Reciprocal Family, Friendship and Church Support Networks of African Americans: Findings from the National Survey of American Life.

Science.gov (United States)

Taylor, Robert Joseph; Mouzon, Dawne M; Nguyen, Ann W; Chatters, Linda M

2016-12-01

This study examined reciprocal support networks involving extended family, friends and church members among African Americans. Our analysis examined specific patterns of reciprocal support (i.e., received only, gave only, both gave and received, neither gave or received), as well as network characteristics (i.e., contact and subjective closeness) as correlates of reciprocal support. The analysis is based on the African American sub-sample of the National Survey of American Life (NSAL). Overall, our findings indicate that African Americans are very involved in reciprocal support networks with their extended family, friends and church members. Respondents were most extensively involved in reciprocal supports with extended family members, followed closely by friends and church networks. Network characteristics (i.e., contact and subjective closeness) were significantly and consistently associated with involvement with reciprocal support exchanges for all three networks. These and other findings are discussed in detail. This study complements previous work on the complementary roles of family, friend and congregational support networks, as well as studies of racial differences in informal support networks.

Developing electricity distribution networks and their regulation to support sustainable energy

International Nuclear Information System (INIS)

Shaw, Rita; Attree, Mike; Jackson, Tim

2010-01-01

A more sustainable energy system will alter the current patterns of electricity demand and generation. This means technical, commercial and regulatory change for electricity network systems such as distribution networks. This paper traces the links in Great Britain between changes in energy policy since privatisation, changes in the objectives of the electricity regulator and changes in the objectives of the distribution networks and their owners, the distribution network operators (DNOs). The paper identifies tensions in regulatory policy and suggests reforms to the regulatory framework to support a lower-carbon future. DNOs are licensed regional infrastructure providers. In addition to their network services, the network companies can potentially deliver public policy objectives to facilitate heat infrastructure, energy-efficiency and distributed renewables. The paper identifies the potential benefits of a novel approach to facilitating renewable energy feed-in tariffs for electricity and heat, using DNOs.

Maximum-entropy networks pattern detection, network reconstruction and graph combinatorics

CERN Document Server

Squartini, Tiziano

2017-01-01

This book is an introduction to maximum-entropy models of random graphs with given topological properties and their applications. Its original contribution is the reformulation of many seemingly different problems in the study of both real networks and graph theory within the unified framework of maximum entropy. Particular emphasis is put on the detection of structural patterns in real networks, on the reconstruction of the properties of networks from partial information, and on the enumeration and sampling of graphs with given properties.  After a first introductory chapter explaining the motivation, focus, aim and message of the book, chapter 2 introduces the formal construction of maximum-entropy ensembles of graphs with local topological constraints. Chapter 3 focuses on the problem of pattern detection in real networks and provides a powerful way to disentangle nontrivial higher-order structural features from those that can be traced back to simpler local constraints. Chapter 4 focuses on the problem o...

The Science DMZ: A Network Design Pattern for Data-Intensive Science

Energy Technology Data Exchange (ETDEWEB)

Dart, Eli; Rotman, Lauren; Tierney, Brian; Hester, Mary; Zurawski, Jason

2013-08-13

The ever-increasing scale of scientific data has become a significant challenge for researchers that rely on networks to interact with remote computing systems and transfer results to collaborators worldwide. Despite the availability of high-capacity connections, scientists struggle with inadequate cyberinfrastructure that cripples data transfer performance, and impedes scientific progress. The Science DMZ paradigm comprises a proven set of network design patterns that collectively address these problems for scientists. We explain the Science DMZ model, including network architecture, system configuration, cybersecurity, and performance tools, that creates an optimized network environment for science. We describe use cases from universities, supercomputing centers and research laboratories, highlighting the effectiveness of the Science DMZ model in diverse operational settings. In all, the Science DMZ model is a solid platform that supports any science workflow, and flexibly accommodates emerging network technologies. As a result, the Science DMZ vastly improves collaboration, accelerating scientific discovery.

Network approach to patterns in stratocumulus clouds

Science.gov (United States)

Glassmeier, Franziska; Feingold, Graham

2017-10-01

Stratocumulus clouds (Sc) have a significant impact on the amount of sunlight reflected back to space, with important implications for Earth’s climate. Representing Sc and their radiative impact is one of the largest challenges for global climate models. Sc fields self-organize into cellular patterns and thus lend themselves to analysis and quantification in terms of natural cellular networks. Based on large-eddy simulations of Sc fields, we present a first analysis of the geometric structure and self-organization of Sc patterns from this network perspective. Our network analysis shows that the Sc pattern is scale-invariant as a consequence of entropy maximization that is known as Lewis’s Law (scaling parameter: 0.16) and is largely independent of the Sc regime (cloud-free vs. cloudy cell centers). Cells are, on average, hexagonal with a neighbor number variance of about 2, and larger cells tend to be surrounded by smaller cells, as described by an Aboav-Weaire parameter of 0.9. The network structure is neither completely random nor characteristic of natural convection. Instead, it emerges from Sc-specific versions of cell division and cell merging that are shaped by cell expansion. This is shown with a heuristic model of network dynamics that incorporates our physical understanding of cloud processes.

Developing electricity distribution networks and their regulation to support sustainable energy

Energy Technology Data Exchange (ETDEWEB)

Shaw, Rita; Attree, Mike [Electricity North West Ltd., 304 Bridgewater Place, Birchwood, Warrington, Cheshire WA3 6XG (United Kingdom); Jackson, Tim [RESOLVE, Centre for Environmental Strategy D3, University of Surrey, Guildford, Surrey GU2 7XH (United Kingdom)

2010-10-15

A more sustainable energy system will alter the current patterns of electricity demand and generation. This means technical, commercial and regulatory change for electricity network systems such as distribution networks. This paper traces the links in Great Britain between changes in energy policy since privatisation, changes in the objectives of the electricity regulator and changes in the objectives of the distribution networks and their owners, the distribution network operators (DNOs). The paper identifies tensions in regulatory policy and suggests reforms to the regulatory framework to support a lower-carbon future. DNOs are licensed regional infrastructure providers. In addition to their network services, the network companies can potentially deliver public policy objectives to facilitate heat infrastructure, energy-efficiency and distributed renewables. The paper identifies the potential benefits of a novel approach to facilitating renewable energy feed-in tariffs for electricity and heat, using DNOs. (author)

Firms' innovation benefiting from networking and institutional support

DEFF Research Database (Denmark)

Schøtt, Thomas; Jensen, Kent Wickstrøm

2016-01-01

Firms' networking for innovation is embedded in institutions of society, where national policies are increasingly designed to provide institutional support for firms' networking and thereby benefit innovation. But, globally, what are the quantitative and qualitative effects of institutional support...... for networking and, in turn, for innovation? 68 countries with 18,880 firms were surveyed in the Global Entrepreneurship Monitor, enabling generalization to the firms in the countries around the world. Two-level modeling shows that firms' networking benefits both process and product innovation. Institutional...... support does not significantly affect quantity of networking, but greatly enhances quality of networking in the sense that support for networking in a country enhances the benefits of networking for both process and product innovation. Contrasting low and high support for networking leads to estimating...

Motif distributions in phase-space networks for characterizing experimental two-phase flow patterns with chaotic features.

Science.gov (United States)

Gao, Zhong-Ke; Jin, Ning-De; Wang, Wen-Xu; Lai, Ying-Cheng

2010-07-01

The dynamics of two-phase flows have been a challenging problem in nonlinear dynamics and fluid mechanics. We propose a method to characterize and distinguish patterns from inclined water-oil flow experiments based on the concept of network motifs that have found great usage in network science and systems biology. In particular, we construct from measured time series phase-space complex networks and then calculate the distribution of a set of distinct network motifs. To gain insight, we first test the approach using time series from classical chaotic systems and find a universal feature: motif distributions from different chaotic systems are generally highly heterogeneous. Our main finding is that the distributions from experimental two-phase flows tend to be heterogeneous as well, suggesting the underlying chaotic nature of the flow patterns. Calculation of the maximal Lyapunov exponent provides further support for this. Motif distributions can thus be a feasible tool to understand the dynamics of realistic two-phase flow patterns.

Social embeddedness and late-life parenthood: Community activity, close ties, and support networks

NARCIS (Netherlands)

Wenger, G.C.; Dykstra, P.A.; Melkas, T.; Knipscheer, C.P.M.

2007-01-01

This article focuses on the ways in which patterns of marriage and fertility shape older people's involvement in community groups and their support networks. The data are from Australia, Finland, Germany, Israel, Japan, the Netherlands, Spain, the United Kingdom, and the United States. Findings show

Methods for discriminating gas-liquid two phase flow patterns based on gray neural networks and SVM

International Nuclear Information System (INIS)

Li Jingjing; Zhou Tao; Duan Jun; Zhang Lei

2013-01-01

Background: The flow patterns of two phase flow will directly influence the heat transfer and mass transfer of the flow. Purpose: By wavelet analysis of the pressure drop experimental data, the wavelet coefficients of different frequency can be obtained. Methods: Get the wavelet energy and then train them in the model of BP neural network to distinguish the flow patterns. Introduced the implant gray neural networks model and use it for the two phase flow for the first time. At the same time, set up the method of training the pressure data and wavelet energy data in the support vector machine. Results: Through treatment of the gray layer, the result of the neural network is more accuracy. It can obviously reduce the effect of data marginalization. The accuracy of the pressure drop Lib-SVM method is 95.2%. Conclusions: The results show that these three methods can make a distinction among the different flow patterns and the Lib-SVM method gets the best result, then the gray neural networks, and at last the BP neural networks. (authors)

The Science DMZ: A Network Design Pattern for Data-Intensive Science

Directory of Open Access Journals (Sweden)

Eli Dart

2014-01-01

Full Text Available The ever-increasing scale of scientific data has become a significant challenge for researchers that rely on networks to interact with remote computing systems and transfer results to collaborators worldwide. Despite the availability of high-capacity connections, scientists struggle with inadequate cyberinfrastructure that cripples data transfer performance, and impedes scientific progress. The Science DMZ paradigm comprises a proven set of network design patterns that collectively address these problems for scientists. We explain the Science DMZ model, including network architecture, system configuration, cybersecurity, and performance tools, that creates an optimized network environment for science. We describe use cases from universities, supercomputing centers and research laboratories, highlighting the effectiveness of the Science DMZ model in diverse operational settings. In all, the Science DMZ model is a solid platform that supports any science workflow, and flexibly accommodates emerging network technologies. As a result, the Science DMZ vastly improves collaboration, accelerating scientific discovery.

Exploring Spatio-temporal Dynamics of Cellular Automata for Pattern Recognition in Networks

Science.gov (United States)

Miranda, Gisele Helena Barboni; Machicao, Jeaneth; Bruno, Odemir Martinez

2016-11-01

Network science is an interdisciplinary field which provides an integrative approach for the study of complex systems. In recent years, network modeling has been used for the study of emergent phenomena in many real-world applications. Pattern recognition in networks has been drawing attention to the importance of network characterization, which may lead to understanding the topological properties that are related to the network model. In this paper, the Life-Like Network Automata (LLNA) method is introduced, which was designed for pattern recognition in networks. LLNA uses the network topology as a tessellation of Cellular Automata (CA), whose dynamics produces a spatio-temporal pattern used to extract the feature vector for network characterization. The method was evaluated using synthetic and real-world networks. In the latter, three pattern recognition applications were used: (i) identifying organisms from distinct domains of life through their metabolic networks, (ii) identifying online social networks and (iii) classifying stomata distribution patterns varying according to different lighting conditions. LLNA was compared to structural measurements and surpasses them in real-world applications, achieving improvement in the classification rate as high as 23%, 4% and 7% respectively. Therefore, the proposed method is a good choice for pattern recognition applications using networks and demonstrates potential for general applicability.

Support network and social support for children with special health care need

Directory of Open Access Journals (Sweden)

Thaís Araújo Barbosa

2016-02-01

Full Text Available Objective: to understand and identify the support network and social support from the perspective of families of children with chronic conditions. Methods: a qualitative study, with content analysis of 134 records, followed by ten semi-structured interviews. Results: the analysis has revealed that the primary caregiver, the mother, participates in a network of limited support, only with the help of her husband, children, grandparents and the child´s godparents. They also have a social network through a multidisciplinary team, which in some cases is not effective. Conclusion: families have a deficient and limited support network and the demand for care rely only on the support of the husband, grandparents, children, and godparents. Social networking refers to the philanthropic institutions, while the aid of public service, basic health unit is basic.

Social Embeddedness and Late-Life Parenthood : Community Activity, Close Ties, and Support Networks

NARCIS (Netherlands)

Wenger, G. Clare; Dykstra, Pearl A.; Melkas, Tuula; Knipscheer, Kees C.P.M.

2007-01-01

This article focuses on the ways in which patterns of marriage and fertility shape older people’s involvement in community groups and their support networks. The data are from Australia, Finland, Germany, Israel, Japan, the Netherlands, Spain, the United Kingdom, and the United States. Findings show

Social embeddedness and late-life parenthood: community activity, close ties and support networks

NARCIS (Netherlands)

Wenger, G.; Dykstra, P.A.; Melkas, T.; Knipscheer, K.

2007-01-01

This article focuses on the ways in which patterns of marriage and fertility shape older people’s involvement in community groups and their support networks. The data are from Australia, Finland, Germany, Israel, Japan, the Netherlands, Spain, the United Kingdom, and the United States. Findings show

Effects of traffic generation patterns on the robustness of complex networks

Science.gov (United States)

Wu, Jiajing; Zeng, Junwen; Chen, Zhenhao; Tse, Chi K.; Chen, Bokui

2018-02-01

Cascading failures in communication networks with heterogeneous node functions are studied in this paper. In such networks, the traffic dynamics are highly dependent on the traffic generation patterns which are in turn determined by the locations of the hosts. The data-packet traffic model is applied to Barabási-Albert scale-free networks to study the cascading failures in such networks and to explore the effects of traffic generation patterns on network robustness. It is found that placing the hosts at high-degree nodes in a network can make the network more robust against both intentional attacks and random failures. It is also shown that the traffic generation pattern plays an important role in network design.

Study on Dissemination Patterns in Location-Aware Gossiping Networks

Science.gov (United States)

Kami, Nobuharu; Baba, Teruyuki; Yoshikawa, Takashi; Morikawa, Hiroyuki

We study the properties of information dissemination over location-aware gossiping networks leveraging location-based real-time communication applications. Gossiping is a promising method for quickly disseminating messages in a large-scale system, but in its application to information dissemination for location-aware applications, it is important to consider the network topology and patterns of spatial dissemination over the network in order to achieve effective delivery of messages to potentially interested users. To this end, we propose a continuous-space network model extended from Kleinberg's small-world model applicable to actual location-based applications. Analytical and simulation-based study shows that the proposed network achieves high dissemination efficiency resulting from geographically neutral dissemination patterns as well as selective dissemination to proximate users. We have designed a highly scalable location management method capable of promptly updating the network topology in response to node movement and have implemented a distributed simulator to perform dynamic target pursuit experiments as one example of applications that are the most sensitive to message forwarding delay. The experimental results show that the proposed network surpasses other types of networks in pursuit efficiency and achieves the desirable dissemination patterns.

Spatial-temporal-spectral EEG patterns of BOLD functional network connectivity dynamics

Science.gov (United States)

Lamoš, Martin; Mareček, Radek; Slavíček, Tomáš; Mikl, Michal; Rektor, Ivan; Jan, Jiří

2018-06-01

Objective. Growing interest in the examination of large-scale brain network functional connectivity dynamics is accompanied by an effort to find the electrophysiological correlates. The commonly used constraints applied to spatial and spectral domains during electroencephalogram (EEG) data analysis may leave part of the neural activity unrecognized. We propose an approach that blindly reveals multimodal EEG spectral patterns that are related to the dynamics of the BOLD functional network connectivity. Approach. The blind decomposition of EEG spectrogram by parallel factor analysis has been shown to be a useful technique for uncovering patterns of neural activity. The simultaneously acquired BOLD fMRI data were decomposed by independent component analysis. Dynamic functional connectivity was computed on the component’s time series using a sliding window correlation, and between-network connectivity states were then defined based on the values of the correlation coefficients. ANOVA tests were performed to assess the relationships between the dynamics of between-network connectivity states and the fluctuations of EEG spectral patterns. Main results. We found three patterns related to the dynamics of between-network connectivity states. The first pattern has dominant peaks in the alpha, beta, and gamma bands and is related to the dynamics between the auditory, sensorimotor, and attentional networks. The second pattern, with dominant peaks in the theta and low alpha bands, is related to the visual and default mode network. The third pattern, also with peaks in the theta and low alpha bands, is related to the auditory and frontal network. Significance. Our previous findings revealed a relationship between EEG spectral pattern fluctuations and the hemodynamics of large-scale brain networks. In this study, we suggest that the relationship also exists at the level of functional connectivity dynamics among large-scale brain networks when no standard spatial and spectral

Network periodic solutions: patterns of phase-shift synchrony

International Nuclear Information System (INIS)

Golubitsky, Martin; Wang, Yunjiao; Romano, David

2012-01-01

We prove the rigid phase conjecture of Stewart and Parker. It then follows from previous results (of Stewart and Parker and our own) that rigid phase-shifts in periodic solutions on a transitive network are produced by a cyclic symmetry on a quotient network. More precisely, let X(t) = (x 1 (t), ..., x n (t)) be a hyperbolic T-periodic solution of an admissible system on an n-node network. Two nodes c and d are phase-related if there exists a phase-shift θ cd in [0, 1) such that x d (t) = x c (t + θ cd T). The conjecture states that if phase relations persist under all small admissible perturbations (that is, the phase relations are rigid), then for each pair of phase-related cells, their input signals are also phase-related to the same phase-shift. For a transitive network, rigid phase relations can also be described abstractly as a Z m permutation symmetry of a quotient network. We discuss how patterns of phase-shift synchrony lead to rigid synchrony, rigid phase synchrony, and rigid multirhythms, and we show that for each phase pattern there exists an admissible system with a periodic solution with that phase pattern. Finally, we generalize the results to nontransitive networks where we show that the symmetry that generates rigid phase-shifts occurs on an extension of a quotient network

Cooperative and supportive neural networks

International Nuclear Information System (INIS)

Sree Hari Rao, V.; Raja Sekhara Rao, P.

2007-01-01

This Letter deals with the concepts of co-operation and support among neurons existing in a network which contribute to their collective capabilities and distributed operations. Activational dynamical properties of these networks are discussed

Social Embeddedness and Late-Life Parenthood: Community Activity, Close Ties, and Support Networks

Science.gov (United States)

Wenger, G. Clare; Dykstra, Pearl A.; Melkas, Tuula; Knipscheer, Kees C. P. M.

2007-01-01

This article focuses on the ways in which patterns of marriage and fertility shape older people's involvement in community groups and their support networks. The data are from Australia, Finland, Germany, Israel, Japan, the Netherlands, Spain, the United Kingdom, and the United States. Findings show that childless older adults, regardless of…

Network Patterns of Inventor Collaboration and Their Effects on Innovation Outputs

Directory of Open Access Journals (Sweden)

Wonchang Hur

2016-03-01

Full Text Available The purpose of this study is to examine how the collaboration structure among inventors in an R and D organization affects its capability to create impactful innovations. Specifically, this study is focused on examining whether a certain type of network mechanism found in collaboration among inventors contributes more to enhancing the future impacts of collaboration outputs, which is represented by the forward citations of their patents. To this end, co-invention networks for R and D organizations are constructed from an inventor-patent database, and the three structural patterns are measured by using network analytic constructs, namely, structural holes, strength of ties, and centralization. The results show that the presence of structural holes and strong ties are positively associated with the increasing forward citations, and that decentralized collaboration has also a positive impact. The findings offer support for both structural hole and network closure perspectives on social capital, which have been considered contradictive in the literature.

Visualizing neuronal network connectivity with connectivity pattern tables

Directory of Open Access Journals (Sweden)

Eilen Nordlie

2010-01-01

Full Text Available Complex ideas are best conveyed through well-designed illustrations. Up to now, computational neuroscientists have mostly relied on box-and-arrow diagrams of even complex neuronal networks, often using ad hoc notations with conflicting use of symbols from paper to paper. This significantly impedes the communication of ideas in neuronal network modeling. We present here Connectivity Pattern Tables (CPTs as a clutter-free visualization of connectivity in large neuronal networks containing two-dimensional populations of neurons. CPTs can be generated automatically from the same script code used to create the actual network in the NEST simulator. Through aggregation, CPTs can be viewed at different levels, providing either full detail or summary information. We also provide the open source ConnPlotter tool as a means to create connectivity pattern tables.

Genotet: An Interactive Web-based Visual Exploration Framework to Support Validation of Gene Regulatory Networks.

Science.gov (United States)

Yu, Bowen; Doraiswamy, Harish; Chen, Xi; Miraldi, Emily; Arrieta-Ortiz, Mario Luis; Hafemeister, Christoph; Madar, Aviv; Bonneau, Richard; Silva, Cláudio T

2014-12-01

Elucidation of transcriptional regulatory networks (TRNs) is a fundamental goal in biology, and one of the most important components of TRNs are transcription factors (TFs), proteins that specifically bind to gene promoter and enhancer regions to alter target gene expression patterns. Advances in genomic technologies as well as advances in computational biology have led to multiple large regulatory network models (directed networks) each with a large corpus of supporting data and gene-annotation. There are multiple possible biological motivations for exploring large regulatory network models, including: validating TF-target gene relationships, figuring out co-regulation patterns, and exploring the coordination of cell processes in response to changes in cell state or environment. Here we focus on queries aimed at validating regulatory network models, and on coordinating visualization of primary data and directed weighted gene regulatory networks. The large size of both the network models and the primary data can make such coordinated queries cumbersome with existing tools and, in particular, inhibits the sharing of results between collaborators. In this work, we develop and demonstrate a web-based framework for coordinating visualization and exploration of expression data (RNA-seq, microarray), network models and gene-binding data (ChIP-seq). Using specialized data structures and multiple coordinated views, we design an efficient querying model to support interactive analysis of the data. Finally, we show the effectiveness of our framework through case studies for the mouse immune system (a dataset focused on a subset of key cellular functions) and a model bacteria (a small genome with high data-completeness).

A mutual support mechanism through intercellular movement of CAPRICE and GLABRA3 can pattern the Arabidopsis root epidermis.

Directory of Open Access Journals (Sweden)

Natasha Saint Savage

2008-09-01

Full Text Available The patterning of the Arabidopsis root epidermis depends on a genetic regulatory network that operates both within and between cells. Genetic studies have identified a number of key components of this network, but a clear picture of the functional logic of the network is lacking. Here, we integrate existing genetic and biochemical data in a mathematical model that allows us to explore both the sufficiency of known network interactions and the extent to which additional assumptions about the model can account for wild-type and mutant data. Our model shows that an existing hypothesis concerning the autoregulation of WEREWOLF does not account fully for the expression patterns of components of the network. We confirm the lack of WEREWOLF autoregulation experimentally in transgenic plants. Rather, our modelling suggests that patterning depends on the movement of the CAPRICE and GLABRA3 transcriptional regulators between epidermal cells. Our combined modelling and experimental studies show that WEREWOLF autoregulation does not contribute to the initial patterning of epidermal cell fates in the Arabidopsis seedling root. In contrast to a patterning mechanism relying on local activation, we propose a mechanism based on lateral inhibition with feedback. The active intercellular movements of proteins that are central to our model underlie a mechanism for pattern formation in planar groups of cells that is centred on the mutual support of two cell fates rather than on local activation and lateral inhibition.

Fracture network modeling and GoldSim simulation support

International Nuclear Information System (INIS)

Sugita, Kenichiro; Dershowitz, William

2003-01-01

During Heisei-14, Golder Associates provided support for JNC Tokai through data analysis and simulation of the MIU Underground Rock Laboratory, participation in Task 6 of the Aespoe Task Force on Modelling of Groundwater Flow and Transport, and analysis of repository safety assessment technologies including cell networks for evaluation of the disturbed rock zone (DRZ) and total systems performance assessment (TSPA). MIU Underground Rock Laboratory support during H-14 involved discrete fracture network (DFN) modelling in support of the Multiple Modelling Project (MMP) and the Long Term Pumping Test (LPT). Golder developed updated DFN models for the MIU site, reflecting updated analyses of fracture data. Golder also developed scripts to support JNC simulations of flow and transport pathways within the MMP. Golder supported JNC participation in Task 6 of the Aespoe Task Force on Modelling of Groundwater Flow and Transport during H-14. Task 6A and 6B compared safety assessment (PA) and experimental time scale simulations along a pipe transport pathway. Task 6B2 extended Task 6B simulations from 1-D to 2-D. For Task 6B2, Golder carried out single fracture transport simulations on a wide variety of generic heterogeneous 2D fractures using both experimental and safety assessment boundary conditions. The heterogeneous 2D fractures were implemented according to a variety of in plane heterogeneity patterns. Multiple immobile zones were considered including stagnant zones, infillings, altered wall rock, and intact rock. During H-14, JNC carried out extensive studies of the distributed rock zone (DRZ) surrounding repository tunnels and drifts. Golder supported this activity be evaluating the calculation time necessary for simulating a reference heterogeneous DRZ cell network for a range of computational strategies. To support the development of JNC's total system performance assessment (TSPA) strategy, Golder carried out a review of the US DOE Yucca Mountain Project TSPA. This

Bio-inspired patterned networks (BIPS) for development of wearable/disposable biosensors

Science.gov (United States)

McLamore, E. S.; Convertino, M.; Hondred, John; Das, Suprem; Claussen, J. C.; Vanegas, D. C.; Gomes, C.

2016-05-01

Here we demonstrate a novel approach for fabricating point of care (POC) wearable electrochemical biosensors based on 3D patterning of bionanocomposite networks. To create Bio-Inspired Patterned network (BIPS) electrodes, we first generate fractal network in silico models that optimize transport of network fluxes according to an energy function. Network patterns are then inkjet printed onto flexible substrate using conductive graphene ink. We then deposit fractal nanometal structures onto the graphene to create a 3D nanocomposite network. Finally, we biofunctionalize the surface with biorecognition agents using covalent bonding. In this paper, BIPS are used to develop high efficiency, low cost biosensors for measuring glucose as a proof of concept. Our results on the fundamental performance of BIPS sensors show that the biomimetic nanostructures significantly enhance biosensor sensitivity, accuracy, response time, limit of detection, and hysteresis compared to conventional POC non fractal electrodes (serpentine, interdigitated, and screen printed electrodes). BIPs, in particular Apollonian patterned BIPS, represent a new generation of POC biosensors based on nanoscale and microscale fractal networks that significantly improve electrical connectivity, leading to enhanced sensor performance.

Network Regulation and Support Schemes

DEFF Research Database (Denmark)

Ropenus, Stephanie; Schröder, Sascha Thorsten; Jacobsen, Henrik

2009-01-01

-in tariffs to market-based quota systems, and network regulation approaches, comprising rate-of-return and incentive regulation. National regulation and the vertical structure of the electricity sector shape the incentives of market agents, notably of distributed generators and network operators......At present, there exists no explicit European policy framework on distributed generation. Various Directives encompass distributed generation; inherently, their implementation is to the discretion of the Member States. The latter have adopted different kinds of support schemes, ranging from feed....... This article seeks to investigate the interactions between the policy dimensions of support schemes and network regulation and how they affect the deployment of distributed generation. Firstly, a conceptual analysis examines how the incentives of the different market agents are affected. In particular...

Granular neural networks, pattern recognition and bioinformatics

CERN Document Server

Pal, Sankar K; Ganivada, Avatharam

2017-01-01

This book provides a uniform framework describing how fuzzy rough granular neural network technologies can be formulated and used in building efficient pattern recognition and mining models. It also discusses the formation of granules in the notion of both fuzzy and rough sets. Judicious integration in forming fuzzy-rough information granules based on lower approximate regions enables the network to determine the exactness in class shape as well as to handle the uncertainties arising from overlapping regions, resulting in efficient and speedy learning with enhanced performance. Layered network and self-organizing analysis maps, which have a strong potential in big data, are considered as basic modules,. The book is structured according to the major phases of a pattern recognition system (e.g., classification, clustering, and feature selection) with a balanced mixture of theory, algorithm, and application. It covers the latest findings as well as directions for future research, particularly highlighting bioinf...

Learning-induced pattern classification in a chaotic neural network

International Nuclear Information System (INIS)

Li, Yang; Zhu, Ping; Xie, Xiaoping; He, Guoguang; Aihara, Kazuyuki

2012-01-01

In this Letter, we propose a Hebbian learning rule with passive forgetting (HLRPF) for use in a chaotic neural network (CNN). We then define the indices based on the Euclidean distance to investigate the evolution of the weights in a simplified way. Numerical simulations demonstrate that, under suitable external stimulations, the CNN with the proposed HLRPF acts as a fuzzy-like pattern classifier that performs much better than an ordinary CNN. The results imply relationship between learning and recognition. -- Highlights: ► Proposing a Hebbian learning rule with passive forgetting (HLRPF). ► Defining indices to investigate the evolution of the weights simply. ► The chaotic neural network with HLRPF acts as a fuzzy-like pattern classifier. ► The pattern classifier ability of the network is improved much.

Supporting networks for realizing rights

DEFF Research Database (Denmark)

Wilson, Fiona

2005-01-01

The chapter explores how DFID, the British bi-lateral aid donor, adopted an innovative rights' based approach that rested on supporting in existing networks in Peru. Focus is put on the history and challenges of DFID's engagement with three networks in particular: in the fields of health, local...

Network based approaches reveal clustering in protein point patterns

Science.gov (United States)

Parker, Joshua; Barr, Valarie; Aldridge, Joshua; Samelson, Lawrence E.; Losert, Wolfgang

2014-03-01

Recent advances in super-resolution imaging have allowed for the sub-diffraction measurement of the spatial location of proteins on the surfaces of T-cells. The challenge is to connect these complex point patterns to the internal processes and interactions, both protein-protein and protein-membrane. We begin analyzing these patterns by forming a geometric network amongst the proteins and looking at network measures, such the degree distribution. This allows us to compare experimentally observed patterns to models. Specifically, we find that the experimental patterns differ from heterogeneous Poisson processes, highlighting an internal clustering structure. Further work will be to compare our results to simulated protein-protein interactions to determine clustering mechanisms.

Modeling urbanization patterns with generative adversarial networks

OpenAIRE

Albert, Adrian; Strano, Emanuele; Kaur, Jasleen; Gonzalez, Marta

2018-01-01

In this study we propose a new method to simulate hyper-realistic urban patterns using Generative Adversarial Networks trained with a global urban land-use inventory. We generated a synthetic urban "universe" that qualitatively reproduces the complex spatial organization observed in global urban patterns, while being able to quantitatively recover certain key high-level urban spatial metrics.

Investigating univariate temporal patterns for intrinsic connectivity networks based on complexity and low-frequency oscillation: a test-retest reliability study.

Science.gov (United States)

Wang, X; Jiao, Y; Tang, T; Wang, H; Lu, Z

2013-12-19

Intrinsic connectivity networks (ICNs) are composed of spatial components and time courses. The spatial components of ICNs were discovered with moderate-to-high reliability. So far as we know, few studies focused on the reliability of the temporal patterns for ICNs based their individual time courses. The goals of this study were twofold: to investigate the test-retest reliability of temporal patterns for ICNs, and to analyze these informative univariate metrics. Additionally, a correlation analysis was performed to enhance interpretability. Our study included three datasets: (a) short- and long-term scans, (b) multi-band echo-planar imaging (mEPI), and (c) eyes open or closed. Using dual regression, we obtained the time courses of ICNs for each subject. To produce temporal patterns for ICNs, we applied two categories of univariate metrics: network-wise complexity and network-wise low-frequency oscillation. Furthermore, we validated the test-retest reliability for each metric. The network-wise temporal patterns for most ICNs (especially for default mode network, DMN) exhibited moderate-to-high reliability and reproducibility under different scan conditions. Network-wise complexity for DMN exhibited fair reliability (ICC<0.5) based on eyes-closed sessions. Specially, our results supported that mEPI could be a useful method with high reliability and reproducibility. In addition, these temporal patterns were with physiological meanings, and certain temporal patterns were correlated to the node strength of the corresponding ICN. Overall, network-wise temporal patterns of ICNs were reliable and informative and could be complementary to spatial patterns of ICNs for further study. Copyright © 2013 IBRO. Published by Elsevier Ltd. All rights reserved.

Synchronization transmission of laser pattern signal within uncertain switched network

Science.gov (United States)

Lü, Ling; Li, Chengren; Li, Gang; Sun, Ao; Yan, Zhe; Rong, Tingting; Gao, Yan

2017-06-01

We propose a new technology for synchronization transmission of laser pattern signal within uncertain network with controllable topology. In synchronization process, the connection of dynamic network can vary at all time according to different demands. Especially, we construct the Lyapunov function of network through designing a special semi-positive definite function, and the synchronization transmission of laser pattern signal within uncertain network with controllable topology can be realized perfectly, which effectively avoids the complicated calculation for solving the second largest eignvalue of the coupling matrix of the dynamic network in order to obtain the network synchronization condition. At the same time, the uncertain parameters in dynamic equations belonging to network nodes can also be identified accurately via designing the identification laws of uncertain parameters. In addition, there are not any limitations for the synchronization target of network in the new technology, in other words, the target can either be a state variable signal of an arbitrary node within the network or an exterior signal.

Network support for e-Science in Latin America

International Nuclear Information System (INIS)

Stanton, M.; Macahdo, I.; Faerman, M.; Moura, A. L.

2007-01-01

Computer networks in Latin America have connected scientists in the region to their peers in other parts of the world since 1986. Starting with the creation of Internet2 in 1996, a new global research network has been extended throughout the world, providing communications infrastructure for large-scale international scientific collaboration. With the creation of the RedCLARA network and its links to Europe and the US between 2004 and 2005, this global network reached the majority of Latin America countries, setting the stage for much closer collaboration between scientists in Latin America and their counterparts in other countries. In this article we describe the development of the research networking infrastructure currently available within the region together with its inter-regional connections, and how this infrastructure is being used for support of e-science. Particular attention is given to the role of the national research and education networks (NRENs) in the region, and of their association, CLARA, in providing networking support for e-science projects. CLARA and Latin American NRENs are active partners in the EU-supported EELA and RINGrid projects, and also are making significant supporting contributions to the success of other international projects with Latin American partners, in fields such as High-Energy Physics, Astronomy and Astrophysics and Space Geodesy, to single out the early adopters of advanced networking technologies. These contributions are described in the article. The article concludes describing future trends in networking infrastructure in the region, in order to meet foreseeable demands for e-science support. These include the widespread adoption of optical networking and support for grid-based applications, as well as the provisioning of significantly higher international bandwidth to meet the declared needs for international collaboration in a number of fields including those mentioned above. (Author)

Cellular-automata-based learning network for pattern recognition

Science.gov (United States)

Tzionas, Panagiotis G.; Tsalides, Phillippos G.; Thanailakis, Adonios

1991-11-01

Most classification techniques either adopt an approach based directly on the statistical characteristics of the pattern classes involved, or they transform the patterns in a feature space and try to separate the point clusters in this space. An alternative approach based on memory networks has been presented, its novelty being that it can be implemented in parallel and it utilizes direct features of the patterns rather than statistical characteristics. This study presents a new approach for pattern classification using pseudo 2-D binary cellular automata (CA). This approach resembles the memory network classifier in the sense that it is based on an adaptive knowledge based formed during a training phase, and also in the fact that both methods utilize pattern features that are directly available. The main advantage of this approach is that the sensitivity of the pattern classifier can be controlled. The proposed pattern classifier has been designed using 1.5 micrometers design rules for an N-well CMOS process. Layout has been achieved using SOLO 1400. Binary pseudo 2-D hybrid additive CA (HACA) is described in the second section of this paper. The third section describes the operation of the pattern classifier and the fourth section presents some possible applications. The VLSI implementation of the pattern classifier is presented in the fifth section and, finally, the sixth section draws conclusions from the results obtained.

A systematic review of the impact of stroke on social support and social networks: associated factors and patterns of change.

Science.gov (United States)

Northcott, Sarah; Moss, Becky; Harrison, Kirsty; Hilari, Katerina

2016-08-01

Identify what factors are associated with functional social support and social network post stroke; explore stroke survivors' perspectives on what changes occur and how they are perceived. The following electronic databases were systematically searched up to May 2015: Academic Search Complete; CINAHL Plus; E-journals; Health Policy Reference Centre; MEDLINE; PsycARTICLES; PsycINFO; and SocINDEX. PRISMA guidelines were followed in the conduct and reporting of this review. All included studies were critically appraised using the Critical Appraisal Skills Program tools. Meta-ethnographic techniques were used to integrate findings from the qualitative studies. Given the heterogeneous nature of the quantitative studies, data synthesis was narrative. Seventy research reports met the eligibility criteria: 22 qualitative and 48 quantitative reporting on 4,816 stroke survivors. The qualitative studies described a contraction of the social network, with non-kin contact being vulnerable. Although family were more robust network members, significant strain was observed within the family unit. In the quantitative studies, poor functional social support was associated with depression (13/14 studies), reduced quality of life (6/6 studies) and worse physical recovery (2/2 studies). Reduced social network was associated with depression (7/8 studies), severity of disability (2/2 studies) and aphasia (2/2 studies). Although most indicators of social network reduced post stroke (for example, contact with friends, 5/5 studies), the perception of feeling supported remained relatively stable (4/4 studies). Following a stroke non-kin contact is vulnerable, strain is observed within the family unit, and poor social support is associated with depressive symptoms. © The Author(s) 2015.

Oscillator Neural Network Retrieving Sparsely Coded Phase Patterns

Science.gov (United States)

Aoyagi, Toshio; Nomura, Masaki

1999-08-01

Little is known theoretically about the associative memory capabilities of neural networks in which information is encoded not only in the mean firing rate but also in the timing of firings. Particularly, in the case of sparsely coded patterns, it is biologically important to consider the timings of firings and to study how such consideration influences storage capacities and quality of recalled patterns. For this purpose, we propose a simple extended model of oscillator neural networks to allow for expression of a nonfiring state. Analyzing both equilibrium states and dynamical properties in recalling processes, we find that the system possesses good associative memory.

Classification of data patterns using an autoassociative neural network topology

Science.gov (United States)

Dietz, W. E.; Kiech, E. L.; Ali, M.

1989-01-01

A diagnostic expert system based on neural networks is developed and applied to the real-time diagnosis of jet and rocket engines. The expert system methodologies are based on the analysis of patterns of behavior of physical mechanisms. In this approach, fault diagnosis is conceptualized as the mapping or association of patterns of sensor data to patterns representing fault conditions. The approach addresses deficiencies inherent in many feedforward neural network models and greatly reduces the number of networks necessary to identify the existence of a fault condition and estimate the duration and severity of the identified fault. The network topology used in the present implementation of the diagnostic system is described, as well as the training regimen used and the response of the system to inputs representing both previously observed and unknown fault scenarios. Noise effects on the integrity of the diagnosis are also evaluated.

Discovering Preferential Patterns in Sectoral Trade Networks.

Science.gov (United States)

Cingolani, Isabella; Piccardi, Carlo; Tajoli, Lucia

2015-01-01

We analyze the patterns of import/export bilateral relations, with the aim of assessing the relevance and shape of "preferentiality" in countries' trade decisions. Preferentiality here is defined as the tendency to concentrate trade on one or few partners. With this purpose, we adopt a systemic approach through the use of the tools of complex network analysis. In particular, we apply a pattern detection approach based on community and pseudocommunity analysis, in order to highlight the groups of countries within which most of members' trade occur. The method is applied to two intra-industry trade networks consisting of 221 countries, relative to the low-tech "Textiles and Textile Articles" and the high-tech "Electronics" sectors for the year 2006, to look at the structure of world trade before the start of the international financial crisis. It turns out that the two networks display some similarities and some differences in preferential trade patterns: they both include few significant communities that define narrow sets of countries trading with each other as preferential destinations markets or supply sources, and they are characterized by the presence of similar hierarchical structures, led by the largest economies. But there are also distinctive features due to the characteristics of the industries examined, in which the organization of production and the destination markets are different. Overall, the extent of preferentiality and partner selection at the sector level confirm the relevance of international trade costs still today, inducing countries to seek the highest efficiency in their trade patterns.

IP access networks with QoS support

Science.gov (United States)

Sargento, Susana; Valadas, Rui J. M. T.; Goncalves, Jorge; Sousa, Henrique

2001-07-01

The increasing demand of new services and applications is pushing for drastic changes on the design of access networks targeted mainly for residential and SOHO users. Future access networks will provide full service integration (including multimedia), resource sharing at the packet level and QoS support. It is expected that using IP as the base technology, the ideal plug-and-play scenario, where the management actions of the access network operator are kept to a minimum, will be achieved easily. This paper proposes an architecture for access networks based on layer 2 or layer 3 multiplexers that allows a number of simplifications in the network elements and protocols (e.g. in the routing and addressing functions). We discuss two possible steps in the evolution of access networks towards a more efficient support of IP based services. The first one still provides no QoS support and was designed with the goal of reusing as much as possible current technologies; it is based on tunneling to transport PPP sessions. The second one introduces QoS support through the use of emerging technologies and protocols. We illustrate the different phases of a multimedia Internet access session, when using SIP for session initiation, COPS for the management of QoS policies including the AAA functions and RSVP for resource reservation.

DETECTION OF TOPOLOGICAL PATTERNS IN PROTEIN NETWORKS.

Energy Technology Data Exchange (ETDEWEB)

MASLOV,S.SNEPPEN,K.

2003-11-17

interesting property of many biological networks that was recently brought to attention of the scientific community [3, 4, 5] is an extremely broad distribution of node connectivities defined as the number of immediate neighbors of a given node in the network. While the majority of nodes have just a few edges connecting them to other nodes in the network, there exist some nodes, that we will refer to as ''hubs'', with an unusually large number of neighbors. The connectivity of the most connected hub in such a network is typically several orders of magnitude larger than the average connectivity in the network. Often the distribution of connectivities of individual nodes can be approximated by a scale-free power law form [3] in which case the network is referred to as scale-free. Among biological networks distributions of node connectivities in metabolic [4], protein interaction [5], and brain functional [6] networks can be reasonably approximated by a power law extending for several orders of magnitude. The set of connectivities of individual nodes is an example of a low-level (single-node) topological property of a network. While it answers the question about how many neighbors a given node has, it gives no information about the identity of those neighbors. It is clear that most functional properties of networks are defined at a higher topological level in the exact pattern of connections of nodes to each other. However, such multi-node connectivity patterns are rather difficult to quantify and compare between networks. In this work we concentrate on multi-node topological properties of protein networks. These networks (as any other biological networks) lack the top-down design. Instead, selective forces of biological evolution shape them from raw material provided by random events such as mutations within individual genes, and gene duplications. As a result their connections are characterized by a large degree of randomness. One may wonder which

Pattern recognition of state variables by neural networks

International Nuclear Information System (INIS)

Faria, Eduardo Fernandes; Pereira, Claubia

1996-01-01

An artificial intelligence system based on artificial neural networks can be used to classify predefined events and emergency procedures. These systems are being used in different areas. In the nuclear reactors safety, the goal is the classification of events whose data can be processed and recognized by neural networks. In this works we present a preliminary simple system, using neural networks in the recognition of patterns the recognition of variables which define a situation. (author)

Divisibility patterns of natural numbers on a complex network.

Science.gov (United States)

Shekatkar, Snehal M; Bhagwat, Chandrasheel; Ambika, G

2015-09-16

Investigation of divisibility properties of natural numbers is one of the most important themes in the theory of numbers. Various tools have been developed over the centuries to discover and study the various patterns in the sequence of natural numbers in the context of divisibility. In the present paper, we study the divisibility of natural numbers using the framework of a growing complex network. In particular, using tools from the field of statistical inference, we show that the network is scale-free but has a non-stationary degree distribution. Along with this, we report a new kind of similarity pattern for the local clustering, which we call "stretching similarity", in this network. We also show that the various characteristics like average degree, global clustering coefficient and assortativity coefficient of the network vary smoothly with the size of the network. Using analytical arguments we estimate the asymptotic behavior of global clustering and average degree which is validated using numerical analysis.

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)

Childhood adversity, social support networks and well-being among youth aging out of care: An exploratory study of mediation.

Science.gov (United States)

Melkman, Eran P

2017-10-01

The goals of the present study are to examine the relationship between childhood adversity and adult well-being among vulnerable young adults formerly placed in substitute care, and to investigate how characteristics of their social support networks mediate this association. A sample of 345 Israeli young adults (ages 18-25), who had aged out of foster or residential care, responded to standardized self-report questionnaires tapping their social support network characteristics (e.g., network size or adequacy) vis-à-vis several types of social support (emotional, practical, information and guidance), experiences of childhood adversity, and measures of well-being (psychological distress, loneliness, and life satisfaction). Structural equation modelling (SEM) provided support for the mediating role of social support in the relationship between early adversity and adult well-being. Although network size, frequency of contact with its members, satisfaction with support, and network adequacy, were all negatively related to early adversity, only network adequacy showed a major and consistent contribution to the various measures of well-being. While patterns were similar across the types of support, the effects of practical and guidance support were most substantial. The findings suggest that the detrimental long-term consequences of early adversity on adult well-being are related not only to impaired structural aspects of support (e.g., network size), but also to a decreased ability to recognize available support and mobilize it. Practical and guidance support, more than emotional support, seem to be of critical importance. Copyright © 2017 Elsevier Ltd. All rights reserved.

Master stability functions reveal diffusion-driven pattern formation in networks

Science.gov (United States)

Brechtel, Andreas; Gramlich, Philipp; Ritterskamp, Daniel; Drossel, Barbara; Gross, Thilo

2018-03-01

We study diffusion-driven pattern formation in networks of networks, a class of multilayer systems, where different layers have the same topology, but different internal dynamics. Agents are assumed to disperse within a layer by undergoing random walks, while they can be created or destroyed by reactions between or within a layer. We show that the stability of homogeneous steady states can be analyzed with a master stability function approach that reveals a deep analogy between pattern formation in networks and pattern formation in continuous space. For illustration, we consider a generalized model of ecological meta-food webs. This fairly complex model describes the dispersal of many different species across a region consisting of a network of individual habitats while subject to realistic, nonlinear predator-prey interactions. In this example, the method reveals the intricate dependence of the dynamics on the spatial structure. The ability of the proposed approach to deal with this fairly complex system highlights it as a promising tool for ecology and other applications.

