Robust network topologies for generating switch-like cellular responses.

Directory of Open Access Journals (Sweden)

Najaf A Shah

2011-06-01

Full Text Available Signaling networks that convert graded stimuli into binary, all-or-none cellular responses are critical in processes ranging from cell-cycle control to lineage commitment. To exhaustively enumerate topologies that exhibit this switch-like behavior, we simulated all possible two- and three-component networks on random parameter sets, and assessed the resulting response profiles for both steepness (ultrasensitivity and extent of memory (bistability. Simulations were used to study purely enzymatic networks, purely transcriptional networks, and hybrid enzymatic/transcriptional networks, and the topologies in each class were rank ordered by parametric robustness (i.e., the percentage of applied parameter sets exhibiting ultrasensitivity or bistability. Results reveal that the distribution of network robustness is highly skewed, with the most robust topologies clustering into a small number of motifs. Hybrid networks are the most robust in generating ultrasensitivity (up to 28% and bistability (up to 18%; strikingly, a purely transcriptional framework is the most fragile in generating either ultrasensitive (up to 3% or bistable (up to 1% responses. The disparity in robustness among the network classes is due in part to zero-order ultrasensitivity, an enzyme-specific phenomenon, which repeatedly emerges as a particularly robust mechanism for generating nonlinearity and can act as a building block for switch-like responses. We also highlight experimentally studied examples of topologies enabling switching behavior, in both native and synthetic systems, that rank highly in our simulations. This unbiased approach for identifying topologies capable of a given response may be useful in discovering new natural motifs and in designing robust synthetic gene networks.

AmeriFlux Measurement Network: Science Team Research

Energy Technology Data Exchange (ETDEWEB)

Law, B E

2012-12-12

Research involves analysis and field direction of AmeriFlux operations, and the PI provides scientific leadership of the AmeriFlux network. Activities include the coordination and quality assurance of measurements across AmeriFlux network sites, synthesis of results across the network, organizing and supporting the annual Science Team Meeting, and communicating AmeriFlux results to the scientific community and other users. Objectives of measurement research include (i) coordination of flux and biometric measurement protocols (ii) timely data delivery to the Carbon Dioxide Information and Analysis Center (CDIAC); and (iii) assurance of data quality of flux and ecosystem measurements contributed by AmeriFlux sites. Objectives of integration and synthesis activities include (i) integration of site data into network-wide synthesis products; and (ii) participation in the analysis, modeling and interpretation of network data products. Communications objectives include (i) organizing an annual meeting of AmeriFlux investigators for reporting annual flux measurements and exchanging scientific information on ecosystem carbon budgets; (ii) developing focused topics for analysis and publication; and (iii) developing data reporting protocols in support of AmeriFlux network goals.

Instantiating a Global Network Measurement Framework

Energy Technology Data Exchange (ETDEWEB)

Tierney, Brian L.; Boote, Jeff; Boyd, Eric; Brown, Aaron; Grigoriev, Maxim; Metzger, Joe; Swany, Martin; Zekauskas, Matt; Zurawski, Jason

2008-12-15

perfSONAR is a web services-based infrastructure for collecting and publishing network performance monitoring. A primary goal of perfSONAR is making it easier to solve end-to-end performance problems on paths crossing several networks. It contains a set of services delivering performance measurements in a federated environment. These services act as an intermediate layer, between the performance measurement tools and the diagnostic or visualization applications. This layer is aimed at making and exchanging performance measurements across multiple networks and multiple user communities, using well-defined protocols. This paper summarizes the key perfSONAR components, and describes how they are deployed by the US-LHC community to monitor the networks distributing LHC data from CERN. All monitoring data described herein is publicly available, and we hope the availability of this data via a standard schema will inspire others to contribute to the effort by building network data analysis applications that use perfSONAR.

Measurement methods on the complexity of network

Institute of Scientific and Technical Information of China (English)

LIN Lin; DING Gang; CHEN Guo-song

2010-01-01

Based on the size of network and the number of paths in the network,we proposed a model of topology complexity of a network to measure the topology complexity of the network.Based on the analyses of the effects of the number of the equipment,the types of equipment and the processing time of the node on the complexity of the network with the equipment-constrained,a complexity model of equipment-constrained network was constructed to measure the integrated complexity of the equipment-constrained network.The algorithms for the two models were also developed.An automatic generator of the random single label network was developed to test the models.The results show that the models can correctly evaluate the topology complexity and the integrated complexity of the networks.

Evaluating airline energy efficiency: An integrated approach with Network Epsilon-based Measure and Network Slacks-based Measure

International Nuclear Information System (INIS)

Xu, Xin; Cui, Qiang

2017-01-01

This paper focuses on evaluating airline energy efficiency, which is firstly divided into four stages: Operations Stage, Fleet Maintenance Stage, Services Stage and Sales Stage. The new four-stage network structure of airline energy efficiency is a modification of existing models. A new approach, integrated with Network Epsilon-based Measure and Network Slacks-based Measure, is applied to assess the overall energy efficiency and divisional efficiency of 19 international airlines from 2008 to 2014. The influencing factors of airline energy efficiency are analyzed through the regression analysis. The results indicate the followings: 1. The integrated model can identify the benchmarking airlines in the overall system and stages. 2. Most airlines' energy efficiencies keep steady during the period, except for some sharply fluctuations. The efficiency decreases mainly centralized in the year 2008–2011, affected by the financial crisis in the USA. 3. The average age of fleet is positively correlated with the overall energy efficiency, and each divisional efficiency has different significant influencing factors. - Highlights: • An integrated approach with Network Epsilon-based Measure and Network Slacks-based Measure is developed. • 19 airlines' energy efficiencies are evaluated. • Garuda Indonesia has the highest overall energy efficiency.

Measuring distances between complex networks

International Nuclear Information System (INIS)

Andrade, Roberto F.S.; Miranda, Jose G.V.; Pinho, Suani T.R.; Lobao, Thierry Petit

2008-01-01

A previously introduced concept of higher order neighborhoods in complex networks, [R.F.S. Andrade, J.G.V. Miranda, T.P. Lobao, Phys. Rev. E 73 (2006) 046101] is used to define a distance between networks with the same number of nodes. With such measure, expressed in terms of the matrix elements of the neighborhood matrices of each network, it is possible to compare, in a quantitative way, how far apart in the space of neighborhood matrices two networks are. The distance between these matrices depends on both the network topologies and the adopted node numberings. While the numbering of one network is fixed, a Monte Carlo algorithm is used to find the best numbering of the other network, in the sense that it minimizes the distance between the matrices. The minimal value found for the distance reflects differences in the neighborhood structures of the two networks that arise only from distinct topologies. This procedure ends up by providing a projection of the first network on the pattern of the second one. Examples are worked out allowing for a quantitative comparison for distances among distinct networks, as well as among distinct realizations of random networks

Investments in power networks and alternative measures

International Nuclear Information System (INIS)

2003-01-01

Measures taken with respect to production and consumption are often alternatives to investments in the power networks. While decisions about production and consumption are taken in the market, the network operation is subject to monopoly regulation. In the central network, Statnett's commission is to invest on the basis of socioeconomic profitability. There is a need for much better coordination between network investments and other measures in the power system. The price signal from the market and general tariffs are not sufficient to realize optimal solutions, and there is a need for a ''visible hand'' that can contribute to the realization of the solutions that are the best in each individual situation. It is desirable to create processes and incentives that realize the best solutions, independently of dealing with network investments, local power production or other measures.

Measurement of Online Social Networks

Science.gov (United States)

Gjoka, Mina

2010-01-01

In recent years, the popularity of online social networks (OSN) has risen to unprecedented levels, with the most popular ones having hundreds of millions of users. This success has generated interest within the networking community and has given rise to a number of measurement and characterization studies, which provide a first step towards their…

National network of environment radioactivity measurements. Press kit

International Nuclear Information System (INIS)

2010-01-01

This document first presents the objectives, challenges, context, operation and actors of the French national network of environment radioactivity measurements. It discusses the reasons for these measurements, the way they are performed, who perform them and how they are transmitted to the national network. It describes the quality policy for these measurements, and how this network is at the service of authorities, experts and population. It outlines the originality of the French approach within the European Union, and how this network takes the population expectations and their evolution into account

A method of reconstructing the spatial measurement network by mobile measurement transmitter for shipbuilding

International Nuclear Information System (INIS)

Guo, Siyang; Lin, Jiarui; Yang, Linghui; Ren, Yongjie; Guo, Yin

2017-01-01

The workshop Measurement Position System (wMPS) is a distributed measurement system which is suitable for the large-scale metrology. However, there are some inevitable measurement problems in the shipbuilding industry, such as the restriction by obstacles and limited measurement range. To deal with these factors, this paper presents a method of reconstructing the spatial measurement network by mobile transmitter. A high-precision coordinate control network with more than six target points is established. The mobile measuring transmitter can be added into the measurement network using this coordinate control network with the spatial resection method. This method reconstructs the measurement network and broadens the measurement scope efficiently. To verify this method, two comparison experiments are designed with the laser tracker as the reference. The results demonstrate that the accuracy of point-to-point length is better than 0.4mm and the accuracy of coordinate measurement is better than 0.6mm. (paper)

The new challenges of multiplex networks: Measures and models

Science.gov (United States)

Battiston, Federico; Nicosia, Vincenzo; Latora, Vito

2017-02-01

What do societies, the Internet, and the human brain have in common? They are all examples of complex relational systems, whose emerging behaviours are largely determined by the non-trivial networks of interactions among their constituents, namely individuals, computers, or neurons, rather than only by the properties of the units themselves. In the last two decades, network scientists have proposed models of increasing complexity to better understand real-world systems. Only recently we have realised that multiplexity, i.e. the coexistence of several types of interactions among the constituents of a complex system, is responsible for substantial qualitative and quantitative differences in the type and variety of behaviours that a complex system can exhibit. As a consequence, multilayer and multiplex networks have become a hot topic in complexity science. Here we provide an overview of some of the measures proposed so far to characterise the structure of multiplex networks, and a selection of models aiming at reproducing those structural properties and quantifying their statistical significance. Focusing on a subset of relevant topics, this brief review is a quite comprehensive introduction to the most basic tools for the analysis of multiplex networks observed in the real-world. The wide applicability of multiplex networks as a framework to model complex systems in different fields, from biology to social sciences, and the colloquial tone of the paper will make it an interesting read for researchers working on both theoretical and experimental analysis of networked systems.

Multi-attribute integrated measurement of node importance in complex networks.

Science.gov (United States)

Wang, Shibo; Zhao, Jinlou

2015-11-01

The measure of node importance in complex networks is very important to the research of networks stability and robustness; it also can ensure the security of the whole network. Most researchers have used a single indicator to measure the networks node importance, so that the obtained measurement results only reflect certain aspects of the networks with a loss of information. Meanwhile, because of the difference of networks topology, the nodes' importance should be described by combining the character of the networks topology. Most of the existing evaluation algorithms cannot completely reflect the circumstances of complex networks, so this paper takes into account the degree of centrality, the relative closeness centrality, clustering coefficient, and topology potential and raises an integrated measuring method to measure the nodes' importance. This method can reflect nodes' internal and outside attributes and eliminate the influence of network structure on the node importance. The experiments of karate network and dolphin network show that networks topology structure integrated measure has smaller range of metrical result than a single indicator and more universal. Experiments show that attacking the North American power grid and the Internet network with the method has a faster convergence speed than other methods.

Robustness of weighted networks

Science.gov (United States)

Bellingeri, Michele; Cassi, Davide

2018-01-01

Complex network response to node loss is a central question in different fields of network science because node failure can cause the fragmentation of the network, thus compromising the system functioning. Previous studies considered binary networks where the intensity (weight) of the links is not accounted for, i.e. a link is either present or absent. However, in real-world networks the weights of connections, and thus their importance for network functioning, can be widely different. Here, we analyzed the response of real-world and model networks to node loss accounting for link intensity and the weighted structure of the network. We used both classic binary node properties and network functioning measure, introduced a weighted rank for node importance (node strength), and used a measure for network functioning that accounts for the weight of the links (weighted efficiency). We find that: (i) the efficiency of the attack strategies changed using binary or weighted network functioning measures, both for real-world or model networks; (ii) in some cases, removing nodes according to weighted rank produced the highest damage when functioning was measured by the weighted efficiency; (iii) adopting weighted measure for the network damage changed the efficacy of the attack strategy with respect the binary analyses. Our results show that if the weighted structure of complex networks is not taken into account, this may produce misleading models to forecast the system response to node failure, i.e. consider binary links may not unveil the real damage induced in the system. Last, once weighted measures are introduced, in order to discover the best attack strategy, it is important to analyze the network response to node loss using nodes rank accounting the intensity of the links to the node.

Functional neural networks underlying response inhibition in adolescents and adults.

Science.gov (United States)

Stevens, Michael C; Kiehl, Kent A; Pearlson, Godfrey D; Calhoun, Vince D

2007-07-19

This study provides the first description of neural network dynamics associated with response inhibition in healthy adolescents and adults. Functional and effective connectivity analyses of whole brain hemodynamic activity elicited during performance of a Go/No-Go task were used to identify functionally integrated neural networks and characterize their causal interactions. Three response inhibition circuits formed a hierarchical, inter-dependent system wherein thalamic modulation of input to premotor cortex by fronto-striatal regions led to response suppression. Adolescents differed from adults in the degree of network engagement, regional fronto-striatal-thalamic connectivity, and network dynamics. We identify and characterize several age-related differences in the function of neural circuits that are associated with behavioral performance changes across adolescent development.

Enhancing Electrophoretic Display Lifetime: Thiol-Polybutadiene Evaporation Barrier Property Response to Network Microstructure

Energy Technology Data Exchange (ETDEWEB)

Cook, Caitlyn Christian [California State Polytechnic State Univ., San Luis Obispo, CA (United States)

2017-02-27

An evaporation barrier is required to enhance the lifetime of electrophoretic deposition (EPD) displays. As EPD functions on the basis of reversible deposition and resuspension of colloids suspended in a solvent, evaporation of the solvent ultimately leads to device failure. Incorporation of a thiol-polybutadiene elastomer into EPD displays enabled display lifetime surpassing six months in counting and catalyzed rigid display transition into a flexible package. Final flexible display transition to mass production compels an electronic-ink approach to encapsulate display suspension within an elastomer shell. Final thiol-polybutadiene photosensitive resin network microstructure was idealized to be dense, homogeneous, and expose an elastic response to deformation. Research at hand details an approach to understanding microstructural change within display elastomers. Polybutadiene-based resin properties are modified via polymer chain structure, with and without added aromatic urethane methacrylate difunctionality, and in measuring network response to variation in thiol and initiator concentration. Dynamic mechanical analysis results signify that cross-linked segments within a difunctionalized polybutadiene network were on average eight times more elastically active than that of linked segments within a non-functionalized polybutadiene network. Difunctionalized polybutadiene samples also showed a 2.5 times greater maximum elastic modulus than non-functionalized samples. Hybrid polymer composed of both polybutadiene chains encompassed TE-2000 stiffness and B-1000 elasticity for use in encapsulating display suspension. Later experiments measured kinetic and rheological response due to alteration in dithiol cross-linker chain length via real time Fourier transform infrared spectroscopy and real-time dynamic rheology. Distinct differences were discovered between dithiol resin systems, as maximum thiol conversion achieved in short and long chain length dithiols was 86% and

Structured chaos shapes spike-response noise entropy in balanced neural networks

Directory of Open Access Journals (Sweden)

Guillaume eLajoie

2014-10-01

Full Text Available Large networks of sparsely coupled, excitatory and inhibitory cells occur throughout the brain. For many models of these networks, a striking feature is that their dynamics are chaotic and thus, are sensitive to small perturbations. How does this chaos manifest in the neural code? Specifically, how variable are the spike patterns that such a network produces in response to an input signal? To answer this, we derive a bound for a general measure of variability -- spike-train entropy. This leads to important insights on the variability of multi-cell spike pattern distributions in large recurrent networks of spiking neurons responding to fluctuating inputs. The analysis is based on results from random dynamical systems theory and is complemented by detailed numerical simulations. We find that the spike pattern entropy is an order of magnitude lower than what would be extrapolated from single cells. This holds despite the fact that network coupling becomes vanishingly sparse as network size grows -- a phenomenon that depends on ``extensive chaos, as previously discovered for balanced networks without stimulus drive. Moreover, we show how spike pattern entropy is controlled by temporal features of the inputs. Our findings provide insight into how neural networks may encode stimuli in the presence of inherently chaotic dynamics.

Centrality measures for immunization of weighted networks

Directory of Open Access Journals (Sweden)

Mohammad Khansari

2016-03-01

Full Text Available Effective immunization of individual communities with minimal cost in vaccination has made great discussion surrounding the realm of complex networks. Meanwhile, proper realization of relationship among people in society and applying it to social networks brings about substantial improvements in immunization. Accordingly, weighted graph in which link weights represent the intensity and intimacy of relationships is an acceptable approach. In this work we employ weighted graphs and a wide variety of weighted centrality measures to distinguish important individuals in contagion of diseases. Furthermore, we propose new centrality measures for weighted networks. Our experimental results show that Radiality-Degree centrality is satisfying for weighted BA networks. Additionally, PageRank-Degree and Radiality-Degree centralities showmoreacceptable performance in targeted immunization of weighted networks.

On Measuring the Complexity of Networks: Kolmogorov Complexity versus Entropy

Directory of Open Access Journals (Sweden)

Mikołaj Morzy

2017-01-01

Full Text Available One of the most popular methods of estimating the complexity of networks is to measure the entropy of network invariants, such as adjacency matrices or degree sequences. Unfortunately, entropy and all entropy-based information-theoretic measures have several vulnerabilities. These measures neither are independent of a particular representation of the network nor can capture the properties of the generative process, which produces the network. Instead, we advocate the use of the algorithmic entropy as the basis for complexity definition for networks. Algorithmic entropy (also known as Kolmogorov complexity or K-complexity for short evaluates the complexity of the description required for a lossless recreation of the network. This measure is not affected by a particular choice of network features and it does not depend on the method of network representation. We perform experiments on Shannon entropy and K-complexity for gradually evolving networks. The results of these experiments point to K-complexity as the more robust and reliable measure of network complexity. The original contribution of the paper includes the introduction of several new entropy-deceiving networks and the empirical comparison of entropy and K-complexity as fundamental quantities for constructing complexity measures for networks.

Representative Delay Measurements (RDM: Facing the Challenge of Modern Networks

Directory of Open Access Journals (Sweden)

Joachim Fabini

2015-02-01

Full Text Available Network access technologies have evolved significantly in the last years. They deploy novel mechanisms like reactive capacity allocation and time-slotted operation to optimize overall network capacity. From a single node's perspective, such optimizations decrease network determinism and measurement repeatability. Evolving application fields like machine to machine (M2M communications or real-time gaming often have strict real-time requirements to operate correctly. Highly accurate delay measurements are necessary to monitor network compliance with application demands or to detect deviations of normal network behavior, which may be caused by network failures, misconfigurations or attacks. This paper analyzes factors that challenge active delay measurements in modern networks. It introduces the Representative Delay Measurement tool (RDM that addresses these factors and proposes solutions that conform to requirements of the recently published RFC7312. Delay measurement results acquired using RDM in live networks confirm that advanced measurement methods can significantly improve the quality of measurement samples by isolating systematic network behavior. The resulting high-quality samples are one prerequisite for accurate statistics that support proper operation of subsequent algorithms and applications.

Toward Measuring Network Aesthetics Based on Symmetry

Directory of Open Access Journals (Sweden)

Zengqiang Chen

2017-05-01

Full Text Available In this exploratory paper, we discuss quantitative graph-theoretical measures of network aesthetics. Related work in this area has typically focused on geometrical features (e.g., line crossings or edge bendiness of drawings or visual representations of graphs which purportedly affect an observer’s perception. Here we take a very different approach, abandoning reliance on geometrical properties, and apply information-theoretic measures to abstract graphs and networks directly (rather than to their visual representaions as a means of capturing classical appreciation of structural symmetry. Examples are used solely to motivate the approach to measurement, and to elucidate our symmetry-based mathematical theory of network aesthetics.

Microscale force response and morphology of tunable co-polymerized cytoskeleton networks

Science.gov (United States)

Ricketts, Shea; Yadav, Vikrant; Ross, Jennifer L.; Robertson-Anderson, Rae M.

The cytoskeleton is largely comprised of actin and microtubules that entangle and crosslink to form complex networks and structures, giving rise to nonlinear multifunctional mechanics in cells. The relative concentrations of semiflexible actin filaments and rigid microtubules tune cytoskeleton function, allowing cells to move and divide while maintaining rigidity and resilience. To elucidate this complex tunability, we create in vitro composites of co-polymerized actin and microtubules with actin:microtubule molar ratios of 0:1-1:0. We use optical tweezers and confocal microscopy to characterize the nonlinear microscale force response and morphology of the composites. We optically drag a microsphere 30 μm through varying actin-microtubule networks at 10 μm/s and 20 μm/s, and measure the force the networks exerts to resist the strain and the force relaxation following strain. We use dual-color confocal microscopy to image distinctly-labeled filaments in the networks, and characterize the integration of actin and microtubules, network connectivity, and filament rigidity. We find that increasing the fraction of microtubules in networks non-monotonically increases elasticity and stiffness, and hinders force relaxation by suppressing network mobility and fluctuations. NSF CAREER Award (DMR-1255446), Scialog Collaborative Innovation Award funded by Research Corporation for Scientific Advancement (Grant No. 24192).

Is a Responsive Default Mode Network Required for Successful Working Memory Task Performance?

Science.gov (United States)

Čeko, Marta; Gracely, John L; Fitzcharles, Mary-Ann; Seminowicz, David A; Schweinhardt, Petra; Bushnell, M Catherine

2015-08-19

In studies of cognitive processing using tasks with externally directed attention, regions showing increased (external-task-positive) and decreased or "negative" [default-mode network (DMN)] fMRI responses during task performance are dynamically responsive to increasing task difficulty. Responsiveness (modulation of fMRI signal by increasing load) has been linked directly to successful cognitive task performance in external-task-positive regions but not in DMN regions. To investigate whether a responsive DMN is required for successful cognitive performance, we compared healthy human subjects (n = 23) with individuals shown to have decreased DMN engagement (chronic pain patients, n = 28). Subjects performed a multilevel working-memory task (N-back) during fMRI. If a responsive DMN is required for successful performance, patients having reduced DMN responsiveness should show worsened performance; if performance is not reduced, their brains should show compensatory activation in external-task-positive regions or elsewhere. All subjects showed decreased accuracy and increased reaction times with increasing task level, with no significant group differences on either measure at any level. Patients had significantly reduced negative fMRI response (deactivation) of DMN regions (posterior cingulate/precuneus, medial prefrontal cortex). Controls showed expected modulation of DMN deactivation with increasing task difficulty. Patients showed significantly reduced modulation of DMN deactivation by task difficulty, despite their successful task performance. We found no evidence of compensatory neural recruitment in external-task-positive regions or elsewhere. Individual responsiveness of the external-task-positive ventrolateral prefrontal cortex, but not of DMN regions, correlated with task accuracy. These findings suggest that a responsive DMN may not be required for successful cognitive performance; a responsive external-task-positive network may be sufficient. We studied the

Using Convolutional Neural Network Filters to Measure Left-Right Mirror Symmetry in Images

Directory of Open Access Journals (Sweden)

Anselm Brachmann

2016-12-01

Full Text Available We propose a method for measuring symmetry in images by using filter responses from Convolutional Neural Networks (CNNs. The aim of the method is to model human perception of left/right symmetry as closely as possible. Using the Convolutional Neural Network (CNN approach has two main advantages: First, CNN filter responses closely match the responses of neurons in the human visual system; they take information on color, edges and texture into account simultaneously. Second, we can measure higher-order symmetry, which relies not only on color, edges and texture, but also on the shapes and objects that are depicted in images. We validated our algorithm on a dataset of 300 music album covers, which were rated according to their symmetry by 20 human observers, and compared results with those from a previously proposed method. With our method, human perception of symmetry can be predicted with high accuracy. Moreover, we demonstrate that the inclusion of features from higher CNN layers, which encode more abstract image content, increases the performance further. In conclusion, we introduce a model of left/right symmetry that closely models human perception of symmetry in CD album covers.

Analyzing complex networks through correlations in centrality measurements

International Nuclear Information System (INIS)

Ricardo Furlan Ronqui, José; Travieso, Gonzalo

2015-01-01

Many real world systems can be expressed as complex networks of interconnected nodes. It is frequently important to be able to quantify the relative importance of the various nodes in the network, a task accomplished by defining some centrality measures, with different centrality definitions stressing different aspects of the network. It is interesting to know to what extent these different centrality definitions are related for different networks. In this work, we study the correlation between pairs of a set of centrality measures for different real world networks and two network models. We show that the centralities are in general correlated, but with stronger correlations for network models than for real networks. We also show that the strength of the correlation of each pair of centralities varies from network to network. Taking this fact into account, we propose the use of a centrality correlation profile, consisting of the values of the correlation coefficients between all pairs of centralities of interest, as a way to characterize networks. Using the yeast protein interaction network as an example we show also that the centrality correlation profile can be used to assess the adequacy of a network model as a representation of a given real network. (paper)

Vector network analyzer (VNA) measurements and uncertainty assessment

CERN Document Server

Shoaib, Nosherwan

2017-01-01

This book describes vector network analyzer measurements and uncertainty assessments, particularly in waveguide test-set environments, in order to establish their compatibility to the International System of Units (SI) for accurate and reliable characterization of communication networks. It proposes a fully analytical approach to measurement uncertainty evaluation, while also highlighting the interaction and the linear propagation of different uncertainty sources to compute the final uncertainties associated with the measurements. The book subsequently discusses the dimensional characterization of waveguide standards and the quality of the vector network analyzer (VNA) calibration techniques. The book concludes with an in-depth description of the novel verification artefacts used to assess the performance of the VNAs. It offers a comprehensive reference guide for beginners to experts, in both academia and industry, whose work involves the field of network analysis, instrumentation and measurements.

A complex network-based importance measure for mechatronics systems

Science.gov (United States)

Wang, Yanhui; Bi, Lifeng; Lin, Shuai; Li, Man; Shi, Hao

2017-01-01

In view of the negative impact of functional dependency, this paper attempts to provide an alternative importance measure called Improved-PageRank (IPR) for measuring the importance of components in mechatronics systems. IPR is a meaningful extension of the centrality measures in complex network, which considers usage reliability of components and functional dependency between components to increase importance measures usefulness. Our work makes two important contributions. First, this paper integrates the literature of mechatronic architecture and complex networks theory to define component network. Second, based on the notion of component network, a meaningful IPR is brought into the identifying of important components. In addition, the IPR component importance measures, and an algorithm to perform stochastic ordering of components due to the time-varying nature of usage reliability of components and functional dependency between components, are illustrated with a component network of bogie system that consists of 27 components.

Local and global responses in complex gene regulation networks

Science.gov (United States)

Tsuchiya, Masa; Selvarajoo, Kumar; Piras, Vincent; Tomita, Masaru; Giuliani, Alessandro

2009-04-01

An exacerbated sensitivity to apparently minor stimuli and a general resilience of the entire system stay together side-by-side in biological systems. This apparent paradox can be explained by the consideration of biological systems as very strongly interconnected network systems. Some nodes of these networks, thanks to their peculiar location in the network architecture, are responsible for the sensitivity aspects, while the large degree of interconnection is at the basis of the resilience properties of the system. One relevant feature of the high degree of connectivity of gene regulation networks is the emergence of collective ordered phenomena influencing the entire genome and not only a specific portion of transcripts. The great majority of existing gene regulation models give the impression of purely local ‘hard-wired’ mechanisms disregarding the emergence of global ordered behavior encompassing thousands of genes while the general, genome wide, aspects are less known. Here we address, on a data analysis perspective, the discrimination between local and global scale regulations, this goal was achieved by means of the examination of two biological systems: innate immune response in macrophages and oscillating growth dynamics in yeast. Our aim was to reconcile the ‘hard-wired’ local view of gene regulation with a global continuous and scalable one borrowed from statistical physics. This reconciliation is based on the network paradigm in which the local ‘hard-wired’ activities correspond to the activation of specific crucial nodes in the regulation network, while the scalable continuous responses can be equated to the collective oscillations of the network after a perturbation.

Building and measuring a high performance network architecture

Energy Technology Data Exchange (ETDEWEB)

Kramer, William T.C.; Toole, Timothy; Fisher, Chuck; Dugan, Jon; Wheeler, David; Wing, William R; Nickless, William; Goddard, Gregory; Corbato, Steven; Love, E. Paul; Daspit, Paul; Edwards, Hal; Mercer, Linden; Koester, David; Decina, Basil; Dart, Eli; Paul Reisinger, Paul; Kurihara, Riki; Zekauskas, Matthew J; Plesset, Eric; Wulf, Julie; Luce, Douglas; Rogers, James; Duncan, Rex; Mauth, Jeffery

2001-04-20

Once a year, the SC conferences present a unique opportunity to create and build one of the most complex and highest performance networks in the world. At SC2000, large-scale and complex local and wide area networking connections were demonstrated, including large-scale distributed applications running on different architectures. This project was designed to use the unique opportunity presented at SC2000 to create a testbed network environment and then use that network to demonstrate and evaluate high performance computational and communication applications. This testbed was designed to incorporate many interoperable systems and services and was designed for measurement from the very beginning. The end results were key insights into how to use novel, high performance networking technologies and to accumulate measurements that will give insights into the networks of the future.

Critical field measurements in a superconducting networks

International Nuclear Information System (INIS)

Pannetier, B.; Chaussy, J.; Rammal, R.

1984-01-01

We have measured the critical field of a periodic two-dimensional network of superconducting indium. At low fields, the critical line Hsub(c)(T) reflects the network topology and exhibits well-defined cusps due to flux quantization corresponding to both integer and rational number of flux quanta phi 0 = h/2e per unit loop of the network [fr

Measuring network competence in buyer-supplier relationships

Directory of Open Access Journals (Sweden)

Gert Human

2011-04-01

Full Text Available Managing multiple buyer-seller relationships in business-to-business networks demands an understanding of a firm’s competence to manage in an interconnected environment.  This paper reports on an attempt to measure network competence by using the NetCompTest scale in business-to-business markets in South Africa. Based on a pilot study refinement, the paper proposes an adjusted measurement scale and details the results of a second round of measurement conducted amongst 495 business-to-business managers in South Africa. The results established partial support for the use of the NetCompTest scale in a South African context, and analysis of variance indicated that some differences in the measurement based on firm and individual characteristics can be observed in the data. The paper assists in theory-building and provides managerial insights for managing buyer-supplier relationships in networks.

Natural semantic networks in the Social Representations of Responsibility

Directory of Open Access Journals (Sweden)

Humberto Emilio Aguilera Arévalo

2010-07-01

Full Text Available The study of social representations of responsibility is a fundamental construct of the present democratic societies. Different empirical techniques such as natural semantic networks can significantly improve the approach to the object of study than the traditional associationist techniques. The present study examines natural semantic networks of six stimulus words with respect to responsibility and irresponsibility at the individual, in group and out group level in a sample of Guatemalan students.

Geographically Locating an Internet Node Using Network Latency Measurement

National Research Council Canada - National Science Library

Turnbaugh, Eugene

2004-01-01

.... The difficulties include accurate latency measure, network address translation (NAT) masking, service blocking, disparate physical configuration, dissimilar network hardware, and inaccurate and limited measuring tools...

Is a Responsive Default Mode Network Required for Successful Working Memory Task Performance?

Science.gov (United States)

Čeko, Marta; Gracely, John L.; Fitzcharles, Mary-Ann; Seminowicz, David A.; Schweinhardt, Petra

2015-01-01

In studies of cognitive processing using tasks with externally directed attention, regions showing increased (external-task-positive) and decreased or “negative” [default-mode network (DMN)] fMRI responses during task performance are dynamically responsive to increasing task difficulty. Responsiveness (modulation of fMRI signal by increasing load) has been linked directly to successful cognitive task performance in external-task-positive regions but not in DMN regions. To investigate whether a responsive DMN is required for successful cognitive performance, we compared healthy human subjects (n = 23) with individuals shown to have decreased DMN engagement (chronic pain patients, n = 28). Subjects performed a multilevel working-memory task (N-back) during fMRI. If a responsive DMN is required for successful performance, patients having reduced DMN responsiveness should show worsened performance; if performance is not reduced, their brains should show compensatory activation in external-task-positive regions or elsewhere. All subjects showed decreased accuracy and increased reaction times with increasing task level, with no significant group differences on either measure at any level. Patients had significantly reduced negative fMRI response (deactivation) of DMN regions (posterior cingulate/precuneus, medial prefrontal cortex). Controls showed expected modulation of DMN deactivation with increasing task difficulty. Patients showed significantly reduced modulation of DMN deactivation by task difficulty, despite their successful task performance. We found no evidence of compensatory neural recruitment in external-task-positive regions or elsewhere. Individual responsiveness of the external-task-positive ventrolateral prefrontal cortex, but not of DMN regions, correlated with task accuracy. These findings suggest that a responsive DMN may not be required for successful cognitive performance; a responsive external-task-positive network may be sufficient

Measure of Node Similarity in Multilayer Networks

DEFF Research Database (Denmark)

Møllgaard, Anders; Zettler, Ingo; Dammeyer, Jesper

2016-01-01

The weight of links in a network is often related to the similarity of thenodes. Here, we introduce a simple tunable measure for analysing the similarityof nodes across different link weights. In particular, we use the measure toanalyze homophily in a group of 659 freshman students at a large...... university.Our analysis is based on data obtained using smartphones equipped with customdata collection software, complemented by questionnaire-based data. The networkof social contacts is represented as a weighted multilayer network constructedfrom different channels of telecommunication as well as data...... might bepresent in one layer of the multilayer network and simultaneously be absent inthe other layers. For a variable such as gender, our measure reveals atransition from similarity between nodes connected with links of relatively lowweight to dis-similarity for the nodes connected by the strongest...

A New Resilience Measure for Supply Chain Networks

Directory of Open Access Journals (Sweden)

Ruiying Li

2017-01-01

Full Text Available Currently, supply chain networks can span the whole world, and any disruption of these networks may cause economic losses, decreases in sales and unsustainable supplies. Resilience, the ability of the system to withstand disruption and return to a normal state quickly, has become a new challenge during the supply chain network design. This paper defines a new resilience measure as the ratio of the integral of the normalized system performance within its maximum allowable recovery time after the disruption to the integral of the performance in the normal state. Using the maximum allowable recovery time of the system as the time interval under consideration, this measure allows the resilience of different systems to be compared on the same relative scale, and be used under both scenarios that the system can or cannot restore in the given time. Two specific resilience measures, the resilience based on the amount of product delivered and the resilience based on the average delivery distance, are provided for supply chain networks. To estimate the resilience of a given supply chain network, a resilience simulation method is proposed based on the Monte Carlo method. A four-layered hierarchial mobile phone supply chain network is used to illustrate the resilience quantification process and show how network structure affects the resilience of supply chain networks.

Hyperbolicity measures democracy in real-world networks

Science.gov (United States)

Borassi, Michele; Chessa, Alessandro; Caldarelli, Guido

2015-09-01

In this work, we analyze the hyperbolicity of real-world networks, a geometric quantity that measures if a space is negatively curved. We provide two improvements in our understanding of this quantity: first of all, in our interpretation, a hyperbolic network is "aristocratic", since few elements "connect" the system, while a non-hyperbolic network has a more "democratic" structure with a larger number of crucial elements. The second contribution is the introduction of the average hyperbolicity of the neighbors of a given node. Through this definition, we outline an "influence area" for the vertices in the graph. We show that in real networks the influence area of the highest degree vertex is small in what we define "local" networks (i.e., social or peer-to-peer networks), and large in "global" networks (i.e., power grid, metabolic networks, or autonomous system networks).

Topologically determined optimal stochastic resonance responses of spatially embedded networks

International Nuclear Information System (INIS)

Gosak, Marko; Marhl, Marko; Korosak, Dean

2011-01-01

We have analyzed the stochastic resonance phenomenon on spatial networks of bistable and excitable oscillators, which are connected according to their location and the amplitude of external forcing. By smoothly altering the network topology from a scale-free (SF) network with dominating long-range connections to a network where principally only adjacent oscillators are connected, we reveal that besides an optimal noise intensity, there is also a most favorable interaction topology at which the best correlation between the response of the network and the imposed weak external forcing is achieved. For various distributions of the amplitudes of external forcing, the optimal topology is always found in the intermediate regime between the highly heterogeneous SF network and the strong geometric regime. Our findings thus indicate that a suitable number of hubs and with that an optimal ratio between short- and long-range connections is necessary in order to obtain the best global response of a spatial network. Furthermore, we link the existence of the optimal interaction topology to a critical point indicating the transition from a long-range interactions-dominated network to a more lattice-like network structure.

Measure of Node Similarity in Multilayer Networks.

Directory of Open Access Journals (Sweden)

Anders Mollgaard

Full Text Available The weight of links in a network is often related to the similarity of the nodes. Here, we introduce a simple tunable measure for analysing the similarity of nodes across different link weights. In particular, we use the measure to analyze homophily in a group of 659 freshman students at a large university. Our analysis is based on data obtained using smartphones equipped with custom data collection software, complemented by questionnaire-based data. The network of social contacts is represented as a weighted multilayer network constructed from different channels of telecommunication as well as data on face-to-face contacts. We find that even strongly connected individuals are not more similar with respect to basic personality traits than randomly chosen pairs of individuals. In contrast, several socio-demographics variables have a significant degree of similarity. We further observe that similarity might be present in one layer of the multilayer network and simultaneously be absent in the other layers. For a variable such as gender, our measure reveals a transition from similarity between nodes connected with links of relatively low weight to dis-similarity for the nodes connected by the strongest links. We finally analyze the overlap between layers in the network for different levels of acquaintanceships.

Combined techniques for network measurements at accelerator facilities

International Nuclear Information System (INIS)

Pschorn, I.

1999-01-01

Usually network measurements at GSi (Gesellschaft fur Schwerionen forschung) are carried out by employing the Leica tachymeter TC2002K etc. Due to time constraints and the fact that GSi possesses only one of these selected, high precision total-stations, it was suddenly necessary to think about employing a Laser tracker as the major instrument for a reference network measurement. The idea was to compare the different instruments and to proof if it is possible at all to carry out a precise network measurement using a laser tracker. In the end the SMX Tracker4500 combined with Leica NA3000 for network measurements at GSi, Darmstadt and at BESSY Il, Berlin (both located in Germany) was applied. A few results are shown in the following chapters. A new technology in 3D metrology came up. Some ideas of applying these new tools in the field of accelerator measurements are given. Finally aspects of calibration and checking the performance of the employed high precision instrument are pointed out in this paper. (author)

An Attractor-Based Complexity Measurement for Boolean Recurrent Neural Networks

Science.gov (United States)

Cabessa, Jérémie; Villa, Alessandro E. P.

2014-01-01

We provide a novel refined attractor-based complexity measurement for Boolean recurrent neural networks that represents an assessment of their computational power in terms of the significance of their attractor dynamics. This complexity measurement is achieved by first proving a computational equivalence between Boolean recurrent neural networks and some specific class of -automata, and then translating the most refined classification of -automata to the Boolean neural network context. As a result, a hierarchical classification of Boolean neural networks based on their attractive dynamics is obtained, thus providing a novel refined attractor-based complexity measurement for Boolean recurrent neural networks. These results provide new theoretical insights to the computational and dynamical capabilities of neural networks according to their attractive potentialities. An application of our findings is illustrated by the analysis of the dynamics of a simplified model of the basal ganglia-thalamocortical network simulated by a Boolean recurrent neural network. This example shows the significance of measuring network complexity, and how our results bear new founding elements for the understanding of the complexity of real brain circuits. PMID:24727866

National network of radioactivity measurement in environment

International Nuclear Information System (INIS)

2006-01-01

This document constitutes the report of management for the year 2006 of the national network of measurement of radioactivity in environment, instituted by the article R.1333-11 of the Public Health code. According to the 5. of the decree of 27. june 2005, the Institute of radiation protection and nuclear safety (I.R.S.N.) has for mission to write every year a report of management of the national network of radioactivity measurement in environment. This report has for principal objectives: to do an evaluation on organisation and functioning of the piloting committee; to realize a synthesis on the different tasks lead by the working groups; as well as on the human and financial resources devoted to this project; to debrief on the development project of the national network information system. This report must allow to the network actors, as to the professional people and the public, to understand the functioning of the national network and the process implemented for the development of centralization, management and public diffusion tools, of the radioactivity data in environment. The year 2006 was marked by the opening of an Internet gate of the national network. (N.C.)

Development of a Real-Time Radiological Area Monitoring Network for Emergency Response at Lawrence Livermore National Laboratory

International Nuclear Information System (INIS)

Bertoldo, N; Hunter, S; Fertig, R; Laguna, G; MacQueen, D

2004-01-01

A real-time radiological sensor network for emergency response was developed and deployed at the Lawrence Livermore National Laboratory (LLNL). The Real-Time Radiological Area Monitoring (RTRAM) network is comprised of 16 Geiger-Mueller (GM) sensors positioned on the LLNL Livermore site perimeter to continuously monitor for a radiological condition resulting from a terrorist threat to site security and the health and safety of LLNL personnel. The RTRAM network sensor locations coincide with wind sector directions to provide thorough coverage of the one square mile site. These loW--power sensors are supported by a central command center (CCC) and transmit measurement data back to the CCC computer through the LLNL telecommunications infrastructure. Alarm conditions are identified by comparing current data to predetermined threshold parameters and are validated by comparison with plausible dispersion modeling scenarios and prevailing meteorological conditions. Emergency response personnel are notified of alarm conditions by automatic radio and computer based notifications. A secure intranet provides emergency response personnel with current condition assessment data that enable them to direct field response efforts remotely. The RTRAM network has proven to be a reliable system since initial deployment in August 2001 and maintains stability during inclement weather conditions

Social network analysis of public health programs to measure partnership.

Science.gov (United States)

Schoen, Martin W; Moreland-Russell, Sarah; Prewitt, Kim; Carothers, Bobbi J

2014-12-01

In order to prevent chronic diseases, community-based programs are encouraged to take an ecological approach to public health promotion and involve many diverse partners. Little is known about measuring partnership in implementing public health strategies. We collected data from 23 Missouri communities in early 2012 that received funding from three separate programs to prevent obesity and/or reduce tobacco use. While all of these funding programs encourage partnership, only the Social Innovation for Missouri (SIM) program included a focus on building community capacity and enhancing collaboration. Social network analysis techniques were used to understand contact and collaboration networks in community organizations. Measurements of average degree, density, degree centralization, and betweenness centralization were calculated for each network. Because of the various sizes of the networks, we conducted comparative analyses with and without adjustment for network size. SIM programs had increased measurements of average degree for partner collaboration and larger networks. When controlling for network size, SIM groups had higher measures of network density and lower measures of degree centralization and betweenness centralization. SIM collaboration networks were more dense and less centralized, indicating increased partnership. The methods described in this paper can be used to compare partnership in community networks of various sizes. Further research is necessary to define causal mechanisms of partnership development and their relationship to public health outcomes. Copyright © 2014 Elsevier Ltd. All rights reserved.

Artificial Neural Networks for Nonlinear Dynamic Response Simulation in Mechanical Systems

DEFF Research Database (Denmark)

Christiansen, Niels Hørbye; Høgsberg, Jan Becker; Winther, Ole

2011-01-01

It is shown how artificial neural networks can be trained to predict dynamic response of a simple nonlinear structure. Data generated using a nonlinear finite element model of a simplified wind turbine is used to train a one layer artificial neural network. When trained properly the network is ab...... to perform accurate response prediction much faster than the corresponding finite element model. Initial result indicate a reduction in cpu time by two orders of magnitude....

Transaction costs and social networks in productivity measurement

DEFF Research Database (Denmark)

Henningsen, Geraldine; Henningsen, Arne; Henning, Christian H. C. A.

2015-01-01

. Hence, both the absolute productivity measures and, more importantly, the productivity ranking will be distorted. A major driver of transaction costs is poor access to information and contract enforcement assistance. Social networks often catalyse information exchange as well as generate trust...... and support. Hence, we use measures of a firm’s access to social networks as a proxy for the transaction costs the firm faces. We develop a microeconomic production model that takes into account transaction costs and networks. Using a data set of 384 Polish farms, we empirically estimate this model...... and compare different parametric, semiparametric, and nonparametric model specifications. Our results generally support our hypothesis. Especially, large trading networks and dense household networks have a positive influence on a farm’s productivity. Furthermore, our results indicate that transaction costs...

Multiple Social Networks, Data Models and Measures for

DEFF Research Database (Denmark)

Magnani, Matteo; Rossi, Luca

2017-01-01

Multiple Social Network Analysis is a discipline defining models, measures, methodologies, and algorithms to study multiple social networks together as a single social system. It is particularly valuable when the networks are interconnected, e.g., the same actors are present in more than one...

Energy Consumption Model and Measurement Results for Network Coding-enabled IEEE 802.11 Meshed Wireless Networks

DEFF Research Database (Denmark)

Paramanathan, Achuthan; Rasmussen, Ulrik Wilken; Hundebøll, Martin

2012-01-01

This paper presents an energy model and energy measurements for network coding enabled wireless meshed networks based on IEEE 802.11 technology. The energy model and the energy measurement testbed is limited to a simple Alice and Bob scenario. For this toy scenario we compare the energy usages...... for a system with and without network coding support. While network coding reduces the number of radio transmissions, the operational activity on the devices due to coding will be increased. We derive an analytical model for the energy consumption and compare it to real measurements for which we build...... a flexible, low cost tool to be able to measure at any given node in a meshed network. We verify the precision of our tool by comparing it to a sophisticated device. Our main results in this paper are the derivation of an analytical energy model, the implementation of a distributed energy measurement testbed...

Risk measures on networks and expected utility

International Nuclear Information System (INIS)

Cerqueti, Roy; Lupi, Claudio

2016-01-01

In reliability theory projects are usually evaluated in terms of their riskiness, and often decision under risk is intended as the one-shot-type binary choice of accepting or not accepting the risk. In this paper we elaborate on the concept of risk acceptance, and propose a theoretical framework based on network theory. In doing this, we deal with system reliability, where the interconnections among the random quantities involved in the decision process are explicitly taken into account. Furthermore, we explore the conditions to be satisfied for risk-acceptance criteria to be consistent with the axiomatization of standard expected utility theory within the network framework. In accordance with existing literature, we show that a risk evaluation criterion can be meaningful even if it is not consistent with the standard axiomatization of expected utility, once this is suitably reinterpreted in the light of networks. Finally, we provide some illustrative examples. - Highlights: • We discuss risk acceptance and theoretically develop this theme on the basis of network theory. • We propose an original framework for describing the algebraic structure of the set of the networks, when they are viewed as risks. • We introduce the risk measures on networks, which induce total orders on the set of networks. • We state conditions on the risk measures on networks to let the induced risk-acceptance criterion be consistent with a new formulation of the expected utility theory.

Measurement with Persons: A European Network

NARCIS (Netherlands)

Pendrill, L.R.; Emardson, R.; Berglund, B.; Gröning, M.; Höglund, A.; Cancedda, A.; Quinti, G.; Crenna, F.; Rossi, G.B.; Drnovek, J.; Gersak, G.; Goodman, T.; Harris, S.; Heijden, van der G.W.A.M.; Kallinen, K.; Ravaja, N.

2010-01-01

The European ‘Measuring the Impossible’ Network MINET promotes new research activities in measurement dependent on human perception and/or interpretation. This includes the perceived attributes of products and services, such as quality or desirability, and societal parameters such as security and

Correlated measurement error hampers association network inference

NARCIS (Netherlands)

Kaduk, M.; Hoefsloot, H.C.J.; Vis, D.J.; Reijmers, T.; Greef, J. van der; Smilde, A.K.; Hendriks, M.M.W.B.

2014-01-01

Modern chromatography-based metabolomics measurements generate large amounts of data in the form of abundances of metabolites. An increasingly popular way of representing and analyzing such data is by means of association networks. Ideally, such a network can be interpreted in terms of the

Settings in Social Networks : a Measurement Model

NARCIS (Netherlands)

Schweinberger, Michael; Snijders, Tom A.B.

2003-01-01

A class of statistical models is proposed that aims to recover latent settings structures in social networks. Settings may be regarded as clusters of vertices. The measurement model is based on two assumptions. (1) The observed network is generated by hierarchically nested latent transitive

Spatiotemporal characteristics of retinal response to network-mediated photovoltaic stimulation.

