A graph-based network-vulnerability analysis system

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

Swiler, L.P.; Phillips, C.; Gaylor, T.

1998-01-01

This report presents a graph-based approach to network vulnerability analysis. The method is flexible, allowing analysis of attacks from both outside and inside the network. It can analyze risks to a specific network asset, or examine the universe of possible consequences following a successful attack. The analysis system requires as input a database of common attacks, broken into atomic steps, specific network configuration and topology information, and an attacker profile. The attack information is matched with the network configuration information and an attacker profile to create a superset attack graph. Nodes identify a stage of attack, for example the classmore » of machines the attacker has accessed and the user privilege level he or she has compromised. The arcs in the attack graph represent attacks or stages of attacks. By assigning probabilities of success on the arcs or costs representing level-of-effort for the attacker, various graph algorithms such as shortest-path algorithms can identify the attack paths with the highest probability of success.« less

Scientific and Technical Information in Canada, Part II, Chapter 6: Libraries.

ERIC Educational Resources Information Center

Science Council of Canada, Ottawa (Ontario).

The four types of libraries - special, academic, public, and school - collectively constitute a large part of the knowledge available in Canada. Consequently, a scientific and technical information network will be heavily dependent on these established library collections. Communications across the "type of library" boundaries is…

Visibility Graph Based Time Series Analysis

PubMed Central

Stephen, Mutua; Gu, Changgui; Yang, Huijie

2015-01-01

Network based time series analysis has made considerable achievements in the recent years. By mapping mono/multivariate time series into networks, one can investigate both it’s microscopic and macroscopic behaviors. However, most proposed approaches lead to the construction of static networks consequently providing limited information on evolutionary behaviors. In the present paper we propose a method called visibility graph based time series analysis, in which series segments are mapped to visibility graphs as being descriptions of the corresponding states and the successively occurring states are linked. This procedure converts a time series to a temporal network and at the same time a network of networks. Findings from empirical records for stock markets in USA (S&P500 and Nasdaq) and artificial series generated by means of fractional Gaussian motions show that the method can provide us rich information benefiting short-term and long-term predictions. Theoretically, we propose a method to investigate time series from the viewpoint of network of networks. PMID:26571115

Chaotic, informational and synchronous behaviour of multiplex networks

NASA Astrophysics Data System (ADS)

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

2016-03-01

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

eHealth services and Directive on Electronic Commerce 2000/31/EC.

PubMed

Van Gyseghem, Jean-Marc

2008-01-01

We often restrict the analysis of eHealth services to a concept of privacy. In this article, we'll demonstrate that other legislation can apply to those services as Directive 2000/31/EC on Ecommerce. By creating telematic networks or infrastructure, eHealth services are offering information services. But what are the consequences with such concept? What are the duties and rights for the actors of the network(s)? We'll try to answer to some questions, even if it won't be exhaustive.

The enhancement of security in healthcare information systems.

PubMed

Liu, Chia-Hui; Chung, Yu-Fang; Chen, Tzer-Shyong; Wang, Sheng-De

2012-06-01

With the progress and the development of information technology, the internal data in medical organizations have become computerized and are further established the medical information system. Moreover, the use of the Internet enhances the information communication as well as affects the development of the medical information system that a lot of medical information is transmitted with the Internet. Since there is a network within another network, when all networks are connected together, they will form the "Internet". For this reason, the Internet is considered as a high-risk and public environment which is easily destroyed and invaded so that a relevant protection is acquired. Besides, the data in the medical network system are confidential that it is necessary to protect the personal privacy, such as electronic patient records, medical confidential information, and authorization-controlled data in the hospital. As a consequence, a medical network system is considered as a network requiring high security that excellent protections and managerial strategies are inevitable to prevent illegal events and external attacks from happening. This study proposes secure medical managerial strategies being applied to the network environment of the medical organization information system so as to avoid the external or internal information security events, allow the medical system to work smoothly and safely that not only benefits the patients, but also allows the doctors to use it more conveniently, and further promote the overall medical quality. The objectives could be achieved by preventing from illegal invasion or medical information being stolen, protecting the completeness and security of medical information, avoiding the managerial mistakes of the internal information system in medical organizations, and providing the highly-reliable medical information system.

Information for Developing Countries: Definitions, Institutions and Issues. A Contribution towards Forming an Understanding of the Potential for Consultancy, Marketing and Training Related Activities. Kingston Polytechnic School of Information Systems Research Report 87-3.

ERIC Educational Resources Information Center

Lindsay, John

This paper reports on the emerging market in information on development-related activities in terms of the European capacity in databases and information networking. The first of its two parts addresses issues that are emerging consequent to the introduction of information technology in developing countries. Problems of definition and interest in…

Rural women and violence situation: access and accessibility limits to the healthcare network.

PubMed

Costa, Marta Cocco da; Silva, Ethel Bastos da; Soares, Joannie Dos Santos Fachinelli; Borth, Luana Cristina; Honnef, Fernanda

2017-07-13

To analyze the access and accessibility to the healthcare network of women dwelling in rural contexts undergoing violence situation, as seen from the professionals' speeches. A qualitative, exploratory, descriptive study with professionals from the healthcare network services about coping with violence in four municipalities in the northern region of Rio Grande do Sul. The information derived from interviews, which have been analyzed by thematic modality. (Lack of) information of women, distance, restricted access to transportation, dependence on the partner and (lack of) attention by professionals to welcome women undergoing violence situation and (non)-articulation of the network are factors that limit the access and, as a consequence, they result in the lack of confrontation of this problem. To bring closer the services which integrate the confrontation network of violence against women and to qualify professionals to welcome these situations are factors that can facilitate the access and adhesion of rural women to the services.

2015 Global Information Technology Report: Consequences on Knowledge Management in Higher Education Institutions in Nigeria

ERIC Educational Resources Information Center

Ololube, Nwachukwu Prince; Agbor, Comfort Nkogho; Major, Nanighe Baldwin; Agabi, Chinyere O.; Wali, Worlu I.

2016-01-01

This research is a continuation of a theoretical review that evaluated ICT Policy Outcomes for National Development in relation to Networked Readiness Index (NRI) and the impact it has on knowledge integration and management in higher education institutions in Nigeria. A new dawn in information technology (IT) has initiated new trends in…

The Academic and Social Life Styles of Students and Teachers of Higher Education Institutions in Bangladesh as Consequences of Using Social Network Sites

ERIC Educational Resources Information Center

Clement, Che Kum

2014-01-01

With the emergence of social network sites (SNS), students and teachers of higher education institutions all over the world have been making efforts to meet up with the demands of these information and communication technology (ICT) tools. This paper presents the findings of a study conducted at four private universities in Bangladesh with the aim…

A Network Analysis Perspective to Implementation: The Example of Health Links to Promote Coordinated Care.

PubMed

Yousefi Nooraie, Reza; Khan, Sobia; Gutberg, Jennifer; Baker, G Ross

2018-01-01

Although implementation models broadly recognize the importance of social relationships, our knowledge about applying social network analysis (SNA) to formative, process, and outcome evaluations of health system interventions is limited. We explored applications of adopting an SNA lens to inform implementation planning, engagement and execution, and evaluation. We used Health Links, a province-wide program in Canada aiming to improve care coordination among multiple providers of high-needs patients, as an example of a health system intervention. At the planning phase, an SNA can depict the structure, network influencers, and composition of clusters at various levels. It can inform the engagement and execution by identifying potential targets (e.g., opinion leaders) and by revealing structural gaps and clusters. It can also be used to assess the outcomes of the intervention, such as its success in increasing network connectivity; changing the position of certain actors; and bridging across specialties, organizations, and sectors. We provided an overview of how an SNA lens can shed light on the complexity of implementation along the entire implementation pathway, by revealing the relational barriers and facilitators, the application of network-informed and network-altering interventions, and testing hypotheses on network consequences of the implementation.

A conceptual model for site-level ecology of the giant gartersnake (Thamnophis gigas) in the Sacramento Valley, California

USGS Publications Warehouse

Halstead, Brian J.; Wylie, Glenn D.; Casazza, Michael L.; Hansen, Eric C.; Scherer, Rick D.; Patterson, Laura C.

2015-08-14

Bayesian networks further provide a clear visual display of the model that facilitates understanding among various stakeholders (Marcot and others, 2001; Uusitalo , 2007). Empirical data and expert judgment can be combined, as continuous or categorical variables, to update knowledge about the system (Marcot and others, 2001; Uusitalo , 2007). Importantly, Bayesian network models allow inference from causes to consequences, but also from consequences to causes, so that data can inform the states of nodes (values of different random variables) in either direction (Marcot and others, 2001; Uusitalo , 2007). Because they can incorporate both decision nodes that represent management actions and utility nodes that quantify the costs and benefits of outcomes, Bayesian networks are ideally suited to risk analysis and adaptive management (Nyberg and others, 2006; Howes and others, 2010). Thus, Bayesian network models are useful in situations where empirical data are not available, such as questions concerning the responses of giant gartersnakes to management.

Effects of rewiring strategies on information spreading in complex dynamic networks

NASA Astrophysics Data System (ADS)

Ally, Abdulla F.; Zhang, Ning

2018-04-01

Recent advances in networks and communication services have attracted much interest to understand information spreading in social networks. Consequently, numerous studies have been devoted to provide effective and accurate models for mimicking information spreading. However, knowledge on how to spread information faster and more widely remains a contentious issue. Yet, most existing works are based on static networks which limit the reality of dynamism of entities that participate in information spreading. Using the SIR epidemic model, this study explores and compares effects of two rewiring models (Fermi-Dirac and Linear functions) on information spreading in scale free and small world networks. Our results show that for all the rewiring strategies, the spreading influence replenishes with time but stabilizes in a steady state at later time-steps. This means that information spreading takes-off during the initial spreading steps, after which the spreading prevalence settles toward its equilibrium, with majority of the population having recovered and thus, no longer affecting the spreading. Meanwhile, rewiring strategy based on Fermi-Dirac distribution function in one way or another impedes the spreading process, however, the structure of the networks mimic the spreading, even with a low spreading rate. The worst case can be when the spreading rate is extremely small. The results emphasize that despite a big role of such networks in mimicking the spreading, the role of the parameters cannot be simply ignored. Apparently, the probability of giant degree neighbors being informed grows much faster with the rewiring strategy of linear function compared to that of Fermi-Dirac distribution function. Clearly, rewiring model based on linear function generates the fastest spreading across the networks. Therefore, if we are interested in speeding up the spreading process in stochastic modeling, linear function may play a pivotal role.

Community-level demographic consequences of urbanization: an ecological network approach.

PubMed

Rodewald, Amanda D; Rohr, Rudolf P; Fortuna, Miguel A; Bascompte, Jordi

2014-11-01

Ecological networks are known to influence ecosystem attributes, but we poorly understand how interspecific network structure affect population demography of multiple species, particularly for vertebrates. Establishing the link between network structure and demography is at the crux of being able to use networks to understand population dynamics and to inform conservation. We addressed the critical but unanswered question, does network structure explain demographic consequences of urbanization? We studied 141 ecological networks representing interactions between plants and nesting birds in forests across an urbanization gradient in Ohio, USA, from 2001 to 2011. Nest predators were identified by video-recording nests and surveyed from 2004 to 2011. As landscapes urbanized, bird-plant networks were more nested, less compartmentalized and dominated by strong interactions between a few species (i.e. low evenness). Evenness of interaction strengths promoted avian nest survival, and evenness explained demography better than urbanization, level of invasion, numbers of predators or other qualitative network metrics. Highly uneven networks had approximately half the nesting success as the most even networks. Thus, nest survival reflected how urbanization altered species interactions, particularly with respect to how nest placement affected search efficiency of predators. The demographic effects of urbanization were not direct, but were filtered through bird-plant networks. This study illustrates how network structure can influence demography at the community level and further, that knowledge of species interactions and a network approach may be requisite to understanding demographic responses to environmental change. © 2014 The Authors. Journal of Animal Ecology © 2014 British Ecological Society.

PGTandMe: social networking-based genetic testing and the evolving research model.

PubMed

Koch, Valerie Gutmann

2012-01-01

The opportunity to use extensive genetic data, personal information, and family medical history for research purposes may be naturally appealing to the personal genetic testing (PGT) industry, which is already coupling direct-to-consumer (DTC) products with social networking technologies, as well as to potential industry or institutional partners. This article evaluates the transformation in research that the hybrid of PGT and social networking will bring about, and--highlighting the challenges associated with a new paradigm of "patient-driven" genomic research--focuses on the consequences of shifting the structure, locus, timing, and scope of research through genetic crowd-sourcing. This article also explores potential ethical, legal, and regulatory issues that arise from the hybrid between personal genomic research and online social networking, particularly regarding informed consent, institutional review board (IRB) oversight, and ownership/intellectual property (IP) considerations.

Briefer assessment of social network drinking: A test of the Important People Instrument-5 (IP-5).

PubMed

Hallgren, Kevin A; Barnett, Nancy P

2016-12-01

The Important People instrument (IP; Longabaugh et al., 2010) is one of the most commonly used measures of social network drinking. Although its reliability and validity are well-supported, the length of the instrument may limit its use in many settings. The present study evaluated whether a briefer, 5-person version of the IP (IP-5) adequately reproduces scores from the full IP. College freshmen (N = 1,053) reported their own past-month drinking, alcohol-related consequences, and information about drinking in their close social networks at baseline and 1 year later. From this we derived network members' drinking frequency, percentage of drinkers, and percentage of heavy drinkers, assessed for up to 10 (full IP) or 5 (IP-5) network members. We first modeled the expected concordance between full-IP scores and scores from simulated shorter IP instruments by sampling smaller subsets of network members from full IP data. Then, using quasi-experimental methods, we administered the full IP and IP-5 and compared the 2 instruments' score distributions and concurrent and year-lagged associations with participants' alcohol consumption and consequences. Most of the full-IP variance was reproduced from simulated shorter versions of the IP (ICCs ≥ 0.80). The full IP and IP-5 yielded similar score distributions, concurrent associations with drinking (r = 0.22 to 0.52), and year-lagged associations with drinking. The IP-5 retains most of the information about social network drinking from the full IP. The shorter instrument may be useful in clinical and research settings that require frequent measure administration, yielding greater temporal resolution for monitoring social network drinking. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

“Guilt by Association” Is the Exception Rather Than the Rule in Gene Networks

PubMed Central

Gillis, Jesse; Pavlidis, Paul

2012-01-01

Gene networks are commonly interpreted as encoding functional information in their connections. An extensively validated principle called guilt by association states that genes which are associated or interacting are more likely to share function. Guilt by association provides the central top-down principle for analyzing gene networks in functional terms or assessing their quality in encoding functional information. In this work, we show that functional information within gene networks is typically concentrated in only a very few interactions whose properties cannot be reliably related to the rest of the network. In effect, the apparent encoding of function within networks has been largely driven by outliers whose behaviour cannot even be generalized to individual genes, let alone to the network at large. While experimentalist-driven analysis of interactions may use prior expert knowledge to focus on the small fraction of critically important data, large-scale computational analyses have typically assumed that high-performance cross-validation in a network is due to a generalizable encoding of function. Because we find that gene function is not systemically encoded in networks, but dependent on specific and critical interactions, we conclude it is necessary to focus on the details of how networks encode function and what information computational analyses use to extract functional meaning. We explore a number of consequences of this and find that network structure itself provides clues as to which connections are critical and that systemic properties, such as scale-free-like behaviour, do not map onto the functional connectivity within networks. PMID:22479173

Measures of node centrality in mobile social networks

NASA Astrophysics Data System (ADS)

Gao, Zhenxiang; Shi, Yan; Chen, Shanzhi

2015-02-01

Mobile social networks exploit human mobility and consequent device-to-device contact to opportunistically create data paths over time. While links in mobile social networks are time-varied and strongly impacted by human mobility, discovering influential nodes is one of the important issues for efficient information propagation in mobile social networks. Although traditional centrality definitions give metrics to identify the nodes with central positions in static binary networks, they cannot effectively identify the influential nodes for information propagation in mobile social networks. In this paper, we address the problems of discovering the influential nodes in mobile social networks. We first use the temporal evolution graph model which can more accurately capture the topology dynamics of the mobile social network over time. Based on the model, we explore human social relations and mobility patterns to redefine three common centrality metrics: degree centrality, closeness centrality and betweenness centrality. We then employ empirical traces to evaluate the benefits of the proposed centrality metrics, and discuss the predictability of nodes' global centrality ranking by nodes' local centrality ranking. Results demonstrate the efficiency of the proposed centrality metrics.

Systemic Risk Analysis on Reconstructed Economic and Financial Networks

PubMed Central

Cimini, Giulio; Squartini, Tiziano; Garlaschelli, Diego; Gabrielli, Andrea

2015-01-01

We address a fundamental problem that is systematically encountered when modeling real-world complex systems of societal relevance: the limitedness of the information available. In the case of economic and financial networks, privacy issues severely limit the information that can be accessed and, as a consequence, the possibility of correctly estimating the resilience of these systems to events such as financial shocks, crises and cascade failures. Here we present an innovative method to reconstruct the structure of such partially-accessible systems, based on the knowledge of intrinsic node-specific properties and of the number of connections of only a limited subset of nodes. This information is used to calibrate an inference procedure based on fundamental concepts derived from statistical physics, which allows to generate ensembles of directed weighted networks intended to represent the real system—so that the real network properties can be estimated as their average values within the ensemble. We test the method both on synthetic and empirical networks, focusing on the properties that are commonly used to measure systemic risk. Indeed, the method shows a remarkable robustness with respect to the limitedness of the information available, thus representing a valuable tool for gaining insights on privacy-protected economic and financial systems. PMID:26507849

Improved image classification with neural networks by fusing multispectral signatures with topological data

NASA Technical Reports Server (NTRS)

Harston, Craig; Schumacher, Chris

1992-01-01

Automated schemes are needed to classify multispectral remotely sensed data. Human intelligence is often required to correctly interpret images from satellites and aircraft. Humans suceed because they use various types of cues about a scene to accurately define the contents of the image. Consequently, it follows that computer techniques that integrate and use different types of information would perform better than single source approaches. This research illustrated that multispectral signatures and topographical information could be used in concert. Significantly, this dual source tactic classified a remotely sensed image better than the multispectral classification alone. These classifications were accomplished by fusing spectral signatures with topographical information using neural network technology. A neural network was trained to classify Landsat mulitspectral signatures. A file of georeferenced ground truth classifications were used as the training criterion. The network was trained to classify urban, agriculture, range, and forest with an accuracy of 65.7 percent. Another neural network was programmed and trained to fuse these multispectral signature results with a file of georeferenced altitude data. This topological file contained 10 levels of elevations. When this nonspectral elevation information was fused with the spectral signatures, the classifications were improved to 73.7 and 75.7 percent.

Systemic Risk Analysis on Reconstructed Economic and Financial Networks

NASA Astrophysics Data System (ADS)

Cimini, Giulio; Squartini, Tiziano; Garlaschelli, Diego; Gabrielli, Andrea

2015-10-01

We address a fundamental problem that is systematically encountered when modeling real-world complex systems of societal relevance: the limitedness of the information available. In the case of economic and financial networks, privacy issues severely limit the information that can be accessed and, as a consequence, the possibility of correctly estimating the resilience of these systems to events such as financial shocks, crises and cascade failures. Here we present an innovative method to reconstruct the structure of such partially-accessible systems, based on the knowledge of intrinsic node-specific properties and of the number of connections of only a limited subset of nodes. This information is used to calibrate an inference procedure based on fundamental concepts derived from statistical physics, which allows to generate ensembles of directed weighted networks intended to represent the real system—so that the real network properties can be estimated as their average values within the ensemble. We test the method both on synthetic and empirical networks, focusing on the properties that are commonly used to measure systemic risk. Indeed, the method shows a remarkable robustness with respect to the limitedness of the information available, thus representing a valuable tool for gaining insights on privacy-protected economic and financial systems.

Structural and Network-based Methods for Knowledge-Based Systems

DTIC Science & Technology

2011-12-01

depth) provide important information about knowledge gaps in the KB. For example, if SuccessEstimate (causes-EventEvent, Typhoid - Fever , 1, 3) is...equal to 0, it points toward lack of biological knowledge about Typhoid - Fever in our KB. Similar information can also be obtained from the...position of the consequent. ⋃ ( ( ) ) Therefore, if Q does not contain Typhoid - Fever , then obtaining

The neural representation of social networks.

PubMed

Weaverdyck, Miriam E; Parkinson, Carolyn

2018-05-24

The computational demands associated with navigating large, complexly bonded social groups are thought to have significantly shaped human brain evolution. Yet, research on social network representation and cognitive neuroscience have progressed largely independently. Thus, little is known about how the human brain encodes the structure of the social networks in which it is embedded. This review highlights recent work seeking to bridge this gap in understanding. While the majority of research linking social network analysis and neuroimaging has focused on relating neuroanatomy to social network size, researchers have begun to define the neural architecture that encodes social network structure, cognitive and behavioral consequences of encoding this information, and individual differences in how people represent the structure of their social world. Copyright © 2018 Elsevier Ltd. All rights reserved.

Causal influence in neural systems: Reconciling mechanistic-reductionist and statistical perspectives. Comment on "Foundational perspectives on causality in large-scale brain networks" by M. Mannino & S.L. Bressler

NASA Astrophysics Data System (ADS)

Griffiths, John D.

2015-12-01

The modern understanding of the brain as a large, complex network of interacting elements is a natural consequence of the Neuron Doctrine [1,2] that has been bolstered in recent years by the tools and concepts of connectomics. In this abstracted, network-centric view, the essence of neural and cognitive function derives from the flows between network elements of activity and information - or, more generally, causal influence. The appropriate characterization of causality in neural systems, therefore, is a question at the very heart of systems neuroscience.

The hydraulic capacity of deteriorating sewer systems.

PubMed

Pollert, J; Ugarelli, R; Saegrov, S; Schilling, W; Di Federico, V

2005-01-01

Sewer and wastewater systems suffer from insufficient capacity, construction flaws and pipe deterioration. Consequences are structural failures, local floods, surface erosion and pollution of receiving waters bodies. European cities spend in the order of five billion Euro per year for wastewater network rehabilitation. This amount is estimated to increase due to network ageing. The project CARE-S (Computer Aided RE-habilitation of Sewer Networks) deals with sewer and storm water networks. The final project goal is to develop integrated software, which provides the most cost-efficient system of maintenance, repair and rehabilitation of sewer networks. Decisions on investments in rehabilitation often have to be made with uncertain information about the structural condition and the hydraulic performance of a sewer system. Because of this, decision-making involves considerable risks. This paper presents the results of research focused on the study of hydraulic effects caused by failures due to temporal decline of sewer systems. Hydraulic simulations are usually carried out by running commercial models that apply, as input, default values of parameters that strongly influence results. Using CCTV inspections information as dataset to catalogue principal types of failures affecting pipes, a 3D model was used to evaluate their hydraulic consequences. The translation of failures effects in parameters values producing the same hydraulic conditions caused by failures was carried out through the comparison of laboratory experiences and 3D simulations results. Those parameters could be the input of 1D commercial models instead of the default values commonly inserted.

Research to inform policy on headwater streams: ongoing and future directions

EPA Science Inventory

Headwater streams are the exterior links of stream networks and represent a substantial proportion of U.S. stream miles. Alteration and loss of headwater streams have occurred without an understanding of the potential consequences to larger downstream waterbodies. Recent court ca...

Knowledgeable Lemurs Become More Central in Social Networks.

PubMed

Kulahci, Ipek G; Ghazanfar, Asif A; Rubenstein, Daniel I

2018-04-23

Strong relationships exist between social connections and information transmission [1-9], where individuals' network position plays a key role in whether or not they acquire novel information [2, 3, 5, 6]. The relationships between social connections and information acquisition may be bidirectional if learning novel information, in addition to being influenced by it, influences network position. Individuals who acquire information quickly and use it frequently may receive more affiliative behaviors [10, 11] and may thus have a central network position. However, the potential influence of learning on network centrality has not been theoretically or empirically addressed. To bridge this epistemic gap, we investigated whether ring-tailed lemurs' (Lemur catta) centrality in affiliation networks changed after they learned how to solve a novel foraging task. Lemurs who had frequently initiated interactions and approached conspecifics before the learning experiment were more likely to observe and learn the task solution. Comparing social networks before and after the learning experiment revealed that the frequently observed lemurs received more affiliative behaviors than they did before-they became more central after the experiment. This change persisted even after the task was removed and was not caused by the observed lemurs initiating more affiliative behaviors. Consequently, quantifying received and initiated interactions separately provides unique insights into the relationships between learning and centrality. While the factors that influence network position are not fully understood, our results suggest that individual differences in learning and becoming successful can play a major role in social centrality, especially when learning from others is advantageous. Copyright © 2018 Elsevier Ltd. All rights reserved.

Multirate control with incomplete information over Profibus-DP network

NASA Astrophysics Data System (ADS)

Salt, J.; Casanova, V.; Cuenca, A.; Pizá, R.

2014-07-01

When a process field bus-decentralized peripherals (Profibus-DP) network is used in an industrial environment, a deterministic behaviour is usually claimed. However, due to some concerns such as bandwidth limitations, lack of synchronisation among different clocks and existence of time-varying delays, a more complex problem must be faced. This problem implies the transmission of irregular and, even, random sequences of incomplete information. The main consequence of this issue is the appearance of different sampling periods at different network devices. In this paper, this aspect is checked by means of a detailed Profibus-DP timescale study. In addition, in order to deal with the different periods, a delay-dependent dual-rate proportional-integral-derivative control is introduced. Stability for the proposed control system is analysed in terms of linear matrix inequalities.

Detecting Statistically Significant Communities of Triangle Motifs in Undirected Networks

DTIC Science & Technology

2015-03-16

moderately-sized networks. As a consequence, throughout this effort, a simulated annealing (SA) algorithm will be employed to effectively search the...then increment k by 1 and repeat the search to find z∗3. Once can continue to increment k until W < zδ, at which point the algorithm will stop and...collection of information is estimated to average 1 hour per response, including the time for reviewing instructions, searching existing data sources

Using social knowledge networking technology to enable meaningful use of electronic health record technology in hospitals and health systems.

PubMed

Rangachari, Pavani

2014-12-01

Despite the federal policy momentum towards "meaningful use" of Electronic Health Records, the healthcare organizational literature remains replete with reports of unintended adverse consequences of implementing Electronic Health Records, including: increased work for clinicians, unfavorable workflow changes, and unexpected changes in communication patterns & practices. In addition to being costly and unsafe, these unintended adverse consequences may pose a formidable barrier to "meaningful use" of Electronic Health Records. Correspondingly, it is essential for hospital administrators to understand and detect the causes of unintended adverse consequences, to ensure successful implementation of Electronic Health Records. The longstanding Technology-in-Practice framework emphasizes the role of human agency in enacting structures of technology use or "technologies-in-practice." Given a set of unintended adverse consequences from health information technology implementation, this framework could help trace them back to specific actions (types of technology-in-practice) and institutional conditions (social structures). On the other hand, the more recent Knowledge-in-Practice framework helps understand how information and communication technologies ( e.g. , social knowledge networking systems) could be implemented alongside existing technology systems, to create new social structures, generate new knowledge-in-practice, and transform technology-in-practice. Therefore, integrating the two literature streams could serve the dual purpose of understanding and overcoming unintended adverse consequences of Electronic Health Record implementation. This paper seeks to: (1) review the theoretical literatures on technology use & implementation, and identify a framework for understanding & overcoming unintended adverse consequences of implementing Electronic Health Records; (2) outline a broad project proposal to test the applicability of the framework in enabling "meaningful use" of Electronic Health Records in a healthcare context; and (3) identify strategies for successful implementation of Electronic Health Records in hospitals & health systems, based on the literature review and application.

Methodologies for assessing the use-phase power consumption and greenhouse gas emissions of telecommunications network services.

PubMed

Chan, Chien A; Gygax, André F; Wong, Elaine; Leckie, Christopher A; Nirmalathas, Ampalavanapillai; Kilper, Daniel C

2013-01-02

Internet traffic has grown rapidly in recent years and is expected to continue to expand significantly over the next decade. Consequently, the resulting greenhouse gas (GHG) emissions of telecommunications service-supporting infrastructures have become an important issue. In this study, we develop a set of models for assessing the use-phase power consumption and carbon dioxide emissions of telecom network services to help telecom providers gain a better understanding of the GHG emissions associated with the energy required for their networks and services. Due to the fact that measuring the power consumption and traffic in a telecom network is a challenging task, these models utilize different granularities of available network information. As the granularity of the network measurement information decreases, the corresponding models have the potential to produce larger estimation errors. Therefore, we examine the accuracy of these models under various network scenarios using two approaches: (i) a sensitivity analysis through simulations and (ii) a case study of a deployed network. Both approaches show that the accuracy of the models depends on the network size, the total amount of network service traffic (i.e., for the service under assessment), and the number of network nodes used to process the service.

The role of conflict minerals, artisanal mining, and informal trading networks in African intrastate and regional conflicts

USGS Publications Warehouse

Chirico, Peter G.; Malpeli, Katherine C.

2014-01-01

The relationship between natural resources and armed conflict gained public and political attention in the 1990s, when it became evident that the mining and trading of diamonds were connected with brutal rebellions in several African nations. Easily extracted resources such as alluvial diamonds and gold have been and continue to be exploited by rebel groups to fund their activities. Artisanal and small-scale miners operating under a quasi-legal status often mine these mineral deposits. While many African countries have legalized artisanal mining and established flow chains through which production is intended to travel, informal trading networks frequently emerge in which miners seek to evade taxes and fees by selling to unauthorized buyers. These networks have the potential to become international in scope, with actors operating in multiple countries. The lack of government control over the artisanal mining sector and the prominence of informal trade networks can have severe social, political, and economic consequences. In the past, mineral extraction fuelled violent civil wars in Sierra Leone, Liberia, and Angola, and it continues to do so today in several other countries. The significant influence of the informal network that surrounds artisanal mining is therefore an important security concern that can extend across borders and have far-reaching impacts.

Designing a Network and Systems Computing Curriculum: The Stakeholders and the Issues

ERIC Educational Resources Information Center

Tan, Grace; Venables, Anne

2010-01-01

Since 2001, there has been a dramatic decline in Information Technology and Computer Science student enrolments worldwide. As a consequence, many institutions have evaluated their offerings and revamped their programs to include units designed to capture students' interests and increase subsequent enrolment. Likewise, at Victoria University the…

Virtual Voices with Real-Life Consequences: Teaching Students about Cyber-Vetting

ERIC Educational Resources Information Center

Hanasono, Lisa Kiyomi

2013-01-01

Despite its pervasiveness, many students do not realize how online communication can impact their careers and relationships. Cyber-vetting occurs when people use online search engines, social networking sites, and other Internet tools to uncover information about others. Because cyber-vetting is a relatively new concept, most communication…

Spatial networks

NASA Astrophysics Data System (ADS)

Barthélemy, Marc

2011-02-01

Complex systems are very often organized under the form of networks where nodes and edges are embedded in space. Transportation and mobility networks, Internet, mobile phone networks, power grids, social and contact networks, and neural networks, are all examples where space is relevant and where topology alone does not contain all the information. Characterizing and understanding the structure and the evolution of spatial networks is thus crucial for many different fields, ranging from urbanism to epidemiology. An important consequence of space on networks is that there is a cost associated with the length of edges which in turn has dramatic effects on the topological structure of these networks. We will thoroughly explain the current state of our understanding of how the spatial constraints affect the structure and properties of these networks. We will review the most recent empirical observations and the most important models of spatial networks. We will also discuss various processes which take place on these spatial networks, such as phase transitions, random walks, synchronization, navigation, resilience, and disease spread.

A graph-based system for network-vulnerability analysis

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

Swiler, L.P.; Phillips, C.

1998-06-01

This paper presents a graph-based approach to network vulnerability analysis. The method is flexible, allowing analysis of attacks from both outside and inside the network. It can analyze risks to a specific network asset, or examine the universe of possible consequences following a successful attack. The graph-based tool can identify the set of attack paths that have a high probability of success (or a low effort cost) for the attacker. The system could be used to test the effectiveness of making configuration changes, implementing an intrusion detection system, etc. The analysis system requires as input a database of common attacks,more » broken into atomic steps, specific network configuration and topology information, and an attacker profile. The attack information is matched with the network configuration information and an attacker profile to create a superset attack graph. Nodes identify a stage of attack, for example the class of machines the attacker has accessed and the user privilege level he or she has compromised. The arcs in the attack graph represent attacks or stages of attacks. By assigning probabilities of success on the arcs or costs representing level-of-effort for the attacker, various graph algorithms such as shortest-path algorithms can identify the attack paths with the highest probability of success.« less

Indirect adaptive fuzzy wavelet neural network with self- recurrent consequent part for AC servo system.

PubMed

Hou, Runmin; Wang, Li; Gao, Qiang; Hou, Yuanglong; Wang, Chao

2017-09-01

This paper proposes a novel indirect adaptive fuzzy wavelet neural network (IAFWNN) to control the nonlinearity, wide variations in loads, time-variation and uncertain disturbance of the ac servo system. In the proposed approach, the self-recurrent wavelet neural network (SRWNN) is employed to construct an adaptive self-recurrent consequent part for each fuzzy rule of TSK fuzzy model. For the IAFWNN controller, the online learning algorithm is based on back propagation (BP) algorithm. Moreover, an improved particle swarm optimization (IPSO) is used to adapt the learning rate. The aid of an adaptive SRWNN identifier offers the real-time gradient information to the adaptive fuzzy wavelet neural controller to overcome the impact of parameter variations, load disturbances and other uncertainties effectively, and has a good dynamic. The asymptotical stability of the system is guaranteed by using the Lyapunov method. The result of the simulation and the prototype test prove that the proposed are effective and suitable. Copyright © 2017. Published by Elsevier Ltd.

Network information attacks on the control systems of power facilities belonging to the critical infrastructure

NASA Astrophysics Data System (ADS)

Loginov, E. L.; Raikov, A. N.

2015-04-01

The most large-scale accidents occurred as a consequence of network information attacks on the control systems of power facilities belonging to the United States' critical infrastructure are analyzed in the context of possibilities available in modern decision support systems. Trends in the development of technologies for inflicting damage to smart grids are formulated. A volume matrix of parameters characterizing attacks on facilities is constructed. A model describing the performance of a critical infrastructure's control system after an attack is developed. The recently adopted measures and legislation acts aimed at achieving more efficient protection of critical infrastructure are considered. Approaches to cognitive modeling and networked expertise of intricate situations for supporting the decision-making process, and to setting up a system of indicators for anticipatory monitoring of critical infrastructure are proposed.

Sharing sensitive personal health information through Facebook: the unintended consequences.

PubMed

Househ, Mowafa

2011-01-01

The purpose of this paper was to explore the types of sensitive health information posted by individuals through social network media sites such as Facebook. The researcher found several instances in which individuals, who could be identified by their user profiles, posted personal and sensitive health information related to mental and genetic disorders and sexually transmitted diseases. The data suggest that Facebook users should be made aware of the potential harm that may occur when sharing sensitive health information publicly through Facebook. Ethical considerations in undertaking such research are also examined.

Finding Influential Spreaders from Human Activity beyond Network Location.

PubMed

Min, Byungjoon; Liljeros, Fredrik; Makse, Hernán A

2015-01-01

Most centralities proposed for identifying influential spreaders on social networks to either spread a message or to stop an epidemic require the full topological information of the network on which spreading occurs. In practice, however, collecting all connections between agents in social networks can be hardly achieved. As a result, such metrics could be difficult to apply to real social networks. Consequently, a new approach for identifying influential people without the explicit network information is demanded in order to provide an efficient immunization or spreading strategy, in a practical sense. In this study, we seek a possible way for finding influential spreaders by using the social mechanisms of how social connections are formed in real networks. We find that a reliable immunization scheme can be achieved by asking people how they interact with each other. From these surveys we find that the probabilistic tendency to connect to a hub has the strongest predictive power for influential spreaders among tested social mechanisms. Our observation also suggests that people who connect different communities is more likely to be an influential spreader when a network has a strong modular structure. Our finding implies that not only the effect of network location but also the behavior of individuals is important to design optimal immunization or spreading schemes.

Learning to Predict Consequences as a Method of Knowledge Transfer in Reinforcement Learning.

PubMed

Chalmers, Eric; Contreras, Edgar Bermudez; Robertson, Brandon; Luczak, Artur; Gruber, Aaron

2017-04-17

The reinforcement learning (RL) paradigm allows agents to solve tasks through trial-and-error learning. To be capable of efficient, long-term learning, RL agents should be able to apply knowledge gained in the past to new tasks they may encounter in the future. The ability to predict actions' consequences may facilitate such knowledge transfer. We consider here domains where an RL agent has access to two kinds of information: agent-centric information with constant semantics across tasks, and environment-centric information, which is necessary to solve the task, but with semantics that differ between tasks. For example, in robot navigation, environment-centric information may include the robot's geographic location, while agent-centric information may include sensor readings of various nearby obstacles. We propose that these situations provide an opportunity for a very natural style of knowledge transfer, in which the agent learns to predict actions' environmental consequences using agent-centric information. These predictions contain important information about the affordances and dangers present in a novel environment, and can effectively transfer knowledge from agent-centric to environment-centric learning systems. Using several example problems including spatial navigation and network routing, we show that our knowledge transfer approach can allow faster and lower cost learning than existing alternatives.

The Complexity of Crime Network Data: A Case Study of Its Consequences for Crime Control and the Study of Networks

PubMed Central

Rostami, Amir; Mondani, Hernan

2015-01-01

The field of social network analysis has received increasing attention during the past decades and has been used to tackle a variety of research questions, from prevention of sexually transmitted diseases to humanitarian relief operations. In particular, social network analyses are becoming an important component in studies of criminal networks and in criminal intelligence analysis. At the same time, intelligence analyses and assessments have become a vital component of modern approaches in policing, with policy implications for crime prevention, especially in the fight against organized crime. In this study, we have a unique opportunity to examine one specific Swedish street gang with three different datasets. These datasets are the most common information sources in studies of criminal networks: intelligence, surveillance and co-offending data. We use the data sources to build networks, and compare them by computing distance, centrality, and clustering measures. This study shows the complexity factor by which different data sources about the same object of study have a fundamental impact on the results. The same individuals have different importance ranking depending on the dataset and measure. Consequently, the data source plays a vital role in grasping the complexity of the phenomenon under study. Researchers, policy makers, and practitioners should therefore pay greater attention to the biases affecting the sources of the analysis, and be cautious when drawing conclusions based on intelligence assessments and limited network data. This study contributes to strengthening social network analysis as a reliable tool for understanding and analyzing criminality and criminal networks. PMID:25775130

The complexity of crime network data: a case study of its consequences for crime control and the study of networks.

PubMed

Rostami, Amir; Mondani, Hernan

2015-01-01

The field of social network analysis has received increasing attention during the past decades and has been used to tackle a variety of research questions, from prevention of sexually transmitted diseases to humanitarian relief operations. In particular, social network analyses are becoming an important component in studies of criminal networks and in criminal intelligence analysis. At the same time, intelligence analyses and assessments have become a vital component of modern approaches in policing, with policy implications for crime prevention, especially in the fight against organized crime. In this study, we have a unique opportunity to examine one specific Swedish street gang with three different datasets. These datasets are the most common information sources in studies of criminal networks: intelligence, surveillance and co-offending data. We use the data sources to build networks, and compare them by computing distance, centrality, and clustering measures. This study shows the complexity factor by which different data sources about the same object of study have a fundamental impact on the results. The same individuals have different importance ranking depending on the dataset and measure. Consequently, the data source plays a vital role in grasping the complexity of the phenomenon under study. Researchers, policy makers, and practitioners should therefore pay greater attention to the biases affecting the sources of the analysis, and be cautious when drawing conclusions based on intelligence assessments and limited network data. This study contributes to strengthening social network analysis as a reliable tool for understanding and analyzing criminality and criminal networks.

A Heuristic Decision Making Model to Mitigate Adverse Consequences in a Network Centric Warfare/Sense and Respond System

DTIC Science & Technology

2005-05-01

made. 4. Do military decision makers identify / analyze adverse consequences presently? Few do based on this research and most don’t do it effectively ...A HEURISTIC DECISION MAKING MODEL TO MITIGATE ADVERSE CONSEQUENCES IN A NETWORK CENTRIC WARFARE / SENSE AND RESPOND SYSTEM...ENS/05-01 A HEURISTIC DECISION MAKING MODEL TO MITIGATE ADVERSE CONSEQUENCES IN A NETWORK CENTRIC WARFARE / SENSE AND RESPOND SYSTEM

A Bayesian network to predict vulnerability to sea-level rise: data report

USGS Publications Warehouse

Gutierrez, Benjamin T.; Plant, Nathaniel G.; Thieler, E. Robert

2011-01-01

During the 21st century, sea-level rise is projected to have a wide range of effects on coastal environments, development, and infrastructure. Consequently, there has been an increased focus on developing modeling or other analytical approaches to evaluate potential impacts to inform coastal management. This report provides the data that were used to develop and evaluate the performance of a Bayesian network designed to predict long-term shoreline change due to sea-level rise. The data include local rates of relative sea-level rise, wave height, tide range, geomorphic classification, coastal slope, and shoreline-change rate compiled as part of the U.S. Geological Survey Coastal Vulnerability Index for the U.S. Atlantic coast. In this project, the Bayesian network is used to define relationships among driving forces, geologic constraints, and coastal responses. Using this information, the Bayesian network is used to make probabilistic predictions of shoreline change in response to different future sea-level-rise scenarios.

Community Size Effects on Epidemic Spreading in Multiplex Social Networks.

PubMed

Liu, Ting; Li, Ping; Chen, Yan; Zhang, Jie

2016-01-01

The dynamical process of epidemic spreading has drawn much attention of the complex network community. In the network paradigm, diseases spread from one person to another through the social ties amongst the population. There are a variety of factors that govern the processes of disease spreading on the networks. A common but not negligible factor is people's reaction to the outbreak of epidemics. Such reaction can be related information dissemination or self-protection. In this work, we explore the interactions between disease spreading and population response in terms of information diffusion and individuals' alertness. We model the system by mapping multiplex networks into two-layer networks and incorporating individuals' risk awareness, on the assumption that their response to the disease spreading depends on the size of the community they belong to. By comparing the final incidence of diseases in multiplex networks, we find that there is considerable mitigation of diseases spreading for full phase of spreading speed when individuals' protection responses are introduced. Interestingly, the degree of community overlap between the two layers is found to be critical factor that affects the final incidence. We also analyze the consequences of the epidemic incidence in communities with different sizes and the impacts of community overlap between two layers. Specifically, as the diseases information makes individuals alert and take measures to prevent the diseases, the effective protection is more striking in small community. These phenomena can be explained by the multiplexity of the networked system and the competition between two spreading processes.

Community Size Effects on Epidemic Spreading in Multiplex Social Networks

PubMed Central

Liu, Ting; Li, Ping; Chen, Yan; Zhang, Jie

2016-01-01

The dynamical process of epidemic spreading has drawn much attention of the complex network community. In the network paradigm, diseases spread from one person to another through the social ties amongst the population. There are a variety of factors that govern the processes of disease spreading on the networks. A common but not negligible factor is people’s reaction to the outbreak of epidemics. Such reaction can be related information dissemination or self-protection. In this work, we explore the interactions between disease spreading and population response in terms of information diffusion and individuals’ alertness. We model the system by mapping multiplex networks into two-layer networks and incorporating individuals’ risk awareness, on the assumption that their response to the disease spreading depends on the size of the community they belong to. By comparing the final incidence of diseases in multiplex networks, we find that there is considerable mitigation of diseases spreading for full phase of spreading speed when individuals’ protection responses are introduced. Interestingly, the degree of community overlap between the two layers is found to be critical factor that affects the final incidence. We also analyze the consequences of the epidemic incidence in communities with different sizes and the impacts of community overlap between two layers. Specifically, as the diseases information makes individuals alert and take measures to prevent the diseases, the effective protection is more striking in small community. These phenomena can be explained by the multiplexity of the networked system and the competition between two spreading processes. PMID:27007112

An Approach to Automated Fusion System Design and Adaptation

PubMed Central

Fritze, Alexander; Mönks, Uwe; Holst, Christoph-Alexander; Lohweg, Volker

2017-01-01

Industrial applications are in transition towards modular and flexible architectures that are capable of self-configuration and -optimisation. This is due to the demand of mass customisation and the increasing complexity of industrial systems. The conversion to modular systems is related to challenges in all disciplines. Consequently, diverse tasks such as information processing, extensive networking, or system monitoring using sensor and information fusion systems need to be reconsidered. The focus of this contribution is on distributed sensor and information fusion systems for system monitoring, which must reflect the increasing flexibility of fusion systems. This contribution thus proposes an approach, which relies on a network of self-descriptive intelligent sensor nodes, for the automatic design and update of sensor and information fusion systems. This article encompasses the fusion system configuration and adaptation as well as communication aspects. Manual interaction with the flexibly changing system is reduced to a minimum. PMID:28300762

An Approach to Automated Fusion System Design and Adaptation.

PubMed

Fritze, Alexander; Mönks, Uwe; Holst, Christoph-Alexander; Lohweg, Volker

2017-03-16

Industrial applications are in transition towards modular and flexible architectures that are capable of self-configuration and -optimisation. This is due to the demand of mass customisation and the increasing complexity of industrial systems. The conversion to modular systems is related to challenges in all disciplines. Consequently, diverse tasks such as information processing, extensive networking, or system monitoring using sensor and information fusion systems need to be reconsidered. The focus of this contribution is on distributed sensor and information fusion systems for system monitoring, which must reflect the increasing flexibility of fusion systems. This contribution thus proposes an approach, which relies on a network of self-descriptive intelligent sensor nodes, for the automatic design and update of sensor and information fusion systems. This article encompasses the fusion system configuration and adaptation as well as communication aspects. Manual interaction with the flexibly changing system is reduced to a minimum.

Searching for superspreaders of information in real-world social media.

PubMed

Pei, Sen; Muchnik, Lev; Andrade, José S; Zheng, Zhiming; Makse, Hernán A

2014-07-03

A number of predictors have been suggested to detect the most influential spreaders of information in online social media across various domains such as Twitter or Facebook. In particular, degree, PageRank, k-core and other centralities have been adopted to rank the spreading capability of users in information dissemination media. So far, validation of the proposed predictors has been done by simulating the spreading dynamics rather than following real information flow in social networks. Consequently, only model-dependent contradictory results have been achieved so far for the best predictor. Here, we address this issue directly. We search for influential spreaders by following the real spreading dynamics in a wide range of networks. We find that the widely-used degree and PageRank fail in ranking users' influence. We find that the best spreaders are consistently located in the k-core across dissimilar social platforms such as Twitter, Facebook, Livejournal and scientific publishing in the American Physical Society. Furthermore, when the complete global network structure is unavailable, we find that the sum of the nearest neighbors' degree is a reliable local proxy for user's influence. Our analysis provides practical instructions for optimal design of strategies for "viral" information dissemination in relevant applications.

Searching for superspreaders of information in real-world social media

NASA Astrophysics Data System (ADS)

Pei, Sen; Muchnik, Lev; Andrade, José S., Jr.; Zheng, Zhiming; Makse, Hernán A.

2014-07-01

A number of predictors have been suggested to detect the most influential spreaders of information in online social media across various domains such as Twitter or Facebook. In particular, degree, PageRank, k-core and other centralities have been adopted to rank the spreading capability of users in information dissemination media. So far, validation of the proposed predictors has been done by simulating the spreading dynamics rather than following real information flow in social networks. Consequently, only model-dependent contradictory results have been achieved so far for the best predictor. Here, we address this issue directly. We search for influential spreaders by following the real spreading dynamics in a wide range of networks. We find that the widely-used degree and PageRank fail in ranking users' influence. We find that the best spreaders are consistently located in the k-core across dissimilar social platforms such as Twitter, Facebook, Livejournal and scientific publishing in the American Physical Society. Furthermore, when the complete global network structure is unavailable, we find that the sum of the nearest neighbors' degree is a reliable local proxy for user's influence. Our analysis provides practical instructions for optimal design of strategies for ``viral'' information dissemination in relevant applications.

Searching for superspreaders of information in real-world social media

PubMed Central

Pei, Sen; Muchnik, Lev; Andrade, Jr., José S.; Zheng, Zhiming; Makse, Hernán A.

2014-01-01

A number of predictors have been suggested to detect the most influential spreaders of information in online social media across various domains such as Twitter or Facebook. In particular, degree, PageRank, k-core and other centralities have been adopted to rank the spreading capability of users in information dissemination media. So far, validation of the proposed predictors has been done by simulating the spreading dynamics rather than following real information flow in social networks. Consequently, only model-dependent contradictory results have been achieved so far for the best predictor. Here, we address this issue directly. We search for influential spreaders by following the real spreading dynamics in a wide range of networks. We find that the widely-used degree and PageRank fail in ranking users' influence. We find that the best spreaders are consistently located in the k-core across dissimilar social platforms such as Twitter, Facebook, Livejournal and scientific publishing in the American Physical Society. Furthermore, when the complete global network structure is unavailable, we find that the sum of the nearest neighbors' degree is a reliable local proxy for user's influence. Our analysis provides practical instructions for optimal design of strategies for “viral” information dissemination in relevant applications. PMID:24989148

The Emergence of Selective Attention through Probabilistic Associations between Stimuli and Actions.

PubMed

Simione, Luca; Nolfi, Stefano

2016-01-01

In this paper we show how a multilayer neural network trained to master a context-dependent task in which the action co-varies with a certain stimulus in a first context and with a second stimulus in an alternative context exhibits selective attention, i.e. filtering out of irrelevant information. This effect is rather robust and it is observed in several variations of the experiment in which the characteristics of the network as well as of the training procedure have been varied. Our result demonstrates how the filtering out of irrelevant information can originate spontaneously as a consequence of the regularities present in context-dependent training set and therefore does not necessarily depend on specific architectural constraints. The post-evaluation of the network in an instructed-delay experimental scenario shows how the behaviour of the network is consistent with the data collected in neuropsychological studies. The analysis of the network at the end of the training process indicates how selective attention originates as a result of the effects caused by relevant and irrelevant stimuli mediated by context-dependent and context-independent bidirectional associations between stimuli and actions that are extracted by the network during the learning.

Optimizing Energy Consumption in Vehicular Sensor Networks by Clustering Using Fuzzy C-Means and Fuzzy Subtractive Algorithms

NASA Astrophysics Data System (ADS)

Ebrahimi, A.; Pahlavani, P.; Masoumi, Z.

2017-09-01

Traffic monitoring and managing in urban intelligent transportation systems (ITS) can be carried out based on vehicular sensor networks. In a vehicular sensor network, vehicles equipped with sensors such as GPS, can act as mobile sensors for sensing the urban traffic and sending the reports to a traffic monitoring center (TMC) for traffic estimation. The energy consumption by the sensor nodes is a main problem in the wireless sensor networks (WSNs); moreover, it is the most important feature in designing these networks. Clustering the sensor nodes is considered as an effective solution to reduce the energy consumption of WSNs. Each cluster should have a Cluster Head (CH), and a number of nodes located within its supervision area. The cluster heads are responsible for gathering and aggregating the information of clusters. Then, it transmits the information to the data collection center. Hence, the use of clustering decreases the volume of transmitting information, and, consequently, reduces the energy consumption of network. In this paper, Fuzzy C-Means (FCM) and Fuzzy Subtractive algorithms are employed to cluster sensors and investigate their performance on the energy consumption of sensors. It can be seen that the FCM algorithm and Fuzzy Subtractive have been reduced energy consumption of vehicle sensors up to 90.68% and 92.18%, respectively. Comparing the performance of the algorithms implies the 1.5 percent improvement in Fuzzy Subtractive algorithm in comparison.

Value of information analysis for groundwater quality monitoring network design Case study: Eocene Aquifer, Palestine

NASA Astrophysics Data System (ADS)

Khader, A.; McKee, M.

2010-12-01

Value of information (VOI) analysis evaluates the benefit of collecting additional information to reduce or eliminate uncertainty in a specific decision-making context. It makes explicit any expected potential losses from errors in decision making due to uncertainty and identifies the “best” information collection strategy as one that leads to the greatest expected net benefit to the decision-maker. This study investigates the willingness to pay for groundwater quality monitoring in the Eocene Aquifer, Palestine, which is an unconfined aquifer located in the northern part of the West Bank. The aquifer is being used by 128,000 Palestinians to fulfill domestic and agricultural demands. The study takes into account the consequences of pollution and the options the decision maker might face. Since nitrate is the major pollutant in the aquifer, the consequences of nitrate pollution were analyzed, which mainly consists of the possibility of methemoglobinemia (blue baby syndrome). In this case, the value of monitoring was compared to the costs of treating for methemoglobinemia or the costs of other options like water treatment, using bottled water or importing water from outside the aquifer. And finally, an optimal monitoring network that takes into account the uncertainties in recharge (climate), aquifer properties (hydraulic conductivity), pollutant chemical reaction (decay factor), and the value of monitoring is designed by utilizing a sparse Bayesian modeling algorithm called a relevance vector machine.

The Strength of the Strongest Ties in Collaborative Problem Solving

NASA Astrophysics Data System (ADS)

de Montjoye, Yves-Alexandre; Stopczynski, Arkadiusz; Shmueli, Erez; Pentland, Alex; Lehmann, Sune

2014-06-01

Complex problem solving in science, engineering, and business has become a highly collaborative endeavor. Teams of scientists or engineers collaborate on projects using their social networks to gather new ideas and feedback. Here we bridge the literature on team performance and information networks by studying teams' problem solving abilities as a function of both their within-team networks and their members' extended networks. We show that, while an assigned team's performance is strongly correlated with its networks of expressive and instrumental ties, only the strongest ties in both networks have an effect on performance. Both networks of strong ties explain more of the variance than other factors, such as measured or self-evaluated technical competencies, or the personalities of the team members. In fact, the inclusion of the network of strong ties renders these factors non-significant in the statistical analysis. Our results have consequences for the organization of teams of scientists, engineers, and other knowledge workers tackling today's most complex problems.

The strength of the strongest ties in collaborative problem solving.

PubMed

de Montjoye, Yves-Alexandre; Stopczynski, Arkadiusz; Shmueli, Erez; Pentland, Alex; Lehmann, Sune

2014-06-20

Complex problem solving in science, engineering, and business has become a highly collaborative endeavor. Teams of scientists or engineers collaborate on projects using their social networks to gather new ideas and feedback. Here we bridge the literature on team performance and information networks by studying teams' problem solving abilities as a function of both their within-team networks and their members' extended networks. We show that, while an assigned team's performance is strongly correlated with its networks of expressive and instrumental ties, only the strongest ties in both networks have an effect on performance. Both networks of strong ties explain more of the variance than other factors, such as measured or self-evaluated technical competencies, or the personalities of the team members. In fact, the inclusion of the network of strong ties renders these factors non-significant in the statistical analysis. Our results have consequences for the organization of teams of scientists, engineers, and other knowledge workers tackling today's most complex problems.

Gender and socio-economic inequalities in health and living conditions among co-resident informal caregivers: a nationwide survey in Spain.

PubMed

Abajo, María; Rodríguez-Sanz, Maica; Malmusi, Davide; Salvador, María; Borrell, Carme

2017-03-01

To explore the associations between social determinants, caregiver's network support, burden of care and their consequences in health and living conditions of informal caregivers. The socio-demographic trends regarding population ageing and changes in family models trigger an increased demand for care. Cross-sectional study based on the 2008 edition of the National Disability, Independence and Dependency Situations Survey (DIDSS-2008) conducted by the National Statistics Institute in Spain. Analyses focused on persons identified as primary caregivers who co-reside with the dependent person. The associations between social determinants of caregivers, burden of care, support network and problems attributed to informal care (impaired health, depression, professional, economic and personal issues) were estimated by fitting robust Poisson regression models. Analyses were conducted separately for women and men. The study sample included 6923 caregivers, 73% of women and 27% of men. Gender and socio-economic inequalities were found in assumption of responsibilities and burden of caring for dependents, which tend to fall more on women and persons of lower socio-economic level, who in turn have less access to formal support. These aspects translate into a higher prevalence of health, professional, economic and personal problems. The study highlights gender and socio-economic inequalities in informal caregiving and its negative consequences. These findings may be useful in the design of policies and support programmes targeting the most affected groups of informal caregivers. © 2016 John Wiley & Sons Ltd.

Job Search Methods: Consequences for Gender-based Earnings Inequality.

ERIC Educational Resources Information Center

Huffman, Matt L.; Torres, Lisa

2001-01-01

Data from adults in Atlanta, Boston, and Los Angeles (n=1,942) who searched for work using formal (ads, agencies) or informal (networks) methods indicated that type of method used did not contribute to the gender gap in earnings. Results do not support formal job search as a way to reduce gender inequality. (Contains 55 references.) (SK)

The Network Structure of Symptoms of the Diagnostic and Statistical Manual of Mental Disorders.

PubMed

Boschloo, Lynn; van Borkulo, Claudia D; Rhemtulla, Mijke; Keyes, Katherine M; Borsboom, Denny; Schoevers, Robert A

2015-01-01

Although current classification systems have greatly contributed to the reliability of psychiatric diagnoses, they ignore the unique role of individual symptoms and, consequently, potentially important information is lost. The network approach, in contrast, assumes that psychopathology results from the causal interplay between psychiatric symptoms and focuses specifically on these symptoms and their complex associations. By using a sophisticated network analysis technique, this study constructed an empirically based network structure of 120 psychiatric symptoms of twelve major DSM-IV diagnoses using cross-sectional data of the National Epidemiologic Survey on Alcohol and Related Conditions (NESARC, second wave; N = 34,653). The resulting network demonstrated that symptoms within the same diagnosis showed differential associations and indicated that the strategy of summing symptoms, as in current classification systems, leads to loss of information. In addition, some symptoms showed strong connections with symptoms of other diagnoses, and these specific symptom pairs, which both concerned overlapping and non-overlapping symptoms, may help to explain the comorbidity across diagnoses. Taken together, our findings indicated that psychopathology is very complex and can be more adequately captured by sophisticated network models than current classification systems. The network approach is, therefore, promising in improving our understanding of psychopathology and moving our field forward.

Modeling the influence of information on the coevolution of contact networks and the dynamics of infectious diseases

NASA Astrophysics Data System (ADS)

Zhang, Haifeng; Small, Michael; Fu, Xinchu; Sun, Guiquan; Wang, Binghong

2012-09-01

Outbreaks of infectious diseases may awaken the awareness of individuals, consequently, they may adjust their contact patterns according to the perceived risk from disease. In this paper, we assume that individuals make decisions on breaking or recovering links according to the information of diseases spreading which they have acquired. They will reduce some links when diseases are prevalent and have high risks; otherwise, they will recover some original links when the diseases are controlled or present minimal risk. Under such an assumption, we study the effects of information of diseases on the contact patterns within the population and on the dynamics of epidemics. By extensive simulations and theoretical analysis, we find that, due to the time-delayed information of diseases, both the density of the disease and the topology of the network vary with time in a periodic form. Our results indicate that the quality of information available to individuals can have an important effect on the spreading of infectious diseases and implications for related problems.

Risk analysis of urban gas pipeline network based on improved bow-tie model

NASA Astrophysics Data System (ADS)

Hao, M. J.; You, Q. J.; Yue, Z.

2017-11-01

Gas pipeline network is a major hazard source in urban areas. In the event of an accident, there could be grave consequences. In order to understand more clearly the causes and consequences of gas pipeline network accidents, and to develop prevention and mitigation measures, the author puts forward the application of improved bow-tie model to analyze risks of urban gas pipeline network. The improved bow-tie model analyzes accident causes from four aspects: human, materials, environment and management; it also analyzes the consequences from four aspects: casualty, property loss, environment and society. Then it quantifies the causes and consequences. Risk identification, risk analysis, risk assessment, risk control, and risk management will be clearly shown in the model figures. Then it can suggest prevention and mitigation measures accordingly to help reduce accident rate of gas pipeline network. The results show that the whole process of an accident can be visually investigated using the bow-tie model. It can also provide reasons for and predict consequences of an unfortunate event. It is of great significance in order to analyze leakage failure of gas pipeline network.

Infant Joint Attention, Neural Networks and Social Cognition

PubMed Central

Mundy, Peter; Jarrold, William

2010-01-01

Neural network models of attention can provide a unifying approach to the study of human cognitive and emotional development (Posner & Rothbart, 2007). This paper we argue that a neural networks approach to the infant development of joint attention can inform our understanding of the nature of human social learning, symbolic thought process and social cognition. At its most basic, joint attention involves the capacity to coordinate one’s own visual attention with that of another person. We propose that joint attention development involves increments in the capacity to engage in simultaneous or parallel processing of information about one’s own attention and the attention of other people. Infant practice with joint attention is both a consequence and organizer of the development of a distributed and integrated brain network involving frontal and parietal cortical systems. This executive distributed network first serves to regulate the capacity of infants to respond to and direct the overt behavior of other people in order to share experience with others through the social coordination of visual attention. In this paper we describe this parallel and distributed neural network model of joint attention development and discuss two hypotheses that stem from this model. One is that activation of this distributed network during coordinated attention enhances to depth of information processing and encoding beginning in the first year of life. We also propose that with development joint attention becomes internalized as the capacity to socially coordinate mental attention to internal representations. As this occurs the executive joint attention network makes vital contributions to the development of human symbolic thinking and social cognition. PMID:20884172

Uncertainty Quantification of Hypothesis Testing for the Integrated Knowledge Engine

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

Cuellar, Leticia

2012-05-31

The Integrated Knowledge Engine (IKE) is a tool of Bayesian analysis, based on Bayesian Belief Networks or Bayesian networks for short. A Bayesian network is a graphical model (directed acyclic graph) that allows representing the probabilistic structure of many variables assuming a localized type of dependency called the Markov property. The Markov property in this instance makes any node or random variable to be independent of any non-descendant node given information about its parent. A direct consequence of this property is that it is relatively easy to incorporate new evidence and derive the appropriate consequences, which in general is notmore » an easy or feasible task. Typically we use Bayesian networks as predictive models for a small subset of the variables, either the leave nodes or the root nodes. In IKE, since most applications deal with diagnostics, we are interested in predicting the likelihood of the root nodes given new observations on any of the children nodes. The root nodes represent the various possible outcomes of the analysis, and an important problem is to determine when we have gathered enough evidence to lean toward one of these particular outcomes. This document presents criteria to decide when the evidence gathered is sufficient to draw a particular conclusion or decide in favor of a particular outcome by quantifying the uncertainty in the conclusions that are drawn from the data. The material in this document is organized as follows: Section 2 presents briefly a forensics Bayesian network, and we explore evaluating the information provided by new evidence by looking first at the posterior distribution of the nodes of interest, and then at the corresponding posterior odds ratios. Section 3 presents a third alternative: Bayes Factors. In section 4 we finalize by showing the relation between the posterior odds ratios and Bayes factors and showing examples these cases, and in section 5 we conclude by providing clear guidelines of how to use these for the type of Bayesian networks used in IKE.« less

Social influence and bullying behavior: intervention-based network dynamics of the fairplayer.manual bullying prevention program.

PubMed

Wölfer, Ralf; Scheithauer, Herbert

2014-01-01

Bullying is a social phenomenon and although preventive interventions consequently address social mechanisms, evaluations hardly consider the complexity of peer processes. Therefore, the present study analyzes the efficacy of the fairplayer.manual bullying prevention program from a social network perspective. Within a pretest-posttest control group design, longitudinal data were available from 328 middle-school students (MAge  = 13.7 years; 51% girls), who provided information on bullying behavior and interaction patterns. The revealed network parameters were utilized to examine the network change (MANCOVA) and the network dynamics (SIENA). Across both forms of analyses, findings revealed the hypothesized intervention-based decrease of bullies' social influence. Hence the present bullying prevention program, as one example of programs that successfully addresses both individual skills and social mechanisms, demonstrates the desired effect of reducing contextual opportunities for the exhibition of bullying behavior. © 2014 Wiley Periodicals, Inc.