A simplified memory network model based on pattern formations

Science.gov (United States)

Xu, Kesheng; Zhang, Xiyun; Wang, Chaoqing; Liu, Zonghua

2014-12-01

Many experiments have evidenced the transition with different time scales from short-term memory (STM) to long-term memory (LTM) in mammalian brains, while its theoretical understanding is still under debate. To understand its underlying mechanism, it has recently been shown that it is possible to have a long-period rhythmic synchronous firing in a scale-free network, provided the existence of both the high-degree hubs and the loops formed by low-degree nodes. We here present a simplified memory network model to show that the self-sustained synchronous firing can be observed even without these two necessary conditions. This simplified network consists of two loops of coupled excitable neurons with different synaptic conductance and with one node being the sensory neuron to receive an external stimulus signal. This model can be further used to show how the diversity of firing patterns can be selectively formed by varying the signal frequency, duration of the stimulus and network topology, which corresponds to the patterns of STM and LTM with different time scales. A theoretical analysis is presented to explain the underlying mechanism of firing patterns.

A host-endoparasite network of Neotropical marine fish: are there organizational patterns?

Science.gov (United States)

Bellay, Sybelle; Lima, Dilermando P; Takemoto, Ricardo M; Luque, José L

2011-12-01

Properties of ecological networks facilitate the understanding of interaction patterns in host-parasite systems as well as the importance of each species in the interaction structure of a community. The present study evaluates the network structure, functional role of all species and patterns of parasite co-occurrence in a host-parasite network to determine the organization level of a host-parasite system consisting of 170 taxa of gastrointestinal metazoans of 39 marine fish species on the coast of Brazil. The network proved to be nested and modular, with a low degree of connectance. Host-parasite interactions were influenced by host phylogeny. Randomness in parasite co-occurrence was observed in most modules and component communities, although species segregation patterns were also observed. The low degree of connectance in the network may be the cause of properties such as nestedness and modularity, which indicate the presence of a high number of peripheral species. Segregation patterns among parasite species in modules underscore the role of host specificity. Knowledge of ecological networks allows detection of keystone species for the maintenance of biodiversity and the conduction of further studies on the stability of networks in relation to frequent environmental changes.

A Network Based Methodology to Reveal Patterns in Knowledge Transfer

Directory of Open Access Journals (Sweden)

Orlando López-Cruz

2015-12-01

Full Text Available This paper motivates, presents and demonstrates in use a methodology based in complex network analysis to support research aimed at identification of sources in the process of knowledge transfer at the interorganizational level. The importance of this methodology is that it states a unified model to reveal knowledge sharing patterns and to compare results from multiple researches on data from different periods of time and different sectors of the economy. This methodology does not address the underlying statistical processes. To do this, national statistics departments (NSD provide documents and tools at their websites. But this proposal provides a guide to model information inferences gathered from data processing revealing links between sources and recipients of knowledge being transferred and that the recipient detects as main source to new knowledge creation. Some national statistics departments set as objective for these surveys the characterization of innovation dynamics in firms and to analyze the use of public support instruments. From this characterization scholars conduct different researches. Measures of dimensions of the network composed by manufacturing firms and other organizations conform the base to inquiry the structure that emerges from taking ideas from other organizations to incept innovations. These two sets of data are actors of a two- mode-network. The link between two actors (network nodes, one acting as the source of the idea. The second one acting as the destination comes from organizations or events organized by organizations that “provide” ideas to other group of firms. The resulting demonstrated design satisfies the objective of being a methodological model to identify sources in knowledge transfer of knowledge effectively used in innovation.

Pattern Recognition for Reliability Assessment of Water Distribution Networks

NARCIS (Netherlands)

Trifunovi?, N.

2012-01-01

The study presented in this manuscript investigates the patterns that describe reliability of water distribution networks focusing to the node connectivity, energy balance, and economics of construction, operation and maintenance. A number of measures to evaluate the network resilience has been

Implementation Support of Security Design Patterns Using Test Templates

Directory of Open Access Journals (Sweden)

Masatoshi Yoshizawa

2016-06-01

Full Text Available Security patterns are intended to support software developers as the patterns encapsulate security expert knowledge. However, these patterns may be inappropriately applied because most developers are not security experts, leading to threats and vulnerabilities. Here we propose a support method for security design patterns in the implementation phase of software development. Our method creates a test template from a security design pattern, consisting of an “aspect test template” to observe the internal processing and a “test case template”. Providing design information creates a test from the test template with a tool. Because our test template is reusable, it can easily perform a test to validate a security design pattern. In an experiment involving four students majoring in information sciences, we confirm that our method can realize an effective test, verify pattern applications, and support pattern implementation.

Effects of behavioral patterns and network topology structures on Parrondo’s paradox

Science.gov (United States)

Ye, Ye; Cheong, Kang Hao; Cen, Yu-Wan; Xie, Neng-Gang

2016-11-01

A multi-agent Parrondo’s model based on complex networks is used in the current study. For Parrondo’s game A, the individual interaction can be categorized into five types of behavioral patterns: the Matthew effect, harmony, cooperation, poor-competition-rich-cooperation and a random mode. The parameter space of Parrondo’s paradox pertaining to each behavioral pattern, and the gradual change of the parameter space from a two-dimensional lattice to a random network and from a random network to a scale-free network was analyzed. The simulation results suggest that the size of the region of the parameter space that elicits Parrondo’s paradox is positively correlated with the heterogeneity of the degree distribution of the network. For two distinct sets of probability parameters, the microcosmic reasons underlying the occurrence of the paradox under the scale-free network are elaborated. Common interaction mechanisms of the asymmetric structure of game B, behavioral patterns and network topology are also revealed.

Efficient Mobility Management Signalling in Network Mobility Supported PMIPV6.

Science.gov (United States)

Samuelraj, Ananthi Jebaseeli; Jayapal, Sundararajan

2015-01-01

Proxy Mobile IPV6 (PMIPV6) is a network based mobility management protocol which supports node's mobility without the contribution from the respective mobile node. PMIPV6 is initially designed to support individual node mobility and it should be enhanced to support mobile network movement. NEMO-BSP is an existing protocol to support network mobility (NEMO) in PMIPV6 network. Due to the underlying differences in basic protocols, NEMO-BSP cannot be directly applied to PMIPV6 network. Mobility management signaling and data structures used for individual node's mobility should be modified to support group nodes' mobility management efficiently. Though a lot of research work is in progress to implement mobile network movement in PMIPV6, it is not yet standardized and each suffers with different shortcomings. This research work proposes modifications in NEMO-BSP and PMIPV6 to achieve NEMO support in PMIPV6. It mainly concentrates on optimizing the number and size of mobility signaling exchanged while mobile network or mobile network node changes its access point.

Efficient Mobility Management Signalling in Network Mobility Supported PMIPV6

Directory of Open Access Journals (Sweden)

Ananthi Jebaseeli Samuelraj

2015-01-01

Full Text Available Proxy Mobile IPV6 (PMIPV6 is a network based mobility management protocol which supports node’s mobility without the contribution from the respective mobile node. PMIPV6 is initially designed to support individual node mobility and it should be enhanced to support mobile network movement. NEMO-BSP is an existing protocol to support network mobility (NEMO in PMIPV6 network. Due to the underlying differences in basic protocols, NEMO-BSP cannot be directly applied to PMIPV6 network. Mobility management signaling and data structures used for individual node’s mobility should be modified to support group nodes’ mobility management efficiently. Though a lot of research work is in progress to implement mobile network movement in PMIPV6, it is not yet standardized and each suffers with different shortcomings. This research work proposes modifications in NEMO-BSP and PMIPV6 to achieve NEMO support in PMIPV6. It mainly concentrates on optimizing the number and size of mobility signaling exchanged while mobile network or mobile network node changes its access point.

Patterns recognition of electric brain activity using artificial neural networks

Science.gov (United States)

Musatov, V. Yu.; Pchelintseva, S. V.; Runnova, A. E.; Hramov, A. E.

2017-04-01

An approach for the recognition of various cognitive processes in the brain activity in the perception of ambiguous images. On the basis of developed theoretical background and the experimental data, we propose a new classification of oscillating patterns in the human EEG by using an artificial neural network approach. After learning of the artificial neural network reliably identified cube recognition processes, for example, left-handed or right-oriented Necker cube with different intensity of their edges, construct an artificial neural network based on Perceptron architecture and demonstrate its effectiveness in the pattern recognition of the EEG in the experimental.

Social Network Mixing Patterns In Mergers & Acquisitions - A Simulation Experiment

Directory of Open Access Journals (Sweden)

Robert Fabac

2011-01-01

Full Text Available In the contemporary world of global business and continuously growing competition, organizations tend to use mergers and acquisitions to enforce their position on the market. The future organization’s design is a critical success factor in such undertakings. The field of social network analysis can enhance our uderstanding of these processes as it lets us reason about the development of networks, regardless of their origin. The analysis of mixing patterns is particularly useful as it provides an insight into how nodes in a network connect with each other. We hypothesize that organizational networks with compatible mixing patterns will be integrated more successfully. After conducting a simulation experiment, we suggest an integration model based on the analysis of network assortativity. The model can be a guideline for organizational integration, such as occurs in mergers and acquisitions.

[Scale effect of Nanjing urban green infrastructure network pattern and connectivity analysis.

Science.gov (United States)

Yu, Ya Ping; Yin, Hai Wei; Kong, Fan Hua; Wang, Jing Jing; Xu, Wen Bin

2016-07-01

Based on ArcGIS, Erdas, GuidosToolbox, Conefor and other software platforms, using morphological spatial pattern analysis (MSPA) and landscape connectivity analysis methods, this paper quantitatively analysed the scale effect, edge effect and distance effect of the Nanjing urban green infrastructure network pattern in 2013 by setting different pixel sizes (P) and edge widths in MSPA analysis, and setting different dispersal distance thresholds in landscape connectivity analysis. The results showed that the type of landscape acquired based on the MSPA had a clear scale effect and edge effect, and scale effects only slightly affected landscape types, whereas edge effects were more obvious. Different dispersal distances had a great impact on the landscape connectivity, 2 km or 2.5 km dispersal distance was a critical threshold for Nanjing. When selecting the pixel size 30 m of the input data and the edge wide 30 m used in the morphological model, we could get more detailed landscape information of Nanjing UGI network. Based on MSPA and landscape connectivity, analysis of the scale effect, edge effect, and distance effect on the landscape types of the urban green infrastructure (UGI) network was helpful for selecting the appropriate size, edge width, and dispersal distance when developing these networks, and for better understanding the spatial pattern of UGI networks and the effects of scale and distance on the ecology of a UGI network. This would facilitate a more scientifically valid set of design parameters for UGI network spatiotemporal pattern analysis. The results of this study provided an important reference for Nanjing UGI networks and a basis for the analysis of the spatial and temporal patterns of medium-scale UGI landscape networks in other regions.

Generalised power graph compression reveals dominant relationship patterns in complex networks.

Science.gov (United States)

Ahnert, Sebastian E

2014-03-25

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

An approach to evaluate the topological significance of motifs and other patterns in regulatory networks

Directory of Open Access Journals (Sweden)

Wingender Edgar

2009-05-01

Full Text Available Abstract Background The identification of network motifs as statistically over-represented topological patterns has become one of the most promising topics in the analysis of complex networks. The main focus is commonly made on how they operate by means of their internal organization. Yet, their contribution to a network's global architecture is poorly understood. However, this requires switching from the abstract view of a topological pattern to the level of its instances. Here, we show how a recently proposed metric, the pairwise disconnectivity index, can be adapted to survey if and which kind of topological patterns and their instances are most important for sustaining the connectivity within a network. Results The pairwise disconnectivity index of a pattern instance quantifies the dependency of the pairwise connections between vertices in a network on the presence of this pattern instance. Thereby, it particularly considers how the coherence between the unique constituents of a pattern instance relates to the rest of a network. We have applied the method exemplarily to the analysis of 3-vertex topological pattern instances in the transcription networks of a bacteria (E. coli, a unicellular eukaryote (S. cerevisiae and higher eukaryotes (human, mouse, rat. We found that in these networks only very few pattern instances break lots of the pairwise connections between vertices upon the removal of an instance. Among them network motifs do not prevail. Rather, those patterns that are shared by the three networks exhibit a conspicuously enhanced pairwise disconnectivity index. Additionally, these are often located in close vicinity to each other or are even overlapping, since only a small number of genes are repeatedly present in most of them. Moreover, evidence has gathered that the importance of these pattern instances is due to synergistic rather than merely additive effects between their constituents. Conclusion A new method has been proposed

Supporting Scientific Research with the Energy Sciences Network

CERN Multimedia

CERN. Geneva; Monga, Inder

2016-01-01

The Energy Sciences Network (ESnet) is a high-performance, unclassified national network built to support scientific research. Funded by the U.S. Department of Energy’s Office of Science (SC) and managed by Lawrence Berkeley National Laboratory, ESnet provides services to more than 40 DOE research sites, including the entire National Laboratory system, its supercomputing facilities, and its major scientific instruments. ESnet also connects to 140 research and commercial networks, permitting DOE-funded scientists to productively collaborate with partners around the world. ESnet Division Director (Interim) Inder Monga and ESnet Networking Engineer David Mitchell will present current ESnet projects and research activities which help support the HEP community. ESnet  helps support the CERN community by providing 100Gbps trans-Atlantic network transport for the LHCONE and LHCOPN services. ESnet is also actively engaged in researching connectivity to cloud computing resources for HEP workflows a...

An in-depth longitudinal analysis of mixing patterns in a small scientific collaboration network

Energy Technology Data Exchange (ETDEWEB)

Rodriguez, Marko A [Los Alamos National Laboratory; Pepe, Alberto [UCLA

2009-01-01

Many investigations of scientific collaboration are based on large-scale statistical analyses of networks constructed from bibliographic repositories. These investigations often rely on a wealth of bibliographic data, but very little or no other information about the individuals in the network, and thus, fail to illustate the broader social and academic landscape in which collaboration takes place. In this article, we perform an in-depth longitudinal analysis of a small-scale network of scientific collaboration (N = 291) constructed from the bibliographic record of a research center involved in the development and application of sensor network technologies. We perform a preliminary analysis of selected structural properties of the network, computing its range, configuration and topology. We then support our preliminary statistical analysis with an in-depth temporal investigation of the assortativity mixing of these node characteristics: academic department, affiliation, position, and country of origin of the individuals in the network. Our qualitative analysis of mixing patterns offers clues as to the nature of the scientific community being modeled in relation to its organizational, disciplinary, institutional, and international arrangements of collaboration.

Core regulatory network motif underlies the ocellar complex patterning in Drosophila melanogaster

Science.gov (United States)

Aguilar-Hidalgo, D.; Lemos, M. C.; Córdoba, A.

2015-03-01

During organogenesis, developmental programs governed by Gene Regulatory Networks (GRN) define the functionality, size and shape of the different constituents of living organisms. Robustness, thus, is an essential characteristic that GRNs need to fulfill in order to maintain viability and reproducibility in a species. In the present work we analyze the robustness of the patterning for the ocellar complex formation in Drosophila melanogaster fly. We have systematically pruned the GRN that drives the development of this visual system to obtain the minimum pathway able to satisfy this pattern. We found that the mechanism underlying the patterning obeys to the dynamics of a 3-nodes network motif with a double negative feedback loop fed by a morphogenetic gradient that triggers the inhibition in a French flag problem fashion. A Boolean modeling of the GRN confirms robustness in the patterning mechanism showing the same result for different network complexity levels. Interestingly, the network provides a steady state solution in the interocellar part of the patterning and an oscillatory regime in the ocelli. This theoretical result predicts that the ocellar pattern may underlie oscillatory dynamics in its genetic regulation.

Construct Validation of Wenger's Support Network Typology.

Science.gov (United States)

Szabo, Agnes; Stephens, Christine; Allen, Joanne; Alpass, Fiona

2016-10-07

The study aimed to validate Wenger's empirically derived support network typology of responses to the Practitioner Assessment of Network Type (PANT) in an older New Zealander population. The configuration of network types was tested across ethnic groups and in the total sample. Data (N = 872, Mage = 67 years, SDage = 1.56 years) from the 2006 wave of the New Zealand Health, Work and Retirement study were analyzed using latent profile analysis. In addition, demographic differences among the emerging profiles were tested. Competing models were evaluated based on a range of fit criteria, which supported a five-profile solution. The "locally integrated," "community-focused," "local self-contained," "private-restricted," and "friend- and family-dependent" network types were identified as latent profiles underlying the data. There were no differences between Māori and non-Māori in final profile configurations. However, Māori were more likely to report integrated network types. Findings confirm the validity of Wenger's network types. However, the level to which participants endorse accessibility of family, frequency of interactions, and community engagement can be influenced by sample and contextual characteristics. Future research using the PANT items should empirically verify and derive the social support network types, rather than use a predefined scoring system. © The Author 2016. Published by Oxford University Press on behalf of The Gerontological Society of America. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Friendship networks of inner-city adults: a latent class analysis and multi-level regression of supporter types and the association of supporter latent class membership with supporter and recipient drug use.

Science.gov (United States)

Bohnert, Amy S B; German, Danielle; Knowlton, Amy R; Latkin, Carl A

2010-03-01

Social support is a multi-dimensional construct that is important to drug use cessation. The present study identified types of supportive friends among the social network members in a community-based sample and examined the relationship of supporter-type classes with supporter, recipient, and supporter-recipient relationship characteristics. We hypothesized that the most supportive network members and their support recipients would be less likely to be current heroin/cocaine users. Participants (n=1453) were recruited from low-income neighborhoods with a high prevalence of drug use. Participants identified their friends via a network inventory, and all nominated friends were included in a latent class analysis and grouped based on their probability of providing seven types of support. These latent classes were included as the dependent variable in a multi-level regression of supporter drug use, recipient drug use, and other characteristics. The best-fitting latent class model identified five support patterns: friends who provided Little/No Support, Low/Moderate Support, High Support, Socialization Support, and Financial Support. In bivariate models, friends in the High, Low/Moderate, and Financial Support were less likely to use heroin or cocaine and had less conflict with and were more trusted by the support recipient than friends in the Low/No Support class. Individuals with supporters in those same support classes compared to the Low/No Support class were less likely to use heroin or cocaine, or to be homeless or female. Multivariable models suggested similar trends. Those with current heroin/cocaine use were less likely to provide or receive comprehensive support from friends. Published by Elsevier Ireland Ltd.

Social support and employee well-being: the conditioning effect of perceived patterns of supportive exchange.

Science.gov (United States)

Nahum-Shani, Inbal; Bamberger, Peter A; Bacharach, Samuel B

2011-03-01

Seeking to explain divergent empirical findings regarding the direct effect of social support on well-being, the authors posit that the pattern of supportive exchange (i.e., reciprocal, under-, or over-reciprocating) determines the impact of receiving support on well-being. Findings generated on the basis of longitudinal data collected from a sample of older blue-collar workers support the authors' predictions, indicating that receiving emotional support is associated with enhanced well-being when the pattern of supportive exchange is perceived by an individual as being reciprocal (support received equals support given), with this association being weaker when the exchange of support is perceived as being under-reciprocating (support given exceeds support received). Moreover, receiving support was found to adversely affect well-being when the pattern of exchange was perceived as being over-reciprocating (support received exceeds support given). Theoretical and practical implications of these findings are discussed.

Pattern formation and firing synchronization in networks of map neurons

International Nuclear Information System (INIS)

Wang Qingyun; Duan Zhisheng; Huang Lin; Chen Guanrong; Lu Qishao

2007-01-01

Patterns and collective phenomena such as firing synchronization are studied in networks of nonhomogeneous oscillatory neurons and mixtures of oscillatory and excitable neurons, with dynamics of each neuron described by a two-dimensional (2D) Rulkov map neuron. It is shown that as the coupling strength is increased, typical patterns emerge spatially, which propagate through the networks in the form of beautiful target waves or parallel ones depending on the size of networks. Furthermore, we investigate the transitions of firing synchronization characterized by the rate of firing when the coupling strength is increased. It is found that there exists an intermediate coupling strength; firing synchronization is minimal simultaneously irrespective of the size of networks. For further increasing the coupling strength, synchronization is enhanced. Since noise is inevitable in real neurons, we also investigate the effects of white noise on firing synchronization for different networks. For the networks of oscillatory neurons, it is shown that firing synchronization decreases when the noise level increases. For the missed networks, firing synchronization is robust under the noise conditions considered in this paper. Results presented in this paper should prove to be valuable for understanding the properties of collective dynamics in real neuronal networks

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.

Chimera patterns in two-dimensional networks of coupled neurons

Science.gov (United States)

Schmidt, Alexander; Kasimatis, Theodoros; Hizanidis, Johanne; Provata, Astero; Hövel, Philipp

2017-03-01

We discuss synchronization patterns in networks of FitzHugh-Nagumo and leaky integrate-and-fire oscillators coupled in a two-dimensional toroidal geometry. A common feature between the two models is the presence of fast and slow dynamics, a typical characteristic of neurons. Earlier studies have demonstrated that both models when coupled nonlocally in one-dimensional ring networks produce chimera states for a large range of parameter values. In this study, we give evidence of a plethora of two-dimensional chimera patterns of various shapes, including spots, rings, stripes, and grids, observed in both models, as well as additional patterns found mainly in the FitzHugh-Nagumo system. Both systems exhibit multistability: For the same parameter values, different initial conditions give rise to different dynamical states. Transitions occur between various patterns when the parameters (coupling range, coupling strength, refractory period, and coupling phase) are varied. Many patterns observed in the two models follow similar rules. For example, the diameter of the rings grows linearly with the coupling radius.

Should government support business angel networks? The tale of Danish business angels network

DEFF Research Database (Denmark)

Christensen, Jesper Lindgaard

2011-01-01

. This article discusses the possible rationale for governments to support BANs and what criteria to apply when evaluating such networks. The article is based on an in-depth observation study of the whole life cycle of a national BAN – the Danish Business Angel Network (DBAN) – and a comparison with a similar......Policies promoting informal venture capital generally and business angel networks (BANs) in particular have gained increased attention in recent years. As a consequence, BANs are now widespread across Europe. However, there continues to be a debate whether BANs should be supported with public money...... whether to provide continuing support to BANs they should evaluate not only their immediate effectiveness but also whether BANs should be considered a part of the general small business support infrastructure....

Collaboration in sensor network research: an in-depth longitudinal analysis of assortative mixing patterns.

Science.gov (United States)

Pepe, Alberto; Rodriguez, Marko A

2010-09-01

Many investigations of scientific collaboration are based on statistical analyses of large networks constructed from bibliographic repositories. These investigations often rely on a wealth of bibliographic data, but very little or no other information about the individuals in the network, and thus, fail to illustrate the broader social and academic landscape in which collaboration takes place. In this article, we perform an in-depth longitudinal analysis of a relatively small network of scientific collaboration (N = 291) constructed from the bibliographic record of a research centerin the development and application of wireless and sensor network technologies. We perform a preliminary analysis of selected structural properties of the network, computing its range, configuration and topology. We then support our preliminary statistical analysis with an in-depth temporal investigation of the assortative mixing of selected node characteristics, unveiling the researchers' propensity to collaborate preferentially with others with a similar academic profile. Our qualitative analysis of mixing patterns offers clues as to the nature of the scientific community being modeled in relation to its organizational, disciplinary, institutional, and international arrangements of collaboration.

Inferring Gene Regulatory Networks Using Conditional Regulation Pattern to Guide Candidate Genes.

Directory of Open Access Journals (Sweden)

Fei Xiao

Full Text Available Combining path consistency (PC algorithms with conditional mutual information (CMI are widely used in reconstruction of gene regulatory networks. CMI has many advantages over Pearson correlation coefficient in measuring non-linear dependence to infer gene regulatory networks. It can also discriminate the direct regulations from indirect ones. However, it is still a challenge to select the conditional genes in an optimal way, which affects the performance and computation complexity of the PC algorithm. In this study, we develop a novel conditional mutual information-based algorithm, namely RPNI (Regulation Pattern based Network Inference, to infer gene regulatory networks. For conditional gene selection, we define the co-regulation pattern, indirect-regulation pattern and mixture-regulation pattern as three candidate patterns to guide the selection of candidate genes. To demonstrate the potential of our algorithm, we apply it to gene expression data from DREAM challenge. Experimental results show that RPNI outperforms existing conditional mutual information-based methods in both accuracy and time complexity for different sizes of gene samples. Furthermore, the robustness of our algorithm is demonstrated by noisy interference analysis using different types of noise.

Social relations: network, support and relational strain

DEFF Research Database (Denmark)

Due, P; Holstein, B; Lund, Rikke

1999-01-01

We introduce a conceptual framework with social relations as the main concept and the structure and the function of social relations as subconcepts. The structure of social relations covers aspects of formal relations and social network. The function of social relations covers social support......,011. The postal questionnaires were answered by a random sample in each of the age groups. The results show marked age and gender differences in both the structure and the function of social relations. The social network, measured as weekly contacts, weakens with age and so does instrumental support. Emotional...... support is unrelated to this decline in contact frequency and appears to be at the same level for younger and older individuals. Relational strain, measured as conflicts, declines with age for all kinds of social relations. The weakening of the social network with age does not seem to affect the level...

Using Network Science to Support Design Research

DEFF Research Database (Denmark)

Parraguez Ruiz, Pedro; Maier, Anja

2016-01-01

and societal impact. This chapter contributes to the use of network science in empirical studies of design organisations. It focuses on introducing a network-based perspective on the design process and in particular on making use of network science to support design research and practice. The main contribution...... of this chapter is an overview of the methodological challenges and core decision points when embarking on network-based design research, namely defining the overall research purpose and selecting network features. We furthermore highlight the potential for using archival data, the opportunities for navigating...

Social networks, support and early psychosis: a systematic review.

Science.gov (United States)

Gayer-Anderson, C; Morgan, C

2013-06-01

Background. There is strong evidence that those with a long-standing psychotic disorder have fewer social contacts and less social support than comparison groups. There is less research on the extent of social contacts and support prior to or at the onset of psychosis. In the light of recent evidence implicating a range of social experiences and contexts at the onset of psychosis, it is relevant to establish whether social networks and support diminished before or at the time of onset and whether the absence of such supports might contribute to risk, either directly or indirectly. We, therefore, conducted a systematic review of this literature to establish what is currently known about the relationship between social networks, support and early psychosis. Methods. We identified all studies investigating social networks and support in first episode psychosis samples and in general population samples with measures of psychotic experiences or schizotype by conducting systematic searches of electronic databases using pre-defined search terms and criteria. Findings were synthesized using non-quantitative approaches. Results. Thirty-eight papers were identified that met inclusion criteria. There was marked methodological heterogeneity, which limits the capacity to draw direct comparisons. Nonetheless, the existing literature suggests social networks (particularly close friends) and support diminished both among first episode samples and among non-clinical samples reporting psychotic experiences or with schizotype traits, compared with varying comparison groups. These differences may be more marked for men and for those from minority ethnic populations. Conclusions. Tentatively, reduced social networks and support appear to pre-date onset of psychotic disorder. However, the substantial methodological heterogeneity among the existing studies makes comparisons difficult and suggests a need for more robust and comparable studies on networks, support and early psychosis.

Understanding spatial and temporal patterning of astrocyte calcium transients via interactions between network transport and extracellular diffusion

Science.gov (United States)

Shtrahman, E.; Maruyama, D.; Olariu, E.; Fink, C. G.; Zochowski, M.

2017-02-01

Astrocytes form interconnected networks in the brain and communicate via calcium signaling. We investigate how modes of coupling between astrocytes influence the spatio-temporal patterns of calcium signaling within astrocyte networks and specifically how these network interactions promote coordination within this group of cells. To investigate these complex phenomena, we study reduced cultured networks of astrocytes and neurons. We image the spatial temporal patterns of astrocyte calcium activity and quantify how perturbing the coupling between astrocytes influences astrocyte activity patterns. To gain insight into the pattern formation observed in these cultured networks, we compare the experimentally observed calcium activity patterns to the patterns produced by a reduced computational model, where we represent astrocytes as simple units that integrate input through two mechanisms: gap junction coupling (network transport) and chemical release (extracellular diffusion). We examine the activity patterns in the simulated astrocyte network and their dependence upon these two coupling mechanisms. We find that gap junctions and extracellular chemical release interact in astrocyte networks to modulate the spatiotemporal patterns of their calcium dynamics. We show agreement between the computational and experimental findings, which suggests that the complex global patterns can be understood as a result of simple local coupling mechanisms.

Unsupervised discrimination of patterns in spiking neural networks with excitatory and inhibitory synaptic plasticity.

Science.gov (United States)

Srinivasa, Narayan; Cho, Youngkwan

2014-01-01

A spiking neural network model is described for learning to discriminate among spatial patterns in an unsupervised manner. The network anatomy consists of source neurons that are activated by external inputs, a reservoir that resembles a generic cortical layer with an excitatory-inhibitory (EI) network and a sink layer of neurons for readout. Synaptic plasticity in the form of STDP is imposed on all the excitatory and inhibitory synapses at all times. While long-term excitatory STDP enables sparse and efficient learning of the salient features in inputs, inhibitory STDP enables this learning to be stable by establishing a balance between excitatory and inhibitory currents at each neuron in the network. The synaptic weights between source and reservoir neurons form a basis set for the input patterns. The neural trajectories generated in the reservoir due to input stimulation and lateral connections between reservoir neurons can be readout by the sink layer neurons. This activity is used for adaptation of synapses between reservoir and sink layer neurons. A new measure called the discriminability index (DI) is introduced to compute if the network can discriminate between old patterns already presented in an initial training session. The DI is also used to compute if the network adapts to new patterns without losing its ability to discriminate among old patterns. The final outcome is that the network is able to correctly discriminate between all patterns-both old and new. This result holds as long as inhibitory synapses employ STDP to continuously enable current balance in the network. The results suggest a possible direction for future investigation into how spiking neural networks could address the stability-plasticity question despite having continuous synaptic plasticity.

Hypothetical Pattern Recognition Design Using Multi-Layer Perceptorn Neural Network For Supervised Learning

Directory of Open Access Journals (Sweden)

Md. Abdullah-al-mamun

2015-08-01

Full Text Available Abstract Humans are capable to identifying diverse shape in the different pattern in the real world as effortless fashion due to their intelligence is grow since born with facing several learning process. Same way we can prepared an machine using human like brain called Artificial Neural Network that can be recognize different pattern from the real world object. Although the various techniques is exists to implementation the pattern recognition but recently the artificial neural network approaches have been giving the significant attention. Because the approached of artificial neural network is like a human brain that is learn from different observation and give a decision the previously learning rule. Over the 50 years research now a days pattern recognition for machine learning using artificial neural network got a significant achievement. For this reason many real world problem can be solve by modeling the pattern recognition process. The objective of this paper is to present the theoretical concept for pattern recognition design using Multi-Layer Perceptorn neural networkin the algorithm of artificial Intelligence as the best possible way of utilizing available resources to make a decision that can be a human like performance.

Microcomb-Based True-Time-Delay Network for Microwave Beamforming With Arbitrary Beam Pattern Control

Science.gov (United States)

Xue, Xiaoxiao; Xuan, Yi; Bao, Chengying; Li, Shangyuan; Zheng, Xiaoping; Zhou, Bingkun; Qi, Minghao; Weiner, Andrew M.

2018-06-01

Microwave phased array antennas (PAAs) are very attractive to defense applications and high-speed wireless communications for their abilities of fast beam scanning and complex beam pattern control. However, traditional PAAs based on phase shifters suffer from the beam-squint problem and have limited bandwidths. True-time-delay (TTD) beamforming based on low-loss photonic delay lines can solve this problem. But it is still quite challenging to build large-scale photonic TTD beamformers due to their high hardware complexity. In this paper, we demonstrate a photonic TTD beamforming network based on a miniature microresonator frequency comb (microcomb) source and dispersive time delay. A method incorporating optical phase modulation and programmable spectral shaping is proposed for positive and negative apodization weighting to achieve arbitrary microwave beam pattern control. The experimentally demonstrated TTD beamforming network can support a PAA with 21 elements. The microwave frequency range is $\\mathbf{8\\sim20\\ {GHz}}$, and the beam scanning range is $\\mathbf{\\pm 60.2^\\circ}$. Detailed measurements of the microwave amplitudes and phases are performed. The beamforming performances of Gaussian, rectangular beams and beam notch steering are evaluated through simulations by assuming a uniform radiating antenna array. The scheme can potentially support larger PAAs with hundreds of elements by increasing the number of comb lines with broadband microcomb generation.

Support Vector Machines for Pattern Classification

CERN Document Server

Abe, Shigeo

2010-01-01

A guide on the use of SVMs in pattern classification, including a rigorous performance comparison of classifiers and regressors. The book presents architectures for multiclass classification and function approximation problems, as well as evaluation criteria for classifiers and regressors. Features: Clarifies the characteristics of two-class SVMs; Discusses kernel methods for improving the generalization ability of neural networks and fuzzy systems; Contains ample illustrations and examples; Includes performance evaluation using publicly available data sets; Examines Mahalanobis kernels, empir

Support network of adolescents with chronic disease: adolescents' perspective.

Science.gov (United States)

Kyngäs, Helvi

2004-12-01

The purpose of this study was to describe the support network of adolescents with a chronic disease from their own perspective. Data were collected by interviewing adolescents with asthma, epilepsy, juvenile rheumatoid arthritis (JRA) and insulin-dependent diabetes mellitus (IDDM). The sample consisted of 40 adolescents aged between 13 and 17 years. Interview data were examined using content analysis. Six main categories were established to describe the support network of adolescents with a chronic disease: parents, peers, school, health care providers, technology and pets. Peers were divided into two groups: fellow sufferers and peers without a chronic disease. At school, teachers, school nurses and classmates were part of the support network. Health care providers included nurses, physicians and physiotherapists. Technology was also part of the support network and included four techniques that may be used to communicate: computers, mobile telephones, television and videos. The results provided a useful insight into the social network of adolescents with chronic disease and serve to raise awareness of the problems and opinions experienced by adolescents with this condition.

Social networks and patterns of health risk behaviours over two decades: A multi-cohort study.

Science.gov (United States)

Kauppi, Maarit; Elovainio, Marko; Stenholm, Sari; Virtanen, Marianna; Aalto, Ville; Koskenvuo, Markku; Kivimäki, Mika; Vahtera, Jussi

2017-08-01

To determine the associations between social network size and subsequent long-term health behaviour patterns, as indicated by alcohol use, smoking, and physical activity. Repeat data from up to six surveys over a 15- or 20-year follow-up were drawn from the Finnish Public Sector study (Raisio-Turku cohort, n=986; Hospital cohort, n=7307), and the Health and Social Support study (n=20,115). Social network size was determined at baseline, and health risk behaviours were assessed using repeated data from baseline and follow-up. We pooled cohort-specific results from repeated-measures log-binomial regression with the generalized estimating equations (GEE) method using fixed-effects meta-analysis. Participants with up to 10 members in their social network at baseline had an unhealthy risk factor profile throughout the follow-up. The pooled relative risks adjusted for age, gender, survey year, chronic conditions and education were 1.15 for heavy alcohol use (95% CI: 1.06-1.24), 1.19 for smoking (95% CI: 1.12-1.27), and 1.25 for low physical activity (95% CI: 1.21-1.29), as compared with those with >20 members in their social network. These associations appeared to be similar in subgroups stratified according to gender, age and education. Social network size predicted persistent behaviour-related health risk patterns up to at least two decades. Copyright © 2017 Elsevier Inc. All rights reserved.

Supervision, mentorship and peer networks: how Estonian early career researchers get (or fail to get support

Directory of Open Access Journals (Sweden)

Jaana Eigi

2018-03-01

Full Text Available The paper analyses issues related to supervision and support of early career researchers in Estonian academia. We use nine focus groups interviews conducted in 2015 with representatives of social sciences in order to identify early career researchers’ needs with respect to support, frustrations they may experience, and resources they may have for addressing them. Our crucial contribution is the identification of wider support networks of peers and colleagues that may compensate, partially or even fully, for failures of official supervision. On the basis of our analysis we argue that support for early career researchers should take into account the resources they already possess but also recognise the importance of wider academic culture, including funding and employment patterns, and the roles of supervisors and senior researchers in ensuring successful functioning of support networks. Through analysing the conditions for the development of early career researchers – producers of knowledge – our paper contributes to social epistemology understood as analysis of specific forms of social organisation of knowledge production.

Visibility Network Patterns and Methods for Studying Visual Relational Phenomena in Archeology

Directory of Open Access Journals (Sweden)

Tom Brughmans

2017-08-01

Full Text Available A review of the archeological and non-archeological use of visibility networks reveals the use of a limited range of formal techniques, in particular for representing visibility theories. This paper aims to contribute to the study of complex visual relational phenomena in landscape archeology by proposing a range of visibility network patterns and methods. We propose first- and second-order visibility graph representations of total and cumulative viewsheds, and two-mode representations of cumulative viewsheds. We present network patterns that can be used to represent aspects of visibility theories and that can be used in statistical simulation models to compare theorized networks with observed networks. We argue for the need to incorporate observed visibility network density in these simulation models, by illustrating strong differences in visibility network density in three example landscapes. The approach is illustrated through a brief case study of visibility networks of long barrows in Cranborne Chase.

Active patterning and asymmetric transport in a model actomyosin network

Energy Technology Data Exchange (ETDEWEB)

Wang, Shenshen [Department of Chemical Engineering and Department of Physics, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139 (United States); Wolynes, Peter G. [Department of Chemistry and Center for Theoretical Biological Physics, Rice University, Houston, Texas 77005 (United States)

2013-12-21

Cytoskeletal networks, which are essentially motor-filament assemblies, play a major role in many developmental processes involving structural remodeling and shape changes. These are achieved by nonequilibrium self-organization processes that generate functional patterns and drive intracellular transport. We construct a minimal physical model that incorporates the coupling between nonlinear elastic responses of individual filaments and force-dependent motor action. By performing stochastic simulations we show that the interplay of motor processes, described as driving anti-correlated motion of the network vertices, and the network connectivity, which determines the percolation character of the structure, can indeed capture the dynamical and structural cooperativity which gives rise to diverse patterns observed experimentally. The buckling instability of individual filaments is found to play a key role in localizing collapse events due to local force imbalance. Motor-driven buckling-induced node aggregation provides a dynamic mechanism that stabilizes the two-dimensional patterns below the apparent static percolation limit. Coordinated motor action is also shown to suppress random thermal noise on large time scales, the two-dimensional configuration that the system starts with thus remaining planar during the structural development. By carrying out similar simulations on a three-dimensional anchored network, we find that the myosin-driven isotropic contraction of a well-connected actin network, when combined with mechanical anchoring that confers directionality to the collective motion, may represent a novel mechanism of intracellular transport, as revealed by chromosome translocation in the starfish oocyte.

Social networks as ICT collaborative and supportive learning media ...

African Journals Online (AJOL)

... ICT collaborative and supportive learning media utilisation within the Nigerian educational system. The concept of ICT was concisely explained vis-à-vis the social network concept, theory and collaborative and supportive learning media utilisation. Different types of social network are highlighted among which Facebook, ...

Pattern Recognition and Classification of Fatal Traffic Accidents in Israel A Neural Network Approach

DEFF Research Database (Denmark)

Prato, Carlo Giacomo; Gitelman, Victoria; Bekhor, Shlomo

2011-01-01

on 1,793 fatal traffic accidents occurred during the period between 2003 and 2006 and applies Kohonen and feed-forward back-propagation neural networks with the objective of extracting from the data typical patterns and relevant factors. Kohonen neural networks reveal five compelling accident patterns....... Feed-forward back-propagation neural networks indicate that sociodemographic characteristics of drivers and victims, accident location, and period of the day are extremely relevant factors. Accident patterns suggest that countermeasures are necessary for identified problems concerning mainly vulnerable...

A deep convolutional neural network to analyze position averaged convergent beam electron diffraction patterns.

Science.gov (United States)

Xu, W; LeBeau, J M

2018-05-01

We establish a series of deep convolutional neural networks to automatically analyze position averaged convergent beam electron diffraction patterns. The networks first calibrate the zero-order disk size, center position, and rotation without the need for pretreating the data. With the aligned data, additional networks then measure the sample thickness and tilt. The performance of the network is explored as a function of a variety of variables including thickness, tilt, and dose. A methodology to explore the response of the neural network to various pattern features is also presented. Processing patterns at a rate of  ∼ 0.1 s/pattern, the network is shown to be orders of magnitude faster than a brute force method while maintaining accuracy. The approach is thus suitable for automatically processing big, 4D STEM data. We also discuss the generality of the method to other materials/orientations as well as a hybrid approach that combines the features of the neural network with least squares fitting for even more robust analysis. The source code is available at https://github.com/subangstrom/DeepDiffraction. Copyright © 2018 Elsevier B.V. All rights reserved.

Patterning human neuronal networks on photolithographically engineered silicon dioxide substrates functionalized with glial analogues.

Science.gov (United States)

Hughes, Mark A; Brennan, Paul M; Bunting, Andrew S; Cameron, Katherine; Murray, Alan F; Shipston, Mike J

2014-05-01

Interfacing neurons with silicon semiconductors is a challenge being tackled through various bioengineering approaches. Such constructs inform our understanding of neuronal coding and learning and ultimately guide us toward creating intelligent neuroprostheses. A fundamental prerequisite is to dictate the spatial organization of neuronal cells. We sought to pattern neurons using photolithographically defined arrays of polymer parylene-C, activated with fetal calf serum. We used a purified human neuronal cell line [Lund human mesencephalic (LUHMES)] to establish whether neurons remain viable when isolated on-chip or whether they require a supporting cell substrate. When cultured in isolation, LUHMES neurons failed to pattern and did not show any morphological signs of differentiation. We therefore sought a cell type with which to prepattern parylene regions, hypothesizing that this cellular template would enable secondary neuronal adhesion and network formation. From a range of cell lines tested, human embryonal kidney (HEK) 293 cells patterned with highest accuracy. LUHMES neurons adhered to pre-established HEK 293 cell clusters and this coculture environment promoted morphological differentiation of neurons. Neurites extended between islands of adherent cell somata, creating an orthogonally arranged neuronal network. HEK 293 cells appear to fulfill a role analogous to glia, dictating cell adhesion, and generating an environment conducive to neuronal survival. We next replaced HEK 293 cells with slower growing glioma-derived precursors. These primary human cells patterned accurately on parylene and provided a similarly effective scaffold for neuronal adhesion. These findings advance the use of this microfabrication-compatible platform for neuronal patterning. Copyright © 2013 Wiley Periodicals, Inc.

Implementing e-network-supported inquiry learning in science

DEFF Research Database (Denmark)

Williams, John; Cowie, Bronwen; Khoo, Elaine

2013-01-01

The successful implementation of electronically networked (e-networked) tools to support an inquiry-learning approach in secondary science classrooms is dependent on a range of factors spread between teachers, schools, and students. The teacher must have a clear understanding of the nature......-construct knowledge using a wide range of resources for meaning making and expression of ideas. These outcomes were, however, contingent on the interplay of teacher understanding of the nature of science inquiry and school provision of an effective technological infrastructure and support for flexible curriculum...... of inquiry, the school must provide effective technological infrastructure and sympathetic curriculum parameters, and the students need to be carefully scaffolded to the point of engaging with the inquiry process. Within this study, e-networks supported students to exercise agency, collaborate, and co...

Complex networks from experimental horizontal oil–water flows: Community structure detection versus flow pattern discrimination

International Nuclear Information System (INIS)

Gao, Zhong-Ke; Fang, Peng-Cheng; Ding, Mei-Shuang; Yang, Dan; Jin, Ning-De

2015-01-01

We propose a complex network-based method to distinguish complex patterns arising from experimental horizontal oil–water two-phase flow. We first use the adaptive optimal kernel time–frequency representation (AOK TFR) to characterize flow pattern behaviors from the energy and frequency point of view. Then, we infer two-phase flow complex networks from experimental measurements and detect the community structures associated with flow patterns. The results suggest that the community detection in two-phase flow complex network allows objectively discriminating complex horizontal oil–water flow patterns, especially for the segregated and dispersed flow patterns, a task that existing method based on AOK TFR fails to work. - Highlights: • We combine time–frequency analysis and complex network to identify flow patterns. • We explore the transitional flow behaviors in terms of betweenness centrality. • Our analysis provides a novel way for recognizing complex flow patterns. • Broader applicability of our method is demonstrated and articulated

Synchronization stability and pattern selection in a memristive neuronal network

Science.gov (United States)

Wang, Chunni; Lv, Mi; Alsaedi, Ahmed; Ma, Jun

2017-11-01

Spatial pattern formation and selection depend on the intrinsic self-organization and cooperation between nodes in spatiotemporal systems. Based on a memory neuron model, a regular network with electromagnetic induction is proposed to investigate the synchronization and pattern selection. In our model, the memristor is used to bridge the coupling between the magnetic flux and the membrane potential, and the induction current results from the time-varying electromagnetic field contributed by the exchange of ion currents and the distribution of charged ions. The statistical factor of synchronization predicts the transition of synchronization and pattern stability. The bifurcation analysis of the sampled time series for the membrane potential reveals the mode transition in electrical activity and pattern selection. A formation mechanism is outlined to account for the emergence of target waves. Although an external stimulus is imposed on each neuron uniformly, the diversity in the magnetic flux and the induction current leads to emergence of target waves in the studied network.

Synchronization stability and pattern selection in a memristive neuronal network.

Science.gov (United States)

Wang, Chunni; Lv, Mi; Alsaedi, Ahmed; Ma, Jun

2017-11-01

Spatial pattern formation and selection depend on the intrinsic self-organization and cooperation between nodes in spatiotemporal systems. Based on a memory neuron model, a regular network with electromagnetic induction is proposed to investigate the synchronization and pattern selection. In our model, the memristor is used to bridge the coupling between the magnetic flux and the membrane potential, and the induction current results from the time-varying electromagnetic field contributed by the exchange of ion currents and the distribution of charged ions. The statistical factor of synchronization predicts the transition of synchronization and pattern stability. The bifurcation analysis of the sampled time series for the membrane potential reveals the mode transition in electrical activity and pattern selection. A formation mechanism is outlined to account for the emergence of target waves. Although an external stimulus is imposed on each neuron uniformly, the diversity in the magnetic flux and the induction current leads to emergence of target waves in the studied network.

Flow-pattern identification and nonlinear dynamics of gas-liquid two-phase flow in complex networks.