Science.gov (United States)

Ho, Elton; Smith, Richard; Goetz, Georges; Lei, Xin; Galambos, Ludwig; Kamins, Theodore I; Harris, James; Mathieson, Keith; Palanker, Daniel; Sher, Alexander

2018-02-01

Subretinal prostheses aim at restoring sight to patients blinded by photoreceptor degeneration using electrical activation of the surviving inner retinal neurons. Today, such implants deliver visual information with low-frequency stimulation, resulting in discontinuous visual percepts. We measured retinal responses to complex visual stimuli delivered at video rate via a photovoltaic subretinal implant and by visible light. Using a multielectrode array to record from retinal ganglion cells (RGCs) in the healthy and degenerated rat retina ex vivo, we estimated their spatiotemporal properties from the spike-triggered average responses to photovoltaic binary white noise stimulus with 70-μm pixel size at 20-Hz frame rate. The average photovoltaic receptive field size was 194 ± 3 μm (mean ± SE), similar to that of visual responses (221 ± 4 μm), but response latency was significantly shorter with photovoltaic stimulation. Both visual and photovoltaic receptive fields had an opposing center-surround structure. In the healthy retina, ON RGCs had photovoltaic OFF responses, and vice versa. This reversal is consistent with depolarization of photoreceptors by electrical pulses, as opposed to their hyperpolarization under increasing light, although alternative mechanisms cannot be excluded. In degenerate retina, both ON and OFF photovoltaic responses were observed, but in the absence of visual responses, it is not clear what functional RGC types they correspond to. Degenerate retina maintained the antagonistic center-surround organization of receptive fields. These fast and spatially localized network-mediated ON and OFF responses to subretinal stimulation via photovoltaic pixels with local return electrodes raise confidence in the possibility of providing more functional prosthetic vision. NEW & NOTEWORTHY Retinal prostheses currently in clinical use have struggled to deliver visual information at naturalistic frequencies, resulting in discontinuous percepts. We

EIGENVECTOR-BASED CENTRALITY MEASURES FOR TEMPORAL NETWORKS*

Science.gov (United States)

TAYLOR, DANE; MYERS, SEAN A.; CLAUSET, AARON; PORTER, MASON A.; MUCHA, PETER J.

2017-01-01

Numerous centrality measures have been developed to quantify the importances of nodes in time-independent networks, and many of them can be expressed as the leading eigenvector of some matrix. With the increasing availability of network data that changes in time, it is important to extend such eigenvector-based centrality measures to time-dependent networks. In this paper, we introduce a principled generalization of network centrality measures that is valid for any eigenvector-based centrality. We consider a temporal network with N nodes as a sequence of T layers that describe the network during different time windows, and we couple centrality matrices for the layers into a supra-centrality matrix of size NT × NT whose dominant eigenvector gives the centrality of each node i at each time t. We refer to this eigenvector and its components as a joint centrality, as it reflects the importances of both the node i and the time layer t. We also introduce the concepts of marginal and conditional centralities, which facilitate the study of centrality trajectories over time. We find that the strength of coupling between layers is important for determining multiscale properties of centrality, such as localization phenomena and the time scale of centrality changes. In the strong-coupling regime, we derive expressions for time-averaged centralities, which are given by the zeroth-order terms of a singular perturbation expansion. We also study first-order terms to obtain first-order-mover scores, which concisely describe the magnitude of nodes’ centrality changes over time. As examples, we apply our method to three empirical temporal networks: the United States Ph.D. exchange in mathematics, costarring relationships among top-billed actors during the Golden Age of Hollywood, and citations of decisions from the United States Supreme Court. PMID:29046619

Template measurement for plutonium pit based on neural networks

International Nuclear Information System (INIS)

Zhang Changfan; Gong Jian; Liu Suping; Hu Guangchun; Xiang Yongchun

2012-01-01

Template measurement for plutonium pit extracts characteristic data from-ray spectrum and the neutron counts emitted by plutonium. The characteristic data of the suspicious object are compared with data of the declared plutonium pit to verify if they are of the same type. In this paper, neural networks are enhanced as the comparison algorithm for template measurement of plutonium pit. Two kinds of neural networks are created, i.e. the BP and LVQ neural networks. They are applied in different aspects for the template measurement and identification. BP neural network is used for classification for different types of plutonium pits, which is often used for management of nuclear materials. LVQ neural network is used for comparison of inspected objects to the declared one, which is usually applied in the field of nuclear disarmament and verification. (authors)

Artificial Neural Network-Based Early-Age Concrete Strength Monitoring Using Dynamic Response Signals.

Science.gov (United States)

Kim, Junkyeong; Lee, Chaggil; Park, Seunghee

2017-06-07

Concrete is one of the most common materials used to construct a variety of civil infrastructures. However, since concrete might be susceptible to brittle fracture, it is essential to confirm the strength of concrete at the early-age stage of the curing process to prevent unexpected collapse. To address this issue, this study proposes a novel method to estimate the early-age strength of concrete, by integrating an artificial neural network algorithm with a dynamic response measurement of the concrete material. The dynamic response signals of the concrete, including both electromechanical impedances and guided ultrasonic waves, are obtained from an embedded piezoelectric sensor module. The cross-correlation coefficient of the electromechanical impedance signals and the amplitude of the guided ultrasonic wave signals are selected to quantify the variation in dynamic responses according to the strength of the concrete. Furthermore, an artificial neural network algorithm is used to verify a relationship between the variation in dynamic response signals and concrete strength. The results of an experimental study confirm that the proposed approach can be effectively applied to estimate the strength of concrete material from the early-age stage of the curing process.

Simulation of Stimuli-Responsive Polymer Networks

Directory of Open Access Journals (Sweden)

Thomas Gruhn

2013-11-01

Full Text Available The structure and material properties of polymer networks can depend sensitively on changes in the environment. There is a great deal of progress in the development of stimuli-responsive hydrogels for applications like sensors, self-repairing materials or actuators. Biocompatible, smart hydrogels can be used for applications, such as controlled drug delivery and release, or for artificial muscles. Numerical studies have been performed on different length scales and levels of details. Macroscopic theories that describe the network systems with the help of continuous fields are suited to study effects like the stimuli-induced deformation of hydrogels on large scales. In this article, we discuss various macroscopic approaches and describe, in more detail, our phase field model, which allows the calculation of the hydrogel dynamics with the help of a free energy that considers physical and chemical impacts. On a mesoscopic level, polymer systems can be modeled with the help of the self-consistent field theory, which includes the interactions, connectivity, and the entropy of the polymer chains, and does not depend on constitutive equations. We present our recent extension of the method that allows the study of the formation of nano domains in reversibly crosslinked block copolymer networks. Molecular simulations of polymer networks allow the investigation of the behavior of specific systems on a microscopic scale. As an example for microscopic modeling of stimuli sensitive polymer networks, we present our Monte Carlo simulations of a filament network system with crosslinkers.

Time response prediction of Brazilian Nuclear Power Plant temperature sensors using neural networks

Energy Technology Data Exchange (ETDEWEB)

Santos, Roberto Carlos dos; Pereira, Iraci Martinez, E-mail: rcsantos@ipen.br [Instituto de Pesquisas Energeticas e Nucleares (IPEN/CNEN-SP), Sao Paulo, SP (Brazil)

2011-07-01

This work presents the results of the time constants values predicted from ANN using Angra I Brazilian nuclear power plant data. The signals obtained from LCSR loop current step response test sensors installed in the process presents noise end fluctuations that are inherent of operational conditions. Angra I nuclear power plant has 20 RTDs as part of the protection reactor system. The results were compared with those obtained from traditional way. Primary coolant RTDs (Resistance Temperature Detector) typically feed the plant's control and safety systems and must, therefore, be very accurate and have good dynamic performance. An in-situ test method called LCSR - loop current step response test was developed to measure remotely the response time of RTDs. In the LCSR method, the response time of the sensor is identified by means of the LCSR transformation that involves the dynamic response modal time constants determination using a nodal heat transfer model. For this reason, this calculation is not simple and requires specialized personnel. This work combines the two methodologies, Plunge test and LCSR test, using neural networks. With the use of neural networks it will not be necessary to use the LCSR transformation to determine sensor's time constant and this leads to more robust results. (author)

Time response prediction of Brazilian Nuclear Power Plant temperature sensors using neural networks

International Nuclear Information System (INIS)

Santos, Roberto Carlos dos; Pereira, Iraci Martinez

2011-01-01

This work presents the results of the time constants values predicted from ANN using Angra I Brazilian nuclear power plant data. The signals obtained from LCSR loop current step response test sensors installed in the process presents noise end fluctuations that are inherent of operational conditions. Angra I nuclear power plant has 20 RTDs as part of the protection reactor system. The results were compared with those obtained from traditional way. Primary coolant RTDs (Resistance Temperature Detector) typically feed the plant's control and safety systems and must, therefore, be very accurate and have good dynamic performance. An in-situ test method called LCSR - loop current step response test was developed to measure remotely the response time of RTDs. In the LCSR method, the response time of the sensor is identified by means of the LCSR transformation that involves the dynamic response modal time constants determination using a nodal heat transfer model. For this reason, this calculation is not simple and requires specialized personnel. This work combines the two methodologies, Plunge test and LCSR test, using neural networks. With the use of neural networks it will not be necessary to use the LCSR transformation to determine sensor's time constant and this leads to more robust results. (author)

Cooperative adaptive responses in gene regulatory networks with many degrees of freedom.

Science.gov (United States)

Inoue, Masayo; Kaneko, Kunihiko

2013-04-01

Cells generally adapt to environmental changes by first exhibiting an immediate response and then gradually returning to their original state to achieve homeostasis. Although simple network motifs consisting of a few genes have been shown to exhibit such adaptive dynamics, they do not reflect the complexity of real cells, where the expression of a large number of genes activates or represses other genes, permitting adaptive behaviors. Here, we investigated the responses of gene regulatory networks containing many genes that have undergone numerical evolution to achieve high fitness due to the adaptive response of only a single target gene; this single target gene responds to changes in external inputs and later returns to basal levels. Despite setting a single target, most genes showed adaptive responses after evolution. Such adaptive dynamics were not due to common motifs within a few genes; even without such motifs, almost all genes showed adaptation, albeit sometimes partial adaptation, in the sense that expression levels did not always return to original levels. The genes split into two groups: genes in the first group exhibited an initial increase in expression and then returned to basal levels, while genes in the second group exhibited the opposite changes in expression. From this model, genes in the first group received positive input from other genes within the first group, but negative input from genes in the second group, and vice versa. Thus, the adaptation dynamics of genes from both groups were consolidated. This cooperative adaptive behavior was commonly observed if the number of genes involved was larger than the order of ten. These results have implications in the collective responses of gene expression networks in microarray measurements of yeast Saccharomyces cerevisiae and the significance to the biological homeostasis of systems with many components.

Integration of metabolic and gene regulatory networks modulates the C. elegans dietary response.

Science.gov (United States)

Watson, Emma; MacNeil, Lesley T; Arda, H Efsun; Zhu, Lihua Julie; Walhout, Albertha J M

2013-03-28

Expression profiles are tailored according to dietary input. However, the networks that control dietary responses remain largely uncharacterized. Here, we combine forward and reverse genetic screens to delineate a network of 184 genes that affect the C. elegans dietary response to Comamonas DA1877 bacteria. We find that perturbation of a mitochondrial network composed of enzymes involved in amino acid metabolism and the TCA cycle affects the dietary response. In humans, mutations in the corresponding genes cause inborn diseases of amino acid metabolism, most of which are treated by dietary intervention. We identify several transcription factors (TFs) that mediate the changes in gene expression upon metabolic network perturbations. Altogether, our findings unveil a transcriptional response system that is poised to sense dietary cues and metabolic imbalances, illustrating extensive communication between metabolic networks in the mitochondria and gene regulatory networks in the nucleus. Copyright © 2013 Elsevier Inc. All rights reserved.

Processing horizontal networks measured by integrated terrestrial and GPS technologies

Directory of Open Access Journals (Sweden)

Vincent Jakub

2003-09-01

Full Text Available Local horizontal networks in which GPS and terrestrial measurements (TER are done are often established at present. Iin other networks, the previous terrestrial measurements can be completed with quantities from contemporary GPS observations (tunnel nets, mining nets with surface and underground parts and other long-shaped nets.The processing of such heterobeneous (GPS, TER networks whose terrestrial measurements are performed as point coordinate measurements (∆X, ∆Y using (geodetic total stationIn is presented in this paper. In such network structures it is then available:- the values ∆X, ∆Y from TER observations which are transformed in the plane of S-JTSK for adjustement,- the values ∆X, ∆Y in the plane S-JTSK that can be obtained by 3D transformation of WGS84 netpoint coordinates from GPS observations to corresponding coordinates S-JTSK.For common adjusting all the ∆X, ∆Y, some elements of the network geometry (e.g. distances should be measured by both methods (GPS, TER. This approach makes possible an effective homogenisation of both network parts what is equivalent to saying that an expressive influence reduction on local frame realizations of S-JTSK in the whole network can be made.Results of network processing obtained in proposed manner are acceptable in general and they are equivalent (accuracy, reliability to results of another processing methods.

Displacement and deformation measurement for large structures by camera network

Science.gov (United States)

Shang, Yang; Yu, Qifeng; Yang, Zhen; Xu, Zhiqiang; Zhang, Xiaohu

2014-03-01

A displacement and deformation measurement method for large structures by a series-parallel connection camera network is presented. By taking the dynamic monitoring of a large-scale crane in lifting operation as an example, a series-parallel connection camera network is designed, and the displacement and deformation measurement method by using this series-parallel connection camera network is studied. The movement range of the crane body is small, and that of the crane arm is large. The displacement of the crane body, the displacement of the crane arm relative to the body and the deformation of the arm are measured. Compared with a pure series or parallel connection camera network, the designed series-parallel connection camera network can be used to measure not only the movement and displacement of a large structure but also the relative movement and deformation of some interesting parts of the large structure by a relatively simple optical measurement system.

Development of visible-light responsive and mechanically enhanced "smart" UCST interpenetrating network hydrogels.

Science.gov (United States)

Xu, Yifei; Ghag, Onkar; Reimann, Morgan; Sitterle, Philip; Chatterjee, Prithwish; Nofen, Elizabeth; Yu, Hongyu; Jiang, Hanqing; Dai, Lenore L

2017-12-20

An interpenetrating polymer network (IPN), chlorophyllin-incorporated environmentally responsive hydrogel was synthesized and exhibited the following features: enhanced mechanical properties, upper critical solution temperature (UCST) swelling behavior, and promising visible-light responsiveness. Poor mechanical properties are known challenges for hydrogel-based materials. By forming an interpenetrating network between polyacrylamide (PAAm) and poly(acrylic acid) (PAAc) polymer networks, the mechanical properties of the synthesized IPN hydrogels were significantly improved compared to hydrogels made of a single network of each polymer. The formation of the interpenetrating network was confirmed by Fourier Transform Infrared Spectroscopy (FTIR), the analysis of glass transition temperature, and a unique UCST responsive swelling behavior, which is in contrast to the more prevalent lower critical solution temperature (LCST) behaviour of environmentally responsive hydrogels. The visible-light responsiveness of the synthesized hydrogel also demonstrated a positive swelling behavior, and the effect of incorporating chlorophyllin as the chromophore unit was observed to reduce the average pore size and further enhance the mechanical properties of the hydrogel. This interpenetrating network system shows potential to serve as a new route in developing "smart" hydrogels using visible-light as a simple, inexpensive, and remotely controllable stimulus.

The Strategic Impact of Corporate Responsibility and Criminal Networks on Value Co-Creation

Directory of Open Access Journals (Sweden)

Peter Zettinig

2011-02-01

Full Text Available This article is motivated by the increasing concern about the ever-declining security of pharmaceutical products due to the abundance of counterfeit network actors. We argue that if networks are effective mechanisms for criminal organizations to infiltrate into any value chain, then networks should also work for responsible businesses in their quests to counter this phenomenon of value destruction, which is ultimately detrimental to the value co-creation process. Thus, this article demonstrates a nuanced understanding of the strategic impact of corporate responsibility of actors in networks on value co-creation. The current discourse on value co-creation in business networks is structured in such a way that it precludes its inherent corporate responsibility component even though they are not mutually exclusive. Moreover, research on value co-creation aimed at the proactive and responsible defence of a network substance via value co-protection has been mostly scant. We propose a model of value-optimization through value co-protection and ethical responsibility. This way of theorizing has several implications for both policy making and managerial decision making in the pharmaceutical industry and beyond.

5-HTTLPR differentially predicts brain network responses to emotional faces

DEFF Research Database (Denmark)

Fisher, Patrick M; Grady, Cheryl L; Madsen, Martin K

2015-01-01

The effects of the 5-HTTLPR polymorphism on neural responses to emotionally salient faces have been studied extensively, focusing on amygdala reactivity and amygdala-prefrontal interactions. Despite compelling evidence that emotional face paradigms engage a distributed network of brain regions...... to fearful faces was significantly greater in S' carriers compared to LA LA individuals. These findings provide novel evidence for emotion-specific 5-HTTLPR effects on the response of a distributed set of brain regions including areas responsive to emotionally salient stimuli and critical components...... involved in emotion, cognitive and visual processing, less is known about 5-HTTLPR effects on broader network responses. To address this, we evaluated 5-HTTLPR differences in the whole-brain response to an emotional faces paradigm including neutral, angry and fearful faces using functional magnetic...

MicroRNA-mediated networks underlie immune response regulation in papillary thyroid carcinoma

Science.gov (United States)

Huang, Chen-Tsung; Oyang, Yen-Jen; Huang, Hsuan-Cheng; Juan, Hsueh-Fen

2014-09-01

Papillary thyroid carcinoma (PTC) is a common endocrine malignancy with low death rate but increased incidence and recurrence in recent years. MicroRNAs (miRNAs) are small non-coding RNAs with diverse regulatory capacities in eukaryotes and have been frequently implied in human cancer. Despite current progress, however, a panoramic overview concerning miRNA regulatory networks in PTC is still lacking. Here, we analyzed the expression datasets of PTC from The Cancer Genome Atlas (TCGA) Data Portal and demonstrate for the first time that immune responses are significantly enriched and under specific regulation in the direct miRNA-target network among distinctive PTC variants to different extents. Additionally, considering the unconventional properties of miRNAs, we explore the protein-coding competing endogenous RNA (ceRNA) and the modulatory networks in PTC and unexpectedly disclose concerted regulation of immune responses from these networks. Interestingly, miRNAs from these conventional and unconventional networks share general similarities and differences but tend to be disparate as regulatory activities increase, coordinately tuning the immune responses that in part account for PTC tumor biology. Together, our systematic results uncover the intensive regulation of immune responses underlain by miRNA-mediated networks in PTC, opening up new avenues in the management of thyroid cancer.

Transaction costs and social networks in productivity measurement

DEFF Research Database (Denmark)

Henningsen, Geraldine; Henningsen, Arne; Henning, Christian H. C. A.

2015-01-01

and support. Hence, we use measures of a firm’s access to social networks as a proxy for the transaction costs the firm faces. We develop a microeconomic production model that takes into account transaction costs and networks. Using a data set of 384 Polish farms, we empirically estimate this model......We argue that in the presence of transaction costs, observed productivity measures may in many cases understate the true productivity, as production data seldom distinguish between resources entering the production process and resources of a similar type that are sacrificed for transaction costs....... Hence, both the absolute productivity measures and, more importantly, the productivity ranking will be distorted. A major driver of transaction costs is poor access to information and contract enforcement assistance. Social networks often catalyse information exchange as well as generate trust...

Flow-based vulnerability measures for network component importance: Experimentation with preparedness planning

International Nuclear Information System (INIS)

Nicholson, Charles D.; Barker, Kash; Ramirez-Marquez, Jose E.

2016-01-01

This work develops and compares several flow-based vulnerability measures to prioritize important network edges for the implementation of preparedness options. These network vulnerability measures quantify different characteristics and perspectives on enabling maximum flow, creating bottlenecks, and partitioning into cutsets, among others. The efficacy of these vulnerability measures to motivate preparedness options against experimental geographically located disruption simulations is measured. Results suggest that a weighted flow capacity rate, which accounts for both (i) the contribution of an edge to maximum network flow and (ii) the extent to which the edge is a bottleneck in the network, shows most promise across four instances of varying network sizes and densities. - Highlights: • We develop new flow-based measures of network vulnerability. • We apply these measures to determine the importance of edges after disruptions. • Networks of varying size and density are explored.

Time Synchronized Wireless Sensor Network for Vibration Measurement

Science.gov (United States)

Uchimura, Yutaka; Nasu, Tadashi; Takahashi, Motoichi

Network based wireless sensing has become an important area of research and various new applications for remote sensing are expected to emerge. One of the promising applications is structural health monitoring of building or civil engineering structure and it often requires vibration measurement. For the vibration measurement via wireless network, time synchronization is indispensable. In this paper, we introduce a newly developed time synchronized wireless sensor network system. The system employs IEEE 802.11 standard based TSF counter and sends the measured data with the counter value. TSF based synchronization enables consistency on common clock among different wireless nodes. We consider the scale effect on the synchronization accuracy and the effect is evaluated by stochastic analysis and simulation studies. A new wireless sensing system is developed and the hardware and software specifications are shown. The experiments are conducted in a reinforced concrete building and results show good performance enough for vibration measurement purpose.

Reverse engineering biological networks :applications in immune responses to bio-toxins.

Energy Technology Data Exchange (ETDEWEB)

Martino, Anthony A.; Sinclair, Michael B.; Davidson, George S.; Haaland, David Michael; Timlin, Jerilyn Ann; Thomas, Edward Victor; Slepoy, Alexander; Zhang, Zhaoduo; May, Elebeoba Eni; Martin, Shawn Bryan; Faulon, Jean-Loup Michel

2005-12-01

Our aim is to determine the network of events, or the regulatory network, that defines an immune response to a bio-toxin. As a model system, we are studying T cell regulatory network triggered through tyrosine kinase receptor activation using a combination of pathway stimulation and time-series microarray experiments. Our approach is composed of five steps (1) microarray experiments and data error analysis, (2) data clustering, (3) data smoothing and discretization, (4) network reverse engineering, and (5) network dynamics analysis and fingerprint identification. The technological outcome of this study is a suite of experimental protocols and computational tools that reverse engineer regulatory networks provided gene expression data. The practical biological outcome of this work is an immune response fingerprint in terms of gene expression levels. Inferring regulatory networks from microarray data is a new field of investigation that is no more than five years old. To the best of our knowledge, this work is the first attempt that integrates experiments, error analyses, data clustering, inference, and network analysis to solve a practical problem. Our systematic approach of counting, enumeration, and sampling networks matching experimental data is new to the field of network reverse engineering. The resulting mathematical analyses and computational tools lead to new results on their own and should be useful to others who analyze and infer networks.

Construction and comparison of gene co-expression networks shows complex plant immune responses

Directory of Open Access Journals (Sweden)

Luis Guillermo Leal

2014-10-01

Full Text Available Gene co-expression networks (GCNs are graphic representations that depict the coordinated transcription of genes in response to certain stimuli. GCNs provide functional annotations of genes whose function is unknown and are further used in studies of translational functional genomics among species. In this work, a methodology for the reconstruction and comparison of GCNs is presented. This approach was applied using gene expression data that were obtained from immunity experiments in Arabidopsis thaliana, rice, soybean, tomato and cassava. After the evaluation of diverse similarity metrics for the GCN reconstruction, we recommended the mutual information coefficient measurement and a clustering coefficient-based method for similarity threshold selection. To compare GCNs, we proposed a multivariate approach based on the Principal Component Analysis (PCA. Branches of plant immunity that were exemplified by each experiment were analyzed in conjunction with the PCA results, suggesting both the robustness and the dynamic nature of the cellular responses. The dynamic of molecular plant responses produced networks with different characteristics that are differentiable using our methodology. The comparison of GCNs from plant pathosystems, showed that in response to similar pathogens plants could activate conserved signaling pathways. The results confirmed that the closeness of GCNs projected on the principal component space is an indicative of similarity among GCNs. This also can be used to understand global patterns of events triggered during plant immune responses.

Dissociation of rapid response learning and facilitation in perceptual and conceptual networks of person recognition.

Science.gov (United States)

Valt, Christian; Klein, Christoph; Boehm, Stephan G

2015-08-01

Repetition priming is a prominent example of non-declarative memory, and it increases the accuracy and speed of responses to repeatedly processed stimuli. Major long-hold memory theories posit that repetition priming results from facilitation within perceptual and conceptual networks for stimulus recognition and categorization. Stimuli can also be bound to particular responses, and it has recently been suggested that this rapid response learning, not network facilitation, provides a sound theory of priming of object recognition. Here, we addressed the relevance of network facilitation and rapid response learning for priming of person recognition with a view to advance general theories of priming. In four experiments, participants performed conceptual decisions like occupation or nationality judgments for famous faces. The magnitude of rapid response learning varied across experiments, and rapid response learning co-occurred and interacted with facilitation in perceptual and conceptual networks. These findings indicate that rapid response learning and facilitation in perceptual and conceptual networks are complementary rather than competing theories of priming. Thus, future memory theories need to incorporate both rapid response learning and network facilitation as individual facets of priming. © 2014 The British Psychological Society.

Traffic measurement for big network data

CERN Document Server

Chen, Shigang; Xiao, Qingjun

2017-01-01

This book presents several compact and fast methods for online traffic measurement of big network data. It describes challenges of online traffic measurement, discusses the state of the field, and provides an overview of the potential solutions to major problems. The authors introduce the problem of per-flow size measurement for big network data and present a fast and scalable counter architecture, called Counter Tree, which leverages a two-dimensional counter sharing scheme to achieve far better memory efficiency and significantly extend estimation range. Unlike traditional approaches to cardinality estimation problems that allocate a separated data structure (called estimator) for each flow, this book takes a different design path by viewing all the flows together as a whole: each flow is allocated with a virtual estimator, and these virtual estimators share a common memory space. A framework of virtual estimators is designed to apply the idea of sharing to an array of cardinality estimation solutions, achi...

Demand Response in Low Voltage Distribution Networks with High PV Penetration

DEFF Research Database (Denmark)

Nainar, Karthikeyan; Pokhrel, Basanta Raj; Pillai, Jayakrishnan Radhakrishna

2017-01-01

the required flexibility from the electricity market through an aggregator. The optimum demand response enables consumption of maximum renewable energy within the network constraints. Simulation studies are conducted using Matlab and DigSilent Power factory software on a Danish low-voltage distribution system......In this paper, application of demand response to accommodate maximum PV power in a low-voltage distribution network is discussed. A centralized control based on model predictive control method is proposed for the computation of optimal demand response on an hourly basis. The proposed method uses PV...

Active self-testing noise measurement sensors for large-scale environmental sensor networks.

Science.gov (United States)

Domínguez, Federico; Cuong, Nguyen The; Reinoso, Felipe; Touhafi, Abdellah; Steenhaut, Kris

2013-12-13

Large-scale noise pollution sensor networks consist of hundreds of spatially distributed microphones that measure environmental noise. These networks provide historical and real-time environmental data to citizens and decision makers and are therefore a key technology to steer environmental policy. However, the high cost of certified environmental microphone sensors render large-scale environmental networks prohibitively expensive. Several environmental network projects have started using off-the-shelf low-cost microphone sensors to reduce their costs, but these sensors have higher failure rates and produce lower quality data. To offset this disadvantage, we developed a low-cost noise sensor that actively checks its condition and indirectly the integrity of the data it produces. The main design concept is to embed a 13 mm speaker in the noise sensor casing and, by regularly scheduling a frequency sweep, estimate the evolution of the microphone's frequency response over time. This paper presents our noise sensor's hardware and software design together with the results of a test deployment in a large-scale environmental network in Belgium. Our middle-range-value sensor (around €50) effectively detected all experienced malfunctions, in laboratory tests and outdoor deployments, with a few false positives. Future improvements could further lower the cost of our sensor below €10.

Centrality measures and thermodynamic formalism for complex networks.

Science.gov (United States)

Delvenne, Jean-Charles; Libert, Anne-Sophie

2011-04-01

In the study of small and large networks it is customary to perform a simple random walk where the random walker jumps from one node to one of its neighbors with uniform probability. The properties of this random walk are intimately related to the combinatorial properties of the network. In this paper we propose to use the Ruelle-Bowens random walk instead, whose probability transitions are chosen in order to maximize the entropy rate of the walk on an unweighted graph. If the graph is weighted, then a free energy is optimized instead of the entropy rate. Specifically, we introduce a centrality measure for large networks, which is the stationary distribution attained by the Ruelle-Bowens random walk; we name it entropy rank. We introduce a more general version, which is able to deal with disconnected networks, under the name of free-energy rank. We compare the properties of those centrality measures with the classic PageRank and hyperlink-induced topic search (HITS) on both toy and real-life examples, in particular their robustness to small modifications of the network. We show that our centrality measures are more discriminating than PageRank, since they are able to distinguish clearly pages that PageRank regards as almost equally interesting, and are more sensitive to the medium-scale details of the graph.

Integration of white matter network is associated with interindividual differences in psychologically mediated placebo response in migraine patients.

Science.gov (United States)

Liu, Jixin; Ma, Shaohui; Mu, Junya; Chen, Tao; Xu, Qing; Dun, Wanghuan; Tian, Jie; Zhang, Ming

2017-10-01

Individual differences of brain changes of neural communication and integration in the modular architecture of the human brain network exist for the repeated migraine attack and physical or psychological stressors. However, whether the interindividual variability in the migraine brain connectome predicts placebo response to placebo treatment is still unclear. Using DTI and graph theory approaches, we systematically investigated the topological organization of white matter networks in 71 patients with migraine without aura (MO) and 50 matched healthy controls at three levels: global network measure, nodal efficiency, and nodal intramodule/intermodule efficiency. All patients participated in an 8-week sham acupuncture treatment to induce analgesia. In our results, 30% (n = 21) of patients had 50% change in migraine days from baseline after placebo treatment. At baseline, abnormal increased network integration was found in MO patients as compared with the HC group, and the increased global efficiency before starting clinical treatment was associated with their following placebo response. For nodal efficiency, significantly increased within-subnetwork nodal efficiency and intersubnetwork connectivity of the hippocampus and middle frontal gyrus in patients' white matter network were correlated with the responses of follow-up placebo treatment. Our findings suggested that the trait-like individual differences in pain-related maladaptive stress interfered with and diminished the capacity of chronic pain modulation differently, and the placebo response for treatment could be predicted from a prior white matter network modular structure in migraineurs. Hum Brain Mapp 38:5250-5259, 2017. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

The impact of measurement errors in the identification of regulatory networks

Directory of Open Access Journals (Sweden)

Sato João R

2009-12-01

Full Text Available Abstract Background There are several studies in the literature depicting measurement error in gene expression data and also, several others about regulatory network models. However, only a little fraction describes a combination of measurement error in mathematical regulatory networks and shows how to identify these networks under different rates of noise. Results This article investigates the effects of measurement error on the estimation of the parameters in regulatory networks. Simulation studies indicate that, in both time series (dependent and non-time series (independent data, the measurement error strongly affects the estimated parameters of the regulatory network models, biasing them as predicted by the theory. Moreover, when testing the parameters of the regulatory network models, p-values computed by ignoring the measurement error are not reliable, since the rate of false positives are not controlled under the null hypothesis. In order to overcome these problems, we present an improved version of the Ordinary Least Square estimator in independent (regression models and dependent (autoregressive models data when the variables are subject to noises. Moreover, measurement error estimation procedures for microarrays are also described. Simulation results also show that both corrected methods perform better than the standard ones (i.e., ignoring measurement error. The proposed methodologies are illustrated using microarray data from lung cancer patients and mouse liver time series data. Conclusions Measurement error dangerously affects the identification of regulatory network models, thus, they must be reduced or taken into account in order to avoid erroneous conclusions. This could be one of the reasons for high biological false positive rates identified in actual regulatory network models.

Tariffing of energy measured consumers in the distribution network

International Nuclear Information System (INIS)

2006-01-01

Criteria for socio-economic effective tariffing of energy-measured clients in the distribution network are discussed (i.e. households, leisure homes and smaller business clients), this means consumers that do not have hourly measurements or effect measurements. The tariffs should be based on variable segments that reflect short-term marginal costs in the network (in practice loss of transfer) and fixed segments that to the least extent possible influence the consumers' decisions in the choice of energy solutions, both in short term and long term. High-priced energy segments and effect based fixed segments may give unfortunate socio-economic price signals compared to the marginal long-term network costs. A fixed segment per measurement unit is in principle completely neutral, but it is to some extent vulnerable to strategic adjustments if the consumers choose collective measurement. This is not necessarily a big problem in practice (author)

A Step towards Developing a Sustainability Performance Measure within Industrial Networks

Directory of Open Access Journals (Sweden)

Samaneh Shokravi

2014-04-01

Full Text Available Despite the plethora of literature in sustainability and supply chain management in the recent years, a quantitative tool that measures the sustainability performance of an industrial supply network, considering the uncertainties of existing data, is hard to find. This conceptual paper is aimed at establishing a quantitative measure for the sustainability performance of industrial supply networks that considers aleatory and epistemic uncertainties in its environmental performance evaluation. The measure is built upon economic, environmental and social performance evaluation models. These models address a number of shortcomings in the literature, such as incomplete and inaccurate calculation of environmental impacts, as well as the disregard for aleatory and epistemic uncertainties in the input data and, more importantly, the scarce number of quantitative social sustainability measures. Dyadic interactions are chosen for the network, while the network members have a revenue-sharing relationship. This relationship promotes sharing of the required information for the use of the proposed model. This measure provides an approach to quantify the environmental, social and economic sustainability performances of a supply network. Moreover, as this measure is not specifically designed for an industrial sector, it can be employed over an evolving and diverse industrial network.

Harmonization of European Laboratory Response networks by implementing CWA 15793: Use of a gap analysis and an "insider" exercise as tools

NARCIS (Netherlands)

Sundqvist, B.; Allard Bengtsson, U.; Wisselink, H.J.; Peeters, B.P.H.; Rotterdam, van B.; Kampert, E.; Bereczky, S.; Olsson, N.G.J.; Szekely Björndal, A.; Zini, S.; Allix, S.; Knutsson, R.

2013-01-01

Laboratory response networks (LRNs) have been established for security reasons in several countries including the Netherlands, France, and Sweden. LRNs function in these countries as a preparedness measure for a coordinated diagnostic response capability in case of a bioterrorism incident or other

Testing the Feasibility of a Low-Cost Network Performance Measurement Infrastructure

Energy Technology Data Exchange (ETDEWEB)

Chevalier, Scott [Indiana Univ., Bloomington, IN (United States). International Networks; Schopf, Jennifer M. [Indiana Univ., Bloomington, IN (United States). International Networks; Miller, Kenneth [Pennsylvania State Univ., University Park, PA (United States). Telecommunications and Networking Services; Zurawski, Jason [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Energy Sciences Network

2016-07-01

Todays science collaborations depend on reliable, high performance networks, but monitoring the end-to-end performance of a network can be costly and difficult. The most accurate approaches involve using measurement equipment in many locations, which can be both expensive and difficult to manage due to immobile or complicated assets. The perfSONAR framework facilitates network measurement making management of the tests more reasonable. Traditional deployments have used over-provisioned servers, which can be expensive to deploy and maintain. As scientific network uses proliferate, there is a desire to instrument more facets of a network to better understand trends. This work explores low cost alternatives to assist with network measurement. Benefits include the ability to deploy more resources quickly, and reduced capital and operating expenditures. Finally, we present candidate platforms and a testing scenario that evaluated the relative merits of four types of small form factor equipment to deliver accurate performance measurements.

Signalling network construction for modelling plant defence response.

Directory of Open Access Journals (Sweden)

Dragana Miljkovic

Full Text Available Plant defence signalling response against various pathogens, including viruses, is a complex phenomenon. In resistant interaction a plant cell perceives the pathogen signal, transduces it within the cell and performs a reprogramming of the cell metabolism leading to the pathogen replication arrest. This work focuses on signalling pathways crucial for the plant defence response, i.e., the salicylic acid, jasmonic acid and ethylene signal transduction pathways, in the Arabidopsis thaliana model plant. The initial signalling network topology was constructed manually by defining the representation formalism, encoding the information from public databases and literature, and composing a pathway diagram. The manually constructed network structure consists of 175 components and 387 reactions. In order to complement the network topology with possibly missing relations, a new approach to automated information extraction from biological literature was developed. This approach, named Bio3graph, allows for automated extraction of biological relations from the literature, resulting in a set of (component1, reaction, component2 triplets and composing a graph structure which can be visualised, compared to the manually constructed topology and examined by the experts. Using a plant defence response vocabulary of components and reaction types, Bio3graph was applied to a set of 9,586 relevant full text articles, resulting in 137 newly detected reactions between the components. Finally, the manually constructed topology and the new reactions were merged to form a network structure consisting of 175 components and 524 reactions. The resulting pathway diagram of plant defence signalling represents a valuable source for further computational modelling and interpretation of omics data. The developed Bio3graph approach, implemented as an executable language processing and graph visualisation workflow, is publically available at http://ropot.ijs.si/bio3graph/and can be

Responses to olfactory signals reflect network structure of flower-visitor interactions.

Science.gov (United States)

Junker, Robert R; Höcherl, Nicole; Blüthgen, Nico

2010-07-01

1. Network analyses provide insights into the diversity and complexity of ecological interactions and have motivated conclusions about community stability and co-evolution. However, biological traits and mechanisms such as chemical signals regulating the interactions between individual species--the microstructure of a network--are poorly understood. 2. We linked the responses of receivers (flower visitors) towards signals (flower scent) to the structure of a highly diverse natural flower-insect network. For each interaction, we define link temperature--a newly developed metric--as the deviation of the observed interaction strength from neutrality, assuming that animals randomly interact with flowers. 3. Link temperature was positively correlated to the specific visitors' responses to floral scents, experimentally examined in a mobile olfactometer. Thus, communication between plants and consumers via phytochemical signals reflects a significant part of the microstructure in a complex network. Negative as well as positive responses towards floral scents contributed to these results, where individual experience was important apart from innate behaviour. 4. Our results indicate that: (1) biological mechanisms have a profound impact on the microstructure of complex networks that underlies the outcome of aggregate statistics, and (2) floral scents act as a filter, promoting the visitation of some flower visitors, but also inhibiting the visitation of others.

IAEA Response and Assistance Network. Date Effective: 1 September 2013

International Nuclear Information System (INIS)

2013-01-01

The Parties to the Convention on Assistance in the Case of a Nuclear Accident or Radiological Emergency (the 'Assistance Convention') have undertaken to cooperate between themselves and with the IAEA to facilitate the timely provision of assistance in the case of a nuclear accident or radiological emergency, in order to mitigate its consequences. In September 2000, the General Conference of the IAEA, in resolution GC(44)/RES/16, encouraged Member States ''to implement instruments for improving their response, in particular their contribution to international response, to nuclear and radiological emergencies'' as well as ''to participate actively in the process of strengthening international, national and regional capabilities for responding to nuclear and radiological emergencies and to make those capabilities more consistent and coherent''. As part of the IAEA's strategy for supporting the practical implementation of the Assistance Convention, in 2000 the IAEA Secretariat established a global Emergency Response Network (ERNET) of teams suitably qualified to respond to nuclear or radiological emergencies rapidly and, in principle, on a regional basis. The IAEA Secretariat published IAEA Emergency Response Network - ERNET (EPR-ERNET) in 2000, which set out the criteria and requirements to be met by members of the network. An updated edition was published in 2002. The Second Meeting of the Representatives of Competent Authorities Identified under the Convention on Early Notification of a Nuclear Accident and the Convention on Assistance in the Case of a Nuclear Accident or Radiological Emergency, held in Vienna in June 2003, recommended that the IAEA Secretariat convene a Technical Meeting to formulate recommendations aimed at improving participation in the network. Participants in a Technical Meeting held in March 2004 developed a new concept for the network and a completely new draft of the publication. In July 2005, the Third Meeting of Competent Authorities

Effects of the network structure and coupling strength on the noise-induced response delay of a neuronal network

International Nuclear Information System (INIS)

Ozer, Mahmut; Uzuntarla, Muhammet

2008-01-01

The Hodgkin-Huxley (H-H) neuron model driven by stimuli just above threshold shows a noise-induced response delay with respect to time to the first spike for a certain range of noise strengths, an effect called 'noise delayed decay' (NDD). We study the response time of a network of coupled H-H neurons, and investigate how the NDD can be affected by the connection topology of the network and the coupling strength. We show that the NDD effect exists for weak and intermediate coupling strengths, whereas it disappears for strong coupling strength regardless of the connection topology. We also show that although the network structure has very little effect on the NDD for a weak coupling strength, the network structure plays a key role for an intermediate coupling strength by decreasing the NDD effect with the increasing number of random shortcuts, and thus provides an additional operating regime, that is absent in the regular network, in which the neurons may also exploit a spike time code

Measuring structural similarity in large online networks.

Science.gov (United States)

Shi, Yongren; Macy, Michael

2016-09-01

Structural similarity based on bipartite graphs can be used to detect meaningful communities, but the networks have been tiny compared to massive online networks. Scalability is important in applications involving tens of millions of individuals with highly skewed degree distributions. Simulation analysis holding underlying similarity constant shows that two widely used measures - Jaccard index and cosine similarity - are biased by the distribution of out-degree in web-scale networks. However, an alternative measure, the Standardized Co-incident Ratio (SCR), is unbiased. We apply SCR to members of Congress, musical artists, and professional sports teams to show how massive co-following on Twitter can be used to map meaningful affiliations among cultural entities, even in the absence of direct connections to one another. Our results show how structural similarity can be used to map cultural alignments and demonstrate the potential usefulness of social media data in the study of culture, politics, and organizations across the social and behavioral sciences. Copyright © 2016 Elsevier Inc. All rights reserved.

Skill networks and measures of complex human capital.

Science.gov (United States)

Anderson, Katharine A

2017-11-28

We propose a network-based method for measuring worker skills. We illustrate the method using data from an online freelance website. Using the tools of network analysis, we divide skills into endogenous categories based on their relationship with other skills in the market. Workers who specialize in these different areas earn dramatically different wages. We then show that, in this market, network-based measures of human capital provide additional insight into wages beyond traditional measures. In particular, we show that workers with diverse skills earn higher wages than those with more specialized skills. Moreover, we can distinguish between two different types of workers benefiting from skill diversity: jacks-of-all-trades, whose skills can be applied independently on a wide range of jobs, and synergistic workers, whose skills are useful in combination and fill a hole in the labor market. On average, workers whose skills are synergistic earn more than jacks-of-all-trades. Copyright © 2017 the Author(s). Published by PNAS.

Synchronization of Switched Interval Networks and Applications to Chaotic Neural Networks

OpenAIRE

Cao, Jinde; Alofi, Abdulaziz; Al-Mazrooei, Abdullah; Elaiw, Ahmed

2013-01-01

This paper investigates synchronization problem of switched delay networks with interval parameters uncertainty, based on the theories of the switched systems and drive-response technique, a mathematical model of the switched interval drive-response error system is established. Without constructing Lyapunov-Krasovskii functions, introducing matrix measure method for the first time to switched time-varying delay networks, combining Halanay inequality technique, synchroniza...

Field Measurement-Based System Identification and Dynamic Response Prediction of a Unique MIT Building.

Science.gov (United States)

Cha, Young-Jin; Trocha, Peter; Büyüköztürk, Oral

2016-07-01

Tall buildings are ubiquitous in major cities and house the homes and workplaces of many individuals. However, relatively few studies have been carried out to study the dynamic characteristics of tall buildings based on field measurements. In this paper, the dynamic behavior of the Green Building, a unique 21-story tall structure located on the campus of the Massachusetts Institute of Technology (MIT, Cambridge, MA, USA), was characterized and modeled as a simplified lumped-mass beam model (SLMM), using data from a network of accelerometers. The accelerometer network was used to record structural responses due to ambient vibrations, blast loading, and the October 16th 2012 earthquake near Hollis Center (ME, USA). Spectral and signal coherence analysis of the collected data was used to identify natural frequencies, modes, foundation rocking behavior, and structural asymmetries. A relation between foundation rocking and structural natural frequencies was also found. Natural frequencies and structural acceleration from the field measurements were compared with those predicted by the SLMM which was updated by inverse solving based on advanced multiobjective optimization methods using the measured structural responses and found to have good agreement.

Field Measurement-Based System Identification and Dynamic Response Prediction of a Unique MIT Building

Directory of Open Access Journals (Sweden)

Young-Jin Cha

2016-07-01

Full Text Available Tall buildings are ubiquitous in major cities and house the homes and workplaces of many individuals. However, relatively few studies have been carried out to study the dynamic characteristics of tall buildings based on field measurements. In this paper, the dynamic behavior of the Green Building, a unique 21-story tall structure located on the campus of the Massachusetts Institute of Technology (MIT, Cambridge, MA, USA, was characterized and modeled as a simplified lumped-mass beam model (SLMM, using data from a network of accelerometers. The accelerometer network was used to record structural responses due to ambient vibrations, blast loading, and the October 16th 2012 earthquake near Hollis Center (ME, USA. Spectral and signal coherence analysis of the collected data was used to identify natural frequencies, modes, foundation rocking behavior, and structural asymmetries. A relation between foundation rocking and structural natural frequencies was also found. Natural frequencies and structural acceleration from the field measurements were compared with those predicted by the SLMM which was updated by inverse solving based on advanced multiobjective optimization methods using the measured structural responses and found to have good agreement.

Field Measurement-Based System Identification and Dynamic Response Prediction of a Unique MIT Building

Science.gov (United States)

Cha, Young-Jin; Trocha, Peter; Büyüköztürk, Oral

2016-01-01

Tall buildings are ubiquitous in major cities and house the homes and workplaces of many individuals. However, relatively few studies have been carried out to study the dynamic characteristics of tall buildings based on field measurements. In this paper, the dynamic behavior of the Green Building, a unique 21-story tall structure located on the campus of the Massachusetts Institute of Technology (MIT, Cambridge, MA, USA), was characterized and modeled as a simplified lumped-mass beam model (SLMM), using data from a network of accelerometers. The accelerometer network was used to record structural responses due to ambient vibrations, blast loading, and the October 16th 2012 earthquake near Hollis Center (ME, USA). Spectral and signal coherence analysis of the collected data was used to identify natural frequencies, modes, foundation rocking behavior, and structural asymmetries. A relation between foundation rocking and structural natural frequencies was also found. Natural frequencies and structural acceleration from the field measurements were compared with those predicted by the SLMM which was updated by inverse solving based on advanced multiobjective optimization methods using the measured structural responses and found to have good agreement. PMID:27376303

Information loss method to measure node similarity in networks

Science.gov (United States)

Li, Yongli; Luo, Peng; Wu, Chong

2014-09-01

Similarity measurement for the network node has been paid increasing attention in the field of statistical physics. In this paper, we propose an entropy-based information loss method to measure the node similarity. The whole model is established based on this idea that less information loss is caused by seeing two more similar nodes as the same. The proposed new method has relatively low algorithm complexity, making it less time-consuming and more efficient to deal with the large scale real-world network. In order to clarify its availability and accuracy, this new approach was compared with some other selected approaches on two artificial examples and synthetic networks. Furthermore, the proposed method is also successfully applied to predict the network evolution and predict the unknown nodes' attributions in the two application examples.

Network neighborhood analysis with the multi-node topological overlap measure.

Science.gov (United States)

Li, Ai; Horvath, Steve

2007-01-15

The goal of neighborhood analysis is to find a set of genes (the neighborhood) that is similar to an initial 'seed' set of genes. Neighborhood analysis methods for network data are important in systems biology. If individual network connections are susceptible to noise, it can be advantageous to define neighborhoods on the basis of a robust interconnectedness measure, e.g. the topological overlap measure. Since the use of multiple nodes in the seed set may lead to more informative neighborhoods, it can be advantageous to define multi-node similarity measures. The pairwise topological overlap measure is generalized to multiple network nodes and subsequently used in a recursive neighborhood construction method. A local permutation scheme is used to determine the neighborhood size. Using four network applications and a simulated example, we provide empirical evidence that the resulting neighborhoods are biologically meaningful, e.g. we use neighborhood analysis to identify brain cancer related genes. An executable Windows program and tutorial for multi-node topological overlap measure (MTOM) based analysis can be downloaded from the webpage (http://www.genetics.ucla.edu/labs/horvath/MTOM/).

Tower-Based Greenhouse Gas Measurement Network Design---The National Institute of Standards and Technology North East Corridor Testbed.

