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Sample records for actor network theory

  1. Actor-Network Theory of Cosmopolitan Education

    ERIC Educational Resources Information Center

    Saito, Hiro

    2010-01-01

    In the past, philosophers discussed cosmopolitanism as a normative ideal of allegiance to humanity as a whole. A debate among social theorists, however, has examined cosmopolitanism as an incipient empirical phenomenon: an orientation of openness to foreign others and cultures. This paper introduces actor-network theory to elaborate the…

  2. Using actor network theory to understand network centric healthcare operations.

    PubMed

    Wickramasinghe, Nilmini; Bali, Rajeev K; Tatnall, Arthur

    2007-01-01

    The adoption and diffusion of e-health and the application of ICT in healthcare is being heralded as the panacea with both European and US governments making e-health a priority on their agendas. In this context, a model of networkcentric healthcare operations has been proffered as the best way to maximise the benefits of ICT use in healthcare. We suggest that, before we can move forward and realise such a state, it is vital to examine the critical issues, likely barriers and facilitators and, most importantly, the critical success factors. To do this however, we need an appropriate cognitive lens through which we can capture all the complexities of healthcare dynamics. In this paper we suggest why Actor Network Theory (ANT) should be this lens. PMID:18048305

  3. Reassembling the Social - An Introduction to Actor-Network-Theory

    NASA Astrophysics Data System (ADS)

    Latour, Bruno

    2005-09-01

    Reassembling the Social is a fundamental challenge from one of the world's leading social theorists to how we understand society and the 'social'. Bruno Latour's contention is that the world 'social' as used by Social Scientists has become laden with assumptions to the point where it has become misnomer. When the adjective is applied to a phenomenon, it is used to indicate a stabilized state of affairs, a bundle of ties that in due course may be used to account for another phenomenon. But Latour also finds the word used as if it described a type of material, in a comparable way to an adjective such as 'wooden' or 'steely'. Rather than simply indicating what is already assembled together, it is now used in a way that makes assumptions about the nature of what is assembled. It has become a word that designates two distinct things: a process of assembling: and a type of material, distinct from others. Latour shows why 'the social' cannot be thought of as a kind of material or domain, and disputes attempts to provide a 'social explanation' of other states of affairs. While these attempts have been productive (and probably necessary) in the past, the very success of the social sciences mean that they are largely no longer so. At the present stage it is no longer possible to inspect the precise constituents entering the social domain. Latour returns to the original meaning of 'the social' to redefine the notion and allow it to trace connections again. It will then be possible to resume the traditional goal of the social sciences, but using more refined tools. Drawing on his extensive work examining the 'assemblages' of nature, Latour finds it necessary to scrutinize thoroughly the exact content of what is assembled under the umbrella of Society. This approach, a 'sociology of associations' has become known as Actor-Network-Theory, and this book is an essential introduction both for those seeking to understand Actor-Network-Theory, or the ideas of one of its most

  4. Nonhumans Unbound: Actor-Network Theory and the Reconsideration of "Things" in Educational Foundations

    ERIC Educational Resources Information Center

    Waltz, Scott B.

    2006-01-01

    The aim of this paper is to call attention to the missing discourse of non-humans as social actors in the Social Foundations of Education. The paper outlines three common figuring metaphors that impede the adoption of such a theoretical discourse and shows how Actor-Network Theory (ANT), more recently developed in the nascent field of Science and…

  5. Reading Educational Reform with Actor Network Theory: Fluid Spaces, Otherings, and Ambivalences

    ERIC Educational Resources Information Center

    Fenwick, Tara

    2011-01-01

    In considering two extended examples of educational reform efforts, this discussion traces relations that become visible through analytic approaches associated with actor-network theory (ANT). The strategy here is to present multiple readings of the two examples. The first reading adopts an ANT approach to follow ways that all actors--human and…

  6. ("Un")Doing Standards in Education with Actor-Network Theory

    ERIC Educational Resources Information Center

    Fenwick, Tara J.

    2010-01-01

    Recent critiques have drawn important attention to the depoliticized consensus and empty promises embedded in network discourses of educational policy. While acceding this critique, this discussion argues that some forms of network analysis--specifically those adopting actor-network theory (ANT) approaches--actually offer useful theoretical…

  7. Theorising big IT programmes in healthcare: strong structuration theory meets actor-network theory.

    PubMed

    Greenhalgh, Trisha; Stones, Rob

    2010-05-01

    The UK National Health Service is grappling with various large and controversial IT programmes. We sought to develop a sharper theoretical perspective on the question "What happens - at macro-, meso- and micro-level - when government tries to modernise a health service with the help of big IT?" Using examples from data fragments at the micro-level of clinical work, we considered how structuration theory and actor-network theory (ANT) might be combined to inform empirical investigation. Giddens (1984) argued that social structures and human agency are recursively linked and co-evolve. ANT studies the relationships that link people and technologies in dynamic networks. It considers how discourses become inscribed in data structures and decision models of software, making certain network relations irreversible. Stones' (2005) strong structuration theory (SST) is a refinement of Giddens' work, systematically concerned with empirical research. It views human agents as linked in dynamic networks of position-practices. A quadripartite approcach considers [a] external social structures (conditions for action); [b] internal social structures (agents' capabilities and what they 'know' about the social world); [c] active agency and actions and [d] outcomes as they feed back on the position-practice network. In contrast to early structuration theory and ANT, SST insists on disciplined conceptual methodology and linking this with empirical evidence. In this paper, we adapt SST for the study of technology programmes, integrating elements from material interactionism and ANT. We argue, for example, that the position-practice network can be a socio-technical one in which technologies in conjunction with humans can be studied as 'actants'. Human agents, with their complex socio-cultural frames, are required to instantiate technology in social practices. Structurally relevant properties inscribed and embedded in technological artefacts constrain and enable human agency. The fortunes

  8. `The Social' and Beyond: Introducing Actor-Network Theory

    NASA Astrophysics Data System (ADS)

    Dolwick, Jim S.

    2009-06-01

    In recent years, it has been suggested (e.g. TAG 2002, 2006; IKUWA3 2008) that it is necessary for the discipline to move beyond the study of ships and boats towards the ‘wider social contexts’ of seafaring and maritime activity. This paper investigates the contours of ‘social’ as an object of study. Two questions are asked: (1) how is this object defined within sociology, classical and contemporary social theory, and archaeology; and (2) what is the status of nonhumans, physical-material things, artefacts, plants, animals, etc.? After taking a look at several different theories, it is argued that it is not necessary for us to move beyond ships and boats. Instead, an alternative approach is offered, one that allows us to move beyond the restrictive ontology of the social.

