a multichannel quantummore » network across separate solid-state substrates.« less

Research on Closed Residential Area Based on Balanced Distribution Theory

NASA Astrophysics Data System (ADS)

Lan, Si; Fang, Ni; Lin, Hai Peng; Ye, Shi Qi

2018-06-01

With the promotion of the street system, residential quarters and units of the compound gradually open. In this paper, the relationship between traffic flow and traffic flow is established for external roads, and the road resistance model is established by internal roads. We propose a balanced distribution model from the two aspects of road opening conditions and traffic flow inside and outside the district, and quantitatively analyze the impact of the opening and closing on the surrounding roads. Finally, it puts forward feasible suggestions to improve the traffic situation and optimize the network structure.

Empirical analysis of online social networks in the age of Web 2.0

NASA Astrophysics Data System (ADS)

Fu, Feng; Liu, Lianghuan; Wang, Long

2008-01-01

Today the World Wide Web is undergoing a subtle but profound shift to Web 2.0, to become more of a social web. The use of collaborative technologies such as blogs and social networking site (SNS) leads to instant online community in which people communicate rapidly and conveniently with each other. Moreover, there are growing interest and concern regarding the topological structure of these new online social networks. In this paper, we present empirical analysis of statistical properties of two important Chinese online social networks-a blogging network and an SNS open to college students. They are both emerging in the age of Web 2.0. We demonstrate that both networks possess small-world and scale-free features already observed in real-world and artificial networks. In addition, we investigate the distribution of topological distance. Furthermore, we study the correlations between degree (in/out) and degree (in/out), clustering coefficient and degree, popularity (in terms of number of page views) and in-degree (for the blogging network), respectively. We find that the blogging network shows disassortative mixing pattern, whereas the SNS network is an assortative one. Our research may help us to elucidate the self-organizing structural characteristics of these online social networks embedded in technical forms.

Network neuroscience

PubMed Central

Bassett, Danielle S; Sporns, Olaf

2017-01-01

Despite substantial recent progress, our understanding of the principles and mechanisms underlying complex brain function and cognition remains incomplete. Network neuroscience proposes to tackle these enduring challenges. Approaching brain structure and function from an explicitly integrative perspective, network neuroscience pursues new ways to map, record, analyze and model the elements and interactions of neurobiological systems. Two parallel trends drive the approach: the availability of new empirical tools to create comprehensive maps and record dynamic patterns among molecules, neurons, brain areas and social systems; and the theoretical framework and computational tools of modern network science. The convergence of empirical and computational advances opens new frontiers of scientific inquiry, including network dynamics, manipulation and control of brain networks, and integration of network processes across spatiotemporal domains. We review emerging trends in network neuroscience and attempt to chart a path toward a better understanding of the brain as a multiscale networked system. PMID:28230844

Closed-Loop Control of Complex Networks: A Trade-Off between Time and Energy

NASA Astrophysics Data System (ADS)

Sun, Yong-Zheng; Leng, Si-Yang; Lai, Ying-Cheng; Grebogi, Celso; Lin, Wei

2017-11-01

Controlling complex nonlinear networks is largely an unsolved problem at the present. Existing works focus either on open-loop control strategies and their energy consumptions or on closed-loop control schemes with an infinite-time duration. We articulate a finite-time, closed-loop controller with an eye toward the physical and mathematical underpinnings of the trade-off between the control time and energy as well as their dependence on the network parameters and structure. The closed-loop controller is tested on a large number of real systems including stem cell differentiation, food webs, random ecosystems, and spiking neuronal networks. Our results represent a step forward in developing a rigorous and general framework to control nonlinear dynamical networks with a complex topology.

Design and Evaluation of a Proxy-Based Monitoring System for OpenFlow Networks.

PubMed

Taniguchi, Yoshiaki; Tsutsumi, Hiroaki; Iguchi, Nobukazu; Watanabe, Kenzi

2016-01-01

Software-Defined Networking (SDN) has attracted attention along with the popularization of cloud environment and server virtualization. In SDN, the control plane and the data plane are decoupled so that the logical topology and routing control can be configured dynamically depending on network conditions. To obtain network conditions precisely, a network monitoring mechanism is necessary. In this paper, we focus on OpenFlow which is a core technology to realize SDN. We propose, design, implement, and evaluate a network monitoring system for OpenFlow networks. Our proposed system acts as a proxy between an OpenFlow controller and OpenFlow switches. Through experimental evaluations, we confirm that our proposed system can capture packets and monitor traffic information depending on administrator's configuration. In addition, we show that our proposed system does not influence significant performance degradation to overall network performance.

Design and Evaluation of a Proxy-Based Monitoring System for OpenFlow Networks

PubMed Central

Taniguchi, Yoshiaki; Tsutsumi, Hiroaki; Iguchi, Nobukazu; Watanabe, Kenzi

2016-01-01

Software-Defined Networking (SDN) has attracted attention along with the popularization of cloud environment and server virtualization. In SDN, the control plane and the data plane are decoupled so that the logical topology and routing control can be configured dynamically depending on network conditions. To obtain network conditions precisely, a network monitoring mechanism is necessary. In this paper, we focus on OpenFlow which is a core technology to realize SDN. We propose, design, implement, and evaluate a network monitoring system for OpenFlow networks. Our proposed system acts as a proxy between an OpenFlow controller and OpenFlow switches. Through experimental evaluations, we confirm that our proposed system can capture packets and monitor traffic information depending on administrator's configuration. In addition, we show that our proposed system does not influence significant performance degradation to overall network performance. PMID:27006977

PREMER: a Tool to Infer Biological Networks.

PubMed

Villaverde, Alejandro F; Becker, Kolja; Banga, Julio R

2017-10-04

Inferring the structure of unknown cellular networks is a main challenge in computational biology. Data-driven approaches based on information theory can determine the existence of interactions among network nodes automatically. However, the elucidation of certain features - such as distinguishing between direct and indirect interactions or determining the direction of a causal link - requires estimating information-theoretic quantities in a multidimensional space. This can be a computationally demanding task, which acts as a bottleneck for the application of elaborate algorithms to large-scale network inference problems. The computational cost of such calculations can be alleviated by the use of compiled programs and parallelization. To this end we have developed PREMER (Parallel Reverse Engineering with Mutual information & Entropy Reduction), a software toolbox that can run in parallel and sequential environments. It uses information theoretic criteria to recover network topology and determine the strength and causality of interactions, and allows incorporating prior knowledge, imputing missing data, and correcting outliers. PREMER is a free, open source software tool that does not require any commercial software. Its core algorithms are programmed in FORTRAN 90 and implement OpenMP directives. It has user interfaces in Python and MATLAB/Octave, and runs on Windows, Linux and OSX (https://sites.google.com/site/premertoolbox/).

Development of AN Open-Source Automatic Deformation Monitoring System for Geodetical and Geotechnical Measurements

NASA Astrophysics Data System (ADS)

Engel, P.; Schweimler, B.

2016-04-01

The deformation monitoring of structures and buildings is an important task field of modern engineering surveying, ensuring the standing and reliability of supervised objects over a long period. Several commercial hardware and software solutions for the realization of such monitoring measurements are available on the market. In addition to them, a research team at the Neubrandenburg University of Applied Sciences (NUAS) is actively developing a software package for monitoring purposes in geodesy and geotechnics, which is distributed under an open source licence and free of charge. The task of managing an open source project is well-known in computer science, but it is fairly new in a geodetic context. This paper contributes to that issue by detailing applications, frameworks, and interfaces for the design and implementation of open hardware and software solutions for sensor control, sensor networks, and data management in automatic deformation monitoring. It will be discussed how the development effort of networked applications can be reduced by using free programming tools, cloud computing technologies, and rapid prototyping methods.

Causality: Physics and Philosophy

ERIC Educational Resources Information Center

Chatterjee, Atanu

2013-01-01

Nature is a complex causal network exhibiting diverse forms and species. These forms or rather systems are physically open, structurally complex and naturally adaptive. They interact with the surrounding media by operating a positive-feedback loop through which, they adapt, organize and self-organize themselves in response to the ever-changing…

Human factors for capacity building: lessons learned from the OpenMRS implementers network.

PubMed

Seebregts, C J; Mamlin, B W; Biondich, P G; Fraser, H S F; Wolfe, B A; Jazayeri, D; Miranda, J; Blaya, J; Sinha, C; Bailey, C T; Kanter, A S

2010-01-01

The overall objective of this project was to investigate ways to strengthen the OpenMRS community by (i) developing capacity and implementing a network focusing specifically on the needs of OpenMRS implementers, (ii) strengthening community-driven aspects of OpenMRS and providing a dedicated forum for implementation-specific issues, and; (iii) providing regional support for OpenMRS implementations as well as mentorship and training. The methods used included (i) face-to-face networking using meetings and workshops; (ii) online collaboration tools, peer support and mentorship programmes; (iii) capacity and community development programmes, and; (iv) community outreach programmes. The community-driven approach, combined with a few simple interventions, has been a key factor in the growth and success of the OpenMRS Implementers Network. It has contributed to implementations in at least twenty-three different countries using basic online tools; and provided mentorship and peer support through an annual meeting, workshops and an internship program. The OpenMRS Implementers Network has formed collaborations with several other open source networks and is evolving regional OpenMRS Centres of Excellence to provide localized support for OpenMRS development and implementation. These initiatives are increasing the range of functionality and sustainability of open source software in the health domain, resulting in improved adoption and enterprise-readiness. Social organization and capacity development activities are important in growing a successful community-driven open source software model.

An open-source wireless sensor stack: from Arduino to SDI-12 to Water One Flow

NASA Astrophysics Data System (ADS)

Hicks, S.; Damiano, S. G.; Smith, K. M.; Olexy, J.; Horsburgh, J. S.; Mayorga, E.; Aufdenkampe, A. K.

2013-12-01

Implementing a large-scale streaming environmental sensor network has previously been limited by the high cost of the datalogging and data communication infrastructure. The Christina River Basin Critical Zone Observatory (CRB-CZO) is overcoming the obstacles to large near-real-time data collection networks by using Arduino, an open source electronics platform, in combination with XBee ZigBee wireless radio modules. These extremely low-cost and easy-to-use open source electronics are at the heart of the new DIY movement and have provided solutions to countless projects by over half a million users worldwide. However, their use in environmental sensing is in its infancy. At present a primary limitation to widespread deployment of open-source electronics for environmental sensing is the lack of a simple, open-source software stack to manage streaming data from heterogeneous sensor networks. Here we present a functioning prototype software stack that receives sensor data over a self-meshing ZigBee wireless network from over a hundred sensors, stores the data locally and serves it on demand as a CUAHSI Water One Flow (WOF) web service. We highlight a few new, innovative components, including: (1) a versatile open data logger design based the Arduino electronics platform and ZigBee radios; (2) a software library implementing SDI-12 communication protocol between any Arduino platform and SDI12-enabled sensors without the need for additional hardware (https://github.com/StroudCenter/Arduino-SDI-12); and (3) 'midStream', a light-weight set of Python code that receives streaming sensor data, appends it with metadata on the fly by querying a relational database structured on an early version of the Observations Data Model version 2.0 (ODM2), and uses the WOFpy library to serve the data as WaterML via SOAP and REST web services.

Development and Implementation of the X.25 Protocol for the Universal Network Interface Device (UNID) II. Volume 1.

DTIC Science & Technology

1985-12-01

development of an improved Universal Network Interface Device (UNID II). The UNID II’s architecture was based on a preliminary design project at...interface device, performing all functions required ,: the multi-ring LAN. The device depicted by RADC’s studies would connect a highly variable group of host...used the ISO Open Systems Ilterconnection (OSI) seven layer model as the basic structure for data flow and program development . In 1982 Cuomo

A Comprehensive Study of the Tocks Island Lake Project and Alternatives. Part C. Analysis of Alternatives to Supply Resource Needs

DTIC Science & Technology

1975-06-01

TILP cannot be plugged into a network to meet service area needs irrespective of its location. The recreation issue is further complicated by the...Pennsylvania law, future structures in the floodway induced by this feeling of assurance from Tocks will be forbidden. The potential for devop - ment along the... networks in their presently suburbanized locations. There are, however, broad reaches of open spaces in both locations presently suitable for recreation

Toward elucidating the heat activation mechanism of the TRPV1 channel gating by molecular dynamics simulation

PubMed Central

Wen, Han; Qin, Feng; Zheng, Wenjun

2016-01-01

As a key cellular sensor, the TRPV1 cation channel undergoes a gating transition from a closed state to an open state in response to various physical and chemical stimuli including noxious heat. Despite years of study, the heat activation mechanism of TRPV1 gating remains enigmatic at the molecular level. Toward elucidating the structural and energetic basis of TRPV1 gating, we have performed molecular dynamics (MD) simulations (with cumulative simulation time of 3 μs), starting from the high-resolution closed and open structures of TRPV1 solved by cryo-electron microscopy. In the closed-state simulations at 30°C, we observed a stably closed channel constricted at the lower gate (near residue I679), while the upper gate (near residues G643 and M644) is dynamic and undergoes flickery opening/closing. In the open-state simulations at 60°C, we found higher conformational variation consistent with a large entropy increase required for the heat activation, and both the lower and upper gates are dynamic with transient opening/closing. Through ensemble-based structural analyses of the closed state vs. the open state, we revealed pronounced closed-to-open conformational changes involving the membrane proximal domain (MPD) linker, the outer pore, and the TRP helix, which are accompanied by breaking/forming of a network of closed/open-state specific hydrogen bonds. By comparing the closed-state simulations at 30°C and 60°C, we observed heat-activated conformational changes in the MPD linker, the outer pore, and the TRP helix that resemble the closed-to-open conformational changes, along with partial formation of the open-state specific hydrogen bonds. Some of the residues involved in the above key hydrogen bonds were validated by previous mutational studies. Taken together, our MD simulations have offered rich structural and dynamic details beyond the static structures of TRPV1, and promising targets for future mutagenesis and functional studies of the TRPV1 channel. PMID:27699868

Internal Communication Study. 1974-75 Evaluation Report.

ERIC Educational Resources Information Center

Austin Independent School District, TX. Office of Research and Evaluation.

This report attempts to identify some communication problem areas in the Austin Independent School District, based on an open-ended interview questionnaire and a network analysis. Guidelines based on a review of the literature are included for communicators at all levels of the organizational structure. Backup summaries of that review are also…

Knowledge Cartography for Open Sensemaking Communities

ERIC Educational Resources Information Center

Shum, Simon Buckingham; Okada, Alexandra

2008-01-01

Knowledge Cartography is the discipline of visually mapping the conceptual structure of ideas, such as the connections between issues, concepts, answers, arguments and evidence. The cognitive process of externalising one's understanding clarifies one's own grasp of the situation, as well as communicating it to others as a network that invites…

Automatic Tool for Local Assembly Structures

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

Whole community shotgun sequencing of total DNA (i.e. metagenomics) and total RNA (i.e. metatranscriptomics) has provided a wealth of information in the microbial community structure, predicted functions, metabolic networks, and is even able to reconstruct complete genomes directly. Here we present ATLAS (Automatic Tool for Local Assembly Structures) a comprehensive pipeline for assembly, annotation, genomic binning of metagenomic and metatranscriptomic data with an integrated framework for Multi-Omics. This will provide an open source tool for the Multi-Omic community at large.

HipMCL: a high-performance parallel implementation of the Markov clustering algorithm for large-scale networks

PubMed Central

Azad, Ariful; Ouzounis, Christos A; Kyrpides, Nikos C; Buluç, Aydin

2018-01-01

Abstract Biological networks capture structural or functional properties of relevant entities such as molecules, proteins or genes. Characteristic examples are gene expression networks or protein–protein interaction networks, which hold information about functional affinities or structural similarities. Such networks have been expanding in size due to increasing scale and abundance of biological data. While various clustering algorithms have been proposed to find highly connected regions, Markov Clustering (MCL) has been one of the most successful approaches to cluster sequence similarity or expression networks. Despite its popularity, MCL’s scalability to cluster large datasets still remains a bottleneck due to high running times and memory demands. Here, we present High-performance MCL (HipMCL), a parallel implementation of the original MCL algorithm that can run on distributed-memory computers. We show that HipMCL can efficiently utilize 2000 compute nodes and cluster a network of ∼70 million nodes with ∼68 billion edges in ∼2.4 h. By exploiting distributed-memory environments, HipMCL clusters large-scale networks several orders of magnitude faster than MCL and enables clustering of even bigger networks. HipMCL is based on MPI and OpenMP and is freely available under a modified BSD license. PMID:29315405

Reconfigurable optical implementation of quantum complex networks

NASA Astrophysics Data System (ADS)

Nokkala, J.; Arzani, F.; Galve, F.; Zambrini, R.; Maniscalco, S.; Piilo, J.; Treps, N.; Parigi, V.

2018-05-01

Network theory has played a dominant role in understanding the structure of complex systems and their dynamics. Recently, quantum complex networks, i.e. collections of quantum systems arranged in a non-regular topology, have been theoretically explored leading to significant progress in a multitude of diverse contexts including, e.g., quantum transport, open quantum systems, quantum communication, extreme violation of local realism, and quantum gravity theories. Despite important progress in several quantum platforms, the implementation of complex networks with arbitrary topology in quantum experiments is still a demanding task, especially if we require both a significant size of the network and the capability of generating arbitrary topology—from regular to any kind of non-trivial structure—in a single setup. Here we propose an all optical and reconfigurable implementation of quantum complex networks. The experimental proposal is based on optical frequency combs, parametric processes, pulse shaping and multimode measurements allowing the arbitrary control of the number of the nodes (optical modes) and topology of the links (interactions between the modes) within the network. Moreover, we also show how to simulate quantum dynamics within the network combined with the ability to address its individual nodes. To demonstrate the versatility of these features, we discuss the implementation of two recently proposed probing techniques for quantum complex networks and structured environments.

HipMCL: a high-performance parallel implementation of the Markov clustering algorithm for large-scale networks

DOE PAGES

Azad, Ariful; Pavlopoulos, Georgios A.; Ouzounis, Christos A.; ...

2018-01-05

Biological networks capture structural or functional properties of relevant entities such as molecules, proteins or genes. Characteristic examples are gene expression networks or protein–protein interaction networks, which hold information about functional affinities or structural similarities. Such networks have been expanding in size due to increasing scale and abundance of biological data. While various clustering algorithms have been proposed to find highly connected regions, Markov Clustering (MCL) has been one of the most successful approaches to cluster sequence similarity or expression networks. Despite its popularity, MCL’s scalability to cluster large datasets still remains a bottleneck due to high running times andmore » memory demands. In this paper, we present High-performance MCL (HipMCL), a parallel implementation of the original MCL algorithm that can run on distributed-memory computers. We show that HipMCL can efficiently utilize 2000 compute nodes and cluster a network of ~70 million nodes with ~68 billion edges in ~2.4 h. By exploiting distributed-memory environments, HipMCL clusters large-scale networks several orders of magnitude faster than MCL and enables clustering of even bigger networks. Finally, HipMCL is based on MPI and OpenMP and is freely available under a modified BSD license.« less

HipMCL: a high-performance parallel implementation of the Markov clustering algorithm for large-scale networks

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

Azad, Ariful; Pavlopoulos, Georgios A.; Ouzounis, Christos A.

Biological networks capture structural or functional properties of relevant entities such as molecules, proteins or genes. Characteristic examples are gene expression networks or protein–protein interaction networks, which hold information about functional affinities or structural similarities. Such networks have been expanding in size due to increasing scale and abundance of biological data. While various clustering algorithms have been proposed to find highly connected regions, Markov Clustering (MCL) has been one of the most successful approaches to cluster sequence similarity or expression networks. Despite its popularity, MCL’s scalability to cluster large datasets still remains a bottleneck due to high running times andmore » memory demands. In this paper, we present High-performance MCL (HipMCL), a parallel implementation of the original MCL algorithm that can run on distributed-memory computers. We show that HipMCL can efficiently utilize 2000 compute nodes and cluster a network of ~70 million nodes with ~68 billion edges in ~2.4 h. By exploiting distributed-memory environments, HipMCL clusters large-scale networks several orders of magnitude faster than MCL and enables clustering of even bigger networks. Finally, HipMCL is based on MPI and OpenMP and is freely available under a modified BSD license.« less

OpenMS: a flexible open-source software platform for mass spectrometry data analysis.

PubMed

Röst, Hannes L; Sachsenberg, Timo; Aiche, Stephan; Bielow, Chris; Weisser, Hendrik; Aicheler, Fabian; Andreotti, Sandro; Ehrlich, Hans-Christian; Gutenbrunner, Petra; Kenar, Erhan; Liang, Xiao; Nahnsen, Sven; Nilse, Lars; Pfeuffer, Julianus; Rosenberger, George; Rurik, Marc; Schmitt, Uwe; Veit, Johannes; Walzer, Mathias; Wojnar, David; Wolski, Witold E; Schilling, Oliver; Choudhary, Jyoti S; Malmström, Lars; Aebersold, Ruedi; Reinert, Knut; Kohlbacher, Oliver

2016-08-30

High-resolution mass spectrometry (MS) has become an important tool in the life sciences, contributing to the diagnosis and understanding of human diseases, elucidating biomolecular structural information and characterizing cellular signaling networks. However, the rapid growth in the volume and complexity of MS data makes transparent, accurate and reproducible analysis difficult. We present OpenMS 2.0 (http://www.openms.de), a robust, open-source, cross-platform software specifically designed for the flexible and reproducible analysis of high-throughput MS data. The extensible OpenMS software implements common mass spectrometric data processing tasks through a well-defined application programming interface in C++ and Python and through standardized open data formats. OpenMS additionally provides a set of 185 tools and ready-made workflows for common mass spectrometric data processing tasks, which enable users to perform complex quantitative mass spectrometric analyses with ease.

Network of anatomical texts (NAnaTex), an open-source project for visualizing the interaction between anatomical terms.

PubMed

Momota, Ryusuke; Ohtsuka, Aiji

2018-01-01

Anatomy is the science and art of understanding the structure of the body and its components in relation to the functions of the whole-body system. Medicine is based on a deep understanding of anatomy, but quite a few introductory-level learners are overwhelmed by the sheer amount of anatomical terminology that must be understood, so they regard anatomy as a dull and dense subject. To help them learn anatomical terms in a more contextual way, we started a new open-source project, the Network of Anatomical Texts (NAnaTex), which visualizes relationships of body components by integrating text-based anatomical information using Cytoscape, a network visualization software platform. Here, we present a network of bones and muscles produced from literature descriptions. As this network is primarily text-based and does not require any programming knowledge, it is easy to implement new functions or provide extra information by making changes to the original text files. To facilitate collaborations, we deposited the source code files for the network into the GitHub repository ( https://github.com/ryusukemomota/nanatex ) so that anybody can participate in the evolution of the network and use it for their own non-profit purposes. This project should help not only introductory-level learners but also professional medical practitioners, who could use it as a quick reference.

Functional RNA structures throughout the Hepatitis C Virus genome.

PubMed

Adams, Rebecca L; Pirakitikulr, Nathan; Pyle, Anna Marie

2017-06-01

The single-stranded Hepatitis C Virus (HCV) genome adopts a set of elaborate RNA structures that are involved in every stage of the viral lifecycle. Recent advances in chemical probing, sequencing, and structural biology have facilitated analysis of RNA folding on a genome-wide scale, revealing novel structures and networks of interactions. These studies have underscored the active role played by RNA in every function of HCV and they open the door to new types of RNA-targeted therapeutics. Copyright © 2017 Elsevier B.V. All rights reserved.

Self-assembly of thin, triangular prisms into open networks at a flat air-water interface

NASA Astrophysics Data System (ADS)

Solomon, Michael; Ferrar, Joseph; Bedi, Deshpreet; Zhou, Shangnan; Mao, Xiaoming

We observe capillary-driven binding between thin, equilateral triangle microprisms at a flat air-water interface. The triangles are fabricated from epoxy resin via SU-8 photolithography. For small thickness to length (T/L) ratios, two distinct pairwise particle-particle binding events occur with roughly equal frequency, and optical and environmental scanning electron microscopy (eSEM) demonstrate that these two distinct binding events are driven by the specific manner in which the interface is pinned to the particle surface. Additionally, particle bending is observed for the lowest T/L ratios, which leads to enhanced interface curvature and thus enhanced strength of capillary-driven attractions, and may also play a pivotal role in the dichotomy in particle-particle binding. Dichotomy in particle-particle binding is not observed at thicker T/L ratios, although capillary-driven binding still occurs. Ultimately, the particles self-assemble into space-spanning open networks, and the results suggest design parameters for the fabrication of building blocks of ordered open structures, such as the Kagome lattice.

Design and Implementation of a Modern Automatic Deformation Monitoring System

NASA Astrophysics Data System (ADS)

Engel, Philipp; Schweimler, Björn

2016-03-01

The deformation monitoring of structures and buildings is an important task field of modern engineering surveying, ensuring the standing and reliability of supervised objects over a long period. Several commercial hardware and software solutions for the realization of such monitoring measurements are available on the market. In addition to them, a research team at the University of Applied Sciences in Neubrandenburg (NUAS) is actively developing a software package for monitoring purposes in geodesy and geotechnics, which is distributed under an open source licence and free of charge. The task of managing an open source project is well-known in computer science, but it is fairly new in a geodetic context. This paper contributes to that issue by detailing applications, frameworks, and interfaces for the design and implementation of open hardware and software solutions for sensor control, sensor networks, and data management in automatic deformation monitoring. It will be discussed how the development effort of networked applications can be reduced by using free programming tools, cloud computing technologies, and rapid prototyping methods.

Using OpenSSH to secure mobile LAN network traffic

NASA Astrophysics Data System (ADS)

Luu, Brian B.; Gopaul, Richard D.

2002-08-01

Mobile Internet Protocol (IP) Local Area Network (LAN) is a technique, developed by the U.S. Army Research Laboratory, which allows a LAN to be IP mobile when attaching to a foreign IP-based network and using this network as a means to retain connectivity to its home network. In this paper, we describe a technique that uses Open Secure Shell (OpenSSH) software to ensure secure, encrypted transmission of a mobile LAN's network traffic. Whenever a mobile LAN, implemented with Mobile IP LAN, moves to a foreign network, its gateway (router) obtains an IP address from the new network. IP tunnels, using IP encapsulation, are then established from the gateway through the foreign network to a home agent on its home network. These tunnels provide a virtual two-way connection to the home network for the mobile LAN as if the LAN were connected directly to its home network. Hence, when IP mobile, a mobile LAN's tunneled network traffic must traverse one or more foreign networks that may not be trusted. This traffic could be subject to eavesdropping, interception, modification, or redirection by malicious nodes in these foreign networks. To protect network traffic passing through the tunnels, OpenSSH is used as a means of encryption because it prevents surveillance, modification, and redirection of mobile LAN traffic passing across foreign networks. Since the software is found in the public domain, is available for most current operating systems, and is commonly used to provide secure network communications, OpenSSH is the software of choice.

OpenSHMEM-UCX : Evaluation of UCX for implementing OpenSHMEM Programming Model

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

Baker, Matthew B; Gorentla Venkata, Manjunath; Aderholdt, William Ferrol

2016-01-01

The OpenSHMEM reference implementation was developed towards the goal of developing an open source and high-performing Open- SHMEM implementation. To achieve portability and performance across various networks, the OpenSHMEM reference implementation uses GAS- Net and UCCS for network operations. Recently, new network layers have emerged with the promise of providing high-performance, scalabil- ity, and portability for HPC applications. In this paper, we implement the OpenSHMEM reference implementation to use the UCX framework for network operations. Then, we evaluate its performance and scalabil- ity on Cray XK systems to understand UCX s suitability for developing the OpenSHMEM programming model. Further, wemore » develop a bench- mark called SHOMS for evaluating the OpenSHMEM implementation. Our experimental results show that OpenSHMEM-UCX outperforms the vendor supplied OpenSHMEM implementation in most cases on the Cray XK system by up to 40% with respect to message rate and up to 70% for the execution of application kernels.« less

Open-Source Selective Laser Sintering (OpenSLS) of Nylon and Biocompatible Polycaprolactone

PubMed Central

Paulsen, Samantha J.; Hwang, Daniel H.; Ta, Anderson H.; Yalacki, David R.; Schmidt, Tim; Miller, Jordan S.

2016-01-01

Selective Laser Sintering (SLS) is an additive manufacturing process that uses a laser to fuse powdered starting materials into solid 3D structures. Despite the potential for fabrication of complex, high-resolution structures with SLS using diverse starting materials (including biomaterials), prohibitive costs of commercial SLS systems have hindered the wide adoption of this technology in the scientific community. Here, we developed a low-cost, open-source SLS system (OpenSLS) and demonstrated its capacity to fabricate structures in nylon with sub-millimeter features and overhanging regions. Subsequently, we demonstrated fabrication of polycaprolactone (PCL) into macroporous structures such as a diamond lattice. Widespread interest in using PCL for bone tissue engineering suggests that PCL lattices are relevant model scaffold geometries for engineering bone. SLS of materials with large powder grain size (~500 μm) leads to part surfaces with high roughness, so we further introduced a simple vapor-smoothing technique to reduce the surface roughness of sintered PCL structures which further improves their elastic modulus and yield stress. Vapor-smoothed PCL can also be used for sacrificial templating of perfusable fluidic networks within orthogonal materials such as poly(dimethylsiloxane) silicone. Finally, we demonstrated that human mesenchymal stem cells were able to adhere, survive, and differentiate down an osteogenic lineage on sintered and smoothed PCL surfaces, suggesting that OpenSLS has the potential to produce PCL scaffolds useful for cell studies. OpenSLS provides the scientific community with an accessible platform for the study of laser sintering and the fabrication of complex geometries in diverse materials. PMID:26841023

Open-Source Selective Laser Sintering (OpenSLS) of Nylon and Biocompatible Polycaprolactone.

PubMed

Kinstlinger, Ian S; Bastian, Andreas; Paulsen, Samantha J; Hwang, Daniel H; Ta, Anderson H; Yalacki, David R; Schmidt, Tim; Miller, Jordan S

2016-01-01

Selective Laser Sintering (SLS) is an additive manufacturing process that uses a laser to fuse powdered starting materials into solid 3D structures. Despite the potential for fabrication of complex, high-resolution structures with SLS using diverse starting materials (including biomaterials), prohibitive costs of commercial SLS systems have hindered the wide adoption of this technology in the scientific community. Here, we developed a low-cost, open-source SLS system (OpenSLS) and demonstrated its capacity to fabricate structures in nylon with sub-millimeter features and overhanging regions. Subsequently, we demonstrated fabrication of polycaprolactone (PCL) into macroporous structures such as a diamond lattice. Widespread interest in using PCL for bone tissue engineering suggests that PCL lattices are relevant model scaffold geometries for engineering bone. SLS of materials with large powder grain size (~500 μm) leads to part surfaces with high roughness, so we further introduced a simple vapor-smoothing technique to reduce the surface roughness of sintered PCL structures which further improves their elastic modulus and yield stress. Vapor-smoothed PCL can also be used for sacrificial templating of perfusable fluidic networks within orthogonal materials such as poly(dimethylsiloxane) silicone. Finally, we demonstrated that human mesenchymal stem cells were able to adhere, survive, and differentiate down an osteogenic lineage on sintered and smoothed PCL surfaces, suggesting that OpenSLS has the potential to produce PCL scaffolds useful for cell studies. OpenSLS provides the scientific community with an accessible platform for the study of laser sintering and the fabrication of complex geometries in diverse materials.

First field demonstration of cloud datacenter workflow automation employing dynamic optical transport network resources under OpenStack and OpenFlow orchestration.

PubMed

Szyrkowiec, Thomas; Autenrieth, Achim; Gunning, Paul; Wright, Paul; Lord, Andrew; Elbers, Jörg-Peter; Lumb, Alan

2014-02-10

For the first time, we demonstrate the orchestration of elastic datacenter and inter-datacenter transport network resources using a combination of OpenStack and OpenFlow. Programmatic control allows a datacenter operator to dynamically request optical lightpaths from a transport network operator to accommodate rapid changes of inter-datacenter workflows.

Wireless Sensor Network Radio Power Management and Simulation Models

DTIC Science & Technology

2010-01-01

The Open Electrical & Electronic Engineering Journal, 2010, 4, 21-31 21 1874-1290/10 2010 Bentham Open Open Access Wireless Sensor Network Radio...Air Force Institute of Technology, Wright-Patterson AFB, OH, USA Abstract: Wireless sensor networks (WSNs) create a new frontier in collecting and...consumption. Keywords: Wireless sensor network , power management, energy-efficiency, medium access control (MAC), simulation pa- rameters. 1

Tensor network methods for the simulation of open quantum dynamics in multichromophore systems: Application to singlet fission in novel pentacene dimers

NASA Astrophysics Data System (ADS)

Chin, Alex

Singlet fission (SF) is an ultrafast process in which a singlet exciton spontaneously converts into a pair of entangled triplet excitons on neighbouring organic molecules. As a mechanism of multiple exciton generation, it has been suggested as a way to increase the efficiency of organic photovoltaic devices, and its underlying photophysics across a wide range of molecules and materials has attracted significant theoretical attention. Recently, a number of studies using ultrafast nonlinear optics have underscored the importance of intramolecular vibrational dynamics in efficient SF systems, prompting a need for methods capable of simulating open quantum dynamics in the presence of highly structured and strongly coupled environments. Here, a combination of ab initio electronic structure techniques and a new tensor-network methodology for simulating open vibronic dynamics is presented and applied to a recently synthesised dimer of pentacene (DP-Mes). We show that ultrafast (300 fs) SF in this system is driven entirely by symmetry breaking vibrations, and our many-body approach enables the real-time identification and tracking of the ''functional' vibrational dynamics and the role of the ''bath''-like parts of the environment. Deeper analysis of the emerging wave functions points to interesting links between the time at which parts of the environment become relevant to the SF process and the optimal topology of the tensor networks, highlighting the additional insight provided by moving the problem into the natural language of correlated quantum states and how this could lead to simulations of much larger multichromophore systems Supported by The Winton Programme for the Physics of Sustainability.

Conformational transitions of uracil transporter UraA from Escherichia coli: a molecular simulation study.

PubMed

Yang, Liu; Yang, Lianjuan; Yu, Hui; Liu, Lu; Zhao, Xi; Huang, Xuri

2017-10-26

The Escherichia coli uracil/H + symporter UraA, known as the representative nucleobase/cation symporter 2(NCS2) protein, gets involved in several crucial physiological processes for most living organisms on Earth, such as the uptake of nucleobases and transport of vitamin C. Some experiments proposed a working model to explain proton-coupling and uracil transporting process of UraA on the basis of the crystal structure of NCS2 protein, but the details of conformational changes remained unknown. Thus, in order to make clear conformational changes caused by the protonation and deprotonation process of some conserved proton-coupled residues, the molecular dynamics simulation was used to study the conformation of UraA complexes in different protonation states. The results demonstrated that the protonation of residue Glu241 and Glu290 resulted in the whole conformational transition from the inward-open to the outward-open state. It can be concluded that Glu290 was crucial in a network of hydrogen-bonds in the middle of the core domain involving another essential residue, mainly including tyr288 in TM8, Tyr342, Ser338 in TM12, and the network of hydrogen-bonds was the key to maintain the stability of conformation. Protonation of Glu290 affects the stability of network of H-bond and changed the domains TM3 TM10 TM12. Thus, Glu290 may play a vital role as a 'proton trigger' that affects spatial structural of amino and residues near substrate binding side leading to an outward-open conformation transition.

From partnerships to networks: new approaches for measuring U.S. National Heritage Area effectiveness.

PubMed

Laven, Daniel N; Krymkowski, Daniel H; Ventriss, Curtis L; Manning, Robert E; Mitchell, Nora J

2010-08-01

National Heritage Areas (NHAs) are an alternative and increasingly popular form of protected area management in the United States. NHAs seek to integrate environmental objectives with community and economic objectives at regional or landscape scales. NHA designations have increased rapidly in the last 20 years, generating a substantial need for evaluative information about (a) how NHAs work; (b) outcomes associated with the NHA process; and (c) the costs and benefits of investing public moneys into the NHA approach. Qualitative evaluation studies recently conducted at three NHAs have identified the importance of understanding network structure and function in the context of evaluating NHA management effectiveness. This article extends these case studies by examining quantitative network data from each of the sites. The authors analyze these data using both a descriptive approach and a statistically more robust approach known as exponential random graph modeling. Study findings indicate the presence of transitive structures and the absence of three-cycle structures in each of these networks. This suggests that these networks are relatively ''open,'' which may be desirable, given the uncertainty of the environments in which they operate. These findings also suggest, at least at the sites reported here, that the NHA approach may be an effective way to activate and develop networks of intersectoral organizational partners. Finally, this study demonstrates the utility of using quantitative network analysis to better understand the effectiveness of protected area management models that rely on partnership networks to achieve their intended outcomes.

Generating community-built tools for data sharing and analysis in environmental networks

USGS Publications Warehouse

Read, Jordan S.; Gries, Corinna; Read, Emily K.; Klug, Jennifer; Hanson, Paul C.; Hipsey, Matthew R.; Jennings, Eleanor; O'Reilley, Catherine; Winslow, Luke A.; Pierson, Don; McBride, Christopher G.; Hamilton, David

2016-01-01

Rapid data growth in many environmental sectors has necessitated tools to manage and analyze these data. The development of tools often lags behind the proliferation of data, however, which may slow exploratory opportunities and scientific progress. The Global Lake Ecological Observatory Network (GLEON) collaborative model supports an efficient and comprehensive data–analysis–insight life cycle, including implementations of data quality control checks, statistical calculations/derivations, models, and data visualizations. These tools are community-built and openly shared. We discuss the network structure that enables tool development and a culture of sharing, leading to optimized output from limited resources. Specifically, data sharing and a flat collaborative structure encourage the development of tools that enable scientific insights from these data. Here we provide a cross-section of scientific advances derived from global-scale analyses in GLEON. We document enhancements to science capabilities made possible by the development of analytical tools and highlight opportunities to expand this framework to benefit other environmental networks.

Hybrid multiphoton volumetric functional imaging of large-scale bioengineered neuronal networks

NASA Astrophysics Data System (ADS)

Dana, Hod; Marom, Anat; Paluch, Shir; Dvorkin, Roman; Brosh, Inbar; Shoham, Shy

2014-06-01

Planar neural networks and interfaces serve as versatile in vitro models of central nervous system physiology, but adaptations of related methods to three dimensions (3D) have met with limited success. Here, we demonstrate for the first time volumetric functional imaging in a bioengineered neural tissue growing in a transparent hydrogel with cortical cellular and synaptic densities, by introducing complementary new developments in nonlinear microscopy and neural tissue engineering. Our system uses a novel hybrid multiphoton microscope design combining a 3D scanning-line temporal-focusing subsystem and a conventional laser-scanning multiphoton microscope to provide functional and structural volumetric imaging capabilities: dense microscopic 3D sampling at tens of volumes per second of structures with mm-scale dimensions containing a network of over 1,000 developing cells with complex spontaneous activity patterns. These developments open new opportunities for large-scale neuronal interfacing and for applications of 3D engineered networks ranging from basic neuroscience to the screening of neuroactive substances.

A portable structural analysis library for reaction networks.

PubMed

Bedaso, Yosef; Bergmann, Frank T; Choi, Kiri; Medley, Kyle; Sauro, Herbert M

2018-07-01

The topology of a reaction network can have a significant influence on the network's dynamical properties. Such influences can include constraints on network flows and concentration changes or more insidiously result in the emergence of feedback loops. These effects are due entirely to mass constraints imposed by the network configuration and are important considerations before any dynamical analysis is made. Most established simulation software tools usually carry out some kind of structural analysis of a network before any attempt is made at dynamic simulation. In this paper, we describe a portable software library, libStructural, that can carry out a variety of popular structural analyses that includes conservation analysis, flux dependency analysis and enumerating elementary modes. The library employs robust algorithms that allow it to be used on large networks with more than a two thousand nodes. The library accepts either a raw or fully labeled stoichiometry matrix or models written in SBML format. The software is written in standard C/C++ and comes with extensive on-line documentation and a test suite. The software is available for Windows, Mac OS X, and can be compiled easily on any Linux operating system. A language binding for Python is also available through the pip package manager making it simple to install on any standard Python distribution. The bulk of the source code is licensed under the open source BSD license with other parts using as either the MIT license or more simply public domain. All source is available on GitHub (https://github.com/sys-bio/Libstructural). Copyright © 2018 Elsevier B.V. All rights reserved.

Appplication of statistical mechanical methods to the modeling of social networks

NASA Astrophysics Data System (ADS)

Strathman, Anthony Robert

With the recent availability of large-scale social data sets, social networks have become open to quantitative analysis via the methods of statistical physics. We examine the statistical properties of a real large-scale social network, generated from cellular phone call-trace logs. We find this network, like many other social networks to be assortative (r = 0.31) and clustered (i.e., strongly transitive, C = 0.21). We measure fluctuation scaling to identify the presence of internal structure in the network and find that structural inhomogeneity effectively disappears at the scale of a few hundred nodes, though there is no sharp cutoff. We introduce an agent-based model of social behavior, designed to model the formation and dissolution of social ties. The model is a modified Metropolis algorithm containing agents operating under the basic sociological constraints of reciprocity, communication need and transitivity. The model introduces the concept of a social temperature. We go on to show that this simple model reproduces the global statistical network features (incl. assortativity, connected fraction, mean degree, clustering, and mean shortest path length) of the real network data and undergoes two phase transitions, one being from a "gas" to a "liquid" state and the second from a liquid to a glassy state as function of this social temperature.

The Role of the Australian Open Learning Information Network.

ERIC Educational Resources Information Center

Bishop, Robin; And Others

Three documents are presented which describe the Australian Open Learning Information Network (AOLIN)--a national, independent, and self-supporting network of educational researchers with a common interest in the use of information technology for open and distance education--and discuss two evaluative studies undertaken by the organization. The…

Unified functional network and nonlinear time series analysis for complex systems science: The pyunicorn package

NASA Astrophysics Data System (ADS)

Donges, Jonathan; Heitzig, Jobst; Beronov, Boyan; Wiedermann, Marc; Runge, Jakob; Feng, Qing Yi; Tupikina, Liubov; Stolbova, Veronika; Donner, Reik; Marwan, Norbert; Dijkstra, Henk; Kurths, Jürgen

2016-04-01

We introduce the pyunicorn (Pythonic unified complex network and recurrence analysis toolbox) open source software package for applying and combining modern methods of data analysis and modeling from complex network theory and nonlinear time series analysis. pyunicorn is a fully object-oriented and easily parallelizable package written in the language Python. It allows for the construction of functional networks such as climate networks in climatology or functional brain networks in neuroscience representing the structure of statistical interrelationships in large data sets of time series and, subsequently, investigating this structure using advanced methods of complex network theory such as measures and models for spatial networks, networks of interacting networks, node-weighted statistics, or network surrogates. Additionally, pyunicorn provides insights into the nonlinear dynamics of complex systems as recorded in uni- and multivariate time series from a non-traditional perspective by means of recurrence quantification analysis, recurrence networks, visibility graphs, and construction of surrogate time series. The range of possible applications of the library is outlined, drawing on several examples mainly from the field of climatology. pyunicorn is available online at https://github.com/pik-copan/pyunicorn. Reference: J.F. Donges, J. Heitzig, B. Beronov, M. Wiedermann, J. Runge, Q.-Y. Feng, L. Tupikina, V. Stolbova, R.V. Donner, N. Marwan, H.A. Dijkstra, and J. Kurths, Unified functional network and nonlinear time series analysis for complex systems science: The pyunicorn package, Chaos 25, 113101 (2015), DOI: 10.1063/1.4934554, Preprint: arxiv.org:1507.01571 [physics.data-an].

The epidemic spreading model and the direction of information flow in brain networks.

PubMed

Meier, J; Zhou, X; Hillebrand, A; Tewarie, P; Stam, C J; Van Mieghem, P

2017-05-15

The interplay between structural connections and emerging information flow in the human brain remains an open research problem. A recent study observed global patterns of directional information flow in empirical data using the measure of transfer entropy. For higher frequency bands, the overall direction of information flow was from posterior to anterior regions whereas an anterior-to-posterior pattern was observed in lower frequency bands. In this study, we applied a simple Susceptible-Infected-Susceptible (SIS) epidemic spreading model on the human connectome with the aim to reveal the topological properties of the structural network that give rise to these global patterns. We found that direct structural connections induced higher transfer entropy between two brain regions and that transfer entropy decreased with increasing distance between nodes (in terms of hops in the structural network). Applying the SIS model, we were able to confirm the empirically observed opposite information flow patterns and posterior hubs in the structural network seem to play a dominant role in the network dynamics. For small time scales, when these hubs acted as strong receivers of information, the global pattern of information flow was in the posterior-to-anterior direction and in the opposite direction when they were strong senders. Our analysis suggests that these global patterns of directional information flow are the result of an unequal spatial distribution of the structural degree between posterior and anterior regions and their directions seem to be linked to different time scales of the spreading process. Copyright © 2017 Elsevier Inc. All rights reserved.

Stability of ecological industry chain: an entropy model approach.

PubMed

Wang, Qingsong; Qiu, Shishou; Yuan, Xueliang; Zuo, Jian; Cao, Dayong; Hong, Jinglan; Zhang, Jian; Dong, Yong; Zheng, Ying

2016-07-01

A novel methodology is proposed in this study to examine the stability of ecological industry chain network based on entropy theory. This methodology is developed according to the associated dissipative structure characteristics, i.e., complexity, openness, and nonlinear. As defined in the methodology, network organization is the object while the main focus is the identification of core enterprises and core industry chains. It is proposed that the chain network should be established around the core enterprise while supplementation to the core industry chain helps to improve system stability, which is verified quantitatively. Relational entropy model can be used to identify core enterprise and core eco-industry chain. It could determine the core of the network organization and core eco-industry chain through the link form and direction of node enterprises. Similarly, the conductive mechanism of different node enterprises can be examined quantitatively despite the absence of key data. Structural entropy model can be employed to solve the problem of order degree for network organization. Results showed that the stability of the entire system could be enhanced by the supplemented chain around the core enterprise in eco-industry chain network organization. As a result, the sustainability of the entire system could be further improved.

Reconfigurable origami-inspired acoustic waveguides

PubMed Central

Babaee, Sahab; Overvelde, Johannes T. B.; Chen, Elizabeth R.; Tournat, Vincent; Bertoldi, Katia

2016-01-01

We combine numerical simulations and experiments to design a new class of reconfigurable waveguides based on three-dimensional origami-inspired metamaterials. Our strategy builds on the fact that the rigid plates and hinges forming these structures define networks of tubes that can be easily reconfigured. As such, they provide an ideal platform to actively control and redirect the propagation of sound. We design reconfigurable systems that, depending on the externally applied deformation, can act as networks of waveguides oriented along one, two, or three preferential directions. Moreover, we demonstrate that the capability of the structure to guide and radiate acoustic energy along predefined directions can be easily switched on and off, as the networks of tubes are reversibly formed and disrupted. The proposed designs expand the ability of existing acoustic metamaterials and exploit complex waveguiding to enhance control over propagation and radiation of acoustic energy, opening avenues for the design of a new class of tunable acoustic functional systems. PMID:28138527

High-resolution of particle contacts via fluorophore exclusion in deep-imaging of jammed colloidal packings

NASA Astrophysics Data System (ADS)

Kyeyune-Nyombi, Eru; Morone, Flaviano; Liu, Wenwei; Li, Shuiqing; Gilchrist, M. Lane; Makse, Hernán A.

2018-01-01

Understanding the structural properties of random packings of jammed colloids requires an unprecedented high-resolution determination of the contact network providing mechanical stability to the packing. Here, we address the determination of the contact network by a novel strategy based on fluorophore signal exclusion of quantum dot nanoparticles from the contact points. We use fluorescence labeling schemes on particles inspired by biology and biointerface science in conjunction with fluorophore exclusion at the contact region. The method provides high-resolution contact network data that allows us to measure structural properties of the colloidal packing near marginal stability. We determine scaling laws of force distributions, soft modes, correlation functions, coordination number and free volume that define the universality class of jammed colloidal packings and can be compared with theoretical predictions. The contact detection method opens up further experimental testing at the interface of jamming and glass physics.

Using graphene networks to build bioinspired self-monitoring ceramics

PubMed Central

Picot, Olivier T.; Rocha, Victoria G.; Ferraro, Claudio; Ni, Na; D'Elia, Eleonora; Meille, Sylvain; Chevalier, Jerome; Saunders, Theo; Peijs, Ton; Reece, Mike J.; Saiz, Eduardo

2017-01-01

The properties of graphene open new opportunities for the fabrication of composites exhibiting unique structural and functional capabilities. However, to achieve this goal we should build materials with carefully designed architectures. Here, we describe the fabrication of ceramic-graphene composites by combining graphene foams with pre-ceramic polymers and spark plasma sintering. The result is a material containing an interconnected, microscopic network of very thin (20–30 nm), electrically conductive, carbon interfaces. This network generates electrical conductivities up to two orders of magnitude higher than those of other ceramics with similar graphene or carbon nanotube contents and can be used to monitor ‘in situ' structural integrity. In addition, it directs crack propagation, promoting stable crack growth and increasing the fracture resistance by an order of magnitude. These results demonstrate that the rational integration of nanomaterials could be a fruitful path towards building composites combining unique mechanical and functional performances. PMID:28181518

Research on e-commerce transaction networks using multi-agent modelling and open application programming interface

NASA Astrophysics Data System (ADS)

Piao, Chunhui; Han, Xufang; Wu, Harris

2010-08-01

We provide a formal definition of an e-commerce transaction network. Agent-based modelling is used to simulate e-commerce transaction networks. For real-world analysis, we studied the open application programming interfaces (APIs) from eBay and Taobao e-commerce websites and captured real transaction data. Pajek is used to visualise the agent relationships in the transaction network. We derived one-mode networks from the transaction network and analysed them using degree and betweenness centrality. Integrating multi-agent modelling, open APIs and social network analysis, we propose a new way to study large-scale e-commerce systems.

Plant pollinator networks along a gradient of urbanisation.

PubMed

Geslin, Benoît; Gauzens, Benoit; Thébault, Elisa; Dajoz, Isabelle

2013-01-01

Habitat loss is one of the principal causes of the current pollinator decline. With agricultural intensification, increasing urbanisation is among the main drivers of habitat loss. Consequently studies focusing on pollinator community structure along urbanisation gradients have increased in recent years. However, few studies have investigated how urbanisation affects plant-pollinator interaction networks. Here we assessed modifications of plant-pollinator interactions along an urbanisation gradient based on the study of their morphological relationships. Along an urbanisation gradient comprising four types of landscape contexts (semi-natural, agricultural, suburban, urban), we set up experimental plant communities containing two plant functional groups differing in their morphological traits ("open flowers" and "tubular flowers"). Insect visitations on these communities were recorded to build plant-pollinator networks. A total of 17 857 interactions were recorded between experimental plant communities and flower-visitors. The number of interactions performed by flower-visitors was significantly lower in urban landscape context than in semi-natural and agricultural ones. In particular, insects such as Syrphidae and solitary bees that mostly visited the open flower functional group were significantly impacted by urbanisation, which was not the case for bumblebees. Urbanisation also impacted the generalism of flower-visitors and we detected higher interaction evenness in urban landscape context than in agricultural and suburban ones. Finally, in urban context, these modifications lowered the potential reproductive success of the open flowers functional group. Our findings show that open flower plant species and their specific flower-visitors are especially sensitive to increasing urbanisation. These results provide new clues to improve conservation measures within urbanised areas in favour of specialist flower-visitors. To complete this functional approach, studies using networks resolved to the species level along urbanised gradients would be required.

Plant Pollinator Networks along a Gradient of Urbanisation

PubMed Central

Geslin, Benoît; Gauzens, Benoit; Thébault, Elisa; Dajoz, Isabelle

2013-01-01

Background Habitat loss is one of the principal causes of the current pollinator decline. With agricultural intensification, increasing urbanisation is among the main drivers of habitat loss. Consequently studies focusing on pollinator community structure along urbanisation gradients have increased in recent years. However, few studies have investigated how urbanisation affects plant-pollinator interaction networks. Here we assessed modifications of plant-pollinator interactions along an urbanisation gradient based on the study of their morphological relationships. Methodology/Principal Findings Along an urbanisation gradient comprising four types of landscape contexts (semi-natural, agricultural, suburban, urban), we set up experimental plant communities containing two plant functional groups differing in their morphological traits (“open flowers” and “tubular flowers”). Insect visitations on these communities were recorded to build plant-pollinator networks. A total of 17 857 interactions were recorded between experimental plant communities and flower-visitors. The number of interactions performed by flower-visitors was significantly lower in urban landscape context than in semi-natural and agricultural ones. In particular, insects such as Syrphidae and solitary bees that mostly visited the open flower functional group were significantly impacted by urbanisation, which was not the case for bumblebees. Urbanisation also impacted the generalism of flower-visitors and we detected higher interaction evenness in urban landscape context than in agricultural and suburban ones. Finally, in urban context, these modifications lowered the potential reproductive success of the open flowers functional group. Conclusions/Significance Our findings show that open flower plant species and their specific flower-visitors are especially sensitive to increasing urbanisation. These results provide new clues to improve conservation measures within urbanised areas in favour of specialist flower-visitors. To complete this functional approach, studies using networks resolved to the species level along urbanised gradients would be required. PMID:23717421

D Topological Indoor Building Modeling Integrated with Open Street Map

NASA Astrophysics Data System (ADS)

Jamali, A.; Rahman, A. Abdul; Boguslawski, P.

2016-09-01

Considering various fields of applications for building surveying and various demands, geometry representation of a building is the most crucial aspect of a building survey. The interiors of the buildings need to be described along with the relative locations of the rooms, corridors, doors and exits in many kinds of emergency response, such as fire, bombs, smoke, and pollution. Topological representation is a challenging task within the Geography Information Science (GIS) environment, as the data structures required to express these relationships are particularly difficult to develop. Even within the Computer Aided Design (CAD) community, the structures for expressing the relationships between adjacent building parts are complex and often incomplete. In this paper, an integration of 3D topological indoor building modeling in Dual Half Edge (DHE) data structure and outdoor navigation network from Open Street Map (OSM) is presented.

Community Landscapes: An Integrative Approach to Determine Overlapping Network Module Hierarchy, Identify Key Nodes and Predict Network Dynamics

PubMed Central

Kovács, István A.; Palotai, Robin; Szalay, Máté S.; Csermely, Peter

2010-01-01

Background Network communities help the functional organization and evolution of complex networks. However, the development of a method, which is both fast and accurate, provides modular overlaps and partitions of a heterogeneous network, has proven to be rather difficult. Methodology/Principal Findings Here we introduce the novel concept of ModuLand, an integrative method family determining overlapping network modules as hills of an influence function-based, centrality-type community landscape, and including several widely used modularization methods as special cases. As various adaptations of the method family, we developed several algorithms, which provide an efficient analysis of weighted and directed networks, and (1) determine pervasively overlapping modules with high resolution; (2) uncover a detailed hierarchical network structure allowing an efficient, zoom-in analysis of large networks; (3) allow the determination of key network nodes and (4) help to predict network dynamics. Conclusions/Significance The concept opens a wide range of possibilities to develop new approaches and applications including network routing, classification, comparison and prediction. PMID:20824084

Machine Learning and Network Analysis of Molecular Dynamics Trajectories Reveal Two Chains of Red/Ox-specific Residue Interactions in Human Protein Disulfide Isomerase.

PubMed

Karamzadeh, Razieh; Karimi-Jafari, Mohammad Hossein; Sharifi-Zarchi, Ali; Chitsaz, Hamidreza; Salekdeh, Ghasem Hosseini; Moosavi-Movahedi, Ali Akbar

2017-06-16

The human protein disulfide isomerase (hPDI), is an essential four-domain multifunctional enzyme. As a result of disulfide shuffling in its terminal domains, hPDI exists in two oxidation states with different conformational preferences which are important for substrate binding and functional activities. Here, we address the redox-dependent conformational dynamics of hPDI through molecular dynamics (MD) simulations. Collective domain motions are identified by the principal component analysis of MD trajectories and redox-dependent opening-closing structure variations are highlighted on projected free energy landscapes. Then, important structural features that exhibit considerable differences in dynamics of redox states are extracted by statistical machine learning methods. Mapping the structural variations to time series of residue interaction networks also provides a holistic representation of the dynamical redox differences. With emphasizing on persistent long-lasting interactions, an approach is proposed that compiled these time series networks to a single dynamic residue interaction network (DRIN). Differential comparison of DRIN in oxidized and reduced states reveals chains of residue interactions that represent potential allosteric paths between catalytic and ligand binding sites of hPDI.