Science.gov (United States)

Lopez-Coto, Israel; Ghosh, Subhomoy; Prasad, Kuldeep; Whetstone, James

2017-09-01

The North-East Corridor (NEC) Testbed project is the 3rd of three NIST (National Institute of Standards and Technology) greenhouse gas emissions testbeds designed to advance greenhouse gas measurements capabilities. A design approach for a dense observing network combined with atmospheric inversion methodologies is described. The Advanced Research Weather Research and Forecasting Model with the Stochastic Time-Inverted Lagrangian Transport model were used to derive the sensitivity of hypothetical observations to surface greenhouse gas emissions (footprints). Unlike other network design algorithms, an iterative selection algorithm, based on a k -means clustering method, was applied to minimize the similarities between the temporal response of each site and maximize sensitivity to the urban emissions contribution. Once a network was selected, a synthetic inversion Bayesian Kalman filter was used to evaluate observing system performance. We present the performances of various measurement network configurations consisting of differing numbers of towers and tower locations. Results show that an overly spatially compact network has decreased spatial coverage, as the spatial information added per site is then suboptimal as to cover the largest possible area, whilst networks dispersed too broadly lose capabilities of constraining flux uncertainties. In addition, we explore the possibility of using a very high density network of lower cost and performance sensors characterized by larger uncertainties and temporal drift. Analysis convergence is faster with a large number of observing locations, reducing the response time of the filter. Larger uncertainties in the observations implies lower values of uncertainty reduction. On the other hand, the drift is a bias in nature, which is added to the observations and, therefore, biasing the retrieved fluxes.

Characterizing root response phenotypes by neural network analysis

OpenAIRE

Hatzig, Sarah V.; Schiessl, Sarah; Stahl, Andreas; Snowdon, Rod J.

2015-01-01

Roots play an immediate role as the interface for water acquisition. To improve sustainability in low-water environments, breeders of major crops must therefore pay closer attention to advantageous root phenotypes; however, the complexity of root architecture in response to stress can be difficult to quantify. Here, the Sholl method, an established technique from neurobiology used for the characterization of neural network anatomy, was adapted to more adequately describe root responses to osm...

Procedure to Solve Network DEA Based on a Virtual Gap Measurement Model

Directory of Open Access Journals (Sweden)

Fuh-hwa Franklin Liu

2017-01-01

Full Text Available Network DEA models assess production systems that contain a set of network-structured subsystems. Each subsystem has input and output measures from and to the external network and has intermediate measures that link to other subsystems. Most published studies demonstrate how to employ DEA models to establish network DEA models. Neither static nor dynamic network DEA models adjust the links. This paper applies the virtual gap measurement (VGM model to construct a mixed integer program to solve dynamic network DEA problems. The mixed integer program sets the total numbers of “as-input” and “as-output” equal to the total number of links in the objective function. To obtain the best-practice efficiency, each DMU determines a set of weights for inputs, outputs, and links. The links are played either “as-input” or “as-output.” Input and as-input measures reduce slack, whereas output and as-output measures increase slacks to attain their target on the production frontier.

IMPLICATIONS OF SOCIAL RESPONSIBILITY DISCLOSURE ON GLOBAL PRODUCTION NETWORK

OpenAIRE

Le Bo; Dan Shen; Jin Jun Bo

2014-01-01

This paper aims to discuss effectiveness of social responsibility disclosure in promoting global production network. Through a critical review on the theoretical development from supply chain to global production network, the global supply chain management of Apple Inc., as a case, is investigated, with focus on corporate and NGOs’ social disclosure on the environmental and labor rights' issues of its suppliers in China. The paper concludes that effectiveness of corporate social disclosure on...

Simulating Quantitative Cellular Responses Using Asynchronous Threshold Boolean Network Ensembles

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Shah Imran

2011-07-01

Full Text Available Abstract Background With increasing knowledge about the potential mechanisms underlying cellular functions, it is becoming feasible to predict the response of biological systems to genetic and environmental perturbations. Due to the lack of homogeneity in living tissues it is difficult to estimate the physiological effect of chemicals, including potential toxicity. Here we investigate a biologically motivated model for estimating tissue level responses by aggregating the behavior of a cell population. We assume that the molecular state of individual cells is independently governed by discrete non-deterministic signaling mechanisms. This results in noisy but highly reproducible aggregate level responses that are consistent with experimental data. Results We developed an asynchronous threshold Boolean network simulation algorithm to model signal transduction in a single cell, and then used an ensemble of these models to estimate the aggregate response across a cell population. Using published data, we derived a putative crosstalk network involving growth factors and cytokines - i.e., Epidermal Growth Factor, Insulin, Insulin like Growth Factor Type 1, and Tumor Necrosis Factor α - to describe early signaling events in cell proliferation signal transduction. Reproducibility of the modeling technique across ensembles of Boolean networks representing cell populations is investigated. Furthermore, we compare our simulation results to experimental observations of hepatocytes reported in the literature. Conclusion A systematic analysis of the results following differential stimulation of this model by growth factors and cytokines suggests that: (a using Boolean network ensembles with asynchronous updating provides biologically plausible noisy individual cellular responses with reproducible mean behavior for large cell populations, and (b with sufficient data our model can estimate the response to different concentrations of extracellular ligands. Our

Calibration-measurement unit for the automation of vector network analyzer measurements

Directory of Open Access Journals (Sweden)

I. Rolfes

2008-05-01

Full Text Available With the availability of multi-port vector network analyzers, the need for automated, calibrated measurement facilities increases. In this contribution, a calibration-measurement unit is presented which realizes a repeatable automated calibration of the measurement setup as well as a user-friendly measurement of the device under test (DUT. In difference to commercially available calibration units, which are connected to the ports of the vector network analyzer preceding a measurement and which are then removed so that the DUT can be connected, the presented calibration-measurement unit is permanently connected to the ports of the VNA for the calibration as well as for the measurement of the DUT. This helps to simplify the calibrated measurement of complex scattering parameters. Moreover, a full integration of the calibration unit into the analyzer setup becomes possible. The calibration-measurement unit is based on a multiport switch setup of e.g. electromechanical relays. Under the assumption of symmetry of a switch, on the one hand the unit realizes the connection of calibration standards like one-port reflection standards and two-port through connections between different ports and on the other hand it enables the connection of the DUT. The calibration-measurement unit is applicable for two-port VNAs as well as for multiport VNAs. For the calibration of the unit, methods with completely known calibration standards like SOLT (short, open, load, through as well as self-calibration procedures like TMR or TLR can be applied.

Brain network response underlying decisions about abstract reinforcers.

Science.gov (United States)

Mills-Finnerty, Colleen; Hanson, Catherine; Hanson, Stephen Jose

2014-12-01

Decision making studies typically use tasks that involve concrete action-outcome contingencies, in which subjects do something and get something. No studies have addressed decision making involving abstract reinforcers, where there are no action-outcome contingencies and choices are entirely hypothetical. The present study examines these kinds of choices, as well as whether the same biases that exist for concrete reinforcer decisions, specifically framing effects, also apply during abstract reinforcer decisions. We use both General Linear Model as well as Bayes network connectivity analysis using the Independent Multi-sample Greedy Equivalence Search (IMaGES) algorithm to examine network response underlying choices for abstract reinforcers under positive and negative framing. We find for the first time that abstract reinforcer decisions activate the same network of brain regions as concrete reinforcer decisions, including the striatum, insula, anterior cingulate, and VMPFC, results that are further supported via comparison to a meta-analysis of decision making studies. Positive and negative framing activated different parts of this network, with stronger activation in VMPFC during negative framing and in DLPFC during positive, suggesting different decision making pathways depending on frame. These results were further clarified using connectivity analysis, which revealed stronger connections between anterior cingulate, insula, and accumbens during negative framing compared to positive. Taken together, these results suggest that not only do abstract reinforcer decisions rely on the same brain substrates as concrete reinforcers, but that the response underlying framing effects on abstract reinforcers also resemble those for concrete reinforcers, specifically increased limbic system connectivity during negative frames. Copyright © 2014 Elsevier Inc. All rights reserved.

Response times in a two-node queueing network with feedback

NARCIS (Netherlands)

van der Mei, R.D.; Gijsen, B.M.M.; in 't Veld, N.; van den Berg, J.L.

2002-01-01

The study presented in this paper is motivated by the performance analysis of response times in distributed information systems, where transactions are handled by iterative server and database actions. We model system response times as sojourn times in a two-node open queueing network with a

Response times in a two-node queueing network with feedback

NARCIS (Netherlands)

van der Mei, R.D.; Gijsen, B.M.M.; Gijsen, B.M.M.; in 't Veld, N.; van den Berg, Hans Leo

The study presented in this paper is motivated by the performance analysis of response times in distributed information systems, where transactions are handled by iterative server and database actions. We model system response times as sojourn times in a two-node open queueing network with a

Atomoxetine restores the response inhibition network in Parkinson's disease.

Science.gov (United States)

Rae, Charlotte L; Nombela, Cristina; Rodríguez, Patricia Vázquez; Ye, Zheng; Hughes, Laura E; Jones, P Simon; Ham, Timothy; Rittman, Timothy; Coyle-Gilchrist, Ian; Regenthal, Ralf; Sahakian, Barbara J; Barker, Roger A; Robbins, Trevor W; Rowe, James B

2016-08-01

Parkinson's disease impairs the inhibition of responses, and whilst impulsivity is mild for some patients, severe impulse control disorders affect ∼10% of cases. Based on preclinical models we proposed that noradrenergic denervation contributes to the impairment of response inhibition, via changes in the prefrontal cortex and its subcortical connections. Previous work in Parkinson's disease found that the selective noradrenaline reuptake inhibitor atomoxetine could improve response inhibition, gambling decisions and reflection impulsivity. Here we tested the hypotheses that atomoxetine can restore functional brain networks for response inhibition in Parkinson's disease, and that both structural and functional connectivity determine the behavioural effect. In a randomized, double-blind placebo-controlled crossover study, 19 patients with mild-to-moderate idiopathic Parkinson's disease underwent functional magnetic resonance imaging during a stop-signal task, while on their usual dopaminergic therapy. Patients received 40 mg atomoxetine or placebo, orally. This regimen anticipates that noradrenergic therapies for behavioural symptoms would be adjunctive to, not a replacement for, dopaminergic therapy. Twenty matched control participants provided normative data. Arterial spin labelling identified no significant changes in regional perfusion. We assessed functional interactions between key frontal and subcortical brain areas for response inhibition, by comparing 20 dynamic causal models of the response inhibition network, inverted to the functional magnetic resonance imaging data and compared using random effects model selection. We found that the normal interaction between pre-supplementary motor cortex and the inferior frontal gyrus was absent in Parkinson's disease patients on placebo (despite dopaminergic therapy), but this connection was restored by atomoxetine. The behavioural change in response inhibition (improvement indicated by reduced stop-signal reaction

Synchronization of Switched Interval Networks and Applications to Chaotic Neural Networks

Directory of Open Access Journals (Sweden)

Jinde Cao

2013-01-01

Full Text Available This paper investigates synchronization problem of switched delay networks with interval parameters uncertainty, based on the theories of the switched systems and drive-response technique, a mathematical model of the switched interval drive-response error system is established. Without constructing Lyapunov-Krasovskii functions, introducing matrix measure method for the first time to switched time-varying delay networks, combining Halanay inequality technique, synchronization criteria are derived for switched interval networks under the arbitrary switching rule, which are easy to verify in practice. Moreover, as an application, the proposed scheme is then applied to chaotic neural networks. Finally, numerical simulations are provided to illustrate the effectiveness of the theoretical results.

Prefrontal mediation of the reading network predicts intervention response in dyslexia.

Science.gov (United States)

Aboud, Katherine S; Barquero, Laura A; Cutting, Laurie E

2018-04-01

A primary challenge facing the development of interventions for dyslexia is identifying effective predictors of intervention response. While behavioral literature has identified core cognitive characteristics of response, the distinction of reading versus executive cognitive contributions to response profiles remains unclear, due in part to the difficulty of segregating these constructs using behavioral outputs. In the current study we used functional neuroimaging to piece apart the mechanisms of how/whether executive and reading network relationships are predictive of intervention response. We found that readers who are responsive to intervention have more typical pre-intervention functional interactions between executive and reading systems compared to nonresponsive readers. These findings suggest that intervention response in dyslexia is influenced not only by domain-specific reading regions, but also by contributions from intervening domain-general networks. Our results make a significant gain in identifying predictive bio-markers of outcomes in dyslexia, and have important implications for the development of personalized clinical interventions. Copyright © 2018 Elsevier Ltd. All rights reserved.

Research on the method of measuring space information network capacity in communication service

Directory of Open Access Journals (Sweden)

Zhu Shichao

2017-02-01

Full Text Available Because of the large scale characteristic of space information network in terms of space and time and the increasing of its complexity,existing measuring methods of information transmission capacity have been unable to measure the existing and future space information networkeffectively.In this study,we firstly established a complex model of space information network,and measured the whole space information network capacity by means of analyzing data access capability to the network and data transmission capability within the network.At last,we verified the rationality of the proposed measuring method by using STK and Matlab simulation software for collaborative simulation.

Plasticity of the MAPK signaling network in response to mechanical stress.

Directory of Open Access Journals (Sweden)

Andrea M Pereira

Full Text Available Cells display versatile responses to mechanical inputs and recent studies have identified the mitogen-activated protein kinase (MAPK cascades mediating the biological effects observed upon mechanical stimulation. Although, MAPK pathways can act insulated from each other, several mechanisms facilitate the crosstalk between the components of these cascades. Yet, the combinatorial complexity of potential molecular interactions between these elements have prevented the understanding of their concerted functions. To analyze the plasticity of the MAPK signaling network in response to mechanical stress we performed a non-saturating epistatic screen in resting and stretched conditions employing as readout a JNK responsive dJun-FRET biosensor. By knocking down MAPKs, and JNK pathway regulators, singly or in pairs in Drosophila S2R+ cells, we have uncovered unexpected regulatory links between JNK cascade kinases, Rho GTPases, MAPKs and the JNK phosphatase Puc. These relationships have been integrated in a system network model at equilibrium accounting for all experimentally validated interactions. This model allows predicting the global reaction of the network to its modulation in response to mechanical stress. It also highlights its context-dependent sensitivity.

A Game-Theoretic Response Strategy for Coordinator Attack in Wireless Sensor Networks

Science.gov (United States)

Liu, Jianhua; Yue, Guangxue; Shang, Huiliang; Li, Hongjie

2014-01-01

The coordinator is a specific node that controls the whole network and has a significant impact on the performance in cooperative multihop ZigBee wireless sensor networks (ZWSNs). However, the malicious node attacks coordinator nodes in an effort to waste the resources and disrupt the operation of the network. Attacking leads to a failure of one round of communication between the source nodes and destination nodes. Coordinator selection is a technique that can considerably defend against attack and reduce the data delivery delay, and increase network performance of cooperative communications. In this paper, we propose an adaptive coordinator selection algorithm using game and fuzzy logic aiming at both minimizing the average number of hops and maximizing network lifetime. The proposed game model consists of two interrelated formulations: a stochastic game for dynamic defense and a best response policy using evolutionary game formulation for coordinator selection. The stable equilibrium best policy to response defense is obtained from this game model. It is shown that the proposed scheme can improve reliability and save energy during the network lifetime with respect to security. PMID:25105171

IAEA Response and Assistance Network. Date Effective: 1 January 2011

International Nuclear Information System (INIS)

2010-01-01

This publication is a tool for (1) supporting the provision of international assistance in the event of a nuclear or radiological incident or emergency, (2) cooperation between States, their competent authorities and the IAEA, and (3) harmonization of response capabilities of States offering assistance under the Response and Assistance Network (RANET). The publication may also assist competent authorities and other response organizations in their efforts to establish and/or maintain their own response capabilities.

Network Science Based Quantification of Resilience Demonstrated on the Indian Railways Network

Science.gov (United States)

Bhatia, Udit; Kumar, Devashish; Kodra, Evan; Ganguly, Auroop R.

2015-01-01

The structure, interdependence, and fragility of systems ranging from power-grids and transportation to ecology, climate, biology and even human communities and the Internet have been examined through network science. While response to perturbations has been quantified, recovery strategies for perturbed networks have usually been either discussed conceptually or through anecdotal case studies. Here we develop a network science based quantitative framework for measuring, comparing and interpreting hazard responses as well as recovery strategies. The framework, motivated by the recently proposed temporal resilience paradigm, is demonstrated with the Indian Railways Network. Simulations inspired by the 2004 Indian Ocean Tsunami and the 2012 North Indian blackout as well as a cyber-physical attack scenario illustrate hazard responses and effectiveness of proposed recovery strategies. Multiple metrics are used to generate various recovery strategies, which are simply sequences in which system components should be recovered after a disruption. Quantitative evaluation of these strategies suggests that faster and more efficient recovery is possible through network centrality measures. Optimal recovery strategies may be different per hazard, per community within a network, and for different measures of partial recovery. In addition, topological characterization provides a means for interpreting the comparative performance of proposed recovery strategies. The methods can be directly extended to other Large-Scale Critical Lifeline Infrastructure Networks including transportation, water, energy and communications systems that are threatened by natural or human-induced hazards, including cascading failures. Furthermore, the quantitative framework developed here can generalize across natural, engineered and human systems, offering an actionable and generalizable approach for emergency management in particular as well as for network resilience in general. PMID:26536227

Network Science Based Quantification of Resilience Demonstrated on the Indian Railways Network.

Science.gov (United States)

Bhatia, Udit; Kumar, Devashish; Kodra, Evan; Ganguly, Auroop R

2015-01-01

The structure, interdependence, and fragility of systems ranging from power-grids and transportation to ecology, climate, biology and even human communities and the Internet have been examined through network science. While response to perturbations has been quantified, recovery strategies for perturbed networks have usually been either discussed conceptually or through anecdotal case studies. Here we develop a network science based quantitative framework for measuring, comparing and interpreting hazard responses as well as recovery strategies. The framework, motivated by the recently proposed temporal resilience paradigm, is demonstrated with the Indian Railways Network. Simulations inspired by the 2004 Indian Ocean Tsunami and the 2012 North Indian blackout as well as a cyber-physical attack scenario illustrate hazard responses and effectiveness of proposed recovery strategies. Multiple metrics are used to generate various recovery strategies, which are simply sequences in which system components should be recovered after a disruption. Quantitative evaluation of these strategies suggests that faster and more efficient recovery is possible through network centrality measures. Optimal recovery strategies may be different per hazard, per community within a network, and for different measures of partial recovery. In addition, topological characterization provides a means for interpreting the comparative performance of proposed recovery strategies. The methods can be directly extended to other Large-Scale Critical Lifeline Infrastructure Networks including transportation, water, energy and communications systems that are threatened by natural or human-induced hazards, including cascading failures. Furthermore, the quantitative framework developed here can generalize across natural, engineered and human systems, offering an actionable and generalizable approach for emergency management in particular as well as for network resilience in general.

Network Science Based Quantification of Resilience Demonstrated on the Indian Railways Network.

Directory of Open Access Journals (Sweden)

Udit Bhatia

Full Text Available The structure, interdependence, and fragility of systems ranging from power-grids and transportation to ecology, climate, biology and even human communities and the Internet have been examined through network science. While response to perturbations has been quantified, recovery strategies for perturbed networks have usually been either discussed conceptually or through anecdotal case studies. Here we develop a network science based quantitative framework for measuring, comparing and interpreting hazard responses as well as recovery strategies. The framework, motivated by the recently proposed temporal resilience paradigm, is demonstrated with the Indian Railways Network. Simulations inspired by the 2004 Indian Ocean Tsunami and the 2012 North Indian blackout as well as a cyber-physical attack scenario illustrate hazard responses and effectiveness of proposed recovery strategies. Multiple metrics are used to generate various recovery strategies, which are simply sequences in which system components should be recovered after a disruption. Quantitative evaluation of these strategies suggests that faster and more efficient recovery is possible through network centrality measures. Optimal recovery strategies may be different per hazard, per community within a network, and for different measures of partial recovery. In addition, topological characterization provides a means for interpreting the comparative performance of proposed recovery strategies. The methods can be directly extended to other Large-Scale Critical Lifeline Infrastructure Networks including transportation, water, energy and communications systems that are threatened by natural or human-induced hazards, including cascading failures. Furthermore, the quantitative framework developed here can generalize across natural, engineered and human systems, offering an actionable and generalizable approach for emergency management in particular as well as for network resilience in general.

Measuring social networks in British primary schools through scientific engagement

Science.gov (United States)

Conlan, A. J. K.; Eames, K. T. D.; Gage, J. A.; von Kirchbach, J. C.; Ross, J. V.; Saenz, R. A.; Gog, J. R.

2011-01-01

Primary schools constitute a key risk group for the transmission of infectious diseases, concentrating great numbers of immunologically naive individuals at high densities. Despite this, very little is known about the social patterns of mixing within a school, which are likely to contribute to disease transmission. In this study, we present a novel approach where scientific engagement was used as a tool to access school populations and measure social networks between young (4–11 years) children. By embedding our research project within enrichment activities to older secondary school (13–15) children, we could exploit the existing links between schools to achieve a high response rate for our study population (around 90% in most schools). Social contacts of primary school children were measured through self-reporting based on a questionnaire design, and analysed using the techniques of social network analysis. We find evidence of marked social structure and gender assortativity within and between classrooms in the same school. These patterns have been previously reported in smaller studies, but to our knowledge no study has attempted to exhaustively sample entire school populations. Our innovative approach facilitates access to a vitally important (but difficult to sample) epidemiological sub-group. It provides a model whereby scientific communication can be used to enhance, rather than merely complement, the outcomes of research. PMID:21047859

Measure of robustness for complex networks

Science.gov (United States)

Youssef, Mina Nabil

Critical infrastructures are repeatedly attacked by external triggers causing tremendous amount of damages. Any infrastructure can be studied using the powerful theory of complex networks. A complex network is composed of extremely large number of different elements that exchange commodities providing significant services. The main functions of complex networks can be damaged by different types of attacks and failures that degrade the network performance. These attacks and failures are considered as disturbing dynamics, such as the spread of viruses in computer networks, the spread of epidemics in social networks, and the cascading failures in power grids. Depending on the network structure and the attack strength, every network differently suffers damages and performance degradation. Hence, quantifying the robustness of complex networks becomes an essential task. In this dissertation, new metrics are introduced to measure the robustness of technological and social networks with respect to the spread of epidemics, and the robustness of power grids with respect to cascading failures. First, we introduce a new metric called the Viral Conductance (VCSIS ) to assess the robustness of networks with respect to the spread of epidemics that are modeled through the susceptible/infected/susceptible (SIS) epidemic approach. In contrast to assessing the robustness of networks based on a classical metric, the epidemic threshold, the new metric integrates the fraction of infected nodes at steady state for all possible effective infection strengths. Through examples, VCSIS provides more insights about the robustness of networks than the epidemic threshold. In addition, both the paradoxical robustness of Barabasi-Albert preferential attachment networks and the effect of the topology on the steady state infection are studied, to show the importance of quantifying the robustness of networks. Second, a new metric VCSIR is introduced to assess the robustness of networks with respect

A game theory-based trust measurement model for social networks.

Science.gov (United States)

Wang, Yingjie; Cai, Zhipeng; Yin, Guisheng; Gao, Yang; Tong, Xiangrong; Han, Qilong

2016-01-01

In social networks, trust is a complex social network. Participants in online social networks want to share information and experiences with as many reliable users as possible. However, the modeling of trust is complicated and application dependent. Modeling trust needs to consider interaction history, recommendation, user behaviors and so on. Therefore, modeling trust is an important focus for online social networks. We propose a game theory-based trust measurement model for social networks. The trust degree is calculated from three aspects, service reliability, feedback effectiveness, recommendation credibility, to get more accurate result. In addition, to alleviate the free-riding problem, we propose a game theory-based punishment mechanism for specific trust and global trust, respectively. We prove that the proposed trust measurement model is effective. The free-riding problem can be resolved effectively through adding the proposed punishment mechanism.

Characterizations of the Beta and the Degree Network Power Measure

NARCIS (Netherlands)

van den Brink, J.R.; Borm, P.; Hendrickx, R.; Owen, G.

2008-01-01

A symmetric network consists of a set of positions and a set of bilateral links between these positions. For every symmetric network we define a cooperative transferable utility game that measures the "power" of each coalition of positions in the network. Applying the Shapley value to this game

Response Time Test for The Application of the Data Communication Network to Nuclear Power Plant

International Nuclear Information System (INIS)

Shin, Y.C.; Lee, J.Y.; Park, H.Y.; Seong, S.H.; Chung, H.Y.

2002-01-01

This paper discusses the response time test for the application of the Data Communication Network (DCN) to Nuclear Power Plant (NPP). Conventional Instrumentation and Control (I and C) Systems using the analog technology in NPP have raised many problems regarding the lack of spare parts, maintenance burden, inaccuracy, etc.. In order to solve the problems, the Korean Next Generation Reactor (KNGR) I and C system has adopted the digital technology and new design features of using the data communication networks. It is essential to prove the response time requirements that arise from the introduction of digital I and C technology and data communication networks to nuclear power plant design. For the response time test, a high reliable data communication network structure has been developed to meet the requirements of redundancy, diversity, and segmentation. This paper presents the results of network load analysis and response time test for the KNGR DCN prototype. The test has been focused on the response time from the field components to the gateway because the response times from the gateway to the specific systems are similar to those of the existing design. It is verified that the response time requirements are met through the prototype test for KNGR I and C systems. (authors)

Link-quality measurement and reporting in wireless sensor networks.

Science.gov (United States)

Chehri, Abdellah; Jeon, Gwanggil; Choi, Byoungjo

2013-03-04

Wireless Sensor networks (WSNs) are created by small hardware devices that possess the necessary functionalities to measure and exchange a variety of environmental data in their deployment setting. In this paper, we discuss the experiments in deploying a testbed as a first step towards creating a fully functional heterogeneous wireless network-based underground monitoring system. The system is mainly composed of mobile and static ZigBee nodes, which are deployed on the underground mine galleries for measuring ambient temperature. In addition, we describe the measured results of link characteristics such as received signal strength, latency and throughput for different scenarios.

Link-Quality Measurement and Reporting in Wireless Sensor Networks

Directory of Open Access Journals (Sweden)

Byoungjo Choi

2013-03-01

Full Text Available Wireless Sensor networks (WSNs are created by small hardware devices that possess the necessary functionalities to measure and exchange a variety of environmental data in their deployment setting. In this paper, we discuss the experiments in deploying a testbed as a first step towards creating a fully functional heterogeneous wireless network-based underground monitoring system. The system is mainly composed of mobile and static ZigBee nodes, which are deployed on the underground mine galleries for measuring ambient temperature. In addition, we describe the measured results of link characteristics such as received signal strength, latency and throughput for different scenarios.

Definition of Distribution Network Tariffs Considering Distribution Generation and Demand Response

DEFF Research Database (Denmark)

Soares, Tiago; Faria, Pedro; Vale, Zita

2014-01-01

The use of distribution networks in the current scenario of high penetration of Distributed Generation (DG) is a problem of great importance. In the competitive environment of electricity markets and smart grids, Demand Response (DR) is also gaining notable impact with several benefits for the wh......The use of distribution networks in the current scenario of high penetration of Distributed Generation (DG) is a problem of great importance. In the competitive environment of electricity markets and smart grids, Demand Response (DR) is also gaining notable impact with several benefits...... the determination of topological distribution factors, and consequent application of the MW-mile method. The application of the proposed tariffs definition methodology is illustrated in a distribution network with 33 buses, 66 DG units, and 32 consumers with DR capacity...

Atomoxetine restores the response inhibition network in Parkinson’s disease

Science.gov (United States)

Rae, Charlotte L.; Nombela, Cristina; Rodríguez, Patricia Vázquez; Ye, Zheng; Hughes, Laura E.; Jones, P. Simon; Ham, Timothy; Rittman, Timothy; Coyle-Gilchrist, Ian; Regenthal, Ralf; Sahakian, Barbara J.; Barker, Roger A.; Robbins, Trevor W.

2016-01-01

Abstract Parkinson’s disease impairs the inhibition of responses, and whilst impulsivity is mild for some patients, severe impulse control disorders affect ∼10% of cases. Based on preclinical models we proposed that noradrenergic denervation contributes to the impairment of response inhibition, via changes in the prefrontal cortex and its subcortical connections. Previous work in Parkinson’s disease found that the selective noradrenaline reuptake inhibitor atomoxetine could improve response inhibition, gambling decisions and reflection impulsivity. Here we tested the hypotheses that atomoxetine can restore functional brain networks for response inhibition in Parkinson’s disease, and that both structural and functional connectivity determine the behavioural effect. In a randomized, double-blind placebo-controlled crossover study, 19 patients with mild-to-moderate idiopathic Parkinson’s disease underwent functional magnetic resonance imaging during a stop-signal task, while on their usual dopaminergic therapy. Patients received 40 mg atomoxetine or placebo, orally. This regimen anticipates that noradrenergic therapies for behavioural symptoms would be adjunctive to, not a replacement for, dopaminergic therapy. Twenty matched control participants provided normative data. Arterial spin labelling identified no significant changes in regional perfusion. We assessed functional interactions between key frontal and subcortical brain areas for response inhibition, by comparing 20 dynamic causal models of the response inhibition network, inverted to the functional magnetic resonance imaging data and compared using random effects model selection. We found that the normal interaction between pre-supplementary motor cortex and the inferior frontal gyrus was absent in Parkinson’s disease patients on placebo (despite dopaminergic therapy), but this connection was restored by atomoxetine. The behavioural change in response inhibition (improvement indicated by reduced

Response of pressurized water reactor (PWR) to network power generation demands

International Nuclear Information System (INIS)

Schreiner, L.A.

1991-01-01

The flexibility of the PWR type reactor in terms of response to the variations of the network power demands, is demonstrated. The factors that affect the transitory flexibility and some design prospects that allow the reactor fits the requirements of the network power demands, are also discussed. (M.J.A.)

Computer Network Availability at Sandia National Laboratories, Albuquerque NM: Measurement and Perception; TOPICAL

International Nuclear Information System (INIS)

NELSON, SPENCER D.; TOLENDINO, LAWRENCE F.

1999-01-01

The desire to provide a measure of computer network availability at Sandia National Laboratories has existed for along time. Several attempts were made to build this measure by accurately recording network failures, identifying the type of network element involved, the root cause of the problem, and the time to repair the fault. Recognizing the limitations of available methods, it became obvious that another approach of determining network availability had to be defined. The chosen concept involved the periodic sampling of network services and applications from various network locations. A measure of ''network'' availability was then calculated based on the ratio of polling success to failure. The effort required to gather the information and produce a useful metric is not prohibitive and the information gained has verified long held feelings regarding network performance with real data

Role of architecture in the elastic response of semiflexible polymer and fiber networks

Science.gov (United States)

Heussinger, Claus; Frey, Erwin

2007-01-01

We study the elasticity of cross-linked networks of thermally fluctuating stiff polymers. As compared to their purely mechanical counterparts, it is shown that these thermal networks have a qualitatively different elastic response. By accounting for the entropic origin of the single-polymer elasticity, the networks acquire a strong susceptibility to polydispersity and structural randomness that is completely absent in athermal models. In extensive numerical studies we systematically vary the architecture of the networks and identify a wealth of phenomena that clearly show the strong dependence of the emergent macroscopic moduli on the underlying mesoscopic network structure. In particular, we highlight the importance of the polymer length, which to a large extent controls the elastic response of the network, surprisingly, even in parameter regions where it does not enter the macroscopic moduli explicitly. Understanding these subtle effects is only possible by going beyond the conventional approach that considers the response of typical polymer segments only. Instead, we propose to describe the elasticity in terms of a typical polymer filament and the spatial distribution of cross-links along its backbone. We provide theoretical scaling arguments to relate the observed macroscopic elasticity to the physical mechanisms on the microscopic and mesoscopic scales.

Measure of Node Similarity in Multilayer Networks

DEFF Research Database (Denmark)

Møllgaard, Anders; Zettler, Ingo; Dammeyer, Jesper

2016-01-01

university.Our analysis is based on data obtained using smartphones equipped with customdata collection software, complemented by questionnaire-based data. The networkof social contacts is represented as a weighted multilayer network constructedfrom different channels of telecommunication as well as data...... might bepresent in one layer of the multilayer network and simultaneously be absent inthe other layers. For a variable such as gender, our measure reveals atransition from similarity between nodes connected with links of relatively lowweight to dis-similarity for the nodes connected by the strongest...

Genetic dissection of acute ethanol responsive gene networks in prefrontal cortex: functional and mechanistic implications.

Directory of Open Access Journals (Sweden)

Aaron R Wolen

Full Text Available Individual differences in initial sensitivity to ethanol are strongly related to the heritable risk of alcoholism in humans. To elucidate key molecular networks that modulate ethanol sensitivity we performed the first systems genetics analysis of ethanol-responsive gene expression in brain regions of the mesocorticolimbic reward circuit (prefrontal cortex, nucleus accumbens, and ventral midbrain across a highly diverse family of 27 isogenic mouse strains (BXD panel before and after treatment with ethanol.Acute ethanol altered the expression of ~2,750 genes in one or more regions and 400 transcripts were jointly modulated in all three. Ethanol-responsive gene networks were extracted with a powerful graph theoretical method that efficiently summarized ethanol's effects. These networks correlated with acute behavioral responses to ethanol and other drugs of abuse. As predicted, networks were heavily populated by genes controlling synaptic transmission and neuroplasticity. Several of the most densely interconnected network hubs, including Kcnma1 and Gsk3β, are known to influence behavioral or physiological responses to ethanol, validating our overall approach. Other major hub genes like Grm3, Pten and Nrg3 represent novel targets of ethanol effects. Networks were under strong genetic control by variants that we mapped to a small number of chromosomal loci. Using a novel combination of genetic, bioinformatic and network-based approaches, we identified high priority cis-regulatory candidate genes, including Scn1b, Gria1, Sncb and Nell2.The ethanol-responsive gene networks identified here represent a previously uncharacterized intermediate phenotype between DNA variation and ethanol sensitivity in mice. Networks involved in synaptic transmission were strongly regulated by ethanol and could contribute to behavioral plasticity seen with chronic ethanol. Our novel finding that hub genes and a small number of loci exert major influence over the ethanol

Photovoltaic spectral responsivity measurements

Energy Technology Data Exchange (ETDEWEB)

Emery, K.; Dunlavy, D.; Field, H.; Moriarty, T. [National Renewable Energy Lab., Golden, CO (United States)

1998-09-01

This paper discusses the various elemental random and nonrandom error sources in typical spectral responsivity measurement systems. The authors focus specifically on the filter and grating monochrometer-based spectral responsivity measurement systems used by the Photovoltaic (PV) performance characterization team at NREL. A variety of subtle measurement errors can occur that arise from a finite photo-current response time, bandwidth of the monochromatic light, waveform of the monochromatic light, and spatial uniformity of the monochromatic and bias lights; the errors depend on the light source, PV technology, and measurement system. The quantum efficiency can be a function of he voltage bias, light bias level, and, for some structures, the spectral content of the bias light or location on the PV device. This paper compares the advantages and problems associated with semiconductor-detector-based calibrations and pyroelectric-detector-based calibrations. Different current-to-voltage conversion and ac photo-current detection strategies employed at NREL are compared and contrasted.

Development and validation of a survey to measure features of clinical networks.

Science.gov (United States)

Brown, Bernadette Bea; Haines, Mary; Middleton, Sandy; Paul, Christine; D'Este, Catherine; Klineberg, Emily; Elliott, Elizabeth

2016-09-30

Networks of clinical experts are increasingly being implemented as a strategy to improve health care processes and outcomes and achieve change in the health system. Few are ever formally evaluated and, when this is done, not all networks are equally successful in their efforts. There is a need to formatively assess the strategic and operational management and leadership of networks to identify where functioning could be improved to maximise impact. This paper outlines the development and psychometric evaluation of an Internet survey to measure features of clinical networks and provides descriptive results from a sample of members of 19 diverse clinical networks responsible for evidence-based quality improvement across a large geographical region. Instrument development was based on: a review of published and grey literature; a qualitative study of clinical network members; a program logic framework; and consultation with stakeholders. The resulting domain structure was validated for a sample of 592 clinical network members using confirmatory factor analysis. Scale reliability was assessed using Cronbach's alpha. A summary score was calculated for each domain and aggregate level means and ranges are reported. The instrument was shown to have good construct validity across seven domains as demonstrated by a high level of internal consistency, and all Cronbach's α coefficients were equal to or above 0.75. In the survey sample of network members there was strong reported commitment and belief in network-led quality improvement initiatives, which were perceived to have improved quality of care (72.8 %) and patient outcomes (63.2 %). Network managers were perceived to be effective leaders and clinical co-chairs were perceived as champions for change. Perceived external support had the lowest summary score across the seven domains. This survey, which has good construct validity and internal reliability, provides a valid instrument to use in future research related to

Arrester Resistive Current Measuring System Based on Heterogeneous Network

Science.gov (United States)

Zhang, Yun Hua; Li, Zai Lin; Yuan, Feng; Hou Pan, Feng; Guo, Zhan Nan; Han, Yue

2018-03-01

Metal Oxide Arrester (MOA) suffers from aging and poor insulation due to long-term impulse voltage and environmental impact, and the value and variation tendency of resistive current can reflect the health conditions of MOA. The common wired MOA detection need to use long cables, which is complicated to operate, and that wireless measurement methods are facing the problems of poor data synchronization and instability. Therefore a novel synchronous measurement system of arrester current resistive based on heterogeneous network is proposed, which simplifies the calculation process and improves synchronization, accuracy and stability and of the measuring system. This system combines LoRa wireless network, high speed wireless personal area network and the process layer communication, and realizes the detection of arrester working condition. Field test data shows that the system has the characteristics of high accuracy, strong anti-interference ability and good synchronization, which plays an important role in ensuring the stable operation of the power grid.

Using Social Network Analysis to Assess Mentorship and Collaboration in a Public Health Network.

Science.gov (United States)

Petrescu-Prahova, Miruna; Belza, Basia; Leith, Katherine; Allen, Peg; Coe, Norma B; Anderson, Lynda A

2015-08-20

Addressing chronic disease burden requires the creation of collaborative networks to promote systemic changes and engage stakeholders. Although many such networks exist, they are rarely assessed with tools that account for their complexity. This study examined the structure of mentorship and collaboration relationships among members of the Healthy Aging Research Network (HAN) using social network analysis (SNA). We invited 97 HAN members and partners to complete an online social network survey that included closed-ended questions about HAN-specific mentorship and collaboration during the previous 12 months. Collaboration was measured by examining the activity of the network on 6 types of products: published articles, in-progress manuscripts, grant applications, tools, research projects, and presentations. We computed network-level measures such as density, number of components, and centralization to assess the cohesiveness of the network. Sixty-three respondents completed the survey (response rate, 65%). Responses, which included information about collaboration with nonrespondents, suggested that 74% of HAN members were connected through mentorship ties and that all 97 members were connected through at least one form of collaboration. Mentorship and collaboration ties were present both within and across boundaries of HAN member organizations. SNA of public health collaborative networks provides understanding about the structure of relationships that are formed as a result of participation in network activities. This approach may offer members and funders a way to assess the impact of such networks that goes beyond simply measuring products and participation at the individual level.

Questions of trust in health research on social capital: what aspects of personal network social capital do they measure?

Science.gov (United States)

Carpiano, Richard M; Fitterer, Lisa M

2014-09-01

Health research on personal social capital has often utilized measures of respondents' perceived trust of others as either a proxy for one's social capital in the absence of more focused measures or as a subjective component of social capital. Little empirical work has evaluated the validity of such practices. We test the construct validity of two trust measures used commonly in health research on social capital-generalized trust and trust of neighbors-with respect to measures of people's general network-, organization-, family-, friend-, and neighborhood-based social capital and the extent to which these two trust measures are associated with self-rated general health and mental health when social capital measures are included in the same models. Analyses of 2008 Canadian General Social Survey data (response rate 57.3%) indicate that generalized trust and trust of neighbors are both positively-yet modestly-associated with measures of several domains of network-based social capital. Both trust measures are positively associated with general and mental health, but these associations remain robust after adjusting for social capital measures. Our findings suggest that (a) trust is conceptually distinct from social capital, (b) trust measures are inadequate proxies for actual personal social networks, and (c) trust measures may only be capturing psychological aspects relevant to-but not indicative of-social capital. Though links between perceived trust and health deserve study, health research on social capital needs to utilize measures of respondents' actual social networks and their inherent resources. Copyright © 2014 Elsevier Ltd. All rights reserved.

Black Carbon Measurements From Ireland's Transboundary Network (TXB)

Science.gov (United States)

Spohn, T. K.; Martin, D.; O'Dowd, C. D. D.

2017-12-01

Black Carbon (BC) is carbonaceous aerosol formed by incomplete fossil fuel combustion. Named for its light absorbing properties, it acts to trap heat in the atmosphere, thus behaving like a greenhouse gas, and is considered a strong, short-lived climate forcer by the International Panel on Climate Change (IPCC). Carbonaceous aerosols from biomass burning (BB) such as forest fires and residential wood burning, also known as brown carbon, affect the ultra violet (UV) light absorption in the atmosphere as well. In 2016 a three node black carbon monitoring network was established in Ireland as part of a Transboundary Monitoring Network (TXB). The three sites (Mace Head, Malin Head, and Carnsore Point) are coastal locations on opposing sides of the country, and offer the opportunity to assess typical northern hemispheric background concentrations as well national and European pollution events. The instruments deployed in this network (Magee Scientific AE33) facilitate elimination of the changes in response due to `aerosol loading' effects; and a real-time calculation of the `loading compensation' parameter which offers insights into aerosol optical properties. Additionally, these instruments have an inbuilt algorithm, which estimates the difference in absorption in the ultraviolet wavelengths (mostly by brown carbon) and the near infrared wavelengths (only by black carbon).Presented here are the first results of the BC measurements from the three Irish stations, including instrument validation, seasonal variation as well as local, regional, and transboundary influences based on air mass trajectories as well as concurrent in-situ observations (meteorological parameters, particle number, and aerosol composition). A comparison of the instrumental algorithm to off-line sensitivity calculations will also be made to assess the contribution of biomass burning to BC pollution events.

Local difference measures between complex networks for dynamical system model evaluation.

Science.gov (United States)

Lange, Stefan; Donges, Jonathan F; Volkholz, Jan; Kurths, Jürgen

2015-01-01

A faithful modeling of real-world dynamical systems necessitates model evaluation. A recent promising methodological approach to this problem has been based on complex networks, which in turn have proven useful for the characterization of dynamical systems. In this context, we introduce three local network difference measures and demonstrate their capabilities in the field of climate modeling, where these measures facilitate a spatially explicit model evaluation.Building on a recent study by Feldhoff et al. [8] we comparatively analyze statistical and dynamical regional climate simulations of the South American monsoon system [corrected]. types of climate networks representing different aspects of rainfall dynamics are constructed from the modeled precipitation space-time series. Specifically, we define simple graphs based on positive as well as negative rank correlations between rainfall anomaly time series at different locations, and such based on spatial synchronizations of extreme rain events. An evaluation against respective networks built from daily satellite data provided by the Tropical Rainfall Measuring Mission 3B42 V7 reveals far greater differences in model performance between network types for a fixed but arbitrary climate model than between climate models for a fixed but arbitrary network type. We identify two sources of uncertainty in this respect. Firstly, climate variability limits fidelity, particularly in the case of the extreme event network; and secondly, larger geographical link lengths render link misplacements more likely, most notably in the case of the anticorrelation network; both contributions are quantified using suitable ensembles of surrogate networks. Our model evaluation approach is applicable to any multidimensional dynamical system and especially our simple graph difference measures are highly versatile as the graphs to be compared may be constructed in whatever way required. Generalizations to directed as well as edge- and node

THE MEASUREMENT ELECTROMAGNETIC INTERFERENCE IN THE REVERSE TRACTION NETWORK

Directory of Open Access Journals (Sweden)

T. M. Serdiuk

2009-09-01

Full Text Available The original automated method of measurement of electrical noise in the return electric-traction network is proposed. It is realized on the base of car-laboratory “Automatics, telemechanics and communication”. The mathematic model of return electric-traction network is developed to scientific bases of automated measurement. It allows us obtaining the mathematic expressions for change of voltage and current harmonics in the rail net and taking into account the inhomogeneity of lines for the following analytic determination of a source of electric noise.

Feedback Models for Collaboration and Trust in Crisis Response Networks

National Research Council Canada - National Science Library

Hudgens, Bryan J; Bordetsky, Alex

2008-01-01

.... Coordination within disaster response networks is difficult for several reasons, including the chaotic nature of the crisis, a need for the various organizations to balance shared goals (crisis amelioration...

Evaluation of Techniques to Detect Significant Network Performance Problems using End-to-End Active Network Measurements

Energy Technology Data Exchange (ETDEWEB)

Cottrell, R.Les; Logg, Connie; Chhaparia, Mahesh; /SLAC; Grigoriev, Maxim; /Fermilab; Haro, Felipe; /Chile U., Catolica; Nazir, Fawad; /NUST, Rawalpindi; Sandford, Mark

2006-01-25

End-to-End fault and performance problems detection in wide area production networks is becoming increasingly hard as the complexity of the paths, the diversity of the performance, and dependency on the network increase. Several monitoring infrastructures are built to monitor different network metrics and collect monitoring information from thousands of hosts around the globe. Typically there are hundreds to thousands of time-series plots of network metrics which need to be looked at to identify network performance problems or anomalous variations in the traffic. Furthermore, most commercial products rely on a comparison with user configured static thresholds and often require access to SNMP-MIB information, to which a typical end-user does not usually have access. In our paper we propose new techniques to detect network performance problems proactively in close to realtime and we do not rely on static thresholds and SNMP-MIB information. We describe and compare the use of several different algorithms that we have implemented to detect persistent network problems using anomalous variations analysis in real end-to-end Internet performance measurements. We also provide methods and/or guidance for how to set the user settable parameters. The measurements are based on active probes running on 40 production network paths with bottlenecks varying from 0.5Mbits/s to 1000Mbit/s. For well behaved data (no missed measurements and no very large outliers) with small seasonal changes most algorithms identify similar events. We compare the algorithms' robustness with respect to false positives and missed events especially when there are large seasonal effects in the data. Our proposed techniques cover a wide variety of network paths and traffic patterns. We also discuss the applicability of the algorithms in terms of their intuitiveness, their speed of execution as implemented, and areas of applicability. Our encouraging results compare and evaluate the accuracy of our

pO2 measurements in arteriolar networks.

Science.gov (United States)

Torres Filho, I P; Kerger, H; Intaglietta, M

1996-03-01

Previous studies from our laboratory have shown that the average arteriolar pO2 in the hamster skinfold preparation is lower than arterial systemic pO2. In the present work we tested the hypothesis that there is a longitudinal gradient of pO2 along precapillary vessels. Experiments were performed in Syrian golden hamsters bearing a dorsal skin chamber. The oxygen-dependent quenching of phosphorescence of palladium-porphyrin complexes was used to measure intravascular pO2 in the microcirculation. Arterioles were classified in four orders according to their position in the network, first-order vessels being the entrance points. Simultaneous determinations of diameter (D), red blood cell velocity, and systemic blood gases were also made. There was a significant fall of pO2 between vessels of different orders. First-order arterioles (mean D = 64 microns) had pO2 of 51.8 +/- 9.8 mm Hg (mean +/- SD) which was equivalent to approximately equal to 73% of the arterial systemic pO2. Within the arteriolar network, further decreases of intravascular pO2 were measured, leading to a pO2 of 34.0 +/- 7.9 mm Hg in terminal arterioles (mean D = 7.7 microns). In some vessels pO2 was measured in different positions of the same arteriole. The average longitudinal arteriolar oxygen saturation gradient was 3.4 +/- 0.4 delta %/mm (range 0.8-7.2). A significant and positive correlation was found between pO2 and microhemodynamic parameters when arterioles were grouped according to their order. This relation was not significant for venules which showed a mean pO2 of 30.8 +/- 10.8 mm Hg. Tissue pO2 averaged 24.6 +/- 5.8 mm Hg. We conclude that: (1) There is an oxygen loss in arterial vessels larger than 100 micrograms in diameter, (2) arteriolar pO2 in this preparation depends on the position of the vessel within the network, (3) a substantial portion of oxygen delivery to the hamster skin is provided by the arteriolar network, and (4) only a small pO2 gradient exists between terminal

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

Science.gov (United States)

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

2018-02-01

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

The impact of heterogeneous response on coupled spreading dynamics in multiplex networks

Science.gov (United States)

Nie, Xiaoyu; Tang, Ming; Zou, Yong; Guan, Shuguang; Zhou, Jie

2017-10-01

Many recent studies have demonstrated that individual awareness of disease may significantly affect the spreading process of infectious disease. In the majority of these studies, the response of the awareness is generally treated homogeneously. Considering of diversity and heterogeneity in the human behavior which widely exist under different circumstances, in this paper we study heterogeneous response when people are aware of the prevalence of infectious diseases. Specifically, we consider that an individual with more neighbors may take more preventive measures as a reaction when he is aware of the disease. A suppression strength is introduced to describe such heterogeneity, and we find that a more evident heterogeneity may cause a more effective suppressing effect to the spreading of epidemics. A mean-field theory is developed to support the results which are verified on the multiplex networks with different interlayer degree correlation.