  9. Actor-network theory: a tool to support ethical analysis of commercial genetic testing.

    PubMed

    Williams-Jones, Bryn; Graham, Janice E

    2003-12-01

    Social, ethical and policy analysis of the issues arising from gene patenting and commercial genetic testing is enhanced by the application of science and technology studies, and Actor-Network Theory (ANT) in particular. We suggest the potential for transferring ANT's flexible nature to an applied heuristic methodology for gathering empirical information and for analysing the complex networks involved in the development of genetic technologies. Three concepts are explored in this paper--actor-networks, translation, and drift--and applied to the case of Myriad Genetics and their commercial BRACAnalysis genetic susceptibility test for hereditary breast cancer. Treating this test as an active participant in socio-technical networks clarifies the extent to which it interacts with, shapes and is shaped by people, other technologies, and institutions. Such an understanding enables more sophisticated and nuanced technology assessment, academic analysis, as well as public debate about the social, ethical and policy implications of the commercialization of new genetic technologies. PMID:15115034

  10. The proof is in the pudding: putting Actor-Network-Theory to work in medical education.

    PubMed

    Bleakley, Alan

    2012-01-01

    What constitutes valid evidence from medical education research is typically grounded in the scientific paradigm of proof through experiment. Here, explanation through single meaning is privileged over exploration of multiple presentations of phenomena--short, interpretation eclipses appreciation. This approach is challenged as reductive by naturalistic qualitative methods such as rich ethnographic field reports, presented as narratives. Contemporary ethnographic approaches have entered medical education by a back door--disguised as a stable of 'social learning theories'. Communities of Practice theory, Activity Theory and Actor-Network-Theory (ANT) all serve as research practices forming identifiable contemporary ethnographies. 'Evidence' is conceived as exploratory rather than explanatory, through baroque descriptions of innovations in learning organizations, including medicine. ANT is then both a theory of innovation in organizations and an ethnographic method, where practice and theory coincide. ANT is interested primarily not in epistemologies, but in how a phenomenon such as an 'illness' is conceived across differing practices as multiple ontologies (experienced meanings), each meaning generated and suspended within a particular network of effects. How such networks are initiated and developed has significance for rethinking the nature of 'evidence', restoring faith in the value of a good story. PMID:22489979

  11. Actor-Network Theory and its role in understanding the implementation of information technology developments in healthcare

    PubMed Central

    2010-01-01

    Background Actor-Network Theory (ANT) is an increasingly influential, but still deeply contested, approach to understand humans and their interactions with inanimate objects. We argue that health services research, and in particular evaluations of complex IT systems in health service organisations, may benefit from being informed by Actor-Network Theory perspectives. Discussion Despite some limitations, an Actor-Network Theory-based approach is conceptually useful in helping to appreciate the complexity of reality (including the complexity of organisations) and the active role of technology in this context. This can prove helpful in understanding how social effects are generated as a result of associations between different actors in a network. Of central importance in this respect is that Actor-Network Theory provides a lens through which to view the role of technology in shaping social processes. Attention to this shaping role can contribute to a more holistic appreciation of the complexity of technology introduction in healthcare settings. It can also prove practically useful in providing a theoretically informed approach to sampling (by drawing on informants that are related to the technology in question) and analysis (by providing a conceptual tool and vocabulary that can form the basis for interpretations). We draw on existing empirical work in this area and our ongoing work investigating the integration of electronic health record systems introduced as part of England's National Programme for Information Technology to illustrate salient points. Summary Actor-Network Theory needs to be used pragmatically with an appreciation of its shortcomings. Our experiences suggest it can be helpful in investigating technology implementations in healthcare settings. PMID:21040575

  12. Actor-Network Theory as a sociotechnical lens to explore the relationship of nurses and technology in practice: methodological considerations for nursing research.

    PubMed

    Booth, Richard G; Andrusyszyn, Mary-Anne; Iwasiw, Carroll; Donelle, Lorie; Compeau, Deborah

    2016-06-01

    Actor-Network Theory is a research lens that has gained popularity in the nursing and health sciences domains. The perspective allows a researcher to describe the interaction of actors (both human and non-human) within networked sociomaterial contexts, including complex practice environments where nurses and health technology operate. This study will describe Actor-Network Theory and provide methodological considerations for researchers who are interested in using this sociotechnical lens within nursing and informatics-related research. Considerations related to technology conceptualization, levels of analysis, and sampling procedures in Actor-Network Theory based research are addressed. Finally, implications for future nursing research within complex environments are highlighted. PMID:26531190

  13. Learning about a Fish from an ANT: Actor Network Theory and Science Education in the Postgenomic Era

    ERIC Educational Resources Information Center

    Pierce, Clayton

    2015-01-01

    This article uses actor network theory (ANT) to develop a more appropriate model of scientific literacy for students, teachers, and citizens in a society increasingly populated with biotechnological and bioscientific nonhumans. In so doing, I take the recent debate surrounding the first genetically engineered animal food product under review by…

  14. Thinking Management and Leadership within Colleges and Schools Somewhat Differently: A Practice-Based, Actor-Network Theory Perspective

    ERIC Educational Resources Information Center

    Mulcahy, Dianne; Perillo, Suzanne

    2011-01-01

    This article examines the significance of materiality for management and leadership in education using resources provided by actor-network theory (ANT). Espousing the idea that human interactions are mediated by material objects and that these objects participate in the production of practices, ANT affords thinking management and leadership in a…

  15. Opening up the solar box: Cultural resource management and actor network theory in solar energy projects in the Mojave Desert

    NASA Astrophysics Data System (ADS)

    Gorrie, Bryan F.

    This project considers the ways that Actor-Network Theory (ANT) can be brought to bear upon Cultural Resource Management (CRM) practices on renewable energy projects. ANT is a way of making inquiry into scientific knowledge practices and as CRM is intended to preserve environmental, historic, and prehistoric resources, it necessarily involves certain kinds of knowledge generation about regions in which projects are being developed. Because the practice of CRM is complex, involving a range of actors from developers to biologists, native peoples to academics, private landholders to environmental and cultural activists, it is imperative to account for the interests of all stakeholders and to resist devolving into the polemical relations of winners and losers, good and bad participants, or simple situations of right and wrong. This project intends to account for the "matters of concern" of various actors, both primary and secondary, by examining the case study of a single solar installation project in the Mojave Desert. A theoretical description of ANT is provided at the beginning and the concerns of this theory are brought to bear upon the case study project through describing the project, discussing the laws governing CRM on federal lands and in the state of California, and providing the points of view of various interviewees who worked directly or indirectly on various aspects of CRM for the solar project. The creators of ANT claim that it is not a methodology but it does speak to ethnomethodologies in that it insists that there is always something more to learn from inquiring into and describing any given situation. These descriptions avoid generalizations, providing instead various points of entry, from diverse perspectives to the project. There is an invitation to avoid assuming that one knows all there is to know about a given situation and to choose instead to continue investigating and thus give voice to the more obscure, often marginalized, voices in the

  16. An Actor-Network Theory Analysis of Policy Innovation for Smoke-Free Places: Understanding Change in Complex Systems

    PubMed Central

    Borland, Ron; Coghill, Ken

    2010-01-01

    Complex, transnational issues like the tobacco epidemic are major challenges that defy analysis and management by conventional methods, as are other public health issues, such as those associated with global food distribution and climate change. We examined the evolution of indoor smoke-free regulations, a tobacco control policy innovation, and identified the key attributes of those jurisdictions that successfully pursued this innovation and those that to date have not. In doing so, we employed the actor-network theory, a comprehensive framework for the analysis of fundamental system change. Through our analysis, we identified approaches to help overcome some systemic barriers to the solution of the tobacco problem and comment on other complex transnational problems. PMID:20466949

  17. Learning about a fish from an ANT: actor network theory and science education in the postgenomic era

    NASA Astrophysics Data System (ADS)

    Pierce, Clayton

    2015-03-01

    This article uses actor network theory (ANT) to develop a more appropriate model of scientific literacy for students, teachers, and citizens in a society increasingly populated with biotechnological and bioscientific nonhumans. In so doing, I take the recent debate surrounding the first genetically engineered animal food product under review by the FDA, AquaBounty Technologies' AquAdvantage® salmon, as a vehicle for exploring the ways in which the biosciences have fundamentally altered the boundary between nature and culture and thus the way the public understands both. In response to the new challenges of a postgenomic society, I outline three frameworks for using ANT literacies in classroom settings. Each frame, I argue, is foundational to the development of a scientific literacy that can trace and map actors involved in controversies such as the AquAdvantage® salmon. In examining these frames I follow the actor of a salmon through an environmental history lens, the technoscientific literacy operating in AquaBounty's FDA application and the National Academies new science education framework, and finally to a model of democracy rooted in an ethic of the common. The ultimate claim of this article is that until science education (and education in general) can begin to include nonhumans such as the AquAdvantage® salmon as part of a common political framework, students, educators, and community members will continue to be at the mercy of experts and corporate stakeholders for defining the terms in which people heal, feed, and educate themselves now and in the future.