The TensorMol-0.1 model chemistry: a neural network augmented with long-range physics.

PubMed

Yao, Kun; Herr, John E; Toth, David W; Mckintyre, Ryker; Parkhill, John

2018-02-28

Traditional force fields cannot model chemical reactivity, and suffer from low generality without re-fitting. Neural network potentials promise to address these problems, offering energies and forces with near ab initio accuracy at low cost. However a data-driven approach is naturally inefficient for long-range interatomic forces that have simple physical formulas. In this manuscript we construct a hybrid model chemistry consisting of a nearsighted neural network potential with screened long-range electrostatic and van der Waals physics. This trained potential, simply dubbed "TensorMol-0.1", is offered in an open-source Python package capable of many of the simulation types commonly used to study chemistry: geometry optimizations, harmonic spectra, open or periodic molecular dynamics, Monte Carlo, and nudged elastic band calculations. We describe the robustness and speed of the package, demonstrating its millihartree accuracy and scalability to tens-of-thousands of atoms on ordinary laptops. We demonstrate the performance of the model by reproducing vibrational spectra, and simulating the molecular dynamics of a protein. Our comparisons with electronic structure theory and experimental data demonstrate that neural network molecular dynamics is poised to become an important tool for molecular simulation, lowering the resource barrier to simulating chemistry.

Research on virtual network load balancing based on OpenFlow

NASA Astrophysics Data System (ADS)

Peng, Rong; Ding, Lei

2017-08-01

The Network based on OpenFlow technology separate the control module and data forwarding module. Global deployment of load balancing strategy through network view of control plane is fast and of high efficiency. This paper proposes a Weighted Round-Robin Scheduling algorithm for virtual network and a load balancing plan for server load based on OpenFlow. Load of service nodes and load balancing tasks distribution algorithm will be taken into account.

Open Software Tools Applied to Jordan's National Multi-Agent Water Management Model

NASA Astrophysics Data System (ADS)

Knox, Stephen; Meier, Philipp; Harou, Julien; Yoon, Jim; Selby, Philip; Lachaut, Thibaut; Klassert, Christian; Avisse, Nicolas; Khadem, Majed; Tilmant, Amaury; Gorelick, Steven

2016-04-01

Jordan is the fourth most water scarce country in the world, where demand exceeds supply in a politically and demographically unstable context. The Jordan Water Project (JWP) aims to perform policy evaluation by modelling the hydrology, economics, and governance of Jordan's water resource system. The multidisciplinary nature of the project requires a modelling software system capable of integrating submodels from multiple disciplines into a single decision making process and communicating results to stakeholders. This requires a tool for building an integrated model and a system where diverse data sets can be managed and visualised. The integrated Jordan model is built using Pynsim, an open-source multi-agent simulation framework implemented in Python. Pynsim operates on network structures of nodes and links and supports institutional hierarchies, where an institution represents a grouping of nodes, links or other institutions. At each time step, code within each node, link and institution can executed independently, allowing for their fully autonomous behaviour. Additionally, engines (sub-models) perform actions over the entire network or on a subset of the network, such as taking a decision on a set of nodes. Pynsim is modular in design, allowing distinct modules to be modified easily without affecting others. Data management and visualisation is performed using Hydra (www.hydraplatform.org), an open software platform allowing users to manage network structure and data. The Hydra data manager connects to Pynsim, providing necessary input parameters for the integrated model. By providing a high-level portal to the model, Hydra removes a barrier between the users of the model (researchers, stakeholders, planners etc) and the model itself, allowing them to manage data, run the model and visualise results all through a single user interface. Pynsim's ability to represent institutional hierarchies, inter-network communication and the separation of node, link and institutional logic from higher level processes (engine) suit JWP's requirements. The use of Hydra Platform and Pynsim helps make complex customised models such as the JWP model easier to run and manage with international groups of researchers.

Generalizing entanglement

NASA Astrophysics Data System (ADS)

Jia, Ding

2017-12-01

The expected indefinite causal structure in quantum gravity poses a challenge to the notion of entanglement: If two parties are in an indefinite causal relation of being causally connected and not, can they still be entangled? If so, how does one measure the amount of entanglement? We propose to generalize the notions of entanglement and entanglement measure to address these questions. Importantly, the generalization opens the path to study quantum entanglement of states, channels, networks, and processes with definite or indefinite causal structure in a unified fashion, e.g., we show that the entanglement distillation capacity of a state, the quantum communication capacity of a channel, and the entanglement generation capacity of a network or a process are different manifestations of one and the same entanglement measure.

Crystal structure of a transcribing RNA Polymerase II complex reveals a complete transcription bubble

PubMed Central

Barnes, Christopher O.; Calero, Monica; Malik, Indranil; Graham, Brian W.; Spahr, Henrik; Lin, Guowu; Cohen, Aina; Brown, Ian S.; Zhang, Qiangmin; Pullara, Filippo; Trakselis, Michael A.; Kaplan, Craig D.; Calero, Guillermo

2015-01-01

Summary Notwithstanding numerous published structures of RNA Polymerase II (Pol II), structural details of Pol II engaging a complete nucleic acid scaffold have been lacking. Here, we report the structures of TFIIF stabilized transcribing Pol II complexes, revealing the upstream duplex and full transcription bubble. The upstream duplex lies over a wedge-shaped loop from Rpb2 that engages its minor groove, providing part of the structural framework for DNA tracking during elongation. At the upstream transcription bubble fork, rudder and fork loop-1 residues spatially coordinate strand annealing and the nascent RNA transcript. At the downstream fork, a network of Pol II interactions with the non-template strand forms a rigid domain with the Trigger Loop (TL), allowing visualization of its open state. Overall, our observations suggest that “open/closed” conformational transitions of the TL may be linked to interactions with the non-template strand, possibly in a synchronized ratcheting manner conducive to polymerase translocation. PMID:26186291

CollaborationViz: Interactive Visual Exploration of Biomedical Research Collaboration Networks

PubMed Central

Bian, Jiang; Xie, Mengjun; Hudson, Teresa J.; Eswaran, Hari; Brochhausen, Mathias; Hanna, Josh; Hogan, William R.

2014-01-01

Social network analysis (SNA) helps us understand patterns of interaction between social entities. A number of SNA studies have shed light on the characteristics of research collaboration networks (RCNs). Especially, in the Clinical Translational Science Award (CTSA) community, SNA provides us a set of effective tools to quantitatively assess research collaborations and the impact of CTSA. However, descriptive network statistics are difficult for non-experts to understand. In this article, we present our experiences of building meaningful network visualizations to facilitate a series of visual analysis tasks. The basis of our design is multidimensional, visual aggregation of network dynamics. The resulting visualizations can help uncover hidden structures in the networks, elicit new observations of the network dynamics, compare different investigators and investigator groups, determine critical factors to the network evolution, and help direct further analyses. We applied our visualization techniques to explore the biomedical RCNs at the University of Arkansas for Medical Sciences – a CTSA institution. And, we created CollaborationViz, an open-source visual analytical tool to help network researchers and administration apprehend the network dynamics of research collaborations through interactive visualization. PMID:25405477

OpenFlow arbitrated programmable network channels for managing quantum metadata

DOE PAGES

Dasari, Venkat R.; Humble, Travis S.

2016-10-10

Quantum networks must classically exchange complex metadata between devices in order to carry out information for protocols such as teleportation, super-dense coding, and quantum key distribution. Demonstrating the integration of these new communication methods with existing network protocols, channels, and data forwarding mechanisms remains an open challenge. Software-defined networking (SDN) offers robust and flexible strategies for managing diverse network devices and uses. We adapt the principles of SDN to the deployment of quantum networks, which are composed from unique devices that operate according to the laws of quantum mechanics. We show how quantum metadata can be managed within a software-definedmore » network using the OpenFlow protocol, and we describe how OpenFlow management of classical optical channels is compatible with emerging quantum communication protocols. We next give an example specification of the metadata needed to manage and control quantum physical layer (QPHY) behavior and we extend the OpenFlow interface to accommodate this quantum metadata. Here, we conclude by discussing near-term experimental efforts that can realize SDN’s principles for quantum communication.« less

OpenFlow arbitrated programmable network channels for managing quantum metadata

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

Dasari, Venkat R.; Humble, Travis S.

Quantum networks must classically exchange complex metadata between devices in order to carry out information for protocols such as teleportation, super-dense coding, and quantum key distribution. Demonstrating the integration of these new communication methods with existing network protocols, channels, and data forwarding mechanisms remains an open challenge. Software-defined networking (SDN) offers robust and flexible strategies for managing diverse network devices and uses. We adapt the principles of SDN to the deployment of quantum networks, which are composed from unique devices that operate according to the laws of quantum mechanics. We show how quantum metadata can be managed within a software-definedmore » network using the OpenFlow protocol, and we describe how OpenFlow management of classical optical channels is compatible with emerging quantum communication protocols. We next give an example specification of the metadata needed to manage and control quantum physical layer (QPHY) behavior and we extend the OpenFlow interface to accommodate this quantum metadata. Here, we conclude by discussing near-term experimental efforts that can realize SDN’s principles for quantum communication.« less

A compositional framework for reaction networks

NASA Astrophysics Data System (ADS)

Baez, John C.; Pollard, Blake S.

Reaction networks, or equivalently Petri nets, are a general framework for describing processes in which entities of various kinds interact and turn into other entities. In chemistry, where the reactions are assigned ‘rate constants’, any reaction network gives rise to a nonlinear dynamical system called its ‘rate equation’. Here we generalize these ideas to ‘open’ reaction networks, which allow entities to flow in and out at certain designated inputs and outputs. We treat open reaction networks as morphisms in a category. Composing two such morphisms connects the outputs of the first to the inputs of the second. We construct a functor sending any open reaction network to its corresponding ‘open dynamical system’. This provides a compositional framework for studying the dynamics of reaction networks. We then turn to statics: that is, steady state solutions of open dynamical systems. We construct a ‘black-boxing’ functor that sends any open dynamical system to the relation that it imposes between input and output variables in steady states. This extends our earlier work on black-boxing for Markov processes.

Hydrologic Geospatial Fabric as Community Cyberinfrastructure: International standardization best practices and the U.S. Open Water Data Initiative implementation.

NASA Astrophysics Data System (ADS)

Blodgett, D. L.

2016-12-01

Recent prolonged droughts, catastrophic flooding, and the need to protect and restore aquatic ecosystems, has increased the emphasis on information sharing in the water resources science and engineering domains. Internationally the joint World Meteorological Organization (WMO) and Open Geospatial Consortium (OGC) Hydrology Domain Working Group (HDWG) has been working toward a comprehensive system of standards and best practices for the Hydrology Domain. In the U.S. the multi-agency led and open to all U.S. Advisory Committee on Water Information (ACWI) was tasked to implement an Open Water Data Initiative (OWDI), "that will integrate currently fragmented water information into a connected, national water data framework"[1]. The status of both will be presented with focus on a community hydrologic geospatial fabric. Hydrology observations data standardization was the emphasis of the first 5 years of the HDWG. This work included WaterML 2.0 parts 1 - timeseries and part 2 - ratings and gagings. In 2016, the first of two new hydrographic feature models, GroundwaterML2, was completed and the second, for surface water features, was in active development. The WMO Commission for Hydrology is considering adoption of all these standards and their adoption is central to the U.S. OWDI. OWDI participants have produced a special collection in the Journal of American Water Resources Association and several initiative working groups have concluded their activities. One early deliverable from the OWDI was a new easier to use structure for the NHDPlus dataset. Building on this, a project to create a national Network Linked Data Index (NLDI) is being undertaken as an open-source community endeavor. The NLDI centralizes river network data, network navigation tools, crawlers that index data to the network, and utilities to register or remove data from the network. Research that informed the design of the NLDI will be presented along with recent development and findings of the project. This specific activity will be put in the context of the methods for and status of international standards and best practices development intended to help realize such national and international goals. [1] http://acwi.gov/spatial/open_water_data_charge_to_fgdc_june23_2014.pdf

BioJazz: in silico evolution of cellular networks with unbounded complexity using rule-based modeling.

PubMed

Feng, Song; Ollivier, Julien F; Swain, Peter S; Soyer, Orkun S

2015-10-30

Systems biologists aim to decipher the structure and dynamics of signaling and regulatory networks underpinning cellular responses; synthetic biologists can use this insight to alter existing networks or engineer de novo ones. Both tasks will benefit from an understanding of which structural and dynamic features of networks can emerge from evolutionary processes, through which intermediary steps these arise, and whether they embody general design principles. As natural evolution at the level of network dynamics is difficult to study, in silico evolution of network models can provide important insights. However, current tools used for in silico evolution of network dynamics are limited to ad hoc computer simulations and models. Here we introduce BioJazz, an extendable, user-friendly tool for simulating the evolution of dynamic biochemical networks. Unlike previous tools for in silico evolution, BioJazz allows for the evolution of cellular networks with unbounded complexity by combining rule-based modeling with an encoding of networks that is akin to a genome. We show that BioJazz can be used to implement biologically realistic selective pressures and allows exploration of the space of network architectures and dynamics that implement prescribed physiological functions. BioJazz is provided as an open-source tool to facilitate its further development and use. Source code and user manuals are available at: http://oss-lab.github.io/biojazz and http://osslab.lifesci.warwick.ac.uk/BioJazz.aspx. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

A Topological Criterion for Filtering Information in Complex Brain Networks

PubMed Central

Latora, Vito; Chavez, Mario

2017-01-01

In many biological systems, the network of interactions between the elements can only be inferred from experimental measurements. In neuroscience, non-invasive imaging tools are extensively used to derive either structural or functional brain networks in-vivo. As a result of the inference process, we obtain a matrix of values corresponding to a fully connected and weighted network. To turn this into a useful sparse network, thresholding is typically adopted to cancel a percentage of the weakest connections. The structural properties of the resulting network depend on how much of the inferred connectivity is eventually retained. However, how to objectively fix this threshold is still an open issue. We introduce a criterion, the efficiency cost optimization (ECO), to select a threshold based on the optimization of the trade-off between the efficiency of a network and its wiring cost. We prove analytically and we confirm through numerical simulations that the connection density maximizing this trade-off emphasizes the intrinsic properties of a given network, while preserving its sparsity. Moreover, this density threshold can be determined a-priori, since the number of connections to filter only depends on the network size according to a power-law. We validate this result on several brain networks, from micro- to macro-scales, obtained with different imaging modalities. Finally, we test the potential of ECO in discriminating brain states with respect to alternative filtering methods. ECO advances our ability to analyze and compare biological networks, inferred from experimental data, in a fast and principled way. PMID:28076353

Information Assurance Tasks Supporting the Processing of Electronic Records Archives

DTIC Science & Technology

2007-03-01

3 Table 2. OpenVPN evaluation results...........................................................................................10 iv 1...operation of necessary security features and compare the network performance under OpenVPN (openvpn.net) operation with the network performance under no...VPN operation (non-VPN) in a gigabit network environment. The reason for selecting OpenVPN product was based on the previous findings of Khanvilkar

78 FR 72667 - First Responder Network Authority Board Meeting

Federal Register 2010, 2011, 2012, 2013, 2014

2013-12-03

... Network Authority Board Meeting AGENCY: National Telecommunications and Information Administration, U.S. Department of Commerce. ACTION: Notice of Open Public Meeting of the First Responder Network Authority. SUMMARY: The Board of the First Responder Network Authority (FirstNet) will convene an open public meeting...

Toward elucidating the heat activation mechanism of the TRPV1 channel gating by molecular dynamics simulation.

PubMed

Wen, Han; Qin, Feng; Zheng, Wenjun

2016-12-01

As a key cellular sensor, the TRPV1 cation channel undergoes a gating transition from a closed state to an open state in response to various physical and chemical stimuli including noxious heat. Despite years of study, the heat activation mechanism of TRPV1 gating remains enigmatic at the molecular level. Toward elucidating the structural and energetic basis of TRPV1 gating, we have performed molecular dynamics (MD) simulations (with cumulative simulation time of 3 μs), starting from the high-resolution closed and open structures of TRPV1 solved by cryo-electron microscopy. In the closed-state simulations at 30°C, we observed a stably closed channel constricted at the lower gate (near residue I679), while the upper gate (near residues G643 and M644) is dynamic and undergoes flickery opening/closing. In the open-state simulations at 60°C, we found higher conformational variation consistent with a large entropy increase required for the heat activation, and both the lower and upper gates are dynamic with transient opening/closing. Through ensemble-based structural analyses of the closed state versus the open state, we revealed pronounced closed-to-open conformational changes involving the membrane proximal domain (MPD) linker, the outer pore, and the TRP helix, which are accompanied by breaking/forming of a network of closed/open-state specific hydrogen bonds. By comparing the closed-state simulations at 30°C and 60°C, we observed heat-activated conformational changes in the MPD linker, the outer pore, and the TRP helix that resemble the closed-to-open conformational changes, along with partial formation of the open-state specific hydrogen bonds. Some of the residues involved in the above key hydrogen bonds were validated by previous mutational studies. Taken together, our MD simulations have offered rich structural and dynamic details beyond the static structures of TRPV1, and promising targets for future mutagenesis and functional studies of the TRPV1 channel. Proteins 2016; 84:1938-1949. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Neuropsychological Definition of Learning: Strategies for Rewiring Neural Networks

ERIC Educational Resources Information Center

Barwegen, Laura

2008-01-01

For many years, most scientists believed that the physical structure of our brains, and by definition the people we had become, was set after the initial developmental period of early childhood and adolescence. New research in the area of neurology and neuropsychology is revealing that our brain is a much more open system than ever thought…

TOPSAN: a dynamic web database for structural genomics.

PubMed

Ellrott, Kyle; Zmasek, Christian M; Weekes, Dana; Sri Krishna, S; Bakolitsa, Constantina; Godzik, Adam; Wooley, John

2011-01-01

The Open Protein Structure Annotation Network (TOPSAN) is a web-based collaboration platform for exploring and annotating structures determined by structural genomics efforts. Characterization of those structures presents a challenge since the majority of the proteins themselves have not yet been characterized. Responding to this challenge, the TOPSAN platform facilitates collaborative annotation and investigation via a user-friendly web-based interface pre-populated with automatically generated information. Semantic web technologies expand and enrich TOPSAN's content through links to larger sets of related databases, and thus, enable data integration from disparate sources and data mining via conventional query languages. TOPSAN can be found at http://www.topsan.org.

A Case for Open Network Health Systems: Systems as Networks in Public Mental Health.

PubMed

Rhodes, Michael Grant; de Vries, Marten W

2017-01-08

Increases in incidents involving so-called confused persons have brought attention to the potential costs of recent changes to public mental health (PMH) services in the Netherlands. Decentralized under the (Community) Participation Act (2014), local governments must find resources to compensate for reduced central funding to such services or "innovate." But innovation, even when pressure for change is intense, is difficult. This perspective paper describes experience during and after an investigation into a particularly violent incident and murder. The aim was to provide recommendations to improve the functioning of local PMH services. The investigation concluded that no specific failure by an individual professional or service provider facility led to the murder. Instead, also as a result of the Participation Act that severed communication lines between individuals and organizations, information sharing failures were likely to have reduced system level capacity to identify risks. The methods and analytical frameworks employed to reach this conclusion, also lead to discussion as to the plausibility of an unconventional solution. If improving communication is the primary problem, non-hierarchical information, and organizational networks arise as possible and innovative system solutions. The proposal for debate is that traditional "health system" definitions, literature and narratives, and operating assumptions in public (mental) health are 'locked in' constraining technical and organization innovations. If we view a "health system" as an adaptive system of economic and social "networks," it becomes clear that the current orthodox solution, the so-called integrated health system, typically results in a "centralized hierarchical" or "tree" network. An overlooked alternative that breaks out of the established policy narratives is the view of a 'health systems' as a non-hierarchical organizational structure or 'Open Network.' In turn, this opens new technological and organizational possibilities in seeking policy solutions, and suggests an alternative governance model of huge potential value in public health both locally and globally. © 2017 The Author(s); Published by Kerman University of Medical Sciences. This is an open-access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Design and performance evaluation of an OpenFlow-based control plane for software-defined elastic optical networks with direct-detection optical OFDM (DDO-OFDM) transmission.

PubMed

Liu, Lei; Peng, Wei-Ren; Casellas, Ramon; Tsuritani, Takehiro; Morita, Itsuro; Martínez, Ricardo; Muñoz, Raül; Yoo, S J B

2014-01-13

Optical Orthogonal Frequency Division Multiplexing (O-OFDM), which transmits high speed optical signals using multiple spectrally overlapped lower-speed subcarriers, is a promising candidate for supporting future elastic optical networks. In contrast to previous works which focus on Coherent Optical OFDM (CO-OFDM), in this paper, we consider the direct-detection optical OFDM (DDO-OFDM) as the transport technique, which leads to simpler hardware and software realizations, potentially offering a low-cost solution for elastic optical networks, especially in metro networks, and short or medium distance core networks. Based on this network scenario, we design and deploy a software-defined networking (SDN) control plane enabled by extending OpenFlow, detailing the network architecture, the routing and spectrum assignment algorithm, OpenFlow protocol extensions and the experimental validation. To the best of our knowledge, it is the first time that an OpenFlow-based control plane is reported and its performance is quantitatively measured in an elastic optical network with DDO-OFDM transmission.

A collection of public transport network data sets for 25 cities

PubMed Central

Kujala, Rainer; Weckström, Christoffer; Darst, Richard K.; Mladenović, Miloš N; Saramäki, Jari

2018-01-01

Various public transport (PT) agencies publish their route and timetable information with the General Transit Feed Specification (GTFS) as the standard open format. Timetable data are commonly used for PT passenger routing. They can also be used for studying the structure and organization of PT networks, as well as the accessibility and the level of service these networks provide. However, using raw GTFS data is challenging as researchers need to understand the details of the GTFS data format, make sure that the data contain all relevant modes of public transport, and have no errors. To lower the barrier for using GTFS data in research, we publish a curated collection of 25 cities' public transport networks in multiple easy-to-use formats including network edge lists, temporal network event lists, SQLite databases, GeoJSON files, and the GTFS data format. This collection promotes the study of how PT is organized across the globe, and also provides a testbed for developing tools for PT network analysis and PT routing algorithms. PMID:29762553

Characterizing Crowd Participation and Productivity of Foldit Through Web Scraping

DTIC Science & Technology

2016-03-01

Berkeley Open Infrastructure for Network Computing CDF Cumulative Distribution Function CPU Central Processing Unit CSSG Crowdsourced Serious Game...computers at once can create a similar capacity. According to Anderson [6], principal investigator for the Berkeley Open Infrastructure for Network...extraterrestrial life. From this project, a software-based distributed computing platform called the Berkeley Open Infrastructure for Network Computing

A new, accurate, global hydrography data for remote sensing and modelling of river hydrodynamics

NASA Astrophysics Data System (ADS)

Yamazaki, D.

2017-12-01

A high-resolution hydrography data is an important baseline data for remote sensing and modelling of river hydrodynamics, given the spatial scale of river network is much smaller than that of land hydrology or atmosphere/ocean circulations. For about 10 years, HydroSHEDS, developed based on the SRTM3 DEM, has been the only available global-scale hydrography data. However, the data availability at the time of HydroSHEDS development limited the quality of the represented river networks. Here, we developed a new global hydrography data using latest geodata such as the multi-error-removed elevation data (MERIT DEM), Landsat-based global water body data (GSWO & G3WBM), cloud-sourced open geography database (OpenStreetMap). The new hydrography data covers the entire globe (including boreal regions above 60N), and it represents more detailed structure of the world river network and contains consistent supplementary data layers such as hydrologically adjusted elevations and river channel width. In the AGU meeting, the developing methodology, assessed quality, and potential applications of the new global hydrography data will be introduced.

Optical and physical properties of samarium doped lithium diborate glasses

NASA Astrophysics Data System (ADS)

Hanumantharaju, N.; Sardarpasha, K. R.; Gowda, V. C. Veeranna

2018-05-01

Sm3+ doped lithium di-borate glasses with composition 30Li2O-60B2O3-(10-x) PbO, (where 0 < x < 2 mole. %) were prepared by melt quenching method. The addition of modifier oxide to vitreous B2O3 modifies the glass network by converting three coordinated trigonal boron units (BO3) to weaker anionic four coordinated tetrahedral borons (BO4). The decrease in density and increase in molar volume with samarium ion content indicates the openness of the glass structure. The gradual increase in average separation of boron-boron atoms with VmB clearly indicates deterioration of borate glass network, which in turn leads to decrease in the oxygen packing density. The replacements of Sm2O3 for PbO depolymerise the chain structure and that would increase the concentration of non-bridging oxygens. The marginal increase of optical band gap energy after 1.0 mol.% of Sm2O3 is explained by considering the structural modification in lead-borate. The influence of Sm3+ ion on physical and optical properties in lithium-lead-borate glasses is investigated and the results were discussed in view of the structure of borate glass network.

Residents Perceptions of Friendship and Positive Social Networks Within a Nursing Home.

PubMed

Casey, Anne-Nicole S; Low, Lee-Fay; Jeon, Yun-Hee; Brodaty, Henry

2016-10-01

(i) To describe nursing home residents' perceptions of their friendship networks using social network analysis (SNA) and (ii) to contribute to theory regarding resident friendship schema, network structure, and connections between network ties and social support. Cross-sectional interviews, standardized assessments, and observational data were collected in three care units, including a Dementia Specific Unit (DSU), of a 94-bed Sydney nursing home. Full participation consent was obtained for 36 residents aged 63-94 years. Able residents answered open-ended questions about friendship, identified friendship ties, and completed measures of nonfamily social support. Residents retained clear concepts of friendship and reported small, sparse networks. Nonparametric pairwise comparisons indicated that DSU residents reported less perceived social support (median = 7) than residents from the other units (median = 17; U = 10.0, p = .034, r = -.51), (median = 14; U = 0.0, p = .003, r = -.82). Greater perceived social support was moderately associated with higher number of reciprocated ties [ρ(25) = .49, p = .013]. Though some residents had friendships, many reported that nursing home social opportunities did not align with their expectations of friendship. Relationships with coresidents were associated with perceptions of social support. SNA's relational perspective elucidated network size, tie direction, and density, advancing understanding of the structure of residents' networks and flow of subjective social support through that structure. Understanding resident expectations and perceptions of their social networks is important for care providers wishing to improve quality of life in nursing homes. © The Author 2015. Published by Oxford University Press on behalf of The Gerontological Society of America. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

A new model linking elastic properties and ionic conductivity of mixed network former glasses.

PubMed

Wang, Weimin; Christensen, Randilynn; Curtis, Brittany; Martin, Steve W; Kieffer, John

2018-01-17

Glasses are promising candidate materials for all-solid-state electrolytes for rechargeable batteries due to their outstanding mechanical stability, wide electrochemical stability range, and open structure for potentially high conductivity. Mechanical stiffness and ionic conductivity are two key parameters for solid-state electrolytes. In this study, we investigate two mixed-network former glass systems, sodium borosilicate 0.2Na 2 O + 0.8[xBO 1.5 + (1 - x)SiO 2 ] and sodium borogermanate 0.2Na 2 O + 0.8[xBO 1.5 + (1 - x)GeO 2 ] glasses. With mixed-network formers, the structure of the network changes while the network modifier mole fraction is kept constant, i.e., x = 0.2, which allows us to analyze the effect of the network structure on various properties, including ionic conductivity and elastic properties. Besides the non-linear, non-additive mixed glass former effect, we find that the longitudinal, shear and Young's moduli depend on the combined number density of tetrahedrally and octahedrally coordinated network former elements. These units provide connectivity in three dimensions, which is required for the networks to exhibit restoring forces in response to isotropic and shear deformations. Moreover, the activation energy for modifier cation, Na + , migration is strongly correlated with the bulk modulus, suggesting that the elastic strain energy associated with the passageway dilation for the sodium ions is governed by the bulk modulus of the glass. The detailed analysis provided here gives an estimate for the number of atoms in the vicinity of the migrating cation that are affected by elastic deformation during the activated process. The larger this number and the more compliant the glass network, the lower is the activation energy for the cation jump.

Molecular ecological network analyses.

PubMed

Deng, Ye; Jiang, Yi-Huei; Yang, Yunfeng; He, Zhili; Luo, Feng; Zhou, Jizhong

2012-05-30

Understanding the interaction among different species within a community and their responses to environmental changes is a central goal in ecology. However, defining the network structure in a microbial community is very challenging due to their extremely high diversity and as-yet uncultivated status. Although recent advance of metagenomic technologies, such as high throughout sequencing and functional gene arrays, provide revolutionary tools for analyzing microbial community structure, it is still difficult to examine network interactions in a microbial community based on high-throughput metagenomics data. Here, we describe a novel mathematical and bioinformatics framework to construct ecological association networks named molecular ecological networks (MENs) through Random Matrix Theory (RMT)-based methods. Compared to other network construction methods, this approach is remarkable in that the network is automatically defined and robust to noise, thus providing excellent solutions to several common issues associated with high-throughput metagenomics data. We applied it to determine the network structure of microbial communities subjected to long-term experimental warming based on pyrosequencing data of 16 S rRNA genes. We showed that the constructed MENs under both warming and unwarming conditions exhibited topological features of scale free, small world and modularity, which were consistent with previously described molecular ecological networks. Eigengene analysis indicated that the eigengenes represented the module profiles relatively well. In consistency with many other studies, several major environmental traits including temperature and soil pH were found to be important in determining network interactions in the microbial communities examined. To facilitate its application by the scientific community, all these methods and statistical tools have been integrated into a comprehensive Molecular Ecological Network Analysis Pipeline (MENAP), which is open-accessible now (http://ieg2.ou.edu/MENA). The RMT-based molecular ecological network analysis provides powerful tools to elucidate network interactions in microbial communities and their responses to environmental changes, which are fundamentally important for research in microbial ecology and environmental microbiology.

Visible-Light Initiated Free-Radical/Cationic Ring-Opening Hybrid Photopolymerization of Methacrylate/Epoxy: Polymerization Kinetics, Crosslinking Structure, and Dynamic Mechanical Properties.

PubMed

Ge, Xueping; Ye, Qiang; Song, Linyong; Misra, Anil; Spencer, Paulette

2015-04-01

The effects of polymerization kinetics and chemical miscibility on the crosslinking structure and mechanical properties of polymers cured by visible-light initiated free-radical/cationic ring-opening hybrid photopolymerization are determined. A three-component initiator system is used and the monomer system contains methacrylates and epoxides. The photopolymerization kinetics is monitored in situ by Fourier transform infrared-attenuated total reflectance. The crosslinking structure is studied by modulated differential scanning calorimetry and dynamic mechanical analysis. X-ray microcomputed tomography is used to evaluate microphase separation. The mechanical properties of polymers formed by hybrid formed by free-radical polymerization. These investigations mark the first time that the benefits of the chain transfer reaction between epoxy and hydroxyl groups of methacrylate, on the crosslinking network and microphase separation during hybrid visible-light initiated photopolymerization, have been determined.

Programmable multi-node quantum network design and simulation

NASA Astrophysics Data System (ADS)

Dasari, Venkat R.; Sadlier, Ronald J.; Prout, Ryan; Williams, Brian P.; Humble, Travis S.

2016-05-01

Software-defined networking offers a device-agnostic programmable framework to encode new network functions. Externally centralized control plane intelligence allows programmers to write network applications and to build functional network designs. OpenFlow is a key protocol widely adopted to build programmable networks because of its programmability, flexibility and ability to interconnect heterogeneous network devices. We simulate the functional topology of a multi-node quantum network that uses programmable network principles to manage quantum metadata for protocols such as teleportation, superdense coding, and quantum key distribution. We first show how the OpenFlow protocol can manage the quantum metadata needed to control the quantum channel. We then use numerical simulation to demonstrate robust programmability of a quantum switch via the OpenFlow network controller while executing an application of superdense coding. We describe the software framework implemented to carry out these simulations and we discuss near-term efforts to realize these applications.

European Science Notes Information Bulletin. Reports on Current European and Middle Eastern Science

DTIC Science & Technology

1993-01-01

network. Mechanical properties of ormolytes can tion of TiO2 to "open-up" the structure tb.r Li be modified by altering the structure of the silicate...Cambridge es. The group from the University of California, group has demonstrated that the color (wavelength) Santa Barbara, and Uniax Corporation...A.J. of the electroluminescence can be tuned over a Heeger, F. Wudi, P. Smith) reported on their work range of colors . with polymer 12 in several talks

A review of active learning approaches to experimental design for uncovering biological networks

PubMed Central

2017-01-01

Various types of biological knowledge describe networks of interactions among elementary entities. For example, transcriptional regulatory networks consist of interactions among proteins and genes. Current knowledge about the exact structure of such networks is highly incomplete, and laboratory experiments that manipulate the entities involved are conducted to test hypotheses about these networks. In recent years, various automated approaches to experiment selection have been proposed. Many of these approaches can be characterized as active machine learning algorithms. Active learning is an iterative process in which a model is learned from data, hypotheses are generated from the model to propose informative experiments, and the experiments yield new data that is used to update the model. This review describes the various models, experiment selection strategies, validation techniques, and successful applications described in the literature; highlights common themes and notable distinctions among methods; and identifies likely directions of future research and open problems in the area. PMID:28570593

Neuron-Like Networks Between Ribosomal Proteins Within the Ribosome

NASA Astrophysics Data System (ADS)

Poirot, Olivier; Timsit, Youri

2016-05-01

From brain to the World Wide Web, information-processing networks share common scale invariant properties. Here, we reveal the existence of neural-like networks at a molecular scale within the ribosome. We show that with their extensions, ribosomal proteins form complex assortative interaction networks through which they communicate through tiny interfaces. The analysis of the crystal structures of 50S eubacterial particles reveals that most of these interfaces involve key phylogenetically conserved residues. The systematic observation of interactions between basic and aromatic amino acids at the interfaces and along the extension provides new structural insights that may contribute to decipher the molecular mechanisms of signal transmission within or between the ribosomal proteins. Similar to neurons interacting through “molecular synapses”, ribosomal proteins form a network that suggest an analogy with a simple molecular brain in which the “sensory-proteins” innervate the functional ribosomal sites, while the “inter-proteins” interconnect them into circuits suitable to process the information flow that circulates during protein synthesis. It is likely that these circuits have evolved to coordinate both the complex macromolecular motions and the binding of the multiple factors during translation. This opens new perspectives on nanoscale information transfer and processing.

Systems biology of the structural proteome.

PubMed

Brunk, Elizabeth; Mih, Nathan; Monk, Jonathan; Zhang, Zhen; O'Brien, Edward J; Bliven, Spencer E; Chen, Ke; Chang, Roger L; Bourne, Philip E; Palsson, Bernhard O

2016-03-11

The success of genome-scale models (GEMs) can be attributed to the high-quality, bottom-up reconstructions of metabolic, protein synthesis, and transcriptional regulatory networks on an organism-specific basis. Such reconstructions are biochemically, genetically, and genomically structured knowledge bases that can be converted into a mathematical format to enable a myriad of computational biological studies. In recent years, genome-scale reconstructions have been extended to include protein structural information, which has opened up new vistas in systems biology research and empowered applications in structural systems biology and systems pharmacology. Here, we present the generation, application, and dissemination of genome-scale models with protein structures (GEM-PRO) for Escherichia coli and Thermotoga maritima. We show the utility of integrating molecular scale analyses with systems biology approaches by discussing several comparative analyses on the temperature dependence of growth, the distribution of protein fold families, substrate specificity, and characteristic features of whole cell proteomes. Finally, to aid in the grand challenge of big data to knowledge, we provide several explicit tutorials of how protein-related information can be linked to genome-scale models in a public GitHub repository ( https://github.com/SBRG/GEMPro/tree/master/GEMPro_recon/). Translating genome-scale, protein-related information to structured data in the format of a GEM provides a direct mapping of gene to gene-product to protein structure to biochemical reaction to network states to phenotypic function. Integration of molecular-level details of individual proteins, such as their physical, chemical, and structural properties, further expands the description of biochemical network-level properties, and can ultimately influence how to model and predict whole cell phenotypes as well as perform comparative systems biology approaches to study differences between organisms. GEM-PRO offers insight into the physical embodiment of an organism's genotype, and its use in this comparative framework enables exploration of adaptive strategies for these organisms, opening the door to many new lines of research. With these provided tools, tutorials, and background, the reader will be in a position to run GEM-PRO for their own purposes.

An Open, Snow-based Hydrologic System on Noachian Mars

NASA Technical Reports Server (NTRS)

Zent, A. P.

1999-01-01

Properties of Noachian valley networks on Mars suggest that the conditions under which they formed were marginal for liquid water formation. The networks are sparsely scattered, poorly dissected, and tend to be small; a majority occupy areas only a few hundred kilometers in extent. Models in which networks formed by mass wasting are contra-indicated by the discovery of channels within the valleys. Greenhouse hypotheses for the stability of liquid water have foundered on familiar problems: first, a very substantial CO2 atmosphere would be required to bring global average conditions to 273 K; the CO2 should still be present in extensive carbonate deposits that have not been detected. Explanations that call upon groundwater sapping are hampered by the need for a hydrologic system to recharge the groundwater system, which effectively reinstates the need for a heavy CO2 atmosphere. Based upon field experience and geomorphic similarities between drainage developed in the periglacial terrain in and around the Haughton impact structure, Devon Island, Nuunavuut, Canada, we have suggested that some of the channel networks may have formed either subglacially, or as ice marginal structures.

OpenSWPC: an open-source integrated parallel simulation code for modeling seismic wave propagation in 3D heterogeneous viscoelastic media

NASA Astrophysics Data System (ADS)

Maeda, Takuto; Takemura, Shunsuke; Furumura, Takashi

2017-07-01

We have developed an open-source software package, Open-source Seismic Wave Propagation Code (OpenSWPC), for parallel numerical simulations of seismic wave propagation in 3D and 2D (P-SV and SH) viscoelastic media based on the finite difference method in local-to-regional scales. This code is equipped with a frequency-independent attenuation model based on the generalized Zener body and an efficient perfectly matched layer for absorbing boundary condition. A hybrid-style programming using OpenMP and the Message Passing Interface (MPI) is adopted for efficient parallel computation. OpenSWPC has wide applicability for seismological studies and great portability to allowing excellent performance from PC clusters to supercomputers. Without modifying the code, users can conduct seismic wave propagation simulations using their own velocity structure models and the necessary source representations by specifying them in an input parameter file. The code has various modes for different types of velocity structure model input and different source representations such as single force, moment tensor and plane-wave incidence, which can easily be selected via the input parameters. Widely used binary data formats, the Network Common Data Form (NetCDF) and the Seismic Analysis Code (SAC) are adopted for the input of the heterogeneous structure model and the outputs of the simulation results, so users can easily handle the input/output datasets. All codes are written in Fortran 2003 and are available with detailed documents in a public repository.[Figure not available: see fulltext.

Undermining and Strengthening Social Networks through Network Modification

PubMed Central

Mellon, Jonathan; Yoder, Jordan; Evans, Daniel

2016-01-01

Social networks have well documented effects at the individual and aggregate level. Consequently it is often useful to understand how an attempt to influence a network will change its structure and consequently achieve other goals. We develop a framework for network modification that allows for arbitrary objective functions, types of modification (e.g. edge weight addition, edge weight removal, node removal, and covariate value change), and recovery mechanisms (i.e. how a network responds to interventions). The framework outlined in this paper helps both to situate the existing work on network interventions but also opens up many new possibilities for intervening in networks. In particular use two case studies to highlight the potential impact of empirically calibrating the objective function and network recovery mechanisms as well as showing how interventions beyond node removal can be optimised. First, we simulate an optimal removal of nodes from the Noordin terrorist network in order to reduce the expected number of attacks (based on empirically predicting the terrorist collaboration network from multiple types of network ties). Second, we simulate optimally strengthening ties within entrepreneurial ecosystems in six developing countries. In both cases we estimate ERGM models to simulate how a network will endogenously evolve after intervention. PMID:27703198

Undermining and Strengthening Social Networks through Network Modification.

PubMed

Mellon, Jonathan; Yoder, Jordan; Evans, Daniel

2016-10-05

Social networks have well documented effects at the individual and aggregate level. Consequently it is often useful to understand how an attempt to influence a network will change its structure and consequently achieve other goals. We develop a framework for network modification that allows for arbitrary objective functions, types of modification (e.g. edge weight addition, edge weight removal, node removal, and covariate value change), and recovery mechanisms (i.e. how a network responds to interventions). The framework outlined in this paper helps both to situate the existing work on network interventions but also opens up many new possibilities for intervening in networks. In particular use two case studies to highlight the potential impact of empirically calibrating the objective function and network recovery mechanisms as well as showing how interventions beyond node removal can be optimised. First, we simulate an optimal removal of nodes from the Noordin terrorist network in order to reduce the expected number of attacks (based on empirically predicting the terrorist collaboration network from multiple types of network ties). Second, we simulate optimally strengthening ties within entrepreneurial ecosystems in six developing countries. In both cases we estimate ERGM models to simulate how a network will endogenously evolve after intervention.

Undermining and Strengthening Social Networks through Network Modification

NASA Astrophysics Data System (ADS)

Mellon, Jonathan; Yoder, Jordan; Evans, Daniel

2016-10-01

Social networks have well documented effects at the individual and aggregate level. Consequently it is often useful to understand how an attempt to influence a network will change its structure and consequently achieve other goals. We develop a framework for network modification that allows for arbitrary objective functions, types of modification (e.g. edge weight addition, edge weight removal, node removal, and covariate value change), and recovery mechanisms (i.e. how a network responds to interventions). The framework outlined in this paper helps both to situate the existing work on network interventions but also opens up many new possibilities for intervening in networks. In particular use two case studies to highlight the potential impact of empirically calibrating the objective function and network recovery mechanisms as well as showing how interventions beyond node removal can be optimised. First, we simulate an optimal removal of nodes from the Noordin terrorist network in order to reduce the expected number of attacks (based on empirically predicting the terrorist collaboration network from multiple types of network ties). Second, we simulate optimally strengthening ties within entrepreneurial ecosystems in six developing countries. In both cases we estimate ERGM models to simulate how a network will endogenously evolve after intervention.

Individual T1-weighted/T2-weighted ratio brain networks: Small-worldness, hubs and modular organization

NASA Astrophysics Data System (ADS)

Wu, Huijun; Wang, Hao; Lü, Linyuan

Applying network science to investigate the complex systems has become a hot topic. In neuroscience, understanding the architectures of complex brain networks was a vital issue. An enormous amount of evidence had supported the brain was cost/efficiency trade-off with small-worldness, hubness and modular organization through the functional MRI and structural MRI investigations. However, the T1-weighted/T2-weighted (T1w/T2w) ratio brain networks were mostly unexplored. Here, we utilized a KL divergence-based method to construct large-scale individual T1w/T2w ratio brain networks and investigated the underlying topological attributes of these networks. Our results supported that the T1w/T2w ratio brain networks were comprised of small-worldness, an exponentially truncated power-law degree distribution, frontal-parietal hubs and modular organization. Besides, there were significant positive correlations between the network metrics and fluid intelligence. Thus, the T1w/T2w ratio brain networks open a new avenue to understand the human brain and are a necessary supplement for future MRI studies.

Highly-ordered supportless three-dimensional nanowire networks with tunable complexity and interwire connectivity for device integration.

PubMed

Rauber, Markus; Alber, Ina; Müller, Sven; Neumann, Reinhard; Picht, Oliver; Roth, Christina; Schökel, Alexander; Toimil-Molares, Maria Eugenia; Ensinger, Wolfgang

2011-06-08

The fabrication of three-dimensional assemblies consisting of large quantities of nanowires is of great technological importance for various applications including (electro-)catalysis, sensitive sensing, and improvement of electronic devices. Because the spatial distribution of the nanostructured material can strongly influence the properties, architectural design is required in order to use assembled nanowires to their full potential. In addition, special effort has to be dedicated to the development of efficient methods that allow precise control over structural parameters of the nanoscale building blocks as a means of tuning their characteristics. This paper reports the direct synthesis of highly ordered large-area nanowire networks by a method based on hard templates using electrodeposition within nanochannels of ion track-etched polymer membranes. Control over the complexity of the networks and the dimensions of the integrated nanostructures are achieved by a modified template fabrication. The networks possess high surface area and excellent transport properties, turning them into a promising electrocatalyst material as demonstrated by cyclic voltammetry studies on platinum nanowire networks catalyzing methanol oxidation. Our method opens up a new general route for interconnecting nanowires to stable macroscopic network structures of very high integration level that allow easy handling of nanowires while maintaining their connectivity.

47 CFR 76.1508 - Network non-duplication.

Code of Federal Regulations, 2014 CFR

2014-10-01

... MULTICHANNEL VIDEO AND CABLE TELEVISION SERVICE Open Video Systems § 76.1508 Network non-duplication. (a) Sections 76.92 through 76.97 shall apply to open video systems in accordance with the provisions contained... unit” shall apply to an open video system or that portion of an open video system that operates or will...

47 CFR 76.1508 - Network non-duplication.

Code of Federal Regulations, 2012 CFR

2012-10-01

... MULTICHANNEL VIDEO AND CABLE TELEVISION SERVICE Open Video Systems § 76.1508 Network non-duplication. (a) Sections 76.92 through 76.97 shall apply to open video systems in accordance with the provisions contained... unit” shall apply to an open video system or that portion of an open video system that operates or will...

47 CFR 76.1508 - Network non-duplication.

Code of Federal Regulations, 2013 CFR

2013-10-01

... MULTICHANNEL VIDEO AND CABLE TELEVISION SERVICE Open Video Systems § 76.1508 Network non-duplication. (a) Sections 76.92 through 76.97 shall apply to open video systems in accordance with the provisions contained... unit” shall apply to an open video system or that portion of an open video system that operates or will...

47 CFR 76.1508 - Network non-duplication.

Code of Federal Regulations, 2011 CFR

2011-10-01

... MULTICHANNEL VIDEO AND CABLE TELEVISION SERVICE Open Video Systems § 76.1508 Network non-duplication. (a) Sections 76.92 through 76.97 shall apply to open video systems in accordance with the provisions contained... unit” shall apply to an open video system or that portion of an open video system that operates or will...

Fractal multi-level organisation of human groups in a virtual world.

PubMed

Fuchs, Benedikt; Sornette, Didier; Thurner, Stefan

2014-10-06

Humans are fundamentally social. They form societies which consist of hierarchically layered nested groups of various quality, size, and structure. The anthropologic literature has classified these groups as support cliques, sympathy groups, bands, cognitive groups, tribes, linguistic groups, and so on. Anthropologic data show that, on average, each group consists of approximately three subgroups. However, a general understanding of the structural dependence of groups at different layers is largely missing. We extend these early findings to a very large high-precision large-scale internet-based social network data. We analyse the organisational structure of a complete, multi-relational, large social multiplex network of a human society consisting of about 400,000 odd players of an open-ended massive multiplayer online game for which we know all about their various group memberships at different layers. Remarkably, the online players' society exhibits the same type of structured hierarchical layers as found in hunter-gatherer societies. Our findings suggest that the hierarchical organisation of human society is deeply nested in human psychology.

Fractal multi-level organisation of human groups in a virtual world

PubMed Central

Fuchs, Benedikt; Sornette, Didier; Thurner, Stefan

2014-01-01

Humans are fundamentally social. They form societies which consist of hierarchically layered nested groups of various quality, size, and structure. The anthropologic literature has classified these groups as support cliques, sympathy groups, bands, cognitive groups, tribes, linguistic groups, and so on. Anthropologic data show that, on average, each group consists of approximately three subgroups. However, a general understanding of the structural dependence of groups at different layers is largely missing. We extend these early findings to a very large high-precision large-scale internet-based social network data. We analyse the organisational structure of a complete, multi-relational, large social multiplex network of a human society consisting of about 400,000 odd players of an open-ended massive multiplayer online game for which we know all about their various group memberships at different layers. Remarkably, the online players' society exhibits the same type of structured hierarchical layers as found in hunter-gatherer societies. Our findings suggest that the hierarchical organisation of human society is deeply nested in human psychology. PMID:25283998

Fractal multi-level organisation of human groups in a virtual world

NASA Astrophysics Data System (ADS)

Fuchs, Benedikt; Sornette, Didier; Thurner, Stefan

2014-10-01

Humans are fundamentally social. They form societies which consist of hierarchically layered nested groups of various quality, size, and structure. The anthropologic literature has classified these groups as support cliques, sympathy groups, bands, cognitive groups, tribes, linguistic groups, and so on. Anthropologic data show that, on average, each group consists of approximately three subgroups. However, a general understanding of the structural dependence of groups at different layers is largely missing. We extend these early findings to a very large high-precision large-scale internet-based social network data. We analyse the organisational structure of a complete, multi-relational, large social multiplex network of a human society consisting of about 400,000 odd players of an open-ended massive multiplayer online game for which we know all about their various group memberships at different layers. Remarkably, the online players' society exhibits the same type of structured hierarchical layers as found in hunter-gatherer societies. Our findings suggest that the hierarchical organisation of human society is deeply nested in human psychology.

Network Flow Simulation of Fluid Transients in Rocket Propulsion Systems

NASA Technical Reports Server (NTRS)

Bandyopadhyay, Alak; Hamill, Brian; Ramachandran, Narayanan; Majumdar, Alok

2011-01-01

Fluid transients, also known as water hammer, can have a significant impact on the design and operation of both spacecraft and launch vehicle propulsion systems. These transients often occur at system activation and shutdown. The pressure rise due to sudden opening and closing of valves of propulsion feed lines can cause serious damage during activation and shutdown of propulsion systems. During activation (valve opening) and shutdown (valve closing), pressure surges must be predicted accurately to ensure structural integrity of the propulsion system fluid network. In the current work, a network flow simulation software (Generalized Fluid System Simulation Program) based on Finite Volume Method has been used to predict the pressure surges in the feed line due to both valve closing and valve opening using two separate geometrical configurations. The valve opening pressure surge results are compared with experimental data available in the literature and the numerical results compared very well within reasonable accuracy (< 5%) for a wide range of inlet-to-initial pressure ratios. A Fast Fourier Transform is preformed on the pressure oscillations to predict the various modal frequencies of the pressure wave. The shutdown problem, i.e. valve closing problem, the simulation results are compared with the results of Method of Characteristics. Most rocket engines experience a longitudinal acceleration, known as "pogo" during the later stage of engine burn. In the shutdown example problem, an accumulator has been used in the feed system to demonstrate the "pogo" mitigation effects in the feed system of propellant. The simulation results using GFSSP compared very well with the results of Method of Characteristics.

Molecular Dynamics Simulation Reveals Correlated Inter-Lobe Motion in Protein Lysine Methyltransferase SMYD2.

PubMed

Spellmon, Nicholas; Sun, Xiaonan; Sirinupong, Nualpun; Edwards, Brian; Li, Chunying; Yang, Zhe

2015-01-01

SMYD proteins are an exciting field of study as they are linked to many types of cancer-related pathways. Cardiac and skeletal muscle development and function also depend on SMYD proteins opening a possible avenue for cardiac-related treatment. Previous crystal structure studies have revealed that this special class of protein lysine methyltransferases have a bilobal structure, and an open-closed motion may regulate substrate specificity. Here we use the molecular dynamics simulation to investigate the still-poorly-understood SMYD2 dynamics. Cross-correlation analysis reveals that SMYD2 exhibits a negative correlated inter-lobe motion. Principle component analysis suggests that this correlated dynamic is contributed to by a twisting motion of the C-lobe with respect to the N-lobe and a clamshell-like motion between the lobes. Dynamical network analysis defines possible allosteric paths for the correlated dynamics. There are nine communities in the dynamical network with six in the N-lobe and three in the C-lobe, and the communication between the lobes is mediated by a lobe-bridging β hairpin. This study provides insight into the dynamical nature of SMYD2 and could facilitate better understanding of SMYD2 substrate specificity.

Chaos synchronization in networks of semiconductor superlattices

NASA Astrophysics Data System (ADS)

Li, Wen; Aviad, Yaara; Reidler, Igor; Song, Helun; Huang, Yuyang; Biermann, Klaus; Rosenbluh, Michael; Zhang, Yaohui; Grahn, Holger T.; Kanter, Ido

2015-11-01

Chaos synchronization has been demonstrated as a useful building block for various tasks in secure communications, including a source of all-electronic ultrafast physical random number generators based on room temperature spontaneous chaotic oscillations in a DC-biased weakly coupled GaAs/Al0.45Ga0.55As semiconductor superlattice (SSL). Here, we experimentally demonstrate the emergence of several types of chaos synchronization, e.g. leader-laggard, face-to-face and zero-lag synchronization in network motifs of coupled SSLs consisting of unidirectional and mutual coupling as well as self-feedback coupling. Each type of synchronization clearly reflects the symmetry of the topology of its network motif. The emergence of a chaotic SSL without external feedback and synchronization among different structured SSLs open up the possibility for advanced secure multi-user communication methods based on large networks of coupled SSLs.

Molecular Simulation Uncovers the Conformational Space of the λ Cro Dimer in Solution

PubMed Central

Ahlstrom, Logan S.; Miyashita, Osamu

2011-01-01

The significant variation among solved structures of the λ Cro dimer suggests its flexibility. However, contacts in the crystal lattice could have stabilized a conformation which is unrepresentative of its dominant solution form. Here we report on the conformational space of the Cro dimer in solution using replica exchange molecular dynamics in explicit solvent. The simulated ensemble shows remarkable correlation with available x-ray structures. Network analysis and a free energy surface reveal the predominance of closed and semi-open dimers, with a modest barrier separating these two states. The fully open conformation lies higher in free energy, indicating that it requires stabilization by DNA or crystal contacts. Most NMR models are found to be unstable conformations in solution. Intersubunit salt bridging between Arg4 and Glu53 during simulation stabilizes closed conformations. Because a semi-open state is among the low-energy conformations sampled in simulation, we propose that Cro-DNA binding may not entail a large conformational change relative to the dominant dimer forms in solution. PMID:22098751

Determining Open Education Related Social Media Usage Trends in Turkey Using a Holistic Social Network Analysis

ERIC Educational Resources Information Center

Firat, Mehmet; Altinpulluk, Hakan; Kilinç, Hakan; Büyük, Köksal

2017-01-01

The aim of this study is to reveal Open Education related social media usage in Turkey through social network analyses. To this end, the most widely used social media network in Turkey, Facebook, was chosen. All the pages and groups created on Facebook related to Open Education were found. A total of 207 groups and 521 pages were accessed and…

A Case for Open Network Health Systems: Systems as Networks in Public Mental Health

PubMed Central

Rhodes, Michael Grant; de Vries, Marten W.