Science.gov (United States)

Gao, Zhongke; Jin, Ningde

2009-06-01

The identification of flow pattern is a basic and important issue in multiphase systems. Because of the complexity of phase interaction in gas-liquid two-phase flow, it is difficult to discern its flow pattern objectively. In this paper, we make a systematic study on the vertical upward gas-liquid two-phase flow using complex network. Three unique network construction methods are proposed to build three types of networks, i.e., flow pattern complex network (FPCN), fluid dynamic complex network (FDCN), and fluid structure complex network (FSCN). Through detecting the community structure of FPCN by the community-detection algorithm based on K -mean clustering, useful and interesting results are found which can be used for identifying five vertical upward gas-liquid two-phase flow patterns. To investigate the dynamic characteristics of gas-liquid two-phase flow, we construct 50 FDCNs under different flow conditions, and find that the power-law exponent and the network information entropy, which are sensitive to the flow pattern transition, can both characterize the nonlinear dynamics of gas-liquid two-phase flow. Furthermore, we construct FSCN and demonstrate how network statistic can be used to reveal the fluid structure of gas-liquid two-phase flow. In this paper, from a different perspective, we not only introduce complex network theory to the study of gas-liquid two-phase flow but also indicate that complex network may be a powerful tool for exploring nonlinear time series in practice.

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

Science.gov (United States)

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

2017-09-07

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

Gait pattern recognition in cerebral palsy patients using neural network modelling

International Nuclear Information System (INIS)

Muhammad, J.; Gibbs, S.; Abboud, R.; Anand, S.

2015-01-01

Interpretation of gait data obtained from modern 3D gait analysis is a challenging and time consuming task. The aim of this study was to create neural network models which can recognise the gait patterns from pre- and post-treatment and the normal ones. Neural network is a method which works on the principle of learning from experience and then uses the obtained knowledge to predict the unknown. Methods: Twenty-eight patients with cerebral palsy were recruited as subjects whose gait was analysed in pre- and post-treatment. A group of twenty-six normal subjects also participated in this study as control group. All subjects gait was analysed using Vicon Nexus to obtain the gait parameters and kinetic and kinematic parameters of hip, knee and ankle joints in three planes of both limbs. The gait data was used as input to create neural network models. A total of approximately 300 trials were split into 70% and 30% to train and test the models, respectively. Different models were built using different parameters. The gait was categorised as three patterns, i.e., normal, pre- and post-treatments. Result: The results showed that the models using all parameters or using the joint angles and moments could predict the gait patterns with approximately 95% accuracy. Some of the models e.g., the models using joint power and moments, had lower rate in recognition of gait patterns with approximately 70-90% successful ratio. Conclusion: Neural network model can be used in clinical practice to recognise the gait pattern for cerebral palsy patients. (author)

Storage of phase-coded patterns via STDP in fully-connected and sparse network: a study of the network capacity

Directory of Open Access Journals (Sweden)

Silvia Scarpetta

2010-08-01

Full Text Available We study the storage and retrieval of phase-coded patterns as stable dynamical attractors in recurrent neural networks, for both an analog and a integrate-and-fire spiking model. The synaptic strength is determined by a learning rule based on spike-time-dependent plasticity, with an asymmetric time window depending on the relative timing between pre- and post-synaptic activity. We store multiple patterns and study the network capacity. For the analog model, we find that the network capacity scales linearly with the network size, and that both capacity and the oscillation frequency of the retrieval state depend on the asymmetry of the learning time window. In addition to fully-connected networks, we study sparse networks, where each neuron is connected only to a small number $zll N$ of other neurons. Connections can be short range, between neighboring neurons placed on a regular lattice, or long range, between randomly chosen pairs of neurons. We find that a small fraction of long range connections is able to amplify the capacity of the network. This imply that a small-world-network topology is optimal, as a compromise between the cost of long range connections and the capacity increase. Also in the spiking integrate and fire model the crucial result of storing and retrieval of multiple phase-coded patterns is observed. The capacity of the fully-connected spiking network is investigated, together with the relation between oscillation frequency of retrieval state and window asymmetry.

Extracting Association Patterns in Network Communications

Science.gov (United States)

Portela, Javier; Villalba, Luis Javier García; Trujillo, Alejandra Guadalupe Silva; Orozco, Ana Lucila Sandoval; Kim, Tai-hoon

2015-01-01

In network communications, mixes provide protection against observers hiding the appearance of messages, patterns, length and links between senders and receivers. Statistical disclosure attacks aim to reveal the identity of senders and receivers in a communication network setting when it is protected by standard techniques based on mixes. This work aims to develop a global statistical disclosure attack to detect relationships between users. The only information used by the attacker is the number of messages sent and received by each user for each round, the batch of messages grouped by the anonymity system. A new modeling framework based on contingency tables is used. The assumptions are more flexible than those used in the literature, allowing to apply the method to multiple situations automatically, such as email data or social networks data. A classification scheme based on combinatoric solutions of the space of rounds retrieved is developed. Solutions about relationships between users are provided for all pairs of users simultaneously, since the dependence of the data retrieved needs to be addressed in a global sense. PMID:25679311

Extracting Association Patterns in Network Communications

Directory of Open Access Journals (Sweden)

Javier Portela

2015-02-01

Full Text Available In network communications, mixes provide protection against observers hiding the appearance of messages, patterns, length and links between senders and receivers. Statistical disclosure attacks aim to reveal the identity of senders and receivers in a communication network setting when it is protected by standard techniques based on mixes. This work aims to develop a global statistical disclosure attack to detect relationships between users. The only information used by the attacker is the number of messages sent and received by each user for each round, the batch of messages grouped by the anonymity system. A new modeling framework based on contingency tables is used. The assumptions are more flexible than those used in the literature, allowing to apply the method to multiple situations automatically, such as email data or social networks data. A classification scheme based on combinatoric solutions of the space of rounds retrieved is developed. Solutions about relationships between users are provided for all pairs of users simultaneously, since the dependence of the data retrieved needs to be addressed in a global sense.

Patterns of Workplace Supervisor Support Desired by Abused Women

Science.gov (United States)

Perrin, Nancy A.; Yragui, Nanette L.; Hanson, Ginger C.; Glass, Nancy

2011-01-01

The purpose of this study was to understand differences in patterns of supervisor support desired by female victims of intimate partner violence (IPV) and to examine whether the pattern of support desired at work is reflective of a woman's stage of change in the abusive relationship, IPV-related work interference, and IPV-related job reprimands or…

NESSIE: Network Example Source Supporting Innovative Experimentation

Science.gov (United States)

Taylor, Alan; Higham, Desmond J.

We describe a new web-based facility that makes available some realistic examples of complex networks. NESSIE (Network Example Source Supporting Innovative Experimentation) currently contains 12 specific networks from a diverse range of application areas, with a Scottish emphasis. This collection of data sets is designed to be useful for researchers in network science who wish to evaluate new algorithms, concepts and models. The data sets are available to download in two formats (MATLAB's .mat format and .txt files readable by packages such as Pajek), and some basic MATLAB tools for computing summary statistics are also provided.

Global patterns of interaction specialization in bird-flower networks

DEFF Research Database (Denmark)

Zanata, Thais B.; Dalsgaard, Bo; Passos, Fernando C.

2017-01-01

, such as plant species richness, asymmetry, latitude, insularity, topography, sampling methods and intensity. Results: Hummingbird–flower networks were more specialized than honeyeater–flower networks. Specifically, hummingbird–flower networks had a lower proportion of realized interactions (lower C), decreased...... in the interaction patterns with their floral resources. Location: Americas, Africa, Asia and Oceania/Australia. Methods: We compiled interaction networks between birds and floral resources for 79 hummingbird, nine sunbird and 33 honeyeater communities. Interaction specialization was quantified through connectance...... (C), complementary specialization (H2′), binary (QB) and weighted modularity (Q), with both observed and null-model corrected values. We compared interaction specialization among the three types of bird–flower communities, both independently and while controlling for potential confounding variables...

Family interaction and a supportive social network as salutogenic factors in childhood atopic illness.

Science.gov (United States)

Gustafsson, Per A; Kjellman, N-I Max; Björkstén, Bengt

2002-02-01

The role of psycho-social factors in the development of allergy was studied prospectively in 82 infants with a family history of atopy. The family participated in a standardized family test when the children were 18 months old. The ability to adjust to demands of the situation ('adaptability'), and the balance between emotional closeness and distance ('cohesion'), were assessed from videotapes by independent raters. Families rated as functional in both of these aspects were classified as 'functional', otherwise as 'dysfunctional'. The social network, life events, atopic symptoms (based on postal inquiries regarding symptoms answered by the parents, and on physical examinations), psychiatric symptoms, and socio-economic circumstances of the families were evaluated when the children were 18 months and 3 years of age. The children were classified as atopic (asthmatic symptoms or eczema) or as non-atopic. All but two children with atopic disease at 3 years of age had atopic disease before 18 months of age, while 32 of 60 children with atopic disease at 18 months of age had no problems by 3 years of age. An unbalanced family interplay at 18 months was associated with a relative risk (RR) of 1.99 for continuing atopic illness at 3 years of age (1.18 eczema on three or more localizations (RR reduced by 4.5%), and the amount of cat allergen in household dust (RR reduced by 3%). Recovery from atopic illness between 18 months and 3 years of age was four times as probable in families with functional interaction and a good social supportive network when children were 18 months of age, than in dysfunctional families with a poor social network (74% versus 20% p emotional distress than did healthy children (p = 0.02). Dysfunctional family interaction patterns were more commonly observed in families of children who at 3 years of age still had atopic symptoms, than in children who had recovered. The patterns included expression of emotion and reaction to the needs of others

Competition, transmission and pattern evolution: A network analysis of global oil trade

International Nuclear Information System (INIS)

Zhang, Hai-Ying; Ji, Qiang; Fan, Ying

2014-01-01

This paper studies the competition among oil importers using complex network theory, combined with several alternative measures of competition intensity, to analyze the evolution of the pattern and transmission of oil-trading competition. The results indicate that oil trade has formed a global competition pattern and that the role played by the Asian-Pacific region in the evolution of this competition pattern is becoming increasingly prominent. In addition, global competition intensity has continued to rise, and non-OECD countries have become the main driving force for this increase in global competition intensity. The large oil importers are the most significant parts of the global oil-trading competition pattern. They are not only the major participants in the competition for oil resources but also play important roles in the transmission of oil-trading competition. China and the United States especially display the feature of globalization, whose impacts of transmission reach across the whole oil-trading competition network. Finally, a “5C” (changeability, contestability, cooperation, commitment and circumstances) policy framework is put forward to maintain the stability of oil trade and improve the energy security of oil importers in various aspects. - Highlights: • An oil-trading competition network is constructed using complex network theory. • Oil trade has formed a global competition pattern and its intensity has kept rising. • The status of the Asian-Pacific region in the competition pattern becomes prominent. • Large oil importers play important roles in transmitting the trading competition. • A “5C” policy framework is put forward to cope with the intensive competition

Integrating Entropy and Closed Frequent Pattern Mining for Social Network Modelling and Analysis

Science.gov (United States)

Adnan, Muhaimenul; Alhajj, Reda; Rokne, Jon

The recent increase in the explicitly available social networks has attracted the attention of the research community to investigate how it would be possible to benefit from such a powerful model in producing effective solutions for problems in other domains where the social network is implicit; we argue that social networks do exist around us but the key issue is how to realize and analyze them. This chapter presents a novel approach for constructing a social network model by an integrated framework that first preparing the data to be analyzed and then applies entropy and frequent closed patterns mining for network construction. For a given problem, we first prepare the data by identifying items and transactions, which arc the basic ingredients for frequent closed patterns mining. Items arc main objects in the problem and a transaction is a set of items that could exist together at one time (e.g., items purchased in one visit to the supermarket). Transactions could be analyzed to discover frequent closed patterns using any of the well-known techniques. Frequent closed patterns have the advantage that they successfully grab the inherent information content of the dataset and is applicable to a broader set of domains. Entropies of the frequent closed patterns arc used to keep the dimensionality of the feature vectors to a reasonable size; it is a kind of feature reduction process. Finally, we analyze the dynamic behavior of the constructed social network. Experiments were conducted on a synthetic dataset and on the Enron corpus email dataset. The results presented in the chapter show that social networks extracted from a feature set as frequent closed patterns successfully carry the community structure information. Moreover, for the Enron email dataset, we present an analysis to dynamically indicate the deviations from each user's individual and community profile. These indications of deviations can be very useful to identify unusual events.

Three-dimensional chimera patterns in networks of spiking neuron oscillators

Science.gov (United States)

Kasimatis, T.; Hizanidis, J.; Provata, A.

2018-05-01

We study the stable spatiotemporal patterns that arise in a three-dimensional (3D) network of neuron oscillators, whose dynamics is described by the leaky integrate-and-fire (LIF) model. More specifically, we investigate the form of the chimera states induced by a 3D coupling matrix with nonlocal topology. The observed patterns are in many cases direct generalizations of the corresponding two-dimensional (2D) patterns, e.g., spheres, layers, and cylinder grids. We also find cylindrical and "cross-layered" chimeras that do not have an equivalent in 2D systems. Quantitative measures are calculated, such as the ratio of synchronized and unsynchronized neurons as a function of the coupling range, the mean phase velocities, and the distribution of neurons in mean phase velocities. Based on these measures, the chimeras are categorized in two families. The first family of patterns is observed for weaker coupling and exhibits higher mean phase velocities for the unsynchronized areas of the network. The opposite holds for the second family, where the unsynchronized areas have lower mean phase velocities. The various measures demonstrate discontinuities, indicating criticality as the parameters cross from the first family of patterns to the second.

Operations Plan for Support Network Development

Energy Technology Data Exchange (ETDEWEB)

None

2008-06-30

This report describes the operational processes and strategies that are building a support network for the National Security Technology Incubator (NSTI) program. The NSTI program currently is under development as part of the National Security Preparedness Project (NSPP), funded by Department of Energy (DOE)/National Nuclear Security Administration (NNSA) Grant No. DE FG52-07NA28084. Although the NSTI program offers a wide array of in-house business services, there are a certain number of services that will be provided by entities outside of Arrowhead Center. This report identifies the steps needed to develop an appropriate support network. The Arrowhead Center is working with external service providers and key stakeholders to establish feasible referral and implementation mechanics offering NSTI program participants the most comprehensive incubation services possible.

Modelling and predicting biogeographical patterns in river networks

Directory of Open Access Journals (Sweden)

Sabela Lois

2016-04-01

Full Text Available Statistical analysis and interpretation of biogeographical phenomena in rivers is now possible using a spatially explicit modelling framework, which has seen significant developments in the past decade. I used this approach to identify a spatial extent (geostatistical range in which the abundance of the parasitic freshwater pearl mussel (Margaritifera margaritifera L. is spatially autocorrelated in river networks. I show that biomass and abundance of host fish are a likely explanation for the autocorrelation in mussel abundance within a 15-km spatial extent. The application of universal kriging with the empirical model enabled precise prediction of mussel abundance within segments of river networks, something that has the potential to inform conservation biogeography. Although I used a variety of modelling approaches in my thesis, I focus here on the details of this relatively new spatial stream network model, thus advancing the study of biogeographical patterns in river networks.

Developing networks to support science teachers work

DEFF Research Database (Denmark)

Sillasen, Martin Krabbe; Valero, Paola

2012-01-01

In educational research literature constructing networks among practitioners has been suggested as a strategy to support teachers’ professional development (Huberman, 1995; Jackson & Temperley, 2007; Van Driel, Beijaard, & Verloop, 2001). The purpose of this paper is to report on a study about how...... networks provide opportunities for teachers from different schools to collaborate on improving the quality of their own science teaching practices. These networks exist at the meso-level of the educational system between the micro-realities of teachers’ individual practice and the macro-level, where...... to develop collaborative activities in primary science teacher communities in schools to improve individual teachers practice and in networks between teachers from different schools in each municipality. Each network was organized and moderated by a municipal science coordinator....

Flower-Visiting Social Wasps and Plants Interaction: Network Pattern and Environmental Complexity

Directory of Open Access Journals (Sweden)

Mateus Aparecido Clemente

2012-01-01

Full Text Available Network analysis as a tool for ecological interactions studies has been widely used since last decade. However, there are few studies on the factors that shape network patterns in communities. In this sense, we compared the topological properties of the interaction network between flower-visiting social wasps and plants in two distinct phytophysiognomies in a Brazilian savanna (Riparian Forest and Rocky Grassland. Results showed that the landscapes differed in species richness and composition, and also the interaction networks between wasps and plants had different patterns. The network was more complex in the Riparian Forest, with a larger number of species and individuals and a greater amount of connections between them. The network specialization degree was more generalist in the Riparian Forest than in the Rocky Grassland. This result was corroborated by means of the nestedness index. In both networks was found asymmetry, with a large number of wasps per plant species. In general aspects, most wasps had low niche amplitude, visiting from one to three plant species. Our results suggest that differences in structural complexity of the environment directly influence the structure of the interaction network between flower-visiting social wasps and plants.

Recurrent Neural Network For Forecasting Time Series With Long Memory Pattern

Science.gov (United States)

Walid; Alamsyah

2017-04-01

Recurrent Neural Network as one of the hybrid models are often used to predict and estimate the issues related to electricity, can be used to describe the cause of the swelling of electrical load which experienced by PLN. In this research will be developed RNN forecasting procedures at the time series with long memory patterns. Considering the application is the national electrical load which of course has a different trend with the condition of the electrical load in any country. This research produces the algorithm of time series forecasting which has long memory pattern using E-RNN after this referred to the algorithm of integrated fractional recurrent neural networks (FIRNN).The prediction results of long memory time series using models Fractional Integrated Recurrent Neural Network (FIRNN) showed that the model with the selection of data difference in the range of [-1,1] and the model of Fractional Integrated Recurrent Neural Network (FIRNN) (24,6,1) provides the smallest MSE value, which is 0.00149684.

Curriculum Assessment Using Artificial Neural Network and Support Vector Machine Modeling Approaches: A Case Study. IR Applications. Volume 29

Science.gov (United States)

Chen, Chau-Kuang

2010-01-01

Artificial Neural Network (ANN) and Support Vector Machine (SVM) approaches have been on the cutting edge of science and technology for pattern recognition and data classification. In the ANN model, classification accuracy can be achieved by using the feed-forward of inputs, back-propagation of errors, and the adjustment of connection weights. In…

Age and Gender Differences in Social Network Composition and Social Support Among Older Rural South Africans: Findings From the HAALSI Study.

Science.gov (United States)

Harling, Guy; Morris, Katherine Ann; Manderson, Lenore; Perkins, Jessica M; Berkman, Lisa F

2018-03-26

Drawing on the "Health and Aging in Africa: A Longitudinal Study of an INDEPTH community in South Africa" (HAALSI) baseline survey, we present data on older adults' social networks and receipt of social support in rural South Africa. We examine how age and gender differences in social network characteristics matched with patterns predicted by theories of choice- and constraint-based network contraction in older adults. We used regression analysis on data for 5,059 South African adults aged 40 and older. Older respondents reported fewer important social contacts and less frequent communication than their middle-aged peers, largely due to fewer nonkin connections. Network size difference between older and younger respondents was greater for women than for men. These gender and age differences were explicable by much higher levels of widowhood among older women compared to younger women and older men. There was no evidence for employment-related network contraction or selective retention of emotionally supportive ties. Marriage-related structural constraints impacted on older women's social networks in rural South Africa, but did not explain choice-based network contraction. These findings suggest that many older women in rural Africa, a growing population, may have an unmet need for social support.

State Support: A Prerequisite for Global Health Network Effectiveness

Science.gov (United States)

Marten, Robert; Smith, Richard D.

2018-01-01

Shiffman recently summarized lessons for network effectiveness from an impressive collection of case-studies. However, in common with most global health governance analysis in recent years, Shiffman underplays the important role of states in these global networks. As the body which decides and signs international agreements, often provides the resourcing, and is responsible for implementing initiatives all contributing to the prioritization of certain issues over others, state recognition and support is a prerequisite to enabling and determining global health networks’ success. The role of states deserves greater attention, analysis and consideration. We reflect upon the underappreciated role of the state within the current discourse on global health. We present the tobacco case study to illustrate the decisive role of states in determining progress for global health networks, and highlight how states use a legitimacy loop to gain legitimacy from and provide legitimacy to global health networks. Moving forward in assessing global health networks’ effectiveness, further investigating state support as a determinant of success will be critical. Understanding how global health networks and states interact and evolve to shape and support their respective interests should be a focus for future research. PMID:29524958

Working with NASA's OSS E/PO Support Network

Science.gov (United States)

Miner, E. D.; Lowes, L. L.

2001-11-01

With greater and greater emphasis on the inclusion of a public engagement component in all government-supported research funding, many members of the DPS are finding it difficult to find sufficient time and funding to develop a wide-reaching and effective E/PO program. NASA's Office of Space Science, over the last five years, has built a Support Network to assist its funded scientists to establish partnerships with local and/or national science formal or informal education organizations, who are anxious to connect with and use the expertise of space scientists. The OSS Support Network consists of four theme-based 'Forums,' including the Solar System Exploration (SSE) Forum, specifically designed for working with planetary scientists, and seven regional 'Brokers-Facilitators' who are more familiar with partnership and other potential avenues for involvement by scientists. The services provided by the Support Network are free to both the scientists and their potential partners and is not limited to NASA-funded scientists. In addition to its assistance to space scientists, the Support Network is involved in a number of other overarching efforts, including support of a Solar System Ambassador Program, a Solar System Educator Program, Space Place (web and e-mail science products for libraries and small planetariums and museums), an on-line Space Science Resource Directory, annual reports of Space Science E/PO activity, identifying and filling in 'holes' and 'over-populations' in a solar system E/PO product matrix of grade level versus product versus content, research on product effectiveness, and scientific and educational evaluation of space science products. Forum and Broker-Facilitator contact information is available at http://spacescience.nasa.gov/education/resources/ecosystem/index.htm. Handouts with additional information will be available at the meeting.

Pattern classification and recognition of invertebrate functional groups using self-organizing neural networks.

Science.gov (United States)

Zhang, WenJun

2007-07-01

Self-organizing neural networks can be used to mimic non-linear systems. The main objective of this study is to make pattern classification and recognition on sampling information using two self-organizing neural network models. Invertebrate functional groups sampled in the irrigated rice field were classified and recognized using one-dimensional self-organizing map and self-organizing competitive learning neural networks. Comparisons between neural network models, distance (similarity) measures, and number of neurons were conducted. The results showed that self-organizing map and self-organizing competitive learning neural network models were effective in pattern classification and recognition of sampling information. Overall the performance of one-dimensional self-organizing map neural network was better than self-organizing competitive learning neural network. The number of neurons could determine the number of classes in the classification. Different neural network models with various distance (similarity) measures yielded similar classifications. Some differences, dependent upon the specific network structure, would be found. The pattern of an unrecognized functional group was recognized with the self-organizing neural network. A relative consistent classification indicated that the following invertebrate functional groups, terrestrial blood sucker; terrestrial flyer; tourist (nonpredatory species with no known functional role other than as prey in ecosystem); gall former; collector (gather, deposit feeder); predator and parasitoid; leaf miner; idiobiont (acarine ectoparasitoid), were classified into the same group, and the following invertebrate functional groups, external plant feeder; terrestrial crawler, walker, jumper or hunter; neustonic (water surface) swimmer (semi-aquatic), were classified into another group. It was concluded that reliable conclusions could be drawn from comparisons of different neural network models that use different distance

Organization of Anti-Phase Synchronization Pattern in Neural Networks: What are the Key Factors?

Science.gov (United States)

Li, Dong; Zhou, Changsong

2011-01-01

Anti-phase oscillation has been widely observed in cortical neural network. Elucidating the mechanism underlying the organization of anti-phase pattern is of significance for better understanding more complicated pattern formations in brain networks. In dynamical systems theory, the organization of anti-phase oscillation pattern has usually been considered to relate to time delay in coupling. This is consistent to conduction delays in real neural networks in the brain due to finite propagation velocity of action potentials. However, other structural factors in cortical neural network, such as modular organization (connection density) and the coupling types (excitatory or inhibitory), could also play an important role. In this work, we investigate the anti-phase oscillation pattern organized on a two-module network of either neuronal cell model or neural mass model, and analyze the impact of the conduction delay times, the connection densities, and coupling types. Our results show that delay times and coupling types can play key roles in this organization. The connection densities may have an influence on the stability if an anti-phase pattern exists due to the other factors. Furthermore, we show that anti-phase synchronization of slow oscillations can be achieved with small delay times if there is interaction between slow and fast oscillations. These results are significant for further understanding more realistic spatiotemporal dynamics of cortico-cortical communications. PMID:22232576

Support surfaces for pressure ulcer prevention: A network meta-analysis

Science.gov (United States)

Dumville, Jo C.; Cullum, Nicky

2018-01-01

Background Pressure ulcers are a prevalent and global issue and support surfaces are widely used for preventing ulceration. However, the diversity of available support surfaces and the lack of direct comparisons in RCTs make decision-making difficult. Objectives To determine, using network meta-analysis, the relative effects of different support surfaces in reducing pressure ulcer incidence and comfort and to rank these support surfaces in order of their effectiveness. Methods We conducted a systematic review, using a literature search up to November 2016, to identify randomised trials comparing support surfaces for pressure ulcer prevention. Two reviewers independently performed study selection, risk of bias assessment and data extraction. We grouped the support surfaces according to their characteristics and formed evidence networks using these groups. We used network meta-analysis to estimate the relative effects and effectiveness ranking of the groups for the outcomes of pressure ulcer incidence and participant comfort. GRADE was used to assess the certainty of evidence. Main results We included 65 studies in the review. The network for assessing pressure ulcer incidence comprised evidence of low or very low certainty for most network contrasts. There was moderate-certainty evidence that powered active air surfaces and powered hybrid air surfaces probably reduce pressure ulcer incidence compared with standard hospital surfaces (risk ratios (RR) 0.42, 95% confidence intervals (CI) 0.29 to 0.63; 0.22, 0.07 to 0.66, respectively). The network for comfort suggested that powered active air-surfaces are probably slightly less comfortable than standard hospital mattresses (RR 0.80, 95% CI 0.69 to 0.94; moderate-certainty evidence). Conclusions This is the first network meta-analysis of the effects of support surfaces for pressure ulcer prevention. Powered active air-surfaces probably reduce pressure ulcer incidence, but are probably less comfortable than standard

Support surfaces for pressure ulcer prevention: A network meta-analysis.

Science.gov (United States)

Shi, Chunhu; Dumville, Jo C; Cullum, Nicky

2018-01-01

Pressure ulcers are a prevalent and global issue and support surfaces are widely used for preventing ulceration. However, the diversity of available support surfaces and the lack of direct comparisons in RCTs make decision-making difficult. To determine, using network meta-analysis, the relative effects of different support surfaces in reducing pressure ulcer incidence and comfort and to rank these support surfaces in order of their effectiveness. We conducted a systematic review, using a literature search up to November 2016, to identify randomised trials comparing support surfaces for pressure ulcer prevention. Two reviewers independently performed study selection, risk of bias assessment and data extraction. We grouped the support surfaces according to their characteristics and formed evidence networks using these groups. We used network meta-analysis to estimate the relative effects and effectiveness ranking of the groups for the outcomes of pressure ulcer incidence and participant comfort. GRADE was used to assess the certainty of evidence. We included 65 studies in the review. The network for assessing pressure ulcer incidence comprised evidence of low or very low certainty for most network contrasts. There was moderate-certainty evidence that powered active air surfaces and powered hybrid air surfaces probably reduce pressure ulcer incidence compared with standard hospital surfaces (risk ratios (RR) 0.42, 95% confidence intervals (CI) 0.29 to 0.63; 0.22, 0.07 to 0.66, respectively). The network for comfort suggested that powered active air-surfaces are probably slightly less comfortable than standard hospital mattresses (RR 0.80, 95% CI 0.69 to 0.94; moderate-certainty evidence). This is the first network meta-analysis of the effects of support surfaces for pressure ulcer prevention. Powered active air-surfaces probably reduce pressure ulcer incidence, but are probably less comfortable than standard hospital surfaces. Most prevention evidence was of low or

Support surfaces for pressure ulcer prevention: A network meta-analysis.

Directory of Open Access Journals (Sweden)

Chunhu Shi

Full Text Available Pressure ulcers are a prevalent and global issue and support surfaces are widely used for preventing ulceration. However, the diversity of available support surfaces and the lack of direct comparisons in RCTs make decision-making difficult.To determine, using network meta-analysis, the relative effects of different support surfaces in reducing pressure ulcer incidence and comfort and to rank these support surfaces in order of their effectiveness.We conducted a systematic review, using a literature search up to November 2016, to identify randomised trials comparing support surfaces for pressure ulcer prevention. Two reviewers independently performed study selection, risk of bias assessment and data extraction. We grouped the support surfaces according to their characteristics and formed evidence networks using these groups. We used network meta-analysis to estimate the relative effects and effectiveness ranking of the groups for the outcomes of pressure ulcer incidence and participant comfort. GRADE was used to assess the certainty of evidence.We included 65 studies in the review. The network for assessing pressure ulcer incidence comprised evidence of low or very low certainty for most network contrasts. There was moderate-certainty evidence that powered active air surfaces and powered hybrid air surfaces probably reduce pressure ulcer incidence compared with standard hospital surfaces (risk ratios (RR 0.42, 95% confidence intervals (CI 0.29 to 0.63; 0.22, 0.07 to 0.66, respectively. The network for comfort suggested that powered active air-surfaces are probably slightly less comfortable than standard hospital mattresses (RR 0.80, 95% CI 0.69 to 0.94; moderate-certainty evidence.This is the first network meta-analysis of the effects of support surfaces for pressure ulcer prevention. Powered active air-surfaces probably reduce pressure ulcer incidence, but are probably less comfortable than standard hospital surfaces. Most prevention evidence was

Modular Neural Networks and Type-2 Fuzzy Systems for Pattern Recognition

CERN Document Server

Melin, Patricia

2012-01-01

This book describes hybrid intelligent systems using type-2 fuzzy logic and modular neural networks for pattern recognition applications. Hybrid intelligent systems combine several intelligent computing paradigms, including fuzzy logic, neural networks, and bio-inspired optimization algorithms, which can be used to produce powerful pattern recognition systems. Type-2 fuzzy logic is an extension of traditional type-1 fuzzy logic that enables managing higher levels of uncertainty in complex real world problems, which are of particular importance in the area of pattern recognition. The book is organized in three main parts, each containing a group of chapters built around a similar subject. The first part consists of chapters with the main theme of theory and design algorithms, which are basically chapters that propose new models and concepts, which are the basis for achieving intelligent pattern recognition. The second part contains chapters with the main theme of using type-2 fuzzy models and modular neural ne...

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

Energy Technology Data Exchange (ETDEWEB)

Dasari, Venkat [U.S. Army Research Laboratory, Aberdeen Proving Ground, MD; Sadlier, Ronald J [ORNL; Geerhart, Mr. Billy [U.S. Army Research Laboratory, Aberdeen Proving Ground, MD; Snow, Nikolai [U.S. Army Research Laboratory, Aberdeen Proving Ground, MD; Williams, Brian P [ORNL; Humble, Travis S [ORNL

2017-01-01

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

Networks in Later Life: An Examination of Race Differences in Social Support Networks.

Science.gov (United States)

Peek, M. Kristen; O'Neill, Gregory S.

2001-01-01

Considers race differences in the determinants of social support network characteristics using data from Established Populations for Epidemiological Studies of the Elderly. Focuses on the extent to which race differences in network dimensions are present and whether variations can be attributed to social structural positions held. Results indicate…

Social Support and Social Networks in COPD: A Scoping Review.

Science.gov (United States)

Barton, Christopher; Effing, Tanya W; Cafarella, Paul

2015-01-01

A scoping review was conducted to determine the size and nature of the evidence describing associations between social support and networks on health, management and clinical outcomes amongst patients with COPD. Searches of PubMed, PsychInfo and CINAHL were undertaken for the period 1966-December 2013. A descriptive synthesis of the main findings was undertaken to demonstrate where there is current evidence for associations between social support, networks and health outcomes, and where further research is needed. The search yielded 318 papers of which 287 were excluded after applying selection criteria. Two areas emerged in which there was consistent evidence of benefit of social support; namely mental health and self-efficacy. There was inconsistent evidence for a relationship between perceived social support and quality of life, physical functioning and self-rated health. Hospital readmission was not associated with level of perceived social support. Only a small number of studies (3 articles) have reported on the social network of individuals with COPD. There remains a need to identify the factors that promote and enable social support. In particular, there is a need to further understand the characteristics of social networks within the broader social structural conditions in which COPD patients live and manage their illness.

An Assessment of the Emerging Networks of Support for Street ...

African Journals Online (AJOL)

Nigeria, being asignatory to the Convention on the Rights of the Child (UNCRC, 1989) promulgated the Child Rights Act 2003, which aimed at ameliorating the condition of street children in Nigeria. In line with this, there are emerging networks of support for street children. The extent to which these support networks are ...

Stationary patterns in star networks of bistable units: Theory and application to chemical reactions.

Science.gov (United States)

Kouvaris, Nikos E; Sebek, Michael; Iribarne, Albert; Díaz-Guilera, Albert; Kiss, István Z

2017-04-01

We present theoretical and experimental studies on pattern formation with bistable dynamical units coupled in a star network configuration. By applying a localized perturbation to the central or the peripheral elements, we demonstrate the subsequent spreading, pinning, or retraction of the activations; such analysis enables the characterization of the formation of stationary patterns of localized activity. The results are interpreted with a theoretical analysis of a simplified bistable reaction-diffusion model. Weak coupling results in trivial pinned states where the activation cannot propagate. At strong coupling, a uniform state is expected with active or inactive elements at small or large degree networks, respectively. A nontrivial stationary spatial pattern, corresponding to an activation pinning, is predicted to occur at an intermediate number of peripheral elements and at intermediate coupling strengths, where the central activation of the network is pinned, but the peripheral activation propagates toward the center. The results are confirmed in experiments with star networks of bistable electrochemical reactions. The experiments confirm the existence of the stationary spatial patterns and the dependence of coupling strength on the number of peripheral elements for transitions between pinned and retreating or spreading fronts in forced network configurations (where the central or periphery elements are forced to maintain their states).

The social support and social network characteristics of smokers in methadone maintenance treatment.

Science.gov (United States)

de Dios, Marcel Alejandro; Stanton, Cassandra A; Caviness, Celeste M; Niaura, Raymond; Stein, Michael

2013-01-01

Previous studies have shown social support and social network variables to be important factors in smoking cessation treatment. Tobacco use is highly prevalent among individuals in methadone maintenance treatment (MMT). However, smoking cessation treatment outcomes in this vulnerable subpopulation have been poor and social support and social network variables may contribute. The current study examined the social support and social network characteristics of 151 MMT smokers involved in a randomized clinical trial of smoking cessation treatments. Participants were 50% women and 78% Caucasian. A high proportion (57%) of MMT smokers had spouses or partners who smoke and over two-thirds of households (68.5%) included at least one smoker. Our sample was characterized by relatively small social networks, but high levels of general social support and quitting support. The number of cigarettes per day was found to be positively associated with the number of smokers in the social network (r = .239, p social support and social networks of smokers in MMT.

Topological patterns in street networks of self-organized urban settlements

Science.gov (United States)

Buhl, J.; Gautrais, J.; Reeves, N.; Solé, R. V.; Valverde, S.; Kuntz, P.; Theraulaz, G.

2006-02-01

Many urban settlements result from a spatially distributed, decentralized building process. Here we analyze the topological patterns of organization of a large collection of such settlements using the approach of complex networks. The global efficiency (based on the inverse of shortest-path lengths), robustness to disconnections and cost (in terms of length) of these graphs is studied and their possible origins analyzed. A wide range of patterns is found, from tree-like settlements (highly vulnerable to random failures) to meshed urban patterns. The latter are shown to be more robust and efficient.

Social networking patterns/hazards among teenagers.

Science.gov (United States)

Machold, C; Judge, G; Mavrinac, A; Elliott, J; Murphy, A M; Roche, E

2012-05-01

Social Networking Sites (SNSs) have grown substantially, posing new hazards to teenagers. This study aimed to determine general patterns of Internet usage among Irish teenagers aged 11-16 years, and to identify potential hazards, including; bullying, inappropriate contact, overuse, addiction and invasion of users' privacy. A cross-sectional study design was employed to survey students at three Irish secondary schools, with a sample of 474 completing a questionnaire. 202 (44%) (n = 460) accessed the Internet using a shared home computer. Two hours or less were spent online daily by 285(62%), of whom 450 (98%) were unsupervised. 306 (72%) (n = 425) reported frequent usage of SNSs, 403 (95%) of whom were Facebook users. 42 (10%) males and 51 (12%) females experienced bullying online, while 114 (27%) reported inappropriate contact from others. Concerning overuse and the risk of addiction, 140 (33%) felt they accessed SNSs too often. These patterns among Irish teenagers suggest that SNS usage poses significant dangers, which are going largely unaddressed.

Social networking patterns/hazards among teenagers.

LENUS (Irish Health Repository)

Machold, C

2012-05-01

Social Networking Sites (SNSs) have grown substantially, posing new hazards to teenagers. This study aimed to determine general patterns of Internet usage among Irish teenagers aged 11-16 years, and to identify potential hazards, including; bullying, inappropriate contact, overuse, addiction and invasion of users\\' privacy. A cross-sectional study design was employed to survey students at three Irish secondary schools, with a sample of 474 completing a questionnaire. 202 (44%) (n = 460) accessed the Internet using a shared home computer. Two hours or less were spent online daily by 285(62%), of whom 450 (98%) were unsupervised. 306 (72%) (n = 425) reported frequent usage of SNSs, 403 (95%) of whom were Facebook users. 42 (10%) males and 51 (12%) females experienced bullying online, while 114 (27%) reported inappropriate contact from others. Concerning overuse and the risk of addiction, 140 (33%) felt they accessed SNSs too often. These patterns among Irish teenagers suggest that SNS usage poses significant dangers, which are going largely unaddressed.

Satisfaction with support versus size of network: differential effects of social support on psychological distress in parents of pediatric cancer patients.

Science.gov (United States)

Harper, Felicity W K; Peterson, Amy M; Albrecht, Terrance L; Taub, Jeffrey W; Phipps, Sean; Penner, Louis A

2016-05-01

This study examined the direct and buffering effects of social support on longer-term global psychological distress among parents coping with pediatric cancer. In both sets of analyses, we examined whether these effects depended on the dimension of social support provided (i.e., satisfaction with support versus size of support network). Participants were 102 parents of pediatric cancer patients. At study entry, parents reported their trait anxiety, depression, and two dimensions of their social support network (satisfaction with support and size of support network). Parents subsequently reported their psychological distress in 3- and 9-month follow-up assessments. Parents' satisfaction with support had a direct effect on longer-term psychological distress; satisfaction was negatively associated with distress at both follow-ups. In contrast, size of support network buffered (moderated) the impact of trait anxiety and depression on later distress. Parents with smaller support networks and higher levels of trait anxiety and depression at baseline had higher levels of psychological distress at both follow-ups; for parents with larger support networks, there was no relationship. Social support can attenuate psychological distress in parents coping with pediatric cancer; however, the nature of the effect depends on the dimension of support. Whereas interventions that focus on increasing satisfaction with social support may benefit all parents, at-risk parents will likely benefit from interventions that ensure they have an adequate number of support resources. Copyright © 2015 John Wiley & Sons, Ltd.

Examining the Relationships Between Education, Social Networks and Democratic Support With ABM

Science.gov (United States)

Drucker, Nick; Campbell, Kenyth

2011-01-01

This paper introduces an agent-based model that explores the relationships between education, social networks, and support for democratic ideals. This study examines two factors thai affect democratic support, education, and social networks. Current theory concerning these two variables suggests that positive relationships exist between education and democratic support and between social networks and the spread of ideas. The model contains multiple variables of democratic support, two of which are evaluated through experimentation. The model allows individual entities within the system to make "decisions" about their democratic support independent of one another. The agent based approach also allows entities to utilize their social networks to spread ideas. Current theory supports experimentation results. In addion , these results show the model is capable of reproducing real world outcomes. This paper addresses the model creation process and the experimentation procedure, as well as future research avenues and potential shortcomings of the model

Modern Social Support Structures: Online Social Networks and their Implications for Social Workers

Directory of Open Access Journals (Sweden)

Kala Chakradhar

2009-03-01

Full Text Available Mapping and assessing social networks and the quality of their social support is a valuable intervention strategy for social workers. These networks have now spread onto the digital realm in the form of Online Social Networks (OSNs. This study investigated the nature of social support provided by such networks to their users in a rural mid-South University (USA and explored parallels with the current understanding of social support in conventional social networks. A web-based survey administered to college students revealed that users of these online networks were predominantly undergraduate first year students, female, single, unemployed and from a variety of academic disciplines. The examination of the components of OSNs appears to mirror those of offline networks. They also seem to complement the effects of each other while contributing to an individual's support system. The paper concludes with critical implications of such online social networking for University students and social workers in practice and education.

Local community detection as pattern restoration by attractor dynamics of recurrent neural networks.

Science.gov (United States)

Okamoto, Hiroshi

2016-08-01

Densely connected parts in networks are referred to as "communities". Community structure is a hallmark of a variety of real-world networks. Individual communities in networks form functional modules of complex systems described by networks. Therefore, finding communities in networks is essential to approaching and understanding complex systems described by networks. In fact, network science has made a great deal of effort to develop effective and efficient methods for detecting communities in networks. Here we put forward a type of community detection, which has been little examined so far but will be practically useful. Suppose that we are given a set of source nodes that includes some (but not all) of "true" members of a particular community; suppose also that the set includes some nodes that are not the members of this community (i.e., "false" members of the community). We propose to detect the community from this "imperfect" and "inaccurate" set of source nodes using attractor dynamics of recurrent neural networks. Community detection by the proposed method can be viewed as restoration of the original pattern from a deteriorated pattern, which is analogous to cue-triggered recall of short-term memory in the brain. We demonstrate the effectiveness of the proposed method using synthetic networks and real social networks for which correct communities are known. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

On the origin of distribution patterns of motifs in biological networks

Directory of Open Access Journals (Sweden)

Lesk Arthur M

2008-08-01

Full Text Available Abstract Background Inventories of small subgraphs in biological networks have identified commonly-recurring patterns, called motifs. The inference that these motifs have been selected for function rests on the idea that their occurrences are significantly more frequent than random. Results Our analysis of several large biological networks suggests, in contrast, that the frequencies of appearance of common subgraphs are similar in natural and corresponding random networks. Conclusion Indeed, certain topological features of biological networks give rise naturally to the common appearance of the motifs. We therefore question whether frequencies of occurrences are reasonable evidence that the structures of motifs have been selected for their functional contribution to the operation of networks.

Towards integrated crisis support of regional emergency networks.

Science.gov (United States)

Caro, D H

1999-01-01

Emergency and crisis management pose multidimensional information systems challenges for communities across North America. In the quest to reduce mortality and morbidity risks and to increase the level of crisis preparedness, regional emergency management networks have evolved. Integrated Crisis Support Systems (ICSS) are enabling information technologies that assist emergency managers by enhancing the ability to strategically manage and control these regional emergency networks efficiently and effectively. This article underscores the ICCS development, control and leadership issues and their promising implications for regional emergency management networks.

Social Support Networks Among Diverse Sexual Minority Populations

Science.gov (United States)

Frost, David M.; Meyer, Ilan H.; Schwartz, Sharon

2016-01-01

This paper reports a study of the function and composition of social support networks among diverse lesbian, gay and bisexual (LGB) men and women (n = 396) in comparison to their heterosexual peers (n = 128). Data were collected using a structured social support network matrix in a community sample recruited in New York City. Our findings show that gay and bisexual men may rely on “chosen families” within LGBT communities more so than lesbian and bisexual women. Both heterosexuals and LGBs relied less on family and more on other people (e.g., friends, co-workers) for everyday social support (e.g., recreational and social activities, talking about problems). Providers of everyday social support were most often of the same sexual orientation and race/ethnicity as participants. In seeking major support (e.g., borrowing large sums of money), heterosexual men and women along with lesbian and bisexual women relied primarily on their families, but gay and bisexual men relied primarily on other LGB individuals. Racial/ethnic minority LGBs relied on LGB similar others at the same rate at White LGBs but, notably, racial/ethnic minority LGBs reported receiving fewer dimensions of support. PMID:26752447

Exploring the patterns and evolution of self-organized urban street networks through modeling

Science.gov (United States)

Rui, Yikang; Ban, Yifang; Wang, Jiechen; Haas, Jan

2013-03-01

As one of the most important subsystems in cities, urban street networks have recently been well studied by using the approach of complex networks. This paper proposes a growing model for self-organized urban street networks. The model involves a competition among new centers with different values of attraction radius and a local optimal principle of both geometrical and topological factors. We find that with the model growth, the local optimization in the connection process and appropriate probability for the loop construction well reflect the evolution strategy in real-world cities. Moreover, different values of attraction radius in centers competition process lead to morphological change in patterns including urban network, polycentric and monocentric structures. The model succeeds in reproducing a large diversity of road network patterns by varying parameters. The similarity between the properties of our model and empirical results implies that a simple universal growth mechanism exists in self-organized cities.

Support Networks for the Greek Family with Preschool or School-Age Disabled Children

Science.gov (United States)

Tsibidaki, Assimina; Tsamparli, Anastasia

2007-01-01

Introduction: The interaction of the family with disabled children with the support networks is a research area of high interest (Hendriks, De Moor, Oud & Savelberg, 2000). It has been shown that support networks may prove to be very helpful for a family and especially for a family with a disabled child. Support networks play a primordial role…

Compact holographic optical neural network system for real-time pattern recognition

Science.gov (United States)

Lu, Taiwei; Mintzer, David T.; Kostrzewski, Andrew A.; Lin, Freddie S.

1996-08-01

One of the important characteristics of artificial neural networks is their capability for massive interconnection and parallel processing. Recently, specialized electronic neural network processors and VLSI neural chips have been introduced in the commercial market. The number of parallel channels they can handle is limited because of the limited parallel interconnections that can be implemented with 1D electronic wires. High-resolution pattern recognition problems can require a large number of neurons for parallel processing of an image. This paper describes a holographic optical neural network (HONN) that is based on high- resolution volume holographic materials and is capable of performing massive 3D parallel interconnection of tens of thousands of neurons. A HONN with more than 16,000 neurons packaged in an attache case has been developed. Rotation- shift-scale-invariant pattern recognition operations have been demonstrated with this system. System parameters such as the signal-to-noise ratio, dynamic range, and processing speed are discussed.