  18. Institutional Ethnography and Actor-Network Theory: A Framework for Researching the Assessment of Trainee Teachers

    ERIC Educational Resources Information Center

    Tummons, Jonathan

    2010-01-01

    This article provides an analysis of assessment practices on one university-led teacher-training course in England, delivered across a network of further education colleges. After establishing that assessment practices are bound up in texts of different kinds, this article draws on two theoretical frameworks--institutional ethnography and…

  19. Actor Networks and the Division of Knowledge in the University.

    ERIC Educational Resources Information Center

    Busch, Lawrence

    This paper discusses the current division of knowledge at the college and university level, its historical roots, and the application of Actor Network Theory (ANT) to arrive at an explanation of the permanence of the current division of knowledge as well as what form a new division of knowledge might take. It finds fragmentation and disintegration…

  20. Collaboration and entanglement: An actor-network theory analysis of team-based intraprofessional care for patients with advanced heart failure.

    PubMed

    McDougall, A; Goldszmidt, M; Kinsella, E A; Smith, S; Lingard, L

    2016-09-01

    Despite calls for more interprofessional and intraprofessional team-based approaches in healthcare, we lack sufficient understanding of how this happens in the context of patient care teams. This multi-perspective, team-based interview study examined how medical teams negotiated collaborative tensions. From 2011 to 2013, 50 patients across five sites in three Canadian provinces were interviewed about their care experiences and were asked to identify members of their health care teams. Patient-identified team members were subsequently interviewed to form 50 "Team Sampling Units" (TSUs), consisting of 209 interviews with patients, caregivers and healthcare providers. Results are gathered from a focused analysis of 13 TSUs where intraprofessional collaborative tensions involved treating fluid overload, or edema, a common HF symptom. Drawing on actor-network theory (ANT), the analysis focused on intraprofessional collaboration between specialty care teams in cardiology and nephrology. The study found that despite a shared narrative of common purpose between cardiology teams and nephrology teams, fluid management tools and techniques formed sites of collaborative tension. In particular, care activities involved asynchronous clinical interpretations, geographically distributed specialist care, fragmented forms of communication, and uncertainty due to clinical complexity. Teams 'disentangled' fluid in order to focus on its physiological function and mobilisation. Teams also used distinct 'framings' of fluid management that created perceived collaborative tensions. This study advances collaborative entanglement as a conceptual framework for understanding, teaching, and potentially ameliorating some of the tensions that manifest during intraprofessional care for patients with complex, chronic disease. PMID:27490299

  1. Ship Finds and Their Management as Actor Network

    NASA Astrophysics Data System (ADS)

    Tuddenham, David Berg

    2012-12-01

    Ship finds in Norwegian waters that are more than 100 years old came under the jurisdiction of the Cultural Heritage Management (CHM) in 1963, when section 12a of the Norwegian Cultural Heritage Act was implemented. As a consequence, a functional division between land and sea was created where management objects receive different values depending on whether or not they belong to a ship. The objective of this paper is to review Norwegian CHM underwater policy, and discuss the creation of a new management object and its borders with the introduction of a section on ship finds specifically focusing on Actor Network Theory. It is argued that the understanding of the ship find and its belongings can not be understood as something based on inherent qualities to the management object. Instead this paper proposes to comprehend the ship find as a phenomenon held together within a heterogeneous network.

  2. Exchange Studies as Actor-Networks: Following Korean Exchange Students in Swedish Higher Education

    ERIC Educational Resources Information Center

    Ahn, Song-ee

    2011-01-01

    This article explores how Korean exchange students organized their studies during exchange programs in Swedish higher education. For most students, the programs became a disordered period in relation to their education. The value of exchange studies seems mainly to be extra-curricular. Drawing upon actor network theory, the article argues that the…

  3. ("un")Doing the Next Generation Science Standards: Climate Change Education Actor-Networks in Oklahoma

    ERIC Educational Resources Information Center

    Colston, Nicole M.; Ivey, Toni A.

    2015-01-01

    This exploratory research investigated how science education communities of practice in Oklahoma engage in translations of climate change education (CCE). Applications of actor-network theory to educational policymaking facilitate this analysis of the spaces of prescription and spaces of negotiation that characterize CCE in Oklahoma. Informed by…

  4. Ordering Subjects: Actor-Networks and Intellectual Technologies in Lifelong Learning.

    ERIC Educational Resources Information Center

    Edwards, Richard

    2003-01-01

    Argues that discourses of lifelong learning act as intellectual technologies that construct individuals as subjects in a learning society. Discuses three discourses using actor-network theory: (1) economics/human capital (individuals as accumulators of skills for competitiveness); (2) humanistic psychology (individuals seeking fulfilment through…

  5. Extended mind and after: socially extended mind and actor-network.

    PubMed

    Kono, Tetsuya

    2014-03-01

    The concept of extended mind has been impressively developed over the last 10 years by many philosophers and cognitive scientists. The extended mind thesis (EM) affirms that the mind is not simply ensconced inside the head, but extends to the whole system of brain-body-environment. Recently, some philosophers and psychologists try to adapt the idea of EM to the domain of social cognition research. Mind is socially extended (SEM). However, EM/SEM theory has problems to analyze the interactions among a subject and its surroundings with opposition, antagonism, or conflict; it also tends to think that the environment surrounding the subject is passive or static, and to neglect the power of non-human actants to direct and regulate the human subject. In these points, actor-network theory (ANT) proposed by Latour and Callon is more persuasive, while sharing some important ideas with EM/SEM theory. Actor-network is a hybrid community which is composed of a series of heterogeneous elements, animate and inanimate for a certain period of time. I shall conclude that EM/SEM could be best analyzed as a special case of actor-network. EM/SEM is a system which can be controlled by a human agent alone. In order to understand collective behavior, philosophy and psychology have to study the actor-network in which human individuals are situated. PMID:23975479

  6. Reactors, Weapons, X-Rays, and Solar Panels: Using SCOT, Technological Frame, Epistemic Culture, and Actor Network Theory to Investigate Technology

    ERIC Educational Resources Information Center

    Sovacool, Benjamin K.

    2006-01-01

    The article explores how four different theories have been used to investigate technology. It highlights the worth and limitations of each theory and argues that an eclectic, ever-evolving approach to the study of technology is warranted. (Contains 1 table.)

  7. Cognitively Central Actors and Their Personal Networks in an Energy Efficiency Training Program

    ERIC Educational Resources Information Center

    Hytönen, Kaisa; Palonen, Tuire; Hakkarainen, Kai

    2014-01-01

    This article aims to examine cognitively central actors and their personal networks in the emerging field of energy efficiency. Cognitively central actors are frequently sought for professional advice by other actors and, therefore, they are positioned in the middle of a social network. They often are important knowledge resources, especially in…

  8. Two-factor theory, the actor-critic model, and conditioned avoidance.

    PubMed

    Maia, Tiago V

    2010-02-01

    Two-factor theory (Mowrer, 1947, 1951, 1956) remains one of the most influential theories of avoidance, but it is at odds with empirical findings that demonstrate sustained avoidance responding in situations in which the theory predicts that the response should extinguish. This article shows that the well-known actor-critic model seamlessly addresses the problems with two-factor theory, while simultaneously being consistent with the core ideas that underlie that theory. More specifically, the article shows that (1) the actor-critic model bears striking similarities to two-factor theory and explains all of the empirical phenomena that two-factor theory explains, in much the same way, and (2) there are subtle but important differences between the actor-critic model and two-factor theory, which result in the actor-critic model predicting the persistence of avoidance responses that is found empirically. PMID:20065349

  9. Representing Micro-Macro Linkages by Actor-Based Dynamic Network Models

    PubMed Central

    Snijders, Tom A.B.; Steglich, Christian E.G.