Comparison of Neural Network Error Measures for Simulation of Slender Marine Structures

DEFF Research Database (Denmark)

Christiansen, Niels H.; Voie, Per Erlend Torbergsen; Winther, Ole

2014-01-01

Training of an artificial neural network (ANN) adjusts the internal weights of the network in order to minimize a predefined error measure. This error measure is given by an error function. Several different error functions are suggested in the literature. However, the far most common measure...

Measuring co-authorship and networking-adjusted scientific impact.

Directory of Open Access Journals (Sweden)

John P A Ioannidis

Full Text Available Appraisal of the scientific impact of researchers, teams and institutions with productivity and citation metrics has major repercussions. Funding and promotion of individuals and survival of teams and institutions depend on publications and citations. In this competitive environment, the number of authors per paper is increasing and apparently some co-authors don't satisfy authorship criteria. Listing of individual contributions is still sporadic and also open to manipulation. Metrics are needed to measure the networking intensity for a single scientist or group of scientists accounting for patterns of co-authorship. Here, I define I(1 for a single scientist as the number of authors who appear in at least I(1 papers of the specific scientist. For a group of scientists or institution, I(n is defined as the number of authors who appear in at least I(n papers that bear the affiliation of the group or institution. I(1 depends on the number of papers authored N(p. The power exponent R of the relationship between I(1 and N(p categorizes scientists as solitary (R>2.5, nuclear (R = 2.25-2.5, networked (R = 2-2.25, extensively networked (R = 1.75-2 or collaborators (R<1.75. R may be used to adjust for co-authorship networking the citation impact of a scientist. I(n similarly provides a simple measure of the effective networking size to adjust the citation impact of groups or institutions. Empirical data are provided for single scientists and institutions for the proposed metrics. Cautious adoption of adjustments for co-authorship and networking in scientific appraisals may offer incentives for more accountable co-authorship behaviour in published articles.

Resiliency as a component importance measure in network reliability

International Nuclear Information System (INIS)

Whitson, John C.; Ramirez-Marquez, Jose Emmanuel

2009-01-01

This paper seeks to define the concept of resiliency as a component importance measure related to network reliability. Resiliency can be defined as a composite of: (1) the ability of a network to provide service despite external failures and (2) the time to restore service when in the presence of such failures. Although, Resiliency has been extensively studied in different research areas, this paper will study the specific aspects of quantifiable network resiliency when the network is experiencing potential catastrophic failures from external events and/or influences, and when it is not known a priori which specific components within the network will fail. A formal definition for Category I resiliency is proposed and a step-by-step approach based on Monte-Carlo simulation to calculate it is defined. To illustrate the approach, two-terminal networks with varying degrees of redundancy, have been considered. The results obtained for test networks show that this new quantifiable concept of resiliency provides insight into the performance and topology of the network. Future use for this work could include methods for safeguarding critical network components and optimizing the use of redundancy as a technique to improve network resiliency.

Filling the gap between disaster preparedness and response networks of urban emergency management: Following the 2013 Seoul Floods.

Science.gov (United States)

Song, Minsun; Jung, Kyujin

2015-01-01

To examine the gap between disaster preparedness and response networks following the 2013 Seoul Floods in which the rapid transmission of disaster information and resources was impeded by severe changes of interorganizational collaboration networks. This research uses the 2013 Seoul Emergency Management Survey data that were collected before and after the floods, and total 94 organizations involving in coping with the floods were analyzed in bootstrap independent-sample t-test and social network analysis through UCINET 6 and STATA 12. The findings show that despite the primary network form that is more hierarchical, horizontal collaboration has been relatively invigorated in actual response. Also, interorganizational collaboration networks for response operations seem to be more flexible grounded on improvisation to coping with unexpected victims and damages. Local organizations under urban emergency management are recommended to tightly build a strong commitment for joint response operations through full-size exercises at the metropolitan level before a catastrophic event. Also, interorganizational emergency management networks need to be restructured by reflecting the actual response networks to reduce collaboration risk during a disaster. This research presents a critical insight into inverse thinking of the view designing urban emergency management networks and provides original evidences for filling the gap between previously coordinated networks for disaster preparedness and practical response operations after a disaster.

Photo-responsive liquid crystalline epoxy networks with exchangeable disulfide bonds

Energy Technology Data Exchange (ETDEWEB)

Li, Yuzhan [Washington State Univ., Pullman, WA (United States); Zhang, Yuehong [Washington State Univ., Pullman, WA (United States); Rios, Orlando [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Keum, Jong K. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Kessler, Michael R. [Washington State Univ., Pullman, WA (United States); North Dakota State Univ., Fargo, ND (United States)

2017-07-27

The increasing demand for intelligent materials has driven the development of polymers with a variety of functionalities. However, combining multiple functionalities within one polymer is still challenging because of the difficulties encountered in coordinating different functional building blocks during fabrication. In this work, we demonstrate the fabrication of a multifunctional liquid crystalline epoxy network (LCEN) using the combination of thermotropic liquid crystals, photo-responsive azobenzene molecules, and exchangeable disulfide bonds. In addition to shape memory behavior enabled by the reversible liquid crystalline phase transition and photo-induced bending behavior resulting from the photo-responsive azobenzene molecules, the introduction of dynamic disulfide bonds into the LCEN resulted in a structurally dynamic network, allowing the reshaping, repairing, and recycling of the material.

Pyramidal resistor networks for electrical impedance tomography with partial boundary measurements

International Nuclear Information System (INIS)

Borcea, L; Mamonov, A V; Druskin, V; Vasquez, F Guevara

2010-01-01

We introduce an inversion algorithm for electrical impedance tomography (EIT) with partial boundary measurements in two dimensions. It gives stable and fast reconstructions using sparse parameterizations of the unknown conductivity on optimal grids that are computed as part of the inversion. We follow the approach in Borcea et al (2008 Inverse Problems 24 035013) and Vasquez (2006 PhD thesis Rice University, Houston, TX, USA) that connects inverse discrete problems for resistor networks to continuum EIT problems, using optimal grids. The algorithm in Borcea et al (2008 Inverse Problems 24 035013) and Vasquez (2006 PhD Thesis Rice University, Houston, TX, USA) is based on circular resistor networks, and solves the EIT problem with full boundary measurements. It is extended in Borcea et al (2010 Inverse Problems 26 045010) to EIT with partial boundary measurements, using extremal quasi-conformal mappings that transform the problem to one with full boundary measurements. Here we introduce a different class of optimal grids, based on resistor networks with pyramidal topology, that is better suited for the partial measurements setup. We prove the unique solvability of the discrete inverse problem for these networks and develop an algorithm for finding them from the measurements of the Dirichlet to Neumann map. Then, we show how to use the networks to define the optimal grids and to approximate the unknown conductivity. We assess the performance of our approach with numerical simulations and compare the results with those in Borcea et al (2010)

Reduced Social Network Drinking is Associated with Improved Response Inhibition in Women During Early Recovery from Alcohol Use Disorders: A Pilot Study.

Science.gov (United States)

McCutcheon, Vivia V; Luke, Douglas A; Lessov-Schlaggar, Christina N

2016-01-01

Social support for recovery from alcohol use disorders (AUDs) is associated with improvements in self-reported impulsive behavior in individuals treated for AUDs. We build on these findings using a behavioral task-based measure of response inhibition, a well-defined component of impulsivity, to examine the association of disinhibition with alcohol-specific social network characteristics during early recovery. Women (n = 28) were recruited from treatment for AUD within 3 to 4 weeks of their last drink and were assessed at baseline and again 3 months later. Outcome measures were level of disinhibition at baseline and change in disinhibition from baseline to follow-up, measured using a computer-based continuous performance test. The primary independent variables were level of drinking in the social network at baseline and change in network drinking from baseline to follow-up. The sample [50% black, age M (SD) = 42.3 (9.5)] reported high rates of physical and sexual abuse before age 13 (43%), psychiatric disorder (71%), drug use disorder (78%), and previous treatment (71%). More drinking in participants' social networks was associated with greater disinhibition at baseline (β = 12.5, 95% CI = 6.3, 18.7). A reduction in network drinking from baseline to follow-up was associated with reduced disinhibition (β = -6.0, 95% CI = -11.3, -0.78) independent of IQ, recent alcohol consumption, and self-reported negative urgency. This study extends previous findings of an association between social networks and self-reported impulsivity to a neurobehavioral phenotype, response inhibition, suggesting that abstinence-supporting social networks may play a role in cognitive change during early recovery from AUDs. Copyright © 2015 by the Research Society on Alcoholism.

Application of artificial neural networks for response surface modelling in HPLC method development

Directory of Open Access Journals (Sweden)

Mohamed A. Korany

2012-01-01

Full Text Available This paper discusses the usefulness of artificial neural networks (ANNs for response surface modelling in HPLC method development. In this study, the combined effect of pH and mobile phase composition on the reversed-phase liquid chromatographic behaviour of a mixture of salbutamol (SAL and guaiphenesin (GUA, combination I, and a mixture of ascorbic acid (ASC, paracetamol (PAR and guaiphenesin (GUA, combination II, was investigated. The results were compared with those produced using multiple regression (REG analysis. To examine the respective predictive power of the regression model and the neural network model, experimental and predicted response factor values, mean of squares error (MSE, average error percentage (Er%, and coefficients of correlation (r were compared. It was clear that the best networks were able to predict the experimental responses more accurately than the multiple regression analysis.

Transcriptional profiling uncovers a network of cholesterol-responsive atherosclerosis target genes.

Directory of Open Access Journals (Sweden)

Josefin Skogsberg

2008-03-01

Full Text Available Despite the well-documented effects of plasma lipid lowering regimes halting atherosclerosis lesion development and reducing morbidity and mortality of coronary artery disease and stroke, the transcriptional response in the atherosclerotic lesion mediating these beneficial effects has not yet been carefully investigated. We performed transcriptional profiling at 10-week intervals in atherosclerosis-prone mice with human-like hypercholesterolemia and a genetic switch to lower plasma lipoproteins (Ldlr(-/-Apo(100/100Mttp(flox/flox Mx1-Cre. Atherosclerotic lesions progressed slowly at first, then expanded rapidly, and plateaued after advanced lesions formed. Analysis of lesion expression profiles indicated that accumulation of lipid-poor macrophages reached a point that led to the rapid expansion phase with accelerated foam-cell formation and inflammation, an interpretation supported by lesion histology. Genetic lowering of plasma cholesterol (e.g., lipoproteins at this point all together prevented the formation of advanced plaques and parallel transcriptional profiling of the atherosclerotic arterial wall identified 37 cholesterol-responsive genes mediating this effect. Validation by siRNA-inhibition in macrophages incubated with acetylated-LDL revealed a network of eight cholesterol-responsive atherosclerosis genes regulating cholesterol-ester accumulation. Taken together, we have identified a network of atherosclerosis genes that in response to plasma cholesterol-lowering prevents the formation of advanced plaques. This network should be of interest for the development of novel atherosclerosis therapies.

Dynamical Response of Networks Under External Perturbations: Exact Results

Science.gov (United States)

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

2015-04-01

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

An assessment of available measures to reduce traction energy use in railway networks

International Nuclear Information System (INIS)

Douglas, Heather; Roberts, Clive; Hillmansen, Stuart; Schmid, Felix

2015-01-01

Highlights: • Railway networks are defined in terms of their distinguishing features. • Current energy saving measures are reviewed and categorised by the energy use they target. • The achievable energy savings of different measures are compared dependent on the network type. • The success of a measure depends on the characteristics of the network, vehicle and service. • Measures should be evaluated at system level due to interdependencies. - Abstract: Rail is becoming an increasingly popular choice to satisfy transportation demands locally, nationally and internationally, due to its inherent efficiency and high capacity. Despite this, operators are facing pressure to reduce rail energy consumption to meet efficiency targets, whilst still maintaining service quality and managing increased demand. A number of individual measures have been proposed to reduce energy in the rail sector, often showing good results on specific case studies. It is generally agreed that the attainable savings of a given measure change dependant on the route, vehicle and service characteristics. However, there is little information in the literature specifically regarding which measures are most suitable for given network types, or how they interact. This paper therefore aims to begin evaluating the available measures in terms of their suitability for different systems. Firstly, networks are defined in terms of their distinguishing features. As traction accounts for the majority of all energy use in the rail sector, the traction flow through a vehicle is considered as the starting point for an evaluation of measures. Current technologies and procedures are reviewed and categorised based on which area of traction use they target. Thought is given to the factors that affect implementation and the networks where they are applied. A key output of this paper is a comparison of the achievable energy savings of different measures dependent on the network type. It is hoped that this will

3D Facial Similarity Measure Based on Geodesic Network and Curvatures

Directory of Open Access Journals (Sweden)

Junli Zhao

2014-01-01

Full Text Available Automated 3D facial similarity measure is a challenging and valuable research topic in anthropology and computer graphics. It is widely used in various fields, such as criminal investigation, kinship confirmation, and face recognition. This paper proposes a 3D facial similarity measure method based on a combination of geodesic and curvature features. Firstly, a geodesic network is generated for each face with geodesics and iso-geodesics determined and these network points are adopted as the correspondence across face models. Then, four metrics associated with curvatures, that is, the mean curvature, Gaussian curvature, shape index, and curvedness, are computed for each network point by using a weighted average of its neighborhood points. Finally, correlation coefficients according to these metrics are computed, respectively, as the similarity measures between two 3D face models. Experiments of different persons’ 3D facial models and different 3D facial models of the same person are implemented and compared with a subjective face similarity study. The results show that the geodesic network plays an important role in 3D facial similarity measure. The similarity measure defined by shape index is consistent with human’s subjective evaluation basically, and it can measure the 3D face similarity more objectively than the other indices.

Output power distributions of mobile radio base stations based on network measurements

International Nuclear Information System (INIS)

Colombi, D; Thors, B; Persson, T; Törnevik, C; Wirén, N; Larsson, L-E

2013-01-01

In this work output power distributions of mobile radio base stations have been analyzed for 2G and 3G telecommunication systems. The approach is based on measurements in selected networks using performance surveillance tools part of the network Operational Support System (OSS). For the 3G network considered, direct measurements of output power levels were possible, while for the 2G networks, output power levels were estimated from measurements of traffic volumes. Both voice and data services were included in the investigation. Measurements were conducted for large geographical areas, to ensure good overall statistics, as well as for smaller areas to investigate the impact of different environments. For high traffic hours, the 90th percentile of the averaged output power was found to be below 65% and 45% of the available output power for the 2G and 3G systems, respectively.

Output power distributions of mobile radio base stations based on network measurements

Science.gov (United States)

Colombi, D.; Thors, B.; Persson, T.; Wirén, N.; Larsson, L.-E.; Törnevik, C.

2013-04-01

In this work output power distributions of mobile radio base stations have been analyzed for 2G and 3G telecommunication systems. The approach is based on measurements in selected networks using performance surveillance tools part of the network Operational Support System (OSS). For the 3G network considered, direct measurements of output power levels were possible, while for the 2G networks, output power levels were estimated from measurements of traffic volumes. Both voice and data services were included in the investigation. Measurements were conducted for large geographical areas, to ensure good overall statistics, as well as for smaller areas to investigate the impact of different environments. For high traffic hours, the 90th percentile of the averaged output power was found to be below 65% and 45% of the available output power for the 2G and 3G systems, respectively.

Acute LSD effects on response inhibition neural networks.

Science.gov (United States)

Schmidt, A; Müller, F; Lenz, C; Dolder, P C; Schmid, Y; Zanchi, D; Lang, U E; Liechti, M E; Borgwardt, S

2017-10-02

Recent evidence shows that the serotonin 2A receptor (5-hydroxytryptamine2A receptor, 5-HT2AR) is critically involved in the formation of visual hallucinations and cognitive impairments in lysergic acid diethylamide (LSD)-induced states and neuropsychiatric diseases. However, the interaction between 5-HT2AR activation, cognitive impairments and visual hallucinations is still poorly understood. This study explored the effect of 5-HT2AR activation on response inhibition neural networks in healthy subjects by using LSD and further tested whether brain activation during response inhibition under LSD exposure was related to LSD-induced visual hallucinations. In a double-blind, randomized, placebo-controlled, cross-over study, LSD (100 µg) and placebo were administered to 18 healthy subjects. Response inhibition was assessed using a functional magnetic resonance imaging Go/No-Go task. LSD-induced visual hallucinations were measured using the 5 Dimensions of Altered States of Consciousness (5D-ASC) questionnaire. Relative to placebo, LSD administration impaired inhibitory performance and reduced brain activation in the right middle temporal gyrus, superior/middle/inferior frontal gyrus and anterior cingulate cortex and in the left superior frontal and postcentral gyrus and cerebellum. Parahippocampal activation during response inhibition was differently related to inhibitory performance after placebo and LSD administration. Finally, activation in the left superior frontal gyrus under LSD exposure was negatively related to LSD-induced cognitive impairments and visual imagery. Our findings show that 5-HT2AR activation by LSD leads to a hippocampal-prefrontal cortex-mediated breakdown of inhibitory processing, which might subsequently promote the formation of LSD-induced visual imageries. These findings help to better understand the neuropsychopharmacological mechanisms of visual hallucinations in LSD-induced states and neuropsychiatric disorders.

Complex Projective Synchronization in Drive-Response Stochastic Complex Networks by Impulsive Pinning Control

Directory of Open Access Journals (Sweden)

Xuefei Wu

2014-01-01

Full Text Available The complex projective synchronization in drive-response stochastic coupled networks with complex-variable systems is considered. The impulsive pinning control scheme is adopted to achieve complex projective synchronization and several simple and practical sufficient conditions are obtained in a general drive-response network. In addition, the adaptive feedback algorithms are proposed to adjust the control strength. Several numerical simulations are provided to show the effectiveness and feasibility of the proposed methods.

Network centrality measures and systemic risk: An application to the Turkish financial crisis

Science.gov (United States)

Kuzubaş, Tolga Umut; Ömercikoğlu, Inci; Saltoğlu, Burak

2014-07-01

In this paper, we analyze the performance of several network centrality measures in detecting systemically important financial institutions (SIFI) using data from the Turkish Interbank market during the financial crisis in 2000. We employ various network investigation tools such as volume, transactions, links, connectivity and reciprocity to gain a clearer picture of the network topology of the interbank market. We study the main borrower role of Demirbank in the crash of the banking system with network centrality measures which are extensively used in the network theory. This ex-post analysis of the crisis shows that centrality measures perform well in identifying and monitoring systemically important financial institutions which provide useful insights for financial regulations.

A new centrality measure for identifying influential nodes in social networks

Science.gov (United States)

Rhouma, Delel; Ben Romdhane, Lotfi

2018-04-01

The identification of central nodes has been a key problem in the field of social network analysis. In fact, it is a measure that accounts the popularity or the visibility of an actor within a network. In order to capture this concept, various measures, either sample or more elaborate, has been developed. Nevertheless, many of "traditional" measures are not designed to be applicable to huge data. This paper sets out a new node centrality index suitable for large social network. It uses the amount of the neighbors of a node and connections between them to characterize a "pivot" node in the graph. We presented experimental results on real data sets which show the efficiency of our proposal.

Internal Interface Diversification as a Security Measure in Sensor Networks

Directory of Open Access Journals (Sweden)

Sampsa Rauti

2018-03-01

Full Text Available More actuator and sensor devices are connected to the Internet of Things (IoT every day, and the network keeps growing, while software security of the devices is often incomplete. Sensor networks and the IoT in general currently cover a large number of devices with an identical internal interface structure. By diversifying the internal interfaces, the interfaces on each node of the network are made unique, and it is possible to break the software monoculture of easily exploitable identical systems. This paper proposes internal interface diversification as a security measure for sensor networks. We conduct a study on diversifiable internal interfaces in 20 IoT operating systems. We also present two proof-of-concept implementations and perform experiments to gauge the feasibility in the IoT environment. Internal interface diversification has practical limitations, and not all IoT operating systems have that many diversifiable interfaces. However, because of low resource requirements, compatibility with other security measures and wide applicability to several interfaces, we believe internal interface diversification is a promising and effective approach for securing nodes in sensor networks.

The French National Network for the Measurement of Environmental Radioactivity

International Nuclear Information System (INIS)

Jaunet, P.

2010-01-01

After Chernobyl accident in 1986, the government began to implement mechanisms to ensure the quality of measurements of environmental radioactivity and to assure the transparency of information on environmental radioactivity monitoring results. Within this context, the French National Network for the Measurement of Environmental Radioactivity (RNM), is created in 2002 under the Public Health Code. This network is developed under the auspices of ASN in collaboration with IRSN and in partnership with government departments, major nuclear licensees, health agencies and environmental protection associations. In order to centralize information on environmental radioactivity and to provide access to measurement results, a single database that includes an the results of measurements of radioactivity in the environment on the national territory is build and a new web-site www.mesure-radioactivite.fr is launched. It provides quick and easy access to this database. The quality of measurements is performed by a laboratory system through an ASN decision. Novel initiative in Europe, the French National Network for the Measurement of Environmental Radioactivity web-site gives the user keys to understand the measurement results on the radiological state of the environment. The site will be improved over the time taking into account the feedback of the users. (author)

Cognitive radio-aided wireless sensor networks for emergency response

International Nuclear Information System (INIS)

Arkoulis, Stamatios; Spanos, Dimitrios-Emmanuel; Barbounakis, Socrates; Zafeiropoulos, Anastasios; Mitrou, Nikolas

2010-01-01

A lot of research effort has been put into wireless sensor networks (WSNs) and several methods have been proposed to minimize the energy consumption and maximize the network's lifetime. However, little work has been carried out regarding WSNs deployed for emergency situations. We argue that such WSNs should function under a flexible channel allocation scheme when needed and be able to operate and adapt in dynamic, ever-changing environments coexisting with other interfering networks (IEEE 802.11b/g, 802.15.4, 802.15.1). In this paper, a simple and efficient method for the detection of a single operational frequency channel that guarantees satisfactory communication among all network nodes is proposed. Experimental measurements carried out in a real environment reveal the coexistence problem among networks in close proximity that operate in the same frequency band and prove the validity and efficiency of our approach

The National Response System: The Need to Leverage Networks and Knowledge

National Research Council Canada - National Science Library

Compagnoni, Barry A

2006-01-01

.... When viewing our national response from the perspective of network theory and knowledge management, specific gaps are identified in doctrine, organizational composition and technological capability...

Magnetic Field Response Measurement Acquisition System

Science.gov (United States)

Woodard, Stanley E.; Taylor,Bryant D.; Shams, Qamar A.; Fox, Robert L.

2007-01-01

This paper presents a measurement acquisition method that alleviates many shortcomings of traditional measurement systems. The shortcomings are a finite number of measurement channels, weight penalty associated with measurements, electrical arcing, wire degradations due to wear or chemical decay and the logistics needed to add new sensors. Wire degradation has resulted in aircraft fatalities and critical space launches being delayed. The key to this method is the use of sensors designed as passive inductor-capacitor circuits that produce magnetic field responses. The response attributes correspond to states of physical properties for which the sensors measure. Power is wirelessly provided to the sensing element by using Faraday induction. A radio frequency antenna produces a time-varying magnetic field used to power the sensor and receive the magnetic field response of the sensor. An interrogation system for discerning changes in the sensor response frequency, resistance and amplitude has been developed and is presented herein. Multiple sensors can be interrogated using this method. The method eliminates the need for a data acquisition channel dedicated to each sensor. The method does not require the sensors to be near the acquisition hardware. Methods of developing magnetic field response sensors and the influence of key parameters on measurement acquisition are discussed. Examples of magnetic field response sensors and the respective measurement characterizations are presented. Implementation of this method on an aerospace system is discussed.

Network measures for characterising team adaptation processes

NARCIS (Netherlands)

Barth, S.K.; Schraagen, J.M.C.; Schmettow, M.

2015-01-01

The aim of this study was to advance the conceptualisation of team adaptation by applying social network analysis (SNA) measures in a field study of a paediatric cardiac surgical team adapting to changes in task complexity and ongoing dynamic complexity. Forty surgical procedures were observed by

A quantitative approach to measure road network information based on edge diversity

Science.gov (United States)

Wu, Xun; Zhang, Hong; Lan, Tian; Cao, Weiwei; He, Jing

2015-12-01

The measure of map information has been one of the key issues in assessing cartographic quality and map generalization algorithms. It is also important for developing efficient approaches to transfer geospatial information. Road network is the most common linear object in real world. Approximately describe road network information will benefit road map generalization, navigation map production and urban planning. Most of current approaches focused on node diversities and supposed that all the edges are the same, which is inconsistent to real-life condition, and thus show limitations in measuring network information. As real-life traffic flow are directed and of different quantities, the original undirected vector road map was first converted to a directed topographic connectivity map. Then in consideration of preferential attachment in complex network study and rich-club phenomenon in social network, the from and to weights of each edge are assigned. The from weight of a given edge is defined as the connectivity of its end node to the sum of the connectivities of all the neighbors of the from nodes of the edge. After getting the from and to weights of each edge, edge information, node information and the whole network structure information entropies could be obtained based on information theory. The approach has been applied to several 1 square mile road network samples. Results show that information entropies based on edge diversities could successfully describe the structural differences of road networks. This approach is a complementarity to current map information measurements, and can be extended to measure other kinds of geographical objects.

A cascade reaction network mimicking the basic functional steps of acquired immune response

Science.gov (United States)

Han, Da; Wu, Cuichen; You, Mingxu; Zhang, Tao; Wan, Shuo; Chen, Tao; Qiu, Liping; Zheng, Zheng; Liang, Hao; Tan, Weihong

2015-01-01

Biological systems use complex ‘information processing cores’ composed of molecular networks to coordinate their external environment and internal states. An example of this is the acquired, or adaptive, immune system (AIS), which is composed of both humoral and cell-mediated components. Here we report the step-by-step construction of a prototype mimic of the AIS which we call Adaptive Immune Response Simulator (AIRS). DNA and enzymes are used as simple artificial analogues of the components of the AIS to create a system which responds to specific molecular stimuli in vitro. We show that this network of reactions can function in a manner which is superficially similar to the most basic responses of the vertebrate acquired immune system, including reaction sequences that mimic both humoral and cellular responses. As such, AIRS provides guidelines for the design and engineering of artificial reaction networks and molecular devices. PMID:26391084

A cascade reaction network mimicking the basic functional steps of adaptive immune response.

Science.gov (United States)

Han, Da; Wu, Cuichen; You, Mingxu; Zhang, Tao; Wan, Shuo; Chen, Tao; Qiu, Liping; Zheng, Zheng; Liang, Hao; Tan, Weihong

2015-10-01

Biological systems use complex 'information-processing cores' composed of molecular networks to coordinate their external environment and internal states. An example of this is the acquired, or adaptive, immune system (AIS), which is composed of both humoral and cell-mediated components. Here we report the step-by-step construction of a prototype mimic of the AIS that we call an adaptive immune response simulator (AIRS). DNA and enzymes are used as simple artificial analogues of the components of the AIS to create a system that responds to specific molecular stimuli in vitro. We show that this network of reactions can function in a manner that is superficially similar to the most basic responses of the vertebrate AIS, including reaction sequences that mimic both humoral and cellular responses. As such, AIRS provides guidelines for the design and engineering of artificial reaction networks and molecular devices.

Elucidation of time-dependent systems biology cell response patterns with time course network enrichment

DEFF Research Database (Denmark)

Wiwie, Christian; Rauch, Alexander; Haakonsson, Anders

2018-01-01

, no methods exist to integrate time series data with networks, thus preventing the identification of time-dependent systems biology responses. We close this gap with Time Course Network Enrichment (TiCoNE). It combines a new kind of human-augmented clustering with a novel approach to network enrichment...

Responsibility as a dimension of HIV prevention normative beliefs: measurement in three drug-using samples.

Science.gov (United States)

Ross, M W; Timpson, S C; Williams, M L; Amos, C; McCurdy, S; Bowen, A M; Kilonzo, G P

2007-03-01

The concept of responsibility was derived originally from principles of morality, as part of a network of rights, duties and obligations. HIV risk-related studies have suggested that a sense of responsibility for condom use to protect a partner is a potentially important predictor of condom use in drug-using populations. We created a four-item scale measuring Self responsibility to use condoms and Partner's responsibility to use condoms. Data were collected from three drug-using samples: crack smokers, HIV seropositive crack smokers in an intervention study in Houston, Texas, and Tanzanian heroin users in Dar es Salaam. Data indicated that the four responsibility items had high alpha coefficients in each sample, and that there were moderate to high intercorrelations between equivalent self and partner responsibility items. There were significant differences in scale scores between the crack smokers and the HIV positive crack smokers and the Tanzanian samples, but no significant differences between the HIV positive and Tanzanian samples. Comparing within the first crack-smoker sample those who were HIV positive and negative showed significant differences in the direction of higher beliefs in responsibility to use condoms in the HIV positive group. These data suggest that responsibility is measurable, holds similar psychometric properties across three samples differing in culture and HIV serostatus, and that condom use responsibility is conceptualized as a measure of general responsibility rather than as a reciprocal self/partner responsibility.

A working group for Japanese nuclear data measurement network

International Nuclear Information System (INIS)

Watanabe, Yukinobu

2013-01-01

A new working group in the Japanese Nuclear Data Committee has been established to make a cooperative network among researchers involved in nuclear data measurements and to discuss the strategy for nuclear data measurements. The working group activities are reported. (author)

Discriminating response groups in metabolic and regulatory pathway networks.

Science.gov (United States)

Van Hemert, John L; Dickerson, Julie A

2012-04-01

Analysis of omics experiments generates lists of entities (genes, metabolites, etc.) selected based on specific behavior, such as changes in response to stress or other signals. Functional interpretation of these lists often uses category enrichment tests using functional annotations like Gene Ontology terms and pathway membership. This approach does not consider the connected structure of biochemical pathways or the causal directionality of events. The Omics Response Group (ORG) method, described in this work, interprets omics lists in the context of metabolic pathway and regulatory networks using a statistical model for flow within the networks. Statistical results for all response groups are visualized in a novel Pathway Flow plot. The statistical tests are based on the Erlang distribution model under the assumption of independent and identically Exponential-distributed random walk flows through pathways. As a proof of concept, we applied our method to an Escherichia coli transcriptomics dataset where we confirmed common knowledge of the E.coli transcriptional response to Lipid A deprivation. The main response is related to osmotic stress, and we were also able to detect novel responses that are supported by the literature. We also applied our method to an Arabidopsis thaliana expression dataset from an abscisic acid study. In both cases, conventional pathway enrichment tests detected nothing, while our approach discovered biological processes beyond the original studies. We created a prototype for an interactive ORG web tool at http://ecoserver.vrac.iastate.edu/pathwayflow (source code is available from https://subversion.vrac.iastate.edu/Subversion/jlv/public/jlv/pathwayflow). The prototype is described along with additional figures and tables in Supplementary Material. julied@iastate.edu Supplementary data are available at Bioinformatics online.

Magnetic-Field-Response Measurement-Acquisition System

Science.gov (United States)

Woodward, Stanley E.; Shams, Qamar A.; Fox, Robert L.; Taylor, Bryant D.

2006-01-01

A measurement-acquisition system uses magnetic fields to power sensors and to acquire measurements from sensors. The system alleviates many shortcomings of traditional measurement-acquisition systems, which include a finite number of measurement channels, weight penalty associated with wires, use limited to a single type of measurement, wire degradation due to wear or chemical decay, and the logistics needed to add new sensors. Eliminating wiring for acquiring measurements can alleviate potential hazards associated with wires, such as damaged wires becoming ignition sources due to arcing. The sensors are designed as electrically passive inductive-capacitive or passive inductive-capacitive-resistive circuits that produce magnetic-field-responses. One or more electrical parameters (inductance, capacitance, and resistance) of each sensor can be variable and corresponds to a measured physical state of interest. The magnetic-field- response attributes (frequency, amplitude, and bandwidth) of the inductor correspond to the states of physical properties for which each sensor measures. For each sensor, the measurement-acquisition system produces a series of increasing magnetic-field harmonics within a frequency range dedicated to that sensor. For each harmonic, an antenna electrically coupled to an oscillating current (the frequency of which is that of the harmonic) produces an oscillating magnetic field. Faraday induction via the harmonic magnetic fields produces an electromotive force and therefore a current in the sensor. Once electrically active, the sensor produces its own harmonic magnetic field as the inductor stores and releases magnetic energy. The antenna of the measurement- acquisition system is switched from a transmitting to a receiving mode to acquire the magnetic-field response of the sensor. The rectified amplitude of the received response is compared to previous responses to prior transmitted harmonics, to ascertain if the measurement system has detected a

Development of Light Powered Sensor Networks for Thermal Comfort Measurement

Directory of Open Access Journals (Sweden)

Dasheng Lee

2008-10-01

Full Text Available Recent technological advances in wireless communications have enabled easy installation of sensor networks with air conditioning equipment control applications. However, the sensor node power supply, through either power lines or battery power, still presents obstacles to the distribution of the sensing systems. In this study, a novel sensor network, powered by the artificial light, was constructed to achieve wireless power transfer and wireless data communications for thermal comfort measurements. The sensing node integrates an IC-based temperature sensor, a radiation thermometer, a relative humidity sensor, a micro machined flow sensor and a microprocessor for predicting mean vote (PMV calculation. The 935 MHz band RF module was employed for the wireless data communication with a specific protocol based on a special energy beacon enabled mode capable of achieving zero power consumption during the inactive periods of the nodes. A 5W spotlight, with a dual axis tilt platform, can power the distributed nodes over a distance of up to 5 meters. A special algorithm, the maximum entropy method, was developed to estimate the sensing quantity of climate parameters if the communication module did not receive any response from the distributed nodes within a certain time limit. The light-powered sensor networks were able to gather indoor comfort-sensing index levels in good agreement with the comfort-sensing vote (CSV preferred by a human being and the experimental results within the environment suggested that the sensing system could be used in air conditioning systems to implement a comfort-optimal control strategy.

Dynamical Networks Characterization of Geomagnetic Substorms and Transient Response to the Solar Wind State.

Science.gov (United States)

Chapman, S. C.; Dods, J.; Gjerloev, J. W.

2017-12-01

Observations of how the solar wind interacts with earth's magnetosphere, and its dynamical response, are increasingly becoming a data analytics challenge. Constellations of satellites observe the solar corona, the upstream solar wind and throughout earth's magnetosphere. These data are multipoint in space and extended in time, so in principle are ideal for study using dynamical networks to characterize the full time evolving spatial pattern. We focus here on analysis of data from the full set of 100+ auroral ground based magnetometer stations that have been collated by SuperMAG. Spatio-temporal patterns of correlation between the magnetometer time series can be used to form a dynamical network [1]. The properties of the network can then be captured by (time dependent) network parameters. This offers the possibility of characterizing detailed spatio-temporal pattern by a few parameters, so that many events can then be compared [2] with each other. Whilst networks are in widespread use in the data analytics of societal and commercial data, there are additional challenges in their application to physical timeseries. Determining whether two nodes (here, ground based magnetometer stations) are connected in a network (seeing the same dynamics) requires normalization w.r.t. the detailed sensitivities and dynamical responses of specific observing stations and seasonal conductivity variations and we have developed methods to achieve this dynamical normalization. The detailed properties of the network capture time dependent spatial correlation in the magnetometer responses and we will show how this can be used to infer a transient current system response to magnetospheric activity. [l] Dods et al, J. Geophys. Res 120, doi:10.1002/2015JA02 (2015). [2] Dods et al, J. Geophys. Res. 122, doi:10.1002/2016JA02 (2017).

Designing Green Networks and Network Operations Saving Run-the-Engine Costs

CERN Document Server

Minoli, Daniel

2011-01-01

In recent years the confluence of socio-political trends toward environmental responsibility and the pressing need to reduce Run-the-Engine (RTE) costs has given birth to a nascent discipline of Green IT. A clear and concise introduction to green networks and green network operations, this book examines analytical measures and discusses virtualization, network computing, and web services as approaches for green data centers and networks. It identifies some strategies for green appliance and end devices and examines the methodical steps that can be taken over time to achieve a seamless migratio

Neural Responses to Heartbeats in the Default Network Encode the Self in Spontaneous Thoughts

Science.gov (United States)

Babo-Rebelo, Mariana; Richter, Craig G.

2016-01-01

The default network (DN) has been consistently associated with self-related cognition, but also to bodily state monitoring and autonomic regulation. We hypothesized that these two seemingly disparate functional roles of the DN are functionally coupled, in line with theories proposing that selfhood is grounded in the neural monitoring of internal organs, such as the heart. We measured with magnetoencephalograhy neural responses evoked by heartbeats while human participants freely mind-wandered. When interrupted by a visual stimulus at random intervals, participants scored the self-relatedness of the interrupted thought. They evaluated their involvement as the first-person perspective subject or agent in the thought (“I”), and on another scale to what degree they were thinking about themselves (“Me”). During the interrupted thought, neural responses to heartbeats in two regions of the DN, the ventral precuneus and the ventromedial prefrontal cortex, covaried, respectively, with the “I” and the “Me” dimensions of the self, even at the single-trial level. No covariation between self-relatedness and peripheral autonomic measures (heart rate, heart rate variability, pupil diameter, electrodermal activity, respiration rate, and phase) or alpha power was observed. Our results reveal a direct link between selfhood and neural responses to heartbeats in the DN and thus directly support theories grounding selfhood in the neural monitoring of visceral inputs. More generally, the tight functional coupling between self-related processing and cardiac monitoring observed here implies that, even in the absence of measured changes in peripheral bodily measures, physiological and cognitive functions have to be considered jointly in the DN. SIGNIFICANCE STATEMENT The default network (DN) has been consistently associated with self-processing but also with autonomic regulation. We hypothesized that these two functions could be functionally coupled in the DN, inspired by

Least-squares methods for identifying biochemical regulatory networks from noisy measurements

Directory of Open Access Journals (Sweden)

Heslop-Harrison Pat

2007-01-01

Full Text Available Abstract Background We consider the problem of identifying the dynamic interactions in biochemical networks from noisy experimental data. Typically, approaches for solving this problem make use of an estimation algorithm such as the well-known linear Least-Squares (LS estimation technique. We demonstrate that when time-series measurements are corrupted by white noise and/or drift noise, more accurate and reliable identification of network interactions can be achieved by employing an estimation algorithm known as Constrained Total Least Squares (CTLS. The Total Least Squares (TLS technique is a generalised least squares method to solve an overdetermined set of equations whose coefficients are noisy. The CTLS is a natural extension of TLS to the case where the noise components of the coefficients are correlated, as is usually the case with time-series measurements of concentrations and expression profiles in gene networks. Results The superior performance of the CTLS method in identifying network interactions is demonstrated on three examples: a genetic network containing four genes, a network describing p53 activity and mdm2 messenger RNA interactions, and a recently proposed kinetic model for interleukin (IL-6 and (IL-12b messenger RNA expression as a function of ATF3 and NF-κB promoter binding. For the first example, the CTLS significantly reduces the errors in the estimation of the Jacobian for the gene network. For the second, the CTLS reduces the errors from the measurements that are corrupted by white noise and the effect of neglected kinetics. For the third, it allows the correct identification, from noisy data, of the negative regulation of (IL-6 and (IL-12b by ATF3. Conclusion The significant improvements in performance demonstrated by the CTLS method under the wide range of conditions tested here, including different levels and types of measurement noise and different numbers of data points, suggests that its application will enable

Measuring and evaluating energy consumption in street lighting networks

International Nuclear Information System (INIS)

Janiga, P.; Gasparovsky, D.

2012-01-01

Smart metering and smart grid are incoming technologies that provide new opportunities in various fields. In connection with the issue of evaluation of the energy aspects of public lighting networks opens up the possibility of evaluating and measuring consumption. Based on the obtained values would be possible to determine energy consumption of lighting systems. This obtained value could serve as a basis for comparing the relevant networks and thus the optimality assessment of lighting designs. Currently, the measure placed in the switchboard of public lighting. If we have considered sections parametramim same lighting, it is necessary to obtain more value from the measured or determined to assess the consumption of time. Proposal of such methods is still under construction but the basic methods have already been outlined. (Authors)

Real-Time Alpine Measurement System Using Wireless Sensor Networks

Directory of Open Access Journals (Sweden)

Sami A. Malek

2017-11-01

Full Text Available Monitoring the snow pack is crucial for many stakeholders, whether for hydro-power optimization, water management or flood control. Traditional forecasting relies on regression methods, which often results in snow melt runoff predictions of low accuracy in non-average years. Existing ground-based real-time measurement systems do not cover enough physiographic variability and are mostly installed at low elevations. We present the hardware and software design of a state-of-the-art distributed Wireless Sensor Network (WSN-based autonomous measurement system with real-time remote data transmission that gathers data of snow depth, air temperature, air relative humidity, soil moisture, soil temperature, and solar radiation in physiographically representative locations. Elevation, aspect, slope and vegetation are used to select network locations, and distribute sensors throughout a given network location, since they govern snow pack variability at various scales. Three WSNs were installed in the Sierra Nevada of Northern California throughout the North Fork of the Feather River, upstream of the Oroville dam and multiple powerhouses along the river. The WSNs gathered hydrologic variables and network health statistics throughout the 2017 water year, one of northern Sierra’s wettest years on record. These networks leverage an ultra-low-power wireless technology to interconnect their components and offer recovery features, resilience to data loss due to weather and wildlife disturbances and real-time topological visualizations of the network health. Data show considerable spatial variability of snow depth, even within a 1 km 2 network location. Combined with existing systems, these WSNs can better detect precipitation timing and phase in, monitor sub-daily dynamics of infiltration and surface runoff during precipitation or snow melt, and inform hydro power managers about actual ablation and end-of-season date across the landscape.

Real-Time Alpine Measurement System Using Wireless Sensor Networks.

Science.gov (United States)

Malek, Sami A; Avanzi, Francesco; Brun-Laguna, Keoma; Maurer, Tessa; Oroza, Carlos A; Hartsough, Peter C; Watteyne, Thomas; Glaser, Steven D

2017-11-09

Monitoring the snow pack is crucial for many stakeholders, whether for hydro-power optimization, water management or flood control. Traditional forecasting relies on regression methods, which often results in snow melt runoff predictions of low accuracy in non-average years. Existing ground-based real-time measurement systems do not cover enough physiographic variability and are mostly installed at low elevations. We present the hardware and software design of a state-of-the-art distributed Wireless Sensor Network (WSN)-based autonomous measurement system with real-time remote data transmission that gathers data of snow depth, air temperature, air relative humidity, soil moisture, soil temperature, and solar radiation in physiographically representative locations. Elevation, aspect, slope and vegetation are used to select network locations, and distribute sensors throughout a given network location, since they govern snow pack variability at various scales. Three WSNs were installed in the Sierra Nevada of Northern California throughout the North Fork of the Feather River, upstream of the Oroville dam and multiple powerhouses along the river. The WSNs gathered hydrologic variables and network health statistics throughout the 2017 water year, one of northern Sierra's wettest years on record. These networks leverage an ultra-low-power wireless technology to interconnect their components and offer recovery features, resilience to data loss due to weather and wildlife disturbances and real-time topological visualizations of the network health. Data show considerable spatial variability of snow depth, even within a 1 km 2 network location. Combined with existing systems, these WSNs can better detect precipitation timing and phase in, monitor sub-daily dynamics of infiltration and surface runoff during precipitation or snow melt, and inform hydro power managers about actual ablation and end-of-season date across the landscape.

Facing a Problem of Electrical Energy Quality in Ship Networks-measurements, Estimation, Control

Institute of Scientific and Technical Information of China (English)

Tomasz Tarasiuk; Janusz Mindykowski; Xiaoyan Xu

2003-01-01

In this paper, electrical energy quality and its indices in ship electric networks are introduced, especially the meaning of electrical energy quality terms in voltage and active and reactive power distribution indices. Then methods of measurement of marine electrical energy indices are introduced in details and a microprocessor measurement-diagnosis system with the function of measurement and control is designed. Afterwards, estimation and control of electrical power quality of marine electrical power networks are introduced. And finally, according to the existing method of measurement and control of electrical power quality in ship power networks, the improvement of relative method is proposed.

Dynamic network reconstruction from gene expression data applied to immune response during bacterial infection.

Science.gov (United States)

Guthke, Reinhard; Möller, Ulrich; Hoffmann, Martin; Thies, Frank; Töpfer, Susanne

2005-04-15

The immune response to bacterial infection represents a complex network of dynamic gene and protein interactions. We present an optimized reverse engineering strategy aimed at a reconstruction of this kind of interaction networks. The proposed approach is based on both microarray data and available biological knowledge. The main kinetics of the immune response were identified by fuzzy clustering of gene expression profiles (time series). The number of clusters was optimized using various evaluation criteria. For each cluster a representative gene with a high fuzzy-membership was chosen in accordance with available physiological knowledge. Then hypothetical network structures were identified by seeking systems of ordinary differential equations, whose simulated kinetics could fit the gene expression profiles of the cluster-representative genes. For the construction of hypothetical network structures singular value decomposition (SVD) based methods and a newly introduced heuristic Network Generation Method here were compared. It turned out that the proposed novel method could find sparser networks and gave better fits to the experimental data. Reinhard.Guthke@hki-jena.de.

Energy and Power Measurements for Network Coding in the Context of Green Mobile Clouds

DEFF Research Database (Denmark)

Paramanathan, Achuthan; Pedersen, Morten Videbæk; Roetter, Daniel Enrique Lucani

2013-01-01

results for inter-session network coding in Open-Mesh routers underline that the energy invested in performing network coding pays off by dramatically reducing the total energy for the transmission of data over wireless links. We also show measurements for intra-session network coding in three different......This paper presents an in-depth power and energy measurement campaign for inter- and intra-session network coding enabled communication in mobile clouds. The measurements are carried out on different commercial platforms with focus on routers and mobile phones with different CPU capabilities. Our...

Growing complex network of citations of scientific papers: Modeling and measurements.

Science.gov (United States)

Golosovsky, Michael; Solomon, Sorin

2017-01-01

We consider the network of citations of scientific papers and use a combination of the theoretical and experimental tools to uncover microscopic details of this network growth. Namely, we develop a stochastic model of citation dynamics based on the copying-redirection-triadic closure mechanism. In a complementary and coherent way, the model accounts both for statistics of references of scientific papers and for their citation dynamics. Originating in empirical measurements, the model is cast in such a way that it can be verified quantitatively in every aspect. Such validation is performed by measuring citation dynamics of physics papers. The measurements revealed nonlinear citation dynamics, the nonlinearity being intricately related to network topology. The nonlinearity has far-reaching consequences including nonstationary citation distributions, diverging citation trajectories of similar papers, runaways or "immortal papers" with infinite citation lifetime, etc. Thus nonlinearity in complex network growth is our most important finding. In a more specific context, our results can be a basis for quantitative probabilistic prediction of citation dynamics of individual papers and of the journal impact factor.

Novel method for water vapour monitoring using wireless communication networks measurements

Science.gov (United States)

David, N.; Alpert, P.; Messer, H.

2010-09-01

We propose a new technique for monitoring near-surface water vapour, by estimating humidity from data collected through existing wireless communication networks. Weather conditions and atmospheric phenomena affect the electromagnetic channel, causing attenuations to the radio signals. Thus, wireless communication networks are in effect built-in environmental monitoring facilities. The wireless microwave links, used in these networks, are widely deployed by cellular providers for backhaul communication between base stations, a few tens of meters above ground level. As a result, if all available measurements are used, the proposed method can provide moisture observations with high spatial resolution and potentially high temporal resolution. Further, the implementation cost is minimal, since the data used are already collected and saved by the cellular operators. In addition - many of these links are installed in areas where access is difficult such as orographic terrain and complex topography. As such, our method enables measurements in places that have been hard to measure in the past, or have never been measured before. The technique is restricted to weather conditions which exclude rain, fog or clouds along the propagation path. Strong winds that may cause movement of the link transmitter or receiver (or both) may also interfere with the ability to conduct accurate measurements. We present results from real-data measurements taken from microwave links used in a backhaul cellular network that show very good correlation with surface station humidity measurements (comparisons were performed for several links, found at different locations, during different time periods, showing correlations in the range of 0.5-0.9).