Social Networks, Interpersonal Social Support, and Health Outcomes: A Health Communication Perspective

OpenAIRE

Wright, Kevin

2016-01-01

This manuscript discusses the development, impact, and several major research findings of studies in the area of social network support and health outcomes. The review focuses largely on the development of online social support networks and the ways in which they may interact with face-to-face support networks to influence physical and psychological health outcomes. The manuscript discusses this area, and it presents a research agenda for future work in this area from an Associate Editor’s pe...

Decompositions of injection patterns for nodal flow allocation in renewable electricity networks

Science.gov (United States)

Schäfer, Mirko; Tranberg, Bo; Hempel, Sabrina; Schramm, Stefan; Greiner, Martin

2017-08-01

The large-scale integration of fluctuating renewable power generation represents a challenge to the technical and economical design of a sustainable future electricity system. In this context, the increasing significance of long-range power transmission calls for innovative methods to understand the emerging complex flow patterns and to integrate price signals about the respective infrastructure needs into the energy market design. We introduce a decomposition method of injection patterns. Contrary to standard flow tracing approaches, it provides nodal allocations of link flows and costs in electricity networks by decomposing the network injection pattern into market-inspired elementary import/export building blocks. We apply the new approach to a simplified data-driven model of a European electricity grid with a high share of renewable wind and solar power generation.

Research on intrusion detection based on Kohonen network and support vector machine

Science.gov (United States)

Shuai, Chunyan; Yang, Hengcheng; Gong, Zeweiyi

2018-05-01

In view of the problem of low detection accuracy and the long detection time of support vector machine, which directly applied to the network intrusion detection system. Optimization of SVM parameters can greatly improve the detection accuracy, but it can not be applied to high-speed network because of the long detection time. a method based on Kohonen neural network feature selection is proposed to reduce the optimization time of support vector machine parameters. Firstly, this paper is to calculate the weights of the KDD99 network intrusion data by Kohonen network and select feature by weight. Then, after the feature selection is completed, genetic algorithm (GA) and grid search method are used for parameter optimization to find the appropriate parameters and classify them by support vector machines. By comparing experiments, it is concluded that feature selection can reduce the time of parameter optimization, which has little influence on the accuracy of classification. The experiments suggest that the support vector machine can be used in the network intrusion detection system and reduce the missing rate.

Experimental study of flow patterns near tube support structures

International Nuclear Information System (INIS)

Rummens, H.E.C.; Turner, C.W.

1994-07-01

Extensive blockage of broached support plates in steam generators has occurred at the Bruce A Nuclear Generating Station (NGS), forcing unit derating in 1988 March. Blockage has also been found on the lower broached plates of the Pickering B and Point Lepreau NGSs. Water chemistry and operating conditions are known to influence fouling directly. We suspect that flow patterns also play a role, that these patterns are influenced by the geometry of steam generator (SG) components, and that particularly the broached plate design actively creates an environment favorable to deposition. Experiments are in progress to examine the flow patterns near various tube supports: the broached plate, two types of lattice bars, and the formed bars. Preliminary tests in an air/water loop with 1/2- and 7-tube SG mockups containing the tube supports have been completed. Flow patterns were visualized using injected air bubbles. Local velocities and turbulence levels were measured using a laser technique, which confirmed observations of flow recirculation and stagnation. Axial pressure profiles were measured to determine overall resistance coefficients, and to identify local pressure extremes. Some visualization tests were also carried out on an artificially fouled broached plate. Based on results to date, several deposition mechanisms are proposed: deposition of particles in stagnant regions, deposition of solubles due to flashing in low-pressure regions, and deposition in smaller channels due to steam migration toward larger channels. A qualitative assessment of the tube support designs based on these mechanisms implies that the relative resistances to fouling are: (WORST) broach plate << lattice bars << formed bars (BEST). As the air/water simulation shows only hydraulic flow patterns, further tests will be done in a simple liquid/vapor Freon loop to examine thermal effects. (author). 3 refs., 10 figs

Do networks of social interactions reflect patterns of kinship?

Institute of Scientific and Technical Information of China (English)

Joah R. MADDEN; Johanna F. NIEL SEN; Tim H. CLUTTON-BROCK

2012-01-01

The underlying kin structure of groups of animals may be glimpsed from patterns of spatial position or temporal association between individuals,and is presumed to facilitate inclusive fitness benefits.Such structure may be evident at a finer,behavioural,scale with individuals preferentially interacting with kin.We tested whether kin structure within groups of meerkats Suricata suricatta matched three forms of social interaction networks:grooming,dominance or foraging competitions.Networks of dominance interactions were positively related to networks of kinship,with close relatives engaging in dominance interactions with each other.This relationship persisted even after excluding the breeding dominant pair and when we restricted the kinship network to only include links between first order kin,which are most likely to be able to discern kin through simple rules of thumb.Conversely,we found no relationship between kinship networks and either grooming networks or networks of foraging competitions.This is surprising because a positive association between kin in a grooming network,or a negative association between kin in a network of foraging competitions offers opportunities for inclusive fitness benefits.Indeed,the positive association between kin in a network of dominance interactions that we did detect does not offer clear inclusive fitness benefits to group members.We conclude that kin structure in behavioural interactions in meerkats may be driven by factors other than indirect fitness benefits,and that networks of cooperative behaviours such as grooming may be driven by direct benefits accruing to individuals perhaps through mutualism or manipulation [Current Zoology 58 (2):319-328,2012].

Do networks of social interactions reflect patterns of kinship?

Directory of Open Access Journals (Sweden)

Joah R. MADDEN, Johanna F. NIELSEN, Tim H. CLUTTON-BROCK

2012-04-01

Full Text Available The underlying kin structure of groups of animals may be glimpsed from patterns of spatial position or temporal association between individuals, and is presumed to facilitate inclusive fitness benefits. Such structure may be evident at a finer, behavioural, scale with individuals preferentially interacting with kin. We tested whether kin structure within groups of meerkats Suricata suricatta matched three forms of social interaction networks: grooming, dominance or foraging competitions. Networks of dominance interactions were positively related to networks of kinship, with close relatives engaging in dominance interactions with each other. This relationship persisted even after excluding the breeding dominant pair and when we restricted the kinship network to only include links between first order kin, which are most likely to be able to discern kin through simple rules of thumb. Conversely, we found no relationship between kinship networks and either grooming networks or networks of foraging competitions. This is surprising because a positive association between kin in a grooming network, or a negative association between kin in a network of foraging competitions offers opportunities for inclusive fitness benefits. Indeed, the positive association between kin in a network of dominance interactions that we did detect does not offer clear inclusive fitness benefits to group members. We conclude that kin structure in behavioural interactions in meerkats may be driven by factors other than indirect fitness benefits, and that networks of cooperative behaviours such as grooming may be driven by direct benefits accruing to individuals perhaps through mutualism or manipulation [Current Zoology 58 (2: 319-328, 2012].

Real-time distributed scheduling algorithm for supporting QoS over WDM networks

Science.gov (United States)

Kam, Anthony C.; Siu, Kai-Yeung

1998-10-01

Most existing or proposed WDM networks employ circuit switching, typically with one session having exclusive use of one entire wavelength. Consequently they are not suitable for data applications involving bursty traffic patterns. The MIT AON Consortium has developed an all-optical LAN/MAN testbed which provides time-slotted WDM service and employs fast-tunable transceivers in each optical terminal. In this paper, we explore extensions of this service to achieve fine-grained statistical multiplexing with different virtual circuits time-sharing the wavelengths in a fair manner. In particular, we develop a real-time distributed protocol for best-effort traffic over this time-slotted WDM service with near-optical fairness and throughput characteristics. As an additional design feature, our protocol supports the allocation of guaranteed bandwidths to selected connections. This feature acts as a first step towards supporting integrated services and quality-of-service guarantees over WDM networks. To achieve high throughput, our approach is based on scheduling transmissions, as opposed to collision- based schemes. Our distributed protocol involves one MAN scheduler and several LAN schedulers (one per LAN) in a master-slave arrangement. Because of propagation delays and limits on control channel capacities, all schedulers are designed to work with partial, delayed traffic information. Our distributed protocol is of the `greedy' type to ensure fast execution in real-time in response to dynamic traffic changes. It employs a hybrid form of rate and credit control for resource allocation. We have performed extensive simulations, which show that our protocol allocates resources (transmitters, receivers, wavelengths) fairly with high throughput, and supports bandwidth guarantees.

Municipal consultants’ participation in building networks to support science teachers’ work

DEFF Research Database (Denmark)

Sillasen, Martin Krabbe; Valero, Paola

2013-01-01

This paper focuses particularly on the role of municipal science consultants in developing and maintaining network activities and connections among primary school science teachers. The hypothesis is that consultants play a crucial role in supporting strategic planning, and sustaining contacts...... and activities within professional learning networks. The research is framed by a project that involved 80 primary science teachers in 20 schools. The aim of the project was to develop network activities that facilitate sustainable change of the participating schools’ collective culture and practice of science...... science consultants’ participation in supporting network activities enable the participants to share and develop teaching activities....

Core Support to Global Development Network (GND) - Phase II ...

International Development Research Centre (IDRC) Digital Library (Canada)

The Global Development Network (GDN) was launched by the World Bank in 1999 on the premise that good policy research, properly applied, can accelerate development and improve people's lives. Working mainly through regional networks, GDN supports economic and, increasingly, social science research in and on ...

Probing the reaching-grasping network in humans through multivoxel pattern decoding.

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Di Bono, Maria Grazia; Begliomini, Chiara; Castiello, Umberto; Zorzi, Marco

2015-11-01

The quest for a putative human homolog of the reaching-grasping network identified in monkeys has been the focus of many neuropsychological and neuroimaging studies in recent years. These studies have shown that the network underlying reaching-only and reach-to-grasp movements includes the superior parieto-occipital cortex (SPOC), the anterior part of the human intraparietal sulcus (hAIP), the ventral and the dorsal portion of the premotor cortex, and the primary motor cortex (M1). Recent evidence for a wider frontoparietal network coding for different aspects of reaching-only and reach-to-grasp actions calls for a more fine-grained assessment of the reaching-grasping network in humans by exploiting pattern decoding methods (multivoxel pattern analysis--MVPA). Here, we used MPVA on functional magnetic resonance imaging (fMRI) data to assess whether regions of the frontoparietal network discriminate between reaching-only and reach-to-grasp actions, natural and constrained grasping, different grasp types, and object sizes. Participants were required to perform either reaching-only movements or two reach-to-grasp types (precision or whole hand grasp) upon spherical objects of different sizes. Multivoxel pattern analysis highlighted that, independently from the object size, all the selected regions of both hemispheres contribute in coding for grasp type, with the exception of SPOC and the right hAIP. Consistent with recent neurophysiological findings on monkeys, there was no evidence for a clear-cut distinction between a dorsomedial and a dorsolateral pathway that would be specialized for reaching-only and reach-to-grasp actions, respectively. Nevertheless, the comparison of decoding accuracy across brain areas highlighted their different contributions to reaching-only and grasping actions. Altogether, our findings enrich the current knowledge regarding the functional role of key brain areas involved in the cortical control of reaching-only and reach-to-grasp actions

Geographic patterns of networks derived from extreme precipitation over the Indian subcontinent

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Stolbova, Veronika; Bookhagen, Bodo; Marwan, Norbert; Kurths, Juergen

2014-05-01

Complex networks (CN) and event synchronization (ES) methods have been applied to study a number of climate phenomena such as Indian Summer Monsoon (ISM), South-American Monsoon, and African Monsoon. These methods proved to be powerful tools to infer interdependencies in climate dynamics between geographical sites, spatial structures, and key regions of the considered climate phenomenon. Here, we use these methods to study the spatial temporal variability of the extreme rainfall over the Indian subcontinent, in order to filter the data by coarse-graining the network, and to identify geographic patterns that are signature features (spatial signatures) of the ISM. We find four main geographic patterns of networks derived from extreme precipitation over the Indian subcontinent using up-to-date satellite-derived, and high temporal and spatial resolution rain-gauge interpolated daily rainfall datasets. In order to prove that our results are also relevant for other climatic variables like pressure and temperature, we use re-analysis data provided by the National Center for Environmental Prediction and National Center for Atmospheric Research (NCEP/NCAR). We find that two of the patterns revealed from the CN extreme rainfall analysis coincide with those obtained for the pressure and temperature fields, and all four above mentioned patterns can be explained by topography, winds, and monsoon circulation. CN and ES enable to select the most informative regions for the ISM, providing realistic description of the ISM dynamics with fewer data, and also help to infer geographic pattern that are spatial signatures of the ISM. These patterns deserve a special attention for the meteorologists and can be used as markers of the ISM variability.

Estimating Urban Traffic Patterns through Probabilistic Interconnectivity of Road Network Junctions.

Directory of Open Access Journals (Sweden)

Ed Manley

Full Text Available The emergence of large, fine-grained mobility datasets offers significant opportunities for the development and application of new methodologies for transportation analysis. In this paper, the link between routing behaviour and traffic patterns in urban areas is examined, introducing a method to derive estimates of traffic patterns from a large collection of fine-grained routing data. Using this dataset, the interconnectivity between road network junctions is extracted in the form of a Markov chain. This representation encodes the probability of the successive usage of adjacent road junctions, encoding routes as flows between decision points rather than flows along road segments. This network of functional interactions is then integrated within a modified Markov chain Monte Carlo (MCMC framework, adapted for the estimation of urban traffic patterns. As part of this approach, the data-derived links between major junctions influence the movement of directed random walks executed across the network to model origin-destination journeys. The simulation process yields estimates of traffic distribution across the road network. The paper presents an implementation of the modified MCMC approach for London, United Kingdom, building an MCMC model based on a dataset of nearly 700000 minicab routes. Validation of the approach clarifies how each element of the MCMC framework contributes to junction prediction performance, and finds promising results in relation to the estimation of junction choice and minicab traffic distribution. The paper concludes by summarising the potential for the development and extension of this approach to the wider urban modelling domain.

Intelligent Configuration of Social Support Networks around Depressed Persons

NARCIS (Netherlands)

Aziz, A.A.; Klein, M.C.A.; Treur, J.

2011-01-01

Helping someone who is depressed can be very important to the depressed person. A number of supportive family members or friends can often make a big difference. This paper addresses how a social support network can be formed, taking the needs of the support recipient and the possibilities of the

Social networking in online support groups for health: how online social networking benefits patients.

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Chung, Jae Eun

2014-01-01

An increasing number of online support groups (OSGs) have embraced the features of social networking. So far, little is known about how patients use and benefit from these features. By implementing the uses-and-gratifications framework, the author conducted an online survey with current users of OSGs to examine associations among motivation, use of specific features of OSG, and support outcomes. Findings suggest that OSG users make selective use of varied features depending on their needs, and that perceptions of receiving emotional and informational support are associated more with the use of some features than others. For example, those with strong motivation for social interaction use diverse features of OSG and make one-to-one connections with other users by friending. In contrast, those with strong motivation for information seeking limit their use primarily to discussion boards. Results also show that online social networking features, such as friending and sharing of personal stories on blogs, are helpful in satisfying the need for emotional support. The present study sheds light on online social networking features in the context of health-related OSGs and provides practical lessons on how to improve the capacity of OSGs to serve the needs of their users.

Patterns of interactions of a large fish-parasite network in a tropical floodplain.

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Lima, Dilermando P; Giacomini, Henrique C; Takemoto, Ricardo M; Agostinho, Angelo A; Bini, Luis M

2012-07-01

1. Describing and explaining the structure of species interaction networks is of paramount importance for community ecology. Yet much has to be learned about the mechanisms responsible for major patterns, such as nestedness and modularity in different kinds of systems, of which large and diverse networks are a still underrepresented and scarcely studied fraction. 2. We assembled information on fishes and their parasites living in a large floodplain of key ecological importance for freshwater ecosystems in the Paraná River basin in South America. The resulting fish-parasite network containing 72 and 324 species of fishes and parasites, respectively, was analysed to investigate the patterns of nestedness and modularity as related to fish and parasite features. 3. Nestedness was found in the entire network and among endoparasites, multiple-host life cycle parasites and native hosts, but not in networks of ectoparasites, single-host life cycle parasites and non-native fishes. All networks were significantly modular. Taxonomy was the major host's attribute influencing both nestedness and modularity: more closely related host species tended to be associated with more nested parasite compositions and had greater chance of belonging to the same network module. Nevertheless, host abundance had a positive relationship with nestedness when only native host species pairs of the same network module were considered for analysis. 4. These results highlight the importance of evolutionary history of hosts in linking patterns of nestedness and formation of modules in the network. They also show that functional attributes of parasites (i.e. parasitism mode and life cycle) and origin of host populations (i.e. natives versus non-natives) are crucial to define the relative contribution of these two network properties and their dependence on other ecological factors (e.g. host abundance), with potential implications for community dynamics and stability. © 2012 The Authors

Mining Emerging Sequential Patterns for Activity Recognition in Body Sensor Networks

DEFF Research Database (Denmark)

Gu, Tao; Wang, Liang; Chen, Hanhua

2010-01-01

Body Sensor Networks oer many applications in healthcare, well-being and entertainment. One of the emerging applications is recognizing activities of daily living. In this paper, we introduce a novel knowledge pattern named Emerging Sequential Pattern (ESP)|a sequential pattern that discovers...... signicant class dierences|to recognize both simple (i.e., sequential) and complex (i.e., interleaved and concurrent) activities. Based on ESPs, we build our complex activity models directly upon the sequential model to recognize both activity types. We conduct comprehensive empirical studies to evaluate...

Cohort Differences in Received Social Support in Later Life: The Role of Network Type.

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Suanet, Bianca; Antonucci, Toni C

2017-07-01

The objective is to assess cohort differences in received emotional and instrumental support in relation to network types. The main guiding hypothesis is that due to increased salience of non-kin with recent social change, those in friend-focused and diverse network types receive more support in later birth cohorts than earlier birth cohorts. Data from the Longitudinal Aging Study Amsterdam are employed. We investigate cohort differences in total received emotional and instrumental support in a series of linear regression models comparing birth cohorts aged 55-64, 65-74, 75-84, and 85-94 across three time periods (1992, 2002, and 2012). Four network types (friend, family, restricted, and diverse) are identified. Friend-focused networks are more common in later birth cohorts, restrictive networks less common. Those in friend-focused networks in later cohorts report receiving more emotional and instrumental support. No differences in received support are evident upon diverse networks. The increased salience of non-kin is reflected in an increase in received emotional and instrumental support in friend-focused networks in later birth cohorts. The preponderance of non-kin in networks should not be perceived as a deficit model for social relationships as restrictive networks are declining across birth cohorts. © The Author 2016. Published by Oxford University Press on behalf of The Gerontological Society of America. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Optimization of patterns of control bars using neural networks

International Nuclear Information System (INIS)

Mejia S, D.M.; Ortiz S, J.J.

2005-01-01

In this work the RENOPBC system that is based on a recurrent multi state neural network, for the optimization of patterns of control bars in a cycle of balance of a boiling water reactor (BWR for their initials in English) is presented. The design of patterns of bars is based on the execution of operation thermal limits, to maintain criticizes the reactor and that the axial profile of power is adjusted to one predetermined along several steps of burnt. The patterns of control bars proposed by the system are comparable to those proposed by human experts with many hour-man of experience. These results are compared with those proposed by other techniques as genetic algorithms, colonies of ants and tabu search for the same operation cycle. As consequence it is appreciated that the proposed patterns of control bars, have bigger operation easiness that those proposed by the other techniques. (Author)

Support for Protests in Latin America: Classifications and the Role of Online Networking

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Rachel R. Mourão

2016-09-01

Full Text Available In recent years, Latin Americans marched the streets in a wave of protests that swept almost every country in the region. Yet few studies have assessed how Latin Americans support various forms of protest, and how new technologies affect attitudes toward protest tactics. Using data from the Latin American Public Opinion Project (N = 37,102, cluster analyses grouped citizens into four distinct groups depending on their support for protests. Most Latin Americans support moderate forms of protest, rejecting more radical tactics. Online networking is associated with support for both moderate and radical protests. But those who support only moderate protests use online networking sites more than Latin Americans as a whole, while those who support radical protests use online networking sites significantly less. Our findings suggest that only peaceful and legal demonstrations have been normalized in the region, and online networking foments support for moderate protest tactics.

Pattern-recalling processes in quantum Hopfield networks far from saturation

International Nuclear Information System (INIS)

Inoue, Jun-ichi

2011-01-01

As a mathematical model of associative memories, the Hopfield model was now well-established and a lot of studies to reveal the pattern-recalling process have been done from various different approaches. As well-known, a single neuron is itself an uncertain, noisy unit with a finite unnegligible error in the input-output relation. To model the situation artificially, a kind of 'heat bath' that surrounds neurons is introduced. The heat bath, which is a source of noise, is specified by the 'temperature'. Several studies concerning the pattern-recalling processes of the Hopfield model governed by the Glauber-dynamics at finite temperature were already reported. However, we might extend the 'thermal noise' to the quantum-mechanical variant. In this paper, in terms of the stochastic process of quantum-mechanical Markov chain Monte Carlo method (the quantum MCMC), we analytically derive macroscopically deterministic equations of order parameters such as 'overlap' in a quantum-mechanical variant of the Hopfield neural networks (let us call quantum Hopfield model or quantum Hopfield networks). For the case in which non-extensive number p of patterns are embedded via asymmetric Hebbian connections, namely, p/N → 0 for the number of neuron N → ∞ ('far from saturation'), we evaluate the recalling processes for one of the built-in patterns under the influence of quantum-mechanical noise.

Designing a Pattern Recognition Neural Network with a Reject Output and Many Sets of Weights and Biases

OpenAIRE

Dung, Le; Mizukawa, Makoto

2008-01-01

Adding the reject output to the pattern recognition neural network is an approach to help the neural network can classify almost all patterns of a training data set by using many sets of weights and biases, even if the neural network is small. With a smaller number of neurons, we can implement the neural network on a hardware-based platform more easily and also reduce the response time of it. With the reject output the neural network can produce not only right or wrong results but also reject...

Fracture network modeling and GoldSim simulation support

International Nuclear Information System (INIS)

Sugita, Kenichiro; Dershowitz, William

2004-01-01

During Heisei-15, Golder Associates provided support for JNC Tokai through discrete fracture network data analysis and simulation of the MIU Underground Rock Laboratory, participation in Task 6 of the Aespoe Task Force on Modelling of Groundwater Flow and Transport, and development of methodologies for analysis of repository site characterization strategies and safety assessment. MIU Underground Rock Laboratory support during H-15 involved development of new discrete fracture network (DFN) models for the MIU Shoba-sama Site, in the region of shaft development. Golder developed three DFN models for the site using discrete fracture network, equivalent porous medium (EPM), and nested DFN/EPM approaches. Each of these models were compared based upon criteria established for the multiple modeling project (MMP). Golder supported JNC participation in Task 6AB, 6D and 6E of the Aespoe Task Force on Modelling of Groundwater Flow and Transport during H-15. For Task 6AB, Golder implemented an updated microstructural model in GoldSim, and used this updated model to simulate the propagation of uncertainty from experimental to safety assessment time scales, for 5 m scale transport path lengths. Task 6D and 6E compared safety assessment (PA) and experimental time scale simulations in a 200 m scale discrete fracture network. For Task 6D, Golder implemented a DFN model using FracMan/PA Works, and determined the sensitivity of solute transport to a range of material property and geometric assumptions. For Task 6E, Golder carried out demonstration FracMan/PA Works transport calculations at a 1 million year time scale, to ensure that task specifications are realistic. The majority of work for Task 6E will be carried out during H-16. During H-15, Golder supported JNC's Total System Performance Assessment (TSPO) strategy by developing technologies for the analysis of precipitant concentration. These approaches were based on the GoldSim precipitant data management features, and were

QoS support over ultrafast TDM optical networks

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Narvaez, Paolo; Siu, Kai-Yeung; Finn, Steven G.

1999-08-01

HLAN is a promising architecture to realize Tb/s access networks based on ultra-fast optical TDM technologies. This paper presents new research results on efficient algorithms for the support of quality of service over the HLAN network architecture. In particular, we propose a new scheduling algorithm that emulates fair queuing in a distributed manner for bandwidth allocation purpose. The proposed scheduler collects information on the queue of each host on the network and then instructs each host how much data to send. Our new scheduling algorithm ensures full bandwidth utilization, while guaranteeing fairness among all hosts.

Network-aware support for mobile distributed teams

NARCIS (Netherlands)

Kleij, R. van der; Jong, A. de; Brake, G.M. te; Greefe, T.E.

2009-01-01

An experiment evaluated network-aware support to increase understanding of the factors that are important for successful teamwork in mobile geographically dispersed teams of first responders. Participants performed a simulated search and rescue team task and were equipped with a digitized map and

Efficient Mining and Detection of Sequential Intrusion Patterns for Network Intrusion Detection Systems

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Shyu, Mei-Ling; Huang, Zifang; Luo, Hongli

In recent years, pervasive computing infrastructures have greatly improved the interaction between human and system. As we put more reliance on these computing infrastructures, we also face threats of network intrusion and/or any new forms of undesirable IT-based activities. Hence, network security has become an extremely important issue, which is closely connected with homeland security, business transactions, and people's daily life. Accurate and efficient intrusion detection technologies are required to safeguard the network systems and the critical information transmitted in the network systems. In this chapter, a novel network intrusion detection framework for mining and detecting sequential intrusion patterns is proposed. The proposed framework consists of a Collateral Representative Subspace Projection Modeling (C-RSPM) component for supervised classification, and an inter-transactional association rule mining method based on Layer Divided Modeling (LDM) for temporal pattern analysis. Experiments on the KDD99 data set and the traffic data set generated by a private LAN testbed show promising results with high detection rates, low processing time, and low false alarm rates in mining and detecting sequential intrusion detections.

Abnormal network flow detection based on application execution patterns from Web of Things (WoT) platforms.

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Yoon, Young; Jung, Hyunwoo; Lee, Hana

2018-01-01

In this paper, we present a research work on a novel methodology of identifying abnormal behaviors at the underlying network monitor layer during runtime based on the execution patterns of Web of Things (WoT) applications. An execution pattern of a WoT application is a sequence of profiled time delays between the invocations of involved Web services, and it can be obtained from WoT platforms. We convert the execution pattern to a time sequence of network flows that are generated when the WoT applications are executed. We consider such time sequences as a whitelist. This whitelist reflects the valid application execution patterns. At the network monitor layer, our applied RETE algorithm examines whether any given runtime sequence of network flow instances does not conform to the whitelist. Through this approach, it is possible to interpret a sequence of network flows with regard to application logic. Given such contextual information, we believe that the administrators can detect and reason about any abnormal behaviors more effectively. Our empirical evaluation shows that our RETE-based algorithm outperforms the baseline algorithm in terms of memory usage.

BRAIN NETWORKS. Correlated gene expression supports synchronous activity in brain networks.

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Richiardi, Jonas; Altmann, Andre; Milazzo, Anna-Clare; Chang, Catie; Chakravarty, M Mallar; Banaschewski, Tobias; Barker, Gareth J; Bokde, Arun L W; Bromberg, Uli; Büchel, Christian; Conrod, Patricia; Fauth-Bühler, Mira; Flor, Herta; Frouin, Vincent; Gallinat, Jürgen; Garavan, Hugh; Gowland, Penny; Heinz, Andreas; Lemaître, Hervé; Mann, Karl F; Martinot, Jean-Luc; Nees, Frauke; Paus, Tomáš; Pausova, Zdenka; Rietschel, Marcella; Robbins, Trevor W; Smolka, Michael N; Spanagel, Rainer; Ströhle, Andreas; Schumann, Gunter; Hawrylycz, Mike; Poline, Jean-Baptiste; Greicius, Michael D

2015-06-12

During rest, brain activity is synchronized between different regions widely distributed throughout the brain, forming functional networks. However, the molecular mechanisms supporting functional connectivity remain undefined. We show that functional brain networks defined with resting-state functional magnetic resonance imaging can be recapitulated by using measures of correlated gene expression in a post mortem brain tissue data set. The set of 136 genes we identify is significantly enriched for ion channels. Polymorphisms in this set of genes significantly affect resting-state functional connectivity in a large sample of healthy adolescents. Expression levels of these genes are also significantly associated with axonal connectivity in the mouse. The results provide convergent, multimodal evidence that resting-state functional networks correlate with the orchestrated activity of dozens of genes linked to ion channel activity and synaptic function. Copyright © 2015, American Association for the Advancement of Science.

Nationwide Network of TalentPoints: The Hungarian Approach to Talent Support

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Csermely, Peter; Rajnai, Gabor; Sulyok, Katalin

2013-01-01

In 2006 a novel approach to talent support was promoted by several talent support programmes in Hungary. The new idea was a network approach. The nationwide network of so-called TalentPoints and its framework, the Hungarian Genius Program, gained substantial European Union funding in 2009, and today it is growing rapidly. A novel concept of talent…

The structural and functional brain networks that support human social networks.

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Noonan, M P; Mars, R B; Sallet, J; Dunbar, R I M; Fellows, L K

2018-02-20

Social skills rely on a specific set of cognitive processes, raising the possibility that individual differences in social networks are related to differences in specific brain structural and functional networks. Here, we tested this hypothesis with multimodality neuroimaging. With diffusion MRI (DMRI), we showed that differences in structural integrity of particular white matter (WM) tracts, including cingulum bundle, extreme capsule and arcuate fasciculus were associated with an individual's social network size (SNS). A voxel-based morphology analysis demonstrated correlations between gray matter (GM) volume and SNS in limbic and temporal lobe regions. These structural changes co-occured with functional network differences. As a function of SNS, dorsomedial and dorsolateral prefrontal cortex showed altered resting-state functional connectivity with the default mode network (DMN). Finally, we integrated these three complementary methods, interrogating the relationship between social GM clusters and specific WM and resting-state networks (RSNs). Probabilistic tractography seeded in these GM nodes utilized the SNS-related WM pathways. Further, the spatial and functional overlap between the social GM clusters and the DMN was significantly closer than other control RSNs. These integrative analyses provide convergent evidence of the role of specific circuits in SNS, likely supporting the adaptive behavior necessary for success in extensive social environments. Crown Copyright © 2018. Published by Elsevier B.V. All rights reserved.

Cultured Neural Networks: Optimization of Patterned Network Adhesiveness and Characterization of their Neural Activity

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W. L. C. Rutten

2006-01-01

Full Text Available One type of future, improved neural interface is the “cultured probe”. It is a hybrid type of neural information transducer or prosthesis, for stimulation and/or recording of neural activity. It would consist of a microelectrode array (MEA on a planar substrate, each electrode being covered and surrounded by a local circularly confined network (“island” of cultured neurons. The main purpose of the local networks is that they act as biofriendly intermediates for collateral sprouts from the in vivo system, thus allowing for an effective and selective neuron–electrode interface. As a secondary purpose, one may envisage future information processing applications of these intermediary networks. In this paper, first, progress is shown on how substrates can be chemically modified to confine developing networks, cultured from dissociated rat cortex cells, to “islands” surrounding an electrode site. Additional coating of neurophobic, polyimide-coated substrate by triblock-copolymer coating enhances neurophilic-neurophobic adhesion contrast. Secondly, results are given on neuronal activity in patterned, unconnected and connected, circular “island” networks. For connected islands, the larger the island diameter (50, 100 or 150 μm, the more spontaneous activity is seen. Also, activity may show a very high degree of synchronization between two islands. For unconnected islands, activity may start at 22 days in vitro (DIV, which is two weeks later than in unpatterned networks.

Posting Behaviour Patterns in an Online Smoking Cessation Social Network: Implications for Intervention Design and Development

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Healey, Benjamin; Hoek, Janet; Edwards, Richard

2014-01-01

Objectives Online Cessation Support Networks (OCSNs) are associated with increased quit success rates, but few studies have examined their use over time. We identified usage patterns in New Zealand's largest OCSN over two years and explored implications for OCSN intervention design and evaluation. Methods We analysed metadata relating to 133,096 OCSN interactions during 2011 and 2012. Metrics covered aggregate network activity, user posting activity and longevity, and between-user commenting. Binary logistic regression models were estimated to investigate the feasibility of predicting low user engagement using early interaction data. Results Repeating periodic peaks and troughs in aggregate activity related not only to seasonality (e.g., New Year), but also to day of the week. Out of 2,062 unique users, 69 Highly Engaged Users (180+ interactions each) contributed 69% of all OCSN interactions in 2012 compared to 1.3% contributed by 864 Minimally Engaged Users (metrics including posts and comments, this change did not coincide with large gains in first-time user persistence. Researchers assessing intervention effects should therefore examine multiple measures when evaluating changes in network dynamics over time. PMID:25192174

Patterns of work attitudes: A neural network approach

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Mengov, George D.; Zinovieva, Irina L.; Sotirov, George R.

2000-05-01

In this paper we introduce a neural networks based approach to analyzing empirical data and models from work and organizational psychology (WOP), and suggest possible implications for the practice of managers and business consultants. With this method it becomes possible to have quantitative answers to a bunch of questions like: What are the characteristics of an organization in terms of its employees' motivation? What distinct attitudes towards the work exist? Which pattern is most desirable from the standpoint of productivity and professional achievement? What will be the dynamics of behavior as quantified by our method, during an ongoing organizational change or consultancy intervention? Etc. Our investigation is founded on the theoretical achievements of Maslow (1954, 1970) in human motivation, and of Hackman & Oldham (1975, 1980) in job diagnostics, and applies the mathematical algorithm of the dARTMAP variation (Carpenter et al., 1998) of the Adaptive Resonance Theory (ART) neural networks introduced by Grossberg (1976). We exploit the ART capabilities to visualize the knowledge accumulated in the network's long-term memory in order to interpret the findings in organizational research.

Social networks, social support and psychiatric symptoms: social determinants and associations within a multicultural community population.

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Smyth, Natasha; Siriwardhana, Chesmal; Hotopf, Matthew; Hatch, Stephani L

2015-07-01

Little is known about how social networks and social support are distributed within diverse communities and how different types of each are associated with a range of psychiatric symptoms. This study aims to address such shortcomings by: (1) describing the demographic and socioeconomic characteristics of social networks and social support in a multicultural population and (2) examining how each is associated with multiple mental health outcomes. Data is drawn from the South East London Community Health Study; a cross-sectional study of 1,698 adults conducted between 2008 and 2010. The findings demonstrate variation in social networks and social support by socio-demographic factors. Ethnic minority groups reported larger family networks but less perceived instrumental support. Older individuals and migrant groups reported lower levels of particular network and support types. Individuals from lower socioeconomic groups tended to report less social networks and support across the indicators measured. Perceived emotional and instrumental support, family and friend network size emerged as protective factors for common mental disorder, personality dysfunction and psychotic experiences. In contrast, both social networks and social support appear less relevant for hazardous alcohol use. The findings both confirm established knowledge that social networks and social support exert differential effects on mental health and furthermore suggest that the particular type of social support may be important. In contrast, different types of social network appear to impact upon poor mental health in a more uniform way. Future psychosocial strategies promoting mental health should consider which social groups are vulnerable to reduced social networks and poor social support and which diagnostic groups may benefit most.

The Role of Informal Support Networks in Teaching the Nature of Science

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Herman, Benjamin C.; Olson, Joanne K.; Clough, Michael P.

2017-06-01

This study reports the participation of 13 secondary science teachers in informal support networks and how that participation was associated with their nature of science (NOS) teaching practices 2 to 5 years after having graduated from the same science teacher education program. The nine teachers who participated in informal support networks taught the NOS at high/medium levels, while the four non-participating teachers taught the NOS at low levels. The nine high/medium NOS implementation teachers credited the informal support networks for maintaining/heightening their sense of responsibility for teaching NOS and for helping them navigate institutional constraints that impede effective NOS instruction. Several high/medium NOS instruction implementers initially struggled to autonomously frame and resolve the complexities experienced in schools and thus drew from the support networks to engage in more sophisticated forms of teacher decision-making. In contrast, the NOS pedagogical decisions of the four teachers not participating in support networks were governed primarily by the expectations and constraints experienced in their schools. Implications of this study include the need for reconsidering the structure of teacher mentorship programs to ensure they do not promote archaic science teaching practices that are at odds with reform efforts in science education.

Flexible brain network reconfiguration supporting inhibitory control.

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Spielberg, Jeffrey M; Miller, Gregory A; Heller, Wendy; Banich, Marie T

2015-08-11

The ability to inhibit distracting stimuli from interfering with goal-directed behavior is crucial for success in most spheres of life. Despite an abundance of studies examining regional brain activation, knowledge of the brain networks involved in inhibitory control remains quite limited. To address this critical gap, we applied graph theory tools to functional magnetic resonance imaging data collected while a large sample of adults (n = 101) performed a color-word Stroop task. Higher demand for inhibitory control was associated with restructuring of the global network into a configuration that was more optimized for specialized processing (functional segregation), more efficient at communicating the output of such processing across the network (functional integration), and more resilient to potential interruption (resilience). In addition, there were regional changes with right inferior frontal sulcus and right anterior insula occupying more central positions as network hubs, and dorsal anterior cingulate cortex becoming more tightly coupled with its regional subnetwork. Given the crucial role of inhibitory control in goal-directed behavior, present findings identifying functional network organization supporting inhibitory control have the potential to provide additional insights into how inhibitory control may break down in a wide variety of individuals with neurological or psychiatric difficulties.

Social network, social support, and risk of incident stroke: Atherosclerosis Risk in Communities study.

Science.gov (United States)

Nagayoshi, Mako; Everson-Rose, Susan A; Iso, Hiroyasu; Mosley, Thomas H; Rose, Kathryn M; Lutsey, Pamela L

2014-10-01

Having a small social network and lack of social support have been associated with incident coronary heart disease; however, epidemiological evidence for incident stroke is limited. We assessed the longitudinal association of a small social network and lack of social support with risk of incident stroke and evaluated whether the association was partly mediated by vital exhaustion and inflammation. The Atherosclerosis Risk in Communities study measured social network and social support in 13 686 men and women (mean, 57 years; 56% women; 24% black; 76% white) without a history of stroke. Social network was assessed by the 10-item Lubben Social Network Scale and social support by a 16-item Interpersonal Support Evaluation List-Short Form. During a median follow-up of 18.6 years, 905 incident strokes occurred. Relative to participants with a large social network, those with a small social network had a higher risk of stroke (hazard ratio [95% confidence interval], 1.44 [1.02-2.04]) after adjustment for demographics, socioeconomic variables, marital status, behavioral risk factors, and major stroke risk factors. Vital exhaustion, but not inflammation, partly mediated the association between a small social network and incident stroke. Social support was unrelated to incident stroke. In this sample of US community-dwelling men and women, having a small social network was associated with excess risk of incident stroke. As with other cardiovascular conditions, having a small social network may be associated with a modestly increased risk of incident stroke. © 2014 American Heart Association, Inc.

Social support networks and eating disorders: an integrative review of the literature

Directory of Open Access Journals (Sweden)

Leonidas C

2014-05-01

Full Text Available Carolina Leonidas, Manoel Antônio dos Santos Department of Psychology, Faculty of Philosophy, Sciences and Letters of Ribeirão Preto, University of São Paulo, Brazil Aims: This study aimed to analyze the scientific literature about social networks and social support in eating disorders (ED. Methods: By combining keywords, an integrative review was performed. It included publications from 2006–2013, retrieved from the MEDLINE, LILACS, PsycINFO, and CINAHL databases. The selection of articles was based on preestablished inclusion and exclusion criteria. Results: A total of 24 articles were selected for data extraction. There was a predominance of studies that used nonexperimental and descriptive designs, and which were published in international journals. This review provided evidence of the fact that fully consolidated literature regarding social support and social networks in patients with ED is not available, given the small number of studies dedicated to the subject. We identified evidence that the family social network of patients with ED has been widely explored by the literature, although there is a lack of studies about other networks and sources of social support outside the family. Conclusion: The evidence presented in this study shows the need to include other social networks in health care. This expansion beyond family networks would include significant others – such as friends, colleagues, neighbors, people from religious groups, among others – who could help the individual coping with the disorder. The study also highlights the need for future research on this topic, as well as a need for greater investment in publications on the various dimensions of social support and social networks. Keywords: eating disorders, social networks, social support, family relations, peer relations

Assembly and patterning of the vascular network of the vertebrate hindbrain

OpenAIRE

Fujita, Misato; Cha, Young R.; Pham, Van N.; Sakurai, Atsuko; Roman, Beth L.; Gutkind, J. Silvio; Weinstein, Brant M.

2011-01-01

The cranial vasculature is essential for the survival and development of the central nervous system and is important in stroke and other brain pathologies. Cranial vessels form in a reproducible and evolutionarily conserved manner, but the process by which these vessels assemble and acquire their stereotypic patterning remains unclear. Here, we examine the stepwise assembly and patterning of the vascular network of the zebrafish hindbrain. The major artery supplying the hindbrain, the basilar...

Discovery of spatio-temporal patterns from location-based social networks

Science.gov (United States)

Béjar, J.; Álvarez, S.; García, D.; Gómez, I.; Oliva, L.; Tejeda, A.; Vázquez-Salceda, J.

2016-03-01

Location-based social networks (LBSNs) such as Twitter or Instagram are a good source for user spatio-temporal behaviour. These networks collect data from users in such a way that they can be seen as a set of collective and distributed sensors of a geographical area. A low rate sampling of user's location information can be obtained during large intervals of time that can be used to discover complex patterns, including mobility profiles, points of interest or unusual events. These patterns can be used as the elements of a knowledge base for different applications in different domains such as mobility route planning, touristic recommendation systems or city planning. The aim of this paper is twofold, first to analyse the frequent spatio-temporal patterns that users share when living and visiting a city. This behaviour is studied by means of frequent itemsets algorithms in order to establish some associations among visits that can be interpreted as interesting routes or spatio-temporal connections. Second, to analyse how the spatio-temporal behaviour of a large number of users can be segmented in different profiles. These behavioural profiles are obtained by means of clustering algorithms that show the different patterns of behaviour of visitors and citizens. The data analysed were obtained from the public data feeds of Twitter and Instagram within an area surrounding the cities of Barcelona and Milan for a period of several months. The analysis of these data shows that these kinds of algorithms can be successfully applied to data from any city (or general area) to discover useful patterns that can be interpreted on terms of singular places and areas and their temporal relationships.

Why and how selection patterns in classroom networks differ between students.The potential influence of networks size preferences, level of information, and group membership.

Directory of Open Access Journals (Sweden)

Baerveldt, Chris

2010-12-01

Full Text Available High school students can select class mates for new friendships using a repertoire of patterns. They can actively pursue new friendships, make use of the existing network structure, and/ or use the scarce and often erroneous information about candidates. In this theoretical paper, we argue that such selection patterns should not be studied as the result of general rules, as is usually done in social network studies. Specifically, we state that network size preferences, the level of information about individual attributes of fellow classmates, and group membership are likely to differ among high school students, and that as a result, also their selection patterns are likely to be different. In this paper we sketch the theoretical articulations between these.

Network topology: patterns and mechanisms in plant-herbivore and host-parasitoid food webs.

Science.gov (United States)

Cagnolo, Luciano; Salvo, Adriana; Valladares, Graciela

2011-03-01

1. Biological communities are organized in complex interaction networks such as food webs, which topology appears to be non-random. Gradients, compartments, nested subsets and even combinations of these structures have been shown in bipartite networks. However, in most studies only one pattern is tested against randomness and mechanistic hypotheses are generally lacking. 2. Here we examined the topology of regional, coexisting plant-herbivore and host-parasitoid food webs to discriminate between the mentioned network patterns. We also evaluated the role of species body size, local abundance, regional frequency and phylogeny as determinants of network topology. 3. We found both food webs to be compartmented, with interaction range boundaries imposed by host phylogeny. Species degree within compartments was mostly related to their regional frequency and local abundance. Only one compartment showed an internal nested structure in the distribution of interactions between species, but species position within this compartment was unrelated to species size or abundance. 4. These results suggest that compartmentalization may be more common than previously considered, and that network structure is a result of multiple, hierarchical, non-exclusive processes. © 2010 The Authors. Journal compilation © 2010 British Ecological Society.

Multiple Spatial Coherence Resonances and Spatial Patterns in a Noise-Driven Heterogeneous Neuronal Network

International Nuclear Information System (INIS)

Li Yu-Ye; Ding Xue-Li

2014-01-01

Heterogeneity of the neurons and noise are inevitable in the real neuronal network. In this paper, Gaussian white noise induced spatial patterns including spiral waves and multiple spatial coherence resonances are studied in a network composed of Morris—Lecar neurons with heterogeneity characterized by parameter diversity. The relationship between the resonances and the transitions between ordered spiral waves and disordered spatial patterns are achieved. When parameter diversity is introduced, the maxima of multiple resonances increases first, and then decreases as diversity strength increases, which implies that the coherence degrees induced by noise are enhanced at an intermediate diversity strength. The synchronization degree of spatial patterns including ordered spiral waves and disordered patterns is identified to be a very low level. The results suggest that the nervous system can profit from both heterogeneity and noise, and the multiple spatial coherence resonances are achieved via the emergency of spiral waves instead of synchronization patterns. (interdisciplinary physics and related areas of science and technology)

Multiple Spatial Coherence Resonances and Spatial Patterns in a Noise-Driven Heterogeneous Neuronal Network

Science.gov (United States)

Li, Yu-Ye; Ding, Xue-Li

2014-12-01

Heterogeneity of the neurons and noise are inevitable in the real neuronal network. In this paper, Gaussian white noise induced spatial patterns including spiral waves and multiple spatial coherence resonances are studied in a network composed of Morris—Lecar neurons with heterogeneity characterized by parameter diversity. The relationship between the resonances and the transitions between ordered spiral waves and disordered spatial patterns are achieved. When parameter diversity is introduced, the maxima of multiple resonances increases first, and then decreases as diversity strength increases, which implies that the coherence degrees induced by noise are enhanced at an intermediate diversity strength. The synchronization degree of spatial patterns including ordered spiral waves and disordered patterns is identified to be a very low level. The results suggest that the nervous system can profit from both heterogeneity and noise, and the multiple spatial coherence resonances are achieved via the emergency of spiral waves instead of synchronization patterns.