    2014-01-01

    Stochastic actor-based models for network dynamics have the primary aim of statistical inference about processes of network change, but may be regarded as a kind of agent-based models. Similar to many other agent-based models, they are based on local rules for actor behavior. Different from many other agent-based models, by including elements of generalized linear statistical models they aim to be realistic detailed representations of network dynamics in empirical data sets. Statistical parallels to micro-macro considerations can be found in the estimation of parameters determining local actor behavior from empirical data, and the assessment of goodness of fit from the correspondence with network-level descriptives. This article studies several network-level consequences of dynamic actor-based models applied to represent cross-sectional network data. Two examples illustrate how network-level characteristics can be obtained as emergent features implied by micro-specifications of actor-based models. PMID:25960578

  10. Ethics in actor networks, or: what Latour could learn from Darwin and Dewey.

    PubMed

    Waelbers, Katinka; Dorstewitz, Philipp

    2014-03-01

    In contemporary Science, Technology and Society (STS) studies, Bruno Latour's Actor Network Theory (ANT) is often used to study how social change arises from interaction between people and technologies. Though Latour's approach is rich in the sense of enabling scholars to appreciate the complexity of many relevant technological, environmental, and social factors in their studies, the approach is poor from an ethical point of view: the doings of things and people are couched in one and the same behaviorist (third person) vocabulary without giving due recognition to the ethical relevance of human intelligence, sympathy and reflection in making responsible choices. This article argues that two other naturalist projects, the non-teleological virtue ethics of Charles Darwin and the pragmatist instrumentalism of John Dewey can enrich ANT-based STS studies, both, in a descriptive and in a normative sense. PMID:23371512

  11. Beyond Dyadic Interdependence: Actor-Oriented Models for Co-Evolving Social Networks and Individual Behaviors

    ERIC Educational Resources Information Center

    Burk, William J.; Steglich, Christian E. G.; Snijders, Tom A. B.

    2007-01-01

    Actor-oriented models are described as a longitudinal strategy for examining the co-evolution of social networks and individual behaviors. We argue that these models provide advantages over conventional approaches due to their ability to account for inherent dependencies between individuals embedded in a social network (i.e., reciprocity,…

  12. Post Disaster Governance, Complexity and Network Theory

    PubMed Central

    Lassa, Jonatan A.

    2015-01-01

    This research aims to understand the organizational network typology of large­-scale disaster intervention in developing countries and to understand the complexity of post-­disaster intervention, through the use of network theory based on empirical data from post-­tsunami reconstruction in Aceh, Indonesia, during 2005/­2007. The findings suggest that the ‘ degrees of separation’ (or network diameter) between any two organizations in the field is 5, thus reflecting ‘small­ world’ realities and therefore making no significant difference with the real human networks, as found in previous experiments. There are also significant loops in the network reflecting the fact that some actors tend to not cooperate, which challenges post­ disaster coordination. The findings show the landscape of humanitarian actors is not randomly distributed. Many actors were connected to each other through certain hubs, while hundreds of actors make ‘scattered’ single ‘principal-­client’ links. The paper concludes that by understanding the distribution of degree, centrality, ‘degrees of separation’ and visualization of the network, authorities can improve their understanding of the realities of coordination, from macro to micro scales. PMID:26236562

  13. A spiking neural network model of an actor-critic learning agent.

    PubMed

    Potjans, Wiebke; Morrison, Abigail; Diesmann, Markus

    2009-02-01

    The ability to adapt behavior to maximize reward as a result of interactions with the environment is crucial for the survival of any higher organism. In the framework of reinforcement learning, temporal-difference learning algorithms provide an effective strategy for such goal-directed adaptation, but it is unclear to what extent these algorithms are compatible with neural computation. In this article, we present a spiking neural network model that implements actor-critic temporal-difference learning by combining local plasticity rules with a global reward signal. The network is capable of solving a nontrivial gridworld task with sparse rewards. We derive a quantitative mapping of plasticity parameters and synaptic weights to the corresponding variables in the standard algorithmic formulation and demonstrate that the network learns with a similar speed to its discrete time counterpart and attains the same equilibrium performance. PMID:19196231

  14. Actors and networks in resource conflict resolution under climate change in rural Kenya

    NASA Astrophysics Data System (ADS)

    Ngaruiya, Grace W.; Scheffran, Jürgen

    2016-05-01

    The change from consensual decision-making arrangements into centralized hierarchical chieftaincy schemes through colonization disrupted many rural conflict resolution mechanisms in Africa. In addition, climate change impacts on land use have introduced additional socio-ecological factors that complicate rural conflict dynamics. Despite the current urgent need for conflict-sensitive adaptation, resolution efficiency of these fused rural institutions has hardly been documented. In this context, we analyse the Loitoktok network for implemented resource conflict resolution structures and identify potential actors to guide conflict-sensitive adaptation. This is based on social network data and processes that are collected using the saturation sampling technique to analyse mechanisms of brokerage. We find that there are three different forms of fused conflict resolution arrangements that integrate traditional institutions and private investors in the community. To effectively implement conflict-sensitive adaptation, we recommend the extension officers, the council of elders, local chiefs and private investors as potential conduits of knowledge in rural areas. In conclusion, efficiency of these fused conflict resolution institutions is aided by the presence of holistic resource management policies and diversification in conflict resolution actors and networks.

  15. Multirate parallel distributed compensation of a cluster in wireless sensor and actor networks

    NASA Astrophysics Data System (ADS)

    Yang, Chun-xi; Huang, Ling-yun; Zhang, Hao; Hua, Wang

    2016-01-01

    The stabilisation problem for one of the clusters with bounded multiple random time delays and packet dropouts in wireless sensor and actor networks is investigated in this paper. A new multirate switching model is constructed to describe the feature of this single input multiple output linear system. According to the difficulty of controller design under multi-constraints in multirate switching model, this model can be converted to a Takagi-Sugeno fuzzy model. By designing a multirate parallel distributed compensation, a sufficient condition is established to ensure this closed-loop fuzzy control system to be globally exponentially stable. The solution of the multirate parallel distributed compensation gains can be obtained by solving an auxiliary convex optimisation problem. Finally, two numerical examples are given to show, compared with solving switching controller, multirate parallel distributed compensation can be obtained easily. Furthermore, it has stronger robust stability than arbitrary switching controller and single-rate parallel distributed compensation under the same conditions.