Incorporating price-responsive customers in day-ahead scheduling of smart distribution networks

International Nuclear Information System (INIS)

Mazidi, Mohammadreza; Monsef, Hassan; Siano, Pierluigi

2016-01-01

Highlights: • Proposing a model for incorporating price-responsive customers in day-ahead scheduling of smart distribution networks; this model provides a win–win situation. • Introducing a risk management model based on a bi-level information-gap decision theory and recasting it into its equivalent single-level robust optimization problem using Karush–Kuhn–Tucker optimality conditions. • Utilizing mixed-integer linear programing formulation that is efficiently solved by commercial optimization software. - Abstract: Demand response and real-time pricing of electricity are key factors in a smart grid as they can increase economic efficiency and technical performances of power grids. This paper focuses on incorporating price-responsive customers in day-ahead scheduling of smart distribution networks under a dynamic pricing environment. A novel method is proposed and formulated as a tractable mixed integer linear programming optimization problem whose objective is to find hourly sale prices offered to customers, transactions (purchase/sale) with the wholesale market, commitment of distribution generation units, dispatch of battery energy storage systems and planning of interruptible loads in a way that the profit of the distribution network operator is maximized while customers’ benefit is guaranteed. To hedge distribution network operator against financial risk arising from uncertainty of wholesale market prices, a risk management model based on a bi-level information-gap decision theory is proposed. The proposed bi-level problem is solved by recasting it into its equivalent single-level robust optimization problem using Karush–Kuhn–Tucker optimality conditions. Performance of the proposed model is verified by applying it to a modified version of the IEEE 33-bus distribution test network. Numerical results demonstrate the effectiveness and efficiency of the proposed method.

Responsive and resilient supply chain network design under operational and disruption risks with delivery lead-time sensitive customers

DEFF Research Database (Denmark)

Fattahi, Mohammad; Govindan, Kannan; Keyvanshokooh, Esmaeil

2017-01-01

We address a multi-period supply chain (SC) network design where demands of customers depend on facilities serving them based on their delivery lead-times. Potential customer demands are stochastic, and facilities’ capacity varies randomly because of possible disruptions. Accordingly, we develop...... a multi-stage stochastic program, and model disruptions’ effect on facilities’ capacity. The SC responsiveness risk is limited and, to obtain a resilient network, both mitigation and contingency strategies are exploited. Computational results on a real-life case study and randomly generated problem...... instances demonstrate the model's applicability, risk-measurement policies’ performance, and the influence of mitigation and contingency strategies on SC's resiliency....

Network module detection: Affinity search technique with the multi-node topological overlap measure.

Science.gov (United States)

Li, Ai; Horvath, Steve

2009-07-20

Many clustering procedures only allow the user to input a pairwise dissimilarity or distance measure between objects. We propose a clustering method that can input a multi-point dissimilarity measure d(i1, i2, ..., iP) where the number of points P can be larger than 2. The work is motivated by gene network analysis where clusters correspond to modules of highly interconnected nodes. Here, we define modules as clusters of network nodes with high multi-node topological overlap. The topological overlap measure is a robust measure of interconnectedness which is based on shared network neighbors. In previous work, we have shown that the multi-node topological overlap measure yields biologically meaningful results when used as input of network neighborhood analysis. We adapt network neighborhood analysis for the use of module detection. We propose the Module Affinity Search Technique (MAST), which is a generalized version of the Cluster Affinity Search Technique (CAST). MAST can accommodate a multi-node dissimilarity measure. Clusters grow around user-defined or automatically chosen seeds (e.g. hub nodes). We propose both local and global cluster growth stopping rules. We use several simulations and a gene co-expression network application to argue that the MAST approach leads to biologically meaningful results. We compare MAST with hierarchical clustering and partitioning around medoid clustering. Our flexible module detection method is implemented in the MTOM software which can be downloaded from the following webpage: http://www.genetics.ucla.edu/labs/horvath/MTOM/

Measurements of Voltage Harmonics in 400 kV Transmission Network

Directory of Open Access Journals (Sweden)

Ryszard Pawełek

2014-06-01

Full Text Available The paper deals with the analysis of voltage harmonics measurements performed in the 400 kV transmission network. The voltage was measured by means of three transducers: resistive voltage divider, inductive measuring transformer and capacitive voltage measuring transformer. Instrument errors were estimated for measuring transformers with reference to the harmonic values obtained from the voltage divider.

Guest editorial - Networked collaboration, sharing and response

Directory of Open Access Journals (Sweden)

Olav Skundberg

2008-11-01

Full Text Available  This issue of Seminar.net contains three articles that were written in connection with a Norwegian e-learning conference titled “Networked collaboration, sharing and response”. The conference was held in Mars 2008 in Trondheim, and the presentations from the conference is available (in norwegian language at http://www.nvu.no. Networked collaboration was chosen as a theme because collaboration is important to achieve learning, according to the social-constructivistic pedagogy that has a strong standing in Norway, but how should this occur on the net? Sharing of content, as in digital learning resources, is a phenomenon with increasing popularity as described in the OECD-report “Giving Knowledge for Free”. But to achieve reuse of content, not only publishing it, it is important with a networked community where the plethora of information can be sorted with relevance to specific topics. Response is about guiding, coaching and tutoring. In what ways may resources and tools be used to move in the direction of solving Bloom’s two sigma problem/challenge? The first article, by Morten Flate Paulsen, shows how cooperative learning can be implemented successfully so that students have optimal individual freedom within online learning communities. The second article, by Carl F. Dons, shows how student teachers can be prepared to deal with pupils who have a wide range of experiences of the digital world. The third and last article, by Kristin Dale, is sharing experiences with multiple choice-tests to give midterm responses to students. In addition, this issue has a commentary article by Rune Krumsvik discussing the need to develop new practices for teachers and students on the background of the digital developments. The conference and articles covers three big themes. It may be difficult to find more important issues, apart from finding money and time to support its development. Olav Skundberg, guest editorAssociate professor

Identification and network-enabled characterization of auxin response factor genes in Medicago truncatula

Directory of Open Access Journals (Sweden)

David J. Burks

2016-12-01

Full Text Available The Auxin Response Factor (ARF family of transcription factors is an important regulator of environmental response and symbiotic nodulation in the legume Medicago truncatula. While previous studies have identified members of this family, a recent spurt in gene expression data coupled with genome update and reannotation calls for a reassessment of the prevalence of ARF genes and their interaction networks in M. truncatula. We performed a comprehensive analysis of the M. truncatula genome and transcriptome that entailed search for novel ARF genes and the co-expression networks. Our investigation revealed 8 novel M. truncatula ARF (MtARF genes, of the total 22 identified, and uncovered novel gene co-expression networks as well. Furthermore, the topological clustering and single enrichment analysis of several network models revealed the roles of individual members of the MtARF family in nitrogen regulation, nodule initiation, and post-embryonic development through a specialized protein packaging and secretory pathway. In summary, this study not just shines new light on an important gene family, but also provides a guideline for identification of new members of gene families and their functional characterization through network analyses.

A NOVEL PIPELINE FOR DRUG DISCOVERY IN NEUROPSYCHIATRIC DISORDERS USING HIGH-CONTENT SINGLE-CELL SCREENING OF SIGNALLING NETWORK RESPONSES EX VIVO

OpenAIRE

Lago Cooke, Santiago Guillermo

2016-01-01

The current work entails the development of a novel high content platform for the measurement of kinetic ligand responses across cell signalling networks at the single-cell level in distinct PBMC subtypes ex vivo. Using automated sample preparation, fluorescent cellular barcoding and flow cytometry the platform is capable of detecting 21, 840 parallel cell signalling responses in each PBMC sample. We apply this platform to characterize the effects of neuropsychiatric treatments and CNS ligand...

Identification of PEG-induced water stress responsive transcripts using co-expression network in Eucalyptus grandis.

Science.gov (United States)

Ghosh Dasgupta, Modhumita; Dharanishanthi, Veeramuthu

2017-09-05

Ecophysiological studies in Eucalyptus have shown that water is the principal factor limiting stem growth. Effect of water deficit conditions on physiological and biochemical parameters has been extensively reported in Eucalyptus. The present study was conducted to identify major polyethylene glycol induced water stress responsive transcripts in Eucalyptus grandis using gene co-expression network. A customized array representing 3359 water stress responsive genes was designed to document their expression in leaves of E. grandis cuttings subjected to -0.225MPa of PEG treatment. The differentially expressed transcripts were documented and significantly co-expressed transcripts were used for construction of network. The co-expression network was constructed with 915 nodes and 3454 edges with degree ranging from 2 to 45. Ninety four GO categories and 117 functional pathways were identified in the network. MCODE analysis generated 27 modules and module 6 with 479 nodes and 1005 edges was identified as the biologically relevant network. The major water responsive transcripts represented in the module included dehydrin, osmotin, LEA protein, expansin, arabinogalactans, heat shock proteins, major facilitator proteins, ARM repeat proteins, raffinose synthase, tonoplast intrinsic protein and transcription factors like DREB2A, ARF9, AGL24, UNE12, WLIM1 and MYB66, MYB70, MYB 55, MYB 16 and MYB 103. The coordinated analysis of gene expression patterns and coexpression networks developed in this study identified an array of transcripts that may regulate PEG induced water stress responses in E. grandis. Copyright © 2017 Elsevier B.V. All rights reserved.

Networks and learning: communities, practices and the metaphor of networks–a response

Directory of Open Access Journals (Sweden)

Chris Jones

2004-12-01

Full Text Available I am pleased to have the opportunity to react to Bruce Ingraham's response to my article ‘Networks and learning: communities, practices and the metaphor of networks' (Jones, 2004. It is rare to have a dialogue with someone who has taken the time and trouble to consider what you have written for a journal. All too often reviewing is a one-way process with the reviewer remaining anonymous. It is all the more pleasant to have a response to what you have written that gets to grips with some of the issues that the author also finds troubling. It is in that spirit that I write this reaction to Ingraham; it is an opportunity for me to develop some of the points he has identified as problematic in the original article. I want to concentrate on two main issues, firstly the network metaphor itself and secondly the usefulness of abstraction and representations of various types.

Measuring dynamic process of working memory training with functional brain networks

Directory of Open Access Journals (Sweden)

Hong Wang

2015-12-01

Full Text Available In this paper, we proposed the functional brain networks and graphic theory method to measure the effect of working memory training on the neural activities. 12 subjects were recruited in this study, and they did the same working memory task before they had been trained and after training. We architected functional brain networks based on EEG coherence and calculated properties of brain networks to measure the neural co-activities and the working memory level of subjects. As the result, the internal connections in frontal region decreased after working memory training, but the connection between frontal region and top region increased. And the more small-world feature was observed after training. The features observed above were in alpha (8-13 Hz and beta (13-30 Hz bands. The functional brain networks based on EEG coherence proposed in this paper can be used as the indicator of working memory level.

Reactor building indoor wireless network channel quality estimation using RSSI measurement of wireless sensor network

International Nuclear Information System (INIS)

Merat, S.

2008-01-01

Expanding wireless communication network reception inside reactor buildings (RB) and service wings (SW) has always been a technical challenge for operations service team. This is driven by the volume of metal equipment inside the Reactor Buildings (RB) that blocks and somehow shields the signal throughout the link. In this study, to improve wireless reception inside the Reactor Building (RB), an experimental model using indoor localization mesh based on IEEE 802.15 is developed to implement a wireless sensor network. This experimental model estimates the distance between different nodes by measuring the RSSI (Received Signal Strength Indicator). Then by using triangulation and RSSI measurement, the validity of the estimation techniques is verified to simulate the physical environmental obstacles, which block the signal transmission. (author)

Reactor building indoor wireless network channel quality estimation using RSSI measurement of wireless sensor network

Energy Technology Data Exchange (ETDEWEB)

Merat, S. [Wardrop Engineering Inc., Toronto, Ontario (Canada)

2008-07-01

Expanding wireless communication network reception inside reactor buildings (RB) and service wings (SW) has always been a technical challenge for operations service team. This is driven by the volume of metal equipment inside the Reactor Buildings (RB) that blocks and somehow shields the signal throughout the link. In this study, to improve wireless reception inside the Reactor Building (RB), an experimental model using indoor localization mesh based on IEEE 802.15 is developed to implement a wireless sensor network. This experimental model estimates the distance between different nodes by measuring the RSSI (Received Signal Strength Indicator). Then by using triangulation and RSSI measurement, the validity of the estimation techniques is verified to simulate the physical environmental obstacles, which block the signal transmission. (author)

VPN (Virtual Private Network) Performance Measurements

Energy Technology Data Exchange (ETDEWEB)

Calderon, Calixto; Goncalves, Joao G.M.; Sequeira, Vitor [Joint Research Centre, Ispra (Italy). Inst. for the Protection and Security of the Citizen; Vandaele, Roland; Meylemans, Paul [European Commission, DG-TREN (Luxembourg)

2003-05-01

Virtual Private Networks (VPN) is an important technology allowing for secure communications through insecure transmission media (i.e., Internet) by adding authentication and encryption to the existing protocols. This paper describes some VPN performance indicators measured over international communication links. An ISDN based VPN link was established between the Joint Research Centre, Ispra site, Italy, and EURATOM Safeguards in Luxembourg. This link connected two EURATOM Safeguards FAST surveillance stations, and used different vendor solutions hardware (Cisco router 1720 and Nokia CC-500 Gateway). To authenticate and secure this international link, we have used several methods at the different levels of the seven-layered ISO network protocol stack (i.e., Callback feature, CHAP - Challenge Handshake Protocol - authentication protocol). The tests made involved the use of different encryption algorithms and the way session secret keys are periodically renewed, considering these elements influence significantly the transmission throughput. Future tests will include the use of a wide variety of wireless media transmission and terminal equipment technologies, in particular PDAs (Personal Digital Assistants) and Notebook PCs. These tests aim at characterising the functionality of VPNs whenever field inspectors wish to contact headquarters to access information from a central archive database or transmit local measurements or documents. These technologies cover wireless transmission needs at different geographical scales: roombased level Bluetooth, floor or building level Wi-Fi and region or country level GPRS.

Altered Behavioral and Autonomic Pain Responses in Alzheimer’s Disease Are Associated with Dysfunctional Affective, Self-Reflective and Salience Network Resting-State Connectivity

Directory of Open Access Journals (Sweden)

Paul A. Beach

2017-09-01

Full Text Available While pain behaviors are increased in Alzheimer’s disease (AD patients compared to healthy seniors (HS across multiple disease stages, autonomic responses are reduced with advancing AD. To better understand the neural mechanisms underlying these phenomena, we undertook a controlled cross-sectional study examining behavioral (Pain Assessment in Advanced Dementia, PAINAD scores and autonomic (heart rate, HR pain responses in 24 HS and 20 AD subjects using acute pressure stimuli. Resting-state fMRI was utilized to investigate how group connectivity differences were related to altered pain responses. Pain behaviors (slope of PAINAD score change and mean PAINAD score were increased in patients vs. controls. Autonomic measures (HR change intercept and mean HR change were reduced in severe vs. mildly affected AD patients. Group functional connectivity differences associated with greater pain behavior reactivity in patients included: connectivity within a temporal limbic network (TLN and between the TLN and ventromedial prefrontal cortex (vmPFC; between default mode network (DMN subcomponents; between the DMN and ventral salience network (vSN. Reduced HR responses within the AD group were associated with connectivity changes within the DMN and vSN—specifically the precuneus and vmPFC. Discriminant classification indicated HR-related connectivity within the vSN to the vmPFC best distinguished AD severity. Thus, altered behavioral and autonomic pain responses in AD reflects dysfunction of networks and structures subserving affective, self-reflective, salience and autonomic regulation.

Repeated exposure to media violence is associated with diminished response in an inhibitory frontolimbic network.

Directory of Open Access Journals (Sweden)

Christopher R Kelly

Full Text Available BACKGROUND: Media depictions of violence, although often claimed to induce viewer aggression, have not been shown to affect the cortical networks that regulate behavior. METHODOLOGY/PRINCIPAL FINDINGS: Using functional magnetic resonance imaging (fMRI, we found that repeated exposure to violent media, but not to other equally arousing media, led to both diminished response in right lateral orbitofrontal cortex (right ltOFC and a decrease in right ltOFC-amygdala interaction. Reduced function in this network has been previously associated with decreased control over a variety of behaviors, including reactive aggression. Indeed, we found reduced right ltOFC responses to be characteristic of those subjects that reported greater tendencies toward reactive aggression. Furthermore, the violence-induced reduction in right ltOFC response coincided with increased throughput to behavior planning regions. CONCLUSIONS: These novel findings establish that even short-term exposure to violent media can result in diminished responsiveness of a network associated with behaviors such as reactive aggression.

Snapshot of iron response in Shewanella oneidensis by gene network reconstruction

Energy Technology Data Exchange (ETDEWEB)

Yang, Yunfeng; Harris, Daniel P.; Luo, Feng; Xiong, Wenlu; Joachimiak, Marcin; Wu, Liyou; Dehal, Paramvir; Jacobsen, Janet; Yang, Zamin; Palumbo, Anthony V.; Arkin, Adam P.; Zhou, Jizhong

2008-10-09

Background: Iron homeostasis of Shewanella oneidensis, a gamma-proteobacterium possessing high iron content, is regulated by a global transcription factor Fur. However, knowledge is incomplete about other biological pathways that respond to changes in iron concentration, as well as details of the responses. In this work, we integrate physiological, transcriptomics and genetic approaches to delineate the iron response of S. oneidensis. Results: We show that the iron response in S. oneidensis is a rapid process. Temporal gene expression profiles were examined for iron depletion and repletion, and a gene co-expression network was reconstructed. Modules of iron acquisition systems, anaerobic energy metabolism and protein degradation were the most noteworthy in the gene network. Bioinformatics analyses suggested that genes in each of the modules might be regulated by DNA-binding proteins Fur, CRP and RpoH, respectively. Closer inspection of these modules revealed a transcriptional regulator (SO2426) involved in iron acquisition and ten transcriptional factors involved in anaerobic energy metabolism. Selected genes in the network were analyzed by genetic studies. Disruption of genes encoding a putative alcaligin biosynthesis protein (SO3032) and a gene previously implicated in protein degradation (SO2017) led to severe growth deficiency under iron depletion conditions. Disruption of a novel transcriptional factor (SO1415) caused deficiency in both anaerobic iron reduction and growth with thiosulfate or TMAO as an electronic acceptor, suggesting that SO1415 is required for specific branches of anaerobic energy metabolism pathways. Conclusions: Using a reconstructed gene network, we identified major biological pathways that were differentially expressed during iron depletion and repletion. Genetic studies not only demonstrated the importance of iron acquisition and protein degradation for iron depletion, but also characterized a novel transcriptional factor (SO1415) with a

Physical and Radiological Characterisation of Measuring Sites Within The Croatian Gamma Dose Rate Early Warning Network

International Nuclear Information System (INIS)

Cindro, M.; Stepisnik, M.; Pinezic, D.; Sinka, D.; Skanata, D.

2016-01-01

The work described in this paper was done within the EU funded project 'Upgrading the systems for the on- and off-line monitoring of radioactivity in the environment in Croatia in regular and emergency situations'. The existing system of early warning in case of nuclear accident in Croatia (SPUNN), managed by the State Office for Radiological and Nuclear Safety, includes 33 stations for measuring ambient gamma dose rate (GDR). The aim of the project was to determine appropriate correction factors that will allow the results from this network to be used not only for timely warning in case of nuclear accident but also in routine environmental monitoring to determine the background radiation. Additionally, in the case of fresh deposition due to radioactive contamination, the corrected values are better suited to be used as an input for support systems for decision making in the case of emergency (such as RODOS), as well as for international data exchange (EURDEP) or automatic interpolation and mapping of radiological data (INTAMAP). The response of the individual probes to natural or accidental radiation mostly depends on the geometry or topography, surrounding buildings, vegetation (trees) and the type of soil beneath the detector. In the case of measuring the dose rate, objects such as buildings act as a shield against gamma radiation and limit the field of vision of the detector. If we want to have representative values that can be compared with other measuring sites, it is clear that we need to define standard conditions that each location has to meet. This is true not only for the probes within the same network, but can also be applied more broadly, at the international level, since data exchange mechanisms for GDR data already exist across Europe. The response of each probe is not determined only by the physical features, it is also important to understand the radiological characteristics of the site. Radiological characterization was performed through

Measurement campaign on connectivity of mesh networks formed by mobile devices

DEFF Research Database (Denmark)

Pietrarca, Beatrice; Sasso, Giovanni; Perrucci, Gian Paolo

2007-01-01

This paper reports the results of a measurement campaign on the connectivity level of mobile devices using Bluetooth (BT) to form cooperative mobile mesh networks. Such mobile mesh networks composed of mobile devices are the basis for any peer-to-peer communication like wireless grids or social...

A Neural Network Approach to Fluid Quantity Measurement in Dynamic Environments

CERN Document Server

Terzic, Edin; Nagarajah, Romesh; Alamgir, Muhammad

2012-01-01

Sloshing causes liquid to fluctuate, making accurate level readings difficult to obtain in dynamic environments. The measurement system described uses a single-tube capacitive sensor to obtain an instantaneous level reading of the fluid surface, thereby accurately determining the fluid quantity in the presence of slosh. A neural network based classification technique has been applied to predict the actual quantity of the fluid contained in a tank under sloshing conditions.   In A neural network approach to fluid quantity measurement in dynamic environments, effects of temperature variations and contamination on the capacitive sensor are discussed, and the authors propose that these effects can also be eliminated with the proposed neural network based classification system. To examine the performance of the classification system, many field trials were carried out on a running vehicle at various tank volume levels that range from 5 L to 50 L. The effectiveness of signal enhancement on the neural network base...

An approach to unfold the response of a multi-element system using an artificial neural network

International Nuclear Information System (INIS)

Cordes, E.; Fehrenbacher, G.; Schuetz, R.; Sprunck, M.; Hahn, K.; Hofmann, R.; Wahl, W.

1998-01-01

An unfolding procedure is proposed which aims at obtaining spectral information of a neutron radiation field by the analysis of the response of a multi-element system consisting of converter type semiconductors. For the unfolding procedure an artificial neural network (feed forward network), trained by the back-propagation method, was used. The response functions of the single elements to neutron radiation were calculated by application of a computational model for an energy range from 10 -2 eV to 10 MeV. The training of the artificial neural network was based on the computation of responses of a six-element system for a set of 300 neutron spectra and the application of the back-propagation method. The validation was performed by the unfolding of 100 computed responses. Two unfolding examples were pointed out for the determination of the neutron spectra. The spectra resulting from the unfolding procedure agree well with the original spectra used for the response computation

Response of moose to a high‐density road network

Science.gov (United States)

Wattles, David W.; Zeller, Katherine A.; DeStefano, Stephen

2018-01-01

Road networks and the disturbance associated with vehicle traffic alter animal behavior, movements, and habitat selection. The response of moose (Alces americanus) to roads has been documented in relatively rural areas, but less is known about moose response to roads in more highly roaded landscapes. We examined road‐crossing frequencies and habitat use of global positioning system (GPS)‐collared moose in Massachusetts, USA, where moose home ranges have road densities approximately twice that of previous studies. We compared seasonal road‐crossing frequencies of moose with a null movement model. We estimated moose travel speeds during road‐crossing events and compared them with speeds during other home range movements. To estimate the extent of the road effect zone and determine how roads influenced moose habitat use, we fit a third‐order resource selection function. With the exception of the lowest use road class (roads less than expected based on the null movement model and frequency decreased with increasing road size and traffic. Moose crossed roads faster than they traveled during other times. This effect increased with increasing road use intensity. Overall, roads were a major factor determining what portions of Massachusetts moose used and how they moved among habitat patches. Our results suggest that moose in Massachusetts can adapt to a high‐density road network, but the road effect is still strongly negative and, in some cases, is more pronounced than in study areas with lower road densities. Future road construction and the expansion of road networks may have a large effect on moose and other wildlife.

Measuring large-scale social networks with high resolution.

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Arkadiusz Stopczynski

Full Text Available This paper describes the deployment of a large-scale study designed to measure human interactions across a variety of communication channels, with high temporal resolution and spanning multiple years-the Copenhagen Networks Study. Specifically, we collect data on face-to-face interactions, telecommunication, social networks, location, and background information (personality, demographics, health, politics for a densely connected population of 1000 individuals, using state-of-the-art smartphones as social sensors. Here we provide an overview of the related work and describe the motivation and research agenda driving the study. Additionally, the paper details the data-types measured, and the technical infrastructure in terms of both backend and phone software, as well as an outline of the deployment procedures. We document the participant privacy procedures and their underlying principles. The paper is concluded with early results from data analysis, illustrating the importance of multi-channel high-resolution approach to data collection.

Measurement of traffic network vulnerability for Mississippi coastal region : final research report.

Science.gov (United States)

2017-08-15

Natural disasters such as a hurricane can cause great damages to the transportation networks and significantly affect the evacuation trip operations. An accurate understanding and measurement of the network vulnerability can enhance the evacuees p...

Comparison of functional network connectivity for passive-listening and active-response narrative comprehension in adolescents.

Science.gov (United States)

Wang, Yingying; Holland, Scott K

2014-05-01

Comprehension of narrative stories plays an important role in the development of language skills. In this study, we compared brain activity elicited by a passive-listening version and an active-response (AR) version of a narrative comprehension task by using independent component (IC) analysis on functional magnetic resonance imaging data from 21 adolescents (ages 14-18 years). Furthermore, we explored differences in functional network connectivity engaged by two versions of the task and investigated the relationship between the online response time and the strength of connectivity between each pair of ICs. Despite similar brain region involvements in auditory, temporoparietal, and frontoparietal language networks for both versions, the AR version engages some additional network elements including the left dorsolateral prefrontal, anterior cingulate, and sensorimotor networks. These additional involvements are likely associated with working memory and maintenance of attention, which can be attributed to the differences in cognitive strategic aspects of the two versions. We found significant positive correlation between the online response time and the strength of connectivity between an IC in left inferior frontal region and an IC in sensorimotor region. An explanation for this finding is that longer reaction time indicates stronger connection between the frontal and sensorimotor networks caused by increased activation in adolescents who require more effort to complete the task.

Talking and learning physics: Predicting future grades from network measures and Force Concept Inventory pretest scores

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Jesper Bruun

2013-07-01

Full Text Available The role of student interactions in learning situations is a foundation of sociocultural learning theory, and social network analysis can be used to quantify student relations. We discuss how self-reported student interactions can be viewed as processes of meaning making and use this to understand how quantitative measures that describe the position in a network, called centrality measures, can be understood in terms of interactions that happen in the context of a university physics course. We apply this discussion to an empirical data set of self-reported student interactions. In a weekly administered survey, first year university students enrolled in an introductory physics course at a Danish university indicated with whom they remembered having communicated within different interaction categories. For three categories pertaining to (1 communication about how to solve physics problems in the course (called the PS category, (2 communications about the nature of physics concepts (called the CD category, and (3 social interactions that are not strictly related to the content of the physics classes (called the ICS category in the introductory mechanics course, we use the survey data to create networks of student interaction. For each of these networks, we calculate centrality measures for each student and correlate these measures with grades from the introductory course, grades from two subsequent courses, and the pretest Force Concept Inventory (FCI scores. We find highly significant correlations (p<0.001 between network centrality measures and grades in all networks. We find the highest correlations between network centrality measures and future grades. In the network composed of interactions regarding problem solving (the PS network, the centrality measures hide and PageRank show the highest correlations (r=-0.32 and r=0.33, respectively with future grades. In the CD network, the network measure target entropy shows the highest correlation

Accessibility in networks: A useful measure for understanding social insect nest architecture

International Nuclear Information System (INIS)

Viana, Matheus P.; Fourcassié, Vincent; Perna, Andrea; Costa, Luciano da F.; Jost, Christian

2013-01-01

Networks and the associated tools from graph theory have now become well-established approaches to study natural as well as human-made systems. While early studies focused on topology and connectivity, the recent literature has acknowledged the importance of the dynamical properties of these networks. Here we focus on such a dynamic measure: accessibility. It characterizes for any given movement dynamics (such as random walks) the average number of nodes that can be reached in exactly h steps (out-accessibility), or the average number of nodes from which a given node can be reached (in-accessibility). This focus on dynamics makes accessibility particularly appropriate to study movement on networks and to detect complementary properties with respect to topology-based measurements such as betweenness centrality. We apply this measure to six nests of Cubitermes termites. Their mushroom-like 3D architectures consist of chambers and connecting tunnels that can be associated to nodes and edges in a communication network. Accessibilities turn out to be particularly low in the bottom part of the nests that link them to their underground tunneling network. We interpret this result in the context of anti-predator (ants) behavior and/or as a side effect of the global nest shape.

Prediction of Force Measurements of a Microbend Sensor Based on an Artificial Neural Network

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Kemal Fidanboylu

2009-09-01

Full Text Available Artificial neural network (ANN based prediction of the response of a microbend fiber optic sensor is presented. To the best of our knowledge no similar work has been previously reported in the literature. Parallel corrugated plates with three deformation cycles, 6 mm thickness of the spacer material and 16 mm mechanical periodicity between deformations were used in the microbend sensor. Multilayer Perceptron (MLP with different training algorithms, Radial Basis Function (RBF network and General Regression Neural Network (GRNN are used as ANN models in this work. All of these models can predict the sensor responses with considerable errors. RBF has the best performance with the smallest mean square error (MSE values of training and test results. Among the MLP algorithms and GRNN the Levenberg-Marquardt algorithm has good results. These models successfully predict the sensor responses, hence ANNs can be used as useful tool in the design of more robust fiber optic sensors.

Cortical Network Models of Firing Rates in the Resting and Active States Predict BOLD Responses.

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Maxwell R Bennett

Full Text Available Measurements of blood oxygenation level dependent (BOLD signals have produced some surprising observations. One is that their amplitude is proportional to the entire activity in a region of interest and not just the fluctuations in this activity. Another is that during sleep and anesthesia the average BOLD correlations between regions of interest decline as the activity declines. Mechanistic explanations of these phenomena are described here using a cortical network model consisting of modules with excitatory and inhibitory neurons, taken as regions of cortical interest, each receiving excitatory inputs from outside the network, taken as subcortical driving inputs in addition to extrinsic (intermodular connections, such as provided by associational fibers. The model shows that the standard deviation of the firing rate is proportional to the mean frequency of the firing when the extrinsic connections are decreased, so that the mean BOLD signal is proportional to both as is observed experimentally. The model also shows that if these extrinsic connections are decreased or the frequency of firing reaching the network from the subcortical driving inputs is decreased, or both decline, there is a decrease in the mean firing rate in the modules accompanied by decreases in the mean BOLD correlations between the modules, consistent with the observed changes during NREM sleep and under anesthesia. Finally, the model explains why a transient increase in the BOLD signal in a cortical area, due to a transient subcortical input, gives rises to responses throughout the cortex as observed, with these responses mediated by the extrinsic (intermodular connections.

Information theory perspective on network robustness

International Nuclear Information System (INIS)

Schieber, Tiago A.; Carpi, Laura; Frery, Alejandro C.; Rosso, Osvaldo A.; Pardalos, Panos M.; Ravetti, Martín G.

2016-01-01

A crucial challenge in network theory is the study of the robustness of a network when facing a sequence of failures. In this work, we propose a dynamical definition of network robustness based on Information Theory, that considers measurements of the structural changes caused by failures of the network's components. Failures are defined here as a temporal process defined in a sequence. Robustness is then evaluated by measuring dissimilarities between topologies after each time step of the sequence, providing a dynamical information about the topological damage. We thoroughly analyze the efficiency of the method in capturing small perturbations by considering different probability distributions on networks. In particular, we find that distributions based on distances are more consistent in capturing network structural deviations, as better reflect the consequences of the failures. Theoretical examples and real networks are used to study the performance of this methodology. - Highlights: • A novel methodology to measure the robustness of a network to component failure or targeted attacks is proposed. • The use of the network's distance PDF allows a precise analysis. • The method provides a dynamic robustness profile showing the response of the topology to each failure event. • The measure is capable to detect network's critical elements.

The grand illusion? corporate social responsibility in global garment production networks

OpenAIRE

Starmanns, M

2010-01-01

This PhD aims to generate a better understanding of corporate social responsibility (CSR) in global production networks. CSR is an umbrella term that deals with voluntary activities undertaken by companies and that indicate an ethos to act responsibly in society. This research focuses on CSR practices that aim towards improving working conditions in outsourced production factories by implementing so-called social standards, which often derive from core norms of the International Labour Organi...

A large scale analysis of information-theoretic network complexity measures using chemical structures.

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Matthias Dehmer

Full Text Available This paper aims to investigate information-theoretic network complexity measures which have already been intensely used in mathematical- and medicinal chemistry including drug design. Numerous such measures have been developed so far but many of them lack a meaningful interpretation, e.g., we want to examine which kind of structural information they detect. Therefore, our main contribution is to shed light on the relatedness between some selected information measures for graphs by performing a large scale analysis using chemical networks. Starting from several sets containing real and synthetic chemical structures represented by graphs, we study the relatedness between a classical (partition-based complexity measure called the topological information content of a graph and some others inferred by a different paradigm leading to partition-independent measures. Moreover, we evaluate the uniqueness of network complexity measures numerically. Generally, a high uniqueness is an important and desirable property when designing novel topological descriptors having the potential to be applied to large chemical databases.

Rapid-response Sensor Networks Leveraging Open Standards and the Internet of Things

Science.gov (United States)

Bermudez, L. E.; Lieberman, J. E.; Lewis, L.; Botts, M.; Liang, S.

2016-12-01

New sensor technologies provide an unparalleled capability to collect large numbers of diverse observations about the world around us. Networks of such sensors are especially effective for capturing and analyzing unexpected, fast moving events if they can be deployed with a minimum of time, effort, and cost. A rapid-response sensing and processing capability is extremely important in quickly unfolding events not only to collect data for future research.but also to support response efforts that may be needed by providing up-to-date knowledge of the situation. A recent pilot activity coordinated by the Open Geospatial Consortium combined Sensor Web Enablement (SWE) standards with Internet of Things (IoT) practices to understand better how to set up rapid-response sensor networks in comparable event situations involving accidents or disasters. The networks included weather and environmental sensors, georeferenced UAV and PTZ imagery collectors, and observations from "citizen sensors", as well as virtual observations generated by predictive models. A key feature of each "SWE-IoT" network was one or more Sensor Hubs that connected local, often proprietary sensor device protocols to a common set of standard SWE data types and standard Web interfaces on an IP-based internetwork. This IoT approach provided direct, common, interoperable access to all sensor readings from anywhere on the internetwork of sensors, Hubs, and applications. Sensor Hubs also supported an automated discovery protocol in which activated Hubs registered themselves with a canonical catalog service. As each sensor (wireless or wired) was activated within range of an authorized Hub, it registered itself with that Hub, which in turn registered the sensor and its capabilities with the catalog. Sensor Hub functions were implemented in a range of component types, from personal devices such as smartphones and Raspberry Pi's to full cloud-based sensor services platforms. Connected into a network

How prepared are we? : The organizational network responses in two infectious disease outbreak scenarios in the Netherlands

NARCIS (Netherlands)

Kenis, P.N.; Raab, J.; Kraaij – Dirkzwager, Marleen; Timen, A.

2017-01-01

The paper will report results of a research project on the organizational network response to prevent or contain an outbreak of an infectious disease in the Netherlands. The paper is one of the first to present an attempt to conduct an ex ante evaluation of a response network in a likely future

Optical track width measurements below 100 nm using artificial neural networks

Science.gov (United States)

Smith, R. J.; See, C. W.; Somekh, M. G.; Yacoot, A.; Choi, E.

2005-12-01

This paper discusses the feasibility of using artificial neural networks (ANNs), together with a high precision scanning optical profiler, to measure very fine track widths that are considerably below the conventional diffraction limit of a conventional optical microscope. The ANN is trained using optical profiles obtained from tracks of known widths, the network is then assessed by applying it to test profiles. The optical profiler is an ultra-stable common path scanning interferometer, which provides extremely precise surface measurements. Preliminary results, obtained with a 0.3 NA objective lens and a laser wavelength of 633 nm, show that the system is capable of measuring a 50 nm track width, with a standard deviation less than 4 nm.

Use of artificial neural networks on optical track width measurements

Science.gov (United States)

Smith, Richard J.; See, Chung W.; Somekh, Mike G.; Yacoot, Andrew

2007-08-01

We have demonstrated recently that, by using an ultrastable optical interferometer together with artificial neural networks (ANNs), track widths down to 60 nm can be measured with a 0.3 NA objective lens. We investigate the effective conditions for training ANNs. Experimental results will be used to show the characteristics of the training samples and the data format of the ANN inputs required to produce suitably trained ANNs. Results obtained with networks measuring double tracks, and classifying different structures, will be presented to illustrate the capability of the technique. We include a discussion on expansion of the application areas of the system, allowing it to be used as a general purpose instrument.

Measuring Social Capital in Virtual Social Networks; Introducing Workable Indices

Directory of Open Access Journals (Sweden)

Hamid Abdollahian

2013-12-01

Full Text Available This paper will attempt to offer a set of indicators that together construct a model which will help to measure social capital among users of social networks. The world is now experiencing some new changes that are affecting conceptual equations in social sciences, two of which are of our concern here: 1- the concept of social capital that has opened its way into epistemological basis of social sciences, and; 2- the world has welcomed the birth and development of social networks in our daily life, affecting many aspects of social actions. There is Facebook from among a handful of social networks that has reached the threshold of international networking capacity with roughly one billion users. We will use Robert Putnam's theory of social capital alongside Frank's methodological innovation regarding measuring tools of social capital in order to create a marriage between these two as well as to address a yet more problematizing issue, i.e., how to measure social capital of the Facebook users. Accordingly the paper will focus on Facebook as the field of research and will introduce triangulation approach that we used in order to come up with the set of indicators. Participatory observation and online survey were used as constructing elements of triangulation approach so to generate the necessary data for the above purpose. At first, we used participatory observation through which 14 targeted samples were selected and whatever they had in their profile in Facebook were collected and analyzed. This analysis helped us to construct our questionnaire which was launched through Google docs. In the end, some 218 respondent returned their completed questionnaires. The final stage of analysis consisted of finding out how we can use the results to offer a new tool for measuring social capital of Facebook users. The research findings indicated that there are 10 indicators which should be put together if social capital is to be properly measured.

Design and Development of a Pressure Transmitter Using Modified Inductance Measuring Network and Bellow Sensor

OpenAIRE

Venkata Lakshmi Narayana K.; Bhujanga Rao A.

2013-01-01

In this paper, a pressure transmitter using a modified op-amp based network for inductance measurement using a bellow as sensor has been proposed to measure the pressure and to convert pressure changes in to an electrical current which can be transmitted to a remote indicator. The change in inductance due to change in pressure is measured by an improved modified operational amplifier based network. The proposed network permits offset inductance compensation of sensing coil and also minimizes ...

Analysis on the dynamic error for optoelectronic scanning coordinate measurement network

Science.gov (United States)

Shi, Shendong; Yang, Linghui; Lin, Jiarui; Guo, Siyang; Ren, Yongjie

2018-01-01

Large-scale dynamic three-dimension coordinate measurement technique is eagerly demanded in equipment manufacturing. Noted for advantages of high accuracy, scale expandability and multitask parallel measurement, optoelectronic scanning measurement network has got close attention. It is widely used in large components jointing, spacecraft rendezvous and docking simulation, digital shipbuilding and automated guided vehicle navigation. At present, most research about optoelectronic scanning measurement network is focused on static measurement capacity and research about dynamic accuracy is insufficient. Limited by the measurement principle, the dynamic error is non-negligible and restricts the application. The workshop measurement and positioning system is a representative which can realize dynamic measurement function in theory. In this paper we conduct deep research on dynamic error resources and divide them two parts: phase error and synchronization error. Dynamic error model is constructed. Based on the theory above, simulation about dynamic error is carried out. Dynamic error is quantized and the rule of volatility and periodicity has been found. Dynamic error characteristics are shown in detail. The research result lays foundation for further accuracy improvement.

Recurrence network measures for hypothesis testing using surrogate data: Application to black hole light curves

Science.gov (United States)

Jacob, Rinku; Harikrishnan, K. P.; Misra, R.; Ambika, G.

2018-01-01

Recurrence networks and the associated statistical measures have become important tools in the analysis of time series data. In this work, we test how effective the recurrence network measures are in analyzing real world data involving two main types of noise, white noise and colored noise. We use two prominent network measures as discriminating statistic for hypothesis testing using surrogate data for a specific null hypothesis that the data is derived from a linear stochastic process. We show that the characteristic path length is especially efficient as a discriminating measure with the conclusions reasonably accurate even with limited number of data points in the time series. We also highlight an additional advantage of the network approach in identifying the dimensionality of the system underlying the time series through a convergence measure derived from the probability distribution of the local clustering coefficients. As examples of real world data, we use the light curves from a prominent black hole system and show that a combined analysis using three primary network measures can provide vital information regarding the nature of temporal variability of light curves from different spectroscopic classes.

Measuring Asymmetry in Insect-Plant Networks

Energy Technology Data Exchange (ETDEWEB)

Cruz, Claudia P T [Programa de Pos-Graduacao em Fisica, Universidade Federal do Rio Grande do Norte, UFRN - Campus Universitario, Lagoa Nova, CEP 59078 972, Natal, RN (Brazil); De Almeida, Adriana M [Departamento de Botanica, Ecologia e Zoologia, Centro de Biociencias, Universidade Federal do Rio Grande do Norte, UFRN - Campus Universitario, Lagoa Nova, CEP 59078 972, Natal, RN (Brazil); Corso, Gilberto, E-mail: claudia@dfte.ufrn.br, E-mail: adrianam@ufrn.br, E-mail: corso@cb.ufrn.br [Departamento de Biofisica e Farmacologia, Centro de Biociencias, Universidade Federal do Rio Grande do Norte, UFRN - Campus Universitario, Lagoa Nova, CEP 59078 972, Natal, RN (Brazil)

2011-03-01

In this work we focus on interaction networks between insects and plants and in the characterization of insect plant asymmetry, an important issue in coevolution and evolutionary biology. We analyze in particular the asymmetry in the interaction matrix of animals (herbivorous insects) and plants (food resource for the insects). Instead of driving our attention to the interaction matrix itself we derive two networks associated to the bipartite network: the animal network, D{sub 1}, and the plant network, D{sub 2}. These networks are constructed according to the following recipe: two animal species are linked once if they interact with the same plant. In a similar way, in the plant network, two plants are linked if they interact with the same animal. To explore the asymmetry between D{sub 2} and D{sub 1} we test for a set of 23 networks from the ecologic literature networks: the difference in size, {Delta}L, clustering coefficient difference, {Delta}C, and mean connectivity difference, {Delta}. We used a nonparametric statistical test to check the differences in {Delta}L, {Delta}C and {Delta}. Our results indicate that {Delta}L and {Delta} show a significative asymmetry.

The construction of corporate social responsibility in network societies: A communication view

NARCIS (Netherlands)

Schultz, F.; Castello, I.; Morsing, M.

2013-01-01

The paper introduces the communication view on Corporate Social Responsibility (CSR), which regards CSR as communicatively constructed in dynamic interaction processes in today's networked societies. Building on the idea that communication constitutes organizations we discuss the potentially

A core filamentation response network in Candida albicans is restricted to eight genes.

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Ronny Martin

Full Text Available Although morphological plasticity is a central virulence trait of Candida albicans, the number of filament-associated genes and the interplay of mechanisms regulating their expression remain unknown. By correlation-based network modeling of the transcriptional response to different defined external stimuli for morphogenesis we identified a set of eight genes with highly correlated expression patterns, forming a core filamentation response. This group of genes included ALS3, ECE1, HGT2, HWP1, IHD1 and RBT1 which are known or supposed to encode for cell- wall associated proteins as well as the Rac1 guanine nucleotide exchange factor encoding gene DCK1 and the unknown function open reading frame orf19.2457. The validity of network modeling was confirmed using a dataset of advanced complexity that describes the transcriptional response of C. albicans during epithelial invasion as well as comparing our results with other previously published transcriptome studies. Although the set of core filamentation response genes was quite small, several transcriptional regulators are involved in the control of their expression, depending on the environmental condition.

Hydrogen Detection With a Gas Sensor Array – Processing and Recognition of Dynamic Responses Using Neural Networks

Directory of Open Access Journals (Sweden)

Gwiżdż Patryk

2015-03-01

Full Text Available An array consisting of four commercial gas sensors with target specifications for hydrocarbons, ammonia, alcohol, explosive gases has been constructed and tested. The sensors in the array operate in the dynamic mode upon the temperature modulation from 350°C to 500°C. Changes in the sensor operating temperature lead to distinct resistance responses affected by the gas type, its concentration and the humidity level. The measurements are performed upon various hydrogen (17-3000 ppm, methane (167-3000 ppm and propane (167-3000 ppm concentrations at relative humidity levels of 0-75%RH. The measured dynamic response signals are further processed with the Discrete Fourier Transform. Absolute values of the dc component and the first five harmonics of each sensor are analysed by a feed-forward back-propagation neural network. The ultimate aim of this research is to achieve a reliable hydrogen detection despite an interference of the humidity and residual gases.

Modeling the controllable pH-responsive swelling and pore size of networked alginate based biomaterials.

Science.gov (United States)

Chan, Ariel W; Neufeld, Ronald J

2009-10-01

Semisynthetic network alginate polymer (SNAP), synthesized by acetalization of linear alginate with di-aldehyde, is a pH-responsive tetrafunctionally linked 3D gel network, and has potential application in oral delivery of protein therapeutics and active biologicals, and as tissue bioscaffold for regenerative medicine. A constitutive polyelectrolyte gel model based on non-Gaussian polymer elasticity, Flory-Huggins liquid lattice theory, and non-ideal Donnan membrane equilibria was derived, to describe SNAP gel swelling in dilute and ionic solutions containing uni-univalent, uni-bivalent, bi-univalent or bi-bi-valent electrolyte solutions. Flory-Huggins interaction parameters as a function of ionic strength and characteristic ratio of alginates of various molecular weights were determined experimentally to numerically predict SNAP hydrogel swelling. SNAP hydrogel swells pronouncedly to 1000 times in dilute solution, compared to its compact polymer volume, while behaving as a neutral polymer with limited swelling in high ionic strength or low pH solutions. The derived model accurately describes the pH-responsive swelling of SNAP hydrogel in acid and alkaline solutions of wide range of ionic strength. The pore sizes of the synthesized SNAP hydrogels of various crosslink densities were estimated from the derived model to be in the range of 30-450 nm which were comparable to that measured by thermoporometry, and diffusion of bovine serum albumin. The derived equilibrium swelling model can characterize hydrogel structure such as molecular weight between crosslinks and crosslinking density, or can be used as predictive model for swelling, pore size and mechanical properties if gel structural information is known, and can potentially be applied to other point-link network polyelectrolytes such as hyaluronic acid gel.

Network Analysis Reveals a Common Host–Pathogen Interaction Pattern in Arabidopsis Immune Responses

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Hong Li

2017-05-01

Full Text Available Many plant pathogens secrete virulence effectors into host cells to target important proteins in host cellular network. However, the dynamic interactions between effectors and host cellular network have not been fully understood. Here, an integrative network analysis was conducted by combining Arabidopsis thaliana protein–protein interaction network, known targets of Pseudomonas syringae and Hyaloperonospora arabidopsidis effectors, and gene expression profiles in the immune response. In particular, we focused on the characteristic network topology of the effector targets and differentially expressed genes (DEGs. We found that effectors tended to manipulate key network positions with higher betweenness centrality. The effector targets, especially those that are common targets of an individual effector, tended to be clustered together in the network. Moreover, the distances between the effector targets and DEGs increased over time during infection. In line with this observation, pathogen-susceptible mutants tended to have more DEGs surrounding the effector targets compared with resistant mutants. Our results suggest a common plant–pathogen interaction pattern at the cellular network level, where pathogens employ potent local impact mode to interfere with key positions in the host network, and plant organizes an in-depth defense by sequentially activating genes distal to the effector targets.