Social networks of HIV-positive women and their association with social support and depression symptoms.

Science.gov (United States)

Cederbaum, Julie A; Rice, Eric; Craddock, Jaih; Pimentel, Veronica; Beaver, Patty

2017-02-01

Social support is important to the mental health and well-being of HIV-positive women. Limited information exists about the specific structure and composition of HIV-positive women's support networks or associations of these network properties with mental health outcomes. In this pilot study, the authors examine whether support network characteristics were associated with depressive symptoms. Survey and network data were collected from HIV-positive women (N = 46) via a web-based survey and an iPad application in August 2012. Data were analyzed using multivariate linear regression models in SAS. Depressive symptoms were positively associated with a greater number of doctors in a woman's network; having more HIV-positive network members was associated with less symptom reporting. Women who reported more individuals who could care for them had more family support. Those who reported feeling loved were less likely to report disclosure stigma. This work highlighted that detailed social network data can increase our understanding of social support so as to identify interventions to support the mental health of HIV-positive women. Most significant is the ongoing need for support from peers.

Social support networks and eating disorders: an integrative review of the literature.

Science.gov (United States)

Leonidas, Carolina; Dos Santos, Manoel Antônio

2014-01-01

This study aimed to analyze the scientific literature about social networks and social support in eating disorders (ED). By combining keywords, an integrative review was performed. It included publications from 2006-2013, retrieved from the MEDLINE, LILACS, PsycINFO, and CINAHL databases. The selection of articles was based on preestablished inclusion and exclusion criteria. A total of 24 articles were selected for data extraction. There was a predominance of studies that used nonexperimental and descriptive designs, and which were published in international journals. This review provided evidence of the fact that fully consolidated literature regarding social support and social networks in patients with ED is not available, given the small number of studies dedicated to the subject. We identified evidence that the family social network of patients with ED has been widely explored by the literature, although there is a lack of studies about other networks and sources of social support outside the family. The evidence presented in this study shows the need to include other social networks in health care. This expansion beyond family networks would include significant others - such as friends, colleagues, neighbors, people from religious groups, among others - who could help the individual coping with the disorder. The study also highlights the need for future research on this topic, as well as a need for greater investment in publications on the various dimensions of social support and social networks.

Network characteristics, perceived social support, and psychological adjustment in mothers of children with autism spectrum disorder.

Science.gov (United States)

Benson, Paul R

2012-12-01

This study examined the characteristics of the support networks of 106 mothers of children with ASD and their relationship to perceived social support, depressed mood, and subjective well-being. Using structural equation modeling, two competing sets of hypotheses were assessed: (1) that network characteristics would impact psychological adjustment directly, and (2) that network effects on adjustment would be indirect, mediated by perceived social support. Results primarily lent support to the latter hypotheses, with measures of network structure (network size) and function (proportion of network members providing emotional support) predicting increased levels of perceived social support which, in turn, predicted decreased depressed mood and increased well-being. Results also indicated that increased interpersonal strain in the maternal network was directly and indirectly associated with increased maternal depression, while being indirectly linked to reduced well-being. Study limitations and implications are discussed.

Dynamical patterns of calcium signaling in a functional model of neuron-astrocyte networks

DEFF Research Database (Denmark)

Postnov, D.E.; Koreshkov, R.N.; Brazhe, N.A.

2009-01-01

We propose a functional mathematical model for neuron-astrocyte networks. The model incorporates elements of the tripartite synapse and the spatial branching structure of coupled astrocytes. We consider glutamate-induced calcium signaling as a specific mode of excitability and transmission...... in astrocytic-neuronal networks. We reproduce local and global dynamical patterns observed experimentally....

Application of support vector machine based on pattern spectrum entropy in fault diagnostics of rolling element bearings

International Nuclear Information System (INIS)

Hao, Rujiang; Chu, Fulei; Peng, Zhike; Feng, Zhipeng

2011-01-01

This paper presents a novel pattern classification approach for the fault diagnostics of rolling element bearings, which combines the morphological multi-scale analysis and the 'one to others' support vector machine (SVM) classifiers. The morphological pattern spectrum describes the shape characteristics of the inspected signal based on the morphological opening operation with multi-scale structuring elements. The pattern spectrum entropy and the barycenter scale location of the spectrum curve are extracted as the feature vectors presenting different faults of the bearing, which are more effective and representative than the kurtosis and the enveloping demodulation spectrum. The 'one to others' SVM algorithm is adopted to distinguish six kinds of fault signals which were measured in the experimental test rig under eight different working conditions. The recognition results of the SVM are ideal and more precise than those of the artificial neural network even though the training samples are few. The combination of the morphological pattern spectrum parameters and the 'one to others' multi-class SVM algorithm is suitable for the on-line automated fault diagnosis of the rolling element bearings. This application is promising and worth well exploiting

Exploring patterns of alteration in Alzheimer’s disease brain networks: a combined structural and functional connectomics analysis

Directory of Open Access Journals (Sweden)

Fulvia Palesi

2016-09-01

Full Text Available Alzheimer’s disease (AD is a neurodegenerative disorder characterized by a severe derangement of cognitive functions, primarily memory, in elderly subjects. As far as the functional impairment is concerned, growing evidence supports the disconnection syndrome hypothesis. Recent investigations using fMRI have revealed a generalized alteration of resting state networks in patients affected by AD and mild cognitive impairment (MCI. However, it was unclear whether the changes in functional connectivity were accompanied by corresponding structural network changes. In this work, we have developed a novel structural/functional connectomic approach: resting state fMRI was used to identify the functional cortical network nodes and diffusion MRI to reconstruct the fiber tracts to give a weight to internodal subcortical connections. Then, local and global efficiency were determined for different networks, exploring specific alterations of integration and segregation patterns in AD and MCI patients compared to healthy controls (HC. In the default mode network (DMN, that was the most affected, axonal loss and reduced axonal integrity appeared to compromise both local and global efficiency along posterior-anterior connections. In the basal ganglia network (BGN, disruption of white matter integrity implied that main alterations occurred in local microstructure. In the anterior insular network (AIN, neuronal loss probably subtended a compromised communication with the insular cortex. Cognitive performance, evaluated by neuropsychological examinations, revealed a dependency on integration and segregation of brain networks. These findings are indicative of the fact that cognitive deficits in AD could be associated not only with cortical alterations (revealed by fMRI but also with subcortical alterations (revealed by diffusion MRI that extend beyond the areas primarily damaged by neurodegeneration, towards the support of an emerging concept of AD as a

Effects of Social Support Network Size on Mortality Risk: Considerations by Diabetes Status.

Science.gov (United States)

Loprinzi, Paul D; Ford, M Allison

2018-05-01

Previous work demonstrates that social support is inversely associated with mortality risk. Less research, however, has examined the effects of the size of the social support network on mortality risk among those with and without diabetes, which was the purpose of this study. Data from the 1999-2008 National Health and Nutrition Examination Survey were used, with participants followed through 2011. This study included 1,412 older adults (≥60 years of age) with diabetes and 5,872 older adults without diabetes. The size of the social support network was assessed via self-report and reported as the number of participants' close friends. Among those without diabetes, various levels of social support network size were inversely associated with mortality risk. However, among those with diabetes, only those with a high social support network size (i.e., at least six close friends) had a reduced risk of all-cause mortality. That is, compared to those with zero close friends, those with diabetes who had six or more close friends had a 49% reduced risk of all-cause mortality (hazard ratio 0.51, 95% CI 0.27-0.94). To mitigate mortality risk, a greater social support network size may be needed for those with diabetes.

Communication competence, social support, and depression among college students: a model of facebook and face-to-face support network influence.

Science.gov (United States)

Wright, Kevin B; Rosenberg, Jenny; Egbert, Nicole; Ploeger, Nicole A; Bernard, Daniel R; King, Shawn

2013-01-01

This study examined the influence of the social networking site Facebook and face-to-face support networks on depression among (N = 361) college students. The authors used the Relational Health Communication Competence Model as a framework for examining the influence of communication competence on social support network satisfaction and depression. Moreover, they examined the influence of interpersonal and social integrative motives as exogenous variables. On the basis of previous work, the authors propose and test a theoretical model using structural equation modeling. The results indicated empirical support for the model, with interpersonal motives predicting increased face-to-face and computer-mediated competence, increased social support satisfaction with face-to-face and Facebook support, and lower depression scores. The implications of the findings for theory, key limitations, and directions for future research are discussed.

Social networks, social support mechanisms, and quality of life after breast cancer diagnosis.

Science.gov (United States)

Kroenke, Candyce H; Kwan, Marilyn L; Neugut, Alfred I; Ergas, Isaac J; Wright, Jaime D; Caan, Bette J; Hershman, Dawn; Kushi, Lawrence H

2013-06-01

We examined mechanisms through which social relationships influence quality of life (QOL) in breast cancer survivors. This study included 3,139 women from the Pathways Study who were diagnosed with breast cancer from 2006 to 2011 and provided data on social networks (the presence of a spouse or intimate partner, religious/social ties, volunteering, and numbers of close friends and relatives), social support (tangible support, emotional/informational support, affection, positive social interaction), and QOL, measured by the FACT-B, approximately 2 months post diagnosis. We used logistic models to evaluate associations between social network size, social support, and lower versus higher than median QOL scores. We further stratified by stage at diagnosis and treatment. In multivariate-adjusted analyses, women who were characterized as socially isolated had significantly lower FACT-B (OR = 2.18, 95 % CI: 1.72-2.77), physical well-being (WB) (OR = 1.61, 95 % CI: 1.27-2.03), functional WB (OR = 2.08, 95 % CI: 1.65-2.63), social WB (OR = 3.46, 95 % CI: 2.73-4.39), and emotional WB (OR = 1.67, 95 % CI: 1.33-2.11) scores and higher breast cancer symptoms (OR = 1.48, 95 % CI: 1.18-1.87) compared with socially integrated women. Each social network member independently predicted higher QOL. Simultaneous adjustment for social networks and social support partially attenuated associations between social networks and QOL. The strongest mediator and type of social support that was most predictive of QOL outcomes was "positive social interaction." However, each type of support was important depending on outcome, stage, and treatment status. Larger social networks and greater social support were related to higher QOL after a diagnosis of breast cancer. Effective social support interventions need to evolve beyond social-emotional interventions and need to account for disease severity and treatment status.

Patterns of workplace supervisor support desired by abused women.

Science.gov (United States)

Perrin, Nancy A; Yragui, Nanette L; Hanson, Ginger C; Glass, Nancy

2011-07-01

The purpose of this study was to understand differences in patterns of supervisor support desired by female victims of intimate partner violence (IPV) and to examine whether the pattern of support desired at work is reflective of a woman's stage of change in the abusive relationship, IPV-related work interference, and IPV-related job reprimands or job loss. We conducted interviews in Spanish or English with adult women working in low-income jobs who had been physically or sexually abused by an intimate partner/ ex-partner in the past year ( N = 133). Cluster analysis revealed three distinct clusters that form a hierarchy of type of support wanted: those who desired limited support; those who desired confidential, time-off, and emotional support; and those who desired support in wide variety of ways from their supervisor. The clusters appeared to reflect stages of behavior change in an abusive relationship. Specifically, the limited-support cluster may represent an early precontemplation stage, with women reporting the least interference with work. The support-in-every-way cluster may represent later stages of change, in which women are breaking away from the abusive partner and report the greatest interference with work. Women in the confidential-, time-off-, and emotional-support cluster are in a transition stage in which they are considering change and are exploring options in their abusive relationship. Understanding the hierarchy of the type of support desired, and its relationship to stages of change in the abusive relationship and work interference, may provide a strong foundation for developing appropriate and effective workplace interventions to guide supervisors in providing support to women experiencing IPV.

Social support network characteristics of incarcerated women with co-occurring major depressive and substance use disorders.

Science.gov (United States)

Nargiso, Jessica E; Kuo, Caroline C; Zlotnick, Caron; Johnson, Jennifer E

2014-01-01

The nature of social support available to incarcerated women is not well-understood, particularly among women at high risk of negative outcomes, including women dually diagnosed with Major Depressive Disorder and a Substance Use Disorder (MDD-SUD). Descriptive statistics and paired-tests were conducted on 60 incarcerated MDD-SUD women receiving in-prison substance use and depression treatments to characterize the women's social networks, including the strength of support, network characteristics, and types of support provided as well as to determine what aspects of social support may be amenable to change during incarceration and post-release. Study results showed that, on average, women perceived they had moderately supportive individuals in their lives, although more than a quarter of the sample could not identify any regular supporters in their network at baseline. During incarceration, women's social networks significantly increased in general supportiveness, and decreased in network size and percentage of substance users in their networks. Participants maintained positive social support gains post-release in most areas while also significantly increasing the size of their support network post-release. Findings suggest that there are aspects of incarcerated MDD-SUD women's social networks that are amenable to change during incarceration and post-release and provide insight into treatment targets for this vulnerable population.

Social Networks, Psychosocial Adaptation, and Preventive/Developmental Interventions: The Support Development Workshop.

Science.gov (United States)

Todd, David M.

The Support Development Group is an approach which explores and develops a theory for the relationship between network characteristics and notions of psychosocial adaptation. The approach is based on the assumption that teaching people to view their social world in network terms can be helpful to them. The Support Development Workshop is presented…

Software/hardware distributed processing network supporting the Ada environment

Science.gov (United States)

Wood, Richard J.; Pryk, Zen

1993-09-01

A high-performance, fault-tolerant, distributed network has been developed, tested, and demonstrated. The network is based on the MIPS Computer Systems, Inc. R3000 Risc for processing, VHSIC ASICs for high speed, reliable, inter-node communications and compatible commercial memory and I/O boards. The network is an evolution of the Advanced Onboard Signal Processor (AOSP) architecture. It supports Ada application software with an Ada- implemented operating system. A six-node implementation (capable of expansion up to 256 nodes) of the RISC multiprocessor architecture provides 120 MIPS of scalar throughput, 96 Mbytes of RAM and 24 Mbytes of non-volatile memory. The network provides for all ground processing applications, has merit for space-qualified RISC-based network, and interfaces to advanced Computer Aided Software Engineering (CASE) tools for application software development.

International Nuclear Security Education Network (INSEN) and the Nuclear Security Training and Support Centre (NSSC) Network

International Nuclear Information System (INIS)

Nikonov, Dmitriy

2013-01-01

International Nuclear Security Education Network established in 2010: A partnership between the IAEA and universities, research institutions and other stakeholders - •Promotion of nuclear security education; • Development of educational materials; • Professional development for faculty members; • Collaborative research and resource sharing. Currently over 90 members from 38 member states. Mission: to enhance global nuclear security by developing, sharing and promoting excellence in nuclear security education. Nuclear Security Support Centre: Primary objectives are: • Develop human resources through the implementation of a tailored training programme; • Develop a network of experts; • Provide technical support for lifecycle equipment management and scientific support for the detection of and the response to nuclear security events

Community detection in complex networks using proximate support vector clustering

Science.gov (United States)

Wang, Feifan; Zhang, Baihai; Chai, Senchun; Xia, Yuanqing

2018-03-01

Community structure, one of the most attention attracting properties in complex networks, has been a cornerstone in advances of various scientific branches. A number of tools have been involved in recent studies concentrating on the community detection algorithms. In this paper, we propose a support vector clustering method based on a proximity graph, owing to which the introduced algorithm surpasses the traditional support vector approach both in accuracy and complexity. Results of extensive experiments undertaken on computer generated networks and real world data sets illustrate competent performances in comparison with the other counterparts.

Support network for families of children and adolescents with visual impairment: strengths and weaknesses.

Science.gov (United States)

Barbieri, Mayara Caroline; Broekman, Gabriela Van Der Zwaan; Souza, Renata Olzon Dionysio de; Lima, Regina Aparecida Garcia de; Wernet, Monika; Dupas, Giselle

2016-10-01

This study aimed to understand the interactions established between social support networks and families that have children and adolescents with visual impairment, in two different cities in the state of Sao Paulo, Brazil. This was a qualitative, descriptive study with symbolic interactionism as a theoretical framework. A genogram, ecomap and semi-structured interviews with 18 families were used. The method adopted for data analysis was narrative analysis. Two themes were found: potentials derived from the relationship with the support network, and, counterpoints in the support network. The family members accessed other members of their own family, friends, spiritual and cultural activities, health services, government institutions, and philanthropic organizations as support networks. The weakness in health services support is an obstacle to comprehensive healthcare for children and adolescents living in city A. In city B, other possibilities exist because it has a reference service. Despite the weaknesses in the support network in both cities, the family articulates and develops a foundation so that they can provide the best situation possible for their child or adolescent. It is up to health professionals to provide support to families and empower them to care for their members.

Ad hoc Sensor Networks to Support Maritime Interdiction Operations

OpenAIRE

Osmundson, John; Bordetsky, Alex

2014-01-01

Networking sensors, decision centers, and boarding parties supports success in Maritime Interdiction Operations. Led by a team from Naval Post-graduate School (NPS), experiments were conducted in 2012 to test the use of ad-hoc, self-forming communication networks to link sensors, people, and decision centers. The experiments involved international participants and successfully shared valuable biometric and radiological sensor data between boarding parties and decis...

In-House Communication Support System Based on the Information Propagation Model Utilizes Social Network

Science.gov (United States)

Takeuchi, Susumu; Teranishi, Yuuichi; Harumoto, Kaname; Shimojo, Shinji

Almost all companies are now utilizing computer networks to support speedier and more effective in-house information-sharing and communication. However, existing systems are designed to support communications only within the same department. Therefore, in our research, we propose an in-house communication support system which is based on the “Information Propagation Model (IPM).” The IPM is proposed to realize word-of-mouth communication in a social network, and to support information-sharing on the network. By applying the system in a real company, we found that information could be exchanged between different and unrelated departments, and such exchanges of information could help to build new relationships between the users who are apart on the social network.

Spatial Pattern and Regional Relevance Analysis of the Maritime Silk Road Shipping Network

Directory of Open Access Journals (Sweden)

Naixia Mou

2018-03-01

Full Text Available Under the strategy of “One Belt and One Road”, this paper explores the spatial pattern and the status quo of regional trade relevance of the Maritime Silk Road shipping network. Based on complex network theory, a topological structure map of shipping networks for containers, tankers, and bulk carriers was constructed, and the spatial characteristics of shipping networks were analyzed. Using the mode of spatial arrangement and the Herfindahl–Hirschman Index, this paper further analyzes the traffic flow pattern of regional trade of three kinds of goods. It is shown that the shipping network of containers, tankers and bulk carriers are unevenly distributed and have regional agglomeration phenomena. There is a strong correlation between the interior of the region and the adjacent areas, and the port competition is fierce. Among them, the container ships network is the most competitive in the region, while the competitiveness of the tankers network is relatively the lowest. The inter-regional correlation is weak, and a few transit hub ports have obvious competitive advantages. The ports in Northeast Asia and Southeast Asia are the most significant. The research results combined with the Maritime Silk Road policy can provide reference for port construction, route optimization, and coordinated development of regional trade, which will help to save time and cost of marine transportation, reduce energy consumption, and promote the sustainable development of marine environment and regional trade on the Maritime Silk Road.

A support network typology for application in older populations with a preponderance of multigenerational households.

Science.gov (United States)

Burholt, Vanessa; Dobbs, Christine

2014-08-01

This paper considers the support networks of older people in populations with a preponderance of multigenerational households and examines the most vulnerable network types in terms of loneliness and isolation. Current common typologies of support networks may not be sensitive to differences within and between different cultures. This paper uses cross-sectional data drawn from 590 elders (Gujaratis, Punjabis and Sylhetis) living in the United Kingdom and South Asia. Six variables were used in K-means cluster analysis to establish a new network typology. Two logistic regression models using loneliness and isolation as dependent variables assessed the contribution of the new network type to wellbeing. Four support networks were identified: 'Multigenerational Households: Older Integrated Networks', 'Multigenerational Households: Younger Family Networks', 'Family and Friends Integrated Networks' and 'Non-kin Restricted Networks'. Older South Asians with 'Non-kin Restricted Networks' were more likely to be lonely and isolated compared to others. Using network typologies developed with individualistically oriented cultures, distributions are skewed towards more robust network types and could underestimate the support needs of older people from familistic cultures, who may be isolated and lonely and with limited informal sources of help. The new typology identifies different network types within multigenerational households, identifies a greater proportion of older people with vulnerable networks and could positively contribute to service planning.

CIRCUIT-DESIGN SOLUTIONS AND INFORMATION SUPPORT OF CITY ELECTRIC NETWORKS IN THE CONDITIONS OF THE SMART GRID

Directory of Open Access Journals (Sweden)

M. I. Fursanov

2017-01-01

Full Text Available The structure, circuit-design solutions and information support of the city electric networks in the conditions of the SMART GRID have been analyzed. It is demonstrated that the new conditions of functioning of electric power engineering, increasing demands for its technological state and reliability in most countries determined the transition to a restructuring of electrical networks to be based on the SMART GRID (intelligent power networks innovative new structure. The definitions of the SMART GRID, its various attributes and characteristics in most developed countries including Belarus are presented. It is revealed that the existing and future circuit and constructive solutions that can automate the process of managing modes of urban electric networks under the SMART GRID conditions are manifold. At present, the most common in distribution networks are the sources of distributed generation (combustion turbines, wind turbines, photovoltaic installations, mini-hydro, etc.. The patterns and problems of information traceability of a traditional urban networks of the unified energy system of Belarus have been analyzed, and it is demonstrated that in the conditions of the SMART GRID most of the problems of the control mode that are characteristic for traditional distribution networks 6–10 kV and 0.38 kV, lose their relevance. Therefore, the present article presents and features the main directions of development of automatic control modes of the SMART GRID.

Organization of anti-phase synchronization pattern in neural networks: what are the key factors?

Directory of Open Access Journals (Sweden)

Dong eLi

2011-12-01

Full Text Available Anti-phase oscillation has been widely observed in cortical neuralnetwork. Elucidating the mechanism underlying the organization ofanti-phase pattern is of significance for better understanding morecomplicated pattern formations in brain networks. In dynamicalsystems theory, the organization of anti-phase oscillation patternhas usually been considered to relate to time-delay in coupling.This is consistent to conduction delays in real neural networks inthe brain due to finite propagation velocity of action potentials.However, other structural factors in cortical neural network, suchas modular organization (connection density and the coupling types(excitatory or inhibitory, could also play an important role. Inthis work, we investigate the anti-phase oscillation patternorganized on a two-module network of either neuronal cell model orneural mass model, and analyze the impact of the conduction delaytimes, the connection densities, and coupling types. Our resultsshow that delay times and coupling types can play key roles in thisorganization. The connection densities may have an influence on thestability if an anti-phase pattern exists due to the other factors.Furthermore, we show that anti-phase synchronization of slowoscillations can be achieved with small delay times if there isinteraction between slow and fast oscillations. These results aresignificant for further understanding more realistic spatiotemporaldynamics of cortico-cortical communications.

Personal support networks, social capital, and risk of relapse among individuals treated for substance use issues.

Science.gov (United States)

Panebianco, Daria; Gallupe, Owen; Carrington, Peter J; Colozzi, Ivo

2016-01-01

The success of treatment for substance use issues varies with personal and social factors, including the composition and structure of the individual's personal support network. This paper describes the personal support networks and social capital of a sample of Italian adults after long-term residential therapeutic treatment for substance use issues, and analyses network correlates of post-treatment substance use (relapse). Using a social network analysis approach, data were obtained from structured interviews (90-120 min long) with 80 former clients of a large non-governmental therapeutic treatment agency in Italy providing voluntary residential treatments and rehabilitation services for substance use issues. Participants had concluded the program at least six months prior. Data were collected on socio-demographic variables, addiction history, current drug use status (drug-free or relapsed), and the composition and structure of personal support networks. Factors related to risk of relapse were assessed using bivariate and multivariate logistic regression models. A main goal of this study was to identify differences between the support network profiles of drug free and relapsed participants. Drug free participants had larger, less dense, more heterogeneous and reciprocal support networks, and more brokerage social capital than relapsed participants. Additionally, a lower risk of relapse was associated with higher socio-economic status, being married/cohabiting, and having network members with higher socio-economic status, who have greater occupational heterogeneity, and reciprocate support. Post-treatment relapse was found to be negatively associated with the socioeconomic status and occupational heterogeneity of ego's support network, reciprocity in the ties between ego and network members, and a support network in which the members are relatively loosely connected with one another (i.e., ego possesses "brokerage social capital"). These findings suggest the

Time Course of Brain Network Reconfiguration Supporting Inhibitory Control.

Science.gov (United States)

Popov, Tzvetan; Westner, Britta U; Silton, Rebecca L; Sass, Sarah M; Spielberg, Jeffrey M; Rockstroh, Brigitte; Heller, Wendy; Miller, Gregory A

2018-05-02

Hemodynamic research has recently clarified key nodes and links in brain networks implementing inhibitory control. Although fMRI methods are optimized for identifying the structure of brain networks, the relatively slow temporal course of fMRI limits the ability to characterize network operation. The latter is crucial for developing a mechanistic understanding of how brain networks shift dynamically to support inhibitory control. To address this critical gap, we applied spectrally resolved Granger causality (GC) and random forest machine learning tools to human EEG data in two large samples of adults (test sample n = 96, replication sample n = 237, total N = 333, both sexes) who performed a color-word Stroop task. Time-frequency analysis confirmed that recruitment of inhibitory control accompanied by slower behavioral responses was related to changes in theta and alpha/beta power. GC analyses revealed directionally asymmetric exchanges within frontal and between frontal and parietal brain areas: top-down influence of superior frontal gyrus (SFG) over both dorsal ACC (dACC) and inferior frontal gyrus (IFG), dACC control over middle frontal gyrus (MFG), and frontal-parietal exchanges (IFG, precuneus, MFG). Predictive analytics confirmed a combination of behavioral and brain-derived variables as the best set of predictors of inhibitory control demands, with SFG theta bearing higher classification importance than dACC theta and posterior beta tracking the onset of behavioral response. The present results provide mechanistic insight into the biological implementation of a psychological phenomenon: inhibitory control is implemented by dynamic routing processes during which the target response is upregulated via theta-mediated effective connectivity within key PFC nodes and via beta-mediated motor preparation. SIGNIFICANCE STATEMENT Hemodynamic neuroimaging research has recently clarified regional structures in brain networks supporting inhibitory control. However, due to

State Support: A Prerequisite for Global Health Network Effectiveness Comment on "Four Challenges that Global Health Networks Face".

Science.gov (United States)

Marten, Robert; Smith, Richard D

2017-07-24

Shiffman recently summarized lessons for network effectiveness from an impressive collection of case-studies. However, in common with most global health governance analysis in recent years, Shiffman underplays the important role of states in these global networks. As the body which decides and signs international agreements, often provides the resourcing, and is responsible for implementing initiatives all contributing to the prioritization of certain issues over others, state recognition and support is a prerequisite to enabling and determining global health networks' success. The role of states deserves greater attention, analysis and consideration. We reflect upon the underappreciated role of the state within the current discourse on global health. We present the tobacco case study to illustrate the decisive role of states in determining progress for global health networks, and highlight how states use a legitimacy loop to gain legitimacy from and provide legitimacy to global health networks. Moving forward in assessing global health networks' effectiveness, further investigating state support as a determinant of success will be critical. Understanding how global health networks and states interact and evolve to shape and support their respective interests should be a focus for future research. © 2018 The Author(s); Published by Kerman University of Medical Sciences. This is an open-access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Discordant patterns of genetic and phenotypic differentiation in five grasshopper species codistributed across a microreserve network.

Science.gov (United States)

Ortego, Joaquín; García-Navas, Vicente; Noguerales, Víctor; Cordero, Pedro J

2015-12-01

Conservation plans can be greatly improved when information on the evolutionary and demographic consequences of habitat fragmentation is available for several codistributed species. Here, we study spatial patterns of phenotypic and genetic variation among five grasshopper species that are codistributed across a network of microreserves but show remarkable differences in dispersal-related morphology (body size and wing length), degree of habitat specialization and extent of fragmentation of their respective habitats in the study region. In particular, we tested the hypothesis that species with preferences for highly fragmented microhabitats show stronger genetic and phenotypic structure than codistributed generalist taxa inhabiting a continuous matrix of suitable habitat. We also hypothesized a higher resemblance of spatial patterns of genetic and phenotypic variability among species that have experienced a higher degree of habitat fragmentation due to their more similar responses to the parallel large-scale destruction of their natural habitats. In partial agreement with our first hypothesis, we found that genetic structure, but not phenotypic differentiation, was higher in species linked to highly fragmented habitats. We did not find support for congruent patterns of phenotypic and genetic variability among any studied species, indicating that they show idiosyncratic evolutionary trajectories and distinctive demographic responses to habitat fragmentation across a common landscape. This suggests that conservation practices in networks of protected areas require detailed ecological and evolutionary information on target species to focus management efforts on those taxa that are more sensitive to the effects of habitat fragmentation. © 2015 John Wiley & Sons Ltd.

Multi-channels coupling-induced pattern transition in a tri-layer neuronal network

Science.gov (United States)

Wu, Fuqiang; Wang, Ya; Ma, Jun; Jin, Wuyin; Hobiny, Aatef

2018-03-01

Neurons in nerve system show complex electrical behaviors due to complex connection types and diversity in excitability. A tri-layer network is constructed to investigate the signal propagation and pattern formation by selecting different coupling channels between layers. Each layer is set as different states, and the local kinetics is described by Hindmarsh-Rose neuron model. By changing the number of coupling channels between layers and the state of the first layer, the collective behaviors of each layer and synchronization pattern of network are investigated. A statistical factor of synchronization on each layer is calculated. It is found that quiescent state in the second layer can be excited and disordered state in the third layer is suppressed when the first layer is controlled by a pacemaker, and the developed state is dependent on the number of coupling channels. Furthermore, the collapse in the first layer can cause breakdown of other layers in the network, and the mechanism is that disordered state in the third layer is enhanced when sampled signals from the collapsed layer can impose continuous disturbance on the next layer.

Network-level accident-mapping: Distance based pattern matching using artificial neural network.

Science.gov (United States)

Deka, Lipika; Quddus, Mohammed

2014-04-01

The objective of an accident-mapping algorithm is to snap traffic accidents onto the correct road segments. Assigning accidents onto the correct segments facilitate to robustly carry out some key analyses in accident research including the identification of accident hot-spots, network-level risk mapping and segment-level accident risk modelling. Existing risk mapping algorithms have some severe limitations: (i) they are not easily 'transferable' as the algorithms are specific to given accident datasets; (ii) they do not perform well in all road-network environments such as in areas of dense road network; and (iii) the methods used do not perform well in addressing inaccuracies inherent in and type of road environment. The purpose of this paper is to develop a new accident mapping algorithm based on the common variables observed in most accident databases (e.g. road name and type, direction of vehicle movement before the accident and recorded accident location). The challenges here are to: (i) develop a method that takes into account uncertainties inherent to the recorded traffic accident data and the underlying digital road network data, (ii) accurately determine the type and proportion of inaccuracies, and (iii) develop a robust algorithm that can be adapted for any accident set and road network of varying complexity. In order to overcome these challenges, a distance based pattern-matching approach is used to identify the correct road segment. This is based on vectors containing feature values that are common in the accident data and the network data. Since each feature does not contribute equally towards the identification of the correct road segments, an ANN approach using the single-layer perceptron is used to assist in "learning" the relative importance of each feature in the distance calculation and hence the correct link identification. The performance of the developed algorithm was evaluated based on a reference accident dataset from the UK confirming that

Fracture network modeling and GoldSim simulation support

International Nuclear Information System (INIS)

Sugita, Kenichirou; Dershowitz, W.

2005-01-01

During Heisei-16, Golder Associates provided support for JNC Tokai through discrete fracture network data analysis and simulation of the Mizunami Underground Research Laboratory (MIU), participation in Task 6 of the AEspoe Task Force on Modeling of Groundwater Flow and Transport, and development of methodologies for analysis of repository site characterization strategies and safety assessment. MIU support during H-16 involved updating the H-15 FracMan discrete fracture network (DFN) models for the MIU shaft region, and developing improved simulation procedures. Updates to the conceptual model included incorporation of 'Step2' (2004) versions of the deterministic structures, and revision of background fractures to be consistent with conductive structure data from the DH-2 borehole. Golder developed improved simulation procedures for these models through the use of hybrid discrete fracture network (DFN), equivalent porous medium (EPM), and nested DFN/EPM approaches. For each of these models, procedures were documented for the entire modeling process including model implementation, MMP simulation, and shaft grouting simulation. Golder supported JNC participation in Task 6AB, 6D and 6E of the AEspoe Task Force on Modeling of Groundwater Flow and Transport during H-16. For Task 6AB, Golder developed a new technique to evaluate the role of grout in performance assessment time-scale transport. For Task 6D, Golder submitted a report of H-15 simulations to SKB. For Task 6E, Golder carried out safety assessment time-scale simulations at the block scale, using the Laplace Transform Galerkin method. During H-16, Golder supported JNC's Total System Performance Assessment (TSPA) strategy by developing technologies for the analysis of the use site characterization data in safety assessment. This approach will aid in the understanding of the use of site characterization to progressively reduce site characterization uncertainty. (author)

Analytical maximum-likelihood method to detect patterns in real networks

International Nuclear Information System (INIS)

Squartini, Tiziano; Garlaschelli, Diego

2011-01-01

In order to detect patterns in real networks, randomized graph ensembles that preserve only part of the topology of an observed network are systematically used as fundamental null models. However, the generation of them is still problematic. Existing approaches are either computationally demanding and beyond analytic control or analytically accessible but highly approximate. Here, we propose a solution to this long-standing problem by introducing a fast method that allows one to obtain expectation values and standard deviations of any topological property analytically, for any binary, weighted, directed or undirected network. Remarkably, the time required to obtain the expectation value of any property analytically across the entire graph ensemble is as short as that required to compute the same property using the adjacency matrix of the single original network. Our method reveals that the null behavior of various correlation properties is different from what was believed previously, and is highly sensitive to the particular network considered. Moreover, our approach shows that important structural properties (such as the modularity used in community detection problems) are currently based on incorrect expressions, and provides the exact quantities that should replace them.

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

Science.gov (United States)

Galleske, I; Castellanos, J

2002-05-01

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

Interfacing Nuclear Security and Safeguards through Education and Support Centre Networks

International Nuclear Information System (INIS)

Nikonov, D.

2015-01-01

This paper presents the work of the International Nuclear Security Education Network (INSEN) and the International Nuclear Security Training and Support Centre Network (NSSC) as the means to achieve sustainable human resource development in member states. The paper also examines how both security and safeguards can benefit from collaborative and coordinated activities when such networks focus on practical achievements. (author)

A Pattern Construction Scheme for Neural Network-Based Cognitive Communication

Directory of Open Access Journals (Sweden)

Ozgur Orcay

2011-01-01

Full Text Available Inefficient utilization of the frequency spectrum due to conventional regulatory limitations and physical performance limiting factors, mainly the Signal to Noise Ratio (SNR, are prominent restrictions in digital wireless communication. Pattern Based Communication System (PBCS is an adaptive and perceptual communication method based on a Cognitive Radio (CR approach. It intends an SNR oriented cognition mechanism in the physical layer for improvement of Link Spectral Efficiency (LSE. The key to this system is construction of optimal communication signals, which consist of encoded data in different pattern forms (waveforms depending on spectral availabilities. The signals distorted in the communication medium are recovered according to the pre-trained pattern glossary by the perceptual receiver. In this study, we have shown that it is possible to improve the bandwidth efficiency when largely uncorrelated signal patterns are chosen in order to form a glossary that represents symbols for different length data groups and the information can be recovered by the Artificial Neural Network (ANN in the receiver site.

Research on the Spatial-Temporal Distribution Pattern of the Network Attention of Fog and Haze in China

Science.gov (United States)

Weng, Lingyan; Han, Xugao

2018-01-01

Understanding the spatial-temporal distribution pattern of fog and haze is the base to deal with them by adjusting measures to local conditions. Taking 31 provinces in China mainland as the research areas, this paper collected data from Baidu index on the network attention of fog and haze in relevant areas from 2011 to 2016, and conducted an analysis of their spatial-temporal distribution pattern by using autocorrelation analysis. The results show that the network attention of fog and haze has an overall spatial distribution pattern of “higher in the eastern and central, lower in the western China”. There are regional differences in different provinces in terms of network attention. Network attention of fog and haze indicates an obvious geographical agglomeration phenomenon, which is a gradual enlargement of the agglomeration area of higher value with a slight shrinking of those lower value agglomeration areas.

Encoding sensory and motor patterns as time-invariant trajectories in recurrent neural networks.

Science.gov (United States)

Goudar, Vishwa; Buonomano, Dean V

2018-03-14

Much of the information the brain processes and stores is temporal in nature-a spoken word or a handwritten signature, for example, is defined by how it unfolds in time. However, it remains unclear how neural circuits encode complex time-varying patterns. We show that by tuning the weights of a recurrent neural network (RNN), it can recognize and then transcribe spoken digits. The model elucidates how neural dynamics in cortical networks may resolve three fundamental challenges: first, encode multiple time-varying sensory and motor patterns as stable neural trajectories; second, generalize across relevant spatial features; third, identify the same stimuli played at different speeds-we show that this temporal invariance emerges because the recurrent dynamics generate neural trajectories with appropriately modulated angular velocities. Together our results generate testable predictions as to how recurrent networks may use different mechanisms to generalize across the relevant spatial and temporal features of complex time-varying stimuli. © 2018, Goudar et al.

[Characteristics of social supportive network serving the older female sex workers in Qingdao].

Science.gov (United States)

Xu, Y Q; Li, Y F; Jiang, Z X; Zhang, X J; Yuan, X; Zhang, N; Li, X F; Jiang, B F

2016-02-01

To overview the status of social support on older female sex workers (OFSWs) in Qingdao and to better understand the characteristics of this egocentric social support networks. Ucinet 6 software was used to analyze the characteristics of egocentric social networks which involving 400 OFSWs who were recruited by respondent-driven sampling (RDS) method in Qingdao during March 2014 to June. Structural equation model (SEM) was used for data analysis, fitted test and estimation. A total of 400 OFSWs of Qingdao nominated 1 617 social supportive members, and the average size of egocentric social networks of OFSWs was (4.0 ± 1.5). Among all the alter egos (social support network members of the egos), 613 were female sex workers fellows, accounted for the most important part of all the social ties (37.91%). Characteristics of small size and non-relative relationships were seen more obviously among OFSWs with non-local registration and the ratings of emotional support (4.42±2.38) was significantly lower than the tangible support (5.73 ± 1.69) (Psocial support from friends who were also female sex workers. Stronger the joint strength between egos and alters, greater the homogeneity between the two was seen. Tighter relations among the alter egos, higher degree of average social support of the egos were acquired.

Social networks, social support mechanisms, and quality of life after breast cancer diagnosis

Science.gov (United States)

Kroenke, Candyce H; Kwan, Marilyn L.; Neugut, Alfred I.; Ergas, Isaac J.; Wright, Jaime D.; Caan, Bette J.; Hershman, Dawn; Kushi, Lawrence H.

2013-01-01

Purpose We examined mechanisms through which social relationships influence quality of life (QOL) in breast cancer survivors. Methods This study included 3,139 women from the Pathways Study who were diagnosed with breast cancer from 2006-2011 and provided data on social networks (presence of spouse or intimate partner, religious/social ties, volunteering, and numbers of close friends and relatives), social support (tangible, emotional/informational, affection, positive social interaction), and quality of life (QOL), measured by the FACT-B, approximately two months post-diagnosis. We used logistic models to evaluate associations between social network size, social support, and lower vs. higher than median QOL scores. We further stratified by stage at diagnosis and treatment. Results In multivariate-adjusted analyses, women who were characterized as socially isolated had significantly lower FACT-B (OR=2.18, 95%CI:1.72-2.77), physical well-being (WB) (OR=1.61, 95%CI:1.27-2.03), functional WB (OR=2.08, 95%CI:1.65-2.63), social WB (OR=3.46, 95%CI:2.73-4.39), and emotional WB (OR=1.67, 95%CI:1.33-2.11) scores and higher breast cancer symptoms (OR=1.48, 95%CI:1.18-1.87), compared with socially integrated women. Each social network member independently predicted higher QOL. Simultaneous adjustment for social networks and social support partially attenuated associations between social networks and QOL. The strongest mediator and type of social support that was most predictive of QOL outcomes was “positive social interaction”. However, each type of support was important depending on outcome, stage, and treatment status. Conclusions Larger social networks and greater social support were related to higher QOL after a diagnosis of breast cancer. Effective social support interventions need to evolve beyond social-emotional interventions and need to account for disease severity and treatment status. PMID:23657404

Support for Programming Models in Network-on-Chip-based Many-core Systems

DEFF Research Database (Denmark)

Rasmussen, Morten Sleth

This thesis addresses aspects of support for programming models in Network-on- Chip-based many-core architectures. The main focus is to consider architectural support for a plethora of programming models in a single system. The thesis has three main parts. The first part considers parallelization...... models to be supported by a single architecture. The architecture features a specialized network interface processor which allows extensive configurability of the memory system. Based on this architecture, a detailed implementation of the cache coherent shared memory programming model is presented...

Identifying changes in the support networks of end-of-life carers using social network analysis.

Science.gov (United States)

Leonard, Rosemary; Horsfall, Debbie; Noonan, Kerrie

2015-06-01

End-of-life caring is often associated with reduced social networks for both the dying person and for the carer. However, those adopting a community participation and development approach, see the potential for the expansion and strengthening of networks. This paper uses Knox, Savage and Harvey's definitions of three generations social network analysis to analyse the caring networks of people with a terminal illness who are being cared for at home and identifies changes in these caring networks that occurred over the period of caring. Participatory network mapping of initial and current networks was used in nine focus groups. The analysis used key concepts from social network analysis (size, density, transitivity, betweenness and local clustering) together with qualitative analyses of the group's reflections on the maps. The results showed an increase in the size of the networks and that ties between the original members of the network strengthened. The qualitative data revealed the importance between core and peripheral network members and the diverse contributions of the network members. The research supports the value of third generation social network analysis and the potential for end-of-life caring to build social capital. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

Firing patterns transition and desynchronization induced by time delay in neural networks

Science.gov (United States)

Huang, Shoufang; Zhang, Jiqian; Wang, Maosheng; Hu, Chin-Kun

2018-06-01

We used the Hindmarsh-Rose (HR) model (Hindmarsh and Rose, 1984) to study the effect of time delay on the transition of firing behaviors and desynchronization in neural networks. As time delay is increased, neural networks exhibit diversity of firing behaviors, including regular spiking or bursting and firing patterns transitions (FPTs). Meanwhile, the desynchronization of firing and unstable bursting with decreasing amplitude in neural system, are also increasingly enhanced with the increase of time delay. Furthermore, we also studied the effect of coupling strength and network randomness on these phenomena. Our results imply that time delays can induce transition and desynchronization of firing behaviors in neural networks. These findings provide new insight into the role of time delay in the firing activities of neural networks, and can help to better understand the firing phenomena in complex systems of neural networks. A possible mechanism in brain that can cause the increase of time delay is discussed.

A study on the applications of expert systems and neural networks for the development of operator support systems in nuclear power plants

International Nuclear Information System (INIS)

Cheon, Se Woo

1993-02-01

In order to assist operators in effectively maintaining plant safety and to enhance plant availability, the need to develop operator support systems is growing to increase. The application of both expert system and neural network technologies to the operator support has the potential to increase the performance of these systems. A prototype integrated operator support system, called NSSS-DS, has been developed for multiple alarm processing, plant trip diagnosis, and the failure diagnosis of three main systems (a rod control system, reactor coolant pumps (RCPs) and a pressurizer) in the primary side of the Kori-2 nuclear power plant. This system diagnoses system malfunction quickly and offers appropriate guidance to operators. The system uses rule-based deduction with certainty factor operation. Diagnosis is performed using an establish-refine inference strategy. This strategy is to match a set of symptoms with a specific malfunction hypothesis in a predetermined structure of possible hypotheses. The diagnostic symptoms include alarms, indication lamps, parameter values and valve lineup that can be acquired at a main control room. The overall plant-wide diagnosis is performed at the main control part which can process multiple alarms and diagnose possible failure modes and failed systems in the plant. The method of alarm processing is the object-oriented approach in which each alarm can be represented as an active data element, an object. The alarm processing is performed using alarm processing meta rules and alarm processing frames. Also, the diagnosis of a plant trip can be performed at the main control part. The specific diagnosis of the three main systems can be performed followed by the diagnostic results of the main control part. The system also provides follow-up treatments to the operators. The application to these systems is described from the point of view of diagnostic strategies. For the applications of the neural network technology, two feasibility

Pattern detection in stream networks: Quantifying spatialvariability in fish distribution

Science.gov (United States)

Torgersen, Christian E.; Gresswell, Robert E.; Bateman, Douglas S.

2004-01-01

Biological and physical properties of rivers and streams are inherently difficult to sample and visualize at the resolution and extent necessary to detect fine-scale distributional patterns over large areas. Satellite imagery and broad-scale fish survey methods are effective for quantifying spatial variability in biological and physical variables over a range of scales in marine environments but are often too coarse in resolution to address conservation needs in inland fisheries management. We present methods for sampling and analyzing multiscale, spatially continuous patterns of stream fishes and physical habitat in small- to medium-size watersheds (500–1000 hectares). Geospatial tools, including geographic information system (GIS) software such as ArcInfo dynamic segmentation and ArcScene 3D analyst modules, were used to display complex biological and physical datasets. These tools also provided spatial referencing information (e.g. Cartesian and route-measure coordinates) necessary for conducting geostatistical analyses of spatial patterns (empirical semivariograms and wavelet analysis) in linear stream networks. Graphical depiction of fish distribution along a one-dimensional longitudinal profile and throughout the stream network (superimposed on a 10-metre digital elevation model) provided the spatial context necessary for describing and interpreting the relationship between landscape pattern and the distribution of coastal cutthroat trout (Oncorhynchus clarki clarki) in western Oregon, U.S.A. The distribution of coastal cutthroat trout was highly autocorrelated and exhibited a spherical semivariogram with a defined nugget, sill, and range. Wavelet analysis of the main-stem longitudinal profile revealed periodicity in trout distribution at three nested spatial scales corresponding ostensibly to landscape disturbances and the spacing of tributary junctions.