  16. The Pursuit of Memory: Examining Art Teaching and Pedagogical Practices through Hannah Arendt's Actor-Spectator Theory

    ERIC Educational Resources Information Center

    Lee, Mun Yee

    2011-01-01

    Memories of our schooling and teaching experiences shape our curriculum and pedagogical decision-making process in art education when we become teachers and teacher educators. In this paper, using Hannah Arendt's Actor-Spectator Theory, I engage in retrospective critical introspection of my practices as an art teacher and curriculum developer in…

  17. Holding-based network of nations based on listed energy companies: An empirical study on two-mode affiliation network of two sets of actors

    NASA Astrophysics Data System (ADS)

    Li, Huajiao; Fang, Wei; An, Haizhong; Gao, Xiangyun; Yan, Lili

    2016-05-01

    Economic networks in the real world are not homogeneous; therefore, it is important to study economic networks with heterogeneous nodes and edges to simulate a real network more precisely. In this paper, we present an empirical study of the one-mode derivative holding-based network constructed by the two-mode affiliation network of two sets of actors using the data of worldwide listed energy companies and their shareholders. First, we identify the primitive relationship in the two-mode affiliation network of the two sets of actors. Then, we present the method used to construct the derivative network based on the shareholding relationship between two sets of actors and the affiliation relationship between actors and events. After constructing the derivative network, we analyze different topological features on the node level, edge level and entire network level and explain the meanings of the different values of the topological features combining the empirical data. This study is helpful for expanding the usage of complex networks to heterogeneous economic networks. For empirical research on the worldwide listed energy stock market, this study is useful for discovering the inner relationships between the nations and regions from a new perspective.

  18. 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

  19. Potential Theory for Directed Networks

    PubMed Central

    Zhang, Qian-Ming; Lü, Linyuan; Wang, Wen-Qiang; Zhou, Tao

    2013-01-01

    Uncovering factors underlying the network formation is a long-standing challenge for data mining and network analysis. In particular, the microscopic organizing principles of directed networks are less understood than those of undirected networks. This article proposes a hypothesis named potential theory, which assumes that every directed link corresponds to a decrease of a unit potential and subgraphs with definable potential values for all nodes are preferred. Combining the potential theory with the clustering and homophily mechanisms, it is deduced that the Bi-fan structure consisting of 4 nodes and 4 directed links is the most favored local structure in directed networks. Our hypothesis receives strongly positive supports from extensive experiments on 15 directed networks drawn from disparate fields, as indicated by the most accurate and robust performance of Bi-fan predictor within the link prediction framework. In summary, our main contribution is twofold: (i) We propose a new mechanism for the local organization of directed networks; (ii) We design the corresponding link prediction algorithm, which can not only testify our hypothesis, but also find out direct applications in missing link prediction and friendship recommendation. PMID:23408979

  20. Place-Based Initiatives to Improve Health in Disadvantaged Communities: Cross-Sector Characteristics and Networks of Local Actors in North Carolina

    PubMed Central

    Moody, James; Nelson, Alicia; Willis, Janese M.; Fuller, Lori; Smart, Allen J.; Easterling, Doug; Silberberg, Mina

    2016-01-01

    Objectives. To examine the leadership attributes and collaborative connections of local actors from the health sector and those outside the health sector in a major place-based health initiative. Methods. We used survey data from 340 individuals in 4 Healthy Places North Carolina counties from 2014 to assess the leadership attributes (awareness, attitudes, and capacity) and network connections of local actors by their organizational sector. Results. Respondents’ leadership attributes—scored on 5-point Likert scales—were similar across Healthy Places North Carolina counties. Although local actors reported high levels of awareness and collaboration around community health improvement, we found lower levels of capacity for connecting diversity, identifying barriers, and using resources in new ways to improve community health. Actors outside the health sector had generally lower levels of capacity than actors in the health sector. Those in the health sector exhibited the majority of network ties in their community; however, they were also the most segregated from actors in other sectors. Conclusions. More capacity building around strategic action—particularly in nonhealth sectors—is needed to support efforts in making widespread changes to community health. PMID:27459443

  1. Networks in Action: New Actors and Practices in Education Policy in Brazil

    ERIC Educational Resources Information Center

    Shiroma, Eneida Oto

    2014-01-01

    This paper focuses on the role of networks in the policy-making process in education and discusses the potential of network analysis as an analytical tool for education policy research. Drawing on publically available data from personal or institutional websites, this paper reports the findings from research carried out between 2005 and 2011.…

  2. Structuring an integrated care system: interpreted through the enacted diversity of the actors involved—the case of a French healthcare network

    PubMed Central

    Grenier, Corinne

    2011-01-01

    Research question We are looking at the process of structuring an integrated care system as an innovative process that swings back and forth between the diversity of the actors involved, local aspirations and national and regional regulations. We believe that innovation is enriched by the variety of the actors involved, but may also be blocked or disrupted by that diversity. Our research aims to add to other research, which, when questioning these integrated systems, analyses how the actors involved deal with diversity without really questioning it. Case study The empirical basis of the paper is provided by case study analysis. The studied integrated care system is a French healthcare network that brings together healthcare professionals and various organisations in order to improve the way in which interventions are coordinated and formalised, in order to promote better detection and diagnosis procedures and the implementation of a care protocol. We consider this case as instrumental in developing theoretical proposals for structuring an integrated care system in light of the diversity of the actors involved. Results and discussion We are proposing a model for structuring an integrated care system in light of the enacted diversity of the actors involved. This model is based on three factors: the diversity enacted by the leaders, three stances for considering the contribution made by diversity in the structuring process and the specific leading role played by those in charge of the structuring process. Through this process, they determined how the actors involved in the project were differentiated, and on what basis those actors were involved. By mobilising enacted diversity, the leaders are seeking to channel the emergence of a network in light of their own representation of that network. This model adds to published research on the structuring of integrated care systems. PMID:21637706

  3. Interdisciplinary and physics challenges of network theory

    NASA Astrophysics Data System (ADS)

    Bianconi, Ginestra

    2015-09-01

    Network theory has unveiled the underlying structure of complex systems such as the Internet or the biological networks in the cell. It has identified universal properties of complex networks, and the interplay between their structure and dynamics. After almost twenty years of the field, new challenges lie ahead. These challenges concern the multilayer structure of most of the networks, the formulation of a network geometry and topology, and the development of a quantum theory of networks. Making progress on these aspects of network theory can open new venues to address interdisciplinary and physics challenges including progress on brain dynamics, new insights into quantum technologies, and quantum gravity.

  4. Short Cuts and Extended Techniques: Rethinking Relations between Technology and Educational Theory

    ERIC Educational Resources Information Center

    Thumlert, Kurt; de Castell, Suzanne; Jenson, Jennifer

    2015-01-01

    Building upon a recent call to renew actor-network theory (ANT) for educational research, this article reconsiders relations between technology and educational theory. Taking cues from actor-network theorists, this discussion considers the technologically-mediated networks in which learning actors are situated, acted upon, and acting, and traces…

  5. Actor and partner effects of perceived HIV stigma on social network components among people living with HIV/AIDS and their caregivers

    PubMed Central

    Hao, Chun; Liu, Hongjie

    2014-01-01

    Background Few studies have investigated the relationship between HIV stigma and social network components at the dyadic level. The objective of this study was to examine the actor and partner effects of perceived HIV stigma by people living with HIV/AIDS (PLWHAs) and their caregivers on social network variables at the dyadic level. Method An egocentric social network study was conducted among 147 dyads consisting of one PLWHA and one caregiver (294 participants) in Nanning, China. The actor-partner interdependence model (APIM) was used to analyze the relationships between perceived HIV stigma and social network components (network relations, network structures, and network functions) at the dyadic level. Results We found in this dyadic analysis that: (1) social network components were similar between PLWHAs and their caregivers; (2) HIV stigma perceived by PLWHAs influenced their own social network components, whereas this influence did not exist between caregivers' perceived HIV stigma and their own social network components; (3) a few significant partner effects were observed between HIV stigma and social network components among both PLWHAs and caregivers. Conclusion The interrelationships between HIV stigma and social network components were complex at the dyadic level. Future interventions programs targeting HIV stigma should focus on the interpersonal relationship at the dyadic level, beyond the intrapersonal factors. PMID:25085478