Energy coding in biological neural networks

PubMed Central

Zhang, Zhikang

2007-01-01

According to the experimental result of signal transmission and neuronal energetic demands being tightly coupled to information coding in the cerebral cortex, we present a brand new scientific theory that offers an unique mechanism for brain information processing. We demonstrate that the neural coding produced by the activity of the brain is well described by our theory of energy coding. Due to the energy coding model’s ability to reveal mechanisms of brain information processing based upon known biophysical properties, we can not only reproduce various experimental results of neuro-electrophysiology, but also quantitatively explain the recent experimental results from neuroscientists at Yale University by means of the principle of energy coding. Due to the theory of energy coding to bridge the gap between functional connections within a biological neural network and energetic consumption, we estimate that the theory has very important consequences for quantitative research of cognitive function. PMID:19003513

Resilience in the face of post-election violence in Kenya: the mediating role of social networks on wellbeing among older people in the Korogocho informal settlement, Nairobi.

PubMed

Bennett, Rachel; Chepngeno-Langat, Gloria; Evandrou, Maria; Falkingham, Jane

2015-03-01

Older people in slum settings are a vulnerable sub-group during crises, yet have received minimal attention in the development discourse. This paper examines the protective role of different types of social networks for older slum dwellers' wellbeing during adversity by investigating the relationship between social networks, the Kenyan 2007/08 post-election violence, and dimensions of wellbeing namely self-rated health, life satisfaction and happiness amongst older people in the Korogocho slum, Nairobi. The analyses are based on conditional change logistic regression models using data from a unique longitudinal survey of the health and wellbeing of older people. The results show that maintaining or increasing formal local networks reduced the detrimental effects of the post-election violence for older people's wellbeing, whilst household environment and informal local and non-local networks did not influence the relationship. Consequently, the paper provides evidence that supporting inclusive community organisations which are accessible to older people can be valuable in promoting the resilience of this population group. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

Educational Innovation in the United States. Volume 1: The National Survey: The Substance and the Process.

ERIC Educational Resources Information Center

Havelock, Ronald G.; And Others

This document reports on a project undertaken to determine the feasibility of a periodic national survey of a sample of U.S. school districts to obtain information on the performance of the existing dissemination and utilization network for educational innovations. The first section of volume 1 describes the content and consequences of innovation,…

The Laureate English Program: Taking a Research Informed Approach to Blended Learning

ERIC Educational Resources Information Center

Johnson, Christopher; Marsh, Debra

2013-01-01

The aim of this case study is to describe the implementation of the Laureate English Program (LEP), the consequent decision to roll out blended learning across the network, and the Laureate-Cambridge University Press research partnership. Phase 1 of the research was completed in September 2012. The goal of this first phase was to gain a general…

Cyberbullying and Academic Achievement: Research into the Rates of Incidence, Knowledge of Consequences, and Behavioral Patterns of Cyberbullying

ERIC Educational Resources Information Center

Mitchell, Melissa Sue

2011-01-01

Cyberbullying takes place through the information technology that students access every day: cell phones, text messages, email, Internet messaging, social networks, pictures, and video clips. With the world paying more attention to this new form of bullying, scholars have been researching the topic in an attempt to learn more about this…

A user exposure based approach for non-structural road network vulnerability analysis

PubMed Central

Jin, Lei; Wang, Haizhong; Yu, Le; Liu, Lin

2017-01-01

Aiming at the dense urban road network vulnerability without structural negative consequences, this paper proposes a novel non-structural road network vulnerability analysis framework. Three aspects of the framework are mainly described: (i) the rationality of non-structural road network vulnerability, (ii) the metrics for negative consequences accounting for variant road conditions, and (iii) the introduction of a new vulnerability index based on user exposure. Based on the proposed methodology, a case study in the Sioux Falls network which was usually threatened by regular heavy snow during wintertime is detailedly discussed. The vulnerability ranking of links of Sioux Falls network with respect to heavy snow scenario is identified. As a result of non-structural consequences accompanied by conceivable degeneration of network, there are significant increases in generalized travel time costs which are measurements for “emotionally hurt” of topological road network. PMID:29176832

Dissociable meta-analytic brain networks contribute to coordinated emotional processing.

PubMed

Riedel, Michael C; Yanes, Julio A; Ray, Kimberly L; Eickhoff, Simon B; Fox, Peter T; Sutherland, Matthew T; Laird, Angela R

2018-06-01

Meta-analytic techniques for mining the neuroimaging literature continue to exert an impact on our conceptualization of functional brain networks contributing to human emotion and cognition. Traditional theories regarding the neurobiological substrates contributing to affective processing are shifting from regional- towards more network-based heuristic frameworks. To elucidate differential brain network involvement linked to distinct aspects of emotion processing, we applied an emergent meta-analytic clustering approach to the extensive body of affective neuroimaging results archived in the BrainMap database. Specifically, we performed hierarchical clustering on the modeled activation maps from 1,747 experiments in the affective processing domain, resulting in five meta-analytic groupings of experiments demonstrating whole-brain recruitment. Behavioral inference analyses conducted for each of these groupings suggested dissociable networks supporting: (1) visual perception within primary and associative visual cortices, (2) auditory perception within primary auditory cortices, (3) attention to emotionally salient information within insular, anterior cingulate, and subcortical regions, (4) appraisal and prediction of emotional events within medial prefrontal and posterior cingulate cortices, and (5) induction of emotional responses within amygdala and fusiform gyri. These meta-analytic outcomes are consistent with a contemporary psychological model of affective processing in which emotionally salient information from perceived stimuli are integrated with previous experiences to engender a subjective affective response. This study highlights the utility of using emergent meta-analytic methods to inform and extend psychological theories and suggests that emotions are manifest as the eventual consequence of interactions between large-scale brain networks. © 2018 Wiley Periodicals, Inc.

Globalisation and human dignity: the case of the information superhighway.

PubMed

Hamelink, C J

1996-01-01

In 1994, Vice President Al Gore coined the concept of the Information Superhighway during a speech in Buenos Aires in which he proposed the development of a global information infrastructure. The project envisions the incorporation of all existing communication networks into one system, facilitating the globalization of markets. The internet, a decentralized network of computer networks, is one small-scale, existing model of what the superhighway could be, a public space owned by nobody in which communication takes place largely for noncommercial purposes. The internet currently connects 40 million computer users from at least 90 countries. The alternative model for the superhighway is the privately managed global shopping mall, a global interactive marketplace for information, entertainment, and advertising. The author warns, however, that it is not possible to predict the future social impact of such an information superhighway. Decision makers nonetheless push ahead in development, full of confidence in the merit and infallibility of technology. Since one cannot accurately predict the future, it rational to assume that social consequences may both promote and threaten human dignity. The author explains at which level he believes the superhighway threatens the human rights norms of equality, inviolability, and liberty, and discusses what the World Association for Christian Communication can do.

Citizen science networks in natural history and the collective validation of biodiversity data.

PubMed

Turnhout, Esther; Lawrence, Anna; Turnhout, Sander

2016-06-01

Biodiversity data are in increasing demand to inform policy and management. A substantial portion of these data is generated in citizen science networks. To ensure the quality of biodiversity data, standards and criteria for validation have been put in place. We used interviews and document analysis from the United Kingdom and The Netherlands to examine how data validation serves as a point of connection between the diverse people and practices in natural history citizen science networks. We found that rather than a unidirectional imposition of standards, validation was performed collectively. Specifically, it was enacted in ongoing circulations of biodiversity records between recorders and validators as they jointly negotiated the biodiversity that was observed and the validity of the records. These collective validation practices contributed to the citizen science character or natural history networks and tied these networks together. However, when biodiversity records were included in biodiversity-information initiatives on different policy levels and scales, the circulation of records diminished. These initiatives took on a more extractive mode of data use. Validation ceased to be collective with important consequences for the natural history networks involved and citizen science more generally. © 2016 The Authors. Conservation Biology published by Wiley Periodicals, Inc. on behalf of Society for Conservation Biology.

Parameter space exploration within dynamic simulations of signaling networks.

PubMed

De Ambrosi, Cristina; Barla, Annalisa; Tortolina, Lorenzo; Castagnino, Nicoletta; Pesenti, Raffaele; Verri, Alessandro; Ballestrero, Alberto; Patrone, Franco; Parodi, Silvio

2013-02-01

We started offering an introduction to very basic aspects of molecular biology, for the reader coming from computer sciences, information technology, mathematics. Similarly we offered a minimum of information about pathways and networks in graph theory, for a reader coming from the bio-medical sector. At the crossover about the two different types of expertise, we offered some definition about Systems Biology. The core of the article deals with a Molecular Interaction Map (MIM), a network of biochemical interactions involved in a small signaling-network sub-region relevant in breast cancer. We explored robustness/sensitivity to random perturbations. It turns out that our MIM is a non-isomorphic directed graph. For non physiological directions of propagation of the signal the network is quite resistant to perturbations. The opposite happens for biologically significant directions of signal propagation. In these cases we can have no signal attenuation, and even signal amplification. Signal propagation along a given pathway is highly unidirectional, with the exception of signal-feedbacks, that again have a specific biological role and significance. In conclusion, even a relatively small network like our present MIM reveals the preponderance of specific biological functions over unspecific isomorphic behaviors. This is perhaps the consequence of hundreds of millions of years of biological evolution.

Information sharing and relationships on social networking sites.

PubMed

Steijn, Wouter M P; Schouten, Alexander P

2013-08-01

This article investigates the relationship between sharing personal information and relationship development in the context of social networking sites (SNSs). Information disclosed on these sites could affect relationships in a different manner compared to more traditional interactions, such as instant messaging or face-to-face interaction. Respondents in the age range of 12 to 83 were surveyed about experiences of relationship development as a consequence of contact through Facebook or Hyves-the most popular Dutch SNSs. Results showed a primarily positive effect of information sharing on SNSs on our relationships. Furthermore, relationship development mainly occurs among acquaintances and friends, and public posts are most strongly related to relationship development. These findings suggest that SNSs might affect relationships in a distinct fashion as acquaintances and friends gain access to public self-disclosures that might normally only be reserved for close friends and family. Overall, this study provides an insight into some of the positive aspects of the public nature of SNSs in contrast with the general negative associations.

Network systems security analysis

NASA Astrophysics Data System (ADS)

Yilmaz, Ä.°smail

2015-05-01

Network Systems Security Analysis has utmost importance in today's world. Many companies, like banks which give priority to data management, test their own data security systems with "Penetration Tests" by time to time. In this context, companies must also test their own network/server systems and take precautions, as the data security draws attention. Based on this idea, the study cyber-attacks are researched throughoutly and Penetration Test technics are examined. With these information on, classification is made for the cyber-attacks and later network systems' security is tested systematically. After the testing period, all data is reported and filed for future reference. Consequently, it is found out that human beings are the weakest circle of the chain and simple mistakes may unintentionally cause huge problems. Thus, it is clear that some precautions must be taken to avoid such threats like updating the security software.

The effects of types of social networks, perceived social support, and loneliness on the health of older people: accounting for the social context.

PubMed

Stephens, Christine; Alpass, Fiona; Towers, Andy; Stevenson, Brendan

2011-09-01

To use an ecological model of ageing (Berkman, Glass, Brissette, & Seeman, 2000) which includes upstream social context factors and downstream social support factors to examine the effects of social networks on health. Postal survey responses from a representative population sample of New Zealanders aged 55 to 70 years (N = 6,662). Correlations and multiple regression analyses provided support for a model in which social context contributes to social network type, which affects perceived social support and loneliness, and consequent mental and physical health. Ethnicity was related to social networks and health but this was largely accounted for by other contextual variables measuring socioeconomic status. Gender and age were also significant variables in the model. Social network type is a useful way to assess social integration within this model of cascading effects. More detailed information could be gained through the development of our network assessment instruments for older people.

Matching-centrality decomposition and the forecasting of new links in networks.

PubMed

Rohr, Rudolf P; Naisbit, Russell E; Mazza, Christian; Bersier, Louis-Félix

2016-02-10

Networks play a prominent role in the study of complex systems of interacting entities in biology, sociology, and economics. Despite this diversity, we demonstrate here that a statistical model decomposing networks into matching and centrality components provides a comprehensive and unifying quantification of their architecture. The matching term quantifies the assortative structure in which node makes links with which other node, whereas the centrality term quantifies the number of links that nodes make. We show, for a diverse set of networks, that this decomposition can provide a tight fit to observed networks. Then we provide three applications. First, we show that the model allows very accurate prediction of missing links in partially known networks. Second, when node characteristics are known, we show how the matching-centrality decomposition can be related to this external information. Consequently, it offers us a simple and versatile tool to explore how node characteristics explain network architecture. Finally, we demonstrate the efficiency and flexibility of the model to forecast the links that a novel node would create if it were to join an existing network. © 2016 The Author(s).

Matching–centrality decomposition and the forecasting of new links in networks

PubMed Central

Rohr, Rudolf P.; Naisbit, Russell E.; Mazza, Christian; Bersier, Louis-Félix

2016-01-01

Networks play a prominent role in the study of complex systems of interacting entities in biology, sociology, and economics. Despite this diversity, we demonstrate here that a statistical model decomposing networks into matching and centrality components provides a comprehensive and unifying quantification of their architecture. The matching term quantifies the assortative structure in which node makes links with which other node, whereas the centrality term quantifies the number of links that nodes make. We show, for a diverse set of networks, that this decomposition can provide a tight fit to observed networks. Then we provide three applications. First, we show that the model allows very accurate prediction of missing links in partially known networks. Second, when node characteristics are known, we show how the matching–centrality decomposition can be related to this external information. Consequently, it offers us a simple and versatile tool to explore how node characteristics explain network architecture. Finally, we demonstrate the efficiency and flexibility of the model to forecast the links that a novel node would create if it were to join an existing network. PMID:26842568

Infant joint attention, neural networks and social cognition.

PubMed

Mundy, Peter; Jarrold, William

2010-01-01

Neural network models of attention can provide a unifying approach to the study of human cognitive and emotional development (Posner & Rothbart, 2007). In this paper we argue that a neural network approach to the infant development of joint attention can inform our understanding of the nature of human social learning, symbolic thought process and social cognition. At its most basic, joint attention involves the capacity to coordinate one's own visual attention with that of another person. We propose that joint attention development involves increments in the capacity to engage in simultaneous or parallel processing of information about one's own attention and the attention of other people. Infant practice with joint attention is both a consequence and an organizer of the development of a distributed and integrated brain network involving frontal and parietal cortical systems. This executive distributed network first serves to regulate the capacity of infants to respond to and direct the overt behavior of other people in order to share experience with others through the social coordination of visual attention. In this paper we describe this parallel and distributed neural network model of joint attention development and discuss two hypotheses that stem from this model. One is that activation of this distributed network during coordinated attention enhances the depth of information processing and encoding beginning in the first year of life. We also propose that with development, joint attention becomes internalized as the capacity to socially coordinate mental attention to internal representations. As this occurs the executive joint attention network makes vital contributions to the development of human symbolic thinking and social cognition. Copyright © 2010 Elsevier Ltd. All rights reserved.

Assessing Middle School Students' Knowledge of Conduct and Consequences and Their Behaviors regarding the Use of Social Networking Sites

ERIC Educational Resources Information Center

Kite, Stacey L.; Gable, Robert; Filippelli, Lawrence

2010-01-01

Cyberbullying and threats of Internet predators, not to mention the enduring consequences of postings, may lead to dangerous, unspeakable consequences. Cyberbullying and threats of Internet predators through social networking sites and instant messaging programs are initiating numerous problems for parents, school administrators, and law…

Development and Deployment of a Health Information Exchange to Understand the Transmission of MRSA across Hospitals via Molecular Genotyping and Social Networking Analysis

ERIC Educational Resources Information Center

Khan, Yosef M.

2012-01-01

Background: Methicillin Resistant Staphylococcus aureus (MRSA) is a hardy and extremely virulent multidrug resistant organism that has been a major cause of hospital acquired infections ever since its discovery in the 1960's. It has severe consequences such as causing increased hospital length of stay, economic burden, morbidity, and mortality.…

Using existing thinning studies to investigate the carbon consequences of thinning: learning from the past to craft the future

Treesearch

Coeli M. Hoover

2010-01-01

Although long-term research is a critical tool for answering forest management questions, managers must often make decisions before results from such experiments are available. One way to meet those information needs is to reanalyze existing long-term data sets to address current research questions; the Forest Service Experimental Forests and Ranges (EFRs) network...

Qualitative Comparison of Streamflow Information Programs of the U.S. Geological Survey and Three Non-Federal Agencies

USGS Publications Warehouse

Norris, J. Michael; Lewis, Michael; Dorsey, Michael; Kimbrough, Robert; Holmes, Robert R.; Staubitz, Ward

2008-01-01

A qualitative comparison was made of the streamgaging programs of the U.S. Geological Survey (USGS) and three non-Federal agencies in terms of approximate costs and streamflow-information products produced. The three non-Federal agencies provided the USGS with detailed information on their streamgaging program and related costs, and the USGS explored, through publicly available Web sites and one-on-one discussions, the comparability of the streamflow information produced. The type and purpose of streamgages operated, the quality of streamflow record produced, and cost-accounting methods have a great effect on streamgaging costs. There are many uses of streamflow information, and the information requirements for streamgaging programs differ greatly across this range of purposes. A premise of the USGS streamgaging program is that the network must produce consistent data of sufficient quality to support the broadest range of possible uses. Other networks may have a narrower range of purposes; as a consequence, the method of operation, data-quality objectives, and information delivery may be different from those for a multipurpose network. As a result, direct comparison of the overall cost (or of the cost per streamgage) among these programs is not possible. The analysis is, nonetheless, very instructive and provides USGS program managers, agency leadership, and other agency streamgaging program managers useful insight to influence future decisions. Even though the comparison of streamgaging costs and streamflow information products was qualitative, this analysis does offer useful insights on longstanding questions of USGS streamgaging costs.

Enhancing response coordination through the assessment of response network structural dynamics.

PubMed

Abbasi, Alireza; Sadeghi-Niaraki, Abolghasem; Jalili, Mahdi; Choi, Soo-Mi

2018-01-01

Preparing for intensifying threats of emergencies in unexpected, dangerous, and serious natural or man-made events, and consequent management of the situation, is highly demanding in terms of coordinating the personnel and resources to support human lives and the environment. This necessitates prompt action to manage the uncertainties and risks imposed by such extreme events, which requires collaborative operation among different stakeholders (i.e., the personnel from both the state and local communities). This research aims to find a way to enhance the coordination of multi-organizational response operations. To do so, this manuscript investigates the role of participants in the formed coordination response network and also the emergence and temporal dynamics of the network. By analyzing an inter-personal response coordination operation to an extreme bushfire event, the networks' and participants' structural change is evaluated during the evolution of the operation network over four time durations. The results reveal that the coordination response network becomes more decentralized over time due to the high volume of communication required to exchange information. New emerging communication structures often do not fit the developed plans, which stress the need for coordination by feedback in addition to by plan. In addition, we find that the participant's brokering role in the response operation network identifies a formal and informal coordination role. This is useful for comparison of network structures to examine whether what really happens during response operations complies with the initial policy.

Evidence of zolpidem abuse and dependence: results of the French Centre for Evaluation and Information on Pharmacodependence (CEIP) network survey

PubMed Central

Victorri-Vigneau, Caroline; Dailly, Eric; Veyrac, Gwenaëlle; Jolliet, Pascale

2007-01-01

Aim To show that the nonbenzodiazepine hypnotic zolpidem has a higher abuse potential than previously documented. Method An official enquiry was carried out by the Nantes Centre for Evaluation and Information on Pharmacodependence (CEIP). The authors made a review of literature and analysed French data corresponding to the drug's postmarketing period collected by the CEIP network from 1993 to 2002. Results The literature review yielded mixed results concerning the behavioural effects of zolpidem. Data from the CEIP and the 53 literature case reports highlight significant dependence and abuse potential of zolpidem. Conclusions This study adds to the growing evidence that zolpidem has the potential for abuse and dependence. As a consequence, the French drug monograph has been modified by the French Health Authorities. PMID:17324242

Non-Equlibrium Driven Dynamics of Continuous Attractors in Place Cell Networks

NASA Astrophysics Data System (ADS)

Zhong, Weishun; Kim, Hyun Jin; Schwab, David; Murugan, Arvind

Attractors have found much use in neuroscience as a means of information processing and decision making. Examples include associative memory with point and continuous attractors, spatial navigation and planning using place cell networks, dynamic pattern recognition among others. The functional use of such attractors requires the action of spatially and temporally varying external driving signals and yet, most theoretical work on attractors has been in the limit of small or no drive. We take steps towards understanding the non-equilibrium driven dynamics of continuous attractors in place cell networks. We establish an `equivalence principle' that relates fluctuations under a time-dependent external force to equilibrium fluctuations in a `co-moving' frame with only static forces, much like in Newtonian physics. Consequently, we analytically derive a network's capacity to encode multiple attractors as a function of the driving signal size and rate of change.

Water Security Toolkit User Manual: Version 1.3 | Science ...

EPA Pesticide Factsheets

User manual: Data Product/Software The Water Security Toolkit (WST) is a suite of tools that help provide the information necessary to make good decisions resulting in the minimization of further human exposure to contaminants, and the maximization of the effectiveness of intervention strategies. WST assists in the evaluation of multiple response actions in order to select the most beneficial consequence management strategy. It includes hydraulic and water quality modeling software and optimization methodologies to identify: (1) sensor locations to detect contamination, (2) locations in the network in which the contamination was introduced, (3) hydrants to remove contaminated water from the distribution system, (4) locations in the network to inject decontamination agents to inactivate, remove or destroy contaminants, (5) locations in the network to take grab sample to confirm contamination or cleanup and (6) valves to close in order to isolate contaminated areas of the network.

Mention effect in information diffusion on a micro-blogging network.

PubMed

Bao, Peng; Shen, Hua-Wei; Huang, Junming; Chen, Haiqiang

2018-01-01

Micro-blogging systems have become one of the most important ways for information sharing. Network structure and users' interactions such as forwarding behaviors have aroused considerable research attention, while mention, as a key feature in micro-blogging platforms which can improve the visibility of a message and direct it to a particular user beyond the underlying social structure, is seldom studied in previous works. In this paper, we empirically study the mention effect in information diffusion, using the dataset from a population-scale social media website. We find that users with high number of followers would receive much more mentions than others. We further investigate the effect of mention in information diffusion by examining the response probability with respect to the number of mentions in a message and observe a saturation at around 5 mentions. Furthermore, we find that the response probability is the highest when a reciprocal followship exists between users, and one is more likely to receive a target user's response if they have similar social status. To illustrate these findings, we propose the response prediction task and formulate it as a binary classification problem. Extensive evaluation demonstrates the effectiveness of discovered factors. Our results have consequences for the understanding of human dynamics on the social network, and potential implications for viral marketing and public opinion monitoring.

Curvature and temperature of complex networks.

PubMed

Krioukov, Dmitri; Papadopoulos, Fragkiskos; Vahdat, Amin; Boguñá, Marián

2009-09-01

We show that heterogeneous degree distributions in observed scale-free topologies of complex networks can emerge as a consequence of the exponential expansion of hidden hyperbolic space. Fermi-Dirac statistics provides a physical interpretation of hyperbolic distances as energies of links. The hidden space curvature affects the heterogeneity of the degree distribution, while clustering is a function of temperature. We embed the internet into the hyperbolic plane and find a remarkable congruency between the embedding and our hyperbolic model. Besides proving our model realistic, this embedding may be used for routing with only local information, which holds significant promise for improving the performance of internet routing.

Science, pseudoscience, and the frontline practitioner: the vaccination/autism debate.

PubMed

White, Erina

2014-01-01

This article demonstrates how misinformation concerning autism and vaccinations was created and suggests that social workers may be perfectly poised to challenge pseudoscience interpretations. Utilizing social network theory, this article illustrates how erroneous research, mass media, and public opinion led to a decreased use of vaccinations in the United States and a seven-fold increase in measles outbreaks. It traces the dissemination of spurious research results and demonstrates how information was transmitted via a system of social network nodes and community ties. This article encourages social workers, as frontline knowledge brokers, to counter misinformation, which may lead to significant public health consequences.

Citizen-sensor-networks to confront government decision-makers: Two lessons from the Netherlands.

PubMed

Carton, Linda; Ache, Peter

2017-07-01

This paper presents one emerging social-technical innovation: The evolution of citizen-sensor-networks where citizens organize themselves from the 'bottom up', for the sake of confronting governance officials with measured information about environmental qualities. We have observed how citizen-sensor-networks have been initiated in the Netherlands in cases where official government monitoring and business organizations leave gaps. The formed citizen-sensor-networks collect information about issues that affect the local community in their quality-of-living. In particular, two community initiatives are described where the sensed environmental information, on noise pollution and gas-extraction induced earthquakes respectively, is published through networked geographic information methods. Both community initiatives pioneered in developing an approach that comprises the combined setting-up of sensor data flows, real-time map portals and community organization. Two particular cases are analyzed to trace the emergence and network operation of such 'networked geo-information tools' in practice: (1) The Groningen earthquake monitor, and (2) The Airplane Monitor Schiphol. In both cases, environmental 'externalities' of spatial-economic activities play an important role, having economic dimensions of national importance (e.g. gas extraction and national airport development) while simultaneously affecting the regional community with environmental consequences. The monitoring systems analyzed in this paper are established bottom-up, by citizens for citizens, to serve as 'information power' in dialogue with government institutions. The goal of this paper is to gain insight in how these citizen-sensor-networks come about: how the idea for establishing a sensor network originated, how their value gets recognized and adopted in the overall 'system of governance'; to what extent they bring countervailing power against vested interests and established discourses to the table and influence power-laden conflicts over environmental pressures; and whether or not they achieve (some form of) institutionalization and, ultimately, policy change. We find that the studied-citizen-sensor networks gain strength by uniting efforts and activities in crowdsourcing data, providing factual, 'objectivized data' or 'evidence' of the situation 'on the ground' on a matter of local community-wide concern. By filling an information need of the local community, a process of 'collective sense-making' combined with citizen empowerment could grow, which influenced societal discourse and challenged prevailing truth-claims of public institutions. In both cases similar, 'competing' web-portals were developed in response, both by the gas-extraction company and the airport. But with the citizen-sensor-networks alongside, we conclude there is a shift in power balance involved between government and affected communities, as the government no longer has information monopoly on environmental measurements. Copyright © 2017 Elsevier Ltd. All rights reserved.

Automatic analysis of attack data from distributed honeypot network

NASA Astrophysics Data System (ADS)

Safarik, Jakub; Voznak, MIroslav; Rezac, Filip; Partila, Pavol; Tomala, Karel

2013-05-01

There are many ways of getting real data about malicious activity in a network. One of them relies on masquerading monitoring servers as a production one. These servers are called honeypots and data about attacks on them brings us valuable information about actual attacks and techniques used by hackers. The article describes distributed topology of honeypots, which was developed with a strong orientation on monitoring of IP telephony traffic. IP telephony servers can be easily exposed to various types of attacks, and without protection, this situation can lead to loss of money and other unpleasant consequences. Using a distributed topology with honeypots placed in different geological locations and networks provides more valuable and independent results. With automatic system of gathering information from all honeypots, it is possible to work with all information on one centralized point. Communication between honeypots and centralized data store use secure SSH tunnels and server communicates only with authorized honeypots. The centralized server also automatically analyses data from each honeypot. Results of this analysis and also other statistical data about malicious activity are simply accessible through a built-in web server. All statistical and analysis reports serve as information basis for an algorithm which classifies different types of used VoIP attacks. The web interface then brings a tool for quick comparison and evaluation of actual attacks in all monitored networks. The article describes both, the honeypots nodes in distributed architecture, which monitor suspicious activity, and also methods and algorithms used on the server side for analysis of gathered data.

Puerto Rico Seismic Network Operations During and After the Hurricane Maria: Response, Continuity of Operations, and Experiences

NASA Astrophysics Data System (ADS)

Vanacore, E. A.; Baez-Sanchez, G.; Huerfano, V.; Lopez, A. M.; Lugo, J.

2017-12-01

The Puerto Rico Seismic Network (PRSN) is an integral part of earthquake and tsunami monitoring in Puerto Rico and the Virgin Islands. The PRSN conducts scientific research as part of the University of Puerto Rico Mayaguez, conducts the earthquake monitoring for the region, runs extensive earthquake and tsunami education and outreach programs, and acts as a Tsunami Warning Focal Point Alternate for Puerto Rico. During and in the immediate aftermath of Hurricane Maria, the PRSN duties and responsibilities evolved from a seismic network to a major information and communications center for the western side of Puerto Rico. Hurricane Maria effectively destroyed most communications on island, critically between the eastern side of the island where Puerto Rico's Emergency Management's (PREMA) main office and the National Weather Service (NWS) is based and the western side of the island. Additionally, many local emergency management agencies on the western side of the island lost a satellite based emergency management information system called EMWIN which provides critical tsunami and weather information. PRSN's EMWIN system remained functional and consequently via this system and radio communications PRSN became the only information source for NWS warnings and bulletins, tsunami alerts, and earthquake information for western Puerto Rico. Additionally, given the functional radio and geographic location of the PRSN, the network became a critical communications relay for local emergency management. Here we will present the PRSN response in relation to Hurricane Maria including the activation of the PRSN devolution plan, adoption of duties, experiences and lessons learned for continuity of operations and adoption of responsibilities during future catastrophic events.

The Community Structure of the European Network of Interlocking Directorates 2005–2010

PubMed Central

Heemskerk, Eelke M.; Daolio, Fabio; Tomassini, Marco

2013-01-01

The boards of directors at large European companies overlap with each other to a sizable extent both within and across national borders. This could have important economic, political and management consequences. In this work we study in detail the topological structure of the networks that arise from this phenomenon. Using a comprehensive information database, we reconstruct the implicit networks of shared directorates among the top 300 European firms in 2005 and 2010, and suggest a number of novel ways to explore the trans-nationality of such business elite networks. Powerful community detection heuristics indicate that geography still plays an important role: there exist clear communities and they have a distinct national character. Nonetheless, from 2005 to 2010 we observe a densification of the boards interlocks network and a larger transnational orientation in its communities. Together with central actors and assortativity analyses, we provide statistical evidence that, at the level of corporate governance, Europe is getting closer. PMID:23894318

The community structure of the European network of interlocking directorates 2005-2010.

PubMed

Heemskerk, Eelke M; Daolio, Fabio; Tomassini, Marco

2013-01-01

The boards of directors at large European companies overlap with each other to a sizable extent both within and across national borders. This could have important economic, political and management consequences. In this work we study in detail the topological structure of the networks that arise from this phenomenon. Using a comprehensive information database, we reconstruct the implicit networks of shared directorates among the top 300 European firms in 2005 and 2010, and suggest a number of novel ways to explore the trans-nationality of such business elite networks. Powerful community detection heuristics indicate that geography still plays an important role: there exist clear communities and they have a distinct national character. Nonetheless, from 2005 to 2010 we observe a densification of the boards interlocks network and a larger transnational orientation in its communities. Together with central actors and assortativity analyses, we provide statistical evidence that, at the level of corporate governance, Europe is getting closer.

Can multilayer brain networks be a real step forward?. Comment on "Network science of biological systems at different scales: A review" by M. Gosak et al.

NASA Astrophysics Data System (ADS)

Buldú, Javier M.; Papo, David

2018-03-01

Over the last two decades Network Science has become one of the most active fields in science, whose growth has been supported by four fundamental pillars: statistical physics, nonlinear dynamics, graph theory and Big Data [1]. Initially concerned with analyzing the structure of networks, Network Science rapidly turned its attention, focused on the implications of network topology, on the dynamics of and processes unfolding on networked systems, greatly improving our understanding of diffusion, synchronization, epidemics and information transmission in complex systems [2]. The network approach typically considered complex systems as evolving in a vacuum; however real networks are generally not isolated systems, but are in continuous and evolving contact with other networks, with which they interact in multiple qualitative different and typically time-varying ways. These systems can then be represented as a collection of subsystems with connectivity layers, which are simply collapsed when considering the traditional monolayer representation. Surprisingly, such an "unpacking" of layers has proven to bear profound consequences on the structural and dynamical properties of networks, leading for instance to counter-intuitive synchronization phenomena, where maximization synchronization is achieved through strategies opposite of those maximizing synchronization in isolated networks [3].

Cyberspace Operations Concept Capability Plan 2016-2028

DTIC Science & Technology

2010-02-22

effectively in this emerging environment, the Army must realign its information "Aim Point." Army leaders and Soldiers must possess an in -depth...communications technology (ICT) and its consequent effect in social networks and in society impact the OE. The diverse and wide arrays of agents who use...fails in this contest, or that cannot operate effectively when their systems are degraded or disrupted, cedes a significant advantage to the adversary

Enhancing response coordination through the assessment of response network structural dynamics

PubMed Central

Jalili, Mahdi; Choi, Soo-Mi

2018-01-01

Preparing for intensifying threats of emergencies in unexpected, dangerous, and serious natural or man-made events, and consequent management of the situation, is highly demanding in terms of coordinating the personnel and resources to support human lives and the environment. This necessitates prompt action to manage the uncertainties and risks imposed by such extreme events, which requires collaborative operation among different stakeholders (i.e., the personnel from both the state and local communities). This research aims to find a way to enhance the coordination of multi-organizational response operations. To do so, this manuscript investigates the role of participants in the formed coordination response network and also the emergence and temporal dynamics of the network. By analyzing an inter-personal response coordination operation to an extreme bushfire event, the networks’ and participants’ structural change is evaluated during the evolution of the operation network over four time durations. The results reveal that the coordination response network becomes more decentralized over time due to the high volume of communication required to exchange information. New emerging communication structures often do not fit the developed plans, which stress the need for coordination by feedback in addition to by plan. In addition, we find that the participant’s brokering role in the response operation network identifies a formal and informal coordination role. This is useful for comparison of network structures to examine whether what really happens during response operations complies with the initial policy. PMID:29447192

Predictive Coding of Dynamical Variables in Balanced Spiking Networks

PubMed Central

Boerlin, Martin; Machens, Christian K.; Denève, Sophie

2013-01-01

Two observations about the cortex have puzzled neuroscientists for a long time. First, neural responses are highly variable. Second, the level of excitation and inhibition received by each neuron is tightly balanced at all times. Here, we demonstrate that both properties are necessary consequences of neural networks that represent information efficiently in their spikes. We illustrate this insight with spiking networks that represent dynamical variables. Our approach is based on two assumptions: We assume that information about dynamical variables can be read out linearly from neural spike trains, and we assume that neurons only fire a spike if that improves the representation of the dynamical variables. Based on these assumptions, we derive a network of leaky integrate-and-fire neurons that is able to implement arbitrary linear dynamical systems. We show that the membrane voltage of the neurons is equivalent to a prediction error about a common population-level signal. Among other things, our approach allows us to construct an integrator network of spiking neurons that is robust against many perturbations. Most importantly, neural variability in our networks cannot be equated to noise. Despite exhibiting the same single unit properties as widely used population code models (e.g. tuning curves, Poisson distributed spike trains), balanced networks are orders of magnitudes more reliable. Our approach suggests that spikes do matter when considering how the brain computes, and that the reliability of cortical representations could have been strongly underestimated. PMID:24244113

EPMOSt: An Energy-Efficient Passive Monitoring System for Wireless Sensor Networks

PubMed Central

Garcia, Fernando P.; Andrade, Rossana M. C.; Oliveira, Carina T.; de Souza, José Neuman

2014-01-01

Monitoring systems are important for debugging and analyzing Wireless Sensor Networks (WSN). In passive monitoring, a monitoring network needs to be deployed in addition to the network to be monitored, named the target network. The monitoring network captures and analyzes packets transmitted by the target network. An energy-efficient passive monitoring system is necessary when we need to monitor a WSN in a real scenario because the lifetime of the monitoring network is extended and, consequently, the target network benefits from the monitoring for a longer time. In this work, we have identified, analyzed and compared the main passive monitoring systems proposed for WSN. During our research, we did not identify any passive monitoring system for WSN that aims to reduce the energy consumption of the monitoring network. Therefore, we propose an Energy-efficient Passive MOnitoring SysTem for WSN named EPMOSt that provides monitoring information using a Simple Network Management Protocol (SNMP) agent. Thus, any management tool that supports the SNMP protocol can be integrated with this monitoring system. Experiments with real sensors were performed in several scenarios. The results obtained show the energy efficiency of the proposed monitoring system and the viability of using it to monitor WSN in real scenarios. PMID:24949639

Maritime Transportation Risk Assessment of Tianjin Port with Bayesian Belief Networks.

PubMed

Zhang, Jinfen; Teixeira, Ângelo P; Guedes Soares, C; Yan, Xinping; Liu, Kezhong

2016-06-01

This article develops a Bayesian belief network model for the prediction of accident consequences in the Tianjin port. The study starts with a statistical analysis of historical accident data of six years from 2008 to 2013. Then a Bayesian belief network is constructed to express the dependencies between the indicator variables and accident consequences. The statistics and expert knowledge are synthesized in the Bayesian belief network model to obtain the probability distribution of the consequences. By a sensitivity analysis, several indicator variables that have influence on the consequences are identified, including navigational area, ship type and time of the day. The results indicate that the consequences are most sensitive to the position where the accidents occurred, followed by time of day and ship length. The results also reflect that the navigational risk of the Tianjin port is at the acceptable level, despite that there is more room of improvement. These results can be used by the Maritime Safety Administration to take effective measures to enhance maritime safety in the Tianjin port. © 2016 Society for Risk Analysis.

International Digestive Endoscopy Network 2014: Turnpike to the Future

PubMed Central

Kim, Eun Young; Kwon, Kwang An; Choi, Il Ju; Ryu, Ji Kon

2014-01-01

Social networks are useful in the study of relationships between individuals or entire populations, and the ties through which any given social unit connects. Those represent the convergence of the various social contacts of that unit. Consequently, the term "social networking service" (SNS) became extremely familiar. Similar to familiar SNSs, International Digestive Endoscopy Network (IDEN) 2014 was based on an international network composed of an impressive 2-day scientific program dealing with a variety of topics for gastrointestinal (GI) diseases, which connects physicians and researchers from all over the world. The scientific programs included live endoscopic demonstrations and provided cutting-edge information and practice tips as well as the latest advances concerning upper GI, lower GI, and pancreatobiliary endoscopy. IDEN 2014 featured American Society for Gastrointestinal Endoscopy-Korean Society of Gastrointestinal Endoscopy (ASGE-KSGE)-joint sessions prepared through cooperation between ASGE and KSGE. Furthermore, IDEN 2014 provided a special program for young scientists called the 'Asian Young Endoscopist Award Forum' to foster networks, with many young endoscopists from Asian countries taking an active interest and participation. PMID:25324994

International digestive endoscopy network 2014: turnpike to the future.

PubMed

Kim, Eun Young; Kwon, Kwang An; Choi, Il Ju; Ryu, Ji Kon; Hahm, Ki Baik

2014-09-01

Social networks are useful in the study of relationships between individuals or entire populations, and the ties through which any given social unit connects. Those represent the convergence of the various social contacts of that unit. Consequently, the term "social networking service" (SNS) became extremely familiar. Similar to familiar SNSs, International Digestive Endoscopy Network (IDEN) 2014 was based on an international network composed of an impressive 2-day scientific program dealing with a variety of topics for gastrointestinal (GI) diseases, which connects physicians and researchers from all over the world. The scientific programs included live endoscopic demonstrations and provided cutting-edge information and practice tips as well as the latest advances concerning upper GI, lower GI, and pancreatobiliary endoscopy. IDEN 2014 featured American Society for Gastrointestinal Endoscopy-Korean Society of Gastrointestinal Endoscopy (ASGE-KSGE)-joint sessions prepared through cooperation between ASGE and KSGE. Furthermore, IDEN 2014 provided a special program for young scientists called the 'Asian Young Endoscopist Award Forum' to foster networks, with many young endoscopists from Asian countries taking an active interest and participation.

Demonstration of a roving-host wireless sensor network for rapid assessment monitoring of structural health

NASA Astrophysics Data System (ADS)

Mascarenas, David D. L.; Flynn, Eric; Lin, Kaisen; Farinholt, Kevin; Park, Gyuhae; Gupta, Rajesh; Todd, Michael; Farrar, Charles

2008-03-01

A major challenge impeding the deployment of wireless sensor networks for structural health monitoring (SHM) is developing means to supply power to the sensor nodes in a cost-effective manner. In this work an initial test of a roving-host wireless sensor network was performed on a bridge near Truth or Consequences, NM in August of 2007. The roving-host wireless sensor network features a radio controlled helicopter responsible for wirelessly delivering energy to sensor nodes on an "as-needed" basis. In addition, the helicopter also serves as a central data repository and processing center for the information collected by the sensor network. The sensor nodes used on the bridge were developed for measuring the peak displacement of the bridge, as well as measuring the preload of some of the bolted joints in the bridge. These sensors and sensor nodes were specifically designed to be able to operate from energy supplied wirelessly from the helicopter. The ultimate goal of this research is to ease the requirement for battery power supplies in wireless sensor networks.

Dynamics of deceptive interactions in social networks.

PubMed

Barrio, Rafael A; Govezensky, Tzipe; Dunbar, Robin; Iñiguez, Gerardo; Kaski, Kimmo

2015-11-06

In this paper, we examine the role of lies in human social relations by implementing some salient characteristics of deceptive interactions into an opinion formation model, so as to describe the dynamical behaviour of a social network more realistically. In this model, we take into account such basic properties of social networks as the dynamics of the intensity of interactions, the influence of public opinion and the fact that in every human interaction it might be convenient to deceive or withhold information depending on the instantaneous situation of each individual in the network. We find that lies shape the topology of social networks, especially the formation of tightly linked, small communities with loose connections between them. We also find that agents with a larger proportion of deceptive interactions are the ones that connect communities of different opinion, and, in this sense, they have substantial centrality in the network. We then discuss the consequences of these results for the social behaviour of humans and predict the changes that could arise due to a varying tolerance for lies in society. © 2015 The Author(s).

Mutual information, neural networks and the renormalization group

NASA Astrophysics Data System (ADS)

Koch-Janusz, Maciej; Ringel, Zohar

2018-06-01

Physical systems differing in their microscopic details often display strikingly similar behaviour when probed at macroscopic scales. Those universal properties, largely determining their physical characteristics, are revealed by the powerful renormalization group (RG) procedure, which systematically retains `slow' degrees of freedom and integrates out the rest. However, the important degrees of freedom may be difficult to identify. Here we demonstrate a machine-learning algorithm capable of identifying the relevant degrees of freedom and executing RG steps iteratively without any prior knowledge about the system. We introduce an artificial neural network based on a model-independent, information-theoretic characterization of a real-space RG procedure, which performs this task. We apply the algorithm to classical statistical physics problems in one and two dimensions. We demonstrate RG flow and extract the Ising critical exponent. Our results demonstrate that machine-learning techniques can extract abstract physical concepts and consequently become an integral part of theory- and model-building.

Evolution of cosmic string networks

NASA Technical Reports Server (NTRS)

Albrecht, Andreas; Turok, Neil

1989-01-01

A discussion of the evolution and observable consequences of a network of cosmic strings is given. A simple model for the evolution of the string network is presented, and related to the statistical mechanics of string networks. The model predicts the long string density throughout the history of the universe from a single parameter, which researchers calculate in radiation era simulations. The statistical mechanics arguments indicate a particular thermal form for the spectrum of loops chopped off the network. Detailed numerical simulations of string networks in expanding backgrounds are performed to test the model. Consequences for large scale structure, the microwave and gravity wave backgrounds, nucleosynthesis and gravitational lensing are calculated.

MOCASSIN-prot: a multi-objective clustering approach for protein similarity networks.

PubMed

Keel, Brittney N; Deng, Bo; Moriyama, Etsuko N

2018-04-15

Proteins often include multiple conserved domains. Various evolutionary events including duplication and loss of domains, domain shuffling, as well as sequence divergence contribute to generating complexities in protein structures, and consequently, in their functions. The evolutionary history of proteins is hence best modeled through networks that incorporate information both from the sequence divergence and the domain content. Here, a game-theoretic approach proposed for protein network construction is adapted into the framework of multi-objective optimization, and extended to incorporate clustering refinement procedure. The new method, MOCASSIN-prot, was applied to cluster multi-domain proteins from ten genomes. The performance of MOCASSIN-prot was compared against two protein clustering methods, Markov clustering (TRIBE-MCL) and spectral clustering (SCPS). We showed that compared to these two methods, MOCASSIN-prot, which uses both domain composition and quantitative sequence similarity information, generates fewer false positives. It achieves more functionally coherent protein clusters and better differentiates protein families. MOCASSIN-prot, implemented in Perl and Matlab, is freely available at http://bioinfolab.unl.edu/emlab/MOCASSINprot. emoriyama2@unl.edu. Supplementary data are available at Bioinformatics online.

Secrets and Misperceptions: The Creation of Self-Fulfilling Illusions

PubMed Central

Cowan, Sarah K.

2015-01-01

This study examines who hears what secrets, comparing two similar secrets-one that is highly stigmatized and one that is less so. Using a unique survey representative of American adults and intake forms from a medical clinic, I document marked differences in who hears these secrets. People who are sympathetic to the stigmatizing secret are more likely to hear of it than those who may react negatively. This is a consequence of people not just selectively disclosing their own secrets but selectively sharing others’ as well. As a result, people in the same social network will be exposed to and influenced by different information about those they know and hence experience that network differently. When people effectively exist in networks tailored by others not to offend, then the information they hear tends to be that of which they already approve. Were they to hear secrets they disapproved of, then their attitudes might change, but they are less likely to hear those secrets. As such, the patterns of secret hearing contribute to a stasis in public opinion. PMID:26082932

Anthropomorphic robot for recognition of objects

NASA Astrophysics Data System (ADS)

Ginzburg, Vera M.

1999-08-01

Heated debates were taking place a few decades ago between the proponents of digital and analog methods in information. Technology have resulted in unequivocal triumph of the former. However, some serious technological problems confronting the world civilization on the threshold of the new millennium, such as Y2K and computer network vulnerability, probably spring from this one-sided approach. Dire consequences of problems of this kind can be alleviated through learning from the nature.

Assessing the Climate Resilience of Transport Infrastructure Investments in Tanzania

NASA Astrophysics Data System (ADS)

Hall, J. W.; Pant, R.; Koks, E.; Thacker, S.; Russell, T.

2017-12-01

Whilst there is an urgent need for infrastructure investment in developing countries, there is a risk that poorly planned and built infrastructure will introduce new vulnerabilities. As climate change increases the magnitudes and frequency of natural hazard events, incidence of disruptive infrastructure failures are likely to become more frequent. Therefore, it is important that infrastructure planning and investment is underpinned by climate risk assessment that can inform adaptation planning. Tanzania's rapid economic growth is placing considerable strain on the country's transportation infrastructure (roads, railways, shipping and aviation); especially at the port of Dar es Salaam and its linking transport corridors. A growing number of natural hazard events, in particular flooding, are impacting the reliability of this already over-used network. Here we report on new methodology to analyse vulnerabilities and risks due to failures of key locations in the intermodal transport network of Tanzania, including strategic connectivity to neighboring countries. To perform the national-scale risk analysis we will utilize a system-of-systems methodology. The main components of this general risk assessment, when applied to transportation systems, include: (1) Assembling data on: spatially coherent extreme hazards and intermodal transportation networks; (2) Intersecting hazards with transport network models to initiate failure conditions that trigger failure propagation across interdependent networks; (3) Quantifying failure outcomes in terms of social impacts (customers/passengers disrupted) and/or macroeconomic consequences (across multiple sectors); and (4) Simulating, testing and collecting multiple failure scenarios to perform an exhaustive risk assessment in terms of probabilities and consequences. The methodology is being used to pinpoint vulnerability and reduce climate risks to transport infrastructure investments.

Research Note: The consequences of different methods for handling missing network data in Stochastic Actor Based Models

PubMed Central

Hipp, John R.; Wang, Cheng; Butts, Carter T.; Jose, Rupa; Lakon, Cynthia M.

2015-01-01

Although stochastic actor based models (e.g., as implemented in the SIENA software program) are growing in popularity as a technique for estimating longitudinal network data, a relatively understudied issue is the consequence of missing network data for longitudinal analysis. We explore this issue in our research note by utilizing data from four schools in an existing dataset (the AddHealth dataset) over three time points, assessing the substantive consequences of using four different strategies for addressing missing network data. The results indicate that whereas some measures in such models are estimated relatively robustly regardless of the strategy chosen for addressing missing network data, some of the substantive conclusions will differ based on the missing data strategy chosen. These results have important implications for this burgeoning applied research area, implying that researchers should more carefully consider how they address missing data when estimating such models. PMID:25745276

Research Note: The consequences of different methods for handling missing network data in Stochastic Actor Based Models.

PubMed

Hipp, John R; Wang, Cheng; Butts, Carter T; Jose, Rupa; Lakon, Cynthia M

2015-05-01

Although stochastic actor based models (e.g., as implemented in the SIENA software program) are growing in popularity as a technique for estimating longitudinal network data, a relatively understudied issue is the consequence of missing network data for longitudinal analysis. We explore this issue in our research note by utilizing data from four schools in an existing dataset (the AddHealth dataset) over three time points, assessing the substantive consequences of using four different strategies for addressing missing network data. The results indicate that whereas some measures in such models are estimated relatively robustly regardless of the strategy chosen for addressing missing network data, some of the substantive conclusions will differ based on the missing data strategy chosen. These results have important implications for this burgeoning applied research area, implying that researchers should more carefully consider how they address missing data when estimating such models.

Network-Cognizant Design of Decentralized Volt/VAR Controllers

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

Baker, Kyri A; Bernstein, Andrey; Zhao, Changhong

This paper considers the problem of designing decentralized Volt/VAR controllers for distributed energy resources (DERs). The voltage-reactive power characteristics of individual DERs are obtained by solving a convex optimization problem, where given performance objectives (e.g., minimization of the voltage deviations from a given profile) are specified and stability constraints are enforced. The resultant Volt/VAR characteristics are network-cognizant, in the sense that they embed information on the location of the DERs and, consequently, on the effect of reactive-power adjustments on the voltages throughout the feeder. Bounds on the maximum voltage deviation incurred by the controllers are analytically established. Numerical results aremore » reported to corroborate the technical findings.« less

Social Media Mourning.

PubMed

Moore, Jensen; Magee, Sara; Gamreklidze, Ellada; Kowalewski, Jennifer

2017-01-01

This article uses grounded theory methodology to analyze in-depth interviews conducted with mourners who used social networking sites during bereavement. The social media mourning (SMM) model outlines how social networking sites are used to grieve using one or more of the following: (a) one-way communication, (b) two-way communication, and (c) immortality communication. The model indicates causal conditions of SMM: (a) sharing information with family or friends and (sometimes) beginning a dialog, (b) discussing death with others mourning, (c) discussing death with a broader mourning community, and (d) commemorating and continuing connection to the deceased. The article includes actions and consequences associated with SMM and suggests several ways in which SMM changes or influences the bereavement process.

Impaired Tuning of Neural Ensembles and the Pathophysiology of Schizophrenia: A Translational and Computational Neuroscience Perspective.

PubMed

Krystal, John H; Anticevic, Alan; Yang, Genevieve J; Dragoi, George; Driesen, Naomi R; Wang, Xiao-Jing; Murray, John D

2017-05-15

The functional optimization of neural ensembles is central to human higher cognitive functions. When the functions through which neural activity is tuned fail to develop or break down, symptoms and cognitive impairments arise. This review considers ways in which disturbances in the balance of excitation and inhibition might develop and be expressed in cortical networks in association with schizophrenia. This presentation is framed within a developmental perspective that begins with disturbances in glutamate synaptic development in utero. It considers developmental correlates and consequences, including compensatory mechanisms that increase intrinsic excitability or reduce inhibitory tone. It also considers the possibility that these homeostatic increases in excitability have potential negative functional and structural consequences. These negative functional consequences of disinhibition may include reduced working memory-related cortical activity associated with the downslope of the "inverted-U" input-output curve, impaired spatial tuning of neural activity and impaired sparse coding of information, and deficits in the temporal tuning of neural activity and its implication for neural codes. The review concludes by considering the functional significance of noisy activity for neural network function. The presentation draws on computational neuroscience and pharmacologic and genetic studies in animals and humans, particularly those involving N-methyl-D-aspartate glutamate receptor antagonists, to illustrate principles of network regulation that give rise to features of neural dysfunction associated with schizophrenia. While this presentation focuses on schizophrenia, the general principles outlined in the review may have broad implications for considering disturbances in the regulation of neural ensembles in psychiatric disorders. Published by Elsevier Inc.

Mention effect in information diffusion on a micro-blogging network

PubMed Central

Shen, Hua-Wei; Huang, Junming; Chen, Haiqiang

2018-01-01

Micro-blogging systems have become one of the most important ways for information sharing. Network structure and users’ interactions such as forwarding behaviors have aroused considerable research attention, while mention, as a key feature in micro-blogging platforms which can improve the visibility of a message and direct it to a particular user beyond the underlying social structure, is seldom studied in previous works. In this paper, we empirically study the mention effect in information diffusion, using the dataset from a population-scale social media website. We find that users with high number of followers would receive much more mentions than others. We further investigate the effect of mention in information diffusion by examining the response probability with respect to the number of mentions in a message and observe a saturation at around 5 mentions. Furthermore, we find that the response probability is the highest when a reciprocal followship exists between users, and one is more likely to receive a target user’s response if they have similar social status. To illustrate these findings, we propose the response prediction task and formulate it as a binary classification problem. Extensive evaluation demonstrates the effectiveness of discovered factors. Our results have consequences for the understanding of human dynamics on the social network, and potential implications for viral marketing and public opinion monitoring. PMID:29558498

Lost in transportation: Information measures and cognitive limits in multilayer navigation.

PubMed

Gallotti, Riccardo; Porter, Mason A; Barthelemy, Marc

2016-02-01

Cities and their transportation systems become increasingly complex and multimodal as they grow, and it is natural to wonder whether it is possible to quantitatively characterize our difficulty navigating in them and whether such navigation exceeds our cognitive limits. A transition between different search strategies for navigating in metropolitan maps has been observed for large, complex metropolitan networks. This evidence suggests the existence of a limit associated with cognitive overload and caused by a large amount of information that needs to be processed. In this light, we analyzed the world's 15 largest metropolitan networks and estimated the information limit for determining a trip in a transportation system to be on the order of 8 bits. Similar to the "Dunbar number," which represents a limit to the size of an individual's friendship circle, our cognitive limit suggests that maps should not consist of more than 250 connection points to be easily readable. We also show that including connections with other transportation modes dramatically increases the information needed to navigate in multilayer transportation networks. In large cities such as New York, Paris, and Tokyo, more than 80% of the trips are above the 8-bit limit. Multimodal transportation systems in large cities have thus already exceeded human cognitive limits and, consequently, the traditional view of navigation in cities has to be revised substantially.

Lost in transportation: Information measures and cognitive limits in multilayer navigation

PubMed Central

Gallotti, Riccardo; Porter, Mason A.; Barthelemy, Marc

2016-01-01

Cities and their transportation systems become increasingly complex and multimodal as they grow, and it is natural to wonder whether it is possible to quantitatively characterize our difficulty navigating in them and whether such navigation exceeds our cognitive limits. A transition between different search strategies for navigating in metropolitan maps has been observed for large, complex metropolitan networks. This evidence suggests the existence of a limit associated with cognitive overload and caused by a large amount of information that needs to be processed. In this light, we analyzed the world’s 15 largest metropolitan networks and estimated the information limit for determining a trip in a transportation system to be on the order of 8 bits. Similar to the “Dunbar number,” which represents a limit to the size of an individual’s friendship circle, our cognitive limit suggests that maps should not consist of more than 250 connection points to be easily readable. We also show that including connections with other transportation modes dramatically increases the information needed to navigate in multilayer transportation networks. In large cities such as New York, Paris, and Tokyo, more than 80% of the trips are above the 8-bit limit. Multimodal transportation systems in large cities have thus already exceeded human cognitive limits and, consequently, the traditional view of navigation in cities has to be revised substantially. PMID:26989769

Disruption of River Networks in Nature and Models

NASA Astrophysics Data System (ADS)

Perron, J. T.; Black, B. A.; Stokes, M.; McCoy, S. W.; Goldberg, S. L.

2017-12-01

Many natural systems display especially informative behavior as they respond to perturbations. Landscapes are no exception. For example, longitudinal elevation profiles of rivers responding to changes in uplift rate can reveal differences among erosional mechanisms that are obscured while the profiles are in equilibrium. The responses of erosional river networks to perturbations, including disruption of their network structure by diversion, truncation, resurfacing, or river capture, may be equally revealing. In this presentation, we draw attention to features of disrupted erosional river networks that a general model of landscape evolution should be able to reproduce, including the consequences of different styles of planetary tectonics and the response to heterogeneous bedrock structure and deformation. A comparison of global drainage directions with long-wavelength topography on Earth, Mars, and Saturn's moon Titan reveals the extent to which persistent and relatively rapid crustal deformation has disrupted river networks on Earth. Motivated by this example and others, we ask whether current models of river network evolution adequately capture the disruption of river networks by tectonic, lithologic, or climatic perturbations. In some cases the answer appears to be no, and we suggest some processes that models may be missing.

Online HIV awareness and technology affordance benefits for black female collegians - maybe not: the case of stigma.

PubMed

Payton, Fay Cobb; Kvasny, Lynette

2016-11-01

We investigate the technology affordances associated with and anticipated from an online human immunodeficiency virus (HIV) prevention awareness platform, myHealthImpactNetwork, intended to reach black female college students. This population is at increased risk for HIV transmission, but is not often studied. In addition, this population regularly uses digital tools, including Web sites and social media platforms, to engage in health information seeking. We conducted 11 focus groups with 60 black female college students attending 2 universities in the United States. Focus groups were recorded, transcribed, and analyzed using content analyses. Contrary to our proposition, the participants' information needs did not align with the anticipated benefits associated with the technology affordances of the prevention awareness platform. Concerns about personal online social capital, reputation management, and stigma limited participants' willingness to engage with the HIV prevention content on the website. Although the participants use digital tools as a primary means of becoming informed about health, concerns that friends, family, and others in their social networks would assume that they were HIV infected limited their willingness to engage with myHealthImpactNetwork. Print media and conversations with health care professionals were preferred channels for obtaining HIV prevention information. Perceptions of stigma associated with HIV negatively impact health information seeking and sharing in the online social networks in which black college students engage. However, by understanding the unanticipated consequences, researchers can effectively design for cultures and subcultures infected and affected by health disparities. © The Author 2016. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

ICT approaches to integrating institutional and non-institutional data services for better understanding of hydro-meteorological phenomena

NASA Astrophysics Data System (ADS)

Bedrina, T.; Parodi, A.; Quarati, A.; Clematis, A.

2012-06-01

It is widely recognised that an effective exploitation of Information and Communication Technologies (ICT) is an enabling factor to achieve major advancements in Hydro-Meteorological Research (HMR). Recently, a lot of attention has been devoted to the use of ICT in HMR activities, e.g. in order to facilitate data exchange and integration, to improve computational capabilities and consequently model resolution and quality. Nowadays, ICT technologies have demonstrated that it is possible to extend monitoring networks by integrating sensors and other sources of data managed by volunteer's communities. These networks are constituted by peers that span a wide portion of the territory in many countries. The peers are "location aware" in the sense that they provide information strictly related with their geospatial location. The coverage of these networks, in general, is not uniform and the location of peers may follow random distribution. The ICT features used to set up the network are lightweight and user friendly, thus, permitting the peers to join the network without the necessity of specialised ICT knowledge. In this perspective it is of increasing interest for HMR activities to elaborate of Personal Weather Station (PWS) networks, capable to provide almost real-time, location aware, weather data. Moreover, different big players of the web arena are now providing world-wide backbones, suitable to present on detailed map location aware information, obtained by mashing up data from different sources. This is the case, for example, with Google Earth and Google Maps. This paper presents the design of a mashup application aimed at aggregating, refining and visualizing near real-time hydro-meteorological datasets. In particular, we focused on the integration of instant precipitation depths, registered either by widespread semi-professional weather stations and official ones. This sort of information has high importance and usefulness in decision support systems and Civil Protection applications. As a significant case study, we analysed the rainfall data observed during the severe flash-flood event of 4 November 2011 over Liguria region, Italy. The joint use of official observation network with PWS networks and meteorological radar allowed for the making of evident finger-like convection structure.

Physically secured orthogonal frequency division multiplexing-passive optical network employing noise-based encryption and signal recovery process

NASA Astrophysics Data System (ADS)

Jin, Wei; Zhang, Chongfu; Yuan, Weicheng

2016-02-01

We propose a physically enhanced secure scheme for direct detection-orthogonal frequency division multiplexing-passive optical network (DD-OFDM-PON) and long reach coherent detection-orthogonal frequency division multiplexing-passive optical network (LRCO-OFDM-PON), by employing noise-based encryption and channel/phase estimation. The noise data generated by chaos mapping are used to substitute training sequences in preamble to realize channel estimation and frame synchronization, and also to be embedded on variable number of key-selected randomly spaced pilot subcarriers to implement phase estimation. Consequently, the information used for signal recovery is totally hidden as unpredictable noise information in OFDM frames to mask useful information and to prevent illegal users from correctly realizing OFDM demodulation, and thereby enhancing resistance to attackers. The levels of illegal-decryption complexity and implementation complexity are theoretically discussed. Through extensive simulations, the performances of the proposed channel/phase estimation and the security introduced by encrypted pilot carriers have been investigated in both DD-OFDM and LRCO-OFDM systems. In addition, in the proposed secure DD-OFDM/LRCO-OFDM PON models, both legal and illegal receiving scenarios have been considered. These results show that, by utilizing the proposed scheme, the resistance to attackers can be significantly enhanced in DD-OFDM-PON and LRCO-OFDM-PON systems without performance degradations.

Many-objective Groundwater Monitoring Network Design Using Bias-Aware Ensemble Kalman Filtering and Evolutionary Optimization

NASA Astrophysics Data System (ADS)

Kollat, J. B.; Reed, P. M.

2009-12-01

This study contributes the ASSIST (Adaptive Strategies for Sampling in Space and Time) framework for improving long-term groundwater monitoring decisions across space and time while accounting for the influences of systematic model errors (or predictive bias). The ASSIST framework combines contaminant flow-and-transport modeling, bias-aware ensemble Kalman filtering (EnKF) and many-objective evolutionary optimization. Our goal in this work is to provide decision makers with a fuller understanding of the information tradeoffs they must confront when performing long-term groundwater monitoring network design. Our many-objective analysis considers up to 6 design objectives simultaneously and consequently synthesizes prior monitoring network design methodologies into a single, flexible framework. This study demonstrates the ASSIST framework using a tracer study conducted within a physical aquifer transport experimental tank located at the University of Vermont. The tank tracer experiment was extensively sampled to provide high resolution estimates of tracer plume behavior. The simulation component of the ASSIST framework consists of stochastic ensemble flow-and-transport predictions using ParFlow coupled with the Lagrangian SLIM transport model. The ParFlow and SLIM ensemble predictions are conditioned with tracer observations using a bias-aware EnKF. The EnKF allows decision makers to enhance plume transport predictions in space and time in the presence of uncertain and biased model predictions by conditioning them on uncertain measurement data. In this initial demonstration, the position and frequency of sampling were optimized to: (i) minimize monitoring cost, (ii) maximize information provided to the EnKF, (iii) minimize failure to detect the tracer, (iv) maximize the detection of tracer flux, (v) minimize error in quantifying tracer mass, and (vi) minimize error in quantifying the moment of the tracer plume. The results demonstrate that the many-objective problem formulation provides a tremendous amount of information for decision makers. Specifically our many-objective analysis highlights the limitations and potentially negative design consequences of traditional single and two-objective problem formulations. These consequences become apparent through visual exploration of high-dimensional tradeoffs and the identification of regions with interesting compromise solutions. The prediction characteristics of these compromise designs are explored in detail, as well as their implications for subsequent design decisions in both space and time.

Encouraging information sharing to boost the name-your-own-price auction

NASA Astrophysics Data System (ADS)

Chen, Yahong; Li, Jinlin; Huang, He; Ran, Lun; Hu, Yusheng

2017-08-01

During a name-your-own-price (NYOP) auction, buyers can learn a lot of knowledge from their socially connected peers. Such social learning process makes them become more active to attend the auction and also helps them make decisions on what price to submit. Combining an information diffusion model and a belief decision model, we explore three effects of bidders' information sharing on the buyers' behaviors and the seller profit. The results indicate that information sharing significantly increases the NYOP popularity and the seller profit. When enlarging the quality or quantity of information sharing, or increasing the spreading efficiency of the network topology, the number of attenders and the seller profit are increased significantly. However, the spread of information may make bidders be more likely to bid higher and consequently lose surplus. In addition, the different but interdependent influence of the successful information and failure information are discussed in this work.