In-vivo determination of chewing patterns using FBG and artificial neural networks

Science.gov (United States)

Pegorini, Vinicius; Zen Karam, Leandro; Rocha Pitta, Christiano S.; Ribeiro, Richardson; Simioni Assmann, Tangriani; Cardozo da Silva, Jean Carlos; Bertotti, Fábio L.; Kalinowski, Hypolito J.; Cardoso, Rafael

2015-09-01

This paper reports the process of pattern classification of the chewing process of ruminants. We propose a simplified signal processing scheme for optical fiber Bragg grating (FBG) sensors based on machine learning techniques. The FBG sensors measure the biomechanical forces during jaw movements and an artificial neural network is responsible for the classification of the associated chewing pattern. In this study, three patterns associated to dietary supplement, hay and ryegrass were considered. Additionally, two other important events for ingestive behavior studies were monitored, rumination and idle period. Experimental results show that the proposed approach for pattern classification has been capable of differentiating the materials involved in the chewing process with a small classification error.

Efficient spiking neural network model of pattern motion selectivity in visual cortex.

Science.gov (United States)

Beyeler, Michael; Richert, Micah; Dutt, Nikil D; Krichmar, Jeffrey L

2014-07-01

Simulating large-scale models of biological motion perception is challenging, due to the required memory to store the network structure and the computational power needed to quickly solve the neuronal dynamics. A low-cost yet high-performance approach to simulating large-scale neural network models in real-time is to leverage the parallel processing capability of graphics processing units (GPUs). Based on this approach, we present a two-stage model of visual area MT that we believe to be the first large-scale spiking network to demonstrate pattern direction selectivity. In this model, component-direction-selective (CDS) cells in MT linearly combine inputs from V1 cells that have spatiotemporal receptive fields according to the motion energy model of Simoncelli and Heeger. Pattern-direction-selective (PDS) cells in MT are constructed by pooling over MT CDS cells with a wide range of preferred directions. Responses of our model neurons are comparable to electrophysiological results for grating and plaid stimuli as well as speed tuning. The behavioral response of the network in a motion discrimination task is in agreement with psychophysical data. Moreover, our implementation outperforms a previous implementation of the motion energy model by orders of magnitude in terms of computational speed and memory usage. The full network, which comprises 153,216 neurons and approximately 40 million synapses, processes 20 frames per second of a 40 × 40 input video in real-time using a single off-the-shelf GPU. To promote the use of this algorithm among neuroscientists and computer vision researchers, the source code for the simulator, the network, and analysis scripts are publicly available.

Requirements for advanced decision support tools in future distribution network planning

NARCIS (Netherlands)

Grond, M.O.W.; Morren, J.; Slootweg, J.G.

2013-01-01

This paper describes the need and requirements for advanced decision support tools in future network planning from a distribution network operator perspective. The existing tools will no longer be satisfactory for future application due to present developments in the electricity sector that increase

Supports for shock, vibration and seismic isolation for tube networks

International Nuclear Information System (INIS)

Prisecaru, Ilie; Serban, Viorel; Sandrea Madalina

2005-01-01

The paper presents a solution for diminishing the shocks, vibrations and seismic movements in pipe networks, with a simultaneous reduction in the general stress conditions in piping and supports. Total removal or reduction of vibrations is a hard problem which was not yet tackled either theoretically, in the sense of an analytical procedure for the analysis of occurrence and development of shocks and vibrations in complex systems, or practically, since the current supports and dampers cannot provide enough damping within all the frequency ranges met in the technical domain. Stiffness of classical supports do not allow always satisfactory source isolation to prevent propagation from environment of shocks and vibrations, Considering the actual condition met in the nuclear power plants, power plants and thermal power plants, etc. this paper represents a major practical aid because it provides new solutions for diminishing shocks, vibrations and seismic movements. Aiming at diminishing the effects of vibrations in pipe networks, this paper presents the results obtained in the design, construction and testing of new types of supports that include sandwich type components made up of elastic blade packages with controlled distortion provided by the central and peripheral stiff parts called SERB. With the new type of supports, the control of the distortion at static and dynamic loads and the thermal displacements is achieved by the relative movement among the sandwich structure subassemblies and by the sandwich structure distortion controlled by the central and peripheral distorting parts that generate a non - linear geometric response which has an easily controllable stiffness and damping, due to their non - linear geometric behavior. The supports of the new type are adjustable to the load and distortion level without overstressing the component material, due to a non - linear geometric behavior while the contact pressure among the blades is limited to pre-set values. Due

The effect of road network patterns on pedestrian safety: A zone-based Bayesian spatial modeling approach.

Science.gov (United States)

Guo, Qiang; Xu, Pengpeng; Pei, Xin; Wong, S C; Yao, Danya

2017-02-01

Pedestrian safety is increasingly recognized as a major public health concern. Extensive safety studies have been conducted to examine the influence of multiple variables on the occurrence of pedestrian-vehicle crashes. However, the explicit relationship between pedestrian safety and road network characteristics remains unknown. This study particularly focused on the role of different road network patterns on the occurrence of crashes involving pedestrians. A global integration index via space syntax was introduced to quantify the topological structures of road networks. The Bayesian Poisson-lognormal (PLN) models with conditional autoregressive (CAR) prior were then developed via three different proximity structures: contiguity, geometry-centroid distance, and road network connectivity. The models were also compared with the PLN counterpart without spatial correlation effects. The analysis was based on a comprehensive crash dataset from 131 selected traffic analysis zones in Hong Kong. The results indicated that higher global integration was associated with more pedestrian-vehicle crashes; the irregular pattern network was proved to be safest in terms of pedestrian crash occurrences, whereas the grid pattern was the least safe; the CAR model with a neighborhood structure based on road network connectivity was found to outperform in model goodness-of-fit, implying the importance of accurately accounting for spatial correlation when modeling spatially aggregated crash data. Copyright © 2016 Elsevier Ltd. All rights reserved.

Rotation and scale change invariant point pattern relaxation matching by the Hopfield neural network

Science.gov (United States)

Sang, Nong; Zhang, Tianxu

1997-12-01

Relaxation matching is one of the most relevant methods for image matching. The original relaxation matching technique using point patterns is sensitive to rotations and scale changes. We improve the original point pattern relaxation matching technique to be invariant to rotations and scale changes. A method that makes the Hopfield neural network perform this matching process is discussed. An advantage of this is that the relaxation matching process can be performed in real time with the neural network's massively parallel capability to process information. Experimental results with large simulated images demonstrate the effectiveness and feasibility of the method to perform point patten relaxation matching invariant to rotations and scale changes and the method to perform this matching by the Hopfield neural network. In addition, we show that the method presented can be tolerant to small random error.

Whose Balance Sheet is this? Neural Networks for Banks' Pattern Recognition

NARCIS (Netherlands)

Leon Rincon, Carlos; Moreno, José Fernando; Cely, Jorge

2017-01-01

The balance sheet is a snapshot that portraits the financial position of a firm at a specific point of time. Under the reasonable assumption that the financial position of a firm is unique and representative, we use a basic artificial neural network pattern recognition method on Colombian banks’

Network support for system initiated checkpoints

Science.gov (United States)

Chen, Dong; Heidelberger, Philip

2013-01-29

A system, method and computer program product for supporting system initiated checkpoints in parallel computing systems. The system and method generates selective control signals to perform checkpointing of system related data in presence of messaging activity associated with a user application running at the node. The checkpointing is initiated by the system such that checkpoint data of a plurality of network nodes may be obtained even in the presence of user applications running on highly parallel computers that include ongoing user messaging activity.

Wireless networks of opportunity in support of secure field operations

Science.gov (United States)

Stehle, Roy H.; Lewis, Mark

1997-02-01

Under funding from the Defense Advanced Research Projects Agency (DARPA) for joint military and law enforcement technologies, demonstrations of secure information transfer in support of law enforcement and military operations other than war, using wireless and wired technology, were held in September 1996 at several locations in the United States. In this paper, the network architecture, protocols, and equipment supporting the demonstration's scenarios are presented, together with initial results, including lessons learned and desired system enhancements. Wireless networks of opportunity encompassed in-building (wireless-LAN), campus-wide (Metricom Inc.), metropolitan (AMPS cellular, CDPD), and national (one- and two-way satellite) systems. Evolving DARPA-sponsored packet radio technology was incorporated. All data was encrypted, using multilevel information system security initiative (MISSI)FORTEZZA technology, for carriage over unsecured and unclassified commercial networks. The identification and authentication process inherent in the security system permitted logging for database accesses and provided an audit trail useful in evidence gathering. Wireless and wireline communications support, to and between modeled crisis management centers, was demonstrated. Mechanisms for the guarded transport of data through the secret-high military tactical Internet were included, to support joint law enforcement and crisis management missions. A secure World Wide Web (WWW) browser forms the primary, user-friendly interface for information retrieval and submission. The WWW pages were structured to be sensitive to the bandwidth, error rate, and cost of the communications medium in use (e.g., the use of and resolution for graphical data). Both still and motion compressed video were demonstrated, along with secure voice transmission from laptop computers in the field. Issues of network bandwidth, airtime costs, and deployment status are discussed.

Organized network for supporting the amateur-scientist co-operation in Finland

Science.gov (United States)

Mäkelä, V.; Haukka, H.; Oksanen, A.; Hentunen, V.-P.

2014-04-01

PROAM network is a working group of Ursa Astronomical Association [1] for supporting Finnish amateur astronomers participating to co-operation projects between professional and amateur astronomers. The network relays the information on projects, maintains professional contacts and arranges training on technical skills for research work.

State Support: A Prerequisite for Global Health Network Effectiveness; Comment on “Four Challenges that Global Health Networks Face”

Directory of Open Access Journals (Sweden)

Robert Marten

2018-03-01

Full Text Available Shiffman recently summarized lessons for network effectiveness from an impressive collection of case-studies. However, in common with most global health governance analysis in recent years, Shiffman underplays the important role of states in these global networks. As the body which decides and signs international agreements, often provides the resourcing, and is responsible for implementing initiatives all contributing to the prioritization of certain issues over others, state recognition and support is a prerequisite to enabling and determining global health networks’ success. The role of states deserves greater attention, analysis and consideration. We reflect upon the underappreciated role of the state within the current discourse on global health. We present the tobacco case study to illustrate the decisive role of states in determining progress for global health networks, and highlight how states use a legitimacy loop to gain legitimacy from and provide legitimacy to global health networks. Moving forward in assessing global health networks’ effectiveness, further investigating state support as a determinant of success will be critical. Understanding how global health networks and states interact and evolve to shape and support their respective interests should be a focus for future research.

General asymmetric neutral networks and structure design by genetic algorithms: A learning rule for temporal patterns

Energy Technology Data Exchange (ETDEWEB)

Bornholdt, S. [Heidelberg Univ., (Germany). Inst., fuer Theoretische Physik; Graudenz, D. [Lawrence Berkeley Lab., CA (United States)

1993-07-01

A learning algorithm based on genetic algorithms for asymmetric neural networks with an arbitrary structure is presented. It is suited for the learning of temporal patterns and leads to stable neural networks with feedback.

General asymmetric neutral networks and structure design by genetic algorithms: A learning rule for temporal patterns

International Nuclear Information System (INIS)

Bornholdt, S.

1993-07-01

A learning algorithm based on genetic algorithms for asymmetric neural networks with an arbitrary structure is presented. It is suited for the learning of temporal patterns and leads to stable neural networks with feedback

Algorithms for Regular Tree Grammar Network Search and Their Application to Mining Human-viral Infection Patterns.

Science.gov (United States)

Smoly, Ilan; Carmel, Amir; Shemer-Avni, Yonat; Yeger-Lotem, Esti; Ziv-Ukelson, Michal

2016-03-01

Network querying is a powerful approach to mine molecular interaction networks. Most state-of-the-art network querying tools either confine the search to a prespecified topology in the form of some template subnetwork, or do not specify any topological constraints at all. Another approach is grammar-based queries, which are more flexible and expressive as they allow for expressing the topology of the sought pattern according to some grammar-based logic. Previous grammar-based network querying tools were confined to the identification of paths. In this article, we extend the patterns identified by grammar-based query approaches from paths to trees. For this, we adopt a higher order query descriptor in the form of a regular tree grammar (RTG). We introduce a novel problem and propose an algorithm to search a given graph for the k highest scoring subgraphs matching a tree accepted by an RTG. Our algorithm is based on the combination of dynamic programming with color coding, and includes an extension of previous k-best parsing optimization approaches to avoid isomorphic trees in the output. We implement the new algorithm and exemplify its application to mining viral infection patterns within molecular interaction networks. Our code is available online.

Spontaneous Plasticity of Multineuronal Activity Patterns in Activated Hippocampal Networks

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Atsushi Usami

2008-01-01

Full Text Available Using functional multineuron imaging with single-cell resolution, we examined how hippocampal networks by themselves change the spatiotemporal patterns of spontaneous activity during the course of emitting spontaneous activity. When extracellular ionic concentrations were changed to those that mimicked in vivo conditions, spontaneous activity was increased in active cell number and activity frequency. When ionic compositions were restored to the control conditions, the activity level returned to baseline, but the weighted spatial dispersion of active cells, as assessed by entropy-based metrics, did not. Thus, the networks can modify themselves by altering the internal structure of their correlated activity, even though they as a whole maintained the same level of activity in space and time.

Networking support for collaborative virtual reality projects in national, european and international context

OpenAIRE

Hommes, F.; Pless, E.

2004-01-01

The report describes experiences from networking support for two three years virtual reality projects. Networking requirements depending on the virtual reality environment and the planned distributed scenarios are specified and verified in the real network. Networking problems especially due to the collaborative, distributed character of interaction via the Internet are presented.

Improving Pattern Recognition and Neural Network Algorithms with Applications to Solar Panel Energy Optimization

Science.gov (United States)

Zamora Ramos, Ernesto

Artificial Intelligence is a big part of automation and with today's technological advances, artificial intelligence has taken great strides towards positioning itself as the technology of the future to control, enhance and perfect automation. Computer vision includes pattern recognition and classification and machine learning. Computer vision is at the core of decision making and it is a vast and fruitful branch of artificial intelligence. In this work, we expose novel algorithms and techniques built upon existing technologies to improve pattern recognition and neural network training, initially motivated by a multidisciplinary effort to build a robot that helps maintain and optimize solar panel energy production. Our contributions detail an improved non-linear pre-processing technique to enhance poorly illuminated images based on modifications to the standard histogram equalization for an image. While the original motivation was to improve nocturnal navigation, the results have applications in surveillance, search and rescue, medical imaging enhancing, and many others. We created a vision system for precise camera distance positioning motivated to correctly locate the robot for capture of solar panel images for classification. The classification algorithm marks solar panels as clean or dirty for later processing. Our algorithm extends past image classification and, based on historical and experimental data, it identifies the optimal moment in which to perform maintenance on marked solar panels as to minimize the energy and profit loss. In order to improve upon the classification algorithm, we delved into feedforward neural networks because of their recent advancements, proven universal approximation and classification capabilities, and excellent recognition rates. We explore state-of-the-art neural network training techniques offering pointers and insights, culminating on the implementation of a complete library with support for modern deep learning architectures

Fast convergence of spike sequences to periodic patterns in recurrent networks

International Nuclear Information System (INIS)

Jin, Dezhe Z.

2002-01-01

The dynamical attractors are thought to underlie many biological functions of recurrent neural networks. Here we show that stable periodic spike sequences with precise timings are the attractors of the spiking dynamics of recurrent neural networks with global inhibition. Almost all spike sequences converge within a finite number of transient spikes to these attractors. The convergence is fast, especially when the global inhibition is strong. These results support the possibility that precise spatiotemporal sequences of spikes are useful for information encoding and processing in biological neural networks

Pattern recognition and data mining software based on artificial neural networks applied to proton transfer in aqueous environments

International Nuclear Information System (INIS)

Tahat Amani; Marti Jordi; Khwaldeh Ali; Tahat Kaher

2014-01-01

In computational physics proton transfer phenomena could be viewed as pattern classification problems based on a set of input features allowing classification of the proton motion into two categories: transfer ‘occurred’ and transfer ‘not occurred’. The goal of this paper is to evaluate the use of artificial neural networks in the classification of proton transfer events, based on the feed-forward back propagation neural network, used as a classifier to distinguish between the two transfer cases. In this paper, we use a new developed data mining and pattern recognition tool for automating, controlling, and drawing charts of the output data of an Empirical Valence Bond existing code. The study analyzes the need for pattern recognition in aqueous proton transfer processes and how the learning approach in error back propagation (multilayer perceptron algorithms) could be satisfactorily employed in the present case. We present a tool for pattern recognition and validate the code including a real physical case study. The results of applying the artificial neural networks methodology to crowd patterns based upon selected physical properties (e.g., temperature, density) show the abilities of the network to learn proton transfer patterns corresponding to properties of the aqueous environments, which is in turn proved to be fully compatible with previous proton transfer studies. (condensed matter: structural, mechanical, and thermal properties)

A probabilistic approach to quantifying spatial patterns of flow regimes and network-scale connectivity

Science.gov (United States)

Garbin, Silvia; Alessi Celegon, Elisa; Fanton, Pietro; Botter, Gianluca

2017-04-01

The temporal variability of river flow regime is a key feature structuring and controlling fluvial ecological communities and ecosystem processes. In particular, streamflow variability induced by climate/landscape heterogeneities or other anthropogenic factors significantly affects the connectivity between streams with notable implication for river fragmentation. Hydrologic connectivity is a fundamental property that guarantees species persistence and ecosystem integrity in riverine systems. In riverine landscapes, most ecological transitions are flow-dependent and the structure of flow regimes may affect ecological functions of endemic biota (i.e., fish spawning or grazing of invertebrate species). Therefore, minimum flow thresholds must be guaranteed to support specific ecosystem services, like fish migration, aquatic biodiversity and habitat suitability. In this contribution, we present a probabilistic approach aiming at a spatially-explicit, quantitative assessment of hydrologic connectivity at the network-scale as derived from river flow variability. Dynamics of daily streamflows are estimated based on catchment-scale climatic and morphological features, integrating a stochastic, physically based approach that accounts for the stochasticity of rainfall with a water balance model and a geomorphic recession flow model. The non-exceedance probability of ecologically meaningful flow thresholds is used to evaluate the fragmentation of individual stream reaches, and the ensuing network-scale connectivity metrics. A multi-dimensional Poisson Process for the stochastic generation of rainfall is used to evaluate the impact of climate signature on reach-scale and catchment-scale connectivity. The analysis shows that streamflow patterns and network-scale connectivity are influenced by the topology of the river network and the spatial variability of climatic properties (rainfall, evapotranspiration). The framework offers a robust basis for the prediction of the impact of

Ex vivo determination of chewing patterns using FBG and artificial neural networks

Science.gov (United States)

Karam, L. Z.; Pegorini, V.; Pitta, C. S. R.; Assmann, T. S.; Cardoso, R.; Kalinowski, H. J.; Silva, J. C. C.

2014-05-01

This paper reports the experimental procedures performed in a bovine head for the determination of chewing patterns during the mastication process. Mandible movements during the chewing have been simulated either by using two plasticine materials with different textures or without material. Fibre Bragg grating sensors were fixed in the jaw to monitor the biomechanical forces involved in the chewing process. The acquired signals from the sensors fed the input of an artificial neural network aiming at the classification of the measured chewing patterns for each material used in the experiment. The results obtained from the simulation of the chewing process presented different patterns for the different textures of plasticine, resulting on the determination of three chewing patterns with a classification error of 5%.

Reconfiguration of brain network architecture to support executive control in aging.

Science.gov (United States)

Gallen, Courtney L; Turner, Gary R; Adnan, Areeba; D'Esposito, Mark

2016-08-01

Aging is accompanied by declines in executive control abilities and changes in underlying brain network architecture. Here, we examined brain networks in young and older adults during a task-free resting state and an N-back task and investigated age-related changes in the modular network organization of the brain. Compared with young adults, older adults showed larger changes in network organization between resting state and task. Although young adults exhibited increased connectivity between lateral frontal regions and other network modules during the most difficult task condition, older adults also exhibited this pattern of increased connectivity during less-demanding task conditions. Moreover, the increase in between-module connectivity in older adults was related to faster task performance and greater fractional anisotropy of the superior longitudinal fasciculus. These results demonstrate that older adults who exhibit more pronounced network changes between a resting state and task have better executive control performance and greater structural connectivity of a core frontal-posterior white matter pathway. Copyright © 2016 Elsevier Inc. All rights reserved.

Patient referral patterns and the spread of hospital-acquired infections through national health care networks.

Directory of Open Access Journals (Sweden)

Tjibbe Donker

2010-03-01

Full Text Available Rates of hospital-acquired infections, such as methicillin-resistant Staphylococcus aureus (MRSA, are increasingly used as quality indicators for hospital hygiene. Alternatively, these rates may vary between hospitals, because hospitals differ in admission and referral of potentially colonized patients. We assessed if different referral patterns between hospitals in health care networks can influence rates of hospital-acquired infections like MRSA. We used the Dutch medical registration of 2004 to measure the connectedness between hospitals. This allowed us to reconstruct the network of hospitals in the Netherlands. We used mathematical models to assess the effect of different patient referral patterns on the potential spread of hospital-acquired infections between hospitals, and between categories of hospitals (University medical centers, top clinical hospitals and general hospitals. University hospitals have a higher number of shared patients than teaching or general hospitals, and are therefore more likely to be among the first to receive colonized patients. Moreover, as the network is directional towards university hospitals, they have a higher prevalence, even when infection control measures are equally effective in all hospitals. Patient referral patterns have a profound effect on the spread of health care-associated infections like hospital-acquired MRSA. The MRSA prevalence therefore differs between hospitals with the position of each hospital within the health care network. Any comparison of MRSA rates between hospitals, as a benchmark for hospital hygiene, should therefore take the position of a hospital within the network into account.

Identification of Abnormal System Noise Temperature Patterns in Deep Space Network Antennas Using Neural Network Trained Fuzzy Logic

Science.gov (United States)

Lu, Thomas; Pham, Timothy; Liao, Jason

2011-01-01

This paper presents the development of a fuzzy logic function trained by an artificial neural network to classify the system noise temperature (SNT) of antennas in the NASA Deep Space Network (DSN). The SNT data were classified into normal, marginal, and abnormal classes. The irregular SNT pattern was further correlated with link margin and weather data. A reasonably good correlation is detected among high SNT, low link margin and the effect of bad weather; however we also saw some unexpected non-correlations which merit further study in the future.

YouTube Social Network as a Business Support

OpenAIRE

Phí, Manh Hoang

2017-01-01

This bachelor thesis is focused on familiarizing the reader with the phenomenon of the YouTube social network and its possibilities for business support. The first chapter of the theoretical part introduces the reader to the basic characteristics of online marketing and its tools. The second chapter is dedicated to the YouTube social network, where the reader first learns about the key moments in YouTube history and current statistical facts. Furthermore the bachelor thesis describes the YouT...

Perception of adult men on their preventive practices and health support networks

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Guilherme Oliveira de Arruda

2015-07-01

Full Text Available Objectives: to know the preventive practices adopted by adult men in daily life and to identify health support networks. Methods: a descriptive qualitative study, made during the months of November and December 2012, at two emergency units, along with 32 men aged between 20 and 59 years. Data were collected through semi-structured interviews and subjected to content analysis with thematic modality. Results: men highlighted different preventive practices such as sanitizing hands, eating properly, having screening tests, avoiding psychoactive substance abuse, using personal protective equipment at work and condoms during sex. Most of the participants had nuclear family and its members were their primary support network regarding the health-disease process. Conclusion: it is for health team members to try to leverage the adoption of preventive practices by adult men from the support networks they consider significant.

Algebraic connectivity of brain networks shows patterns of segregation leading to reduced network robustness in Alzheimer's disease

Science.gov (United States)

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

2015-01-01

Measures of network topology and connectivity aid the understanding of network breakdown as the brain degenerates in Alzheimer's disease (AD). We analyzed 3-Tesla diffusion-weighted images from 202 patients scanned by the Alzheimer's Disease Neuroimaging Initiative – 50 healthy controls, 72 with early- and 38 with late-stage mild cognitive impairment (eMCI/lMCI) and 42 with AD. Using whole-brain tractography, we reconstructed structural connectivity networks representing connections between pairs of cortical regions. We examined, for the first time in this context, the network's Laplacian matrix and its Fiedler value, describing the network's algebraic connectivity, and the Fiedler vector, used to partition a graph. We assessed algebraic connectivity and four additional supporting metrics, revealing a decrease in network robustness and increasing disarray among nodes as dementia progressed. Network components became more disconnected and segregated, and their modularity increased. These measures are sensitive to diagnostic group differences, and may help understand the complex changes in AD. PMID:26640830

The Interaction Network Ontology-supported modeling and mining of complex interactions represented with multiple keywords in biomedical literature.

Science.gov (United States)

Özgür, Arzucan; Hur, Junguk; He, Yongqun

2016-01-01

The Interaction Network Ontology (INO) logically represents biological interactions, pathways, and networks. INO has been demonstrated to be valuable in providing a set of structured ontological terms and associated keywords to support literature mining of gene-gene interactions from biomedical literature. However, previous work using INO focused on single keyword matching, while many interactions are represented with two or more interaction keywords used in combination. This paper reports our extension of INO to include combinatory patterns of two or more literature mining keywords co-existing in one sentence to represent specific INO interaction classes. Such keyword combinations and related INO interaction type information could be automatically obtained via SPARQL queries, formatted in Excel format, and used in an INO-supported SciMiner, an in-house literature mining program. We studied the gene interaction sentences from the commonly used benchmark Learning Logic in Language (LLL) dataset and one internally generated vaccine-related dataset to identify and analyze interaction types containing multiple keywords. Patterns obtained from the dependency parse trees of the sentences were used to identify the interaction keywords that are related to each other and collectively represent an interaction type. The INO ontology currently has 575 terms including 202 terms under the interaction branch. The relations between the INO interaction types and associated keywords are represented using the INO annotation relations: 'has literature mining keywords' and 'has keyword dependency pattern'. The keyword dependency patterns were generated via running the Stanford Parser to obtain dependency relation types. Out of the 107 interactions in the LLL dataset represented with two-keyword interaction types, 86 were identified by using the direct dependency relations. The LLL dataset contained 34 gene regulation interaction types, each of which associated with multiple keywords. A

Patterning of leaf vein networks by convergent auxin transport pathways.

Science.gov (United States)

Sawchuk, Megan G; Edgar, Alexander; Scarpella, Enrico

2013-01-01

The formation of leaf vein patterns has fascinated biologists for centuries. Transport of the plant signal auxin has long been implicated in vein patterning, but molecular details have remained unclear. Varied evidence suggests a central role for the plasma-membrane (PM)-localized PIN-FORMED1 (PIN1) intercellular auxin transporter of Arabidopsis thaliana in auxin-transport-dependent vein patterning. However, in contrast to the severe vein-pattern defects induced by auxin transport inhibitors, pin1 mutant leaves have only mild vein-pattern defects. These defects have been interpreted as evidence of redundancy between PIN1 and the other four PM-localized PIN proteins in vein patterning, redundancy that underlies many developmental processes. By contrast, we show here that vein patterning in the Arabidopsis leaf is controlled by two distinct and convergent auxin-transport pathways: intercellular auxin transport mediated by PM-localized PIN1 and intracellular auxin transport mediated by the evolutionarily older, endoplasmic-reticulum-localized PIN6, PIN8, and PIN5. PIN6 and PIN8 are expressed, as PIN1 and PIN5, at sites of vein formation. pin6 synthetically enhances pin1 vein-pattern defects, and pin8 quantitatively enhances pin1pin6 vein-pattern defects. Function of PIN6 is necessary, redundantly with that of PIN8, and sufficient to control auxin response levels, PIN1 expression, and vein network formation; and the vein pattern defects induced by ectopic PIN6 expression are mimicked by ectopic PIN8 expression. Finally, vein patterning functions of PIN6 and PIN8 are antagonized by PIN5 function. Our data define a new level of control of vein patterning, one with repercussions on other patterning processes in the plant, and suggest a mechanism to select cell files specialized for vascular function that predates evolution of PM-localized PIN proteins.

Patterning of leaf vein networks by convergent auxin transport pathways.

Directory of Open Access Journals (Sweden)

Megan G Sawchuk

Full Text Available The formation of leaf vein patterns has fascinated biologists for centuries. Transport of the plant signal auxin has long been implicated in vein patterning, but molecular details have remained unclear. Varied evidence suggests a central role for the plasma-membrane (PM-localized PIN-FORMED1 (PIN1 intercellular auxin transporter of Arabidopsis thaliana in auxin-transport-dependent vein patterning. However, in contrast to the severe vein-pattern defects induced by auxin transport inhibitors, pin1 mutant leaves have only mild vein-pattern defects. These defects have been interpreted as evidence of redundancy between PIN1 and the other four PM-localized PIN proteins in vein patterning, redundancy that underlies many developmental processes. By contrast, we show here that vein patterning in the Arabidopsis leaf is controlled by two distinct and convergent auxin-transport pathways: intercellular auxin transport mediated by PM-localized PIN1 and intracellular auxin transport mediated by the evolutionarily older, endoplasmic-reticulum-localized PIN6, PIN8, and PIN5. PIN6 and PIN8 are expressed, as PIN1 and PIN5, at sites of vein formation. pin6 synthetically enhances pin1 vein-pattern defects, and pin8 quantitatively enhances pin1pin6 vein-pattern defects. Function of PIN6 is necessary, redundantly with that of PIN8, and sufficient to control auxin response levels, PIN1 expression, and vein network formation; and the vein pattern defects induced by ectopic PIN6 expression are mimicked by ectopic PIN8 expression. Finally, vein patterning functions of PIN6 and PIN8 are antagonized by PIN5 function. Our data define a new level of control of vein patterning, one with repercussions on other patterning processes in the plant, and suggest a mechanism to select cell files specialized for vascular function that predates evolution of PM-localized PIN proteins.

The structural connectivity pattern of the default mode network and its association with memory and anxiety

Directory of Open Access Journals (Sweden)

Yan eTao

2015-11-01

Full Text Available The default mode network (DMN is one of the most widely studied resting state functional networks. The structural basis for the DMN is of particular interest and has been studied by several researchers using diffusion tensor imaging (DTI. Most of these previous studies focused on a few regions or white matter tracts of the DMN so that the global structural connectivity pattern and network properties of the DMN remain unclear. Moreover, evidences indicate that the DMN is involved in both memory and emotion, but how the DMN regulates memory and anxiety from the perspective of the whole DMN structural network remains unknown. We used multimodal neuroimaging methods to investigate the structural connectivity pattern of the DMN and the association of its network properties with memory and anxiety in 205 young healthy subjects. Using a probabilistic fiber tractography technique based on DTI data and graph theory methods, we constructed the global structural connectivity pattern of the DMN and found that memory quotient (MQ score was significantly positively correlated with the global and local efficiency of the DMN whereas anxiety was found to be negatively correlated with the efficiency. The strong structural connectivity between multiple brain regions within DMN may reflect that the DMN has certain structural basis. Meanwhile, we found the network efficiency of the DMN were related to memory and anxiety measures, which indicated that the DMN may play a role in the memory and anxiety.

Emergence of structural patterns out of synchronization in networks with competitive interactions

Science.gov (United States)

Assenza, Salvatore; Gutiérrez, Ricardo; Gómez-Gardeñes, Jesús; Latora, Vito; Boccaletti, Stefano

2011-09-01

Synchronization is a collective phenomenon occurring in systems of interacting units, and is ubiquitous in nature, society and technology. Recent studies have enlightened the important role played by the interaction topology on the emergence of synchronized states. However, most of these studies neglect that real world systems change their interaction patterns in time. Here, we analyze synchronization features in networks in which structural and dynamical features co-evolve. The feedback of the node dynamics on the interaction pattern is ruled by the competition of two mechanisms: homophily (reinforcing those interactions with other correlated units in the graph) and homeostasis (preserving the value of the input strength received by each unit). The competition between these two adaptive principles leads to the emergence of key structural properties observed in real world networks, such as modular and scale-free structures, together with a striking enhancement of local synchronization in systems with no global order.

Social networks, sexual networks and HIV risk in men who have sex with men.

Science.gov (United States)

Amirkhanian, Yuri A

2014-03-01

Worldwide, men who have sex with men (MSM) remain one of the most HIV-vulnerable community populations. A global public health priority is developing new methods of reaching MSM, understanding HIV transmission patterns, and intervening to reduce their risk. Increased attention is being given to the role that MSM networks play in HIV epidemiology. This review of MSM network research studies demonstrates that: (1) Members of the same social network often share similar norms, attitudes, and HIV risk behavior levels; (2) Network interventions are feasible and powerful for reducing unprotected sex and potentially for increasing HIV testing uptake; (3) HIV vulnerability among African American MSM increases when an individual enters a high-risk sexual network characterized by high density and racial homogeneity; and (4) Networks are primary sources of social support for MSM, particularly for those living with HIV, with greater support predicting higher care uptake and adherence.

Five-year trajectories of social networks and social support in older adults with major depression.

Science.gov (United States)

Voils, Corrine I; Allaire, Jason C; Olsen, Maren K; Steffens, David C; Hoyle, Rick H; Bosworth, Hayden B

2007-12-01

Research with nondepressed adults suggests that social networks and social support are stable over the life course until very late age. This may not hold true for older adults with depression. We examined baseline status and trajectories of social networks and social support at the group and individual levels over five years. The sample consisted of 339 initially depressed adults aged 59 or older (M = 69 years) enrolled in a naturalistic study of depression. Measures of social ties, including social network size, frequency of interaction, instrumental support, and subjective support, were administered at baseline and yearly for five years. Latent growth curve models were estimated for each aspect of social ties. On average, social network size and frequency of interaction were low at baseline and remained stable over time, whereas subjective and instrumental support were high at baseline yet increased over time. There was significant variation in the direction and rate of change over time, which was not predicted by demographic or clinical factors. Because increasing social networks may be ineffective and may not be possible for a portion of people who already receive maximal support, interventions to increase social support may only work for a portion of older depressed adults.

An novel frequent probability pattern mining algorithm based on circuit simulation method in uncertain biological networks

Science.gov (United States)

2014-01-01

Background Motif mining has always been a hot research topic in bioinformatics. Most of current research on biological networks focuses on exact motif mining. However, due to the inevitable experimental error and noisy data, biological network data represented as the probability model could better reflect the authenticity and biological significance, therefore, it is more biological meaningful to discover probability motif in uncertain biological networks. One of the key steps in probability motif mining is frequent pattern discovery which is usually based on the possible world model having a relatively high computational complexity. Methods In this paper, we present a novel method for detecting frequent probability patterns based on circuit simulation in the uncertain biological networks. First, the partition based efficient search is applied to the non-tree like subgraph mining where the probability of occurrence in random networks is small. Then, an algorithm of probability isomorphic based on circuit simulation is proposed. The probability isomorphic combines the analysis of circuit topology structure with related physical properties of voltage in order to evaluate the probability isomorphism between probability subgraphs. The circuit simulation based probability isomorphic can avoid using traditional possible world model. Finally, based on the algorithm of probability subgraph isomorphism, two-step hierarchical clustering method is used to cluster subgraphs, and discover frequent probability patterns from the clusters. Results The experiment results on data sets of the Protein-Protein Interaction (PPI) networks and the transcriptional regulatory networks of E. coli and S. cerevisiae show that the proposed method can efficiently discover the frequent probability subgraphs. The discovered subgraphs in our study contain all probability motifs reported in the experiments published in other related papers. Conclusions The algorithm of probability graph isomorphism

Support networks and people with physical disabilities: social inclusion and access to health services.

Science.gov (United States)

Holanda, Cristina Marques de Almeida; De Andrade, Fabienne Louise Juvêncio Paes; Bezerra, Maria Aparecida; Nascimento, João Paulo da Silva; Neves, Robson da Fonseca; Alves, Simone Bezerra; Ribeiro, Kátia Suely Queiroz Silva

2015-01-01

This study seeks to identify the formation of social support networks of people with physical disabilities, and how these networks can help facilitate access to health services and promote social inclusion. It is a cross-sectional study, with data collected via a form applied to physically disabled persons over eighteen years of age registered with the Family Health Teams of the municipal district of João Pessoa in the state of Paraíba. It was observed that the support networks of these individuals predominantly consist of family members (parents, siblings, children, spouses) and people outside the family (friends and neighbors). However, 50% of the interviewees declared that they could not count on any support from outside the family. It was observed that the support network contributes to access to the services and participation in social groups. However, reduced social inclusion was detected, due to locomotion difficulties, this being the main barrier to social interaction. Among those individuals who began to interact in society, the part played by social support was fundamental.

Association of Social Support Network Size With Receipt of Cataract Surgery in Older Adults.

Science.gov (United States)

Stagg, Brian C; Choi, HwaJung; Woodward, Maria A; Ehrlich, Joshua R

2018-04-01

Cataract-related vision impairment is an important public health issue that tends to affect older adults. Little is known about the association between older adults' social support networks and their likelihood of receiving cataract surgery. To determine if older adults with smaller social support networks are less likely to receive cataract surgery. Retrospective cohort study. The National Health and Aging Trends Study, a nationally representative US survey, administered annually from 2011 to 2015 to a cohort of Medicare beneficiaries 65 years and older with no cataract surgery prior to the start of the study. Multivariable logistic regression was performed to evaluate if the number of persons in an individual's social support network influenced whether that individual received cataract surgery during a given year of the study. Overall, 3448 participants were interviewed from 2011 to 2015 for a total of 9760 observations. Of these observations, 3084 (weighted, 38.81%; 95% CI, 37.28-40.35) were aged 70 to 74 years, 5211 (weighted, 52.32%; 95% CI, 50.19-54.44) were women; 5899 (weighted, 78.53%; 95% CI, 76.29-80.61) were white, 2249 (weighted, 9.55%; 95% CI, 8.45-10.78) were black, 537 (weighted, 7.18%; 95% CI, 5.88-8.73) were Hispanic, and 303 (weighted, 4.74%; 95% CI, 3.56-62.9) reported other races. Medicare beneficiaries with smaller social support networks (0-2 individuals) were less likely to receive cataract surgery in a given year (adjusted odds ratio, 0.60; 95% CI, 0.37-0.96) than those with larger support networks (≥3 individuals). The adjusted predicted proportion of Medicare beneficiaries undergoing cataract surgery was 4.7% (95% CI, 2.7%-6.7%) and 7.5% (95% CI, 6.9%-8.1%) for those with small and large social support networks, respectively. Having fewer non-spouse/partner family members in the support network was associated with decreased odds of receiving cataract surgery (adjusted odds ratio, 0.60; 95% CI, 0.43-0.85), but having spouses

Decoding of visual activity patterns from fMRI responses using multivariate pattern analyses and convolutional neural network.

Science.gov (United States)

Zafar, Raheel; Kamel, Nidal; Naufal, Mohamad; Malik, Aamir Saeed; Dass, Sarat C; Ahmad, Rana Fayyaz; Abdullah, Jafri M; Reza, Faruque

2017-01-01

Decoding of human brain activity has always been a primary goal in neuroscience especially with functional magnetic resonance imaging (fMRI) data. In recent years, Convolutional neural network (CNN) has become a popular method for the extraction of features due to its higher accuracy, however it needs a lot of computation and training data. In this study, an algorithm is developed using Multivariate pattern analysis (MVPA) and modified CNN to decode the behavior of brain for different images with limited data set. Selection of significant features is an important part of fMRI data analysis, since it reduces the computational burden and improves the prediction performance; significant features are selected using t-test. MVPA uses machine learning algorithms to classify different brain states and helps in prediction during the task. General linear model (GLM) is used to find the unknown parameters of every individual voxel and the classification is done using multi-class support vector machine (SVM). MVPA-CNN based proposed algorithm is compared with region of interest (ROI) based method and MVPA based estimated values. The proposed method showed better overall accuracy (68.6%) compared to ROI (61.88%) and estimation values (64.17%).

A network architecture supporting consistent rich behavior in collaborative interactive applications.

Science.gov (United States)

Marsh, James; Glencross, Mashhuda; Pettifer, Steve; Hubbold, Roger

2006-01-01

Network architectures for collaborative virtual reality have traditionally been dominated by client-server and peer-to-peer approaches, with peer-to-peer strategies typically being favored where minimizing latency is a priority, and client-server where consistency is key. With increasingly sophisticated behavior models and the demand for better support for haptics, we argue that neither approach provides sufficient support for these scenarios and, thus, a hybrid architecture is required. We discuss the relative performance of different distribution strategies in the face of real network conditions and illustrate the problems they face. Finally, we present an architecture that successfully meets many of these challenges and demonstrate its use in a distributed virtual prototyping application which supports simultaneous collaboration for assembly, maintenance, and training applications utilizing haptics.

Evolution-development congruence in pattern formation dynamics: Bifurcations in gene expression and regulation of networks structures.

Science.gov (United States)

Kohsokabe, Takahiro; Kaneko, Kunihiko

2016-01-01

Search for possible relationships between phylogeny and ontogeny is important in evolutionary-developmental biology. Here we uncover such relationships by numerical evolution and unveil their origin in terms of dynamical systems theory. By representing developmental dynamics of spatially located cells with gene expression dynamics with cell-to-cell interaction under external morphogen gradient, gene regulation networks are evolved under mutation and selection with the fitness to approach a prescribed spatial pattern of expressed genes. For most numerical evolution experiments, evolution of pattern over generations and development of pattern by an evolved network exhibit remarkable congruence. Both in the evolution and development pattern changes consist of several epochs where stripes are formed in a short time, while for other temporal regimes, pattern hardly changes. In evolution, these quasi-stationary regimes are generations needed to hit relevant mutations, while in development, they are due to some gene expression that varies slowly and controls the pattern change. The morphogenesis is regulated by combinations of feedback or feedforward regulations, where the upstream feedforward network reads the external morphogen gradient, and generates a pattern used as a boundary condition for the later patterns. The ordering from up to downstream is common in evolution and development, while the successive epochal changes in development and evolution are represented as common bifurcations in dynamical-systems theory, which lead to the evolution-development congruence. Mechanism of exceptional violation of the congruence is also unveiled. Our results provide a new look on developmental stages, punctuated equilibrium, developmental bottlenecks, and evolutionary acquisition of novelty in morphogenesis. © 2015 The Authors. Journal of Experimental Zoology Part B: Molecular and Developmental Evolution Published by Wiley Periodicals, Inc.

A Support Vector Learning-Based Particle Filter Scheme for Target Localization in Communication-Constrained Underwater Acoustic Sensor Networks.

Science.gov (United States)

Li, Xinbin; Zhang, Chenglin; Yan, Lei; Han, Song; Guan, Xinping

2017-12-21

Target localization, which aims to estimate the location of an unknown target, is one of the key issues in applications of underwater acoustic sensor networks (UASNs). However, the constrained property of an underwater environment, such as restricted communication capacity of sensor nodes and sensing noises, makes target localization a challenging problem. This paper relies on fractional sensor nodes to formulate a support vector learning-based particle filter algorithm for the localization problem in communication-constrained underwater acoustic sensor networks. A node-selection strategy is exploited to pick fractional sensor nodes with short-distance pattern to participate in the sensing process at each time frame. Subsequently, we propose a least-square support vector regression (LSSVR)-based observation function, through which an iterative regression strategy is used to deal with the distorted data caused by sensing noises, to improve the observation accuracy. At the same time, we integrate the observation to formulate the likelihood function, which effectively update the weights of particles. Thus, the particle effectiveness is enhanced to avoid "particle degeneracy" problem and improve localization accuracy. In order to validate the performance of the proposed localization algorithm, two different noise scenarios are investigated. The simulation results show that the proposed localization algorithm can efficiently improve the localization accuracy. In addition, the node-selection strategy can effectively select the subset of sensor nodes to improve the communication efficiency of the sensor network.

Mobility support and networking for women in STEM

Science.gov (United States)

Avellis, Giovanna; Didenkulova, Ira

2017-04-01

Mobility support for women in STEM (Science, Technology, Engineering and Mathematics) career is an increasingly important issue in today's world. Cutting edge research tends to be undertaken via international collaboration, often within networks built up by moving to a new country. In addition, many of today's funding opportunities are geared towards international cooperation. There have been quite a few debates and several projects based on extended surveys to understand the role and impact of mobility on a scientific career. Although in general it is true that these issues are sensitive to the country and the scientific field for example, it is believed by the scientific community at least, that there is a connection between mobility and scientific excellence. Rewarding mobility is becoming a concern at the European level because mechanisms to measure in the best and objective way possible scientific excellence are not homogeneous. But still mobility is a key issue to strengthen a researcher's scientific curriculum and be recognised at the international level. Women have been widely recognised as a source of untapped potential. Different steps have been taken so far for a deeper understanding of barriers and different obstacles faced by women in the Science field. Present calls in the Science in Society panel in HORIZON 2020 deal with the horizontal and vertical segregation experienced by women in their careers and best practices to manage these issues. The general aim is to foster women participation in all scientific fields with particular regard to male dominated disciplines as STEM and increase the number and the effective representation of women in decision-making positions, to help also speed up the whole process. Mobility has demonstrated to be partly gender sensitive and this needs to be addressed in some way in order to ensure at least equal opportunities to male and female scientists regarding possibilities and benefits offered by mobility programmes

Patterns of the cosmic microwave background from evolving string networks

International Nuclear Information System (INIS)

Bouchet, F.R.; Bennett, D.P.; Stebbins, A.

1988-01-01

A network of cosmic strings generated in the early Universe may still exist today. As the strings move across the sky, they produce, by gravitational lensing, a characteristic pattern of anisotropies in the temperature of the cosmic microwave background. The observed absence of such anisotropies places constraints on theories in which galaxy formation is seeded by strings, but it is anticipated that the next generation of experiments will detect them. (author)

Imbalanced pattern completion vs. separation in cognitive disease: network simulations of synaptic pathologies predict a personalized therapeutics strategy

Directory of Open Access Journals (Sweden)

Hanson Jesse E

2010-08-01

Full Text Available Abstract Background Diverse Mouse genetic models of neurodevelopmental, neuropsychiatric, and neurodegenerative causes of impaired cognition exhibit at least four convergent points of synaptic malfunction: 1 Strength of long-term potentiation (LTP, 2 Strength of long-term depression (LTD, 3 Relative inhibition levels (Inhibition, and 4 Excitatory connectivity levels (Connectivity. Results To test the hypothesis that pathological increases or decreases in these synaptic properties could underlie imbalances at the level of basic neural network function, we explored each type of malfunction in a simulation of autoassociative memory. These network simulations revealed that one impact of impairments or excesses in each of these synaptic properties is to shift the trade-off between pattern separation and pattern completion performance during memory storage and recall. Each type of synaptic pathology either pushed the network balance towards intolerable error in pattern separation or intolerable error in pattern completion. Imbalances caused by pathological impairments or excesses in LTP, LTD, inhibition, or connectivity, could all be exacerbated, or rescued, by the simultaneous modulation of any of the other three synaptic properties. Conclusions Because appropriate modulation of any of the synaptic properties could help re-balance network function, regardless of the origins of the imbalance, we propose a new strategy of personalized cognitive therapeutics guided by assay of pattern completion vs. pattern separation function. Simulated examples and testable predictions of this theorized approach to cognitive therapeutics are presented.