  6. An Actor-Based Model of Social Network Influence on Adolescent Body Size, Screen Time, and Playing Sports

    PubMed Central

    Shoham, David A.; Tong, Liping; Lamberson, Peter J.; Auchincloss, Amy H.; Zhang, Jun; Dugas, Lara; Kaufman, Jay S.; Cooper, Richard S.; Luke, Amy

    2012-01-01

    Recent studies suggest that obesity may be “contagious” between individuals in social networks. Social contagion (influence), however, may not be identifiable using traditional statistical approaches because they cannot distinguish contagion from homophily (the propensity for individuals to select friends who are similar to themselves) or from shared environmental influences. In this paper, we apply the stochastic actor-based model (SABM) framework developed by Snijders and colleagues to data on adolescent body mass index (BMI), screen time, and playing active sports. Our primary hypothesis was that social influences on adolescent body size and related behaviors are independent of friend selection. Employing the SABM, we simultaneously modeled network dynamics (friendship selection based on homophily and structural characteristics of the network) and social influence. We focused on the 2 largest schools in the National Longitudinal Study of Adolescent Health (Add Health) and held the school environment constant by examining the 2 school networks separately (N = 624 and 1151). Results show support in both schools for homophily on BMI, but also for social influence on BMI. There was no evidence of homophily on screen time in either school, while only one of the schools showed homophily on playing active sports. There was, however, evidence of social influence on screen time in one of the schools, and playing active sports in both schools. These results suggest that both homophily and social influence are important in understanding patterns of adolescent obesity. Intervention efforts should take into consideration peers’ influence on one another, rather than treating “high risk” adolescents in isolation. PMID:22768124

  7. When private actors matter: Information-sharing network and surveillance of Highly Pathogenic Avian Influenza in Vietnam.

    PubMed

    Delabouglise, A; Dao, T H; Truong, D B; Nguyen, T T; Nguyen, N T X; Duboz, R; Fournié, G; Antoine-Moussiaux, N; Grosbois, V; Vu, D T; Le, T H; Nguyen, V K; Salem, G; Peyre, M

    2015-07-01

    The effectiveness of animal health surveillance systems depends on their capacity to gather sanitary information from the animal production sector. In order to assess this capacity we analyzed the flow of sanitary information regarding Highly Pathogenic Avian Influenza (HPAI) suspicions in poultry in Vietnam. Participatory methods were applied to assess the type of actors and likelihood of information sharing between actors in case of HPAI suspicion in poultry. While the reporting of HPAI suspicions is mandatory, private actors had more access to information than public actors. Actors of the upstream sector (medicine and feed sellers) played a key role in the diffusion of information. The central role of these actors and the influence of the information flow on the adoption by poultry production stakeholders of behaviors limiting (e.g. prevention measures) or promoting disease transmission (e.g. increased animal movements) should be accounted for in the design of surveillance and control programs. PMID:25847263

  8. Actors and arenas in hybrid networks: implications for environmental policymaking in the Baltic Sea region.

    PubMed

    Joas, Marko; Kern, Kristine; Sandberg, Siv

    2007-04-01

    Policymaking within and among states is under pressure for change. One feature of this change is empirically observed as an activation of different network structures in the Baltic Sea Region, especially since the collapse of the Iron Curtain, the initiation of the Rio process, and the enlargement of the European Union. The contemporary theoretical debates about governance highlight the changing conditions for policymaking and implementation on all societal levels. This process of change, especially evident concerning environmental policies, includes new types of networks crossing state borders both at the supranational and the subnational levels. This article illuminates this process of change with empirical data from the project "Governing a Common Sea" (GOVCOM) within the Baltic Sea Research Program (BIREME). PMID:17520939

  9. Network theory for inhomogeneous thermoelectrics

    NASA Astrophysics Data System (ADS)

    Angst, Sebastian; Wolf, Dietrich E.

    2016-04-01

    The Onsager–de Groot–Callen transport theory, implemented as a network model, is used to simulate the transient Harman method, which is widely used experimentally to determine all thermoelectric transport coefficients in a single measurement setup. It is shown that this method systematically overestimates the Seebeck coefficient for samples composed of two different materials. As a consequence, the figure of merit is also overestimated, if the thermal coupling of the measurement setup to the environment is weak. For a mixture of metal and semiconductor particles near metal percolation the figure of merit obtained by the Harman method is more than 100% too large. For a correct interpretation of the experimental data, information on composition and microstructure of the sample are indispensable.

  10. Application of actor level social characteristic indicator selection for the precursory detection of bullies in online social networks

    NASA Astrophysics Data System (ADS)

    White, Holly M.; Fields, Jeremy; Hall, Robert T.; White, Joshua S.

    2016-05-01

    Bullying is a national problem for families, courts, schools, and the economy. Social, educational, and professional lives of victims are affected. Early detection of bullies mitigates destructive effects of bullying. Our previous research found, given specific characteristics of an actor, actor logics can be developed utilizing input from natural language processing and graph analysis. Given similar characteristics of cyberbullies, in this paper, we create specific actor logics and apply these to a select social media dataset for the purpose of rapid identification of cyberbullying.

  11. Social Network Theory and Educational Change

    ERIC Educational Resources Information Center

    Daly, Alan J., Ed.

    2010-01-01

    "Social Network Theory and Educational Change" offers a provocative and fascinating exploration of how social networks in schools can impede or facilitate the work of education reform. Drawing on the work of leading scholars, the book comprises a series of studies examining networks among teachers and school leaders, contrasting formal and…

  12. Beyond mean field theory: statistical field theory for neural networks

    PubMed Central

    Buice, Michael A; Chow, Carson C

    2014-01-01

    Mean field theories have been a stalwart for studying the dynamics of networks of coupled neurons. They are convenient because they are relatively simple and possible to analyze. However, classical mean field theory neglects the effects of fluctuations and correlations due to single neuron effects. Here, we consider various possible approaches for going beyond mean field theory and incorporating correlation effects. Statistical field theory methods, in particular the Doi–Peliti–Janssen formalism, are particularly useful in this regard. PMID:25243014

  13. The role of state and non-state actors in the policy process: the contribution of policy networks to the scale-up of antiretroviral therapy in Thailand.

    PubMed

    Tantivess, Sripen; Walt, Gill

    2008-09-01

    Antiretroviral therapy (ART) is difficult in poor settings. In 2001, the Thai government adopted the policy to scale-up its treatment initiative to meet the needs of all its people. Employing qualitative approaches, including in-depth interviews, document review and direct observation, this study examines the processes by which the universal ART policy developed between 2001 and 2007, with the focus on the connections between actors who shared common interests--so-called policy networks. Research findings illustrate the crucial contributions of non-state networks in the policy process. The supportive roles of public-civic networks could be observed at every policy stage, and at different levels of the health sector. Although this particular health policy may be unique in case and setting, it does suggest clearly that while the state dominated the policy process initially, non-state actors played extremely important roles. Their contribution was not simply at agenda-setting stages--for example by lobbying government--but in the actual development and implementation of health policy. Further it illustrates that these processes were dynamic, took place over long periods and were not limited to national borders, but extended beyond, to include global actors and processes. PMID:18658197

  14. Information theory perspective on network robustness

    NASA Astrophysics Data System (ADS)

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

    2016-01-01

    A crucial challenge in network theory is the study of the robustness of a network when facing a sequence of failures. In this work, we propose a dynamical definition of network robustness based on Information Theory, that considers measurements of the structural changes caused by failures of the network's components. Failures are defined here as a temporal process defined in a sequence. Robustness is then evaluated by measuring dissimilarities between topologies after each time step of the sequence, providing a dynamical information about the topological damage. We thoroughly analyze the efficiency of the method in capturing small perturbations by considering different probability distributions on networks. In particular, we find that distributions based on distances are more consistent in capturing network structural deviations, as better reflect the consequences of the failures. Theoretical examples and real networks are used to study the performance of this methodology.