2017-01-01

Increases in incidents involving so-called confused persons have brought attention to the potential costs of recent changes to public mental health (PMH) services in the Netherlands. Decentralized under the (Community) Participation Act (2014), local governments must find resources to compensate for reduced central funding to such services or "innovate." But innovation, even when pressure for change is intense, is difficult. This perspective paper describes experience during and after an investigation into a particularly violent incident and murder. The aim was to provide recommendations to improve the functioning of local PMH services. The investigation concluded that no specific failure by an individual professional or service provider facility led to the murder. Instead, also as a result of the Participation Act that severed communication lines between individuals and organizations, information sharing failures were likely to have reduced system level capacity to identify risks. The methods and analytical frameworks employed to reach this conclusion, also lead to discussion as to the plausibility of an unconventional solution. If improving communication is the primary problem, non-hierarchical information, and organizational networks arise as possible and innovative system solutions. The proposal for debate is that traditional "health system" definitions, literature and narratives, and operating assumptions in public (mental) health are ‘locked in’ constraining technical and organization innovations. If we view a "health system" as an adaptive system of economic and social "networks," it becomes clear that the current orthodox solution, the so-called integrated health system, typically results in a "centralized hierarchical" or "tree" network. An overlooked alternative that breaks out of the established policy narratives is the view of a ‘health systems’ as a non-hierarchical organizational structure or ‘Open Network.’ In turn, this opens new technological and organizational possibilities in seeking policy solutions, and suggests an alternative governance model of huge potential value in public health both locally and globally. PMID:28812792

Facile solid-state synthesis of Ni@C nanosheet-assembled hierarchical network for high-performance lithium storage

NASA Astrophysics Data System (ADS)

Gu, Jinghe; Li, Qiyun; Zeng, Pan; Meng, Yulin; Zhang, Xiukui; Wu, Ping; Zhou, Yiming

2017-08-01

Micro/nano-architectured transition-metal@C hybrids possess unique structural and compositional features toward lithium storage, and are thus expected to manifest ideal anodic performances in advanced lithium-ion batteries (LIBs). Herein, we propose a facile and scalable solid-state coordination and subsequent pyrolysis route for the formation of a novel type of micro/nano-architectured transition-metal@C hybrid (i.e., Ni@C nanosheet-assembled hierarchical network, Ni@C network). Moreover, this coordination-pyrolysis route has also been applied for the construction of bare carbon network using zinc salts instead of nickel salts as precursors. When applied as potential anodic materials in LIBs, the Ni@C network exhibits Ni-content-dependent electrochemical performances, and the partially-etched Ni@C network manifests markedly enhanced Li-storage performances in terms of specific capacities, cycle life, and rate capability than the pristine Ni@C network and carbon network. The proposed solid-state coordination and pyrolysis strategy would open up new opportunities for constructing micro/nano-architectured transition-metal@C hybrids as advanced anode materials for LIBs.

Localization of multilayer networks by optimized single-layer rewiring.

PubMed

Jalan, Sarika; Pradhan, Priodyuti

2018-04-01

We study localization properties of principal eigenvectors (PEVs) of multilayer networks (MNs). Starting with a multilayer network corresponding to a delocalized PEV, we rewire the network edges using an optimization technique such that the PEV of the rewired multilayer network becomes more localized. The framework allows us to scrutinize structural and spectral properties of the networks at various localization points during the rewiring process. We show that rewiring only one layer is enough to attain a MN having a highly localized PEV. Our investigation reveals that a single edge rewiring of the optimized MN can lead to the complete delocalization of a highly localized PEV. This sensitivity in the localization behavior of PEVs is accompanied with the second largest eigenvalue lying very close to the largest one. This observation opens an avenue to gain a deeper insight into the origin of PEV localization of networks. Furthermore, analysis of multilayer networks constructed using real-world social and biological data shows that the localization properties of these real-world multilayer networks are in good agreement with the simulation results for the model multilayer network. This paper is relevant to applications that require understanding propagation of perturbation in multilayer networks.

Localization of multilayer networks by optimized single-layer rewiring

NASA Astrophysics Data System (ADS)

Jalan, Sarika; Pradhan, Priodyuti

2018-04-01

We study localization properties of principal eigenvectors (PEVs) of multilayer networks (MNs). Starting with a multilayer network corresponding to a delocalized PEV, we rewire the network edges using an optimization technique such that the PEV of the rewired multilayer network becomes more localized. The framework allows us to scrutinize structural and spectral properties of the networks at various localization points during the rewiring process. We show that rewiring only one layer is enough to attain a MN having a highly localized PEV. Our investigation reveals that a single edge rewiring of the optimized MN can lead to the complete delocalization of a highly localized PEV. This sensitivity in the localization behavior of PEVs is accompanied with the second largest eigenvalue lying very close to the largest one. This observation opens an avenue to gain a deeper insight into the origin of PEV localization of networks. Furthermore, analysis of multilayer networks constructed using real-world social and biological data shows that the localization properties of these real-world multilayer networks are in good agreement with the simulation results for the model multilayer network. This paper is relevant to applications that require understanding propagation of perturbation in multilayer networks.

A proposal for an SDN-based SIEPON architecture

NASA Astrophysics Data System (ADS)

Khalili, Hamzeh; Sallent, Sebastià; Piney, José Ramón; Rincón, David

2017-11-01

Passive Optical Network (PON) elements such as Optical Line Terminal (OLT) and Optical Network Units (ONUs) are currently managed by inflexible legacy network management systems. Software-Defined Networking (SDN) is a new networking paradigm that improves the operation and management of networks. In this paper, we propose a novel architecture, based on the SDN concept, for Ethernet Passive Optical Networks (EPON) that includes the Service Interoperability standard (SIEPON). In our proposal, the OLT is partially virtualized and some of its functionalities are allocated to the core network management system, while the OLT itself is replaced by an OpenFlow (OF) switch. A new MultiPoint MAC Control (MPMC) sublayer extension based on the OpenFlow protocol is presented. This would allow the SDN controller to manage and enhance the resource utilization, flow monitoring, bandwidth assignment, quality-of-service (QoS) guarantees, and energy management of the optical network access, to name a few possibilities. The OpenFlow switch is extended with synchronous ports to retain the time-critical nature of the EPON network. OpenFlow messages are also extended with new functionalities to implement the concept of EPON Service Paths (ESPs). Our simulation-based results demonstrate the effectiveness of the new architecture, while retaining a similar (or improved) performance in terms of delay and throughput when compared to legacy PONs.

Synthesis, crystal structure, and magnetic properties of a two-fold interpenetrated diamondoid open framework

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

Wu, Jing-Yun, E-mail: jyunwu@ncnu.edu.tw; Cheng, Fu-Yin; Chiang, Ming-Hsi, E-mail: mhchiang@chem.sinica.edu.tw

2016-10-15

Self-assembly of an enlarged angular pyridinecarboxylate ligand and cobalt(II) acetate under mild conditions afforded a three-dimensional open-framework coordination polymer, [Co{sub 2}(μ-H{sub 2}O)(pyca-43){sub 4}]{sub n} (1, Hpyca-43=(E)−3-((pyridin-4-yl)methyleneamino)benzoic acid). The molecular structure of 1 has rationalized to be a porous two-fold interpenetrated diamondoid-like network, with dinuclear Co{sub 2}(μ-H{sub 2}O)(O{sub 2}C){sub 4}N{sub 4} clusters as tetrahedral secondary building units (SBUs), possessing highly solvent accessible volume of approximately 53.0%. Least-squares fit of the magnetic susceptibility data (20–300 K) of 1 yields Curie constant C=6.15 cm{sup 3} mol{sup –1} K and Weiss constant θ=–11.6 K. Every Co{sub 2} subunit within the network is magnetically insulatedmore » to other dimers. The magnetic exchange parameter between Co(II) centers is estimated to −0.72 cm{sup –1}, suggesting a weak antiferromagnetic interaction. The g{sub av} value of 4.65 from fitting to the Lines model indicates that the decrease of the χ{sub M}T value upon cooling is dominated by depopulation of the excited Kramer's states to the effective ground singlet. In addition, the thermal stability and adsorption properties of 1 are also reported. - Graphical abstract: This work has synthesized and structurally characterized a porous two-fold interpenetrated diamondoid-like network, which possesses highly solvent accessible volume of approximately 53.0% and shows a weak antiferromagnetic interaction between the Co(II) centers.« less

Personality, Parasites, Political Attitudes, and Cooperation: A Model of How Infection Prevalence Influences Openness and Social Group Formation.

PubMed

Brown, Gordon D A; Fincher, Corey L; Walasek, Lukasz

2016-01-01

What is the origin of individual differences in ideology and personality? According to the parasite stress hypothesis, the structure of a society and the values of individuals within it are both influenced by the prevalence of infectious disease within the society's geographical region. High levels of infection threat are associated with more ethnocentric and collectivist social structures and greater adherence to social norms, as well as with socially conservative political ideology and less open but more conscientious personalities. Here we use an agent-based model to explore a specific opportunities-parasites trade-off (OPTO) hypothesis, according to which utility-maximizing agents place themselves at an optimal point on a trade-off between (a) the gains that may be achieved through accessing the resources of geographically or socially distant out-group members through openness to out-group interaction, and (b) the losses arising due to consequently increased risks of exotic infection to which immunity has not been developed. We examine the evolution of cooperation and the formation of social groups within social networks, and we show that the groups that spontaneously form exhibit greater local rather than global cooperative networks when levels of infection are high. It is suggested that the OPTO model offers a first step toward understanding the specific mechanisms through which environmental conditions may influence cognition, ideology, personality, and social organization. Copyright © 2015 The Authors. Topics in Cognitive Science published by Wiley Periodicals, Inc. on behalf of Cognitive Science Society.

Graph theoretical modeling of baby brain networks.

PubMed

Zhao, Tengda; Xu, Yuehua; He, Yong

2018-06-12

The human brain undergoes explosive growth during the prenatal period and the first few postnatal years, establishing an early infrastructure for the later development of behaviors and cognitions. Revealing the developmental rules during the early phrase is essential in understanding the emergence of brain function and the origin of developmental disorders. The graph-theoretical network modeling in combination with multiple neuroimaging probes provides an important research framework to explore early development of the topological wiring and organizational paradigms of the brain. Here, we reviewed studies which employed neuroimaging and graph-theoretical modeling to investigate brain network development from approximately 20 gestational weeks to 2 years of age. Specifically, the structural and functional brain networks have evolved to highly efficient topological architectures in the early stage; where the structural network remains ahead and paves the way for the development of functional network. The brain network develops in a heterogeneous order, from primary to higher-order systems and from a tendency of network segregation to network integration in the prenatal and postnatal periods. The early brain network topologies show abilities in predicting certain cognitive and behavior performance in later life, and their impairments are likely to continue into childhood and even adulthood. These macroscopic topological changes are found to be associated with possible microstructural maturations, such as axonal growth and myelinations. Collectively, this review provides a detailed delineation of the early changes of the baby brains in the graph-theoretical modeling framework, which opens up a new avenue to understand the developmental principles of the connectome. Copyright © 2018. Published by Elsevier Inc.

Image understanding systems based on the unifying representation of perceptual and conceptual information and the solution of mid-level and high-level vision problems

NASA Astrophysics Data System (ADS)

Kuvychko, Igor

2001-10-01

Vision is a part of a larger information system that converts visual information into knowledge structures. These structures drive vision process, resolving ambiguity and uncertainty via feedback, and provide image understanding, that is an interpretation of visual information in terms of such knowledge models. A computer vision system based on such principles requires unifying representation of perceptual and conceptual information. Computer simulation models are built on the basis of graphs/networks. The ability of human brain to emulate similar graph/networks models is found. That means a very important shift of paradigm in our knowledge about brain from neural networks to the cortical software. Starting from the primary visual areas, brain analyzes an image as a graph-type spatial structure. Primary areas provide active fusion of image features on a spatial grid-like structure, where nodes are cortical columns. The spatial combination of different neighbor features cannot be described as a statistical/integral characteristic of the analyzed region, but uniquely characterizes such region itself. Spatial logic and topology naturally present in such structures. Mid-level vision processes like clustering, perceptual grouping, multilevel hierarchical compression, separation of figure from ground, etc. are special kinds of graph/network transformations. They convert low-level image structure into the set of more abstract ones, which represent objects and visual scene, making them easy for analysis by higher-level knowledge structures. Higher-level vision phenomena like shape from shading, occlusion, etc. are results of such analysis. Such approach gives opportunity not only to explain frequently unexplainable results of the cognitive science, but also to create intelligent computer vision systems that simulate perceptional processes in both what and where visual pathways. Such systems can open new horizons for robotic and computer vision industries.

Implementation of Phased Array Antenna Technology Providing a Wireless Local Area Network to Enhance Port Security and Maritime Interdiction Operations

DTIC Science & Technology

2009-09-01

boarding team, COTS, WLAN, smart antenna, OpenVPN application, wireless base station, OFDM, latency, point-to-point wireless link. 16. PRICE CODE 17...16 c. SSL/TLS .................................17 2. OpenVPN ......................................17 III. EXPERIMENT METHODOLOGY...network frame at Layer 2 has already been secured by encryption at a higher level. 2. OpenVPN OpenVPN is open source software that provides a VPN

The influence of floral traits on specialization and modularity of plant–pollinator networks in a biodiversity hotspot in the Peruvian Andes

PubMed Central

Watts, Stella; Dormann, Carsten F.; Martín González, Ana M.; Ollerton, Jeff

2016-01-01

Background and Aims Modularity is a ubiquitous and important structural property of ecological networks which describes the relative strengths of sets of interacting species and gives insights into the dynamics of ecological communities. However, this has rarely been studied in species-rich, tropical plant–pollinator networks. Working in a biodiversity hotspot in the Peruvian Andes we assessed the structure of quantitative plant–pollinator networks in nine valleys, quantifying modularity among networks, defining the topological roles of species and the influence of floral traits on specialization. Methods A total of 90 transects were surveyed for plants and pollinators at different altitudes and across different life zones. Quantitative modularity (QuanBiMo) was used to detect modularity and six indices were used to quantify specialization. Key Results All networks were highly structured, moderately specialized and significantly modular regardless of size. The strongest hubs were Baccharis plants, Apis mellifera, Bombus funebris and Diptera spp., which were the most ubiquitous and abundant species with the longest phenologies. Species strength showed a strong association with the modular structure of plant–pollinator networks. Hubs and connectors were the most centralized participants in the networks and were ranked highest (high generalization) when quantifying specialization with most indices. However, complementary specialization d' quantified hubs and connectors as moderately specialized. Specialization and topological roles of species were remarkably constant across some sites, but highly variable in others. Networks were dominated by ecologically and functionally generalist plant species with open access flowers which are closely related taxonomically with similar morphology and rewards. Plants associated with hummingbirds had the highest level of complementary specialization and exclusivity in modules (functional specialists) and the longest corollas. Conclusions We have demonstrated that the topology of networks in this tropical montane environment was non-random and highly organized. Our findings underline that specialization indices convey different concepts of specialization and hence quantify different aspects, and that measuring specialization requires careful consideration of what defines a specialist. PMID:27562649

The influence of floral traits on specialization and modularity of plant-pollinator networks in a biodiversity hotspot in the Peruvian Andes.

PubMed

Watts, Stella; Dormann, Carsten F; Martín González, Ana M; Ollerton, Jeff

2016-09-01

Modularity is a ubiquitous and important structural property of ecological networks which describes the relative strengths of sets of interacting species and gives insights into the dynamics of ecological communities. However, this has rarely been studied in species-rich, tropical plant-pollinator networks. Working in a biodiversity hotspot in the Peruvian Andes we assessed the structure of quantitative plant-pollinator networks in nine valleys, quantifying modularity among networks, defining the topological roles of species and the influence of floral traits on specialization. A total of 90 transects were surveyed for plants and pollinators at different altitudes and across different life zones. Quantitative modularity (QuanBiMo) was used to detect modularity and six indices were used to quantify specialization. All networks were highly structured, moderately specialized and significantly modular regardless of size. The strongest hubs were Baccharis plants, Apis mellifera, Bombus funebris and Diptera spp., which were the most ubiquitous and abundant species with the longest phenologies. Species strength showed a strong association with the modular structure of plant-pollinator networks. Hubs and connectors were the most centralized participants in the networks and were ranked highest (high generalization) when quantifying specialization with most indices. However, complementary specialization d' quantified hubs and connectors as moderately specialized. Specialization and topological roles of species were remarkably constant across some sites, but highly variable in others. Networks were dominated by ecologically and functionally generalist plant species with open access flowers which are closely related taxonomically with similar morphology and rewards. Plants associated with hummingbirds had the highest level of complementary specialization and exclusivity in modules (functional specialists) and the longest corollas. We have demonstrated that the topology of networks in this tropical montane environment was non-random and highly organized. Our findings underline that specialization indices convey different concepts of specialization and hence quantify different aspects, and that measuring specialization requires careful consideration of what defines a specialist. © The Author 2016. Published by Oxford University Press on behalf of the Annals of Botany Company. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

An Educational Technology Tool That Developed in the Natural Flow of Life among Students: WhatsApp

ERIC Educational Resources Information Center

Cetinkaya, Levent

2017-01-01

This study was carried out to identify the benefits and drawbacks of using mobile social network application WhatsApp in the education of Secondary Education students. In this research, survey model was used and open-ended question form to 145 students together with semi-structured interview technique to 6 students were employed and answer to the…

Structurally Driven Enhancement of Resonant Tunneling and Nanomechanical Properties in Diamond-like Carbon Superlattices.

PubMed

Dwivedi, Neeraj; McIntosh, Ross; Dhand, Chetna; Kumar, Sushil; Malik, Hitendra K; Bhattacharyya, Somnath

2015-09-23

We report nitrogen-induced enhanced electron tunnel transport and improved nanomechanical properties in band gap-modulated nitrogen doped DLC (N-DLC) quantum superlattice (QSL) structures. The electrical characteristics of such superlattice devices revealed negative differential resistance (NDR) behavior. The interpretation of these measurements is supported by 1D tight binding calculations of disordered superlattice structures (chains), which include bond alternation in sp(3)-hybridized regions. Tandem theoretical and experimental analysis shows improved tunnel transport, which can be ascribed to nitrogen-driven structural modification of the N-DLC QSL structures, especially the increased sp(2) clustering that provides additional conduction paths throughout the network. The introduction of nitrogen also improved the nanomechanical properties, resulting in enhanced elastic recovery, hardness, and elastic modulus, which is unusual but is most likely due to the onset of cross-linking of the network. Moreover, the materials' stress of N-DLC QSL structures was reduced with the nitrogen doping. In general, the combination of enhanced electron tunnel transport and nanomechanical properties in N-DLC QSL structures/devices can open a platform for the development of a new class of cost-effective and mechanically robust advanced electronic devices for a wide range of applications.

Open Lung Approach for the Acute Respiratory Distress Syndrome: A Pilot, Randomized Controlled Trial.

PubMed

Kacmarek, Robert M; Villar, Jesús; Sulemanji, Demet; Montiel, Raquel; Ferrando, Carlos; Blanco, Jesús; Koh, Younsuck; Soler, Juan Alfonso; Martínez, Domingo; Hernández, Marianela; Tucci, Mauro; Borges, Joao Batista; Lubillo, Santiago; Santos, Arnoldo; Araujo, Juan B; Amato, Marcelo B P; Suárez-Sipmann, Fernando

2016-01-01

The open lung approach is a mechanical ventilation strategy involving lung recruitment and a decremental positive end-expiratory pressure trial. We compared the Acute Respiratory Distress Syndrome network protocol using low levels of positive end-expiratory pressure with open lung approach resulting in moderate to high levels of positive end-expiratory pressure for the management of established moderate/severe acute respiratory distress syndrome. A prospective, multicenter, pilot, randomized controlled trial. A network of 20 multidisciplinary ICUs. Patients meeting the American-European Consensus Conference definition for acute respiratory distress syndrome were considered for the study. At 12-36 hours after acute respiratory distress syndrome onset, patients were assessed under standardized ventilator settings (FIO2≥0.5, positive end-expiratory pressure ≥10 cm H2O). If Pao2/FIO2 ratio remained less than or equal to 200 mm Hg, patients were randomized to open lung approach or Acute Respiratory Distress Syndrome network protocol. All patients were ventilated with a tidal volume of 4 to 8 ml/kg predicted body weight. From 1,874 screened patients with acute respiratory distress syndrome, 200 were randomized: 99 to open lung approach and 101 to Acute Respiratory Distress Syndrome network protocol. Main outcome measures were 60-day and ICU mortalities, and ventilator-free days. Mortality at day-60 (29% open lung approach vs. 33% Acute Respiratory Distress Syndrome Network protocol, p = 0.18, log rank test), ICU mortality (25% open lung approach vs. 30% Acute Respiratory Distress Syndrome network protocol, p = 0.53 Fisher's exact test), and ventilator-free days (8 [0-20] open lung approach vs. 7 [0-20] d Acute Respiratory Distress Syndrome network protocol, p = 0.53 Wilcoxon rank test) were not significantly different. Airway driving pressure (plateau pressure - positive end-expiratory pressure) and PaO2/FIO2 improved significantly at 24, 48 and 72 hours in patients in open lung approach compared with patients in Acute Respiratory Distress Syndrome network protocol. Barotrauma rate was similar in both groups. In patients with established acute respiratory distress syndrome, open lung approach improved oxygenation and driving pressure, without detrimental effects on mortality, ventilator-free days, or barotrauma. This pilot study supports the need for a large, multicenter trial using recruitment maneuvers and a decremental positive end-expiratory pressure trial in persistent acute respiratory distress syndrome.

Wireless and embedded carbon nanotube networks for damage detection in concrete structures

NASA Astrophysics Data System (ADS)

Saafi, Mohamed

2009-09-01

Concrete structures undergo an uncontrollable damage process manifesting in the form of cracks due to the coupling of fatigue loading and environmental effects. In order to achieve long-term durability and performance, continuous health monitoring systems are needed to make critical decisions regarding operation, maintenance and repairs. Recent advances in nanostructured materials such as carbon nanotubes have opened the door for new smart and advanced sensing materials that could effectively be used in health monitoring of structures where wireless and real time sensing could provide information on damage development. In this paper, carbon nanotube networks were embedded into a cement matrix to develop an in situ wireless and embedded sensor for damage detection in concrete structures. By wirelessly measuring the change in the electrical resistance of the carbon nanotube networks, the progress of damage can be detected and monitored. As a proof of concept, wireless cement-carbon nanotube sensors were embedded into concrete beams and subjected to monotonic and cyclic loading to evaluate the effect of damage on their response. Experimental results showed that the wireless response of the embedded nanotube sensors changes due to the formation of cracks during loading. In addition, the nanotube sensors were able to detect the initiation of damage at an early stage of loading.

Allometric relationships between traveltime channel networks, convex hulls, and convexity measures

NASA Astrophysics Data System (ADS)

Tay, Lea Tien; Sagar, B. S. Daya; Chuah, Hean Teik

2006-06-01

The channel network (S) is a nonconvex set, while its basin [C(S)] is convex. We remove open-end points of the channel connectivity network iteratively to generate a traveltime sequence of networks (Sn). The convex hulls of these traveltime networks provide an interesting topological quantity, which has not been noted thus far. We compute lengths of shrinking traveltime networks L(Sn) and areas of corresponding convex hulls C(Sn), the ratios of which provide convexity measures CM(Sn) of traveltime networks. A statistically significant scaling relationship is found for a model network in the form L(Sn) ˜ A[C(Sn)]0.57. From the plots of the lengths of these traveltime networks and the areas of their corresponding convex hulls as functions of convexity measures, new power law relations are derived. Such relations for a model network are CM(Sn) ˜ ? and CM(Sn) ˜ ?. In addition to the model study, these relations for networks derived from seven subbasins of Cameron Highlands region of Peninsular Malaysia are provided. Further studies are needed on a large number of channel networks of distinct sizes and topologies to understand the relationships of these new exponents with other scaling exponents that define the scaling structure of river networks.

Will choice-based reform work for Medicare? Evidence from the Federal Employees Health Benefits Program.

PubMed

Florence, Curtis S; Atherly, Adam; Thorpe, Kenneth E

2006-10-01

. To examine the effect of premiums and benefits on the health plan choices of older enrollees who choose Federal Employees Health Benefits Program (FEHBP) health plans as their primary payer. Administrative enrollment data from the Office of Personnel Management (OPM) and plan premiums and benefits data taken from the Checkbook Guide to health plans. We estimate individual plan choice models where the choice of health plan is a function of out-of-pocket premium, actuarial value, plan attributes, and individual characteristics. Plan attributes include plan structure (fee-for-service/preferred provider organization, point-of-service, or health maintenance organization), drug benefit structure, and whether or not the plan covers other types of spending such as dental services and diabetic supplies. The models are estimated by conditional logit. Our study focuses on three populations that currently choose FEHBP as their primary health care coverage and are similar to the Medicare population: current employees and retirees who are approaching the age of Medicare eligibility (ages 60-64) and current federal employees age 65+. Current employees age 65+ are eligible for Medicare, but their FEHBP plan is their primary payer. Retirees and employees 60-64 are not yet eligible for Medicare but are similar in many respects to recently age-eligible Medicare beneficiaries. We also estimate our model for current employees age 55 and younger as a comparison group. We select a random sample of retirees and employees age 60-64, as well as all current employees age 65+, from the OPM administrative database for the calendar year 2001. The plan choices available to each person are determined by the plans participating in their metropolitan statistical area. We match plan premium and attribute information from the Checkbook Guide to each plan in the enrollee's list of choices. We find that current workers 65+, 60-64, and non-Medicare eligible retirees are sensitive to variation in plan premiums. The premium elasticities for these groups are similar in magnitude to those of the age 55 and under employee group. Older workers and retirees not yet eligible for Medicare are willing to pay a substantial amount for plans with open provider networks. The willingness to pay for open networks is significantly greater for these groups than for younger employees. Willingness to pay for open network plans varies significantly by income, but varies little by age within group. Our finding that older workers and non-Medicare eligible retirees are sensitive to plan premiums suggests that choice-based reform of Medicare would lead to cost-conscious choices by Medicare beneficiaries. However, our finding that these groups are willing to pay more for open network plans than younger employees suggest that higher risk individuals may migrate toward higher benefit, higher cost plans. Our findings on the relationship between income and willingness to pay for open network plans suggest that means testing is a viable reform for lowering Medicare program costs.

What's in a crowd? Analysis of face-to-face behavioral networks.

PubMed

Isella, Lorenzo; Stehlé, Juliette; Barrat, Alain; Cattuto, Ciro; Pinton, Jean-François; Van den Broeck, Wouter

2011-02-21

The availability of new data sources on human mobility is opening new avenues for investigating the interplay of social networks, human mobility and dynamical processes such as epidemic spreading. Here we analyze data on the time-resolved face-to-face proximity of individuals in large-scale real-world scenarios. We compare two settings with very different properties, a scientific conference and a long-running museum exhibition. We track the behavioral networks of face-to-face proximity, and characterize them from both a static and a dynamic point of view, exposing differences and similarities. We use our data to investigate the dynamics of a susceptible-infected model for epidemic spreading that unfolds on the dynamical networks of human proximity. The spreading patterns are markedly different for the conference and the museum case, and they are strongly impacted by the causal structure of the network data. A deeper study of the spreading paths shows that the mere knowledge of static aggregated networks would lead to erroneous conclusions about the transmission paths on the dynamical networks. Copyright © 2010 Elsevier Ltd. All rights reserved.

Delta-Flux: An eddy covariance network for a climate-smart Lower Mississippi Basin

USGS Publications Warehouse

Runkle, Benjamin R. K.; Rigby, James R.; Reba, Michele L.; Anapalli, Saseendran S.; Bhattacharjee, Joydeep; Krauss, Ken W.; Liang, Lu; Locke, Martin A.; Novick, Kimberly A.; Sui, Ruixiu; Suvočarev, Kosana; White, Paul M.

2017-01-01

Networks of remotely monitored research sites are increasingly the tool used to study regional agricultural impacts on carbon and water fluxes. However, key national networks such as the National Ecological Observatory Network and AmeriFlux lack contributions from the Lower Mississippi River Basin (LMRB), a highly productive agricultural area with opportunities for soil carbon sequestration through conservation practices. The authors describe the rationale to create the new Delta-Flux network, which will coordinate efforts to quantify carbon and water budgets at seventeen eddy covariance flux tower sites in the LMRB. The network structure will facilitate climate-smart management strategies based on production-scale and continuous measurements of carbon and water fluxes from the landscape to the atmosphere under different soil and water management conditions. The seventeen instrumented field sites are expected to monitor fluxes within the most characteristic landscapes of the target area: row-crop fields, pasture, grasslands, forests, and marshes. The network participants are committed to open collaboration and efficient regionalization of site-level findings to support sustainable agricultural and forestry management and conservation of natural resources.

Social networks to biological networks: systems biology of Mycobacterium tuberculosis.

PubMed

Vashisht, Rohit; Bhardwaj, Anshu; Osdd Consortium; Brahmachari, Samir K

2013-07-01

Contextualizing relevant information to construct a network that represents a given biological process presents a fundamental challenge in the network science of biology. The quality of network for the organism of interest is critically dependent on the extent of functional annotation of its genome. Mostly the automated annotation pipelines do not account for unstructured information present in volumes of literature and hence large fraction of genome remains poorly annotated. However, if used, this information could substantially enhance the functional annotation of a genome, aiding the development of a more comprehensive network. Mining unstructured information buried in volumes of literature often requires manual intervention to a great extent and thus becomes a bottleneck for most of the automated pipelines. In this review, we discuss the potential of scientific social networking as a solution for systematic manual mining of data. Focusing on Mycobacterium tuberculosis, as a case study, we discuss our open innovative approach for the functional annotation of its genome. Furthermore, we highlight the strength of such collated structured data in the context of drug target prediction based on systems level analysis of pathogen.

X-ray and neutron scattering studies of liquid formic acid DCOOD at various temperatures and under pressure

NASA Astrophysics Data System (ADS)

Nasr, Salah; Bellissent-Funel, Marie-Claire; Cortès, Robert

1999-06-01

A structural investigation of fully deuterated liquid formic acid was performed by neutron scattering at pressure up to 3 kbar. The molecular pair correlation function was also deduced from x-ray study of DCOOD at ambient pressure and at 294 K. The results could be explained in terms of an open-chain structure with only two H bonds per molecule. The mean O⋯O distance is about 2.72 Å. The effect of both temperature and pressure on the hydrogen bond network is examined.

Role of Open and Distance Education in Integrating Education with Development--Emerging Model of Networked Collaborative Learning and Net-working.

ERIC Educational Resources Information Center

Takwale, Ram

1998-01-01

Discusses the evolution of the educational system in India, developments in new communication technologies, and plans by the open and distance education system to develop educational networks. Policies and programs adopted by the Distance Education Council are outlined. (AEF)

A Study of the Predictive Relationship between Online Social Presence and ONLE Interaction

ERIC Educational Resources Information Center

Tu, Chih-Hsiung; Yen, Cherng-Jyh; Blocher, J. Michael; Chan, Junn-Yih

2012-01-01

Open Network Learning Environments (ONLE) are online networks that afford learners the opportunity to participate in creative content endeavors, personalized identity projections, networked mechanism management, and effective collaborative community integration by applying Web 2.0 tools in open environments. It supports social interaction by…

Single-photon-level quantum image memory based on cold atomic ensembles

PubMed Central

Ding, Dong-Sheng; Zhou, Zhi-Yuan; Shi, Bao-Sen; Guo, Guang-Can

2013-01-01

A quantum memory is a key component for quantum networks, which will enable the distribution of quantum information. Its successful development requires storage of single-photon light. Encoding photons with spatial shape through higher-dimensional states significantly increases their information-carrying capability and network capacity. However, constructing such quantum memories is challenging. Here we report the first experimental realization of a true single-photon-carrying orbital angular momentum stored via electromagnetically induced transparency in a cold atomic ensemble. Our experiments show that the non-classical pair correlation between trigger photon and retrieved photon is retained, and the spatial structure of input and retrieved photons exhibits strong similarity. More importantly, we demonstrate that single-photon coherence is preserved during storage. The ability to store spatial structure at the single-photon level opens the possibility for high-dimensional quantum memories. PMID:24084711

The adaptive safety analysis and monitoring system

NASA Astrophysics Data System (ADS)

Tu, Haiying; Allanach, Jeffrey; Singh, Satnam; Pattipati, Krishna R.; Willett, Peter

2004-09-01

The Adaptive Safety Analysis and Monitoring (ASAM) system is a hybrid model-based software tool for assisting intelligence analysts to identify terrorist threats, to predict possible evolution of the terrorist activities, and to suggest strategies for countering terrorism. The ASAM system provides a distributed processing structure for gathering, sharing, understanding, and using information to assess and predict terrorist network states. In combination with counter-terrorist network models, it can also suggest feasible actions to inhibit potential terrorist threats. In this paper, we will introduce the architecture of the ASAM system, and discuss the hybrid modeling approach embedded in it, viz., Hidden Markov Models (HMMs) to detect and provide soft evidence on the states of terrorist network nodes based on partial and imperfect observations, and Bayesian networks (BNs) to integrate soft evidence from multiple HMMs. The functionality of the ASAM system is illustrated by way of application to the Indian Airlines Hijacking, as modeled from open sources.

3D reconstruction of the porous microstructure of Al2O3-coatings based on sequentially revealed surface data

NASA Astrophysics Data System (ADS)

Loftfield, Nina; Kästner, Markus; Reithmeier, Eduard

2018-06-01

Local and global liquid transport properties correlate strongly with the morphology of porous materials. Therefore, by characterizing the porous network information is indirectly gained on the materials properties. Properties like the open-porosity are easily accessible with techniques like mercury porosimetry. However, the 3D image reconstruction, destructive or non-destructive, holds advantages like an accurate spatially resolved representation of the investigated material. Common 3D data acquisition is done by x-ray microtomography or a combination of focused ion beam based milling and scanning electron microscopy. In this work a reconstruction approach similar to the latter one is implemented. The porous network is reconstructed based on an alternating process of milling the surface by fly cutting and measuring the surface data with a confocal laser scanning microscope. This has the benefit of reconstructing the pore network on the basis of surface height data, measuring the structure boundaries directly. The stack of milled surface height data needs to be registered and the pore structure to be segmented. The segmented pore structure is connected throughout each height layer and afterwards meshed. The investigated materials are porous surface coatings of aluminum oxide for the usage in tribological pairings.

Crystal structures of two mixed-valence copper cyanide complexes with N-methyl­ethylenedi­amine

PubMed Central

Sabatino, Alexander

2017-01-01

The crystal structures of two mixed-valence copper cyanide compounds involving N-methyl­ethylenedi­amine (meen), are described. In compound (I), poly[bis(μ3-cyanido-κ3 C:C:N)tris(μ2-cyanido-κ2 C:N)bis(N-methylethane-1,2-di­amine-κ2 N,N′)tricopper(I)copper(II)], [Cu4(CN)5(C3H10N2)2] or Cu4(CN)5meen2, cyanide groups link CuI atoms into a three-dimensional network containing open channels parallel to the b axis. In the network, two tetra­hedrally bound CuI atoms are bonded by the C atoms of two end-on bridging CN groups to form Cu2(CN)6 moieties with the Cu atoms in close contact at 2.560 (1) Å. Other trigonally bound CuI atoms link these units together to form the network. The CuII atoms, coordinated by two meen units, are covalently linked to the network via a cyanide bridge, and project into the open network channels. In the mol­ecular compound (II), [(N-methylethylenediamine-κ2 N,N′)copper(II)]-μ2-cyanido-κ2 C:N-[bis(cyanido-κC)copper(I)] monohydrate, [Cu2(CN)3(C3H10N2)2]·H2O or Cu2(CN)3meen2·H2O, a CN group connects a CuII atom coordinated by two meen groups with a trigonal–planar CuI atom coordinated by CN groups. The mol­ecules are linked into centrosymmetric dimers via hydrogen bonds to two water mol­ecules. In both compounds, the bridging cyanide between the CuII and CuI atoms has the N atom bonded to CuII and the C atom bonded to CuI, and the CuII atoms are in a square-pyramidal coordination. PMID:28217329

SiGN-SSM: open source parallel software for estimating gene networks with state space models.

PubMed

Tamada, Yoshinori; Yamaguchi, Rui; Imoto, Seiya; Hirose, Osamu; Yoshida, Ryo; Nagasaki, Masao; Miyano, Satoru

2011-04-15

SiGN-SSM is an open-source gene network estimation software able to run in parallel on PCs and massively parallel supercomputers. The software estimates a state space model (SSM), that is a statistical dynamic model suitable for analyzing short time and/or replicated time series gene expression profiles. SiGN-SSM implements a novel parameter constraint effective to stabilize the estimated models. Also, by using a supercomputer, it is able to determine the gene network structure by a statistical permutation test in a practical time. SiGN-SSM is applicable not only to analyzing temporal regulatory dependencies between genes, but also to extracting the differentially regulated genes from time series expression profiles. SiGN-SSM is distributed under GNU Affero General Public Licence (GNU AGPL) version 3 and can be downloaded at http://sign.hgc.jp/signssm/. The pre-compiled binaries for some architectures are available in addition to the source code. The pre-installed binaries are also available on the Human Genome Center supercomputer system. The online manual and the supplementary information of SiGN-SSM is available on our web site. tamada@ims.u-tokyo.ac.jp.

Heterogeniety and Heterarchy: How far can network analyses in Earth and space sciences?

NASA Astrophysics Data System (ADS)

Prabhu, A.; Fox, P. A.; Eleish, A.; Li, C.; Pan, F.; Zhong, H.

2017-12-01

The vast majority of explorations of Earth systems are limited in their ability to effectively explore the most important (often most difficult) problems because they are forced to interconnect at the data-element, or syntactic, level rather than at a higher scientific, or conceptual/ semantic, level. Recent successes in the application of complex network theory and algorithms to minerology, fossils and proteins over billions of years of Earth's history, raise expectations that more general graph-based approaches offer the opportunity for new discoveries = needles instead of haystacks. In the past 10 years in the natural sciences there has substantial progress in providing both specialists and non-specialists the ability to describe in machine readable form, geophysical quantities and relations among them in meaningful and natural ways, effectively breaking the prior syntax barrier. The corresponding open-world semantics and reasoning provide higher-level interconnections. That is, semantics provided around the data structures, using open-source tools, allow for discovery at the knowledge level. This presentation will cover the fundamentals of data-rich network analyses for geosciences, provide illustrative examples in mineral evolution and offer future paths for consideration.

Comprehensive mechanism and structure-sensitivity of ethanol oxidation on platinum: new transition-state searching method for resolving the complex reaction network.

PubMed

Wang, Hui-Fang; Liu, Zhi-Pan

2008-08-20

Ethanol oxidation on Pt is a typical multistep and multiselectivity heterogeneous catalytic process. A comprehensive understanding of this fundamental reaction would greatly benefit design of catalysts for use in direct ethanol fuel cells and the degradation of biomass-derived oxygenates. In this work, the reaction network of ethanol oxidation on different Pt surfaces, including close-packed Pt{111}, stepped Pt{211}, and open Pt{100}, is explored thoroughly with an efficient reaction path searching method, which integrates our new transition-state searching technique with periodic density functional theory calculations. Our new technique enables the location of the transition state and saddle points for most surface reactions simply and efficiently by optimization of local minima. We show that the selectivity of ethanol oxidation on Pt depends markedly on the surface structure, which can be attributed to the structure-sensitivity of two key reaction steps: (i) the initial dehydrogenation of ethanol and (ii) the oxidation of acetyl (CH3CO). On open surface sites, ethanol prefers C-C bond cleavage via strongly adsorbed intermediates (CH2CO or CHCO), which leads to complete oxidation to CO2. However, only partial oxidizations to CH3CHO and CH3COOH occur on Pt{111}. Our mechanism points out that the open surface Pt{100} is the best facet to fully oxidize ethanol at low coverages, which sheds light on the origin of the remarkable catalytic performance of Pt tetrahexahedra nanocrystals found recently. The physical origin of the structure-selectivity is rationalized in terms of both thermodynamics and kinetics. Two fundamental quantities that dictate the selectivity of ethanol oxidation are identified: (i) the ability of surface metal atoms to bond with unsaturated C-containing fragments and (ii) the relative stability of hydroxyl at surface atop sites with respect to other sites.

Association between suicidal symptoms and repeat suicidal behaviour within a sample of hospital-treated suicide attempters.

PubMed

de Beurs, Derek P; van Borkulo, Claudia D; O'Connor, Rory C

2017-05-01

Suicidal behaviour is the end result of the complex relation between many factors which are biological, psychological and environmental in nature. Network analysis is a novel method that may help us better understand the complex association between different factors. To examine the relationship between suicidal symptoms as assessed by the Beck Scale for Suicide Ideation and future suicidal behaviour in patients admitted to hospital following a suicide attempt, using network analysis. Secondary analysis was conducted on previously collected data from a sample of 366 patients who were admitted to a Scottish hospital following a suicide attempt. Network models were estimated to visualise and test the association between baseline symptom network structure and suicidal behaviour at 15-month follow-up. Network analysis showed that the desire for an active attempt was found to be the most central, strongly related suicide symptom. Of the 19 suicide symptoms that were assessed at baseline, 10 symptoms were directly related to repeat suicidal behaviour. When comparing baseline network structure of repeaters ( n =94) with the network of non-repeaters ( n =272), no significant differences were found. Network analysis can help us better understand suicidal behaviour by visualising the complex relation between relevant symptoms and by indicating which symptoms are most central within the network. These insights have theoretical implications as well as informing the assessment and treatment of suicidal behaviour. None. © The Royal College of Psychiatrists 2017. This is an open access article distributed under the terms of the Creative Commons Non-Commercial, No Derivatives (CC BY-NC-ND) license.

Shrink wrapping redox-active crystals of polyoxometalate open frameworks with organic polymers via crystal induced polymerisation.

PubMed

Takashima, Yohei; Miras, Haralampos N; Glatzel, Stefan; Cronin, Leroy

2016-06-14

We report examples of crystal surface modification of polyoxometalate open frameworks whereby the use of pyrrole or aniline as monomers leads to the formation of the corresponding polymers via an oxidative polymerization process initiated by the redox active POM scaffolds. Guest-exchange experiments demonstrate that the polymers can finely tune the guest exchange rate and their structural integrity is retained after the surface modifications. In addition, the formation of polyoxometalate-based self-fabricating tubes by the dissolution of Keggin-based network crystals were also modulated by the polymers, allowing a new type of hybrid inorganic polymer with an organic coating to be fabricated.

Individual brain structure and modelling predict seizure propagation

PubMed Central

Proix, Timothée; Bartolomei, Fabrice; Guye, Maxime; Jirsa, Viktor K.

2017-01-01

Abstract See Lytton (doi:10.1093/awx018) for a scientific commentary on this article. Neural network oscillations are a fundamental mechanism for cognition, perception and consciousness. Consequently, perturbations of network activity play an important role in the pathophysiology of brain disorders. When structural information from non-invasive brain imaging is merged with mathematical modelling, then generative brain network models constitute personalized in silico platforms for the exploration of causal mechanisms of brain function and clinical hypothesis testing. We here demonstrate with the example of drug-resistant epilepsy that patient-specific virtual brain models derived from diffusion magnetic resonance imaging have sufficient predictive power to improve diagnosis and surgery outcome. In partial epilepsy, seizures originate in a local network, the so-called epileptogenic zone, before recruiting other close or distant brain regions. We create personalized large-scale brain networks for 15 patients and simulate the individual seizure propagation patterns. Model validation is performed against the presurgical stereotactic electroencephalography data and the standard-of-care clinical evaluation. We demonstrate that the individual brain models account for the patient seizure propagation patterns, explain the variability in postsurgical success, but do not reliably augment with the use of patient-specific connectivity. Our results show that connectome-based brain network models have the capacity to explain changes in the organization of brain activity as observed in some brain disorders, thus opening up avenues towards discovery of novel clinical interventions. PMID:28364550

3D Actin Network Centerline Extraction with Multiple Active Contours

PubMed Central

Xu, Ting; Vavylonis, Dimitrios; Huang, Xiaolei

2013-01-01

Fluorescence microscopy is frequently used to study two and three dimensional network structures formed by cytoskeletal polymer fibers such as actin filaments and actin cables. While these cytoskeletal structures are often dilute enough to allow imaging of individual filaments or bundles of them, quantitative analysis of these images is challenging. To facilitate quantitative, reproducible and objective analysis of the image data, we propose a semi-automated method to extract actin networks and retrieve their topology in 3D. Our method uses multiple Stretching Open Active Contours (SOACs) that are automatically initialized at image intensity ridges and then evolve along the centerlines of filaments in the network. SOACs can merge, stop at junctions, and reconfigure with others to allow smooth crossing at junctions of filaments. The proposed approach is generally applicable to images of curvilinear networks with low SNR. We demonstrate its potential by extracting the centerlines of synthetic meshwork images, actin networks in 2D Total Internal Reflection Fluorescence Microscopy images, and 3D actin cable meshworks of live fission yeast cells imaged by spinning disk confocal microscopy. Quantitative evaluation of the method using synthetic images shows that for images with SNR above 5.0, the average vertex error measured by the distance between our result and ground truth is 1 voxel, and the average Hausdorff distance is below 10 voxels. PMID:24316442

1-3-A Resolution Structure of Human Glutathione S-Transferase With S-Hexyl Glutathione Bound Reveals Possible Extended Ligandin Binding Site

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

Trong, I.Le; Stenkamp, R.E.; Ibarra, C.

2005-08-22

Cytosolic glutathione S-transferases (GSTs) play a critical role in xenobiotic binding and metabolism, as well as in modulation of oxidative stress. Here, the high-resolution X-ray crystal structures of homodimeric human GSTA1-1 in the apo form and in complex with S-hexyl glutathione (two data sets) are reported at 1.8, 1.5, and 1.3A respectively. At this level of resolution, distinct conformations of the alkyl chain of S-hexyl glutathione are observed, reflecting the nonspecific nature of the hydrophobic substrate binding site (H-site). Also, an extensive network of ordered water, including 75 discrete solvent molecules, traverses the open subunit-subunit interface and connects the glutathionemore » binding sites in each subunit. In the highest-resolution structure, three glycerol moieties lie within this network and directly connect the amino termini of the glutathione molecules. A search for ligand binding sites with the docking program Molecular Operating Environment identified the ordered water network binding site, lined mainly with hydrophobic residues, suggesting an extended ligand binding surface for nonsubstrate ligands, the so-called ligandin site. Finally, detailed comparison of the structures reported here with previously published X-ray structures reveal a possible reaction coordinate for ligand-dependent conformational changes in the active site and the C-terminus.« less

Decompositions of large-scale biological systems based on dynamical properties.

PubMed

Soranzo, Nicola; Ramezani, Fahimeh; Iacono, Giovanni; Altafini, Claudio

2012-01-01

Given a large-scale biological network represented as an influence graph, in this article we investigate possible decompositions of the network aimed at highlighting specific dynamical properties. The first decomposition we study consists in finding a maximal directed acyclic subgraph of the network, which dynamically corresponds to searching for a maximal open-loop subsystem of the given system. Another dynamical property investigated is strong monotonicity. We propose two methods to deal with this property, both aimed at decomposing the system into strongly monotone subsystems, but with different structural characteristics: one method tends to produce a single large strongly monotone component, while the other typically generates a set of smaller disjoint strongly monotone subsystems. Original heuristics for the methods investigated are described in the article. altafini@sissa.it

The tensor network theory library

NASA Astrophysics Data System (ADS)

Al-Assam, S.; Clark, S. R.; Jaksch, D.

2017-09-01

In this technical paper we introduce the tensor network theory (TNT) library—an open-source software project aimed at providing a platform for rapidly developing robust, easy to use and highly optimised code for TNT calculations. The objectives of this paper are (i) to give an overview of the structure of TNT library, and (ii) to help scientists decide whether to use the TNT library in their research. We show how to employ the TNT routines by giving examples of ground-state and dynamical calculations of one-dimensional bosonic lattice system. We also discuss different options for gaining access to the software available at www.tensornetworktheory.org.

Adaptive Suspicious Prevention for Defending DoS Attacks in SDN-Based Convergent Networks

PubMed Central

Dao, Nhu-Ngoc; Kim, Joongheon; Park, Minho; Cho, Sungrae

2016-01-01

The convergent communication network will play an important role as a single platform to unify heterogeneous networks and integrate emerging technologies and existing legacy networks. Although there have been proposed many feasible solutions, they could not become convergent frameworks since they mainly focused on converting functions between various protocols and interfaces in edge networks, and handling functions for multiple services in core networks, e.g., the Multi-protocol Label Switching (MPLS) technique. Software-defined networking (SDN), on the other hand, is expected to be the ideal future for the convergent network since it can provide a controllable, dynamic, and cost-effective network. However, SDN has an original structural vulnerability behind a lot of advantages, which is the centralized control plane. As the brains of the network, a controller manages the whole network, which is attractive to attackers. In this context, we proposes a novel solution called adaptive suspicious prevention (ASP) mechanism to protect the controller from the Denial of Service (DoS) attacks that could incapacitate an SDN. The ASP is integrated with OpenFlow protocol to detect and prevent DoS attacks effectively. Our comprehensive experimental results show that the ASP enhances the resilience of an SDN network against DoS attacks by up to 38%. PMID:27494411

Adaptive Suspicious Prevention for Defending DoS Attacks in SDN-Based Convergent Networks.

PubMed

Dao, Nhu-Ngoc; Kim, Joongheon; Park, Minho; Cho, Sungrae

2016-01-01

The convergent communication network will play an important role as a single platform to unify heterogeneous networks and integrate emerging technologies and existing legacy networks. Although there have been proposed many feasible solutions, they could not become convergent frameworks since they mainly focused on converting functions between various protocols and interfaces in edge networks, and handling functions for multiple services in core networks, e.g., the Multi-protocol Label Switching (MPLS) technique. Software-defined networking (SDN), on the other hand, is expected to be the ideal future for the convergent network since it can provide a controllable, dynamic, and cost-effective network. However, SDN has an original structural vulnerability behind a lot of advantages, which is the centralized control plane. As the brains of the network, a controller manages the whole network, which is attractive to attackers. In this context, we proposes a novel solution called adaptive suspicious prevention (ASP) mechanism to protect the controller from the Denial of Service (DoS) attacks that could incapacitate an SDN. The ASP is integrated with OpenFlow protocol to detect and prevent DoS attacks effectively. Our comprehensive experimental results show that the ASP enhances the resilience of an SDN network against DoS attacks by up to 38%.

Dimensionality and entropy of spontaneous and evoked rate activity

NASA Astrophysics Data System (ADS)

Engelken, Rainer; Wolf, Fred

Cortical circuits exhibit complex activity patterns both spontaneously and evoked by external stimuli. Finding low-dimensional structure in population activity is a challenge. What is the diversity of the collective neural activity and how is it affected by an external stimulus? Using concepts from ergodic theory, we calculate the attractor dimensionality and dynamical entropy production of these networks. We obtain these two canonical measures of the collective network dynamics from the full set of Lyapunov exponents. We consider a randomly-wired firing-rate network that exhibits chaotic rate fluctuations for sufficiently strong synaptic weights. We show that dynamical entropy scales logarithmically with synaptic coupling strength, while the attractor dimensionality saturates. Thus, despite the increasing uncertainty, the diversity of collective activity saturates for strong coupling. We find that a time-varying external stimulus drastically reduces both entropy and dimensionality. Finally, we analytically approximate the full Lyapunov spectrum in several limiting cases by random matrix theory. Our study opens a novel avenue to characterize the complex dynamics of rate networks and the geometric structure of the corresponding high-dimensional chaotic attractor. received funding from Evangelisches Studienwerk Villigst, DFG through CRC 889 and Volkswagen Foundation.

Network geometry with flavor: From complexity to quantum geometry

NASA Astrophysics Data System (ADS)

Bianconi, Ginestra; Rahmede, Christoph

2016-03-01

Network geometry is attracting increasing attention because it has a wide range of applications, ranging from data mining to routing protocols in the Internet. At the same time advances in the understanding of the geometrical properties of networks are essential for further progress in quantum gravity. In network geometry, simplicial complexes describing the interaction between two or more nodes play a special role. In fact these structures can be used to discretize a geometrical d -dimensional space, and for this reason they have already been widely used in quantum gravity. Here we introduce the network geometry with flavor s =-1 ,0 ,1 (NGF) describing simplicial complexes defined in arbitrary dimension d and evolving by a nonequilibrium dynamics. The NGF can generate discrete geometries of different natures, ranging from chains and higher-dimensional manifolds to scale-free networks with small-world properties, scale-free degree distribution, and nontrivial community structure. The NGF admits as limiting cases both the Bianconi-Barabási models for complex networks, the stochastic Apollonian network, and the recently introduced model for complex quantum network manifolds. The thermodynamic properties of NGF reveal that NGF obeys a generalized area law opening a new scenario for formulating its coarse-grained limit. The structure of NGF is strongly dependent on the dimensionality d . In d =1 NGFs grow complex networks for which the preferential attachment mechanism is necessary in order to obtain a scale-free degree distribution. Instead, for NGF with dimension d >1 it is not necessary to have an explicit preferential attachment rule to generate scale-free topologies. We also show that NGF admits a quantum mechanical description in terms of associated quantum network states. Quantum network states evolve by a Markovian dynamics and a quantum network state at time t encodes all possible NGF evolutions up to time t . Interestingly the NGF remains fully classical but its statistical properties reveal the relation to its quantum mechanical description. In fact the δ -dimensional faces of the NGF have generalized degrees that follow either the Fermi-Dirac, Boltzmann, or Bose-Einstein statistics depending on the flavor s and the dimensions d and δ .

Network geometry with flavor: From complexity to quantum geometry.

PubMed

Bianconi, Ginestra; Rahmede, Christoph

2016-03-01

Network geometry is attracting increasing attention because it has a wide range of applications, ranging from data mining to routing protocols in the Internet. At the same time advances in the understanding of the geometrical properties of networks are essential for further progress in quantum gravity. In network geometry, simplicial complexes describing the interaction between two or more nodes play a special role. In fact these structures can be used to discretize a geometrical d-dimensional space, and for this reason they have already been widely used in quantum gravity. Here we introduce the network geometry with flavor s=-1,0,1 (NGF) describing simplicial complexes defined in arbitrary dimension d and evolving by a nonequilibrium dynamics. The NGF can generate discrete geometries of different natures, ranging from chains and higher-dimensional manifolds to scale-free networks with small-world properties, scale-free degree distribution, and nontrivial community structure. The NGF admits as limiting cases both the Bianconi-Barabási models for complex networks, the stochastic Apollonian network, and the recently introduced model for complex quantum network manifolds. The thermodynamic properties of NGF reveal that NGF obeys a generalized area law opening a new scenario for formulating its coarse-grained limit. The structure of NGF is strongly dependent on the dimensionality d. In d=1 NGFs grow complex networks for which the preferential attachment mechanism is necessary in order to obtain a scale-free degree distribution. Instead, for NGF with dimension d>1 it is not necessary to have an explicit preferential attachment rule to generate scale-free topologies. We also show that NGF admits a quantum mechanical description in terms of associated quantum network states. Quantum network states evolve by a Markovian dynamics and a quantum network state at time t encodes all possible NGF evolutions up to time t. Interestingly the NGF remains fully classical but its statistical properties reveal the relation to its quantum mechanical description. In fact the δ-dimensional faces of the NGF have generalized degrees that follow either the Fermi-Dirac, Boltzmann, or Bose-Einstein statistics depending on the flavor s and the dimensions d and δ.

Synaptic plasticity and neuronal refractory time cause scaling behaviour of neuronal avalanches

NASA Astrophysics Data System (ADS)

Michiels van Kessenich, L.; de Arcangelis, L.; Herrmann, H. J.

2016-08-01

Neuronal avalanches measured in vitro and in vivo in different cortical networks consistently exhibit power law behaviour for the size and duration distributions with exponents typical for a mean field self-organized branching process. These exponents are also recovered in neuronal network simulations implementing various neuronal dynamics on different network topologies. They can therefore be considered a very robust feature of spontaneous neuronal activity. Interestingly, this scaling behaviour is also observed on regular lattices in finite dimensions, which raises the question about the origin of the mean field behavior observed experimentally. In this study we provide an answer to this open question by investigating the effect of activity dependent plasticity in combination with the neuronal refractory time in a neuronal network. Results show that the refractory time hinders backward avalanches forcing a directed propagation. Hebbian plastic adaptation plays the role of sculpting these directed avalanche patterns into the topology of the network slowly changing it into a branched structure where loops are marginal.

Synaptic plasticity and neuronal refractory time cause scaling behaviour of neuronal avalanches.