Concordant Chemical Reaction Networks and the Species-Reaction Graph

PubMed Central

Shinar, Guy; Feinberg, Martin

2015-01-01

In a recent paper it was shown that, for chemical reaction networks possessing a subtle structural property called concordance, dynamical behavior of a very circumscribed (and largely stable) kind is enforced, so long as the kinetics lies within the very broad and natural weakly monotonic class. In particular, multiple equilibria are precluded, as are degenerate positive equilibria. Moreover, under certain circumstances, also related to concordance, all real eigenvalues associated with a positive equilibrium are negative. Although concordance of a reaction network can be decided by readily available computational means, we show here that, when a nondegenerate network’s Species-Reaction Graph satisfies certain mild conditions, concordance and its dynamical consequences are ensured. These conditions are weaker than earlier ones invoked to establish kinetic system injectivity, which, in turn, is just one ramification of network concordance. Because the Species-Reaction Graph resembles pathway depictions often drawn by biochemists, results here expand the possibility of inferring significant dynamical information directly from standard biochemical reaction diagrams. PMID:22940368

Design of nodes for embedded and ultra low-power wireless sensor networks

NASA Astrophysics Data System (ADS)

Xu, Jun; You, Bo; Cui, Juan; Ma, Jing; Li, Xin

2008-10-01

Sensor network integrates sensor technology, MEMS (Micro-Electro-Mechanical system) technology, embedded computing, wireless communication technology and distributed information management technology. It is of great value to use it where human is quite difficult to reach. Power consumption and size are the most important consideration when nodes are designed for distributed WSN (wireless sensor networks). Consequently, it is of great importance to decrease the size of a node, reduce its power consumption and extend its life in network. WSN nodes have been designed using JN5121-Z01-M01 module produced by jennic company and IEEE 802.15.4/ZigBee technology. Its new features include support for CPU sleep modes and a long-term ultra low power sleep mode for the entire node. In low power configuration the node resembles existing small low power nodes. An embedded temperature sensor node has been developed to verify and explore our architecture. The experiment results indicate that the WSN has the characteristic of high reliability, good stability and ultra low power consumption.

A Scalable Distribution Network Risk Evaluation Framework via Symbolic Dynamics

PubMed Central

Yuan, Kai; Liu, Jian; Liu, Kaipei; Tan, Tianyuan

2015-01-01

Background Evaluations of electric power distribution network risks must address the problems of incomplete information and changing dynamics. A risk evaluation framework should be adaptable to a specific situation and an evolving understanding of risk. Methods This study investigates the use of symbolic dynamics to abstract raw data. After introducing symbolic dynamics operators, Kolmogorov-Sinai entropy and Kullback-Leibler relative entropy are used to quantitatively evaluate relationships between risk sub-factors and main factors. For layered risk indicators, where the factors are categorized into four main factors – device, structure, load and special operation – a merging algorithm using operators to calculate the risk factors is discussed. Finally, an example from the Sanya Power Company is given to demonstrate the feasibility of the proposed method. Conclusion Distribution networks are exposed and can be affected by many things. The topology and the operating mode of a distribution network are dynamic, so the faults and their consequences are probabilistic. PMID:25789859

Mineralization/Anti-Mineralization Networks in the Skin and Vascular Connective Tissues

PubMed Central

Li, Qiaoli; Uitto, Jouni

2014-01-01

Ectopic mineralization has been linked to several common clinical conditions with considerable morbidity and mortality. The mineralization processes, both metastatic and dystrophic, affect the skin and vascular connective tissues. There are several contributing metabolic and environmental factors that make uncovering of the precise pathomechanisms of these acquired disorders exceedingly difficult. Several relatively rare heritable disorders share phenotypic manifestations similar to those in common conditions, and, consequently, they serve as genetically controlled model systems to study the details of the mineralization process in peripheral tissues. This overview will highlight diseases with mineral deposition in the skin and vascular connective tissues, as exemplified by familial tumoral calcinosis, pseudoxanthoma elasticum, generalized arterial calcification of infancy, and arterial calcification due to CD73 deficiency. These diseases, and their corresponding mouse models, provide insight into the pathomechanisms of soft tissue mineralization and point to the existence of intricate mineralization/anti-mineralization networks in these tissues. This information is critical for understanding the pathomechanistic details of different mineralization disorders, and it has provided the perspective to develop pharmacological approaches to counteract the consequences of ectopic mineralization. PMID:23665350

Mobile sociology. 2000.

PubMed

Urry, John

2010-01-01

This article seeks to develop a manifesto for a sociology concerned with the diverse mobilities of peoples, objects, images, information, and wastes; and of the complex interdependencies between, and social consequences of, such diverse mobilities. A number of key concepts relevant for such a sociology are elaborated: 'gamekeeping', networks, fluids, scapes, flows, complexity and iteration. The article concludes by suggesting that a 'global civil society' might constitute the social base of a sociology of mobilities as we move into the twenty-first century.

A Framework for Network Visualisation (Un Cadre Pour la Visualisation des Reseaux)

DTIC Science & Technology

2010-02-01

Business, Communities, and Government” (online), http://www.orgnet.com/inflow3.html (Access Date: 13 June 2008). [32] Batagelj , V., Mrvar , A. and...and NATO Workshops 1996 – 2008 1-7 Table 2-1 Perceptual Modes and Probable Display and Interaction Consequences 2-18 Table 2-2 Informational...RSG) was created in 1996 with the aim of developing methods for presenting to human users the implications of the contents of large, complex and

Mnemonic transmission, social contagion, and emergence of collective memory: Influence of emotional valence, group structure, and information distribution.

PubMed

Choi, Hae-Yoon; Kensinger, Elizabeth A; Rajaram, Suparna

2017-09-01

Social transmission of memory and its consequence on collective memory have generated enduring interdisciplinary interest because of their widespread significance in interpersonal, sociocultural, and political arenas. We tested the influence of 3 key factors-emotional salience of information, group structure, and information distribution-on mnemonic transmission, social contagion, and collective memory. Participants individually studied emotionally salient (negative or positive) and nonemotional (neutral) picture-word pairs that were completely shared, partially shared, or unshared within participant triads, and then completed 3 consecutive recalls in 1 of 3 conditions: individual-individual-individual (control), collaborative-collaborative (identical group; insular structure)-individual, and collaborative-collaborative (reconfigured group; diverse structure)-individual. Collaboration enhanced negative memories especially in insular group structure and especially for shared information, and promoted collective forgetting of positive memories. Diverse group structure reduced this negativity effect. Unequally distributed information led to social contagion that creates false memories; diverse structure propagated a greater variety of false memories whereas insular structure promoted confidence in false recognition and false collective memory. A simultaneous assessment of network structure, information distribution, and emotional valence breaks new ground to specify how network structure shapes the spread of negative memories and false memories, and the emergence of collective memory. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Cyber-Physical System Security With Deceptive Virtual Hosts for Industrial Control Networks

DOE PAGES

Vollmer, Todd; Manic, Milos

2014-05-01

A challenge facing industrial control network administrators is protecting the typically large number of connected assets for which they are responsible. These cyber devices may be tightly coupled with the physical processes they control and human induced failures risk dire real-world consequences. Dynamic virtual honeypots are effective tools for observing and attracting network intruder activity. This paper presents a design and implementation for self-configuring honeypots that passively examine control system network traffic and actively adapt to the observed environment. In contrast to prior work in the field, six tools were analyzed for suitability of network entity information gathering. Ettercap, anmore » established network security tool not commonly used in this capacity, outperformed the other tools and was chosen for implementation. Utilizing Ettercap XML output, a novel four-step algorithm was developed for autonomous creation and update of a Honeyd configuration. This algorithm was tested on an existing small campus grid and sensor network by execution of a collaborative usage scenario. Automatically created virtual hosts were deployed in concert with an anomaly behavior (AB) system in an attack scenario. Virtual hosts were automatically configured with unique emulated network stack behaviors for 92% of the targeted devices. The AB system alerted on 100% of the monitored emulated devices.« less

Ranking in evolving complex networks

NASA Astrophysics Data System (ADS)

Liao, Hao; Mariani, Manuel Sebastian; Medo, Matúš; Zhang, Yi-Cheng; Zhou, Ming-Yang

2017-05-01

Complex networks have emerged as a simple yet powerful framework to represent and analyze a wide range of complex systems. The problem of ranking the nodes and the edges in complex networks is critical for a broad range of real-world problems because it affects how we access online information and products, how success and talent are evaluated in human activities, and how scarce resources are allocated by companies and policymakers, among others. This calls for a deep understanding of how existing ranking algorithms perform, and which are their possible biases that may impair their effectiveness. Many popular ranking algorithms (such as Google's PageRank) are static in nature and, as a consequence, they exhibit important shortcomings when applied to real networks that rapidly evolve in time. At the same time, recent advances in the understanding and modeling of evolving networks have enabled the development of a wide and diverse range of ranking algorithms that take the temporal dimension into account. The aim of this review is to survey the existing ranking algorithms, both static and time-aware, and their applications to evolving networks. We emphasize both the impact of network evolution on well-established static algorithms and the benefits from including the temporal dimension for tasks such as prediction of network traffic, prediction of future links, and identification of significant nodes.

Disaster management and mitigation: the telecommunications infrastructure.

PubMed

Patricelli, Frédéric; Beakley, James E; Carnevale, Angelo; Tarabochia, Marcello; von Lubitz, Dag K J E

2009-03-01

Among the most typical consequences of disasters is the near or complete collapse of terrestrial telecommunications infrastructures (especially the distribution network--the 'last mile') and their concomitant unavailability to the rescuers and the higher echelons of mitigation teams. Even when such damage does not take place, the communications overload/congestion resulting from significantly elevated traffic generated by affected residents can be highly disturbing. The paper proposes innovative remedies to the telecommunications difficulties in disaster struck regions. The offered solutions are network-centric operations-cap able, and can be employed in management of disasters of any magnitude (local to national or international). Their implementation provide ground rescue teams (such as law enforcement, firemen, healthcare personnel, civilian authorities) with tactical connectivity among themselves, and, through the Next Generation Network backbone, ensure the essential bidirectional free flow of information and distribution of Actionable Knowledge among ground units, command/control centres, and civilian and military agencies participating in the rescue effort.

Cart'Eaux: an automatic mapping procedure for wastewater networks using machine learning and data mining

NASA Astrophysics Data System (ADS)

Bailly, J. S.; Delenne, C.; Chahinian, N.; Bringay, S.; Commandré, B.; Chaumont, M.; Derras, M.; Deruelle, L.; Roche, M.; Rodriguez, F.; Subsol, G.; Teisseire, M.

2017-12-01

In France, local government institutions must establish a detailed description of wastewater networks. The information should be available, but it remains fragmented (different formats held by different stakeholders) and incomplete. In the "Cart'Eaux" project, a multidisciplinary team, including an industrial partner, develops a global methodology using Machine Learning and Data Mining approaches applied to various types of large data to recover information in the aim of mapping urban sewage systems for hydraulic modelling. Deep-learning is first applied using a Convolution Neural Network to localize manhole covers on 5 cm resolution aerial RGB images. The detected manhole covers are then automatically connected using a tree-shaped graph constrained by industry rules. Based on a Delaunay triangulation, connections are chosen to minimize a cost function depending on pipe length, slope and possible intersection with roads or buildings. A stochastic version of this algorithm is currently being developed to account for positional uncertainty and detection errors, and generate sets of probable networks. As more information is required for hydraulic modeling (slopes, diameters, materials, etc.), text data mining is used to extract network characteristics from data posted on the Web or available through governmental or specific databases. Using an appropriate list of keywords, the web is scoured for documents which are saved in text format. The thematic entities are identified and linked to the surrounding spatial and temporal entities. The methodology is developed and tested on two towns in southern France. The primary results are encouraging: 54% of manhole covers are detected with few false detections, enabling the reconstruction of probable networks. The data mining results are still being investigated. It is clear at this stage that getting numerical values on specific pipes will be challenging. Thus, when no information is found, decision rules will be used to assign admissible numerical values to enable the final hydraulic modelling. Consequently, sensitivity analysis of the hydraulic model will be performed to take into account the uncertainty associated with each piece of information. Project funded by the European Regional Development Fund and the Occitanie Region.

Artificial astrocytes improve neural network performance.

PubMed

Porto-Pazos, Ana B; Veiguela, Noha; Mesejo, Pablo; Navarrete, Marta; Alvarellos, Alberto; Ibáñez, Oscar; Pazos, Alejandro; Araque, Alfonso

2011-04-19

Compelling evidence indicates the existence of bidirectional communication between astrocytes and neurons. Astrocytes, a type of glial cells classically considered to be passive supportive cells, have been recently demonstrated to be actively involved in the processing and regulation of synaptic information, suggesting that brain function arises from the activity of neuron-glia networks. However, the actual impact of astrocytes in neural network function is largely unknown and its application in artificial intelligence remains untested. We have investigated the consequences of including artificial astrocytes, which present the biologically defined properties involved in astrocyte-neuron communication, on artificial neural network performance. Using connectionist systems and evolutionary algorithms, we have compared the performance of artificial neural networks (NN) and artificial neuron-glia networks (NGN) to solve classification problems. We show that the degree of success of NGN is superior to NN. Analysis of performances of NN with different number of neurons or different architectures indicate that the effects of NGN cannot be accounted for an increased number of network elements, but rather they are specifically due to astrocytes. Furthermore, the relative efficacy of NGN vs. NN increases as the complexity of the network increases. These results indicate that artificial astrocytes improve neural network performance, and established the concept of Artificial Neuron-Glia Networks, which represents a novel concept in Artificial Intelligence with implications in computational science as well as in the understanding of brain function.

Artificial Astrocytes Improve Neural Network Performance

PubMed Central

Porto-Pazos, Ana B.; Veiguela, Noha; Mesejo, Pablo; Navarrete, Marta; Alvarellos, Alberto; Ibáñez, Oscar; Pazos, Alejandro; Araque, Alfonso

2011-01-01

Compelling evidence indicates the existence of bidirectional communication between astrocytes and neurons. Astrocytes, a type of glial cells classically considered to be passive supportive cells, have been recently demonstrated to be actively involved in the processing and regulation of synaptic information, suggesting that brain function arises from the activity of neuron-glia networks. However, the actual impact of astrocytes in neural network function is largely unknown and its application in artificial intelligence remains untested. We have investigated the consequences of including artificial astrocytes, which present the biologically defined properties involved in astrocyte-neuron communication, on artificial neural network performance. Using connectionist systems and evolutionary algorithms, we have compared the performance of artificial neural networks (NN) and artificial neuron-glia networks (NGN) to solve classification problems. We show that the degree of success of NGN is superior to NN. Analysis of performances of NN with different number of neurons or different architectures indicate that the effects of NGN cannot be accounted for an increased number of network elements, but rather they are specifically due to astrocytes. Furthermore, the relative efficacy of NGN vs. NN increases as the complexity of the network increases. These results indicate that artificial astrocytes improve neural network performance, and established the concept of Artificial Neuron-Glia Networks, which represents a novel concept in Artificial Intelligence with implications in computational science as well as in the understanding of brain function. PMID:21526157

Constraints of nonresponding flows based on cross layers in the networks

NASA Astrophysics Data System (ADS)

Zhou, Zhi-Chao; Xiao, Yang; Wang, Dong

2016-02-01

In the active queue management (AQM) scheme, core routers cannot manage and constrain user datagram protocol (UDP) data flows by the sliding window control mechanism in the transport layer due to the nonresponsive nature of such traffic flows. However, the UDP traffics occupy a large part of the network service nowadays which brings a great challenge to the stability of the more and more complex networks. To solve the uncontrollable problem, this paper proposes a cross layers random early detection (CLRED) scheme, which can control the nonresponding UDP-like flows rate effectively when congestion occurs in the access point (AP). The CLRED makes use of the MAC frame acknowledgement (ACK) transmitting congestion information to the sources nodes and utilizes the back-off windows of the MAC layer throttling data rate. Consequently, the UDP-like flows data rate can be restrained timely by the sources nodes in order to alleviate congestion in the complex networks. The proposed CLRED can constrain the nonresponsive flows availably and make the communication expedite, so that the network can sustain stable. The simulation results of network simulator-2 (NS2) verify the proposed CLRED scheme.

Optimality problem of network topology in stocks market analysis

NASA Astrophysics Data System (ADS)

Djauhari, Maman Abdurachman; Gan, Siew Lee

2015-02-01

Since its introduction fifteen years ago, minimal spanning tree has become an indispensible tool in econophysics. It is to filter the important economic information contained in a complex system of financial markets' commodities. Here we show that, in general, that tool is not optimal in terms of topological properties. Consequently, the economic interpretation of the filtered information might be misleading. To overcome that non-optimality problem, a set of criteria and a selection procedure of an optimal minimal spanning tree will be developed. By using New York Stock Exchange data, the advantages of the proposed method will be illustrated in terms of the power-law of degree distribution.

Literature Review on Modeling Cyber Networks and Evaluating Cyber Risks.

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

Kelic, Andjelka; Campbell, Philip L

The National Infrastructure Simulations and Analysis Center (NISAC) conducted a literature review on modeling cyber networks and evaluating cyber risks. The literature review explores where modeling is used in the cyber regime and ways that consequence and risk are evaluated. The relevant literature clusters in three different spaces: network security, cyber-physical, and mission assurance. In all approaches, some form of modeling is utilized at varying levels of detail, while the ability to understand consequence varies, as do interpretations of risk. This document summarizes the different literature viewpoints and explores their applicability to securing enterprise networks.

Unraveling the disease consequences and mechanisms of modular structure in animal social networks

PubMed Central

Leu, Stephan T.; Cross, Paul C.; Hudson, Peter J.; Bansal, Shweta

2017-01-01

Disease risk is a potential cost of group living. Although modular organization is thought to reduce this cost in animal societies, empirical evidence toward this hypothesis has been conflicting. We analyzed empirical social networks from 43 animal species to motivate our study of the epidemiological consequences of modular structure in animal societies. From these empirical studies, we identified the features of interaction patterns associated with network modularity and developed a theoretical network model to investigate when and how subdivisions in social networks influence disease dynamics. Contrary to prior work, we found that disease risk is largely unaffected by modular structure, although social networks beyond a modular threshold experience smaller disease burden and longer disease duration. Our results illustrate that the lowering of disease burden in highly modular social networks is driven by two mechanisms of modular organization: network fragmentation and subgroup cohesion. Highly fragmented social networks with cohesive subgroups are able to structurally trap infections within a few subgroups and also cause a structural delay to the spread of disease outbreaks. Finally, we show that network models incorporating modular structure are necessary only when prior knowledge suggests that interactions within the population are highly subdivided. Otherwise, null networks based on basic knowledge about group size and local contact heterogeneity may be sufficient when data-limited estimates of epidemic consequences are necessary. Overall, our work does not support the hypothesis that modular structure universally mitigates the disease impact of group living. PMID:28373567

Unraveling the disease consequences and mechanisms of modular structure in animal social networks

USGS Publications Warehouse

Sah, Pratha; Leu, Stephan T.; Cross, Paul C.; Hudson, Peter J.; Bansal, Shweta

2017-01-01

Disease risk is a potential cost of group living. Although modular organization is thought to reduce this cost in animal societies, empirical evidence toward this hypothesis has been conflicting. We analyzed empirical social networks from 43 animal species to motivate our study of the epidemiological consequences of modular structure in animal societies. From these empirical studies, we identified the features of interaction patterns associated with network modularity and developed a theoretical network model to investigate when and how subdivisions in social networks influence disease dynamics. Contrary to prior work, we found that disease risk is largely unaffected by modular structure, although social networks beyond a modular threshold experience smaller disease burden and longer disease duration. Our results illustrate that the lowering of disease burden in highly modular social networks is driven by two mechanisms of modular organization: network fragmentation and subgroup cohesion. Highly fragmented social networks with cohesive subgroups are able to structurally trap infections within a few subgroups and also cause a structural delay to the spread of disease outbreaks. Finally, we show that network models incorporating modular structure are necessary only when prior knowledge suggests that interactions within the population are highly subdivided. Otherwise, null networks based on basic knowledge about group size and local contact heterogeneity may be sufficient when data-limited estimates of epidemic consequences are necessary. Overall, our work does not support the hypothesis that modular structure universally mitigates the disease impact of group living.

Unraveling the disease consequences and mechanisms of modular structure in animal social networks.

PubMed

Sah, Pratha; Leu, Stephan T; Cross, Paul C; Hudson, Peter J; Bansal, Shweta

2017-04-18

Disease risk is a potential cost of group living. Although modular organization is thought to reduce this cost in animal societies, empirical evidence toward this hypothesis has been conflicting. We analyzed empirical social networks from 43 animal species to motivate our study of the epidemiological consequences of modular structure in animal societies. From these empirical studies, we identified the features of interaction patterns associated with network modularity and developed a theoretical network model to investigate when and how subdivisions in social networks influence disease dynamics. Contrary to prior work, we found that disease risk is largely unaffected by modular structure, although social networks beyond a modular threshold experience smaller disease burden and longer disease duration. Our results illustrate that the lowering of disease burden in highly modular social networks is driven by two mechanisms of modular organization: network fragmentation and subgroup cohesion. Highly fragmented social networks with cohesive subgroups are able to structurally trap infections within a few subgroups and also cause a structural delay to the spread of disease outbreaks. Finally, we show that network models incorporating modular structure are necessary only when prior knowledge suggests that interactions within the population are highly subdivided. Otherwise, null networks based on basic knowledge about group size and local contact heterogeneity may be sufficient when data-limited estimates of epidemic consequences are necessary. Overall, our work does not support the hypothesis that modular structure universally mitigates the disease impact of group living.

Network Access Control List Situation Awareness

ERIC Educational Resources Information Center

Reifers, Andrew

2010-01-01

Network security is a large and complex problem being addressed by multiple communities. Nevertheless, current theories in networking security appear to overestimate network administrators' ability to understand network access control lists (NACLs), providing few context specific user analyses. Consequently, the current research generally seems to…

Partnering with patients to realize the benefits of social media.

PubMed

Colbert, James A; Lehmann, Lisa Soleymani

2015-03-01

Despite widespread concern about the potential risks of the use of social media, we are optimistic that social networks and blogs have the potential to enhance the practice of medicine by allowing clinicians to share ideas and information within the health care community, with patients, and with the general public. In particular, we believe that there can be value in posting information related to a patient encounter on social media, but only if care has been taken to consider the consequences of such a post from the patient's perspective. Thus, having a discussion with a patient and obtaining verbal consent before posting even deidentified patient information should become standard practice for all physicians who use social media. Copyright © 2015 Elsevier Inc. All rights reserved.

Exploring Vietnamese co-authorship patterns in social sciences with basic network measures of 2008-2017 Scopus data.

PubMed

Ho, Tung Manh; Nguyen, Ha Viet; Vuong, Thu-Trang; Dam, Quang-Minh; Pham, Hiep-Hung; Vuong, Quan-Hoang

2017-01-01

Background: Collaboration is a common occurrence among Vietnamese scientists; however, insights into Vietnamese scientific collaborations have been scarce. On the other hand, the application of social network analysis in studying science collaboration has gained much attention all over the world. The technique could be employed to explore Vietnam's scientific community. Methods: This paper employs network theory to explore characteristics of a network of 412 Vietnamese social scientists whose papers can be found indexed in the Scopus database. Two basic network measures, density and clustering coefficient, were taken, and the entire network was studied in comparison with two of its largest components. Results: The networks connections are very sparse, with a density of only 0.47%, while the clustering coefficient is very high (58.64%). This suggests an inefficient dissemination of information, knowledge, and expertise in the network. Secondly, the disparity in levels of connection among individuals indicates that the network would easily fall apart if a few highly-connected nodes are removed. Finally, the two largest components of the network were found to differ from the entire networks in terms of measures and were both led by the most productive and well-connected researchers. Conclusions: High clustering and low density seems to be tied to inefficient dissemination of expertise among Vietnamese social scientists, and consequently low scientific output. Also low in robustness, the network shows the potential of an intellectual elite composed of well-connected, productive, and socially significant individuals.

Exploring Vietnamese co-authorship patterns in social sciences with basic network measures of 2008-2017 Scopus data

PubMed Central

Ho, Tung Manh; Nguyen, Ha Viet; Vuong, Thu-Trang; Dam, Quang-Minh; Pham, Hiep-Hung; Vuong, Quan-Hoang

2017-01-01

Background: Collaboration is a common occurrence among Vietnamese scientists; however, insights into Vietnamese scientific collaborations have been scarce. On the other hand, the application of social network analysis in studying science collaboration has gained much attention all over the world. The technique could be employed to explore Vietnam’s scientific community. Methods: This paper employs network theory to explore characteristics of a network of 412 Vietnamese social scientists whose papers can be found indexed in the Scopus database. Two basic network measures, density and clustering coefficient, were taken, and the entire network was studied in comparison with two of its largest components. Results: The networks connections are very sparse, with a density of only 0.47%, while the clustering coefficient is very high (58.64%). This suggests an inefficient dissemination of information, knowledge, and expertise in the network. Secondly, the disparity in levels of connection among individuals indicates that the network would easily fall apart if a few highly-connected nodes are removed. Finally, the two largest components of the network were found to differ from the entire networks in terms of measures and were both led by the most productive and well-connected researchers. Conclusions: High clustering and low density seems to be tied to inefficient dissemination of expertise among Vietnamese social scientists, and consequently low scientific output. Also low in robustness, the network shows the potential of an intellectual elite composed of well-connected, productive, and socially significant individuals. PMID:28928958

Current progress in multiple-image blind demixing algorithms

NASA Astrophysics Data System (ADS)

Szu, Harold H.

2000-06-01

Imagery edges occur naturally in human visual systems as a consequence of redundancy reduction towards `sparse and orthogonality feature maps,' which have been recently derived from the maximum entropy information-theoretical first principle of artificial neural networks. After a brief match review of such an Independent Component Analysis or Blind Source Separation of edge maps, we explore the de- mixing condition for more than two imagery objects recognizable by an intelligent pair of cameras with memory in a time-multiplex fashion.

A case analysis of INFOMED: the Cuban national health care telecommunications network and portal.

PubMed

Séror, Ann C

2006-01-27

The Internet and telecommunications technologies contribute to national health care system infrastructures and extend global health care services markets. The Cuban national health care system offers a model to show how a national information portal can contribute to system integration, including research, education, and service delivery as well as international trade in products and services. The objectives of this paper are (1) to present the context of the Cuban national health care system since the revolution in 1959, (2) to identify virtual institutional infrastructures of the system associated with the Cuban National Health Care Telecommunications Network and Portal (INFOMED), and (3) to show how they contribute to Cuban trade in international health care service markets. Qualitative case research methods were used to identify the integrated virtual infrastructure of INFOMED and to show how it reflects socialist ideology. Virtual institutional infrastructures include electronic medical and information services and the structure of national networks linking such services. Analysis of INFOMED infrastructures shows integration of health care information, research, and education as well as the interface between Cuban national information networks and the global Internet. System control mechanisms include horizontal integration and coordination through virtual institutions linked through INFOMED, and vertical control through the Ministry of Public Health and the government hierarchy. Telecommunications technology serves as a foundation for a dual market structure differentiating domestic services from international trade. INFOMED is a model of interest for integrating health care information, research, education, and services. The virtual infrastructures linked through INFOMED support the diffusion of Cuban health care products and services in global markets. Transferability of this model is contingent upon ideology and interpretation of values such as individual intellectual property and confidentiality of individual health information. Future research should focus on examination of these issues and their consequences for global markets in health care.

A Case Analysis of INFOMED: The Cuban National Health Care Telecommunications Network and Portal

PubMed Central

2006-01-01

Background The Internet and telecommunications technologies contribute to national health care system infrastructures and extend global health care services markets. The Cuban national health care system offers a model to show how a national information portal can contribute to system integration, including research, education, and service delivery as well as international trade in products and services. Objective The objectives of this paper are (1) to present the context of the Cuban national health care system since the revolution in 1959, (2) to identify virtual institutional infrastructures of the system associated with the Cuban National Health Care Telecommunications Network and Portal (INFOMED), and (3) to show how they contribute to Cuban trade in international health care service markets. Methods Qualitative case research methods were used to identify the integrated virtual infrastructure of INFOMED and to show how it reflects socialist ideology. Virtual institutional infrastructures include electronic medical and information services and the structure of national networks linking such services. Results Analysis of INFOMED infrastructures shows integration of health care information, research, and education as well as the interface between Cuban national information networks and the global Internet. System control mechanisms include horizontal integration and coordination through virtual institutions linked through INFOMED, and vertical control through the Ministry of Public Health and the government hierarchy. Telecommunications technology serves as a foundation for a dual market structure differentiating domestic services from international trade. Conclusions INFOMED is a model of interest for integrating health care information, research, education, and services. The virtual infrastructures linked through INFOMED support the diffusion of Cuban health care products and services in global markets. Transferability of this model is contingent upon ideology and interpretation of values such as individual intellectual property and confidentiality of individual health information. Future research should focus on examination of these issues and their consequences for global markets in health care. PMID:16585025

Understanding veterinary students' use of and attitudes toward the social networking site, Facebook, to assist in developing curricula to address online professionalism.

PubMed

Coe, Jason B; Weijs, Cynthia A; Muise, Amy; Christofides, Emily; Desmarais, Serge

2012-01-01

Social media is an increasingly common form of communication, with Facebook being the preferred social-networking site among post-secondary students. Numerous studies suggest post-secondary students practice high self-disclosure on Facebook. Research evaluating veterinary students' use of social media found a notable proportion of student-posted content deemed inappropriate. Lack of discretion in posting content can have significant repercussions for aspiring veterinary professionals, their college of study, and the veterinary profession they represent. Veterinarians-in-training at three veterinary colleges across Canada were surveyed to explore their use of and attitude toward the social networking site, Facebook. Students were invited to complete an online survey with questions relating to their knowledge of privacy in relation to using Facebook, their views on the acceptability of posting certain types of information, and their level of professional accountability online. Linear regression modeling was used to further examine factors related to veterinary students' disclosure of personal information on Facebook. Need for popularity (p<.01) and awareness of consequences (p<.001) were found to be positively and negatively associated, respectively, with students' personal disclosure of information on Facebook. Understanding veterinary students' use of and attitudes toward social media, such as Facebook, reveals a need, and provides a basis, for developing educational programs to address online professionalism. Educators and administrators at veterinary schools may use this information to assist in developing veterinary curricula that addresses the escalating issue of online professionalism.

Exploring the evolution of node neighborhoods in Dynamic Networks

NASA Astrophysics Data System (ADS)

Orman, Günce Keziban; Labatut, Vincent; Naskali, Ahmet Teoman

2017-09-01

Dynamic Networks are a popular way of modeling and studying the behavior of evolving systems. However, their analysis constitutes a relatively recent subfield of Network Science, and the number of available tools is consequently much smaller than for static networks. In this work, we propose a method specifically designed to take advantage of the longitudinal nature of dynamic networks. It characterizes each individual node by studying the evolution of its direct neighborhood, based on the assumption that the way this neighborhood changes reflects the role and position of the node in the whole network. For this purpose, we define the concept of neighborhood event, which corresponds to the various transformations such groups of nodes can undergo, and describe an algorithm for detecting such events. We demonstrate the interest of our method on three real-world networks: DBLP, LastFM and Enron. We apply frequent pattern mining to extract meaningful information from temporal sequences of neighborhood events. This results in the identification of behavioral trends emerging in the whole network, as well as the individual characterization of specific nodes. We also perform a cluster analysis, which reveals that, in all three networks, one can distinguish two types of nodes exhibiting different behaviors: a very small group of active nodes, whose neighborhood undergo diverse and frequent events, and a very large group of stable nodes.

Analysis of the enzyme network involved in cattle milk production using graph theory.

PubMed

Ghorbani, Sholeh; Tahmoorespur, Mojtaba; Masoudi Nejad, Ali; Nasiri, Mohammad; Asgari, Yazdan

2015-06-01

Understanding cattle metabolism and its relationship with milk products is important in bovine breeding. A systemic view could lead to consequences that will result in a better understanding of existing concepts. Topological indices and quantitative characterizations mostly result from the application of graph theory on biological data. In the present work, the enzyme network involved in cattle milk production was reconstructed and analyzed based on available bovine genome information using several public datasets (NCBI, Uniprot, KEGG, and Brenda). The reconstructed network consisted of 3605 reactions named by KEGG compound numbers and 646 enzymes that catalyzed the corresponding reactions. The characteristics of the directed and undirected network were analyzed using Graph Theory. The mean path length was calculated to be4.39 and 5.41 for directed and undirected networks, respectively. The top 11 hub enzymes whose abnormality could harm bovine health and reduce milk production were determined. Therefore, the aim of constructing the enzyme centric network was twofold; first to find out whether such network followed the same properties of other biological networks, and second, to find the key enzymes. The results of the present study can improve our understanding of milk production in cattle. Also, analysis of the enzyme network can help improve the modeling and simulation of biological systems and help design desired phenotypes to increase milk production quality or quantity.

A perspective on the advancement of natural language processing tasks via topological analysis of complex networks. Comment on "Approaching human language with complex networks" by Cong and Liu

NASA Astrophysics Data System (ADS)

Amancio, Diego Raphael

2014-12-01

Concepts and methods of complex networks have been applied to probe the properties of a myriad of real systems [1]. The finding that written texts modeled as graphs share several properties of other completely different real systems has inspired the study of language as a complex system [2]. Actually, language can be represented as a complex network in its several levels of complexity. As a consequence, morphological, syntactical and semantical properties have been employed in the construction of linguistic networks [3]. Even the character level has been useful to unfold particular patterns [4,5]. In the review by Cong and Liu [6], the authors emphasize the need to use the topological information of complex networks modeling the various spheres of the language to better understand its origins, evolution and organization. In addition, the authors cite the use of networks in applications aiming at holistic typology and stylistic variations. In this context, I will discuss some possible directions that could be followed in future research directed towards the understanding of language via topological characterization of complex linguistic networks. In addition, I will comment the use of network models for language processing applications. Additional prospects for future practical research lines will also be discussed in this comment.

Supply network science: Emergence of a new perspective on a classical field

NASA Astrophysics Data System (ADS)

Brintrup, Alexandra; Ledwoch, Anna

2018-03-01

Supply networks emerge as companies procure goods from one another to produce their own products. Due to a chronic lack of data, studies on these emergent structures have long focussed on local neighbourhoods, assuming simple, chain-like structures. However, studies conducted since 2001 have shown that supply chains are indeed complex networks that exhibit similar organisational patterns to other network types. In this paper, we present a critical review of theoretical and model based studies which conceptualise supply chains from a network science perspective, showing that empirical data do not always support theoretical models that were developed, and argue that different industrial settings may present different characteristics. Consequently, a need that arises is the development and reconciliation of interpretation across different supply network layers such as contractual relations, material flow, financial links, and co-patenting, as these different projections tend to remain in disciplinary siloes. Other gaps include a lack of null models that show whether the observed properties are meaningful, a lack of dynamical models that can inform how layers evolve and adopt to changes, and a lack of studies that investigate how local decisions enable emergent outcomes. We conclude by asking the network science community to help bridge these gaps by engaging with this important area of research.

Supply network science: Emergence of a new perspective on a classical field.

PubMed

Brintrup, Alexandra; Ledwoch, Anna

2018-03-01

Supply networks emerge as companies procure goods from one another to produce their own products. Due to a chronic lack of data, studies on these emergent structures have long focussed on local neighbourhoods, assuming simple, chain-like structures. However, studies conducted since 2001 have shown that supply chains are indeed complex networks that exhibit similar organisational patterns to other network types. In this paper, we present a critical review of theoretical and model based studies which conceptualise supply chains from a network science perspective, showing that empirical data do not always support theoretical models that were developed, and argue that different industrial settings may present different characteristics. Consequently, a need that arises is the development and reconciliation of interpretation across different supply network layers such as contractual relations, material flow, financial links, and co-patenting, as these different projections tend to remain in disciplinary siloes. Other gaps include a lack of null models that show whether the observed properties are meaningful, a lack of dynamical models that can inform how layers evolve and adopt to changes, and a lack of studies that investigate how local decisions enable emergent outcomes. We conclude by asking the network science community to help bridge these gaps by engaging with this important area of research.

[Problems encountered by hospital pharmacists with information systems: Analysis of exchanges within social networks].

PubMed

Charpiat, B; Mille, F; Fombeur, P; Machon, J; Zawadzki, E; Bobay-Madic, A

2018-05-21

The development of information systems in French hospitals is mandatory. The aim of this work was to analyze the content of exchanges carried out within social networks, dealing with problems encountered with hospital pharmacies information systems. Messages exchanged via the mailing list of the Association pour le Digital et l'Information en Pharmacie and abstracts of communications presented at hospital pharmacists trade union congresses were analyzed. Those referring to information systems used in hospital pharmacies were selected. From March 2015 to June 2016, 122 e-mails sent by 80 pharmacists concerned information systems. From 2002 to 2016, 45 abstracts dealt with this topic. Problems most often addressed in these 167 documents were "parameterization and/or functionalities" (n=116), interfaces and complexity of the hospital information systems (n=52), relationship with health information technologies vendors and poor reactivity (n=32), additional workload (n=32), ergonomics (n=30), insufficient user training (n=22). These problems are interdependent, lead to errors and in order to mitigate their consequences, they compel pharmacy professionals to divert a significant amount of working hours to the detriment of pharmaceutical care and dispensing and preparing drugs. Hospital pharmacists are faced with many problems of insecurity and inefficiency generated by information systems. Researches are warranted to determine their cost, specify their deleterious effects on care and identify the safest information systems. Copyright © 2018 Académie Nationale de Pharmacie. Published by Elsevier Masson SAS. All rights reserved.

Informing the implementation of evidence-informed decision making interventions using a social network analysis perspective; a mixed-methods study.

PubMed

Yousefi Nooraie, Reza; Lohfeld, Lynne; Marin, Alexandra; Hanneman, Robert; Dobbins, Maureen

2017-02-08

Workforce development is an important aspect of evidence-informed decision making (EIDM) interventions. The structure of formal and informal social networks can influence, and be influenced, by the implementation of EIDM interventions. In a mixed methods study we assessed the outcomes of a targeted training intervention to promote EIDM among the staff in three public health units in Ontario, Canada. This report focuses on the qualitative phase of the study in which key staff were interviewed about the process of engagement in the intervention, communications during the intervention, and social consequences. Senior managers identified staff to take part in the intervention. Engagement was a top-down process determined by the way organizational leaders promoted EIDM and the relevance of staff's jobs to EIDM. Communication among staff participating in the workshops and ongoing progress meetings was influential in overcoming personal and normative barriers to implementing EIDM, and promoted the formation of long-lasting social connections among staff. Organization-wide presentations and meetings facilitated the recognition of expertise that the trained staff gained, including their reputation as experts according to their peers in different divisions. Selective training and capacity development interventions can result in forming an elite versus ordinary pattern that facilitates the recognition of in-house qualified experts while also strengthening social status inequality. The role of leadership in public health units is pivotal in championing and overseeing the implementation process. Network analysis can guide and inform the design, process, and evaluation of the EIDM training interventions.

Modelling dendritic ecological networks in space: An integrated network perspective

Treesearch

Erin E. Peterson; Jay M. Ver Hoef; Dan J. Isaak; Jeffrey A. Falke; Marie-Josee Fortin; Chris E. Jordan; Kristina McNyset; Pascal Monestiez; Aaron S. Ruesch; Aritra Sengupta; Nicholas Som; E. Ashley Steel; David M. Theobald; Christian E. Torgersen; Seth J. Wenger

2013-01-01

Dendritic ecological networks (DENs) are a unique form of ecological networks that exhibit a dendritic network topology (e.g. stream and cave networks or plant architecture). DENs have a dual spatial representation; as points within the network and as points in geographical space. Consequently, some analytical methods used to quantify relationships in other types of...

The evolution of social networks through the implementation of evidence-informed decision-making interventions: a longitudinal analysis of three public health units in Canada.

PubMed

Yousefi-Nooraie, Reza; Dobbins, Maureen; Marin, Alexandra; Hanneman, Robert; Lohfeld, Lynne

2015-12-03

We studied the evolution of information-seeking networks over a 2-year period during which an organization-wide intervention was implemented to promote evidence-informed decision-making (EIDM) in three public health units in Ontario, Canada. We tested whether engagement of staff in the intervention and their EIDM behavior were associated with being chosen as information source and how the trend of inter-divisional communications and the dominance of experts evolved over time. Local managers at each health unit selected a group of staff to get engage in Knowledge Broker-led workshops and development of evidence summaries to address local public health problems. The staff were invited to answer three online surveys (at baseline and two annual follow-ups) including name generator questions eliciting the list of the staff they would turn to for help integrating research evidence into practice. We used stochastic actor-oriented modeling to study the evolution of networks. We tested the effect of engagement in the intervention, EIDM behavior scores, organizational divisions, and structural dynamics of social networks on the tendency of staff to select information sources, and the change in its trend between year 1 and year 2 of follow-up. In all the three health units, and especially in the two units with higher levels of engagement in the intervention, the network evolved towards a more centralized structure, with an increasing significance of already central staff. The staff showed greater tendencies to seek information from peers with higher EIDM behavior scores. In the public health unit that had highest engagement and stronger leadership support, the engaged staff became more central. In all public health units, the engaged staff showed an increasing tendency towards forming clusters. The staff in the three public health units showed a tendency towards limiting their connections within their divisions. The longitudinal analysis provided us with a means to study the microstructural changes in public health units, clues to the sustainability of the implementation. The hierarchical transformation of networks towards experts and formation of clusters among staff who were engaged in the intervention show how implementing organizational interventions to promote EIDM may affect the knowledge flow and distribution in health care communities, which may lead to unanticipated consequences.

Recommendations to harmonize European early warning dosimetry network systems

NASA Astrophysics Data System (ADS)

Dombrowski, H.; Bleher, M.; De Cort, M.; Dabrowski, R.; Neumaier, S.; Stöhlker, U.

2017-12-01

After the Chernobyl nuclear power plant accident in 1986, followed by the Fukushima Nuclear power plant accident 25 years later, it became obvious that real-time information is required to quickly gain radiological information. As a consequence, the European countries established early warning network systems with the aim to provide an immediate warning in case of a major radiological emergency, to supply reliable information on area dose rates, contamination levels, radioactivity concentrations in air and finally to assess public exposure. This is relevant for governmental decisions on intervention measures in an emergency situation. Since different methods are used by national environmental monitoring systems to measure area dose rate values and activity concentrations, there are significant differences in the results provided by different countries. Because European and neighboring countries report area dose rate data to a central data base operated on behalf of the European Commission, the comparability of the data is crucial for its meaningful interpretation, especially in the case of a nuclear accident with transboundary implications. Only by harmonizing measuring methods and data evaluation, is the comparability of the dose rate data ensured. This publication concentrates on technical requirements and methods with the goal to effectively harmonize area dose rate monitoring data provided by automatic early warning network systems. The requirements and procedures laid down in this publication are based on studies within the MetroERM project, taking into account realistic technical approaches and tested procedures.

TBC2health: a database of experimentally validated health-beneficial effects of tea bioactive compounds.

PubMed

Zhang, Shihua; Xuan, Hongdong; Zhang, Liang; Fu, Sicong; Wang, Yijun; Yang, Hua; Tai, Yuling; Song, Youhong; Zhang, Jinsong; Ho, Chi-Tang; Li, Shaowen; Wan, Xiaochun

2017-09-01

Tea is one of the most consumed beverages in the world. Considerable studies show the exceptional health benefits (e.g. antioxidation, cancer prevention) of tea owing to its various bioactive components. However, data from these extensively published papers had not been made available in a central database. To lay a foundation in improving the understanding of healthy tea functions, we established a TBC2health database that currently documents 1338 relationships between 497 tea bioactive compounds and 206 diseases (or phenotypes) manually culled from over 300 published articles. Each entry in TBC2health contains comprehensive information about a bioactive relationship that can be accessed in three aspects: (i) compound information, (ii) disease (or phenotype) information and (iii) evidence and reference. Using the curated bioactive relationships, a bipartite network was reconstructed and the corresponding network (or sub-network) visualization and topological analyses are provided for users. This database has a user-friendly interface for entry browse, search and download. In addition, TBC2health provides a submission page and several useful tools (e.g. BLAST, molecular docking) to facilitate use of the database. Consequently, TBC2health can serve as a valuable bioinformatics platform for the exploration of beneficial effects of tea on human health. TBC2health is freely available at http://camellia.ahau.edu.cn/TBC2health. © The Author 2016. Published by Oxford University Press.

Differentiating unipolar and bipolar depression by alterations in large-scale brain networks.

PubMed

Goya-Maldonado, Roberto; Brodmann, Katja; Keil, Maria; Trost, Sarah; Dechent, Peter; Gruber, Oliver

2016-02-01

Misdiagnosing bipolar depression can lead to very deleterious consequences of mistreatment. Although depressive symptoms may be similarly expressed in unipolar and bipolar disorder, changes in specific brain networks could be very distinct, being therefore informative markers for the differential diagnosis. We aimed to characterize specific alterations in candidate large-scale networks (frontoparietal, cingulo-opercular, and default mode) in symptomatic unipolar and bipolar patients using resting state fMRI, a cognitively low demanding paradigm ideal to investigate patients. Networks were selected after independent component analysis, compared across 40 patients acutely depressed (20 unipolar, 20 bipolar), and 20 controls well-matched for age, gender, and education levels, and alterations were correlated to clinical parameters. Despite comparable symptoms, patient groups were robustly differentiated by large-scale network alterations. Differences were driven in bipolar patients by increased functional connectivity in the frontoparietal network, a central executive and externally-oriented network. Conversely, unipolar patients presented increased functional connectivity in the default mode network, an introspective and self-referential network, as much as reduced connectivity of the cingulo-opercular network to default mode regions, a network involved in detecting the need to switch between internally and externally oriented demands. These findings were mostly unaffected by current medication, comorbidity, and structural changes. Moreover, network alterations in unipolar patients were significantly correlated to the number of depressive episodes. Unipolar and bipolar groups displaying similar symptomatology could be clearly distinguished by characteristic changes in large-scale networks, encouraging further investigation of network fingerprints for clinical use. Hum Brain Mapp 37:808-818, 2016. © 2015 Wiley Periodicals, Inc. © 2015 Wiley Periodicals, Inc.

Information technology as tool for change.

PubMed

Itkonen, P

1999-12-01

It looks that networking welfare thinking and implementations of network projects only follow the development of data transfer possibilities. It is a danger that seamless chain of care in health care is just a data transferring generator based on easy connections, only creating needs for new data transferring. This is an 'illusion of core skills' that does not extend to the development of the contents of services. Easy access to the system makes more contacts and need for more also clinical services. New needs for data transfer burden the personnel with unnecessary information and networking functional model does not emancipate them to use their substantial skills. It means more costs and it is also a danger that normal life will be medicated. Public sector cannot finance all these new possibilities and consequences of modern technology. Does all this create a new combination of public and private sector and push them to allocate responsibilities in developing work? If the public and private sectors do not find the balance in controlling this development, also actors outside health care get to influence the choices and health care loses its autonomy. It becomes a business means for companies producing data transfer and network services. From the prioritization point of view this is not a good vision for financing and delivery of health care services either in public or private sector.

Caught in the middle? How women deal with conflicting pregnancy-advice from health professionals and their social networks.

PubMed

Schölmerich, Vera L N; Ghorashi, Halleh; Denktaş, Semiha; Groenewegen, Peter

2016-04-01

to investigate how pregnant women deal with conflicting advice from their social networks and their caregivers and how this influenced their pregnancy-related behaviours. a qualitative study based on face-to-face interviews and focus-groups. We applied an inductive analysis technique closely following the 'Gioia method'. impoverished neighbourhoods in Rotterdam, the Netherlands. 40 women who were pregnant, or had given birth within the last 12 months. 12 women were Native Dutch, 16 had a Moroccan background, and 12 had a Turkish background. all women faced a misalignment of advice by health professionals and social networks. For the native Dutch respondents, this misalignment did not seem to present a challenge. They had a strongly articulated preference for the advice of health professionals, and did not fear any social consequences for openly following their advice. For the women with a Turkish/Moroccan background, however, this discrepancy in advice presented a dilemma. Following one piece of advice seemed to exclude also following the other one, which would possibly entail social consequences. These women employed one of the three strategies to deal with this dilemma: a) avoiding the dilemma (secretly not following the advice of one side), b) embracing the dilemma (combining conflicting advice), and c) resolving the dilemma (communicating between both sides). we argue that the currently popular interventions geared towards increasing the health literacy of non-Western ethnic minority pregnant women and improving communication between ethnic minority clients and caregivers are not sufficient, and might even exacerbate the dilemma some pregnant women face. As an alternative, we recommend involving not only caregivers but also women's social network in intervention efforts. Interventions could aim to increase the negotiation capacity of the target group, but also to increase the health literacy of the members of their social network to enable the circulation of 'new' information within a rather homogeneous, tight-knit network. Copyright © 2016 Elsevier Ltd. All rights reserved.

Information flow and work productivity through integrated information technology

NASA Technical Reports Server (NTRS)

Wigand, R. T.

1985-01-01

The work environment surrounding integrated office systems is reviewed. The known effects of automated office technologies is synthesized and their known impact on work efficiency is reviewed. These effects are explored with regard to their impact on networks, work flow/processes, as well as organizational structure and power. Particular emphasis is given to structural changes due to the introduction of newer information technologies in organizations. The new information technologies have restructed the average organization's middle banks and, as a consequence, they have shrunk drastically. Organizational pyramids have flattened with fewer levels since executives have realized that they can get ahold of the needed information via the new technologies quicker and directly and do not have to rely on middle-level managers. Power shifts are typically accompanied with the introduction of these technologies resulting in the generation of a new form of organizational power.

Using FDA reports to inform a classification for health information technology safety problems

PubMed Central

Ong, Mei-Sing; Runciman, William; Coiera, Enrico

2011-01-01

Objective To expand an emerging classification for problems with health information technology (HIT) using reports submitted to the US Food and Drug Administration Manufacturer and User Facility Device Experience (MAUDE) database. Design HIT events submitted to MAUDE were retrieved using a standardized search strategy. Using an emerging classification with 32 categories of HIT problems, a subset of relevant events were iteratively analyzed to identify new categories. Two coders then independently classified the remaining events into one or more categories. Free-text descriptions were analyzed to identify the consequences of events. Measurements Descriptive statistics by number of reported problems per category and by consequence; inter-rater reliability analysis using the κ statistic for the major categories and consequences. Results A search of 899 768 reports from January 2008 to July 2010 yielded 1100 reports about HIT. After removing duplicate and unrelated reports, 678 reports describing 436 events remained. The authors identified four new categories to describe problems with software functionality, system configuration, interface with devices, and network configuration; the authors' classification with 32 categories of HIT problems was expanded by the addition of these four categories. Examination of the 436 events revealed 712 problems, 96% were machine-related, and 4% were problems at the human–computer interface. Almost half (46%) of the events related to hazardous circumstances. Of the 46 events (11%) associated with patient harm, four deaths were linked to HIT problems (0.9% of 436 events). Conclusions Only 0.1% of the MAUDE reports searched were related to HIT. Nevertheless, Food and Drug Administration reports did prove to be a useful new source of information about the nature of software problems and their safety implications with potential to inform strategies for safe design and implementation. PMID:21903979

Energy recovery from waste incineration: assessing the importance of district heating networks.

PubMed

Fruergaard, T; Christensen, T H; Astrup, T

2010-07-01

Municipal solid waste incineration contributes with 20% of the heat supplied to the more than 400 district heating networks in Denmark. In evaluation of the environmental consequences of this heat production, the typical approach has been to assume that other (fossil) fuels could be saved on a 1:1 basis (e.g. 1GJ of waste heat delivered substitutes for 1GJ of coal-based heat). This paper investigates consequences of waste-based heat substitution in two specific Danish district heating networks and the energy-associated interactions between the plants connected to these networks. Despite almost equal electricity and heat efficiencies at the waste incinerators connected to the two district heating networks, the energy and CO(2) accounts showed significantly different results: waste incineration in one network caused a CO(2) saving of 48 kg CO(2)/GJ energy input while in the other network a load of 43 kg CO(2)/GJ. This was caused mainly by differences in operation mode and fuel types of the other heat producing plants attached to the networks. The paper clearly indicates that simple evaluations of waste-to-energy efficiencies at the incinerator are insufficient for assessing the consequences of heat substitution in district heating network systems. The paper also shows that using national averages for heat substitution will not provide a correct answer: local conditions need to be addressed thoroughly otherwise we may fail to assess correctly the heat recovery from waste incineration. Copyright (c) 2010 Elsevier Ltd. All rights reserved.

Western Australian women's perceptions of conflicting advice around breast feeding.

PubMed

Hauck, Yvonne L; Graham-Smith, Catherine; McInerney, Justine; Kay, Sue

2011-10-01

to explore women's perceptions of conflicting advice around breast feeding from formal support networks, specifically health professionals involved in postnatal support. a qualitative exploratory design was employed using the critical incident technique. Data were obtained from 62 Western Australian women who responded to an invitation to share incidents of receiving conflicting advice. Women who had breast fed a child within the past 12 months shared their experience through a telephone interview (n = 50) or completing a brief questionnaire (n = 12) addressing the following questions: Describe a situation in detail where you felt you received conflicting advice about breast feeding from a health professional. How did this situation affect you and/or your breast feeding? a modified constant comparison method was used to analyse the critical incidents revealing commonalities under who offered conflicting advice; what contributed to advice being perceived as conflicting; topic areas more inclined to being regarded as conflicting; what protected against advice being perceived as conflicting; the consequences of receiving conflicting advice; and strategies that women used to manage these incidents. advice that was viewed as conflicting extended beyond the provision of information that was inconsistent or directly contradictory, and included issues around information overload and disparities between the mother's and health professional's expectations. The manner of presenting information or advice, the skills of using effective communication, demonstration of a caring attitude with an empathic approach and focusing upon the woman as an individual were seen to be important to minimise these incidents. Attention to women's perceptions and the consequences of conflicting advice must be addressed, otherwise the credibility and confidence in health professionals' knowledge and ability to support breast feeding is questioned, resulting in a valuable support network being selectively ignored. Copyright © 2010 Elsevier Ltd. All rights reserved.

Why is social network drinking associated with college students' alcohol use? Focus on psychological mediators.

PubMed

Reid, Allecia E; Carey, Kate B

2018-06-01

Level of drinking in the social network is strongly associated with college students' alcohol use. However, mechanisms through which networks are associated with personal drinking have been underexplored thus far. The present study examined theoretically derived constructs-sociability outcome expectancies, attitudes toward heavy drinking, self-efficacy for use of protective strategies, and descriptive norms-as potential mediators of the association between egocentric social network drinking and personal consumption. College students (N = 274) self-reported their social network's level of alcohol consumption, all mediators, drinks per week, and consequences at both baseline (Time 1) and a 1-month follow-up (Time 2). Autoregressive mediation models focused on the longitudinal associations between Time 1 network drinking and the Time 2 mediators and between the Time 1 mediators and the Time 2 outcomes. Consistent with hypotheses, Time 1 social network drinking was significantly associated with Time 2 drinks per week and consequences. Only attitudes significantly mediated social network associations with drinks per week and consequences, though the proportion of the total effects accounted for by attitudes was small. After accounting for the stability of constructs over time, social network drinking was generally un- or weakly related to sociability expectancies, self-efficacy, and descriptive norms. Results support reducing attitudes toward heavy drinking as a potential avenue for mitigating network effects, but also highlight the need to evaluate additional potential mechanisms of network effects. Intervention efforts that aim to address the social network have the potential to substantially reduce alcohol consumption, thereby enhancing the overall efficacy of alcohol risk-reduction interventions. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Combined neurostimulation and neuroimaging in cognitive neuroscience: past, present, and future.

PubMed

Bestmann, Sven; Feredoes, Eva

2013-08-01

Modern neurostimulation approaches in humans provide controlled inputs into the operations of cortical regions, with highly specific behavioral consequences. This enables causal structure-function inferences, and in combination with neuroimaging, has provided novel insights into the basic mechanisms of action of neurostimulation on distributed networks. For example, more recent work has established the capacity of transcranial magnetic stimulation (TMS) to probe causal interregional influences, and their interaction with cognitive state changes. Combinations of neurostimulation and neuroimaging now face the challenge of integrating the known physiological effects of neurostimulation with theoretical and biological models of cognition, for example, when theoretical stalemates between opposing cognitive theories need to be resolved. This will be driven by novel developments, including biologically informed computational network analyses for predicting the impact of neurostimulation on brain networks, as well as novel neuroimaging and neurostimulation techniques. Such future developments may offer an expanded set of tools with which to investigate structure-function relationships, and to formulate and reconceptualize testable hypotheses about complex neural network interactions and their causal roles in cognition. © 2013 New York Academy of Sciences.

Undermining and Strengthening Social Networks through Network Modification

PubMed Central

Mellon, Jonathan; Yoder, Jordan; Evans, Daniel

2016-01-01

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

Undermining and Strengthening Social Networks through Network Modification.

PubMed

Mellon, Jonathan; Yoder, Jordan; Evans, Daniel

2016-10-05

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

Undermining and Strengthening Social Networks through Network Modification

NASA Astrophysics Data System (ADS)

Mellon, Jonathan; Yoder, Jordan; Evans, Daniel

2016-10-01

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

Privacy Issues of a National Research and Education Network.

ERIC Educational Resources Information Center

Katz, James E.; Graveman, Richard F.

1991-01-01

Discussion of the right to privacy of communications focuses on privacy expectations within a National Research and Education Network (NREN). Highlights include privacy needs in scientific and education communications; academic and research networks; network security and privacy concerns; protection strategies; and consequences of privacy…

Inequality and visibility of wealth in experimental social networks.

PubMed

Nishi, Akihiro; Shirado, Hirokazu; Rand, David G; Christakis, Nicholas A

2015-10-15

Humans prefer relatively equal distributions of resources, yet societies have varying degrees of economic inequality. To investigate some of the possible determinants and consequences of inequality, here we perform experiments involving a networked public goods game in which subjects interact and gain or lose wealth. Subjects (n = 1,462) were randomly assigned to have higher or lower initial endowments, and were embedded within social networks with three levels of economic inequality (Gini coefficient = 0.0, 0.2, and 0.4). In addition, we manipulated the visibility of the wealth of network neighbours. We show that wealth visibility facilitates the downstream consequences of initial inequality-in initially more unequal situations, wealth visibility leads to greater inequality than when wealth is invisible. This result reflects a heterogeneous response to visibility in richer versus poorer subjects. We also find that making wealth visible has adverse welfare consequences, yielding lower levels of overall cooperation, inter-connectedness, and wealth. High initial levels of economic inequality alone, however, have relatively few deleterious welfare effects.

Social media use of older adults: a mini-review.

PubMed

Leist, Anja K

2013-01-01

Maintaining social relationships has been defined as a core element of aging well. With a considerable amount of older adults living alone, social media provides the possibility to engage in meaningful social contact, e.g. by joining online social networks and online discussion forums. The review encompasses current knowledge of prerequisites in social media use of older adults such as functional capacity, information and communications technology-related knowledge, and favorable attitudes towards social media. Then, the potential of social media use for clinical practice and possible negative consequences are outlined. Literature on social media use from a gerontological perspective was reviewed in July and August 2012. Online communities are suitable for providing and receiving social support when confronted with a difficult life situation, regardless of geographical location or time. From a practitioner's perspective, social media can be used to advance health-related knowledge such as information on prevention, diagnosis, and treatment of specific conditions and disorders. Further positive consequences have been shown to be overcoming loneliness, relieving stress, and raising feelings of control and self-efficacy. Possible negative consequences could be misuse of personal data as well as the distribution and uncritical adoption of potentially harmful information via online communities. The potential of social media in clinical practice is reflected in a wide range of intervention possibilities for older adults. However, with the rise of social media, new threats emerge for older adults as well. Copyright © 2013 S. Karger AG, Basel.

Predicting behavior change from persuasive messages using neural representational similarity and social network analyses.

PubMed

Pegors, Teresa K; Tompson, Steven; O'Donnell, Matthew Brook; Falk, Emily B

2017-08-15

Neural activity in medial prefrontal cortex (MPFC), identified as engaging in self-related processing, predicts later health behavior change. However, it is unknown to what extent individual differences in neural representation of content and lived experience influence this brain-behavior relationship. We examined whether the strength of content-specific representations during persuasive messaging relates to later behavior change, and whether these relationships change as a function of individuals' social network composition. In our study, smokers viewed anti-smoking messages while undergoing fMRI and we measured changes in their smoking behavior one month later. Using representational similarity analyses, we found that the degree to which message content (i.e. health, social, or valence information) was represented in a self-related processing MPFC region was associated with later smoking behavior, with increased representations of negatively valenced (risk) information corresponding to greater message-consistent behavior change. Furthermore, the relationship between representations and behavior change depended on social network composition: smokers who had proportionally fewer smokers in their network showed increases in smoking behavior when social or health content was strongly represented in MPFC, whereas message-consistent behavior (i.e., less smoking) was more likely for those with proportionally more smokers in their social network who represented social or health consequences more strongly. These results highlight the dynamic relationship between representations in MPFC and key outcomes such as health behavior change; a complete understanding of the role of MPFC in motivation and action should take into account individual differences in neural representation of stimulus attributes and social context variables such as social network composition. Copyright © 2017 Elsevier Inc. All rights reserved.

The Complexity of Dynamics in Small Neural Circuits

PubMed Central

Panzeri, Stefano

2016-01-01

Mean-field approximations are a powerful tool for studying large neural networks. However, they do not describe well the behavior of networks composed of a small number of neurons. In this case, major differences between the mean-field approximation and the real behavior of the network can arise. Yet, many interesting problems in neuroscience involve the study of mesoscopic networks composed of a few tens of neurons. Nonetheless, mathematical methods that correctly describe networks of small size are still rare, and this prevents us to make progress in understanding neural dynamics at these intermediate scales. Here we develop a novel systematic analysis of the dynamics of arbitrarily small networks composed of homogeneous populations of excitatory and inhibitory firing-rate neurons. We study the local bifurcations of their neural activity with an approach that is largely analytically tractable, and we numerically determine the global bifurcations. We find that for strong inhibition these networks give rise to very complex dynamics, caused by the formation of multiple branching solutions of the neural dynamics equations that emerge through spontaneous symmetry-breaking. This qualitative change of the neural dynamics is a finite-size effect of the network, that reveals qualitative and previously unexplored differences between mesoscopic cortical circuits and their mean-field approximation. The most important consequence of spontaneous symmetry-breaking is the ability of mesoscopic networks to regulate their degree of functional heterogeneity, which is thought to help reducing the detrimental effect of noise correlations on cortical information processing. PMID:27494737

Friends of friends: are indirect connections in social networks important to animal behaviour?

PubMed

Brent, Lauren J N

2015-05-01

Friend of a friend relationships, or the indirect connections between people, influence our health, well-being, financial success and reproductive output. As with humans, social behaviours in other animals often occur within a broad interconnected network of social ties. Yet studies of animal social behaviour tend to focus on associations between pairs of individuals. With the increase in popularity of social network analysis, researchers have started to look beyond the dyad to examine the role of indirect connections in animal societies. Here, I provide an overview of the new knowledge that has been uncovered by these studies. I focus on research that has addressed both the causes of social behaviours, i.e. the cognitive and genetic basis of indirect connections, as well as their consequences, i.e. the impact of indirect connections on social cohesion, information transfer, cultural practices and fitness. From these studies, it is apparent that indirect connections play an important role in animal behaviour, although future research is needed to clarify their contribution.

Friends of friends: are indirect connections in social networks important to animal behaviour?

PubMed Central

Brent, Lauren J. N.