  15. Networking Theories by Iterative Unpacking

    ERIC Educational Resources Information Center

    Koichu, Boris

    2014-01-01

    An iterative unpacking strategy consists of sequencing empirically-based theoretical developments so that at each step of theorizing one theory serves as an overarching conceptual framework, in which another theory, either existing or emerging, is embedded in order to elaborate on the chosen element(s) of the overarching theory. The strategy is…

  16. Post Disaster Governance, Complexity and Network Theory: Evidence from Aceh, Indonesia After the Indian Ocean Tsunami 2004.

    PubMed

    Lassa, Jonatan A

    2015-01-01

    This research aims to understand the organizational network typology of large--scale disaster intervention in developing countries and to understand the complexity of post--disaster intervention, through the use of network theory based on empirical data from post--tsunami reconstruction in Aceh, Indonesia, during 2005/-2007. The findings suggest that the ' degrees of separation' (or network diameter) between any two organizations in the field is 5, thus reflecting 'small- world' realities and therefore making no significant difference with the real human networks, as found in previous experiments. There are also significant loops in the network reflecting the fact that some actors tend to not cooperate, which challenges post- disaster coordination. The findings show the landscape of humanitarian actors is not randomly distributed. Many actors were connected to each other through certain hubs, while hundreds of actors make 'scattered' single 'principal--client' links. The paper concludes that by understanding the distribution of degree, centrality, 'degrees of separation' and visualization of the network, authorities can improve their understanding of the realities of coordination, from macro to micro scales. PMID:26236562

  17. Graphical Model Theory for Wireless Sensor Networks

    SciTech Connect

    Davis, William B.

    2002-12-08

    Information processing in sensor networks, with many small processors, demands a theory of computation that allows the minimization of processing effort, and the distribution of this effort throughout the network. Graphical model theory provides a probabilistic theory of computation that explicitly addresses complexity and decentralization for optimizing network computation. The junction tree algorithm, for decentralized inference on graphical probability models, can be instantiated in a variety of applications useful for wireless sensor networks, including: sensor validation and fusion; data compression and channel coding; expert systems, with decentralized data structures, and efficient local queries; pattern classification, and machine learning. Graphical models for these applications are sketched, and a model of dynamic sensor validation and fusion is presented in more depth, to illustrate the junction tree algorithm.

  18. Network Security Validation Using Game Theory

    NASA Astrophysics Data System (ADS)

    Papadopoulou, Vicky; Gregoriades, Andreas

    Non-functional requirements (NFR) such as network security recently gained widespread attention in distributed information systems. Despite their importance however, there is no systematic approach to validate these requirements given the complexity and uncertainty characterizing modern networks. Traditionally, network security requirements specification has been the results of a reactive process. This however, limited the immunity property of the distributed systems that depended on these networks. Security requirements specification need a proactive approach. Networks' infrastructure is constantly under attack by hackers and malicious software that aim to break into computers. To combat these threats, network designers need sophisticated security validation techniques that will guarantee the minimum level of security for their future networks. This paper presents a game-theoretic approach to security requirements validation. An introduction to game theory is presented along with an example that demonstrates the application of the approach.

  19. Queuing theory models for computer networks

    NASA Technical Reports Server (NTRS)

    Galant, David C.

    1989-01-01

    A set of simple queuing theory models which can model the average response of a network of computers to a given traffic load has been implemented using a spreadsheet. The impact of variations in traffic patterns and intensities, channel capacities, and message protocols can be assessed using them because of the lack of fine detail in the network traffic rates, traffic patterns, and the hardware used to implement the networks. A sample use of the models applied to a realistic problem is included in appendix A. Appendix B provides a glossary of terms used in this paper. This Ames Research Center computer communication network is an evolving network of local area networks (LANs) connected via gateways and high-speed backbone communication channels. Intelligent planning of expansion and improvement requires understanding the behavior of the individual LANs as well as the collection of networks as a whole.

  20. Psychology and social networks: a dynamic network theory perspective.

    PubMed

    Westaby, James D; Pfaff, Danielle L; Redding, Nicholas

    2014-04-01

    Research on social networks has grown exponentially in recent years. However, despite its relevance, the field of psychology has been relatively slow to explain the underlying goal pursuit and resistance processes influencing social networks in the first place. In this vein, this article aims to demonstrate how a dynamic network theory perspective explains the way in which social networks influence these processes and related outcomes, such as goal achievement, performance, learning, and emotional contagion at the interpersonal level of analysis. The theory integrates goal pursuit, motivation, and conflict conceptualizations from psychology with social network concepts from sociology and organizational science to provide a taxonomy of social network role behaviors, such as goal striving, system supporting, goal preventing, system negating, and observing. This theoretical perspective provides psychologists with new tools to map social networks (e.g., dynamic network charts), which can help inform the development of change interventions. Implications for social, industrial-organizational, and counseling psychology as well as conflict resolution are discussed, and new opportunities for research are highlighted, such as those related to dynamic network intelligence (also known as cognitive accuracy), levels of analysis, methodological/ethical issues, and the need to theoretically broaden the study of social networking and social media behavior. (PsycINFO Database Record (c) 2014 APA, all rights reserved). PMID:24750076

  1. Technologies for Learning? An Actor-Network Theory Critique of "Affordances" in Research on Mobile Learning

    ERIC Educational Resources Information Center

    Wright, Steve; Parchoma, Gale

    2011-01-01

    How is the link between learner and technology made in mobile learning? What is the value of the concept of "affordances"? And how does research articulating this concept act to position mobile devices as "technologies for learning"? This literature review used both unstructured and structured search samples of published research on mobile…

  2. Accountability Practices in Adult Education: Insights from Actor-Network Theory

    ERIC Educational Resources Information Center

    Fenwick, Tara

    2010-01-01

    Accountability mechanisms in adult education, their constitution and their effects, are of increasing concern in an era threatening massive reductions to resources for adult education activity. Such mechanisms are frequently portrayed as unassailably oppressive. However, alternative analyses have illuminated contradictions and ambiguities in the…

  3. Polymer networks and gels: Simulation and theory

    NASA Astrophysics Data System (ADS)

    Kenkare, Nirupama Ramamurthy

    1998-12-01

    network pressure is treated as the sum of liquid-like and elastic components. The liquid-like component is obtained by extending the Generalized Flory-Dimer theory to networks, and the elastic component is obtained by treating the network as a set of interpenetrated tree-like structures and using a ideal chain-spring analogy to calculate the free energy. The theoretical predictions for network pressure are in very good agreement with simulation data. Our simulation results for the network chain properties show that the chain end-to-end vectors scale affinely with macroscopic deformation at large densities, but show a weaker-than-affine scaling at low densities. A combined discontinuous molecular dynamics and Monte Carlo simulation technique is used to study the swelling of trifunctional networks of chain lengths 20 and 35 in an athermal solvent. The swelling simulations are conducted under conditions of constant pressure and chemical potential. The gel packing fraction and solvent fraction at swelling equilibrium were found to increase with pressure as expected. We present a simple, analytical theory for gel swelling, grounded in our previous theoretical work for solvent-free networks. The predictions of this theory for the gel properties at swelling equilibrium show remarkably good agreement with simulation results.