PubMed

Michiels van Kessenich, L; de Arcangelis, L; Herrmann, H J

2016-08-18

Neuronal avalanches measured in vitro and in vivo in different cortical networks consistently exhibit power law behaviour for the size and duration distributions with exponents typical for a mean field self-organized branching process. These exponents are also recovered in neuronal network simulations implementing various neuronal dynamics on different network topologies. They can therefore be considered a very robust feature of spontaneous neuronal activity. Interestingly, this scaling behaviour is also observed on regular lattices in finite dimensions, which raises the question about the origin of the mean field behavior observed experimentally. In this study we provide an answer to this open question by investigating the effect of activity dependent plasticity in combination with the neuronal refractory time in a neuronal network. Results show that the refractory time hinders backward avalanches forcing a directed propagation. Hebbian plastic adaptation plays the role of sculpting these directed avalanche patterns into the topology of the network slowly changing it into a branched structure where loops are marginal.

When Educational Resources Are Open

ERIC Educational Resources Information Center

Breck, Judy

2007-01-01

This article is a partial look at what the future of education might be if educational resources become open online. Intertwingularity is discussed as a general term for what OER will do online. Predictions about an open education future are based on nine quotations from books by popular writers about our networked age. When the network mechanisms…

Recasting Distance Learning with Network-Enabled Open Education: An Interview with Vijay Kumar

ERIC Educational Resources Information Center

Morrison, James L.; Kumar, Vijay

2008-01-01

In an interview with James Morrison, "Innovate's" editor-in-chief, Vijay Kumar describes how rethinking distance learning as network-enabled open education can catalyze a whole new set of learning opportunities. The growing open-education movement has made an increasing number and variety of resources freely available online, including everything…

Open Source in Higher Education: Towards an Understanding of Networked Universities

ERIC Educational Resources Information Center

Quint-Rapoport, Mia

2012-01-01

This article addresses the question of understanding more about networked universities by looking at open source software developers working in academic contexts. It sketches their identities and work as an emerging professional community that both relies upon and develops digitally mediated networks and contributes to the progress of academic…

Massively Open Online Course for Educators (MOOC-Ed) Network Dataset

ERIC Educational Resources Information Center

Kellogg, Shaun; Edelmann, Achim

2015-01-01

This paper presents the Massively Open Online Course for Educators (MOOC-Ed) network dataset. It entails information on two online communication networks resulting from two consecutive offerings of the MOOC called "The Digital Learning Transition in K-12 Schools" in spring and fall 2013. The courses were offered to educators from the USA…

HPC enabled real-time remote processing of laparoscopic surgery

NASA Astrophysics Data System (ADS)

Ronaghi, Zahra; Sapra, Karan; Izard, Ryan; Duffy, Edward; Smith, Melissa C.; Wang, Kuang-Ching; Kwartowitz, David M.

2016-03-01

Laparoscopic surgery is a minimally invasive surgical technique. The benefit of small incisions has a disadvantage of limited visualization of subsurface tissues. Image-guided surgery (IGS) uses pre-operative and intra-operative images to map subsurface structures. One particular laparoscopic system is the daVinci-si robotic surgical system. The video streams generate approximately 360 megabytes of data per second. Real-time processing this large stream of data on a bedside PC, single or dual node setup, has become challenging and a high-performance computing (HPC) environment may not always be available at the point of care. To process this data on remote HPC clusters at the typical 30 frames per second rate, it is required that each 11.9 MB video frame be processed by a server and returned within 1/30th of a second. We have implement and compared performance of compression, segmentation and registration algorithms on Clemson's Palmetto supercomputer using dual NVIDIA K40 GPUs per node. Our computing framework will also enable reliability using replication of computation. We will securely transfer the files to remote HPC clusters utilizing an OpenFlow-based network service, Steroid OpenFlow Service (SOS) that can increase performance of large data transfers over long-distance and high bandwidth networks. As a result, utilizing high-speed OpenFlow- based network to access computing clusters with GPUs will improve surgical procedures by providing real-time medical image processing and laparoscopic data.

A Stigmergy Collaboration Approach in the Open Source Software Developer Community

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

Cui, Xiaohui; Pullum, Laura L; Treadwell, Jim N

2009-01-01

The communication model of some self-organized online communities is significantly different from the traditional social network based community. It is problematic to use social network analysis to analyze the collaboration structure and emergent behaviors in these communities because these communities lack peer-to-peer connections. Stigmergy theory provides an explanation of the collaboration model of these communities. In this research, we present a stigmergy approach for building an agent-based simulation to simulate the collaboration model in the open source software (OSS) developer community. We used a group of actors who collaborate on OSS projects through forums as our frame of reference andmore » investigated how the choices actors make in contributing their work on the projects determines the global status of the whole OSS project. In our simulation, the forum posts serve as the digital pheromone and the modified Pierre-Paul Grasse pheromone model is used for computing the developer agents behavior selection probability.« less

Self-Assembly of Phenylalanine Oligopeptides: Insights from Experiments and Simulations

PubMed Central

Tamamis, Phanourios; Adler-Abramovich, Lihi; Reches, Meital; Marshall, Karen; Sikorski, Pawel; Serpell, Louise; Gazit, Ehud; Archontis, Georgios

2009-01-01

Abstract Studies of peptide-based nanostructures provide general insights into biomolecular self-assembly and can lead material engineering toward technological applications. The diphenylalanine peptide (FF) self-assembles into discrete, hollow, well ordered nanotubes, and its derivatives form nanoassemblies of various morphologies. Here we demonstrate for the first time, to our knowledge, the formation of planar nanostructures with β-sheet content by the triphenylalanine peptide (FFF). We characterize these structures using various microscopy and spectroscopy techniques. We also obtain insights into the interactions and structural properties of the FF and FFF nanostructures by 0.4-μs, implicit-solvent, replica-exchange, molecular-dynamics simulations of aqueous FF and FFF solutions. In the simulations the peptides form aggregates, which often contain open or ring-like peptide networks, as well as elementary and network-containing structures with β-sheet characteristics. The networks are stabilized by polar and nonpolar interactions, and by the surrounding aggregate. In particular, the charged termini of neighbor peptides are involved in hydrogen-bonding interactions and their aromatic side chains form “T-shaped” contacts, as in three-dimensional FF crystals. These interactions may assist the FF and FFF self-assembly at the early stage, and may also stabilize the mature nanostructures. The FFF peptides have higher network propensities and increased aggregate stabilities with respect to FF, which can be interpreted energetically. PMID:19527662

Multicausal systems ask for multicausal approaches: A network perspective on subjective well-being in individuals with autism spectrum disorder.

PubMed

Deserno, Marie K; Borsboom, Denny; Begeer, Sander; Geurts, Hilde M

2017-11-01

Given the heterogeneity of autism spectrum disorder, an important limitation of much autism spectrum disorder research is that outcome measures are statistically modeled as separate dependent variables. Often, their multivariate structure is either ignored or treated as a nuisance. This study aims to lift this limitation by applying network analysis to explicate the multivariate pattern of risk and success factors for subjective well-being in autism spectrum disorder. We estimated a network structure for 27 potential factors in 2341 individuals with autism spectrum disorder to assess the centrality of specific life domains and their importance for well-being. The data included both self- and proxy-reported information. We identified social satisfaction and societal contribution as the strongest direct paths to subjective well-being. The results suggest that an important contribution to well-being lies in resources that allow the individual to engage in social relations, which influence well-being directly. Factors most important in determining the network's structure include self-reported IQ, living situation, level of daily activity, and happiness. Number of family members with autism spectrum disorder and openness about one's diagnosis are least important of all factors for subjective well-being. These types of results can serve as a roadmap for interventions directed at improving the well-being of individuals with autism spectrum disorder.

First Observation of Photoinduced Magnetization for the Cyano-Bridged 3d 4f Heterobimetallic Assembly Nd(DMF)4(H2O)3(μ-CN)Fe(CN)5ṡH2O (DMF=N,N-Dimethylformamide)

NASA Astrophysics Data System (ADS)

Li, Guangming; Akitsu, Takashiro; Sato, Osamu; Einaga, Yasuaki

2004-12-01

Photoinduced magnetization of the cyano-bridged 3d 4f hetero-bimetallic assembly Nd (DMF)4(H2O)3(μ-CN)Fe(CN)5ṡH2O (1) (DMF=N,N-dimethylformamide) is described in this paper. The χM T values are enhanced by about 45% after UV light illumination in the temperature range of 5 50 K. We propose that UV light illumination induces a structural distortion in 1. This small structural change is propagated by molecular interactions in the inorganic network. Furthermore, the cooperativity resulting from the molecular interaction functions to increase the activation energy of the relaxation processes, which makes observation of the photoexcited state possible. The flexible network structure through the hydrogen bonds in 1 plays an essential role for the photoinduced phenomenon. This finding may open up a new domain for developing molecule-based magnetic materials.

Capturing the DSM-5 Alternative Personality Disorder Model Traits in the Five-Factor Model's Nomological Net.

PubMed

Suzuki, Takakuni; Griffin, Sarah A; Samuel, Douglas B

2017-04-01

Several studies have shown structural and statistical similarities between the Diagnostic and Statistical Manual of Mental Disorders (5th ed.; DSM-5) alternative personality disorder model and the Five-Factor Model (FFM). However, no study to date has evaluated the nomological network similarities between the two models. The relations of the Revised NEO Personality Inventory (NEO PI-R) and the Personality Inventory for DSM-5 (PID-5) with relevant criterion variables were examined in a sample of 336 undergraduate students (M age  = 19.4; 59.8% female). The resulting profiles for each instrument were statistically compared for similarity. Four of the five domains of the two models have highly similar nomological networks, with the exception being FFM Openness to Experience and PID-5 Psychoticism. Further probing of that pair suggested that the NEO PI-R domain scores obscured meaningful similarity between PID-5 Psychoticism and specific aspects and lower-order facets of Openness. The results support the notion that the DSM-5 alternative personality disorder model trait domains represent variants of the FFM domains. Similarities of Openness and Psychoticism domains were supported when the lower-order aspects and facets of Openness domain were considered. The findings support the view that the DSM-5 trait model represents an instantiation of the FFM. © 2015 Wiley Periodicals, Inc.

Inter-subunit interactions across the upper voltage sensing-pore domain interface contribute to the concerted pore opening transition of Kv channels.

PubMed

Shem-Ad, Tzilhav; Irit, Orr; Yifrach, Ofer

2013-01-01

The tight electro-mechanical coupling between the voltage-sensing and pore domains of Kv channels lies at the heart of their fundamental roles in electrical signaling. Structural data have identified two voltage sensor pore inter-domain interaction surfaces, thus providing a framework to explain the molecular basis for the tight coupling of these domains. While the contribution of the intra-subunit lower domain interface to the electro-mechanical coupling that underlies channel opening is relatively well understood, the contribution of the inter-subunit upper interface to channel gating is not yet clear. Relying on energy perturbation and thermodynamic coupling analyses of tandem-dimeric Shaker Kv channels, we show that mutation of upper interface residues from both sides of the voltage sensor-pore domain interface stabilizes the closed channel state. These mutations, however, do not affect slow inactivation gating. We, moreover, find that upper interface residues form a network of state-dependent interactions that stabilize the open channel state. Finally, we note that the observed residue interaction network does not change during slow inactivation gating. The upper voltage sensing-pore interaction surface thus only undergoes conformational rearrangements during channel activation gating. We suggest that inter-subunit interactions across the upper domain interface mediate allosteric communication between channel subunits that contributes to the concerted nature of the late pore opening transition of Kv channels.

Foam structure :from soap froth to solid foams.

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

Kraynik, Andrew Michael

2003-01-01

The properties of solid foams depend on their structure, which usually evolves in the fluid state as gas bubbles expand to form polyhedral cells. The characteristic feature of foam structure-randomly packed cells of different sizes and shapes-is examined in this article by considering soap froth. This material can be modeled as a network of minimal surfaces that divide space into polyhedral cells. The cell-level geometry of random soap froth is calculated with Brakke's Surface Evolver software. The distribution of cell volumes ranges from monodisperse to highly polydisperse. Topological and geometric properties, such as surface area and edge length, of themore » entire foam and individual cells, are discussed. The shape of struts in solid foams is related to Plateau borders in liquid foams and calculated for different volume fractions of material. The models of soap froth are used as templates to produce finite element models of open-cell foams. Three-dimensional images of open-cell foams obtained with x-ray microtomography allow virtual reconstruction of skeletal structures that compare well with the Surface Evolver simulations of soap-froth geometry.« less

Aligning Biomolecular Networks Using Modular Graph Kernels

NASA Astrophysics Data System (ADS)

Towfic, Fadi; Greenlee, M. Heather West; Honavar, Vasant

Comparative analysis of biomolecular networks constructed using measurements from different conditions, tissues, and organisms offer a powerful approach to understanding the structure, function, dynamics, and evolution of complex biological systems. We explore a class of algorithms for aligning large biomolecular networks by breaking down such networks into subgraphs and computing the alignment of the networks based on the alignment of their subgraphs. The resulting subnetworks are compared using graph kernels as scoring functions. We provide implementations of the resulting algorithms as part of BiNA, an open source biomolecular network alignment toolkit. Our experiments using Drosophila melanogaster, Saccharomyces cerevisiae, Mus musculus and Homo sapiens protein-protein interaction networks extracted from the DIP repository of protein-protein interaction data demonstrate that the performance of the proposed algorithms (as measured by % GO term enrichment of subnetworks identified by the alignment) is competitive with some of the state-of-the-art algorithms for pair-wise alignment of large protein-protein interaction networks. Our results also show that the inter-species similarity scores computed based on graph kernels can be used to cluster the species into a species tree that is consistent with the known phylogenetic relationships among the species.

Online social network data as sociometric markers.

PubMed

Binder, Jens F; Buglass, Sarah L; Betts, Lucy R; Underwood, Jean D M

2017-10-01

Data from online social networks carry enormous potential for psychological research, yet their use and the ethical implications thereof are currently hotly debated. The present work aims to outline in detail the unique information richness of this data type and, in doing so, to support researchers when deciding on ethically appropriate ways of collecting, storing, publishing, and sharing data from online sources. Focusing on the very nature of social networks, their structural characteristics, and depth of information, we provide a detailed and accessible account of the challenges associated with data management and data storage. In particular, the general nonanonymity of network data sets is discussed, and an approach is developed to quantify the level of uniqueness that a particular online network bestows upon the individual maintaining it. Using graph enumeration techniques, we show that comparatively sparse information on a network is suitable as a sociometric marker that allows for the identification of an individual from the global population of online users. The impossibility of anonymizing specific types of network data carries implications for ethical guidelines and research practice. At the same time, network uniqueness opens up opportunities for novel research in psychology. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Weaving a knowledge network for Deep Carbon Science

NASA Astrophysics Data System (ADS)

Ma, Xiaogang; West, Patrick; Zednik, Stephan; Erickson, John; Eleish, Ahmed; Chen, Yu; Wang, Han; Zhong, Hao; Fox, Peter

2017-05-01

Geoscience researchers are increasingly dependent on informatics and the Web to conduct their research. Geoscience is one of the first domains that take lead in initiatives such as open data, open code, open access, and open collections, which comprise key topics of Open Science in academia. The meaning of being open can be understood at two levels. The lower level is to make data, code, sample collections and publications, etc. freely accessible online and allow reuse, modification and sharing. The higher level is the annotation and connection between those resources to establish a network for collaborative scientific research. In the data science component of the Deep Carbon Observatory (DCO), we have leveraged state-of-the-art information technologies and existing online resources to deploy a web portal for the over 1000 researchers in the DCO community. An initial aim of the portal is to keep track of all research and outputs related to the DCO community. Further, we intend for the portal to establish a knowledge network, which supports various stages of an open scientific process within and beyond the DCO community. Annotation and linking are the key characteristics of the knowledge network. Not only are key assets, including DCO data and methods, published in an open and inter-linked fashion, but the people, organizations, groups, grants, projects, samples, field sites, instruments, software programs, activities, meetings, etc. are recorded and connected to each other through relationships based on well-defined, formal conceptual models. The network promotes collaboration among DCO participants, improves the openness and reproducibility of carbon-related research, facilitates accreditation to resource contributors, and eventually stimulates new ideas and findings in deep carbon-related studies.

Fiber optic sensor and method for making

DOEpatents

Vartuli, James Scott; Bousman, Kenneth Sherwood; Deng, Kung-Li; McEvoy, Kevin Paul; Xia, Hua

2010-05-18

A fiber optic sensor including a fiber having a modified surface integral with the fiber wherein the modified surface includes an open pore network with optical agents dispersed within the open pores of the open pore network. Methods for preparing the fiber optic sensor are also provided. The fiber optic sensors can withstand high temperatures and harsh environments.

Effects of temporal correlations in social multiplex networks.

PubMed

Starnini, Michele; Baronchelli, Andrea; Pastor-Satorras, Romualdo

2017-08-17

Multi-layered networks represent a major advance in the description of natural complex systems, and their study has shed light on new physical phenomena. Despite its importance, however, the role of the temporal dimension in their structure and function has not been investigated in much detail so far. Here we study the temporal correlations between layers exhibited by real social multiplex networks. At a basic level, the presence of such correlations implies a certain degree of predictability in the contact pattern, as we quantify by an extension of the entropy and mutual information analyses proposed for the single-layer case. At a different level, we demonstrate that temporal correlations are a signature of a 'multitasking' behavior of network agents, characterized by a higher level of switching between different social activities than expected in a uncorrelated pattern. Moreover, temporal correlations significantly affect the dynamics of coupled epidemic processes unfolding on the network. Our work opens the way for the systematic study of temporal multiplex networks and we anticipate it will be of interest to researchers in a broad array of fields.

Remote Sensing of Subsurface Fractures in the Otway Basin, South Australia

NASA Astrophysics Data System (ADS)

Bailey, Adam; King, Rosalind; Holford, Simon; Hand, Martin

2013-04-01

A detailed understanding of naturally occurring fracture networks within the subsurface is becoming increasingly important to the energy sector, as the focus of exploration has expanded to include unconventional reservoirs such as coal seam gas, shale gas, tight gas, and engineered geothermal systems. Successful production from such reservoirs, where primary porosity and permeability is often negligible, is heavily reliant on structural permeability provided by naturally occurring and induced fracture networks, permeability, which is often not provided for through primary porosity and permeability. In this study the Penola Trough, located within the onshore Otway Basin in South Australia, is presented as a case study for remotely detecting and defining subsurface fracture networks that may contribute to secondary permeability. This area is prospective for shale and tight gas and geothermal energy. The existence and nature of natural fractures is verified through an integrated analysis of geophysical logs (including wellbore image logs) and 3D seismic data. Wellbore image logs from 11 petroleum wells within the Penola Trough were interpreted for both stress indicators and natural fractures. A total of 507 naturally occurring fractures were identified, striking approximately WNE-ESE. Fractures which are aligned in the in-situ stress field are optimally oriented for reactivation, and are hence likely to be open to fluid flow. Fractures are identifiable as being either resistive or conductive sinusoids on the resistivity image logs used in this study. Resistive fractures, of which 239 were identified, are considered to be cemented with electrically resistive cements (such as quartz or calcite) and thus closed to fluid flow. Conductive fractures, of which 268 were identified, are considered to be uncemented and open to fluid flow, and thus important to geothermal exploration. Fracture susceptibility diagrams constructed for the identified fractures illustrate that the conductive fractures are optimally oriented for reactivation in the present-day strike-slip fault regime, and so are likely to be open to fluid flow. To gain an understanding of the broader extent of these natural fractures, it is necessary to analyse more regional 3D seismic data. It is well documented that fault and fracture networks like those generally observed in image logs lie well below seismic amplitude resolution, making them difficult to observe directly on amplitude data. However, seismic attributes can be calculated to provide some information on sub-seismic scale structural and stratigraphic features. Using the merged Balnaves/Haselgrove 3D seismic cube acquired over the Penola Trough, attribute maps of complex multi-trace dip-steered coherency and most positive curvature, among others, were used to document the presence of discontinuities within the seismic data which area likely to represent natural fractures, and to best constrain the likely extent of the fracture network which they form. The resulting fracture network model displays relatively good connectivity surrounding structural features intersecting the studied horizons, although large areas lacking significant discontinuities are observed. These areas make it unlikely that the fracture network contributes to permeability on a basin-wide scale, though observed features are optimally oriented for reactivation under contemporary stress conditions and are thus likely to provide at least local increases in permeability.

Structural-Diagenetic Controls on Fracture Opening in Tight Gas Sandstone Reservoirs, Alberta Foothills

NASA Astrophysics Data System (ADS)

Ukar, Estibalitz; Eichhubl, Peter; Fall, Andras; Hooker, John

2013-04-01

In tight gas reservoirs, understanding the characteristics, orientation and distribution of natural open fractures, and how these relate to the structural and stratigraphic setting are important for exploration and production. Outcrops provide the opportunity to sample fracture characteristics that would otherwise be unknown due to the limitations of sampling by cores and well logs. However, fractures in exhumed outcrops may not be representative of fractures in the reservoir because of differences in burial and exhumation history. Appropriate outcrop analogs of producing reservoirs with comparable geologic history, structural setting, fracture networks, and diagenetic attributes are desirable but rare. The Jurassic to Lower Cretaceous Nikanassin Formation from the Alberta Foothills produces gas at commercial rates where it contains a network of open fractures. Fractures from outcrops have the same diagenetic attributes as those observed in cores <100 km away, thus offering an ideal opportunity to 1) evaluate the distribution and characteristics of opening mode fractures relative to fold cores, hinges and limbs, 2) compare the distribution and attributes of fractures in outcrop vs. core samples, 3) estimate the timing of fracture formation relative to the evolution of the fold-and-thrust belt, and 4) estimate the degradation of fracture porosity due to postkinematic cementation. Cathodoluminescence images of cemented fractures in both outcrop and core samples reveal several generations of quartz and ankerite cement that is synkinematic and postkinematic relative to fracture opening. Crack-seal textures in synkinematic quartz are ubiquitous, and well-developed cement bridges abundant. Fracture porosity may be preserved in fractures wider than ~100 microns. 1-D scanlines in outcrop and core samples indicate fractures are most abundant within small parasitic folds within larger, tight, mesoscopic folds. Fracture intensity is lower away from parasitic folds; intensity progressively decreases from the faulted cores of mesoscopic folds to their forelimbs, with lowest intensities within relatively undeformed backlimb strata. Fracture apertures locally increase adjacent to reverse faults without an overall increase in fracture frequency. Fluid inclusion analyses of crack-seal quartz cement indicate both aqueous and methane-rich inclusions are present. Homogenization temperatures of two-phase inclusions indicate synkinematic fracture cement precipitation and fracture opening under conditions at or near maximum burial of 190-210°C in core samples, and 120-160°C in outcrop samples. In comparison with the fracture evolution in other, less deformed tight-gas sandstone reservoirs such as the Piceance and East Texas basins where fracture opening is primarily controlled by gas generation, gas charge, and pore fluid pressure, these results suggest a strong control of regional tectonic processes on fracture generation. In conjunction with timing and rate of gas charge, rates of fracture cement growth, and stratigraphic-lithological controls, these processes determine the overall distribution of open fractures in these reservoirs.

Structural-Diagenetic Controls on Fracture Opening in Tight Gas Sandstone Reservoirs, Alberta Foothills

NASA Astrophysics Data System (ADS)

Ukar, E.; Eichhubl, P.; Fall, A.; Hooker, J. N.

2012-12-01

In tight gas reservoirs, understanding the characteristics, orientation and distribution of natural open fractures, and how these relate to the structural and stratigraphic setting are important for exploration and production. Outcrops provide the opportunity to sample fracture characteristics that would otherwise be unknown due to the limitations of sampling by cores and well logs. However, fractures in exhumed outcrops may not be representative of fractures in the reservoir because of differences in burial and exhumation history. Appropriate outcrop analogs of producing reservoirs with comparable geologic history, structural setting, fracture networks, and diagenetic attributes are desirable but rare. The Jurassic to Lower Cretaceous Nikanassin Formation from the Alberta Foothills produces gas at commercial rates where it contains a network of open fractures. Fractures from outcrops have the same diagenetic attributes as those observed in cores <100 km away, thus offering an ideal opportunity to 1) evaluate the distribution and characteristics of opening mode fractures relative to fold cores, hinges and limbs, 2) compare the distribution and attributes of fractures in outcrop vs. core samples, 3) estimate the timing of fracture formation relative to the evolution of the fold-and-thrust belt, and 4) estimate the degradation of fracture porosity due to postkinematic cementation. Cathodoluminescence images of cemented fractures in both outcrop and core samples reveal several generations of quartz and ankerite cement that is synkinematic and postkinematic relative to fracture opening. Crack-seal textures in synkinematic quartz are ubiquitous, and well-developed cement bridges abundant. Fracture porosity may be preserved in fractures wider than ~100 microns. 1-D scanlines in outcrop and core samples indicate fractures are most abundant within small parasitic folds within larger, tight, mesoscopic folds. Fracture intensity is lower away from parasitic folds; intensity progressively decreases from the faulted cores of mesoscopic folds to their forelimbs, with lowest intensities within relatively undeformed backlimb strata. Fracture apertures locally increase adjacent to reverse faults without an overall increase in fracture frequency. Fluid inclusion analyses of crack-seal quartz cement indicate both aqueous and methane-rich inclusions are present. Homogenization temperatures of two-phase inclusions indicate synkinematic fracture cement precipitation and fracture opening under conditions at or near maximum burial of 190-210°C in core samples, and 120-160°C in outcrop samples. In comparison with the fracture evolution in other, less deformed tight-gas sandstone reservoirs such as the Piceance and East Texas basins where fracture opening is primarily controlled by gas generation, gas charge, and pore fluid pressure, these results suggest a strong control of regional tectonic processes on fracture generation. In conjunction with timing and rate of gas charge, rates of fracture cement growth, and stratigraphic-lithological controls, these processes determine the overall distribution of open fractures in these reservoirs.

Virtualized Networks and Virtualized Optical Line Terminal (vOLT)

NASA Astrophysics Data System (ADS)

Ma, Jonathan; Israel, Stephen

2017-03-01

The success of the Internet and the proliferation of the Internet of Things (IoT) devices is forcing telecommunications carriers to re-architecture a central office as a datacenter (CORD) so as to bring the datacenter economics and cloud agility to a central office (CO). The Open Network Operating System (ONOS) is the first open-source software-defined network (SDN) operating system which is capable of managing and controlling network, computing, and storage resources to support CORD infrastructure and network virtualization. The virtualized Optical Line Termination (vOLT) is one of the key components in such virtualized networks.

Integration of Sensors, Controllers and Instruments Using a Novel OPC Architecture

PubMed Central

2017-01-01

The interconnection between sensors, controllers and instruments through a communication network plays a vital role in the performance and effectiveness of a control system. Since its inception in the 90s, the Object Linking and Embedding for Process Control (OPC) protocol has provided open connectivity for monitoring and automation systems. It has been widely used in several environments such as industrial facilities, building and energy automation, engineering education and many others. This paper presents a novel OPC-based architecture to implement automation systems devoted to R&D and educational activities. The proposal is a novel conceptual framework, structured into four functional layers where the diverse components are categorized aiming to foster the systematic design and implementation of automation systems involving OPC communication. Due to the benefits of OPC, the proposed architecture provides features like open connectivity, reliability, scalability, and flexibility. Furthermore, four successful experimental applications of such an architecture, developed at the University of Extremadura (UEX), are reported. These cases are a proof of concept of the ability of this architecture to support interoperability for different domains. Namely, the automation of energy systems like a smart microgrid and photobioreactor facilities, the implementation of a network-accessible industrial laboratory and the development of an educational hardware-in-the-loop platform are described. All cases include a Programmable Logic Controller (PLC) to automate and control the plant behavior, which exchanges operative data (measurements and signals) with a multiplicity of sensors, instruments and supervisory systems under the structure of the novel OPC architecture. Finally, the main conclusions and open research directions are highlighted. PMID:28654002

Integration of Sensors, Controllers and Instruments Using a Novel OPC Architecture.

PubMed

González, Isaías; Calderón, Antonio José; Barragán, Antonio Javier; Andújar, José Manuel

2017-06-27

The interconnection between sensors, controllers and instruments through a communication network plays a vital role in the performance and effectiveness of a control system. Since its inception in the 90s, the Object Linking and Embedding for Process Control (OPC) protocol has provided open connectivity for monitoring and automation systems. It has been widely used in several environments such as industrial facilities, building and energy automation, engineering education and many others. This paper presents a novel OPC-based architecture to implement automation systems devoted to R&D and educational activities. The proposal is a novel conceptual framework, structured into four functional layers where the diverse components are categorized aiming to foster the systematic design and implementation of automation systems involving OPC communication. Due to the benefits of OPC, the proposed architecture provides features like open connectivity, reliability, scalability, and flexibility. Furthermore, four successful experimental applications of such an architecture, developed at the University of Extremadura (UEX), are reported. These cases are a proof of concept of the ability of this architecture to support interoperability for different domains. Namely, the automation of energy systems like a smart microgrid and photobioreactor facilities, the implementation of a network-accessible industrial laboratory and the development of an educational hardware-in-the-loop platform are described. All cases include a Programmable Logic Controller (PLC) to automate and control the plant behavior, which exchanges operative data (measurements and signals) with a multiplicity of sensors, instruments and supervisory systems under the structure of the novel OPC architecture. Finally, the main conclusions and open research directions are highlighted.

Open quantum generalisation of Hopfield neural networks

NASA Astrophysics Data System (ADS)

Rotondo, P.; Marcuzzi, M.; Garrahan, J. P.; Lesanovsky, I.; Müller, M.

2018-03-01

We propose a new framework to understand how quantum effects may impact on the dynamics of neural networks. We implement the dynamics of neural networks in terms of Markovian open quantum systems, which allows us to treat thermal and quantum coherent effects on the same footing. In particular, we propose an open quantum generalisation of the Hopfield neural network, the simplest toy model of associative memory. We determine its phase diagram and show that quantum fluctuations give rise to a qualitatively new non-equilibrium phase. This novel phase is characterised by limit cycles corresponding to high-dimensional stationary manifolds that may be regarded as a generalisation of storage patterns to the quantum domain.

The dynamics of information-driven coordination phenomena: A transfer entropy analysis

PubMed Central

Borge-Holthoefer, Javier; Perra, Nicola; Gonçalves, Bruno; González-Bailón, Sandra; Arenas, Alex; Moreno, Yamir; Vespignani, Alessandro

2016-01-01

Data from social media provide unprecedented opportunities to investigate the processes that govern the dynamics of collective social phenomena. We consider an information theoretical approach to define and measure the temporal and structural signatures typical of collective social events as they arise and gain prominence. We use the symbolic transfer entropy analysis of microblogging time series to extract directed networks of influence among geolocalized subunits in social systems. This methodology captures the emergence of system-level dynamics close to the onset of socially relevant collective phenomena. The framework is validated against a detailed empirical analysis of five case studies. In particular, we identify a change in the characteristic time scale of the information transfer that flags the onset of information-driven collective phenomena. Furthermore, our approach identifies an order-disorder transition in the directed network of influence between social subunits. In the absence of clear exogenous driving, social collective phenomena can be represented as endogenously driven structural transitions of the information transfer network. This study provides results that can help define models and predictive algorithms for the analysis of societal events based on open source data. PMID:27051875

The dynamics of information-driven coordination phenomena: A transfer entropy analysis.

PubMed

Borge-Holthoefer, Javier; Perra, Nicola; Gonçalves, Bruno; González-Bailón, Sandra; Arenas, Alex; Moreno, Yamir; Vespignani, Alessandro

2016-04-01

Data from social media provide unprecedented opportunities to investigate the processes that govern the dynamics of collective social phenomena. We consider an information theoretical approach to define and measure the temporal and structural signatures typical of collective social events as they arise and gain prominence. We use the symbolic transfer entropy analysis of microblogging time series to extract directed networks of influence among geolocalized subunits in social systems. This methodology captures the emergence of system-level dynamics close to the onset of socially relevant collective phenomena. The framework is validated against a detailed empirical analysis of five case studies. In particular, we identify a change in the characteristic time scale of the information transfer that flags the onset of information-driven collective phenomena. Furthermore, our approach identifies an order-disorder transition in the directed network of influence between social subunits. In the absence of clear exogenous driving, social collective phenomena can be represented as endogenously driven structural transitions of the information transfer network. This study provides results that can help define models and predictive algorithms for the analysis of societal events based on open source data.

Multimodal Neuroimaging in Schizophrenia: Description and Dissemination.

PubMed

Aine, C J; Bockholt, H J; Bustillo, J R; Cañive, J M; Caprihan, A; Gasparovic, C; Hanlon, F M; Houck, J M; Jung, R E; Lauriello, J; Liu, J; Mayer, A R; Perrone-Bizzozero, N I; Posse, S; Stephen, J M; Turner, J A; Clark, V P; Calhoun, Vince D

2017-10-01

In this paper we describe an open-access collection of multimodal neuroimaging data in schizophrenia for release to the community. Data were acquired from approximately 100 patients with schizophrenia and 100 age-matched controls during rest as well as several task activation paradigms targeting a hierarchy of cognitive constructs. Neuroimaging data include structural MRI, functional MRI, diffusion MRI, MR spectroscopic imaging, and magnetoencephalography. For three of the hypothesis-driven projects, task activation paradigms were acquired on subsets of ~200 volunteers which examined a range of sensory and cognitive processes (e.g., auditory sensory gating, auditory/visual multisensory integration, visual transverse patterning). Neuropsychological data were also acquired and genetic material via saliva samples were collected from most of the participants and have been typed for both genome-wide polymorphism data as well as genome-wide methylation data. Some results are also presented from the individual studies as well as from our data-driven multimodal analyses (e.g., multimodal examinations of network structure and network dynamics and multitask fMRI data analysis across projects). All data will be released through the Mind Research Network's collaborative informatics and neuroimaging suite (COINS).

Ad Hoc Networking for Unmanned Ground Vehicles: Design and Evaluation at Command, Control, Communications, Intelligence, Surveillance and Reconnaissance On-the-Move

DTIC Science & Technology

2006-11-01

software components used in the ad hoc nodes for the C4ISR OTM experiment were OLSRD, an open-source proactive MANET routing software, and OpenVPN , an...developed by Mike Baker (openwrt.org). 6OpenVPN is a trademark of OpenVPN Solutions LLC. 6 Secure communications in the MANET are achieved with...encryption provided by Wired Equivalent Privacy (WEP) and OpenVPN . The WEP protocol, which is part of the IEEE 802.11 wireless networking standard

Evolutionary dynamics of incubation periods

PubMed Central

Ottino-Loffler, Bertrand; Scott, Jacob G

2017-01-01

The incubation period for typhoid, polio, measles, leukemia and many other diseases follows a right-skewed, approximately lognormal distribution. Although this pattern was discovered more than sixty years ago, it remains an open question to explain its ubiquity. Here, we propose an explanation based on evolutionary dynamics on graphs. For simple models of a mutant or pathogen invading a network-structured population of healthy cells, we show that skewed distributions of incubation periods emerge for a wide range of assumptions about invader fitness, competition dynamics, and network structure. The skewness stems from stochastic mechanisms associated with two classic problems in probability theory: the coupon collector and the random walk. Unlike previous explanations that rely crucially on heterogeneity, our results hold even for homogeneous populations. Thus, we predict that two equally healthy individuals subjected to equal doses of equally pathogenic agents may, by chance alone, show remarkably different time courses of disease. PMID:29266000

Evolutionary dynamics of incubation periods.

PubMed

Ottino-Loffler, Bertrand; Scott, Jacob G; Strogatz, Steven H

2017-12-21

The incubation period for typhoid, polio, measles, leukemia and many other diseases follows a right-skewed, approximately lognormal distribution. Although this pattern was discovered more than sixty years ago, it remains an open question to explain its ubiquity. Here, we propose an explanation based on evolutionary dynamics on graphs. For simple models of a mutant or pathogen invading a network-structured population of healthy cells, we show that skewed distributions of incubation periods emerge for a wide range of assumptions about invader fitness, competition dynamics, and network structure. The skewness stems from stochastic mechanisms associated with two classic problems in probability theory: the coupon collector and the random walk. Unlike previous explanations that rely crucially on heterogeneity, our results hold even for homogeneous populations. Thus, we predict that two equally healthy individuals subjected to equal doses of equally pathogenic agents may, by chance alone, show remarkably different time courses of disease.

Long-term reorganization of structural brain networks in a rabbit model of intrauterine growth restriction.

PubMed

Batalle, Dafnis; Muñoz-Moreno, Emma; Arbat-Plana, Ariadna; Illa, Miriam; Figueras, Francesc; Eixarch, Elisenda; Gratacos, Eduard

2014-10-15

Characterization of brain changes produced by intrauterine growth restriction (IUGR) is among the main challenges of modern fetal medicine and pediatrics. This condition affects 5-10% of all pregnancies and is associated with a wide range of neurodevelopmental disorders. Better understanding of the brain reorganization produced by IUGR opens a window of opportunity to find potential imaging biomarkers in order to identify the infants with a high risk of having neurodevelopmental problems and apply therapies to improve their outcomes. Structural brain networks obtained from diffusion magnetic resonance imaging (MRI) is a promising tool to study brain reorganization and to be used as a biomarker of neurodevelopmental alterations. In the present study this technique is applied to a rabbit animal model of IUGR, which presents some advantages including a controlled environment and the possibility to obtain high quality MRI with long acquisition times. Using a Q-Ball diffusion model, and a previously published rabbit brain MRI atlas, structural brain networks of 15 IUGR and 14 control rabbits at 70 days of age (equivalent to pre-adolescence human age) were obtained. The analysis of graph theory features showed a decreased network infrastructure (degree and binary global efficiency) associated with IUGR condition and a set of generalized fractional anisotropy (GFA) weighted measures associated with abnormal neurobehavior. Interestingly, when assessing the brain network organization independently of network infrastructure by means of normalized networks, IUGR showed increased global and local efficiencies. We hypothesize that this effect could reflect a compensatory response to reduced infrastructure in IUGR. These results present new evidence on the long-term persistence of the brain reorganization produced by IUGR that could underlie behavioral and developmental alterations previously described. The described changes in network organization have the potential to be used as biomarkers to monitor brain changes produced by experimental therapies in IUGR animal model. Copyright © 2014 Elsevier Inc. All rights reserved.

Inner and Outer Recursive Neural Networks for Chemoinformatics Applications.

PubMed

Urban, Gregor; Subrahmanya, Niranjan; Baldi, Pierre

2018-02-26

Deep learning methods applied to problems in chemoinformatics often require the use of recursive neural networks to handle data with graphical structure and variable size. We present a useful classification of recursive neural network approaches into two classes, the inner and outer approach. The inner approach uses recursion inside the underlying graph, to essentially "crawl" the edges of the graph, while the outer approach uses recursion outside the underlying graph, to aggregate information over progressively longer distances in an orthogonal direction. We illustrate the inner and outer approaches on several examples. More importantly, we provide open-source implementations [available at www.github.com/Chemoinformatics/InnerOuterRNN and cdb.ics.uci.edu ] for both approaches in Tensorflow which can be used in combination with training data to produce efficient models for predicting the physical, chemical, and biological properties of small molecules.

Association between suicidal symptoms and repeat suicidal behaviour within a sample of hospital-treated suicide attempters

PubMed Central

van Borkulo, Claudia D.; O’Connor, Rory C.

2017-01-01

Background Suicidal behaviour is the end result of the complex relation between many factors which are biological, psychological and environmental in nature. Network analysis is a novel method that may help us better understand the complex association between different factors. Aims To examine the relationship between suicidal symptoms as assessed by the Beck Scale for Suicide Ideation and future suicidal behaviour in patients admitted to hospital following a suicide attempt, using network analysis. Method Secondary analysis was conducted on previously collected data from a sample of 366 patients who were admitted to a Scottish hospital following a suicide attempt. Network models were estimated to visualise and test the association between baseline symptom network structure and suicidal behaviour at 15-month follow-up. Results Network analysis showed that the desire for an active attempt was found to be the most central, strongly related suicide symptom. Of the 19 suicide symptoms that were assessed at baseline, 10 symptoms were directly related to repeat suicidal behaviour. When comparing baseline network structure of repeaters (n=94) with the network of non-repeaters (n=272), no significant differences were found. Conclusions Network analysis can help us better understand suicidal behaviour by visualising the complex relation between relevant symptoms and by indicating which symptoms are most central within the network. These insights have theoretical implications as well as informing the assessment and treatment of suicidal behaviour. Declaration of interest None. Copyright and usage © The Royal College of Psychiatrists 2017. This is an open access article distributed under the terms of the Creative Commons Non-Commercial, No Derivatives (CC BY-NC-ND) license. PMID:28507771

Modularity and evolutionary constraints in a baculovirus gene regulatory network

PubMed Central

2013-01-01

Background The structure of regulatory networks remains an open question in our understanding of complex biological systems. Interactions during complete viral life cycles present unique opportunities to understand how host-parasite network take shape and behave. The Anticarsia gemmatalis multiple nucleopolyhedrovirus (AgMNPV) is a large double-stranded DNA virus, whose genome may encode for 152 open reading frames (ORFs). Here we present the analysis of the ordered cascade of the AgMNPV gene expression. Results We observed an earlier onset of the expression than previously reported for other baculoviruses, especially for genes involved in DNA replication. Most ORFs were expressed at higher levels in a more permissive host cell line. Genes with more than one copy in the genome had distinct expression profiles, which could indicate the acquisition of new functionalities. The transcription gene regulatory network (GRN) for 149 ORFs had a modular topology comprising five communities of highly interconnected nodes that separated key genes that are functionally related on different communities, possibly maximizing redundancy and GRN robustness by compartmentalization of important functions. Core conserved functions showed expression synchronicity, distinct GRN features and significantly less genetic diversity, consistent with evolutionary constraints imposed in key elements of biological systems. This reduced genetic diversity also had a positive correlation with the importance of the gene in our estimated GRN, supporting a relationship between phylogenetic data of baculovirus genes and network features inferred from expression data. We also observed that gene arrangement in overlapping transcripts was conserved among related baculoviruses, suggesting a principle of genome organization. Conclusions Albeit with a reduced number of nodes (149), the AgMNPV GRN had a topology and key characteristics similar to those observed in complex cellular organisms, which indicates that modularity may be a general feature of biological gene regulatory networks. PMID:24006890

MMM: A toolbox for integrative structure modeling.

PubMed

Jeschke, Gunnar

2018-01-01

Structural characterization of proteins and their complexes may require integration of restraints from various experimental techniques. MMM (Multiscale Modeling of Macromolecules) is a Matlab-based open-source modeling toolbox for this purpose with a particular emphasis on distance distribution restraints obtained from electron paramagnetic resonance experiments on spin-labelled proteins and nucleic acids and their combination with atomistic structures of domains or whole protomers, small-angle scattering data, secondary structure information, homology information, and elastic network models. MMM does not only integrate various types of restraints, but also various existing modeling tools by providing a common graphical user interface to them. The types of restraints that can support such modeling and the available model types are illustrated by recent application examples. © 2017 The Protein Society.

Produsage in hybrid networks: sociotechnical skills in the case of Arduino

NASA Astrophysics Data System (ADS)

De Paoli, Stefano; Storni, Cristiano

2011-04-01

In 1this paper we investigate produsage using Actor-Network Theory with a focus on (produsage) skills, their development, and transformation. We argue that produsage is not a model that determines a change in the traditional consumption/production paradigm through a series of essential preconditions (such as open participation, peer-sharing, or common ownership). Rather, we explain produsage as the open-ended result of a series of heterogeneous actor-networking strategies. In this view, the so-called preconditions do not explain produsage but have to be explained along with its establishment as an actor-network. Drawing on this approach, we discuss a case study of an open hardware project: the Arduino board, and we develop a perspective that maps the skills of human and non-human entities in produsage actor-networks, showing how skills are symmetrical, relational, and circulating.

Imaging functional and structural brain connectomics in attention-deficit/hyperactivity disorder.

PubMed

Cao, Miao; Shu, Ni; Cao, Qingjiu; Wang, Yufeng; He, Yong

2014-12-01

Attention-deficit/hyperactivity disorder (ADHD) is one of the most common neurodevelopment disorders in childhood. Clinically, the core symptoms of this disorder include inattention, hyperactivity, and impulsivity. Previous studies have documented that these behavior deficits in ADHD children are associated with not only regional brain abnormalities but also changes in functional and structural connectivity among regions. In the past several years, our understanding of how ADHD affects the brain's connectivity has been greatly advanced by mapping topological alterations of large-scale brain networks (i.e., connectomes) using noninvasive neurophysiological and neuroimaging techniques (e.g., electroencephalograph, functional MRI, and diffusion MRI) in combination with graph theoretical approaches. In this review, we summarize the recent progresses of functional and structural brain connectomics in ADHD, focusing on graphic analysis of large-scale brain systems. Convergent evidence suggests that children with ADHD had abnormal small-world properties in both functional and structural brain networks characterized by higher local clustering and lower global integrity, suggesting a disorder-related shift of network topology toward regular configurations. Moreover, ADHD children showed the redistribution of regional nodes and connectivity involving the default-mode, attention, and sensorimotor systems. Importantly, these ADHD-associated alterations significantly correlated with behavior disturbances (e.g., inattention and hyperactivity/impulsivity symptoms) and exhibited differential patterns between clinical subtypes. Together, these connectome-based studies highlight brain network dysfunction in ADHD, thus opening up a new window into our understanding of the pathophysiological mechanisms of this disorder. These works might also have important implications on the development of imaging-based biomarkers for clinical diagnosis and treatment evaluation in ADHD.

NATbox: a network analysis toolbox in R.

PubMed

Chavan, Shweta S; Bauer, Michael A; Scutari, Marco; Nagarajan, Radhakrishnan

2009-10-08

There has been recent interest in capturing the functional relationships (FRs) from high-throughput assays using suitable computational techniques. FRs elucidate the working of genes in concert as a system as opposed to independent entities hence may provide preliminary insights into biological pathways and signalling mechanisms. Bayesian structure learning (BSL) techniques and its extensions have been used successfully for modelling FRs from expression profiles. Such techniques are especially useful in discovering undocumented FRs, investigating non-canonical signalling mechanisms and cross-talk between pathways. The objective of the present study is to develop a graphical user interface (GUI), NATbox: Network Analysis Toolbox in the language R that houses a battery of BSL algorithms in conjunction with suitable statistical tools for modelling FRs in the form of acyclic networks from gene expression profiles and their subsequent analysis. NATbox is a menu-driven open-source GUI implemented in the R statistical language for modelling and analysis of FRs from gene expression profiles. It provides options to (i) impute missing observations in the given data (ii) model FRs and network structure from gene expression profiles using a battery of BSL algorithms and identify robust dependencies using a bootstrap procedure, (iii) present the FRs in the form of acyclic graphs for visualization and investigate its topological properties using network analysis metrics, (iv) retrieve FRs of interest from published literature. Subsequently, use these FRs as structural priors in BSL (v) enhance scalability of BSL across high-dimensional data by parallelizing the bootstrap routines. NATbox provides a menu-driven GUI for modelling and analysis of FRs from gene expression profiles. By incorporating readily available functions from existing R-packages, it minimizes redundancy and improves reproducibility, transparency and sustainability, characteristic of open-source environments. NATbox is especially suited for interdisciplinary researchers and biologists with minimal programming experience and would like to use systems biology approaches without delving into the algorithmic aspects. The GUI provides appropriate parameter recommendations for the various menu options including default parameter choices for the user. NATbox can also prove to be a useful demonstration and teaching tool in graduate and undergraduate course in systems biology. It has been tested successfully under Windows and Linux operating systems. The source code along with installation instructions and accompanying tutorial can be found at http://bioinformatics.ualr.edu/natboxWiki/index.php/Main_Page.

Effect of crystals and fibrous network polymer additives on cellular morphology of microcellular foams

NASA Astrophysics Data System (ADS)

Miyamoto, Ryoma; Utano, Tatsumi; Yasuhara, Shunya; Ishihara, Shota; Ohshima, Masahiro

2015-05-01

In this study, the core-back foam injection molding was used for preparing microcelluar polypropylene (PP) foam with either a 1,3:2,4 bis-O-(4-methylbenzylidene)-D-sorbitol gelling agent (Gel-all MD) or a fibros network polymer additive (Metablen 3000). Both agent and addiive could effectively control the celluar morphology in foams but somehow different ways. In course of cooling the polymer with Gel-all MD in the mold caity, the agent enhanced the crystal nucleation and resulted in the large number of small crystals. The crystals acted as effective bubble nucleation agent in foaming process. Thus, the agent reduced the cell size and increased the cell density, drastically. Furthermore, the small crystals provided an inhomogenuity to the expanding cell wall and produced the high open cell content with nano-scale fibril structure. Gell-all as well as Metablene 3000 formed a gel-like fibrous network in melt. The network increased the elongational viscosity and tended to prevent the cell wall from breaking up. The foaming temperature window was widened by the presence of the network. Especially, the temperature window where the macro-fibrous structure was formed was expanded to the higher temperature. The effects of crystal nucleating agent and PTFE on crystals' size and number, viscoelsticity, rheological propreties of PP and cellular morphology were compared and thorougly investigated.

Individual brain structure and modelling predict seizure propagation.

PubMed

Proix, Timothée; Bartolomei, Fabrice; Guye, Maxime; Jirsa, Viktor K

2017-03-01

See Lytton (doi:10.1093/awx018) for a scientific commentary on this article.Neural network oscillations are a fundamental mechanism for cognition, perception and consciousness. Consequently, perturbations of network activity play an important role in the pathophysiology of brain disorders. When structural information from non-invasive brain imaging is merged with mathematical modelling, then generative brain network models constitute personalized in silico platforms for the exploration of causal mechanisms of brain function and clinical hypothesis testing. We here demonstrate with the example of drug-resistant epilepsy that patient-specific virtual brain models derived from diffusion magnetic resonance imaging have sufficient predictive power to improve diagnosis and surgery outcome. In partial epilepsy, seizures originate in a local network, the so-called epileptogenic zone, before recruiting other close or distant brain regions. We create personalized large-scale brain networks for 15 patients and simulate the individual seizure propagation patterns. Model validation is performed against the presurgical stereotactic electroencephalography data and the standard-of-care clinical evaluation. We demonstrate that the individual brain models account for the patient seizure propagation patterns, explain the variability in postsurgical success, but do not reliably augment with the use of patient-specific connectivity. Our results show that connectome-based brain network models have the capacity to explain changes in the organization of brain activity as observed in some brain disorders, thus opening up avenues towards discovery of novel clinical interventions. © The Author (2017). Published by Oxford University Press on behalf of the Guarantors of Brain.

Network Community Detection based on the Physarum-inspired Computational Framework.

PubMed

Gao, Chao; Liang, Mingxin; Li, Xianghua; Zhang, Zili; Wang, Zhen; Zhou, Zhili

2016-12-13

Community detection is a crucial and essential problem in the structure analytics of complex networks, which can help us understand and predict the characteristics and functions of complex networks. Many methods, ranging from the optimization-based algorithms to the heuristic-based algorithms, have been proposed for solving such a problem. Due to the inherent complexity of identifying network structure, how to design an effective algorithm with a higher accuracy and a lower computational cost still remains an open problem. Inspired by the computational capability and positive feedback mechanism in the wake of foraging process of Physarum, which is a large amoeba-like cell consisting of a dendritic network of tube-like pseudopodia, a general Physarum-based computational framework for community detection is proposed in this paper. Based on the proposed framework, the inter-community edges can be identified from the intra-community edges in a network and the positive feedback of solving process in an algorithm can be further enhanced, which are used to improve the efficiency of original optimization-based and heuristic-based community detection algorithms, respectively. Some typical algorithms (e.g., genetic algorithm, ant colony optimization algorithm, and Markov clustering algorithm) and real-world datasets have been used to estimate the efficiency of our proposed computational framework. Experiments show that the algorithms optimized by Physarum-inspired computational framework perform better than the original ones, in terms of accuracy and computational cost. Moreover, a computational complexity analysis verifies the scalability of our framework.

What Explains the Patterns of Diversification in Drug Trafficking Organizations

DTIC Science & Technology

2016-06-01

warehouse,”61 with built-in arrangements such as a rail system, an oxygen ventilation system for proper breathing, and re-enforced structures...they take great effort to persuade state officials through usage of bribes to achieve “institutionalized corruption.”29 In effect , this opens new...just gotten better and are more effective and efficient, at what they do. Ronfeldt argues that the current society values the networks of

A Framework for Building and Reasoning with Adaptive and Interoperable PMESII Models

DTIC Science & Technology

2007-11-01

Description Logic SOA Service Oriented Architecture SPARQL Simple Protocol And RDF Query Language SQL Standard Query Language SROM Stability and...another by providing a more expressive ontological structure for one of the models, e.g., semantic networks can be mapped to first- order logical...Pellet is an open-source reasoner that works with OWL-DL. It accepts the SPARQL protocol and RDF query language ( SPARQL ) and provides a Java API to

Greater Engagement Among Members of Gay-Straight Alliances: Individual and Structural Contributors

PubMed Central

Poteat, V. Paul; Heck, Nicholas C.; Yoshikawa, Hirokazu; Calzo, Jerel P.