2015-01-01

Friend of a friend relationships, or the indirect connections between people, influence our health, well-being, financial success and reproductive output. As with humans, social behaviours in other animals often occur within a broad interconnected network of social ties. Yet studies of animal social behaviour tend to focus on associations between pairs of individuals. With the increase in popularity of social network analysis, researchers have started to look beyond the dyad to examine the role of indirect connections in animal societies. Here, I provide an overview of the new knowledge that has been uncovered by these studies. I focus on research that has addressed both the causes of social behaviours, i.e. the cognitive and genetic basis of indirect connections, as well as their consequences, i.e. the impact of indirect connections on social cohesion, information transfer, cultural practices and fitness. From these studies, it is apparent that indirect connections play an important role in animal behaviour, although future research is needed to clarify their contribution. PMID:25937639

Visual behavior characterization for intrusion and misuse detection

NASA Astrophysics Data System (ADS)

Erbacher, Robert F.; Frincke, Deborah

2001-05-01

As computer and network intrusions become more and more of a concern, the need for better capabilities, to assist in the detection and analysis of intrusions also increase. System administrators typically rely on log files to analyze usage and detect misuse. However, as a consequence of the amount of data collected by each machine, multiplied by the tens or hundreds of machines under the system administrator's auspices, the entirety of the data available is neither collected nor analyzed. This is compounded by the need to analyze network traffic data as well. We propose a methodology for analyzing network and computer log information visually based on the analysis of the behavior of the users. Each user's behavior is the key to determining their intent and overriding activity, whether they attempt to hide their actions or not. Proficient hackers will attempt to hide their ultimate activities, which hinders the reliability of log file analysis. Visually analyzing the users''s behavior however, is much more adaptable and difficult to counteract.

Local classifiers for evoked potentials recorded from behaving rats.

PubMed

Jakuczun, Wit; Kublik, Ewa; Wójcik, Daniel K; Wróbel, Andrzej

2005-01-01

Dynamic states of the brain determine the way information is processed in local neural networks. We have applied classical conditioning paradigm in order to study whether habituated and aroused states can be differentiated in single barrel column of rat's somatosensory cortex by means of analysis of field potentials evoked by stimulation of a single vibrissa. A new method using local classifiers is presented which allows for reliable and meaningful classification of single evoked potentials which might be consequently attributed to different functional states of the cortical column.

Associative memory - An optimum binary neuron representation

NASA Technical Reports Server (NTRS)

Awwal, A. A.; Karim, M. A.; Liu, H. K.

1989-01-01

Convergence mechanism of vectors in the Hopfield's neural network is studied in terms of both weights (i.e., inner products) and Hamming distance. It is shown that Hamming distance should not always be used in determining the convergence of vectors. Instead, weights (which in turn depend on the neuron representation) are found to play a more dominant role in the convergence mechanism. Consequently, a new binary neuron representation for associative memory is proposed. With the new neuron representation, the associative memory responds unambiguously to the partial input in retrieving the stored information.

A Digital Ethnography of Medical Students who Use Twitter for Professional Development.

PubMed

Chretien, Katherine C; Tuck, Matthew G; Simon, Michael; Singh, Lisa O; Kind, Terry

2015-11-01

While researchers have studied negative professional consequences of medical trainee social media use, little is known about how medical students informally use social media for education and career development. This knowledge may help future and current physicians succeed in the digital age. We aimed to explore how and why medical students use Twitter for professional development. This was a digital ethnography. Medical student "superusers" of Twitter participated in the study The postings ("tweets") of 31 medical student superusers were observed for 8 months (May-December 2013), and structured field notes recorded. Through purposive sampling, individual key informant interviews were conducted to explore Twitter use and values until thematic saturation was reached (ten students). Three faculty key informant interviews were also conducted. Ego network and subnetwork analysis of student key informants was performed. Qualitative analysis included inductive coding of field notes and interviews, triangulation of data, and analytic memos in an iterative process. Twitter served as a professional tool that supplemented the traditional medical school experience. Superusers approached their use of Twitter with purpose and were mindful of online professionalism as well as of being good Twitter citizens. Their tweets reflected a mix of personal and professional content. Student key informants had a high number of followers. The subnetwork of key informants was well-connected, showing evidence of a social network versus information network. Twitter provided value in two major domains: access and voice. Students gained access to information, to experts, to a variety of perspectives including patient and public perspectives, and to communities of support. They also gained a platform for advocacy, control of their digital footprint, and a sense of equalization within the medical hierarchy. Twitter can serve as a professional tool that supplements traditional education. Students' practices and guiding principles can serve as best practices for other students as well as faculty.

Networks: A Route to Improving Performance in Manufacturing SMEs

ERIC Educational Resources Information Center

Coleman, J.

2003-01-01

Perceived as important contributors to economic growth, network and cluster groups are currently receiving much attention. The same may be said of SMEs. But practical and theoretical perspectives indicate that SMEs, and particularly the owner-managers, place little value on networks and have only limited networking resources. Consequently, they do…

Intelligent model-based OPC

NASA Astrophysics Data System (ADS)

Huang, W. C.; Lai, C. M.; Luo, B.; Tsai, C. K.; Chih, M. H.; Lai, C. W.; Kuo, C. C.; Liu, R. G.; Lin, H. T.

2006-03-01

Optical proximity correction is the technique of pre-distorting mask layouts so that the printed patterns are as close to the desired shapes as possible. For model-based optical proximity correction, a lithographic model to predict the edge position (contour) of patterns on the wafer after lithographic processing is needed. Generally, segmentation of edges is performed prior to the correction. Pattern edges are dissected into several small segments with corresponding target points. During the correction, the edges are moved back and forth from the initial drawn position, assisted by the lithographic model, to finally settle on the proper positions. When the correction converges, the intensity predicted by the model in every target points hits the model-specific threshold value. Several iterations are required to achieve the convergence and the computation time increases with the increase of the required iterations. An artificial neural network is an information-processing paradigm inspired by biological nervous systems, such as how the brain processes information. It is composed of a large number of highly interconnected processing elements (neurons) working in unison to solve specific problems. A neural network can be a powerful data-modeling tool that is able to capture and represent complex input/output relationships. The network can accurately predict the behavior of a system via the learning procedure. A radial basis function network, a variant of artificial neural network, is an efficient function approximator. In this paper, a radial basis function network was used to build a mapping from the segment characteristics to the edge shift from the drawn position. This network can provide a good initial guess for each segment that OPC has carried out. The good initial guess reduces the required iterations. Consequently, cycle time can be shortened effectively. The optimization of the radial basis function network for this system was practiced by genetic algorithm, which is an artificially intelligent optimization method with a high probability to obtain global optimization. From preliminary results, the required iterations were reduced from 5 to 2 for a simple dumbbell-shape layout.

Social and place-focused communities in location-based online social networks

NASA Astrophysics Data System (ADS)

Brown, Chloë; Nicosia, Vincenzo; Scellato, Salvatore; Noulas, Anastasios; Mascolo, Cecilia

2013-06-01

Thanks to widely available, cheap Internet access and the ubiquity of smartphones, millions of people around the world now use online location-based social networking services. Understanding the structural properties of these systems and their dependence upon users' habits and mobility has many potential applications, including resource recommendation and link prediction. Here, we construct and characterise social and place-focused graphs by using longitudinal information about declared social relationships and about users' visits to physical places collected from a popular online location-based social service. We show that although the social and place-focused graphs are constructed from the same data set, they have quite different structural properties. We find that the social and location-focused graphs have different global and meso-scale structure, and in particular that social and place-focused communities have negligible overlap. Consequently, group inference based on community detection performed on the social graph alone fails to isolate place-focused groups, even though these do exist in the network. By studying the evolution of tie structure within communities, we show that the time period over which location data are aggregated has a substantial impact on the stability of place-focused communities, and that information about place-based groups may be more useful for user-centric applications than that obtained from the analysis of social communities alone.

Supporting a friend, housemate or partner with mental health difficulties: The student experience.

PubMed

Byrom, Nicola C

2017-07-14

When experiencing mental health difficulties, university students turn to their friends for support. This study assessed the consequences of caregiving among a university sample, identifying predictors of caregiving burden among students. A total of 79 students with experience of supporting a friend with mental health difficulties were recruited through a UK student mental health charity to complete an online survey. Alongside qualitative data, the online survey used the Experience of Caregiving Inventory and the Involvement Evaluation Questionnaire as measures of the consequences of caregiving. Students supporting friends, housemates or partners were found to experience significant consequences of caregiving. Frequency of face-to-face contact and duration of illness predicted more negative consequences of caregiving, but these relationships were not straightforward. The presence and intensity of professional support did not influence the experience of caregiving. The study suggests that the impact of supporting friends with mental health difficulties is not insubstantial for students. Broadening the network of informal social support may help improve the experience for students supporting a friend, but currently, contact with professional services appears to have a limited effect. © 2017 John Wiley & Sons Australia, Ltd.

Using a network modularity analysis to inform management of a rare endemic plant in the northern Great Plains, USA

USGS Publications Warehouse

Larson, Diane L.; Droege, Sam; Rabie, Paul A.; Larson, Jennifer L.; Devalez, Jelle; Haar, Milton; McDermott-Kubeczko, Margaret

2014-01-01

1. Analyses of flower-visitor interaction networks allow application of community-level information to conservation problems, but management recommendations that ensue from such analyses are not well characterized. Results of modularity analyses, which detect groups of species (modules) that interact more with each other than with species outside their module, may be particularly applicable to management concerns. 2. We conducted modularity analyses of networks surrounding a rare endemic annual plant, Eriogonum visheri, at Badlands National Park, USA, in 2010 and 2011. Plant species visited were determined by pollen on insect bodies and by flower species upon which insects were captured. Roles within modules (network hub, module hub, connector and peripheral, in decreasing order of network structural importance) were determined for each species. 3. Relationships demonstrated by the modularity analysis, in concert with knowledge of pollen species carried by insects, allowed us to infer effects of two invasive species on E. visheri. Sharing a module increased risk of interspecific pollen transfer to E. visheri. Control of invasive Salsola tragus, which shared a module with E. visheri, is therefore a prudent management objective, but lack of control of invasive Melilotus officinalis, which occupied a different module, is unlikely to negatively affect pollination of E. visheri. Eriogonum pauciflorum may occupy a key position in this network, supporting insects from the E. visheri module when E. visheri is less abundant. 4. Year-to-year variation in species' roles suggests management decisions must be based on observations over several years. Information on pollen deposition on stigmas would greatly strengthen inferences made from the modularity analysis. 5. Synthesis and applications: Assessing the consequences of pollination, whether at the community or individual level, is inherently time-consuming. A trade-off exists: rather than an estimate of fitness effects, the network approach provides a broad understanding of the relationships among insect visitors and other plant species that may affect the focal rare plant. Knowledge of such relationships allows managers to detect, target and prioritize control of only the important subset of invasive species present and identify other species that may augment a rare species' population stability, such as E. pauciflorum in our study.

Ecological consequences of colony structure in dynamic ant nest networks.

PubMed

Ellis, Samuel; Franks, Daniel W; Robinson, Elva J H

2017-02-01

Access to resources depends on an individual's position within the environment. This is particularly important to animals that invest heavily in nest construction, such as social insects. Many ant species have a polydomous nesting strategy: a single colony inhabits several spatially separated nests, often exchanging resources between the nests. Different nests in a polydomous colony potentially have differential access to resources, but the ecological consequences of this are unclear. In this study, we investigate how nest survival and budding in polydomous wood ant ( Formica lugubris ) colonies are affected by being part of a multi-nest system. Using field data and novel analytical approaches combining survival models with dynamic network analysis, we show that the survival and budding of nests within a polydomous colony are affected by their position in the nest network structure. Specifically, we find that the flow of resources through a nest, which is based on its position within the wider nest network, determines a nest's likelihood of surviving and of founding new nests. Our results highlight how apparently disparate entities in a biological system can be integrated into a functional ecological unit. We also demonstrate how position within a dynamic network structure can have important ecological consequences.

Mechanism on brain information processing: Energy coding

NASA Astrophysics Data System (ADS)

Wang, Rubin; Zhang, Zhikang; Jiao, Xianfa

2006-09-01

According to the experimental result of signal transmission and neuronal energetic demands being tightly coupled to information coding in the cerebral cortex, the authors present a brand new scientific theory that offers a unique mechanism for brain information processing. They demonstrate that the neural coding produced by the activity of the brain is well described by the theory of energy coding. Due to the energy coding model's ability to reveal mechanisms of brain information processing based upon known biophysical properties, they cannot only reproduce various experimental results of neuroelectrophysiology but also quantitatively explain the recent experimental results from neuroscientists at Yale University by means of the principle of energy coding. Due to the theory of energy coding to bridge the gap between functional connections within a biological neural network and energetic consumption, they estimate that the theory has very important consequences for quantitative research of cognitive function.

Fault gouge evolution during rupture and healing: Continual active-seismic observations across laboratory-scale fault zones

NASA Astrophysics Data System (ADS)

Krysta, M.; Kusmierczyk-Michulec, J.; Nikkinen, M.; Carter, J. A.

2011-12-01

In order to support its mission of monitoring compliance with the treaty banning nuclear explosions, the Comprehensive Nuclear-Test-Ban Treaty Organization (CTBTO) operates four global networks of, respectively, seismic, infrasound, hydroacoustic sensors and air samplers accompanied with radionuclide detectors. The role of the International Data Centre (IDC) of CTBTO is to associate the signals detected in the monitoring networks with the physical phenomena which emitted these signals, by forming events. One of the aspects of associating detections with emitters is the problem of inferring the sources of radionuclides from the detections made at CTBTO radionuclide network stations. This task is particularly challenging because the average transport distance between a release point and detectors is large. Complex processes of turbulent diffusion are responsible for efficient mixing and consequently for decreasing the information content of detections with an increasing distance from the source. The problem is generally addressed in a two-step process. In the first step, an atmospheric transport model establishes a link between the detections and the regions of possible source location. In the second step this link is inverted to infer source information from the detections. In this presentation, we will discuss enhancements of the presently used regression-based inversion algorithm to reconstruct a source of radionuclides. To this aim, modern inversion algorithms accounting for prior information and appropriately regularizing an under-determined reconstruction problem will be briefly introduced. Emphasis will be on the CTBTO context and the choice of inversion methods. An illustration of the first tests will be provided using a framework of twin experiments, i.e. fictitious detections in the CTBTO radionuclide network generated with an atmospheric transport model.

Development of gridded solar radiation data over Belgium based on Meteosat and in-situ observations

NASA Astrophysics Data System (ADS)

Journée, Michel; Vanderveken, Gilles; Bertrand, Cédric

2013-04-01

Knowledge on solar resources is highly important for all forms of solar energy applications. With the recent development in solar-based technologies national meteorological services are faced with increasing demands for high-quality and reliable site-time specific solar resource information. Traditionally, solar radiation is observed by means of networks of meteorological stations. Costs for installation and maintenance of such networks are very high and national networks comprise only few stations. Consequently the availability of ground-based solar radiation measurements has proven to be spatially and temporally inadequate for many applications. To overcome such a limitation, a major effort has been undertaken at the Royal Meteorological Institute of Belgium (RMI) to provide the solar energy industry, the electricity sector, governments, and renewable energy organizations and institutions with the most suitable and accurate information on the solar radiation resources at the Earth's surface over the Belgian territory. Only space-based observations can deliver a global coverage of the solar irradiation impinging on horizontal surface at the ground level. Because only geostationary data allow to capture the diurnal cycle of the solar irradiance at the Earth's surface, a method that combines information from Meteosat Second Generation satellites and ground-measurement has been implemented at RMI to generate high resolution solar products over Belgium on an operational basis. Besides these new products, the annual and seasonal variability of solar energy resource was evaluated, solar radiation climate zones were defined and the recent trend in solar radiation was characterized.

40 CFR 1400.9 - Access to off-site consequence analysis information by State and local government officials.

Code of Federal Regulations, 2014 CFR

2014-07-01

... analysis information by State and local government officials. 1400.9 Section 1400.9 Protection of... CONSEQUENCE ANALYSIS INFORMATION DISTRIBUTION OF OFF-SITE CONSEQUENCE ANALYSIS INFORMATION Access to Off-Site Consequence Analysis Information by Government Officials. § 1400.9 Access to off-site consequence analysis...

40 CFR 1400.9 - Access to off-site consequence analysis information by State and local government officials.

Code of Federal Regulations, 2011 CFR

2011-07-01

... analysis information by State and local government officials. 1400.9 Section 1400.9 Protection of... CONSEQUENCE ANALYSIS INFORMATION DISTRIBUTION OF OFF-SITE CONSEQUENCE ANALYSIS INFORMATION Access to Off-Site Consequence Analysis Information by Government Officials. § 1400.9 Access to off-site consequence analysis...

40 CFR 1400.9 - Access to off-site consequence analysis information by State and local government officials.

Code of Federal Regulations, 2010 CFR

2010-07-01

... analysis information by State and local government officials. 1400.9 Section 1400.9 Protection of... CONSEQUENCE ANALYSIS INFORMATION DISTRIBUTION OF OFF-SITE CONSEQUENCE ANALYSIS INFORMATION Access to Off-Site Consequence Analysis Information by Government Officials. § 1400.9 Access to off-site consequence analysis...

40 CFR 1400.9 - Access to off-site consequence analysis information by State and local government officials.

Code of Federal Regulations, 2013 CFR

2013-07-01

... analysis information by State and local government officials. 1400.9 Section 1400.9 Protection of... CONSEQUENCE ANALYSIS INFORMATION DISTRIBUTION OF OFF-SITE CONSEQUENCE ANALYSIS INFORMATION Access to Off-Site Consequence Analysis Information by Government Officials. § 1400.9 Access to off-site consequence analysis...

40 CFR 1400.9 - Access to off-site consequence analysis information by State and local government officials.

Code of Federal Regulations, 2012 CFR

2012-07-01

... analysis information by State and local government officials. 1400.9 Section 1400.9 Protection of... CONSEQUENCE ANALYSIS INFORMATION DISTRIBUTION OF OFF-SITE CONSEQUENCE ANALYSIS INFORMATION Access to Off-Site Consequence Analysis Information by Government Officials. § 1400.9 Access to off-site consequence analysis...

OXC management and control system architecture with scalability, maintenance, and distributed managing environment

NASA Astrophysics Data System (ADS)

Park, Soomyung; Joo, Seong-Soon; Yae, Byung-Ho; Lee, Jong-Hyun

2002-07-01

In this paper, we present the Optical Cross-Connect (OXC) Management Control System Architecture, which has the scalability and robust maintenance and provides the distributed managing environment in the optical transport network. The OXC system we are developing, which is divided into the hardware and the internal and external software for the OXC system, is made up the OXC subsystem with the Optical Transport Network (OTN) sub layers-hardware and the optical switch control system, the signaling control protocol subsystem performing the User-to-Network Interface (UNI) and Network-to-Network Interface (NNI) signaling control, the Operation Administration Maintenance & Provisioning (OAM&P) subsystem, and the network management subsystem. And the OXC management control system has the features that can support the flexible expansion of the optical transport network, provide the connectivity to heterogeneous external network elements, be added or deleted without interrupting OAM&P services, be remotely operated, provide the global view and detail information for network planner and operator, and have Common Object Request Broker Architecture (CORBA) based the open system architecture adding and deleting the intelligent service networking functions easily in future. To meet these considerations, we adopt the object oriented development method in the whole developing steps of the system analysis, design, and implementation to build the OXC management control system with the scalability, the maintenance, and the distributed managing environment. As a consequently, the componentification for the OXC operation management functions of each subsystem makes the robust maintenance, and increases code reusability. Also, the component based OXC management control system architecture will have the flexibility and scalability in nature.

Brain network disturbance related to posttraumatic stress and traumatic brain injury in veterans.

PubMed

Spielberg, Jeffrey M; McGlinchey, Regina E; Milberg, William P; Salat, David H

2015-08-01

Understanding the neural causes and consequences of posttraumatic stress disorder (PTSD) and mild traumatic brain injury (mTBI) is a high research priority, given the high rates of associated disability and suicide. Despite remarkable progress in elucidating the brain mechanisms of PTSD and mTBI, a comprehensive understanding of these conditions at the level of brain networks has yet to be achieved. The present study sought to identify functional brain networks and topological properties (measures of network organization and function) related to current PTSD severity and mTBI. Graph theoretic tools were used to analyze resting-state functional magnetic resonance imaging data from 208 veterans of Operation Enduring Freedom, Operation Iraqi Freedom, and Operation New Dawn, all of whom had experienced a traumatic event qualifying for PTSD criterion A. Analyses identified brain networks and topological network properties linked to current PTSD symptom severity, mTBI, and the interaction between PTSD and mTBI. Two brain networks were identified in which weaker connectivity was linked to higher PTSD re-experiencing symptoms, one of which was present only in veterans with comorbid mTBI. Re-experiencing was also linked to worse functional segregation (necessary for specialized processing) and diminished influence of key regions on the network, including the hippocampus. Findings of this study demonstrate that PTSD re-experiencing symptoms are linked to weakened connectivity in a network involved in providing contextual information. A similar relationship was found in a separate network typically engaged in the gating of working memory, but only in veterans with mTBI. Published by Elsevier Inc.

Role of centrality for the identification of influential spreaders in complex networks.

PubMed

de Arruda, Guilherme Ferraz; Barbieri, André Luiz; Rodríguez, Pablo Martín; Rodrigues, Francisco A; Moreno, Yamir; Costa, Luciano da Fontoura

2014-09-01

The identification of the most influential spreaders in networks is important to control and understand the spreading capabilities of the system as well as to ensure an efficient information diffusion such as in rumorlike dynamics. Recent works have suggested that the identification of influential spreaders is not independent of the dynamics being studied. For instance, the key disease spreaders might not necessarily be so important when it comes to analyzing social contagion or rumor propagation. Additionally, it has been shown that different metrics (degree, coreness, etc.) might identify different influential nodes even for the same dynamical processes with diverse degrees of accuracy. In this paper, we investigate how nine centrality measures correlate with the disease and rumor spreading capabilities of the nodes in different synthetic and real-world (both spatial and nonspatial) networks. We also propose a generalization of the random walk accessibility as a new centrality measure and derive analytical expressions for the latter measure for simple network configurations. Our results show that for nonspatial networks, the k-core and degree centralities are the most correlated to epidemic spreading, whereas the average neighborhood degree, the closeness centrality, and accessibility are the most related to rumor dynamics. On the contrary, for spatial networks, the accessibility measure outperforms the rest of the centrality metrics in almost all cases regardless of the kind of dynamics considered. Therefore, an important consequence of our analysis is that previous studies performed in synthetic random networks cannot be generalized to the case of spatial networks.

Networks and Collaboration in Spanish Education Policy

ERIC Educational Resources Information Center

Azorín, Cecilia M.; Muijs, Daniel

2017-01-01

Background: Networks play an important role in today's societies. As a consequence, changes are apparent in the political, economic, cultural, educational and social agendas. Purpose: The main goal of this article is to map the situation of school networks in Spain. The research questions are focused on what forms collaboration and networking take…

Negative consequences from heavy social networking in adolescents: The mediating role of fear of missing out.

PubMed

Oberst, Ursula; Wegmann, Elisa; Stodt, Benjamin; Brand, Matthias; Chamarro, Andrés

2017-02-01

Social networking sites (SNS) are especially attractive for adolescents, but it has also been shown that these users can suffer from negative psychological consequences when using these sites excessively. We analyze the role of fear of missing out (FOMO) and intensity of SNS use for explaining the link between psychopathological symptoms and negative consequences of SNS use via mobile devices. In an online survey, 1468 Spanish-speaking Latin-American social media users between 16 and 18 years old completed the Hospital Anxiety and Depression Scale (HADS), the Social Networking Intensity scale (SNI), the FOMO scale (FOMOs), and a questionnaire on negative consequences of using SNS via mobile device (CERM). Using structural equation modeling, it was found that both FOMO and SNI mediate the link between psychopathology and CERM, but by different mechanisms. Additionally, for girls, feeling depressed seems to trigger higher SNS involvement. For boys, anxiety triggers higher SNS involvement. Copyright © 2016 The Foundation for Professionals in Services for Adolescents. Published by Elsevier Ltd. All rights reserved.

Self-referenced processing, neurodevelopment and joint attention in autism.

PubMed

Mundy, Peter; Gwaltney, Mary; Henderson, Heather

2010-09-01

This article describes a parallel and distributed processing model (PDPM) of joint attention, self-referenced processing and autism. According to this model, autism involves early impairments in the capacity for rapid, integrated processing of self-referenced (proprioceptive and interoceptive) and other-referenced (exteroceptive) information. Measures of joint attention have proven useful in research on autism because they are sensitive to the early development of the 'parallel' and integrated processing of self- and other-referenced stimuli. Moreover, joint attention behaviors are a consequence, but also an organizer of the functional development of a distal distributed cortical system involving anterior networks including the prefrontal and insula cortices, as well as posterior neural networks including the temporal and parietal cortices. Measures of joint attention provide early behavioral indicators of atypical development in this parallel and distributed processing system in autism. In addition it is proposed that an early, chronic disturbance in the capacity for integrating self- and other-referenced information may have cascading effects on the development of self awareness in autism. The assumptions, empirical support and future research implications of this model are discussed.

The Exchange of Social Support on Online Bariatric Surgery Discussion Forums: A Mixed-Methods Content Analysis.

PubMed

Atwood, Molly E; Friedman, Aliza; Meisner, Brad A; Cassin, Stephanie E

2018-05-01

Bariatric surgery patients often experience physical and psychosocial stressors, and difficulty adjusting to significant lifestyle changes. As a result, social support groups that provide patients with support, coping skills, and nutritional information are valuable components of bariatric care. Support group attendance at bariatric centers is associated with greater post-surgery weight loss; however, several barriers hinder attendance at in-person support groups (e.g., travel distance to bariatric centers). Consequently, online support forums are an increasingly utilized resource for patients both before and after surgery. This study examined and described the type and frequency of social support provided on a large online bariatric surgery forum. A total of 1,412 messages in the pre- (n = 822) and post-surgery (n = 590) sections of the forum were coded using qualitative content analysis according to Cutrona and Suhr's (1992) Social Support Behavior Code model (i.e., including informational, tangible, esteem, network, and emotional support types). The majority of messages provided informational and emotional support regarding: a) factual information about the bariatric procedure and nutrition; b) advice for coping with the surgery preparation process, and physical symptoms; and c) encouragement regarding adherence to surgical guidelines, and weight loss progress. Network, esteem, and tangible support types were less frequent than informational and emotional support types. The results inform healthcare providers about the types of social support available to bariatric patients on online support forums and, thus, encourage appropriate referrals to this resource.

The evolutionary advantage of limited network knowledge.

PubMed

Larson, Jennifer M

2016-06-07

Groups of individuals have social networks that structure interactions within the groups; evolutionary theory increasingly uses this fact to explain the emergence of cooperation (Eshel and Cavalli-Sforza, 1982; Boyd and Richerson, 1988, 1989; Ohtsuki et al., 2006; Nowak et al., 2010; Van Veelen et al., 2012). This approach has resulted in a number of important insights for the evolution of cooperation in the biological and social sciences, but omits a key function of social networks that has persisted throughout recent evolutionary history (Apicella et al., 2012): their role in transmitting gossip about behavior within a group. Accounting for this well-established role of social networks among rational agents in a setting of indirect reciprocity not only shows a new mechanism by which the structure of networks is fitness-relevant, but also reveals that knowledge of social networks can be fitness-relevant as well. When groups enforce cooperation by sanctioning peers whom gossip reveals to have deviated, individuals in certain peripheral network positions are tempting targets of uncooperative behavior because gossip they share about misbehavior spreads slowly through the network. The ability to identify these individuals creates incentives to behave uncooperatively. Consequently, groups comprised of individuals who knew precise information about their social networks would be at a fitness disadvantage relative to groups of individuals with a coarser knowledge of their networks. Empirical work has consistently shown that modern humans know little about the structure of their own social networks and perform poorly when tasked with learning new ones. This robust empirical regularity may be the product of natural selection in an environment of strong selective pressure at the group level. Imprecise views of networks make enforcing cooperation easier. Copyright © 2016 Elsevier Ltd. All rights reserved.

Common neighbours and the local-community-paradigm for topological link prediction in bipartite networks

NASA Astrophysics Data System (ADS)

Daminelli, Simone; Thomas, Josephine Maria; Durán, Claudio; Vittorio Cannistraci, Carlo

2015-11-01

Bipartite networks are powerful descriptions of complex systems characterized by two different classes of nodes and connections allowed only across but not within the two classes. Unveiling physical principles, building theories and suggesting physical models to predict bipartite links such as product-consumer connections in recommendation systems or drug-target interactions in molecular networks can provide priceless information to improve e-commerce or to accelerate pharmaceutical research. The prediction of nonobserved connections starting from those already present in the topology of a network is known as the link-prediction problem. It represents an important subject both in many-body interaction theory in physics and in new algorithms for applied tools in computer science. The rationale is that the existing connectivity structure of a network can suggest where new connections can appear with higher likelihood in an evolving network, or where nonobserved connections are missing in a partially known network. Surprisingly, current complex network theory presents a theoretical bottle-neck: a general framework for local-based link prediction directly in the bipartite domain is missing. Here, we overcome this theoretical obstacle and present a formal definition of common neighbour index and local-community-paradigm (LCP) for bipartite networks. As a consequence, we are able to introduce the first node-neighbourhood-based and LCP-based models for topological link prediction that utilize the bipartite domain. We performed link prediction evaluations in several networks of different size and of disparate origin, including technological, social and biological systems. Our models significantly improve topological prediction in many bipartite networks because they exploit local physical driving-forces that participate in the formation and organization of many real-world bipartite networks. Furthermore, we present a local-based formalism that allows to intuitively implement neighbourhood-based link prediction entirely in the bipartite domain.

Analyzing the Dynamics of Communication in Online Social Networks

NASA Astrophysics Data System (ADS)

de Choudhury, Munmun; Sundaram, Hari; John, Ajita; Seligmann, Doree Duncan

This chapter deals with the analysis of interpersonal communication dynamics in online social networks and social media. Communication is central to the evolution of social systems. Today, the different online social sites feature variegated interactional affordances, ranging from blogging, micro-blogging, sharing media elements (i.e., image, video) as well as a rich set of social actions such as tagging, voting, commenting and so on. Consequently, these communication tools have begun to redefine the ways in which we exchange information or concepts, and how the media channels impact our online interactional behavior. Our central hypothesis is that such communication dynamics between individuals manifest themselves via two key aspects: the information or concept that is the content of communication, and the channel i.e., the media via which communication takes place. We present computational models and discuss large-scale quantitative observational studies for both these organizing ideas. First, we develop a computational framework to determine the "interestingness" property of conversations cented around rich media. Second, we present user models of diffusion of social actions and study the impact of homophily on the diffusion process. The outcome of this research is twofold. First, extensive empirical studies on datasets from YouTube have indicated that on rich media sites, the conversations that are deemed "interesting" appear to have consequential impact on the properties of the social network they are associated with: in terms of degree of participation of the individuals in future conversations, thematic diffusion as well as emergent cohesiveness in activity among the concerned participants in the network. Second, observational and computational studies on large social media datasets such as Twitter have indicated that diffusion of social actions in a network can be indicative of future information cascades. Besides, given a topic, these cascades are often a function of attribute homophily existent among the participants. We believe that this chapter can make significant contribution into a better understanding of how we communicate online and how it is redefining our collective sociological behavior.

Convergence

NASA Astrophysics Data System (ADS)

Darcie, Thomas E.; Doverspike, Robert; Zirngibl, Martin; Korotky, Steven K.

2005-09-01

Call for Papers: Convergence The Journal of Optical Networking (JON) invites submissions to a special issue on Convergence. Convergence has become a popular theme in telecommunications, one that has broad implications across all segments of the industry. Continual evolution of technology and applications continues to erase lines between traditionally separate lines of business, with dramatic consequences for vendors, service providers, and consumers. Spectacular advances in all layers of optical networking-leading to abundant, dynamic, cost-effective, and reliable wide-area and local-area connections-have been essential drivers of this evolution. As services and networks continue to evolve towards some notion of convergence, the continued role of optical networks must be explored. One vision of convergence renders all information in a common packet (especially IP) format. This vision is driven by the proliferation of data services. For example, time-division multiplexed (TDM) voice becomes VoIP. Analog cable-television signals become MPEG bits streamed to digital set-top boxes. T1 or OC-N private lines migrate to Ethernet virtual private networks (VPNs). All these packets coexist peacefully within a single packet-routing methodology built on an optical transport layer that combines the flexibility and cost of data networks with telecom-grade reliability. While this vision is appealing in its simplicity and shared widely, specifics of implementation raise many challenges and differences of opinion. For example, many seek to expand the role of Ethernet in these transport networks, while massive efforts are underway to make traditional TDM networks more data friendly within an evolved but backward-compatible SDH/SONET (synchronous digital hierarchy and synchronous optical network) multiplexing hierarchy. From this common underlying theme follow many specific instantiations. Examples include the convergence at the physical, logical, and operational levels of voice and data, video and data, private-line and virtual private-line, fixed and mobile, and local and long-haul services. These trends have many consequences for consumers, vendors, and carriers. Faced with large volumes of low-margin data traffic mixed with traditional voice services, the need for capital conservation and operational efficiency drives carriers away from today's separate overlay networks for each service and towards "converged" platforms. For example, cable operators require transport of multiple services over both hybrid fiber coax (HFC) and DWDM transport technologies. Local carriers seek an economical architecture to deliver integrated services on optically enabled broadband-access networks. Services over wireless-access networks must coexist with those from wired networks. In each case, convergence of networks and services inspires an important set of questions and challenges, driven by the need for low cost, operational efficiency, service performance requirements, and optical transport technology options. This Feature Issue explores the various interpretations and implications of network convergence pertinent to optical networking. How does convergence affect the evolution of optical transport-layer and control approaches? Are the implied directions consistent with research vision for optical networks? Substantial challenges remain. Papers are solicited across the broad spectrum of interests. These include, but are not limited to: Architecture, design and performance of optical wide-area-network (WAN), metro, and access networks Integration strategies for multiservice transport platforms Access methods that bridge traditional and emerging services Network signaling and control methodologies All-optical packet routing and switching techniques To submit to this special issue, follow the normal procedure for submission to JON, indicating "Convergence feature" in the "Comments" field of the online submission form. For all other questions relating to this feature issue, please send an e-mail to jon@osa.org, subject line "Convergence." Additional information can be found on the JON website: http://www.osa-jon.org/submission/ Submission Deadline: 1 October 2005

40 CFR 1400.8 - Access to off-site consequence analysis information by Federal government officials.

Code of Federal Regulations, 2011 CFR

2011-07-01

... analysis information by Federal government officials. 1400.8 Section 1400.8 Protection of Environment... INFORMATION DISTRIBUTION OF OFF-SITE CONSEQUENCE ANALYSIS INFORMATION Access to Off-Site Consequence Analysis Information by Government Officials. § 1400.8 Access to off-site consequence analysis information by Federal...

40 CFR 1400.8 - Access to off-site consequence analysis information by Federal government officials.

Code of Federal Regulations, 2013 CFR

2013-07-01

... analysis information by Federal government officials. 1400.8 Section 1400.8 Protection of Environment... INFORMATION DISTRIBUTION OF OFF-SITE CONSEQUENCE ANALYSIS INFORMATION Access to Off-Site Consequence Analysis Information by Government Officials. § 1400.8 Access to off-site consequence analysis information by Federal...

40 CFR 1400.8 - Access to off-site consequence analysis information by Federal government officials.

Code of Federal Regulations, 2012 CFR

2012-07-01

... analysis information by Federal government officials. 1400.8 Section 1400.8 Protection of Environment... INFORMATION DISTRIBUTION OF OFF-SITE CONSEQUENCE ANALYSIS INFORMATION Access to Off-Site Consequence Analysis Information by Government Officials. § 1400.8 Access to off-site consequence analysis information by Federal...

40 CFR 1400.8 - Access to off-site consequence analysis information by Federal government officials.

Code of Federal Regulations, 2014 CFR

2014-07-01

... analysis information by Federal government officials. 1400.8 Section 1400.8 Protection of Environment... INFORMATION DISTRIBUTION OF OFF-SITE CONSEQUENCE ANALYSIS INFORMATION Access to Off-Site Consequence Analysis Information by Government Officials. § 1400.8 Access to off-site consequence analysis information by Federal...

Slow, bursty dynamics as a consequence of quenched network topologies

NASA Astrophysics Data System (ADS)

Ådor, Géza

2014-04-01

Bursty dynamics of agents is shown to appear at criticality or in extended Griffiths phases, even in case of Poisson processes. I provide numerical evidence for a power-law type of intercommunication time distributions by simulating the contact process and the susceptible-infected-susceptible model. This observation suggests that in the case of nonstationary bursty systems, the observed non-Poissonian behavior can emerge as a consequence of an underlying hidden Poissonian network process, which is either critical or exhibits strong rare-region effects. On the contrary, in time-varying networks, rare-region effects do not cause deviation from the mean-field behavior, and heterogeneity-induced burstyness is absent.

Slow, bursty dynamics as a consequence of quenched network topologies.

PubMed

Ódor, Géza

2014-04-01

Bursty dynamics of agents is shown to appear at criticality or in extended Griffiths phases, even in case of Poisson processes. I provide numerical evidence for a power-law type of intercommunication time distributions by simulating the contact process and the susceptible-infected-susceptible model. This observation suggests that in the case of nonstationary bursty systems, the observed non-Poissonian behavior can emerge as a consequence of an underlying hidden Poissonian network process, which is either critical or exhibits strong rare-region effects. On the contrary, in time-varying networks, rare-region effects do not cause deviation from the mean-field behavior, and heterogeneity-induced burstyness is absent.

How Network Properties Affect One's Ability to Obtain Benefits: A Network Simulation

ERIC Educational Resources Information Center

Trefalt, Špela

2014-01-01

Networks and the social capital that they carry enable people to get things done, to prosper in their careers, and to feel supported. To develop an effective network, one needs to know more than how to make connections with strangers at a reception; understanding the consequences of network properties on one's ability to obtain benefits is…

Unintended Consequences of Incentive Provision for Behaviour Change and Maintenance around Childbirth

PubMed Central

Thomson, Gill; Morgan, Heather; Crossland, Nicola; Bauld, Linda; Dykes, Fiona; Hoddinott, Pat

2014-01-01

Financial (positive or negative) and non-financial incentives or rewards are increasingly used in attempts to influence health behaviours. While unintended consequences of incentive provision are discussed in the literature, evidence syntheses did not identify any primary research with the aim of investigating unintended consequences of incentive interventions for lifestyle behaviour change. Our objective was to investigate perceived positive and negative unintended consequences of incentive provision for a shortlist of seven promising incentive strategies for smoking cessation in pregnancy and breastfeeding. A multi-disciplinary, mixed-methods approach included involving two service-user mother and baby groups from disadvantaged areas with experience of the target behaviours as study co-investigators. Systematic reviews informed the shortlist of incentive strategies. Qualitative semi-structured interviews and a web-based survey of health professionals asked open questions on positive and negative consequences of incentives. The participants from three UK regions were a diverse sample with and without direct experience of incentive interventions: 88 pregnant women/recent mothers/partners/family members; 53 service providers; 24 experts/decision makers and interactive discussions with 63 conference attendees. Maternity and early years health professionals (n = 497) including doctors, midwives, health visitors, public health and related staff participated in the survey. Qualitative analysis identified ethical, political, cultural, social and psychological implications of incentive delivery at population and individual levels. Four key themes emerged: how incentives can address or create inequalities; enhance or diminish intrinsic motivation and wellbeing; have a positive or negative effect on relationships with others within personal networks or health providers; and can impact on health systems and resources by raising awareness and directing service delivery, but may be detrimental to other health care areas. Financial incentives are controversial and generated emotive and oppositional responses. The planning, design and delivery of future incentive interventions should evaluate unexpected consequences to inform the evidence for effectiveness, cost-effectiveness and future implementation. PMID:25357121

Unintended consequences of incentive provision for behaviour change and maintenance around childbirth.

PubMed

Thomson, Gill; Morgan, Heather; Crossland, Nicola; Bauld, Linda; Dykes, Fiona; Hoddinott, Pat; Dombrowski, Stephan; MacLennan, Graeme; Rothnie, Kieran; Stewart, Fiona; Farrar, Shelley; Yi, Deokhee; Hislop, Jenni; Ludbrook, Anne; Campbell, Marion; Moran, Victoria Hall; Sniehotta, Falko; Tappin, David

2014-01-01

Financial (positive or negative) and non-financial incentives or rewards are increasingly used in attempts to influence health behaviours. While unintended consequences of incentive provision are discussed in the literature, evidence syntheses did not identify any primary research with the aim of investigating unintended consequences of incentive interventions for lifestyle behaviour change. Our objective was to investigate perceived positive and negative unintended consequences of incentive provision for a shortlist of seven promising incentive strategies for smoking cessation in pregnancy and breastfeeding. A multi-disciplinary, mixed-methods approach included involving two service-user mother and baby groups from disadvantaged areas with experience of the target behaviours as study co-investigators. Systematic reviews informed the shortlist of incentive strategies. Qualitative semi-structured interviews and a web-based survey of health professionals asked open questions on positive and negative consequences of incentives. The participants from three UK regions were a diverse sample with and without direct experience of incentive interventions: 88 pregnant women/recent mothers/partners/family members; 53 service providers; 24 experts/decision makers and interactive discussions with 63 conference attendees. Maternity and early years health professionals (n = 497) including doctors, midwives, health visitors, public health and related staff participated in the survey. Qualitative analysis identified ethical, political, cultural, social and psychological implications of incentive delivery at population and individual levels. Four key themes emerged: how incentives can address or create inequalities; enhance or diminish intrinsic motivation and wellbeing; have a positive or negative effect on relationships with others within personal networks or health providers; and can impact on health systems and resources by raising awareness and directing service delivery, but may be detrimental to other health care areas. Financial incentives are controversial and generated emotive and oppositional responses. The planning, design and delivery of future incentive interventions should evaluate unexpected consequences to inform the evidence for effectiveness, cost-effectiveness and future implementation.

Individual Tree Crown Delineation Using Multi-Wavelength Titan LIDAR Data

NASA Astrophysics Data System (ADS)

Naveed, F.; Hu, B.

2017-10-01

The inability to detect the Emerald Ash Borer (EAB) at an early stage has led to the enumerable loss of different species of ash trees. Due to the increasing risk being posed by the EAB, a robust and accurate method is needed for identifying Individual Tree Crowns (ITCs) that are at a risk of being infected or are already diseased. This paper attempts to outline an ITC delineation method that employs airborne multi-spectral Light Detection and Ranging (LiDAR) to accurately delineate tree crowns. The raw LiDAR data were initially pre-processed to generate the Digital Surface Models (DSM) and Digital Elevation Models (DEM) using an iterative progressive TIN (Triangulated Irregular Network) densification method. The DSM and DEM were consequently used for Canopy Height Model (CHM) generation, from which the structural information pertaining to the size and shape of the tree crowns was obtained. The structural information along with the spectral information was used to segment ITCs using a region growing algorithm. The availability of the multi-spectral LiDAR data allows for delineation of crowns that have otherwise homogenous structural characteristics and hence cannot be isolated from the CHM alone. This study exploits the spectral data to derive initial approximations of individual tree tops and consequently grow those regions based on the spectral constraints of the individual trees.

The Widening Gulf between Genomics Data Generation and Consumption: A Practical Guide to Big Data Transfer Technology.

PubMed

Feltus, Frank A; Breen, Joseph R; Deng, Juan; Izard, Ryan S; Konger, Christopher A; Ligon, Walter B; Preuss, Don; Wang, Kuang-Ching

2015-01-01

In the last decade, high-throughput DNA sequencing has become a disruptive technology and pushed the life sciences into a distributed ecosystem of sequence data producers and consumers. Given the power of genomics and declining sequencing costs, biology is an emerging "Big Data" discipline that will soon enter the exabyte data range when all subdisciplines are combined. These datasets must be transferred across commercial and research networks in creative ways since sending data without thought can have serious consequences on data processing time frames. Thus, it is imperative that biologists, bioinformaticians, and information technology engineers recalibrate data processing paradigms to fit this emerging reality. This review attempts to provide a snapshot of Big Data transfer across networks, which is often overlooked by many biologists. Specifically, we discuss four key areas: 1) data transfer networks, protocols, and applications; 2) data transfer security including encryption, access, firewalls, and the Science DMZ; 3) data flow control with software-defined networking; and 4) data storage, staging, archiving and access. A primary intention of this article is to orient the biologist in key aspects of the data transfer process in order to frame their genomics-oriented needs to enterprise IT professionals.

Topological and statistical analyses of gene regulatory networks reveal unifying yet quantitatively different emergent properties.

PubMed

Ouma, Wilberforce Zachary; Pogacar, Katja; Grotewold, Erich

2018-04-01

Understanding complexity in physical, biological, social and information systems is predicated on describing interactions amongst different components. Advances in genomics are facilitating the high-throughput identification of molecular interactions, and graphs are emerging as indispensable tools in explaining how the connections in the network drive organismal phenotypic plasticity. Here, we describe the architectural organization and associated emergent topological properties of gene regulatory networks (GRNs) that describe protein-DNA interactions (PDIs) in several model eukaryotes. By analyzing GRN connectivity, our results show that the anticipated scale-free network architectures are characterized by organism-specific power law scaling exponents. These exponents are independent of the fraction of the GRN experimentally sampled, enabling prediction of properties of the complete GRN for an organism. We further demonstrate that the exponents describe inequalities in transcription factor (TF)-target gene recognition across GRNs. These observations have the important biological implication that they predict the existence of an intrinsic organism-specific trans and/or cis regulatory landscape that constrains GRN topologies. Consequently, architectural GRN organization drives not only phenotypic plasticity within a species, but is also likely implicated in species-specific phenotype.

Artificial neuron-glia networks learning approach based on cooperative coevolution.

PubMed

Mesejo, Pablo; Ibáñez, Oscar; Fernández-Blanco, Enrique; Cedrón, Francisco; Pazos, Alejandro; Porto-Pazos, Ana B

2015-06-01

Artificial Neuron-Glia Networks (ANGNs) are a novel bio-inspired machine learning approach. They extend classical Artificial Neural Networks (ANNs) by incorporating recent findings and suppositions about the way information is processed by neural and astrocytic networks in the most evolved living organisms. Although ANGNs are not a consolidated method, their performance against the traditional approach, i.e. without artificial astrocytes, was already demonstrated on classification problems. However, the corresponding learning algorithms developed so far strongly depends on a set of glial parameters which are manually tuned for each specific problem. As a consequence, previous experimental tests have to be done in order to determine an adequate set of values, making such manual parameter configuration time-consuming, error-prone, biased and problem dependent. Thus, in this paper, we propose a novel learning approach for ANGNs that fully automates the learning process, and gives the possibility of testing any kind of reasonable parameter configuration for each specific problem. This new learning algorithm, based on coevolutionary genetic algorithms, is able to properly learn all the ANGNs parameters. Its performance is tested on five classification problems achieving significantly better results than ANGN and competitive results with ANN approaches.

Individual brain structure and modelling predict seizure propagation

PubMed Central

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

2017-01-01

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

Inborn errors of metabolism and the human interactome: a systems medicine approach.

PubMed

Woidy, Mathias; Muntau, Ania C; Gersting, Søren W

2018-02-05

The group of inborn errors of metabolism (IEM) displays a marked heterogeneity and IEM can affect virtually all functions and organs of the human organism; however, IEM share that their associated proteins function in metabolism. Most proteins carry out cellular functions by interacting with other proteins, and thus are organized in biological networks. Therefore, diseases are rarely the consequence of single gene mutations but of the perturbations caused in the related cellular network. Systematic approaches that integrate multi-omics and database information into biological networks have successfully expanded our knowledge of complex disorders but network-based strategies have been rarely applied to study IEM. We analyzed IEM on a proteome scale and found that IEM-associated proteins are organized as a network of linked modules within the human interactome of protein interactions, the IEM interactome. Certain IEM disease groups formed self-contained disease modules, which were highly interlinked. On the other hand, we observed disease modules consisting of proteins from many different disease groups in the IEM interactome. Moreover, we explored the overlap between IEM and non-IEM disease genes and applied network medicine approaches to investigate shared biological pathways, clinical signs and symptoms, and links to drug targets. The provided resources may help to elucidate the molecular mechanisms underlying new IEM, to uncover the significance of disease-associated mutations, to identify new biomarkers, and to develop novel therapeutic strategies.

Control of epidemics on complex networks: Effectiveness of delayed isolation

NASA Astrophysics Data System (ADS)

Pereira, Tiago; Young, Lai-Sang

2015-08-01

We study isolation as a means to control epidemic outbreaks in complex networks, focusing on the consequences of delays in isolating infected nodes. Our analysis uncovers a tipping point: if infected nodes are isolated before a critical day dc, the disease is effectively controlled, whereas for longer delays the number of infected nodes climbs steeply. We show that dc can be estimated explicitly in terms of network properties and disease parameters, connecting lowered values of dc explicitly to heterogeneity in degree distribution. Our results reveal also that initial delays in the implementation of isolation protocols can have catastrophic consequences in heterogeneous networks. As our study is carried out in a general framework, it has the potential to offer insight and suggest proactive strategies for containing outbreaks of a range of serious infectious diseases.

Convergence

NASA Astrophysics Data System (ADS)

Darcie, Thomas E.; Doverspike, Robert; Zirngibl, Martin; Korotky, Steven K.

2004-12-01

Convergence has become a popular theme in telecommunications, one that has broad implications across all segments of the industry. Continual evolution of technology and applications continues to erase lines between traditionally separate lines of business, with dramatic consequences for vendors, service providers, and consumers. Spectacular advances in all layers of optical networking-leading to abundant, dynamic, cost-effective, and reliable wide-area and local-area connections-have been essential drivers of this evolution. As services and networks continue to evolve towards some notion of convergence, the continued role of optical networks must be explored. One vision of convergence renders all information in a common packet (especially IP) format. This vision is driven by the proliferation of data services. For example, time-division multiplexed (TDM) voice becomes VoIP. Analog cable-television signals become MPEG bits streamed to digital set-top boxes. T1 or OC-N private lines migrate to Ethernet virtual private networks (VPNs). All these packets coexist peacefully within a single packet-routing methodology built on an optical transport layer that combines the flexibility and cost of data networks with telecom-grade reliability. While this vision is appealing in its simplicity and shared widely, specifics of implementation raise many challenges and differences of opinion. For example, many seek to expand the role of Ethernet in these transport networks, while massive efforts are underway to make traditional TDM networks more data friendly within an evolved but backward-compatible SDH/SONET (synchronous digital hierarchy and synchronous optical network) multiplexing hierarchy. From this common underlying theme follow many specific instantiations. Examples include the convergence at the physical, logical, and operational levels of voice and data, video and data, private-line and virtual private-line, fixed and mobile, and local and long-haul services. These trends have many consequences for consumers, vendors, and carriers. Faced with large volumes of low-margin data traffic mixed with traditional voice services, the need for capital conservation and operational efficiency drives carriers away from today's separate overlay networks for each service and towards "converged" platforms. For example, cable operators require transport of multiple services over both hybrid fiber coax (HFC) and DWDM transport technologies. Local carriers seek an economical architecture to deliver integrated services on optically enabled broadband-access networks. Services over wireless-access networks must coexist with those from wired networks. In each case, convergence of networks and services inspires an important set of questions and challenges, driven by the need for low cost, operational efficiency, service performance requirements, and optical transport technology options. This Feature Issue explores the various interpretations and implications of network convergence pertinent to optical networking. How does convergence affect the evolution of optical transport-layer and control approaches? Are the implied directions consistent with research vision for optical networks? Substantial challenges remain. Papers are solicited across the broad spectrum of interests. These include, but are not limited to:

• Architecture, design and performance of optical wide-area-network (WAN), metro, and access networks
• Integration strategies for multiservice transport platforms
• Access methods that bridge traditional and emerging services
• Network signaling and control methodologies
• All-optical packet routing and switching techniques

Manuscript Submission

Information Flows? A Critique of Transfer Entropies

NASA Astrophysics Data System (ADS)

James, Ryan G.; Barnett, Nix; Crutchfield, James P.

2016-06-01

A central task in analyzing complex dynamics is to determine the loci of information storage and the communication topology of information flows within a system. Over the last decade and a half, diagnostics for the latter have come to be dominated by the transfer entropy. Via straightforward examples, we show that it and a derivative quantity, the causation entropy, do not, in fact, quantify the flow of information. At one and the same time they can overestimate flow or underestimate influence. We isolate why this is the case and propose several avenues to alternate measures for information flow. We also address an auxiliary consequence: The proliferation of networks as a now-common theoretical model for large-scale systems, in concert with the use of transferlike entropies, has shoehorned dyadic relationships into our structural interpretation of the organization and behavior of complex systems. This interpretation thus fails to include the effects of polyadic dependencies. The net result is that much of the sophisticated organization of complex systems may go undetected.

Designing synthetic networks in silico: a generalised evolutionary algorithm approach.

PubMed

Smith, Robert W; van Sluijs, Bob; Fleck, Christian

2017-12-02

Evolution has led to the development of biological networks that are shaped by environmental signals. Elucidating, understanding and then reconstructing important network motifs is one of the principal aims of Systems & Synthetic Biology. Consequently, previous research has focused on finding optimal network structures and reaction rates that respond to pulses or produce stable oscillations. In this work we present a generalised in silico evolutionary algorithm that simultaneously finds network structures and reaction rates (genotypes) that can satisfy multiple defined objectives (phenotypes). The key step to our approach is to translate a schema/binary-based description of biological networks into systems of ordinary differential equations (ODEs). The ODEs can then be solved numerically to provide dynamic information about an evolved networks functionality. Initially we benchmark algorithm performance by finding optimal networks that can recapitulate concentration time-series data and perform parameter optimisation on oscillatory dynamics of the Repressilator. We go on to show the utility of our algorithm by finding new designs for robust synthetic oscillators, and by performing multi-objective optimisation to find a set of oscillators and feed-forward loops that are optimal at balancing different system properties. In sum, our results not only confirm and build on previous observations but we also provide new designs of synthetic oscillators for experimental construction. In this work we have presented and tested an evolutionary algorithm that can design a biological network to produce desired output. Given that previous designs of synthetic networks have been limited to subregions of network- and parameter-space, the use of our evolutionary optimisation algorithm will enable Synthetic Biologists to construct new systems with the potential to display a wider range of complex responses.

Mechanisms of fibrin polymerization and clinical implications

PubMed Central

Litvinov, Rustem I.

2013-01-01

Research on all stages of fibrin polymerization, using a variety of approaches including naturally occurring and recombinant variants of fibrinogen, x-ray crystallography, electron and light microscopy, and other biophysical approaches, has revealed aspects of the molecular mechanisms involved. The ordered sequence of fibrinopeptide release is essential for the knob-hole interactions that initiate oligomer formation and the subsequent formation of 2-stranded protofibrils. Calcium ions bound both strongly and weakly to fibrin(ogen) have been localized, and some aspects of their roles are beginning to be discovered. Much less is known about the mechanisms of the lateral aggregation of protofibrils and the subsequent branching to yield a 3-dimensional network, although the αC region and B:b knob-hole binding seem to enhance lateral aggregation. Much information now exists about variations in clot structure and properties because of genetic and acquired molecular variants, environmental factors, effects of various intravascular and extravascular cells, hydrodynamic flow, and some functional consequences. The mechanical and chemical stability of clots and thrombi are affected by both the structure of the fibrin network and cross-linking by plasma transglutaminase. There are important clinical consequences to all of these new findings that are relevant for the pathogenesis of diseases, prophylaxis, diagnosis, and treatment. PMID:23305734

Persistence of social signatures in human communication.

PubMed

Saramäki, Jari; Leicht, E A; López, Eduardo; Roberts, Sam G B; Reed-Tsochas, Felix; Dunbar, Robin I M

2014-01-21

The social network maintained by a focal individual, or ego, is intrinsically dynamic and typically exhibits some turnover in membership over time as personal circumstances change. However, the consequences of such changes on the distribution of an ego's network ties are not well understood. Here we use a unique 18-mo dataset that combines mobile phone calls and survey data to track changes in the ego networks and communication patterns of students making the transition from school to university or work. Our analysis reveals that individuals display a distinctive and robust social signature, captured by how interactions are distributed across different alters. Notably, for a given ego, these social signatures tend to persist over time, despite considerable turnover in the identity of alters in the ego network. Thus, as new network members are added, some old network members either are replaced or receive fewer calls, preserving the overall distribution of calls across network members. This is likely to reflect the consequences of finite resources such as the time available for communication, the cognitive and emotional effort required to sustain close relationships, and the ability to make emotional investments.

Persistence of social signatures in human communication

PubMed Central

Saramäki, Jari; Leicht, E. A.; López, Eduardo; Roberts, Sam G. B.; Reed-Tsochas, Felix; Dunbar, Robin I. M.

2014-01-01

The social network maintained by a focal individual, or ego, is intrinsically dynamic and typically exhibits some turnover in membership over time as personal circumstances change. However, the consequences of such changes on the distribution of an ego’s network ties are not well understood. Here we use a unique 18-mo dataset that combines mobile phone calls and survey data to track changes in the ego networks and communication patterns of students making the transition from school to university or work. Our analysis reveals that individuals display a distinctive and robust social signature, captured by how interactions are distributed across different alters. Notably, for a given ego, these social signatures tend to persist over time, despite considerable turnover in the identity of alters in the ego network. Thus, as new network members are added, some old network members either are replaced or receive fewer calls, preserving the overall distribution of calls across network members. This is likely to reflect the consequences of finite resources such as the time available for communication, the cognitive and emotional effort required to sustain close relationships, and the ability to make emotional investments. PMID:24395777

The impact of new forms of large-scale general practice provider collaborations on England's NHS: a systematic review.

PubMed

Pettigrew, Luisa M; Kumpunen, Stephanie; Mays, Nicholas; Rosen, Rebecca; Posaner, Rachel

2018-03-01

Over the past decade, collaboration between general practices in England to form new provider networks and large-scale organisations has been driven largely by grassroots action among GPs. However, it is now being increasingly advocated for by national policymakers. Expectations of what scaling up general practice in England will achieve are significant. To review the evidence of the impact of new forms of large-scale general practice provider collaborations in England. Systematic review. Embase, MEDLINE, Health Management Information Consortium, and Social Sciences Citation Index were searched for studies reporting the impact on clinical processes and outcomes, patient experience, workforce satisfaction, or costs of new forms of provider collaborations between general practices in England. A total of 1782 publications were screened. Five studies met the inclusion criteria and four examined the same general practice networks, limiting generalisability. Substantial financial investment was required to establish the networks and the associated interventions that were targeted at four clinical areas. Quality improvements were achieved through standardised processes, incentives at network level, information technology-enabled performance dashboards, and local network management. The fifth study of a large-scale multisite general practice organisation showed that it may be better placed to implement safety and quality processes than conventional practices. However, unintended consequences may arise, such as perceptions of disenfranchisement among staff and reductions in continuity of care. Good-quality evidence of the impacts of scaling up general practice provider organisations in England is scarce. As more general practice collaborations emerge, evaluation of their impacts will be important to understand which work, in which settings, how, and why. © British Journal of General Practice 2018.

Research Review: Neural response to threat in children, adolescents, and adults after child maltreatment - a quantitative meta-analysis.

PubMed

Hein, Tyler C; Monk, Christopher S

2017-03-01

Child maltreatment is common and has long-term consequences for affective function. Investigations of neural consequences of maltreatment have focused on the amygdala. However, developmental neuroscience indicates that other brain regions are also likely to be affected by child maltreatment, particularly in the social information processing network (SIPN). We conducted a quantitative meta-analysis to: confirm that maltreatment is related to greater bilateral amygdala activation in a large sample that was pooled across studies; investigate other SIPN structures that are likely candidates for altered function; and conduct a data-driven examination to identify additional regions that show altered activation in maltreated children, teens, and adults. We conducted an activation likelihood estimation analysis with 1,733 participants across 20 studies of emotion processing in maltreated individuals. Maltreatment is associated with increased bilateral amygdala activation to emotional faces. One SIPN structure is altered: superior temporal gyrus, of the detection node, is hyperactive in maltreated individuals. The results of the whole-brain corrected analysis also show hyperactivation of the parahippocampal gyrus and insula in maltreated individuals. The meta-analysis confirms that maltreatment is related to increased bilateral amygdala reactivity and also shows that maltreatment affects multiple additional structures in the brain that have received little attention in the literature. Thus, although the majority of studies examining maltreatment and brain function have focused on the amygdala, these findings indicate that the neural consequences of child maltreatment involve a broader network of structures. © 2016 Association for Child and Adolescent Mental Health.

40 CFR 1400.3 - Public access to paper copies of off-site consequence analysis information.

Code of Federal Regulations, 2012 CFR

2012-07-01

...-site consequence analysis information. 1400.3 Section 1400.3 Protection of Environment ENVIRONMENTAL... INFORMATION DISTRIBUTION OF OFF-SITE CONSEQUENCE ANALYSIS INFORMATION Public Access § 1400.3 Public access to paper copies of off-site consequence analysis information. (a) General. The Administrator and the...

40 CFR 1400.3 - Public access to paper copies of off-site consequence analysis information.

Code of Federal Regulations, 2013 CFR

2013-07-01

...-site consequence analysis information. 1400.3 Section 1400.3 Protection of Environment ENVIRONMENTAL... INFORMATION DISTRIBUTION OF OFF-SITE CONSEQUENCE ANALYSIS INFORMATION Public Access § 1400.3 Public access to paper copies of off-site consequence analysis information. (a) General. The Administrator and the...

40 CFR 1400.3 - Public access to paper copies of off-site consequence analysis information.

Code of Federal Regulations, 2011 CFR

2011-07-01

...-site consequence analysis information. 1400.3 Section 1400.3 Protection of Environment ENVIRONMENTAL... INFORMATION DISTRIBUTION OF OFF-SITE CONSEQUENCE ANALYSIS INFORMATION Public Access § 1400.3 Public access to paper copies of off-site consequence analysis information. (a) General. The Administrator and the...

40 CFR 1400.3 - Public access to paper copies of off-site consequence analysis information.

Code of Federal Regulations, 2014 CFR

2014-07-01

...-site consequence analysis information. 1400.3 Section 1400.3 Protection of Environment ENVIRONMENTAL... INFORMATION DISTRIBUTION OF OFF-SITE CONSEQUENCE ANALYSIS INFORMATION Public Access § 1400.3 Public access to paper copies of off-site consequence analysis information. (a) General. The Administrator and the...

Contrasting effects of invasive plants in plant-pollinator networks.

PubMed

Bartomeus, Ignasi; Vilà, Montserrat; Santamaría, Luís

2008-04-01

The structural organization of mutualism networks, typified by interspecific positive interactions, is important to maintain community diversity. However, there is little information available about the effect of introduced species on the structure of such networks. We compared uninvaded and invaded ecological communities, to examine how two species of invasive plants with large and showy flowers (Carpobrotus affine acinaciformis and Opuntia stricta) affect the structure of Mediterranean plant-pollinator networks. To attribute differences in pollination to the direct presence of the invasive species, areas were surveyed that contained similar native plant species cover, diversity and floral composition, with or without the invaders. Both invasive plant species received significantly more pollinator visits than any native species and invaders interacted strongly with pollinators. Overall, the pollinator community richness was similar in invaded and uninvaded plots, and only a few generalist pollinators visited invasive species exclusively. Invasive plants acted as pollination super generalists. The two species studied were visited by 43% and 31% of the total insect taxa in the community, respectively, suggesting they play a central role in the plant-pollinator networks. Carpobrotus and Opuntia had contrasting effects on pollinator visitation rates to native plants: Carpobrotus facilitated the visit of pollinators to native species, whereas Opuntia competed for pollinators with native species, increasing the nestedness of the plant-pollinator network. These results indicate that the introduction of a new species to a community can have important consequences for the structure of the plant-pollinator network.