Weighted radial dimension: an improved fractal measurement for highway transportation networks distribution

Science.gov (United States)

Feng, Yongjiu; Liu, Miaolong; Tong, Xiaohua

2007-06-01

An improved fractal measurement, the weighted radial dimension, is put forward for highway transportation networks distribution. The radial dimension (DL), originated from subway investigation in Stuttgart, is a fractal measurement for transportation systems under ideal assumption considering all the network lines to be homogeneous curves, ignoring the difference on spatial structure, quality and level, especially the highway networks. Considering these defects of radial dimension, an improved fractal measurement called weighted radial dimension (D WL) is introduced and the transportation system in Guangdong province is studied in detail using this novel method. Weighted radial dimensions are measured and calculated, and the spatial structure, intensity and connectivity of transportation networks are discussed in Guangdong province and the four sub-areas: the Pearl River Delta area, the East Costal area, the West Costal area and the Northern Guangdong area. In Guangdong province, the fractal spatial pattern characteristics of transportation system vary remarkably: it is the highest in the Pearl River Delta area, moderate in Costal area and lowest in the Northern Guangdong area. With the Pearl River Delta area as the centre, the weighted radial dimensions decrease with the distance increasing, while the decline level is smaller in the costal area and greater in the Northern Guangdong province. By analysis of the conic of highway density, it is recognized that the density decrease with the distance increasing from the calculation centre (Guangzhou), demonstrating the same trend as weighted radial dimensions shown. Evidently, the improved fractal measurement, weighted radial dimension, is an indictor describing the characteristics of highway transportation system more effectively and accurately.

Grafting of Interpenetrating Networks of Two Stimuli-responsive Polymers onto PP

International Nuclear Information System (INIS)

Ruiz, J. C.

2006-01-01

In this work a new strategy was used to prepare interpenetrating polymer networks (IPNs) of two 'stimuli-responsive' polymers: a thermosensitive poly N-isopropylacrylamide (PNIPAAm) and pH sensitive poly acrylic acid (PAAc), the last grafted onto PP films. IPNs are a combination of two or more polymers in network form, which are mixed together (not chemically but physically), with al least one such polymer polymerized and/or crosslinked in the immediate presence of the other(s). The 'stimuli-responsive' polymers, also called 'smart' polymers, exhibit relatively large and sharp physical or chemical changes in response to small physical or chemical stimuli. These polymers are being used as hydrogels or copolymers for technical applications in chemical and mechanical engineering systems such as mass separation, chemical valves, temperature or pH indicators, biomedical and drug delivery systems. For these applications a rapid response and good mechanical properties are necessary. Formerly when PNIPAAm and PAAc were chemically combined their sensitivity was often altered or eliminated and their copolymer had poor mechanical properties. Attempts to solve this problem by creating IPN's with a reduced gel size or by using a macro-porous structure were successful in preserving sensitivity but failed to produce adequate mechanical properties. The object of this paper is to improve the past results of using a binary graft of PNIPAAm and PAAc onto poly(tetrafluoroethylene) PTFE. Poly acrylic acid was grafted onto polypropylene films (with good mechanical properties) by gamma radiation in air (pre-irradiation method), then these grafts were crosslinked using any of the next two methods: The first one, the grafted film in water and argon atmosphere by gamma radiation; and the second one, in the same conditions, but adding a crosslinking agent N, N'-methylenebisacrylamide (MBAAm). The second network was carried out in situ, in the cross-linked PAAc grafted onto PP films, by

Simple measurement-based admission control for DiffServ access networks

Science.gov (United States)

Lakkakorpi, Jani

2002-07-01

In order to provide good Quality of Service (QoS) in a Differentiated Services (DiffServ) network, a dynamic admission control scheme is definitely needed as an alternative to overprovisioning. In this paper, we present a simple measurement-based admission control (MBAC) mechanism for DiffServ-based access networks. Instead of using active measurements only or doing purely static bookkeeping with parameter-based admission control (PBAC), the admission control decisions are based on bandwidth reservations and periodically measured & exponentially averaged link loads. If any link load on the path between two endpoints is over the applicable threshold, access is denied. Link loads are periodically sent to Bandwidth Broker (BB) of the routing domain, which makes the admission control decisions. The information needed in calculating the link loads is retrieved from the router statistics. The proposed admission control mechanism is verified through simulations. Our results prove that it is possible to achieve very high bottleneck link utilization levels and still maintain good QoS.

Two-level Robust Measurement Fusion Kalman Filter for Clustering Sensor Networks

Institute of Scientific and Technical Information of China (English)

ZHANG Peng; QI Wen-Juan; DENG Zi-Li

2014-01-01

This paper investigates the distributed fusion Kalman filtering over clustering sensor networks. The sensor network is partitioned as clusters by the nearest neighbor rule and each cluster consists of sensing nodes and cluster-head. Using the minimax robust estimation principle, based on the worst-case conservative system with the conservative upper bounds of noise variances, two-level robust measurement fusion Kalman filter is presented for the clustering sensor network systems with uncertain noise variances. It can significantly reduce the communication load and save energy when the number of sensors is very large. A Lyapunov equation approach for the robustness analysis is presented, by which the robustness of the local and fused Kalman filters is proved. The concept of the robust accuracy is presented, and the robust accuracy relations among the local and fused robust Kalman filters are proved. It is proved that the robust accuracy of the two-level weighted measurement fuser is equal to that of the global centralized robust fuser and is higher than those of each local robust filter and each local weighted measurement fuser. A simulation example shows the correctness and effectiveness of the proposed results.

Sensory and cross-network contributions to response inhibition in patients with schizophrenia

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Matthew J. Hoptman

Full Text Available Patients with schizophrenia show response inhibition deficits equal to or greater than those seen in impulse-control disorders, and these deficits contribute to poor outcome. However, little is known about the circuit abnormalities underlying this impairment. To address this, we examined stop signal task performance in 21 patients with schizophrenia and 21 healthy controls using event related potential (ERP and resting state functional connectivity. Patients showed prolonged stop signal reaction time (SSRT and reduced N1, N2, and P3 amplitudes compared to controls. Across groups, P3 amplitudes were maximal after SSRT (i.e., after the time associated with the decision to stop occurred, suggesting that this component indexed response monitoring. Multiple regression analyses showed that longer SSRTs were independently related to 1 patient status, 2 reduced N1 amplitude on successful stop trials and 3 reduced anticorrelated resting state functional connectivity between visual and frontoparietal cortical networks. This study used a combined multimodal imaging approach to better understand the network abnormalities that underlie response inhibition in schizophrenia. It is the first of its kind to specifically assess the brain's resting state functional architecture in combination with behavioral and ERP methods to investigate response inhibition in schizophrenia. Keywords: EEG, Stop signal task, Impulsivity, Schizophrenia, Resting state functional connectivity

Hierarchical anatomical brain networks for MCI prediction: revisiting volumetric measures.

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Luping Zhou

Full Text Available Owning to its clinical accessibility, T1-weighted MRI (Magnetic Resonance Imaging has been extensively studied in the past decades for prediction of Alzheimer's disease (AD and mild cognitive impairment (MCI. The volumes of gray matter (GM, white matter (WM and cerebrospinal fluid (CSF are the most commonly used measurements, resulting in many successful applications. It has been widely observed that disease-induced structural changes may not occur at isolated spots, but in several inter-related regions. Therefore, for better characterization of brain pathology, we propose in this paper a means to extract inter-regional correlation based features from local volumetric measurements. Specifically, our approach involves constructing an anatomical brain network for each subject, with each node representing a Region of Interest (ROI and each edge representing Pearson correlation of tissue volumetric measurements between ROI pairs. As second order volumetric measurements, network features are more descriptive but also more sensitive to noise. To overcome this limitation, a hierarchy of ROIs is used to suppress noise at different scales. Pairwise interactions are considered not only for ROIs with the same scale in the same layer of the hierarchy, but also for ROIs across different scales in different layers. To address the high dimensionality problem resulting from the large number of network features, a supervised dimensionality reduction method is further employed to embed a selected subset of features into a low dimensional feature space, while at the same time preserving discriminative information. We demonstrate with experimental results the efficacy of this embedding strategy in comparison with some other commonly used approaches. In addition, although the proposed method can be easily generalized to incorporate other metrics of regional similarities, the benefits of using Pearson correlation in our application are reinforced by the experimental

Radio frequency sensing measurements and methods for location classification in wireless networks

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Maas, Dustin C.

The wireless radio channel is typically thought of as a means to move information from transmitter to receiver, but the radio channel can also be used to detect changes in the environment of the radio link. This dissertation is focused on the measurements we can make at the physical layer of wireless networks, and how we can use those measurements to obtain information about the locations of transceivers and people. The first contribution of this work is the development and testing of an open source, 802.11b sounder and receiver, which is capable of decoding packets and using them to estimate the channel impulse response (CIR) of a radio link at a fraction of the cost of traditional channel sounders. This receiver improves on previous implementations by performing optimized matched filtering on the field-programmable gate array (FPGA) of the Universal Software Radio Peripheral (USRP), allowing it to operate at full bandwidth. The second contribution of this work is an extensive experimental evaluation of a technology called location distinction, i.e., the ability to identify changes in radio transceiver position, via CIR measurements. Previous location distinction work has focused on single-input single-output (SISO) radio links. We extend this work to the context of multiple-input multiple-output (MIMO) radio links, and study system design trade-offs which affect the performance of MIMO location distinction. The third contribution of this work introduces the "exploiting radio windows" (ERW) attack, in which an attacker outside of a building surreptitiously uses the transmissions of an otherwise secure wireless network inside of the building to infer location information about people inside the building. This is possible because of the relative transparency of external walls to radio transmissions. The final contribution of this dissertation is a feasibility study for building a rapidly deployable radio tomographic (RTI) imaging system for special operations forces

Network measurements at the heavy ion synchrotron SIS at GSI

International Nuclear Information System (INIS)

Vossbeck, P.; Pschorn, I.; Gebhard, Moritz

1999-01-01

The Heavy Ion Synchrotron SIS forms together with the Linear Accelerator UNILAC and the Storage Ring ESR the accelerator complex of the Gesellschaft fuer Schwerionenforschung in Darmstadt. It accelerates heavy ions up to Uranium to 1 GeV/amu. The accelerators and beamlines have been surveyed and aligned using the TASA method. For SIS a network was established in order to survey the synchrotron with the TASA method. Goal of a diploma thesis was to establish an alternative network for a Laser Tracker instrument and to reach error ellipsoids below 30 μm. In this paper a comparison of the two methods is given. Since the Tracker measurements are done automatically only one person is needed. That reduces the man power. Time consumption for both methods is about the same, although much more network points were used with the Laser Tracker method. As a consequence of the larger number of network points the homogeneity of the results is better. (authors)

Measuring Networking as an Outcome Variable in Undergraduate Research Experiences.

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Hanauer, David I; Hatfull, Graham

2015-01-01

The aim of this paper is to propose, present, and validate a simple survey instrument to measure student conversational networking. The tool consists of five items that cover personal and professional social networks, and its basic principle is the self-reporting of degrees of conversation, with a range of specific discussion partners. The networking instrument was validated in three studies. The basic psychometric characteristics of the scales were established by conducting a factor analysis and evaluating internal consistency using Cronbach's alpha. The second study used a known-groups comparison and involved comparing outcomes for networking scales between two different undergraduate laboratory courses (one involving a specific effort to enhance networking). The final study looked at potential relationships between specific networking items and the established psychosocial variable of project ownership through a series of binary logistic regressions. Overall, the data from the three studies indicate that the networking scales have high internal consistency (α = 0.88), consist of a unitary dimension, can significantly differentiate between research experiences with low and high networking designs, and are related to project ownership scales. The ramifications of the networking instrument for student retention, the enhancement of public scientific literacy, and the differentiation of laboratory courses are discussed. © 2015 D. I. Hanauer and G. Hatfull. CBE—Life Sciences Education © 2015 The American Society for Cell Biology. This article is distributed by The American Society for Cell Biology under license from the author(s). It is available to the public under an Attribution–Noncommercial–Share Alike 3.0 Unported Creative Commons License (http://creativecommons.org/licenses/by-nc-sa/3.0).

Acoustic stimulation can induce a selective neural network response mediated by piezoelectric nanoparticles

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Rojas, Camilo; Tedesco, Mariateresa; Massobrio, Paolo; Marino, Attilio; Ciofani, Gianni; Martinoia, Sergio; Raiteri, Roberto

2018-06-01

Objective. We aim to develop a novel non-invasive or minimally invasive method for neural stimulation to be applied in the study and treatment of brain (dys)functions and neurological disorders. Approach. We investigate the electrophysiological response of in vitro neuronal networks when subjected to low-intensity pulsed acoustic stimulation, mediated by piezoelectric nanoparticles adsorbed on the neuronal membrane. Main results. We show that the presence of piezoelectric barium titanate nanoparticles induces, in a reproducible way, an increase in network activity when excited by stationary ultrasound waves in the MHz regime. Such a response can be fully recovered when switching the ultrasound pulse off, depending on the generated pressure field amplitude, whilst it is insensitive to the duration of the ultrasound pulse in the range 0.5 s–1.5 s. We demonstrate that the presence of piezoelectric nanoparticles is necessary, and when applying the same acoustic stimulation to neuronal cultures without nanoparticles or with non-piezoelectric nanoparticles with the same size distribution, no network response is observed. Significance. We believe that our results open up an extremely interesting approach when coupled with suitable functionalization strategies of the nanoparticles in order to address specific neurons and/or brain areas and applied in vivo, thus enabling remote, non-invasive, and highly selective modulation of the activity of neuronal subpopulations of the central nervous system of mammalians.

Network of siren, public address and display system to preparedness and response for nuclear emergencies

International Nuclear Information System (INIS)

Joshi, G.H.; Padmanabhan, N.; Raman, N.; Pradeepkumar, K.S.; Sharma, D.N.; Abani, M.C.

2003-01-01

For an effective emergency response and implementation of counter measures, communication during a nuclear emergency is a very important aspect. The declaration of a nuclear emergency must be immediately conveyed to all those working in the plant and around the nuclear site. Besides this, the nature of emergency also needs to be conveyed unambiguously along with corresponding counter measures, such as stay in, evacuation or all clear signal for the relevant plants. This requirement has necessitated the need for a networked signaling system. Based on this requirement, a microcontroller based signaling and a telephone/wireless based communication and display system has been designed at Bhabha Atomic Research Centre. It is proposed to be used as a part of emergency preparedness and response programme at the nuclear facility sites. As per the design made for Bhabha Atomic Research Centre, Trombay site, each plant or area in the site is identified by a unique identification code. The main Site Emergency Control Centre/Emergency Response Centre at Mod. Labs. selectively calls the various plants and declares the nature of emergency to be followed In that plant/area through different siren signals along with display and announcement of instructions. This paper describes the details of the system that is designed for Bhabha Atomic Research Centre, Trombay site and proposed for other nuclear power plant sites. (author)

Adaptive-impulsive synchronization in drive-response networks of continuous systems and its application

International Nuclear Information System (INIS)

Sun Mei; Zeng Changyan; Tao Yangwei; Tian Lixin

2009-01-01

Based on the comparison theorem for the stability of impulsive control system, adaptive-impulsive synchronization in drive-response networks of continuous systems with time-delay and non-time-delay is investigated. And the continuous control input, the simple updated laws and a linear impulsive controller are proposed. Moreover, two numerical examples are presented to verify the effectiveness and correctness of the theorem, using the energy resource system and Lue's system as the nodes of the networks.

Effective comparative analysis of protein-protein interaction networks by measuring the steady-state network flow using a Markov model.

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Jeong, Hyundoo; Qian, Xiaoning; Yoon, Byung-Jun

2016-10-06

Comparative analysis of protein-protein interaction (PPI) networks provides an effective means of detecting conserved functional network modules across different species. Such modules typically consist of orthologous proteins with conserved interactions, which can be exploited to computationally predict the modules through network comparison. In this work, we propose a novel probabilistic framework for comparing PPI networks and effectively predicting the correspondence between proteins, represented as network nodes, that belong to conserved functional modules across the given PPI networks. The basic idea is to estimate the steady-state network flow between nodes that belong to different PPI networks based on a Markov random walk model. The random walker is designed to make random moves to adjacent nodes within a PPI network as well as cross-network moves between potential orthologous nodes with high sequence similarity. Based on this Markov random walk model, we estimate the steady-state network flow - or the long-term relative frequency of the transitions that the random walker makes - between nodes in different PPI networks, which can be used as a probabilistic score measuring their potential correspondence. Subsequently, the estimated scores can be used for detecting orthologous proteins in conserved functional modules through network alignment. Through evaluations based on multiple real PPI networks, we demonstrate that the proposed scheme leads to improved alignment results that are biologically more meaningful at reduced computational cost, outperforming the current state-of-the-art algorithms. The source code and datasets can be downloaded from http://www.ece.tamu.edu/~bjyoon/CUFID .

Dose response relationship in anti-stress gene regulatory networks.

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Zhang, Qiang; Andersen, Melvin E

2007-03-02

To maintain a stable intracellular environment, cells utilize complex and specialized defense systems against a variety of external perturbations, such as electrophilic stress, heat shock, and hypoxia, etc. Irrespective of the type of stress, many adaptive mechanisms contributing to cellular homeostasis appear to operate through gene regulatory networks that are organized into negative feedback loops. In general, the degree of deviation of the controlled variables, such as electrophiles, misfolded proteins, and O2, is first detected by specialized sensor molecules, then the signal is transduced to specific transcription factors. Transcription factors can regulate the expression of a suite of anti-stress genes, many of which encode enzymes functioning to counteract the perturbed variables. The objective of this study was to explore, using control theory and computational approaches, the theoretical basis that underlies the steady-state dose response relationship between cellular stressors and intracellular biochemical species (controlled variables, transcription factors, and gene products) in these gene regulatory networks. Our work indicated that the shape of dose response curves (linear, superlinear, or sublinear) depends on changes in the specific values of local response coefficients (gains) distributed in the feedback loop. Multimerization of anti-stress enzymes and transcription factors into homodimers, homotrimers, or even higher-order multimers, play a significant role in maintaining robust homeostasis. Moreover, our simulation noted that dose response curves for the controlled variables can transition sequentially through four distinct phases as stressor level increases: initial superlinear with lesser control, superlinear more highly controlled, linear uncontrolled, and sublinear catastrophic. Each phase relies on specific gain-changing events that come into play as stressor level increases. The low-dose region is intrinsically nonlinear, and depending on

Dose response relationship in anti-stress gene regulatory networks.

Directory of Open Access Journals (Sweden)

Qiang Zhang

2007-03-01

Full Text Available To maintain a stable intracellular environment, cells utilize complex and specialized defense systems against a variety of external perturbations, such as electrophilic stress, heat shock, and hypoxia, etc. Irrespective of the type of stress, many adaptive mechanisms contributing to cellular homeostasis appear to operate through gene regulatory networks that are organized into negative feedback loops. In general, the degree of deviation of the controlled variables, such as electrophiles, misfolded proteins, and O2, is first detected by specialized sensor molecules, then the signal is transduced to specific transcription factors. Transcription factors can regulate the expression of a suite of anti-stress genes, many of which encode enzymes functioning to counteract the perturbed variables. The objective of this study was to explore, using control theory and computational approaches, the theoretical basis that underlies the steady-state dose response relationship between cellular stressors and intracellular biochemical species (controlled variables, transcription factors, and gene products in these gene regulatory networks. Our work indicated that the shape of dose response curves (linear, superlinear, or sublinear depends on changes in the specific values of local response coefficients (gains distributed in the feedback loop. Multimerization of anti-stress enzymes and transcription factors into homodimers, homotrimers, or even higher-order multimers, play a significant role in maintaining robust homeostasis. Moreover, our simulation noted that dose response curves for the controlled variables can transition sequentially through four distinct phases as stressor level increases: initial superlinear with lesser control, superlinear more highly controlled, linear uncontrolled, and sublinear catastrophic. Each phase relies on specific gain-changing events that come into play as stressor level increases. The low-dose region is intrinsically nonlinear

The Study on the Communication Network of Wide Area Measurement System in Electricity Grid

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Xiaorong, Cheng; Ying, Wang; Yangdan, Ni

Wide area measurement system(WAMS) is a fundamental part of security defense in Smart Grid, and the communication system of WAMS is an important part of Electric power communication network. For a large regional network is concerned, the real-time data which is transferred in the communication network of WAMS will affect the safe operation of the power grid directly. Therefore, WAMS raised higher requirements for real-time, reliability and security to its communication network. In this paper, the architecture of WASM communication network was studied according to the seven layers model of the open systems interconnection(OSI), and the network architecture was researched from all levels. We explored the media of WAMS communication network, the network communication protocol and network technology. Finally, the delay of the network were analyzed.

Technical Note: Novel method for water vapour monitoring using wireless communication networks measurements

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N. David

2009-04-01

Full Text Available We propose a new technique that overcomes the obstacles of the existing methods for monitoring near-surface water vapour, by estimating humidity from data collected through existing wireless communication networks.

Weather conditions and atmospheric phenomena affect the electromagnetic channel, causing attenuations to the radio signals. Thus, wireless communication networks are in effect built-in environmental monitoring facilities. The wireless microwave links, used in these networks, are widely deployed by cellular providers for backhaul communication between base stations, a few tens of meters above ground level. As a result, if all available measurements are used, the proposed method can provide moisture observations with high spatial resolution and potentially high temporal resolution. Further, the implementation cost is minimal, since the data used are already collected and saved by the cellular operators. In addition – many of these links are installed in areas where access is difficult such as orographic terrain and complex topography. As such, our method enables measurements in places that have been hard to measure in the past, or have never been measured before. The technique is restricted to weather conditions which exclude rain, fog or clouds along the propagation path. Strong winds that may cause movement of the link transmitter or receiver (or both may also interfere with the ability to conduct accurate measurements.

We present results from real-data measurements taken from two microwave links used in a backhaul cellular network that show convincing correlation to surface station humidity measurements. The measurements were taken daily in two sites, one in northern Israel (28 measurements, the other in central Israel (29 measurements. The correlation between the microwave link measurements and the humidity gauges were 0.9 and 0.82 for the north and central sites, respectively. The Root Mean Square Differences

Technical Note: Novel method for water vapour monitoring using wireless communication networks measurements

Science.gov (United States)

David, N.; Alpert, P.; Messer, H.

2009-04-01

We propose a new technique that overcomes the obstacles of the existing methods for monitoring near-surface water vapour, by estimating humidity from data collected through existing wireless communication networks. Weather conditions and atmospheric phenomena affect the electromagnetic channel, causing attenuations to the radio signals. Thus, wireless communication networks are in effect built-in environmental monitoring facilities. The wireless microwave links, used in these networks, are widely deployed by cellular providers for backhaul communication between base stations, a few tens of meters above ground level. As a result, if all available measurements are used, the proposed method can provide moisture observations with high spatial resolution and potentially high temporal resolution. Further, the implementation cost is minimal, since the data used are already collected and saved by the cellular operators. In addition - many of these links are installed in areas where access is difficult such as orographic terrain and complex topography. As such, our method enables measurements in places that have been hard to measure in the past, or have never been measured before. The technique is restricted to weather conditions which exclude rain, fog or clouds along the propagation path. Strong winds that may cause movement of the link transmitter or receiver (or both) may also interfere with the ability to conduct accurate measurements. We present results from real-data measurements taken from two microwave links used in a backhaul cellular network that show convincing correlation to surface station humidity measurements. The measurements were taken daily in two sites, one in northern Israel (28 measurements), the other in central Israel (29 measurements). The correlation between the microwave link measurements and the humidity gauges were 0.9 and 0.82 for the north and central sites, respectively. The Root Mean Square Differences (RMSD) were 1.8 g/m3 and 3.4 g/m3 for

Measuring caloric response: comparison of different analysis techniques.

Science.gov (United States)

Mallinson, A I; Longridge, N S; Pace-Asciak, P; Ngo, R

2010-01-01

Electronystagmography (ENG) testing has been supplanted by newer techniques of measuring eye movement with infrared cameras (VNG). Most techniques of quantifying caloric induced nystagmus measure the slow phase velocity in some manner. Although our analysis is carried out by very experienced assessors, some systems have computer algorithms that have been "taught" to locate and quantify maximum responses. We wondered what differences in measurement might show up when measuring calorics using different techniques and systems, the relevance of this being that if there was a change in slow phase velocity between ENG and VNG testing when measuring caloric response, then normative data would have to be changed. There are also some subjective but important aspects of ENG interpretation which comment on the nature of the response (e.g. responses which might be "sporadic" or "scant"). Our experiment compared caloric responses in 100 patients analyzed four different ways. Each caloric was analyzed by our old ENG system, our new VNG system, an inexperienced assessor and the computer algorithm, and data was compared. All four systems made similar measurements but our inexperienced assessor failed to recognize responses as sporadic or scant, and we feel this is a limitation to be kept in mind in the rural setting, as it is an important aspect of assessment in complex patients. Assessment of complex VNGs should be left to an experienced assessor.

Measuring the degree of integration for an integrated service network

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Chenglin Ye

2012-09-01

Full Text Available Background: Integration involves the coordination of services provided by autonomous agencies and improves the organization and delivery of multiple services for target patients. Current measures generally do not distinguish between agencies' perception and expectation. We propose a method for quantifying the agencies' service integration. Using the data from the Children's Treatment Network (CTN, we aimed to measure the degree of integration for the CTN agencies in York and Simcoe.  Theory and Methods: We quantified the integration by the agreement between perceived and expected levels of involvement and calculated four scores from different perspectives for each agency. We used the average score to measure the global network integration and examined the sensitivity of the global score.  Results: Most agencies' integration scores were less than 65%. As measured by the agreement between every other agency's perception and expectation, the overall integration of CTN in Simcoe and York was 44% (95% CI: 39% - 49% and 52% (95% CI: 48% - 56%, respectively. The sensitivity analysis showed that the global scores were robust.  Conclusion: Our method extends existing measures of integration and possesses a good extent of validity. We can also apply the method in monitoring improvement and linking integration with other outcomes.

Measuring the degree of integration for an integrated service network

Directory of Open Access Journals (Sweden)

Chenglin Ye

2012-09-01

Full Text Available Background: Integration involves the coordination of services provided by autonomous agencies and improves the organization and delivery of multiple services for target patients. Current measures generally do not distinguish between agencies' perception and expectation. We propose a method for quantifying the agencies' service integration. Using the data from the Children's Treatment Network (CTN, we aimed to measure the degree of integration for the CTN agencies in York and Simcoe. Theory and Methods: We quantified the integration by the agreement between perceived and expected levels of involvement and calculated four scores from different perspectives for each agency. We used the average score to measure the global network integration and examined the sensitivity of the global score. Results: Most agencies' integration scores were less than 65%. As measured by the agreement between every other agency's perception and expectation, the overall integration of CTN in Simcoe and York was 44% (95% CI: 39% - 49% and 52% (95% CI: 48% - 56%, respectively. The sensitivity analysis showed that the global scores were robust. Conclusion: Our method extends existing measures of integration and possesses a good extent of validity. We can also apply the method in monitoring improvement and linking integration with other outcomes. 

Metastable Features of Economic Networks and Responses to Exogenous Shocks.

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Ali Hosseiny

Full Text Available It is well known that a network structure plays an important role in addressing a collective behavior. In this paper we study a network of firms and corporations for addressing metastable features in an Ising based model. In our model we observe that if in a recession the government imposes a demand shock to stimulate the network, metastable features shape its response. Actually we find that there exists a minimum bound where any demand shock with a size below it is unable to trigger the market out of recession. We then investigate the impact of network characteristics on this minimum bound. We surprisingly observe that in a Watts-Strogatz network, although the minimum bound depends on the average of the degrees, when translated into the language of economics, such a bound is independent of the average degrees. This bound is about 0.44ΔGDP, where ΔGDP is the gap of GDP between recession and expansion. We examine our suggestions for the cases of the United States and the European Union in the recent recession, and compare them with the imposed stimulations. While the stimulation in the US has been above our threshold, in the EU it has been far below our threshold. Beside providing a minimum bound for a successful stimulation, our study on the metastable features suggests that in the time of crisis there is a "golden time passage" in which the minimum bound for successful stimulation can be much lower. Hence, our study strongly suggests stimulations to arise within this time passage.

Measuring the collateral network pressure to minimize paraplegia risk in thoracoabdominal aneurysm resection.

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Etz, Christian D; Zoli, Stefano; Bischoff, Moritz S; Bodian, Carol; Di Luozzo, Gabriele; Griepp, Randall B

2010-12-01

To minimize paraplegia during thoracoabdominal aortic aneurysm repair, the concept of the collateral network was developed. That is, spinal cord perfusion is provided by an interconnecting complex of vessels in the intraspinal, paraspinous, and epidural space and in the paravertebral muscles, including intercostal and lumbar segmental as well as subclavian and hypogastric arteries. Collateral network pressure was measured with a catheter in the distal end of a ligated segmental artery in pigs and human beings. In the pig, collateral network pressure was 75% of the simultaneous mean aortic pressure. With complete segmental arterial ligation, it fell to 27% of baseline, recovering to 40% at 24 hours and 90% at 120 hours. Spinal cord injury occurred in approximately 50% of animals. When all segmental arteries were taken in 2 stages a week apart, collateral network pressure fell only to 50% to 70% of baseline, and spinal cord injury was rare. In human beings, baseline collateral network pressure also was 75% of mean aortic pressure, fell in proportion to the number of segmental arteries ligated, and began recovery within 24 hours. Collateral network pressure was lower with nonpulsatile distal bypass than with pulsatile perfusion. After subtraction of a measure of spinal cord outflow pressure (cerebrospinal fluid pressure or central venous pressure), collateral network pressure provides a clinically useful estimate of spinal cord perfusion pressure. Copyright © 2010. Published by Mosby, Inc.

A Conserved Circular Network of Coregulated Lipids Modulates Innate Immune Responses.

Science.gov (United States)

Köberlin, Marielle S; Snijder, Berend; Heinz, Leonhard X; Baumann, Christoph L; Fauster, Astrid; Vladimer, Gregory I; Gavin, Anne-Claude; Superti-Furga, Giulio

2015-07-02

Lipid composition affects the biophysical properties of membranes that provide a platform for receptor-mediated cellular signaling. To study the regulatory role of membrane lipid composition, we combined genetic perturbations of sphingolipid metabolism with the quantification of diverse steps in Toll-like receptor (TLR) signaling and mass spectrometry-based lipidomics. Membrane lipid composition was broadly affected by these perturbations, revealing a circular network of coregulated sphingolipids and glycerophospholipids. This evolutionarily conserved network architecture simultaneously reflected membrane lipid metabolism, subcellular localization, and adaptation mechanisms. Integration of the diverse TLR-induced inflammatory phenotypes with changes in lipid abundance assigned distinct functional roles to individual lipid species organized across the network. This functional annotation accurately predicted the inflammatory response of cells derived from patients suffering from lipid storage disorders, based solely on their altered membrane lipid composition. The analytical strategy described here empowers the understanding of higher-level organization of membrane lipid function in diverse biological systems. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

Flexible investment under uncertainty in smart distribution networks with demand side response: Assessment framework and practical implementation

International Nuclear Information System (INIS)

Schachter, Jonathan A.; Mancarella, Pierluigi; Moriarty, John; Shaw, Rita

2016-01-01

need altering. The case study results indicate that DSR can be an economical option to delay or even avoid large irreversible capacity investments, thus reducing overall costs for networks and end customers. However, in order for the value and benefits of DSR to be acknowledged, a change in the regulatory framework (currently based on deterministic analysis) that takes explicit account of uncertainty in planning, as suggested by our work, is required. - Highlights: • A real options framework for distribution network investments under uncertainty. • Smart (flexible) and asset-based investment values are compared transparently in Microsoft Excel. • Both economic and physical (interruption) risks are measured in a multi-criterion analysis. • Case study shows the value of demand response for deferring asset-based investments. • Probabilistic regulatory frameworks are thus needed to give flexible investments their fair value.

A Typology of Social Capital and Associated Network Measures

OpenAIRE

Jackson, Matthew O.

2017-01-01

I provide a typology of social capital, breaking it down into seven more fundamental forms of capital: information capital, brokerage capital, coordination and leadership capital, bridging capital, favor capital, reputation capital, and community capital. I discuss how most of these forms of social capital can be identified using different network-based measures.

Measuring Personal Networks and Their Relationship with Scientific Production

Science.gov (United States)

Villanueva-Felez, Africa; Molas-Gallart, Jordi; Escribá-Esteve, Alejandro

2013-01-01

The analysis of social networks has remained a crucial and yet understudied aspect of the efforts to measure Triple Helix linkages. The Triple Helix model aims to explain, among other aspects of knowledge-based societies, "the current research system in its social context" (Etzkowitz and Leydesdorff 2000:109). This paper develops a novel…

Predicting and measuring fluid responsiveness with echocardiography

Directory of Open Access Journals (Sweden)

Ashley Miller

2016-06-01

Full Text Available Echocardiography is ideally suited to guide fluid resuscitation in critically ill patients. It can be used to assess fluid responsiveness by looking at the left ventricle, aortic outflow, inferior vena cava and right ventricle. Static measurements and dynamic variables based on heart–lung interactions all combine to predict and measure fluid responsiveness and assess response to intravenous fluid esuscitation. Thorough knowledge of these variables, the physiology behind them and the pitfalls in their use allows the echocardiographer to confidently assess these patients and in combination with clinical judgement manage them appropriately.

A measurement-driven approach to assess power line telecommunication (PLT) network quality of service (QoS) performance parameters

International Nuclear Information System (INIS)

Betta, G; Capriglione, D; Ferrigno, L; Laracca, M

2009-01-01

Power line telecommunication (PLT) technology offers cheap and fast ways for providing in-home broadband services and local area networking. Its main advantage is due to the possibility of using the pre-existing electrical grid as a communication channel. Nevertheless, technical challenges arise from the difficulty of operating on a hostile medium, not designed for communication purposes, characterized by complex channel modeling and by varying time response. These aspects put practical problems for designers and testers in the assessment of network quality of service performance parameters such as the throughput, the latency, the jitter, and the reliability. The measurement of these parameters has not yet been standardized so that there do not exist reference test set-ups and measurement methodologies (i.e. the type of isolation from the ac main, the observation time and the number of experiments, the measurement uncertainty and so on). Consequently, experiments executed by adopting different methods may lead to incompatible measurement results, thus making it also impossible to have reliable comparisons of different PLT modems. Really, the development of standard procedures is a very difficult task because the scenarios in which the PLT modems can work are very wide and then the application of an exhaustive approach (in which all the parameters influencing the PLT performance should be considered) would be very complex and time consuming, thus making the modem characterization very expensive. In this paper, the authors propose a methodological approach to develop an efficient measurement procedure able to reliably assess the performance of PLT modems (in terms of network quality of service parameters) with a minimum number of experiments. It is based on both creating a reconfigurable grid to which real disturbing loads are connected and implementing an original design of the experiment technique based on the effects of the uncertainty of the measurement results

Optical Calibration Process Developed for Neural-Network-Based Optical Nondestructive Evaluation Method

Science.gov (United States)

Decker, Arthur J.

2004-01-01

A completely optical calibration process has been developed at Glenn for calibrating a neural-network-based nondestructive evaluation (NDE) method. The NDE method itself detects very small changes in the characteristic patterns or vibration mode shapes of vibrating structures as discussed in many references. The mode shapes or characteristic patterns are recorded using television or electronic holography and change when a structure experiences, for example, cracking, debonds, or variations in fastener properties. An artificial neural network can be trained to be very sensitive to changes in the mode shapes, but quantifying or calibrating that sensitivity in a consistent, meaningful, and deliverable manner has been challenging. The standard calibration approach has been difficult to implement, where the response to damage of the trained neural network is compared with the responses of vibration-measurement sensors. In particular, the vibration-measurement sensors are intrusive, insufficiently sensitive, and not numerous enough. In response to these difficulties, a completely optical alternative to the standard calibration approach was proposed and tested successfully. Specifically, the vibration mode to be monitored for structural damage was intentionally contaminated with known amounts of another mode, and the response of the trained neural network was measured as a function of the peak-to-peak amplitude of the contaminating mode. The neural network calibration technique essentially uses the vibration mode shapes of the undamaged structure as standards against which the changed mode shapes are compared. The published response of the network can be made nearly independent of the contaminating mode, if enough vibration modes are used to train the net. The sensitivity of the neural network can be adjusted for the environment in which the test is to be conducted. The response of a neural network trained with measured vibration patterns for use on a vibration isolation

Measuring the evolutionary rewiring of biological networks.

Directory of Open Access Journals (Sweden)

Chong Shou

Full Text Available We have accumulated a large amount of biological network data and expect even more to come. Soon, we anticipate being able to compare many different biological networks as we commonly do for molecular sequences. It has long been believed that many of these networks change, or "rewire", at different rates. It is therefore important to develop a framework to quantify the differences between networks in a unified fashion. We developed such a formalism based on analogy to simple models of sequence evolution, and used it to conduct a systematic study of network rewiring on all the currently available biological networks. We found that, similar to sequences, biological networks show a decreased rate of change at large time divergences, because of saturation in potential substitutions. However, different types of biological networks consistently rewire at different rates. Using comparative genomics and proteomics data, we found a consistent ordering of the rewiring rates: transcription regulatory, phosphorylation regulatory, genetic interaction, miRNA regulatory, protein interaction, and metabolic pathway network, from fast to slow. This ordering was found in all comparisons we did of matched networks between organisms. To gain further intuition on network rewiring, we compared our observed rewirings with those obtained from simulation. We also investigated how readily our formalism could be mapped to other network contexts; in particular, we showed how it could be applied to analyze changes in a range of "commonplace" networks such as family trees, co-authorships and linux-kernel function dependencies.

New approach in subjective and objective speech transmission quality measurement in TCP/IP networks

International Nuclear Information System (INIS)

Souček, Pavel; Slavata, Oldřich; Holub, Jan

2015-01-01

This paper deals with problems of speech transmission quality measurement in modern telecommunication networks. It focuses on problems caused by specific types of distortions and errors caused present in transmissions using TCP/IP networks

Evaluation of Coordination of Emergency Response Team through the Social Network Analysis. Case Study: Oil and Gas Refinery.

Science.gov (United States)

Mohammadfam, Iraj; Bastani, Susan; Esaghi, Mahbobeh; Golmohamadi, Rostam; Saee, Ali

2015-03-01

The purpose of this study was to examine the cohesions status of the coordination within response teams in the emergency response team (ERT) in a refinery. For this study, cohesion indicators of social network analysis (SNA; density, degree centrality, reciprocity, and transitivity) were utilized to examine the coordination of the response teams as a whole network. The ERT of this research, which was a case study, included seven teams consisting of 152 members. The required data were collected through structured interviews and were analyzed using the UCINET 6.0 Social Network Analysis Program. The results reported a relatively low number of triple connections, poor coordination with key members, and a high level of mutual relations in the network with low density, all implying that there were low cohesions of coordination in the ERT. The results showed that SNA provided a quantitative and logical approach for the examination of the coordination status among response teams and it also provided a main opportunity for managers and planners to have a clear understanding of the presented status. The research concluded that fundamental efforts were needed to improve the presented situations.

Vertex centrality as a measure of information flow in Italian Corporate Board Networks

Science.gov (United States)

Grassi, Rosanna

2010-06-01

The aim of this article is to investigate the governance models of companies listed on the Italian Stock Exchange by using a network approach, which describes the interlinks between boards of directors. Following mainstream literature, I construct a weighted graph representing the listed companies (vertices) and their relationships (weighted edges), the Corporate Board Network; I then apply three different vertex centrality measures: degree, betweenness and flow betweenness. What emerges from the network construction and by applying the degree centrality is a structure with a large number of connections but not particularly dense, where the presence of a small number of highly connected nodes (hubs) is evident. Then I focus on betweenness and flow betweenness; indeed I expect that these centrality measures may give a representation of the intensity of the relationship between companies, capturing the volume of information flowing from one vertex to another. Finally, I investigate the possible scale-free structure of the network.

Fibre optical measuring network based on quasi-distributed amplitude sensors for detecting deformation loads

International Nuclear Information System (INIS)

Kul'chin, Yurii N; Kolchinskiy, V A; Kamenev, O T; Petrov, Yu S

2013-01-01

A new design of a sensitive element for a fibre optical sensor of deformation loads is proposed. A distributed fibre optical measuring network, aimed at determining both the load application point and the load mass, has been developed based on these elements. It is shown that neural network methods of data processing make it possible to combine quasi-distributed amplitude sensors of different types into a unified network. The results of the experimental study of a breadboard of a fibre optical measuring network are reported, which demonstrate successful reconstruction of the trajectory of a moving object (load) with a spatial resolution of 8 cm, as well as the load mass in the range of 1 – 10 kg with a sensitivity of 0.043 kg -1 . (laser optics 2012)

Measurement of void fraction distribution in two-phase flow by impedance CT with neural network

International Nuclear Information System (INIS)

Hayashi, Hideaki; Sumida, Isao; Sakai, Sinji; Wakai, Kazunori

1996-01-01

This paper describes a new method for measurement of void distribution using impedance CT with a hierarchical neural network. The present method consists of four processes. First, output electric currents are calculated by simulation of various distributions of void fraction. The relationship between distribution of void fraction and electric current is called 'teaching data'. Second, the neural network learns the teaching data by the back propagation method. Third, output electric currents are measured about actual two-phase flow. Finally, distribution of void fraction is calculated by the taught neural network using the measured electric currents. In this paper, measurement and learning parameters are adjusted, experimental results obtained using the impedance CT method are compared with data obtained by the impedance probe method. The results show that our method is effective for measurement of void fraction distribution. (author)

Examining the resilience of national energy systems: Measurements of diversity in production-based and consumption-based electricity in the globalization of trade networks

International Nuclear Information System (INIS)

Kharrazi, Ali; Sato, Masahiro; Yarime, Masaru; Nakayama, Hirofumi; Yu, Yadong; Kraines, Steven

2015-01-01

Energy is a critical component of achieving sustainable development. In addition to the three aspects of promoting access, renewables, and efficiency, the dimension of resilience in energy systems should also considered. The implementation of resilient energy systems requires a quantitative understanding of the socio-economic practices underlying such systems. Specifically, in line with the increasing globalization of trade, there remains a critical knowledge gap on the link between embodied energy in the production and consumption of traded goods. To bridge this knowledge gap, we investigate the resilience of global energy systems through an examination of a diversity measure of global embodied electricity trade based on multi-regional input-output (MRIO) networks. The significance of this research lies in its ability to utilize high resolution MRIO data sets in assessing the resilience of national energy systems. This research indicates that secure and responsible consumption requires the diversification of not only energy generation but also energy imports. This research will lay the ground for further research in the governance of resilience in global energy networks. - Highlights: • We examine the resilience of global embodied energy based on (MRIO) trade networks. • We propose a secure and responsible mode of thinking for national energy consumption. • Secure & responsible consumption requires diversity in energy generation and imports.

Responses to a self-presented suicide attempt in social media: a social network analysis.

Science.gov (United States)

Fu, King-Wa; Cheng, Qijin; Wong, Paul W C; Yip, Paul S F

2013-01-01

The self-presentation of suicidal acts in social media has become a public health concern. This article centers on a Chinese microblogger who posted a wrist-cutting picture that was widely circulated in Chinese social media in 2011. This exploratory study examines written reactions of a group of Chinese microbloggers exposed to the post containing a self-harming message and photo. In addition, we investigate the pattern of information diffusion via a social network. We systematically collected and analyzed 5,971 generated microblogs and the network of information diffusion. We found that a significant portion of written responses (36.6%) could help vulnerable netizens by providing peer-support and calls for help. These responses were reposted and diffused via an online social network with markedly more clusters of users--and at a faster pace-- than a set of randomly generated networks. We conclude that social media can be a double-edged sword: While it may contagiously affect others by spreading suicidal thoughts and acts, it may also play a positive role by assisting people at risk for suicide, providing rescue or support. More research is needed to learn how suicidally vulnerable people interact with online suicide information, and how we can effectively intervene.

Modeling of Throughput in Production Lines Using Response Surface Methodology and Artificial Neural Networks

Directory of Open Access Journals (Sweden)

Federico Nuñez-Piña

2018-01-01

Full Text Available The problem of assigning buffers in a production line to obtain an optimum production rate is a combinatorial problem of type NP-Hard and it is known as Buffer Allocation Problem. It is of great importance for designers of production systems due to the costs involved in terms of space requirements. In this work, the relationship among the number of buffer slots, the number of work stations, and the production rate is studied. Response surface methodology and artificial neural network were used to develop predictive models to find optimal throughput values. 360 production rate values for different number of buffer slots and workstations were used to obtain a fourth-order mathematical model and four hidden layers’ artificial neural network. Both models have a good performance in predicting the throughput, although the artificial neural network model shows a better fit (R=1.0000 against the response surface methodology (R=0.9996. Moreover, the artificial neural network produces better predictions for data not utilized in the models construction. Finally, this study can be used as a guide to forecast the maximum or near maximum throughput of production lines taking into account the buffer size and the number of machines in the line.

Assessment of Performance Measures for Security of the Maritime Transportation Network, Port Security Metrics : Proposed Measurement of Deterrence Capability

Science.gov (United States)

2007-01-03

This report is the thirs in a series describing the development of performance measures pertaining to the security of the maritime transportation network (port security metrics). THe development of measures to guide improvements in maritime security ...

A measure theoretic approach to traffic flow optimization on networks

OpenAIRE

Cacace, Simone; Camilli, Fabio; De Maio, Raul; Tosin, Andrea

2018-01-01

We consider a class of optimal control problems for measure-valued nonlinear transport equations describing traffic flow problems on networks. The objective isto minimise/maximise macroscopic quantities, such as traffic volume or average speed,controlling few agents, for example smart traffic lights and automated cars. The measuretheoretic approach allows to study in a same setting local and nonlocal drivers interactionsand to consider the control variables as additional measures interacting ...

UMTS rapid response real-time seismic networks: implementation and strategies at INGV

Science.gov (United States)

Govoni, Aladino; Margheriti, Lucia; Moretti, Milena; Lauciani, Valentino; Sensale, Gianpaolo; Bucci, Augusto; Criscuoli, Fabio

2015-04-01

The benefits of portable real-time seismic networks are several and well known. During the management of a temporary experiment from the real-time data it is possible to detect and fix rapidly problems with power supply, time synchronization, disk failures and, most important, seismic signal quality degradation due to unexpected noise sources or sensor alignment/tampering. This usually minimizes field maintenance trips and maximizes both the quantity and the quality of the acquired data. When the area of the temporary experiment is not well monitored by the local permanent network, the real-time data from the temporary experiment can be fed to the permanent network monitoring system improving greatly both the real-time hypocentral locations and the final revised bulletin. All these benefits apply also in case of seismic crises when rapid deployment stations can significantly contribute to the aftershock analysis. Nowadays data transmission using meshed radio networks or satellite systems is not a big technological problem for a permanent seismic network where each site is optimized for the device power consumption and is usually installed by properly specialized technicians that can configure transmission devices and align antennas. This is not usually practical for temporary networks and especially for rapid response networks where the installation time is the main concern. These difficulties are substantially lowered using the now widespread UMTS technology for data transmission. A small (but sometimes power hungry) properly configured device with an omnidirectional antenna must be added to the station assembly. All setups are usually configured before deployment and this allows for an easy installation also by untrained personnel. We describe here the implementation of a UMTS based portable seismic network for both temporary experiments and rapid response applications developed at INGV. The first field experimentation of this approach dates back to the 2009 L

DReAM: Demand Response Architecture for Multi-level District Heating and Cooling Networks

Energy Technology Data Exchange (ETDEWEB)

Bhattacharya, Saptarshi; Chandan, Vikas; Arya, Vijay; Kar, Koushik

2017-05-19

In this paper, we exploit the inherent hierarchy of heat exchangers in District Heating and Cooling (DHC) networks and propose DReAM, a novel Demand Response (DR) architecture for Multi-level DHC networks. DReAM serves to economize system operation while still respecting comfort requirements of individual consumers. Contrary to many present day DR schemes that work on a consumer level granularity, DReAM works at a level of hierarchy above buildings, i.e. substations that supply heat to a group of buildings. This improves the overall DR scalability and reduce the computational complexity. In the first step of the proposed approach, mathematical models of individual substations and their downstream networks are abstracted into appropriately constructed low-complexity structural forms. In the second step, this abstracted information is employed by the utility to perform DR optimization that determines the optimal heat inflow to individual substations rather than buildings, in order to achieve the targeted objectives across the network. We validate the proposed DReAM framework through experimental results under different scenarios on a test network.

Multi-stimulus-responsive shape-memory polymer nanocomposite network cross-linked by cellulose nanocrystals.