2017-01-01

Using youth program models to frame the study of Gay-Straight Alliances (GSAs), we identified individual and structural predictors of greater engagement in these settings with a cross-sectional sample of 295 youth in 33 GSAs from the 2014 Massachusetts GSA Network Survey (69% LGBQ, 68% cisgen-der female, 68% White, Mage = 16.07). Multilevel modeling results indicated that members who perceived more support/socializing from their GSA, had more LGB friends, were longer serving members, and were in GSAs with more open and respectful climates reported greater engagement. Further, there was a curvilinear association between organizational structure in the GSA and engagement: Perceptions of more structure were associated with greater engagement to a point, after which greater structure was related to less engagement. PMID:28757649

An exploration of alternative visualisations of the basic helix-loop-helix protein interaction network

PubMed Central

Holden, Brian J; Pinney, John W; Lovell, Simon C; Amoutzias, Grigoris D; Robertson, David L

2007-01-01

Background Alternative representations of biochemical networks emphasise different aspects of the data and contribute to the understanding of complex biological systems. In this study we present a variety of automated methods for visualisation of a protein-protein interaction network, using the basic helix-loop-helix (bHLH) family of transcription factors as an example. Results Network representations that arrange nodes (proteins) according to either continuous or discrete information are investigated, revealing the existence of protein sub-families and the retention of interactions following gene duplication events. Methods of network visualisation in conjunction with a phylogenetic tree are presented, highlighting the evolutionary relationships between proteins, and clarifying the context of network hubs and interaction clusters. Finally, an optimisation technique is used to create a three-dimensional layout of the phylogenetic tree upon which the protein-protein interactions may be projected. Conclusion We show that by incorporating secondary genomic, functional or phylogenetic information into network visualisation, it is possible to move beyond simple layout algorithms based on network topology towards more biologically meaningful representations. These new visualisations can give structure to complex networks and will greatly help in interpreting their evolutionary origins and functional implications. Three open source software packages (InterView, TVi and OptiMage) implementing our methods are available. PMID:17683601

Will Choice-Based Reform Work for Medicare? Evidence from the Federal Employees Health Benefits Program

PubMed Central

Florence, Curtis S; Atherly, Adam; Thorpe, Kenneth E

2006-01-01

Objective To examine the effect of premiums and benefits on the health plan choices of older enrollees who choose Federal Employees Health Benefits Program (FEHBP) health plans as their primary payer. Data Sources Administrative enrollment data from the Office of Personnel Management (OPM) and plan premiums and benefits data taken from the Checkbook Guide to health plans. Study Design We estimate individual plan choice models where the choice of health plan is a function of out-of-pocket premium, actuarial value, plan attributes, and individual characteristics. Plan attributes include plan structure (fee-for-service/preferred provider organization, point-of-service, or health maintenance organization), drug benefit structure, and whether or not the plan covers other types of spending such as dental services and diabetic supplies. The models are estimated by conditional logit. Our study focuses on three populations that currently choose FEHBP as their primary health care coverage and are similar to the Medicare population: current employees and retirees who are approaching the age of Medicare eligibility (ages 60–64) and current federal employees age 65+. Current employees age 65+ are eligible for Medicare, but their FEHBP plan is their primary payer. Retirees and employees 60–64 are not yet eligible for Medicare but are similar in many respects to recently age-eligible Medicare beneficiaries. We also estimate our model for current employees age 55 and younger as a comparison group. Data Collection Methods We select a random sample of retirees and employees age 60–64, as well as all current employees age 65+, from the OPM administrative database for the calendar year 2001. The plan choices available to each person are determined by the plans participating in their metropolitan statistical area. We match plan premium and attribute information from the Checkbook Guide to each plan in the enrollee's list of choices. Principal Findings We find that current workers 65+, 60–64, and non-Medicare eligible retirees are sensitive to variation in plan premiums. The premium elasticities for these groups are similar in magnitude to those of the age 55 and under employee group. Older workers and retirees not yet eligible for Medicare are willing to pay a substantial amount for plans with open provider networks. The willingness to pay for open networks is significantly greater for these groups than for younger employees. Willingness to pay for open network plans varies significantly by income, but varies little by age within group. Conclusions Our finding that older workers and non-Medicare eligible retirees are sensitive to plan premiums suggests that choice-based reform of Medicare would lead to cost-conscious choices by Medicare beneficiaries. However, our finding that these groups are willing to pay more for open network plans than younger employees suggest that higher risk individuals may migrate toward higher benefit, higher cost plans. Our findings on the relationship between income and willingness to pay for open network plans suggest that means testing is a viable reform for lowering Medicare program costs. PMID:16987300

A palladium-doped ceria@carbon core-sheath nanowire network: a promising catalyst support for alcohol electrooxidation reactions

NASA Astrophysics Data System (ADS)

Tan, Qiang; Du, Chunyu; Sun, Yongrong; Du, Lei; Yin, Geping; Gao, Yunzhi

2015-08-01

A novel palladium-doped ceria and carbon core-sheath nanowire network (Pd-CeO2@C CSNWN) is synthesized by a template-free and surfactant-free solvothermal process, followed by high temperature carbonization. This hierarchical network serves as a new class of catalyst support to enhance the activity and durability of noble metal catalysts for alcohol oxidation reactions. Its supported Pd nanoparticles, Pd/(Pd-CeO2@C CSNWN), exhibit >9 fold increase in activity toward the ethanol oxidation over the state-of-the-art Pd/C catalyst, which is the highest among the reported Pd systems. Moreover, stability tests show a virtually unchanged activity after 1000 cycles. The high activity is mainly attributed to the superior oxygen-species releasing capability of Pd-doped CeO2 nanowires by accelerating the removal of the poisoning intermediate. The unique interconnected one-dimensional core-sheath structure is revealed to facilitate immobilization of the metal catalysts, leading to the improved durability. This core-sheath nanowire network opens up a new strategy for catalyst performance optimization for next-generation fuel cells.A novel palladium-doped ceria and carbon core-sheath nanowire network (Pd-CeO2@C CSNWN) is synthesized by a template-free and surfactant-free solvothermal process, followed by high temperature carbonization. This hierarchical network serves as a new class of catalyst support to enhance the activity and durability of noble metal catalysts for alcohol oxidation reactions. Its supported Pd nanoparticles, Pd/(Pd-CeO2@C CSNWN), exhibit >9 fold increase in activity toward the ethanol oxidation over the state-of-the-art Pd/C catalyst, which is the highest among the reported Pd systems. Moreover, stability tests show a virtually unchanged activity after 1000 cycles. The high activity is mainly attributed to the superior oxygen-species releasing capability of Pd-doped CeO2 nanowires by accelerating the removal of the poisoning intermediate. The unique interconnected one-dimensional core-sheath structure is revealed to facilitate immobilization of the metal catalysts, leading to the improved durability. This core-sheath nanowire network opens up a new strategy for catalyst performance optimization for next-generation fuel cells. Electronic supplementary information (ESI) available. See DOI: 10.1039/c5nr03023d

OpenSim: A Flexible Distributed Neural Network Simulator with Automatic Interactive Graphics.

PubMed

Jarosch, Andreas; Leber, Jean Francois

1997-06-01

An object-oriented simulator called OpenSim is presented that achieves a high degree of flexibility by relying on a small set of building blocks. The state variables and algorithms put in this framework can easily be accessed through a command shell. This allows one to distribute a large-scale simulation over several workstations and to generate the interactive graphics automatically. OpenSim opens new possibilities for cooperation among Neural Network researchers. Copyright 1997 Elsevier Science Ltd.

The Age-ility Project (Phase 1): Structural and functional imaging and electrophysiological data repository.

PubMed

Karayanidis, Frini; Keuken, Max C; Wong, Aaron; Rennie, Jaime L; de Hollander, Gilles; Cooper, Patrick S; Ross Fulham, W; Lenroot, Rhoshel; Parsons, Mark; Phillips, Natalie; Michie, Patricia T; Forstmann, Birte U

2016-01-01

Our understanding of the complex interplay between structural and functional organisation of brain networks is being advanced by the development of novel multi-modal analyses approaches. The Age-ility Project (Phase 1) data repository offers open access to structural MRI, diffusion MRI, and resting-state fMRI scans, as well as resting-state EEG recorded from the same community participants (n=131, 15-35 y, 66 male). Raw imaging and electrophysiological data as well as essential demographics are made available via the NITRC website. All data have been reviewed for artifacts using a rigorous quality control protocol and detailed case notes are provided. Copyright © 2015. Published by Elsevier Inc.

Experimental demonstration of OpenFlow-enabled media ecosystem architecture for high-end applications over metro and core networks.

PubMed

Ntofon, Okung-Dike; Channegowda, Mayur P; Efstathiou, Nikolaos; Rashidi Fard, Mehdi; Nejabati, Reza; Hunter, David K; Simeonidou, Dimitra

2013-02-25

In this paper, a novel Software-Defined Networking (SDN) architecture is proposed for high-end Ultra High Definition (UHD) media applications. UHD media applications require huge amounts of bandwidth that can only be met with high-capacity optical networks. In addition, there are requirements for control frameworks capable of delivering effective application performance with efficient network utilization. A novel SDN-based Controller that tightly integrates application-awareness with network control and management is proposed for such applications. An OpenFlow-enabled test-bed demonstrator is reported with performance evaluations of advanced online and offline media- and network-aware schedulers.

On the relevance of using open wireless sensor networks in environment monitoring.

PubMed

Bagula, Antoine B; Inggs, Gordon; Scott, Simon; Zennaro, Marco

2009-01-01

This paper revisits the problem of the readiness for field deployments of wireless sensor networks by assessing the relevance of using Open Hardware and Software motes for environment monitoring. We propose a new prototype wireless sensor network that fine-tunes SquidBee motes to improve the life-time and sensing performance of an environment monitoring system that measures temperature, humidity and luminosity. Building upon two outdoor sensing scenarios, we evaluate the performance of the newly proposed energy-aware prototype solution in terms of link quality when expressed by the Received Signal Strength, Packet Loss and the battery lifetime. The experimental results reveal the relevance of using the Open Hardware and Software motes when setting up outdoor wireless sensor networks.

AtomPy: an open atomic-data curation environment

NASA Astrophysics Data System (ADS)

Bautista, Manuel; Mendoza, Claudio; Boswell, Josiah S; Ajoku, Chukwuemeka

2014-06-01

We present a cloud-computing environment for atomic data curation, networking among atomic data providers and users, teaching-and-learning, and interfacing with spectral modeling software. The system is based on Google-Drive Sheets, Pandas (Python Data Analysis Library) DataFrames, and IPython Notebooks for open community-driven curation of atomic data for scientific and technological applications. The atomic model for each ionic species is contained in a multi-sheet Google-Drive workbook, where the atomic parameters from all known public sources are progressively stored. Metadata (provenance, community discussion, etc.) accompanying every entry in the database are stored through Notebooks. Education tools on the physics of atomic processes as well as their relevance to plasma and spectral modeling are based on IPython Notebooks that integrate written material, images, videos, and active computer-tool workflows. Data processing workflows and collaborative software developments are encouraged and managed through the GitHub social network. Relevant issues this platform intends to address are: (i) data quality by allowing open access to both data producers and users in order to attain completeness, accuracy, consistency, provenance and currentness; (ii) comparisons of different datasets to facilitate accuracy assessment; (iii) downloading to local data structures (i.e. Pandas DataFrames) for further manipulation and analysis by prospective users; and (iv) data preservation by avoiding the discard of outdated sets.

Energy landscape of LeuT from molecular simulations

NASA Astrophysics Data System (ADS)

Gur, Mert; Zomot, Elia; Cheng, Mary Hongying; Bahar, Ivet

2015-12-01

The bacterial sodium-coupled leucine transporter (LeuT) has been broadly used as a structural model for understanding the structure-dynamics-function of mammalian neurotransmitter transporters as well as other solute carriers that share the same fold (LeuT fold), as the first member of the family crystallographically resolved in multiple states: outward-facing open, outward-facing occluded, and inward-facing open. Yet, a complete picture of the energy landscape of (sub)states visited along the LeuT transport cycle has been elusive. In an attempt to visualize the conformational spectrum of LeuT, we performed extensive simulations of LeuT dimer dynamics in the presence of substrate (Ala or Leu) and co-transported Na+ ions, in explicit membrane and water. We used both conventional molecular dynamics (MD) simulations (with Anton supercomputing machine) and a recently introduced method, collective MD, that takes advantage of collective modes of motions predicted by the anisotropic network model. Free energy landscapes constructed based on ˜40 μs trajectories reveal multiple substates occluded to the extracellular (EC) and/or intracellular (IC) media, varying in the levels of exposure of LeuT to EC or IC vestibules. The IC-facing transmembrane (TM) helical segment TM1a shows an opening, albeit to a smaller extent and in a slightly different direction than that observed in the inward-facing open crystal structure. The study provides insights into the spectrum of conformational substates and paths accessible to LeuT and highlights the differences between Ala- and Leu-bound substates.

Energy landscape of LeuT from molecular simulations.

PubMed

Gur, Mert; Zomot, Elia; Cheng, Mary Hongying; Bahar, Ivet

2015-12-28

The bacterial sodium-coupled leucine transporter (LeuT) has been broadly used as a structural model for understanding the structure-dynamics-function of mammalian neurotransmitter transporters as well as other solute carriers that share the same fold (LeuT fold), as the first member of the family crystallographically resolved in multiple states: outward-facing open, outward-facing occluded, and inward-facing open. Yet, a complete picture of the energy landscape of (sub)states visited along the LeuT transport cycle has been elusive. In an attempt to visualize the conformational spectrum of LeuT, we performed extensive simulations of LeuT dimer dynamics in the presence of substrate (Ala or Leu) and co-transported Na(+) ions, in explicit membrane and water. We used both conventional molecular dynamics (MD) simulations (with Anton supercomputing machine) and a recently introduced method, collective MD, that takes advantage of collective modes of motions predicted by the anisotropic network model. Free energy landscapes constructed based on ∼40 μs trajectories reveal multiple substates occluded to the extracellular (EC) and/or intracellular (IC) media, varying in the levels of exposure of LeuT to EC or IC vestibules. The IC-facing transmembrane (TM) helical segment TM1a shows an opening, albeit to a smaller extent and in a slightly different direction than that observed in the inward-facing open crystal structure. The study provides insights into the spectrum of conformational substates and paths accessible to LeuT and highlights the differences between Ala- and Leu-bound substates.

Energy landscape of LeuT from molecular simulations

PubMed Central

Gur, Mert; Zomot, Elia; Cheng, Mary Hongying; Bahar, Ivet

2015-01-01

The bacterial sodium-coupled leucine transporter (LeuT) has been broadly used as a structural model for understanding the structure-dynamics-function of mammalian neurotransmitter transporters as well as other solute carriers that share the same fold (LeuT fold), as the first member of the family crystallographically resolved in multiple states: outward-facing open, outward-facing occluded, and inward-facing open. Yet, a complete picture of the energy landscape of (sub)states visited along the LeuT transport cycle has been elusive. In an attempt to visualize the conformational spectrum of LeuT, we performed extensive simulations of LeuT dimer dynamics in the presence of substrate (Ala or Leu) and co-transported Na+ ions, in explicit membrane and water. We used both conventional molecular dynamics (MD) simulations (with Anton supercomputing machine) and a recently introduced method, collective MD, that takes advantage of collective modes of motions predicted by the anisotropic network model. Free energy landscapes constructed based on ∼40 μs trajectories reveal multiple substates occluded to the extracellular (EC) and/or intracellular (IC) media, varying in the levels of exposure of LeuT to EC or IC vestibules. The IC-facing transmembrane (TM) helical segment TM1a shows an opening, albeit to a smaller extent and in a slightly different direction than that observed in the inward-facing open crystal structure. The study provides insights into the spectrum of conformational substates and paths accessible to LeuT and highlights the differences between Ala- and Leu-bound substates. PMID:26723619

Open-Source, Web-Based Dashboard Components for DICOM Connectivity.

PubMed

Bustamante, Catalina; Pineda, Julian; Rascovsky, Simon; Arango, Andres

2016-08-01

The administration of a DICOM network within an imaging healthcare institution requires tools that allow for monitoring of connectivity and availability for adequate uptime measurements and help guide technology management strategies. We present the implementation of an open-source widget for the Dashing framework that provides basic dashboard functionality allowing for monitoring of a DICOM network using network "ping" and DICOM "C-ECHO" operations.

Large Scale Comparative Visualisation of Regulatory Networks with TRNDiff

DOE PAGES

Chua, Xin-Yi; Buckingham, Lawrence; Hogan, James M.; ...

2015-06-01

The advent of Next Generation Sequencing (NGS) technologies has seen explosive growth in genomic datasets, and dense coverage of related organisms, supporting study of subtle, strain-specific variations as a determinant of function. Such data collections present fresh and complex challenges for bioinformatics, those of comparing models of complex relationships across hundreds and even thousands of sequences. Transcriptional Regulatory Network (TRN) structures document the influence of regulatory proteins called Transcription Factors (TFs) on associated Target Genes (TGs). TRNs are routinely inferred from model systems or iterative search, and analysis at these scales requires simultaneous displays of multiple networks well beyond thosemore » of existing network visualisation tools [1]. In this paper we describe TRNDiff, an open source system supporting the comparative analysis and visualization of TRNs (and similarly structured data) from many genomes, allowing rapid identification of functional variations within species. The approach is demonstrated through a small scale multiple TRN analysis of the Fur iron-uptake system of Yersinia, suggesting a number of candidate virulence factors; and through a larger study exploiting integration with the RegPrecise database (http://regprecise.lbl.gov; [2]) - a collection of hundreds of manually curated and predicted transcription factor regulons drawn from across the entire spectrum of prokaryotic organisms.« less

Visibility graphlet approach to chaotic time series

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

Mutua, Stephen; Computer Science Department, Masinde Muliro University of Science and Technology, P.O. Box 190-50100, Kakamega; Gu, Changgui, E-mail: gu-changgui@163.com, E-mail: hjyang@ustc.edu.cn

Many novel methods have been proposed for mapping time series into complex networks. Although some dynamical behaviors can be effectively captured by existing approaches, the preservation and tracking of the temporal behaviors of a chaotic system remains an open problem. In this work, we extended the visibility graphlet approach to investigate both discrete and continuous chaotic time series. We applied visibility graphlets to capture the reconstructed local states, so that each is treated as a node and tracked downstream to create a temporal chain link. Our empirical findings show that the approach accurately captures the dynamical properties of chaotic systems.more » Networks constructed from periodic dynamic phases all converge to regular networks and to unique network structures for each model in the chaotic zones. Furthermore, our results show that the characterization of chaotic and non-chaotic zones in the Lorenz system corresponds to the maximal Lyapunov exponent, thus providing a simple and straightforward way to analyze chaotic systems.« less

Design and deployment of an elastic network test-bed in IHEP data center based on SDN

NASA Astrophysics Data System (ADS)

Zeng, Shan; Qi, Fazhi; Chen, Gang

2017-10-01

High energy physics experiments produce huge amounts of raw data, while because of the sharing characteristics of the network resources, there is no guarantee of the available bandwidth for each experiment which may cause link congestion problems. On the other side, with the development of cloud computing technologies, IHEP have established a cloud platform based on OpenStack which can ensure the flexibility of the computing and storage resources, and more and more computing applications have been deployed on virtual machines established by OpenStack. However, under the traditional network architecture, network capability can’t be required elastically, which becomes the bottleneck of restricting the flexible application of cloud computing. In order to solve the above problems, we propose an elastic cloud data center network architecture based on SDN, and we also design a high performance controller cluster based on OpenDaylight. In the end, we present our current test results.

Using Entropy Maximization to Understand the Determinants of Structural Dynamics beyond Native Contact Topology

PubMed Central

Lezon, Timothy R.; Bahar, Ivet

2010-01-01

Comparison of elastic network model predictions with experimental data has provided important insights on the dominant role of the network of inter-residue contacts in defining the global dynamics of proteins. Most of these studies have focused on interpreting the mean-square fluctuations of residues, or deriving the most collective, or softest, modes of motions that are known to be insensitive to structural and energetic details. However, with increasing structural data, we are in a position to perform a more critical assessment of the structure-dynamics relations in proteins, and gain a deeper understanding of the major determinants of not only the mean-square fluctuations and lowest frequency modes, but the covariance or the cross-correlations between residue fluctuations and the shapes of higher modes. A systematic study of a large set of NMR-determined proteins is analyzed using a novel method based on entropy maximization to demonstrate that the next level of refinement in the elastic network model description of proteins ought to take into consideration properties such as contact order (or sequential separation between contacting residues) and the secondary structure types of the interacting residues, whereas the types of amino acids do not play a critical role. Most importantly, an optimal description of observed cross-correlations requires the inclusion of destabilizing, as opposed to exclusively stabilizing, interactions, stipulating the functional significance of local frustration in imparting native-like dynamics. This study provides us with a deeper understanding of the structural basis of experimentally observed behavior, and opens the way to the development of more accurate models for exploring protein dynamics. PMID:20585542

Using entropy maximization to understand the determinants of structural dynamics beyond native contact topology.

PubMed

Lezon, Timothy R; Bahar, Ivet

2010-06-17

Comparison of elastic network model predictions with experimental data has provided important insights on the dominant role of the network of inter-residue contacts in defining the global dynamics of proteins. Most of these studies have focused on interpreting the mean-square fluctuations of residues, or deriving the most collective, or softest, modes of motions that are known to be insensitive to structural and energetic details. However, with increasing structural data, we are in a position to perform a more critical assessment of the structure-dynamics relations in proteins, and gain a deeper understanding of the major determinants of not only the mean-square fluctuations and lowest frequency modes, but the covariance or the cross-correlations between residue fluctuations and the shapes of higher modes. A systematic study of a large set of NMR-determined proteins is analyzed using a novel method based on entropy maximization to demonstrate that the next level of refinement in the elastic network model description of proteins ought to take into consideration properties such as contact order (or sequential separation between contacting residues) and the secondary structure types of the interacting residues, whereas the types of amino acids do not play a critical role. Most importantly, an optimal description of observed cross-correlations requires the inclusion of destabilizing, as opposed to exclusively stabilizing, interactions, stipulating the functional significance of local frustration in imparting native-like dynamics. This study provides us with a deeper understanding of the structural basis of experimentally observed behavior, and opens the way to the development of more accurate models for exploring protein dynamics.

Offline Social Relationships and Online Cancer Communication: Effects of Social and Family Support on Online Social Network Building.

PubMed

Namkoong, Kang; Shah, Dhavan V; Gustafson, David H

2017-11-01

This study investigates how social support and family relationship perceptions influence breast cancer patients' online communication networks in a computer-mediated social support (CMSS) group. To examine social interactions in the CMSS group, we identified two types of online social networks: open and targeted communication networks. The open communication network reflects group communication behaviors (i.e., one-to-many or "broadcast" communication) in which the intended audience is not specified; in contrast, the targeted communication network reflects interpersonal discourses (i.e., one-to-one or directed communication) in which the audience for the message is specified. The communication networks were constructed by tracking CMSS group usage data of 237 breast cancer patients who participated in one of two National Cancer Institute-funded randomized clinical trials. Eligible subjects were within 2 months of a diagnosis of primary breast cancer or recurrence at the time of recruitment. Findings reveal that breast cancer patients who perceived less availability of offline social support had a larger social network size in the open communication network. In contrast, those who perceived less family cohesion had a larger targeted communication network in the CMSS group, meaning they were inclined to use the CMSS group for developing interpersonal relationships.

MB-OFDM-UWB Based Wireless Multimedia Sensor Networks for Underground Coalmine: A Survey.

PubMed

Han, Ruisong; Yang, Wei; You, Kaiming

2016-12-16

Safety production of coalmines is a task of top priority which plays an important role in guaranteeing, supporting and promoting the continuous development of the coal industry. Since traditional wireless sensor networks (WSNs) cannot fully meet the requirements of comprehensive environment monitoring of underground coalmines, wireless multimedia sensor networks (WMSNs), enabling the retrieval of multimedia information, are introduced to realize fine-grained and precise environment surveillance. In this paper, a framework for designing underground coalmine WMSNs based on Multi-Band Orthogonal Frequency-Division Multiplexing Ultra-wide Band (MB-OFDM-UWB) is presented. The selection of MB-OFDM-UWB wireless transmission solution is based on the characteristics of underground coalmines. Network structure and design challenges are analyzed first, which is the foundation for further discussion. Then, key supporting technologies and open research areas in different layers are surveyed, and we provide a detailed literature review of the state of the art strategies, algorithms and general solutions in these issues. Finally, other research issues like localization, information processing, and network management are discussed.

Symmetry Breaking in Space-Time Hierarchies Shapes Brain Dynamics and Behavior.

PubMed

Pillai, Ajay S; Jirsa, Viktor K

2017-06-07

In order to maintain brain function, neural activity needs to be tightly coordinated within the brain network. How this coordination is achieved and related to behavior is largely unknown. It has been previously argued that the study of the link between brain and behavior is impossible without a guiding vision. Here we propose behavioral-level concepts and mechanisms embodied as structured flows on manifold (SFM) that provide a formal description of behavior as a low-dimensional process emerging from a network's dynamics dependent on the symmetry and invariance properties of the network connectivity. Specifically, we demonstrate that the symmetry breaking of network connectivity constitutes a timescale hierarchy resulting in the emergence of an attractive functional subspace. We show that behavior emerges when appropriate conditions imposed upon the couplings are satisfied, justifying the conductance-based nature of synaptic couplings. Our concepts propose design principles for networks predicting how behavior and task rules are represented in real neural circuits and open new avenues for the analyses of neural data. Copyright © 2017 Elsevier Inc. All rights reserved.

MB-OFDM-UWB Based Wireless Multimedia Sensor Networks for Underground Coalmine: A Survey

PubMed Central

Han, Ruisong; Yang, Wei; You, Kaiming

2016-01-01

Safety production of coalmines is a task of top priority which plays an important role in guaranteeing, supporting and promoting the continuous development of the coal industry. Since traditional wireless sensor networks (WSNs) cannot fully meet the requirements of comprehensive environment monitoring of underground coalmines, wireless multimedia sensor networks (WMSNs), enabling the retrieval of multimedia information, are introduced to realize fine-grained and precise environment surveillance. In this paper, a framework for designing underground coalmine WMSNs based on Multi-Band Orthogonal Frequency-Division Multiplexing Ultra-wide Band (MB-OFDM-UWB) is presented. The selection of MB-OFDM-UWB wireless transmission solution is based on the characteristics of underground coalmines. Network structure and design challenges are analyzed first, which is the foundation for further discussion. Then, key supporting technologies and open research areas in different layers are surveyed, and we provide a detailed literature review of the state of the art strategies, algorithms and general solutions in these issues. Finally, other research issues like localization, information processing, and network management are discussed. PMID:27999258

Statistical Physics Approaches to Respiratory Dynamics and Lung Structure

NASA Astrophysics Data System (ADS)

Suki, Bela

2004-03-01

The lung consists of a branching airway tree embedded in viscoelastic tissue and provides life-sustaining gas exchange to the body. In diseases, its structure is damaged and its function is compromised. We review two recent works about lung structure and dynamics and how they change in disease. 1) We introduced a new acoustic imaging approach to study airway structure. When airways in a collapsed lung are inflated, they pop open in avalanches. A single opening emits a sound package called crackle consisting of an initial spike (s) followed by ringing. The distribution n(s) of s follows a power law and the exponent of n(s) can be used to calculate the diameter ratio d defined as the ratio of the diameters of an airway to that of its parent averaged over all bifurcations. To test this method, we measured crackles in dogs, rabbits, rats and mice by inflating collapsed isolated lungs with air or helium while recording crackles with a microphone. In each species, n(s) follows a power law with an exponent that depends on species, but not on gas in agreement with theory. Values of d from crackles compare well with those calculated from morphometric data suggesting that this approach is suitable to study airway structure in disease. 2) Using novel experiments and computer models, we studied pulmonary emphysema which is caused by cigarette smoking. In emphysema, the elastic protein fibers of the tissue are actively remodeled by lung cells due to the chemicals present in smoke. We measured the mechanical properties of tissue sheets from normal and emphysematous lungs and imaged its structure which appears as a heterogeneous hexagonal network of fibers. We found evidence that during uniaxial stretching, the collagen and elastin fibers in emphysematous tissue can fail at a critical stress generating holes of various sizes (h). We developed network models of the failure process. When the failure is governed by mechanical forces, the distribution n(h) of h is a power law which compares well with Computed Tomographic images of patients. These results suggest that the progressive nature of emphysema may be due to a complex breakdown process initiated by chemicals in the smoke and maintained by mechanical failure of the remodeled fiber network.

An open-source software platform for data management, visualisation, model building and model sharing in water, energy and other resource modelling domains.

NASA Astrophysics Data System (ADS)

Knox, S.; Meier, P.; Mohammed, K.; Korteling, B.; Matrosov, E. S.; Hurford, A.; Huskova, I.; Harou, J. J.; Rosenberg, D. E.; Thilmant, A.; Medellin-Azuara, J.; Wicks, J.

2015-12-01

Capacity expansion on resource networks is essential to adapting to economic and population growth and pressures such as climate change. Engineered infrastructure systems such as water, energy, or transport networks require sophisticated and bespoke models to refine management and investment strategies. Successful modeling of such complex systems relies on good data management and advanced methods to visualize and share data.Engineered infrastructure systems are often represented as networks of nodes and links with operating rules describing their interactions. Infrastructure system management and planning can be abstracted to simulating or optimizing new operations and extensions of the network. By separating the data storage of abstract networks from manipulation and modeling we have created a system where infrastructure modeling across various domains is facilitated.We introduce Hydra Platform, a Free Open Source Software designed for analysts and modelers to store, manage and share network topology and data. Hydra Platform is a Python library with a web service layer for remote applications, called Apps, to connect. Apps serve various functions including network or results visualization, data export (e.g. into a proprietary format) or model execution. This Client-Server architecture allows users to manipulate and share centrally stored data. XML templates allow a standardised description of the data structure required for storing network data such that it is compatible with specific models.Hydra Platform represents networks in an abstract way and is therefore not bound to a single modeling domain. It is the Apps that create domain-specific functionality. Using Apps researchers from different domains can incorporate different models within the same network enabling cross-disciplinary modeling while minimizing errors and streamlining data sharing. Separating the Python library from the web layer allows developers to natively expand the software or build web-based apps in other languages for remote functionality. Partner CH2M is developing a commercial user-interface for Hydra Platform however custom interfaces and visualization tools can be built. Hydra Platform is available on GitHub while Apps will be shared on a central repository.

Spontaneous eyelid closures link vigilance fluctuation with fMRI dynamic connectivity states

PubMed Central

Wang, Chenhao; Ong, Ju Lynn; Patanaik, Amiya; Chee, Michael W. L.

2016-01-01

Fluctuations in resting-state functional connectivity occur but their behavioral significance remains unclear, largely because correlating behavioral state with dynamic functional connectivity states (DCS) engages probes that disrupt the very behavioral state we seek to observe. Observing spontaneous eyelid closures following sleep deprivation permits nonintrusive arousal monitoring. During periods of low arousal dominated by eyelid closures, sliding-window correlation analysis uncovered a DCS associated with reduced within-network functional connectivity of default mode and dorsal/ventral attention networks, as well as reduced anticorrelation between these networks. Conversely, during periods when participants’ eyelids were wide open, a second DCS was associated with less decoupling between the visual network and higher-order cognitive networks that included dorsal/ventral attention and default mode networks. In subcortical structures, eyelid closures were associated with increased connectivity between the striatum and thalamus with the ventral attention network, and greater anticorrelation with the dorsal attention network. When applied to task-based fMRI data, these two DCS predicted interindividual differences in frequency of behavioral lapsing and intraindividual temporal fluctuations in response speed. These findings with participants who underwent a night of total sleep deprivation were replicated in an independent dataset involving partially sleep-deprived participants. Fluctuations in functional connectivity thus appear to be clearly associated with changes in arousal. PMID:27512040

PageRank versatility analysis of multilayer modality-based network for exploring the evolution of oil-water slug flow.

PubMed

Gao, Zhong-Ke; Dang, Wei-Dong; Li, Shan; Yang, Yu-Xuan; Wang, Hong-Tao; Sheng, Jing-Ran; Wang, Xiao-Fan

2017-07-14

Numerous irregular flow structures exist in the complicated multiphase flow and result in lots of disparate spatial dynamical flow behaviors. The vertical oil-water slug flow continually attracts plenty of research interests on account of its significant importance. Based on the spatial transient flow information acquired through our designed double-layer distributed-sector conductance sensor, we construct multilayer modality-based network to encode the intricate spatial flow behavior. Particularly, we calculate the PageRank versatility and multilayer weighted clustering coefficient to quantitatively explore the inferred multilayer modality-based networks. Our analysis allows characterizing the complicated evolution of oil-water slug flow, from the opening formation of oil slugs, to the succedent inter-collision and coalescence among oil slugs, and then to the dispersed oil bubbles. These properties render our developed method particularly powerful for mining the essential flow features from the multilayer sensor measurements.

The mouse cortico-striatal projectome

PubMed Central

Hintiryan, Houri; Foster, Nicholas N.; Bowman, Ian; Bay, Maxwell; Song, Monica Y.; Gou, Lin; Yamashita, Seita; Bienkowski, Michael S.; Zingg, Brian; Zhu, Muye; Yang, X. William; Shih, Jean C.; Toga, Arthur W.; Dong, Hong-Wei

2017-01-01

Different cortical areas are organized into distinct intra-cortical subnetworks. How descending pathways from the entire cortex interact subcortically as a network remains unclear. Here, we report an open-access comprehensive mesoscale cortico-striatal projectome—a detailed connectivity projection map from the entire cerebral cortex to the dorsal striatum or caudoputamen (CP) in rodents. Based on these projections, we use novel computational neuroanatomical tools to identify 29 distinct functional striatal domains. Further, we characterize different cortico-striatal networks and how they reconfigure across the rostral-caudal extent of the CP. The workflow was also applied to select cortico-striatal connections in two different mouse models of disconnection syndromes to demonstrate its utility in characterizing circuitry-specific connectopathies. Together, this work provides the structural basis for studying the functional diversity of the dorsal striatum and disruptions of cortico-basal ganglia networks across a broad range of disorders. PMID:27322419

DICOM static and dynamic representation through unified modeling language

NASA Astrophysics Data System (ADS)

Martinez-Martinez, Alfonso; Jimenez-Alaniz, Juan R.; Gonzalez-Marquez, A.; Chavez-Avelar, N.

2004-04-01

The DICOM standard, as all standards, specifies in generic way the management in network and storage media environments of digital medical images and their related information. However, understanding the specifications for particular implementation is not a trivial work. Thus, this work is about understanding and modelling parts of the DICOM standard using Object Oriented methodologies, as part of software development processes. This has offered different static and dynamic views, according with the standard specifications, and the resultant models have been represented through the Unified Modelling Language (UML). The modelled parts are related to network conformance claim: Network Communication Support for Message Exchange, Message Exchange, Information Object Definitions, Service Class Specifications, Data Structures and Encoding, and Data Dictionary. The resultant models have given a better understanding about DICOM parts and have opened the possibility of create a software library to develop DICOM conformable PACS applications.

Water Hammer Simulations of Monomethylhydrazine Propellant

NASA Technical Reports Server (NTRS)

Burkhardt, Zachary; Ramachandran, N.; Majumdar, A.

2017-01-01

Fluid Transient analysis is important for the design of spacecraft propulsion system to ensure structural stability of the system in the event of sudden closing or opening of the valve. Generalized Fluid System Simulation Program (GFSSP), a general purpose flow network code developed at NASA/MSFC is capable of simulating pressure surge due to sudden opening or closing of valve when thermodynamic properties of real fluid are available for the entire range of simulation. Specifically GFSSP needs an accurate representation of pressure density relationship in order to predict pressure surge during a fluid transient. Unfortunately, the available thermodynamic property programs such as REFPROP, GASP or GASPAK do not provide the thermodynamic properties of Monomethylhydrazine(MMH). This work illustrates the process used for building a customized table of properties of state variables from available properties and speed of sound that is required by GFSSP for simulation. Good agreement was found between the simulations and measured data. This method can be adopted for modeling flow networks and systems with other fluids whose properties are not known in detail in order to obtain general technical insight.

Layer-by-layer assembly of MXene and carbon nanotubes on electrospun polymer films for flexible energy storage.

PubMed

Zhou, Zehang; Panatdasirisuk, Weerapha; Mathis, Tyler S; Anasori, Babak; Lu, Canhui; Zhang, Xinxing; Liao, Zhiwei; Gogotsi, Yury; Yang, Shu

2018-03-29

Free-standing, highly flexible and foldable supercapacitor electrodes were fabricated through the spray-coating assisted layer-by-layer assembly of Ti3C2Tx (MXene) nanoflakes together with multi-walled carbon nanotubes (MWCNTs) on electrospun polycaprolactone (PCL) fiber networks. The open structure of the PCL network and the use of MWCNTs as spacers not only limit the restacking of Ti3C2Tx flakes but also increase the accessible surface of the active materials, facilitating fast diffusion of electrolyte ions within the electrode. Composite electrodes have areal capacitance (30-50 mF cm-2) comparable to other templated electrodes reported in the literature, but showed significantly improved rate performance (14-16% capacitance retention at a scan rate of 100 V s-1). Furthermore, the composite electrodes are flexible and foldable, demonstrating good tolerance against repeated mechanical deformation, including twisting and folding. Therefore, these tens of micron thick fiber electrodes will be attractive for applications in energy storage, electroanalytical chemistry, brain electrodes, electrocatalysis and other fields, where flexible freestanding electrodes with an open and accessible surface are highly desired.

Seamless Combination of Fluorescence-Activated Cell Sorting and Hanging-Drop Networks for Individual Handling and Culturing of Stem Cells and Microtissue Spheroids.

PubMed

Birchler, Axel; Berger, Mischa; Jäggin, Verena; Lopes, Telma; Etzrodt, Martin; Misun, Patrick Mark; Pena-Francesch, Maria; Schroeder, Timm; Hierlemann, Andreas; Frey, Olivier

2016-01-19

Open microfluidic cell culturing devices offer new possibilities to simplify loading, culturing, and harvesting of individual cells or microtissues due to the fact that liquids and cells/microtissues are directly accessible. We present a complete workflow for microfluidic handling and culturing of individual cells and microtissue spheroids, which is based on the hanging-drop network concept: The open microfluidic devices are seamlessly combined with fluorescence-activated cell sorting (FACS), so that individual cells, including stem cells, can be directly sorted into specified culturing compartments in a fully automated way and at high accuracy. Moreover, already assembled microtissue spheroids can be loaded into the microfluidic structures by using a conventional pipet. Cell and microtissue culturing is then performed in hanging drops under controlled perfusion. On-chip drop size control measures were applied to stabilize the system. Cells and microtissue spheroids can be retrieved from the chip by using a parallelized transfer method. The presented methodology holds great promise for combinatorial screening of stem-cell and multicellular-spheroid cultures.

Aspiration dynamics in structured population acts as if in a well-mixed one.

PubMed

Du, Jinming; Wu, Bin; Wang, Long

2015-01-26

Understanding the evolution of human interactive behaviors is important. Recent experimental results suggest that human cooperation in spatial structured population is not enhanced as predicted in previous works, when payoff-dependent imitation updating rules are used. This constraint opens up an avenue to shed light on how humans update their strategies in real life. Studies via simulations show that, instead of comparison rules, self-evaluation driven updating rules may explain why spatial structure does not alter the evolutionary outcome. Though inspiring, there is a lack of theoretical result to show the existence of such evolutionary updating rule. Here we study the aspiration dynamics, and show that it does not alter the evolutionary outcome in various population structures. Under weak selection, by analytical approximation, we find that the favored strategy in regular graphs is invariant. Further, we show that this is because the criterion under which a strategy is favored is the same as that of a well-mixed population. By simulation, we show that this holds for random networks. Although how humans update their strategies is an open question to be studied, our results provide a theoretical foundation of the updating rules that may capture the real human updating rules.

Experimental synchronization of chaos in a large ring of mutually coupled single-transistor oscillators: phase, amplitude, and clustering effects.

PubMed

Minati, Ludovico

2014-12-01

In this paper, experimental evidence of multiple synchronization phenomena in a large (n = 30) ring of chaotic oscillators is presented. Each node consists of an elementary circuit, generating spikes of irregular amplitude and comprising one bipolar junction transistor, one capacitor, two inductors, and one biasing resistor. The nodes are mutually coupled to their neighbours via additional variable resistors. As coupling resistance is decreased, phase synchronization followed by complete synchronization is observed, and onset of synchronization is associated with partial synchronization, i.e., emergence of communities (clusters). While component tolerances affect community structure, the general synchronization properties are maintained across three prototypes and in numerical simulations. The clusters are destroyed by adding long distance connections with distant notes, but are otherwise relatively stable with respect to structural connectivity changes. The study provides evidence that several fundamental synchronization phenomena can be reliably observed in a network of elementary single-transistor oscillators, demonstrating their generative potential and opening way to potential applications of this undemanding setup in experimental modelling of the relationship between network structure, synchronization, and dynamical properties.

Variability in functional brain networks predicts expertise during action observation.

PubMed

Amoruso, Lucía; Ibáñez, Agustín; Fonseca, Bruno; Gadea, Sebastián; Sedeño, Lucas; Sigman, Mariano; García, Adolfo M; Fraiman, Ricardo; Fraiman, Daniel

2017-02-01

Observing an action performed by another individual activates, in the observer, similar circuits as those involved in the actual execution of that action. This activation is modulated by prior experience; indeed, sustained training in a particular motor domain leads to structural and functional changes in critical brain areas. Here, we capitalized on a novel graph-theory approach to electroencephalographic data (Fraiman et al., 2016) to test whether variability in functional brain networks implicated in Tango observation can discriminate between groups differing in their level of expertise. We found that experts and beginners significantly differed in the functional organization of task-relevant networks. Specifically, networks in expert Tango dancers exhibited less variability and a more robust functional architecture. Notably, these expertise-dependent effects were captured within networks derived from electrophysiological brain activity recorded in a very short time window (2s). In brief, variability in the organization of task-related networks seems to be a highly sensitive indicator of long-lasting training effects. This finding opens new methodological and theoretical windows to explore the impact of domain-specific expertise on brain plasticity, while highlighting variability as a fruitful measure in neuroimaging research. Copyright © 2016 Elsevier Inc. All rights reserved.

Reactive molecular dynamics of network polymers: Generation, characterization and mechanical properties

NASA Astrophysics Data System (ADS)

Shankar, Chandrashekar

The goal of this research was to gain a fundamental understanding of the properties of networks created by the ring opening metathesis polymerization (ROMP) of dicyclopentadiene (DCPD) used in self-healing materials. To this end we used molecular simulation methods to generate realistic structures of DCPD networks, characterize their structures, and determine their mechanical properties. Density functional theory (DFT) calculations, complemented by structural information derived from molecular dynamics simulations were used to reconstruct experimental Raman spectra and differential scanning calorimetry (DSC) data. We performed coarse-grained simulations comparing networks generated via the ROMP reaction process and compared them to those generated via a RANDOM process, which led to the fundamental realization that the polymer topology has a unique influence on the network properties. We carried out fully atomistic simulations of DCPD using a novel algorithm for recreating ROMP reactions of DCPD molecules. Mechanical properties derived from these atomistic networks are in excellent agreement with those obtained from coarse-grained simulations in which interactions between nodes are subject to angular constraints. This comparison provides self-consistent validation of our simulation results and helps to identify the level of detail necessary for the coarse-grained interaction model. Simulations suggest networks can classified into three stages: fluid-like, rubber-like or glass-like delineated by two thresholds in degree of reaction alpha: The onset of finite magnitudes for the Young's modulus, alphaY, and the departure of the Poisson ration from 0.5, alphaP. In each stage the polymer exhibits a different predominant mechanical response to deformation. At low alpha < alphaY it flows. At alpha Y < alpha < alphaP the response is entropic with no change in internal energy. At alpha > alphaP the response is enthalpic change in internal energy. We developed graph theory-based network characterizations to correlate between network topology and the simulated mechanical properties. (1) Eigenvector centrality (2) Graph fractal dimension, (3) Fiedler partitioning, and (4) Cross-link fraction (Q3+Q4). Of these quantities, the Fiedler partition is the best characteristic for the prediction of Young's Modulus. The new computational tools developed in this research are of great fundamental and practical interest.

OpenMPI and ExxonMobil Topics

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

Hjelm, Nathan Thomas; Pritchard, Howard Porter

These are a series of slides for a presentation for ExxonMobil's visit to Los Alamos National Laboratory. Topics covered are: Open MPI - The Release Story, MPI-3 RMA in Open MPI, MPI dynamic process management and Open MPI, and new options with CLE 6. Open MPI RMA features are: since v2.0.0 full support for the MPI-3.1 specification, support for non-contiguous datatypes, support for direct use of the RDMA capabilities of high performance networks (Cray Gemini/Aries, Infiniband), starting in v2.1.0 will have support for using network atomic operations for MPI_Fetch_and_op and MPI_Compare_and_swap, tested with MPI_THREAD_MULTIPLE.

Open-WiSe: a solar powered wireless sensor network platform.

PubMed

González, Apolinar; Aquino, Raúl; Mata, Walter; Ochoa, Alberto; Saldaña, Pedro; Edwards, Arthur

2012-01-01

Because battery-powered nodes are required in wireless sensor networks and energy consumption represents an important design consideration, alternate energy sources are needed to provide more effective and optimal function. The main goal of this work is to present an energy harvesting wireless sensor network platform, the Open Wireless Sensor node (WiSe). The design and implementation of the solar powered wireless platform is described including the hardware architecture, firmware, and a POSIX Real-Time Kernel. A sleep and wake up strategy was implemented to prolong the lifetime of the wireless sensor network. This platform was developed as a tool for researchers investigating Wireless sensor network or system integrators.

Independent saturation of three TrpRS subsites generates a partially assembled state similar to those observed in molecular simulations

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

Laowanapiban, Poramaet; Kapustina, Maryna; Vonrhein, Clemens

2009-03-05

Two new crystal structures of Bacillus stearothermophilus tryptophanyl-tRNA synthetase (TrpRS) afford evidence that a closed interdomain hinge angle requires a covalent bond between AMP and an occupant of either pyrophosphate or tryptophan subsite. They also are within experimental error of a cluster of structures observed in a nonequilibrium molecular dynamics simulation showing partial active-site assembly. Further, the highest energy structure in a minimum action pathway computed by using elastic network models for Open and Pretransition state (PreTS) conformations for the fully liganded TrpRS monomer is intermediate between that simulated structure and a partially disassembled structure from a nonequilibrium molecular dynamicsmore » trajectory for the unliganded PreTS. These mutual consistencies provide unexpected validation of inferences drawn from molecular simulations.« less

Georgia-Armenia Transboarder seismicity studies

NASA Astrophysics Data System (ADS)

Godoladze, T.; Tvaradze, N.; Javakishvili, Z.; Elashvili, M.; Durgaryan, R.; Arakelyan, A.; Gevorgyan, M.

2012-12-01

In the presented study we performed Comprehensive seismic analyses for the Armenian-Georgian transboarder active seismic fault starting on Armenian territory, cutting the state boarder and having possibly northern termination on Adjara-Triealeti frontal structure in Georgia. In the scope of International projects: ISTC A-1418 "Open network of scientific Centers for mitigation risk of natural hazards in the Southern Caucasus and Central Asia" and NATO SfP- 983284 Project "Caucasus Seismic Emergency Response" in Akhalkalaki (Georgia) seismic center, Regional Summer school trainings and intensive filed investigations were conducted. Main goal was multidisciplinary study of the Javakheti fault structure and better understanding seismicity of the area. Young scientists from Turkey, Armenia, Azerbaijan and Georgia were participated in the deployment of temporal seismic network in order to monitor seisimity on the Javakheti highland and particularly delineate fault scarf and identify active seismic structures. In the scope of international collaboration the common seismic database has been created in the southern Caucasus and collected data from the field works is available now online. Javakheti highland, which is located in the central part of the Caucasus, belongs to the structure of the lesser Caucasus and represents a history of neotectonic volcanism existed in the area. Jasvakheti highland is seismicalu active region devastating from several severe earthquakes(1088, 1283, 1899…). Hypocenters located during analogue network were highly scattered and did not describe real pattern of seismicity of the highland. We relocated hypocenters of the region and improved local velocity model. The hypocenters derived from recently deployed local seismic network in the Javakheti highland, clearly identified seismically active structures. Fault plane solutions of analogue data of the Soviet times have been carefully analyzed and examined. Moment tensor inversion were preformed for the recent moderate size earthquakes and the results are in an agreement with paleo-trenching data showing normal fault mechanism on the south and strake slip on the northern edge of the fault. Local seismic tomography of Javakheti area has been performed in order to improve 3D structure of the region.

Thickness determination of biological samples with a zeta-calibrated scanning tunneling microscope.

PubMed Central

Wang, Z H; Hartmann, T; Baumeister, W; Guckenberger, R

1990-01-01

A single-tube scanning tunneling microscope has been zeta-calibrated by using atomic steps of crystalline gold and was used for measuring the thickness of two biological samples, metal-coated as well as uncoated. The hexagonal surface layer of the bacterium Deinococcus radiodurans with an open network-type structure shows thickness values that are strongly influenced by the substrate and the preparation method. In contrast, the thickness of the purple membrane of Halobacterium halobium with its densely packed less-corrugated structure exhibits very little variation in thickness in coated preparations and the values obtained are in good agreement with x-ray data. Images PMID:2251276

Experiments and 3D simulations of flow structures in junctions and their influence on location of flowmeters.

PubMed

Mignot, E; Bonakdari, H; Knothe, P; Lipeme Kouyi, G; Bessette, A; Rivière, N; Bertrand-Krajewski, J-L

2012-01-01

Open-channel junctions are common occurrences in sewer networks and flow rate measurement often occurs near these singularities. Local flow structures are 3D, impact on the representativeness of the local flow measurements and thus lead to deviations in the flow rate estimation. The present study aims (i) to measure and simulate the flow pattern in a junction flow, (ii) to analyse the impact of the junction on the velocity distribution according to the distance from the junction and thus (iii) to evaluate the typical error derived from the computation of the flow rate close to the junction.

Technology-dependent children and the demand for pharmaceutical care.

PubMed

Okido, Aline Cristiane Cavicchioli; Cunha, Suelen Teles da; Neves, Eliane Tatsch; Dupas, Giselle; Lima, Regina Aparecida Garcia de

2016-01-01

to understand the experience of mothers of technology-dependent children as regards pharmaceutical care. this was a qualitative, descriptive-exploratory study developed based on open interviews using a structured characterization tool, and applied during home visits to 12 mothers caring for technology-dependent children. The data was submitted to inductive content analysis. this study is split into two themes: (i) maternal overload during pharmaceutical care, demonstrating the need to administer drugs continuously and the repercussions of this exhaustive care on the caregivers; (ii) the ease or difficulty of access to the medicines required, showing informal strategies and support networks. pharmaceutical care is a daily challenge expressed in maternal overload and difficulty accessing the drugs, made worse by failures in the care network and coordinated care.

UK Experiences and Lessons Identified Using C-BML in Practical Experiments

DTIC Science & Technology

2014-06-01

network standards. Simple, unclassified networking has been conducted very successfully using OpenVPN [11] tunnels across the internet, even using...relatively low-bandwidth 3G cell-phone bridges. OpenVPN was used for much of the work of MSG-048 and -085. Experimentation has also been conducted using

Open College Networks and National Vocational Qualifications. A Development Paper.

ERIC Educational Resources Information Center

National Council for Vocational Qualifications, London (England).

Both the National Council for Vocational Qualifications (NCVQ) and Open College Networks or Federations (OCNs) have the objective of creating nationally coherent frameworks of qualification and training in Britain. However, they are very different organizations and have distinct, though potentially complementary, roles. Issues where the two…

Mechanical Network in Titin Immunoglobulin from Force Distribution Analysis

PubMed Central

Wilmanns, Matthias; Gräter, Frauke

2009-01-01

The role of mechanical force in cellular processes is increasingly revealed by single molecule experiments and simulations of force-induced transitions in proteins. How the applied force propagates within proteins determines their mechanical behavior yet remains largely unknown. We present a new method based on molecular dynamics simulations to disclose the distribution of strain in protein structures, here for the newly determined high-resolution crystal structure of I27, a titin immunoglobulin (IG) domain. We obtain a sparse, spatially connected, and highly anisotropic mechanical network. This allows us to detect load-bearing motifs composed of interstrand hydrogen bonds and hydrophobic core interactions, including parts distal to the site to which force was applied. The role of the force distribution pattern for mechanical stability is tested by in silico unfolding of I27 mutants. We then compare the observed force pattern to the sparse network of coevolved residues found in this family. We find a remarkable overlap, suggesting the force distribution to reflect constraints for the evolutionary design of mechanical resistance in the IG family. The force distribution analysis provides a molecular interpretation of coevolution and opens the road to the study of the mechanism of signal propagation in proteins in general. PMID:19282960

ChloroKB: A Web Application for the Integration of Knowledge Related to Chloroplast Metabolic Network1[OPEN

PubMed Central

Gloaguen, Pauline; Alban, Claude; Ravanel, Stéphane; Seigneurin-Berny, Daphné; Matringe, Michel; Ferro, Myriam; Bruley, Christophe; Rolland, Norbert; Vandenbrouck, Yves

2017-01-01

Higher plants, as autotrophic organisms, are effective sources of molecules. They hold great promise for metabolic engineering, but the behavior of plant metabolism at the network level is still incompletely described. Although structural models (stoichiometry matrices) and pathway databases are extremely useful, they cannot describe the complexity of the metabolic context, and new tools are required to visually represent integrated biocurated knowledge for use by both humans and computers. Here, we describe ChloroKB, a Web application (http://chlorokb.fr/) for visual exploration and analysis of the Arabidopsis (Arabidopsis thaliana) metabolic network in the chloroplast and related cellular pathways. The network was manually reconstructed through extensive biocuration to provide transparent traceability of experimental data. Proteins and metabolites were placed in their biological context (spatial distribution within cells, connectivity in the network, participation in supramolecular complexes, and regulatory interactions) using CellDesigner software. The network contains 1,147 reviewed proteins (559 localized exclusively in plastids, 68 in at least one additional compartment, and 520 outside the plastid), 122 proteins awaiting biochemical/genetic characterization, and 228 proteins for which genes have not yet been identified. The visual presentation is intuitive and browsing is fluid, providing instant access to the graphical representation of integrated processes and to a wealth of refined qualitative and quantitative data. ChloroKB will be a significant support for structural and quantitative kinetic modeling, for biological reasoning, when comparing novel data with established knowledge, for computer analyses, and for educational purposes. ChloroKB will be enhanced by continuous updates following contributions from plant researchers. PMID:28442501

The electro-structural behaviour of yarn-like carbon nanotube fibres immersed in organic liquids

NASA Astrophysics Data System (ADS)

Terrones, Jeronimo; Windle, Alan H.; Elliott, James A.

2014-10-01

Yarn-like carbon nanotube (CNT) fibres are a hierarchically-structured material with a variety of promising applications such as high performance composites, sensors and actuators, smart textiles, and energy storage and transmission. However, in order to fully realize these possibilities, a more detailed understanding of their interactions with the environment is required. In this work, we describe a simplified representation of the hierarchical structure of the fibres from which several mathematical models are constructed to explain electro-structural interactions of fibres with organic liquids. A balance between the elastic and surface energies of the CNT bundle network in different media allows the determination of the maximum lengths that open junctions can sustain before collapsing to minimize the surface energy. This characteristic length correlates well with the increase of fibre resistance upon immersion in organic liquids. We also study the effect of charge accumulation in open interbundle junctions and derive expressions to describe experimental data on the non-ohmic electrical behaviour of fibres immersed in polar liquids. Our analyses suggest that the non-ohmic behaviour is caused by progressively shorter junctions collapsing as the voltage is increased. Since our models are not based on any property unique to carbon nanotubes, they should also be useful to describe other hierarchical structures.

Communication security in open health care networks.

PubMed

Blobel, B; Pharow, P; Engel, K; Spiegel, V; Krohn, R

1999-01-01

Fulfilling the shared care paradigm, health care networks providing open systems' interoperability in health care are needed. Such communicating and co-operating health information systems, dealing with sensitive personal medical information across organisational, regional, national or even international boundaries, require appropriate security solutions. Based on the generic security model, within the European MEDSEC project an open approach for secure EDI like HL7, EDIFACT, XDT or XML has been developed. The consideration includes both securing the message in an unsecure network and the transport of the unprotected information via secure channels (SSL, TLS etc.). Regarding EDI, an open and widely usable security solution has been specified and practically implemented for the examples of secure mailing and secure file transfer (FTP) via wrapping the sensitive information expressed by the corresponding protocols. The results are currently prepared for standardisation.

Dynamic recruitment of resting state sub-networks

PubMed Central

O'Neill, George C.; Bauer, Markus; Woolrich, Mark W.; Morris, Peter G.; Barnes, Gareth R.; Brookes, Matthew J.

2015-01-01

Resting state networks (RSNs) are of fundamental importance in human systems neuroscience with evidence suggesting that they are integral to healthy brain function and perturbed in pathology. Despite rapid progress in this area, the temporal dynamics governing the functional connectivities that underlie RSN structure remain poorly understood. Here, we present a framework to help further our understanding of RSN dynamics. We describe a methodology which exploits the direct nature and high temporal resolution of magnetoencephalography (MEG). This technique, which builds on previous work, extends from solving fundamental confounds in MEG (source leakage) to multivariate modelling of transient connectivity. The resulting processing pipeline facilitates direct (electrophysiological) measurement of dynamic functional networks. Our results show that, when functional connectivity is assessed in small time windows, the canonical sensorimotor network can be decomposed into a number of transiently synchronising sub-networks, recruitment of which depends on current mental state. These rapidly changing sub-networks are spatially focal with, for example, bilateral primary sensory and motor areas resolved into two separate sub-networks. The likely interpretation is that the larger canonical sensorimotor network most often seen in neuroimaging studies reflects only a temporal aggregate of these transient sub-networks. Our approach opens new frontiers to study RSN dynamics, showing that MEG is capable of revealing the spatial, temporal and spectral signature of the human connectome in health and disease. PMID:25899137

Open hardware: a role to play in wireless sensor networks?

PubMed

Fisher, Roy; Ledwaba, Lehlogonolo; Hancke, Gerhard; Kruger, Carel

2015-03-20

The concept of the Internet of Things is rapidly becoming a reality, with many applications being deployed within industrial and consumer sectors. At the 'thing' level-devices and inter-device network communication-the core technical building blocks are generally the same as those found in wireless sensor network implementations. For the Internet of Things to continue growing, we need more plentiful resources for building intelligent devices and sensor networks. Unfortunately, current commercial devices, e.g., sensor nodes and network gateways, tend to be expensive and proprietary, which presents a barrier to entry and arguably slows down further development. There are, however, an increasing number of open embedded platforms available and also a wide selection of off-the-shelf components that can quickly and easily be built into device and network gateway solutions. The question is whether these solutions measure up to built-for-purpose devices. In the paper, we provide a comparison of existing built-for-purpose devices against open source devices. For comparison, we have also designed and rapidly prototyped a sensor node based on off-the-shelf components. We show that these devices compare favorably to built-for-purpose devices in terms of performance, power and cost. Using open platforms and off-the-shelf components would allow more developers to build intelligent devices and sensor networks, which could result in a better overall development ecosystem, lower barriers to entry and rapid growth in the number of IoT applications.