Examining Food Risk in the Large using a Complex, Networked System-of-sytems Approach

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

Ambrosiano, John; Newkirk, Ryan; Mc Donald, Mark P

2010-12-03

The food production infrastructure is a highly complex system of systems. Characterizing the risks of intentional contamination in multi-ingredient manufactured foods is extremely challenging because the risks depend on the vulnerabilities of food processing facilities and on the intricacies of the supply-distribution networks that link them. A pure engineering approach to modeling the system is impractical because of the overall system complexity and paucity of data. A methodology is needed to assess food contamination risk 'in the large', based on current, high-level information about manufacturing facilities, corrunodities and markets, that will indicate which food categories are most at risk ofmore » intentional contamination and warrant deeper analysis. The approach begins by decomposing the system for producing a multi-ingredient food into instances of two subsystem archetypes: (1) the relevant manufacturing and processing facilities, and (2) the networked corrunodity flows that link them to each other and consumers. Ingredient manufacturing subsystems are modeled as generic systems dynamics models with distributions of key parameters that span the configurations of real facilities. Networks representing the distribution systems are synthesized from general information about food corrunodities. This is done in a series of steps. First, probability networks representing the aggregated flows of food from manufacturers to wholesalers, retailers, other manufacturers, and direct consumers are inferred from high-level approximate information. This is followed by disaggregation of the general flows into flows connecting 'large' and 'small' categories of manufacturers, wholesalers, retailers, and consumers. Optimization methods are then used to determine the most likely network flows consistent with given data. Vulnerability can be assessed for a potential contamination point using a modified CARVER + Shock model. Once the facility and corrunodity flow models are instantiated, a risk consequence analysis can be performed by injecting contaminant at chosen points in the system and propagating the event through the overarching system to arrive at morbidity and mortality figures. A generic chocolate snack cake model, consisting of fluid milk, liquid eggs, and cocoa, is described as an intended proof of concept for multi-ingredient food systems. We aim for an eventual tool that can be used directly by policy makers and planners.« less

Multimedia Workstations: Electronic Assistants for Health-Care Professionals.

PubMed

Degoulet, P; Jean, F-C; Safran, C

1996-01-01

The increasing costs of health care and the economic reality has produced an interesting paradox for the health professional to perform more clinical work with fewer support personnel. Moreover, an explosion of the knowledge-base that underlies sound clinical care not only makes effective time management critical, but also knowledge management compelling. A multimedia workstation is an electronic assistant for the busy health professional that can help with administrative tasks and give access to clinical information and knowledge networks. The multimedia nature of processed information reflects an evolution of medical technologies that involve more and more complex objects such as video sequences or digitized signals. Analysis of the 445 Medline-indexed publications for the January 1991 to December 1994 period, that included the word "workstation" either in their title or in their abstract, helps in refining objectives and challenges both for health professionals and decision makers. From an engineering perspective, development of a workstation requires the integration into the same environments of tools to localize, access, manipulate and communicate the required information. The long-term goal is to establish an easy access in a collaborative working environment that gives the end-user the feeling of a single virtual health enterprise, driven by an integrated computer system when the information system relies on a set of heterogeneous and geographically distributed components. Consequences in terms of migration from traditional client/server architectures to more client/network architectures are considered.

Synergetic and Redundant Information Flow Detected by Unnormalized Granger Causality: Application to Resting State fMRI.

PubMed

Stramaglia, Sebastiano; Angelini, Leonardo; Wu, Guorong; Cortes, Jesus M; Faes, Luca; Marinazzo, Daniele

2016-12-01

We develop a framework for the analysis of synergy and redundancy in the pattern of information flow between subsystems of a complex network. The presence of redundancy and/or synergy in multivariate time series data renders difficulty to estimate the neat flow of information from each driver variable to a given target. We show that adopting an unnormalized definition of Granger causality, one may put in evidence redundant multiplets of variables influencing the target by maximizing the total Granger causality to a given target, over all the possible partitions of the set of driving variables. Consequently, we introduce a pairwise index of synergy which is zero when two independent sources additively influence the future state of the system, differently from previous definitions of synergy. We report the application of the proposed approach to resting state functional magnetic resonance imaging data from the Human Connectome Project showing that redundant pairs of regions arise mainly due to space contiguity and interhemispheric symmetry, while synergy occurs mainly between nonhomologous pairs of regions in opposite hemispheres. Redundancy and synergy, in healthy resting brains, display characteristic patterns, revealed by the proposed approach. The pairwise synergy index, here introduced, maps the informational character of the system at hand into a weighted complex network: the same approach can be applied to other complex systems whose normal state corresponds to a balance between redundant and synergetic circuits.

Convergence

NASA Astrophysics Data System (ADS)

Darcie, Thomas E.; Doverspike, Robert; Zirngibl, Martin; Korotky, Steven K.

2005-02-01

Call for Papers: Convergence Convergence has become a popular theme in telecommunications, one that has broad implications across all segments of the industry. Continual evolution of technology and applications continues to erase lines between traditionally separate lines of business, with dramatic consequences for vendors, service providers, and consumers. Spectacular advances in all layers of optical networking-leading to abundant, dynamic, cost-effective, and reliable wide-area and local-area connections-have been essential drivers of this evolution. As services and networks continue to evolve towards some notion of convergence, the continued role of optical networks must be explored. One vision of convergence renders all information in a common packet (especially IP) format. This vision is driven by the proliferation of data services. For example, time-division multiplexed (TDM) voice becomes VoIP. Analog cable-television signals become MPEG bits streamed to digital set-top boxes. T1 or OC-N private lines migrate to Ethernet virtual private networks (VPNs). All these packets coexist peacefully within a single packet-routing methodology built on an optical transport layer that combines the flexibility and cost of data networks with telecom-grade reliability. While this vision is appealing in its simplicity and shared widely, specifics of implementation raise many challenges and differences of opinion. For example, many seek to expand the role of Ethernet in these transport networks, while massive efforts are underway to make traditional TDM networks more data friendly within an evolved but backward-compatible SDH/SONET (synchronous digital hierarchy and synchronous optical network) multiplexing hierarchy. From this common underlying theme follow many specific instantiations. Examples include the convergence at the physical, logical, and operational levels of voice and data, video and data, private-line and virtual private-line, fixed and mobile, and local and long-haul services. These trends have many consequences for consumers, vendors, and carriers. Faced with large volumes of low-margin data traffic mixed with traditional voice services, the need for capital conservation and operational efficiency drives carriers away from today's separate overlay networks for each service and towards "converged" platforms. For example, cable operators require transport of multiple services over both hybrid fiber coax (HFC) and DWDM transport technologies. Local carriers seek an economical architecture to deliver integrated services on optically enabled broadband-access networks. Services over wireless-access networks must coexist with those from wired networks. In each case, convergence of networks and services inspires an important set of questions and challenges, driven by the need for low cost, operational efficiency, service performance requirements, and optical transport technology options. This Feature Issue explores the various interpretations and implications of network convergence pertinent to optical networking. How does convergence affect the evolution of optical transport-layer and control approaches? Are the implied directions consistent with research vision for optical networks? Substantial challenges remain. Papers are solicited across the broad spectrum of interests. These include, but are not limited to:

Convergence

NASA Astrophysics Data System (ADS)

Darcie, Thomas E.; Doverspike, Robert; Zirngibl, Martin; Korotky, Steven K.

2005-03-01

Call for Papers: Convergence Convergence has become a popular theme in telecommunications, one that has broad implications across all segments of the industry. Continual evolution of technology and applications continues to erase lines between traditionally separate lines of business, with dramatic consequences for vendors, service providers, and consumers. Spectacular advances in all layers of optical networking-leading to abundant, dynamic, cost-effective, and reliable wide-area and local-area connections-have been essential drivers of this evolution. As services and networks continue to evolve towards some notion of convergence, the continued role of optical networks must be explored. One vision of convergence renders all information in a common packet (especially IP) format. This vision is driven by the proliferation of data services. For example, time-division multiplexed (TDM) voice becomes VoIP. Analog cable-television signals become MPEG bits streamed to digital set-top boxes. T1 or OC-N private lines migrate to Ethernet virtual private networks (VPNs). All these packets coexist peacefully within a single packet-routing methodology built on an optical transport layer that combines the flexibility and cost of data networks with telecom-grade reliability. While this vision is appealing in its simplicity and shared widely, specifics of implementation raise many challenges and differences of opinion. For example, many seek to expand the role of Ethernet in these transport networks, while massive efforts are underway to make traditional TDM networks more data friendly within an evolved but backward-compatible SDH/SONET (synchronous digital hierarchy and synchronous optical network) multiplexing hierarchy. From this common underlying theme follow many specific instantiations. Examples include the convergence at the physical, logical, and operational levels of voice and data, video and data, private-line and virtual private-line, fixed and mobile, and local and long-haul services. These trends have many consequences for consumers, vendors, and carriers. Faced with large volumes of low-margin data traffic mixed with traditional voice services, the need for capital conservation and operational efficiency drives carriers away from today's separate overlay networks for each service and towards "converged" platforms. For example, cable operators require transport of multiple services over both hybrid fiber coax (HFC) and DWDM transport technologies. Local carriers seek an economical architecture to deliver integrated services on optically enabled broadband-access networks. Services over wireless-access networks must coexist with those from wired networks. In each case, convergence of networks and services inspires an important set of questions and challenges, driven by the need for low cost, operational efficiency, service performance requirements, and optical transport technology options. This Feature Issue explores the various interpretations and implications of network convergence pertinent to optical networking. How does convergence affect the evolution of optical transport-layer and control approaches? Are the implied directions consistent with research vision for optical networks? Substantial challenges remain. Papers are solicited across the broad spectrum of interests. These include, but are not limited to:

Consequences of plant invasions on compartmentalization and species’ roles in plant–pollinator networks

PubMed Central

Albrecht, Matthias; Padrón, Benigno; Bartomeus, Ignasi; Traveset, Anna

2014-01-01

Compartmentalization—the organization of ecological interaction networks into subsets of species that do not interact with other subsets (true compartments) or interact more frequently among themselves than with other species (modules)—has been identified as a key property for the functioning, stability and evolution of ecological communities. Invasions by entomophilous invasive plants may profoundly alter the way interaction networks are compartmentalized. We analysed a comprehensive dataset of 40 paired plant–pollinator networks (invaded versus uninvaded) to test this hypothesis. We show that invasive plants have higher generalization levels with respect to their pollinators than natives. The consequences for network topology are that—rather than displacing native species from the network—plant invaders attracting pollinators into invaded modules tend to play new important topological roles (i.e. network hubs, module hubs and connectors) and cause role shifts in native species, creating larger modules that are more connected among each other. While the number of true compartments was lower in invaded compared with uninvaded networks, the effect of invasion on modularity was contingent on the study system. Interestingly, the generalization level of the invasive plants partially explains this pattern, with more generalized invaders contributing to a lower modularity. Our findings indicate that the altered interaction structure of invaded networks makes them more robust against simulated random secondary species extinctions, but more vulnerable when the typically highly connected invasive plants go extinct first. The consequences and pathways by which biological invasions alter the interaction structure of plant–pollinator communities highlighted in this study may have important dynamical and functional implications, for example, by influencing multi-species reciprocal selection regimes and coevolutionary processes. PMID:24943368

A Bayesian Belief Network of Threat Anticipation and Terrorist Motivations

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

Olama, Mohammed M; Allgood, Glenn O; Davenport, Kristen M

Recent events highlight the need for efficient tools for anticipating the threat posed by terrorists, whether individual or groups. Antiterrorism includes fostering awareness of potential threats, deterring aggressors, developing security measures, planning for future events, halting an event in process, and ultimately mitigating and managing the consequences of an event. To analyze such components, one must understand various aspects of threat elements like physical assets and their economic and social impacts. To this aim, we developed a three-layer Bayesian belief network (BBN) model that takes into consideration the relative threat of an attack against a particular asset (physical layer) asmore » well as the individual psychology and motivations that would induce a person to either act alone or join a terrorist group and commit terrorist acts (social and economic layers). After researching the many possible motivations to become a terrorist, the main factors are compiled and sorted into categories such as initial and personal indicators, exclusion factors, and predictive behaviors. Assessing such threats requires combining information from disparate data sources most of which involve uncertainties. BBN combines these data in a coherent, analytically defensible, and understandable manner. The developed BBN model takes into consideration the likelihood and consequence of a threat in order to draw inferences about the risk of a terrorist attack so that mitigation efforts can be optimally deployed. The model is constructed using a network engineering process that treats the probability distributions of all the BBN nodes within the broader context of the system development process.« less

Rule-based modeling: a computational approach for studying biomolecular site dynamics in cell signaling systems

PubMed Central

Chylek, Lily A.; Harris, Leonard A.; Tung, Chang-Shung; Faeder, James R.; Lopez, Carlos F.

2013-01-01

Rule-based modeling was developed to address the limitations of traditional approaches for modeling chemical kinetics in cell signaling systems. These systems consist of multiple interacting biomolecules (e.g., proteins), which themselves consist of multiple parts (e.g., domains, linear motifs, and sites of phosphorylation). Consequently, biomolecules that mediate information processing generally have the potential to interact in multiple ways, with the number of possible complexes and post-translational modification states tending to grow exponentially with the number of binary interactions considered. As a result, only large reaction networks capture all possible consequences of the molecular interactions that occur in a cell signaling system, which is problematic because traditional modeling approaches for chemical kinetics (e.g., ordinary differential equations) require explicit network specification. This problem is circumvented through representation of interactions in terms of local rules. With this approach, network specification is implicit and model specification is concise. Concise representation results in a coarse graining of chemical kinetics, which is introduced because all reactions implied by a rule inherit the rate law associated with that rule. Coarse graining can be appropriate if interactions are modular, and the coarseness of a model can be adjusted as needed. Rules can be specified using specialized model-specification languages, and recently developed tools designed for specification of rule-based models allow one to leverage powerful software engineering capabilities. A rule-based model comprises a set of rules, which can be processed by general-purpose simulation and analysis tools to achieve different objectives (e.g., to perform either a deterministic or stochastic simulation). PMID:24123887

Optimal Scheduling for Underwater Communications in Multiple-user Scenarios

DTIC Science & Technology

2014-09-30

underwater acoustic sensor networks . These techniques aim at consuming as less energy as... underwater acoustic networks disrupt the behavior of surrounding species of marine mammals. As a consequence of these two studies, we aim at developing...Markov models of incremental redundancy hybrid ARQ over underwater acoustic channels. Elsevier Journal on Ad-hoc Networks (Special Issue on Underwater Communications and Networks ), 2014. 4

Long-term changes of information environments and computer anxiety of nurse administrators in Japan.

PubMed

Majima, Yukie; Izumi, Takako

2013-01-01

In Japan, medical information systems, including electronic medical records, are being introduced increasingly at medical and nursing fields. Nurse administrators, who are involved in the introduction of medical information systems and who must make proper judgment, are particularly required to have at least minimal knowledge of computers and networks and the ability to think about easy-to-use medical information systems. However, few of the current generation of nurse administrators studied information science subjects in their basic education curriculum. It can be said that information education for nurse administrators has become a pressing issue. Consequently, in this study, we conducted a survey of participants taking the first level program of the education course for Japanese certified nurse administrators to ascertain the actual conditions, such as the information environments that nurse administrators are in, their anxiety attitude to computers. Comparisons over the seven years since 2004 revealed that although introduction of electronic medical records in hospitals was progressing, little change in attributes of participants taking the course was observed, such as computer anxiety.

Dynamics of traffic flow with real-time traffic information

NASA Astrophysics Data System (ADS)

Yokoya, Yasushi

2004-01-01

We studied dynamics of traffic flow with real-time information provided. Provision of the real-time traffic information based on advancements in telecommunication technology is expected to facilitate the efficient utilization of available road capacity. This system has a potentiality of not only engineering for road usage but also the science of complexity series. In the system, the information plays a role of feedback connecting microscopic and macroscopic phenomena beyond the hierarchical structure of statistical physics. In this paper, we tried to clarify how the information works in a network of traffic flow from the perspective of statistical physics. The dynamical feature of the traffic flow is abstracted by a contrastive study between the nonequilibrium statistical physics and a computer simulation based on cellular automaton. We found that the information disrupts the local equilibrium of traffic flow by a characteristic dissipation process due to interaction between the information and individual vehicles. The dissipative structure was observed in the time evolution of traffic flow driven far from equilibrium as a consequence of the breakdown of the local-equilibrium hypothesis.

Network-Cognizant Voltage Droop Control for Distribution Grids

DOE PAGES

Baker, Kyri; Bernstein, Andrey; Dall'Anese, Emiliano; ...

2017-08-07

Our paper examines distribution systems with a high integration of distributed energy resources (DERs) and addresses the design of local control methods for real-time voltage regulation. Particularly, the paper focuses on proportional control strategies where the active and reactive output-powers of DERs are adjusted in response to (and proportionally to) local changes in voltage levels. The design of the voltage-active power and voltage-reactive power characteristics leverages suitable linear approximation of the AC power-flow equations and is network-cognizant; that is, the coefficients of the controllers embed information on the location of the DERs and forecasted non-controllable loads/injections and, consequently, on themore » effect of DER power adjustments on the overall voltage profile. We pursued a robust approach to cope with uncertainty in the forecasted non-controllable loads/power injections. Stability of the proposed local controllers is analytically assessed and numerically corroborated.« less

Network-Cognizant Voltage Droop Control for Distribution Grids

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

Baker, Kyri; Bernstein, Andrey; Dall'Anese, Emiliano

Our paper examines distribution systems with a high integration of distributed energy resources (DERs) and addresses the design of local control methods for real-time voltage regulation. Particularly, the paper focuses on proportional control strategies where the active and reactive output-powers of DERs are adjusted in response to (and proportionally to) local changes in voltage levels. The design of the voltage-active power and voltage-reactive power characteristics leverages suitable linear approximation of the AC power-flow equations and is network-cognizant; that is, the coefficients of the controllers embed information on the location of the DERs and forecasted non-controllable loads/injections and, consequently, on themore » effect of DER power adjustments on the overall voltage profile. We pursued a robust approach to cope with uncertainty in the forecasted non-controllable loads/power injections. Stability of the proposed local controllers is analytically assessed and numerically corroborated.« less

An optimal general type-2 fuzzy controller for Urban Traffic Network.

PubMed

Khooban, Mohammad Hassan; Vafamand, Navid; Liaghat, Alireza; Dragicevic, Tomislav

2017-01-01

Urban traffic network model is illustrated by state-charts and object-diagram. However, they have limitations to show the behavioral perspective of the Traffic Information flow. Consequently, a state space model is used to calculate the half-value waiting time of vehicles. In this study, a combination of the general type-2 fuzzy logic sets and the Modified Backtracking Search Algorithm (MBSA) techniques are used in order to control the traffic signal scheduling and phase succession so as to guarantee a smooth flow of traffic with the least wait times and average queue length. The parameters of input and output membership functions are optimized simultaneously by the novel heuristic algorithm MBSA. A comparison is made between the achieved results with those of optimal and conventional type-1 fuzzy logic controllers. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

Detecting a currency’s dominance using multivariate time series analysis

NASA Astrophysics Data System (ADS)

Syahidah Yusoff, Nur; Sharif, Shamshuritawati

2017-09-01

A currency exchange rate is the price of one country’s currency in terms of another country’s currency. There are four different prices; opening, closing, highest, and lowest can be achieved from daily trading activities. In the past, a lot of studies have been carried out by using closing price only. However, those four prices are interrelated to each other. Thus, the multivariate time series can provide more information than univariate time series. Therefore, the enthusiasm of this paper is to compare the results of two different approaches, which are mean vector and Escoufier’s RV coefficient in constructing similarity matrices of 20 world currencies. Consequently, both matrices are used to substitute the correlation matrix required by network topology. With the help of degree centrality measure, we can detect the currency’s dominance for both networks. The pros and cons for both approaches will be presented at the end of this paper.

Path Flow Estimation Using Time Varying Coefficient State Space Model

NASA Astrophysics Data System (ADS)

Jou, Yow-Jen; Lan, Chien-Lun

2009-08-01

The dynamic path flow information is very crucial in the field of transportation operation and management, i.e., dynamic traffic assignment, scheduling plan, and signal timing. Time-dependent path information, which is important in many aspects, is nearly impossible to be obtained. Consequently, researchers have been seeking estimation methods for deriving valuable path flow information from less expensive traffic data, primarily link traffic counts of surveillance systems. This investigation considers a path flow estimation problem involving the time varying coefficient state space model, Gibbs sampler, and Kalman filter. Numerical examples with part of a real network of the Taipei Mass Rapid Transit with real O-D matrices is demonstrated to address the accuracy of proposed model. Results of this study show that this time-varying coefficient state space model is very effective in the estimation of path flow compared to time-invariant model.

The Role of Node Heterogeneity in the Coupled Spreading of Epidemics and Awareness.

PubMed

Guo, Quantong; Lei, Yanjun; Xia, Chengyi; Guo, Lu; Jiang, Xin; Zheng, Zhiming

2016-01-01

Exploring the interplay between information spreading and epidemic spreading is a topic that has been receiving increasing attention. As an efficient means of depicting the spreading of information, which manifests as a cascade phenomenon, awareness cascading is utilized to investigate this coupled transmission. Because in reality, different individuals facing the same epidemic will exhibit distinct behaviors according to their own experiences and attributes, it is important for us to consider the heterogeneity of individuals. Consequently, we propose a heterogeneous spreading model. To describe the heterogeneity, two of the most important but radically different methods for this purpose, the degree and k-core measures, are studied in this paper through three models based on different assumptions. Adopting a Markov chain approach, we succeed in predicting the epidemic threshold trend. Furthermore, we find that when the k-core measure is used to classify individuals, the spreading process is robust to these models, meaning that regardless of the model used, the spreading process is nearly identical at the macroscopic level. In addition, the k-core measure leads to a much larger final epidemic size than the degree measure. These results are cross-checked through numerous simulations, not only of a synthetic network but also of a real multiplex network. The presented findings provide a better understanding of k-core individuals and reveal the importance of considering network structure when investigating various dynamic processes.

The Role of Node Heterogeneity in the Coupled Spreading of Epidemics and Awareness

PubMed Central

2016-01-01

Exploring the interplay between information spreading and epidemic spreading is a topic that has been receiving increasing attention. As an efficient means of depicting the spreading of information, which manifests as a cascade phenomenon, awareness cascading is utilized to investigate this coupled transmission. Because in reality, different individuals facing the same epidemic will exhibit distinct behaviors according to their own experiences and attributes, it is important for us to consider the heterogeneity of individuals. Consequently, we propose a heterogeneous spreading model. To describe the heterogeneity, two of the most important but radically different methods for this purpose, the degree and k-core measures, are studied in this paper through three models based on different assumptions. Adopting a Markov chain approach, we succeed in predicting the epidemic threshold trend. Furthermore, we find that when the k-core measure is used to classify individuals, the spreading process is robust to these models, meaning that regardless of the model used, the spreading process is nearly identical at the macroscopic level. In addition, the k-core measure leads to a much larger final epidemic size than the degree measure. These results are cross-checked through numerous simulations, not only of a synthetic network but also of a real multiplex network. The presented findings provide a better understanding of k-core individuals and reveal the importance of considering network structure when investigating various dynamic processes. PMID:27517715

The Role of Social Network Technologies in Online Health Promotion: A Narrative Review of Theoretical and Empirical Factors Influencing Intervention Effectiveness.

PubMed

Balatsoukas, Panos; Kennedy, Catriona M; Buchan, Iain; Powell, John; Ainsworth, John

2015-06-11

Social network technologies have become part of health education and wider health promotion—either by design or happenstance. Social support, peer pressure, and information sharing in online communities may affect health behaviors. If there are positive and sustained effects, then social network technologies could increase the effectiveness and efficiency of many public health campaigns. Social media alone, however, may be insufficient to promote health. Furthermore, there may be unintended and potentially harmful consequences of inaccurate or misleading health information. Given these uncertainties, there is a need to understand and synthesize the evidence base for the use of online social networking as part of health promoting interventions to inform future research and practice. Our aim was to review the research on the integration of expert-led health promotion interventions with online social networking in order to determine the extent to which the complementary benefits of each are understood and used. We asked, in particular, (1) How is effectiveness being measured and what are the specific problems in effecting health behavior change?, and (2) To what extent is the designated role of social networking grounded in theory? The narrative synthesis approach to literature review was used to analyze the existing evidence. We searched the indexed scientific literature using keywords associated with health promotion and social networking. The papers included were only those making substantial study of both social networking and health promotion—either reporting the results of the intervention or detailing evidence-based plans. General papers about social networking and health were not included. The search identified 162 potentially relevant documents after review of titles and abstracts. Of these, 42 satisfied the inclusion criteria after full-text review. Six studies described randomized controlled trials (RCTs) evaluating the effectiveness of online social networking within health promotion interventions. Most of the trials investigated the value of a "social networking condition" in general and did not identify specific features that might play a role in effectiveness. Issues about the usability and level of uptake of interventions were more common among pilot studies, while observational studies showed positive evidence about the role of social support. A total of 20 papers showed the use of theory in the design of interventions, but authors evaluated effectiveness in only 10 papers. More research is needed in this area to understand the actual effect of social network technologies on health promotion. More RCTs of greater length need to be conducted taking into account contextual factors such as patient characteristics and types of a social network technology. Also, more evidence is needed regarding the actual usability of online social networking and how different interface design elements may help or hinder behavior change and engagement. Moreover, it is crucial to investigate further the effect of theory on the effectiveness of this type of technology for health promotion. Research is needed linking theoretical grounding with observation and analysis of health promotion in online networks.

Hardware Neural Network for a Visual Inspection System

NASA Astrophysics Data System (ADS)

Chun, Seungwoo; Hayakawa, Yoshihiro; Nakajima, Koji

The visual inspection of defects in products is heavily dependent on human experience and instinct. In this situation, it is difficult to reduce the production costs and to shorten the inspection time and hence the total process time. Consequently people involved in this area desire an automatic inspection system. In this paper, we propose a hardware neural network, which is expected to provide high-speed operation for automatic inspection of products. Since neural networks can learn, this is a suitable method for self-adjustment of criteria for classification. To achieve high-speed operation, we use parallel and pipelining techniques. Furthermore, we use a piecewise linear function instead of a conventional activation function in order to save hardware resources. Consequently, our proposed hardware neural network achieved 6GCPS and 2GCUPS, which in our test sample proved to be sufficiently fast.

An event- and network-level analysis of college students' maximum drinking day.

PubMed

Meisel, Matthew K; DiBello, Angelo M; Balestrieri, Sara G; Ott, Miles Q; DiGuiseppi, Graham T; Clark, Melissa A; Barnett, Nancy P

2018-04-01

Heavy episodic drinking is common among college students and remains a serious public health issue. Previous event-level research among college students has examined behaviors and individual-level characteristics that drive consumption and related consequences but often ignores the social network of people with whom these heavy drinking episodes occur. The main aim of the current study was to investigate the network of social connections between drinkers on their heaviest drinking occasions. Sociocentric network methods were used to collect information from individuals in the first-year class (N=1342) at one university. Past-month drinkers (N=972) reported on the characteristics of their heaviest drinking occasion in the past month and indicated who else among their network connections was present during this occasion. Average max drinking day indegree, or the total number of times a participant was nominated as being present on another students' heaviest drinking occasion, was 2.50 (SD=2.05). Network autocorrelation models indicated that max drinking day indegree (e.g., popularity on heaviest drinking occassions) and peers' number of drinks on their own maximum drinking occasions were significantly associated with participant maximum number of drinks, after controlling for demographic variables, pregaming, and global network indegree (e.g., popularity in the entire first-year class). Being present at other peers' heaviest drinking occasions is associated with greater drinking quantities on one's own heaviest drinking occasion. These findings suggest the potential for interventions that target peer influences within close social networks of drinkers. Copyright © 2017 Elsevier Ltd. All rights reserved.

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

PubMed

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.

Logic-based models in systems biology: a predictive and parameter-free network analysis method†

PubMed Central

Wynn, Michelle L.; Consul, Nikita; Merajver, Sofia D.

2012-01-01

Highly complex molecular networks, which play fundamental roles in almost all cellular processes, are known to be dysregulated in a number of diseases, most notably in cancer. As a consequence, there is a critical need to develop practical methodologies for constructing and analysing molecular networks at a systems level. Mathematical models built with continuous differential equations are an ideal methodology because they can provide a detailed picture of a network’s dynamics. To be predictive, however, differential equation models require that numerous parameters be known a priori and this information is almost never available. An alternative dynamical approach is the use of discrete logic-based models that can provide a good approximation of the qualitative behaviour of a biochemical system without the burden of a large parameter space. Despite their advantages, there remains significant resistance to the use of logic-based models in biology. Here, we address some common concerns and provide a brief tutorial on the use of logic-based models, which we motivate with biological examples. PMID:23072820

Neural Network Based Sensory Fusion for Landmark Detection

NASA Technical Reports Server (NTRS)

Kumbla, Kishan -K.; Akbarzadeh, Mohammad R.

1997-01-01

NASA is planning to send numerous unmanned planetary missions to explore the space. This requires autonomous robotic vehicles which can navigate in an unstructured, unknown, and uncertain environment. Landmark based navigation is a new area of research which differs from the traditional goal-oriented navigation, where a mobile robot starts from an initial point and reaches a destination in accordance with a pre-planned path. The landmark based navigation has the advantage of allowing the robot to find its way without communication with the mission control station and without exact knowledge of its coordinates. Current algorithms based on landmark navigation however pose several constraints. First, they require large memories to store the images. Second, the task of comparing the images using traditional methods is computationally intensive and consequently real-time implementation is difficult. The method proposed here consists of three stages, First stage utilizes a heuristic-based algorithm to identify significant objects. The second stage utilizes a neural network (NN) to efficiently classify images of the identified objects. The third stage combines distance information with the classification results of neural networks for efficient and intelligent navigation.

Using robust Bayesian network to estimate the residuals of fluoroquinolone antibiotic in soil.

PubMed

Li, Xuewen; Xie, Yunfeng; Li, Lianfa; Yang, Xunfeng; Wang, Ning; Wang, Jinfeng

2015-11-01

Prediction of antibiotic pollution and its consequences is difficult, due to the uncertainties and complexities associated with multiple related factors. This article employed domain knowledge and spatial data to construct a Bayesian network (BN) model to assess fluoroquinolone antibiotic (FQs) pollution in the soil of an intensive vegetable cultivation area. The results show: (1) The relationships between FQs pollution and contributory factors: Three factors (cultivation methods, crop rotations, and chicken manure types) were consistently identified as predictors in the topological structures of three FQs, indicating their importance in FQs pollution; deduced with domain knowledge, the cultivation methods are determined by the crop rotations, which require different nutrients (derived from the manure) according to different plant biomass. (2) The performance of BN model: The integrative robust Bayesian network model achieved the highest detection probability (pd) of high-risk and receiver operating characteristic (ROC) area, since it incorporates domain knowledge and model uncertainty. Our encouraging findings have implications for the use of BN as a robust approach to assessment of FQs pollution and for informing decisions on appropriate remedial measures.

On imputing function to structure from the behavioural effects of brain lesions.

PubMed

Young, M P; Hilgetag, C C; Scannell, J W

2000-01-29

What is the link, if any, between the patterns of connections in the brain and the behavioural effects of localized brain lesions? We explored this question in four related ways. First, we investigated the distribution of activity decrements that followed simulated damage to elements of the thalamocortical network, using integrative mechanisms that have recently been used to successfully relate connection data to information on the spread of activation, and to account simultaneously for a variety of lesion effects. Second, we examined the consequences of the patterns of decrement seen in the simulation for each type of inference that has been employed to impute function to structure on the basis of the effects of brain lesions. Every variety of conventional inference, including double dissociation, readily misattributed function to structure. Third, we tried to derive a more reliable framework of inference for imputing function to structure, by clarifying concepts of function, and exploring a more formal framework, in which knowledge of connectivity is necessary but insufficient, based on concepts capable of mathematical specification. Fourth, we applied this framework to inferences about function relating to a simple network that reproduces intact, lesioned and paradoxically restored orientating behaviour. Lesion effects could be used to recover detailed and reliable information on which structures contributed to particular functions in this simple network. Finally, we explored how the effects of brain lesions and this formal approach could be used in conjunction with information from multiple neuroscience methodologies to develop a practical and reliable approach to inferring the functional roles of brain structures.

The Governance of Indigenous Natural Products in Namibia: A Policy Network Analysis.

PubMed

Ndeinoma, Albertina; Wiersum, K Freerk; Arts, Bas

2018-01-09

At the end of the 20th century, optimism existed that non-timber forest products (NTFPs) can form an integral part in conservation and development strategies. However, there is limited knowledge on how the different stakeholders could relate to the state or to each other in promoting commercialization of NTFPs. Applying the policy network as an analytical framework, we investigated the structural patterns of actor relations in the governance structure of indigenous natural products (INPs) in Namibia, to understand the implications of such relations on INP policy process. The findings indicate that the INP policy network in Namibia is multi-dimensional, consisting of the Indigenous Plant Task Team (IPTT)-the key governance structure for resource mobilization and information sharing; and functional relations which serve specific roles in the INP value chain. The existing relations have facilitated policy development particularly for heavily regulated species, such as devil's claw; but for other species, only incremental changes are observed in terms of small-scale processing facilities for value addition and exclusive purchase agreements for sustainable sourcing of INPs. Participation of primary producers, private actors and quality standardization bodies is limited in INPs governance structures, which narrow the scope of information sharing. Consequently, despite that the IPTT has fostered publicly funded explorative pilot projects, ranging from production to marketing of INPs, there are no clear guidelines how these projects results can be transferred to private entities for possible commercialization. Further collaboration and information sharing is needed to guide public sector relations with the private entities and cooperatives.

Comparison study on qualitative and quantitative risk assessment methods for urban natural gas pipeline network.

PubMed

Han, Z Y; Weng, W G

2011-05-15

In this paper, a qualitative and a quantitative risk assessment methods for urban natural gas pipeline network are proposed. The qualitative method is comprised of an index system, which includes a causation index, an inherent risk index, a consequence index and their corresponding weights. The quantitative method consists of a probability assessment, a consequences analysis and a risk evaluation. The outcome of the qualitative method is a qualitative risk value, and for quantitative method the outcomes are individual risk and social risk. In comparison with previous research, the qualitative method proposed in this paper is particularly suitable for urban natural gas pipeline network, and the quantitative method takes different consequences of accidents into consideration, such as toxic gas diffusion, jet flame, fire ball combustion and UVCE. Two sample urban natural gas pipeline networks are used to demonstrate these two methods. It is indicated that both of the two methods can be applied to practical application, and the choice of the methods depends on the actual basic data of the gas pipelines and the precision requirements of risk assessment. Crown Copyright © 2011. Published by Elsevier B.V. All rights reserved.

On genomics, kin, and privacy

PubMed Central

Telenti, Amalio; Ayday, Erman; Hubaux, Jean Pierre

2014-01-01

The storage of greater numbers of exomes or genomes raises the question of loss of privacy for the individual and for families if genomic data are not properly protected. Access to genome data may result from a personal decision to disclose, or from gaps in protection. In either case, revealing genome data has consequences beyond the individual, as it compromises the privacy of family members. Increasing availability of genome data linked or linkable to metadata through online social networks and services adds one additional layer of complexity to the protection of genome privacy.  The field of computer science and information technology offers solutions to secure genomic data so that individuals, medical personnel or researchers can access only the subset of genomic information required for healthcare or dedicated studies. PMID:25254097

Trophic level, successional age and trait matching determine specialization of deadwood-based interaction networks of saproxylic beetles

PubMed Central

Gossner, Martin M.; Grass, Ingo; Arnstadt, Tobias; Hofrichter, Martin; Floren, Andreas; Linsenmair, Karl Eduard; Weisser, Wolfgang W.; Steffan-Dewenter, Ingolf

2017-01-01

The specialization of ecological networks provides important insights into possible consequences of biodiversity loss for ecosystem functioning. However, mostly mutualistic and antagonistic interactions of living organisms have been studied, whereas detritivore networks and their successional changes are largely unexplored. We studied the interactions of saproxylic (deadwood-dependent) beetles with their dead host trees. In a large-scale experiment, 764 logs of 13 tree species were exposed to analyse network structure of three trophic groups of saproxylic beetles over 3 successional years. We found remarkably high specialization of deadwood-feeding xylophages and lower specialization of fungivorous and predatory species. During deadwood succession, community composition, network specialization and network robustness changed differently for the functional groups. To reveal potential drivers of network specialization, we linked species' functional traits to their network roles, and tested for trait matching between plant (i.e. chemical compounds) and beetle (i.e. body size) traits. We found that both plant and animal traits are major drivers of species specialization, and that trait matching can be more important in explaining interactions than neutral processes reflecting species abundance distributions. High network specialization in the early successional stage and decreasing network robustness during succession indicate vulnerability of detritivore networks to reduced tree species diversity and beetle extinctions, with unknown consequences for wood decomposition and nutrient cycling. PMID:28469020

Quantitative analysis of factors that affect oil pipeline network accident based on Bayesian networks: A case study in China

NASA Astrophysics Data System (ADS)

Zhang, Chao; Qin, Ting Xin; Huang, Shuai; Wu, Jian Song; Meng, Xin Yan

2018-06-01

Some factors can affect the consequences of oil pipeline accident and their effects should be analyzed to improve emergency preparation and emergency response. Although there are some qualitative analysis models of risk factors' effects, the quantitative analysis model still should be researched. In this study, we introduce a Bayesian network (BN) model of risk factors' effects analysis in an oil pipeline accident case that happened in China. The incident evolution diagram is built to identify the risk factors. And the BN model is built based on the deployment rule for factor nodes in BN and the expert knowledge by Dempster-Shafer evidence theory. Then the probabilities of incident consequences and risk factors' effects can be calculated. The most likely consequences given by this model are consilient with the case. Meanwhile, the quantitative estimations of risk factors' effects may provide a theoretical basis to take optimal risk treatment measures for oil pipeline management, which can be used in emergency preparation and emergency response.

Understanding transit ridership demand for a multi-destination, multimodal transit network in an American metropolitan area : lessons for increasing choice ridership while maintaining transit dependent ridership.

DOT National Transportation Integrated Search

2012-01-01

This study examines the factors underlying transit demand in the multi-destination, integrated bus and rail transit network for Atlanta, Georgia. Atlanta provides an opportunity to explore the consequences of a multi-destination transit network for b...

The Practices of Student Network as Cooperative Learning in Ethiopia

ERIC Educational Resources Information Center

Reda, Weldemariam Nigusse; Hagos, Girmay Tsegay

2015-01-01

Student network is a teaching strategy introduced as cooperative learning to all educational levels above the upper primary schools (grade 5 and above) in Ethiopia. The study was, therefore, aimed at investigating to what extent the student network in Ethiopia is actually practiced in line with the principles of cooperative learning. Consequently,…

A Revolution in Regional Networking: Linking the Knowledge. AIR 1995 Annual Forum Paper.

ERIC Educational Resources Information Center

Rosmalen, C. M. van

Regional networking and knowledge transfer are considered with a focus on partnerships between business and higher education institutions, conditions for successful strategic allegiances, and the consequences of networking for the higher education mission. The experiences of Utrecht University (the Netherlands) are used to illustrate how a higher…

Class Size, School Size and the Size of the School Network

ERIC Educational Resources Information Center

Coupé, Tom; Olefir, Anna; Alonso, Juan Diego

2016-01-01

In many transition countries, including Ukraine, decreases in population and fertility have led to substantial falls in the number of school-aged children. As a consequence, these countries now have school networks that consist of many small schools, leading many countries to consider reorganizing their networks by closing smaller schools and…

Optimizing the process of recovery after road network break-up

NASA Astrophysics Data System (ADS)

Bíl, Michal; Vodák, Rostislav; Křivánková, Zuzana

2016-04-01

A functioning road network provides accessibility to municipalities, important services and facilities. This basic role of the network can be disrupted by natural disasters which usually affect large areas and cause temporal blockages or even destruction of many roads at the same time. This often leads to road network break-up, when a number of disconnected parts emerge. These parts are often of varying importance to society. Some of them may contain large cities or important facilities such as hospitals. This should be reflected during reconnection works when the most important parts of the network should be reconnected among the first in order to reduce the impact of the event. Decision makers and crisis managers, however, do still not have any dynamic tool which might help them with prioritizing the necessary steps. In our presentation we introduce an algorithm and examples of suitable loss functions which enable us to rapidly identify isolated parts of the network, evaluate them and consequently establish an optimal ranked sequence of interrupted links which have to be repaired to reduce the consequences of the disasters.

Delineating functional principles of the bow tie structure of a kinase-phosphatase network in the budding yeast.

PubMed

Abd-Rabbo, Diala; Michnick, Stephen W

2017-03-16

Kinases and phosphatases (KP) form complex self-regulating networks essential for cellular signal processing. In spite of having a wealth of data about interactions among KPs and their substrates, we have very limited models of the structures of the directed networks they form and consequently our ability to formulate hypotheses about how their structure determines the flow of information in these networks is restricted. We assembled and studied the largest bona fide kinase-phosphatase network (KP-Net) known to date for the yeast Saccharomyces cerevisiae. Application of the vertex sort (VS) algorithm on the KP-Net allowed us to elucidate its hierarchical structure in which nodes are sorted into top, core and bottom layers, forming a bow tie structure with a strongly connected core layer. Surprisingly, phosphatases tend to sort into the top layer, implying they are less regulated by phosphorylation than kinases. Superposition of the widest range of KP biological properties over the KP-Net hierarchy shows that core layer KPs: (i), receive the largest number of inputs; (ii), form bottlenecks implicated in multiple pathways and in decision-making; (iii), and are among the most regulated KPs both temporally and spatially. Moreover, top layer KPs are more abundant and less noisy than those in the bottom layer. Finally, we showed that the VS algorithm depends on node degrees without biasing the biological results of the sorted network. The VS algorithm is available as an R package ( https://cran.r-project.org/web/packages/VertexSort/index.html ). The KP-Net model we propose possesses a bow tie hierarchical structure in which the top layer appears to ensure highest fidelity and the core layer appears to mediate signal integration and cell state-dependent signal interpretation. Our model of the yeast KP-Net provides both functional insight into its organization as we understand today and a framework for future investigation of information processing in yeast and eukaryotes in general.

Environmental Hazards Assessment Program. Volume 4: Annual report, July 1, 1993--June 30, 1994

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

Not Available

The Medical University of South Carolina`s (MUSC) vision is to become the premier national resource for medical information and for environmental/health risk assessment. A key component to the success of the many missions of the Environmental Hazards Assessment Program (EHAP) is timely access to large volumes of data. The significant growth in the number of environmental/health information systems that has occurred over the past few years has made data access challenging. This study documents the results of the needs assessment effort conducted to determine the information access and processing requirements of EHAP. The following topics are addressed in this report:more » immunological consequences of beryllium exposure; assessment of genetic risks to environmental diseases; low dose-rate radiation health effects; environmental risk perception in defined populations; information support and access systems; and environmental medicine and risk communication: curriculum and a professional support network-Department of Family Medicine.« less

Power System Information Delivering System Based on Distributed Object

NASA Astrophysics Data System (ADS)

Tanaka, Tatsuji; Tsuchiya, Takehiko; Tamura, Setsuo; Seki, Tomomichi; Kubota, Kenji

In recent years, improvement in computer performance and development of computer network technology or the distributed information processing technology has a remarkable thing. Moreover, the deregulation is starting and will be spreading in the electric power industry in Japan. Consequently, power suppliers are required to supply low cost power with high quality services to customers. Corresponding to these movements the authors have been proposed SCOPE (System Configuration Of PowEr control system) architecture for distributed EMS/SCADA (Energy Management Systems / Supervisory Control and Data Acquisition) system based on distributed object technology, which offers the flexibility and expandability adapting those movements. In this paper, the authors introduce a prototype of the power system information delivering system, which was developed based on SCOPE architecture. This paper describes the architecture and the evaluation results of this prototype system. The power system information delivering system supplies useful power systems information such as electric power failures to the customers using Internet and distributed object technology. This system is new type of SCADA system which monitors failure of power transmission system and power distribution system with geographic information integrated way.

Essential elements of online information networks on invasive alien species

USGS Publications Warehouse

Simpson, A.; Sellers, E.; Grosse, A.; Xie, Y.

2006-01-01

In order to be effective, information must be placed in the proper context and organized in a manner that is logical and (preferably) standardized. Recently, invasive alien species (IAS) scientists have begun to create online networks to share their information concerning IAS prevention and control. At a special networking session at the Beijing International Symposium on Biological Invasions, an online Eastern Asia-North American IAS Information Network (EA-NA Network) was proposed. To prepare for the development of this network, and to provide models for other regional collaborations, we compare four examples of global, regional, and national online IAS information networks: the Global Invasive Species Information Network, the Invasives Information Network of the Inter-American Biodiversity Information Network, the Chinese Species Information System, and the Invasive Species Information Node of the US National Biological Information Infrastructure. We conclude that IAS networks require a common goal, dedicated leaders, effective communication, and broad endorsement, in order to obtain sustainable, long-term funding and long-term stability. They need to start small, use the experience of other networks, partner with others, and showcase benefits. Global integration and synergy among invasive species networks will succeed with contributions from both the top-down and the bottom-up. ?? 2006 Springer.

Preliminary investigation of Brain Network Activation (BNA) and its clinical utility in sport-related concussion.

PubMed

Reches, A; Kutcher, J; Elbin, R J; Or-Ly, H; Sadeh, B; Greer, J; McAllister, D J; Geva, A; Kontos, A P

2017-01-01

The clinical diagnosis and management of patients with sport-related concussion is largely dependent on subjectively reported symptoms, clinical examinations, cognitive, balance, vestibular and oculomotor testing. Consequently, there is an unmet need for objective assessment tools that can identify the injury from a physiological perspective and add an important layer of information to the clinician's decision-making process. The goal of the study was to evaluate the clinical utility of the EEG-based tool named Brain Network Activation (BNA) as a longitudinal assessment method of brain function in the management of young athletes with concussion. Athletes with concussion (n = 86) and age-matched controls (n = 81) were evaluated at four time points with symptom questionnaires and BNA. BNA scores were calculated by comparing functional networks to a previously defined normative reference brain network model to the same cognitive task. Subjects above 16 years of age exhibited a significant decrease in BNA scores immediately following injury, as well as notable changes in functional network activity, relative to the controls. Three representative case studies of the tested population are discussed in detail, to demonstrate the clinical utility of BNA. The data support the utility of BNA to augment clinical examinations, symptoms and additional tests by providing an effective method for evaluating objective electrophysiological changes associated with sport-related concussions.

Preliminary investigation of Brain Network Activation (BNA) and its clinical utility in sport-related concussion

PubMed Central

Reches, A.; Kutcher, J.; Elbin, R. J.; Or-Ly, H.; Sadeh, B.; Greer, J.; McAllister, D. J.; Geva, A.; Kontos, A. P.

2017-01-01

ABSTRACT Background: The clinical diagnosis and management of patients with sport-related concussion is largely dependent on subjectively reported symptoms, clinical examinations, cognitive, balance, vestibular and oculomotor testing. Consequently, there is an unmet need for objective assessment tools that can identify the injury from a physiological perspective and add an important layer of information to the clinician’s decision-making process. Objective: The goal of the study was to evaluate the clinical utility of the EEG-based tool named Brain Network Activation (BNA) as a longitudinal assessment method of brain function in the management of young athletes with concussion. Methods: Athletes with concussion (n = 86) and age-matched controls (n = 81) were evaluated at four time points with symptom questionnaires and BNA. BNA scores were calculated by comparing functional networks to a previously defined normative reference brain network model to the same cognitive task. Results: Subjects above 16 years of age exhibited a significant decrease in BNA scores immediately following injury, as well as notable changes in functional network activity, relative to the controls. Three representative case studies of the tested population are discussed in detail, to demonstrate the clinical utility of BNA. Conclusion: The data support the utility of BNA to augment clinical examinations, symptoms and additional tests by providing an effective method for evaluating objective electrophysiological changes associated with sport-related concussions. PMID:28055228

Informal Discussions in Substance Abuse Treatment Sessions with Spanish-speaking Clients

PubMed Central

Bamatter, Wendy; Carroll, Kathleen M.; Añez, Luis M.; Paris, Manuel; Ball, Samuel A.; Nich, Charla; Frankforter, Tami L.; Suarez-Morales, Lourdes; Szapocznik, Jose; Martino, Steve

2010-01-01

This study investigated the extent to which bilingual counselors initiated informal discussions about topics that were unrelated to the treatment of their monolingual Spanish-speaking Hispanic clients in a National Institute on Drug Abuse Clinical Trial Network protocol examining the effectiveness of motivational enhancement therapy (MET). Session audiotapes were independently rated to assess counselor treatment fidelity and the incidence of informal discussions. Eighty-three percent of the 23 counselors participating in the trial initiated informal discussions at least once in one or more of their sessions. Counselors delivering MET in the trial initiated informal discussion significantly less often than the counselors delivering standard treatment. Counselors delivering standard treatment were likely to talk informally the most when they were ethnically non-Latin. Additionally, informal discussion was found to have significant inverse correlations with client motivation to reduce substance use and client retention in treatment. These results suggest that informal discussion may have adverse consequences on Hispanic clients’ motivation for change and substance abuse treatment outcomes and that maintaining a more formal relationship in early treatment sessions may work best with Hispanic clients. Careful counselor training and supervision in MET may suppress the tendency of counselors to talk informally in sessions. PMID:20817381

Individual brain structure and modelling predict seizure propagation.

PubMed

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

2017-03-01

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

Experimental manipulation of avian social structure reveals segregation is carried over across contexts

PubMed Central

Firth, Josh A.; Sheldon, Ben C.

2015-01-01

Our current understanding of animal social networks is largely based on observations or experiments that do not directly manipulate associations between individuals. Consequently, evidence relating to the causal processes underlying such networks is limited. By imposing specified rules controlling individual access to feeding stations, we directly manipulated the foraging social network of a wild bird community, thus demonstrating how external factors can shape social structure. We show that experimentally imposed constraints were carried over into patterns of association at unrestricted, ephemeral food patches, as well as at nesting sites during breeding territory prospecting. Hence, different social contexts can be causally linked, and constraints at one level may have consequences that extend into other aspects of sociality. Finally, the imposed assortment was lost following the cessation of the experimental manipulation, indicating the potential for previously perturbed social networks of wild animals to recover from segregation driven by external constraints. PMID:25652839

Trophic groups and modules: two levels of group detection in food webs

PubMed Central

Gauzens, Benoit; Thébault, Elisa; Lacroix, Gérard; Legendre, Stéphane

2015-01-01

Within food webs, species can be partitioned into groups according to various criteria. Two notions have received particular attention: trophic groups (TGs), which have been used for decades in the ecological literature, and more recently, modules. The relationship between these two group concepts remains unknown in empirical food webs. While recent developments in network theory have led to efficient methods for detecting modules in food webs, the determination of TGs (groups of species that are functionally similar) is largely based on subjective expert knowledge. We develop a novel algorithm for TG detection. We apply this method to empirical food webs and show that aggregation into TGs allows for the simplification of food webs while preserving their information content. Furthermore, we reveal a two-level hierarchical structure where modules partition food webs into large bottom–top trophic pathways, whereas TGs further partition these pathways into groups of species with similar trophic connections. This provides new perspectives for the study of dynamical and functional consequences of food-web structure, bridging topological and dynamical analysis. TGs have a clear ecological meaning and are found to provide a trade-off between network complexity and information loss. PMID:25878127

Managing Errors to Reduce Accidents in High Consequence Networked Information Systems

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

Ganter, J.H.

1999-02-01

Computers have always helped to amplify and propagate errors made by people. The emergence of Networked Information Systems (NISs), which allow people and systems to quickly interact worldwide, has made understanding and minimizing human error more critical. This paper applies concepts from system safety to analyze how hazards (from hackers to power disruptions) penetrate NIS defenses (e.g., firewalls and operating systems) to cause accidents. Such events usually result from both active, easily identified failures and more subtle latent conditions that have resided in the system for long periods. Both active failures and latent conditions result from human errors. We classifymore » these into several types (slips, lapses, mistakes, etc.) and provide NIS examples of how they occur. Next we examine error minimization throughout the NIS lifecycle, from design through operation to reengineering. At each stage, steps can be taken to minimize the occurrence and effects of human errors. These include defensive design philosophies, architectural patterns to guide developers, and collaborative design that incorporates operational experiences and surprises into design efforts. We conclude by looking at three aspects of NISs that will cause continuing challenges in error and accident management: immaturity of the industry, limited risk perception, and resource tradeoffs.« less

40 CFR 1400.2 - Definitions.

Code of Federal Regulations, 2012 CFR

2012-07-01

... OFF-SITE CONSEQUENCE ANALYSIS INFORMATION DISTRIBUTION OF OFF-SITE CONSEQUENCE ANALYSIS INFORMATION... analysis (OCA) information means sections 2 through 5 of a risk management plan (consisting of an... consequence analysis (OCA) data elements means the results of the off-site consequence analysis conducted by a...

40 CFR 1400.2 - Definitions.

Code of Federal Regulations, 2011 CFR

2011-07-01

... OFF-SITE CONSEQUENCE ANALYSIS INFORMATION DISTRIBUTION OF OFF-SITE CONSEQUENCE ANALYSIS INFORMATION... analysis (OCA) information means sections 2 through 5 of a risk management plan (consisting of an... consequence analysis (OCA) data elements means the results of the off-site consequence analysis conducted by a...

40 CFR 1400.2 - Definitions.

Code of Federal Regulations, 2013 CFR

2013-07-01

... OFF-SITE CONSEQUENCE ANALYSIS INFORMATION DISTRIBUTION OF OFF-SITE CONSEQUENCE ANALYSIS INFORMATION... analysis (OCA) information means sections 2 through 5 of a risk management plan (consisting of an... consequence analysis (OCA) data elements means the results of the off-site consequence analysis conducted by a...

40 CFR 1400.2 - Definitions.

Code of Federal Regulations, 2014 CFR

2014-07-01

... OFF-SITE CONSEQUENCE ANALYSIS INFORMATION DISTRIBUTION OF OFF-SITE CONSEQUENCE ANALYSIS INFORMATION... analysis (OCA) information means sections 2 through 5 of a risk management plan (consisting of an... consequence analysis (OCA) data elements means the results of the off-site consequence analysis conducted by a...

ADVANCED SURVEILLANCE OF ENVIROMENTAL RADIATION IN AUTOMATIC NETWORKS.

PubMed

Benito, G; Sáez, J C; Blázquez, J B; Quiñones, J

2018-06-01

The objective of this study is the verification of the operation of a radiation monitoring network conformed by several sensors. The malfunction of a surveillance network has security and economic consequences, which derive from its maintenance and could be avoided with an early detection. The proposed method is based on a kind of multivariate distance, and the verification for the methodology has been tested at CIEMAT's local radiological early warning network.

Exploring the future with anticipatory networks

NASA Astrophysics Data System (ADS)

Skulimowski, A. M. J.

2013-01-01

This paper presents a theory of anticipatory networks that originates from anticipatory models of consequences in multicriteria decision problems. When making a decision, the decision maker takes into account the anticipated outcomes of each future decision problem linked by the causal relations with the present one. In a network of linked decision problems, the causal relations are defined between time-ordered nodes. The scenarios of future consequences of each decision are modeled by multiple vertices starting from an appropriate node. The network is supplemented by one or more relations of anticipation, or future feedback, which describe a situation where decision makers take into account the anticipated results of some future optimization problems while making their choice. So arises a multigraph of decision problems linked causally and by one or more anticipation relation, termed here the anticipatory network. We will present the properties of anticipatory networks and propose a method of reducing, transforming and using them to solve current decision problems. Furthermore, it will be shown that most anticipatory networks can be regarded as superanticipatory systems, i.e. systems that are anticipatory in the Rosen sense and contain a future model of at least one other anticipatory system. The anticipatory networks can also be applied to filter the set of future scenarios in a foresight exercise.

Revealing the hidden networks of interaction in mobile animal groups allows prediction of complex behavioral contagion.

PubMed

Rosenthal, Sara Brin; Twomey, Colin R; Hartnett, Andrew T; Wu, Hai Shan; Couzin, Iain D

2015-04-14

Coordination among social animals requires rapid and efficient transfer of information among individuals, which may depend crucially on the underlying structure of the communication network. Establishing the decision-making circuits and networks that give rise to individual behavior has been a central goal of neuroscience. However, the analogous problem of determining the structure of the communication network among organisms that gives rise to coordinated collective behavior, such as is exhibited by schooling fish and flocking birds, has remained almost entirely neglected. Here, we study collective evasion maneuvers, manifested through rapid waves, or cascades, of behavioral change (a ubiquitous behavior among taxa) in schooling fish (Notemigonus crysoleucas). We automatically track the positions and body postures, calculate visual fields of all individuals in schools of ∼150 fish, and determine the functional mapping between socially generated sensory input and motor response during collective evasion. We find that individuals use simple, robust measures to assess behavioral changes in neighbors, and that the resulting networks by which behavior propagates throughout groups are complex, being weighted, directed, and heterogeneous. By studying these interaction networks, we reveal the (complex, fractional) nature of social contagion and establish that individuals with relatively few, but strongly connected, neighbors are both most socially influential and most susceptible to social influence. Furthermore, we demonstrate that we can predict complex cascades of behavioral change at their moment of initiation, before they actually occur. Consequently, despite the intrinsic stochasticity of individual behavior, establishing the hidden communication networks in large self-organized groups facilitates a quantitative understanding of behavioral contagion.

Revealing the hidden networks of interaction in mobile animal groups allows prediction of complex behavioral contagion

PubMed Central

Rosenthal, Sara Brin; Twomey, Colin R.; Hartnett, Andrew T.; Wu, Hai Shan; Couzin, Iain D.

2015-01-01

Coordination among social animals requires rapid and efficient transfer of information among individuals, which may depend crucially on the underlying structure of the communication network. Establishing the decision-making circuits and networks that give rise to individual behavior has been a central goal of neuroscience. However, the analogous problem of determining the structure of the communication network among organisms that gives rise to coordinated collective behavior, such as is exhibited by schooling fish and flocking birds, has remained almost entirely neglected. Here, we study collective evasion maneuvers, manifested through rapid waves, or cascades, of behavioral change (a ubiquitous behavior among taxa) in schooling fish (Notemigonus crysoleucas). We automatically track the positions and body postures, calculate visual fields of all individuals in schools of ∼150 fish, and determine the functional mapping between socially generated sensory input and motor response during collective evasion. We find that individuals use simple, robust measures to assess behavioral changes in neighbors, and that the resulting networks by which behavior propagates throughout groups are complex, being weighted, directed, and heterogeneous. By studying these interaction networks, we reveal the (complex, fractional) nature of social contagion and establish that individuals with relatively few, but strongly connected, neighbors are both most socially influential and most susceptible to social influence. Furthermore, we demonstrate that we can predict complex cascades of behavioral change at their moment of initiation, before they actually occur. Consequently, despite the intrinsic stochasticity of individual behavior, establishing the hidden communication networks in large self-organized groups facilitates a quantitative understanding of behavioral contagion. PMID:25825752

Formulation and Optimization of Robust Sensor Placement Problems for Drinking Water Contamination Warning Systems

DOE PAGES

Watson, Jean-Paul; Murray, Regan; Hart, William E.

2009-11-13

We report that the sensor placement problem in contamination warning system design for municipal water distribution networks involves maximizing the protection level afforded by limited numbers of sensors, typically quantified as the expected impact of a contamination event; the issue of how to mitigate against high-consequence events is either handled implicitly or ignored entirely. Consequently, expected-case sensor placements run the risk of failing to protect against high-consequence 9/11-style attacks. In contrast, robust sensor placements address this concern by focusing strictly on high-consequence events and placing sensors to minimize the impact of these events. We introduce several robust variations of themore » sensor placement problem, distinguished by how they quantify the potential damage due to high-consequence events. We explore the nature of robust versus expected-case sensor placements on three real-world large-scale distribution networks. We find that robust sensor placements can yield large reductions in the number and magnitude of high-consequence events, with only modest increases in expected impact. Finally, the ability to trade-off between robust and expected-case impacts is a key unexplored dimension in contamination warning system design.« less

The Widening Gulf between Genomics Data Generation and Consumption: A Practical Guide to Big Data Transfer Technology

PubMed Central

Feltus, Frank A.; Breen, Joseph R.; Deng, Juan; Izard, Ryan S.; Konger, Christopher A.; Ligon, Walter B.; Preuss, Don; Wang, Kuang-Ching

2015-01-01

In the last decade, high-throughput DNA sequencing has become a disruptive technology and pushed the life sciences into a distributed ecosystem of sequence data producers and consumers. Given the power of genomics and declining sequencing costs, biology is an emerging “Big Data” discipline that will soon enter the exabyte data range when all subdisciplines are combined. These datasets must be transferred across commercial and research networks in creative ways since sending data without thought can have serious consequences on data processing time frames. Thus, it is imperative that biologists, bioinformaticians, and information technology engineers recalibrate data processing paradigms to fit this emerging reality. This review attempts to provide a snapshot of Big Data transfer across networks, which is often overlooked by many biologists. Specifically, we discuss four key areas: 1) data transfer networks, protocols, and applications; 2) data transfer security including encryption, access, firewalls, and the Science DMZ; 3) data flow control with software-defined networking; and 4) data storage, staging, archiving and access. A primary intention of this article is to orient the biologist in key aspects of the data transfer process in order to frame their genomics-oriented needs to enterprise IT professionals. PMID:26568680

Patient centredness in integrated care: results of a qualitative study based on a systems theoretical framework

PubMed Central

Lüdecke, Daniel

2014-01-01

Introduction Health care providers seek to improve patient-centred care. Due to fragmentation of services, this can only be achieved by establishing integrated care partnerships. The challenge is both to control costs while enhancing the quality of care and to coordinate this process in a setting with many organisations involved. The problem is to establish control mechanisms, which ensure sufficiently consideration of patient centredness. Theory and methods Seventeen qualitative interviews have been conducted in hospitals of metropolitan areas in northern Germany. The documentary method, embedded into a systems theoretical framework, was used to describe and analyse the data and to provide an insight into the specific perception of organisational behaviour in integrated care. Results The findings suggest that integrated care partnerships rely on networks based on professional autonomy in the context of reliability. The relationships of network partners are heavily based on informality. This correlates with a systems theoretical conception of organisations, which are assumed autonomous in their decision-making. Conclusion and discussion Networks based on formal contracts may restrict professional autonomy and competition. Contractual bindings that suppress the competitive environment have negative consequences for patient-centred care. Drawbacks remain due to missing self-regulation of the network. To conclude, less regimentation of integrated care partnerships is recommended. PMID:25411573

Patient centredness in integrated care: results of a qualitative study based on a systems theoretical framework.

PubMed

Lüdecke, Daniel

2014-10-01

Health care providers seek to improve patient-centred care. Due to fragmentation of services, this can only be achieved by establishing integrated care partnerships. The challenge is both to control costs while enhancing the quality of care and to coordinate this process in a setting with many organisations involved. The problem is to establish control mechanisms, which ensure sufficiently consideration of patient centredness. Seventeen qualitative interviews have been conducted in hospitals of metropolitan areas in northern Germany. The documentary method, embedded into a systems theoretical framework, was used to describe and analyse the data and to provide an insight into the specific perception of organisational behaviour in integrated care. The findings suggest that integrated care partnerships rely on networks based on professional autonomy in the context of reliability. The relationships of network partners are heavily based on informality. This correlates with a systems theoretical conception of organisations, which are assumed autonomous in their decision-making. Networks based on formal contracts may restrict professional autonomy and competition. Contractual bindings that suppress the competitive environment have negative consequences for patient-centred care. Drawbacks remain due to missing self-regulation of the network. To conclude, less regimentation of integrated care partnerships is recommended.

Soil geohazard mapping for improved asset management of UK local roads

NASA Astrophysics Data System (ADS)

Pritchard, O. G.; Hallett, S. H.; Farewell, T. S.

2015-09-01

Unclassified roads comprise 60 % of the road network in the United Kingdom (UK). The resilience of this locally important network is declining. It is considered by the Institution of Civil Engineers to be "at risk" and is ranked 26th in the world. Many factors contribute to the degradation and ultimate failure of particular road sections. However, several UK local authorities have identified that in drought conditions, road sections founded upon shrink-swell susceptible clay soils undergo significant deterioration compared with sections on non-susceptible soils. This arises from the local road network having little, if any, structural foundations. Consequently, droughts in East Anglia have resulted in millions of pounds of damage, leading authorities to seek emergency governmental funding. This paper assesses the use of soil-related geohazard assessments in providing soil-informed maintenance strategies for the asset management of the locally important road network of the UK. A case study draws upon the UK administrative county of Lincolnshire, where road assessment data have been analysed against mapped clay-subsidence risk. This reveals a statistically significant relationship between road condition and susceptible clay soils. Furthermore, incorporation of UKCP09 future climate projections within the geohazard models has highlighted roads likely to be at future risk of clay-related subsidence.

Soil geohazard mapping for improved asset management of UK local roads

NASA Astrophysics Data System (ADS)

Pritchard, O. G.; Hallett, S. H.; Farewell, T. S.