A model for the electronic support of practice-based research networks.

Science.gov (United States)

Peterson, Kevin A; Delaney, Brendan C; Arvanitis, Theodoros N; Taweel, Adel; Sandberg, Elisabeth A; Speedie, Stuart; Richard Hobbs, F D

2012-01-01

The principal goal of the electronic Primary Care Research Network (ePCRN) is to enable the development of an electronic infrastructure to support clinical research activities in primary care practice-based research networks (PBRNs). We describe the model that the ePCRN developed to enhance the growth and to expand the reach of PBRN research. Use cases and activity diagrams were developed from interviews with key informants from 11 PBRNs from the United States and United Kingdom. Discrete functions were identified and aggregated into logical components. Interaction diagrams were created, and an overall composite diagram was constructed describing the proposed software behavior. Software for each component was written and aggregated, and the resulting prototype application was pilot tested for feasibility. A practical model was then created by separating application activities into distinct software packages based on existing PBRN business rules, hardware requirements, network requirements, and security concerns. We present an information architecture that provides for essential interactions, activities, data flows, and structural elements necessary for providing support for PBRN translational research activities. The model describes research information exchange between investigators and clusters of independent data sites supported by a contracted research director. The model was designed to support recruitment for clinical trials, collection of aggregated anonymous data, and retrieval of identifiable data from previously consented patients across hundreds of practices. The proposed model advances our understanding of the fundamental roles and activities of PBRNs and defines the information exchange commonly used by PBRNs to successfully engage community health care clinicians in translational research activities. By describing the network architecture in a language familiar to that used by software developers, the model provides an important foundation for the

Effects of Game Design Patterns on Basic Life Support Training Content

Science.gov (United States)

Kelle, Sebastian; Klemke, Roland; Specht, Marcus

2013-01-01

Based on a previous analysis of game design patterns and related effects in an educational scenario, the following paper presents an experimental study. In the study a course for Basic Life Support training has been evaluated and two game design patterns have been applied to the course. The hypotheses evaluated in this paper relate to game design…

Social support and social network as intermediary social determinants of dental caries in adolescents.

Science.gov (United States)

Fontanini, Humberto; Marshman, Zoe; Vettore, Mario

2015-04-01

The aim of this study was to investigate the association between intermediary social determinants, namely social support and social network with dental caries in adolescents. An adapted version of the WHO social determinants of health conceptual framework was used to organize structural and intermediary social determinants of dental caries into six blocks including perceived social support and number of social networks. A cross-sectional study was conducted with a representative sample of 542 students between 12 and 14 years of age in public schools located in the city of Dourados, Brazil in 2012. The outcome variables were caries experience (DMFT ≥ 1) and current dental caries (component D of DMFT ≥ 1) recorded by a calibrated dentist. Individual interviews were performed to collect data on perceived social support and numbers of social networks from family and friends and covariates. Multivariate Poisson regressions using hierarchical models were conducted. The prevalence of adolescents with caries experience and current dental caries was 55.2% and 32.1%, respectively. Adolescents with low numbers of social networks and low levels of social support from family (PR 1.47; 95% CI = 1.01-2.14) were more likely to have DMFT ≥ 1. Current dental caries was associated with low numbers of social networks and low levels of social support from family (PR 2.26; 95% CI = 1.15-4.44). Social support and social network were influential psychosocial factors to dental caries in adolescents. This finding requires confirmation in other countries but potentially has implications for programmes to promote oral health. © 2014 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Pattern of Family Support among HIV Patients in a Tertiary Health ...

African Journals Online (AJOL)

Background: The impact of the HIV/AIDS pandemic on the social and economic development of Nigeria has been substantial. Adequate family support remains a critical factor for the achievement of optimal HIVcare. This study investigated the level and pattern of family support received by people living with HIV/AIDS ...

The influence of social networks on self-management support: a metasynthesis.

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Vassilev, Ivaylo; Rogers, Anne; Kennedy, Anne; Koetsenruijter, Jan

2014-07-15

There is increasing recognition that chronic illness management (CIM) is not just an individual but a collective process where social networks can potentially make a considerable contribution to improving health outcomes for people with chronic illness. However, the mechanisms (processes, activities) taking place within social networks are insufficiently understood. The aim of this review was to focus on identifying the mechanisms linking social networks with CIM. Here we consider network mechanisms as located within a broader social context that shapes practices, behaviours, and the multiplicity of functions and roles that network members fulfil. A systematic search of qualitative studies was undertaken on Medline, Embase, and Web for papers published between 1st January 2002 and 1st December 2013. Eligible for inclusion were studies dealing with diabetes, and with conditions or health behaviours relevant for diabetes management; and studies exploring the relationship between social networks, self-management, and deprivation. 25 papers met the inclusion criteria. A qualitative metasynthesis was undertaken and the review followed a line of argument synthesis. The main themes identified were: 1) sharing knowledge and experiences in a personal community; 2) accessing and mediation of resources; 3) self-management support requires awareness of and ability to deal with network relationships. These translated into line of argument synthesis in which three network mechanisms were identified. These were network navigation (identifying and connecting with relevant existing resources in a network), negotiation within networks (re-shaping relationships, roles, expectations, means of engagement and communication between network members), and collective efficacy (developing a shared perception and capacity to successfully perform behaviour through shared effort, beliefs, influence, perseverance, and objectives). These network mechanisms bring to the fore the close

Ecological Networks and Community Attachment and Support Among Recently Resettled Refugees.

Science.gov (United States)

Soller, Brian; Goodkind, Jessica R; Greene, R Neil; Browning, Christopher R; Shantzek, Cece

2018-03-25

Interventions aimed at enhancing mental health are increasingly centered around promoting community attachment and support. However, few have examined and tested the specific ecological factors that give rise to these key community processes. Drawing from insights from the ecological network perspective, we tested whether spatial and social overlap in routine activity settings (e.g., work, school, childcare) with fellow ethnic community members is associated with individuals' attachment to their ethnic communities and access to social resources embedded in their communities. Data on routine activity locations drawn from the Refugee Well-Being Project (based in a city in the Southwestern United States) were used to reconstruct the ecological networks of recently resettled refugee communities, which were two-mode networks that comprise individuals and their routine activity locations. Results indicated that respondents' community attachment and support increased with their ecological network extensity-which taps the extent to which respondents share routine activity locations with other community members. Our study highlights a key ecological process that potentially enhances individuals' ethnic community attachment that extends beyond residential neighborhoods. © Society for Community Research and Action 2018.

Contingent association between the size of the social support network and osteoporosis among Korean elderly women.

Science.gov (United States)

Lee, Seungwon; Seo, Da Hea; Kim, Kyoung Min; Lee, Eun Young; Kim, Hyeon Chang; Kim, Chang Oh; Youm, Yoosik; Rhee, Yumie

2017-01-01

To investigate the association between the number of personal ties (or the size of the social support network) and the incidence of osteoporosis among older women in Korea. Data from the Korean Urban Rural Elderly Study were used. Bone density was measured by dual-energy X-ray absorptiometry at the lumbar spine (L1-L4) and femur neck. T-score, the standardized bone density compared with what is normally expected in a healthy young adult, was measured and the presence of osteoporosis was determined, if the T-score was social support network size was measured by self-responses (number of confidants and spouse). Of the 1,846 participants, 44.9% were diagnosed with osteoporosis. The association between the social support network size and the incidence of osteoporosis was curvilinear in both bivariate and multivariate analyses. Having more people in one's social support network size was associated with lower risk of osteoporosis until it reached around four. Increasing the social support network size beyond four, in contrast, was associated with a higher risk of osteoporosis. This association was contingent on the average intimacy level of the social network. At the highest average intimacy level ("extremely close"), increasing the number of social support network members from one to six was associated with linear decrease in the predicted probability of osteoporosis from 45% to 30%. However, at the lowest average intimacy level ("not very close"), the predicted probability of osteoporosis dramatically increased from 48% to 80% as the size of the social network increased from one to six. Our results show that maintaining a large and intimate social support network is associated with a lower risk of osteoporosis among elderly Korean women, while a large but less-intimate social relationship is associated with a higher risk.

Integrated Multimedia Based Intelligent Group Decision Support System for Electrical Power Network

Directory of Open Access Journals (Sweden)

Ajay Kumar Saxena

2002-05-01

Full Text Available Electrical Power Network in recent time requires an intelligent, virtual environment based decision process for the coordination of all its individual elements and the interrelated tasks. Its ultimate goal is to achieve maximum productivity and efficiency through the efficient and effective application of generation, transmission, distribution, pricing and regulatory systems. However, the complexity of electrical power network and the presence of conflicting multiple goals and objectives postulated by various groups emphasized the need of an intelligent group decision support system approach in this field. In this paper, an Integrated Multimedia based Intelligent Group Decision Support System (IM1GDSS is presented, and its main components are analyzed and discussed. In particular attention is focused on the Data Base, Model Base, Central Black Board (CBB and Multicriteria Futuristic Decision Process (MFDP module. The model base interacts with Electrical Power Network Load Forecasting and Planning (EPNLFP Module; Resource Optimization, Modeling and Simulation (ROMAS Module; Electrical Power Network Control and Evaluation Process (EPNCAEP Module, and MFDP Module through CBB for strategic planning, management control, operational planning and transaction processing. The richness of multimedia channels adds a totally new dimension in a group decision making for Electrical Power Network. The proposed IMIGDSS is a user friendly, highly interactive group decision making system, based on efficient intelligent and multimedia communication support for group discussions, retrieval of content and multi criteria decision analysis.

Flexible establishment of functional brain networks supports attentional modulation of unconscious cognition.

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Ulrich, Martin; Adams, Sarah C; Kiefer, Markus

2014-11-01

In classical theories of attention, unconscious automatic processes are thought to be independent of higher-level attentional influences. Here, we propose that unconscious processing depends on attentional enhancement of task-congruent processing pathways implemented by a dynamic modulation of the functional communication between brain regions. Using functional magnetic resonance imaging, we tested our model with a subliminally primed lexical decision task preceded by an induction task preparing either a semantic or a perceptual task set. Subliminal semantic priming was significantly greater after semantic compared to perceptual induction in ventral occipito-temporal (vOT) and inferior frontal cortex, brain areas known to be involved in semantic processing. The functional connectivity pattern of vOT varied depending on the induction task and successfully predicted the magnitude of behavioral and neural priming. Together, these findings support the proposal that dynamic establishment of functional networks by task sets is an important mechanism in the attentional control of unconscious processing. © 2014 Wiley Periodicals, Inc.

Support to women who denounce experiences of violence based on her social network

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Letícia Becker Vieira

2015-10-01

Full Text Available Objective: to analyze the possibilities of help/support through the mapping and acknowledgement of the social network of women who denounce experiences of violence at a Police Precinct for Women.Method: qualitative study based on the theoretical-methodological framework of Lia Sanicola's Social Network, through interviews with 19 women.Results: the analysis of the network maps evidenced that the primary social network was more present than the secondary on and, despite consisting of significant relations, it demonstrates limitations. The women access the secondary network occasionally in the violence problem and/or its repercussions in their life and health. The discrete presence of the health network in the composition of the social network was revealed and, when mentioned, the relation between the health professional and the woman was characterized as fragile.Conclusion: the importance of the social network relates to the creation of spaces of help/support for the women beyond the moment of the aggression, which accompany them throughout their process of emancipation from an experience annulled by violence, considering that each woman acts and makes decisions in the relational context when she is ready for it.

A decision support system for pre-earthquake planning of lifeline networks

Energy Technology Data Exchange (ETDEWEB)

Liang, J.W. [Tianjin Univ. (China). Dept. of Civil Engineering

1996-12-01

This paper describes the frame of a decision support system for pre-earthquake planning of gas and water networks. The system is mainly based on the earthquake experiences and lessons from the 1976 Tangshan earthquake. The objective of the system is to offer countermeasures and help make decisions for seismic strengthening, remaking, and upgrading of gas and water networks.

Analyzing collaboration networks and developmental patterns of nano-enabled drug delivery (NEDD for brain cancer

Directory of Open Access Journals (Sweden)

Ying Huang

2015-07-01

Full Text Available The rapid development of new and emerging science & technologies (NESTs brings unprecedented challenges, but also opportunities. In this paper, we use bibliometric and social network analyses, at country, institution, and individual levels, to explore the patterns of scientific networking for a key nano area – nano-enabled drug delivery (NEDD. NEDD has successfully been used clinically to modulate drug release and to target particular diseased tissues. The data for this research come from a global compilation of research publication information on NEDD directed at brain cancer. We derive a family of indicators that address multiple facets of research collaboration and knowledge transfer patterns. Results show that: (1 international cooperation is increasing, but networking characteristics change over time; (2 highly productive institutions also lead in influence, as measured by citation to their work, with American institutes leading; (3 research collaboration is dominated by local relationships, with interesting information available from authorship patterns that go well beyond journal impact factors. Results offer useful technical intelligence to help researchers identify potential collaborators and to help inform R&D management and science & innovation policy for such nanotechnologies.

Evolution‐development congruence in pattern formation dynamics: Bifurcations in gene expression and regulation of networks structures

Science.gov (United States)

Kohsokabe, Takahiro

2016-01-01

ABSTRACT Search for possible relationships between phylogeny and ontogeny is important in evolutionary‐developmental biology. Here we uncover such relationships by numerical evolution and unveil their origin in terms of dynamical systems theory. By representing developmental dynamics of spatially located cells with gene expression dynamics with cell‐to‐cell interaction under external morphogen gradient, gene regulation networks are evolved under mutation and selection with the fitness to approach a prescribed spatial pattern of expressed genes. For most numerical evolution experiments, evolution of pattern over generations and development of pattern by an evolved network exhibit remarkable congruence. Both in the evolution and development pattern changes consist of several epochs where stripes are formed in a short time, while for other temporal regimes, pattern hardly changes. In evolution, these quasi‐stationary regimes are generations needed to hit relevant mutations, while in development, they are due to some gene expression that varies slowly and controls the pattern change. The morphogenesis is regulated by combinations of feedback or feedforward regulations, where the upstream feedforward network reads the external morphogen gradient, and generates a pattern used as a boundary condition for the later patterns. The ordering from up to downstream is common in evolution and development, while the successive epochal changes in development and evolution are represented as common bifurcations in dynamical‐systems theory, which lead to the evolution‐development congruence. Mechanism of exceptional violation of the congruence is also unveiled. Our results provide a new look on developmental stages, punctuated equilibrium, developmental bottlenecks, and evolutionary acquisition of novelty in morphogenesis. J. Exp. Zool. (Mol. Dev. Evol.) 326B:61–84, 2016. © 2015 The Authors. Journal of Experimental Zoology Part B: Molecular and Developmental Evolution

Decision Support System for Hepatitis Disease Diagnosis using Bayesian Network

Directory of Open Access Journals (Sweden)

Shamshad Lakho

2017-12-01

Full Text Available Medical judgments are tough and challenging as the decisions are often based on the deficient and ambiguous information. Moreover, the result of decision process has direct effects on human lives. The act of human decision declines in emergency situations due to the complication, time limit, and high risks. Therefore, provision of medical diagnosis plays a dynamic role, specifically in the preliminary stage when a physician has limited diagnosis experience and identifies the directions to be taken for the treatment process. Computerized Decision Support Systems have brought a revolution in the medical diagnosis. These automatic systems support the diagnosticians in the course of diagnosis. The major role of Decision Support Systems is to support the medical personnel in decision-making procedures regarding disease diagnosis and treatment recommendation. The proposed system provides easy support in Hepatitis disease recognition. The system is developed using the Bayesian network model. The physician provides the input to the system in the form of symptoms stated by the patient. These signs and symptoms match with the casual relationships present in the knowledge model. The Bayesian network infers conclusion from the knowledge model and calculates the probability of occurrence of Hepatitis B, C and D disorders.

Identification of Resting State Networks Involved in Executive Function.

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Connolly, Joanna; McNulty, Jonathan P; Boran, Lorraine; Roche, Richard A P; Delany, David; Bokde, Arun L W

2016-06-01

The structural networks in the human brain are consistent across subjects, and this is reflected also in that functional networks across subjects are relatively consistent. These findings are not only present during performance of a goal oriented task but there are also consistent functional networks during resting state. It suggests that goal oriented activation patterns may be a function of component networks identified using resting state. The current study examines the relationship between resting state networks measured and patterns of neural activation elicited during a Stroop task. The association between the Stroop-activated networks and the resting state networks was quantified using spatial linear regression. In addition, we investigated if the degree of spatial association of resting state networks with the Stroop task may predict performance on the Stroop task. The results of this investigation demonstrated that the Stroop activated network can be decomposed into a number of resting state networks, which were primarily associated with attention, executive function, visual perception, and the default mode network. The close spatial correspondence between the functional organization of the resting brain and task-evoked patterns supports the relevance of resting state networks in cognitive function.

Persistence and storage of activity patterns in spiking recurrent cortical networks: modulation of sigmoid signals by after-hyperpolarization currents and acetylcholine.

Science.gov (United States)

Palma, Jesse; Grossberg, Stephen; Versace, Massimiliano

2012-01-01

Many cortical networks contain recurrent architectures that transform input patterns before storing them in short-term memory (STM). Theorems in the 1970's showed how feedback signal functions in rate-based recurrent on-center off-surround networks control this process. A sigmoid signal function induces a quenching threshold below which inputs are suppressed as noise and above which they are contrast-enhanced before pattern storage. This article describes how changes in feedback signaling, neuromodulation, and recurrent connectivity may alter pattern processing in recurrent on-center off-surround networks of spiking neurons. In spiking neurons, fast, medium, and slow after-hyperpolarization (AHP) currents control sigmoid signal threshold and slope. Modulation of AHP currents by acetylcholine (ACh) can change sigmoid shape and, with it, network dynamics. For example, decreasing signal function threshold and increasing slope can lengthen the persistence of a partially contrast-enhanced pattern, increase the number of active cells stored in STM, or, if connectivity is distance-dependent, cause cell activities to cluster. These results clarify how cholinergic modulation by the basal forebrain may alter the vigilance of category learning circuits, and thus their sensitivity to predictive mismatches, thereby controlling whether learned categories code concrete or abstract features, as predicted by Adaptive Resonance Theory. The analysis includes global, distance-dependent, and interneuron-mediated circuits. With an appropriate degree of recurrent excitation and inhibition, spiking networks maintain a partially contrast-enhanced pattern for 800 ms or longer after stimuli offset, then resolve to no stored pattern, or to winner-take-all (WTA) stored patterns with one or multiple winners. Strengthening inhibition prolongs a partially contrast-enhanced pattern by slowing the transition to stability, while strengthening excitation causes more winners when the network

Persistence and storage of activity patterns in spiking recurrent cortical networks:Modulation of sigmoid signals by after-hyperpolarization currents and acetylcholine

Directory of Open Access Journals (Sweden)

Jesse ePalma

2012-06-01

Full Text Available Many cortical networks contain recurrent architectures that transform input patterns before storing them in short-term memory (STM. Theorems in the 1970’s showed how feedback signal functions in rate-based recurrent on-center off-surround networks control this process. A sigmoid signal function induces a quenching threshold below which inputs are suppressed as noise and above which they are contrast-enhanced before pattern storage. This article describes how changes in feedback signaling, neuromodulation, and recurrent connectivity may alter pattern processing in recurrent on-center off-surround networks of spiking neurons. In spiking neurons, fast, medium, and slow after-hyperpolarization (AHP currents control sigmoid signal threshold and slope. Modulation of AHP currents by acetylcholine (ACh can change sigmoid shape and, with it, network dynamics. For example, decreasing signal function threshold and increasing slope can lengthen the persistence of a partially contrast-enhanced pattern, increase the number of active cells stored in STM, or, if connectivity is distance-dependent, cause cell activities to cluster. These results clarify how cholinergic modulation by the basal forebrain may alter the vigilance of category learning circuits, and thus their sensitivity to predictive mismatches, thereby controlling whether learned categories code concrete or abstract features, as predicted by Adaptive Resonance Theory. The analysis includes global, distance-dependent, and interneuron-mediated circuits. With an appropriate degree of recurrent excitation and inhibition, spiking networks maintain a partially contrast-enhanced pattern for 800 milliseconds or longer after stimuli offset, then resolve to no stored pattern, or to winner-take-all stored patterns with one or multiple winners. Strengthening inhibition prolongs a partially contrast-enhanced pattern by slowing the transition to stability, while strengthening excitation causes more winners

Fibrin network pattern changes of platelet-rich fibrin in young versus old age group of individuals: A cell block cytology study

Directory of Open Access Journals (Sweden)

Shravanthi Raghav Yajamanya

2016-01-01

Full Text Available Background: To evaluate variations in fibrin network patterns of the platelet-rich fibrin (PRF in different age groups. Materials and Methods: Ninety-five patients were divided into three age groups: Group 1: (20–39 years; Group 2: (40–59 years; and Group 3: (60 years and above. PRF was prepared from blood samples of all patients and were subjected to cell block cytology method of histological analysis and slides were prepared to histologically assess the age-related changes in (i fibrin network patterns in terms of density and (ii entrapment of platelets and white blood cells (WBCs within fibrin meshwork. Results: Two types of fibrin network pattern arrangements noticed: Dense and loose types in three age groups. However, there was a noticeable decrease in the dense type of fibrin network with progressing age and increase in the loose type of fibrin arrangement. Furthermore, variation in a number of platelets and WBCs entrapped within fibrin network in relation to age was noticed. Conclusion: From the current study it can be concluded that age can be considered as one of the influencing factors on quality of PRF in terms of fibrin network patterns and hence, platelet and WBCs entrapment within these fibrin networks.

Detecting the Community Structure and Activity Patterns of Temporal Networks: A Non-Negative Tensor Factorization Approach

Science.gov (United States)

Gauvin, Laetitia; Panisson, André; Cattuto, Ciro

2014-01-01

The increasing availability of temporal network data is calling for more research on extracting and characterizing mesoscopic structures in temporal networks and on relating such structure to specific functions or properties of the system. An outstanding challenge is the extension of the results achieved for static networks to time-varying networks, where the topological structure of the system and the temporal activity patterns of its components are intertwined. Here we investigate the use of a latent factor decomposition technique, non-negative tensor factorization, to extract the community-activity structure of temporal networks. The method is intrinsically temporal and allows to simultaneously identify communities and to track their activity over time. We represent the time-varying adjacency matrix of a temporal network as a three-way tensor and approximate this tensor as a sum of terms that can be interpreted as communities of nodes with an associated activity time series. We summarize known computational techniques for tensor decomposition and discuss some quality metrics that can be used to tune the complexity of the factorized representation. We subsequently apply tensor factorization to a temporal network for which a ground truth is available for both the community structure and the temporal activity patterns. The data we use describe the social interactions of students in a school, the associations between students and school classes, and the spatio-temporal trajectories of students over time. We show that non-negative tensor factorization is capable of recovering the class structure with high accuracy. In particular, the extracted tensor components can be validated either as known school classes, or in terms of correlated activity patterns, i.e., of spatial and temporal coincidences that are determined by the known school activity schedule. PMID:24497935

Predictors of change in social networks, support and satisfaction following a first episode psychosis: A cohort study.

Science.gov (United States)

Renwick, Laoise; Owens, Liz; Lyne, John; O'Donoghue, Brian; Roche, Eric; Drennan, Jonathan; Sheridan, Ann; Pilling, Mark; O'Callaghan, Eadbhard; Clarke, Mary

2017-11-01

Diminished social networks are common in psychosis but few studies have measured these comprehensively and prospectively to determine how networks and support evolve during the early phase. There is little information regarding perceived support in the early phase of illness. The aim of this study was to describe social support, networks and perceived satisfaction, explore the clinical correlates of these outcomes and examine whether phases of untreated psychosis are linked with social network variables to determine potential opportunities for intervention. During the study period, we assessed 222 people with first-episode psychosis at entry into treatment using valid and reliable measures of diagnosis, positive and negative symptoms, periods of untreated psychosis and prodrome and premorbid adjustment. For follow-up we contacted participants to conduct a second assessment (n=158). There were 97 people who participated which represented 61% of those eligible. Social network and support information obtained at both time points included the number of friends, self-reported satisfaction with support and social network size and clinician's evaluation of the degree of support received through networks. Mixed effects modelling determined the contribution of potential explanatory variables to social support measured. A number of clinical variables were linked with social networks, support and perceived support and satisfaction. The size of networks did not change over time but those with no friends and duration of untreated psychosis was significantly longer for those with no friends at entry into treatment (n=129, Median=24.5mths, IQR=7.25-69.25; Mann-Whitney U=11.78, p=0.008). Social support at baseline and at one year was predicted by homelessness (t=-2.98, p=0.001, CI -4.74 to -1.21), duration of untreated psychosis (t=-0.86, p=0.031, CI -1.65 to -0.08) and premorbid adjustment (t=-2.26, p=0.017, CI -4.11 to -0.42). Social support improved over time but the duration

Beyond ectomycorrhizal bipartite networks: projected networks demonstrate contrasted patterns between early- and late-successional plants in Corsica.

Directory of Open Access Journals (Sweden)

Adrien eTaudiere

2015-10-01

Full Text Available The ectomycorrhizal (ECM symbiosis connects mutualistic plants and fungal species into bipartite networks. While links between one focal ECM plant and its fungal symbionts have been widely documented, systemic views of ECM networks are lacking, in particular, concerning the ability of fungal species to mediate indirect ecological interactions between ECM plant species (projected-ECM networks. We assembled a large dataset of plant-fungi associations at the species level and at the scale of Corsica using molecular data and unambiguously host-assigned records to: (i examine the correlation between the number of fungal symbionts of a plant species and the average specialization of these fungal species, (ii explore the structure of the plant-plant projected network and (iii compare plant association patterns in regard to their position along the ecological succession. Our analysis reveals no trade-off between specialization of plants and specialization of their partners and a saturation of the plant projected network. Moreover, there is a significantly lower-than-expected sharing of partners between early- and late-successional plant species, with fewer fungal partners for early-successional ones and similar average specialization of symbionts of early- and late-successional plants. Our work paves the way for ecological readings of Mediterranean landscapes that include the astonishing diversity of below-ground interactions.

Energy prediction using spatiotemporal pattern networks

Energy Technology Data Exchange (ETDEWEB)

Jiang, Zhanhong; Liu, Chao; Akintayo, Adedotun; Henze, Gregor P.; Sarkar, Soumik

2017-11-01

This paper presents a novel data-driven technique based on the spatiotemporal pattern network (STPN) for energy/power prediction for complex dynamical systems. Built on symbolic dynamical filtering, the STPN framework is used to capture not only the individual system characteristics but also the pair-wise causal dependencies among different sub-systems. To quantify causal dependencies, a mutual information based metric is presented and an energy prediction approach is subsequently proposed based on the STPN framework. To validate the proposed scheme, two case studies are presented, one involving wind turbine power prediction (supply side energy) using the Western Wind Integration data set generated by the National Renewable Energy Laboratory (NREL) for identifying spatiotemporal characteristics, and the other, residential electric energy disaggregation (demand side energy) using the Building America 2010 data set from NREL for exploring temporal features. In the energy disaggregation context, convex programming techniques beyond the STPN framework are developed and applied to achieve improved disaggregation performance.

Social networks, time homeless, and social support: A study of men on Skid Row.

Science.gov (United States)

Green, Harold D; Tucker, Joan S; Golinelli, Daniela; Wenzel, Suzanne L

2013-12-18

Homeless men are frequently unsheltered and isolated, disconnected from supportive organizations and individuals. However, little research has investigated these men's social networks. We investigate the structure and composition of homeless men's social networks, vis-a-vis short- and long-term homelessness with a sample of men drawn randomly from meal lines on Skid Row in Los Angeles. Men continuously homeless for the past six months display networks composed of riskier members when compared to men intermittently homeless during that time. Men who report chronic, long-term homelessness display greater social network fragmentation when compared to non-chronically homeless men. While intermittent homelessness affects network composition in ways that may be addressable with existing interventions, chronic homelessness fragments networks, which may be more difficult to address with those interventions. These findings have implications for access to social support from network members which, in turn, impacts the resources homeless men require from other sources such as the government or NGOs.

Fracture Network Modeling and GoldSim Simulation Support

OpenAIRE

杉田 健一郎; Dershowiz, W.

2003-01-01

During Heisei-14, Golder Associates provided support for JNC Tokai through data analysis and simulation of the MIU Underground Rock Laboratory, participation in Task 6 of the Aspo Task Force on Modelling of Groundwater Flow and Transport, and analysis of repository safety assessment technologies including cell networks for evaluation of the disturbed rock zone (DRZ) and total systems performance assessment (TSPA).

Method of Parallel-Hierarchical Network Self-Training and its Application for Pattern Classification and Recognition

Directory of Open Access Journals (Sweden)

TIMCHENKO, L.

2012-11-01

Full Text Available Propositions necessary for development of parallel-hierarchical (PH network training methods are discussed in this article. Unlike already known structures of the artificial neural network, where non-normalized (absolute similarity criteria are used for comparison, the suggested structure uses a normalized criterion. Based on the analysis of training rules, a conclusion is made that application of two training methods with a teacher is optimal for PH network training: error correction-based training and memory-based training. Mathematical models of training and a combined method of PH network training for recognition of static and dynamic patterns are developed.

Neural Network Based Recognition of Signal Patterns in Application to Automatic Testing of Rails

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Tomasz Ciszewski

2006-01-01

Full Text Available The paper describes the application of neural network for recognition of signal patterns in measuring data gathered by the railroad ultrasound testing car. Digital conversion of the measuring signal allows to store and process large quantities of data. The elaboration of smart, effective and automatic procedures recognizing the obtained patterns on the basisof measured signal amplitude has been presented. The test shows only two classes of pattern recognition. In authors’ opinion if we deliver big enough quantity of training data, presented method is applicable to a system that recognizes many classes.

Explaining the Variable Effects of Social Support on Work-Based Stressor-Strain Relations: The Role of Perceived Pattern of Support Exchange.

Science.gov (United States)

Nahum-Shani, Inbal; Bamberger, Peter A

2011-01-01

Seeking to explain mixed empirical findings regarding the buffering effect of social support on work-based stress-strain relations, we posit that whether an increase in the level of support received buffers or exacerbates the harmful effects of workload on employee health and well-being is contingent upon the general pattern characterizing an employee supportive exchanges across his/her close relationships. Specifically, we propose that the buffering effect of receiving social support depends on whether the employee perceives his/her social exchanges as reciprocal (support given equals support received), under-reciprocating (support given exceeds support received), or over-reciprocating (support received exceeds support given). Based on longitudinal data collected from a random sample of blue-collar workers, our findings support our predictions, indicating that the buffering effect of social support on the relationship between work hours (on the one hand) and employee health and well-being (on the other) varies as a function of the pattern of exchange relations between an employee and his/her close support providers.

Explaining the Variable Effects of Social Support on Work-Based Stressor-Strain Relations: The Role of Perceived Pattern of Support Exchange

Science.gov (United States)

Nahum-Shani, Inbal; Bamberger, Peter A.

2010-01-01

Seeking to explain mixed empirical findings regarding the buffering effect of social support on work-based stress-strain relations, we posit that whether an increase in the level of support received buffers or exacerbates the harmful effects of workload on employee health and well-being is contingent upon the general pattern characterizing an employee supportive exchanges across his/her close relationships. Specifically, we propose that the buffering effect of receiving social support depends on whether the employee perceives his/her social exchanges as reciprocal (support given equals support received), under-reciprocating (support given exceeds support received), or over-reciprocating (support received exceeds support given). Based on longitudinal data collected from a random sample of blue-collar workers, our findings support our predictions, indicating that the buffering effect of social support on the relationship between work hours (on the one hand) and employee health and well-being (on the other) varies as a function of the pattern of exchange relations between an employee and his/her close support providers. PMID:21152110

Network Financial Support and Conflict as Predictors of Depressive Symptoms among a Highly Disadvantaged Population

Science.gov (United States)

Knowlton, Amy R.; Latkin, Carl A.

2007-01-01

The study examined multiple dimensions of social support as predictors of depressive symptoms among a highly vulnerable population. Social network analysis was used to assess perceived and enacted dimensions of support (emotional, financial, instrumental), network conflict, closeness, and composition. Participants were 393 current and former…

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.

Informal support networks of low-income senior women living alone: evidence from Fort St. John, BC.

Science.gov (United States)

Ryser, Laura; Halseth, Greg

2011-01-01

Within the context of an aging Canadian rural and small-town landscape, there is a growing trend of low-income senior women living alone. While there is a perception that rural seniors have well-developed social networks to meet their daily needs, some research suggests that economic and social restructuring processes have impacted the stability of seniors' support networks in small places. While much of the research on seniors' informal networks focuses upon small towns in decline, booming resource economies can also produce challenges for low-income senior women living alone due to both a higher cost of living and the retrenchment of government and service supports. Under such circumstances, an absence of informal supports can impact seniors' health and quality of life and may lead to premature institutionalization. Drawing upon a household survey in Fort St. John, British Columbia, we explore informal supports used by low-income senior women living alone in this different context of the Canadian landscape. Our findings indicate that these women not only have a support network that is comparable to other groups, but that they are also more likely to draw upon such supports to meet their independent-living needs. These women rely heavily on family support, however, and greater efforts are needed to diversify both their formal and informal sources of support as small family networks can quickly become overwhelmed.

Patterns of precipitation and soil moisture extremes in Texas, US: A complex network analysis

Science.gov (United States)

Sun, Alexander Y.; Xia, Youlong; Caldwell, Todd G.; Hao, Zengchao

2018-02-01

Understanding of the spatial and temporal dynamics of extreme precipitation not only improves prediction skills, but also helps to prioritize hazard mitigation efforts. This study seeks to enhance the understanding of spatiotemporal covariation patterns embedded in precipitation (P) and soil moisture (SM) by using an event-based, complex-network-theoretic approach. Events concurrences are quantified using a nonparametric event synchronization measure, and spatial patterns of hydroclimate variables are analyzed by using several network measures and a community detection algorithm. SM-P coupling is examined using a directional event coincidence analysis measure that takes the order of event occurrences into account. The complex network approach is demonstrated for Texas, US, a region possessing a rich set of hydroclimate features and is frequented by catastrophic flooding. Gridded daily observed P data and simulated SM data are used to create complex networks of P and SM extremes. The uncovered high degree centrality regions and community structures are qualitatively in agreement with the overall existing knowledge of hydroclimate extremes in the study region. Our analyses provide new visual insights on the propagation, connectivity, and synchronicity of P extremes, as well as the SM-P coupling, in this flood-prone region, and can be readily used as a basis for event-driven predictive analytics for other regions.

Divergent Drinking Patterns of Restaurant Workers: The Influence of Social Networks and Job Position.

Science.gov (United States)

Duke, Michael R; Ames, Genevieve M; Moore, Roland S; Cunradi, Carol B

2013-01-01

Restaurant workers have higher rates of problem drinking than most occupational groups. However, little is known about the environmental risks and work characteristics that may lead to these behaviors. An exploration of restaurant workers' drinking networks may provide important insights into their alcohol consumption patterns, thus guiding workplace prevention efforts. Drawing from social capital theory, this paper examines the unique characteristics of drinking networks within and between various job categories. Our research suggests that these multiple, complex networks have unique risk characteristics, and that self-selection is based on factors such as job position and college attendance, among other factors.

Social networks, work and network-based resources for the management of long-term conditions: a framework and study protocol for developing self-care support

Directory of Open Access Journals (Sweden)

Kapadia Dharmi

2011-05-01

Full Text Available Abstract Background Increasing the effective targeting and promotion of self-care support for long-term conditions requires more of a focus on patient contexts and networks. The aim of this paper is to describe how within a programme of research and implementation, social networks are viewed as being centrally involved in the mobilisation and deployment of resources in the management of a chronic condition. This forms the basis of a novel approach to understanding, designing, and implementing new forms of self-management support. Methods Drawing on evidence syntheses about social networks and capital and the role of information in self-management, we build on four conceptual approaches to inform the design of our research on the implementation of self-care support for people with long-term conditions. Our approach takes into consideration the form and content of social networks, notions of chronic illness work, normalisation process theory (NPT, and the whole systems informing self-management engagement (WISE approach to self-care support. Discussion The translation and implementation of a self-care agenda in contemporary health and social context needs to acknowledge and incorporate the resources and networks operating in patients' domestic and social environments and everyday lives. The latter compliments the focus on healthcare settings for developing and delivering self-care support by viewing communities and networks, as well as people suffering from long-term conditions, as a key means of support for managing long-term conditions. By focusing on patient work and social-network provision, our aim is to open up a second frontier in implementation research, to translate knowledge into better chronic illness management, and to shift the emphasis towards support that takes place outside formal health services.

Does Artificial Neural Network Support Connectivism's Assumptions?

Science.gov (United States)

AlDahdouh, Alaa A.

2017-01-01

Connectivism was presented as a learning theory for the digital age and connectivists claim that recent developments in Artificial Intelligence (AI) and, more specifically, Artificial Neural Network (ANN) support their assumptions of knowledge connectivity. Yet, very little has been done to investigate this brave allegation. Does the advancement…

Supporting Control Room Operators in Highly Automated Future Power Networks

DEFF Research Database (Denmark)

Chen, Minjiang; Catterson, Victoria; Syed, Mazheruddin

2017-01-01

Operating power systems is an extremely challenging task, not least because power systems have become highly interconnected, as well as the range of network issues that can occur. It is therefore a necessity to develop decision support systems and visualisation that can effectively support the hu...... the human operators for decisionmaking in the complex and dynamic environment of future highly automated power system. This paper aims to investigate the decision support functions associated with frequency deviation events for the proposed Web of Cells concept....

Size of the social network versus quality of social support: which is more protective against PTSD?

Science.gov (United States)

Platt, Jonathan; Keyes, Katherine M; Koenen, Karestan C

2014-08-01

Supportive social networks are important to the post-traumatic response process. However, the effects of social network structure may be distinct from the perceived function of those networks. The present study examined the relative importance of role diversity and perceived strength of social support in mitigating post-traumatic stress disorder (PTSD). Data were drawn from respondents who report lifetime potentially traumatic events in the National Epidemiologic Survey on Alcohol and Related Conditions (N = 31,650). The Social Network Index (SNI) was used to measure the diversity of social connections. The Interpersonal Support Evaluation List (ISEL-12) was used to measure the perceived availability of social support within the network. Odds of current PTSD were compared among individuals representing four dichotomous types of social support: high diversity/high perceived strength, high diversity/low perceived strength, low diversity/high perceived strength, and low diversity/low perceived strength to examine which type of support is more protective against PTSD. Unadjusted odds of PTSD were 1.59 (95 % CI 1.39-1.82) for those with low versus high perceived support strength, and 1.10 (0.94-1.28) among those with non-diverse versus diverse social networks. Compared to the reference group (high diversity/high perceived strength), the adjusted odds of current PTSD were higher for two groups: low diversity/low perceived strength (OR = 1.62; 1.33-1.99), and low diversity/high perceived strength (OR = 1.57; 1.3-1.91). The high diversity/low perceived strength group had no greater odds of PTSD (OR = 1.02; 0.81-1.28). The diversity of a social network is potentially more protective against PTSD than the perception of strong social support. This suggests that programs, which engage individuals in social groups and activities may effectively attenuate the risk of PTSD. A better understanding of how these networks operate with respect to PTSD prevention and mitigation holds

Network and social support in family care of children with diabetes.

Science.gov (United States)

Pennafort, Viviane Peixoto Dos Santos; Queiroz, Maria Veraci Oliveira; Nascimento, Lucila Castanheira; Guedes, Maria Vilani Cavalcante

2016-01-01

to understand the influence of network and social support in the care of a child with type 1 diabetes. qualitative study, with assumptions of ethnonursing, conducted in a reference service specialized in the treatment of diabetes, in 2014, in the city of Fortaleza, state of Ceará, Brazil. Twenty-six members of the family and their respective school children participated in the study. The process of collection and analysis followed the observation-participation-reflection model. the analytical categories showed that the social network in the care of children with diabetes helped sharing of information and experiences, moments of relaxation and aid in the acquisition of supplies for treatment, with positive repercussions in the family context, generating well-being and confidence in the care of children with diabetes. the cultural care provided by nurses strengthens the network and social support because it encourages autonomy in the promotion of the quality of life of children with type 1 diabetes and their families.

Source and Size of Social Support Network on Sedentary Behavior Among Older Adults.

Science.gov (United States)

Loprinzi, Paul D; Crush, Elizabeth A

2018-01-01

To examine the association of source of social support and size of social support network on sedentary behavior among older adults. Cross-sectional. National Health and Nutrition Examination Survey 2003 to 2006. 2519 older adults (60+ years). Sedentary behavior was assessed via accelerometry over a 7-day period. Social support was assessed via self-report. Sources evaluated include spouse, son, daughter, sibling, neighbor, church member, and friend. Regarding size of social network, participants were asked, "In general, how many close friends do you have?" Multivariable linear regression. After adjustment, there was no evidence of an association between the size of social support network and sedentary behavior. With regard to specific sources of social support, spousal social support was associated with less sedentary behavior (β = -11.6; 95% confidence interval: -20.7 to -2.5), with evidence to suggest that this was only true for men. Further, an inverse association was observed between household size and sedentary behavior, with those having a greater number of individuals in the house having lower levels of sedentary behavior. These associations occurred independent of moderate-to-vigorous physical activity, age, gender, race-ethnicity, measured body mass index, total cholesterol, self-reported smoking status, and physician diagnosis of congestive heart failure, coronary artery disease, stroke, cancer, hypertension, or diabetes. Spouse-specific emotion-related social support (particularly for men) and household size were associated with less sedentary behavior.

Social networks and social support for healthy eating among Latina breast cancer survivors: implications for social and behavioral interventions.

Science.gov (United States)

Crookes, Danielle M; Shelton, Rachel C; Tehranifar, Parisa; Aycinena, Corina; Gaffney, Ann Ogden; Koch, Pam; Contento, Isobel R; Greenlee, Heather

2016-04-01

Little is known about Latina breast cancer survivors' social networks or their perceived social support to achieve and maintain a healthy diet. This paper describes the social networks and perceived support for healthy eating in a sample of breast cancer survivors of predominantly Dominican descent living in New York City. Spanish-speaking Latina breast cancer survivors enrolled in a randomized controlled trial of a culturally tailored dietary intervention. Social networks were assessed using Cohen's Social Network Index and a modified General Social Survey Social Networks Module that included assessments of shared health promoting behaviors. Perceived social support from family and friends for healthy, food-related behaviors was assessed. Participants' networks consisted predominantly of family and friends. Family members were more likely than other individuals to be identified as close network members. Participants were more likely to share food-related activities than exercise activities with close network members. Perceived social support for healthy eating was high, although perceived support from spouses and children was higher than support from friends. Despite high levels of perceived support, family was also identified as a barrier to eating healthy foods by nearly half of women. Although friends are part of Latina breast cancer survivors' social networks, spouses and children may provide greater support for healthy eating than friends. Involving family members in dietary interventions for Latina breast cancer survivors may tap into positive sources of support for women, which could facilitate uptake and maintenance of healthy eating behaviors.

Co-authorship patterns and networks of Korean radiation oncologists

International Nuclear Information System (INIS)

Choi, Jin Hyun; Kang, Jin Oh; Park, Seo Hyun; Kim, Sang Ki

2011-01-01

This research aimed to analyze the patterns of co-authorship network among the Korean radiation oncologists and to identify attributing factors for the formation of networks. A total of 1,447 articles including contents of 'Radiation Oncology' and 'Therapeutic Radiology' were searched from the KoreaMed database. The co-authorship was assorted by the author's full name, affiliation and specialties. UCINET 6.0 was used to figure out the author's network centrality and the cluster analysis, and KeyPlayer 1.44 program was used to get a result of key player index. Sociogram was analyzed with the Netdraw 2.090. The statistical comparison was performed by a t-test and ANOVA using SPSS 16.0 with p-value < 0.05 as the significant value. The number of articles written by a radiation oncologist as the fi rst author was 1,025 out of 1,447. The pattern of coauthorship was classified into fi ve groups. For articles of which the fi rst author was a radiation oncologist, the number of single author articles (type-A) was 81; single-institution articles (type-B) was 687; and multiple-author articles (type-C) was 257. For the articles which radiation oncologists participated in as a co-author, the number of single-institution articles (type-D) was 280 while multiple-institution articles (type-E) were 142. There were 8,895 authors from 1,366 co-authored articles, thus the average number of authors per article was 6.51. It was 5.73 for type-B, 6.44 for type-C, 7.90 for type-D, and 7.67 for type-E (p 0.000) in the average number of authors per article. The number of authors for articles from the hospitals published more than 100 articles was 7.23 while form others was 5.94 (p = 0.005). Its number was 5.94 and 7.16 for the articles published before and after 2001 (p = 0.000). The articles written by a radiation oncologist as the fi rst author had 5.92 authors while others for 7.82 (p = 0.025). Its number was 5.57 and 7.71 for the Journal of the Korean Society for Therapeutic Radiology

Online Academic Networks as Knowledge Brokers: The Mediating Role of Organizational Support

Directory of Open Access Journals (Sweden)

Elena-Mădălina Vătămănescu

2018-04-01

Full Text Available Placing online academic networks in the framework of social, cultural and institutional “deterritorialization,” the current paper aims at investigating the functionality of these new forms of transnational and trans-organizational aggregations as knowledge brokers. The emphasis is laid on the influence of human collective intelligence and consistent knowledge flows on research innovation, considering the role of organizational support within higher education systems. In this respect, the research relied on a questionnaire-based survey with 140 academics from European emerging countries, the data collected being processed via a partial least squares structural equation modelling technique. Evidence was brought that, as knowledge brokers, online academic networks are systems aimed to support the access to human collective intelligence and consistent knowledge flows which exert a positive influence on research innovation, both directly and indirectly, by means of formal and informal organizational support. As facilitators of collaborative environments for individuals with specialized knowledge, competence, expertise and experience, online academic networks have set themselves up as an agora for academics worldwide and as an outlet for their acumen and literacy.