Open Hardware: A Role to Play in Wireless Sensor Networks?

PubMed Central

Fisher, Roy; Ledwaba, Lehlogonolo; Hancke, Gerhard; Kruger, Carel

2015-01-01

The concept of the Internet of Things is rapidly becoming a reality, with many applications being deployed within industrial and consumer sectors. At the ‘thing’ level—devices and inter-device network communication—the core technical building blocks are generally the same as those found in wireless sensor network implementations. For the Internet of Things to continue growing, we need more plentiful resources for building intelligent devices and sensor networks. Unfortunately, current commercial devices, e.g., sensor nodes and network gateways, tend to be expensive and proprietary, which presents a barrier to entry and arguably slows down further development. There are, however, an increasing number of open embedded platforms available and also a wide selection of off-the-shelf components that can quickly and easily be built into device and network gateway solutions. The question is whether these solutions measure up to built-for-purpose devices. In the paper, we provide a comparison of existing built-for-purpose devices against open source devices. For comparison, we have also designed and rapidly prototyped a sensor node based on off-the-shelf components. We show that these devices compare favorably to built-for-purpose devices in terms of performance, power and cost. Using open platforms and off-the-shelf components would allow more developers to build intelligent devices and sensor networks, which could result in a better overall development ecosystem, lower barriers to entry and rapid growth in the number of IoT applications. PMID:25803706

Dynamical networks of influence in small group discussions.

PubMed

Moussaïd, Mehdi; Noriega Campero, Alejandro; Almaatouq, Abdullah

2018-01-01

In many domains of life, business and management, numerous problems are addressed by small groups of individuals engaged in face-to-face discussions. While research in social psychology has a long history of studying the determinants of small group performances, the internal dynamics that govern a group discussion are not yet well understood. Here, we rely on computational methods based on network analyses and opinion dynamics to describe how individuals influence each other during a group discussion. We consider the situation in which a small group of three individuals engages in a discussion to solve an estimation task. We propose a model describing how group members gradually influence each other and revise their judgments over the course of the discussion. The main component of the model is an influence network-a weighted, directed graph that determines the extent to which individuals influence each other during the discussion. In simulations, we first study the optimal structure of the influence network that yields the best group performances. Then, we implement a social learning process by which individuals adapt to the past performance of their peers, thereby affecting the structure of the influence network in the long run. We explore the mechanisms underlying the emergence of efficient or maladaptive networks and show that the influence network can converge towards the optimal one, but only when individuals exhibit a social discounting bias by downgrading the relative performances of their peers. Finally, we find a late-speaker effect, whereby individuals who speak later in the discussion are perceived more positively in the long run and are thus more influential. The numerous predictions of the model can serve as a basis for future experiments, and this work opens research on small group discussion to computational social sciences.

The dynamic and geometric phase transition in the cellular network of pancreatic islet

NASA Astrophysics Data System (ADS)

Wang, Xujing

2013-03-01

The pancreatic islet is a micro-organ that contains several thousands of endocrine cells, majority of which being the insulin releasing β - cells . - cellsareexcitablecells , andarecoupledtoeachother through gap junctional channels. Here, using percolation theory, we investigate the role of network structure in determining the dynamics of the β-cell network. We show that the β-cell synchronization depends on network connectivity. More specifically, as the site occupancy is reducing, initially the β-cell synchronization is barely affected, until it reaches around a critical value, where the synchronization exhibit a sudden rapid decline, followed by an slow exponential tail. This critical value coincides with the critical site open probability for percolation transition. The dependence over bond strength is similar, exhibiting critical-behavior like dependence around a certain value of bond strength. These results suggest that the β-cell network undergoes a dynamic phase transition when the network is percolated. We further apply the findings to study diabetes. During the development of diabetes, the β - cellnetworkconnectivitydecreases . Siteoccupancyreducesfromthe reducing β-cell mass, and the bond strength is increasingly impaired from β-cell stress and chronic hyperglycemia. We demonstrate that the network dynamics around the percolation transition explain the disease dynamics around onset, including a long time mystery in diabetes, the honeymoon phenomenon.

A network dynamics approach to chemical reaction networks

NASA Astrophysics Data System (ADS)

van der Schaft, A. J.; Rao, S.; Jayawardhana, B.

2016-04-01

A treatment of a chemical reaction network theory is given from the perspective of nonlinear network dynamics, in particular of consensus dynamics. By starting from the complex-balanced assumption, the reaction dynamics governed by mass action kinetics can be rewritten into a form which allows for a very simple derivation of a number of key results in the chemical reaction network theory, and which directly relates to the thermodynamics and port-Hamiltonian formulation of the system. Central in this formulation is the definition of a balanced Laplacian matrix on the graph of chemical complexes together with a resulting fundamental inequality. This immediately leads to the characterisation of the set of equilibria and their stability. Furthermore, the assumption of complex balancedness is revisited from the point of view of Kirchhoff's matrix tree theorem. Both the form of the dynamics and the deduced behaviour are very similar to consensus dynamics, and provide additional perspectives to the latter. Finally, using the classical idea of extending the graph of chemical complexes by a 'zero' complex, a complete steady-state stability analysis of mass action kinetics reaction networks with constant inflows and mass action kinetics outflows is given, and a unified framework is provided for structure-preserving model reduction of this important class of open reaction networks.

Adaptive Neural Network Based Control of Noncanonical Nonlinear Systems.

PubMed

Zhang, Yanjun; Tao, Gang; Chen, Mou

2016-09-01

This paper presents a new study on the adaptive neural network-based control of a class of noncanonical nonlinear systems with large parametric uncertainties. Unlike commonly studied canonical form nonlinear systems whose neural network approximation system models have explicit relative degree structures, which can directly be used to derive parameterized controllers for adaptation, noncanonical form nonlinear systems usually do not have explicit relative degrees, and thus their approximation system models are also in noncanonical forms. It is well-known that the adaptive control of noncanonical form nonlinear systems involves the parameterization of system dynamics. As demonstrated in this paper, it is also the case for noncanonical neural network approximation system models. Effective control of such systems is an open research problem, especially in the presence of uncertain parameters. This paper shows that it is necessary to reparameterize such neural network system models for adaptive control design, and that such reparameterization can be realized using a relative degree formulation, a concept yet to be studied for general neural network system models. This paper then derives the parameterized controllers that guarantee closed-loop stability and asymptotic output tracking for noncanonical form neural network system models. An illustrative example is presented with the simulation results to demonstrate the control design procedure, and to verify the effectiveness of such a new design method.

[Benefit and Sustainability of Networks for workplace Health Promotion in SME Examined at the SME Networks "Bewegte Unternehmen" and "Vitale Unternehmen"].

PubMed

Müller, Eva; Fischmann, Wolfgang; Kötter, Rudolf; Drexler, Hans; Kiesel, Johannes

2018-05-01

The purpose of the study was to analyze if 2 regional networks of small and medium enterprises (SME) for workplace health promotion are sustainable, and to find out the motivation of the enterprises to join the network. It was also examined if there is a stable culture of cooperation 6 -10 years after the founding of the network. Additionally, the study checked the current work and suggestions for improvement to the network structure, so that in the future, promotion of workplace health can be further improved. 2 regional networks, founded in 2005 and 2009, were studied. Standardized telephone interviews carried out between September 2013 and January 2014 enabled data collection for this cross-sectional study. 42 interviews with 6 open questions were organized with the managers of the companies or the person responsible for workplace health promotion. The results of the study show that 88.1% (n=37) of the network company members profited from the exchange of experiences. 50.0% (n=21) benefited from shared activities and 28.6% (n=12) from making new contacts. 9.5% (n=4) of the respondents expressed concerns about excessive bureaucracy resulting in too much effort for too little benefit and 7.1% (n=3) were also missing comprehensive structural measures. Suggestions for improvement were enhancement of practical work (26.2%, n=11) and the wish for stronger commitment (11.9%, n=5). 90.5% (n=38) considered their expectations as fulfilled and 66.7% (n=28) evaluated the current work as being quite positive. The networks have turned out to be sustainable, proven by the fact that the companies still are members of the networks for 6 and 10 years, respectively and are still satisfied with the network. The study shows that the majority of the members profits from the membership of these regional networks. Networks can help them to implement permanent workplace health promotion. To further improve the work of the network, a systematic and scientific workplace health promotion scheme is recommended. © Georg Thieme Verlag KG Stuttgart · New York.

Software Defined Networking challenges and future direction: A case study of implementing SDN features on OpenStack private cloud

NASA Astrophysics Data System (ADS)

Shamugam, Veeramani; Murray, I.; Leong, J. A.; Sidhu, Amandeep S.

2016-03-01

Cloud computing provides services on demand instantly, such as access to network infrastructure consisting of computing hardware, operating systems, network storage, database and applications. Network usage and demands are growing at a very fast rate and to meet the current requirements, there is a need for automatic infrastructure scaling. Traditional networks are difficult to automate because of the distributed nature of their decision making process for switching or routing which are collocated on the same device. Managing complex environments using traditional networks is time-consuming and expensive, especially in the case of generating virtual machines, migration and network configuration. To mitigate the challenges, network operations require efficient, flexible, agile and scalable software defined networks (SDN). This paper discuss various issues in SDN and suggests how to mitigate the network management related issues. A private cloud prototype test bed was setup to implement the SDN on the OpenStack platform to test and evaluate the various network performances provided by the various configurations.

A Dedicated Computational Platform for Cellular Monte Carlo T-CAD Software Tools

DTIC Science & Technology

2015-07-14

computer that establishes an encrypted Virtual Private Network ( OpenVPN [44]) based on the Secure Socket Layer (SSL) paradigm. Each user is given a...security certificate for each device used to connect to the computing nodes. Stable OpenVPN clients are available for Linux, Microsoft Windows, Apple OSX...platform is granted by an encrypted connection base on the Secure Socket Layer (SSL) protocol, and implemented in the OpenVPN Virtual Personal Network

SEnviro: a sensorized platform proposal using open hardware and open standards.

PubMed

Trilles, Sergio; Luján, Alejandro; Belmonte, Óscar; Montoliu, Raúl; Torres-Sospedra, Joaquín; Huerta, Joaquín

2015-03-06

The need for constant monitoring of environmental conditions has produced an increase in the development of wireless sensor networks (WSN). The drive towards smart cities has produced the need for smart sensors to be able to monitor what is happening in our cities. This, combined with the decrease in hardware component prices and the increase in the popularity of open hardware, has favored the deployment of sensor networks based on open hardware. The new trends in Internet Protocol (IP) communication between sensor nodes allow sensor access via the Internet, turning them into smart objects (Internet of Things and Web of Things). Currently, WSNs provide data in different formats. There is a lack of communication protocol standardization, which turns into interoperability issues when connecting different sensor networks or even when connecting different sensor nodes within the same network. This work presents a sensorized platform proposal that adheres to the principles of the Internet of Things and theWeb of Things. Wireless sensor nodes were built using open hardware solutions, and communications rely on the HTTP/IP Internet protocols. The Open Geospatial Consortium (OGC) SensorThings API candidate standard was used as a neutral format to avoid interoperability issues. An environmental WSN developed following the proposed architecture was built as a proof of concept. Details on how to build each node and a study regarding energy concerns are presented.

SEnviro: A Sensorized Platform Proposal Using Open Hardware and Open Standards

PubMed Central

Trilles, Sergio; Luján, Alejandro; Belmonte, Óscar; Montoliu, Raúl; Torres-Sospedra, Joaquín; Huerta, Joaquín

2015-01-01

The need for constant monitoring of environmental conditions has produced an increase in the development of wireless sensor networks (WSN). The drive towards smart cities has produced the need for smart sensors to be able to monitor what is happening in our cities. This, combined with the decrease in hardware component prices and the increase in the popularity of open hardware, has favored the deployment of sensor networks based on open hardware. The new trends in Internet Protocol (IP) communication between sensor nodes allow sensor access via the Internet, turning them into smart objects (Internet of Things and Web of Things). Currently, WSNs provide data in different formats. There is a lack of communication protocol standardization, which turns into interoperability issues when connecting different sensor networks or even when connecting different sensor nodes within the same network. This work presents a sensorized platform proposal that adheres to the principles of the Internet of Things and the Web of Things. Wireless sensor nodes were built using open hardware solutions, and communications rely on the HTTP/IP Internet protocols. The Open Geospatial Consortium (OGC) SensorThings API candidate standard was used as a neutral format to avoid interoperability issues. An environmental WSN developed following the proposed architecture was built as a proof of concept. Details on how to build each node and a study regarding energy concerns are presented. PMID:25756864

Superconducting Open-Framework Allotrope of Silicon at Ambient Pressure

NASA Astrophysics Data System (ADS)

Sung, Ha-Jun; Han, W. H.; Lee, In-Ho; Chang, K. J.

2018-04-01

Diamond Si is a semiconductor with an indirect band gap that is the basis of modern semiconductor technology. Although many metastable forms of Si were observed using diamond anvil cells for compression and chemical precursors for synthesis, no metallic phase at ambient conditions has been reported thus far. Here we report the prediction of pure metallic Si allotropes with open channels at ambient pressure, unlike a cubic diamond structure in covalent bonding networks. The metallic phase termed P 6 /m -Si6 can be obtained by removing Na after pressure release from a novel Na-Si clathrate called P 6 /m -NaSi6 , which is predicted through first-principles study at high pressure. We identify that both P 6 /m -NaSi6 and P 6 /m -Si6 are stable and superconducting with the critical temperatures of about 13 and 12 K at ambient pressure, respectively. The prediction of new Na-Si and Si clathrate structures presents the possibility of exploring new exotic allotropes useful for Si-based devices.

Superconducting Open-Framework Allotrope of Silicon at Ambient Pressure.

PubMed

Sung, Ha-Jun; Han, W H; Lee, In-Ho; Chang, K J

2018-04-13

Diamond Si is a semiconductor with an indirect band gap that is the basis of modern semiconductor technology. Although many metastable forms of Si were observed using diamond anvil cells for compression and chemical precursors for synthesis, no metallic phase at ambient conditions has been reported thus far. Here we report the prediction of pure metallic Si allotropes with open channels at ambient pressure, unlike a cubic diamond structure in covalent bonding networks. The metallic phase termed P6/m-Si_{6} can be obtained by removing Na after pressure release from a novel Na-Si clathrate called P6/m-NaSi_{6}, which is predicted through first-principles study at high pressure. We identify that both P6/m-NaSi_{6} and P6/m-Si_{6} are stable and superconducting with the critical temperatures of about 13 and 12 K at ambient pressure, respectively. The prediction of new Na-Si and Si clathrate structures presents the possibility of exploring new exotic allotropes useful for Si-based devices.

An open source high-performance solution to extract surface water drainage networks from diverse terrain conditions

USGS Publications Warehouse

Stanislawski, Larry V.; Survila, Kornelijus; Wendel, Jeffrey; Liu, Yan; Buttenfield, Barbara P.

2018-01-01

This paper describes a workflow for automating the extraction of elevation-derived stream lines using open source tools with parallel computing support and testing the effectiveness of procedures in various terrain conditions within the conterminous United States. Drainage networks are extracted from the US Geological Survey 1/3 arc-second 3D Elevation Program elevation data having a nominal cell size of 10 m. This research demonstrates the utility of open source tools with parallel computing support for extracting connected drainage network patterns and handling depressions in 30 subbasins distributed across humid, dry, and transitional climate regions and in terrain conditions exhibiting a range of slopes. Special attention is given to low-slope terrain, where network connectivity is preserved by generating synthetic stream channels through lake and waterbody polygons. Conflation analysis compares the extracted streams with a 1:24,000-scale National Hydrography Dataset flowline network and shows that similarities are greatest for second- and higher-order tributaries.

Opening Public Administration: Exploring Open Innovation Archetypes and Business Model Impacts

NASA Astrophysics Data System (ADS)

Feller, Joseph; Finnegan, Patrick; Nilsson, Olof

This work-in-progress paper presents an exploration of a network of Swedish municipal authorities. Within this network, we have observed a move from isolated innovation to leveraging inflows and outflows of knowledge in a manner characteristic of the open innovation paradigm. This paper presents a characterization of these knowledge exchanges using an existing framework of open innovation archetypes, as well as an initial description of the business model impacts of this innovation approach on the participant municipalities, and the enabling role of information technology. The paper concludes by drawing preliminary conclusions and outlining ongoing research.

Multi-Domain SDN Survivability for Agricultural Wireless Sensor Networks.

PubMed

Huang, Tao; Yan, Siyu; Yang, Fan; Liu, Jiang

2016-11-06

Wireless sensor networks (WSNs) have been widely applied in agriculture field; meanwhile, the advent of multi-domain software-defined networks (SDNs) have improved the wireless resource utilization rate and strengthened network management. In recent times, multi-domain SDNs have been applied to agricultural sensor networks, namely multi-domain software-defined wireless sensor networks (SDWSNs). However, when the SDNs controlling agriculture networks suddenly become unavailable, whether intra-domain or inter-domain, sensor network communication is abnormal because of the loss of control. Moreover, there are controller and switch info-updating problems even if the controller becomes available again. To resolve these problems, this paper proposes a new approach based on an Open vSwitch extension for multi-domain SDWSNs, which can enhance agriculture network survivability and stability. We achieved this by designing a connection-state mechanism, a communication mechanism on both L2 and L3, and an info-updating mechanism based on Open vSwitch. The experimental results show that, whether it is agricultural inter-domain or intra-domain during the controller failure period, the sensor switches can enter failure recovery mode as soon as possible so that the sensor network keeps a stable throughput, a short failure recovery time below 300 ms, and low packet loss. Further, the domain can smoothly control the domain network again once the controller becomes available. This approach based on an Open vSwitch extension can enhance the survivability and stability of multi-domain SDWSNs in precision agriculture.

Multi-Domain SDN Survivability for Agricultural Wireless Sensor Networks

PubMed Central

Huang, Tao; Yan, Siyu; Yang, Fan; Liu, Jiang

2016-01-01

Wireless sensor networks (WSNs) have been widely applied in agriculture field; meanwhile, the advent of multi-domain software-defined networks (SDNs) have improved the wireless resource utilization rate and strengthened network management. In recent times, multi-domain SDNs have been applied to agricultural sensor networks, namely multi-domain software-defined wireless sensor networks (SDWSNs). However, when the SDNs controlling agriculture networks suddenly become unavailable, whether intra-domain or inter-domain, sensor network communication is abnormal because of the loss of control. Moreover, there are controller and switch info-updating problems even if the controller becomes available again. To resolve these problems, this paper proposes a new approach based on an Open vSwitch extension for multi-domain SDWSNs, which can enhance agriculture network survivability and stability. We achieved this by designing a connection-state mechanism, a communication mechanism on both L2 and L3, and an info-updating mechanism based on Open vSwitch. The experimental results show that, whether it is agricultural inter-domain or intra-domain during the controller failure period, the sensor switches can enter failure recovery mode as soon as possible so that the sensor network keeps a stable throughput, a short failure recovery time below 300 ms, and low packet loss. Further, the domain can smoothly control the domain network again once the controller becomes available. This approach based on an Open vSwitch extension can enhance the survivability and stability of multi-domain SDWSNs in precision agriculture. PMID:27827971

Monolithic porous magnesium silicide.

PubMed

Hayati-Roodbari, N; Berger, R J F; Bernardi, J; Kinge, S; Hüsing, N; Elsaesser, M S

2017-07-11

Macroporous magnesium silicide monoliths were successfully prepared by a two-step synthesis procedure. The reaction of gaseous magnesium vapor with macro-/mesoporous silicon, which was generated from hierarchically organized meso-/macroporous silica by a magnesiothermic reduction reaction, resulted in monolithic magnesium silicide with a cellular, open macroporous structure. By adjusting the reaction conditions, such as experimental set-up, temperature and time, challenges namely loss of porosity or phase purity of Mg 2 Si were addressed and monolithic magnesium silicide with a cellular network builtup was obtained.

Effects of gliadin addition on the rheological, microscopic and thermal characteristics of wheat gluten.

PubMed

Khatkar, B S; Barak, Sheweta; Mudgil, Deepak

2013-02-01

In the present study, micro-structural, thermal and rheological changes in the gluten network upon addition of gliadins at 5% and 10% levels were investigated using scanning electron microscopy (SEM), thermo gravimetric analysis (TGA), differential scanning calorimetry (DSC) and dynamic rheometry. The addition of gliadins decreased the peak dough height inferring decrease in dough strength. The dough stability also decreased from 3.20 to 1.40 min upon addition of 10% gliadin to the base flour. The TGA profile and the glass transition behavior of the control gluten and gluten obtained from dough with gliadin added at 5% and 10% levels showed decrease in thermal stability. The SEM micrograph of the control gluten showed foam like protein matrix. As the gliadin percentage in the gluten was increased, the compactness of the gluten structure reduced considerably leading to the formation of a more open weak gluten network. Copyright © 2012 Elsevier B.V. All rights reserved.

Soft network composite materials with deterministic and bio-inspired designs

PubMed Central

Jang, Kyung-In; Chung, Ha Uk; Xu, Sheng; Lee, Chi Hwan; Luan, Haiwen; Jeong, Jaewoong; Cheng, Huanyu; Kim, Gwang-Tae; Han, Sang Youn; Lee, Jung Woo; Kim, Jeonghyun; Cho, Moongee; Miao, Fuxing; Yang, Yiyuan; Jung, Han Na; Flavin, Matthew; Liu, Howard; Kong, Gil Woo; Yu, Ki Jun; Rhee, Sang Il; Chung, Jeahoon; Kim, Byunggik; Kwak, Jean Won; Yun, Myoung Hee; Kim, Jin Young; Song, Young Min; Paik, Ungyu; Zhang, Yihui; Huang, Yonggang; Rogers, John A.

2015-01-01

Hard and soft structural composites found in biology provide inspiration for the design of advanced synthetic materials. Many examples of bio-inspired hard materials can be found in the literature; far less attention has been devoted to soft systems. Here we introduce deterministic routes to low-modulus thin film materials with stress/strain responses that can be tailored precisely to match the non-linear properties of biological tissues, with application opportunities that range from soft biomedical devices to constructs for tissue engineering. The approach combines a low-modulus matrix with an open, stretchable network as a structural reinforcement that can yield classes of composites with a wide range of desired mechanical responses, including anisotropic, spatially heterogeneous, hierarchical and self-similar designs. Demonstrative application examples in thin, skin-mounted electrophysiological sensors with mechanics precisely matched to the human epidermis and in soft, hydrogel-based vehicles for triggered drug release suggest their broad potential uses in biomedical devices. PMID:25782446

Changes in the Structure of the Microbial Community Associated with Nannochloropsis salina following Treatments with Antibiotics and Bioactive Compounds

PubMed Central

Geng, Haifeng; Tran-Gyamfi, Mary B.; Lane, Todd W.; Sale, Kenneth L.; Yu, Eizadora T.

2016-01-01

Open microalgae cultures host a myriad of bacteria, creating a complex system of interacting species that influence algal growth and health. Many algal microbiota studies have been conducted to determine the relative importance of bacterial taxa to algal culture health and physiological states, but these studies have not characterized the interspecies relationships in the microbial communities. We subjected Nanochroloropsis salina cultures to multiple chemical treatments (antibiotics and quorum sensing compounds) and obtained dense time-series data on changes to the microbial community using 16S gene amplicon metagenomic sequencing (21,029,577 reads for 23 samples) to measure microbial taxa-taxa abundance correlations. Short-term treatment with antibiotics resulted in substantially larger shifts in the microbiota structure compared to changes observed following treatment with signaling compounds and glucose. We also calculated operational taxonomic unit (OTU) associations and generated OTU correlation networks to provide an overview of possible bacterial OTU interactions. This analysis identified five major cohesive modules of microbiota with similar co-abundance profiles across different chemical treatments. The Eigengenes of OTU modules were examined for correlation with different external treatment factors. This correlation-based analysis revealed that culture age (time) and treatment types have primary effects on forming network modules and shaping the community structure. Additional network analysis detected Alteromonadeles and Alphaproteobacteria as having the highest centrality, suggesting these species are “keystone” OTUs in the microbial community. Furthermore, we illustrated that the chemical tropodithietic acid, which is secreted by several species in the Alphaproteobacteria taxon, is able to drastically change the structure of the microbiota within 3 h. Taken together, these results provide valuable insights into the structure of the microbiota associated with N. salina cultures and how these structures change in response to chemical perturbations. PMID:27507966

Open-WiSe: A Solar Powered Wireless Sensor Network Platform

PubMed Central

González, Apolinar; Aquino, Raúl; Mata, Walter; Ochoa, Alberto; Saldaña, Pedro; Edwards, Arthur

2012-01-01

Because battery-powered nodes are required in wireless sensor networks and energy consumption represents an important design consideration, alternate energy sources are needed to provide more effective and optimal function. The main goal of this work is to present an energy harvesting wireless sensor network platform, the Open Wireless Sensor node (WiSe). The design and implementation of the solar powered wireless platform is described including the hardware architecture, firmware, and a POSIX Real-Time Kernel. A sleep and wake up strategy was implemented to prolong the lifetime of the wireless sensor network. This platform was developed as a tool for researchers investigating Wireless sensor network or system integrators. PMID:22969396

Modeling ecological drivers in marine viral communities using comparative metagenomics and network analyses.

PubMed

Hurwitz, Bonnie L; Westveld, Anton H; Brum, Jennifer R; Sullivan, Matthew B

2014-07-22

Long-standing questions in marine viral ecology are centered on understanding how viral assemblages change along gradients in space and time. However, investigating these fundamental ecological questions has been challenging due to incomplete representation of naturally occurring viral diversity in single gene- or morphology-based studies and an inability to identify up to 90% of reads in viral metagenomes (viromes). Although protein clustering techniques provide a significant advance by helping organize this unknown metagenomic sequence space, they typically use only ∼75% of the data and rely on assembly methods not yet tuned for naturally occurring sequence variation. Here, we introduce an annotation- and assembly-free strategy for comparative metagenomics that combines shared k-mer and social network analyses (regression modeling). This robust statistical framework enables visualization of complex sample networks and determination of ecological factors driving community structure. Application to 32 viromes from the Pacific Ocean Virome dataset identified clusters of samples broadly delineated by photic zone and revealed that geographic region, depth, and proximity to shore were significant predictors of community structure. Within subsets of this dataset, depth, season, and oxygen concentration were significant drivers of viral community structure at a single open ocean station, whereas variability along onshore-offshore transects was driven by oxygen concentration in an area with an oxygen minimum zone and not depth or proximity to shore, as might be expected. Together these results demonstrate that this highly scalable approach using complete metagenomic network-based comparisons can both test and generate hypotheses for ecological investigation of viral and microbial communities in nature.

Modeling ecological drivers in marine viral communities using comparative metagenomics and network analyses

PubMed Central

Hurwitz, Bonnie L.; Westveld, Anton H.; Brum, Jennifer R.; Sullivan, Matthew B.

2014-01-01

Long-standing questions in marine viral ecology are centered on understanding how viral assemblages change along gradients in space and time. However, investigating these fundamental ecological questions has been challenging due to incomplete representation of naturally occurring viral diversity in single gene- or morphology-based studies and an inability to identify up to 90% of reads in viral metagenomes (viromes). Although protein clustering techniques provide a significant advance by helping organize this unknown metagenomic sequence space, they typically use only ∼75% of the data and rely on assembly methods not yet tuned for naturally occurring sequence variation. Here, we introduce an annotation- and assembly-free strategy for comparative metagenomics that combines shared k-mer and social network analyses (regression modeling). This robust statistical framework enables visualization of complex sample networks and determination of ecological factors driving community structure. Application to 32 viromes from the Pacific Ocean Virome dataset identified clusters of samples broadly delineated by photic zone and revealed that geographic region, depth, and proximity to shore were significant predictors of community structure. Within subsets of this dataset, depth, season, and oxygen concentration were significant drivers of viral community structure at a single open ocean station, whereas variability along onshore–offshore transects was driven by oxygen concentration in an area with an oxygen minimum zone and not depth or proximity to shore, as might be expected. Together these results demonstrate that this highly scalable approach using complete metagenomic network-based comparisons can both test and generate hypotheses for ecological investigation of viral and microbial communities in nature. PMID:25002514

A REST-ful interpretation for embedded modular systems based on open architecture

NASA Astrophysics Data System (ADS)

Lyke, James

2016-05-01

The much-anticipated revolution of the "Internet of things" (IoT) is expected to generate one trillion internet devices within the next 15 years, mostly in the form of simple wireless sensor devices. While this revolution promises to transform silicon markets and drive a number of disruptive changes in society, it is also the case that the protocols, complexity, and security issues of extremely large dynamic, co-mingled networks is still poorly understood. Furthermore, embedded system developers, to include military and aerospace users, have largely ignored the potential (good and bound) of the cloudlike, possibly intermingling networks having variable structure to how future systems might be engineered. In this paper, we consider a new interpretation of IoT inspired modular architecture strategies involving the representational state transfer (REST) model, in which dynamic networks with variable structure employ stateless application programming interface (API) concepts. The power of the method, which extends concepts originally developed for space plug-and-play avionics, is that it allows for the fluid co-mingling of hardware and software in networks whose structure can overlap and evolve. Paradoxically, these systems may have the most stringent determinism and fault-tolerant needs. In this paper we review how RESTful APIs can potentially be used to design, create, test, and deploy systems rapidly while addressing security and referential integrity even when the nodes of many systems might physically co-mingle. We will also explore ways to take advantage of the RESTful paradigm for fault tolerance and what extensions might be necessary to deal with high-performance and determinism.

Social network based dynamic transit service through the OMITS system.

DOT National Transportation Integrated Search

2014-02-01

The Open Mode Integrated Transportation System (OMITS) forms a sustainable information infrastructure for communication within and between the mobile/Internet network, the roadway : network, and the users social network. It manipulates the speed g...

[Development and Use of Hidrosig

NASA Technical Reports Server (NTRS)

Gupta, Vijay K.; Milne, Bruce T.

2003-01-01

The NASA portion of this joint NSF-NASA grant consists of objective 2 and a part of objective 3. A major effort was made on objective 2, and it consisted of developing a numerical GIs environment called Hidrosig. This major research tool is being developed by the University of Colorado for conducting river-network-based scaling analyses of coupled water-energy-landform-vegetation interactions including water and energy balances, and floods and droughts, at multiple space-time scales.Objective 2: To analyze the relevant remotely sensed products from satellites, radars and ground measurements to compute the transported water mass for each complete Strahler stream using an 'assimilated water balance equation' at daily and other appropriate time scales. This objective requires analysis of concurrent data sets for Precipitation (PPT), Evapotranspiration (ET) and stream flows (Q) on river networks. To solve this major problem, our decision was to develop Hidrosig, a new Open-Source GIs software. A research group in Colombia, South America, developed the first version of Hidrosig, and Ricardo Mantilla was part of this effort as an undergraduate student before joining the graduate program at the University of Colorado in 2001. Hydrosig automatically extracts river networks from large DEMs and creates a "link-based" data structure, which is required to conduct a variety of analyses under objective 2. It is programmed in Java, which is a multi-platform programming language freely distributed by SUN under a GPL license. Some existent commercial tools like Arc-Info, RiverTools and others are not suitable for our purpose for two reasons. First, the source code is not available that is needed to build on the network data structure. Second, these tools use different programming languages that are not most versatile for our purposes. For example, RiverTools uses an IDL platform that is not very efficient for organizing diverse data sets on river networks. Hidrosig establishes a clear data organization framework that allows a simultaneous analysis of spatial fields along river network structures involving Horton- Strahler framework. Software tools for network extraction from DEMs and network-based analysis of geomorphologic and topologic variables were developed during the first year and a part of second year.

Social Networking: A Collaborative Open Educational Resource

ERIC Educational Resources Information Center

Toetenel, Lisette

2014-01-01

Studies undertaken since the introduction of Web 2.0 have focussed mainly on open educational resources (OERs) such as email, blogging and virtual learning environments. No consistent efforts have been undertaken to study the use of social networking sites as a tool for learning in the second language classroom. This study examined the use of…

Coupled Hydro-mechanical process of natural fracture network formation in sedimentary basin

NASA Astrophysics Data System (ADS)

Ouraga, zady; Guy, Nicolas; Pouya, amade

2017-04-01

In sedimentary basin numerous phenomenon depending on the geological time span and its history can lead to a decrease in effective stress and therefore result in fracture initiation. Thus, during its formation, under certain conditions, natural fracturing and fracture network formation can occur in various context such as under erosion, tectonic loading and the compaction disequilibrium due to significant sedimentation rate. In this work, natural fracture network and fracture spacing induced by significant sedimentation rate is studied considering mode I fracture propagation, using a coupled hydro-mechanical numerical methods. Assumption of vertical fracture can be considered as a relevant hypothesis in our case of low ratio of horizontal total stress to vertical stress. A particular emphasis is put on synthetic geological structure on which a constant sedimentation rate is imposed on its top. This synthetic geological structure contains defects initially closed and homogeneously distributed. The Fractures are modeled with a constitutive model undergoing damage and the flow is described by poiseuille's law. The damage parameter affects both the mechanical and the hydraulic opening of the fracture. For the numerical simulations, the code Porofis based on finite element modeling is used, fractures are taken into account by cohesive model and the flow is described by Poiseuille's law. The effect of several parameters is also studied and the analysis lead to a fracture network and fracture spacing criterion for basin modeling.

Water-level data for the Albuquerque Basin and adjacent areas, central New Mexico, period of record through September 30, 2013

USGS Publications Warehouse

Beman, Joseph E.

2014-01-01

The Albuquerque Basin, located in central New Mexico, is about 100 miles long and 25–40 miles wide. The basin is defined as the extent of consolidated and unconsolidated deposits of Tertiary and Quaternary age that encompasses the structural Rio Grande Rift within the basin. Drinking-water supplies throughout the basin were obtained solely from groundwater resources until December 2008, when treatment and distribution of surface water from the Rio Grande began. A population increase of about 20 percent in the basin from 1990 to 2000 and a 22-percent increase from 2000 to 2010 resulted in an increased demand for water. An initial network of wells was established by the U.S. Geological Survey (USGS) in cooperation with the City of Albuquerque from April 1982 through September 1983 to monitor changes in groundwater levels throughout the basin. This network consisted of 6 wells with analog-to-digital recorders and 27 wells where water levels were measured monthly in 1983. Currently (2013), the network consists of 123 wells and piezometers. (A piezometer is a specialized well open to a specific depth in the aquifer, often of small diameter and nested with other piezometers open to different depths.) The USGS, in cooperation with the Albuquerque Bernalillo County Water Utility Authority, currently (2013) measures and reports water levels from the 123 wells and piezometers in the network; this report presents water-level data collected by USGS personnel at those 123 sites through water year 2013.

Water-level data for the Albuquerque Basin and adjacent areas, central New Mexico, period of record through September 30, 2012

USGS Publications Warehouse

Beman, Joseph E.

2013-01-01

The Albuquerque Basin, located in central New Mexico, is about 100 miles long and 25-40 miles wide. The basin is defined as the extent of consolidated and unconsolidated deposits of Tertiary and Quaternary age that encompasses the structural Rio Grande Rift within the basin. Drinking-water supplies throughout the basin were obtained solely from groundwater resources until December 2008, when surface water from the Rio Grande began being treated and integrated into the system. A population increase of about 20 percent in the basin from 1990 to 2000 and a 22 percent increase from 2000 to 2010 resulted in an increased demand for water. An initial network of wells was established by the U.S. Geological Survey (USGS) in cooperation with the City of Albuquerque from April 1982 through September 1983 to monitor changes in groundwater levels throughout the basin. This network consisted of 6 wells with analog-to-digital recorders and 27 wells where water levels were measured monthly in 1983. Currently (2012), the network consists of 126 wells and piezometers. (A piezometer is a specialized well open to a specific depth in the aquifer, often of small diameter and nested with other piezometers open to different depths.) The USGS, in cooperation with the Albuquerque Bernalillo County Water Utility Authority (ABCWUA), currently (2012) measures and reports water levels from the 126 wells and piezometers in the network; this report presents water-level data collected by USGS personnel at those 126 sites through water year 2012.

Back to the biology in systems biology: what can we learn from biomolecular networks?

PubMed

Huang, Sui

2004-02-01

Genome-scale molecular networks, including protein interaction and gene regulatory networks, have taken centre stage in the investigation of the burgeoning disciplines of systems biology and biocomplexity. What do networks tell us? Some see in networks simply the comprehensive, detailed description of all cellular pathways, others seek in networks simple, higher-order qualities that emerge from the collective action of the individual pathways. This paper discusses networks from an encompassing category of thinking that will hopefully help readers to bridge the gap between these polarised viewpoints. Systems biology so far has emphasised the characterisation of large pathway maps. Now one has to ask: where is the actual biology in 'systems biology'? As structures midway between genome and phenome, and by serving as an 'extended genotype' or an 'elementary phenotype', molecular networks open a new window to the study of evolution and gene function in complex living systems. For the study of evolution, features in network topology offer a novel starting point for addressing the old debate on the relative contributions of natural selection versus intrinsic constraints to a particular trait. To study the function of genes, it is necessary not only to see them in the context of gene networks, but also to reach beyond describing network topology and to embrace the global dynamics of networks that will reveal higher-order, collective behaviour of the interacting genes. This will pave the way to understanding how the complexity of genome-wide molecular networks collapses to produce a robust whole-cell behaviour that manifests as tightly-regulated switching between distinct cell fates - the basis for multicellular life.

The Evolutionary Origins of Hierarchy

PubMed Central

Huizinga, Joost; Clune, Jeff

2016-01-01

Hierarchical organization—the recursive composition of sub-modules—is ubiquitous in biological networks, including neural, metabolic, ecological, and genetic regulatory networks, and in human-made systems, such as large organizations and the Internet. To date, most research on hierarchy in networks has been limited to quantifying this property. However, an open, important question in evolutionary biology is why hierarchical organization evolves in the first place. It has recently been shown that modularity evolves because of the presence of a cost for network connections. Here we investigate whether such connection costs also tend to cause a hierarchical organization of such modules. In computational simulations, we find that networks without a connection cost do not evolve to be hierarchical, even when the task has a hierarchical structure. However, with a connection cost, networks evolve to be both modular and hierarchical, and these networks exhibit higher overall performance and evolvability (i.e. faster adaptation to new environments). Additional analyses confirm that hierarchy independently improves adaptability after controlling for modularity. Overall, our results suggest that the same force–the cost of connections–promotes the evolution of both hierarchy and modularity, and that these properties are important drivers of network performance and adaptability. In addition to shedding light on the emergence of hierarchy across the many domains in which it appears, these findings will also accelerate future research into evolving more complex, intelligent computational brains in the fields of artificial intelligence and robotics. PMID:27280881

Resistance Genes in Global Crop Breeding Networks.

PubMed

Garrett, K A; Andersen, K F; Asche, F; Bowden, R L; Forbes, G A; Kulakow, P A; Zhou, B

2017-10-01

Resistance genes are a major tool for managing crop diseases. The networks of crop breeders who exchange resistance genes and deploy them in varieties help to determine the global landscape of resistance and epidemics, an important system for maintaining food security. These networks function as a complex adaptive system, with associated strengths and vulnerabilities, and implications for policies to support resistance gene deployment strategies. Extensions of epidemic network analysis can be used to evaluate the multilayer agricultural networks that support and influence crop breeding networks. Here, we evaluate the general structure of crop breeding networks for cassava, potato, rice, and wheat. All four are clustered due to phytosanitary and intellectual property regulations, and linked through CGIAR hubs. Cassava networks primarily include public breeding groups, whereas others are more mixed. These systems must adapt to global change in climate and land use, the emergence of new diseases, and disruptive breeding technologies. Research priorities to support policy include how best to maintain both diversity and redundancy in the roles played by individual crop breeding groups (public versus private and global versus local), and how best to manage connectivity to optimize resistance gene deployment while avoiding risks to the useful life of resistance genes. [Formula: see text] Copyright © 2017 The Author(s). This is an open access article distributed under the CC BY 4.0 International license .

Face recognition via Gabor and convolutional neural network

NASA Astrophysics Data System (ADS)

Lu, Tongwei; Wu, Menglu; Lu, Tao

2018-04-01

In recent years, the powerful feature learning and classification ability of convolutional neural network have attracted widely attention. Compared with the deep learning, the traditional machine learning algorithm has a good explanatory which deep learning does not have. Thus, In this paper, we propose a method to extract the feature of the traditional algorithm as the input of convolution neural network. In order to reduce the complexity of the network, the kernel function of Gabor wavelet is used to extract the feature from different position, frequency and direction of target image. It is sensitive to edge of image which can provide good direction and scale selection. The extraction of the image from eight directions on a scale are as the input of network that we proposed. The network have the advantage of weight sharing and local connection and texture feature of the input image can reduce the influence of facial expression, gesture and illumination. At the same time, we introduced a layer which combined the results of the pooling and convolution can extract deeper features. The training network used the open source caffe framework which is beneficial to feature extraction. The experiment results of the proposed method proved that the network structure effectively overcame the barrier of illumination and had a good robustness as well as more accurate and rapid than the traditional algorithm.

The Evolutionary Origins of Hierarchy.

PubMed

Mengistu, Henok; Huizinga, Joost; Mouret, Jean-Baptiste; Clune, Jeff

2016-06-01

Hierarchical organization-the recursive composition of sub-modules-is ubiquitous in biological networks, including neural, metabolic, ecological, and genetic regulatory networks, and in human-made systems, such as large organizations and the Internet. To date, most research on hierarchy in networks has been limited to quantifying this property. However, an open, important question in evolutionary biology is why hierarchical organization evolves in the first place. It has recently been shown that modularity evolves because of the presence of a cost for network connections. Here we investigate whether such connection costs also tend to cause a hierarchical organization of such modules. In computational simulations, we find that networks without a connection cost do not evolve to be hierarchical, even when the task has a hierarchical structure. However, with a connection cost, networks evolve to be both modular and hierarchical, and these networks exhibit higher overall performance and evolvability (i.e. faster adaptation to new environments). Additional analyses confirm that hierarchy independently improves adaptability after controlling for modularity. Overall, our results suggest that the same force-the cost of connections-promotes the evolution of both hierarchy and modularity, and that these properties are important drivers of network performance and adaptability. In addition to shedding light on the emergence of hierarchy across the many domains in which it appears, these findings will also accelerate future research into evolving more complex, intelligent computational brains in the fields of artificial intelligence and robotics.

Increasing the Reliability of the Work of Artificial Filtering Arrays for the Purification of Quarry Waste Water

NASA Astrophysics Data System (ADS)

Tyulenev, Maxim; Lesin, Yury; Litvin, Oleg; Maliukhina, Elena; Abay, Asmelash

2017-11-01

Features of geological structure of the Kuznetsk coal basin stipulate the application of a low-cost open technique of coal mining, which is more advantageous both from the economic standpoint, and by safety criteria of mining. However, open mining affects significantly the water resources of region. Intensive pollution of reservoirs and water courses, exhaustion of the underground water-bearing layers, violation of a hydrographic network, etc. be-long to the main disadvantages of an open technique of coal mining. Besides, the volume of the water coming into the mining producers exceeds signi-ficantly the needed quantity. According to the data of annual reports of ecology and natural resources department, 348.277 million m3 of water were ta-ken away during production of soft coal, brown coal and lignum fossil from waters of Kemerovo region in 2013 (mostly from underground water objects (96,5%) when draining of mine openings). At the same time, only 87.018 million m3 of water (25%) has been used within a year.

GeneBee-net: Internet-based server for analyzing biopolymers

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

Brodsky, L.I.; Ivanov, V.V.; Nikolaev, V.K.

This work describes a network server for searching databanks of biopolymer structures and performing other biocomputing procedures; it is available via direct Internet connection. Basic server procedures are dedicated to homology (similarity) search of sequence and 3D structure of proteins. The homologies found could be used to build multiple alignments, predict protein and RNA secondary structure, and construct phylogenetic trees. In addition to traditional methods of sequence similarity search, the authors propose {open_quotes}non-matrix{close_quotes} (correlational) search. An analogous approach is used to identify regions of similar tertiary structure of proteins. Algorithm concepts and usage examples are presented for new methods. Servicemore » logic is based upon interaction of a client program and server procedures. The client program allows the compilation of queries and the processing of results of an analysis.« less

Using Self-Organizing Neural Network Map Combined with Ward's Clustering Algorithm for Visualization of Students' Cognitive Structural Models about Aliveness Concept

PubMed Central

Ugulu, Ilker; Aydin, Halil

2016-01-01

We propose an approach to clustering and visualization of students' cognitive structural models. We use the self-organizing map (SOM) combined with Ward's clustering to conduct cluster analysis. In the study carried out on 100 subjects, a conceptual understanding test consisting of open-ended questions was used as a data collection tool. The results of analyses indicated that students constructed the aliveness concept by associating it predominantly with human. Motion appeared as the most frequently associated term with the aliveness concept. The results suggest that the aliveness concept has been constructed using anthropocentric and animistic cognitive structures. In the next step, we used the data obtained from the conceptual understanding test for training the SOM. Consequently, we propose a visualization method about cognitive structure of the aliveness concept. PMID:26819579

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

Aderholdt, Ferrol; Caldwell, Blake A.; Hicks, Susan Elaine

High performance computing environments are often used for a wide variety of workloads ranging from simulation, data transformation and analysis, and complex workflows to name just a few. These systems may process data at various security levels but in so doing are often enclaved at the highest security posture. This approach places significant restrictions on the users of the system even when processing data at a lower security level and exposes data at higher levels of confidentiality to a much broader population than otherwise necessary. The traditional approach of isolation, while effective in establishing security enclaves poses significant challenges formore » the use of shared infrastructure in HPC environments. This report details current state-of-the-art in reconfigurable network enclaving through Software Defined Networking (SDN) and Network Function Virtualization (NFV) and their applicability to secure enclaves in HPC environments. SDN and NFV methods are based on a solid foundation of system wide virtualization. The purpose of which is very straight forward, the system administrator can deploy networks that are more amenable to customer needs, and at the same time achieve increased scalability making it easier to increase overall capacity as needed without negatively affecting functionality. The network administration of both the server system and the virtual sub-systems is simplified allowing control of the infrastructure through well-defined APIs (Application Programming Interface). While SDN and NFV technologies offer significant promise in meeting these goals, they also provide the ability to address a significant component of the multi-tenant challenge in HPC environments, namely resource isolation. Traditional HPC systems are built upon scalable high-performance networking technologies designed to meet specific application requirements. Dynamic isolation of resources within these environments has remained difficult to achieve. SDN and NFV methodology provide us with relevant concepts and available open standards based APIs that isolate compute and storage resources within an otherwise common networking infrastructure. Additionally, the integration of the networking APIs within larger system frameworks such as OpenStack provide the tools necessary to establish isolated enclaves dynamically allowing the benefits of HPC while providing a controlled security structure surrounding these systems.« less

Evolutionary dynamics on any population structure

NASA Astrophysics Data System (ADS)

Allen, Benjamin; Lippner, Gabor; Chen, Yu-Ting; Fotouhi, Babak; Momeni, Naghmeh; Yau, Shing-Tung; Nowak, Martin A.

2017-03-01

Evolution occurs in populations of reproducing individuals. The structure of a population can affect which traits evolve. Understanding evolutionary game dynamics in structured populations remains difficult. Mathematical results are known for special structures in which all individuals have the same number of neighbours. The general case, in which the number of neighbours can vary, has remained open. For arbitrary selection intensity, the problem is in a computational complexity class that suggests there is no efficient algorithm. Whether a simple solution for weak selection exists has remained unanswered. Here we provide a solution for weak selection that applies to any graph or network. Our method relies on calculating the coalescence times of random walks. We evaluate large numbers of diverse population structures for their propensity to favour cooperation. We study how small changes in population structure—graph surgery—affect evolutionary outcomes. We find that cooperation flourishes most in societies that are based on strong pairwise ties.

Integration of Online Parameter Identification and Neural Network for In-Flight Adaptive Control

NASA Technical Reports Server (NTRS)

Hageman, Jacob J.; Smith, Mark S.; Stachowiak, Susan

2003-01-01

An indirect adaptive system has been constructed for robust control of an aircraft with uncertain aerodynamic characteristics. This system consists of a multilayer perceptron pre-trained neural network, online stability and control derivative identification, a dynamic cell structure online learning neural network, and a model following control system based on the stochastic optimal feedforward and feedback technique. The pre-trained neural network and model following control system have been flight-tested, but the online parameter identification and online learning neural network are new additions used for in-flight adaptation of the control system model. A description of the modification and integration of these two stand-alone software packages into the complete system in preparation for initial flight tests is presented. Open-loop results using both simulation and flight data, as well as closed-loop performance of the complete system in a nonlinear, six-degree-of-freedom, flight validated simulation, are analyzed. Results show that this online learning system, in contrast to the nonlearning system, has the ability to adapt to changes in aerodynamic characteristics in a real-time, closed-loop, piloted simulation, resulting in improved flying qualities.

The noisy voter model on complex networks.

PubMed

Carro, Adrián; Toral, Raúl; San Miguel, Maxi

2016-04-20

We propose a new analytical method to study stochastic, binary-state models on complex networks. Moving beyond the usual mean-field theories, this alternative approach is based on the introduction of an annealed approximation for uncorrelated networks, allowing to deal with the network structure as parametric heterogeneity. As an illustration, we study the noisy voter model, a modification of the original voter model including random changes of state. The proposed method is able to unfold the dependence of the model not only on the mean degree (the mean-field prediction) but also on more complex averages over the degree distribution. In particular, we find that the degree heterogeneity--variance of the underlying degree distribution--has a strong influence on the location of the critical point of a noise-induced, finite-size transition occurring in the model, on the local ordering of the system, and on the functional form of its temporal correlations. Finally, we show how this latter point opens the possibility of inferring the degree heterogeneity of the underlying network by observing only the aggregate behavior of the system as a whole, an issue of interest for systems where only macroscopic, population level variables can be measured.

Nanoscale Control over the Mixing Behavior of Surface-Confined Bicomponent Supramolecular Networks Using an Oriented External Electric Field

PubMed Central

2017-01-01

Strong electric fields are known to influence the properties of molecules as well as materials. Here we show that by changing the orientation of an externally applied electric field, one can locally control the mixing behavior of two molecules physisorbed on a solid surface. Whether the starting two-component network evolves into an ordered two-dimensional (2D) cocrystal, yields an amorphous network where the two components phase separate, or shows preferential adsorption of only one component depends on the solution stoichiometry. The experiments are carried out by changing the orientation of the strong electric field that exists between the tip of a scanning tunneling microscope and a solid substrate. The structure of the two-component network typically changes from open porous at negative substrate bias to relatively compact when the polarity of the applied bias is reversed. The electric-field-induced mixing behavior is reversible, and the supramolecular system exhibits excellent stability and good response efficiency. When molecular guests are adsorbed in the porous networks, the field-induced switching behavior was found to be completely different. Plausible reasons behind the field-induced mixing behavior are discussed. PMID:29112378

Evaluation of Supply Chain Efficiency Based on a Novel Network of Data Envelopment Analysis Model

NASA Astrophysics Data System (ADS)

Fu, Li Fang; Meng, Jun; Liu, Ying

2015-12-01

Performance evaluation of supply chain (SC) is a vital topic in SC management and inherently complex problems with multilayered internal linkages and activities of multiple entities. Recently, various Network Data Envelopment Analysis (NDEA) models, which opened the “black box” of conventional DEA, were developed and applied to evaluate the complex SC with a multilayer network structure. However, most of them are input or output oriented models which cannot take into consideration the nonproportional changes of inputs and outputs simultaneously. This paper extends the Slack-based measure (SBM) model to a nonradial, nonoriented network model named as U-NSBM with the presence of undesirable outputs in the SC. A numerical example is presented to demonstrate the applicability of the model in quantifying the efficiency and ranking the supply chain performance. By comparing with the CCR and U-SBM models, it is shown that the proposed model has higher distinguishing ability and gives feasible solution in the presence of undesirable outputs. Meanwhile, it provides more insights for decision makers about the source of inefficiency as well as the guidance to improve the SC performance.

A palladium-doped ceria@carbon core-sheath nanowire network: a promising catalyst support for alcohol electrooxidation reactions.

PubMed

Tan, Qiang; Du, Chunyu; Sun, Yongrong; Du, Lei; Yin, Geping; Gao, Yunzhi

2015-08-28

A novel palladium-doped ceria and carbon core-sheath nanowire network (Pd-CeO2@C CSNWN) is synthesized by a template-free and surfactant-free solvothermal process, followed by high temperature carbonization. This hierarchical network serves as a new class of catalyst support to enhance the activity and durability of noble metal catalysts for alcohol oxidation reactions. Its supported Pd nanoparticles, Pd/(Pd-CeO2@C CSNWN), exhibit >9 fold increase in activity toward the ethanol oxidation over the state-of-the-art Pd/C catalyst, which is the highest among the reported Pd systems. Moreover, stability tests show a virtually unchanged activity after 1000 cycles. The high activity is mainly attributed to the superior oxygen-species releasing capability of Pd-doped CeO2 nanowires by accelerating the removal of the poisoning intermediate. The unique interconnected one-dimensional core-sheath structure is revealed to facilitate immobilization of the metal catalysts, leading to the improved durability. This core-sheath nanowire network opens up a new strategy for catalyst performance optimization for next-generation fuel cells.

Open to Influence: What Counts as Academic Influence in Scholarly Networked "Twitter" Participation

ERIC Educational Resources Information Center

Stewart, Bonnie

2015-01-01

Within the academy, signals of a scholar's academic influence are made manifest in indices like the "h"-index, which rank output. In open scholarly networks, however, signals of influence are less codified, and the ways in which they are enacted and understood have yet to be articulated. Yet the influence scholars cultivate in open…

EduOpen: Italian Network for MOOCs, First Three Months Evaluation after Initiation

ERIC Educational Resources Information Center

Rui, Marina

2016-01-01

EduOpen is an Italian national network devoted to foster the MOOCs diffusion, not just another national provider, being mainly focused to intervene in some crucial fields such as: educational innovation, internationalization strategy, educational research on OER in order to build up some strategy of diffusion and also to make an effort of training…

Experimental demonstration of an OpenFlow based software-defined optical network employing packet, fixed and flexible DWDM grid technologies on an international multi-domain testbed.

PubMed

Channegowda, M; Nejabati, R; Rashidi Fard, M; Peng, S; Amaya, N; Zervas, G; Simeonidou, D; Vilalta, R; Casellas, R; Martínez, R; Muñoz, R; Liu, L; Tsuritani, T; Morita, I; Autenrieth, A; Elbers, J P; Kostecki, P; Kaczmarek, P

2013-03-11

Software defined networking (SDN) and flexible grid optical transport technology are two key technologies that allow network operators to customize their infrastructure based on application requirements and therefore minimizing the extra capital and operational costs required for hosting new applications. In this paper, for the first time we report on design, implementation & demonstration of a novel OpenFlow based SDN unified control plane allowing seamless operation across heterogeneous state-of-the-art optical and packet transport domains. We verify and experimentally evaluate OpenFlow protocol extensions for flexible DWDM grid transport technology along with its integration with fixed DWDM grid and layer-2 packet switching.

The Virtual Mouse Brain: A Computational Neuroinformatics Platform to Study Whole Mouse Brain Dynamics.

PubMed

Melozzi, Francesca; Woodman, Marmaduke M; Jirsa, Viktor K; Bernard, Christophe

2017-01-01

Connectome-based modeling of large-scale brain network dynamics enables causal in silico interrogation of the brain's structure-function relationship, necessitating the close integration of diverse neuroinformatics fields. Here we extend the open-source simulation software The Virtual Brain (TVB) to whole mouse brain network modeling based on individual diffusion magnetic resonance imaging (dMRI)-based or tracer-based detailed mouse connectomes. We provide practical examples on how to use The Virtual Mouse Brain (TVMB) to simulate brain activity, such as seizure propagation and the switching behavior of the resting state dynamics in health and disease. TVMB enables theoretically driven experimental planning and ways to test predictions in the numerous strains of mice available to study brain function in normal and pathological conditions.