2015-05-01

Unclassified roads comprise 60% of the road network in the United Kingdom (UK). The resilience of this locally important network is declining. It is considered by the Institution of Civil Engineers to be "at risk" and is ranked 26th in the world. Many factors contribute to the degradation and ultimate failure of particular road sections. However, several UK local authorities have identified that in drought conditions, road sections founded upon shrink/swell susceptible clay soils undergo significant deterioration compared with sections on non-susceptible soils. This arises from the local road network having little, if any structural foundations. Consequently, droughts in East Anglia have resulted in millions of pounds of damage, leading authorities to seek emergency governmental funding. This paper assesses the use of soil-related geohazard assessments in providing soil-informed maintenance strategies for the asset management of the locally important road network of the UK. A case study draws upon the UK administrative county of Lincolnshire, where road assessment data have been analysed against mapped clay-subsidence risk. This reveals a statistically significant relationship between road condition and susceptible clay soils. Furthermore, incorporation of UKCP09 future climate projections within the geohazard models has highlighted roads likely to be at future risk of clay-related subsidence.

Battle of Narratives

DTIC Science & Technology

2012-06-01

18 De Nooy, Wouter, Andrej Mrvar , and Vladimir Batagelj , Exploratory Social Network Analysis with Pajek (New York: Cambridge University Press, 2005... Mrvar , and Vladimir Batagelj . Exploratory Social Network Analysis with Pajek. New York: Cambridge University Press, 2005. Democratic National...Review 54(1):33-48; Brian Uzzi. 1996 . "The Sources and Consequences of Embeddedness for the Economic Performance of Organizations: The Network Effect

Function of local networks in palliative care: a Dutch view.

PubMed

Nikbakht-Van de Sande, C V M Vahedi; van der Rijt, C C D; Visser, A Ph; ten Voorde, M A; Pruyn, J F A

2005-08-01

Although network formation is considered an effective method of stimulating the integrated delivery of palliative care, scientific evidence on the usefulness of network formation is scarce. In 1998 the Ministry of Health of The Netherlands started a 5-year stimulation program on palliative care by founding and funding six regional Centres for the Development of Palliative Care. These centers were structured around pivotal organizations such as university hospitals and comprehensive cancer centers. As part of the stimulation program a locoregional network model was introduced within each center for the Development of Palliative Care to integrate palliative care services in the Dutch health care system. We performed a study on network formation in the southwestern area of The Netherlands with 2.4 million inhabitants. The study aimed to answer the following questions: (1) how do networks in palliative care develop, which care providers participate and how do they function? (2) which are the achievements of the palliative care networks as perceived by their participants? (3) which are the success factors of the palliative care networks according to their participants and which factors predict the achievements? Between September 2000 and January 2004 eight local palliative care networks in the region of the Center for Development of Palliative Care-Rotterdam (southwestern area of The Netherlands) were closely followed to gain information on their characteristics and developmental course. At the start of the study semistructured interviews were held with the coordinators of the eight networks. The information from these interviews and from the network documents were used to constitute a questionnaire to assess the opinions and experiences of the network participants. According to the vast majority of responders, the most important reason to install the networks was the lack of integration between the existing local health care services. The networks were initiated to stimulate mutual collaboration, improve accessibility to health care services and increase the quality of these services. The most important achievements obtained by the palliative care networks were: increase in personal contacts between colleagues in a region, improved engagement and collaboration between participating organizations, enhanced insight in the health care provisions, joined initiatives for the development of new care products, and organization of patient-tailored care. Important success factors for the networks were deemed: fruitful mutual contacts, regular funding and the collective development of care products. By logistic regression analyses, the collective development of new care products and the organization of case discussions between caregivers from different health care services turned out to be the most important predictors for success of the palliative care networks. Projects that stimulate the communication between professionals appear to improve the mutual collaboration between individual participants and between the participating organizations, which consequently enhances the quality of palliative care.

Decorrelation of Neural-Network Activity by Inhibitory Feedback

PubMed Central

Einevoll, Gaute T.; Diesmann, Markus

2012-01-01

Correlations in spike-train ensembles can seriously impair the encoding of information by their spatio-temporal structure. An inevitable source of correlation in finite neural networks is common presynaptic input to pairs of neurons. Recent studies demonstrate that spike correlations in recurrent neural networks are considerably smaller than expected based on the amount of shared presynaptic input. Here, we explain this observation by means of a linear network model and simulations of networks of leaky integrate-and-fire neurons. We show that inhibitory feedback efficiently suppresses pairwise correlations and, hence, population-rate fluctuations, thereby assigning inhibitory neurons the new role of active decorrelation. We quantify this decorrelation by comparing the responses of the intact recurrent network (feedback system) and systems where the statistics of the feedback channel is perturbed (feedforward system). Manipulations of the feedback statistics can lead to a significant increase in the power and coherence of the population response. In particular, neglecting correlations within the ensemble of feedback channels or between the external stimulus and the feedback amplifies population-rate fluctuations by orders of magnitude. The fluctuation suppression in homogeneous inhibitory networks is explained by a negative feedback loop in the one-dimensional dynamics of the compound activity. Similarly, a change of coordinates exposes an effective negative feedback loop in the compound dynamics of stable excitatory-inhibitory networks. The suppression of input correlations in finite networks is explained by the population averaged correlations in the linear network model: In purely inhibitory networks, shared-input correlations are canceled by negative spike-train correlations. In excitatory-inhibitory networks, spike-train correlations are typically positive. Here, the suppression of input correlations is not a result of the mere existence of correlations between excitatory (E) and inhibitory (I) neurons, but a consequence of a particular structure of correlations among the three possible pairings (EE, EI, II). PMID:23133368

Considering Information Up-to-Dateness to Increase the Accuracy of Therapy Decision Support Systems.

PubMed

Gaebel, Jan; Cypko, Mario A; Oeltze-Jafra, Steffen

2017-01-01

During the diagnostic process a lot of information is generated. All this information is assessed when making a final diagnosis and planning the therapy. While some patient information is stable, e.g., gender, others may become outdated, e.g., tumor size derived from CT data. Quantifying this information up-to-dateness and deriving consequences are difficult. Especially for the implementation in clinical decision support systems, this has not been studied. When information entities tend to become outdated, in practice, clinicians intuitively reduce their impact when making decisions. Therefore, in a system's calculations their impact should be reduced as well. We propose a method of decreasing the certainty of information entities based on their up-to-dateness. The method is tested in a decision support system for TNM staging based on Bayesian networks. We compared the actual N-state in records of 39 patients to the N-state calculated with and without decreasing data certainty. The results under decreased certainty correlated better with the actual states (r=0.958, p=0.008). We conclude that the up-to-dateness must be considered when processing clinical information to enhance decision making and ensure more patient safety.

Integrative Analysis of Genetic, Genomic, and Phenotypic Data for Ethanol Behaviors: A Network-Based Pipeline for Identifying Mechanisms and Potential Drug Targets.

PubMed

Bogenpohl, James W; Mignogna, Kristin M; Smith, Maren L; Miles, Michael F

2017-01-01

Complex behavioral traits, such as alcohol abuse, are caused by an interplay of genetic and environmental factors, producing deleterious functional adaptations in the central nervous system. The long-term behavioral consequences of such changes are of substantial cost to both the individual and society. Substantial progress has been made in the last two decades in understanding elements of brain mechanisms underlying responses to ethanol in animal models and risk factors for alcohol use disorder (AUD) in humans. However, treatments for AUD remain largely ineffective and few medications for this disease state have been licensed. Genome-wide genetic polymorphism analysis (GWAS) in humans, behavioral genetic studies in animal models and brain gene expression studies produced by microarrays or RNA-seq have the potential to produce nonbiased and novel insight into the underlying neurobiology of AUD. However, the complexity of such information, both statistical and informational, has slowed progress toward identifying new targets for intervention in AUD. This chapter describes one approach for integrating behavioral, genetic, and genomic information across animal model and human studies. The goal of this approach is to identify networks of genes functioning in the brain that are most relevant to the underlying mechanisms of a complex disease such as AUD. We illustrate an example of how genomic studies in animal models can be used to produce robust gene networks that have functional implications, and to integrate such animal model genomic data with human genetic studies such as GWAS for AUD. We describe several useful analysis tools for such studies: ComBAT, WGCNA, and EW_dmGWAS. The end result of this analysis is a ranking of gene networks and identification of their cognate hub genes, which might provide eventual targets for future therapeutic development. Furthermore, this combined approach may also improve our understanding of basic mechanisms underlying gene x environmental interactions affecting brain functioning in health and disease.

INTEGRATIVE ANALYSIS OF GENETIC, GENOMIC AND PHENOTYPIC DATA FOR ETHANOL BEHAVIORS: A NETWORK-BASED PIPELINE FOR IDENTIFYING MECHANISMS AND POTENTIAL DRUG TARGETS

PubMed Central

Bogenpohl, James W.; Mignogna, Kristin M.; Smith, Maren L.; Miles, Michael F.

2016-01-01

Complex behavioral traits, such as alcohol abuse, are caused by an interplay of genetic and environmental factors, producing deleterious functional adaptations in the central nervous system. The long-term behavioral consequences of such changes are of substantial cost to both the individual and society. Substantial progress has been made in the last two decades in understanding elements of brain mechanisms underlying responses to ethanol in animal models and risk factors for alcohol use disorder (AUD) in humans. However, treatments for AUD remain largely ineffective and few medications for this disease state have been licensed. Genome-wide genetic polymorphism analysis (GWAS) in humans, behavioral genetic studies in animal models and brain gene expression studies produced by microarrays or RNA-seq have the potential to produce non-biased and novel insight into the underlying neurobiology of AUD. However, the complexity of such information, both statistical and informational, has slowed progress toward identifying new targets for intervention in AUD. This chapter describes one approach for integrating behavioral, genetic, and genomic information across animal model and human studies. The goal of this approach is to identify networks of genes functioning in the brain that are most relevant to the underlying mechanisms of a complex disease such as AUD. We illustrate an example of how genomic studies in animal models can be used to produce robust gene networks that have functional implications, and to integrate such animal model genomic data with human genetic studies such as GWAS for AUD. We describe several useful analysis tools for such studies: ComBAT, WGCNA and EW_dmGWAS. The end result of this analysis is a ranking of gene networks and identification of their cognate hub genes, which might provide eventual targets for future therapeutic development. Furthermore, this combined approach may also improve our understanding of basic mechanisms underlying gene x environmental interactions affecting brain functioning in health and disease. PMID:27933543

The physics of complex systems in information and biology

NASA Astrophysics Data System (ADS)

Walker, Dylan

Citation networks have re-emerged as a topic intense interest in the complex networks community with the recent availability of large-scale data sets. The ranking of citation networks is a necessary practice as a means to improve information navigability and search. Unlike many information networks, the aging characteristics of citation networks require the development of new ranking methods. To account for strong aging characteristics of citation networks, we modify the PageRank algorithm by initially distributing random surfers exponentially with age, in favor of more recent publications. The output of this algorithm, which we call CiteRank, is interpreted as approximate traffic to individual publications in a simple model of how researchers find new information. We optimize parameters of our algorithm to achieve the best performance. The results are compared for two rather different citation networks: all American Physical Society publications between 1893-2003 and the set of high-energy physics theory (hep-th) preprints. Despite major differences between these two networks, we find that their optimal parameters for the CiteRank algorithm are remarkably similar. The advantages and performance of CiteRank over more conventional methods of ranking publications are discussed. Collaborative voting systems have emerged as an abundant form of real-world, complex information systems that exist in a variety of online applications. These systems are comprised of large populations of users that collectively submit and vote on objects. While the specific properties of these systems vary widely, many of them share a core set of features and dynamical behaviors that govern their evolution. We study a subset of these systems that involve material of a time-critical nature as in the popular example of news items. We consider a general model system in which articles are introduced, voted on by a population of users, and subsequently expire after a proscribed period of time. To study the interaction between popularity and quality, we introduce simple stochastic models of user behavior that approximate differing user quality and susceptibility to the common notion of popularity. We define a metric to quantify user reputation in a manner that is self-consistent, adaptable and content-blind and shows good correlation with the probability that a user behaves in an optimal fashion. We further construct a mechanism for ranking documents that take into account user reputation and provides substantial improvement in the time-critical performance of the system. The structure of complex systems have been well studied in the context of both information and biological systems. More recently, dynamics in complex systems that occur over the background of the underlying network has received a great deal of attention. In particular, the study of fluctuations in complex systems has emerged as an issue central to understanding dynamical behavior. We approach the problem of collective effects of the underlying network on dynamical fluctuations by considering the protein-protein interaction networks for the system of the living cell. We consider two types of fluctuations in the mass-action equilibrium in protein binding networks. The first type is driven by relatively slow changes in total concentrations (copy numbers) of interacting proteins. The second type, to which we refer to as spontaneous, is caused by quickly decaying thermodynamic deviations away from the mass-action equilibrium of the system. As such they are amenable to methods of equilibrium statistical mechanics used in our study. We investigate the effects of network connectivity on these fluctuations by comparing them to different scenarios in which the interacting pair is isolated form the rest of the network. Such comparison allows us to analytically derive upper and lower bounds on network fluctuations. The collective effects are shown to sometimes lead to relatively large amplification of spontaneous fluctuations as compared to the expectation for isolated dimers. As a consequence of this, the strength of both types of fluctuations is positively correlated with the overall network connectivity of proteins forming the complex. On the other hand, the relative amplitude of fluctuations is negatively correlated with the equilibrium concentration of the complex. Our general findings are illustrated using a curated network of protein-protein interactions and multi-protein complexes in bakers yeast with experimentally determined protein concentrations.

The Persistence of Experience: Prior Attentional and Emotional State Affects Network Functioning in a Target Detection Task.

PubMed

Stern, Emily R; Muratore, Alexandra F; Taylor, Stephan F; Abelson, James L; Hof, Patrick R; Goodman, Wayne K

2015-09-01

Efficient, adaptive behavior relies on the ability to flexibly move between internally focused (IF) and externally focused (EF) attentional states. Despite evidence that IF cognitive processes such as event imagination comprise a significant amount of awake cognition, the consequences of internal absorption on the subsequent recruitment of brain networks during EF tasks are unknown. The present functional magnetic resonance imaging (fMRI) study employed a novel attentional state switching task. Subjects imagined positive and negative events (IF task) or performed a working memory task (EF task) before switching to a target detection (TD) task also requiring attention to external information, allowing for the investigation of neural functioning during external attention based on prior attentional state. There was a robust increase of activity in frontal, parietal, and temporal regions during TD when subjects were previously performing the EF compared with IF task, an effect that was most pronounced following negative IF. Additionally, dorsolateral prefrontal cortex was less negatively coupled with ventromedial prefrontal and posterior cingulate cortices during TD following IF compared with EF. These findings reveal the striking consequences for brain activity following immersion in an IF attentional state, which have strong implications for psychiatric disorders characterized by excessive internal focus. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Automated Wildfire Detection Through Artificial Neural Networks

NASA Technical Reports Server (NTRS)

Miller, Jerry; Borne, Kirk; Thomas, Brian; Huang, Zhenping; Chi, Yuechen

2005-01-01

Wildfires have a profound impact upon the biosphere and our society in general. They cause loss of life, destruction of personal property and natural resources and alter the chemistry of the atmosphere. In response to the concern over the consequences of wildland fire and to support the fire management community, the National Oceanic and Atmospheric Administration (NOAA), National Environmental Satellite, Data and Information Service (NESDIS) located in Camp Springs, Maryland gradually developed an operational system to routinely monitor wildland fire by satellite observations. The Hazard Mapping System, as it is known today, allows a team of trained fire analysts to examine and integrate, on a daily basis, remote sensing data from Geostationary Operational Environmental Satellite (GOES), Advanced Very High Resolution Radiometer (AVHRR) and Moderate Resolution Imaging Spectroradiometer (MODIS) satellite sensors and generate a 24 hour fire product for the conterminous United States. Although assisted by automated fire detection algorithms, N O M has not been able to eliminate the human element from their fire detection procedures. As a consequence, the manually intensive effort has prevented NOAA from transitioning to a global fire product as urged particularly by climate modelers. NASA at Goddard Space Flight Center in Greenbelt, Maryland is helping N O M more fully automate the Hazard Mapping System by training neural networks to mimic the decision-making process of the frre analyst team as well as the automated algorithms.

Public Health and the Anticorporate Movement: Rationale and Recommendations

PubMed Central

Wiist, William H.

2006-01-01

Institutions and informal networks have formed a movement that is challenging the growing power and pervasive influence of large corporations. The movement’s analyses show that the historical development and current function of the corporate entity requires production of a profit regardless of consequences to health, society, or the environment. As a result, public health professionals frequently address health problems related to products, services, or practices of corporations. There are possibilities for links between public health and the anticorporate movement. Public health research and the professional preparation curriculum should focus on the corporate entity as a social structural determinant of disease. PMID:16809584

Information Exchange Between Resilient and High-Threat Networks: Techniques for Threat Mitigation

DTIC Science & Technology

2004-11-01

Information Exchange between Resilient and High-Threat Networks : Techniques for Threat Mitigation Tim Dean and Graham Wyatt QinetiQ...SUMMARY High resilience military networks frequently have requirements for exchange of information with networks of low assurance, including networks of...assured, two-way, information flow between high resilience networks and other networks of unknown threat. The techniques include conventional and

Patients with alcohol use disorder: initial results from a prospective multicenter registry in the Spanish Network on Addiction Disorders. CohRTA Study.

PubMed

Sanvisens, Arantza; Zuluaga, Paola; Rivas, Inmaculada; Rubio, Gabriel; Gual, Antoni; Torrens, Marta; Short, Antoni; Álvarez, Francisco Javier; Tor, Jordi; Farré, Magí; Rodríguez de Fonseca, Fernando; Muga, Roberto

2017-07-14

The Alcohol Program of the Spanish Network on Addictive Disorders-RTA requires a longitudinal study to address different research questions related to alcoholism. The cohort study (CohRTA) focuses on patients seeking treatment for alcohol use disorder, as a multicentre, collaborative research project aimed to improve secondary prevention and early diagnosis of pathological processes associated with the disorder. multicentre cohort study in adults (>18 years) seeking their first treatment of the disorder. Patients sign an informed consent and data is collected in an online platform specifically designed for the study; patients are also requested to provide biological samples that are stored in a biobank. Baseline and prospective, socio-demographic, epidemiological, clinical and treatment data are collected. Currently there are 10 participating centres that expect to recruit more than 1,000 patients. As of December 2015, 344 patients (77% men) were included. Median age at admission was 50 years (IQR: 43-55 years). Median age at the start of alcohol consumption was 15 years (IQR: 14-18 years) and 61% of cases reported antecedents of alcohol use disorder in the family. During the 30 days prior to admission, alcohol consumption amounted to 12.5 SDU/day (IQR: 7.1-20 SDU/day), 72% of the patients were tobacco smokers and 30% currently used cocaine. Organising an open cohort of patients with alcohol use disorder may be crucial to better understand the clinical consequences of alcoholism in Spain. This cohort may potentiate quantitative and qualitative research within the Spanish Network on Addictive Disorders-RTA/RETICS. Having a well-established, representative cohort of patients will increase translational research on consequences of alcoholism in our country.

40 CFR 1400.7 - In general.

Code of Federal Regulations, 2013 CFR

2013-07-01

... OFF-SITE CONSEQUENCE ANALYSIS INFORMATION DISTRIBUTION OF OFF-SITE CONSEQUENCE ANALYSIS INFORMATION Access to Off-Site Consequence Analysis Information by Government Officials. § 1400.7 In general. The Administrator shall provide OCA information to government officials as provided in this subpart. Any OCA...

40 CFR 1400.7 - In general.

Code of Federal Regulations, 2011 CFR

2011-07-01

... OFF-SITE CONSEQUENCE ANALYSIS INFORMATION DISTRIBUTION OF OFF-SITE CONSEQUENCE ANALYSIS INFORMATION Access to Off-Site Consequence Analysis Information by Government Officials. § 1400.7 In general. The Administrator shall provide OCA information to government officials as provided in this subpart. Any OCA...

40 CFR 1400.7 - In general.

Code of Federal Regulations, 2012 CFR

2012-07-01

... OFF-SITE CONSEQUENCE ANALYSIS INFORMATION DISTRIBUTION OF OFF-SITE CONSEQUENCE ANALYSIS INFORMATION Access to Off-Site Consequence Analysis Information by Government Officials. § 1400.7 In general. The Administrator shall provide OCA information to government officials as provided in this subpart. Any OCA...

40 CFR 1400.7 - In general.

Code of Federal Regulations, 2014 CFR

2014-07-01

... OFF-SITE CONSEQUENCE ANALYSIS INFORMATION DISTRIBUTION OF OFF-SITE CONSEQUENCE ANALYSIS INFORMATION Access to Off-Site Consequence Analysis Information by Government Officials. § 1400.7 In general. The Administrator shall provide OCA information to government officials as provided in this subpart. Any OCA...

Convergence

NASA Astrophysics Data System (ADS)

Darcie, Thomas E.; Doverspike, Robert; Zirngibl, Martin; Korotky, Steven K.

2005-08-01

Call for Papers: Convergence The Journal of Optical Networking (JON) invites submissions to a special issue on Convergence. Convergence has become a popular theme in telecommunications, one that has broad implications across all segments of the industry. Continual evolution of technology and applications continues to erase lines between traditionally separate lines of business, with dramatic consequences for vendors, service providers, and consumers. Spectacular advances in all layers of optical networking-leading to abundant, dynamic, cost-effective, and reliable wide-area and local-area connections-have been essential drivers of this evolution. As services and networks continue to evolve towards some notion of convergence, the continued role of optical networks must be explored. One vision of convergence renders all information in a common packet (especially IP) format. This vision is driven by the proliferation of data services. For example, time-division multiplexed (TDM) voice becomes VoIP. Analog cable-television signals become MPEG bits streamed to digital set-top boxes. T1 or OC-N private lines migrate to Ethernet virtual private networks (VPNs). All these packets coexist peacefully within a single packet-routing methodology built on an optical transport layer that combines the flexibility and cost of data networks with telecom-grade reliability. While this vision is appealing in its simplicity and shared widely, specifics of implementation raise many challenges and differences of opinion. For example, many seek to expand the role of Ethernet in these transport networks, while massive efforts are underway to make traditional TDM networks more data friendly within an evolved but backward-compatible SDH/SONET (synchronous digital hierarchy and synchronous optical network) multiplexing hierarchy. From this common underlying theme follow many specific instantiations. Examples include the convergence at the physical, logical, and operational levels of voice and data, video and data, private-line and virtual private-line, fixed and mobile, and local and long-haul services. These trends have many consequences for consumers, vendors, and carriers. Faced with large volumes of low-margin data traffic mixed with traditional voice services, the need for capital conservation and operational efficiency drives carriers away from today's separate overlay networks for each service and towards "converged" platforms. For example, cable operators require transport of multiple services over both hybrid fiber coax (HFC) and DWDM transport technologies. Local carriers seek an economical architecture to deliver integrated services on optically enabled broadband-access networks. Services over wireless-access networks must coexist with those from wired networks. In each case, convergence of networks and services inspires an important set of questions and challenges, driven by the need for low cost, operational efficiency, service performance requirements, and optical transport technology options. This Feature Issue explores the various interpretations and implications of network convergence pertinent to optical networking. How does convergence affect the evolution of optical transport-layer and control approaches? Are the implied directions consistent with research vision for optical networks? Substantial challenges remain. Papers are solicited across the broad spectrum of interests. These include, but are not limited to: Architecture, design and performance of optical wide-area-network (WAN), metro, and access networks Integration strategies for multiservice transport platforms Access methods that bridge traditional and emerging services Network signaling and control methodologies All-optical packet routing and switching techniques

Convergence

NASA Astrophysics Data System (ADS)

Darcie, Thomas E.; Doverspike, Robert; Zirngibl, Martin; Korotky, Steven K.

2005-06-01

Call for Papers: Convergence The Journal of Optical Networking (JON) invites submissions to a special issue on Convergence. Convergence has become a popular theme in telecommunications, one that has broad implications across all segments of the industry. Continual evolution of technology and applications continues to erase lines between traditionally separate lines of business, with dramatic consequences for vendors, service providers, and consumers. Spectacular advances in all layers of optical networking-leading to abundant, dynamic, cost-effective, and reliable wide-area and local-area connections-have been essential drivers of this evolution. As services and networks continue to evolve towards some notion of convergence, the continued role of optical networks must be explored. One vision of convergence renders all information in a common packet (especially IP) format. This vision is driven by the proliferation of data services. For example, time-division multiplexed (TDM) voice becomes VoIP. Analog cable-television signals become MPEG bits streamed to digital set-top boxes. T1 or OC-N private lines migrate to Ethernet virtual private networks (VPNs). All these packets coexist peacefully within a single packet-routing methodology built on an optical transport layer that combines the flexibility and cost of data networks with telecom-grade reliability. While this vision is appealing in its simplicity and shared widely, specifics of implementation raise many challenges and differences of opinion. For example, many seek to expand the role of Ethernet in these transport networks, while massive efforts are underway to make traditional TDM networks more data friendly within an evolved but backward-compatible SDH/SONET (synchronous digital hierarchy and synchronous optical network) multiplexing hierarchy. From this common underlying theme follow many specific instantiations. Examples include the convergence at the physical, logical, and operational levels of voice and data, video and data, private-line and virtual private-line, fixed and mobile, and local and long-haul services. These trends have many consequences for consumers, vendors, and carriers. Faced with large volumes of low-margin data traffic mixed with traditional voice services, the need for capital conservation and operational efficiency drives carriers away from today's separate overlay networks for each service and towards "converged" platforms. For example, cable operators require transport of multiple services over both hybrid fiber coax (HFC) and DWDM transport technologies. Local carriers seek an economical architecture to deliver integrated services on optically enabled broadband-access networks. Services over wireless-access networks must coexist with those from wired networks. In each case, convergence of networks and services inspires an important set of questions and challenges, driven by the need for low cost, operational efficiency, service performance requirements, and optical transport technology options. This Feature Issue explores the various interpretations and implications of network convergence pertinent to optical networking. How does convergence affect the evolution of optical transport-layer and control approaches? Are the implied directions consistent with research vision for optical networks? Substantial challenges remain. Papers are solicited across the broad spectrum of interests. These include, but are not limited to: Architecture, design and performance of optical wide-area-network (WAN), metro, and access networks Integration strategies for multiservice transport platforms Access methods that bridge traditional and emerging services Network signaling and control methodologies All-optical packet routing and switching techniques

Convergence

NASA Astrophysics Data System (ADS)

Darcie, Thomas E.; Doverspike, Robert; Zirngibl, Martin; Korotky, Steven K.

2005-05-01

Call for Papers: Convergence The Journal of Optical Networking (JON) invites submissions to a special issue on Convergence. Convergence has become a popular theme in telecommunications, one that has broad implications across all segments of the industry. Continual evolution of technology and applications continues to erase lines between traditionally separate lines of business, with dramatic consequences for vendors, service providers, and consumers. Spectacular advances in all layers of optical networking-leading to abundant, dynamic, cost-effective, and reliable wide-area and local-area connections-have been essential drivers of this evolution. As services and networks continue to evolve towards some notion of convergence, the continued role of optical networks must be explored. One vision of convergence renders all information in a common packet (especially IP) format. This vision is driven by the proliferation of data services. For example, time-division multiplexed (TDM) voice becomes VoIP. Analog cable-television signals become MPEG bits streamed to digital set-top boxes. T1 or OC-N private lines migrate to Ethernet virtual private networks (VPNs). All these packets coexist peacefully within a single packet-routing methodology built on an optical transport layer that combines the flexibility and cost of data networks with telecom-grade reliability. While this vision is appealing in its simplicity and shared widely, specifics of implementation raise many challenges and differences of opinion. For example, many seek to expand the role of Ethernet in these transport networks, while massive efforts are underway to make traditional TDM networks more data friendly within an evolved but backward-compatible SDH/SONET (synchronous digital hierarchy and synchronous optical network) multiplexing hierarchy. From this common underlying theme follow many specific instantiations. Examples include the convergence at the physical, logical, and operational levels of voice and data, video and data, private-line and virtual private-line, fixed and mobile, and local and long-haul services. These trends have many consequences for consumers, vendors, and carriers. Faced with large volumes of low-margin data traffic mixed with traditional voice services, the need for capital conservation and operational efficiency drives carriers away from today's separate overlay networks for each service and towards "converged" platforms. For example, cable operators require transport of multiple services over both hybrid fiber coax (HFC) and DWDM transport technologies. Local carriers seek an economical architecture to deliver integrated services on optically enabled broadband-access networks. Services over wireless-access networks must coexist with those from wired networks. In each case, convergence of networks and services inspires an important set of questions and challenges, driven by the need for low cost, operational efficiency, service performance requirements, and optical transport technology options. This Feature Issue explores the various interpretations and implications of network convergence pertinent to optical networking. How does convergence affect the evolution of optical transport-layer and control approaches? Are the implied directions consistent with research vision for optical networks? Substantial challenges remain. Papers are solicited across the broad spectrum of interests. These include, but are not limited to: Architecture, design and performance of optical wide-area-network (WAN), metro, and access networks Integration strategies for multiservice transport platforms Access methods that bridge traditional and emerging services Network signaling and control methodologies All-optical packet routing and switching techniques

Convergence

NASA Astrophysics Data System (ADS)

Darcie, Thomas E.; Doverspike, Robert; Zirngibl, Martin; Korotky, Steven K.

2005-04-01

Call for Papers: Convergence The Journal of Optical Networking (JON) invites submissions to a special issue on Convergence. Convergence has become a popular theme in telecommunications, one that has broad implications across all segments of the industry. Continual evolution of technology and applications continues to erase lines between traditionally separate lines of business, with dramatic consequences for vendors, service providers, and consumers. Spectacular advances in all layers of optical networking-leading to abundant, dynamic, cost-effective, and reliable wide-area and local-area connections-have been essential drivers of this evolution. As services and networks continue to evolve towards some notion of convergence, the continued role of optical networks must be explored. One vision of convergence renders all information in a common packet (especially IP) format. This vision is driven by the proliferation of data services. For example, time-division multiplexed (TDM) voice becomes VoIP. Analog cable-television signals become MPEG bits streamed to digital set-top boxes. T1 or OC-N private lines migrate to Ethernet virtual private networks (VPNs). All these packets coexist peacefully within a single packet-routing methodology built on an optical transport layer that combines the flexibility and cost of data networks with telecom-grade reliability. While this vision is appealing in its simplicity and shared widely, specifics of implementation raise many challenges and differences of opinion. For example, many seek to expand the role of Ethernet in these transport networks, while massive efforts are underway to make traditional TDM networks more data friendly within an evolved but backward-compatible SDH/SONET (synchronous digital hierarchy and synchronous optical network) multiplexing hierarchy. From this common underlying theme follow many specific instantiations. Examples include the convergence at the physical, logical, and operational levels of voice and data, video and data, private-line and virtual private-line, fixed and mobile, and local and long-haul services. These trends have many consequences for consumers, vendors, and carriers. Faced with large volumes of low-margin data traffic mixed with traditional voice services, the need for capital conservation and operational efficiency drives carriers away from today's separate overlay networks for each service and towards "converged" platforms. For example, cable operators require transport of multiple services over both hybrid fiber coax (HFC) and DWDM transport technologies. Local carriers seek an economical architecture to deliver integrated services on optically enabled broadband-access networks. Services over wireless-access networks must coexist with those from wired networks. In each case, convergence of networks and services inspires an important set of questions and challenges, driven by the need for low cost, operational efficiency, service performance requirements, and optical transport technology options. This Feature Issue explores the various interpretations and implications of network convergence pertinent to optical networking. How does convergence affect the evolution of optical transport-layer and control approaches? Are the implied directions consistent with research vision for optical networks? Substantial challenges remain. Papers are solicited across the broad spectrum of interests. These include, but are not limited to: Architecture, design and performance of optical wide-area-network (WAN), metro, and access networks Integration strategies for multiservice transport platforms Access methods that bridge traditional and emerging services Network signaling and control methodologies All-optical packet routing and switching techniques

Convergence

NASA Astrophysics Data System (ADS)

Darcie, Thomas E.; Doverspike, Robert; Zirngibl, Martin; Korotky, Steven K.

2005-01-01

Call for Papers: Convergence

Guest Editors: Thomas E. Darcie, University of Victoria Robert Doverspike, AT&T Martin Zirngibl, Lucent Technologies

Coordinating Associate Editor: Steven K. Korotky, Lucent Technologies

• Architecture, design and performance of optical wide-area-network (WAN), metro, and access networks
• Integration strategies for multiservice transport platforms
• Access methods that bridge traditional and emerging services
• Network signaling and control methodologies
• All-optical packet routing and switching techniques

Manuscript Submission

The Role of Social Network Technologies in Online Health Promotion: A Narrative Review of Theoretical and Empirical Factors Influencing Intervention Effectiveness

PubMed Central

Kennedy, Catriona M; Buchan, Iain; Powell, John; Ainsworth, John

2015-01-01

Background Social network technologies have become part of health education and wider health promotion—either by design or happenstance. Social support, peer pressure, and information sharing in online communities may affect health behaviors. If there are positive and sustained effects, then social network technologies could increase the effectiveness and efficiency of many public health campaigns. Social media alone, however, may be insufficient to promote health. Furthermore, there may be unintended and potentially harmful consequences of inaccurate or misleading health information. Given these uncertainties, there is a need to understand and synthesize the evidence base for the use of online social networking as part of health promoting interventions to inform future research and practice. Objective Our aim was to review the research on the integration of expert-led health promotion interventions with online social networking in order to determine the extent to which the complementary benefits of each are understood and used. We asked, in particular, (1) How is effectiveness being measured and what are the specific problems in effecting health behavior change?, and (2) To what extent is the designated role of social networking grounded in theory? Methods The narrative synthesis approach to literature review was used to analyze the existing evidence. We searched the indexed scientific literature using keywords associated with health promotion and social networking. The papers included were only those making substantial study of both social networking and health promotion—either reporting the results of the intervention or detailing evidence-based plans. General papers about social networking and health were not included. Results The search identified 162 potentially relevant documents after review of titles and abstracts. Of these, 42 satisfied the inclusion criteria after full-text review. Six studies described randomized controlled trials (RCTs) evaluating the effectiveness of online social networking within health promotion interventions. Most of the trials investigated the value of a “social networking condition” in general and did not identify specific features that might play a role in effectiveness. Issues about the usability and level of uptake of interventions were more common among pilot studies, while observational studies showed positive evidence about the role of social support. A total of 20 papers showed the use of theory in the design of interventions, but authors evaluated effectiveness in only 10 papers. Conclusions More research is needed in this area to understand the actual effect of social network technologies on health promotion. More RCTs of greater length need to be conducted taking into account contextual factors such as patient characteristics and types of a social network technology. Also, more evidence is needed regarding the actual usability of online social networking and how different interface design elements may help or hinder behavior change and engagement. Moreover, it is crucial to investigate further the effect of theory on the effectiveness of this type of technology for health promotion. Research is needed linking theoretical grounding with observation and analysis of health promotion in online networks. PMID:26068087

Automatically identifying health- and clinical-related content in wikipedia.

PubMed

Liu, Feifan; Moosavinasab, Soheil; Agarwal, Shashank; Bennett, Andrew S; Yu, Hong

2013-01-01

Physicians are increasingly using the Internet for finding medical information related to patient care. Wikipedia is a valuable online medical resource to be integrated into existing clinical question answering (QA) systems. On the other hand, Wikipedia contains a full spectrum of world's knowledge and therefore comprises a large partition of non-health-related content, which makes disambiguation more challenging and consequently leads to large overhead for existing systems to effectively filter irrelevant information. To overcome this, we have developed both unsupervised and supervised approaches to identify health-related articles as well as clinically relevant articles. Furthermore, we explored novel features by extracting health related hierarchy from the Wikipedia category network, from which a variety of features were derived and evaluated. Our experiments show promising results and also demonstrate that employing the category hierarchy can effectively improve the system performance.

Security protection of DICOM medical images using dual-layer reversible watermarking with tamper detection capability.

PubMed

Tan, Chun Kiat; Ng, Jason Changwei; Xu, Xiaotian; Poh, Chueh Loo; Guan, Yong Liang; Sheah, Kenneth

2011-06-01

Teleradiology applications and universal availability of patient records using web-based technology are rapidly gaining importance. Consequently, digital medical image security has become an important issue when images and their pertinent patient information are transmitted across public networks, such as the Internet. Health mandates such as the Health Insurance Portability and Accountability Act require healthcare providers to adhere to security measures in order to protect sensitive patient information. This paper presents a fully reversible, dual-layer watermarking scheme with tamper detection capability for medical images. The scheme utilizes concepts of public-key cryptography and reversible data-hiding technique. The scheme was tested using medical images in DICOM format. The results show that the scheme is able to ensure image authenticity and integrity, and to locate tampered regions in the images.

Brain systems underlying attentional control and emotional distraction during working memory encoding.

PubMed

Ziaei, Maryam; Peira, Nathalie; Persson, Jonas

2014-02-15

Goal-directed behavior requires that cognitive operations can be protected from emotional distraction induced by task-irrelevant emotional stimuli. The brain processes involved in attending to relevant information while filtering out irrelevant information are still largely unknown. To investigate the neural and behavioral underpinnings of attending to task-relevant emotional stimuli while ignoring irrelevant stimuli, we used fMRI to assess brain responses during attentional instructed encoding within an emotional working memory (WM) paradigm. We showed that instructed attention to emotion during WM encoding resulted in enhanced performance, by means of increased memory performance and reduced reaction time, compared to passive viewing. A similar performance benefit was also demonstrated for recognition memory performance, although for positive pictures only. Functional MRI data revealed a network of regions involved in directed attention to emotional information for both positive and negative pictures that included medial and lateral prefrontal cortices, fusiform gyrus, insula, the parahippocampal gyrus, and the amygdala. Moreover, we demonstrate that regions in the striatum, and regions associated with the default-mode network were differentially activated for emotional distraction compared to neutral distraction. Activation in a sub-set of these regions was related to individual differences in WM and recognition memory performance, thus likely contributing to performing the task at an optimal level. The present results provide initial insights into the behavioral and neural consequences of instructed attention and emotional distraction during WM encoding. © 2013.

Java-based cryptosystem for PACS and tele-imaging

NASA Astrophysics Data System (ADS)

Tjandra, Donny; Wong, Stephen T. C.; Yu, Yuan-Pin

1998-07-01

Traditional PACS systems are based on two-tier client server architectures, and require the use of costly, high-end client workstations for image viewing. Consequently, PACS systems using the two-tier architecture do not scale well as data increases in size and complexity. Furthermore, use of dedicated viewing workstations incurs costs in deployment and maintenance. To address these issues, the use of digital library technologies, such as the World Wide Web, Java, and CORBA, is being explored to distribute PACS data to serve a broader range of healthcare providers in an economic and efficient manner. Integration of PACS systems with digital library technologies allows access to medical information through open networks such as the Internet. However, use of open networks to transmit medical data introduces problems with maintaining privacy and integrity of patient information. Cryptography and digital timestamping is used to protect sensitive information from unauthorized access or tampering. A major concern when using cryptography and digital timestamping is the performance degradation associated with the mathematical calculations needed to encrypt/decrypt an image dataset, or to calculate the hash value of an image. The performance issue is compounded by the extra layer associated with the CORBA middleware, and the use of programming languages interpreted at the client side, such as Java. This paper study the extent to which Java-based cryptography and digital timestamping affects performance in a PACS system integrated with digital library technologies.

Research on Information Sharing Mechanism of Network Organization Based on Evolutionary Game

NASA Astrophysics Data System (ADS)

Wang, Lin; Liu, Gaozhi

2018-02-01

This article first elaborates the concept and effect of network organization, and the ability to share information is analyzed, secondly introduces the evolutionary game theory, network organization for information sharing all kinds of limitations, establishes the evolutionary game model, analyzes the dynamic evolution of network organization of information sharing, through reasoning and evolution. The network information sharing by the initial state and two sides of the game payoff matrix of excess profits and information is the information sharing of cost and risk sharing are the influence of network organization node information sharing decision.

Improving conservation of Florida manatees (Trichechus manatus latirostris): conceptualization and contributions toward a regional warm-water network management strategy for sustainable winter habitat.

PubMed

Flamm, Richard Owen; Reynolds, John Elliot; Harmak, Craig

2013-01-01

We used southwestern Florida as a case study to lay the groundwork for an intended and organized decision-making process for managing warm-water habitat needed by endangered manatees to survive winters in Florida. Scientists and managers have prioritized (a) projecting how the network of warm-water sites will change over the next 50 years as warmed industrial discharges may expire and as flows of natural springs are reduced through redirection of water for human uses, and (b) mitigating such changes to prevent undue consequences to manatees. Given the complexities introduced by manatee ecology; agency organizational structure; shifting public demands; fluctuating resource availability; and managing within interacting cultural, social, political, and environmental contexts, it was clear that a structured decision process was needed. To help promote such a process, we collected information relevant to future decisions including maps of known and suspected warm-water sites and prototyped a characterization of sites and networks. We propose steps that would lead to models that might serve as core tools in manatee/warm-water decision-making, and we summarized topics relevant for informed decision-making (e.g., manatee spatial cognition, risk of cold-stress morbidity and mortality, and human dimensions). A major impetus behind this effort is to ensure proactively that robust modeling tools are available well in advance of the anticipated need for a critical management decision.

Improving Conservation of Florida Manatees ( Trichechus manatus latirostris): Conceptualization and Contributions Toward a Regional Warm-Water Network Management Strategy for Sustainable Winter Habitat

NASA Astrophysics Data System (ADS)

Flamm, Richard Owen; Reynolds, John Elliot; Harmak, Craig

2013-01-01

We used southwestern Florida as a case study to lay the groundwork for an intended and organized decision-making process for managing warm-water habitat needed by endangered manatees to survive winters in Florida. Scientists and managers have prioritized (a) projecting how the network of warm-water sites will change over the next 50 years as warmed industrial discharges may expire and as flows of natural springs are reduced through redirection of water for human uses, and (b) mitigating such changes to prevent undue consequences to manatees. Given the complexities introduced by manatee ecology; agency organizational structure; shifting public demands; fluctuating resource availability; and managing within interacting cultural, social, political, and environmental contexts, it was clear that a structured decision process was needed. To help promote such a process, we collected information relevant to future decisions including maps of known and suspected warm-water sites and prototyped a characterization of sites and networks. We propose steps that would lead to models that might serve as core tools in manatee/warm-water decision-making, and we summarized topics relevant for informed decision-making (e.g., manatee spatial cognition, risk of cold-stress morbidity and mortality, and human dimensions). A major impetus behind this effort is to ensure proactively that robust modeling tools are available well in advance of the anticipated need for a critical management decision.

Generic, network schema agnostic sparse tensor factorization for single-pass clustering of heterogeneous information networks

PubMed Central

Meng, Qinggang; Deng, Su; Huang, Hongbin; Wu, Yahui; Badii, Atta

2017-01-01

Heterogeneous information networks (e.g. bibliographic networks and social media networks) that consist of multiple interconnected objects are ubiquitous. Clustering analysis is an effective method to understand the semantic information and interpretable structure of the heterogeneous information networks, and it has attracted the attention of many researchers in recent years. However, most studies assume that heterogeneous information networks usually follow some simple schemas, such as bi-typed networks or star network schema, and they can only cluster one type of object in the network each time. In this paper, a novel clustering framework is proposed based on sparse tensor factorization for heterogeneous information networks, which can cluster multiple types of objects simultaneously in a single pass without any network schema information. The types of objects and the relations between them in the heterogeneous information networks are modeled as a sparse tensor. The clustering issue is modeled as an optimization problem, which is similar to the well-known Tucker decomposition. Then, an Alternating Least Squares (ALS) algorithm and a feasible initialization method are proposed to solve the optimization problem. Based on the tensor factorization, we simultaneously partition different types of objects into different clusters. The experimental results on both synthetic and real-world datasets have demonstrated that our proposed clustering framework, STFClus, can model heterogeneous information networks efficiently and can outperform state-of-the-art clustering algorithms as a generally applicable single-pass clustering method for heterogeneous network which is network schema agnostic. PMID:28245222

Generic, network schema agnostic sparse tensor factorization for single-pass clustering of heterogeneous information networks.

PubMed

Wu, Jibing; Meng, Qinggang; Deng, Su; Huang, Hongbin; Wu, Yahui; Badii, Atta

2017-01-01

Heterogeneous information networks (e.g. bibliographic networks and social media networks) that consist of multiple interconnected objects are ubiquitous. Clustering analysis is an effective method to understand the semantic information and interpretable structure of the heterogeneous information networks, and it has attracted the attention of many researchers in recent years. However, most studies assume that heterogeneous information networks usually follow some simple schemas, such as bi-typed networks or star network schema, and they can only cluster one type of object in the network each time. In this paper, a novel clustering framework is proposed based on sparse tensor factorization for heterogeneous information networks, which can cluster multiple types of objects simultaneously in a single pass without any network schema information. The types of objects and the relations between them in the heterogeneous information networks are modeled as a sparse tensor. The clustering issue is modeled as an optimization problem, which is similar to the well-known Tucker decomposition. Then, an Alternating Least Squares (ALS) algorithm and a feasible initialization method are proposed to solve the optimization problem. Based on the tensor factorization, we simultaneously partition different types of objects into different clusters. The experimental results on both synthetic and real-world datasets have demonstrated that our proposed clustering framework, STFClus, can model heterogeneous information networks efficiently and can outperform state-of-the-art clustering algorithms as a generally applicable single-pass clustering method for heterogeneous network which is network schema agnostic.

Actin assembly factors regulate the gelation kinetics and architecture of F-actin networks.

PubMed

Falzone, Tobias T; Oakes, Patrick W; Sees, Jennifer; Kovar, David R; Gardel, Margaret L

2013-04-16

Dynamic regulation of the actin cytoskeleton is required for diverse cellular processes. Proteins regulating the assembly kinetics of the cytoskeletal biopolymer F-actin are known to impact the architecture of actin cytoskeletal networks in vivo, but the underlying mechanisms are not well understood. Here, we demonstrate that changes to actin assembly kinetics with physiologically relevant proteins profilin and formin (mDia1 and Cdc12) have dramatic consequences on the architecture and gelation kinetics of otherwise biochemically identical cross-linked F-actin networks. Reduced F-actin nucleation rates promote the formation of a sparse network of thick bundles, whereas increased nucleation rates result in a denser network of thinner bundles. Changes to F-actin elongation rates also have marked consequences. At low elongation rates, gelation ceases and a solution of rigid bundles is formed. By contrast, rapid filament elongation accelerates dynamic arrest and promotes gelation with minimal F-actin density. These results are consistent with a recently developed model of how kinetic constraints regulate network architecture and underscore how molecular control of polymer assembly is exploited to modulate cytoskeletal architecture and material properties. Copyright © 2013 Biophysical Society. Published by Elsevier Inc. All rights reserved.

Actin Assembly Factors Regulate the Gelation Kinetics and Architecture of F-actin Networks

PubMed Central

Falzone, Tobias T.; Oakes, Patrick W.; Sees, Jennifer; Kovar, David R.; Gardel, Margaret L.

2013-01-01

Dynamic regulation of the actin cytoskeleton is required for diverse cellular processes. Proteins regulating the assembly kinetics of the cytoskeletal biopolymer F-actin are known to impact the architecture of actin cytoskeletal networks in vivo, but the underlying mechanisms are not well understood. Here, we demonstrate that changes to actin assembly kinetics with physiologically relevant proteins profilin and formin (mDia1 and Cdc12) have dramatic consequences on the architecture and gelation kinetics of otherwise biochemically identical cross-linked F-actin networks. Reduced F-actin nucleation rates promote the formation of a sparse network of thick bundles, whereas increased nucleation rates result in a denser network of thinner bundles. Changes to F-actin elongation rates also have marked consequences. At low elongation rates, gelation ceases and a solution of rigid bundles is formed. By contrast, rapid filament elongation accelerates dynamic arrest and promotes gelation with minimal F-actin density. These results are consistent with a recently developed model of how kinetic constraints regulate network architecture and underscore how molecular control of polymer assembly is exploited to modulate cytoskeletal architecture and material properties. PMID:23601318

Modeling Belt-Servomechanism by Chebyshev Functional Recurrent Neuro-Fuzzy Network

NASA Astrophysics Data System (ADS)

Huang, Yuan-Ruey; Kang, Yuan; Chu, Ming-Hui; Chang, Yeon-Pun

A novel Chebyshev functional recurrent neuro-fuzzy (CFRNF) network is developed from a combination of the Takagi-Sugeno-Kang (TSK) fuzzy model and the Chebyshev recurrent neural network (CRNN). The CFRNF network can emulate the nonlinear dynamics of a servomechanism system. The system nonlinearity is addressed by enhancing the input dimensions of the consequent parts in the fuzzy rules due to functional expansion of a Chebyshev polynomial. The back propagation algorithm is used to adjust the parameters of the antecedent membership functions as well as those of consequent functions. To verify the performance of the proposed CFRNF, the experiment of the belt servomechanism is presented in this paper. Both of identification methods of adaptive neural fuzzy inference system (ANFIS) and recurrent neural network (RNN) are also studied for modeling of the belt servomechanism. The analysis and comparison results indicate that CFRNF makes identification of complex nonlinear dynamic systems easier. It is verified that the accuracy and convergence of the CFRNF are superior to those of ANFIS and RNN by the identification results of a belt servomechanism.

How Did the Information Flow in the #AlphaGo Hashtag Network? A Social Network Analysis of the Large-Scale Information Network on Twitter.

PubMed

Kim, Jinyoung

2017-12-01

As it becomes common for Internet users to use hashtags when posting and searching information on social media, it is important to understand who builds a hashtag network and how information is circulated within the network. This article focused on unlocking the potential of the #AlphaGo hashtag network by addressing the following questions. First, the current study examined whether traditional opinion leadership (i.e., the influentials hypothesis) or grassroot participation by the public (i.e., the interpersonal hypothesis) drove dissemination of information in the hashtag network. Second, several unique patterns of information distribution by key users were identified. Finally, the association between attributes of key users who exerted great influence on information distribution (i.e., the number of followers and follows) and their central status in the network was tested. To answer the proffered research questions, a social network analysis was conducted using a large-scale hashtag network data set from Twitter (n = 21,870). The results showed that the leading actors in the network were actively receiving information from their followers rather than serving as intermediaries between the original information sources and the public. Moreover, the leading actors played several roles (i.e., conversation starters, influencers, and active engagers) in the network. Furthermore, the number of their follows and followers were significantly associated with their central status in the hashtag network. Based on the results, the current research explained how the information was exchanged in the hashtag network by proposing the reciprocal model of information flow.

78 FR 2992 - Agency Information Collection Activities; Proposed Collection; Comment Request; Distribution of...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-01-15

... Activities; Proposed Collection; Comment Request; Distribution of Offsite Consequence Analysis Information... Collection Request (ICR), Distribution of Offsite Consequence Analysis Information under Section 112(r)(7)(H... Air Act Section 112(r)(7); Distribution of Off-Site Consequence Analysis Information. CAA section 112...

Distributed Data Networks That Support Public Health Information Needs.

PubMed

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.

Application of WebGIS for traffic risk assessment

NASA Astrophysics Data System (ADS)

Voumard, Jérémie; Aye, Zar Chi; Derron, Marc-Henri; Jaboyedoff, Michel

2015-04-01

Roads and railways are threatened throughout the year by several natural hazards around the world, leading to the closing of transportation corridors, loss of access, deviation travels and potentially infrastructures damages and loss of human lives and also financial, social and economic consequences. Protection measures used to reduce the exposure to natural hazards are usually expensive and cannot be deployed on an entire transportation network. It is thus necessary to choose priority areas where protection measures need to be built. The aim of this study is to propose a friendly tool to evaluate and to understand issues and consequences of section closing and affected parts of a transportation network at small region scale. The proposed tool, currently in its design and building phase, will provide ways to simulate different closure scenarios and to analyze their consequences on transportation network; like deviating traffic on others roads and railways sections, additional time and distance travel or accessibility for emergency services like police, firefighters and ambulances. The tool is based on OpenGeo architecture, which is composed of open-source components. It integrates PostGIS for database, GeoServer and GeoWebCache for application servers and finally GeoExt and OpenLayers for user interface. Users will be able to attribute quantitative (like roads and railway type and closure consequences) and qualitative (like section unavailability duration, season, etc.) data to the different roads and railways sections based on their user rights. They will also be able to evaluate different track closures consequences in terms of different scenarios. Once finalized, the goal of this project including natural hazards, traffic and geomatic thematic is to propose a decision support tool for public authorities firstly and for specialists secondly so that they can evaluate easily and accurately as much as possible to highlight the weakpoints of the transportation network in the case track closures due to natural hazards.

Social barriers to Type 2 diabetes self-management: the role of capital.

PubMed

Henderson, Julie; Wilson, Christine; Roberts, Louise; Munt, Rebecca; Crotty, Mikaila

2014-12-01

Approaches to self-management traditionally focus upon individual capacity to make behavioural change. In this paper, we use Bourdieu's concepts of habitus and capital to demonstrate the impact of structural inequalities upon chronic illness self-management through exploring findings from 28 semi-structured interviews conducted with people from a lower socioeconomic region of Adelaide, South Australia who have type 2 diabetes. The data suggests that access to capital is a significant barrier to type 2 diabetes self-management. While many participants described having sufficient cultural capital to access and assess health information, they often lacked economic capital and social capital in the form of support networks who promote health. Participants were often involved in social networks in which activities which are contrary to self-management have symbolic value. As a consequence, they entered relationships with health professionals at a disadvantage. We conclude that structural barriers to self-management arising from habitus resulting in the performance of health behaviours rooted in cultural and class background and limited access to capital in the form of economic resources, social networks, health knowledge and prestige may have a negative impact on capacity for type 2 diabetes self-management. © 2014 John Wiley & Sons Ltd.

Uninformative memories will prevail: the storage of correlated representations and its consequences.

PubMed

Kropff, Emilio; Treves, Alessandro

2007-11-01

Autoassociative networks were proposed in the 80's as simplified models of memory function in the brain, using recurrent connectivity with Hebbian plasticity to store patterns of neural activity that can be later recalled. This type of computation has been suggested to take place in the CA3 region of the hippocampus and at several levels in the cortex. One of the weaknesses of these models is their apparent inability to store correlated patterns of activity. We show, however, that a small and biologically plausible modification in the "learning rule" (associating to each neuron a plasticity threshold that reflects its popularity) enables the network to handle correlations. We study the stability properties of the resulting memories (in terms of their resistance to the damage of neurons or synapses), finding a novel property of autoassociative networks: not all memories are equally robust, and the most informative are also the most sensitive to damage. We relate these results to category-specific effects in semantic memory patients, where concepts related to "non-living things" are usually more resistant to brain damage than those related to "living things," a phenomenon suspected to be rooted in the correlation between representations of concepts in the cortex.

Age-related Multiscale Changes in Brain Signal Variability in Pre-task versus Post-task Resting-state EEG.

PubMed

Wang, Hongye; McIntosh, Anthony R; Kovacevic, Natasa; Karachalios, Maria; Protzner, Andrea B

2016-07-01

Recent empirical work suggests that, during healthy aging, the variability of network dynamics changes during task performance. Such variability appears to reflect the spontaneous formation and dissolution of different functional networks. We sought to extend these observations into resting-state dynamics. We recorded EEG in young, middle-aged, and older adults during a "rest-task-rest" design and investigated if aging modifies the interaction between resting-state activity and external stimulus-induced activity. Using multiscale entropy as our measure of variability, we found that, with increasing age, resting-state dynamics shifts from distributed to more local neural processing, especially at posterior sources. In the young group, resting-state dynamics also changed from pre- to post-task, where fine-scale entropy increased in task-positive regions and coarse-scale entropy increased in the posterior cingulate, a key region associated with the default mode network. Lastly, pre- and post-task resting-state dynamics were linked to performance on the intervening task for all age groups, but this relationship became weaker with increasing age. Our results suggest that age-related changes in resting-state dynamics occur across different spatial and temporal scales and have consequences for information processing capacity.

The complexity of classical music networks

NASA Astrophysics Data System (ADS)

Rolla, Vitor; Kestenberg, Juliano; Velho, Luiz

2018-02-01

Previous works suggest that musical networks often present the scale-free and the small-world properties. From a musician's perspective, the most important aspect missing in those studies was harmony. In addition to that, the previous works made use of outdated statistical methods. Traditionally, least-squares linear regression is utilised to fit a power law to a given data set. However, according to Clauset et al. such a traditional method can produce inaccurate estimates for the power law exponent. In this paper, we present an analysis of musical networks which considers the existence of chords (an essential element of harmony). Here we show that only 52.5% of music in our database presents the scale-free property, while 62.5% of those pieces present the small-world property. Previous works argue that music is highly scale-free; consequently, it sounds appealing and coherent. In contrast, our results show that not all pieces of music present the scale-free and the small-world properties. In summary, this research is focused on the relationship between musical notes (Do, Re, Mi, Fa, Sol, La, Si, and their sharps) and accompaniment in classical music compositions. More information about this research project is available at https://eden.dei.uc.pt/~vitorgr/MS.html.

Sensitivity of proxies on non-linear interactions in the climate system

PubMed Central

Schultz, Johannes A.; Beck, Christoph; Menz, Gunter; Neuwirth, Burkhard; Ohlwein, Christian; Philipp, Andreas

2015-01-01

Recent climate change is affecting the earth system to an unprecedented extent and intensity and has the potential to cause severe ecological and socioeconomic consequences. To understand natural and anthropogenic induced processes, feedbacks, trends, and dynamics in the climate system, it is also essential to consider longer timescales. In this context, annually resolved tree-ring data are often used to reconstruct past temperature or precipitation variability as well as atmospheric or oceanic indices such as the North Atlantic Oscillation (NAO) or the Atlantic Multidecadal Oscillation (AMO). The aim of this study is to assess weather-type sensitivity across the Northern Atlantic region based on two tree-ring width networks. Our results indicate that nonstationarities in superordinate space and time scales of the climate system (here synoptic- to global scale, NAO, AMO) can affect the climate sensitivity of tree-rings in subordinate levels of the system (here meso- to synoptic scale, weather-types). This scale bias effect has the capability to impact even large multiproxy networks and the ability of these networks to provide information about past climate conditions. To avoid scale biases in climate reconstructions, interdependencies between the different scales in the climate system must be considered, especially internal ocean/atmosphere dynamics. PMID:26686001

A case of a large Chiari network mimicking a right atrial thrombus.

PubMed

Erdogan, Sevinc Bayer; Akansel, Serdar; Sargın, Murat; Mete, Muge Evren Tasdemir; Arslanhan, Gokhan; Aka, Serap Aykut

2017-01-01

The Chiari network is described as a reticulated network of fibers connected to the Eustachian valve identified as the embryological remnant of the right valve of the sinus venosus. It is an incidental finding without any significant pathophysiological consequences. However, the presence of the Chiari network in the right atrium obliges the physician to differentiate from other right atrial pathologies. We present a case of a large Chiari network mimicking a right atrial thrombus with incidental finding in a 76-year-old man undergoing coronary artery bypass surgery.

The transfer and transformation of collective network information in gene-matched networks.

PubMed

Kitsukawa, Takashi; Yagi, Takeshi

2015-10-09

Networks, such as the human society network, social and professional networks, and biological system networks, contain vast amounts of information. Information signals in networks are distributed over nodes and transmitted through intricately wired links, making the transfer and transformation of such information difficult to follow. Here we introduce a novel method for describing network information and its transfer using a model network, the Gene-matched network (GMN), in which nodes (neurons) possess attributes (genes). In the GMN, nodes are connected according to their expression of common genes. Because neurons have multiple genes, the GMN is cluster-rich. We show that, in the GMN, information transfer and transformation were controlled systematically, according to the activity level of the network. Furthermore, information transfer and transformation could be traced numerically with a vector using genes expressed in the activated neurons, the active-gene array, which was used to assess the relative activity among overlapping neuronal groups. Interestingly, this coding style closely resembles the cell-assembly neural coding theory. The method introduced here could be applied to many real-world networks, since many systems, including human society and various biological systems, can be represented as a network of this type.

Network cosmology.

PubMed

Krioukov, Dmitri; Kitsak, Maksim; Sinkovits, Robert S; Rideout, David; Meyer, David; Boguñá, Marián

2012-01-01

Prediction and control of the dynamics of complex networks is a central problem in network science. Structural and dynamical similarities of different real networks suggest that some universal laws might accurately describe the dynamics of these networks, albeit the nature and common origin of such laws remain elusive. Here we show that the causal network representing the large-scale structure of spacetime in our accelerating universe is a power-law graph with strong clustering, similar to many complex networks such as the Internet, social, or biological networks. We prove that this structural similarity is a consequence of the asymptotic equivalence between the large-scale growth dynamics of complex networks and causal networks. This equivalence suggests that unexpectedly similar laws govern the dynamics of complex networks and spacetime in the universe, with implications to network science and cosmology.

Network Cosmology

PubMed Central

Krioukov, Dmitri; Kitsak, Maksim; Sinkovits, Robert S.; Rideout, David; Meyer, David; Boguñá, Marián

2012-01-01

Prediction and control of the dynamics of complex networks is a central problem in network science. Structural and dynamical similarities of different real networks suggest that some universal laws might accurately describe the dynamics of these networks, albeit the nature and common origin of such laws remain elusive. Here we show that the causal network representing the large-scale structure of spacetime in our accelerating universe is a power-law graph with strong clustering, similar to many complex networks such as the Internet, social, or biological networks. We prove that this structural similarity is a consequence of the asymptotic equivalence between the large-scale growth dynamics of complex networks and causal networks. This equivalence suggests that unexpectedly similar laws govern the dynamics of complex networks and spacetime in the universe, with implications to network science and cosmology. PMID:23162688

Information network architectures

NASA Technical Reports Server (NTRS)

Murray, N. D.

1985-01-01

Graphs, charts, diagrams and outlines of information relative to information network architectures for advanced aerospace missions, such as the Space Station, are presented. Local area information networks are considered a likely technology solution. The principle needs for the network are listed.

The importance of national and international collaboration in adult congenital heart disease: A network analysis of research output.

PubMed

Orwat, Melanie Iris; Kempny, Aleksander; Bauer, Ulrike; Gatzoulis, Michael A; Baumgartner, Helmut; Diller, Gerhard-Paul

2015-09-15

The determinants of adult congenital heart disease (ACHD) research output are only partially understood. The heterogeneity of ACHD naturally calls for collaborative work; however, limited information exists on the impact of collaboration on academic performance. We aimed to examine the global topology of ACHD research, distribution of research collaboration and its association with cumulative research output. Based on publications presenting original research between 2005 and 2011, a network analysis was performed quantifying centrality measures and key players in the field of ACHD. In addition, network maps were produced to illustrate the global distribution and interconnected nature of ACHD research. The proportion of collaborative research was 35.6 % overall, with a wide variation between countries (7.1 to 62.8%). The degree of research collaboration, as well as measures of network centrality (betweenness and degree centrality), were statistically associated with cumulative research output independently of national wealth and available workforce. The global ACHD research network was found to be scale-free with a small number of central hubs and a relatively large number of peripheral nodes. In addition, we could identify potentially influential hubs based on cluster analysis and measures of centrality/key player analysis. Using network analysis methods the current study illustrates the complex and global structures of ACHD research. It suggests that collaboration between research institutions is associated with higher academic output. As a consequence national and international collaboration in ACHD research should be encouraged and the creation of an adequate supporting infrastructure should be further promoted. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Building gene co-expression networks using transcriptomics data for systems biology investigations: Comparison of methods using microarray data

PubMed Central

Kadarmideen, Haja N; Watson-haigh, Nathan S

2012-01-01

Gene co-expression networks (GCN), built using high-throughput gene expression data are fundamental aspects of systems biology. The main aims of this study were to compare two popular approaches to building and analysing GCN. We use real ovine microarray transcriptomics datasets representing four different treatments with Metyrapone, an inhibitor of cortisol biosynthesis. We conducted several microarray quality control checks before applying GCN methods to filtered datasets. Then we compared the outputs of two methods using connectivity as a criterion, as it measures how well a node (gene) is connected within a network. The two GCN construction methods used were, Weighted Gene Co-expression Network Analysis (WGCNA) and Partial Correlation and Information Theory (PCIT) methods. Nodes were ranked based on their connectivity measures in each of the four different networks created by WGCNA and PCIT and node ranks in two methods were compared to identify those nodes which are highly differentially ranked (HDR). A total of 1,017 HDR nodes were identified across one or more of four networks. We investigated HDR nodes by gene enrichment analyses in relation to their biological relevance to phenotypes. We observed that, in contrast to WGCNA method, PCIT algorithm removes many of the edges of the most highly interconnected nodes. Removal of edges of most highly connected nodes or hub genes will have consequences for downstream analyses and biological interpretations. In general, for large GCN construction (with > 20000 genes) access to large computer clusters, particularly those with larger amounts of shared memory is recommended. PMID:23144540

Comparing models for quantitative risk assessment: an application to the European Registry of foreign body injuries in children.