Science.gov (United States)

Liu, Ye; Li, Ying; Yang, Guang; Zheng, Xiaotong; Zhou, Shaobing

2015-02-25

In this study, we developed a thermoresponsive and water-responsive shape-memory polymer nanocomposite network by chemically cross-linking cellulose nanocrystals (CNCs) with polycaprolactone (PCL) and polyethylene glycol (PEG). The nanocomposite network was fully characterized, including the microstructure, cross-link density, water contact angle, water uptake, crystallinity, thermal properties, and static and dynamic mechanical properties. We found that the PEG[60]-PCL[40]-CNC[10] nanocomposite exhibited excellent thermo-induced and water-induced shape-memory effects in water at 37 °C (close to body temperature), and the introduction of CNC clearly improved the mechanical properties of the mixture of both PEG and PCL polymers with low molecular weights. In addition, Alamar blue assays based on osteoblasts indicated that the nanocomposites possessed good cytocompatibility. Therefore, this thermoresponsive and water-responsive shape-memory nanocomposite could be potentially developed into a new smart biomaterial.

Performance measurement of the after-sales service network: Evidence from the automotive industry

Directory of Open Access Journals (Sweden)

Shahnoush Shahrouzi Fard

2015-10-01

Full Text Available This paper presents an empirical investigation to determine important factors influencing on customer satisfaction in after-sales service network of automotive industry. The study designs two questionnaires, one for measuring the quality of after-sales services and the other for measuring customers’ satisfaction. The study selects a sample of 265 randomly selected customers out of 850 people who received the services from an automotive firm in Iran. Cronbach alpha has calculated as 0.82, which is well above the minimum desirable level. Using Spearman correlation the study has detected a positive and meaningful relationship between services and customer satisfaction (r=0.48, Sig. =0.01, a positive relationship between being responsiveness and customer satisfaction (r=0.51, Sig. =0.01 and finally a positive relationship between speed of operation customer satisfaction (r=0.45, Sig. = 0.01. Moreover, there was a positive and meaningful relationship between cost of services and customer satisfaction (r=0.68, Sig. = 0.01 and a positive relationship between quality of services of after-sales services and customer satisfaction (r = 0.61, Sig. =0.01.

Network analysis of oyster transcriptome revealed a cascade of cellular responses during recovery after heat shock.

Directory of Open Access Journals (Sweden)

Lingling Zhang

Full Text Available Oysters, as a major group of marine bivalves, can tolerate a wide range of natural and anthropogenic stressors including heat stress. Recent studies have shown that oysters pretreated with heat shock can result in induced heat tolerance. A systematic study of cellular recovery from heat shock may provide insights into the mechanism of acquired thermal tolerance. In this study, we performed the first network analysis of oyster transcriptome by reanalyzing microarray data from a previous study. Network analysis revealed a cascade of cellular responses during oyster recovery after heat shock and identified responsive gene modules and key genes. Our study demonstrates the power of network analysis in a non-model organism with poor gene annotations, which can lead to new discoveries that go beyond the focus on individual genes.

Measuring co-authorship and networking-adjusted scientific impact.

Science.gov (United States)

Ioannidis, John P A

2008-07-23

Appraisal of the scientific impact of researchers, teams and institutions with productivity and citation metrics has major repercussions. Funding and promotion of individuals and survival of teams and institutions depend on publications and citations. In this competitive environment, the number of authors per paper is increasing and apparently some co-authors don't satisfy authorship criteria. Listing of individual contributions is still sporadic and also open to manipulation. Metrics are needed to measure the networking intensity for a single scientist or group of scientists accounting for patterns of co-authorship. Here, I define I(1) for a single scientist as the number of authors who appear in at least I(1) papers of the specific scientist. For a group of scientists or institution, I(n) is defined as the number of authors who appear in at least I(n) papers that bear the affiliation of the group or institution. I(1) depends on the number of papers authored N(p). The power exponent R of the relationship between I(1) and N(p) categorizes scientists as solitary (R>2.5), nuclear (R = 2.25-2.5), networked (R = 2-2.25), extensively networked (R = 1.75-2) or collaborators (Raccountable co-authorship behaviour in published articles.

Employing the Gini coefficient to measure participation inequality in treatment-focused Digital Health Social Networks.

Science.gov (United States)

van Mierlo, Trevor; Hyatt, Douglas; Ching, Andrew T

2016-01-01

Digital Health Social Networks (DHSNs) are common; however, there are few metrics that can be used to identify participation inequality. The objective of this study was to investigate whether the Gini coefficient, an economic measure of statistical dispersion traditionally used to measure income inequality, could be employed to measure DHSN inequality. Quarterly Gini coefficients were derived from four long-standing DHSNs. The combined data set included 625,736 posts that were generated from 15,181 actors over 18,671 days. The range of actors (8-2323), posts (29-28,684), and Gini coefficients (0.15-0.37) varied. Pearson correlations indicated statistically significant associations between number of actors and number of posts (0.527-0.835, p  addiction networks (0.619 and 0.276, p  networks ( t  = -4.305 and -5.934, p  network engagement. Further, mixed-methods research investigating quantitative performance metrics is required.

Benchmarking Measures of Network Controllability on Canonical Graph Models

Science.gov (United States)

Wu-Yan, Elena; Betzel, Richard F.; Tang, Evelyn; Gu, Shi; Pasqualetti, Fabio; Bassett, Danielle S.

2018-03-01

The control of networked dynamical systems opens the possibility for new discoveries and therapies in systems biology and neuroscience. Recent theoretical advances provide candidate mechanisms by which a system can be driven from one pre-specified state to another, and computational approaches provide tools to test those mechanisms in real-world systems. Despite already having been applied to study network systems in biology and neuroscience, the practical performance of these tools and associated measures on simple networks with pre-specified structure has yet to be assessed. Here, we study the behavior of four control metrics (global, average, modal, and boundary controllability) on eight canonical graphs (including Erdős-Rényi, regular, small-world, random geometric, Barábasi-Albert preferential attachment, and several modular networks) with different edge weighting schemes (Gaussian, power-law, and two nonparametric distributions from brain networks, as examples of real-world systems). We observe that differences in global controllability across graph models are more salient when edge weight distributions are heavy-tailed as opposed to normal. In contrast, differences in average, modal, and boundary controllability across graph models (as well as across nodes in the graph) are more salient when edge weight distributions are less heavy-tailed. Across graph models and edge weighting schemes, average and modal controllability are negatively correlated with one another across nodes; yet, across graph instances, the relation between average and modal controllability can be positive, negative, or nonsignificant. Collectively, these findings demonstrate that controllability statistics (and their relations) differ across graphs with different topologies and that these differences can be muted or accentuated by differences in the edge weight distributions. More generally, our numerical studies motivate future analytical efforts to better understand the mathematical

Chicago Ebola Response Network (CERN): A Citywide Cross-hospital Collaborative for Infectious Disease Preparedness.

Science.gov (United States)

Lateef, Omar; Hota, Bala; Landon, Emily; Kociolek, Larry K; Morita, Julie; Black, Stephanie; Noskin, Gary; Kelleher, Michael; Curell, Krista; Galat, Amy; Ansell, David; Segreti, John; Weber, Stephen G

2015-11-15

The 2014-2015 Ebola virus disease (EVD) epidemic and international public health emergency has been referred to as a "black swan" event, or an event that is unlikely, hard to predict, and highly impactful once it occurs. The Chicago Ebola Response Network (CERN) was formed in response to EVD and is capable of receiving and managing new cases of EVD, while also laying the foundation for a public health network that can anticipate, manage, and prevent the next black swan public health event. By sharing expertise, risk, and resources among 4 major academic centers, Chicago created a sustainable network to respond to the latest in a series of public health emergencies. In this respect, CERN is a roadmap for how a region can prepare to respond to public health emergencies, thereby preventing negative impacts through planning and implementation. © The Author 2015. Published by Oxford University Press on behalf of the Infectious Diseases Society of America. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Tariffing of energy measured consumers in the distribution network; Tariffering av energimaalte kunder i distribusjonsnettet

Energy Technology Data Exchange (ETDEWEB)

NONE

2006-12-20

Criteria for socio-economic effective tariffing of energy-measured clients in the distribution network are discussed (i.e. households, leisure homes and smaller business clients), this means consumers that do not have hourly measurements or effect measurements. The tariffs should be based on variable segments that reflect short-term marginal costs in the network (in practice loss of transfer) and fixed segments that to the least extent possible influence the consumers' decisions in the choice of energy solutions, both in short term and long term. High-priced energy segments and effect based fixed segments may give unfortunate socio-economic price signals compared to the marginal long-term network costs. A fixed segment per measurement unit is in principle completely neutral, but it is to some extent vulnerable to strategic adjustments if the consumers choose collective measurement. This is not necessarily a big problem in practice (author)

A Simple Network Architecture Accounts for Diverse Reward Time Responses in Primary Visual Cortex.

Science.gov (United States)

Huertas, Marco A; Hussain Shuler, Marshall G; Shouval, Harel Z

2015-09-16

Many actions performed by animals and humans depend on an ability to learn, estimate, and produce temporal intervals of behavioral relevance. Exemplifying such learning of cued expectancies is the observation of reward-timing activity in the primary visual cortex (V1) of rodents, wherein neural responses to visual cues come to predict the time of future reward as behaviorally experienced in the past. These reward-timing responses exhibit significant heterogeneity in at least three qualitatively distinct classes: sustained increase or sustained decrease in firing rate until the time of expected reward, and a class of cells that reach a peak in firing at the expected delay. We elaborate upon our existing model by including inhibitory and excitatory units while imposing simple connectivity rules to demonstrate what role these inhibitory elements and the simple architectures play in sculpting the response dynamics of the network. We find that simply adding inhibition is not sufficient for obtaining the different distinct response classes, and that a broad distribution of inhibitory projections is necessary for obtaining peak-type responses. Furthermore, although changes in connection strength that modulate the effects of inhibition onto excitatory units have a strong impact on the firing rate profile of these peaked responses, the network exhibits robustness in its overall ability to predict the expected time of reward. Finally, we demonstrate how the magnitude of expected reward can be encoded at the expected delay in the network and how peaked responses express this reward expectancy. Heterogeneity in single-neuron responses is a common feature of neuronal systems, although sometimes, in theoretical approaches, it is treated as a nuisance and seldom considered as conveying a different aspect of a signal. In this study, we focus on the heterogeneous responses in the primary visual cortex of rodents trained with a predictable delayed reward time. We describe under what

Modulation of network excitability by persistent activity: how working memory affects the response to incoming stimuli.

Directory of Open Access Journals (Sweden)

Elisa M Tartaglia

2015-02-01

Full Text Available Persistent activity and match effects are widely regarded as neuronal correlates of short-term storage and manipulation of information, with the first serving active maintenance and the latter supporting the comparison between memory contents and incoming sensory information. The mechanistic and functional relationship between these two basic neurophysiological signatures of working memory remains elusive. We propose that match signals are generated as a result of transient changes in local network excitability brought about by persistent activity. Neurons more active will be more excitable, and thus more responsive to external inputs. Accordingly, network responses are jointly determined by the incoming stimulus and the ongoing pattern of persistent activity. Using a spiking model network, we show that this mechanism is able to reproduce most of the experimental phenomenology of match effects as exposed by single-cell recordings during delayed-response tasks. The model provides a unified, parsimonious mechanistic account of the main neuronal correlates of working memory, makes several experimentally testable predictions, and demonstrates a new functional role for persistent activity.

Considerations on command and response language features for a network of heterogeneous autonomous computers

Science.gov (United States)

Engelberg, N.; Shaw, C., III

1984-01-01

The design of a uniform command language to be used in a local area network of heterogeneous, autonomous nodes is considered. After examining the major characteristics of such a network, and after considering the profile of a scientist using the computers on the net as an investigative aid, a set of reasonable requirements for the command language are derived. Taking into account the possible inefficiencies in implementing a guest-layered network operating system and command language on a heterogeneous net, the authors examine command language naming, process/procedure invocation, parameter acquisition, help and response facilities, and other features found in single-node command languages, and conclude that some features may extend simply to the network case, others extend after some restrictions are imposed, and still others require modifications. In addition, it is noted that some requirements considered reasonable (user accounting reports, for example) demand further study before they can be efficiently implemented on a network of the sort described.

An innovative and comprehensive technique to evaluate different measures of medication adherence: The network meta-analysis.

Science.gov (United States)

Tonin, Fernanda S; Wiecek, Elyssa; Torres-Robles, Andrea; Pontarolo, Roberto; Benrimoj, Shalom Charlie I; Fernandez-Llimos, Fernando; Garcia-Cardenas, Victoria

2018-05-19

Poor medication adherence is associated with adverse health outcomes and higher costs of care. However, inconsistencies in the assessment of adherence are found in the literature. To evaluate the effect of different measures of adherence in the comparative effectiveness of complex interventions to enhance patients' adherence to prescribed medications. A systematic review with network meta-analysis was performed. Electronic searches for relevant pairwise meta-analysis including trials of interventions that aimed to improve medication adherence were performed in PubMed. Data extraction was conducted with eligible trials evaluating short-period adherence follow-up (until 3 months) using any measure of adherence: self-report, pill count, or MEMS (medication event monitoring system). To standardize the results obtained with these different measures, an overall composite measure and an objective composite measure were also calculated. Network meta-analyses for each measure of adherence were built. Rank order and surface under the cumulative ranking curve analyses (SUCRA) were performed. Ninety-one trials were included in the network meta-analyses. The five network meta-analyses demonstrated robustness and reliability. Results obtained for all measures of adherence were similar across them and to both composite measures. For both composite measures, interventions comprising economic + technical components were the best option (90% of probability in SUCRA analysis) with statistical superiority against almost all other interventions and against standard care (odds ratio with 95% credibility interval ranging from 0.09 to 0.25 [0.02, 0.98]). The use of network meta-analysis was reliable to compare different measures of adherence of complex interventions in short-periods follow-up. Analyses with longer follow-up periods are needed to confirm these results. Different measures of adherence produced similar results. The use of composite measures revealed reliable alternatives

Communicative dynamics and the polyphony of corporate social responsibility in the network society

NARCIS (Netherlands)

Castello, I.; Morsing, M.; Schultz, F.

2013-01-01

This paper develops a media theoretical extension of the communicative view on corporate social responsibility by elaborating on the characteristics of network societies, arguing that new media increase the speed and connectivity, and lead to higher plurality and the potential polarization of

The design of nuclear radiation measuring instrument of embedded network

International Nuclear Information System (INIS)

Zhang Huaiqiang; Ge Liangquan; Xiong Shengqing

2009-01-01

The design and realization of nuclear radiation measuring instrument is introduced. Due to the current nuclear instrument often used serial interface to communicate the PC, it is widely used for simple design and easy operation. However, as the demand of remote data acquisition and the call of sharing resources, the design of embedded the TCP/IP protocol stack into MCU, it may send the nuclear signal in Internet. Some devices that link each other with the network can be networked. The design is not only realizing remote data acquisition and sharing resources, but also reducing costs and improving the maintainability of the system. (authors)

Network fault response of wind power plants in distribution systems during reverse power flows. Part II

NARCIS (Netherlands)

Boemer, J.C.; Gibescu, M.; vd Meijden, M.A.M.M.; Rawn, B.G.; Kling, W.L.

2013-01-01

Abstract—The ability of wind power park modules to control their response to transmission network faults allows for specification of new control features directed at stabilising the power system response during and after disturbances. However, the ‘effectiveness’ of these features in situations

Directed clustering coefficient as a measure of systemic risk in complex banking networks

Science.gov (United States)

Tabak, Benjamin M.; Takami, Marcelo; Rocha, Jadson M. C.; Cajueiro, Daniel O.; Souza, Sergio R. S.

2014-01-01

Recent literature has focused on the study of systemic risk in complex networks. It is clear now, after the crisis of 2008, that the aggregate behavior of the interaction among agents is not straightforward and it is very difficult to predict. Contributing to this debate, this paper shows that the directed clustering coefficient may be used as a measure of systemic risk in complex networks. Furthermore, using data from the Brazilian interbank network, we show that the directed clustering coefficient is negatively correlated with domestic interest rates.

Multimodal functional network connectivity: an EEG-fMRI fusion in network space.

Directory of Open Access Journals (Sweden)

Xu Lei

Full Text Available EEG and fMRI recordings measure the functional activity of multiple coherent networks distributed in the cerebral cortex. Identifying network interaction from the complementary neuroelectric and hemodynamic signals may help to explain the complex relationships between different brain regions. In this paper, multimodal functional network connectivity (mFNC is proposed for the fusion of EEG and fMRI in network space. First, functional networks (FNs are extracted using spatial independent component analysis (ICA in each modality separately. Then the interactions among FNs in each modality are explored by Granger causality analysis (GCA. Finally, fMRI FNs are matched to EEG FNs in the spatial domain using network-based source imaging (NESOI. Investigations of both synthetic and real data demonstrate that mFNC has the potential to reveal the underlying neural networks of each modality separately and in their combination. With mFNC, comprehensive relationships among FNs might be unveiled for the deep exploration of neural activities and metabolic responses in a specific task or neurological state.

Violence: heightened brain attentional network response is selectively muted in Down syndrome.

Science.gov (United States)

Anderson, Jeffrey S; Treiman, Scott M; Ferguson, Michael A; Nielsen, Jared A; Edgin, Jamie O; Dai, Li; Gerig, Guido; Korenberg, Julie R

2015-01-01

The ability to recognize and respond appropriately to threat is critical to survival, and the neural substrates subserving attention to threat may be probed using depictions of media violence. Whether neural responses to potential threat differ in Down syndrome is not known. We performed functional MRI scans of 15 adolescent and adult Down syndrome and 14 typically developing individuals, group matched by age and gender, during 50 min of passive cartoon viewing. Brain activation to auditory and visual features, violence, and presence of the protagonist and antagonist were compared across cartoon segments. fMRI signal from the brain's dorsal attention network was compared to thematic and violent events within the cartoons between Down syndrome and control samples. We found that in typical development, the brain's dorsal attention network was most active during violent scenes in the cartoons and that this was significantly and specifically reduced in Down syndrome. When the antagonist was on screen, there was significantly less activation in the left medial temporal lobe of individuals with Down syndrome. As scenes represented greater relative threat, the disparity between attentional brain activation in Down syndrome and control individuals increased. There was a reduction in the temporal autocorrelation of the dorsal attention network, consistent with a shortened attention span in Down syndrome. Individuals with Down syndrome exhibited significantly reduced activation in primary sensory cortices, and such perceptual impairments may constrain their ability to respond to more complex social cues such as violence. These findings may indicate a relative deficit in emotive perception of violence in Down syndrome, possibly mediated by impaired sensory perception and hypoactivation of medial temporal structures in response to threats, with relative preservation of activity in pro-social brain regions. These findings indicate that specific genetic differences associated

Network succession reveals the importance of competition in response to emulsified vegetable oil amendment for uranium bioremediation.

Science.gov (United States)

Deng, Ye; Zhang, Ping; Qin, Yujia; Tu, Qichao; Yang, Yunfeng; He, Zhili; Schadt, Christopher Warren; Zhou, Jizhong

2016-01-01

Discerning network interactions among different species/populations in microbial communities has evoked substantial interests in recent years, but little information is available about temporal dynamics of microbial network interactions in response to environmental perturbations. Here, we modified the random matrix theory-based network approach to discern network succession in groundwater microbial communities in response to emulsified vegetable oil (EVO) amendment for uranium bioremediation. Groundwater microbial communities from one control and seven monitor wells were analysed with a functional gene array (GeoChip 3.0), and functional molecular ecological networks (fMENs) at different time points were reconstructed. Our results showed that the network interactions were dramatically altered by EVO amendment. Dynamic and resilient succession was evident: fairly simple at the initial stage (Day 0), increasingly complex at the middle period (Days 4, 17, 31), most complex at Day 80, and then decreasingly complex at a later stage (140-269 days). Unlike previous studies in other habitats, negative interactions predominated in a time-series fMEN, suggesting strong competition among different microbial species in the groundwater systems after EVO injection. Particularly, several keystone sulfate-reducing bacteria showed strong negative interactions with their network neighbours. These results provide mechanistic understanding of the decreased phylogenetic diversity during environmental perturbations. © 2015 Society for Applied Microbiology and John Wiley & Sons Ltd.

Comparing intermittency and network measurements of words and their dependence on authorship

International Nuclear Information System (INIS)

Amancio, Diego Raphael; Oliveira, Osvaldo N Jr; Fontoura Costa, Luciano da; Altmann, Eduardo G

2011-01-01

Many features of texts and languages can now be inferred from statistical analyses using concepts from complex networks and dynamical systems. In this paper, we quantify how topological properties of word co-occurrence networks and intermittency (or burstiness) in word distribution depend on the style of authors. Our database contains 40 books by eight authors who lived in the nineteenth and twentieth centuries, for which the following network measurements were obtained: the clustering coefficient, average shortest path lengths and betweenness. We found that the two factors with stronger dependence on authors were skewness in the distribution of word intermittency and the average shortest paths. Other factors such as betweenness and Zipf's law exponent show only weak dependence on authorship. Also assessed was the contribution from each measurement to authorship recognition using three machine learning methods. The best performance was about 65% accuracy upon combining complex networks and intermittency features with the nearest-neighbor algorithm of automatic authorship. From a detailed analysis of the interdependence of the various metrics, it is concluded that the methods used here are complementary for providing short- and long-scale perspectives on texts, which are useful for applications such as the identification of topical words and information retrieval. (paper)

An ANP-based network to measure the impact of Lean production on organisational performance

Directory of Open Access Journals (Sweden)

José Luis Ruano Pérez

2018-04-01

Full Text Available Purpose: The main objective of this research is to design a decision-making network, based on the Analytic Network Process (ANP technique (Saaty, 1996, which will include the main elements to take into account when stating the effect that the application of LP techniques has got on the performance of an organisation, measured this through a Performance Measurement System (PMS. Design/methodology/approach: The authors have carried out a scientific literature search to state what the main LP techniques are –and how to group them into different clusters- and have then applied the ANP, its first phase, in order to design the decisional network. Findings: There is a gap in the literature when trying to identify and quantify to what extent the implementation of LP techniques affects to organisational performance. The ANP is an appropriate technique to do so due to the need of gathering and quantifying experts’ opinions. Originality/value: The designed ANP-based network to measure the impact of LP over organisational performance is a novel approach. This paper justifies its usage and paves the way to implement the rest of the ANP phases in future research work.

Transcription Factor Networks derived from Breast Cancer Stem Cells control the immune response in the Basal subtype

DEFF Research Database (Denmark)

da Silveira, W A; Palma, P V B; Sicchieri, R D

2017-01-01

Breast cancer is the most common cancer in women worldwide and metastatic dissemination is the principal factor related to death by this disease. Breast cancer stem cells (bCSC) are thought to be responsible for metastasis and chemoresistance. In this study, based on whole transcriptome analysis...... of these networks in patient tumours is predictive of engraftment success. Our findings point out a potential molecular mechanism underlying the balance between immune surveillance and EMT activation in breast cancer. This molecular mechanism may be useful to the development of new target therapies....... and IKZF3 transcription factors which correspond to immune response modulators. Immune response network expression is correlated with pathological response to chemotherapy, and in the Basal subtype is related to better recurrence-free survival. In patient-derived xenografts, the expression...

Communicative Dynamics and the Polyphony of Corporate Social Responsibility in the Network Society

DEFF Research Database (Denmark)

Castello, Itziar; Morsing, Mette; Schultz, Friederike

2013-01-01

This paper develops a media theoretical extension of the communicative view on corporate social responsibility by elaborating on the characteristics of network societies, arguing that new media increase the speed and connectivity, and lead to higher plurality and the potential polarization...... of reality constructions. We discuss the implications for corporate social responsibility of becoming more polyphonic and sketch the contours of “communicative legitimacy.” Finally, we present this special issue and develop some questions for future research....

Neural network modeling of air pollution in tunnels according to indirect measurements

International Nuclear Information System (INIS)

Kaverzneva, T; Lazovskaya, T; Tarkhov, D; Vasilyev, A

2016-01-01

The article deals with the problem of providing the necessary parameters of air of the working area in dead-end tunnels in the case of ventilation systems powered off. An ill-posed initialboundary problem for the diffusion equation is used as a mathematical model for a description and analysis of mass transfer processes in the tunnel. The neural network approach is applied to construct an approximate solution (regularization) of the identification problem in the case of the approximate measurement data and the set of interval parameters of the modeled system. Two types of model measurements included binary data are considered. The direct problem solution and the inverse problem regularization for the offered neural network approach are constructed uniformly. (paper)

Structural health monitoring and damage assessment using measured FRFs from multiple sensors. Part II. Decision making with RBF networks

Energy Technology Data Exchange (ETDEWEB)

Zang, C.; Friswell, M.I. [Dept. of Aerospace Engineering, Univ. of Bristol, Bristol (United Kingdom); Imregun, M. [Dept. of Mechanical Engineering, Imperial Coll., London (United Kingdom)

2003-07-01

This paper is the second of two papers concerned with structural health monitoring and damage assessment using measured FRFs from multiple sensors, and discusses the decision making technique with radial basis function (RBF) neural networks. In PART 1 of the paper, the correlation criteria showed their capability to indicate various changes to the structure's state. PART 2, presented here, develops the methodology of decision theory to identify precisely all of the structure states. Although, the statistical approach can be used for classification, interpreting the information is difficult. Neural network techniques have been proven to possess many advantages for classification due to their learning ability and good generalization. In this paper, the radial basis function neural network is applied for function approximation and recognition. The key idea is to partition the input space (the indicators of the correlation criteria) into a number of subspaces that are in the form of hyper spheres. Then, the widely used k-mean clustering algorithm was selected as a logical approach to detecting the structure states. A bookshelf structure with measured frequency responses from 24 accelerometers was used to demonstrate the effectiveness of the method. The results show the successful classification of all structure states, for instance, the undamaged and damage states, damage locations and damage levels, and the environmental variability. (orig.)

Laser tracker error determination using a network measurement

International Nuclear Information System (INIS)

Hughes, Ben; Forbes, Alistair; Lewis, Andrew; Sun, Wenjuan; Veal, Dan; Nasr, Karim

2011-01-01

We report on a fast, easily implemented method to determine all the geometrical alignment errors of a laser tracker, to high precision. The technique requires no specialist equipment and can be performed in less than an hour. The technique is based on the determination of parameters of a geometric model of the laser tracker, using measurements of a set of fixed target locations, from multiple locations of the tracker. After fitting of the model parameters to the observed data, the model can be used to perform error correction of the raw laser tracker data or to derive correction parameters in the format of the tracker manufacturer's internal error map. In addition to determination of the model parameters, the method also determines the uncertainties and correlations associated with the parameters. We have tested the technique on a commercial laser tracker in the following way. We disabled the tracker's internal error compensation, and used a five-position, fifteen-target network to estimate all the geometric errors of the instrument. Using the error map generated from this network test, the tracker was able to pass a full performance validation test, conducted according to a recognized specification standard (ASME B89.4.19-2006). We conclude that the error correction determined from the network test is as effective as the manufacturer's own error correction methodologies

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

Science.gov (United States)

Taylor, Dane; Larremore, Daniel B.

2012-09-01

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

SKYMONITOR: A Global Network for Sky Brightness Measurements

Science.gov (United States)

Davis, Donald R.; Mckenna, D.; Pulvermacher, R.; Everett, M.

2010-01-01

We are implementing a global network to measure sky brightness at dark-sky critical sites with the goal of creating a multi-decade database. The heart of this project is the Night Sky Brightness Monitor (NSBM), an autonomous 2 channel photometer which measures night sky brightness in the visual wavelengths (Mckenna et al, AAS 2009). Sky brightness is measured every minute at two elevation angles typically zenith and 20 degrees to monitor brightness and transparency. The NSBM consists of two parts, a remote unit and a base station with an internet connection. Currently these devices use 2.4 Ghz transceivers with a range of 100 meters. The remote unit is battery powered with daytime recharging using a solar panel. Data received by the base unit is transmitted via email protocol to IDA offices in Tucson where it will be collected, archived and made available to the user community via a web interface. Two other versions of the NSBM are under development: one for radio sensitive areas using an optical fiber link and the second that reads data directly to a laptop for sites without internet access. NSBM units are currently undergoing field testing at two observatories. With support from the National Science Foundation, we will construct and install a total of 10 units at astronomical observatories. With additional funding, we will locate additional units at other sites such as National Parks, dark-sky preserves and other sites where dark sky preservation is crucial. We will present the current comparison with the National Park Service sky monitoring camera. We anticipate that the SKYMONITOR network will be functioning by the end of 2010.

Measuring Long-Term Impact Based on Network Centrality: Unraveling Cinematic Citations

Science.gov (United States)

Spitz, Andreas; Horvát, Emőke-Ágnes

2014-01-01

Traditional measures of success for film, such as box-office revenue and critical acclaim, lack the ability to quantify long-lasting impact and depend on factors that are largely external to the craft itself. With the growing number of films that are being created and large-scale data becoming available through crowd-sourced online platforms, an endogenous measure of success that is not reliant on manual appraisal is of increasing importance. In this article we propose such a ranking method based on a combination of centrality indices. We apply the method to a network that contains several types of citations between more than 40,000 international feature films. From this network we derive a list of milestone films, which can be considered to constitute the foundations of cinema. In a comparison to various existing lists of ‘greatest’ films, such as personal favourite lists, voting lists, lists of individual experts, and lists deduced from expert polls, the selection of milestone films is more diverse in terms of genres, actors, and main creators. Our results shed light on the potential of a systematic quantitative investigation based on cinematic influences in identifying the most inspiring creations in world cinema. In a broader perspective, we introduce a novel research question to large-scale citation analysis, one of the most intriguing topics that have been at the forefront of scientific enquiries for the past fifty years and have led to the development of various network analytic methods. In doing so, we transfer widely studied approaches from citation analysis to the the newly emerging field of quantification efforts in the arts. The specific contribution of this paper consists in modelling the multidimensional cinematic references as a growing multiplex network and in developing a methodology for the identification of central films in this network. PMID:25295877

Measuring long-term impact based on network centrality: unraveling cinematic citations.

Directory of Open Access Journals (Sweden)

Andreas Spitz

Full Text Available Traditional measures of success for film, such as box-office revenue and critical acclaim, lack the ability to quantify long-lasting impact and depend on factors that are largely external to the craft itself. With the growing number of films that are being created and large-scale data becoming available through crowd-sourced online platforms, an endogenous measure of success that is not reliant on manual appraisal is of increasing importance. In this article we propose such a ranking method based on a combination of centrality indices. We apply the method to a network that contains several types of citations between more than 40,000 international feature films. From this network we derive a list of milestone films, which can be considered to constitute the foundations of cinema. In a comparison to various existing lists of 'greatest' films, such as personal favourite lists, voting lists, lists of individual experts, and lists deduced from expert polls, the selection of milestone films is more diverse in terms of genres, actors, and main creators. Our results shed light on the potential of a systematic quantitative investigation based on cinematic influences in identifying the most inspiring creations in world cinema. In a broader perspective, we introduce a novel research question to large-scale citation analysis, one of the most intriguing topics that have been at the forefront of scientific enquiries for the past fifty years and have led to the development of various network analytic methods. In doing so, we transfer widely studied approaches from citation analysis to the the newly emerging field of quantification efforts in the arts. The specific contribution of this paper consists in modelling the multidimensional cinematic references as a growing multiplex network and in developing a methodology for the identification of central films in this network.

Solar Radiation Measurement Using Raspberry Pi and Its Modelling Using Artificial Neural Networks

Directory of Open Access Journals (Sweden)

Priya Selvanathan Shanmuga

2016-01-01

Full Text Available The advent of solar energy as the best alternative to traditional energy sources has led to an extensive study on the measurement and prediction of solar radiation. Devices such as pyranometer, pyrrheliometer, global UV radiometer are used for the measurement of solar radiation. The solar radiation measuring instruments available at Innovation Center, MIT Manipal were integrated with a Raspberry Pi to allow remote access to the data through the university Local Area Network. The connections of the data loggers and the Raspberry Pi were enclosed in a plastic box to prevent damage from the rainfall and humidity in Manipal. The solar radiation data was used to validate an Artificial Neural Network model which was developed using various meterological data from 2011-2015.

So ware-Defined Network Solutions for Science Scenarios: Performance Testing Framework and Measurements

Energy Technology Data Exchange (ETDEWEB)

Settlemyer, Bradley [Los Alamos National Laboratory (LANL); Kettimuthu, R. [Argonne National Laboratory (ANL); Boley, Josh [Argonne National Laboratory (ANL); Katramatos, Dimitrios [Brookhaven National Laboratory (BNL); Rao, Nageswara S. [ORNL; Sen, Satyabrata [ORNL; Liu, Qiang [ORNL

2018-01-01

High-performance scientific work flows utilize supercomputers, scientific instruments, and large storage systems. Their executions require fast setup of a small number of dedicated network connections across the geographically distributed facility sites. We present Software-Defined Network (SDN) solutions consisting of site daemons that use dpctl, Floodlight, ONOS, or OpenDaylight controllers to set up these connections. The development of these SDN solutions could be quite disruptive to the infrastructure, while requiring a close coordination among multiple sites; in addition, the large number of possible controller and device combinations to investigate could make the infrastructure unavailable to regular users for extended periods of time. In response, we develop a Virtual Science Network Environment (VSNE) using virtual machines, Mininet, and custom scripts that support the development, testing, and evaluation of SDN solutions, without the constraints and expenses of multi-site physical infrastructures; furthermore, the chosen solutions can be directly transferred to production deployments. By complementing VSNE with a physical testbed, we conduct targeted performance tests of various SDN solutions to help choose the best candidates. In addition, we propose a switching response method to assess the setup times and throughput performances of different SDN solutions, and present experimental results that show their advantages and limitations.

The iso-response method: measuring neuronal stimulus integration with closed-loop experiments

Science.gov (United States)

Gollisch, Tim; Herz, Andreas V. M.

2012-01-01

Throughout the nervous system, neurons integrate high-dimensional input streams and transform them into an output of their own. This integration of incoming signals involves filtering processes and complex non-linear operations. The shapes of these filters and non-linearities determine the computational features of single neurons and their functional roles within larger networks. A detailed characterization of signal integration is thus a central ingredient to understanding information processing in neural circuits. Conventional methods for measuring single-neuron response properties, such as reverse correlation, however, are often limited by the implicit assumption that stimulus integration occurs in a linear fashion. Here, we review a conceptual and experimental alternative that is based on exploring the space of those sensory stimuli that result in the same neural output. As demonstrated by recent results in the auditory and visual system, such iso-response stimuli can be used to identify the non-linearities relevant for stimulus integration, disentangle consecutive neural processing steps, and determine their characteristics with unprecedented precision. Automated closed-loop experiments are crucial for this advance, allowing rapid search strategies for identifying iso-response stimuli during experiments. Prime targets for the method are feed-forward neural signaling chains in sensory systems, but the method has also been successfully applied to feedback systems. Depending on the specific question, “iso-response” may refer to a predefined firing rate, single-spike probability, first-spike latency, or other output measures. Examples from different studies show that substantial progress in understanding neural dynamics and coding can be achieved once rapid online data analysis and stimulus generation, adaptive sampling, and computational modeling are tightly integrated into experiments. PMID:23267315

Transcriptional regulatory network triggered by oxidative signals configures the early response mechanisms of japonica rice to chilling stress

Directory of Open Access Journals (Sweden)

Wijaya Edward

2010-01-01

Full Text Available Abstract Background The transcriptional regulatory network involved in low temperature response leading to acclimation has been established in Arabidopsis. In japonica rice, which can only withstand transient exposure to milder cold stress (10°C, an oxidative-mediated network has been proposed to play a key role in configuring early responses and short-term defenses. The components, hierarchical organization and physiological consequences of this network were further dissected by a systems-level approach. Results Regulatory clusters responding directly to oxidative signals were prominent during the initial 6 to 12 hours at 10°C. Early events mirrored a typical oxidative response based on striking similarities of the transcriptome to disease, elicitor and wounding induced processes. Targets of oxidative-mediated mechanisms are likely regulated by several classes of bZIP factors acting on as1/ocs/TGA-like element enriched clusters, ERF factors acting on GCC-box/JAre-like element enriched clusters and R2R3-MYB factors acting on MYB2-like element enriched clusters. Temporal induction of several H2O2-induced bZIP, ERF and MYB genes coincided with the transient H2O2 spikes within the initial 6 to 12 hours. Oxidative-independent responses involve DREB/CBF, RAP2 and RAV1 factors acting on DRE/CRT/rav1-like enriched clusters and bZIP factors acting on ABRE-like enriched clusters. Oxidative-mediated clusters were activated earlier than ABA-mediated clusters. Conclusion Genome-wide, physiological and whole-plant level analyses established a holistic view of chilling stress response mechanism of japonica rice. Early response regulatory network triggered by oxidative signals is critical for prolonged survival under sub-optimal temperature. Integration of stress and developmental responses leads to modulated growth and vigor maintenance contributing to a delay of plastic injuries.

Transcriptional regulatory network triggered by oxidative signals configures the early response mechanisms of japonica rice to chilling stress

KAUST Repository

Yun, Kil-Young

2010-01-25

Background: The transcriptional regulatory network involved in low temperature response leading to acclimation has been established in Arabidopsis. In japonica rice, which can only withstand transient exposure to milder cold stress (10C), an oxidative-mediated network has been proposed to play a key role in configuring early responses and short-term defenses. The components, hierarchical organization and physiological consequences of this network were further dissected by a systems-level approach.Results: Regulatory clusters responding directly to oxidative signals were prominent during the initial 6 to 12 hours at 10C. Early events mirrored a typical oxidative response based on striking similarities of the transcriptome to disease, elicitor and wounding induced processes. Targets of oxidative-mediated mechanisms are likely regulated by several classes of bZIP factors acting on as1/ocs/TGA-like element enriched clusters, ERF factors acting on GCC-box/JAre-like element enriched clusters and R2R3-MYB factors acting on MYB2-like element enriched clusters.Temporal induction of several H2O2-induced bZIP, ERF and MYB genes coincided with the transient H2O2spikes within the initial 6 to 12 hours. Oxidative-independent responses involve DREB/CBF, RAP2 and RAV1 factors acting on DRE/CRT/rav1-like enriched clusters and bZIP factors acting on ABRE-like enriched clusters. Oxidative-mediated clusters were activated earlier than ABA-mediated clusters.Conclusion: Genome-wide, physiological and whole-plant level analyses established a holistic view of chilling stress response mechanism of japonica rice. Early response regulatory network triggered by oxidative signals is critical for prolonged survival under sub-optimal temperature. Integration of stress and developmental responses leads to modulated growth and vigor maintenance contributing to a delay of plastic injuries. 2010 Yun et al; licensee BioMed Central Ltd.

Continuous-variable Measurement-device-independent Quantum Relay Network with Phase-sensitive Amplifiers

Science.gov (United States)

Li, Fei; Zhao, Wei; Guo, Ying

2018-01-01

Continuous-variable (CV) measurement-device-independent (MDI) quantum cryptography is now heading towards solving the practical problem of implementing scalable quantum networks. In this paper, we show that a solution can come from deploying an optical amplifier in the CV-MDI system, aiming to establish a high-rate quantum network. We suggest an improved CV-MDI protocol using the EPR states coupled with optical amplifiers. It can implement a practical quantum network scheme, where the legal participants create the secret correlations by using EPR states connecting to an untrusted relay via insecure links and applying the multi-entangled Greenberger-Horne-Zeilinger (GHZ) state analysis at relay station. Despite the possibility that the relay could be completely tampered with and imperfect links are subject to the powerful attacks, the legal participants are still able to extract a secret key from network communication. The numerical simulation indicates that the quantum network communication can be achieved in an asymmetric scenario, fulfilling the demands of a practical quantum network. Furthermore, we show that the use of optical amplifiers can compensate the inherent imperfections and improve the secret key rate of the CV-MDI system.

Measuring the democratic anchorage of governance networks

DEFF Research Database (Denmark)

Fotel, Trine; Sørensen, Eva; Torfing, Jacob

There has been a growing debate about the democratic problems and potentials of governance networks among political scientists and public managers. While some claim that governance networks tend to undermine democracy, others argue that they have the potential to improve and strengthen democracy....... This debate is found wanting in two respects. First of all, there has been far too little discussion about what democracy means in relation to pluricentric governance networks. Second, the current debate builds on the assumption that it is possible to give a clear-cut answer to the question of the democratic...... problems and merits of governance networks. This assumption is highly questionable, and prevents a more nuanced assessment of the democratic performance of governance networks. As such, it diverts the focus of attention away from the fact that governance networks may be democratic in some respects...

Using neural networks in software repositories

Science.gov (United States)

Eichmann, David (Editor); Srinivas, Kankanahalli; Boetticher, G.

1992-01-01

The first topic is an exploration of the use of neural network techniques to improve the effectiveness of retrieval in software repositories. The second topic relates to a series of experiments conducted to evaluate the feasibility of using adaptive neural networks as a means of deriving (or more specifically, learning) measures on software. Taken together, these two efforts illuminate a very promising mechanism supporting software infrastructures - one based upon a flexible and responsive technology.

Rapid Modeling of and Response to Large Earthquakes Using Real-Time GPS Networks (Invited)

Science.gov (United States)

Crowell, B. W.; Bock, Y.; Squibb, M. B.

2010-12-01

Real-time GPS networks have the advantage of capturing motions throughout the entire earthquake cycle (interseismic, seismic, coseismic, postseismic), and because of this, are ideal for real-time monitoring of fault slip in the region. Real-time GPS networks provide the perfect supplement to seismic networks, which operate with lower noise and higher sampling rates than GPS networks, but only measure accelerations or velocities, putting them at a supreme disadvantage for ascertaining the full extent of slip during a large earthquake in real-time. Here we report on two examples of rapid modeling of recent large earthquakes near large regional real-time GPS networks. The first utilizes Japan’s GEONET consisting of about 1200 stations during the 2003 Mw 8.3 Tokachi-Oki earthquake about 100 km offshore Hokkaido Island and the second investigates the 2010 Mw 7.2 El Mayor-Cucapah earthquake recorded by more than 100 stations in the California Real Time Network. The principal components of strain were computed throughout the networks and utilized as a trigger to initiate earthquake modeling. Total displacement waveforms were then computed in a simulated real-time fashion using a real-time network adjustment algorithm that fixes a station far away from the rupture to obtain a stable reference frame. Initial peak ground displacement measurements can then be used to obtain an initial size through scaling relationships. Finally, a full coseismic model of the event can be run minutes after the event, given predefined fault geometries, allowing emergency first responders and researchers to pinpoint the regions of highest damage. Furthermore, we are also investigating using total displacement waveforms for real-time moment tensor inversions to look at spatiotemporal variations in slip.

Bridging centrality: A new indicator to measure the positioning of actors in R&D networks

Energy Technology Data Exchange (ETDEWEB)

Scherngell, T.; Wanzenboeck, I.; Berge, L.

2016-07-01

In the recent past, we can observe growing interest in the STI community in the notion of positioning indicators, shifting emphasis to actors in the innovation process and their R&D inter-linkages with other actors. In relation to this, we suggest a new approach for assessing the positioning of actors relying on the notion of bridging centrality (BC). Based on the concept of bridging paths, i.e. a set of two links connecting three actors across three different aggregate nodes (e.g. organisations, regions or countries), we argue that triangulation in networks is a key issue for knowledge recombinations and the extension of an actor's knowledge base. As bridges are most often not empirically observable at the individual level of research teams, we propose an approximated BC measure that provides a flexible framework for dealing with the aggregation problem in positioning actors. Hereby, BC is viewed as a function of an aggregate node's (i) participation intensity in the network, (ii) its openness to other nodes (i.e. the relative outward orientation of network links), and iii) the diversification of links to other nodes. In doing so, we provide an integrative perspective that enables us to achieve a better understanding of the positioning of certain actors in R&D networks. An illustrative example on the co-patent network of European regions demonstrates the performance and usefulness of our BC measure for networks constructed at the aggregated level, i.e. regions in our example. A region's outward orientation and the diversification of its network links moderates the influence of regional scale on network centrality. This is a major strength of the measure, and it paves the way for future studies to examine the role of certain aggregate node's, and, by this, contributes to the debate on positioning indicators in the STI context. (Author)

Non-Contact Plant Growth Measurement Method and System Based on Ubiquitous Sensor Network Technologies

Directory of Open Access Journals (Sweden)

Intae Ryoo

2011-04-01

Full Text Available This paper proposes a non-contact plant growth measurement system using infrared sensors based on the ubiquitous sensor network (USN technology. The proposed system measures plant growth parameters such as the stem radius of plants using real-time non-contact methods, and generates diameter, cross-sectional area and thickening form of plant stems using this measured data. Non-contact sensors have been used not to cause any damage to plants during measurement of the growth parameters. Once the growth parameters are measured, they are transmitted to a remote server using the sensor network technology and analyzed in the application program server. The analyzed data are then provided for administrators and a group of interested users. The proposed plant growth measurement system has been designed and implemented using fixed-type and rotary-type infrared sensor based measurement methods and devices. Finally, the system performance is compared and verified with the measurement data that have been obtained by practical field experiments.

Finite-time hybrid projective synchronization of the drive-response complex networks with distributed-delay via adaptive intermittent control

Science.gov (United States)

Cheng, Lin; Yang, Yongqing; Li, Li; Sui, Xin

2018-06-01

This paper studies the finite-time hybrid projective synchronization of the drive-response complex networks. In the model, general transmission delays and distributed delays are also considered. By designing the adaptive intermittent controllers, the response network can achieve hybrid projective synchronization with the drive system in finite time. Based on finite-time stability theory and several differential inequalities, some simple finite-time hybrid projective synchronization criteria are derived. Two numerical examples are given to illustrate the effectiveness of the proposed method.

Integration of neural networks with fuzzy reasoning for measuring operational parameters in a nuclear reactor

International Nuclear Information System (INIS)

Ikonomopoulos, A.; Tsoukalas, L.H.

1993-01-01

A novel approach is described for measuring variables with operational significance in a complex system such as a nuclear reactor. The methodology is based on the integration of artificial neural networks with fuzzy reasoning. Neural networks are used to map dynamic time series to a set of user-defined linguistic labels called fuzzy values. The process takes place in a manner analogous to that of measurement. Hence, the entire procedure is referred to as virtual measurement and its software implementation as a virtual measuring device. An optimization algorithm based on information criteria and fuzzy algebra augments the process and assists in the identification of different states of the monitored parameter. The proposed technique is applied for monitoring parameters such as performance, valve position, transient type, and reactivity. The results obtained from the application of the neural network-fuzzy reasoning integration in a high power research reactor clearly demonstrate the excellent tolerance of the virtual measuring device to faulty signals as well as its ability to accommodate noisy inputs

Co-extinction in a host-parasite network: identifying key hosts for network stability.

Science.gov (United States)

Dallas, Tad; Cornelius, Emily

2015-08-17

Parasites comprise a substantial portion of total biodiversity. Ultimately, this means that host extinction could result in many secondary extinctions of obligate parasites and potentially alter host-parasite network structure. Here, we examined a highly resolved fish-parasite network to determine key hosts responsible for maintaining parasite diversity and network structure (quantified here as nestedness and modularity). We evaluated four possible host extinction orders and compared the resulting co-extinction dynamics to random extinction simulations; including host removal based on estimated extinction risk, parasite species richness and host level contributions to nestedness and modularity. We found that all extinction orders, except the one based on realistic extinction risk, resulted in faster declines in parasite diversity and network structure relative to random biodiversity loss. Further, we determined species-level contributions to network structure were best predicted by parasite species richness and host family. Taken together, we demonstrate that a small proportion of hosts contribute substantially to network structure and that removal of these hosts results in rapid declines in parasite diversity and network structure. As network stability can potentially be inferred through measures of network structure, our findings may provide insight into species traits that confer stability.

Identifying the relevant dependencies of the neural network response on characteristics of the input space

CERN Multimedia

CERN. Geneva

2018-01-01

This talk presents an approach to identify those characteristics of the neural network inputs that are most relevant for the response and therefore provides essential information to determine the systematic uncertainties.

Study on the three-station typical network deployments of workspace Measurement and Positioning System

Science.gov (United States)

Xiong, Zhi; Zhu, J. G.; Xue, B.; Ye, Sh. H.; Xiong, Y.

2013-10-01

As a novel network coordinate measurement system based on multi-directional positioning, workspace Measurement and Positioning System (wMPS) has outstanding advantages of good parallelism, wide measurement range and high measurement accuracy, which makes it to be the research hotspots and important development direction in the field of large-scale measurement. Since station deployment has a significant impact on the measurement range and accuracy, and also restricts the use-cost, the optimization method of station deployment was researched in this paper. Firstly, positioning error model was established. Then focusing on the small network consisted of three stations, the typical deployments and error distribution characteristics were studied. Finally, through measuring the simulated fuselage using typical deployments at the industrial spot and comparing the results with Laser Tracker, some conclusions are obtained. The comparison results show that under existing prototype conditions, I_3 typical deployment of which three stations are distributed in a straight line has an average error of 0.30 mm and the maximum error is 0.50 mm in the range of 12 m. Meanwhile, C_3 typical deployment of which three stations are uniformly distributed in the half-circumference of an circle has an average error of 0.17 mm and the maximum error is 0.28 mm. Obviously, C_3 typical deployment has a higher control effect on precision than I_3 type. The research work provides effective theoretical support for global measurement network optimization in the future work.