Is Multitask Deep Learning Practical for Pharma?

PubMed

Ramsundar, Bharath; Liu, Bowen; Wu, Zhenqin; Verras, Andreas; Tudor, Matthew; Sheridan, Robert P; Pande, Vijay

2017-08-28

Multitask deep learning has emerged as a powerful tool for computational drug discovery. However, despite a number of preliminary studies, multitask deep networks have yet to be widely deployed in the pharmaceutical and biotech industries. This lack of acceptance stems from both software difficulties and lack of understanding of the robustness of multitask deep networks. Our work aims to resolve both of these barriers to adoption. We introduce a high-quality open-source implementation of multitask deep networks as part of the DeepChem open-source platform. Our implementation enables simple python scripts to construct, fit, and evaluate sophisticated deep models. We use our implementation to analyze the performance of multitask deep networks and related deep models on four collections of pharmaceutical data (three of which have not previously been analyzed in the literature). We split these data sets into train/valid/test using time and neighbor splits to test multitask deep learning performance under challenging conditions. Our results demonstrate that multitask deep networks are surprisingly robust and can offer strong improvement over random forests. Our analysis and open-source implementation in DeepChem provide an argument that multitask deep networks are ready for widespread use in commercial drug discovery.

Anatomy of an online misinformation network.

PubMed

Shao, Chengcheng; Hui, Pik-Mai; Wang, Lei; Jiang, Xinwen; Flammini, Alessandro; Menczer, Filippo; Ciampaglia, Giovanni Luca

2018-01-01

Massive amounts of fake news and conspiratorial content have spread over social media before and after the 2016 US Presidential Elections despite intense fact-checking efforts. How do the spread of misinformation and fact-checking compete? What are the structural and dynamic characteristics of the core of the misinformation diffusion network, and who are its main purveyors? How to reduce the overall amount of misinformation? To explore these questions we built Hoaxy, an open platform that enables large-scale, systematic studies of how misinformation and fact-checking spread and compete on Twitter. Hoaxy captures public tweets that include links to articles from low-credibility and fact-checking sources. We perform k-core decomposition on a diffusion network obtained from two million retweets produced by several hundred thousand accounts over the six months before the election. As we move from the periphery to the core of the network, fact-checking nearly disappears, while social bots proliferate. The number of users in the main core reaches equilibrium around the time of the election, with limited churn and increasingly dense connections. We conclude by quantifying how effectively the network can be disrupted by penalizing the most central nodes. These findings provide a first look at the anatomy of a massive online misinformation diffusion network.

Anatomy of an online misinformation network

PubMed Central

Wang, Lei; Jiang, Xinwen; Flammini, Alessandro; Ciampaglia, Giovanni Luca

2018-01-01

Massive amounts of fake news and conspiratorial content have spread over social media before and after the 2016 US Presidential Elections despite intense fact-checking efforts. How do the spread of misinformation and fact-checking compete? What are the structural and dynamic characteristics of the core of the misinformation diffusion network, and who are its main purveyors? How to reduce the overall amount of misinformation? To explore these questions we built Hoaxy, an open platform that enables large-scale, systematic studies of how misinformation and fact-checking spread and compete on Twitter. Hoaxy captures public tweets that include links to articles from low-credibility and fact-checking sources. We perform k-core decomposition on a diffusion network obtained from two million retweets produced by several hundred thousand accounts over the six months before the election. As we move from the periphery to the core of the network, fact-checking nearly disappears, while social bots proliferate. The number of users in the main core reaches equilibrium around the time of the election, with limited churn and increasingly dense connections. We conclude by quantifying how effectively the network can be disrupted by penalizing the most central nodes. These findings provide a first look at the anatomy of a massive online misinformation diffusion network. PMID:29702657

River networks as biodiversity hotlines.

PubMed

Décamps, Henri

2011-05-01

For several years, measures to insure healthy river functions and to protect biodiversity have focused on management at the scale of drainage basins. Indeed, rivers bear witness to the health of their drainage basins, which justifies integrated basin management. However, this vision should not mask two other aspects of the protection of aquatic and riparian biodiversity as well as services provided by rivers. First, although largely depending on the ecological properties of the surrounding terrestrial environment, rivers are ecological systems by themselves, characterized by their linearity: they are organized in connected networks, complex and ever changing, open to the sea. Second, the structure and functions of river networks respond to manipulations of their hydrology, and are particularly vulnerable to climatic variations. Whatever the scale considered, river networks represent "hotlines" for sharing water between ecological and societal systems, as well as for preserving both systems in the face of global change. River hotlines are characterized by spatial as well as temporal legacies: every human impact to a river network may be transmitted far downstream from its point of origin, and may produce effects only after a more or less prolonged latency period. Here, I review some of the current issues of river ecology in light of the linear character of river networks. Copyright © 2011 Académie des sciences. Published by Elsevier SAS. All rights reserved.

A computational geometry approach to pore network construction for granular packings

NASA Astrophysics Data System (ADS)

van der Linden, Joost H.; Sufian, Adnan; Narsilio, Guillermo A.; Russell, Adrian R.; Tordesillas, Antoinette

2018-03-01

Pore network construction provides the ability to characterize and study the pore space of inhomogeneous and geometrically complex granular media in a range of scientific and engineering applications. Various approaches to the construction have been proposed, however subtle implementational details are frequently omitted, open access to source code is limited, and few studies compare multiple algorithms in the context of a specific application. This study presents, in detail, a new pore network construction algorithm, and provides a comprehensive comparison with two other, well-established Delaunay triangulation-based pore network construction methods. Source code is provided to encourage further development. The proposed algorithm avoids the expensive non-linear optimization procedure in existing Delaunay approaches, and is robust in the presence of polydispersity. Algorithms are compared in terms of structural, geometrical and advanced connectivity parameters, focusing on the application of fluid flow characteristics. Sensitivity of the various networks to permeability is assessed through network (Stokes) simulations and finite-element (Navier-Stokes) simulations. Results highlight strong dependencies of pore volume, pore connectivity, throat geometry and fluid conductance on the degree of tetrahedra merging and the specific characteristics of the throats targeted by the merging algorithm. The paper concludes with practical recommendations on the applicability of the three investigated algorithms.

Selected Flight Test Results for Online Learning Neural Network-Based Flight Control System

NASA Technical Reports Server (NTRS)

Williams-Hayes, Peggy S.

2004-01-01

The NASA F-15 Intelligent Flight Control System project team developed a series of flight control concepts designed to demonstrate neural network-based adaptive controller benefits, with the objective to develop and flight-test control systems using neural network technology to optimize aircraft performance under nominal conditions and stabilize the aircraft under failure conditions. This report presents flight-test results for an adaptive controller using stability and control derivative values from an online learning neural network. A dynamic cell structure neural network is used in conjunction with a real-time parameter identification algorithm to estimate aerodynamic stability and control derivative increments to baseline aerodynamic derivatives in flight. This open-loop flight test set was performed in preparation for a future phase in which the learning neural network and parameter identification algorithm output would provide the flight controller with aerodynamic stability and control derivative updates in near real time. Two flight maneuvers are analyzed - pitch frequency sweep and automated flight-test maneuver designed to optimally excite the parameter identification algorithm in all axes. Frequency responses generated from flight data are compared to those obtained from nonlinear simulation runs. Flight data examination shows that addition of flight-identified aerodynamic derivative increments into the simulation improved aircraft pitch handling qualities.

Cognitive radio wireless sensor networks: applications, challenges and research trends.

PubMed

Joshi, Gyanendra Prasad; Nam, Seung Yeob; Kim, Sung Won

2013-08-22

A cognitive radio wireless sensor network is one of the candidate areas where cognitive techniques can be used for opportunistic spectrum access. Research in this area is still in its infancy, but it is progressing rapidly. The aim of this study is to classify the existing literature of this fast emerging application area of cognitive radio wireless sensor networks, highlight the key research that has already been undertaken, and indicate open problems. This paper describes the advantages of cognitive radio wireless sensor networks, the difference between ad hoc cognitive radio networks, wireless sensor networks, and cognitive radio wireless sensor networks, potential application areas of cognitive radio wireless sensor networks, challenges and research trend in cognitive radio wireless sensor networks. The sensing schemes suited for cognitive radio wireless sensor networks scenarios are discussed with an emphasis on cooperation and spectrum access methods that ensure the availability of the required QoS. Finally, this paper lists several open research challenges aimed at drawing the attention of the readers toward the important issues that need to be addressed before the vision of completely autonomous cognitive radio wireless sensor networks can be realized.

Dynamical networks of influence in small group discussions

PubMed Central

Noriega Campero, Alejandro; Almaatouq, Abdullah

2018-01-01

In many domains of life, business and management, numerous problems are addressed by small groups of individuals engaged in face-to-face discussions. While research in social psychology has a long history of studying the determinants of small group performances, the internal dynamics that govern a group discussion are not yet well understood. Here, we rely on computational methods based on network analyses and opinion dynamics to describe how individuals influence each other during a group discussion. We consider the situation in which a small group of three individuals engages in a discussion to solve an estimation task. We propose a model describing how group members gradually influence each other and revise their judgments over the course of the discussion. The main component of the model is an influence network—a weighted, directed graph that determines the extent to which individuals influence each other during the discussion. In simulations, we first study the optimal structure of the influence network that yields the best group performances. Then, we implement a social learning process by which individuals adapt to the past performance of their peers, thereby affecting the structure of the influence network in the long run. We explore the mechanisms underlying the emergence of efficient or maladaptive networks and show that the influence network can converge towards the optimal one, but only when individuals exhibit a social discounting bias by downgrading the relative performances of their peers. Finally, we find a late-speaker effect, whereby individuals who speak later in the discussion are perceived more positively in the long run and are thus more influential. The numerous predictions of the model can serve as a basis for future experiments, and this work opens research on small group discussion to computational social sciences. PMID:29338013

Brain Network Analysis from High-Resolution EEG Signals

NASA Astrophysics Data System (ADS)

de Vico Fallani, Fabrizio; Babiloni, Fabio

Over the last decade, there has been a growing interest in the detection of the functional connectivity in the brain from different neuroelectromagnetic and hemodynamic signals recorded by several neuro-imaging devices such as the functional Magnetic Resonance Imaging (fMRI) scanner, electroencephalography (EEG) and magnetoencephalography (MEG) apparatus. Many methods have been proposed and discussed in the literature with the aim of estimating the functional relationships among different cerebral structures. However, the necessity of an objective comprehension of the network composed by the functional links of different brain regions is assuming an essential role in the Neuroscience. Consequently, there is a wide interest in the development and validation of mathematical tools that are appropriate to spot significant features that could describe concisely the structure of the estimated cerebral networks. The extraction of salient characteristics from brain connectivity patterns is an open challenging topic, since often the estimated cerebral networks have a relative large size and complex structure. Recently, it was realized that the functional connectivity networks estimated from actual brain-imaging technologies (MEG, fMRI and EEG) can be analyzed by means of the graph theory. Since a graph is a mathematical representation of a network, which is essentially reduced to nodes and connections between them, the use of a theoretical graph approach seems relevant and useful as firstly demonstrated on a set of anatomical brain networks. In those studies, the authors have employed two characteristic measures, the average shortest path L and the clustering index C, to extract respectively the global and local properties of the network structure. They have found that anatomical brain networks exhibit many local connections (i.e. a high C) and few random long distance connections (i.e. a low L). These values identify a particular model that interpolate between a regular lattice and a random structure. Such a model has been designated as "small-world" network in analogy with the concept of the small-world phenomenon observed more than 30 years ago in social systems. In a similar way, many types of functional brain networks have been analyzed according to this mathematical approach. In particular, several studies based on different imaging techniques (fMRI, MEG and EEG) have found that the estimated functional networks showed small-world characteristics. In the functional brain connectivity context, these properties have been demonstrated to reflect an optimal architecture for the information processing and propagation among the involved cerebral structures. However, the performance of cognitive and motor tasks as well as the presence of neural diseases has been demonstrated to affect such a small-world topology, as revealed by the significant changes of L and C. Moreover, some functional brain networks have been mostly found to be very unlike the random graphs in their degree-distribution, which gives information about the allocation of the functional links within the connectivity pattern. It was demonstrated that the degree distributions of these networks follow a power-law trend. For this reason those networks are called "scale-free". They still exhibit the small-world phenomenon but tend to contain few nodes that act as highly connected "hubs". Scale-free networks are known to show resistance to failure, facility of synchronization and fast signal processing. Hence, it would be important to see whether the scaling properties of the functional brain networks are altered under various pathologies or experimental tasks. The present Chapter proposes a theoretical graph approach in order to evaluate the functional connectivity patterns obtained from high-resolution EEG signals. In this way, the "Brain Network Analysis" (in analogy with the Social Network Analysis that has emerged as a key technique in modern sociology) represents an effective methodology improving the comprehension of the complex interactions in the brain.

78 FR 72666 - First Responder Network Authority Board Meeting

Federal Register 2010, 2011, 2012, 2013, 2014

2013-12-03

... Network Authority Board Meeting AGENCY: National Telecommunications and Information Administration, U.S... Authority. SUMMARY: The Board of the First Responder Network Authority (FirstNet) will convene open public... single nationwide, interoperable public safety broadband network. The FirstNet Board is responsible for...

Effect of anti-vertigo granule on the opening number and blood flow of mouse ear capillary network

NASA Astrophysics Data System (ADS)

Li, Chongxian; Liu, Xiaobin; Li, Jun; Hao, Shaojun; Wang, Xidong; Li, Wenjun; Zhang, Zhengchen

2018-04-01

To observe the effects of anti-glare particles on the open number and blood flow in the auricle of mice with microcirculation disturbance model. Sixty mice, half male and half female, were randomly divided into 6 groups. The mice were given Kangxuan granule suspension, serum brain granule suspension and normal saline of the same volume, respectively, once a day. The mice were anesthetized by intraperitoneal injection of chloral hydrate at 1 hour after the last administration. The mouse was fixed on the observation platform and the auricle was placed on the transmission stage. BZ-2000 microcirculation microscope and microcirculation analysis system were used to observe the changes of blood velocity and capillary opening volume in auricle of mice before administration. The changes of blood velocity and capillaries opening volume of mouse auricle were observed 2 min after epinephrine injection into tail vein of mice. Bear fruit: Compared with those before epinephrine, the opening number of capillary reticulum of auricle in large dose Kangxuan granule group was significantly decreased (P<0.05), and in normal saline group and middle group. In the small dose Kangxuan granule group, the opening number of capillary network of auricle decreased significantly (P<0.01). Compared with the model group, the large dose Kangxuan granule group could significantly increase the opening number of the auricle capillary network in mice (P<0.01). Yangxuannao granule group could significantly increase the opening number of auricle capillary reticulum in mice (P<0.05), compared with the model group by Ridit test. Both Kangxuan granule group and Yangxuannao granule group could significantly improve the auricle hair of mice with microcirculation disorder. The blood flow in fine blood vessels (P<0.01). Kangxuan granule has a good effect on the opening number of capillary network of auricle and blood flow in mice with microcirculation disorder.

Experimental synchronization of chaos in a large ring of mutually coupled single-transistor oscillators: Phase, amplitude, and clustering effects

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

Minati, Ludovico, E-mail: lminati@ieee.org, E-mail: ludovico.minati@unitn.it

In this paper, experimental evidence of multiple synchronization phenomena in a large (n = 30) ring of chaotic oscillators is presented. Each node consists of an elementary circuit, generating spikes of irregular amplitude and comprising one bipolar junction transistor, one capacitor, two inductors, and one biasing resistor. The nodes are mutually coupled to their neighbours via additional variable resistors. As coupling resistance is decreased, phase synchronization followed by complete synchronization is observed, and onset of synchronization is associated with partial synchronization, i.e., emergence of communities (clusters). While component tolerances affect community structure, the general synchronization properties are maintained across three prototypes andmore » in numerical simulations. The clusters are destroyed by adding long distance connections with distant notes, but are otherwise relatively stable with respect to structural connectivity changes. The study provides evidence that several fundamental synchronization phenomena can be reliably observed in a network of elementary single-transistor oscillators, demonstrating their generative potential and opening way to potential applications of this undemanding setup in experimental modelling of the relationship between network structure, synchronization, and dynamical properties.« less

Tuning the formations of metal-1,3,5-benzenetricarboxylate frameworks via the assistance of amino acids

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

Lei, Xiao-Ping; Lian, Ting-Ting; Chen, Shu-Mei, E-mail: csm@fzu.edu.cn

Seven new metal-1,3,5-benzenetricarboxylate coordination polymers have been synthesized by modification of auxiliary components during the assembly reactions. Their structures have been determined by single-crystal X-ray diffraction analyses and further characterized by XRD and TGA. Interestingly, they show fascinating topological structures. Compounds 1 and 2 possess the undulating layer structure with 3-connected hcb network and (3,6)-connected kgd network. Compound 3 possesses three-dimensional (3D) pillared-layer structure with 3-connected 2-fold interpenetrating srs net. Compound 4 also has the 3D 2-fold interpenetrating pillared-layer structure; however, it has (3,5)-connected hms topology because the Cd(II) center is 5-connected. Compound 5 possess 3D structure through hydrogen bondingmore » interactions between ladder-like layers. Compounds 6 and 7 have the similar 3D frameworks with 4-connected umc net and (3,7)-connected (3.4.5)(3{sup 2}.4{sup 6}.5{sup 5}.6{sup 8}) topology, respectively. The photoluminescent properties of compounds 2–7 were also investigated. - Graphical abstract: Presented here are seven new metal-1,3,5-benzenetricarboxylate coordination polymers with diverse structures from 2D layers to 3D open frameworks. The synthesis and structural diversity of these compounds are determined by the additional amino acids as unusual buffering agents. - Highlights: • Structural diversity of metal-1,3,5-benzenetricarboxylate frameworks. • Tuning structural topologies of MOFs via the assistance of amino acids. • Amino acids as unusual buffering agents for the synthesis of MOFs.« less

Water Hammer Simulations of MMH Propellant - New Capability Demonstration of the Generalized Fluid Flow Simulation Program

NASA Technical Reports Server (NTRS)

Burkhardt, Z.; Ramachandran, N.; Majumdar, A.

2017-01-01

Fluid Transient analysis is important for the design of spacecraft propulsion system to ensure structural stability of the system in the event of sudden closing or opening of the valve. Generalized Fluid System Simulation Program (GFSSP), a general purpose flow network code developed at NASA/MSFC is capable of simulating pressure surge due to sudden opening or closing of valve when thermodynamic properties of real fluid are available for the entire range of simulation. Specifically GFSSP needs an accurate representation of pressure-density relationship in order to predict pressure surge during a fluid transient. Unfortunately, the available thermodynamic property programs such as REFPROP, GASP or GASPAK does not provide the thermodynamic properties of Monomethylhydrazine (MMH). This paper will illustrate the process used for building a customized table of properties of state variables from available properties and speed of sound that is required by GFSSP for simulation. Good agreement was found between the simulations and measured data. This method can be adopted for modeling flow networks and systems with other fluids whose properties are not known in detail in order to obtain general technical insight. Rigorous code validation of this approach will be done and reported at a future date.

Open-source telemedicine platform for wireless medical video communication.

PubMed

Panayides, A; Eleftheriou, I; Pantziaris, M

2013-01-01

An m-health system for real-time wireless communication of medical video based on open-source software is presented. The objective is to deliver a low-cost telemedicine platform which will allow for reliable remote diagnosis m-health applications such as emergency incidents, mass population screening, and medical education purposes. The performance of the proposed system is demonstrated using five atherosclerotic plaque ultrasound videos. The videos are encoded at the clinically acquired resolution, in addition to lower, QCIF, and CIF resolutions, at different bitrates, and four different encoding structures. Commercially available wireless local area network (WLAN) and 3.5G high-speed packet access (HSPA) wireless channels are used to validate the developed platform. Objective video quality assessment is based on PSNR ratings, following calibration using the variable frame delay (VFD) algorithm that removes temporal mismatch between original and received videos. Clinical evaluation is based on atherosclerotic plaque ultrasound video assessment protocol. Experimental results show that adequate diagnostic quality wireless medical video communications are realized using the designed telemedicine platform. HSPA cellular networks provide for ultrasound video transmission at the acquired resolution, while VFD algorithm utilization bridges objective and subjective ratings.

Open-Source Telemedicine Platform for Wireless Medical Video Communication

PubMed Central

Panayides, A.; Eleftheriou, I.; Pantziaris, M.

2013-01-01

An m-health system for real-time wireless communication of medical video based on open-source software is presented. The objective is to deliver a low-cost telemedicine platform which will allow for reliable remote diagnosis m-health applications such as emergency incidents, mass population screening, and medical education purposes. The performance of the proposed system is demonstrated using five atherosclerotic plaque ultrasound videos. The videos are encoded at the clinically acquired resolution, in addition to lower, QCIF, and CIF resolutions, at different bitrates, and four different encoding structures. Commercially available wireless local area network (WLAN) and 3.5G high-speed packet access (HSPA) wireless channels are used to validate the developed platform. Objective video quality assessment is based on PSNR ratings, following calibration using the variable frame delay (VFD) algorithm that removes temporal mismatch between original and received videos. Clinical evaluation is based on atherosclerotic plaque ultrasound video assessment protocol. Experimental results show that adequate diagnostic quality wireless medical video communications are realized using the designed telemedicine platform. HSPA cellular networks provide for ultrasound video transmission at the acquired resolution, while VFD algorithm utilization bridges objective and subjective ratings. PMID:23573082

SME 2.0: Roadmap towards Web 2.0-Based Open Innovation in SME-Networks - A Case Study Based Research Framework

NASA Astrophysics Data System (ADS)

Lindermann, Nadine; Valcárcel, Sylvia; Schaarschmidt, Mario; von Kortzfleisch, Harald

Small- and medium sized enterprises (SMEs) are of high social and economic importance since they represent 99% of European enterprises. With regard to their restricted resources, SMEs are facing a limited capacity for innovation to compete with new challenges in a complex and dynamic competitive environment. Given this context, SMEs need to increasingly cooperate to generate innovations on an extended resource base. Our research project focuses on the aspect of open innovation in SME-networks enabled by Web 2.0 applications and referring to innovative solutions of non-competitive daily life problems. Examples are industrial safety, work-life balance issues or pollution control. The project raises the question whether the use of Web 2.0 applications can foster the exchange of creativity and innovative ideas within a network of SMEs and hence catalyze new forms of innovation processes among its participants. Using Web 2.0 applications within SMEs implies consequently breaking down innovation processes to employees’ level and thus systematically opening up a heterogeneous and broader knowledge base to idea generation. In this paper we address first steps on a roadmap towards Web 2.0-based open innovation processes within SME-networks. It presents a general framework for interaction activities leading to open innovation and recommends a regional marketplace as a viable, trust-building driver for further collaborative activities. These findings are based on field research within a specific SME-network in Rhineland-Palatinate Germany, the “WirtschaftsForum Neuwied e.V.”, which consists of roughly 100 heterogeneous SMEs employing about 8,000 workers.

Visibility graph network analysis of natural gas price: The case of North American market

NASA Astrophysics Data System (ADS)

Sun, Mei; Wang, Yaqi; Gao, Cuixia

2016-11-01

Fluctuations in prices of natural gas significantly affect global economy. Therefore, the research on the characteristics of natural gas price fluctuations, turning points and its influencing cycle on the subsequent price series is of great significance. Global natural gas trade concentrates on three regional markets: the North American market, the European market and the Asia-Pacific market, with North America having the most developed natural gas financial market. In addition, perfect legal supervision and coordinated regulations make the North American market more open and more competitive. This paper focuses on the North American natural gas market specifically. The Henry Hub natural gas spot price time series is converted to a visibility graph network which provides a new direction for macro analysis of time series, and several indicators are investigated: degree and degree distribution, the average shortest path length and community structure. The internal mechanisms underlying price fluctuations are explored through the indicators. The results show that the natural gas prices visibility graph network (NGP-VGN) is of small-world and scale-free properties simultaneously. After random rearrangement of original price time series, the degree distribution of network becomes exponential distribution, different from the original ones. This means that, the original price time series is of long-range negative correlation fractal characteristic. In addition, nodes with large degree correspond to significant geopolitical or economic events. Communities correspond to time cycles in visibility graph network. The cycles of time series and the impact scope of hubs can be found by community structure partition.

Cyberscience and the Knowledge-Based Economy. Open Access and Trade Publishing: From Contradiction to Compatibility with Non-Exclusive Copyright Licensing

ERIC Educational Resources Information Center

Armbruster, Chris

2008-01-01

Open source, open content and open access are set to fundamentally alter the conditions of knowledge production and distribution. Open source, open content and open access are also the most tangible result of the shift towards e-science and digital networking. Yet, widespread misperceptions exist about the impact of this shift on knowledge…

Social networks and secondary health conditions: The critical secondary team for individuals with spinal cord injury

PubMed Central

Guilcher, Sara J. T.; Casciaro, Tiziana; Lemieux-Charles, Louise; Craven, Catharine; McColl, Mary Ann; Jaglal, Susan B.

2012-01-01

Objectives To describe the structure of informal networks for individuals with spinal cord injury (SCI) living in the community, to understand the quality of relationship of informal networks, and to understand the role of informal networks in the prevention and management of secondary health conditions (SHCs). Design Mixed-method descriptive study. Setting Ontario, Canada Participants Community-dwelling adults with an SCI living in Ontario Interventions/methods The Arizona Social Support Interview Survey was used to measure social networks. Participants were asked the following open-ended questions: (1) What have been your experiences with your health care in the community? (2) What have been your experiences with care related to prevention and/or management of SHCs?, (3)What has been the role of your informal social networks (friends/family) related to SHCs? Results Fourteen key informant interviews were conducted (6 men, 8 women). The overall median for available informal networks was 11.0 persons (range 3–19). The informal network engaged in the following roles: (1) advice/validating concerns; (2) knowledge brokers; (3) advocacy; (4) preventing SHCs; (5) assisting with finances; and (6) managing SHCs. Participants described their informal networks as a “secondary team”; a critical and essential force in dealing with SHCs. Conclusions While networks are smaller for persons with SCI compared with the general population, these ties seems to be strong, which is essential when the roles involve a level of trust, certainty, tacit knowledge, and flexibility. These informal networks serve as essential key players in filling the gaps that exist within the formal health care system. PMID:23031170

Cultural Geography Model Validation

DTIC Science & Technology

2010-03-01

the Cultural Geography Model (CGM), a government owned, open source multi - agent system utilizing Bayesian networks, queuing systems, the Theory of...referent determined either from theory or SME opinion. 4. CGM Overview The CGM is a government-owned, open source, data driven multi - agent social...HSCB, validation, social network analysis ABSTRACT: In the current warfighting environment , the military needs robust modeling and simulation (M&S

Bandwidth Management in Resource Constrained Networks

DTIC Science & Technology

2012-03-01

Postgraduate School OSI Open Systems Interconnection QoS Quality of Service TCP Transmission Control Protocol/Internet Protocol TCP/IP Transmission...filtering. B. NORMAL TCP/IP COMMUNICATIONS The Internet is a “complex network WAN that connects LANs and clients around the globe” (Dean, 2009...of the Open Systems Interconnection ( OSI ) model allowing them to route traffic based on MAC address (Kurose & Ross, 2009). While switching

User Expectations for Media Sharing Practices in Open Display Networks

PubMed Central

Jose, Rui; Cardoso, Jorge C. S.; Hong, Jason

2015-01-01

Open Display Networks have the potential to allow many content creators to publish their media to an open-ended set of screen displays. However, this raises the issue of how to match that content to the right displays. In this study, we aim to understand how the perceived utility of particular media sharing scenarios is affected by three independent variables, more specifically: (a) the locativeness of the content being shared; (b) how personal that content is and (c) the scope in which it is being shared. To assess these effects, we composed a set of 24 media sharing scenarios embedded with different treatments of our three independent variables. We then asked 100 participants to express their perception of the relevance of those scenarios. The results suggest a clear preference for scenarios where content is both local and directly related to the person that is publishing it. This is in stark contrast to the types of content that are commonly found in public displays, and confirms the opportunity that open displays networks may represent a new media for self-expression. This novel understanding may inform the design of new publication paradigms that will enable people to share media across the display networks. PMID:26153770

Software Comparison for Renewable Energy Deployment in a Distribution Network

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

Gao, David Wenzhong; Muljadi, Eduard; Tian, Tian

The main objective of this report is to evaluate different software options for performing robust distributed generation (DG) power system modeling. The features and capabilities of four simulation tools, OpenDSS, GridLAB-D, CYMDIST, and PowerWorld Simulator, are compared to analyze their effectiveness in analyzing distribution networks with DG. OpenDSS and GridLAB-D, two open source software, have the capability to simulate networks with fluctuating data values. These packages allow the running of a simulation each time instant by iterating only the main script file. CYMDIST, a commercial software, allows for time-series simulation to study variations on network controls. PowerWorld Simulator, another commercialmore » tool, has a batch mode simulation function through the 'Time Step Simulation' tool, which obtains solutions for a list of specified time points. PowerWorld Simulator is intended for analysis of transmission-level systems, while the other three are designed for distribution systems. CYMDIST and PowerWorld Simulator feature easy-to-use graphical user interfaces (GUIs). OpenDSS and GridLAB-D, on the other hand, are based on command-line programs, which increase the time necessary to become familiar with the software packages.« less

Three-dimensional strutted graphene grown by substrate-free sugar blowing for high-power-density supercapacitors

PubMed Central

Wang, Xuebin; Zhang, Yuanjian; Zhi, Chunyi; Wang, Xi; Tang, Daiming; Xu, Yibin; Weng, Qunhong; Jiang, Xiangfen; Mitome, Masanori; Golberg, Dmitri; Bando, Yoshio

2013-01-01

Three-dimensional graphene architectures in the macroworld can in principle maintain all the extraordinary nanoscale properties of individual graphene flakes. However, current 3D graphene products suffer from poor electrical conductivity, low surface area and insufficient mechanical strength/elasticity; the interconnected self-supported reproducible 3D graphenes remain unavailable. Here we report a sugar-blowing approach based on a polymeric predecessor to synthesize a 3D graphene bubble network. The bubble network consists of mono- or few-layered graphitic membranes that are tightly glued, rigidly fixed and spatially scaffolded by micrometre-scale graphitic struts. Such a topological configuration provides intimate structural interconnectivities, freeway for electron/phonon transports, huge accessible surface area, as well as robust mechanical properties. The graphene network thus overcomes the drawbacks of presently available 3D graphene products and opens up a wide horizon for diverse practical usages, for example, high-power high-energy electrochemical capacitors, as highlighted in this work. PMID:24336225

Three-dimensional strutted graphene grown by substrate-free sugar blowing for high-power-density supercapacitors

NASA Astrophysics Data System (ADS)

Wang, Xuebin; Zhang, Yuanjian; Zhi, Chunyi; Wang, Xi; Tang, Daiming; Xu, Yibin; Weng, Qunhong; Jiang, Xiangfen; Mitome, Masanori; Golberg, Dmitri; Bando, Yoshio

2013-12-01

Three-dimensional graphene architectures in the macroworld can in principle maintain all the extraordinary nanoscale properties of individual graphene flakes. However, current 3D graphene products suffer from poor electrical conductivity, low surface area and insufficient mechanical strength/elasticity; the interconnected self-supported reproducible 3D graphenes remain unavailable. Here we report a sugar-blowing approach based on a polymeric predecessor to synthesize a 3D graphene bubble network. The bubble network consists of mono- or few-layered graphitic membranes that are tightly glued, rigidly fixed and spatially scaffolded by micrometre-scale graphitic struts. Such a topological configuration provides intimate structural interconnectivities, freeway for electron/phonon transports, huge accessible surface area, as well as robust mechanical properties. The graphene network thus overcomes the drawbacks of presently available 3D graphene products and opens up a wide horizon for diverse practical usages, for example, high-power high-energy electrochemical capacitors, as highlighted in this work.

Normal stresses in semiflexible polymer hydrogels

NASA Astrophysics Data System (ADS)

Vahabi, M.; Vos, Bart E.; de Cagny, Henri C. G.; Bonn, Daniel; Koenderink, Gijsje H.; MacKintosh, F. C.

2018-03-01

Biopolymer gels such as fibrin and collagen networks are known to develop tensile axial stress when subject to torsion. This negative normal stress is opposite to the classical Poynting effect observed for most elastic solids including synthetic polymer gels, where torsion provokes a positive normal stress. As shown recently, this anomalous behavior in fibrin gels depends on the open, porous network structure of biopolymer gels, which facilitates interstitial fluid flow during shear and can be described by a phenomenological two-fluid model with viscous coupling between network and solvent. Here we extend this model and develop a microscopic model for the individual diagonal components of the stress tensor that determine the axial response of semiflexible polymer hydrogels. This microscopic model predicts that the magnitude of these stress components depends inversely on the characteristic strain for the onset of nonlinear shear stress, which we confirm experimentally by shear rheometry on fibrin gels. Moreover, our model predicts a transient behavior of the normal stress, which is in excellent agreement with the full time-dependent normal stress we measure.

Template-directed assembly of metal-chalcogenide nanocrystals into ordered mesoporous networks.

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

Vamvasakis, Ioannis; Subrahmanyam, Kota S.; Kanatzidis, Mercouri G.

Although great progress in the synthesis of porous networks of metal and metal oxide nanoparticles with highly accessible pore surface and ordered mesoscale pores has been achieved, synthesis of assembled 3D mesostructures of metal-chalcogenide nanocrystals is still challenging. In this work we demonstrate that ordered mesoporous networks, which comprise well-defined interconnected metal sulfide nanocrystals, can be prepared through a polymer-templated oxidative polymerization process. The resulting self-assembled mesostructures that were obtained after solvent extraction of the polymer template impart the unique combination of light-emitting metal chalcogenide nanocrystals, three-dimensional open-pore structure, high surface area, and uniform pores. We show that the poremore » surface of these materials is active and accessible to incoming molecules, exhibiting high photocatalytic activity and stability, for instance, in oxidation of 1-phenylethanol into acetophenone. We demonstrate through appropriate selection of the synthetic components that this method is general to prepare ordered mesoporous materials from metal chalcogenide nanocrystals with various sizes and compositions.« less

Future Directions for Examination of Brain Networks in Neurodevelopmental Disorders.

PubMed

Uddin, Lucina Q; Karlsgodt, Katherine H

2018-01-01

Neurodevelopmental disorders are associated with atypical development and maturation of brain networks. A recent focus on human connectomics research and the growing popularity of open science initiatives has created the ideal climate in which to make real progress toward understanding the neurobiology of disorders affecting youth. Here we outline future directions for neuroscience researchers examining brain networks in neurodevelopmental disorders, highlighting gaps in the current literature. We emphasize the importance of leveraging large neuroimaging and phenotypic data sets recently made available to the research community, and we suggest specific novel methodological approaches, including analysis of brain dynamics and structural connectivity, that have the potential to produce the greatest clinical insight. Transdiagnostic approaches will also become increasingly necessary as the Research Domain Criteria framework put forth by the National Institute of Mental Health permeates scientific discourse. During this exciting era of big data and increased computational sophistication of analytic tools, the possibilities for significant advancement in understanding neurodevelopmental disorders are limitless.

A mass weighted chemical elastic network model elucidates closed form domain motions in proteins

PubMed Central

Kim, Min Hyeok; Seo, Sangjae; Jeong, Jay Il; Kim, Bum Joon; Liu, Wing Kam; Lim, Byeong Soo; Choi, Jae Boong; Kim, Moon Ki

2013-01-01

An elastic network model (ENM), usually Cα coarse-grained one, has been widely used to study protein dynamics as an alternative to classical molecular dynamics simulation. This simple approach dramatically saves the computational cost, but sometimes fails to describe a feasible conformational change due to unrealistically excessive spring connections. To overcome this limitation, we propose a mass-weighted chemical elastic network model (MWCENM) in which the total mass of each residue is assumed to be concentrated on the representative alpha carbon atom and various stiffness values are precisely assigned according to the types of chemical interactions. We test MWCENM on several well-known proteins of which both closed and open conformations are available as well as three α-helix rich proteins. Their normal mode analysis reveals that MWCENM not only generates more plausible conformational changes, especially for closed forms of proteins, but also preserves protein secondary structures thus distinguishing MWCENM from traditional ENMs. In addition, MWCENM also reduces computational burden by using a more sparse stiffness matrix. PMID:23456820

Finding novel relationships with integrated gene-gene association network analysis of Synechocystis sp. PCC 6803 using species-independent text-mining.

PubMed

Kreula, Sanna M; Kaewphan, Suwisa; Ginter, Filip; Jones, Patrik R

2018-01-01

The increasing move towards open access full-text scientific literature enhances our ability to utilize advanced text-mining methods to construct information-rich networks that no human will be able to grasp simply from 'reading the literature'. The utility of text-mining for well-studied species is obvious though the utility for less studied species, or those with no prior track-record at all, is not clear. Here we present a concept for how advanced text-mining can be used to create information-rich networks even for less well studied species and apply it to generate an open-access gene-gene association network resource for Synechocystis sp. PCC 6803, a representative model organism for cyanobacteria and first case-study for the methodology. By merging the text-mining network with networks generated from species-specific experimental data, network integration was used to enhance the accuracy of predicting novel interactions that are biologically relevant. A rule-based algorithm (filter) was constructed in order to automate the search for novel candidate genes with a high degree of likely association to known target genes by (1) ignoring established relationships from the existing literature, as they are already 'known', and (2) demanding multiple independent evidences for every novel and potentially relevant relationship. Using selected case studies, we demonstrate the utility of the network resource and filter to ( i ) discover novel candidate associations between different genes or proteins in the network, and ( ii ) rapidly evaluate the potential role of any one particular gene or protein. The full network is provided as an open-source resource.

Sponge-Templated Macroporous Graphene Network for Piezoelectric ZnO Nanogenerator.

PubMed

Li, Xinda; Chen, Yi; Kumar, Amit; Mahmoud, Ahmed; Nychka, John A; Chung, Hyun-Joong

2015-09-23

We report a simple approach to fabricate zinc oxide (ZnO) nanowire based electricity generators on three-dimensional (3D) graphene networks by utilizing a commercial polyurethane (PU) sponge as a structural template. Here, a 3D network of graphene oxide is deposited from solution on the template and then is chemically reduced. Following steps of ZnO nanowire growth, polydimethylsiloxane (PDMS) backfilling and electrode lamination completes the fabrication processes. When compared to conventional generators with 2D planar geometry, the sponge template provides a 3D structure that has a potential to increase power density per unit area. The modified one-pot ZnO synthesis method allows the whole process to be inexpensive and environmentally benign. The nanogenerator yields an open circuit voltage of ∼0.5 V and short circuit current density of ∼2 μA/cm(2), while the output was found to be consistent after ∼3000 cycles. Finite element analysis of stress distribution showed that external stress is concentrated to deform ZnO nanowires by orders of magnitude compared to surrounding PU and PDMS, in agreement with our experiment. It is shown that the backfilled PDMS plays a crucial role for the stress concentration, which leads to an efficient electricity generation.

Lowering the barrier to a decentralized NHIN using the open healthcare framework.

PubMed

Smith, Eishay; Kaufman, James H

2006-01-01

In this paper, we discuss two important elements to lowering the barrier to creation of a National Health Information Network. The first element is the adoption of standards that will enable interoperability while guarantee open interfaces (and preventing vendor lock-in). The second element is the role of open source. While adoption of open standards by large EMR vendors is critically important to enterprise healthcare providers and payors, the availability of inexpensive (or free) standardized Healthcare Information Technology for small physician practices is critical. By analogy to the emergence of the World Wide Web, a framework for creating inexpensive and open source applications for physicians will be as important to realizing a National Health Information Network as availability of free browser technology was to the growth of the internet.

Structures of mesophilic and extremophilic citrate synthases reveal rigidity and flexibility for function.

PubMed

Wells, Stephen A; Crennell, Susan J; Danson, Michael J

2014-10-01

Citrate synthase (CS) catalyses the entry of carbon into the citric acid cycle and is highly-conserved structurally across the tree of life. Crystal structures of dimeric CSs are known in both "open" and "closed" forms, which differ by a substantial domain motion that closes the substrate-binding clefts. We explore both the static rigidity and the dynamic flexibility of CS structures from mesophilic and extremophilic organisms from all three evolutionary domains. The computational expense of this wide-ranging exploration is kept to a minimum by the use of rigidity analysis and rapid all-atom simulations of flexible motion, combining geometric simulation and elastic network modeling. CS structures from thermophiles display increased structural rigidity compared with the mesophilic enzyme. A CS structure from a psychrophile, stabilized by strong ionic interactions, appears to display likewise increased rigidity in conventional rigidity analysis; however, a novel modified analysis, taking into account the weakening of the hydrophobic effect at low temperatures, shows a more appropriate decreased rigidity. These rigidity variations do not, however, affect the character of the flexible dynamics, which are well conserved across all the structures studied. Simulation trajectories not only duplicate the crystallographically observed symmetric open-to-closed transitions, but also identify motions describing a previously unidentified antisymmetric functional motion. This antisymmetric motion would not be directly observed in crystallography but is revealed as an intrinsic property of the CS structure by modeling of flexible motion. This suggests that the functional motion closing the binding clefts in CS may be independent rather than symmetric and cooperative. © 2014 Wiley Periodicals, Inc.

Hierarchical learning architecture with automatic feature selection for multiclass protein fold classification.

PubMed

Huang, Chuen-Der; Lin, Chin-Teng; Pal, Nikhil Ranjan

2003-12-01

The structure classification of proteins plays a very important role in bioinformatics, since the relationships and characteristics among those known proteins can be exploited to predict the structure of new proteins. The success of a classification system depends heavily on two things: the tools being used and the features considered. For the bioinformatics applications, the role of appropriate features has not been paid adequate importance. In this investigation we use three novel ideas for multiclass protein fold classification. First, we use the gating neural network, where each input node is associated with a gate. This network can select important features in an online manner when the learning goes on. At the beginning of the training, all gates are almost closed, i.e., no feature is allowed to enter the network. Through the training, gates corresponding to good features are completely opened while gates corresponding to bad features are closed more tightly, and some gates may be partially open. The second novel idea is to use a hierarchical learning architecture (HLA). The classifier in the first level of HLA classifies the protein features into four major classes: all alpha, all beta, alpha + beta, and alpha/beta. And in the next level we have another set of classifiers, which further classifies the protein features into 27 folds. The third novel idea is to induce the indirect coding features from the amino-acid composition sequence of proteins based on the N-gram concept. This provides us with more representative and discriminative new local features of protein sequences for multiclass protein fold classification. The proposed HLA with new indirect coding features increases the protein fold classification accuracy by about 12%. Moreover, the gating neural network is found to reduce the number of features drastically. Using only half of the original features selected by the gating neural network can reach comparable test accuracy as that using all the original features. The gating mechanism also helps us to get a better insight into the folding process of proteins. For example, tracking the evolution of different gates we can find which characteristics (features) of the data are more important for the folding process. And, of course, it also reduces the computation time.

Managing uncertainty in metabolic network structure and improving predictions using EnsembleFBA

PubMed Central

2017-01-01

Genome-scale metabolic network reconstructions (GENREs) are repositories of knowledge about the metabolic processes that occur in an organism. GENREs have been used to discover and interpret metabolic functions, and to engineer novel network structures. A major barrier preventing more widespread use of GENREs, particularly to study non-model organisms, is the extensive time required to produce a high-quality GENRE. Many automated approaches have been developed which reduce this time requirement, but automatically-reconstructed draft GENREs still require curation before useful predictions can be made. We present a novel approach to the analysis of GENREs which improves the predictive capabilities of draft GENREs by representing many alternative network structures, all equally consistent with available data, and generating predictions from this ensemble. This ensemble approach is compatible with many reconstruction methods. We refer to this new approach as Ensemble Flux Balance Analysis (EnsembleFBA). We validate EnsembleFBA by predicting growth and gene essentiality in the model organism Pseudomonas aeruginosa UCBPP-PA14. We demonstrate how EnsembleFBA can be included in a systems biology workflow by predicting essential genes in six Streptococcus species and mapping the essential genes to small molecule ligands from DrugBank. We found that some metabolic subsystems contributed disproportionately to the set of predicted essential reactions in a way that was unique to each Streptococcus species, leading to species-specific outcomes from small molecule interactions. Through our analyses of P. aeruginosa and six Streptococci, we show that ensembles increase the quality of predictions without drastically increasing reconstruction time, thus making GENRE approaches more practical for applications which require predictions for many non-model organisms. All of our functions and accompanying example code are available in an open online repository. PMID:28263984

Managing uncertainty in metabolic network structure and improving predictions using EnsembleFBA.

PubMed

Biggs, Matthew B; Papin, Jason A

2017-03-01

Genome-scale metabolic network reconstructions (GENREs) are repositories of knowledge about the metabolic processes that occur in an organism. GENREs have been used to discover and interpret metabolic functions, and to engineer novel network structures. A major barrier preventing more widespread use of GENREs, particularly to study non-model organisms, is the extensive time required to produce a high-quality GENRE. Many automated approaches have been developed which reduce this time requirement, but automatically-reconstructed draft GENREs still require curation before useful predictions can be made. We present a novel approach to the analysis of GENREs which improves the predictive capabilities of draft GENREs by representing many alternative network structures, all equally consistent with available data, and generating predictions from this ensemble. This ensemble approach is compatible with many reconstruction methods. We refer to this new approach as Ensemble Flux Balance Analysis (EnsembleFBA). We validate EnsembleFBA by predicting growth and gene essentiality in the model organism Pseudomonas aeruginosa UCBPP-PA14. We demonstrate how EnsembleFBA can be included in a systems biology workflow by predicting essential genes in six Streptococcus species and mapping the essential genes to small molecule ligands from DrugBank. We found that some metabolic subsystems contributed disproportionately to the set of predicted essential reactions in a way that was unique to each Streptococcus species, leading to species-specific outcomes from small molecule interactions. Through our analyses of P. aeruginosa and six Streptococci, we show that ensembles increase the quality of predictions without drastically increasing reconstruction time, thus making GENRE approaches more practical for applications which require predictions for many non-model organisms. All of our functions and accompanying example code are available in an open online repository.

Developing an inter-organizational community-based health network: an Australian investigation.

PubMed

Short, Alison; Phillips, Rebecca; Nugus, Peter; Dugdale, Paul; Greenfield, David

2015-12-01

Networks in health care typically involve services delivered by a defined set of organizations. However, networked associations between the healthcare system and consumers or consumer organizations tend to be open, fragmented and are fraught with difficulties. Understanding the role and activities of consumers and consumer groups in a formally initiated inter-organizational health network, and the impacts of the network, is a timely endeavour. This study addresses this aim in three ways. First, the Unbounded Network Inter-organizational Collaborative Impact Model, a purpose-designed framework developed from existing literature, is used to investigate the process and products of inter-organizational network development. Second, the impact of a network artefact is explored. Third, the lessons learned in inter-organizational network development are considered. Data collection methods were: 16 h of ethnographic observation; 10 h of document analysis; six interviews with key informants and a survey (n = 60). Findings suggested that in developing the network, members used common aims, inter-professional collaboration, the power and trust engendered by their participation, and their leadership and management structures in a positive manner. These elements and activities underpinned the inter-organizational network to collaboratively produce the Health Expo network artefact. This event brought together healthcare providers, community groups and consumers to share information. The Health Expo demonstrated and reinforced inter-organizational working and community outreach, providing consumers with community-based information and linkages. Support and resources need to be offered for developing community inter-organizational networks, thereby building consumer capacity for self-management in the community. © The Author (2014). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

OpenSoC Fabric

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

2014-08-21

Recent advancements in technology scaling have shown a trend towards greater integration with large-scale chips containing thousands of processors connected to memories and other I/O devices using non-trivial network topologies. Software simulation proves insufficient to study the tradeoffs in such complex systems due to slow execution time, whereas hardware RTL development is too time-consuming. We present OpenSoC Fabric, an on-chip network generation infrastructure which aims to provide a parameterizable and powerful on-chip network generator for evaluating future high performance computing architectures based on SoC technology. OpenSoC Fabric leverages a new hardware DSL, Chisel, which contains powerful abstractions provided by itsmore » base language, Scala, and generates both software (C++) and hardware (Verilog) models from a single code base. The OpenSoC Fabric2 infrastructure is modeled after existing state-of-the-art simulators, offers large and powerful collections of configuration options, and follows object-oriented design and functional programming to make functionality extension as easy as possible.« less

Technical Report - FINAL

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

Barbara Luke, Director, UNLV Engineering Geophysics Laboratory

2007-04-25

Improve understanding of the earthquake hazard in the Las Vegas Valley and to assess the state of preparedness of the area's population and structures for the next big earthquake. 1. Enhance the seismic monitoring network in the Las Vegas Valley 2. Improve understanding of deep basin structure through active-source seismic refraction and reflection testing 3. Improve understanding of dynamic response of shallow sediments through seismic testing and correlations with lithology 4. Develop credible earthquake scenarios by laboratory and field studies, literature review and analyses 5. Refine ground motion expectations around the Las Vegas Valley through simulations 6. Assess current buildingmore » standards in light of improved understanding of hazards 7. Perform risk assessment for structures and infrastructures, with emphasis on lifelines and critical structures 8. Encourage and facilitate broad and open technical interchange regarding earthquake safety in southern Nevada and efforts to inform citizens of earthquake hazards and mitigation opportunities« less

Tools and Models for Integrating Multiple Cellular Networks

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

Gerstein, Mark

2015-11-06

In this grant, we have systematically investigated the integrated networks, which are responsible for the coordination of activity between metabolic pathways in prokaryotes. We have developed several computational tools to analyze the topology of the integrated networks consisting of metabolic, regulatory, and physical interaction networks. The tools are all open-source, and they are available to download from Github, and can be incorporated in the Knowledgebase. Here, we summarize our work as follow. Understanding the topology of the integrated networks is the first step toward understanding its dynamics and evolution. For Aim 1 of this grant, we have developed a novelmore » algorithm to determine and measure the hierarchical structure of transcriptional regulatory networks [1]. The hierarchy captures the direction of information flow in the network. The algorithm is generally applicable to regulatory networks in prokaryotes, yeast and higher organisms. Integrated datasets are extremely beneficial in understanding the biology of a system in a compact manner due to the conflation of multiple layers of information. Therefore for Aim 2 of this grant, we have developed several tools and carried out analysis for integrating system-wide genomic information. To make use of the structural data, we have developed DynaSIN for protein-protein interactions networks with various dynamical interfaces [2]. We then examined the association between network topology with phenotypic effects such as gene essentiality. In particular, we have organized E. coli and S. cerevisiae transcriptional regulatory networks into hierarchies. We then correlated gene phenotypic effects by tinkering with different layers to elucidate which layers were more tolerant to perturbations [3]. In the context of evolution, we also developed a workflow to guide the comparison between different types of biological networks across various species using the concept of rewiring [4], and Furthermore, we have developed CRIT for correlation analysis in systems biology [5]. For Aim 3, we have further investigated the scaling relationship that the number of Transcription Factors (TFs) in a genome is proportional to the square of the total number of genes. We have extended the analysis from transcription factors to various classes of functional categories, and from individual categories to joint distribution [6]. By introducing a new analytical framework, we have generalized the original toolbox model to take into account of metabolic network with arbitrary network topology [7].« less

The Importance of Biodiversity E-infrastructures for Megadiverse Countries

PubMed Central

Canhos, Dora A. L.; Sousa-Baena, Mariane S.; de Souza, Sidnei; Maia, Leonor C.; Stehmann, João R.; Canhos, Vanderlei P.; De Giovanni, Renato; Bonacelli, Maria B. M.; Los, Wouter; Peterson, A. Townsend

2015-01-01

Addressing the challenges of biodiversity conservation and sustainable development requires global cooperation, support structures, and new governance models to integrate diverse initiatives and achieve massive, open exchange of data, tools, and technology. The traditional paradigm of sharing scientific knowledge through publications is not sufficient to meet contemporary demands that require not only the results but also data, knowledge, and skills to analyze the data. E-infrastructures are key in facilitating access to data and providing the framework for collaboration. Here we discuss the importance of e-infrastructures of public interest and the lack of long-term funding policies. We present the example of Brazil’s speciesLink network, an e-infrastructure that provides free and open access to biodiversity primary data and associated tools. SpeciesLink currently integrates 382 datasets from 135 national institutions and 13 institutions from abroad, openly sharing ~7.4 million records, 94% of which are associated to voucher specimens. Just as important as the data is the network of data providers and users. In 2014, more than 95% of its users were from Brazil, demonstrating the importance of local e-infrastructures in enabling and promoting local use of biodiversity data and knowledge. From the outset, speciesLink has been sustained through project-based funding, normally public grants for 2–4-year periods. In between projects, there are short-term crises in trying to keep the system operational, a fact that has also been observed in global biodiversity portals, as well as in social and physical sciences platforms and even in computing services portals. In the last decade, the open access movement propelled the development of many web platforms for sharing data. Adequate policies unfortunately did not follow the same tempo, and now many initiatives may perish. PMID:26204382

The Importance of Biodiversity E-infrastructures for Megadiverse Countries.

PubMed

Canhos, Dora A L; Sousa-Baena, Mariane S; de Souza, Sidnei; Maia, Leonor C; Stehmann, João R; Canhos, Vanderlei P; De Giovanni, Renato; Bonacelli, Maria B M; Los, Wouter; Peterson, A Townsend

2015-07-01

Addressing the challenges of biodiversity conservation and sustainable development requires global cooperation, support structures, and new governance models to integrate diverse initiatives and achieve massive, open exchange of data, tools, and technology. The traditional paradigm of sharing scientific knowledge through publications is not sufficient to meet contemporary demands that require not only the results but also data, knowledge, and skills to analyze the data. E-infrastructures are key in facilitating access to data and providing the framework for collaboration. Here we discuss the importance of e-infrastructures of public interest and the lack of long-term funding policies. We present the example of Brazil's speciesLink network, an e-infrastructure that provides free and open access to biodiversity primary data and associated tools. SpeciesLink currently integrates 382 datasets from 135 national institutions and 13 institutions from abroad, openly sharing ~7.4 million records, 94% of which are associated to voucher specimens. Just as important as the data is the network of data providers and users. In 2014, more than 95% of its users were from Brazil, demonstrating the importance of local e-infrastructures in enabling and promoting local use of biodiversity data and knowledge. From the outset, speciesLink has been sustained through project-based funding, normally public grants for 2-4-year periods. In between projects, there are short-term crises in trying to keep the system operational, a fact that has also been observed in global biodiversity portals, as well as in social and physical sciences platforms and even in computing services portals. In the last decade, the open access movement propelled the development of many web platforms for sharing data. Adequate policies unfortunately did not follow the same tempo, and now many initiatives may perish.

Experimental demonstration of bandwidth on demand (BoD) provisioning based on time scheduling in software-defined multi-domain optical networks

NASA Astrophysics Data System (ADS)

Zhao, Yongli; Li, Yajie; Wang, Xinbo; Chen, Bowen; Zhang, Jie

2016-09-01

A hierarchical software-defined networking (SDN) control architecture is designed for multi-domain optical networks with the Open Daylight (ODL) controller. The OpenFlow-based Control Virtual Network Interface (CVNI) protocol is deployed between the network orchestrator and the domain controllers. Then, a dynamic bandwidth on demand (BoD) provisioning solution is proposed based on time scheduling in software-defined multi-domain optical networks (SD-MDON). Shared Risk Link Groups (SRLG)-disjoint routing schemes are adopted to separate each tenant for reliability. The SD-MDON testbed is built based on the proposed hierarchical control architecture. Then the proposed time scheduling-based BoD (Ts-BoD) solution is experimentally demonstrated on the testbed. The performance of the Ts-BoD solution is evaluated with respect to blocking probability, resource utilization, and lightpath setup latency.