PubMed

Berchialla, Paola; Scarinzi, Cecilia; Snidero, Silvia; Gregori, Dario

2016-08-01

Risk Assessment is the systematic study of decisions subject to uncertain consequences. An increasing interest has been focused on modeling techniques like Bayesian Networks since their capability of (1) combining in the probabilistic framework different type of evidence including both expert judgments and objective data; (2) overturning previous beliefs in the light of the new information being received and (3) making predictions even with incomplete data. In this work, we proposed a comparison among Bayesian Networks and other classical Quantitative Risk Assessment techniques such as Neural Networks, Classification Trees, Random Forests and Logistic Regression models. Hybrid approaches, combining both Classification Trees and Bayesian Networks, were also considered. Among Bayesian Networks, a clear distinction between purely data-driven approach and combination of expert knowledge with objective data is made. The aim of this paper consists in evaluating among this models which best can be applied, in the framework of Quantitative Risk Assessment, to assess the safety of children who are exposed to the risk of inhalation/insertion/aspiration of consumer products. The issue of preventing injuries in children is of paramount importance, in particular where product design is involved: quantifying the risk associated to product characteristics can be of great usefulness in addressing the product safety design regulation. Data of the European Registry of Foreign Bodies Injuries formed the starting evidence for risk assessment. Results showed that Bayesian Networks appeared to have both the ease of interpretability and accuracy in making prediction, even if simpler models like logistic regression still performed well. © The Author(s) 2013.

Television and Competition.

ERIC Educational Resources Information Center

Noll, Roger G.

The television industry is characterized by numerous imperfections in market competition. The spectrum allocation policy of the Federal Communications Commission (FCC) assures that there will be only three national television networks; consequently in nearly all markets these stations account for 75% to 100% of revenues. These networks in turn…

Multi-period response management to contaminated water distribution networks: dynamic programming versus genetic algorithms

NASA Astrophysics Data System (ADS)

Bashi-Azghadi, Seyyed Nasser; Afshar, Abbas; Afshar, Mohammad Hadi

2018-03-01

Previous studies on consequence management assume that the selected response action including valve closure and/or hydrant opening remains unchanged during the entire management period. This study presents a new embedded simulation-optimization methodology for deriving time-varying operational response actions in which the network topology may change from one stage to another. Dynamic programming (DP) and genetic algorithm (GA) are used in order to minimize selected objective functions. Two networks of small and large sizes are used in order to illustrate the performance of the proposed modelling schemes if a time-dependent consequence management strategy is to be implemented. The results show that for a small number of decision variables even in large-scale networks, DP is superior in terms of accuracy and computer runtime. However, as the number of potential actions grows, DP loses its merit over the GA approach. This study clearly proves the priority of the proposed dynamic operation strategy over the commonly used static strategy.

Automatic summary generating technology of vegetable traceability for information sharing

NASA Astrophysics Data System (ADS)

Zhenxuan, Zhang; Minjing, Peng

2017-06-01

In order to solve problems of excessive data entries and consequent high costs for data collection in vegetable traceablility for farmers in traceability applications, the automatic summary generating technology of vegetable traceability for information sharing was proposed. The proposed technology is an effective way for farmers to share real-time vegetable planting information in social networking platforms to enhance their brands and obtain more customers. In this research, the influencing factors in the vegetable traceablility for customers were analyzed to establish the sub-indicators and target indicators and propose a computing model based on the collected parameter values of the planted vegetables and standard legal systems on food safety. The proposed standard parameter model involves five steps: accessing database, establishing target indicators, establishing sub-indicators, establishing standard reference model and computing scores of indicators. On the basis of establishing and optimizing the standards of food safety and traceability system, this proposed technology could be accepted by more and more farmers and customers.

Feasibility of neuro-morphic computing to emulate error-conflict based decision making.

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

Branch, Darren W.

2009-09-01

A key aspect of decision making is determining when errors or conflicts exist in information and knowing whether to continue or terminate an action. Understanding the error-conflict processing is crucial in order to emulate higher brain functions in hardware and software systems. Specific brain regions, most notably the anterior cingulate cortex (ACC) are known to respond to the presence of conflicts in information by assigning a value to an action. Essentially, this conflict signal triggers strategic adjustments in cognitive control, which serve to prevent further conflict. The most probable mechanism is the ACC reports and discriminates different types of feedback,more » both positive and negative, that relate to different adaptations. Unique cells called spindle neurons that are primarily found in the ACC (layer Vb) are known to be responsible for cognitive dissonance (disambiguation between alternatives). Thus, the ACC through a specific set of cells likely plays a central role in the ability of humans to make difficult decisions and solve challenging problems in the midst of conflicting information. In addition to dealing with cognitive dissonance, decision making in high consequence scenarios also relies on the integration of multiple sets of information (sensory, reward, emotion, etc.). Thus, a second area of interest for this proposal lies in the corticostriatal networks that serve as an integration region for multiple cognitive inputs. In order to engineer neurological decision making processes in silicon devices, we will determine the key cells, inputs, and outputs of conflict/error detection in the ACC region. The second goal is understand in vitro models of corticostriatal networks and the impact of physical deficits on decision making, specifically in stressful scenarios with conflicting streams of data from multiple inputs. We will elucidate the mechanisms of cognitive data integration in order to implement a future corticostriatal-like network in silicon devices for improved decision processing.« less

Computing biological functions using BioΨ, a formal description of biological processes based on elementary bricks of actions

PubMed Central

Pérès, Sabine; Felicori, Liza; Rialle, Stéphanie; Jobard, Elodie; Molina, Franck

2010-01-01

Motivation: In the available databases, biological processes are described from molecular and cellular points of view, but these descriptions are represented with text annotations that make it difficult to handle them for computation. Consequently, there is an obvious need for formal descriptions of biological processes. Results: We present a formalism that uses the BioΨ concepts to model biological processes from molecular details to networks. This computational approach, based on elementary bricks of actions, allows us to calculate on biological functions (e.g. process comparison, mapping structure–function relationships, etc.). We illustrate its application with two examples: the functional comparison of proteases and the functional description of the glycolysis network. This computational approach is compatible with detailed biological knowledge and can be applied to different kinds of systems of simulation. Availability: www.sysdiag.cnrs.fr/publications/supplementary-materials/BioPsi_Manager/ Contact: sabine.peres@sysdiag.cnrs.fr; franck.molina@sysdiag.cnrs.fr Supplementary information: Supplementary data are available at Bioinformatics online. PMID:20448138

Stoichiometric network analysis and associated dimensionless kinetic equations. Application to a model of the Bray-Liebhafsky reaction.

PubMed

Schmitz, Guy; Kolar-Anić, Ljiljana Z; Anić, Slobodan R; Cupić, Zeljko D

2008-12-25

The stoichiometric network analysis (SNA) introduced by B. L. Clarke is applied to a simplified model of the complex oscillating Bray-Liebhafsky reaction under batch conditions, which was not examined by this method earlier. This powerful method for the analysis of steady-states stability is also used to transform the classical differential equations into dimensionless equations. This transformation is easy and leads to a form of the equations combining the advantages of classical dimensionless equations with the advantages of the SNA. The used dimensionless parameters have orders of magnitude given by the experimental information about concentrations and currents. This simplifies greatly the study of the slow manifold and shows which parameters are essential for controlling its shape and consequently have an important influence on the trajectories. The effectiveness of these equations is illustrated on two examples: the study of the bifurcations points and a simple sensitivity analysis, different from the classical one, more based on the chemistry of the studied system.

Security of electronic mental health communication and record-keeping in the digital age.

PubMed

Elhai, Jon D; Frueh, B Christopher

2016-02-01

The mental health field has seen a trend in recent years of the increased use of information technology, including mobile phones, tablets, and laptop computers, to facilitate clinical treatment delivery to individual patients and for record keeping. However, little attention has been paid to ensuring that electronic communication with patients is private and secure. This is despite potentially deleterious consequences of a data breach, which are reported in the news media very frequently in modern times. In this article, we present typical security concerns associated with using technology in clinical services or research. We also discuss enhancing the privacy and security of electronic communication with clinical patients and research participants. We offer practical, easy-to-use software application solutions for clinicians and researchers to secure patient communication and records. We discuss such issues as using encrypted wireless networks, secure e-mail, encrypted messaging and videoconferencing, privacy on social networks, and others. © Copyright 2015 Physicians Postgraduate Press, Inc.

A Discrete Fracture Network Model with Stress-Driven Nucleation and Growth

NASA Astrophysics Data System (ADS)

Lavoine, E.; Darcel, C.; Munier, R.; Davy, P.

2017-12-01

The realism of Discrete Fracture Network (DFN) models, beyond the bulk statistical properties, relies on the spatial organization of fractures, which is not issued by purely stochastic DFN models. The realism can be improved by injecting prior information in DFN from a better knowledge of the geological fracturing processes. We first develop a model using simple kinematic rules for mimicking the growth of fractures from nucleation to arrest, in order to evaluate the consequences of the DFN structure on the network connectivity and flow properties. The model generates fracture networks with power-law scaling distributions and a percentage of T-intersections that are consistent with field observations. Nevertheless, a larger complexity relying on the spatial variability of natural fractures positions cannot be explained by the random nucleation process. We propose to introduce a stress-driven nucleation in the timewise process of this kinematic model to study the correlations between nucleation, growth and existing fracture patterns. The method uses the stress field generated by existing fractures and remote stress as an input for a Monte-Carlo sampling of nuclei centers at each time step. Networks so generated are found to have correlations over a large range of scales, with a correlation dimension that varies with time and with the function that relates the nucleation probability to stress. A sensibility analysis of input parameters has been performed in 3D to quantify the influence of fractures and remote stress field orientations.

Genome Scale Modeling in Systems Biology: Algorithms and Resources

PubMed Central

Najafi, Ali; Bidkhori, Gholamreza; Bozorgmehr, Joseph H.; Koch, Ina; Masoudi-Nejad, Ali

2014-01-01

In recent years, in silico studies and trial simulations have complemented experimental procedures. A model is a description of a system, and a system is any collection of interrelated objects; an object, moreover, is some elemental unit upon which observations can be made but whose internal structure either does not exist or is ignored. Therefore, any network analysis approach is critical for successful quantitative modeling of biological systems. This review highlights some of most popular and important modeling algorithms, tools, and emerging standards for representing, simulating and analyzing cellular networks in five sections. Also, we try to show these concepts by means of simple example and proper images and graphs. Overall, systems biology aims for a holistic description and understanding of biological processes by an integration of analytical experimental approaches along with synthetic computational models. In fact, biological networks have been developed as a platform for integrating information from high to low-throughput experiments for the analysis of biological systems. We provide an overview of all processes used in modeling and simulating biological networks in such a way that they can become easily understandable for researchers with both biological and mathematical backgrounds. Consequently, given the complexity of generated experimental data and cellular networks, it is no surprise that researchers have turned to computer simulation and the development of more theory-based approaches to augment and assist in the development of a fully quantitative understanding of cellular dynamics. PMID:24822031

Optimal Scheduling for Underwater Communications in Multiple-User Scenarios

DTIC Science & Technology

2015-09-30

term goals of this project is to analyze and propose energy-efficient communication techniques for underwater acoustic sensor networks . These...investigate the possibility that these underwater acoustic networks disrupt the behavior of surrounding species of marine mammals. As a consequence of... underwater VHF acoustics , high data rate/short range acoustic communications and networking , and acoustic sensing in the VHF regime. WORK COMPLETED We

78 FR 17418 - Rural Health Information Technology Network Development Grant

Federal Register 2010, 2011, 2012, 2013, 2014

2013-03-21

... Information Technology Network Development Grant AGENCY: Health Resources and Services Administration (HRSA...-competitive replacement award under the Rural Health Information Technology Network Development Grant (RHITND... relinquishing its fiduciary responsibilities for the Rural Health Information Technology Network Development...

How risky are social networking sites? A comparison of places online where youth sexual solicitation and harassment occurs.

PubMed

Ybarra, Michele L; Mitchell, Kimberly J

2008-02-01

Recently, public attention has focused on the possibility that social networking sites such as MySpace and Facebook are being widely used to sexually solicit underage youth, consequently increasing their vulnerability to sexual victimization. Beyond anecdotal accounts, however, whether victimization is more commonly reported in social networking sites is unknown. The Growing up With Media Survey is a national cross-sectional online survey of 1588 youth. Participants were 10- to 15-year-old youth who have used the Internet at least once in the last 6 months. The main outcome measures were unwanted sexual solicitation on the Internet, defined as unwanted requests to talk about sex, provide personal sexual information, and do something sexual, and Internet harassment, defined as rude or mean comments, or spreading of rumors. Fifteen percent of all of the youth reported an unwanted sexual solicitation online in the last year; 4% reported an incident on a social networking site specifically. Thirty-three percent reported an online harassment in the last year; 9% reported an incident on a social networking site specifically. Among targeted youth, solicitations were more commonly reported via instant messaging (43%) and in chat rooms (32%), and harassment was more commonly reported in instant messaging (55%) than through social networking sites (27% and 28%, respectively). Broad claims of victimization risk, at least defined as unwanted sexual solicitation or harassment, associated with social networking sites do not seem justified. Prevention efforts may have a greater impact if they focus on the psychosocial problems of youth instead of a specific Internet application, including funding for online youth outreach programs, school antibullying programs, and online mental health services.

Background Noise of the Aldeia da Serra Region (Portugal) from a temporary broad band network

NASA Astrophysics Data System (ADS)

Wachilala, Piedade; Borges, José; Caldeira, Bento; Bezzeghoud, Mourad

2017-04-01

In this study, we analyse seismic background noise to assess the effect of noise based on the detectability of a temporary network constituted by DOCTAR (Deep Ocean Test Array), who have been deployed in a period between 2011 and 2012 in Portugal mainland, and the Évora permanent seismic station. This network is constituted by 14 digital broadband stations (14 CMG-3ESP and one STS2 sensors) with a flat response between the 60 sec to 50 Hz, 24-bit and 120s to 60Hz respectively. The temporary network was operated in continuous recording mode (three-components) in a region located in the north of the region of Évora, within a radius of about 30 km around the village of Aldeia da Serra, region in which there is an important seismic activity in the context of Portugal mainland. We calculated power spectral densities of background noise for each station/component and compare them with high-noise model and low-noise model of Peterson (1993). We consider different for day and night local and for different periods of the year. Power spectral density estimates show moderate noise levels with all stations falling within the high and low bounds of Peterson (1993). Considering the results of the noise, we estimate the detection limit of each station and consequently the detectability of the network. From this information and taking in attention the events recorded during the period of DOCTAR operation we analyse the improvement promoted by this temporary network regarding the existent seismic networks to the local seismicity study. This work was partially supported by COMPETE 2020 program (POCI-01-0145-FEDER-007690 project). We acknowledge GFZ Potsdam for providing part of the data used in this study.

COM5/443: Health Portals, Search Engines and Intranets: Making order of the chaos - A review article

PubMed Central

Maini, P

1999-01-01

Effective use of technology has led to medical advances that have not only extended life expectancy, but also fuelled an increasingly well informed public's desires to expect more and more from today's healthcare providers. A phenomenal amount of medical information is now present, facilitated by the virtually unrestricted ability to publish on the Internet. The WWW grows by roughly a million pages per day with a significant number devoted to some element of healthcare. As a consequence of the web's rapid, chaotic growth, the resulting network of information lacks organisation and structure and the quest for a method of finding relevant and reliable information quickly is spawning the growth of the Internet Portal Sites. The use of intranets confers some degree of organisation, allowing for structured growth of an organisation's web site but the majority of sites are not sheltered within an intranet. Millions of dollars are being invested in researching the technologies powering search engines and well designed portals, in the hope of imposing some kind of order on the existing chaos. The winner will most likely reap huge financial rewards as advertisers climb on board, hoping to gain massive exposure and the public will undoubtedly gain from relevant and timely answers to their searches and queries. Information is a valuable commodity, but the true value is seen only when it is organised into an accessible and useable form. The coming of age of the Internet has heralded radical changes in the fabric and economics of healthcare and as a consequence our expectations from professionals involved in this industry are greatly increased. Although significant challenges need to be overcome, there are huge benefits to be gained for consumers, although it remains to be seen whether the world becomes a more healthy place.

Framework for Real-Time All-Hazards Global Situational Awareness

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

Omitaomu, Olufemi A; Fernandez, Steven J; Bhaduri, Budhendra L

Information systems play a pivotal role in emergency response by making consequence analysis models based on up-to-date data available to decision makers. While consequence analysis models have been used for years on local scales, their application on national and global scales has been constrained by lack of non-proprietary data. This chapter describes how this has changed using a framework for real-time all-hazards situational awareness called the Energy Awareness and Resiliency Standardized Services (EARSS) as an example. EARSS is a system of systems developed to collect non-proprietary data from diverse open content sources to develop a geodatabase of critical infrastructures allmore » over the world. The EARSS system shows that it is feasible to provide global disaster alerts by producing valuable information such as texting messages about detected hazards, emailing reports about affected areas, estimating an expected number of impacted people and their demographic characteristics, identifying critical infrastructures that may be affected, and analyzing potential downstream effects. This information is provided in real-time to federal agencies and subscribers all over the world for decision making in humanitarian assistance and emergency response. The system also uses live streams of power outages, weather, and satellite surveillance data as events unfold. This, in turn, is combined with other public domain or open content information, such as media reports and postings on social networking websites, for complete coverage of the situation as events unfold. Working with up-to-date information from the EARSS system, emergency responders on the ground could pre-position their staff and resources, such as emergency generators and ice, where they are most needed.« less

Dynamical Graph Theory Networks Methods for the Analysis of Sparse Functional Connectivity Networks and for Determining Pinning Observability in Brain Networks

PubMed Central

Meyer-Bäse, Anke; Roberts, Rodney G.; Illan, Ignacio A.; Meyer-Bäse, Uwe; Lobbes, Marc; Stadlbauer, Andreas; Pinker-Domenig, Katja

2017-01-01

Neuroimaging in combination with graph theory has been successful in analyzing the functional connectome. However almost all analysis are performed based on static graph theory. The derived quantitative graph measures can only describe a snap shot of the disease over time. Neurodegenerative disease evolution is poorly understood and treatment strategies are consequently only of limited efficiency. Fusing modern dynamic graph network theory techniques and modeling strategies at different time scales with pinning observability of complex brain networks will lay the foundation for a transformational paradigm in neurodegnerative diseases research regarding disease evolution at the patient level, treatment response evaluation and revealing some central mechanism in a network that drives alterations in these diseases. We model and analyze brain networks as two-time scale sparse dynamic graph networks with hubs (clusters) representing the fast sub-system and the interconnections between hubs the slow sub-system. Alterations in brain function as seen in dementia can be dynamically modeled by determining the clusters in which disturbance inputs have entered and the impact they have on the large-scale dementia dynamic system. Observing a small fraction of specific nodes in dementia networks such that the others can be recovered is accomplished by the novel concept of pinning observability. In addition, how to control this complex network seems to be crucial in understanding the progressive abnormal neural circuits in many neurodegenerative diseases. Detecting the controlling regions in the networks, which serve as key nodes to control the aberrant dynamics of the networks to a desired state and thus influence the progressive abnormal behavior, will have a huge impact in understanding and developing therapeutic solutions and also will provide useful information about the trajectory of the disease. In this paper, we present the theoretical framework and derive the necessary conditions for (1) area aggregation and time-scale modeling in brain networks and for (2) pinning observability of nodes in dynamic graph networks. Simulation examples are given to illustrate the theoretical concepts. PMID:29051730

Dynamical Graph Theory Networks Methods for the Analysis of Sparse Functional Connectivity Networks and for Determining Pinning Observability in Brain Networks.

PubMed

Meyer-Bäse, Anke; Roberts, Rodney G; Illan, Ignacio A; Meyer-Bäse, Uwe; Lobbes, Marc; Stadlbauer, Andreas; Pinker-Domenig, Katja

2017-01-01

Neuroimaging in combination with graph theory has been successful in analyzing the functional connectome. However almost all analysis are performed based on static graph theory. The derived quantitative graph measures can only describe a snap shot of the disease over time. Neurodegenerative disease evolution is poorly understood and treatment strategies are consequently only of limited efficiency. Fusing modern dynamic graph network theory techniques and modeling strategies at different time scales with pinning observability of complex brain networks will lay the foundation for a transformational paradigm in neurodegnerative diseases research regarding disease evolution at the patient level, treatment response evaluation and revealing some central mechanism in a network that drives alterations in these diseases. We model and analyze brain networks as two-time scale sparse dynamic graph networks with hubs (clusters) representing the fast sub-system and the interconnections between hubs the slow sub-system. Alterations in brain function as seen in dementia can be dynamically modeled by determining the clusters in which disturbance inputs have entered and the impact they have on the large-scale dementia dynamic system. Observing a small fraction of specific nodes in dementia networks such that the others can be recovered is accomplished by the novel concept of pinning observability. In addition, how to control this complex network seems to be crucial in understanding the progressive abnormal neural circuits in many neurodegenerative diseases. Detecting the controlling regions in the networks, which serve as key nodes to control the aberrant dynamics of the networks to a desired state and thus influence the progressive abnormal behavior, will have a huge impact in understanding and developing therapeutic solutions and also will provide useful information about the trajectory of the disease. In this paper, we present the theoretical framework and derive the necessary conditions for (1) area aggregation and time-scale modeling in brain networks and for (2) pinning observability of nodes in dynamic graph networks. Simulation examples are given to illustrate the theoretical concepts.

How "community" matters for how people interact with information: mixed methods study of young men who have sex with other men.

PubMed

Veinot, Tiffany Christine; Meadowbrooke, Chrysta Cathleen; Loveluck, Jimena; Hickok, Andrew; Bauermeister, Jose Artruro

2013-02-21

We lack a systematic portrait of the relationship between community involvement and how people interact with information. Young men who have sex with men (YMSM) are a population for which these relationships are especially salient: their gay community involvement varies and their information technology use is high. YMSM under age 24 are also one of the US populations with the highest risk of HIV/AIDS. To develop, test, and refine a model of gay community involvement (GCI) factors in human-information interaction (HII) as applied to HIV/AIDS information among YMSM, specifically examining the role of Internet use in GCI and HII. Mixed methods included: 1) online questionnaire with 194 YMSM; and 2) qualitative interviews with 19 YMSM with high GCI levels. Recruitment utilized social media, dating websites, health clinics, bars/clubs, and public postings. The survey included questions regarding HIV/AIDS-related information acquisition and use patterns, gay community involvement, risk behaviors, and technology use. For survey data, we tested multiple linear regression models using a series of community- and information-related variables as dependent variables. Independent variables included community- and information-related variables and demographic covariates. We then conducted a recursive path analysis in order to estimate a final model, which we refined through a grounded theory analysis of qualitative interview data. Four community-related variables significantly predicted how people interact with information (HII variables): 1) gay community involvement (GCI), 2) social costs of information seeking, 3) network expertise accessibility, and 4) community relevance. GCI was associated with significantly lower perceived social costs of HIV/AIDS information seeking (R(2)=0.07). GCI and social costs significantly predicted network expertise accessibility (R(2)=0.14). GCI predicted 14% of the variance in community relevance and 9% of the variance in information seeking frequency. Incidental HIV/AIDS information acquisition (IIA) was also significantly predicted by GCI (R(2)=0.16). 28% of the variance in HIV/AIDS information use was explained by community relevance, network expertise access, and both IIA and information seeking. The final path model showed good fit: the RSMEA was 0.054 (90% CI: .000-.101); the Chi-square was non-significant (χ(2)(11)=17.105; P=.105); and the CFI was 0.967. Qualitative findings suggest that the model may be enhanced by including information sharing: organizing events, disseminating messages, encouraging safety, and referring and recommending. Information sharing emerged under conditions of pro-social community value enactment and may have consequences for further HII. YMSM with greater GCI generally used the Internet more, although they chatted online less. HIV/AIDS-related HII and associated technology uses are community-embedded processes. The model provides theoretical mediators that may serve as a focus for intervention: 1) valuing HIV/AIDS information, through believing it is relevant to one's group, and 2) supportive and knowledgeable network members with whom to talk about HIV/AIDS. Pro-social community value endorsement and information sharing may also be important theoretical mediators. Our model could open possibilities for considering how informatics interventions can also be designed as community-level interventions and vice versa.

Nurses' perception and barriers to use of information communication technology in a teaching hospital in Nigeria.

PubMed

Irinoye, Omolola O; Ayandiran, Emmanuel Olufemi; Fakunle, Imoleayo; Mtshali, Ntombifikile

2013-08-01

The impact of information technology on nursing has been a subject of discourse for the latter half of the 20th century and the early part of the 21st. Despite its obvious benefits, adapting information technology to healthcare has been relatively difficult, and rates of use have been limited especially in many developing countries. This quantitative study has shown a generally low usage of information technology among nurses in the study setting. Many of the nurses adjudged themselves as novice in information technology, with 37.8% stating that they had never had formal training in information technology and many rating themselves as possessing little or no skill in the use of spreadsheet, databases, and so on. Many (55.6%) stated that they do not have access to information technology despite the fairly widespread satisfactory perception established among them. Results further showed that unreliable network connections, high work demand, inadequate number of computers, poor access to computers consequent on wrong locations, and poor system design with associated failure to fit work demands are some of the major barriers to the use of information technology in the study setting. These factors therefore need to be taken into consideration in any intervention that seeks to improve the nurses' use of information technology in clinical setting.

34 CFR 668.59 - Consequences of a change in application information.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 34 Education 3 2011-07-01 2011-07-01 false Consequences of a change in application information... Verification of Student Aid Application Information § 668.59 Consequences of a change in application information. (a) For the Federal Pell Grant, ACG, and National SMART Grant programs— (1) Except as provided in...

Hack's relation and optimal channel networks: The elongation of river basins as a consequence of energy minimization

NASA Astrophysics Data System (ADS)

Ijjasz-Vasquez, Ede J.; Bras, Rafael L.; Rodriguez-Iturbe, Ignacio

1993-08-01

As pointed by Hack (1957), river basins tend to become longer and narrower as their size increases. This work shows that this property may be partially regarded as the consequence of competition and minimization of energy expenditure in river basins.

The effect of a loss of model structural detail due to network skeletonization on contamination warning system design: case studies.

PubMed

Davis, Michael J; Janke, Robert

2018-01-04

The effect of limitations in the structural detail available in a network model on contamination warning system (CWS) design was examined in case studies using the original and skeletonized network models for two water distribution systems (WDSs). The skeletonized models were used as proxies for incomplete network models. CWS designs were developed by optimizing sensor placements for worst-case and mean-case contamination events. Designs developed using the skeletonized network models were transplanted into the original network model for evaluation. CWS performance was defined as the number of people who ingest more than some quantity of a contaminant in tap water before the CWS detects the presence of contamination. Lack of structural detail in a network model can result in CWS designs that (1) provide considerably less protection against worst-case contamination events than that obtained when a more complete network model is available and (2) yield substantial underestimates of the consequences associated with a contamination event. Nevertheless, CWSs developed using skeletonized network models can provide useful reductions in consequences for contaminants whose effects are not localized near the injection location. Mean-case designs can yield worst-case performances similar to those for worst-case designs when there is uncertainty in the network model. Improvements in network models for WDSs have the potential to yield significant improvements in CWS designs as well as more realistic evaluations of those designs. Although such improvements would be expected to yield improved CWS performance, the expected improvements in CWS performance have not been quantified previously. The results presented here should be useful to those responsible for the design or implementation of CWSs, particularly managers and engineers in water utilities, and encourage the development of improved network models.

The effect of a loss of model structural detail due to network skeletonization on contamination warning system design: case studies

NASA Astrophysics Data System (ADS)

Davis, Michael J.; Janke, Robert

2018-05-01

The effect of limitations in the structural detail available in a network model on contamination warning system (CWS) design was examined in case studies using the original and skeletonized network models for two water distribution systems (WDSs). The skeletonized models were used as proxies for incomplete network models. CWS designs were developed by optimizing sensor placements for worst-case and mean-case contamination events. Designs developed using the skeletonized network models were transplanted into the original network model for evaluation. CWS performance was defined as the number of people who ingest more than some quantity of a contaminant in tap water before the CWS detects the presence of contamination. Lack of structural detail in a network model can result in CWS designs that (1) provide considerably less protection against worst-case contamination events than that obtained when a more complete network model is available and (2) yield substantial underestimates of the consequences associated with a contamination event. Nevertheless, CWSs developed using skeletonized network models can provide useful reductions in consequences for contaminants whose effects are not localized near the injection location. Mean-case designs can yield worst-case performances similar to those for worst-case designs when there is uncertainty in the network model. Improvements in network models for WDSs have the potential to yield significant improvements in CWS designs as well as more realistic evaluations of those designs. Although such improvements would be expected to yield improved CWS performance, the expected improvements in CWS performance have not been quantified previously. The results presented here should be useful to those responsible for the design or implementation of CWSs, particularly managers and engineers in water utilities, and encourage the development of improved network models.

Assessing the Robustness of Graph Statistics for Network Analysis Under Incomplete Information

DTIC Science & Technology

strategy for dismantling these networks based on their network structure. However, these strategies typically assume complete information about the...combat them with missing information . This thesis analyzes the performance of a variety of network statistics in the context of incomplete information by...leveraging simulation to remove nodes and edges from networks and evaluating the effect this missing information has on our ability to accurately

Differentiable cortical networks for inferences concerning people’s intentions versus physical causality

PubMed Central

Mason, Robert A.; Just, Marcel Adam

2010-01-01

Cortical activity associated with generating an inference was measured using fMRI. Participants read three-sentence passages that differed in whether or not an inference needed to be drawn to understand them. The inference was based on either a protagonist’s intention or a physical consequence of a character’s action. Activation was expected in Theory of Mind brain regions for the passages based on protagonists’ intentions but not for the physical consequence passages. The activation measured in the right temporo-parietal junction was greater in the intentional passages than in the consequence passages, consistent with predictions from a Theory of Mind perspective. In contrast, there was increased occipital activation in the physical inference passages. For both types of passage, the cortical activity related to the reading of the critical inference sentence demonstrated a recruitment of a common inference cortical network. This general inference-related activation appeared bilaterally in the language processing areas (the inferior frontal gyrus, the temporal gyrus, and the angular gyrus), as well as in the medial to superior frontal gyrus, which has been found to be active in Theory of Mind tasks. These findings are consistent with the hypothesis that component areas of the discourse processing network are recruited as needed based on the nature of the inference. A Protagonist monitoring and synthesis network is proposed as a more accurate account for Theory of Mind activation during narrative comprehension. PMID:21229617

Power laws and fragility in flow networks.

PubMed

Shore, Jesse; Chu, Catherine J; Bianchi, Matt T

2013-01-01

What makes economic and ecological networks so unlike other highly skewed networks in their tendency toward turbulence and collapse? Here, we explore the consequences of a defining feature of these networks: their nodes are tied together by flow. We show that flow networks tend to the power law degree distribution (PLDD) due to a self-reinforcing process involving position within the global network structure, and thus present the first random graph model for PLDDs that does not depend on a rich-get-richer function of nodal degree. We also show that in contrast to non-flow networks, PLDD flow networks are dramatically more vulnerable to catastrophic failure than non-PLDD flow networks, a finding with potential explanatory power in our age of resource- and financial-interdependence and turbulence.

It's not about pager replacement: an in-depth look at the interprofessional nature of communication in healthcare.

PubMed

Quan, Sherman D; Wu, Robert C; Rossos, Peter G; Arany, Teri; Groe, Silvi; Morra, Dante; Wong, Brian M; Cavalcanti, Rodrigo; Coke, William; Lau, Francis Y

2013-03-01

Institutions have tried to replace the use of numeric pagers for clinical communication by implementing health information technology (HIT) solutions. However, failing to account for the sociotechnical aspects of HIT or the interplay of technology with existing clinical workflow, culture, and social interactions may create other unintended consequences. To evaluate a Web-based messaging system that allows asynchronous communication between health providers and identify the unintended consequences associated with implementing such technology. Intervention-a Web-based messaging system at the University Health Network to replace numeric paging practices in May 2010. The system facilitated clinical communication on the medical wards for coordinating patient care. Study design-pre-post mixed methods utilizing both quantitative and qualitative measures. Five residents, 8 nurses, 2 pharmacists, and 2 social workers were interviewed. Pre-post interruption-15 residents from 5 clinical teams in both periods. The study compared the type of messages sent to physicians before and after implementation of the Web-based messaging system; a constant comparative analysis of semistructured interviews was used to generate key themes related to unintended consequences. Interruptions increased 233%, from 3 pages received per resident per day pre-implementation to 10 messages received per resident per day post-implementation. Key themes relating to unintended consequences that emerged from the interviews included increase in interruptions, accountability, and tactics to improve personal productivity. Meaningful improvements in clinical communication can occur but require more than just replacing pagers. Introducing HIT without addressing the sociotechnical aspects of HIT that underlie clinical communication can lead to unintended consequences. Copyright © 2013 Society of Hospital Medicine.

Linking social and spatial networks to viral community phylogenetics reveals subtype-specific transmission dynamics in African lions.

PubMed

Fountain-Jones, Nicholas M; Packer, Craig; Troyer, Jennifer L; VanderWaal, Kimberly; Robinson, Stacie; Jacquot, Maude; Craft, Meggan E

2017-10-01

Heterogeneity within pathogen species can have important consequences for how pathogens transmit across landscapes; however, discerning different transmission routes is challenging. Here, we apply both phylodynamic and phylogenetic community ecology techniques to examine the consequences of pathogen heterogeneity on transmission by assessing subtype-specific transmission pathways in a social carnivore. We use comprehensive social and spatial network data to examine transmission pathways for three subtypes of feline immunodeficiency virus (FIV Ple ) in African lions (Panthera leo) at multiple scales in the Serengeti National Park, Tanzania. We used FIV Ple molecular data to examine the role of social organization and lion density in shaping transmission pathways and tested to what extent vertical (i.e., father- and/or mother-offspring relationships) or horizontal (between unrelated individuals) transmission underpinned these patterns for each subtype. Using the same data, we constructed subtype-specific FIV Ple co-occurrence networks and assessed what combination of social networks, spatial networks or co-infection best structured the FIV Ple network. While social organization (i.e., pride) was an important component of FIV Ple transmission pathways at all scales, we find that FIV Ple subtypes exhibited different transmission pathways at within- and between-pride scales. A combination of social and spatial networks, coupled with consideration of subtype co-infection, was likely to be important for FIV Ple transmission for the two major subtypes, but the relative contribution of each factor was strongly subtype-specific. Our study provides evidence that pathogen heterogeneity is important in understanding pathogen transmission, which could have consequences for how endemic pathogens are managed. Furthermore, we demonstrate that community phylogenetic ecology coupled with phylodynamic techniques can reveal insights into the differential evolutionary pressures acting on virus subtypes, which can manifest into landscape-level effects. © 2017 The Authors. Journal of Animal Ecology © 2017 British Ecological Society.

Network Framing of Pest Management Knowledge and Practice

ERIC Educational Resources Information Center

Moore, Keith M.

2008-01-01

Conventional technology transfer is based on the assumption that autonomous individuals independently make behavioral decisions. In contrast, Actor-Network Theory (ANT) suggests that people and technologies are interconnected in ways that reinforce and reproduce some types of knowledge and consequent behavioral practices, but not others. Research…

76 FR 67750 - Homeland Security Information Network Advisory Committee

Federal Register 2010, 2011, 2012, 2013, 2014

2011-11-02

... DEPARTMENT OF HOMELAND SECURITY [Docket No. DHS-2011-0107] Homeland Security Information Network... Information Network Advisory Committee. SUMMARY: The Secretary of Homeland Security has determined that the renewal of the Homeland Security Information Network Advisory Committee (HSINAC) is necessary and in the...

78 FR 7797 - Homeland Security Information Network Advisory Committee (HSINAC)

Federal Register 2010, 2011, 2012, 2013, 2014

2013-02-04

... DEPARTMENT OF HOMELAND SECURITY [Docket No. DHS-2013-0005] Homeland Security Information Network... Committee Meeting. SUMMARY: The Homeland Security Information Network Advisory Committee (HSIN AC) will meet... received by the (Homeland Security Information Network Advisory Committee), go to http://www.regulations...

78 FR 71631 - Committee Name: Homeland Security Information Network Advisory Committee (HSINAC)

Federal Register 2010, 2011, 2012, 2013, 2014

2013-11-29

... Network Advisory Committee (HSINAC) AGENCY: Operation Coordination and Planning/Office of Chief.... SUMMARY: The Homeland Security Information Network Advisory Council (HSINAC) will meet December 17, 2013... , Phone: 202-343-4212. SUPPLEMENTARY INFORMATION: The Homeland Security Information Network Advisory...

78 FR 34665 - Homeland Security Information Network Advisory Committee (HSINAC); Meeting

Federal Register 2010, 2011, 2012, 2013, 2014

2013-06-10

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75 FR 57521 - Networking and Information Technology Research and Development (NITRD) Program: Draft NITRD 2010...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-09-21

... NATIONAL SCIENCE FOUNDATION Networking and Information Technology Research and Development (NITRD...) for Networking and Information Technology Research and Development (NITRD). ACTION: Notice, request.... SUMMARY: With this notice, the National Coordination Office for Networking and Information Technology...

Baby Bell Libraries?--An Update.

ERIC Educational Resources Information Center

Kessler, Jack

1993-01-01

Discusses the emerging three-tiered structure (i.e., the "Baby Bells," network nodes, and information marketers) that will assume responsibility for implementing a new national information network and getting networked information to the public. The role of libraries related to networked information is also considered. (EA)

Memory: Enduring Traces of Perceptual and Reflective Attention

PubMed Central

Chun, Marvin M.; Johnson, Marcia K.

2011-01-01

Attention and memory are typically studied as separate topics, but they are highly intertwined. Here we discuss the relation between memory and two fundamental types of attention: perceptual and reflective. Memory is the persisting consequence of cognitive activities initiated by and/or focused on external information from the environment (perceptual attention) and initiated by and/or focused on internal mental representations (reflective attention). We consider three key questions for advancing a cognitive neuroscience of attention and memory: To what extent do perception and reflection share representational areas? To what extent are the control processes that select, maintain, and manipulate perceptual and reflective information subserved by common areas and networks? During perception and reflection, to what extent are common areas responsible for binding features together to create complex, episodic memories and for reviving them later? Considering similarities and differences in perceptual and reflective attention helps integrate a broad range of findings and raises important unresolved issues. PMID:22099456

Physically Based Virtual Surgery Planning and Simulation Tools for Personal Health Care Systems

NASA Astrophysics Data System (ADS)

Dogan, Firat; Atilgan, Yasemin

The virtual surgery planning and simulation tools have gained a great deal of importance in the last decade in a consequence of increasing capacities at the information technology level. The modern hardware architectures, large scale database systems, grid based computer networks, agile development processes, better 3D visualization and all the other strong aspects of the information technology brings necessary instruments into almost every desk. The last decade’s special software and sophisticated super computer environments are now serving to individual needs inside “tiny smart boxes” for reasonable prices. However, resistance to learning new computerized environments, insufficient training and all the other old habits prevents effective utilization of IT resources by the specialists of the health sector. In this paper, all the aspects of the former and current developments in surgery planning and simulation related tools are presented, future directions and expectations are investigated for better electronic health care systems.

Proto-object categorisation and local gist vision using low-level spatial features.

PubMed

Martins, Jaime A; Rodrigues, J M F; du Buf, J M H

2015-09-01

Object categorisation is a research area with significant challenges, especially in conditions with bad lighting, occlusions, different poses and similar objects. This makes systems that rely on precise information unable to perform efficiently, like a robotic arm that needs to know which objects it can reach. We propose a biologically inspired object detection and categorisation framework that relies on robust low-level object shape. Using only edge conspicuity and disparity features for scene figure-ground segregation and object categorisation, a trained neural network classifier can quickly categorise broad object families and consequently bootstrap a low-level scene gist system. We argue that similar processing is possibly located in the parietal pathway leading to the LIP cortex and, via areas V5/MT and MST, providing useful information to the superior colliculus for eye and head control. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Temporal and spatial distribution of isotopes in river water in Central Europe: 50 years experience with the Austrian network of isotopes in rivers.

PubMed

Rank, Dieter; Wyhlidal, Stefan; Schott, Katharina; Weigand, Silvia; Oblin, Armin

2018-05-01

The Austrian network of isotopes in rivers comprises about 15 sampling locations and has been operated since 1976. The Danube isotope time series goes back to 1963. The isotopic composition of river water in Central Europe is mainly governed by the isotopic composition of precipitation in the catchment area; evaporation effects play only a minor role. Short-term and long-term isotope signals in precipitation are thus transmitted through the whole catchment. The influence of climatic changes has become observable in the long-term stable isotope time series of precipitation and surface waters. Environmental 3 H values were around 8 TU in 2015, short-term 3 H pulses up to about 80 TU in the rivers Danube and March were a consequence of releases from nuclear power plants. The complete isotope data series of this network will be included in the Global Network of Isotopes in Rivers database of the International Atomic Energy Agency (IAEA) in 2017. This article comprises a review of 50 years isotope monitoring on rivers and is also intended to provide base information on the (isotope-)hydrological conditions in Central Europe specifically for the end-users of these data, e.g. for modelling hydrological processes. Furthermore, this paper includes the 2006-2015 supplement adding to the Danube isotope set published earlier.

Adding seismic broadband analysis to characterize Andean backarc seismicity in Argentina

NASA Astrophysics Data System (ADS)

Alvarado, P.; Giuliano, A.; Beck, S.; Zandt, G.

2007-05-01

Characterization of the highly seismically active Andean backarc is crucial for assessment of earthquake hazards in western Argentina. Moderate-to-large crustal earthquakes have caused several deaths, damage and drastic economic consequences in Argentinean history. We have studied the Andean backarc crust between 30°S and 36°S using seismic broadband data available from a previous ("the CHARGE") IRIS-PASSCAL experiment. We collected more than 12 terabytes of continuous seismic data from 22 broadband instruments deployed across Chile and Argentina during 1.5 years. Using free software we modeled full regional broadband waveforms and obtained seismic moment tensor inversions of crustal earthquakes testing for the best focal depth for each event. We also mapped differences in the Andean backarc crustal structure and found a clear correlation with different types of crustal seismicity (i.e. focal depths, focal mechanisms, magnitudes and frequencies of occurrence) and previously mapped terrane boundaries. We now plan to use the same methodology to study other regions in Argentina using near-real time broadband data available from the national seismic (INPRES) network and global seismic networks operating in the region. We will re-design the national seismic network to optimize short-period and broadband seismic station coverage for different network purposes. This work is an international effort that involves researchers and students from universities and national government agencies with the goal of providing more information about earthquake hazards in western Argentina.

A Type-2 fuzzy data fusion approach for building reliable weighted protein interaction networks with application in protein complex detection.

PubMed

Mehranfar, Adele; Ghadiri, Nasser; Kouhsar, Morteza; Golshani, Ashkan

2017-09-01

Detecting the protein complexes is an important task in analyzing the protein interaction networks. Although many algorithms predict protein complexes in different ways, surveys on the interaction networks indicate that about 50% of detected interactions are false positives. Consequently, the accuracy of existing methods needs to be improved. In this paper we propose a novel algorithm to detect the protein complexes in 'noisy' protein interaction data. First, we integrate several biological data sources to determine the reliability of each interaction and determine more accurate weights for the interactions. A data fusion component is used for this step, based on the interval type-2 fuzzy voter that provides an efficient combination of the information sources. This fusion component detects the errors and diminishes their effect on the detection protein complexes. So in the first step, the reliability scores have been assigned for every interaction in the network. In the second step, we have proposed a general protein complex detection algorithm by exploiting and adopting the strong points of other algorithms and existing hypotheses regarding real complexes. Finally, the proposed method has been applied for the yeast interaction datasets for predicting the interactions. The results show that our framework has a better performance regarding precision and F-measure than the existing approaches. Copyright © 2017 Elsevier Ltd. All rights reserved.

New scaling relation for information transfer in biological networks

PubMed Central

Kim, Hyunju; Davies, Paul; Walker, Sara Imari

2015-01-01

We quantify characteristics of the informational architecture of two representative biological networks: the Boolean network model for the cell-cycle regulatory network of the fission yeast Schizosaccharomyces pombe (Davidich et al. 2008 PLoS ONE 3, e1672 (doi:10.1371/journal.pone.0001672)) and that of the budding yeast Saccharomyces cerevisiae (Li et al. 2004 Proc. Natl Acad. Sci. USA 101, 4781–4786 (doi:10.1073/pnas.0305937101)). We compare our results for these biological networks with the same analysis performed on ensembles of two different types of random networks: Erdös–Rényi and scale-free. We show that both biological networks share features in common that are not shared by either random network ensemble. In particular, the biological networks in our study process more information than the random networks on average. Both biological networks also exhibit a scaling relation in information transferred between nodes that distinguishes them from random, where the biological networks stand out as distinct even when compared with random networks that share important topological properties, such as degree distribution, with the biological network. We show that the most biologically distinct regime of this scaling relation is associated with a subset of control nodes that regulate the dynamics and function of each respective biological network. Information processing in biological networks is therefore interpreted as an emergent property of topology (causal structure) and dynamics (function). Our results demonstrate quantitatively how the informational architecture of biologically evolved networks can distinguish them from other classes of network architecture that do not share the same informational properties. PMID:26701883

Social adaptation in multi-agent model of linguistic categorization is affected by network information flow.

PubMed

Zubek, Julian; Denkiewicz, Michał; Barański, Juliusz; Wróblewski, Przemysław; Rączaszek-Leonardi, Joanna; Plewczynski, Dariusz

2017-01-01

This paper explores how information flow properties of a network affect the formation of categories shared between individuals, who are communicating through that network. Our work is based on the established multi-agent model of the emergence of linguistic categories grounded in external environment. We study how network information propagation efficiency and the direction of information flow affect categorization by performing simulations with idealized network topologies optimizing certain network centrality measures. We measure dynamic social adaptation when either network topology or environment is subject to change during the experiment, and the system has to adapt to new conditions. We find that both decentralized network topology efficient in information propagation and the presence of central authority (information flow from the center to peripheries) are beneficial for the formation of global agreement between agents. Systems with central authority cope well with network topology change, but are less robust in the case of environment change. These findings help to understand which network properties affect processes of social adaptation. They are important to inform the debate on the advantages and disadvantages of centralized systems.

Social adaptation in multi-agent model of linguistic categorization is affected by network information flow

PubMed Central

Denkiewicz, Michał; Barański, Juliusz; Wróblewski, Przemysław; Rączaszek-Leonardi, Joanna; Plewczynski, Dariusz

2017-01-01

This paper explores how information flow properties of a network affect the formation of categories shared between individuals, who are communicating through that network. Our work is based on the established multi-agent model of the emergence of linguistic categories grounded in external environment. We study how network information propagation efficiency and the direction of information flow affect categorization by performing simulations with idealized network topologies optimizing certain network centrality measures. We measure dynamic social adaptation when either network topology or environment is subject to change during the experiment, and the system has to adapt to new conditions. We find that both decentralized network topology efficient in information propagation and the presence of central authority (information flow from the center to peripheries) are beneficial for the formation of global agreement between agents. Systems with central authority cope well with network topology change, but are less robust in the case of environment change. These findings help to understand which network properties affect processes of social adaptation. They are important to inform the debate on the advantages and disadvantages of centralized systems. PMID:28809957

47 CFR 64.2011 - Notification of customer proprietary network information security breaches.

Code of Federal Regulations, 2011 CFR

2011-10-01

... 47 Telecommunication 3 2011-10-01 2011-10-01 false Notification of customer proprietary network information security breaches. 64.2011 Section 64.2011 Telecommunication FEDERAL COMMUNICATIONS COMMISSION... Proprietary Network Information § 64.2011 Notification of customer proprietary network information security...

47 CFR 64.2011 - Notification of customer proprietary network information security breaches.

Code of Federal Regulations, 2010 CFR

2010-10-01

... 47 Telecommunication 3 2010-10-01 2010-10-01 false Notification of customer proprietary network information security breaches. 64.2011 Section 64.2011 Telecommunication FEDERAL COMMUNICATIONS COMMISSION... Proprietary Network Information § 64.2011 Notification of customer proprietary network information security...

47 CFR 64.2011 - Notification of customer proprietary network information security breaches.

Code of Federal Regulations, 2013 CFR

2013-10-01

... Proprietary Network Information § 64.2011 Notification of customer proprietary network information security... 47 Telecommunication 3 2013-10-01 2013-10-01 false Notification of customer proprietary network information security breaches. 64.2011 Section 64.2011 Telecommunication FEDERAL COMMUNICATIONS COMMISSION...

47 CFR 64.5111 - Notification of customer proprietary network information security breaches.

Code of Federal Regulations, 2013 CFR

2013-10-01

... Proprietary Network Information. § 64.5111 Notification of customer proprietary network information security... 47 Telecommunication 3 2013-10-01 2013-10-01 false Notification of customer proprietary network information security breaches. 64.5111 Section 64.5111 Telecommunication FEDERAL COMMUNICATIONS COMMISSION...

47 CFR 64.5111 - Notification of customer proprietary network information security breaches.

Code of Federal Regulations, 2014 CFR

2014-10-01

... Proprietary Network Information. § 64.5111 Notification of customer proprietary network information security... 47 Telecommunication 3 2014-10-01 2014-10-01 false Notification of customer proprietary network information security breaches. 64.5111 Section 64.5111 Telecommunication FEDERAL COMMUNICATIONS COMMISSION...

47 CFR 64.2011 - Notification of customer proprietary network information security breaches.

Code of Federal Regulations, 2014 CFR

2014-10-01

... Proprietary Network Information § 64.2011 Notification of customer proprietary network information security... 47 Telecommunication 3 2014-10-01 2014-10-01 false Notification of customer proprietary network information security breaches. 64.2011 Section 64.2011 Telecommunication FEDERAL COMMUNICATIONS COMMISSION...

47 CFR 64.2011 - Notification of customer proprietary network information security breaches.

Code of Federal Regulations, 2012 CFR

2012-10-01

... Proprietary Network Information § 64.2011 Notification of customer proprietary network information security... 47 Telecommunication 3 2012-10-01 2012-10-01 false Notification of customer proprietary network information security breaches. 64.2011 Section 64.2011 Telecommunication FEDERAL COMMUNICATIONS COMMISSION...

Trophic groups and modules: two levels of group detection in food webs.

PubMed

Gauzens, Benoit; Thébault, Elisa; Lacroix, Gérard; Legendre, Stéphane

2015-05-06

Within food webs, species can be partitioned into groups according to various criteria. Two notions have received particular attention: trophic groups (TGs), which have been used for decades in the ecological literature, and more recently, modules. The relationship between these two group concepts remains unknown in empirical food webs. While recent developments in network theory have led to efficient methods for detecting modules in food webs, the determination of TGs (groups of species that are functionally similar) is largely based on subjective expert knowledge. We develop a novel algorithm for TG detection. We apply this method to empirical food webs and show that aggregation into TGs allows for the simplification of food webs while preserving their information content. Furthermore, we reveal a two-level hierarchical structure where modules partition food webs into large bottom-top trophic pathways, whereas TGs further partition these pathways into groups of species with similar trophic connections. This provides new perspectives for the study of dynamical and functional consequences of food-web structure, bridging topological and dynamical analysis. TGs have a clear ecological meaning and are found to provide a trade-off between network complexity and information loss. © 2015 The Author(s) Published by the Royal Society. All rights reserved.

Fusing Panchromatic and SWIR Bands Based on Cnn - a Preliminary Study Over WORLDVIEW-3 Datasets

NASA Astrophysics Data System (ADS)

Guo, M.; Ma, H.; Bao, Y.; Wang, L.

2018-04-01

The traditional fusion methods are based on the fact that the spectral ranges of the Panchromatic (PAN) and multispectral bands (MS) are almost overlapping. In this paper, we propose a new pan-sharpening method for the fusion of PAN and SWIR (short-wave infrared) bands, whose spectral coverages are not overlapping. This problem is addressed with a convolutional neural network (CNN), which is trained by WorldView-3 dataset. CNN can learn the complex relationship among bands, and thus alleviate spectral distortion. Consequently, in our network, we use the simple three-layer basic architecture with 16 × 16 kernels to conduct the experiment. Every layer use different receptive field. The first two layers compute 512 feature maps by using the 16 × 16 and 1 × 1 receptive field respectively and the third layer with a 8 × 8 receptive field. The fusion results are optimized by continuous training. As for assessment, four evaluation indexes including Entropy, CC, SAM and UIQI are selected built on subjective visual effect and quantitative evaluation. The preliminary experimental results demonstrate that the fusion algorithms can effectively enhance the spatial information. Unfortunately, the fusion image has spectral distortion, it cannot maintain the spectral information of the SWIR image.

Surveying multidisciplinary aspects in real-time distributed coding for Wireless Sensor Networks.

PubMed

Braccini, Carlo; Davoli, Franco; Marchese, Mario; Mongelli, Maurizio

2015-01-27

Wireless Sensor Networks (WSNs), where a multiplicity of sensors observe a physical phenomenon and transmit their measurements to one or more sinks, pertain to the class of multi-terminal source and channel coding problems of Information Theory. In this category, "real-time" coding is often encountered for WSNs, referring to the problem of finding the minimum distortion (according to a given measure), under transmission power constraints, attainable by encoding and decoding functions, with stringent limits on delay and complexity. On the other hand, the Decision Theory approach seeks to determine the optimal coding/decoding strategies or some of their structural properties. Since encoder(s) and decoder(s) possess different information, though sharing a common goal, the setting here is that of Team Decision Theory. A more pragmatic vision rooted in Signal Processing consists of fixing the form of the coding strategies (e.g., to linear functions) and, consequently, finding the corresponding optimal decoding strategies and the achievable distortion, generally by applying parametric optimization techniques. All approaches have a long history of past investigations and recent results. The goal of the present paper is to provide the taxonomy of the various formulations, a survey of the vast related literature, examples from the authors' own research, and some highlights on the inter-play of the different theories.

How multiple social networks affect user awareness: The information diffusion process in multiplex networks

NASA Astrophysics Data System (ADS)

Li, Weihua; Tang, Shaoting; Fang, Wenyi; Guo, Quantong; Zhang, Xiao; Zheng, Zhiming

2015-10-01

The information diffusion process in single complex networks has been extensively studied, especially for modeling the spreading activities in online social networks. However, individuals usually use multiple social networks at the same time, and can share the information they have learned from one social network to another. This phenomenon gives rise to a new diffusion process on multiplex networks with more than one network layer. In this paper we account for this multiplex network spreading by proposing a model of information diffusion in two-layer multiplex networks. We develop a theoretical framework using bond percolation and cascading failure to describe the intralayer and interlayer diffusion. This allows us to obtain analytical solutions for the fraction of informed individuals as a function of transmissibility T and the interlayer transmission rate θ . Simulation results show that interaction between layers can greatly enhance the information diffusion process. And explosive diffusion can occur even if the transmissibility of the focal layer is under the critical threshold, due to interlayer transmission.

Information Diffusion in Facebook-Like Social Networks Under Information Overload

NASA Astrophysics Data System (ADS)

Li, Pei; Xing, Kai; Wang, Dapeng; Zhang, Xin; Wang, Hui

2013-07-01

Research on social networks has received remarkable attention, since many people use social networks to broadcast information and stay connected with their friends. However, due to the information overload in social networks, it becomes increasingly difficult for users to find useful information. This paper takes Facebook-like social networks into account, and models the process of information diffusion under information overload. The term view scope is introduced to model the user information-processing capability under information overload, and the average number of times a message appears in view scopes after it is generated is proposed to characterize the information diffusion efficiency. Through theoretical analysis, we find that factors such as network structure and view scope number have no impact on the information diffusion efficiency, which is a surprising result. To verify the results, we conduct simulations and provide the simulation results, which are consistent with the theoretical analysis results perfectly.

Expanding the occupational health methodology: A concatenated artificial neural network approach to model the burnout process in Chinese nurses.

PubMed

Ladstätter, Felix; Garrosa, Eva; Moreno-Jiménez, Bernardo; Ponsoda, Vicente; Reales Aviles, José Manuel; Dai, Junming

2016-01-01

Artificial neural networks are sophisticated modelling and prediction tools capable of extracting complex, non-linear relationships between predictor (input) and predicted (output) variables. This study explores this capacity by modelling non-linearities in the hardiness-modulated burnout process with a neural network. Specifically, two multi-layer feed-forward artificial neural networks are concatenated in an attempt to model the composite non-linear burnout process. Sensitivity analysis, a Monte Carlo-based global simulation technique, is then utilised to examine the first-order effects of the predictor variables on the burnout sub-dimensions and consequences. Results show that (1) this concatenated artificial neural network approach is feasible to model the burnout process, (2) sensitivity analysis is a prolific method to study the relative importance of predictor variables and (3) the relationships among variables involved in the development of burnout and its consequences are to different degrees non-linear. Many relationships among variables (e.g., stressors and strains) are not linear, yet researchers use linear methods such as Pearson correlation or linear regression to analyse these relationships. Artificial neural network analysis is an innovative method to analyse non-linear relationships and in combination with sensitivity analysis superior to linear methods.

Dynamic information routing in complex networks

PubMed Central

Kirst, Christoph; Timme, Marc; Battaglia, Demian

2016-01-01

Flexible information routing fundamentally underlies the function of many biological and artificial networks. Yet, how such systems may specifically communicate and dynamically route information is not well understood. Here we identify a generic mechanism to route information on top of collective dynamical reference states in complex networks. Switching between collective dynamics induces flexible reorganization of information sharing and routing patterns, as quantified by delayed mutual information and transfer entropy measures between activities of a network's units. We demonstrate the power of this mechanism specifically for oscillatory dynamics and analyse how individual unit properties, the network topology and external inputs co-act to systematically organize information routing. For multi-scale, modular architectures, we resolve routing patterns at all levels. Interestingly, local interventions within one sub-network may remotely determine nonlocal network-wide communication. These results help understanding and designing information routing patterns across systems where collective dynamics co-occurs with a communication function. PMID:27067257

Is U.S. climatic diversity well represented within the existing federal protection network?

Treesearch

Enric Batllori; Carol Miller; Marc-Andre Parisien; Sean A. Parks; Max A. Moritz

2014-01-01

Establishing protection networks to ensure that biodiversity and associated ecosystem services persist under changing environments is a major challenge for conservation planning. The potential consequences of altered climates for the structure and function of ecosystems necessitates new and complementary approaches be incorporated into traditional conservation plans....

Environmental monitoring network for India

Treesearch

P.V. Sundareshwar; R. Murtugudde; G. Srinivasan; S. Singh; K.J. Ramesh; R. Ramesh; S.B. Verma; D. Agarwal; D. Baldocchi; C.K. Baru; K.K. Baruah; G.R. Chowdhury; V.K. Dadhwal; C.B.S. Dutt; J. Fuentes; Prabhat Gupta; W.W. Hardgrove; M. Howard; C.S. Jha; S. Lal; W.K. Michener; A.P. Mitra; J.T. Morris; R.R. Myneni; M. Naja; R. Nemani; R. Purvaja; S. Raha; S.K. Santhana Vanan; M. Sharma; A. Subramaniam; R. Sukumar; R.R. Twilley; P.R. Zimmerman

2007-01-01

Understanding the consequences of global environmental change and its mitigation will require an integrated global effort of comprehensive long-term data collection, synthesis, and action (1). The last decade has seen a dramatic global increase in the number of networked monitoring sites. For example, FLUXNET is a global collection of >300 micrometeorological...

Social Capital and Health in a Digital Society

ERIC Educational Resources Information Center

Sharif, Behjat A.

2007-01-01

Quality of life is directly influenced by the quality of social relationships. Social capital, a reflection of the cohesiveness of social networks, is considered a significant determinant of health outcomes. Among social beings, lack of quality social connections correlates with poor health consequences. Membership in social networks and social…

Envisioning, quantifying, and managing thermal regimes on river networks

Treesearch

E. Ashley Steel; Timothy J. Beechie; Christian E. Torgersen; Aimee H. Fullerton

2017-01-01

Water temperatures fluctuate in time and space, creating diverse thermal regimes on river networks. Temporal variability in these thermal landscapes has important biological and ecological consequences because of nonlinearities in physiological reactions; spatial diversity in thermal landscapes provides aquatic organisms with options to maximize growth and survival....

47 CFR 64.2005 - Use of customer proprietary network information without customer approval.

Code of Federal Regulations, 2010 CFR

2010-10-01

... 47 Telecommunication 3 2010-10-01 2010-10-01 false Use of customer proprietary network information without customer approval. 64.2005 Section 64.2005 Telecommunication FEDERAL COMMUNICATIONS COMMISSION... Proprietary Network Information § 64.2005 Use of customer proprietary network information without customer...

77 FR 33229 - Notice of Proposed Information Collection: Comment Request; National Resource Network

Federal Register 2010, 2011, 2012, 2013, 2014

2012-06-05

... Information Collection: Comment Request; National Resource Network AGENCY: Office of the Assistant Secretary... information: Title of Proposal: National Resource Network. OMB Control Number, if applicable: None... and reporting information related to the proposed National Resource Network. The U.S. Department of...

47 CFR 64.2005 - Use of customer proprietary network information without customer approval.

Code of Federal Regulations, 2011 CFR

2011-10-01

... 47 Telecommunication 3 2011-10-01 2011-10-01 false Use of customer proprietary network information without customer approval. 64.2005 Section 64.2005 Telecommunication FEDERAL COMMUNICATIONS COMMISSION... Proprietary Network Information § 64.2005 Use of customer proprietary network information without customer...

Effects of awareness diffusion and self-initiated awareness behavior on epidemic spreading - An approach based on multiplex networks

NASA Astrophysics Data System (ADS)

Kan, Jia-Qian; Zhang, Hai-Feng

2017-03-01

In this paper, we study the interplay between the epidemic spreading and the diffusion of awareness in multiplex networks. In the model, an infectious disease can spread in one network representing the paths of epidemic spreading (contact network), leading to the diffusion of awareness in the other network (information network), and then the diffusion of awareness will cause individuals to take social distances, which in turn affects the epidemic spreading. As for the diffusion of awareness, we assume that, on the one hand, individuals can be informed by other aware neighbors in information network, on the other hand, the susceptible individuals can be self-awareness induced by the infected neighbors in the contact networks (local information) or mass media (global information). Through Markov chain approach and numerical computations, we find that the density of infected individuals and the epidemic threshold can be affected by the structures of the two networks and the effective transmission rate of the awareness. However, we prove that though the introduction of the self-awareness can lower the density of infection, which cannot increase the epidemic threshold no matter of the local information or global information. Our finding is remarkably different to many previous results on single-layer network: local information based behavioral response can alter the epidemic threshold. Furthermore, our results indicate that the nodes with more neighbors (hub nodes) in information networks are easier to be informed, as a result, their risk of infection in contact networks can be effectively reduced.

SOS, the formidable strategy of bacteria against aggressions.

PubMed

Baharoglu, Zeynep; Mazel, Didier

2014-11-01

The presence of an abnormal amount of single-stranded DNA in the bacterial cell constitutes a genotoxic alarm signal that induces the SOS response, a broad regulatory network found in most bacterial species to address DNA damage. The aim of this review was to point out that beyond being a repair process, SOS induction leads to a very strong but transient response to genotoxic stress, during which bacteria can rearrange and mutate their genome, induce several phenotypic changes through differential regulation of genes, and sometimes acquire characteristics that potentiate bacterial survival and adaptation to changing environments. We review here the causes and consequences of SOS induction, but also how this response can be modulated under various circumstances and how it is connected to the network of other important stress responses. In the first section, we review articles describing the induction of the SOS response at the molecular level. The second section discusses consequences of this induction in terms of DNA repair, changes in the genome and gene expression, and sharing of genomic information, with their effects on the bacteria's life and evolution. The third section is about the fine tuning of this response to fit with the bacteria's 'needs'. Finally, we discuss recent findings linking the SOS response to other stress responses. Under these perspectives, SOS can be perceived as a powerful bacterial strategy against aggressions. © 2014 Federation of European Microbiological Societies. Published by John Wiley & Sons Ltd. All rights reserved.