Pore network modeling of drainage process in patterned porous media: a quasi-static study

KAUST Repository

Zhang, Tao

2015-04-17

This work represents a preliminary investigation on the role of wettability conditions on the flow of a two-phase system in porous media. Since such effects have been lumped implicitly in relative permeability-saturation and capillary pressure-saturation relationships, it is quite challenging to isolate its effects explicitly in real porous media applications. However, within the framework of pore network models, it is easy to highlight the effects of wettability conditions on the transport of two-phase systems. We employ quasi-static investigation in which the system undergo slow movement based on slight increment of the imposed pressure. Several numerical experiments of the drainage process are conducted to displace a wetting fluid with a non-wetting one. In all these experiments the network is assigned different scenarios of various wettability patterns. The aim is to show that the drainage process is very much affected by the imposed pattern of wettability. The wettability conditions are imposed by assigning the value of contact angle to each pore throat according to predefined patterns.

Abnormal hubs of white matter networks in the frontal-parieto circuit contribute to depression discrimination via pattern classification.

Science.gov (United States)

Qin, Jiaolong; Wei, Maobin; Liu, Haiyan; Chen, Jianhuai; Yan, Rui; Hua, Lingling; Zhao, Ke; Yao, Zhijian; Lu, Qing

2014-12-01

Previous studies had explored the diagnostic and prognostic value of the structural neuroimaging data of MDD and treated the whole brain voxels, the fractional anisotropy and the structural connectivity as classification features. To our best knowledge, no study examined the potential diagnostic value of the hubs of anatomical brain networks in MDD. The purpose of the current study was to provide an exploratory examination of the potential diagnostic and prognostic values of hubs of white matter brain networks in MDD discrimination and the corresponding impaired hub pattern via a multi-pattern analysis. We constructed white matter brain networks from 29 depressions and 30 healthy controls based on diffusion tensor imaging data, calculated nodal measures and identified hubs. Using these measures as features, two types of feature architectures were established, one only included hubs (HUB) and the other contained both hubs and non hubs. The support vector machine classifiers with Gaussian radial basis kernel were used after the feature selection. Moreover, the relative contribution of the features was estimated by means of the consensus features. Our results presented that the hubs (including the bilateral dorsolateral part of superior frontal gyrus, the left middle frontal gyrus, the bilateral middle temporal gyrus, and the bilateral inferior temporal gyrus) played an important role in distinguishing the depressions from healthy controls with the best accuracy of 83.05%. Moreover, most of the HUB consensus features located in the frontal-parieto circuit. These findings provided evidence that the hubs could be served as valuable potential diagnostic measure for MDD, and the hub-concentrated lesion distribution of MDD was primarily anchored within the frontal-parieto circuit. Copyright © 2014 Elsevier Inc. All rights reserved.

Quality of Service in Networks Supporting Cultural Multimedia Applications

Science.gov (United States)

Kanellopoulos, Dimitris N.

2011-01-01

Purpose: This paper aims to provide an overview of representative multimedia applications in the cultural heritage sector, as well as research results on quality of service (QoS) mechanisms in internet protocol (IP) networks that support such applications. Design/methodology/approach: The paper's approach is a literature review. Findings: Cultural…

A Team Formation and Project-based Learning Support Service for Social Learning Networks

NARCIS (Netherlands)

Spoelstra, Howard; Van Rosmalen, Peter; Van de Vrie, Evert; Obreza, Matija; Sloep, Peter

2014-01-01

The Internet affords new approaches to learning. Geographically dispersed self-directed learners can learn in computer-supported communities, forming social learning networks. However, self-directed learners can suffer from a lack of continuous motivation. And surprisingly, social learning networks

The meaning and validation of social support networks for close family of persons with advanced cancer.

Science.gov (United States)

Sjolander, Catarina; Ahlstrom, Gerd

2012-09-17

To strengthen the mental well-being of close family of persons newly diagnosed as having cancer, it is necessary to acquire a greater understanding of their experiences of social support networks, so as to better assess what resources are available to them from such networks and what professional measures are required. The main aim of the present study was to explore the meaning of these networks for close family of adult persons in the early stage of treatment for advanced lung or gastrointestinal cancer. An additional aim was to validate the study's empirical findings by means of the Finfgeld-Connett conceptual model for social support. The intention was to investigate whether these findings were in accordance with previous research in nursing. Seventeen family members with a relative who 8-14 weeks earlier had been diagnosed as having lung or gastrointestinal cancer were interviewed. The data were subjected to qualitative latent content analysis and validated by means of identifying antecedents and critical attributes. The meaning or main attribute of the social support network was expressed by the theme Confirmation through togetherness, based on six subthemes covering emotional and, to a lesser extent, instrumental support. Confirmation through togetherness derived principally from information, understanding, encouragement, involvement and spiritual community. Three subthemes were identified as the antecedents to social support: Need of support, Desire for a deeper relationship with relatives, Network to turn to. Social support involves reciprocal exchange of verbal and non-verbal information provided mainly by lay persons. The study provides knowledge of the antecedents and attributes of social support networks, particularly from the perspective of close family of adult persons with advanced lung or gastrointestinal cancer. There is a need for measurement instruments that could encourage nurses and other health-care professionals to focus on family members

Combining morphological analysis and Bayesian Networks for strategic decision support

CSIR Research Space (South Africa)

De Waal, AJ

2007-12-01

Full Text Available Morphological analysis (MA) and Bayesian networks (BN) are two closely related modelling methods, each of which has its advantages and disadvantages for strategic decision support modelling. MA is a method for defining, linking and evaluating...

Discursive Deployments: Mobilizing Support for Municipal and Community Wireless Networks in the U.S.

Energy Technology Data Exchange (ETDEWEB)

Alvarez, Rosio; Rodriguez, Juana Maria

2008-08-16

This paper examines Municipal Wireless (MW) deployments in the United States. In particular, the interest is in understanding how discourse has worked to mobilize widespread support for MW networks. We explore how local governments discursively deploy the language of social movements to create a shared understanding of the networking needs of communities. Through the process of"framing" local governments assign meaning to the MW networks in ways intended to mobilize support anddemobilize opposition. The mobilizing potential of a frame varies and is dependent on its centrality and cultural resonance. We examine the framing efforts of MW networks by using a sample of Request for Proposals for community wireless networks, semi-structured interviews and local media sources. Prominent values that are central to a majority of the projects and others that are culturally specific are identified and analyzed for their mobilizing potency.

Spatiotemporal Patterns, Monitoring Network Design, and Environmental Justice of Air Pollution in the Phoenix Metropolitan Region: A Landscape Approach

Science.gov (United States)

Pope, Ronald L.

Air pollution is a serious problem in most urban areas around the world, which has a number of negative ecological and human health impacts. As a result, it's vitally important to detect and characterize air pollutants to protect the health of the urban environment and our citizens. An important early step in this process is ensuring that the air pollution monitoring network is properly designed to capture the patterns of pollution and that all social demographics in the urban population are represented. An important aspect in characterizing air pollution patterns is scale in space and time which, along with pattern and process relationships, is a key subject in the field of landscape ecology. Thus, using multiple landscape ecological methods, this dissertation research begins by characterizing and quantifying the multi-scalar patterns of ozone (O3) and particulate matter (PM10) in the Phoenix, Arizona, metropolitan region. Results showed that pollution patterns are scale-dependent, O3 is a regionally-scaled pollutant at longer temporal scales, and PM10 is a locally-scaled pollutant with patterns sensitive to season. Next, this dissertation examines the monitoring network within Maricopa County. Using a novel multiscale indicator-based approach, the adequacy of the network was quantified by integrating inputs from various academic and government stakeholders. Furthermore, deficiencies were spatially defined and recommendations were made on how to strengthen the design of the network. A sustainability ranking system also provided new insight into the strengths and weaknesses of the network. Lastly, the study addresses the question of whether distinct social groups were experiencing inequitable exposure to pollutants - a key issue of distributive environmental injustice. A novel interdisciplinary method using multi-scalar ambient pollution data and hierarchical multiple regression models revealed environmental inequities between air pollutants and race, ethnicity

Using ELECTRE TRI to support maintenance of water distribution networks

Directory of Open Access Journals (Sweden)

Flavio Trojan

2012-08-01

Full Text Available Problems encountered in the context of the maintenance management of water supply are evidenced by the lack of decision support models which gives a manager overview of the system. This paper, therefore, develops a model that uses, in its framework, the multicriteria outranking method ELECTRE TRI. The objective is to sort the areas of water flow measurement of a water distribution network, by priority of maintenance, with data collected from an automated system of abnormalities detection. This sorting is designed to support maintenance decisions in terms of the measure more appropriate to be applied per region. To illustrate the proposed model, an application was performed in a city with 100 thousand water connections. With this model it becomes possible to improve the allocation of maintenance measures for regions and mainly to improve the operation of the distribution network.

Application of neural network and pattern recognition software to the automated analysis of continuous nuclear monitoring of on-load reactors

Energy Technology Data Exchange (ETDEWEB)

Howell, J.A.; Eccleston, G.W.; Halbig, J.K.; Klosterbuer, S.F. [Los Alamos National Lab., NM (United States); Larson, T.W. [California Polytechnic State Univ., San Luis Obispo, CA (US)

1993-08-01

Automated analysis using pattern recognition and neural network software can help interpret data, call attention to potential anomalies, and improve safeguards effectiveness. Automated software analysis, based on pattern recognition and neural networks, was applied to data collected from a radiation core discharge monitor system located adjacent to an on-load reactor core. Unattended radiation sensors continuously collect data to monitor on-line refueling operations in the reactor. The huge volume of data collected from a number of radiation channels makes it difficult for a safeguards inspector to review it all, check for consistency among the measurement channels, and find anomalies. Pattern recognition and neural network software can analyze large volumes of data from continuous, unattended measurements, thereby improving and automating the detection of anomalies. The authors developed a prototype pattern recognition program that determines the reactor power level and identifies the times when fuel bundles are pushed through the core during on-line refueling. Neural network models were also developed to predict fuel bundle burnup to calculate the region on the on-load reactor face from which fuel bundles were discharged based on the radiation signals. In the preliminary data set, which was limited and consisted of four distinct burnup regions, the neural network model correctly predicted the burnup region with an accuracy of 92%.

Delay-induced cluster patterns in coupled Cayley tree networks

Science.gov (United States)

Singh, A.; Jalan, S.

2013-07-01

We study effects of delay in diffusively coupled logistic maps on the Cayley tree networks. We find that smaller coupling values exhibit sensitiveness to value of delay, and lead to different cluster patterns of self-organized and driven types. Whereas larger coupling strengths exhibit robustness against change in delay values, and lead to stable driven clusters comprising nodes from last generation of the Cayley tree. Furthermore, introduction of delay exhibits suppression as well as enhancement of synchronization depending upon coupling strength values. To the end we discuss the importance of results to understand conflicts and cooperations observed in family business.

Definition of new 3D invariants. Applications to pattern recognition problems with neural networks

International Nuclear Information System (INIS)

Proriol, J.

1996-01-01

We propose a definition of new 3D invariants. Usual pattern recognition methods use 2D descriptions of 3D objects, we propose a 2D approximation of the defined 3D invariants which can be used with neural networks to solve pattern recognition problems. We describe some methods to use the 2 D approximants. This work is an extension of previous 3D invariants used to solve some high energy physics problems. (author)

Attention supports verbal short-term memory via competition between dorsal and ventral attention networks.

Science.gov (United States)

Majerus, Steve; Attout, Lucie; D'Argembeau, Arnaud; Degueldre, Christian; Fias, Wim; Maquet, Pierre; Martinez Perez, Trecy; Stawarczyk, David; Salmon, Eric; Van der Linden, Martial; Phillips, Christophe; Balteau, Evelyne

2012-05-01

Interactions between the neural correlates of short-term memory (STM) and attention have been actively studied in the visual STM domain but much less in the verbal STM domain. Here we show that the same attention mechanisms that have been shown to shape the neural networks of visual STM also shape those of verbal STM. Based on previous research in visual STM, we contrasted the involvement of a dorsal attention network centered on the intraparietal sulcus supporting task-related attention and a ventral attention network centered on the temporoparietal junction supporting stimulus-related attention. We observed that, with increasing STM load, the dorsal attention network was activated while the ventral attention network was deactivated, especially during early maintenance. Importantly, activation in the ventral attention network increased in response to task-irrelevant stimuli briefly presented during the maintenance phase of the STM trials but only during low-load STM conditions, which were associated with the lowest levels of activity in the dorsal attention network during encoding and early maintenance. By demonstrating a trade-off between task-related and stimulus-related attention networks during verbal STM, this study highlights the dynamics of attentional processes involved in verbal STM.

Automatic classification of thermal patterns in diabetic foot based on morphological pattern spectrum

Science.gov (United States)

Hernandez-Contreras, D.; Peregrina-Barreto, H.; Rangel-Magdaleno, J.; Ramirez-Cortes, J.; Renero-Carrillo, F.

2015-11-01

This paper presents a novel approach to characterize and identify patterns of temperature in thermographic images of the human foot plant in support of early diagnosis and follow-up of diabetic patients. Composed feature vectors based on 3D morphological pattern spectrum (pecstrum) and relative position, allow the system to quantitatively characterize and discriminate non-diabetic (control) and diabetic (DM) groups. Non-linear classification using neural networks is used for that purpose. A classification rate of 94.33% in average was obtained with the composed feature extraction process proposed in this paper. Performance evaluation and obtained results are presented.

Theoretical pattern of supporting continuity in physical education of students' personality.

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Vovk V.M.

2011-04-01

Full Text Available Methodological approaches and principles on which theoretical pattern of supporting of continuity in physical education of senior pupil and students' personality are considered. It is proved that effective process of continuity in physical education is impossible without construction of patterns. It is ascertained that continuity is a condition and mechanism of realization for others principles in teaching process that represent itself as major factors in realization of continuity in physical education.

Experiencing Rights within Positive, Person-Centred Support Networks of People with Intellectual Disability in Australia

Science.gov (United States)

Hillman, A.; Donelly, M.; Whitaker, L.; Dew, A.; Stancliffe, R. J.; Knox, M.; Shelley, K.; Parmenter, T. R.

2012-01-01

Background: This research describes issues related to human rights as they arose within the everyday lives of people in nine personal support networks that included adult Australians with an intellectual disability (ID). Method: The research was part of a wider 3-year ethnographic study of nine personal support networks. A major criterion for…

Social Support Theory: A New Framework for Exploring Gender Differences in Business Owner Networks

DEFF Research Database (Denmark)

Neergaard, Helle

The paper argues that to advance knowledge about small firm networks and consider the impact of gender, research should also consider the network experiences of women business owners. To engage in such research, this paper proposes a conceptual model of business owner networking which is informed...... by social support theory....

Social Support Networks and HIV/STI Risk Behaviors Among Latino Immigrants in a New Receiving Environment.

Science.gov (United States)

Althoff, Meghan D; Theall, Katherine; Schmidt, Norine; Hembling, John; Gebrekristos, Hirut T; Thompson, Michelle M; Muth, Stephen Q; Friedman, Samuel R; Kissinger, Patricia

2017-12-01

The objectives of this study were to: (1) describe the quantity and quality of social support networks of Latino immigrants living in a new receiving environment, and (2) determine the role such networks play in their HIV/STI risk behaviors, including substance use. Double incentivized convenience sampling was used to collect egocentric social support network data on 144 Latino immigrants. Latent class analysis was used for data reduction and to identify items best suited to measure quality and quantity of social support. Moderate and high quantity and quality of social support were protective of HIV/STI sexual risk behavior compared to low quantity and quality of support, after adjustment for gender, years in New Orleans and residing with family. Neither measure of social support was associated with binge drinking. The findings suggest that increased quantity and quality of social support decrease HIV/STI sexual risk behaviors but do not influence binge drinking. Interventions that improve the quantity and quality of social support are needed for Latino immigrants.

Evaluation of QoS supported in Network Mobility NEMO environments

International Nuclear Information System (INIS)

Hussien, L F; Abdalla, A H; Habaebi, M H; Khalifa, O O; Hassan, W H

2013-01-01

Network mobility basic support (NEMO BS) protocol is an entire network, roaming as a unit which changes its point of attachment to the Internet and consequently its reachability in the network topology. NEMO BS doesn't provide QoS guarantees to its users same as traditional Internet IP and Mobile IPv6 as well. Typically, all the users will have same level of services without considering about their application requirements. This poses a problem to real-time applications that required QoS guarantees. To gain more effective control of the network, incorporated QoS is needed. Within QoS-enabled network the traffic flow can be distributed to various priorities. Also, the network bandwidth and resources can be allocated to different applications and users. Internet Engineering Task Force (IETF) working group has proposed several QoS solutions for static network such as IntServ, DiffServ and MPLS. These QoS solutions are designed in the context of a static environment (i.e. fixed hosts and networks). However, they are not fully adapted to mobile environments. They essentially demands to be extended and adjusted to meet up various challenges involved in mobile environments. With existing QoS mechanisms many proposals have been developed to provide QoS for individual mobile nodes (i.e. host mobility). In contrary, research based on the movement of the whole mobile network in IPv6 is still undertaking by the IETF working groups (i.e. network mobility). Few researches have been done in the area of providing QoS for roaming networks. Therefore, this paper aims to review and investigate (previous /and current) related works that have been developed to provide QoS in mobile network. Consequently, a new proposed scheme will be introduced to enhance QoS within NEMO environment, achieving by which seamless mobility to users of mobile network node (MNN)

Use of social network to support visually impaired people: A Facebook case study

Directory of Open Access Journals (Sweden)

Gustavo Miranda Caran

Full Text Available The use of Information and Communication Technologies can be seen as an important factor for social inclusion in its different aspects - economic, social, relational and informational, among others. Inclusion potentiality is even more relevant for groups of people who face limiting life conditions which determine social barriers. This study investigated the social support offered to people with disabilities based on the social network analysis method. The research objective was to make the online support dynamics for low vision people, friends and relatives evident, having as case study the Facebook Low Vision group. The social network modelling and quantitative analysis were performed from user data collection, posts, comments and likes. Contents were classified according to the type of support (Emotional or Instrumental and according to its intention (Offered or Requested, represented in graphs as indicators for analysis. Results pointed towards a larger use rate of Instrumental and Offered support although a more intense and comprehensive exchange of Emotional and Requested support was found. Data collection limitations indicate the need for more empirical studies on the social use of socio-technical networks for different types of social support. This theme points to a research agenda about the role of information and communication technologies as a possible condition for inclusion, life quality and well-being of people with disabilities.

Social Networks, Support, and Psychosocial Functioning among American Indian Women in Treatment

Science.gov (United States)

Chong, Jenny; Lopez, Darlene

2005-01-01

The relationship of social networks and social support to the psychosocial functioning (self-efficacy, self-esteem, anxiety, depression, and hostility) of 159 American Indian women undergoing residential substance abuse treatment at Native American Connections was assessed. Social support and active participation by clients' families during…

Artificial Neural Network approach to develop unique Classification and Raga identification tools for Pattern Recognition in Carnatic Music

Science.gov (United States)

Srimani, P. K.; Parimala, Y. G.

2011-12-01

A unique approach has been developed to study patterns in ragas of Carnatic Classical music based on artificial neural networks. Ragas in Carnatic music which have found their roots in the Vedic period, have grown on a Scientific foundation over thousands of years. However owing to its vastness and complexities it has always been a challenge for scientists and musicologists to give an all encompassing perspective both qualitatively and quantitatively. Cognition, comprehension and perception of ragas in Indian classical music have always been the subject of intensive research, highly intriguing and many facets of these are hitherto not unravelled. This paper is an attempt to view the melakartha ragas with a cognitive perspective using artificial neural network based approach which has given raise to very interesting results. The 72 ragas of the melakartha system were defined through the combination of frequencies occurring in each of them. The data sets were trained using several neural networks. 100% accurate pattern recognition and classification was obtained using linear regression, TLRN, MLP and RBF networks. Performance of the different network topologies, by varying various network parameters, were compared. Linear regression was found to be the best performing network.

Social Network Characteristics, Social Support, and Cigarette Smoking among Asian/Pacific Islander Young Adults.

Science.gov (United States)

Pokhrel, Pallav; Fagan, Pebbles; Cassel, Kevin; Trinidad, Dennis R; Kaholokula, Joseph Keawe'aimoku; Herzog, Thaddeus A

2016-06-01

Cigarette smoking may be one of the factors contributing to the high levels of cancer-related mortality experienced by certain Asian/Pacific Islander (A/PI) subgroups (e.g., Native Hawaiian). Given the collectivist cultural orientation attributed to A/PI groups, social strategies are recommended for substance abuse or smoking cessation treatment among A/PI. However, research examining how social network characteristics and social support relate to smoking across A/PI subgroups has been lacking. This study investigated the associations between social network characteristics (e.g., size, composition), perceived social support, and recent cigarette use across Native Hawaiian, Filipino, and East Asian (e.g., Japanese, Chinese) young adults (18-35 year old). Cross-sectional, self-report data were collected from N = 435 participants (M age = 25.6, SD = 8.3; 61% women). Ethnic differences were found in a number of pathways linking social network characteristics, perceived social support, and cigarette smoking. Larger network size was strongly associated with higher perceived social support and lower recent cigarette smoking among Native Hawaiians but not Filipinos or East Asians. Higher perceived social support was associated with lower recent smoking among East Asians and Filipinos but not Native Hawaiians. Implications are discussed with regard to smoking prevention and cessation among A/PI. © Society for Community Research and Action 2016.

Energy-Efficient Region Shift Scheme to Support Mobile Sink Group in Wireless Sensor Networks.

Science.gov (United States)

Yim, Yongbin; Kim, Kyong Hoon; Aldwairi, Monther; Kim, Ki-Il

2017-12-30

Mobile sink groups play crucial roles to perform their own missions in many wireless sensor network (WSN) applications. In order to support mobility of such sink groups, it is important to design a mechanism for effective discovery of the group in motion. However, earlier studies obtain group region information by periodic query. For that reason, the mechanism leads to significant signaling overhead due to frequent flooding for the query regardless of the group movement. Furthermore, the mechanism worsens the problem by the flooding in the whole expected area. To deal with this problem, we propose a novel mobile sink group support scheme with low communication cost, called Region-Shift-based Mobile Geocasting Protocol (RSMGP). In this study, we utilize the group mobility feature for which members of a group have joint motion patterns. Thus, we could trace group movement by shifting the region as much as partial members move out of the previous region. Furthermore, the region acquisition is only performed at the moment by just deviated members without collaboration of all members. Experimental results validate the improved signaling overhead of our study compared to the previous studies.

Deep convolutional neural networks for annotating gene expression patterns in the mouse brain.

Science.gov (United States)

Zeng, Tao; Li, Rongjian; Mukkamala, Ravi; Ye, Jieping; Ji, Shuiwang

2015-05-07

Profiling gene expression in brain structures at various spatial and temporal scales is essential to understanding how genes regulate the development of brain structures. The Allen Developing Mouse Brain Atlas provides high-resolution 3-D in situ hybridization (ISH) gene expression patterns in multiple developing stages of the mouse brain. Currently, the ISH images are annotated with anatomical terms manually. In this paper, we propose a computational approach to annotate gene expression pattern images in the mouse brain at various structural levels over the course of development. We applied deep convolutional neural network that was trained on a large set of natural images to extract features from the ISH images of developing mouse brain. As a baseline representation, we applied invariant image feature descriptors to capture local statistics from ISH images and used the bag-of-words approach to build image-level representations. Both types of features from multiple ISH image sections of the entire brain were then combined to build 3-D, brain-wide gene expression representations. We employed regularized learning methods for discriminating gene expression patterns in different brain structures. Results show that our approach of using convolutional model as feature extractors achieved superior performance in annotating gene expression patterns at multiple levels of brain structures throughout four developing ages. Overall, we achieved average AUC of 0.894 ± 0.014, as compared with 0.820 ± 0.046 yielded by the bag-of-words approach. Deep convolutional neural network model trained on natural image sets and applied to gene expression pattern annotation tasks yielded superior performance, demonstrating its transfer learning property is applicable to such biological image sets.

Social network: evaluation of the support or containment contexts of lesbian mothers

Directory of Open Access Journals (Sweden)

Firley Poliana da Silva Lúcio

Full Text Available ABSTRACT Objective: To evaluate the social network of lesbian mothers, from the social contexts of support or restraint. Method: Descriptive, exploratory study, of qualitative approach, based on the theoretical reference of Social Network, with eight lesbian mothers selected through Snowball technique, using semi-structured interview. Data analysis was performed with IRAMUTEQ software, through Similarity Analysis. Results: The social network is configured as: 1 Emotional distance and non-acceptance of motherhood by the family members - primary network elements; 2 Interference in the socio-cultural medium for the effectiveness of the mother-child bond - secondary network elements. Final considerations: Social network is grounded on trivialized and negative conceptions that highlight prejudice and disrespect. The discussion of this theme contributes to a greater visibility of those new family arrangements as well as to reduce stigmas e prejudices that pervade the social network components of these women.

Scanless functional imaging of hippocampal networks using patterned two-photon illumination through GRIN lenses

KAUST Repository

Moretti, Claudio; Antonini, Andrea; Bovetti, Serena; Liberale, Carlo; Fellin, Tommaso

2016-01-01

functional imaging in rodent hippocampal networks in vivo ~1.2 mm below the brain surface. Our results open the way to the application of patterned illumination approaches to deep regions of highly scattering biological tissues, such as the mammalian brain.

The Earth Science Women's Network (ESWN): A member-driven network approach to supporting women in the Geosciences

Science.gov (United States)

Hastings, M. G.; Kontak, R.; Adams, A. S.; Barnes, R. T.; Fischer, E. V.; Glessmer, M. S.; Holloway, T.; Marin-Spiotta, E.; Rodriguez, C.; Steiner, A. L.; Wiedinmyer, C.; Laursen, S. L.

2013-12-01

The Earth Science Women's Network (ESWN) is an organization of women geoscientists, many in the early stages of their careers. The mission of ESWN is to promote success in scientific careers by facilitating career development, community, informal mentoring and support, and professional collaborations. ESWN currently connects nearly 2000 women across the globe, and includes graduate students, postdoctoral scientists, tenure and non-tenure track faculty from diverse colleges and universities, program managers, and government, non-government and industry researchers. In 2009, ESWN received an NSF ADVANCE PAID award, with the primary goals to grow our membership to serve a wider section of the geosciences community, to design and administer career development workshops, to promote professional networking at scientific conferences, and to develop web resources to build connections, collaborations, and peer mentoring for and among women in the Earth Sciences. Now at the end of the grant, ESWN members have reported gains in a number of aspects of their personal and professional lives including: knowledge about career resources; a greater understanding of the challenges facing women in science and resources to overcome them; a sense of community and less isolation; greater confidence in their own career trajectories; professional collaborations; emotional support on a variety of issues; and greater engagement and retention in scientific careers. The new ESWN web center (www.ESWNonline.org), a major development supported by NSF ADVANCE and AGU, was created to facilitate communication and networking among our members. The web center offers a state-of-the-art social networking platform and features: 1) a public site offering information on ESWN, career resources for all early career scientists, and a 'members' spotlight' highlighting members' scientific and professional achievements; and 2) a password protected member area where users can personalize profiles, create and

Using Hierarchical Temporal Memory for Detecting Anomalous Network Activity

Science.gov (United States)

2008-03-01

warfare, computer network operations, psychological operations, military deception, and operations security, in concert with specified supporting and...you up short—you were subconsciously predicting something else and were surprised by the mismatch” [3]. Notable neurobiologist Horace Barlow of the...malicious network activity is flagged as abnormal . That is, test data should present the N-HTM network with spatial-temporal patterns that do not match 46

Spike Pattern Structure Influences Synaptic Efficacy Variability Under STDP and Synaptic Homeostasis. II: Spike Shuffling Methods on LIF Networks

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Zedong Bi

2016-08-01

Full Text Available Synapses may undergo variable changes during plasticity because of the variability of spike patterns such as temporal stochasticity and spatial randomness. Here, we call the variability of synaptic weight changes during plasticity to be efficacy variability. In this paper, we investigate how four aspects of spike pattern statistics (i.e., synchronous firing, burstiness/regularity, heterogeneity of rates and heterogeneity of cross-correlations influence the efficacy variability under pair-wise additive spike-timing dependent plasticity (STDP and synaptic homeostasis (the mean strength of plastic synapses into a neuron is bounded, by implementing spike shuffling methods onto spike patterns self-organized by a network of excitatory and inhibitory leaky integrate-and-fire (LIF neurons. With the increase of the decay time scale of the inhibitory synaptic currents, the LIF network undergoes a transition from asynchronous state to weak synchronous state and then to synchronous bursting state. We first shuffle these spike patterns using a variety of methods, each designed to evidently change a specific pattern statistics; and then investigate the change of efficacy variability of the synapses under STDP and synaptic homeostasis, when the neurons in the network fire according to the spike patterns before and after being treated by a shuffling method. In this way, we can understand how the change of pattern statistics may cause the change of efficacy variability. Our results are consistent with those of our previous study which implements spike-generating models on converging motifs. We also find that burstiness/regularity is important to determine the efficacy variability under asynchronous states, while heterogeneity of cross-correlations is the main factor to cause efficacy variability when the network moves into synchronous bursting states (the states observed in epilepsy.

Examining ISIS Support and Opposition Networks on Twitter

Science.gov (United States)

2016-01-01

Examining ISIS Support and Opposition Networks on Twitter Elizabeth Bodine-Baron, Todd C. Helmus, Madeline Magnuson, Zev Winkelman C O R P O R A T...Syria (ISIS), like no other terrorist organization before, has used Twitter and other social media channels to broadcast its message, inspire followers...and recruit new fighters. Though much less heralded, ISIS opponents have also taken to Twitter to cas- tigate the ISIS message. This report draws on

The Impacts of Network Centrality and Self-Regulation on an E-Learning Environment with the Support of Social Network Awareness

Science.gov (United States)

Lin, Jian-Wei; Huang, Hsieh-Hong; Chuang, Yuh-Shy

2015-01-01

An e-learning environment that supports social network awareness (SNA) is a highly effective means of increasing peer interaction and assisting student learning by raising awareness of social and learning contexts of peers. Network centrality profoundly impacts student learning in an SNA-related e-learning environment. Additionally,…

The meaning and validation of social support networks for close family of persons with advanced cancer

Directory of Open Access Journals (Sweden)

Sjolander Catarina

2012-09-01

Full Text Available Abstract Background To strengthen the mental well-being of close family of persons newly diagnosed as having cancer, it is necessary to acquire a greater understanding of their experiences of social support networks, so as to better assess what resources are available to them from such networks and what professional measures are required. The main aim of the present study was to explore the meaning of these networks for close family of adult persons in the early stage of treatment for advanced lung or gastrointestinal cancer. An additional aim was to validate the study’s empirical findings by means of the Finfgeld-Connett conceptual model for social support. The intention was to investigate whether these findings were in accordance with previous research in nursing. Methods Seventeen family members with a relative who 8–14 weeks earlier had been diagnosed as having lung or gastrointestinal cancer were interviewed. The data were subjected to qualitative latent content analysis and validated by means of identifying antecedents and critical attributes. Results The meaning or main attribute of the social support network was expressed by the theme Confirmation through togetherness, based on six subthemes covering emotional and, to a lesser extent, instrumental support. Confirmation through togetherness derived principally from information, understanding, encouragement, involvement and spiritual community. Three subthemes were identified as the antecedents to social support: Need of support, Desire for a deeper relationship with relatives, Network to turn to. Social support involves reciprocal exchange of verbal and non-verbal information provided mainly by lay persons. Conclusions The study provides knowledge of the antecedents and attributes of social support networks, particularly from the perspective of close family of adult persons with advanced lung or gastrointestinal cancer. There is a need for measurement instruments that could

Fuzzy logic and neural networks in artificial intelligence and pattern recognition

Science.gov (United States)

Sanchez, Elie

1991-10-01

With the use of fuzzy logic techniques, neural computing can be integrated in symbolic reasoning to solve complex real world problems. In fact, artificial neural networks, expert systems, and fuzzy logic systems, in the context of approximate reasoning, share common features and techniques. A model of Fuzzy Connectionist Expert System is introduced, in which an artificial neural network is designed to construct the knowledge base of an expert system from, training examples (this model can also be used for specifications of rules in fuzzy logic control). Two types of weights are associated with the synaptic connections in an AND-OR structure: primary linguistic weights, interpreted as labels of fuzzy sets, and secondary numerical weights. Cell activation is computed through min-max fuzzy equations of the weights. Learning consists in finding the (numerical) weights and the network topology. This feedforward network is described and first illustrated in a biomedical application (medical diagnosis assistance from inflammatory-syndromes/proteins profiles). Then, it is shown how this methodology can be utilized for handwritten pattern recognition (characters play the role of diagnoses): in a fuzzy neuron describing a number for example, the linguistic weights represent fuzzy sets on cross-detecting lines and the numerical weights reflect the importance (or weakness) of connections between cross-detecting lines and characters.

Memory and pattern storage in neural networks with activity dependent synapses

Science.gov (United States)

Mejias, J. F.; Torres, J. J.

2009-01-01

We present recently obtained results on the influence of the interplay between several activity dependent synaptic mechanisms, such as short-term depression and facilitation, on the maximum memory storage capacity in an attractor neural network [1]. In contrast with the case of synaptic depression, which drastically reduces the capacity of the network to store and retrieve activity patterns [2], synaptic facilitation is able to enhance the memory capacity in different situations. In particular, we find that a convenient balance between depression and facilitation can enhance the memory capacity, reaching maximal values similar to those obtained with static synapses, that is, without activity-dependent processes. We also argue, employing simple arguments, that this level of balance is compatible with experimental data recorded from some cortical areas, where depression and facilitation may play an important role for both memory-oriented tasks and information processing. We conclude that depressing synapses with a certain level of facilitation allow to recover the good retrieval properties of networks with static synapses while maintaining the nonlinear properties of dynamic synapses, convenient for information processing and coding.

Constant load supports attenuating shocks and vibrations for networks of pipes submitted to large thermal dilatation

International Nuclear Information System (INIS)

Prisecaru, Ilie; Panait; Adrian; Serban, Viorel; Ciocan, George; Androne, Marian; Florea, Ioana; State, Elena

2004-01-01

Full text: To avoid some drawbacks in the classical supports employed currently in networks of pipes it was conceived, designed, built and experimentally tested a new type of constant load supports which attenuate largely the shocks and vibrations for networks of pipes subjected to large thermal dilatation. These supports are particularly needed for solving the severe problems of the vibrations in networks of pipes in thermoelectric stations, nuclear power plants, or heavy water production plants. These supports allow building networks of new types, more reliable and of lower cost. The new type of support was developed on the basis of a number of patents protected by OSIM. It has a simple structure, ensures a secure functioning without blocking or other kinds of failures and is resistant to a very large variety of stresses. The new type of support of constant load avoids the drawbacks in classical supports i.e. the stress/deformation diagram is practically independent of stress level. The characteristic of the support is geometrically non-linear and presents a plateau with a small slope over a rather large deformation range which results from a serially mounted structure of sandwiches the deformation of which is controlled by a system of deforming central and peripheral pieces. The new supports of constant load, called SERB-PIPE, present a controlled elasticity and a high degree of damping as the package of elastic blades (the sandwich structure) is made of two sub-packages with relative movements what ensure the attenuation of the shocks and vibrations produced by the fluid flow within the pipes and or by seismic motions. By contrast with classical supports, the new supports have a simple structure and a high reliability. Breakdown under stress leading to severe changes in the stress distribution in pipe networks, which could generate overloads in pipes and over-loading in other supports, cannot occur. One can also mention that these supports can be built in a

The effect of social networks and social support on common mental disorders following specific life events.

Science.gov (United States)

Maulik, P K; Eaton, W W; Bradshaw, C P

2010-08-01

This study examined the association between life events and common mental disorders while accounting for social networks and social supports. Participants included 1920 adults in the Baltimore Epidemiologic Catchment Area Cohort who were interviewed in 1993-1996, of whom 1071 were re-interviewed in 2004-2005. Generalized estimating equations were used to analyze the data. Social support from friends, spouse or relatives was associated with significantly reduced odds of panic disorder and psychological distress, after experiencing specific life events. Social networks or social support had no significant stress-buffering effect. Social networks and social support had almost no direct or buffering effect on major depressive disorder, and no effect on generalized anxiety disorder and alcohol abuse or dependence disorder. The significant association between social support and psychological distress, rather than diagnosable mental disorders, highlights the importance of social support, especially when the severity of a mental health related problem is low.

Temporal prediction of epidemic patterns in community networks

International Nuclear Information System (INIS)

Peng, Xiao-Long; Xu, Xin-Jian; Fu, Xinchu; Small, Michael

2013-01-01

Most previous studies of epidemic dynamics on complex networks suppose that the disease will eventually stabilize at either a disease-free state or an endemic one. In reality, however, some epidemics always exhibit sporadic and recurrent behaviour in one region because of the invasion from an endemic population elsewhere. In this paper we address this issue and study a susceptible–infected–susceptible epidemiological model on a network consisting of two communities, where the disease is endemic in one community but alternates between outbreaks and extinctions in the other. We provide a detailed characterization of the temporal dynamics of epidemic patterns in the latter community. In particular, we investigate the time duration of both outbreak and extinction, and the time interval between two consecutive inter-community infections, as well as their frequency distributions. Based on the mean-field theory, we theoretically analyse these three timescales and their dependence on the average node degree of each community, the transmission parameters and the number of inter-community links, which are in good agreement with simulations, except when the probability of overlaps between successive outbreaks is too large. These findings aid us in better understanding the bursty nature of disease spreading in a local community, and thereby suggesting effective time-dependent control strategies. (paper)

Physician referral patterns and racial disparities in total hip replacement: A network analysis approach.

Directory of Open Access Journals (Sweden)

Hassan M K Ghomrawi

Full Text Available Efforts to reduce racial disparities in total hip replacement (THR have focused mainly on patient behaviors. While these efforts are no doubt important, they ignore the potentially important role of provider- and system-level factors, which may be easier to modify. We aimed to determine whether the patterns of interaction among physicians around THR episodes differ in communities with low versus high concentrations of black residents.We analyzed national Medicare claims from 2008 to 2011, identifying all fee-for-service beneficiaries who underwent THR. Based on physician encounter data, we then mapped the physician referral networks at the hospitals where beneficiaries' procedures were performed. Next, we measured two structural properties of these networks that could affect care coordination and information sharing: clustering, and the number of external ties. Finally, we estimated multivariate regression models to determine the relationship between the concentration of black residents in the community [as measured by the hospital service area (HSA] served by a given network and each of these 2 network properties.Our sample included 336,506 beneficiaries (mean age 76.3 ± SD, 63.1% of whom were women. HSAs with higher concentrations of black residents tended to be more impoverished than those with lower concentrations. While HSAs with higher concentrations of black residents had, on average, more acute care beds and medical specialists, they had fewer surgeons per capita than those with lower concentrations. After adjusting for these differences, we found that HSAs with higher concentrations of black residents were served by physician referral networks that had significantly higher within-network clustering but fewer external ties.We observed differences in the patterns of interaction among physicians around THR episodes in communities with low versus high concentrations of black residents. Studies investigating the impact of these differences

Representational Similarity Analysis Reveals Heterogeneous Networks Supporting Speech Motor Control

DEFF Research Database (Denmark)

Zheng, Zane; Cusack, Rhodri; Johnsrude, Ingrid

The everyday act of speaking involves the complex processes of speech motor control. One important feature of such control is regulation of articulation when auditory concomitants of speech do not correspond to the intended motor gesture. While theoretical accounts of speech monitoring posit...... multiple functional components required for detection of errors in speech planning (e.g., Levelt, 1983), neuroimaging studies generally indicate either single brain regions sensitive to speech production errors, or small, discrete networks. Here we demonstrate that the complex system controlling speech...... is supported by a complex neural network that is involved in linguistic, motoric and sensory processing. With the aid of novel real-time acoustic analyses and representational similarity analyses of fMRI signals, our data show functionally differentiated networks underlying auditory feedback control of speech....

Dissociable intrinsic functional networks support noun-object and verb-action processing.

Science.gov (United States)

Yang, Huichao; Lin, Qixiang; Han, Zaizhu; Li, Hongyu; Song, Luping; Chen, Lingjuan; He, Yong; Bi, Yanchao

2017-12-01

The processing mechanism of verbs-actions and nouns-objects is a central topic of language research, with robust evidence for behavioral dissociation. The neural basis for these two major word and/or conceptual classes, however, remains controversial. Two experiments were conducted to study this question from the network perspective. Experiment 1 found that nodes of the same class, obtained through task-evoked brain imaging meta-analyses, were more strongly connected with each other than nodes of different classes during resting-state, forming segregated network modules. Experiment 2 examined the behavioral relevance of these intrinsic networks using data from 88 brain-damaged patients, finding that across patients the relative strength of functional connectivity of the two networks significantly correlated with the noun-object vs. verb-action relative behavioral performances. In summary, we found that verbs-actions and nouns-objects are supported by separable intrinsic functional networks and that the integrity of such networks accounts for the relative noun-object- and verb-action-selective deficits. Copyright © 2017 Elsevier Inc. All rights reserved.

AWESOME: A widget-based dashboard for awareness-support in Research Networks

NARCIS (Netherlands)

Reinhardt, Wolfgang; Mletzko, Christian; Drachsler, Hendrik; Sloep, Peter

2011-01-01

Reinhardt, W., Mletzko, C., Drachsler, H., & Sloep, P. B. (2011). AWESOME: A widget-based dashboard for awareness-support in Research Networks. In Proceedings of The PLE Conference 2011. July, 11-13, 2011, Southampton, UK.

Oscillation-Driven Spike-Timing Dependent Plasticity Allows Multiple Overlapping Pattern Recognition in Inhibitory Interneuron Networks

DEFF Research Database (Denmark)

Garrido, Jesús A.; Luque, Niceto R.; Tolu, Silvia

2016-01-01

The majority of operations carried out by the brain require learning complex signal patterns for future recognition, retrieval and reuse. Although learning is thought to depend on multiple forms of long-term synaptic plasticity, the way this latter contributes to pattern recognition is still poorly...... and at the inhibitory interneuron-interneuron synapses, the interneurons rapidly learned complex input patterns. Interestingly, induction of plasticity required that the network be entrained into theta-frequency band oscillations, setting the internal phase-reference required to drive STDP. Inhibitory plasticity...... effectively distributed multiple patterns among available interneurons, thus allowing the simultaneous detection of multiple overlapping patterns. The addition of plasticity in intrinsic excitability made the system more robust allowing self-adjustment and rescaling in response to a broad range of input...

Modelling fast spreading patterns of airborne infectious diseases using complex networks

Science.gov (United States)

Brenner, Frank; Marwan, Norbert; Hoffmann, Peter

2017-04-01

The pandemics of SARS (2002/2003) and H1N1 (2009) have impressively shown the potential of epidemic outbreaks of infectious diseases in a world that is strongly connected. Global air travelling established an easy and fast opportunity for pathogens to migrate globally in only a few days. This made epidemiological prediction harder. By understanding this complex development and its link to climate change we can suggest actions to control a part of global human health affairs. In this study we combine the following data components to simulate the outbreak of an airborne infectious disease that is directly transmitted from human to human: em{Global Air Traffic Network (from openflights.org) with information on airports, airport location, direct flight connection, airplane type} em{Global population dataset (from SEDAC, NASA)} em{Susceptible-Infected-Recovered (SIR) compartmental model to simulate disease spreading in the vicinity of airports. A modified Susceptible-Exposed-Infected-Recovered (SEIR) model to analyze the impact of the incubation period.} em{WATCH-Forcing-Data-ERA-Interim (WFDEI) climate data: temperature, specific humidity, surface air pressure, and water vapor pressure} These elements are implemented into a complex network. Nodes inside the network represent airports. Each single node is equipped with its own SIR/SEIR compartmental model with node specific attributes. Edges between those nodes represent direct flight connections that allow infected individuals to move between linked nodes. Therefore the interaction of the set of unique SIR models creates the model dynamics we will analyze. To better figure out the influence on climate change on disease spreading patterns, we focus on Influenza-like-Illnesses (ILI). The transmission rate of ILI has a dependency on climate parameters like humidity and temperature. Even small changes of environmental variables can trigger significant differences in the global outbreak behavior. Apart from the direct

Network Characteristics, Perceived Social Support, and Psychological Adjustment in Mothers of Children with Autism Spectrum Disorder

Science.gov (United States)

Benson, Paul R.

2012-01-01

This study examined the characteristics of the support networks of 106 mothers of children with ASD and their relationship to perceived social support, depressed mood, and subjective well-being. Using structural equation modeling, two competing sets of hypotheses were assessed: (1) that network characteristics would impact psychological adjustment…

Network operations support systems as a competitive advantage

OpenAIRE

Soh, Andrew K. L.

2005-01-01

The overall purpose of this paper is to perfom an analysis of TELUS and to examine if Network Operation Support Systems (OSS) can provide TELUS with a sustainable competitive advantage. The paper begins with the first three chapter exploring overviews of the components of the Canadian Telecommunications services industry, TELUS and its products, and the markets and revenues. The next chapter is an industry analysis of the industry landscape and its players. Michael Porter's Five Forces model ...

A Combination of Central Pattern Generator-based and Reflex-based Neural Networks for Dynamic, Adaptive, Robust Bipedal Locomotion

DEFF Research Database (Denmark)

Di Canio, Giuliano; Larsen, Jørgen Christian; Wörgötter, Florentin

2016-01-01

Robotic systems inspired from humans have always been lightening up the curiosity of engineers and scientists. Of many challenges, human locomotion is a very difficult one where a number of different systems needs to interact in order to generate a correct and balanced pattern. To simulate...... the interaction of these systems, implementations with reflexbased or central pattern generator (CPG)-based controllers have been tested on bipedal robot systems. In this paper we will combine the two controller types, into a controller that works with both reflex and CPG signals. We use a reflex-based neural...... network to generate basic walking patterns of a dynamic bipedal walking robot (DACBOT) and then a CPG-based neural network to ensure robust walking behavior...

Patterns of cortical oscillations organize neural activity into whole-brain functional networks evident in the fMRI BOLD signal