Computational Fluids Domain Reduction to a Simplified Fluid Network

DTIC Science & Technology

2012-04-19

readily available read/ write software library. Code components from the open source projects OpenFoam and Paraview were explored for their adaptability...to the project. Both Paraview and OpenFoam read polyhedral mesh. OpenFoam does not read results data. Paraview actually allows for user “filters

Development of Virtual Resource Based IoT Proxy for Bridging Heterogeneous Web Services in IoT Networks.

PubMed

Jin, Wenquan; Kim, DoHyeun

2018-05-26

The Internet of Things is comprised of heterogeneous devices, applications, and platforms using multiple communication technologies to connect the Internet for providing seamless services ubiquitously. With the requirement of developing Internet of Things products, many protocols, program libraries, frameworks, and standard specifications have been proposed. Therefore, providing a consistent interface to access services from those environments is difficult. Moreover, bridging the existing web services to sensor and actuator networks is also important for providing Internet of Things services in various industry domains. In this paper, an Internet of Things proxy is proposed that is based on virtual resources to bridge heterogeneous web services from the Internet to the Internet of Things network. The proxy enables clients to have transparent access to Internet of Things devices and web services in the network. The proxy is comprised of server and client to forward messages for different communication environments using the virtual resources which include the server for the message sender and the client for the message receiver. We design the proxy for the Open Connectivity Foundation network where the virtual resources are discovered by the clients as Open Connectivity Foundation resources. The virtual resources represent the resources which expose services in the Internet by web service providers. Although the services are provided by web service providers from the Internet, the client can access services using the consistent communication protocol in the Open Connectivity Foundation network. For discovering the resources to access services, the client also uses the consistent discovery interface to discover the Open Connectivity Foundation devices and virtual resources.

Water-level data for the Albuquerque Basin and adjacent areas, central New Mexico, period of record through September 30, 2015

USGS Publications Warehouse

Beman, Joseph E.; Bryant, Christina F.

2016-10-27

The Albuquerque Basin, located in central New Mexico, is about 100 miles long and 25–40 miles wide. The basin is hydrologically defined as the extent of consolidated and unconsolidated deposits of Tertiary and Quaternary age that encompasses the structural Rio Grande Rift between San Acacia to the south and Cochiti Lake to the north. Drinking-water supplies throughout the basin were obtained solely from groundwater resources until December 2008, when the Albuquerque Bernalillo County Water Utility Authority (ABCWUA) began treatment and distribution of surface water from the Rio Grande through the San Juan-Chama Drinking Water Project. A 20-percent population increase in the basin from 1990 to 2000 and a 22-percent population increase from 2000 to 2010 may have resulted in an increased demand for water in areas within the basin.An initial network of wells was established by the U.S. Geological Survey (USGS) in cooperation with the City of Albuquerque from April 1982 through September 1983 to monitor changes in groundwater levels throughout the Albuquerque Basin. In 1983, this network consisted of 6 wells with analog-to-digital recorders and 27 wells where water levels were measured monthly. The network currently (2015) consists of 124 wells and piezometers. (A piezometer is a specialized well open to a specific depth in the aquifer, often of small diameter and nested with other piezometers open to different depths.) The USGS, in cooperation with the ABCWUA, currently (2015) measures and reports water levels from the 124 wells and piezometers in the network; this report presents water-level data collected by USGS personnel at those 124 sites through water year 2015 (October 1, 2014, through September 30, 2015).

Comparative analysis of existing models for power-grid synchronization

NASA Astrophysics Data System (ADS)

Nishikawa, Takashi; Motter, Adilson E.

2015-01-01

The dynamics of power-grid networks is becoming an increasingly active area of research within the physics and network science communities. The results from such studies are typically insightful and illustrative, but are often based on simplifying assumptions that can be either difficult to assess or not fully justified for realistic applications. Here we perform a comprehensive comparative analysis of three leading models recently used to study synchronization dynamics in power-grid networks—a fundamental problem of practical significance given that frequency synchronization of all power generators in the same interconnection is a necessary condition for a power grid to operate. We show that each of these models can be derived from first principles within a common framework based on the classical model of a generator, thereby clarifying all assumptions involved. This framework allows us to view power grids as complex networks of coupled second-order phase oscillators with both forcing and damping terms. Using simple illustrative examples, test systems, and real power-grid datasets, we study the inherent frequencies of the oscillators as well as their coupling structure, comparing across the different models. We demonstrate, in particular, that if the network structure is not homogeneous, generators with identical parameters need to be modeled as non-identical oscillators in general. We also discuss an approach to estimate the required (dynamical) system parameters that are unavailable in typical power-grid datasets, their use for computing the constants of each of the three models, and an open-source MATLAB toolbox that we provide for these computations.

Principles and Policies for International Coordination of Research Data Networks

NASA Astrophysics Data System (ADS)

Parsons, M. A.; Mokrane, M.; Sorvari, S.; Treloar, A.; Smith, C.

2017-12-01

International data networks enable the sharing of data within and between scientific disciplines and countries and thus provide the foundation for Open Science. Developing effective and sustainable international research data networks is critical for progress in many areas of research and for science to address complex global societal challenges. However, the development and maintenance of effective networks is not always easy, particularly in a context where public resources for science are limited and international cooperation is not a priority for many countries. The global landscape for data sharing in science is complex; many international data networks already exist and have highly variable structures. Some are linked to large intergovernmental research infrastructures, have highly developed centralized services and deal mainly with the data needs of single disciplines. Some are highly distributed, have much less rigid governance structures and provide access to data from many different domains. Most are somewhere between these two extremes and they cover different geographic regions, from regional to global. All provide a mix of data and associated data services which meets the needs of the research community to various extents and this provision depends on a mix of hardware, software, standards and protocols and human skills. These come together, working across national boundaries, in technical and social networks. In all of this, what makes a network function effectively or not is unclear. This means that there is also no simple answer to what can usefully be done at the policy level to promote the development of effective and sustainable data networks. Hence the rational for the present project - to study a variety of currently successful networks, explore the challenges that they are facing and the lessons that can be learned from confronting these challenges, and, where applicable, to translate this analysis into potential policy actions. Detailed descriptive, operational and reflective information was collected on a total of 31 international data networks including several in the geosciences domain. This presentation will summarize the lessons learned and overall conclusions and recommendations from the project.

A machine learning pipeline for automated registration and classification of 3D lidar data

NASA Astrophysics Data System (ADS)

Rajagopal, Abhejit; Chellappan, Karthik; Chandrasekaran, Shivkumar; Brown, Andrew P.

2017-05-01

Despite the large availability of geospatial data, registration and exploitation of these datasets remains a persis- tent challenge in geoinformatics. Popular signal processing and machine learning algorithms, such as non-linear SVMs and neural networks, rely on well-formatted input models as well as reliable output labels, which are not always immediately available. In this paper we outline a pipeline for gathering, registering, and classifying initially unlabeled wide-area geospatial data. As an illustrative example, we demonstrate the training and test- ing of a convolutional neural network to recognize 3D models in the OGRIP 2007 LiDAR dataset using fuzzy labels derived from OpenStreetMap as well as other datasets available on OpenTopography.org. When auxiliary label information is required, various text and natural language processing filters are used to extract and cluster keywords useful for identifying potential target classes. A subset of these keywords are subsequently used to form multi-class labels, with no assumption of independence. Finally, we employ class-dependent geometry extraction routines to identify candidates from both training and testing datasets. Our regression networks are able to identify the presence of 6 structural classes, including roads, walls, and buildings, in volumes as big as 8000 m3 in as little as 1.2 seconds on a commodity 4-core Intel CPU. The presented framework is neither dataset nor sensor-modality limited due to the registration process, and is capable of multi-sensor data-fusion.

Water-level data for the Albuquerque Basin and adjacent areas, central New Mexico, period of record through September 30, 2011

USGS Publications Warehouse

Beman, Joseph E.

2012-01-01

The Albuquerque Basin, located in central New Mexico, is about 100 miles long and 25–40 miles wide. The basin is defined as the extent of consolidated and unconsolidated deposits of Tertiary and Quaternary age that encompasses the structural Rio Grande Rift within the basin. Drinking-water supplies throughout the basin were obtained solely from groundwater resources until December 2008, when surface water from the Rio Grande began being treated and integrated into the system. An increase of about 20 percent in the basin human population from 1990 to 2000 and of about 22 percent increase from 2000 to 2010 also resulted in an increased demand for water. A network of wells was established by the U.S. Geological Survey in cooperation with the City of Albuquerque from April 1982 through September 1983 to monitor changes in groundwater levels throughout the basin. This network consisted of 6 wells with analog-to-digital recorders and 27 wells where water levels were measured monthly in 1983. Currently (2011), the network consists of 126 wells and piezometers (a piezometer is a specialized well open to a specific depth in the aquifer and is often of small diameter and nested with other piezometers open to different depths). This report presents water-level data collected by U.S. Geological Survey personnel at those 126 sites through water year 2011 to better help the Albuquerque Bernalillo County Water Utility Authority manage water use.

Wiretapping the Internet

NASA Astrophysics Data System (ADS)

Antonelli, Charles J.; Honeyman, Peter

2001-02-01

This paper describes the Advanced Packet Vault, a technology for creating such a record by collecting and securely storing all packets observed on a network, with a scalable architecture intended to support network speeds in excess of 100 Mbps. Encryption is used to preserve users' security and privacy, permitting selected traffic to be made available without revealing other traffic. The Vault implementation, based on Linux and OpenBSD, is open-source.

The OpenForest Portal as an Open Learning Ecosystem: Co-Developing in the Study of a Multidisciplinary Phenomenon in a Cultural Context

ERIC Educational Resources Information Center

Liljeström, Anu; Enkenberg, Jorma; Vanninen, Petteri; Vartiainen, Henriikka; Pöllänen, Sinikka

2014-01-01

This paper discusses the OpenForest portal and its related multidisciplinary learning project. The OpenForest portal is an open learning environment and ecosystem, in which students can participate in co-developing and co-creating practices. The aim of the OpenForest ecosystem is to create an extensive interactive network of diverse learning…

A Network Optimization Approach for Improving Organizational Design

DTIC Science & Technology

2004-01-01

functions, Dynamic Network Analysis, Social Network Analysis Abstract Organizations are frequently designed and redesigned, often in...links between sites on the web. Hence a change in any one of the four networks in which people are involved can potentially result in a cascade of...in terms of a set of networks that open the possibility of using all networks (both social and dynamic network measures) as indicators of potential

78 FR 57843 - First Responder Network Authority Board Meeting

Federal Register 2010, 2011, 2012, 2013, 2014

2013-09-20

... Network Authority Board Meeting AGENCY: National Telecommunications and Information Administration, U.S... Network Authority (FirstNet). DATES: The meeting will be held on October 17, 2013, from 9 a.m. to 12:30 p... October 15, 2013, in Washington, DC See First Responder Network Authority Board Meeting, Notice of Open...

75 FR 44800 - Notice of Meeting of the Homeland Security Information Network Advisory Committee, Tuesday...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-07-29

... DEPARTMENT OF HOMELAND SECURITY Notice of Meeting of the Homeland Security Information Network... Security. ACTION: Notice of open meeting. SUMMARY: The Homeland Security Information Network Advisory... (Pub. L. 92-463). The mission of the Homeland Security Information Network Advisory Committee is to...

Cognitive Radio Wireless Sensor Networks: Applications, Challenges and Research Trends

PubMed Central

Joshi, Gyanendra Prasad; Nam, Seung Yeob; Kim, Sung Won

2013-01-01

A cognitive radio wireless sensor network is one of the candidate areas where cognitive techniques can be used for opportunistic spectrum access. Research in this area is still in its infancy, but it is progressing rapidly. The aim of this study is to classify the existing literature of this fast emerging application area of cognitive radio wireless sensor networks, highlight the key research that has already been undertaken, and indicate open problems. This paper describes the advantages of cognitive radio wireless sensor networks, the difference between ad hoc cognitive radio networks, wireless sensor networks, and cognitive radio wireless sensor networks, potential application areas of cognitive radio wireless sensor networks, challenges and research trend in cognitive radio wireless sensor networks. The sensing schemes suited for cognitive radio wireless sensor networks scenarios are discussed with an emphasis on cooperation and spectrum access methods that ensure the availability of the required QoS. Finally, this paper lists several open research challenges aimed at drawing the attention of the readers toward the important issues that need to be addressed before the vision of completely autonomous cognitive radio wireless sensor networks can be realized. PMID:23974152

Strategy of thunderstorm measurement with super dense ground-based observation network

NASA Astrophysics Data System (ADS)

Takahashi, Y.; Sato, M.

2014-12-01

It's not easy to understand the inside structure and developing process of thunderstorm only with existing meteorological instruments since its horizontal extent of the storm cell is sometimes smaller than an order of 10 km while one of the densest ground network in Japan, AMEDAS, consists of sites located every 17 km in average and the resolution of meteorological radar is 1-2 km in general. Even the X-band radar realizes the resolution of 250 m or larger. Here we suggest a new super dense observation network with simple and low cost sensors that can be used for measurement both of raindrop and vertical electric field change caused by cloud-to-ground lightning discharge. This sensor consists of two aluminum plates with a diameter of 10-20 cm. We carried out an observation campaign in summer of 2013 in the foothills of Mt. Yastugatake, Yamanashi and Nagano prefectures in Japan, installing 6 plate-type sensors at a distance of about 4 km. Horizontal location, height and charge amount of each lightning discharge are estimated successfully based on the information of electric field changes at several observing sites. Moreover, it was found that the thunderstorm has a very narrow structure well smaller than 300 m that cannot be measured by any other ways, counting the positive and negative pulses caused by attachment of raindrop to the sensor plate, respectively. We plan to construct a new super dense observation network in the north Kanto region, Japan, where the lightning activity is most prominent in summer Japan, distributing more than several tens of sensors at every 4 km or shorter, such as an order of 100 m at minimum. This kind of new type network will reveal the unknown fine structures of thunderstorms and open the door for constructing real time alert system of torrential rainfall and lightning stroke especially in the city area.

A decomposition theory for phylogenetic networks and incompatible characters.

PubMed

Gusfield, Dan; Bansal, Vikas; Bafna, Vineet; Song, Yun S

2007-12-01

Phylogenetic networks are models of evolution that go beyond trees, incorporating non-tree-like biological events such as recombination (or more generally reticulation), which occur either in a single species (meiotic recombination) or between species (reticulation due to lateral gene transfer and hybrid speciation). The central algorithmic problems are to reconstruct a plausible history of mutations and non-tree-like events, or to determine the minimum number of such events needed to derive a given set of binary sequences, allowing one mutation per site. Meiotic recombination, reticulation and recurrent mutation can cause conflict or incompatibility between pairs of sites (or characters) of the input. Previously, we used "conflict graphs" and "incompatibility graphs" to compute lower bounds on the minimum number of recombination nodes needed, and to efficiently solve constrained cases of the minimization problem. Those results exposed the structural and algorithmic importance of the non-trivial connected components of those two graphs. In this paper, we more fully develop the structural importance of non-trivial connected components of the incompatibility and conflict graphs, proving a general decomposition theorem (Gusfield and Bansal, 2005) for phylogenetic networks. The decomposition theorem depends only on the incompatibilities in the input sequences, and hence applies to many types of phylogenetic networks, and to any biological phenomena that causes pairwise incompatibilities. More generally, the proof of the decomposition theorem exposes a maximal embedded tree structure that exists in the network when the sequences cannot be derived on a perfect phylogenetic tree. This extends the theory of perfect phylogeny in a natural and important way. The proof is constructive and leads to a polynomial-time algorithm to find the unique underlying maximal tree structure. We next examine and fully solve the major open question from Gusfield and Bansal (2005): Is it true that for every input there must be a fully decomposed phylogenetic network that minimizes the number of recombination nodes used, over all phylogenetic networks for the input. We previously conjectured that the answer is yes. In this paper, we show that the answer in is no, both for the case that only single-crossover recombination is allowed, and also for the case that unbounded multiple-crossover recombination is allowed. The latter case also resolves a conjecture recently stated in (Huson and Klopper, 2007) in the context of reticulation networks. Although the conjecture from Gusfield and Bansal (2005) is disproved in general, we show that the answer to the conjecture is yes in several natural special cases, and establish necessary combinatorial structure that counterexamples to the conjecture must possess. We also show that counterexamples to the conjecture are rare (for the case of single-crossover recombination) in simulated data.

Recent developments of functional magnetic resonance imaging research for drug development in Alzheimer's disease.

PubMed

Hampel, Harald; Prvulovic, David; Teipel, Stefan J; Bokde, Arun L W

2011-12-01

The objective of this review is to evaluate recent advances in functional magnetic resonance imaging (fMRI) research in Alzheimer's disease for the development of therapeutic agents. The basic building block underpinning cognition is a brain network. The measured brain activity serves as an integrator of the various components, from genes to structural integrity, that impact the function of networks underpinning cognition. Specific networks can be interrogated using cognitive paradigms such as a learning task or a working memory task. In addition, recent advances in our understanding of neural networks allow one to investigate the function of a brain network by investigating the inherent coherency of the brain networks that can be measured during resting state. The coherent resting state networks allow testing in cognitively impaired patients that may not be possible with the use of cognitive paradigms. In particular the default mode network (DMN) includes the medial temporal lobe and posterior cingulate, two key regions that support episodic memory function and are impaired in the earliest stages of Alzheimer's disease (AD). By investigating the effects of a prospective drug compound on this network, it could illuminate the specificity of the compound with a network supporting memory function. This could provide valuable information on the methods of action at physiological and behaviourally relevant levels. Utilizing fMRI opens up new areas of research and a new approach for drug development, as it is an integrative tool to investigate entire networks within the brain. The network based approach provides a new independent method from previous ones to translate preclinical knowledge into the clinical domain. Copyright © 2011 Elsevier Ltd. All rights reserved.

A general model for metabolic scaling in self-similar asymmetric networks

PubMed Central

Savage, Van M.; Enquist, Brian J.

2017-01-01

How a particular attribute of an organism changes or scales with its body size is known as an allometry. Biological allometries, such as metabolic scaling, have been hypothesized to result from selection to maximize how vascular networks fill space yet minimize internal transport distances and resistances. The West, Brown, Enquist (WBE) model argues that these two principles (space-filling and energy minimization) are (i) general principles underlying the evolution of the diversity of biological networks across plants and animals and (ii) can be used to predict how the resulting geometry of biological networks then governs their allometric scaling. Perhaps the most central biological allometry is how metabolic rate scales with body size. A core assumption of the WBE model is that networks are symmetric with respect to their geometric properties. That is, any two given branches within the same generation in the network are assumed to have identical lengths and radii. However, biological networks are rarely if ever symmetric. An open question is: Does incorporating asymmetric branching change or influence the predictions of the WBE model? We derive a general network model that relaxes the symmetric assumption and define two classes of asymmetrically bifurcating networks. We show that asymmetric branching can be incorporated into the WBE model. This asymmetric version of the WBE model results in several theoretical predictions for the structure, physiology, and metabolism of organisms, specifically in the case for the cardiovascular system. We show how network asymmetry can now be incorporated in the many allometric scaling relationships via total network volume. Most importantly, we show that the 3/4 metabolic scaling exponent from Kleiber’s Law can still be attained within many asymmetric networks. PMID:28319153

A general model for metabolic scaling in self-similar asymmetric networks.

PubMed

Brummer, Alexander Byers; Savage, Van M; Enquist, Brian J

2017-03-01

How a particular attribute of an organism changes or scales with its body size is known as an allometry. Biological allometries, such as metabolic scaling, have been hypothesized to result from selection to maximize how vascular networks fill space yet minimize internal transport distances and resistances. The West, Brown, Enquist (WBE) model argues that these two principles (space-filling and energy minimization) are (i) general principles underlying the evolution of the diversity of biological networks across plants and animals and (ii) can be used to predict how the resulting geometry of biological networks then governs their allometric scaling. Perhaps the most central biological allometry is how metabolic rate scales with body size. A core assumption of the WBE model is that networks are symmetric with respect to their geometric properties. That is, any two given branches within the same generation in the network are assumed to have identical lengths and radii. However, biological networks are rarely if ever symmetric. An open question is: Does incorporating asymmetric branching change or influence the predictions of the WBE model? We derive a general network model that relaxes the symmetric assumption and define two classes of asymmetrically bifurcating networks. We show that asymmetric branching can be incorporated into the WBE model. This asymmetric version of the WBE model results in several theoretical predictions for the structure, physiology, and metabolism of organisms, specifically in the case for the cardiovascular system. We show how network asymmetry can now be incorporated in the many allometric scaling relationships via total network volume. Most importantly, we show that the 3/4 metabolic scaling exponent from Kleiber's Law can still be attained within many asymmetric networks.

Thermal actuation in TRPV1: Role of embedded lipids and intracellular domains.

PubMed

Melnick, Corey; Kaviany, Massoud

2018-05-07

The transient response potential cation channel TRPV1 responds to high temperature, but many of the mechanisms driving its thermal actuation remain unclear. Its recently resolved structure has enabled a number of molecular dynamics (MD) studies focused on illuminating these mechanisms. We add to these efforts by performing the first all-atom MD simulations of its most recently resolved structure at different temperatures. While the complete, thermally induced transition of TRPV1 from its closed to open configuration remains elusive, our analysis of the hydrogen bonding networks, thermodynamics, hydration, and principal components of motion provide a wealth of information on the mechanisms which initiate or influence the thermal opening in TRPV1. In particular, we (i) support the previously proposed mechanism driving thermal actuation in the extracellular pore of TRPV1, (ii) present new hypotheses regarding the thermal actuation in the C-terminal and adjacent linker domains, and (iii) support and build upon the existing hypothesis regarding the role of the vanilloid binding pocket and lipids embedded therein. Copyright © 2018 Elsevier Ltd. All rights reserved.

Analysis of structure-function network decoupling in the brain systems of spastic diplegic cerebral palsy.

PubMed

Lee, Dongha; Pae, Chongwon; Lee, Jong Doo; Park, Eun Sook; Cho, Sung-Rae; Um, Min-Hee; Lee, Seung-Koo; Oh, Maeng-Keun; Park, Hae-Jeong

2017-10-01

Manifestation of the functionalities from the structural brain network is becoming increasingly important to understand a brain disease. With the aim of investigating the differential structure-function couplings according to network systems, we investigated the structural and functional brain networks of patients with spastic diplegic cerebral palsy with periventricular leukomalacia compared to healthy controls. The structural and functional networks of the whole brain and motor system, constructed using deterministic and probabilistic tractography of diffusion tensor magnetic resonance images and Pearson and partial correlation analyses of resting-state functional magnetic resonance images, showed differential embedding of functional networks in the structural networks in patients. In the whole-brain network of patients, significantly reduced global network efficiency compared to healthy controls were found in the structural networks but not in the functional networks, resulting in reduced structural-functional coupling. On the contrary, the motor network of patients had a significantly lower functional network efficiency over the intact structural network and a lower structure-function coupling than the control group. This reduced coupling but reverse directionality in the whole-brain and motor networks of patients was prominent particularly between the probabilistic structural and partial correlation-based functional networks. Intact (or less deficient) functional network over impaired structural networks of the whole brain and highly impaired functional network topology over the intact structural motor network might subserve relatively preserved cognitions and impaired motor functions in cerebral palsy. This study suggests that the structure-function relationship, evaluated specifically using sparse functional connectivity, may reveal important clues to functional reorganization in cerebral palsy. Hum Brain Mapp 38:5292-5306, 2017. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Building a Unified Information Network.

ERIC Educational Resources Information Center

Avram, Henriette D.

1988-01-01

Discusses cooperative efforts between research organizations and libraries to create a national information network. Topics discussed include the Linked System Project (LSP); technical processing versus reference and research functions; Open Systems Interconnection (OSI) Reference Model; the National Science Foundation Network (NSFNET); and…

The Idea to Promote the Development of E-Government in the Civil Aviation System

NASA Astrophysics Data System (ADS)

Renliang, Jiang

E-government has a significant impact on the organizational structure, working mechanism, operating methods and behavior patterns of the civil aviation administration department.The purpose of this research is to find some countermeasures propelling the electronization, network and office automation of the civil aviation system.The method used in the study was field and literature research.The studies showed that government departments in the civil aviation system could promote the development of e-government further by promoting open administration and implementing democratic and scientific decision-making, strengthening the popularization of information technology and information technology training on civil servants, paying attention to the integration and sharing of information resources, formulating a standard e-government system for the civil aviation system, developing the legal security system for the e-government and strengthening the network security.

Nanofluidic interfaces in microfluidic networks

DOE PAGES

Millet, Larry J.; Doktycz, Mitchel John; Retterer, Scott T.

2015-09-24

The integration of nano- and microfluidic technologies enables the construction of tunable interfaces to physical and biological systems across relevant length scales. The ability to perform chemical manipulations of miniscule sample volumes is greatly enhanced through these technologies and extends the ability to manipulate and sample the local fluidic environments at subcellular, cellular and community or tissue scales. Here we describe the development of a flexible surface micromachining process for the creation of nanofluidic channel arrays integrated within SU-8 microfluidic networks. The use of a semi-porous, silicon rich, silicon nitride structural layer allows rapid release of the sacrificial silicon dioxidemore » during the nanochannel fabrication. Nanochannel openings that form the interface to biological samples are customized using focused ion beam milling. The compatibility of these interfaces with on-chip microbial culture is demonstrated.« less

Auto-Associative Recurrent Neural Networks and Long Term Dependencies in Novelty Detection for Audio Surveillance Applications

NASA Astrophysics Data System (ADS)

Rossi, A.; Montefoschi, F.; Rizzo, A.; Diligenti, M.; Festucci, C.

2017-10-01

Machine Learning applied to Automatic Audio Surveillance has been attracting increasing attention in recent years. In spite of several investigations based on a large number of different approaches, little attention had been paid to the environmental temporal evolution of the input signal. In this work, we propose an exploration in this direction comparing the temporal correlations extracted at the feature level with the one learned by a representational structure. To this aim we analysed the prediction performances of a Recurrent Neural Network architecture varying the length of the processed input sequence and the size of the time window used in the feature extraction. Results corroborated the hypothesis that sequential models work better when dealing with data characterized by temporal order. However, so far the optimization of the temporal dimension remains an open issue.

Subversion of cytokine networks by virally encoded decoy receptors

PubMed Central

Epperson, Megan L.; Lee, Chung A.; Fremont, Daved H.

2012-01-01

Summary During the course of evolution, viruses have captured or created a diverse array of open reading frames that encode for proteins that serve to evade and sabotage the host innate and adaptive immune responses, which would otherwise lead to their elimination. These viral genomes are some of the best textbooks of immunology ever written. The established arsenal of immunomodulatory proteins encoded by viruses is large and growing and includes specificities for virtually all known inflammatory pathways and targets. The focus of this review is on herpes and poxvirus-encoded cytokine and chemokine binding proteins that serve to undermine the coordination of host immune surveillance. Structural and mechanistic studies of these decoy receptors have provided a wealth of information, not only about viral pathogenesis but also about the inner workings of cytokine signaling networks. PMID:23046131

The Regularity of Optimal Irrigation Patterns

NASA Astrophysics Data System (ADS)

Morel, Jean-Michel; Santambrogio, Filippo

2010-02-01

A branched structure is observable in draining and irrigation systems, in electric power supply systems, and in natural objects like blood vessels, the river basins or the trees. Recent approaches of these networks derive their branched structure from an energy functional whose essential feature is to favor wide routes. Given a flow s in a river, a road, a tube or a wire, the transportation cost per unit length is supposed in these models to be proportional to s α with 0 < α < 1. The aim of this paper is to prove the regularity of paths (rivers, branches,...) when the irrigated measure is the Lebesgue density on a smooth open set and the irrigating measure is a single source. In that case we prove that all branches of optimal irrigation trees satisfy an elliptic equation and that their curvature is a bounded measure. In consequence all branching points in the network have a tangent cone made of a finite number of segments, and all other points have a tangent. An explicit counterexample disproves these regularity properties for non-Lebesgue irrigated measures.

Finding novel relationships with integrated gene-gene association network analysis of Synechocystis sp. PCC 6803 using species-independent text-mining

PubMed Central

Kreula, Sanna M.; Kaewphan, Suwisa; Ginter, Filip

2018-01-01

The increasing move towards open access full-text scientific literature enhances our ability to utilize advanced text-mining methods to construct information-rich networks that no human will be able to grasp simply from ‘reading the literature’. The utility of text-mining for well-studied species is obvious though the utility for less studied species, or those with no prior track-record at all, is not clear. Here we present a concept for how advanced text-mining can be used to create information-rich networks even for less well studied species and apply it to generate an open-access gene-gene association network resource for Synechocystis sp. PCC 6803, a representative model organism for cyanobacteria and first case-study for the methodology. By merging the text-mining network with networks generated from species-specific experimental data, network integration was used to enhance the accuracy of predicting novel interactions that are biologically relevant. A rule-based algorithm (filter) was constructed in order to automate the search for novel candidate genes with a high degree of likely association to known target genes by (1) ignoring established relationships from the existing literature, as they are already ‘known’, and (2) demanding multiple independent evidences for every novel and potentially relevant relationship. Using selected case studies, we demonstrate the utility of the network resource and filter to (i) discover novel candidate associations between different genes or proteins in the network, and (ii) rapidly evaluate the potential role of any one particular gene or protein. The full network is provided as an open-source resource. PMID:29844966

Virtualization of open-source secure web services to support data exchange in a pediatric critical care research network

PubMed Central

Sward, Katherine A; Newth, Christopher JL; Khemani, Robinder G; Cryer, Martin E; Thelen, Julie L; Enriquez, Rene; Shaoyu, Su; Pollack, Murray M; Harrison, Rick E; Meert, Kathleen L; Berg, Robert A; Wessel, David L; Shanley, Thomas P; Dalton, Heidi; Carcillo, Joseph; Jenkins, Tammara L; Dean, J Michael

2015-01-01

Objectives To examine the feasibility of deploying a virtual web service for sharing data within a research network, and to evaluate the impact on data consistency and quality. Material and Methods Virtual machines (VMs) encapsulated an open-source, semantically and syntactically interoperable secure web service infrastructure along with a shadow database. The VMs were deployed to 8 Collaborative Pediatric Critical Care Research Network Clinical Centers. Results Virtual web services could be deployed in hours. The interoperability of the web services reduced format misalignment from 56% to 1% and demonstrated that 99% of the data consistently transferred using the data dictionary and 1% needed human curation. Conclusions Use of virtualized open-source secure web service technology could enable direct electronic abstraction of data from hospital databases for research purposes. PMID:25796596

Beyond Open Source: According to Jim Hirsch, Open Technology, Not Open Source, Is the Wave of the Future

ERIC Educational Resources Information Center

Villano, Matt

2006-01-01

This article presents an interview with Jim Hirsch, an associate superintendent for technology at Piano Independent School District in Piano, Texas. Hirsch serves as a liaison for the open technologies committee of the Consortium for School Networking. In this interview, he shares his opinion on the significance of open source in K-12.

Opening Teaching Landscapes: The Importance of Quality Assurance in the Delivery of Open Educational Resources

ERIC Educational Resources Information Center

Atenas, Javiera; Havemann, Leo; Priego, Ernesto

2014-01-01

Scholars are increasingly being asked to share teaching materials, publish in open access journals, network in social media, and reuse open educational resources (OER). The theoretical benefits of Open Educational Practices (OEP) have become understood in the academic community but thus far, the use of OER has not been rapidly adopted. We aim to…

Cubic law with aperture-length correlation: implications for network scale fluid flow

NASA Astrophysics Data System (ADS)

Klimczak, Christian; Schultz, Richard A.; Parashar, Rishi; Reeves, Donald M.

2010-06-01

Previous studies have computed and modeled fluid flow through fractured rock with the parallel plate approach where the volumetric flow per unit width normal to the direction of flow is proportional to the cubed aperture between the plates, referred to as the traditional cubic law. When combined with the square root relationship of displacement to length scaling of opening-mode fractures, total flow rates through natural opening-mode fractures are found to be proportional to apertures to the fifth power. This new relationship was explored by examining a suite of flow simulations through fracture networks using the discrete fracture network model (DFN). Flow was modeled through fracture networks with the same spatial distribution of fractures for both correlated and uncorrelated fracture length-to-aperture relationships. Results indicate that flow rates are significantly higher for correlated DFNs. Furthermore, the length-to-aperture relations lead to power-law distributions of network hydraulic conductivity which greatly influence equivalent permeability tensor values. These results confirm the importance of the correlated square root relationship of displacement to length scaling for total flow through natural opening-mode fractures and, hence, emphasize the role of these correlations for flow modeling.

Adsorption and release of biocides with mesoporous silica nanoparticles

NASA Astrophysics Data System (ADS)

Popat, Amirali; Liu, Jian; Hu, Qiuhong; Kennedy, Michael; Peters, Brenton; Lu, Gao Qing (Max); Qiao, Shi Zhang

2012-01-01

In this proof-of-concept study, an agricultural biocide (imidacloprid) was effectively loaded into the mesoporous silica nanoparticles (MSNs) with different pore sizes, morphologies and mesoporous structures for termite control. This resulted in nanoparticles with a large surface area, tunable pore diameter and small particle size, which are ideal carriers for adsorption and controlled release of imidacloprid. The effect of pore size, surface area and mesoporous structure on uptake and release of imidacloprid was systematically studied. It was found that the adsorption amount and release profile of imidacloprid were dependent on the type of mesoporous structure and surface area of particles. Specifically, MCM-48 type mesoporous silica nanoparticles with a three dimensional (3D) open network structure and high surface area displayed the highest adsorption capacity compared to other types of silica nanoparticles. Release of imidacloprid from these nanoparticles was found to be controlled over 48 hours. Finally, in vivo laboratory testing on termite control proved the efficacy of these nanoparticles as delivery carriers for biopesticides. We believe that the present study will contribute to the design of more effective controlled and targeted delivery for other biomolecules.In this proof-of-concept study, an agricultural biocide (imidacloprid) was effectively loaded into the mesoporous silica nanoparticles (MSNs) with different pore sizes, morphologies and mesoporous structures for termite control. This resulted in nanoparticles with a large surface area, tunable pore diameter and small particle size, which are ideal carriers for adsorption and controlled release of imidacloprid. The effect of pore size, surface area and mesoporous structure on uptake and release of imidacloprid was systematically studied. It was found that the adsorption amount and release profile of imidacloprid were dependent on the type of mesoporous structure and surface area of particles. Specifically, MCM-48 type mesoporous silica nanoparticles with a three dimensional (3D) open network structure and high surface area displayed the highest adsorption capacity compared to other types of silica nanoparticles. Release of imidacloprid from these nanoparticles was found to be controlled over 48 hours. Finally, in vivo laboratory testing on termite control proved the efficacy of these nanoparticles as delivery carriers for biopesticides. We believe that the present study will contribute to the design of more effective controlled and targeted delivery for other biomolecules. Electronic supplementary information (ESI) available. See DOI: 10.1039/c2nr11691j

Alcohol Affects the Brain's Resting-State Network in Social Drinkers

PubMed Central

Lithari, Chrysa; Klados, Manousos A.; Pappas, Costas; Albani, Maria; Kapoukranidou, Dorothea; Kovatsi, Leda

2012-01-01

Acute alcohol intake is known to enhance inhibition through facilitation of GABAA receptors, which are present in 40% of the synapses all over the brain. Evidence suggests that enhanced GABAergic transmission leads to increased large-scale brain connectivity. Our hypothesis is that acute alcohol intake would increase the functional connectivity of the human brain resting-state network (RSN). To test our hypothesis, electroencephalographic (EEG) measurements were recorded from healthy social drinkers at rest, during eyes-open and eyes-closed sessions, after administering to them an alcoholic beverage or placebo respectively. Salivary alcohol and cortisol served to measure the inebriation and stress levels. By calculating Magnitude Square Coherence (MSC) on standardized Low Resolution Electromagnetic Tomography (sLORETA) solutions, we formed cortical networks over several frequency bands, which were then analyzed in the context of functional connectivity and graph theory. MSC was increased (p<0.05, corrected with False Discovery Rate, FDR corrected) in alpha, beta (eyes-open) and theta bands (eyes-closed) following acute alcohol intake. Graph parameters were accordingly altered in these bands quantifying the effect of alcohol on the structure of brain networks; global efficiency and density were higher and path length was lower during alcohol (vs. placebo, p<0.05). Salivary alcohol concentration was positively correlated with the density of the network in beta band. The degree of specific nodes was elevated following alcohol (vs. placebo). Our findings support the hypothesis that short-term inebriation considerably increases large-scale connectivity in the RSN. The increased baseline functional connectivity can -at least partially- be attributed to the alcohol-induced disruption of the delicate balance between inhibitory and excitatory neurotransmission in favor of inhibitory influences. Thus, it is suggested that short-term inebriation is associated, as expected, to increased GABA transmission and functional connectivity, while long-term alcohol consumption may be linked to exactly the opposite effect. PMID:23119078

Dynamics and thermodynamics of open chemical networks

NASA Astrophysics Data System (ADS)

Esposito, Massimiliano

Open chemical networks (OCN) are large sets of coupled chemical reactions where some of the species are chemostated (i.e. continuously restored from the environment). Cell metabolism is a notable example of OCN. Two results will be presented. First, dissipation in OCN operating in nonequilibrium steady-states strongly depends on the network topology (algebraic properties of the stoichiometric matrix). An application to oligosaccharides exchange dynamics performed by so-called D-enzymes will be provided. Second, at low concentration the dissipation of OCN is in general inaccurately predicted by deterministic dynamics (i.e. nonlinear rate equations for the species concentrations). In this case a description in terms of the chemical master equation is necessary. A notable exception is provided by so-called deficiency zero networks, i.e. chemical networks with no hidden cycles present in the graph of reactant complexes.

MetaMapR: pathway independent metabolomic network analysis incorporating unknowns.

PubMed

Grapov, Dmitry; Wanichthanarak, Kwanjeera; Fiehn, Oliver

2015-08-15

Metabolic network mapping is a widely used approach for integration of metabolomic experimental results with biological domain knowledge. However, current approaches can be limited by biochemical domain or pathway knowledge which results in sparse disconnected graphs for real world metabolomic experiments. MetaMapR integrates enzymatic transformations with metabolite structural similarity, mass spectral similarity and empirical associations to generate richly connected metabolic networks. This open source, web-based or desktop software, written in the R programming language, leverages KEGG and PubChem databases to derive associations between metabolites even in cases where biochemical domain or molecular annotations are unknown. Network calculation is enhanced through an interface to the Chemical Translation System, which allows metabolite identifier translation between >200 common biochemical databases. Analysis results are presented as interactive visualizations or can be exported as high-quality graphics and numerical tables which can be imported into common network analysis and visualization tools. Freely available at http://dgrapov.github.io/MetaMapR/. Requires R and a modern web browser. Installation instructions, tutorials and application examples are available at http://dgrapov.github.io/MetaMapR/. ofiehn@ucdavis.edu. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Encoding, rehearsal, and recall in signers and speakers: shared network but differential engagement.

PubMed

Bavelier, D; Newman, A J; Mukherjee, M; Hauser, P; Kemeny, S; Braun, A; Boutla, M

2008-10-01

Short-term memory (STM), or the ability to hold verbal information in mind for a few seconds, is known to rely on the integrity of a frontoparietal network of areas. Here, we used functional magnetic resonance imaging to ask whether a similar network is engaged when verbal information is conveyed through a visuospatial language, American Sign Language, rather than speech. Deaf native signers and hearing native English speakers performed a verbal recall task, where they had to first encode a list of letters in memory, maintain it for a few seconds, and finally recall it in the order presented. The frontoparietal network described to mediate STM in speakers was also observed in signers, with its recruitment appearing independent of the modality of the language. This finding supports the view that signed and spoken STM rely on similar mechanisms. However, deaf signers and hearing speakers differentially engaged key structures of the frontoparietal network as the stages of STM unfold. In particular, deaf signers relied to a greater extent than hearing speakers on passive memory storage areas during encoding and maintenance, but on executive process areas during recall. This work opens new avenues for understanding similarities and differences in STM performance in signers and speakers.

Encoding, Rehearsal, and Recall in Signers and Speakers: Shared Network but Differential Engagement

PubMed Central

Newman, A. J.; Mukherjee, M.; Hauser, P.; Kemeny, S.; Braun, A.; Boutla, M.

2008-01-01

Short-term memory (STM), or the ability to hold verbal information in mind for a few seconds, is known to rely on the integrity of a frontoparietal network of areas. Here, we used functional magnetic resonance imaging to ask whether a similar network is engaged when verbal information is conveyed through a visuospatial language, American Sign Language, rather than speech. Deaf native signers and hearing native English speakers performed a verbal recall task, where they had to first encode a list of letters in memory, maintain it for a few seconds, and finally recall it in the order presented. The frontoparietal network described to mediate STM in speakers was also observed in signers, with its recruitment appearing independent of the modality of the language. This finding supports the view that signed and spoken STM rely on similar mechanisms. However, deaf signers and hearing speakers differentially engaged key structures of the frontoparietal network as the stages of STM unfold. In particular, deaf signers relied to a greater extent than hearing speakers on passive memory storage areas during encoding and maintenance, but on executive process areas during recall. This work opens new avenues for understanding similarities and differences in STM performance in signers and speakers. PMID:18245041

Social Features of Online Networks: The Strength of Intermediary Ties in Online Social Media

PubMed Central

Grabowicz, Przemyslaw A.; Ramasco, José J.; Moro, Esteban; Pujol, Josep M.; Eguiluz, Victor M.

2012-01-01

An increasing fraction of today's social interactions occur using online social media as communication channels. Recent worldwide events, such as social movements in Spain or revolts in the Middle East, highlight their capacity to boost people's coordination. Online networks display in general a rich internal structure where users can choose among different types and intensity of interactions. Despite this, there are still open questions regarding the social value of online interactions. For example, the existence of users with millions of online friends sheds doubts on the relevance of these relations. In this work, we focus on Twitter, one of the most popular online social networks, and find that the network formed by the basic type of connections is organized in groups. The activity of the users conforms to the landscape determined by such groups. Furthermore, Twitter's distinction between different types of interactions allows us to establish a parallelism between online and offline social networks: personal interactions are more likely to occur on internal links to the groups (the weakness of strong ties); events transmitting new information go preferentially through links connecting different groups (the strength of weak ties) or even more through links connecting to users belonging to several groups that act as brokers (the strength of intermediary ties). PMID:22247773

FRED (a Framework for Reconstructing Epidemic Dynamics): an open-source software system for modeling infectious diseases and control strategies using census-based populations.

PubMed

Grefenstette, John J; Brown, Shawn T; Rosenfeld, Roni; DePasse, Jay; Stone, Nathan T B; Cooley, Phillip C; Wheaton, William D; Fyshe, Alona; Galloway, David D; Sriram, Anuroop; Guclu, Hasan; Abraham, Thomas; Burke, Donald S

2013-10-08

Mathematical and computational models provide valuable tools that help public health planners to evaluate competing health interventions, especially for novel circumstances that cannot be examined through observational or controlled studies, such as pandemic influenza. The spread of diseases like influenza depends on the mixing patterns within the population, and these mixing patterns depend in part on local factors including the spatial distribution and age structure of the population, the distribution of size and composition of households, employment status and commuting patterns of adults, and the size and age structure of schools. Finally, public health planners must take into account the health behavior patterns of the population, patterns that often vary according to socioeconomic factors such as race, household income, and education levels. FRED (a Framework for Reconstructing Epidemic Dynamics) is a freely available open-source agent-based modeling system based closely on models used in previously published studies of pandemic influenza. This version of FRED uses open-access census-based synthetic populations that capture the demographic and geographic heterogeneities of the population, including realistic household, school, and workplace social networks. FRED epidemic models are currently available for every state and county in the United States, and for selected international locations. State and county public health planners can use FRED to explore the effects of possible influenza epidemics in specific geographic regions of interest and to help evaluate the effect of interventions such as vaccination programs and school closure policies. FRED is available under a free open source license in order to contribute to the development of better modeling tools and to encourage open discussion of modeling tools being used to evaluate public health policies. We also welcome participation by other researchers in the further development of FRED.

The role of transmembrane segment 5 (TM5) in Na2 release and the conformational transition of neurotransmitter:sodium symporters toward the inward-open state

PubMed Central

Stolzenberg, Sebastian; Li, Zheng; Quick, Matthias; Malinauskaite, Lina; Nissen, Poul; Weinstein, Harel; Javitch, Jonathan A.; Shi, Lei

2017-01-01

Neurotransmitter:sodium symporters (NSSs) terminate neurotransmission by the reuptake of released neurotransmitters. This active accumulation of substrate against its concentration gradient is driven by the transmembrane Na+ gradient and requires that the transporter traverses several conformational states. LeuT, a prokaryotic NSS homolog, has been crystallized in outward-open, outward-occluded, and inward-open states. Two crystal structures of another prokaryotic NSS homolog, the multihydrophobic amino acid transporter (MhsT) from Bacillus halodurans, have been resolved in novel inward-occluded states, with the extracellular vestibule closed and the intracellular portion of transmembrane segment 5 (TM5i) in either an unwound or a helical conformation. We have investigated the potential involvement of TM5i in binding and unbinding of Na2, i.e. the Na+ bound in the Na2 site, by carrying out comparative molecular dynamics simulations of the models derived from the two MhsT structures. We find that the helical TM5i conformation is associated with a higher propensity for Na2 release, which leads to the repositioning of the N terminus and transition to an inward-open state. By using comparative interaction network analysis, we also identify allosteric pathways connecting TM5i and the Na2 binding site to the extracellular and intracellular regions. Based on our combined computational and mutagenesis studies of MhsT and LeuT, we propose that TM5i plays a key role in Na2 binding and release associated with the conformational transition toward the inward-open state, a role that is likely to be shared across the NSS family. PMID:28320858

Performance Assessment of Network Intrusion-Alert Prediction

DTIC Science & Technology

2012-09-01

the threats. In this thesis, we use Snort to generate the intrusion detection alerts. 2. SNORT Snort is an open source network intrusion...standard for IPS. (Snort, 2012) We choose Snort because it is an open source product that is free to download and can be deployed cross-platform...Learning & prediction in relational time series: A survey. 21st Behavior Representation in Modeling & Simulation ( BRIMS ) Conference 2012, 93–100. Tan

The Struggle to Study. Financial Implications for Adults Studying in London. A Research Report Funded by London's Four Open College Networks: ALFA, CAWLOC, GLEAN, and OCSL.

ERIC Educational Resources Information Center

Sims, Anne; Goddard, Ty

The four Open College Networks in London assessed the climate in inner London for adult students who wished to return to education and training. The research focussed on: the extent to which recent legislative changes threatened adult participation in education and training; the abolition of the Inner London Education Authority (ILEA) and…

Discourse, ideas and power in global health policy networks: political attention for maternal and child health in the millennium development goal era.

PubMed

McDougall, Lori

2016-05-18

Maternal and child health issues have gained global political attention and resources in the past 10 years, due in part to their prominence on the Millennium Development Goal agenda and the use of evidence-based advocacy by policy networks. This paper identifies key factors for this achievement, and raises questions about prospective challenges for sustaining attention in the transition to the post-2015 Sustainable Development Goals, far broader in scope than the Millennium Development Goals. This paper relies on participant observation methods and document analysis to develop a case study of the behaviours of global maternal and child health advocacy networks during 2005-2015. The development of coordinated networks of heterogeneous actors facilitated the rise in attention to maternal and child health during the past 10 years. The strategic use of epidemiological and economic evidence by these networks enabled policy attention and promoted network cohesion. The time-bound opportunity of reaching the 2015 Millennium Development Goals created a window of opportunity for joint action. As the new post-2015 goals emerge, networks seek to sustain attention by repositioning their framing of issues, network structures, and external alliances, including with networks that lay both inside and outside of the health domain. Issues rise on global policy agendas because of how ideas are constructed, portrayed and positioned by actors within given contexts. Policy networks play a critical role by uniting stakeholders to promote persuasive ideas about policy problems and solutions. The behaviours of networks in issue-framing, member-alignment, and strategic outreach can force open windows of opportunity for political attention -- or prevent them from closing.

76 FR 21405 - Notice Pursuant to the National Cooperative Research and Production Act of 1993-Network Centric...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-04-15

... group research project. Membership in this group research project remains open, and Network Centric... Production Act of 1993--Network Centric Operations Industry Consortium, Inc. Notice is hereby given that, on..., 15 U.S.C. 4301 et seq. (``the Act''), Network Centric Operations Industry Consortium, Inc. (``NCOIC...

Networked Participatory Scholarship: Emergent Techno-Cultural Pressures toward Open and Digital Scholarship in Online Networks

ERIC Educational Resources Information Center

Veletsianos, George; Kimmons, Royce

2012-01-01

We examine the relationship between scholarly practice and participatory technologies and explore how such technologies invite and reflect the emergence of a new form of scholarship that we call "Networked Participatory Scholarship": scholars' participation in online social networks to share, reflect upon, critique, improve, validate, and…

ClusterViz: A Cytoscape APP for Cluster Analysis of Biological Network.

PubMed

Wang, Jianxin; Zhong, Jiancheng; Chen, Gang; Li, Min; Wu, Fang-xiang; Pan, Yi

2015-01-01

Cluster analysis of biological networks is one of the most important approaches for identifying functional modules and predicting protein functions. Furthermore, visualization of clustering results is crucial to uncover the structure of biological networks. In this paper, ClusterViz, an APP of Cytoscape 3 for cluster analysis and visualization, has been developed. In order to reduce complexity and enable extendibility for ClusterViz, we designed the architecture of ClusterViz based on the framework of Open Services Gateway Initiative. According to the architecture, the implementation of ClusterViz is partitioned into three modules including interface of ClusterViz, clustering algorithms and visualization and export. ClusterViz fascinates the comparison of the results of different algorithms to do further related analysis. Three commonly used clustering algorithms, FAG-EC, EAGLE and MCODE, are included in the current version. Due to adopting the abstract interface of algorithms in module of the clustering algorithms, more clustering algorithms can be included for the future use. To illustrate usability of ClusterViz, we provided three examples with detailed steps from the important scientific articles, which show that our tool has helped several research teams do their research work on the mechanism of the biological networks.

Global multi-layer network of human mobility

PubMed Central

Belyi, Alexander; Bojic, Iva; Sobolevsky, Stanislav; Sitko, Izabela; Hawelka, Bartosz; Rudikova, Lada; Kurbatski, Alexander; Ratti, Carlo

2017-01-01

ABSTRACT Recent availability of geo-localized data capturing individual human activity together with the statistical data on international migration opened up unprecedented opportunities for a study on global mobility. In this paper, we consider it from the perspective of a multi-layer complex network, built using a combination of three datasets: Twitter, Flickr and official migration data. Those datasets provide different, but equally important insights on the global mobility – while the first two highlight short-term visits of people from one country to another, the last one – migration – shows the long-term mobility perspective, when people relocate for good. The main purpose of the paper is to emphasize importance of this multi-layer approach capturing both aspects of human mobility at the same time. On the one hand, we show that although the general properties of different layers of the global mobility network are similar, there are important quantitative differences among them. On the other hand, we demonstrate that consideration of mobility from a multi-layer perspective can reveal important global spatial patterns in a way more consistent with those observed in other available relevant sources of international connections, in comparison to the spatial structure inferred from each network layer taken separately. PMID:28553155

Quantum stochastic walks on networks for decision-making.

PubMed

Martínez-Martínez, Ismael; Sánchez-Burillo, Eduardo

2016-03-31

Recent experiments report violations of the classical law of total probability and incompatibility of certain mental representations when humans process and react to information. Evidence shows promise of a more general quantum theory providing a better explanation of the dynamics and structure of real decision-making processes than classical probability theory. Inspired by this, we show how the behavioral choice-probabilities can arise as the unique stationary distribution of quantum stochastic walkers on the classical network defined from Luce's response probabilities. This work is relevant because (i) we provide a very general framework integrating the positive characteristics of both quantum and classical approaches previously in confrontation, and (ii) we define a cognitive network which can be used to bring other connectivist approaches to decision-making into the quantum stochastic realm. We model the decision-maker as an open system in contact with her surrounding environment, and the time-length of the decision-making process reveals to be also a measure of the process' degree of interplay between the unitary and irreversible dynamics. Implementing quantum coherence on classical networks may be a door to better integrate human-like reasoning biases in stochastic models for decision-making.

Quantum stochastic walks on networks for decision-making

NASA Astrophysics Data System (ADS)

Martínez-Martínez, Ismael; Sánchez-Burillo, Eduardo

2016-03-01

Recent experiments report violations of the classical law of total probability and incompatibility of certain mental representations when humans process and react to information. Evidence shows promise of a more general quantum theory providing a better explanation of the dynamics and structure of real decision-making processes than classical probability theory. Inspired by this, we show how the behavioral choice-probabilities can arise as the unique stationary distribution of quantum stochastic walkers on the classical network defined from Luce’s response probabilities. This work is relevant because (i) we provide a very general framework integrating the positive characteristics of both quantum and classical approaches previously in confrontation, and (ii) we define a cognitive network which can be used to bring other connectivist approaches to decision-making into the quantum stochastic realm. We model the decision-maker as an open system in contact with her surrounding environment, and the time-length of the decision-making process reveals to be also a measure of the process’ degree of interplay between the unitary and irreversible dynamics. Implementing quantum coherence on classical networks may be a door to better integrate human-like reasoning biases in stochastic models for decision-making.

Quantum stochastic walks on networks for decision-making

PubMed Central

Martínez-Martínez, Ismael; Sánchez-Burillo, Eduardo

2016-01-01

Recent experiments report violations of the classical law of total probability and incompatibility of certain mental representations when humans process and react to information. Evidence shows promise of a more general quantum theory providing a better explanation of the dynamics and structure of real decision-making processes than classical probability theory. Inspired by this, we show how the behavioral choice-probabilities can arise as the unique stationary distribution of quantum stochastic walkers on the classical network defined from Luce’s response probabilities. This work is relevant because (i) we provide a very general framework integrating the positive characteristics of both quantum and classical approaches previously in confrontation, and (ii) we define a cognitive network which can be used to bring other connectivist approaches to decision-making into the quantum stochastic realm. We model the decision-maker as an open system in contact with her surrounding environment, and the time-length of the decision-making process reveals to be also a measure of the process’ degree of interplay between the unitary and irreversible dynamics. Implementing quantum coherence on classical networks may be a door to better integrate human-like reasoning biases in stochastic models for decision-making. PMID:27030372

A key heterogeneous structure of fractal networks based on inverse renormalization scheme

NASA Astrophysics Data System (ADS)

Bai, Yanan; Huang, Ning; Sun, Lina

2018-06-01

Self-similarity property of complex networks was found by the application of renormalization group theory. Based on this theory, network topologies can be classified into universality classes in the space of configurations. In return, through inverse renormalization scheme, a given primitive structure can grow into a pure fractal network, then adding different types of shortcuts, it exhibits different characteristics of complex networks. However, the effect of primitive structure on networks structural property has received less attention. In this paper, we introduce a degree variance index to measure the dispersion of nodes degree in the primitive structure, and investigate the effect of the primitive structure on network structural property quantified by network efficiency. Numerical simulations and theoretical analysis show a primitive structure is a key heterogeneous structure of generated networks based on inverse renormalization scheme, whether or not adding shortcuts, and the network efficiency is positively correlated with degree variance of the primitive structure.

Open Source Software Projects Needing Security Investments

DTIC Science & Technology

2015-06-19

modtls, BouncyCastle, gpg, otr, axolotl. 7. Static analyzers: Clang, Frama-C. 8. Nginx. 9. OpenVPN . It was noted that the funding model may be similar...to OpenSSL, where consulting funds the company. It was also noted that OpenVPN needs to correctly use OpenSSL in order to be secure, so focusing on...Dovecot 4. Other high-impact network services: OpenSSH, OpenVPN , BIND, ISC DHCP, University of Delaware NTPD 5. Core infrastructure data parsers

CAPE-OPEN WITH .NET TRAINING COURSE

EPA Science Inventory

On March 7, 2007 in Heidelberg, Germany, the CAPE-OPEN Laboratories Network (CO-LaN) is offering a one-day training seminar on implementing CAPE-OPEN compliant process modeling components (PMCs) using .NET-based development tools. This seminar will be geared to component develope...