Thermo-, photo-, and mechano-responsive liquid crystal networks enable tunable photonic crystals.

Science.gov (United States)

Akamatsu, N; Hisano, K; Tatsumi, R; Aizawa, M; Barrett, C J; Shishido, A

2017-10-25

Tunable photonic crystals exhibiting optical properties that respond reversibly to external stimuli have been developed using liquid crystal networks (LCNs) and liquid crystal elastomers (LCEs). These tunable photonic crystals possess an inverse opal structure and are photo-responsive, but circumvent the usual requirement to contain dye molecules in the structure that often limit their applicability and cause optical degradation. Herein, we report tunable photonic crystal films that reversibly tune the reflection peak wavelength under thermo-, photo- and mechano-stimuli, through bilayering a stimuli-responsive LCN including azobenzene units with a colourless inverse opal film composed of non-responsive, flexible durable polymers. By mechanically deforming the azobenzene containing LCN via various stimuli, the reflection peak wavelength from the bilayered film assembly could be shifted on demand. We confirm that the reflection peak shift occurs due to the deformation of the stimuli-responsive layer propagating towards and into the inverse opal layer to change its shape in response, and this shift behaviour is repeatable without optical degradation.

Estimation of waves and ship responses using onboard measurements

DEFF Research Database (Denmark)

Montazeri, Najmeh

This thesis focuses on estimation of waves and ship responses using ship-board measurements. This is useful for development of operational safety and performance efficiency in connection with the broader concept of onboard decision support systems. Estimation of sea state is studied using a set...... of measured ship responses, a parametric description of directional wave spectra (a generalised JONSWAP model) and the transfer functions of the ship responses. The difference between the spectral moments of the measured ship responses and the corresponding theoretically calculated moments formulates a cost...... information. The model is tested on simulated data based on known unimodal and bimodal wave scenarios. The wave parameters in the output are then compared with the true wave parameters. In addition to the numerical experiments, two sets of full-scale measurements from container ships are analysed. Herein...

Measuring urban rainfall using microwave links from commercial cellular communication networks

NARCIS (Netherlands)

Overeem, A.; Leijnse, H.; Uijlenhoet, R.

2011-01-01

The estimation of rainfall using commercial microwave links is a new and promising measurement technique. Commercial link networks cover large parts of the land surface of the earth and have a high density, particularly in urban areas. Rainfall attenuates the electromagnetic signals transmitted

Measuring distance through dense weighted networks: The case of hospital-associated pathogens.

Directory of Open Access Journals (Sweden)

Tjibbe Donker

2017-08-01

Full Text Available Hospital networks, formed by patients visiting multiple hospitals, affect the spread of hospital-associated infections, resulting in differences in risks for hospitals depending on their network position. These networks are increasingly used to inform strategies to prevent and control the spread of hospital-associated pathogens. However, many studies only consider patients that are received directly from the initial hospital, without considering the effect of indirect trajectories through the network. We determine the optimal way to measure the distance between hospitals within the network, by reconstructing the English hospital network based on shared patients in 2014-2015, and simulating the spread of a hospital-associated pathogen between hospitals, taking into consideration that each intermediate hospital conveys a delay in the further spread of the pathogen. While the risk of transferring a hospital-associated pathogen between directly neighbouring hospitals is a direct reflection of the number of shared patients, the distance between two hospitals far-away in the network is determined largely by the number of intermediate hospitals in the network. Because the network is dense, most long distance transmission chains in fact involve only few intermediate steps, spreading along the many weak links. The dense connectivity of hospital networks, together with a strong regional structure, causes hospital-associated pathogens to spread from the initial outbreak in a two-step process: first, the directly surrounding hospitals are affected through the strong connections, second all other hospitals receive introductions through the multitude of weaker links. Although the strong connections matter for local spread, weak links in the network can offer ideal routes for hospital-associated pathogens to travel further faster. This hold important implications for infection prevention and control efforts: if a local outbreak is not controlled in time

Using Arduino microcontroller boards to measure response latencies.

Science.gov (United States)

Schubert, Thomas W; D'Ausilio, Alessandro; Canto, Rosario

2013-12-01

Latencies of buttonpresses are a staple of cognitive science paradigms. Often keyboards are employed to collect buttonpresses, but their imprecision and variability decreases test power and increases the risk of false positives. Response boxes and data acquisition cards are precise, but expensive and inflexible, alternatives. We propose using open-source Arduino microcontroller boards as an inexpensive and flexible alternative. These boards connect to standard experimental software using a USB connection and a virtual serial port, or by emulating a keyboard. In our solution, an Arduino measures response latencies after being signaled the start of a trial, and communicates the latency and response back to the PC over a USB connection. We demonstrated the reliability, robustness, and precision of this communication in six studies. Test measures confirmed that the error added to the measurement had an SD of less than 1 ms. Alternatively, emulation of a keyboard results in similarly precise measurement. The Arduino performs as well as a serial response box, and better than a keyboard. In addition, our setup allows for the flexible integration of other sensors, and even actuators, to extend the cognitive science toolbox.

Use of Response Time for Measuring Cognitive Ability

Directory of Open Access Journals (Sweden)

Patrick C. Kyllonen

2016-11-01

Full Text Available The purpose of this paper is to review some of the key literature on response time as it has played a role in cognitive ability measurement, providing a historical perspective as well as covering current research. We discuss the speed-level distinction, dimensions of speed and level in cognitive abilities frameworks, speed–accuracy tradeoff, approaches to addressing speed–accuracy tradeoff, analysis methods, particularly item response theory-based, response time models from cognitive psychology (ex-Gaussian function, and the diffusion model, and other uses of response time in testing besides ability measurement. We discuss several new methods that can be used to provide greater insight into the speed and level aspects of cognitive ability and speed–accuracy tradeoff decisions. These include item-level time limits, the use of feedback (e.g., CUSUMs, explicit scoring rules that combine speed and accuracy information (e.g., count down timing, and cognitive psychology models. We also review some of the key psychometric advances in modeling speed and level, which combine speed and ability measurement, address speed–accuracy tradeoff, allow for distinctions between response times on items responded to correctly and incorrectly, and integrate psychometrics with information-processing modeling. We suggest that the application of these models and tools is likely to advance both the science and measurement of human abilities for theory and applications.

Anomalous Anticipatory Responses in Networked Random Data

International Nuclear Information System (INIS)

Nelson, Roger D.; Bancel, Peter A.

2006-01-01

We examine an 8-year archive of synchronized, parallel time series of random data from a world spanning network of physical random event generators (REGs). The archive is a publicly accessible matrix of normally distributed 200-bit sums recorded at 1 Hz which extends from August 1998 to the present. The primary question is whether these data show non-random structure associated with major events such as natural or man-made disasters, terrible accidents, or grand celebrations. Secondarily, we examine the time course of apparently correlated responses. Statistical analyses of the data reveal consistent evidence that events which strongly affect people engender small but significant effects. These include suggestions of anticipatory responses in some cases, leading to a series of specialized analyses to assess possible non-random structure preceding precisely timed events. A focused examination of data collected around the time of earthquakes with Richter magnitude 6 and greater reveals non-random structure with a number of intriguing, potentially important features. Anomalous effects in the REG data are seen only when the corresponding earthquakes occur in populated areas. No structure is found if they occur in the oceans. We infer that an important contributor to the effect is the relevance of the earthquake to humans. Epoch averaging reveals evidence for changes in the data some hours prior to the main temblor, suggestive of reverse causation

On the feasibility of measuring urban air pollution by wireless distributed sensor networks.

Science.gov (United States)

Moltchanov, Sharon; Levy, Ilan; Etzion, Yael; Lerner, Uri; Broday, David M; Fishbain, Barak

2015-01-01

Accurate evaluation of air pollution on human-wellbeing requires high-resolution measurements. Standard air quality monitoring stations provide accurate pollution levels but due to their sparse distribution they cannot capture the highly resolved spatial variations within cities. Similarly, dedicated field campaigns can use tens of measurement devices and obtain highly dense spatial coverage but normally deployment has been limited to short periods of no more than few weeks. Nowadays, advances in communication and sensory technologies enable the deployment of dense grids of wireless distributed air monitoring nodes, yet their sensor ability to capture the spatiotemporal pollutant variability at the sub-neighborhood scale has never been thoroughly tested. This study reports ambient measurements of gaseous air pollutants by a network of six wireless multi-sensor miniature nodes that have been deployed in three urban sites, about 150 m apart. We demonstrate the network's capability to capture spatiotemporal concentration variations at an exceptional fine resolution but highlight the need for a frequent in-situ calibration to maintain the consistency of some sensors. Accordingly, a procedure for a field calibration is proposed and shown to improve the system's performance. Overall, our results support the compatibility of wireless distributed sensor networks for measuring urban air pollution at a sub-neighborhood spatial resolution, which suits the requirement for highly spatiotemporal resolved measurements at the breathing-height when assessing exposure to urban air pollution. Copyright © 2014 Elsevier B.V. All rights reserved.

Connectivity, excitability and activity patterns in neuronal networks

International Nuclear Information System (INIS)

Le Feber, Joost; Stoyanova, Irina I; Chiappalone, Michela

2014-01-01

Extremely synchronized firing patterns such as those observed in brain diseases like epilepsy may result from excessive network excitability. Although network excitability is closely related to (excitatory) connectivity, a direct measure for network excitability remains unavailable. Several methods currently exist for estimating network connectivity, most of which are related to cross-correlation. An example is the conditional firing probability (CFP) analysis which calculates the pairwise probability (CFP i,j ) that electrode j records an action potential at time t = τ, given that electrode i recorded a spike at t = 0. However, electrode i often records multiple spikes within the analysis interval, and CFP values are biased by the on-going dynamic state of the network. Here we show that in a linear approximation this bias may be removed by deconvoluting CFP i,j with the autocorrelation of i (i.e. CFP i,i ), to obtain the single pulse response (SPR i,j )—the average response at electrode j to a single spike at electrode i. Thus, in a linear system SPRs would be independent of the dynamic network state. Nonlinear components of synaptic transmission, such as facilitation and short term depression, will however still affect SPRs. Therefore SPRs provide a clean measure of network excitability. We used carbachol and ghrelin to moderately activate cultured cortical networks to affect their dynamic state. Both neuromodulators transformed the bursting firing patterns of the isolated networks into more dispersed firing. We show that the influence of the dynamic state on SPRs is much smaller than the effect on CFPs, but not zero. The remaining difference reflects the alteration in network excitability. We conclude that SPRs are less contaminated by the dynamic network state and that mild excitation may decrease network excitability, possibly through short term synaptic depression. (papers)

IAEA emergency response network ERNET. Emergency preparedness and response. Date effective: 1 December 2002

International Nuclear Information System (INIS)

2003-04-01

The Parties to the Convention on Assistance in the Case of a Nuclear Accident or Radiological Emergency have undertaken to co-operate among themselves and with the IAEA in facilitating the prompt provision of assistance in the event of a nuclear accident or radiological emergency, and in minimizing the consequences and in protecting life, property and the environment from the effects of any radioactive releases. As part of the IAEA strategy for supporting such co-operation, the Secretariat of the IAEA is establishing a global Emergency Response Network (ERNET) of teams suitably qualified to respond rapidly, on a regional basis, to nuclear accidents or radiological emergencies. This manual sets out the criteria and requirements to be met by ERNET teams. It is intended for use by institutions in Member States in developing, applying and maintaining their emergency response capabilities and in implementing quality assurance programmes within the context of ERNET. The manual is worded on the assumption that a State Competent Authority designated as the body responsible for reacting to nuclear accidents or radiological emergencies which occur outside the jurisdiction of that State will be the State Contact Point for receiving requests for assistance from the IAEA under the Convention on Assistance in the Case of a Nuclear Accident or Radiological Emergency

IAEA emergency response network ERNET. Emergency preparedness and response. Date effective: 1 December 2000

International Nuclear Information System (INIS)

2000-12-01

The Parties to the Convention on Assistance in the Case of a Nuclear Accident or Radiological Emergency have undertaken to co-operate among themselves and with the IAEA in facilitating the prompt provision of assistance in the event of a nuclear accident or radiological emergency, and in minimizing the consequences and in protecting life, property and the environment from the effects of any radioactive releases. As part of the IAEA strategy for supporting such co-operation, the Secretariat of the IAEA is establishing a global Emergency Response Network (ERNET) of teams suitably qualified to respond rapidly, on a regional basis, to nuclear accidents or radiological emergencies. This manual sets out the criteria and requirements to be met by ERNET teams. It is intended for use by institutions in Member States in developing, applying and maintaining their emergency response capabilities and in implementing quality assurance programmes within the context of ERNET. The manual is worded on the assumption that a State Competent Authority designated as the body responsible for reacting to nuclear accidents or radiological emergencies which occur outside the jurisdiction of that State will be the State Contact Point for receiving requests for assistance from the IAEA under the Convention on Assistance in the Case of a Nuclear Accident or Radiological Emergency

Network Mechanisms of Clinical Response to Transcranial Magnetic Stimulation in Posttraumatic Stress Disorder and Major Depressive Disorder.

Science.gov (United States)

Philip, Noah S; Barredo, Jennifer; van 't Wout-Frank, Mascha; Tyrka, Audrey R; Price, Lawrence H; Carpenter, Linda L

2018-02-01

Repetitive transcranial magnetic stimulation (TMS) therapy can modulate pathological neural network functional connectivity in major depressive disorder (MDD). Posttraumatic stress disorder is often comorbid with MDD, and symptoms of both disorders can be alleviated with TMS therapy. This is the first study to evaluate TMS-associated changes in connectivity in patients with comorbid posttraumatic stress disorder and MDD. Resting-state functional connectivity magnetic resonance imaging was acquired before and after TMS therapy in 33 adult outpatients in a prospective open trial. TMS at 5 Hz was delivered, in up to 40 daily sessions, to the left dorsolateral prefrontal cortex. Analyses used a priori seeds relevant to TMS, posttraumatic stress disorder, or MDD (subgenual anterior cingulate cortex [sgACC], left dorsolateral prefrontal cortex, hippocampus, and basolateral amygdala) to identify imaging predictors of response and to evaluate clinically relevant changes in connectivity after TMS, followed by leave-one-out cross-validation. Imaging results were explored using data-driven multivoxel pattern activation. More negative pretreatment connectivity between the sgACC and the default mode network predicted clinical improvement, as did more positive amygdala-to-ventromedial prefrontal cortex connectivity. After TMS, symptom reduction was associated with reduced connectivity between the sgACC and the default mode network, left dorsolateral prefrontal cortex, and insula, and reduced connectivity between the hippocampus and the salience network. Multivoxel pattern activation confirmed seed-based predictors and correlates of treatment outcomes. These results highlight the central role of the sgACC, default mode network, and salience network as predictors of TMS response and suggest their involvement in mechanisms of action. Furthermore, this work indicates that there may be network-based biomarkers of clinical response relevant to these commonly comorbid disorders

Information transmission in genetic regulatory networks: a review

International Nuclear Information System (INIS)

Tkacik, Gasper; Walczak, Aleksandra M

2011-01-01

Genetic regulatory networks enable cells to respond to changes in internal and external conditions by dynamically coordinating their gene expression profiles. Our ability to make quantitative measurements in these biochemical circuits has deepened our understanding of what kinds of computations genetic regulatory networks can perform, and with what reliability. These advances have motivated researchers to look for connections between the architecture and function of genetic regulatory networks. Transmitting information between a network's inputs and outputs has been proposed as one such possible measure of function, relevant in certain biological contexts. Here we summarize recent developments in the application of information theory to gene regulatory networks. We first review basic concepts in information theory necessary for understanding recent work. We then discuss the functional complexity of gene regulation, which arises from the molecular nature of the regulatory interactions. We end by reviewing some experiments that support the view that genetic networks responsible for early development of multicellular organisms might be maximizing transmitted 'positional information'. (topical review)

A Measurement Study of the Structured Overlay Network in P2P File-Sharing Systems

Directory of Open Access Journals (Sweden)

Mo Zhou

2007-01-01

Full Text Available The architecture of P2P file-sharing applications has been developing to meet the needs of large scale demands. The structured overlay network, also known as DHT, has been used in these applications to improve the scalability, and robustness of the system, and to make it free from single-point failure. We believe that the measurement study of the overlay network used in the real file-sharing P2P systems can provide guidance for the designing of such systems, and improve the performance of the system. In this paper, we perform the measurement in two different aspects. First, a modified client is designed to provide view to the overlay network from a single-user vision. Second, the instances of crawler programs deployed in many nodes managed to crawl the user information of the overlay network as much as possible. We also find a vulnerability in the overlay network, combined with the character of the DNS service, a more serious DDoS attack can be launched.

Optimal and secure measurement protocols for quantum sensor networks

Science.gov (United States)

Eldredge, Zachary; Foss-Feig, Michael; Gross, Jonathan A.; Rolston, S. L.; Gorshkov, Alexey V.

2018-04-01

Studies of quantum metrology have shown that the use of many-body entangled states can lead to an enhancement in sensitivity when compared with unentangled states. In this paper, we quantify the metrological advantage of entanglement in a setting where the measured quantity is a linear function of parameters individually coupled to each qubit. We first generalize the Heisenberg limit to the measurement of nonlocal observables in a quantum network, deriving a bound based on the multiparameter quantum Fisher information. We then propose measurement protocols that can make use of Greenberger-Horne-Zeilinger (GHZ) states or spin-squeezed states and show that in the case of GHZ states the protocol is optimal, i.e., it saturates our bound. We also identify nanoscale magnetic resonance imaging as a promising setting for this technology.

Measurement of agricultural parameters using wireless sensor network (WSN)

Science.gov (United States)

Guaña-Moya, Javier; Sánchez-Almeida, Tarquino; Salgado-Reyes, Nelson

2018-04-01

The technological advances have allowed to create new applications in telecommunications, applying low power and reduced costs in their equipment, thus achieving the evolution of new wireless networks or also denominated Wireless Sensor Network. These technologies allow the generation of measurements and analysis of environmental parameter data and soil. Precision agriculture requires parameters for the improvement of production, obtained through WSN technologies. This research analyzes the climatic requirements and soil parameters in a rose plantation in a greenhouse at an altitude of 3,100 meters above sea level. In the present investigation, maximum parameters were obtained in the production of roses, which are in the optimum range of production, whereas the minimum parameters of temperature, humidity and luminosity, evidenced that these parameters can damage the plants, since temperatures less than 10 °C slow down the growth of the plant and allow the proliferation of diseases and fungi.

Transcriptional regulatory network triggered by oxidative signals configures the early response mechanisms of japonica rice to chilling stress

KAUST Repository

Yun, Kil-Young; Park, Myoung Ryoul; Mohanty, Bijayalaxmi; Herath, Venura; Xu, Fuyu; Mauleon, Ramil; Wijaya, Edward; Bajic, Vladimir B.; Bruskiewich, Richard; de los Reyes, Benildo G

2010-01-01

-plant level analyses established a holistic view of chilling stress response mechanism of japonica rice. Early response regulatory network triggered by oxidative signals is critical for prolonged survival under sub-optimal temperature. Integration of stress

Using item response theory to measure extreme response style in marketing research

NARCIS (Netherlands)

de Jong, Martijn G.; Steenkamp, Jan-Benedict E.M.; Fox, Gerardus J.A.; Baumgartner, Hans

2008-01-01

Extreme response style (ERS) is an important threat to the validity of survey-based marketing research. In this article, the authors present a new item response theory–based model for measuring ERS. This model contributes to the ERS literature in two ways. First, the method improves on existing

The Jackson Queueing Network Model Built Using Poisson Measures. Application To A Bank Model

Directory of Open Access Journals (Sweden)

Ciuiu Daniel

2014-07-01

Full Text Available In this paper we will build a bank model using Poisson measures and Jackson queueing networks. We take into account the relationship between the Poisson and the exponential distributions, and we consider for each credit/deposit type a node where shocks are modeled as the compound Poisson processes. The transmissions of the shocks are modeled as moving between nodes in Jackson queueing networks, the external shocks are modeled as external arrivals, and the absorption of shocks as departures from the network.

Network analysis of surgical innovation: Measuring value and the virality of diffusion in robotic surgery.

Science.gov (United States)

Garas, George; Cingolani, Isabella; Panzarasa, Pietro; Darzi, Ara; Athanasiou, Thanos

2017-01-01

Existing surgical innovation frameworks suffer from a unifying limitation, their qualitative nature. A rigorous approach to measuring surgical innovation is needed that extends beyond detecting simply publication, citation, and patent counts and instead uncovers an implementation-based value from the structure of the entire adoption cascades produced over time by diffusion processes. Based on the principles of evidence-based medicine and existing surgical regulatory frameworks, the surgical innovation funnel is described. This illustrates the different stages through which innovation in surgery typically progresses. The aim is to propose a novel and quantitative network-based framework that will permit modeling and visualizing innovation diffusion cascades in surgery and measuring virality and value of innovations. Network analysis of constructed citation networks of all articles concerned with robotic surgery (n = 13,240, Scopus®) was performed (1974-2014). The virality of each cascade was measured as was innovation value (measured by the innovation index) derived from the evidence-based stage occupied by the corresponding seed article in the surgical innovation funnel. The network-based surgical innovation metrics were also validated against real world big data (National Inpatient Sample-NIS®). Rankings of surgical innovation across specialties by cascade size and structural virality (structural depth and width) were found to correlate closely with the ranking by innovation value (Spearman's rank correlation coefficient = 0.758 (p = 0.01), 0.782 (p = 0.008), 0.624 (p = 0.05), respectively) which in turn matches the ranking based on real world big data from the NIS® (Spearman's coefficient = 0.673;p = 0.033). Network analysis offers unique new opportunities for understanding, modeling and measuring surgical innovation, and ultimately for assessing and comparing generative value between different specialties. The novel surgical innovation metrics developed may

Structure, function and networks of transcription factors involved in abiotic stress responses

DEFF Research Database (Denmark)

Lindemose, Søren; O'Shea, Charlotte; Jensen, Michael Krogh

2013-01-01

Transcription factors (TFs) are master regulators of abiotic stress responses in plants. This review focuses on TFs from seven major TF families, known to play functional roles in response to abiotic stresses, including drought, high salinity, high osmolarity, temperature extremes...... and the phytohormone ABA. Although ectopic expression of several TFs has improved abiotic stress tolerance in plants, fine-tuning of TF expression and protein levels remains a challenge to avoid crop yield loss. To further our understanding of TFs in abiotic stress responses, emerging gene regulatory networks based...... on TFs and their direct targets genes are presented. These revealed components shared between ABA-dependent and independent signaling as well as abiotic and biotic stress signaling. Protein structure analysis suggested that TFs hubs of large interactomes have extended regions with protein intrinsic...

Tiny Integrated Network Analyzer for Noninvasive Measurements of Electrically Small Antennas

DEFF Research Database (Denmark)

Buskgaard, Emil Feldborg; Krøyer, Ben; Tatomirescu, Alexandru

2016-01-01

the system. The tiny integrated network analyzer is a stand-alone Arduino-based measurement system that utilizes the transmit signal of the system under test as its reference. It features a power meter with triggering ability, on-board memory, universal serial bus, and easy extendibility with general...

Simulation of emergency response operations for a static chemical spill within a building using an opportunistic resource utilization network

NARCIS (Netherlands)

Lilien, L.T.; Elbes, M.W.; Ben Othmane, L.; Salih, R.M.

2013-01-01

We investigate supporting emergency response operations with opportunistic resource utilization networks ("oppnets"), based on a network paradigm for inviting and integrating diverse devices and systems available in the environment. We simulate chemical spill on a single floor of a building and

Full Scale Earth Fault Experiments on 10 kV laboratory network with comparative Measurements on Conventional CT's and VT's

DEFF Research Database (Denmark)

Sørensen, Stefan; Nielsen, Hans Ove; Bak-Jensen, Birgitte

2002-01-01

In this paper we present a result of a full scale earth fault carried out on the 10 kV research/laboratory distribution network at Kyndbyvaerket Denmark in May 2001. The network is compensated through a Petersen-Coil and current and voltage measurements were measured on conventional current....... The necessity of high bandwidth measurement equipment for earth fault measurements on compensated distribution networks can be undermined, since it will be shown that the transient signal transfer through conventional CT?s and VT?s for further signal analysis is sufficient. Caused the inadequacy three phase...

Invasive species information networks: Collaboration at multiple scales for prevention, early detection, and rapid response to invasive alien species

Science.gov (United States)

Simpson, Annie; Jarnevich, Catherine S.; Madsen, John; Westbrooks, Randy G.; Fournier, Christine; Mehrhoff, Les; Browne, Michael; Graham, Jim; Sellers, Elizabeth A.

2009-01-01

Accurate analysis of present distributions and effective modeling of future distributions of invasive alien species (IAS) are both highly dependent on the availability and accessibility of occurrence data and natural history information about the species. Invasive alien species monitoring and detection networks (such as the Invasive Plant Atlas of New England and the Invasive Plant Atlas of the MidSouth) generate occurrence data at local and regional levels within the United States, which are shared through the US National Institute of Invasive Species Science. The Inter-American Biodiversity Information Network's Invasives Information Network (I3N), facilitates cooperation on sharing invasive species occurrence data throughout the Western Hemisphere. The I3N and other national and regional networks expose their data globally via the Global Invasive Species Information Network (GISIN). International and interdisciplinary cooperation on data sharing strengthens cooperation on strategies and responses to invasions. However, limitations to effective collaboration among invasive species networks leading to successful early detection and rapid response to invasive species include: lack of interoperability; data accessibility; funding; and technical expertise. This paper proposes various solutions to these obstacles at different geographic levels and briefly describes success stories from the invasive species information networks mentioned above. Using biological informatics to facilitate global information sharing is especially critical in invasive species science, as research has shown that one of the best indicators of the invasiveness of a species is whether it has been invasive elsewhere. Data must also be shared across disciplines because natural history information (e.g. diet, predators, habitat requirements, etc.) about a species in its native range is vital for effective prevention, detection, and rapid response to an invasion. Finally, it has been our

Accuracy assessment of the scalar network analyzer using sliding termination techniques

DEFF Research Database (Denmark)

Knudsen, Bent; Engen, Glenn F.; Guldbrandsen, Birthe

1989-01-01

In the absence of phase response the major, if not the primary, sources of error in the scalar network analyzer are the imperfect directivity, etc., associated with its internal and frequently inaccessible test set or measurement network. An explicit expression is obtained for this error in terms...

Mean and turbulent mass flux measurements in an idealised street network.

Science.gov (United States)

Carpentieri, Matteo; Robins, Alan G; Hayden, Paul; Santi, Edoardo

2018-03-01

Pollutant mass fluxes are rarely measured in the laboratory, especially their turbulent component. They play a major role in the dispersion of gases in urban areas and modern mathematical models often attempt some sort of parametrisation. An experimental technique to measure mean and turbulent fluxes in an idealised urban array was developed and applied to improve our understanding of how the fluxes are distributed in a dense street canyon network. As expected, horizontal advective scalar fluxes were found to be dominant compared with the turbulent components. This is an important result because it reduces the complexity in developing parametrisations for street network models. On the other hand, vertical mean and turbulent fluxes appear to be approximately of the same order of magnitude. Building height variability does not appear to affect the exchange process significantly, while the presence of isolated taller buildings upwind of the area of interest does. One of the most interesting results, again, is the fact that even very simple and regular geometries lead to complex advective patterns at intersections: parametrisations derived from measurements in simpler geometries are unlikely to capture the full complexity of a real urban area. Copyright © 2017 Elsevier Ltd. All rights reserved.

A novel method to produce nonlinear empirical physical formulas for experimental nonlinear electro-optical responses of doped nematic liquid crystals: Feedforward neural network approach

Energy Technology Data Exchange (ETDEWEB)

Yildiz, Nihat, E-mail: nyildiz@cumhuriyet.edu.t [Cumhuriyet University, Faculty of Science and Literature, Department of Physics, 58140 Sivas (Turkey); San, Sait Eren; Okutan, Mustafa [Department of Physics, Gebze Institute of Technology, P.O. Box 141, Gebze 41400, Kocaeli (Turkey); Kaya, Hueseyin [Cumhuriyet University, Faculty of Science and Literature, Department of Physics, 58140 Sivas (Turkey)

2010-04-15

Among other significant obstacles, inherent nonlinearity in experimental physical response data poses severe difficulty in empirical physical formula (EPF) construction. In this paper, we applied a novel method (namely layered feedforward neural network (LFNN) approach) to produce explicit nonlinear EPFs for experimental nonlinear electro-optical responses of doped nematic liquid crystals (NLCs). Our motivation was that, as we showed in a previous theoretical work, an appropriate LFNN, due to its exceptional nonlinear function approximation capabilities, is highly relevant to EPF construction. Therefore, in this paper, we obtained excellently produced LFNN approximation functions as our desired EPFs for above-mentioned highly nonlinear response data of NLCs. In other words, by using suitable LFNNs, we successfully fitted the experimentally measured response and predicted the new (yet-to-be measured) response data. The experimental data (response versus input) were diffraction and dielectric properties versus bias voltage; and they were all taken from our previous experimental work. We conclude that in general, LFNN can be applied to construct various types of EPFs for the corresponding various nonlinear physical perturbation (thermal, electronic, molecular, electric, optical, etc.) data of doped NLCs.

A novel method to produce nonlinear empirical physical formulas for experimental nonlinear electro-optical responses of doped nematic liquid crystals: Feedforward neural network approach

International Nuclear Information System (INIS)

Yildiz, Nihat; San, Sait Eren; Okutan, Mustafa; Kaya, Hueseyin

2010-01-01

Among other significant obstacles, inherent nonlinearity in experimental physical response data poses severe difficulty in empirical physical formula (EPF) construction. In this paper, we applied a novel method (namely layered feedforward neural network (LFNN) approach) to produce explicit nonlinear EPFs for experimental nonlinear electro-optical responses of doped nematic liquid crystals (NLCs). Our motivation was that, as we showed in a previous theoretical work, an appropriate LFNN, due to its exceptional nonlinear function approximation capabilities, is highly relevant to EPF construction. Therefore, in this paper, we obtained excellently produced LFNN approximation functions as our desired EPFs for above-mentioned highly nonlinear response data of NLCs. In other words, by using suitable LFNNs, we successfully fitted the experimentally measured response and predicted the new (yet-to-be measured) response data. The experimental data (response versus input) were diffraction and dielectric properties versus bias voltage; and they were all taken from our previous experimental work. We conclude that in general, LFNN can be applied to construct various types of EPFs for the corresponding various nonlinear physical perturbation (thermal, electronic, molecular, electric, optical, etc.) data of doped NLCs.

Measuring symmetry, asymmetry and randomness in neural network connectivity.

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Umberto Esposito

Full Text Available Cognitive functions are stored in the connectome, the wiring diagram of the brain, which exhibits non-random features, so-called motifs. In this work, we focus on bidirectional, symmetric motifs, i.e. two neurons that project to each other via connections of equal strength, and unidirectional, non-symmetric motifs, i.e. within a pair of neurons only one neuron projects to the other. We hypothesise that such motifs have been shaped via activity dependent synaptic plasticity processes. As a consequence, learning moves the distribution of the synaptic connections away from randomness. Our aim is to provide a global, macroscopic, single parameter characterisation of the statistical occurrence of bidirectional and unidirectional motifs. To this end we define a symmetry measure that does not require any a priori thresholding of the weights or knowledge of their maximal value. We calculate its mean and variance for random uniform or Gaussian distributions, which allows us to introduce a confidence measure of how significantly symmetric or asymmetric a specific configuration is, i.e. how likely it is that the configuration is the result of chance. We demonstrate the discriminatory power of our symmetry measure by inspecting the eigenvalues of different types of connectivity matrices. We show that a Gaussian weight distribution biases the connectivity motifs to more symmetric configurations than a uniform distribution and that introducing a random synaptic pruning, mimicking developmental regulation in synaptogenesis, biases the connectivity motifs to more asymmetric configurations, regardless of the distribution. We expect that our work will benefit the computational modelling community, by providing a systematic way to characterise symmetry and asymmetry in network structures. Further, our symmetry measure will be of use to electrophysiologists that investigate symmetry of network connectivity.

Measuring symmetry, asymmetry and randomness in neural network connectivity.

Science.gov (United States)

Esposito, Umberto; Giugliano, Michele; van Rossum, Mark; Vasilaki, Eleni

2014-01-01

Cognitive functions are stored in the connectome, the wiring diagram of the brain, which exhibits non-random features, so-called motifs. In this work, we focus on bidirectional, symmetric motifs, i.e. two neurons that project to each other via connections of equal strength, and unidirectional, non-symmetric motifs, i.e. within a pair of neurons only one neuron projects to the other. We hypothesise that such motifs have been shaped via activity dependent synaptic plasticity processes. As a consequence, learning moves the distribution of the synaptic connections away from randomness. Our aim is to provide a global, macroscopic, single parameter characterisation of the statistical occurrence of bidirectional and unidirectional motifs. To this end we define a symmetry measure that does not require any a priori thresholding of the weights or knowledge of their maximal value. We calculate its mean and variance for random uniform or Gaussian distributions, which allows us to introduce a confidence measure of how significantly symmetric or asymmetric a specific configuration is, i.e. how likely it is that the configuration is the result of chance. We demonstrate the discriminatory power of our symmetry measure by inspecting the eigenvalues of different types of connectivity matrices. We show that a Gaussian weight distribution biases the connectivity motifs to more symmetric configurations than a uniform distribution and that introducing a random synaptic pruning, mimicking developmental regulation in synaptogenesis, biases the connectivity motifs to more asymmetric configurations, regardless of the distribution. We expect that our work will benefit the computational modelling community, by providing a systematic way to characterise symmetry and asymmetry in network structures. Further, our symmetry measure will be of use to electrophysiologists that investigate symmetry of network connectivity.

Preferential Attachment in Online Networks: Measurement and Explanations

NARCIS (Netherlands)

Kunegis, J; Blattner, M; Moser, C.

2013-01-01

We perform an empirical study of the preferential attachment phenomenon in temporal networks and show that on the Web, networks follow a nonlinear preferential attachment model in which the exponent depends on the type of network considered. The classical preferential attachment model for networks

A Gata2-Dependent Transcription Network Regulates Uterine Progesterone Responsiveness and Endometrial Function

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Cory A. Rubel

2016-10-01

Full Text Available Altered progesterone responsiveness leads to female infertility and cancer, but underlying mechanisms remain unclear. Mice with uterine-specific ablation of GATA binding protein 2 (Gata2 are infertile, showing failures in embryo implantation, endometrial decidualization, and uninhibited estrogen signaling. Gata2 deficiency results in reduced progesterone receptor (PGR expression and attenuated progesterone signaling, as evidenced by genome-wide expression profiling and chromatin immunoprecipitation. GATA2 not only occupies at and promotes expression of the Pgr gene but also regulates downstream progesterone responsive genes in conjunction with the PGR. Additionally, Gata2 knockout uteri exhibit abnormal luminal epithelia with ectopic TRP63 expressing squamous cells and a cancer-related molecular profile in a progesterone-independent manner. Lastly, we found a conserved GATA2-PGR regulatory network in both human and mice based on gene signature and path analyses using gene expression profiles of human endometrial tissues. In conclusion, uterine Gata2 regulates a key regulatory network of gene expression for progesterone signaling at the early pregnancy stage.

Time response of temperature sensors using neural networks; Utilizacao de redes neurais artificiais para determinar o tempo de resposta de sensores de temperatura do tipo RTD

Energy Technology Data Exchange (ETDEWEB)

Santos, Roberto Carlos dos

2010-07-01

In a PWR nuclear power plant, the primary coolant temperature and feedwater temperature are measured using RTDs (Resistance Temperature Detectors). These RTDs typically feed the plant's control and safety systems and must, therefore, be very accurate and have good dynamic performance. The response time of RTDs is characterized by a single parameter called the Plunge Time Constant defined as the time it takes the sensor output to achieve 63.2 percent of its final value after a step change in temperature. Nuclear reactor service conditions are difficult to reproduce in the laboratory, and an in-situ test method called LCSR (Loop Current Step Response) test was developed to measure remotely the response time of RTDs. >From this test, the time constant of the sensor is identified by means of the LCSR transformation that involves the dynamic response modal time constants determination using a nodal heat-transfer model. This calculation is not simple and requires specialized personnel. For this reason an Artificial Neural Network has been developed to predict the time constant of RTD from LCSR test transient. It eliminates the transformations involved in the LCSR application. A series of LCSR tests on RTDs generates the response transients of the sensors, the input data of the networks. Plunge tests are used to determine the time constants of the RTDs, the desired output of the ANN, trained using these sets of input/output data. This methodology was firstly applied to theoretical data simulating 10 RTDs with different time constant values, resulting in an average error of about 0.74 %. Experimental data from three different RTDs was used to predict time constant resulting in a maximum error of 3,34 %. The time constants values predicted from ANN were compared with those obtained from traditional way resulting in an average error of about 18 % and that shows the network is able to predict accurately the sensor time constant. (author)

Reliability Measure Model for Assistive Care Loop Framework Using Wireless Sensor Networks

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Venki Balasubramanian

2010-01-01

Full Text Available Body area wireless sensor networks (BAWSNs are time-critical systems that rely on the collective data of a group of sensor nodes. Reliable data received at the sink is based on the collective data provided by all the source sensor nodes and not on individual data. Unlike conventional reliability, the definition of retransmission is inapplicable in a BAWSN and would only lead to an elapsed data arrival that is not acceptable for time-critical application. Time-driven applications require high data reliability to maintain detection and responses. Hence, the transmission reliability for the BAWSN should be based on the critical time. In this paper, we develop a theoretical model to measure a BAWSN's transmission reliability, based on the critical time. The proposed model is evaluated through simulation and then compared with the experimental results conducted in our existing Active Care Loop Framework (ACLF. We further show the effect of the sink buffer in transmission reliability after a detailed study of various other co-existing parameters.

Detecting earthquakes over a seismic network using single-station similarity measures

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Bergen, Karianne J.; Beroza, Gregory C.

2018-06-01

New blind waveform-similarity-based detection methods, such as Fingerprint and Similarity Thresholding (FAST), have shown promise for detecting weak signals in long-duration, continuous waveform data. While blind detectors are capable of identifying similar or repeating waveforms without templates, they can also be susceptible to false detections due to local correlated noise. In this work, we present a set of three new methods that allow us to extend single-station similarity-based detection over a seismic network; event-pair extraction, pairwise pseudo-association, and event resolution complete a post-processing pipeline that combines single-station similarity measures (e.g. FAST sparse similarity matrix) from each station in a network into a list of candidate events. The core technique, pairwise pseudo-association, leverages the pairwise structure of event detections in its network detection model, which allows it to identify events observed at multiple stations in the network without modeling the expected moveout. Though our approach is general, we apply it to extend FAST over a sparse seismic network. We demonstrate that our network-based extension of FAST is both sensitive and maintains a low false detection rate. As a test case, we apply our approach to 2 weeks of continuous waveform data from five stations during the foreshock sequence prior to the 2014 Mw 8.2 Iquique earthquake. Our method identifies nearly five times as many events as the local seismicity catalogue (including 95 per cent of the catalogue events), and less than 1 per cent of these candidate events are false detections.

Network analysis of epidermal growth factor signaling using integrated genomic, proteomic and phosphorylation data.

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Katrina M Waters

Full Text Available To understand how integration of multiple data types can help decipher cellular responses at the systems level, we analyzed the mitogenic response of human mammary epithelial cells to epidermal growth factor (EGF using whole genome microarrays, mass spectrometry-based proteomics and large-scale western blots with over 1000 antibodies. A time course analysis revealed significant differences in the expression of 3172 genes and 596 proteins, including protein phosphorylation changes measured by western blot. Integration of these disparate data types showed that each contributed qualitatively different components to the observed cell response to EGF and that varying degrees of concordance in gene expression and protein abundance measurements could be linked to specific biological processes. Networks inferred from individual data types were relatively limited, whereas networks derived from the integrated data recapitulated the known major cellular responses to EGF and exhibited more highly connected signaling nodes than networks derived from any individual dataset. While cell cycle regulatory pathways were altered as anticipated, we found the most robust response to mitogenic concentrations of EGF was induction of matrix metalloprotease cascades, highlighting the importance of the EGFR system as a regulator of the extracellular environment. These results demonstrate the value of integrating multiple levels of biological information to more accurately reconstruct networks of cellular response.

Network Analysis of Epidermal Growth Factor Signaling using Integrated Genomic, Proteomic and Phosphorylation Data

Energy Technology Data Exchange (ETDEWEB)

Waters, Katrina M.; Liu, Tao; Quesenberry, Ryan D.; Willse, Alan R.; Bandyopadhyay, Somnath; Kathmann, Loel E.; Weber, Thomas J.; Smith, Richard D.; Wiley, H. S.; Thrall, Brian D.

2012-03-29

To understand how integration of multiple data types can help decipher cellular responses at the systems level, we analyzed the mitogenic response of human mammary epithelial cells to epidermal growth factor (EGF) using whole genome microarrays, mass spectrometry-based proteomics and large-scale western blots with over 1000 antibodies. A time course analysis revealed significant differences in the expression of 3172 genes and 596 proteins, including protein phosphorylation changes measured by western blot. Integration of these disparate data types showed that each contributed qualitatively different components to the observed cell response to EGF and that varying degrees of concordance in gene expression and protein abundance measurements could be linked to specific biological processes. Networks inferred from individual data types were relatively limited, whereas networks derived from the integrated data recapitulated the known major cellular responses to EGF and exhibited more highly connected signaling nodes than networks derived from any individual dataset. While cell cycle regulatory pathways were altered as anticipated, we found the most robust response to mitogenic concentrations of EGF was induction of matrix metalloprotease cascades, highlighting the importance of the EGFR system as a regulator of the extracellular environment. These results demonstrate the value of integrating multiple levels of biological information to more accurately reconstruct networks of cellular response.

Individual and sex-related differences in pain and relief responsiveness are associated with differences in resting-state functional networks in healthy volunteers.

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Galli, Giulia; Santarnecchi, Emiliano; Feurra, Matteo; Bonifazi, Marco; Rossi, Simone; Paulus, Martin P; Rossi, Alessandro

2016-02-01

Pain processing is associated with neural activity in a number of widespread brain regions. Here, we investigated whether functional connectivity at rest between these brain regions is associated with individual and sex-related differences in thermal pain and relief responsiveness. Twenty healthy volunteers (ten females) were scanned with functional magnetic resonance imaging in resting conditions. Half an hour after scanning, we administered thermal pain on the back of their right hand and collected pain and relief ratings in two separate runs of twelve stimuli each. Across the whole group, mean pain ratings were associated with decreased connectivity at rest between brain regions belonging to the default mode and the visual resting-state network. In men, pain measures correlated with increased connectivity within the visual resting-state network. In women, in contrast, decreased connectivity between this network and parietal and prefrontal brain regions implicated in affective cognitive control were associated with both pain and relief ratings. Our findings indicate that the well documented individual variability and sex differences in pain sensitivity may be explained, at least in part, by network dynamics at rest in these brain regions. © 2015 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.

Simulation and measurement of optical access network with different types of optical-fiber amplifiers

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Latal, Jan; Vogl, Jan; Koudelka, Petr; Vitasek, Jan; Siska, Petr; Liner, Andrej; Papes, Martin; Vasinek, Vladimir

2012-01-01

The optical access networks are nowadays swiftly developing in the telecommunications field. These networks can provide higher data transfer rates, and have great potential to the future in terms of transmission possibilities. Many local internet providers responded to these facts and began gradually installing optical access networks into their originally built networks, mostly based on wireless communication. This allowed enlargement of possibilities for end-users in terms of high data rates and also new services such as Triple play, IPTV (Internet Protocol television) etc. However, with this expansion and building-up is also related the potential of reach in case of these networks. Big cities, such as Prague, Brno, Ostrava or Olomouc cannot be simply covered, because of their sizes and also because of their internal regulations given by various organizations in each city. Standard logical and also physical reach of EPON (IEEE 802.3ah - Ethernet Passive Optical Network) optical access network is about 20 km. However, for networks based on Wavelength Division Multiplex the reach can be up to 80 km, if the optical-fiber amplifier is inserted into the network. This article deals with simulation of different types of amplifiers for WDM-PON (Wavelength Division Multiplexing-Passive Optical Network) network in software application Optiwave OptiSystem and than are the values from the application and from real measurement compared.

Node-based measures of connectivity in genetic networks.

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Koen, Erin L; Bowman, Jeff; Wilson, Paul J

2016-01-01

At-site environmental conditions can have strong influences on genetic connectivity, and in particular on the immigration and settlement phases of dispersal. However, at-site processes are rarely explored in landscape genetic analyses. Networks can facilitate the study of at-site processes, where network nodes are used to model site-level effects. We used simulated genetic networks to compare and contrast the performance of 7 node-based (as opposed to edge-based) genetic connectivity metrics. We simulated increasing node connectivity by varying migration in two ways: we increased the number of migrants moving between a focal node and a set number of recipient nodes, and we increased the number of recipient nodes receiving a set number of migrants. We found that two metrics in particular, the average edge weight and the average inverse edge weight, varied linearly with simulated connectivity. Conversely, node degree was not a good measure of connectivity. We demonstrated the use of average inverse edge weight to describe the influence of at-site habitat characteristics on genetic connectivity of 653 American martens (Martes americana) in Ontario, Canada. We found that highly connected nodes had high habitat quality for marten (deep snow and high proportions of coniferous and mature forest) and were farther from the range edge. We recommend the use of node-based genetic connectivity metrics, in particular, average edge weight or average inverse edge weight, to model the influences of at-site habitat conditions on the immigration and settlement phases of dispersal. © 2015 John Wiley & Sons Ltd.

Probabilistic mapping of descriptive health status responses onto health state utilities using Bayesian networks: an empirical analysis converting SF-12 into EQ-5D utility index in a national US sample.

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Le, Quang A; Doctor, Jason N

2011-05-01

As quality-adjusted life years have become the standard metric in health economic evaluations, mapping health-profile or disease-specific measures onto preference-based measures to obtain quality-adjusted life years has become a solution when health utilities are not directly available. However, current mapping methods are limited due to their predictive validity, reliability, and/or other methodological issues. We employ probability theory together with a graphical model, called a Bayesian network, to convert health-profile measures into preference-based measures and to compare the results to those estimated with current mapping methods. A sample of 19,678 adults who completed both the 12-item Short Form Health Survey (SF-12v2) and EuroQoL 5D (EQ-5D) questionnaires from the 2003 Medical Expenditure Panel Survey was split into training and validation sets. Bayesian networks were constructed to explore the probabilistic relationships between each EQ-5D domain and 12 items of the SF-12v2. The EQ-5D utility scores were estimated on the basis of the predicted probability of each response level of the 5 EQ-5D domains obtained from the Bayesian inference process using the following methods: Monte Carlo simulation, expected utility, and most-likely probability. Results were then compared with current mapping methods including multinomial logistic regression, ordinary least squares, and censored least absolute deviations. The Bayesian networks consistently outperformed other mapping models in the overall sample (mean absolute error=0.077, mean square error=0.013, and R overall=0.802), in different age groups, number of chronic conditions, and ranges of the EQ-5D index. Bayesian networks provide a new robust and natural approach to map health status responses into health utility measures for health economic evaluations.

Distributed Data Networks That Support Public Health Information Needs.

Science.gov (United States)

Tabano, David C; Cole, Elizabeth; Holve, Erin; Davidson, Arthur J

Data networks, consisting of pooled electronic health data assets from health care providers serving different patient populations, promote data sharing, population and disease monitoring, and methods to assess interventions. Better understanding of data networks, and their capacity to support public health objectives, will help foster partnerships, expand resources, and grow learning health systems. We conducted semistructured interviews with 16 key informants across the United States, identified as network stakeholders based on their respective experience in advancing health information technology and network functionality. Key informants were asked about their experience with and infrastructure used to develop data networks, including each network's utility to identify and characterize populations, usage, and sustainability. Among 11 identified data networks representing hundreds of thousands of patients, key informants described aggregated health care clinical data contributing to population health measures. Key informant interview responses were thematically grouped to illustrate how networks support public health, including (1) infrastructure and information sharing; (2) population health measures; and (3) network sustainability. Collaboration between clinical data networks and public health entities presents an opportunity to leverage infrastructure investments to support public health. Data networks can provide resources to enhance population health information and infrastructure.