Quasirandom geometric networks from low-discrepancy sequences

NASA Astrophysics Data System (ADS)

Estrada, Ernesto

2017-08-01

We define quasirandom geometric networks using low-discrepancy sequences, such as Halton, Sobol, and Niederreiter. The networks are built in d dimensions by considering the d -tuples of digits generated by these sequences as the coordinates of the vertices of the networks in a d -dimensional Id unit hypercube. Then, two vertices are connected by an edge if they are at a distance smaller than a connection radius. We investigate computationally 11 network-theoretic properties of two-dimensional quasirandom networks and compare them with analogous random geometric networks. We also study their degree distribution and their spectral density distributions. We conclude from this intensive computational study that in terms of the uniformity of the distribution of the vertices in the unit square, the quasirandom networks look more random than the random geometric networks. We include an analysis of potential strategies for generating higher-dimensional quasirandom networks, where it is know that some of the low-discrepancy sequences are highly correlated. In this respect, we conclude that up to dimension 20, the use of scrambling, skipping and leaping strategies generate quasirandom networks with the desired properties of uniformity. Finally, we consider a diffusive process taking place on the nodes and edges of the quasirandom and random geometric graphs. We show that the diffusion time is shorter in the quasirandom graphs as a consequence of their larger structural homogeneity. In the random geometric graphs the diffusion produces clusters of concentration that make the process more slow. Such clusters are a direct consequence of the heterogeneous and irregular distribution of the nodes in the unit square in which the generation of random geometric graphs is based on.

Supervised Detection of Anomalous Light Curves in Massive Astronomical Catalogs

NASA Astrophysics Data System (ADS)

Nun, Isadora; Pichara, Karim; Protopapas, Pavlos; Kim, Dae-Won

2014-09-01

The development of synoptic sky surveys has led to a massive amount of data for which resources needed for analysis are beyond human capabilities. In order to process this information and to extract all possible knowledge, machine learning techniques become necessary. Here we present a new methodology to automatically discover unknown variable objects in large astronomical catalogs. With the aim of taking full advantage of all information we have about known objects, our method is based on a supervised algorithm. In particular, we train a random forest classifier using known variability classes of objects and obtain votes for each of the objects in the training set. We then model this voting distribution with a Bayesian network and obtain the joint voting distribution among the training objects. Consequently, an unknown object is considered as an outlier insofar it has a low joint probability. By leaving out one of the classes on the training set, we perform a validity test and show that when the random forest classifier attempts to classify unknown light curves (the class left out), it votes with an unusual distribution among the classes. This rare voting is detected by the Bayesian network and expressed as a low joint probability. Our method is suitable for exploring massive data sets given that the training process is performed offline. We tested our algorithm on 20 million light curves from the MACHO catalog and generated a list of anomalous candidates. After analysis, we divided the candidates into two main classes of outliers: artifacts and intrinsic outliers. Artifacts were principally due to air mass variation, seasonal variation, bad calibration, or instrumental errors and were consequently removed from our outlier list and added to the training set. After retraining, we selected about 4000 objects, which we passed to a post-analysis stage by performing a cross-match with all publicly available catalogs. Within these candidates we identified certain known but rare objects such as eclipsing Cepheids, blue variables, cataclysmic variables, and X-ray sources. For some outliers there was no additional information. Among them we identified three unknown variability types and a few individual outliers that will be followed up in order to perform a deeper analysis.

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

Nun, Isadora; Pichara, Karim; Protopapas, Pavlos

The development of synoptic sky surveys has led to a massive amount of data for which resources needed for analysis are beyond human capabilities. In order to process this information and to extract all possible knowledge, machine learning techniques become necessary. Here we present a new methodology to automatically discover unknown variable objects in large astronomical catalogs. With the aim of taking full advantage of all information we have about known objects, our method is based on a supervised algorithm. In particular, we train a random forest classifier using known variability classes of objects and obtain votes for each ofmore » the objects in the training set. We then model this voting distribution with a Bayesian network and obtain the joint voting distribution among the training objects. Consequently, an unknown object is considered as an outlier insofar it has a low joint probability. By leaving out one of the classes on the training set, we perform a validity test and show that when the random forest classifier attempts to classify unknown light curves (the class left out), it votes with an unusual distribution among the classes. This rare voting is detected by the Bayesian network and expressed as a low joint probability. Our method is suitable for exploring massive data sets given that the training process is performed offline. We tested our algorithm on 20 million light curves from the MACHO catalog and generated a list of anomalous candidates. After analysis, we divided the candidates into two main classes of outliers: artifacts and intrinsic outliers. Artifacts were principally due to air mass variation, seasonal variation, bad calibration, or instrumental errors and were consequently removed from our outlier list and added to the training set. After retraining, we selected about 4000 objects, which we passed to a post-analysis stage by performing a cross-match with all publicly available catalogs. Within these candidates we identified certain known but rare objects such as eclipsing Cepheids, blue variables, cataclysmic variables, and X-ray sources. For some outliers there was no additional information. Among them we identified three unknown variability types and a few individual outliers that will be followed up in order to perform a deeper analysis.« less

Translating research into maternal health care policy: a qualitative case study of the use of evidence in policies for the treatment of eclampsia and pre-eclampsia in South Africa

PubMed Central

Daniels, Karen; Lewin, Simon

2008-01-01

Background Few empirical studies of research utilisation have been conducted in low and middle income countries. This paper explores how research information, in particular findings from randomised controlled trials and systematic reviews, informed policy making and clinical guideline development for the use of magnesium sulphate in the treatment of eclampsia and pre-eclampsia in South Africa. Methods A qualitative case-study approach was used to examine the policy process. This included a literature review, a policy document review, a timeline of key events and the collection and analysis of 15 interviews with policy makers and academic clinicians involved in these policy processes and sampled using a purposive approach. The data was analysed thematically and explored theoretically through the literature on agenda setting and the policy making process. Results Prior to 1994 there was no national maternal care policy in South Africa. Consequently each tertiary level institution developed its own care guidelines and these recommended a range of approaches to the management of pre-eclampsia and eclampsia. The subsequent emergence of new national policies for maternal care, including for the treatment of pre-eclampsia and eclampsia, was informed by evidence from randomised controlled trials and systematic reviews. This outcome was influenced by a number of factors. The change to a democratic government in the mid 1990s, and the health reforms that followed, created opportunities for maternal health care policy development. The new government was open to academic involvement in policy making and recruited academics from local networks into key policy making positions in the National Department of Health. The local academic obstetric network, which placed high value on evidence-based practice, brought these values into the policy process and was also linked strongly to international evidence based medicine networks. Within this context of openness to policy development, local researchers acted as policy entrepreneurs, bringing attention to priority health issues, and to the use of research evidence in addressing these. This resulted in the new national maternity care guidelines being informed by evidence from randomised controlled trials and recommending explicitly the use of magnesium sulphate for the management of eclampsia. Conclusion Networks of researchers were important not only in using research information to shape policy but also in placing issues on the policy agenda. A policy context which created a window of opportunity for new research-informed policy development was also crucial. PMID:19091083

Management of ATM-based networks supporting multimedia medical information systems

NASA Astrophysics Data System (ADS)

Whitman, Robert A.; Blaine, G. James; Fritz, Kevin; Goodgold, Ken; Heisinger, Patrick

1997-05-01

Medical information systems are acquiring the ability to collect and deliver many different types of medical information. In support of the increased network demands necessitated by these expanded capabilities, asynchronous transfer mode (ATM) based networks are being deployed in medical care systems. While ATM supplies a much greater line rate than currently deployed networks, the management and standards surrounding ATM are yet to mature. This paper explores the management and control issues surrounding an ATM network supporting medical information systems, and examines how management impacts network performance and robustness. A multivendor ATM network at the BJC Health System/Washington University and the applications using the network are discussed. Performance information for specific applications is presented and analyzed. Network management's influence on application reliability is outlined. The information collected is used to show how ATM network standards and management tools influence network reliability and performance. Performance of current applications using the ATM network is discussed. Special attention is given to issues encountered in implementation of hypertext transfer protocol over ATM internet protocol (IP) communications. A classical IP ATM implementation yields greater than twenty percent higher network performance over LANE. Maximum performance for a host's suite of applications can be obtained by establishing multiple individually engineered IP links through its ATM network connection.

47 CFR 64.2008 - Notice required for use of customer proprietary network information.

Code of Federal Regulations, 2011 CFR

2011-10-01

... 47 Telecommunication 3 2011-10-01 2011-10-01 false Notice required for use of customer proprietary network information. 64.2008 Section 64.2008 Telecommunication FEDERAL COMMUNICATIONS COMMISSION... Proprietary Network Information § 64.2008 Notice required for use of customer proprietary network information...

47 CFR 64.2008 - Notice required for use of customer proprietary network information.

Code of Federal Regulations, 2010 CFR

2010-10-01

... 47 Telecommunication 3 2010-10-01 2010-10-01 false Notice required for use of customer proprietary network information. 64.2008 Section 64.2008 Telecommunication FEDERAL COMMUNICATIONS COMMISSION... Proprietary Network Information § 64.2008 Notice required for use of customer proprietary network information...

75 FR 44800 - Notice of Meeting of the Homeland Security Information Network Advisory Committee, Tuesday...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-07-29

... DEPARTMENT OF HOMELAND SECURITY Notice of Meeting of the Homeland Security Information Network... Security. ACTION: Notice of open meeting. SUMMARY: The Homeland Security Information Network Advisory... (Pub. L. 92-463). The mission of the Homeland Security Information Network Advisory Committee is to...

Sailor: Maryland's Online Public Information Network. Sailor Network Assessment Final Report: Findings and Future Sailor Network Development.

ERIC Educational Resources Information Center

Bertot, John Carlo; McClure, Charles R.

This report describes the results of an assessment of Sailor, Maryland's Online Public Information Network, which provides statewide Internet connection to 100% of Maryland public libraries. The concept of a "statewide networked environment" includes information services, products, hardware and software, telecommunications…

Information Security and Privacy in Network Environments.

ERIC Educational Resources Information Center

Congress of the U.S., Washington, DC. Office of Technology Assessment.

The use of information networks for business and government is expanding enormously. Government use of networks features prominently in plans to make government more efficient, effective, and responsive. But the transformation brought about by the networking also raises new concerns for the security and privacy of networked information. This…

An information dimension of weighted complex networks

NASA Astrophysics Data System (ADS)

Wen, Tao; Jiang, Wen

2018-07-01

The fractal and self-similarity are important properties in complex networks. Information dimension is a useful dimension for complex networks to reveal these properties. In this paper, an information dimension is proposed for weighted complex networks. Based on the box-covering algorithm for weighted complex networks (BCANw), the proposed method can deal with the weighted complex networks which appear frequently in the real-world, and it can get the influence of the number of nodes in each box on the information dimension. To show the wide scope of information dimension, some applications are illustrated, indicating that the proposed method is effective and feasible.

Anterior Cingulate Cortex Instigates Adaptive Switches in Choice by Integrating Immediate and Delayed Components of Value in Ventromedial Prefrontal Cortex

PubMed Central

Guitart-Masip, Marc; Kurth-Nelson, Zeb; Dolan, Raymond J.

2014-01-01

Actions can lead to an immediate reward or punishment and a complex set of delayed outcomes. Adaptive choice necessitates the brain track and integrate both of these potential consequences. Here, we designed a sequential task whereby the decision to exploit or forego an available offer was contingent on comparing immediate value and a state-dependent future cost of expending a limited resource. Crucially, the dynamics of the task demanded frequent switches in policy based on an online computation of changing delayed consequences. We found that human subjects choose on the basis of a near-optimal integration of immediate reward and delayed consequences, with the latter computed in a prefrontal network. Within this network, anterior cingulate cortex (ACC) was dynamically coupled to ventromedial prefrontal cortex (vmPFC) when adaptive switches in choice were required. Our results suggest a choice architecture whereby interactions between ACC and vmPFC underpin an integration of immediate and delayed components of value to support flexible policy switching that accommodates the potential delayed consequences of an action. PMID:24573291

Anterior cingulate cortex instigates adaptive switches in choice by integrating immediate and delayed components of value in ventromedial prefrontal cortex.

PubMed

Economides, Marcos; Guitart-Masip, Marc; Kurth-Nelson, Zeb; Dolan, Raymond J

2014-02-26

Actions can lead to an immediate reward or punishment and a complex set of delayed outcomes. Adaptive choice necessitates the brain track and integrate both of these potential consequences. Here, we designed a sequential task whereby the decision to exploit or forego an available offer was contingent on comparing immediate value and a state-dependent future cost of expending a limited resource. Crucially, the dynamics of the task demanded frequent switches in policy based on an online computation of changing delayed consequences. We found that human subjects choose on the basis of a near-optimal integration of immediate reward and delayed consequences, with the latter computed in a prefrontal network. Within this network, anterior cingulate cortex (ACC) was dynamically coupled to ventromedial prefrontal cortex (vmPFC) when adaptive switches in choice were required. Our results suggest a choice architecture whereby interactions between ACC and vmPFC underpin an integration of immediate and delayed components of value to support flexible policy switching that accommodates the potential delayed consequences of an action.

Dynamic Steering for Improved Sensor Autonomy and Catalogue Maintenance

NASA Astrophysics Data System (ADS)

Hobson, T.; Gordon, N.; Clarkson, I.; Rutten, M.; Bessell, T.

A number of international agencies endeavour to maintain catalogues of the man-made resident space objects (RSOs) currently orbiting the Earth. Such catalogues are primarily created to anticipate and avoid destructive collisions involving important space assets such as manned missions and active satellites. An agencys ability to achieve this objective is dependent on the accuracy, reliability and timeliness of the information used to update its catalogue. A primary means for gathering this information is by regularly making direct observations of the tens-of-thousands of currently detectable RSOs via networks of space surveillance sensors. But operational constraints sometimes prevent accurate and timely reacquisition of all known RSOs, which can cause them to become lost to the tracking system. Furthermore, when comprehensive acquisition of new objects does not occur, these objects, in addition to the lost RSOs, result in uncorrelated detections when next observed. Due to the rising number of space-missions and the introduction of newer, more capable space-sensors, the number of uncorrelated targets is at an all-time high. The process of differentiating uncorrelated detections caused by once-acquired now-lost RSOs from newly detected RSOs is a difficult and often labour intensive task. Current methods for overcoming this challenge focus on advancements in orbit propagation and object characterisation to improve prediction accuracy and target identification. In this paper, we describe a complementary approach that incorporates increased awareness of error and failed observations into the RSO tracking solution. Our methodology employs a technique called dynamic steering to improve the autonomy and capability of a space surveillance networks steerable sensors. By co-situating each sensor with a low-cost high-performance computer, the steerable sensor can quickly and intelligently decide how to steer itself. The sensor-system uses a dedicated parallel-processing architecture to enable it to compute a high-fidelity estimate of the targets prior state error distribution in real-time. Negative information, such as when an RSO is targeted for observation but it is not observed, is incorporated to improve the likelihood of reacquiring the target when attempting to observe the target in future. The sensor is consequently capable of improving its utility by planning each observation using a sensor steering solution that is informed by all prior attempts at observing the target. We describe the practical implementation of a single experimental sensor and offer the results of recent field trials. These trials involved reacquisition and constrained Initial Orbit Determination of RSOs, a number of months after prior observation and initial detection. Using the proposed approach, the system is capable of using targeting information that would be unusable by existing space surveillance networks. The system consequently offers a means of enhancing space surveillance for SSA via increased system capacity, a higher degree of autonomy and the ability to reacquire objects whose dynamics are insufficiently modelled to cue a conventional space surveillance system for observation and tracking.

The Global Heat Health Information Network (GHHIN): Putting the Pieces Together

NASA Astrophysics Data System (ADS)

Jones, H.; Shumake, J.; Trtanj, J.

2017-12-01

Human exposure to extreme heat is one of the principal and most manageable impacts of climate on human health. Yet, every year worldwide, tens of thousands of people die as a result of avoidable heat-induced health consequences and countless others experience reduced labor productivity, physiological stress and ill health. The IPCC predicts with high confidence, that the observed trend of longer lasting, more frequent, more intense, and earlier onset heat waves will continue into the future. This situation requires the global health community to aggressively confront this recognized risk. Many countries and cities worldwide have developed heat action plans or heat health early warning systems, but these efforts are only connected in an ad-hoc fashion, use a broad range of non-standardized tools, methods, and approaches, and lack a clear mechanism to learn from each other in order to more rapidly advance health protection. To address this gap and accelerate heat health protection, the Global Heat Health Information Network (GHHIN) was launched in June 2016, by the WMO/WHO joint office for Climate and Health and the NOAA Climate Program Office. GHHIN is envisioned to be an independent, voluntary, member driven forum of scientists, professionals, and policymakers focused on enhancing and multiplying the global and local learning and resilience-building for heat health that is already occurring. GHHIN seeks to serve as a catalyst, knowledge broker, disseminator of good practices, and a forum for facilitating exchange and identifying needs. GHHIN will promote evidence-driven interventions, shared-learning, co-production of information, synthesis of priorities and capacity building to empower actors to take more effective and informed life-saving preparedness and planning measures. GHHIN is working toward several activities in 2018. The first Global Heat Health Synthesis report will be published to synthesize the state of science and practice to monitor, predict, and address extreme heat risks to human health, and the first GHHIN Global Forum will be held to bring together the community of experts and practitioners to share experience, inform a global common agenda, strengthen the network, and formally launch GHHIN. This presentation serves as an overview, status update, and invitation to become involved in GHHIN.

34 CFR 668.59 - Consequences of a change in application information.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 34 Education 3 2010-07-01 2010-07-01 false Consequences of a change in application information. 668.59 Section 668.59 Education Regulations of the Offices of the Department of Education (Continued... Verification of Student Aid Application Information § 668.59 Consequences of a change in application...

Proceedings Second Annual Cyber Security and Information Infrastructure Research Workshop

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

Sheldon, Frederick T; Krings, Axel; Yoo, Seong-Moo

2006-01-01

The workshop theme is Cyber Security: Beyond the Maginot Line Recently the FBI reported that computer crime has skyrocketed costing over $67 billion in 2005 alone and affecting 2.8M+ businesses and organizations. Attack sophistication is unprecedented along with availability of open source concomitant tools. Private, academic, and public sectors invest significant resources in cyber security. Industry primarily performs cyber security research as an investment in future products and services. While the public sector also funds cyber security R&D, the majority of this activity focuses on the specific mission(s) of the funding agency. Thus, broad areas of cyber security remain neglectedmore » or underdeveloped. Consequently, this workshop endeavors to explore issues involving cyber security and related technologies toward strengthening such areas and enabling the development of new tools and methods for securing our information infrastructure critical assets. We aim to assemble new ideas and proposals about robust models on which we can build the architecture of a secure cyberspace including but not limited to: * Knowledge discovery and management * Critical infrastructure protection * De-obfuscating tools for the validation and verification of tamper-proofed software * Computer network defense technologies * Scalable information assurance strategies * Assessment-driven design for trust * Security metrics and testing methodologies * Validation of security and survivability properties * Threat assessment and risk analysis * Early accurate detection of the insider threat * Security hardened sensor networks and ubiquitous computing environments * Mobile software authentication protocols * A new "model" of the threat to replace the "Maginot Line" model and more . . .« less

Determinants of field edge habitat restoration on farms in California's Sacramento Valley.

PubMed

Garbach, Kelly; Long, Rachael Freeman

2017-03-15

Degradation and loss of biodiversity and ecosystem services pose major challenges in simplified agricultural landscapes. Consequently, best management practices to create or restore habitat areas on field edges and other marginal areas have received a great deal of recent attention and policy support. Despite this, remarkably little is known about how landholders (farmers and landowners) learn about field edge management practices and which factors facilitate, or hinder, adoption of field edge plantings. We surveyed 109 landholders in California's Sacramento Valley to determine drivers of adoption of field edge plantings. The results show the important influence of landholders' communication networks, which included two key roles: agencies that provide technical support and fellow landholders. The networks of landholders that adopted field edge plantings included both fellow landholders and agencies, whereas networks of non-adopters included either landholders or agencies. This pattern documents that social learning through peer-to-peer information exchange can serve as a complementary and reinforcing pathway with technical learning that is stimulated by traditional outreach and extension programs. Landholder experience with benefits and concerns associated with field edge plantings were also significant predictors of adoption. Our results suggest that technical learning, stimulated by outreach and extension, may provide critical and necessary support for broad-scale adoption of field-edge plantings, but that this alone may not be sufficient. Instead, outreach and extension efforts may need to be strategically expanded to incorporate peer-to-peer communication, which can provide critical information on benefits and concerns. Copyright © 2016 Elsevier Ltd. All rights reserved.

Energy-efficient neural information processing in individual neurons and neuronal networks.

PubMed

Yu, Lianchun; Yu, Yuguo

2017-11-01

Brains are composed of networks of an enormous number of neurons interconnected with synapses. Neural information is carried by the electrical signals within neurons and the chemical signals among neurons. Generating these electrical and chemical signals is metabolically expensive. The fundamental issue raised here is whether brains have evolved efficient ways of developing an energy-efficient neural code from the molecular level to the circuit level. Here, we summarize the factors and biophysical mechanisms that could contribute to the energy-efficient neural code for processing input signals. The factors range from ion channel kinetics, body temperature, axonal propagation of action potentials, low-probability release of synaptic neurotransmitters, optimal input and noise, the size of neurons and neuronal clusters, excitation/inhibition balance, coding strategy, cortical wiring, and the organization of functional connectivity. Both experimental and computational evidence suggests that neural systems may use these factors to maximize the efficiency of energy consumption in processing neural signals. Studies indicate that efficient energy utilization may be universal in neuronal systems as an evolutionary consequence of the pressure of limited energy. As a result, neuronal connections may be wired in a highly economical manner to lower energy costs and space. Individual neurons within a network may encode independent stimulus components to allow a minimal number of neurons to represent whole stimulus characteristics efficiently. This basic principle may fundamentally change our view of how billions of neurons organize themselves into complex circuits to operate and generate the most powerful intelligent cognition in nature. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Investigating the consequences of urban volcanism using a scenario approach I: Development and application of a hypothetical eruption in the Auckland Volcanic Field, New Zealand

NASA Astrophysics Data System (ADS)

Deligne, Natalia I.; Fitzgerald, Rebecca H.; Blake, Daniel M.; Davies, Alistair J.; Hayes, Josh L.; Stewart, Carol; Wilson, Grant; Wilson, Thomas M.; Castelino, Renella; Kennedy, Ben M.; Muspratt, Scott; Woods, Richard

2017-04-01

What happens when a city has a volcanic eruption within its boundaries? To explore the consequences of this rare but potentially catastrophic combination, we develop a detailed multi-hazard scenario of an Auckland Volcanic Field (AVF) eruption; the AVF underlies New Zealand's largest city, Auckland. We start with an existing AVF unrest scenario sequence and develop it through a month-long hypothetical eruption based on geologic investigations of the AVF and historic similar eruptions from around the world. We devise a credible eruption sequence and include all volcanic hazards that could occur in an AVF eruption. In consultation with Civil Defence and Emergency Management staff, we create a series of evacuation maps for before, during, and after the hypothetical eruption sequence. Our result is a versatile scenario with many possible applications, developed further in companion papers that explore eruption consequences on transportation and water networks. However, here we illustrate one application: evaluating the consequences of an eruption on electricity service provision. In a collaborative approach between scientists and electricity service providers, we evaluate the impact of the hypothetical eruption to electricity generation, transmission, and distribution infrastructure. We then evaluate how the impacted network functions, accounting for network adaptations (e.g., diverting power away from evacuated areas), site access, and restoration factors. We present a series of regional maps showing areas with full service, rolling outages, and no power as a result of the eruption. This illustrative example demonstrates how a detailed scenario can be used to further understand the ramifications of urban volcanism on local and regional populations, and highlights the importance of looking beyond damage to explore the consequences of volcanism.

System level mechanisms of adaptation, learning, memory formation and evolvability: the role of chaperone and other networks.

PubMed

Gyurko, David M; Soti, Csaba; Stetak, Attila; Csermely, Peter

2014-05-01

During the last decade, network approaches became a powerful tool to describe protein structure and dynamics. Here, we describe first the protein structure networks of molecular chaperones, then characterize chaperone containing sub-networks of interactomes called as chaperone-networks or chaperomes. We review the role of molecular chaperones in short-term adaptation of cellular networks in response to stress, and in long-term adaptation discussing their putative functions in the regulation of evolvability. We provide a general overview of possible network mechanisms of adaptation, learning and memory formation. We propose that changes of network rigidity play a key role in learning and memory formation processes. Flexible network topology provides ' learning-competent' state. Here, networks may have much less modular boundaries than locally rigid, highly modular networks, where the learnt information has already been consolidated in a memory formation process. Since modular boundaries are efficient filters of information, in the 'learning-competent' state information filtering may be much smaller, than after memory formation. This mechanism restricts high information transfer to the 'learning competent' state. After memory formation, modular boundary-induced segregation and information filtering protect the stored information. The flexible networks of young organisms are generally in a 'learning competent' state. On the contrary, locally rigid networks of old organisms have lost their 'learning competent' state, but store and protect their learnt information efficiently. We anticipate that the above mechanism may operate at the level of both protein-protein interaction and neuronal networks.

The microeconomics of residential photovoltaics: Tariffs, network operation and maintenance, and ancillary services in distribution-level electricity markets

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

Boero, Riccardo; Backhaus, Scott N.; Edwards, Brian K.

Here, we develop a microeconomic model of a distribution-level electricity market that takes explicit account of residential photovoltaics (PV) adoption. The model allows us to study the consequences of most tariffs on PV adoption and the consequences of increased residential PV adoption under the assumption of economic sustainability for electric utilities. We also validated the model using U.S. data and extend it to consider different pricing schemes for operation and maintenance costs of the distribution network and for ancillary services. Results show that net metering promotes more environmental benefits and social welfare than other tariffs. But, if costs to operatemore » the distribution network increase, net metering will amplify the unequal distribution of surplus among households. In conclusion, maintaining the economic sustainability of electric utilities under net metering may become extremely difficult unless the uneven distribution of surplus is legitimated by environmental benefits.« less

Mitigation of the consequence of seismically induced damage on a utility water network by means of next generation SCADA

NASA Astrophysics Data System (ADS)

Robertson, Jamie; Shinozuka, Masanobu; Wu, Felix

2011-04-01

When a lifeline system such as a water delivery network is damaged due to a severe earthquake, it is critical to identify its location and extent of the damage in real time in order to minimize the potentially disastrous consequence such damage could otherwise entail. This paper demonstrates how the degree of such minimization can be estimated qualitatively by using the water delivery system of Irvine Water Ranch District (IRWD) as testbed, when it is subjected to magnitude 6.6 San Joaquin Hills Earthquake. In this demonstration, we consider two cases when the IRWD system is equipped or not equipped with a next generation SCADA which consists of a network of MEMS acceleration sensors densely populated and optimally located. These sensors are capable of identifying the location and extent of the damage as well as transmitting the data to the SCADA center for monitoring and control.

The microeconomics of residential photovoltaics: Tariffs, network operation and maintenance, and ancillary services in distribution-level electricity markets

DOE PAGES

Boero, Riccardo; Backhaus, Scott N.; Edwards, Brian K.

2016-11-12

Here, we develop a microeconomic model of a distribution-level electricity market that takes explicit account of residential photovoltaics (PV) adoption. The model allows us to study the consequences of most tariffs on PV adoption and the consequences of increased residential PV adoption under the assumption of economic sustainability for electric utilities. We also validated the model using U.S. data and extend it to consider different pricing schemes for operation and maintenance costs of the distribution network and for ancillary services. Results show that net metering promotes more environmental benefits and social welfare than other tariffs. But, if costs to operatemore » the distribution network increase, net metering will amplify the unequal distribution of surplus among households. In conclusion, maintaining the economic sustainability of electric utilities under net metering may become extremely difficult unless the uneven distribution of surplus is legitimated by environmental benefits.« less

Integrated modelling for the evaluation of infiltration effects.

PubMed

Schulz, N; Baur, R; Krebs, P

2005-01-01

The objective of the present study is the estimation of the potential benefits of sewer pipe rehabilitation for the performance of the drainage system and the wastewater treatment plant (WWTP) as well as for the receiving water quality. The relation of sewer system status and the infiltration rate is assessed based on statistical analysis of 470 km of CCTV (Closed Circuit Television) inspected sewers of the city of Dresden. The potential reduction of infiltration rates and the consequent performance improvements of the urban wastewater system are simulated as a function of rehabilitation activities in the network. The integrated model is applied to an artificial system with input from a real sewer network. In this paper, the general design of the integrated model and its data requirements are presented. For an exemplary study, the consequences of the simulations are discussed with respect to the prioritisation of rehabilitation activities in the network.

Toward a theory of multilevel evolution: long-term information integration shapes the mutational landscape and enhances evolvability.

PubMed

Hogeweg, Paulien

2012-01-01

Most of evolutionary theory has abstracted away from how information is coded in the genome and how this information is transformed into traits on which selection takes place. While in the earliest stages of biological evolution, in the RNA world, the mapping from the genotype into function was largely predefined by the physical-chemical properties of the evolving entities (RNA replicators, e.g. from sequence to folded structure and catalytic sites), in present-day organisms, the mapping itself is the result of evolution. I will review results of several in silico evolutionary studies which examine the consequences of evolving the genetic coding, and the ways this information is transformed, while adapting to prevailing environments. Such multilevel evolution leads to long-term information integration. Through genome, network, and dynamical structuring, the occurrence and/or effect of random mutations becomes nonrandom, and facilitates rapid adaptation. This is what does happen in the in silico experiments. Is it also what did happen in biological evolution? I will discuss some data that suggest that it did. In any case, these results provide us with novel search images to tackle the wealth of biological data.

Communication networks for the tactical edge

NASA Astrophysics Data System (ADS)

Evans, Joseph B.; Pennington, Steven G.; Ewy, Benjamin J.

2017-04-01

Information at the tactical level is increasingly critical in today's conflicts. The proliferation of commercial tablets and smart phones has created the ability for extensive information sharing at the tactical edge, beyond the traditional tactical voice communications and location information. This is particularly the case in Gray Zone conflicts, in which tactical decision making and actions are intertwined with information sharing and exploitation. Networking of tactical devices is the key to this information sharing. In this work, we detail and analyze two network models at different parts of the Gray Zone spectrum, and explore a number of networking options including Named Data Networking. We also compare networking approaches in a variety of realistic operating environments. Our results show that Named Data Networking is a good match for the disrupted networking environments found in many tactical situations

Evaluation of QoS supported in Network Mobility NEMO environments

NASA Astrophysics Data System (ADS)

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

2013-12-01

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).

An information spreading model based on online social networks

NASA Astrophysics Data System (ADS)

Wang, Tao; He, Juanjuan; Wang, Xiaoxia

2018-01-01

Online social platforms are very popular in recent years. In addition to spreading information, users could review or collect information on online social platforms. According to the information spreading rules of online social network, a new information spreading model, namely IRCSS model, is proposed in this paper. It includes sharing mechanism, reviewing mechanism, collecting mechanism and stifling mechanism. Mean-field equations are derived to describe the dynamics of the IRCSS model. Moreover, the steady states of reviewers, collectors and stiflers and the effects of parameters on the peak values of reviewers, collectors and sharers are analyzed. Finally, numerical simulations are performed on different networks. Results show that collecting mechanism and reviewing mechanism, as well as the connectivity of the network, make information travel wider and faster, and compared to WS network and ER network, the speed of reviewing, sharing and collecting information is fastest on BA network.

Multimedia Information Networks in Social Media

NASA Astrophysics Data System (ADS)

Cao, Liangliang; Qi, Guojun; Tsai, Shen-Fu; Tsai, Min-Hsuan; Pozo, Andrey Del; Huang, Thomas S.; Zhang, Xuemei; Lim, Suk Hwan

The popularity of personal digital cameras and online photo/video sharing community has lead to an explosion of multimedia information. Unlike traditional multimedia data, many new multimedia datasets are organized in a structural way, incorporating rich information such as semantic ontology, social interaction, community media, geographical maps, in addition to the multimedia contents by themselves. Studies of such structured multimedia data have resulted in a new research area, which is referred to as Multimedia Information Networks. Multimedia information networks are closely related to social networks, but especially focus on understanding the topics and semantics of the multimedia files in the context of network structure. This chapter reviews different categories of recent systems related to multimedia information networks, summarizes the popular inference methods used in recent works, and discusses the applications related to multimedia information networks. We also discuss a wide range of topics including public datasets, related industrial systems, and potential future research directions in this field.

Information theory-based decision support system for integrated design of multivariable hydrometric networks

NASA Astrophysics Data System (ADS)

Keum, Jongho; Coulibaly, Paulin

2017-07-01

Adequate and accurate hydrologic information from optimal hydrometric networks is an essential part of effective water resources management. Although the key hydrologic processes in the water cycle are interconnected, hydrometric networks (e.g., streamflow, precipitation, groundwater level) have been routinely designed individually. A decision support framework is proposed for integrated design of multivariable hydrometric networks. The proposed method is applied to design optimal precipitation and streamflow networks simultaneously. The epsilon-dominance hierarchical Bayesian optimization algorithm was combined with Shannon entropy of information theory to design and evaluate hydrometric networks. Specifically, the joint entropy from the combined networks was maximized to provide the most information, and the total correlation was minimized to reduce redundant information. To further optimize the efficiency between the networks, they were designed by maximizing the conditional entropy of the streamflow network given the information of the precipitation network. Compared to the traditional individual variable design approach, the integrated multivariable design method was able to determine more efficient optimal networks by avoiding the redundant stations. Additionally, four quantization cases were compared to evaluate their effects on the entropy calculations and the determination of the optimal networks. The evaluation results indicate that the quantization methods should be selected after careful consideration for each design problem since the station rankings and the optimal networks can change accordingly.

Leadership in Groups: Social Networks and Perceptions of Formal and Informal Leaders

DTIC Science & Technology

2006-03-01

LEADERSHIP IN GROUPS: SOCIAL NETWORKS AND PERCEPTIONS OF FORMAL AND INFORMAL LEADERS THESIS...01 LEADERSHIP IN GROUPS: SOCIAL NETWORKS AND PERCEPTIONS OF FORMAL AND INFORMAL LEADERS THESIS Presented to the Faculty...DISTRIBUTION UNLIMITED. AFIT/GSS/ENV/06M-01 LEADERSHIP IN GROUPS: SOCIAL NETWORKS AND PERCEPTIONS OF FORMAL AND INFORMAL LEADERS

Advancing the State of the Art in Applying Network Science to C2

DTIC Science & Technology

2014-06-01

technological networks to include information , cognitive and social networks, they have yet to apply the full range of theoretical instruments now...robustness, and processes. While NEC researchers extended their coverage from technological networks to include information , cognitive and social networks...can be found in a wide variety of domains. For example, Newman (2003) surveys work on biological, technological , information , and social networks

Quantifying randomness in real networks

NASA Astrophysics Data System (ADS)

Orsini, Chiara; Dankulov, Marija M.; Colomer-de-Simón, Pol; Jamakovic, Almerima; Mahadevan, Priya; Vahdat, Amin; Bassler, Kevin E.; Toroczkai, Zoltán; Boguñá, Marián; Caldarelli, Guido; Fortunato, Santo; Krioukov, Dmitri

2015-10-01

Represented as graphs, real networks are intricate combinations of order and disorder. Fixing some of the structural properties of network models to their values observed in real networks, many other properties appear as statistical consequences of these fixed observables, plus randomness in other respects. Here we employ the dk-series, a complete set of basic characteristics of the network structure, to study the statistical dependencies between different network properties. We consider six real networks--the Internet, US airport network, human protein interactions, technosocial web of trust, English word network, and an fMRI map of the human brain--and find that many important local and global structural properties of these networks are closely reproduced by dk-random graphs whose degree distributions, degree correlations and clustering are as in the corresponding real network. We discuss important conceptual, methodological, and practical implications of this evaluation of network randomness, and release software to generate dk-random graphs.

NetWall distributed firewall in the use of campus network

NASA Astrophysics Data System (ADS)

He, Junhua; Zhang, Pengshuai

2011-10-01

Internet provides a modern means of education but also non-mainstream consciousness and poor dissemination of information opens the door, network and moral issues have become prominent, poor dissemination of information and network spread rumors and negative effects of new problems, ideological and political education in schools had a huge impact, poses a severe challenge. This paper presents a distributed firewall will NetWall deployed in a campus network solution. The characteristics of the campus network, using technology to filter out bad information on the means of control, of sensitive information related to the record, establish a complete information security management platform for the campus network.

Dynamical analysis of the Indian Ocean climate network and its correlation with Australian Millennium Drought

NASA Astrophysics Data System (ADS)

Carpi, Laura; Masoller, Cristina; Díaz-Guilera, Albert; Ravetti, Martín G.

2015-04-01

During the period between the mid-1990s and late 2000s Australia had suffered one of the worst droughts on record. Severe rainfall deficits affected great part of southeast Australia, causing widespread drought conditions and catastrophic bushfires. The "Millennium Drought", as it was called, was unusual in terms of its severity, duration and extent, leaving important environmental and financial damages. One of the most important drivers of Australia climate variability is the Indian Ocean dipole (IOD), that is a coupled ocean and atmosphere phenomenon in the equatorial Indian Ocean. The IOD is measured by an index (DMI) that is the difference between sea surface temperature (SST) anomalies in the western and eastern equatorial Indian Ocean. Its positive phase is characterized by lower than normal sea surface temperatures in the tropical eastern coast, and higher than normal in the tropical western Indian Ocean. Extreme positive IOD (pIOD) events are associated to severe droughts in countries located over the eastern Indian Ocean, and to severe floods in the western tropical ones. Recent research works projected that the frequency of extreme pIOD events will increase significantly over the twenty-first century and consequently, the frequency of extreme climate conditions in the zones affected by it. In this work we study the dynamics of the Indian Ocean for the period of 1979-2014, by using climate networks of skin temperature and humidity (reanalysis data). Annual networks are constructed by creating links when the Pearson correlation coefficient between two nodes is greater than a specific value. The distance distribution Pd(k), that indicates the fraction of pairs of nodes at distance k, is computed to characterize the dynamics of the network by using Information Theory quantifiers. We found a clear change in the Indian Ocean dynamics and an increment in the network's similarities quantified by the Jensen-Shannon divergence in the late 1990s. We speculate that these findings are capturing mean state changes within the Indian Ocean that result in the increase of extreme positive IOD frequency, among other unknown consequences. We show that the unusual characteristics of the Australian Millennium Drought is strongly associated with this new Indian Ocean dynamics showing its relevance in the Australia climate variability.

Spatial and Social Networks in Organizational Innovation

ERIC Educational Resources Information Center

Wineman, Jean D.; Kabo, Felichism W.; Davis, Gerald F.

2009-01-01

Research on the enabling factors of innovation has focused on either the social component of organizations or on the spatial dimensions involved in the innovation process. But no one has examined the aggregate consequences of the link from spatial layout, to social networks, to innovation. This project enriches our understanding of how innovation…

Synaptic plasticity in a recurrent neural network for versatile and adaptive behaviors of a walking robot.

PubMed

Grinke, Eduard; Tetzlaff, Christian; Wörgötter, Florentin; Manoonpong, Poramate

2015-01-01

Walking animals, like insects, with little neural computing can effectively perform complex behaviors. For example, they can walk around their environment, escape from corners/deadlocks, and avoid or climb over obstacles. While performing all these behaviors, they can also adapt their movements to deal with an unknown situation. As a consequence, they successfully navigate through their complex environment. The versatile and adaptive abilities are the result of an integration of several ingredients embedded in their sensorimotor loop. Biological studies reveal that the ingredients include neural dynamics, plasticity, sensory feedback, and biomechanics. Generating such versatile and adaptive behaviors for a many degrees-of-freedom (DOFs) walking robot is a challenging task. Thus, in this study, we present a bio-inspired approach to solve this task. Specifically, the approach combines neural mechanisms with plasticity, exteroceptive sensory feedback, and biomechanics. The neural mechanisms consist of adaptive neural sensory processing and modular neural locomotion control. The sensory processing is based on a small recurrent neural network consisting of two fully connected neurons. Online correlation-based learning with synaptic scaling is applied to adequately change the connections of the network. By doing so, we can effectively exploit neural dynamics (i.e., hysteresis effects and single attractors) in the network to generate different turning angles with short-term memory for a walking robot. The turning information is transmitted as descending steering signals to the neural locomotion control which translates the signals into motor actions. As a result, the robot can walk around and adapt its turning angle for avoiding obstacles in different situations. The adaptation also enables the robot to effectively escape from sharp corners or deadlocks. Using backbone joint control embedded in the the locomotion control allows the robot to climb over small obstacles. Consequently, it can successfully explore and navigate in complex environments. We firstly tested our approach on a physical simulation environment and then applied it to our real biomechanical walking robot AMOSII with 19 DOFs to adaptively avoid obstacles and navigate in the real world.

Synaptic plasticity in a recurrent neural network for versatile and adaptive behaviors of a walking robot

PubMed Central

Grinke, Eduard; Tetzlaff, Christian; Wörgötter, Florentin; Manoonpong, Poramate

2015-01-01

Walking animals, like insects, with little neural computing can effectively perform complex behaviors. For example, they can walk around their environment, escape from corners/deadlocks, and avoid or climb over obstacles. While performing all these behaviors, they can also adapt their movements to deal with an unknown situation. As a consequence, they successfully navigate through their complex environment. The versatile and adaptive abilities are the result of an integration of several ingredients embedded in their sensorimotor loop. Biological studies reveal that the ingredients include neural dynamics, plasticity, sensory feedback, and biomechanics. Generating such versatile and adaptive behaviors for a many degrees-of-freedom (DOFs) walking robot is a challenging task. Thus, in this study, we present a bio-inspired approach to solve this task. Specifically, the approach combines neural mechanisms with plasticity, exteroceptive sensory feedback, and biomechanics. The neural mechanisms consist of adaptive neural sensory processing and modular neural locomotion control. The sensory processing is based on a small recurrent neural network consisting of two fully connected neurons. Online correlation-based learning with synaptic scaling is applied to adequately change the connections of the network. By doing so, we can effectively exploit neural dynamics (i.e., hysteresis effects and single attractors) in the network to generate different turning angles with short-term memory for a walking robot. The turning information is transmitted as descending steering signals to the neural locomotion control which translates the signals into motor actions. As a result, the robot can walk around and adapt its turning angle for avoiding obstacles in different situations. The adaptation also enables the robot to effectively escape from sharp corners or deadlocks. Using backbone joint control embedded in the the locomotion control allows the robot to climb over small obstacles. Consequently, it can successfully explore and navigate in complex environments. We firstly tested our approach on a physical simulation environment and then applied it to our real biomechanical walking robot AMOSII with 19 DOFs to adaptively avoid obstacles and navigate in the real world. PMID:26528176

Differentiable cortical networks for inferences concerning people's intentions versus physical causality.

PubMed

Mason, Robert A; Just, Marcel Adam

2011-02-01

Cortical activity associated with generating an inference was measured using fMRI. Participants read three-sentence passages that differed in whether or not an inference needed to be drawn to understand them. The inference was based on either a protagonist's intention or a physical consequence of a character's action. Activation was expected in Theory of Mind brain regions for the passages based on protagonists' intentions but not for the physical consequence passages. The activation measured in the right temporo-parietal junction was greater in the intentional passages than in the consequence passages, consistent with predictions from a Theory of Mind perspective. In contrast, there was increased occipital activation in the physical inference passages. For both types of passage, the cortical activity related to the reading of the critical inference sentence demonstrated a recruitment of a common inference cortical network. This general inference-related activation appeared bilaterally in the language processing areas (the inferior frontal gyrus, the temporal gyrus, and the angular gyrus), as well as in the medial to superior frontal gyrus, which has been found to be active in Theory of Mind tasks. These findings are consistent with the hypothesis that component areas of the discourse processing network are recruited as needed based on the nature of the inference. A Protagonist monitoring and synthesis network is proposed as a more accurate account for Theory of Mind activation during narrative comprehension. Copyright © 2010 Wiley-Liss, Inc.

Instrumentation for Scientific Computing in Neural Networks, Information Science, Artificial Intelligence, and Applied Mathematics.

DTIC Science & Technology

1987-10-01

include Security Classification) Instrumentation for scientific computing in neural networks, information science, artificial intelligence, and...instrumentation grant to purchase equipment for support of research in neural networks, information science, artificail intellignece , and applied mathematics...in Neural Networks, Information Science, Artificial Intelligence, and Applied Mathematics Contract AFOSR 86-0282 Principal Investigator: Stephen

Learning control of inverted pendulum system by neural network driven fuzzy reasoning: The learning function of NN-driven fuzzy reasoning under changes of reasoning environment

NASA Technical Reports Server (NTRS)

Hayashi, Isao; Nomura, Hiroyoshi; Wakami, Noboru

1991-01-01

Whereas conventional fuzzy reasonings are associated with tuning problems, which are lack of membership functions and inference rule designs, a neural network driven fuzzy reasoning (NDF) capable of determining membership functions by neural network is formulated. In the antecedent parts of the neural network driven fuzzy reasoning, the optimum membership function is determined by a neural network, while in the consequent parts, an amount of control for each rule is determined by other plural neural networks. By introducing an algorithm of neural network driven fuzzy reasoning, inference rules for making a pendulum stand up from its lowest suspended point are determined for verifying the usefulness of the algorithm.

Aligning incentives in supply chains.

PubMed

Narayanan, V G; Raman, Ananth

2004-11-01

Most companies don't worry about the behavior of their supply chain partners. Instead, they expect the supply chain to work efficiently without interference, as if guided by Adam Smith's famed invisible hand. In their study of more than 50 supply networks, V.G. Narayanan and Ananth Raman found that companies often looked out for their own interests and ignored those of their network partners. Consequently, supply chains performed poorly. Those results aren't shocking when you consider that supply chains extend across several functions and many companies, each with its own priorities and goals. Yet all those functions and firms must pull in the same direction for a chain to deliver goods and services to consumers quickly and cost-effectively. According to the authors, a supply chain works well only if the risks, costs, and rewards of doing business are distributed fairly across the network. In fact, misaligned incentives are often the cause of excess inventory, stock-outs, incorrect forecasts, inadequate sales efforts, and even poor customer service. The fates of all supply chain partners are interlinked: If the firms work together to serve consumers, they will all win. However, they can do that only if incentives are aligned. Companies must acknowledge that the problem of incentive misalignment exists and then determine its root cause and align or redesign incentives. They can improve alignment by, for instance, adopting revenue-sharing contracts, using technology to track previously hidden information, or working with intermediaries to build trust among network partners. It's also important to periodically reassess incentives, because even top-performing networks find that changes in technology or business conditions alter the alignment of incentives.

The Weight-control Information Network (WIN) | NIH MedlinePlus the Magazine

MedlinePlus

... Javascript on. Feature: Reducing Childhood Obesity The Weight-control Information Network (WIN) Past Issues / Spring - Summer 2010 ... overweight children, here are tips from the Weight-control Information Network (WIN), an information service of the ...

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

NASA Astrophysics Data System (ADS)

Hortos, William S.

2006-05-01

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

The role of social support and social networks in health information-seeking behavior among Korean Americans: a qualitative study.

PubMed

Kim, Wonsun; Kreps, Gary L; Shin, Cha-Nam

2015-04-28

This study used social network theory to explore the role of social support and social networks in health information-seeking behavior among Korean American (KA) adults. A descriptive qualitative study using a web-based online survey was conducted from January 2013 to April 2013 in the U.S. The survey included open-ended questions about health information-seeking experiences in personal social networks and their importance in KA adults. Themes emerging from a constant comparative analysis of the narrative comments by 129 of the 202 respondents were analyzed. The sample consisted of 129 KA adults, 64.7% female, with a mean age of 33.2 (SD = 7.7). Friends, church members, and family members were the important network connections for KAs to obtain health information. KAs looked for a broad range of health information from social network members, from recommendations and reviews of hospitals/doctors to specific diseases or health conditions. These social networks were regarded as important for KAs because there were no language barriers, social network members had experiences similar to those of other KAs, they felt a sense of belonging with those in their networks, the network connections promoted increased understanding of different health care systems of the U.S. system, and communication with these network connections helped enhance feelings of being physically and mentally healthy. This study demonstrates the important role that social support and personal social networks perform in the dissemination of health information for a large ethnic population, KAs, who confront distinct cultural challenges when seeking health information in the U.S. Data from this study also illustrate the cultural factors that influence health information acquisition and access to social support for ethnic minorities. This study provides practical insights for professionals in health information services, namely, that social networks can be employed as a channel for disseminating health information to immigrants.

Social networks and secondary health conditions: The critical secondary team for individuals with spinal cord injury

PubMed Central

Guilcher, Sara J. T.; Casciaro, Tiziana; Lemieux-Charles, Louise; Craven, Catharine; McColl, Mary Ann; Jaglal, Susan B.

2012-01-01

Objectives To describe the structure of informal networks for individuals with spinal cord injury (SCI) living in the community, to understand the quality of relationship of informal networks, and to understand the role of informal networks in the prevention and management of secondary health conditions (SHCs). Design Mixed-method descriptive study. Setting Ontario, Canada Participants Community-dwelling adults with an SCI living in Ontario Interventions/methods The Arizona Social Support Interview Survey was used to measure social networks. Participants were asked the following open-ended questions: (1) What have been your experiences with your health care in the community? (2) What have been your experiences with care related to prevention and/or management of SHCs?, (3)What has been the role of your informal social networks (friends/family) related to SHCs? Results Fourteen key informant interviews were conducted (6 men, 8 women). The overall median for available informal networks was 11.0 persons (range 3–19). The informal network engaged in the following roles: (1) advice/validating concerns; (2) knowledge brokers; (3) advocacy; (4) preventing SHCs; (5) assisting with finances; and (6) managing SHCs. Participants described their informal networks as a “secondary team”; a critical and essential force in dealing with SHCs. Conclusions While networks are smaller for persons with SCI compared with the general population, these ties seems to be strong, which is essential when the roles involve a level of trust, certainty, tacit knowledge, and flexibility. These informal networks serve as essential key players in filling the gaps that exist within the formal health care system. PMID:23031170

40 CFR 1400.5 - Internet access to certain off-site consequence analysis data elements.

Code of Federal Regulations, 2012 CFR

2012-07-01

... UNDER THE CLEAN AIR ACT SECTION 112(r)(7); DISTRIBUTION OF OFF-SITE CONSEQUENCE ANALYSIS INFORMATION DISTRIBUTION OF OFF-SITE CONSEQUENCE ANALYSIS INFORMATION Public Access § 1400.5 Internet access to certain off... consequence analysis data elements. 1400.5 Section 1400.5 Protection of Environment ENVIRONMENTAL PROTECTION...

40 CFR 1400.5 - Internet access to certain off-site consequence analysis data elements.

Code of Federal Regulations, 2014 CFR

2014-07-01

... UNDER THE CLEAN AIR ACT SECTION 112(r)(7); DISTRIBUTION OF OFF-SITE CONSEQUENCE ANALYSIS INFORMATION DISTRIBUTION OF OFF-SITE CONSEQUENCE ANALYSIS INFORMATION Public Access § 1400.5 Internet access to certain off... consequence analysis data elements. 1400.5 Section 1400.5 Protection of Environment ENVIRONMENTAL PROTECTION...

40 CFR 1400.5 - Internet access to certain off-site consequence analysis data elements.

Code of Federal Regulations, 2013 CFR

2013-07-01

... UNDER THE CLEAN AIR ACT SECTION 112(r)(7); DISTRIBUTION OF OFF-SITE CONSEQUENCE ANALYSIS INFORMATION DISTRIBUTION OF OFF-SITE CONSEQUENCE ANALYSIS INFORMATION Public Access § 1400.5 Internet access to certain off... consequence analysis data elements. 1400.5 Section 1400.5 Protection of Environment ENVIRONMENTAL PROTECTION...

How "Community" Matters for How People Interact With Information: Mixed Methods Study of Young Men Who Have Sex With Other Men

PubMed Central

Meadowbrooke, Chrysta Cathleen; Loveluck, Jimena; Hickok, Andrew; Bauermeister, Jose Artruro

2013-01-01

Background We lack a systematic portrait of the relationship between community involvement and how people interact with information. Young men who have sex with men (YMSM) are a population for which these relationships are especially salient: their gay community involvement varies and their information technology use is high. YMSM under age 24 are also one of the US populations with the highest risk of HIV/AIDS. Objective To develop, test, and refine a model of gay community involvement (GCI) factors in human-information interaction (HII) as applied to HIV/AIDS information among YMSM, specifically examining the role of Internet use in GCI and HII. Methods Mixed methods included: 1) online questionnaire with 194 YMSM; and 2) qualitative interviews with 19 YMSM with high GCI levels. Recruitment utilized social media, dating websites, health clinics, bars/clubs, and public postings. The survey included questions regarding HIV/AIDS–related information acquisition and use patterns, gay community involvement, risk behaviors, and technology use. For survey data, we tested multiple linear regression models using a series of community- and information-related variables as dependent variables. Independent variables included community- and information-related variables and demographic covariates. We then conducted a recursive path analysis in order to estimate a final model, which we refined through a grounded theory analysis of qualitative interview data. Results Four community-related variables significantly predicted how people interact with information (HII variables): 1) gay community involvement (GCI), 2) social costs of information seeking, 3) network expertise accessibility, and 4) community relevance. GCI was associated with significantly lower perceived social costs of HIV/AIDS information seeking (R 2=0.07). GCI and social costs significantly predicted network expertise accessibility (R 2=0.14). GCI predicted 14% of the variance in community relevance and 9% of the variance in information seeking frequency. Incidental HIV/AIDS information acquisition (IIA) was also significantly predicted by GCI (R 2=0.16). 28% of the variance in HIV/AIDS information use was explained by community relevance, network expertise access, and both IIA and information seeking. The final path model showed good fit: the RSMEA was 0.054 (90% CI: .000-.101); the Chi-square was non-significant (χ2(11)=17.105; P=.105); and the CFI was 0.967. Qualitative findings suggest that the model may be enhanced by including information sharing: organizing events, disseminating messages, encouraging safety, and referring and recommending. Information sharing emerged under conditions of pro-social community value enactment and may have consequences for further HII. YMSM with greater GCI generally used the Internet more, although they chatted online less. Conclusions HIV/AIDS–related HII and associated technology uses are community-embedded processes. The model provides theoretical mediators that may serve as a focus for intervention: 1) valuing HIV/AIDS information, through believing it is relevant to one’s group, and 2) supportive and knowledgeable network members with whom to talk about HIV/AIDS. Pro-social community value endorsement and information sharing may also be important theoretical mediators. Our model could open possibilities for considering how informatics interventions can also be designed as community-level interventions and vice versa. PMID:23428825

Competing spreading processes on multiplex networks: awareness and epidemics.

PubMed

Granell, Clara; Gómez, Sergio; Arenas, Alex

2014-07-01

Epidemiclike spreading processes on top of multilayered interconnected complex networks reveal a rich phase diagram of intertwined competition effects. A recent study by the authors [C. Granell et al., Phys. Rev. Lett. 111, 128701 (2013).] presented an analysis of the interrelation between two processes accounting for the spreading of an epidemic, and the spreading of information awareness to prevent infection, on top of multiplex networks. The results in the case in which awareness implies total immunization to the disease revealed the existence of a metacritical point at which the critical onset of the epidemics starts, depending on completion of the awareness process. Here we present a full analysis of these critical properties in the more general scenario where the awareness spreading does not imply total immunization, and where infection does not imply immediate awareness of it. We find the critical relation between the two competing processes for a wide spectrum of parameters representing the interaction between them. We also analyze the consequences of a massive broadcast of awareness (mass media) on the final outcome of the epidemic incidence. Importantly enough, the mass media make the metacritical point disappear. The results reveal that the main finding, i.e., existence of a metacritical point, is rooted in the competition principle and holds for a large set of scenarios.

Memory formation orchestrates the wiring of adult-born hippocampal neurons into brain circuits.

PubMed

Petsophonsakul, Petnoi; Richetin, Kevin; Andraini, Trinovita; Roybon, Laurent; Rampon, Claire

2017-08-01

During memory formation, structural rearrangements of dendritic spines provide a mean to durably modulate synaptic connectivity within neuronal networks. New neurons generated throughout the adult life in the dentate gyrus of the hippocampus contribute to learning and memory. As these neurons become incorporated into the network, they generate huge numbers of new connections that modify hippocampal circuitry and functioning. However, it is yet unclear as to how the dynamic process of memory formation influences their synaptic integration into neuronal circuits. New memories are established according to a multistep process during which new information is first acquired and then consolidated to form a stable memory trace. Upon recall, memory is transiently destabilized and vulnerable to modification. Using contextual fear conditioning, we found that learning was associated with an acceleration of dendritic spines formation of adult-born neurons, and that spine connectivity becomes strengthened after memory consolidation. Moreover, we observed that afferent connectivity onto adult-born neurons is enhanced after memory retrieval, while extinction training induces a change of spine shapes. Together, these findings reveal that the neuronal activity supporting memory processes strongly influences the structural dendritic integration of adult-born neurons into pre-existing neuronal circuits. Such change of afferent connectivity is likely to impact the overall wiring of hippocampal network, and consequently, to regulate hippocampal function.

Revealing the structure of the world airline network

PubMed Central

Verma, T.; Araújo, N. A. M.; Herrmann, H. J.

2014-01-01

Resilience of most critical infrastructures against failure of elements that appear insignificant is usually taken for granted. The World Airline Network (WAN) is an infrastructure that reduces the geographical gap between societies, both small and large, and brings forth economic gains. With the extensive use of a publicly maintained data set that contains information about airports and alternative connections between these airports, we empirically reveal that the WAN is a redundant and resilient network for long distance air travel, but otherwise breaks down completely due to removal of short and apparently insignificant connections. These short range connections with moderate number of passengers and alternate flights are the connections that keep remote parts of the world accessible. It is surprising, insofar as there exists a highly resilient and strongly connected core consisting of a small fraction of airports (around 2.3%) together with an extremely fragile star-like periphery. Yet, in spite of their relevance, more than 90% of the world airports are still interconnected upon removal of this core. With standard and unconventional removal measures we compare both empirical and topological perceptions for the fragmentation of the world. We identify how the WAN is organized into different classes of clusters based on the physical proximity of airports and analyze the consequence of this fragmentation. PMID:25005934

Local level sustainability policies in the Baltic Sea area: Local Agenda 21 within the Union of the Baltic Cities network.

PubMed

Joas, M; Grönholm, B

2001-08-01

Local Agenda 21 (LA21) processes have 2 central goals. i) On the basis of some of the empirical evidence in this study, the primary goal is to improve democratic (environmental) policy-making processes in such a manner that a larger share of the population will be able to participate in planning and decision making and will also be able to understand the consequences of these decisions. ii) The LA21 processes seek to improve (at least indirectly) the broadly defined environmental situation locally in a manner that takes into account both the local and the global contexts. The first part of this article discusses the concept and methods of LA21 and sheds light on the different action areas that are central to the Baltic LA21 processes. In addition, the study will describe and display the LA21 situation within one network of cities, the Union of the Baltic Cities (UBC). Networking, including transfer of information, models and ideas, has been among the main tools for the diffusion of LA21 ideas especially into newly democratized societies. Finally, the article will conclude with an overall assessment of the LA21 situation on the Baltic rim.

A Low Power Consumption Algorithm for Efficient Energy Consumption in ZigBee Motes

PubMed Central

Muñoz, Pablo; R-Moreno, María D.; F. Barrero, David

2017-01-01

Wireless Sensor Networks (WSNs) are becoming increasingly popular since they can gather information from different locations without wires. This advantage is exploited in applications such as robotic systems, telecare, domotic or smart cities, among others. To gain independence from the electricity grid, WSNs devices are equipped with batteries, therefore their operational time is determined by the time that the batteries can power on the device. As a consequence, engineers must consider low energy consumption as a critical objective to design WSNs. Several approaches can be taken to make efficient use of energy in WSNs, for instance low-duty-cycling sensor networks (LDC-WSN). Based on the LDC-WSNs, we present LOKA, a LOw power Konsumption Algorithm to minimize WSNs energy consumption using different power modes in a sensor mote. The contribution of the work is a novel algorithm called LOKA that implements two duty-cycling mechanisms using the end-device of the ZigBee protocol (of the Application Support Sublayer) and an external microcontroller (Cortex M0+) in order to minimize the energy consumption of a delay tolerant networking. Experiments show that using LOKA, the energy required by the sensor device is reduced to half with respect to the same sensor device without using LOKA. PMID:28937660

A Low Power Consumption Algorithm for Efficient Energy Consumption in ZigBee Motes.

PubMed

Vaquerizo-Hdez, Daniel; Muñoz, Pablo; R-Moreno, María D; F Barrero, David

2017-09-22

Wireless Sensor Networks (WSNs) are becoming increasingly popular since they can gather information from different locations without wires. This advantage is exploited in applications such as robotic systems, telecare, domotic or smart cities, among others. To gain independence from the electricity grid, WSNs devices are equipped with batteries, therefore their operational time is determined by the time that the batteries can power on the device. As a consequence, engineers must consider low energy consumption as a critical objective to design WSNs. Several approaches can be taken to make efficient use of energy in WSNs, for instance low-duty-cycling sensor networks (LDC-WSN). Based on the LDC-WSNs, we present LOKA, a LOw power Konsumption Algorithm to minimize WSNs energy consumption using different power modes in a sensor mote. The contribution of the work is a novel algorithm called LOKA that implements two duty-cycling mechanisms using the end-device of the ZigBee protocol (of the Application Support Sublayer) and an external microcontroller (Cortex M0+) in order to minimize the energy consumption of a delay tolerant networking. Experiments show that using LOKA, the energy required by the sensor device is reduced to half with respect to the same sensor device without using LOKA.

Neonatal Brain Hemorrhage (NBH) of Prematurity: Translational Mechanisms of the Vascular-Neural Network

PubMed Central

Lekic, Tim; Klebe, Damon; Poblete, Roy; Krafft, Paul R.; Rolland, William B.; Tang, Jiping; Zhang, John H.

2015-01-01

Neonatal brain hemorrhage (NBH) of prematurity is an unfortunate consequence of preterm birth. Complications result in shunt dependence and long-term structural changes such as post-hemorrhagic hydrocephalus, periventricular leukomalacia, gliosis, and neurological dysfunction. Several animal models are available to study this condition, and many basic mechanisms, etiological factors, and outcome consequences, are becoming understood. NBH is an important clinical condition, of which treatment may potentially circumvent shunt complication, and improve functional recovery (cerebral palsy, and cognitive impairments). This review highlights key pathophysiological findings of the neonatal vascular-neural network in the context of molecular mechanisms targeting the post-hemorrhagic hydrocephalus affecting this vulnerable infant population. PMID:25620100

Decadal Bering Sea seascape change: consequences for Pacific walruses and indigenous hunters.

PubMed

Ray, G Carleton; Hufford, Gary L; Overland, James E; Krupnik, Igor; McCormick-Ray, Jerry; Frey, Karen; Labunski, Elizabeth

2016-01-01

The most significant factors currently affecting the Pacific walrus (Odobenus rosmarus divergens) population are climate change and consequent changes in sea-ice morphology and dynamics. This paper integrates recent physical sea-ice change in the Bering Sea with biological and ecological conditions of walruses in their winter-spring reproductive habitat. Historically, walrus in winter-spring depended on a critical mass of sea-ice habitat to optimize social networking, reproductive fitness, feeding behavior, migration, and energetic efficiency. During 2003-2013, our cross-disciplinary, multiscale analysis from shipboard observations, satellite imagery, and ice-floe tracking, reinforced by information from indigenous subsistence hunters, documented change of sea-ice structure from a plastic continuum to a "mixing bowl" of ice floes moving more independently. This fragmentation of winter habitat preconditions the walrus population toward dispersal mortality and will also negatively affect the availability of resources for indigenous communities. We urge an expanded research and management agenda that integrates walrus natural history and habitat more completely with changing sea-ice morphology and dynamics at multiple scales, while also meeting the needs of local communities.