  4. Nonequilibrium landscape theory of neural networks

    PubMed Central

    Yan, Han; Zhao, Lei; Hu, Liang; Wang, Xidi; Wang, Erkang; Wang, Jin

    2013-01-01

    The brain map project aims to map out the neuron connections of the human brain. Even with all of the wirings mapped out, the global and physical understandings of the function and behavior are still challenging. Hopfield quantified the learning and memory process of symmetrically connected neural networks globally through equilibrium energy. The energy basins of attractions represent memories, and the memory retrieval dynamics is determined by the energy gradient. However, the realistic neural networks are asymmetrically connected, and oscillations cannot emerge from symmetric neural networks. Here, we developed a nonequilibrium landscape–flux theory for realistic asymmetrically connected neural networks. We uncovered the underlying potential landscape and the associated Lyapunov function for quantifying the global stability and function. We found the dynamics and oscillations in human brains responsible for cognitive processes and physiological rhythm regulations are determined not only by the landscape gradient but also by the flux. We found that the flux is closely related to the degrees of the asymmetric connections in neural networks and is the origin of the neural oscillations. The neural oscillation landscape shows a closed-ring attractor topology. The landscape gradient attracts the network down to the ring. The flux is responsible for coherent oscillations on the ring. We suggest the flux may provide the driving force for associations among memories. We applied our theory to rapid-eye movement sleep cycle. We identified the key regulation factors for function through global sensitivity analysis of landscape topography against wirings, which are in good agreements with experiments. PMID:24145451

  5. Bridging genetic networks and queueing theory

    NASA Astrophysics Data System (ADS)

    Arazi, Arnon; Ben-Jacob, Eshel; Yechiali, Uri

    2004-02-01

    One of the main challenges facing biology today is the understanding of the joint action of genes, proteins and RNA molecules, interwoven in intricate interdependencies commonly known as genetic networks. To this end, several mathematical approaches have been introduced to date. In addition to developing the analytical tools required for this task anew, one can utilize knowledge found in existing disciplines, specializing in the representation and analysis of systems featuring similar aspects. We suggest queueing theory as a possible source of such knowledge. This discipline, which focuses on the study of workloads forming in a variety of scenarios, offers an assortment of tools allowing for the derivation of the statistical properties of the inspected systems. We argue that a proper adaptation of modeling techniques and analytical methods used in queueing theory can contribute to the study of genetic regulatory networks. This is demonstrated by presenting a queueing-inspired model of a genetic network of arbitrary size and structure, for which the probability distribution function is derived. This model is further applied to the description of the lac operon regulation mechanism. In addition, we discuss the possible benefits stemming for queueing theory from the interdisciplinary dialogue with molecular biology-in particular, the incorporation of various dynamical behaviours into queueing networks.

  6. Actor Interdependence in Collaborative Telelearning.

    ERIC Educational Resources Information Center

    Wasson, Barbara; Bourdeau, Jacqueline

    This paper presents a model of collaborative telelearning and describes how coordination theory has provided a framework for the analysis of actor (inter)dependencies in this scenario. The model is intended to inform the instructional design of learning scenarios, the technological design of the telelearning environment, and the design of…

  7. Theory of correlations in stochastic neural networks

    NASA Astrophysics Data System (ADS)

    Ginzburg, Iris; Sompolinsky, Haim

    1994-10-01

    One of the main experimental tools in probing the interactions between neurons has been the measurement of the correlations in their activity. In general, however, the interpretation of the observed correlations is difficult since the correlation between a pair of neurons is influenced not only by the direct interaction between them but also by the dynamic state of the entire network to which they belong. Thus a comparison between the observed correlations and the predictions from specific model networks is needed. In this paper we develop a theory of neuronal correlation functions in large networks comprising several highly connected subpopulations and obeying stochastic dynamic rules. When the networks are in asynchronous states, the cross correlations are relatively weak, i.e., their amplitude relative to that of the autocorrelations is of order of 1/N, N being the size of the interacting populations. Using the weakness of the cross correlations, general equations that express the matrix of cross correlations in terms of the mean neuronal activities and the effective interaction matrix are presented. The effective interactions are the synaptic efficacies multiplied by the gain of the postsynaptic neurons. The time-delayed cross-correlation matrix can be expressed as a sum of exponentially decaying modes that correspond to the (nonorthogonal) eigenvectors of the effective interaction matrix. The theory is extended to networks with random connectivity, such as randomly dilute networks. This allows for a comparison between the contribution from the internal common input and that from the direct interactions to the correlations of monosynaptically coupled pairs. A closely related quantity is the linear response of the neurons to external time-dependent perturbations. We derive the form of the dynamic linear response function of neurons in the above architecture in terms of the eigenmodes of the effective interaction matrix. The behavior of the correlations and the

  8. Stoichiometric network theory for nonequilibrium biochemical systems.

    PubMed

    Qian, Hong; Beard, Daniel A; Liang, Shou-dan

    2003-02-01

    We introduce the basic concepts and develop a theory for nonequilibrium steady-state biochemical systems applicable to analyzing large-scale complex isothermal reaction networks. In terms of the stoichiometric matrix, we demonstrate both Kirchhoff's flux law sigma(l)J(l)=0 over a biochemical species, and potential law sigma(l) mu(l)=0 over a reaction loop. They reflect mass and energy conservation, respectively. For each reaction, its steady-state flux J can be decomposed into forward and backward one-way fluxes J = J+ - J-, with chemical potential difference deltamu = RT ln(J-/J+). The product -Jdeltamu gives the isothermal heat dissipation rate, which is necessarily non-negative according to the second law of thermodynamics. The stoichiometric network theory (SNT) embodies all of the relevant fundamental physics. Knowing J and deltamu of a biochemical reaction, a conductance can be computed which directly reflects the level of gene expression for the particular enzyme. For sufficiently small flux a linear relationship between J and deltamu can be established as the linear flux-force relation in irreversible thermodynamics, analogous to Ohm's law in electrical circuits. PMID:12542691

  9. A game theory model of urban public traffic networks

    NASA Astrophysics Data System (ADS)

    Su, B. B.; Chang, H.; Chen, Y.-Z.; He, D. R.

    2007-06-01

    We have studied urban public traffic networks from the viewpoint of complex networks and game theory. Firstly, we have empirically investigated an urban public traffic network in Beijing in 2003, and obtained its statistical properties. Then a simplified game theory model is proposed for simulating the evolution of the traffic network. The basic idea is that three network manipulators, passengers, an urban public traffic company, and a government traffic management agency, play games in a network evolution process. Each manipulator tries to build the traffic lines to magnify its “benefit”. Simulation results show a good qualitative agreement with the empirical results.

  10. How Might Better Network Theories Support School Leadership Research?

    ERIC Educational Resources Information Center

    Hadfield, Mark; Jopling, Michael

    2012-01-01

    This article explores how recent research in education has applied different aspects of "network" theory to the study of school leadership. Constructs from different network theories are often used because of their perceived potential to clarify two perennial issues in leadership research. The first is the relative importance of formal and…

  11. Nonlinear adaptive networks: A little theory, a few applications

    SciTech Connect

    Jones, R.D.; Qian, S.; Barnes, C.W.; Bisset, K.R.; Bruce, G.M.; Lee, K.; Lee, L.A.; Mead, W.C.; O'Rourke, M.K.; Thode, L.E. ); Lee, Y.C.; Flake, G.W. Maryland Univ., College Park, MD ); Poli, I.J. Bologna Univ. )

    1990-01-01

    We present the theory of nonlinear adaptive networks and discuss a few applications. In particular, we review the theory of feedforward backpropagation networks. We than present the theory of the Connectionist Normalized Linear Spline network in both its feedforward and iterated modes. Also, we briefly discuss the theory of stochastic cellular automata. We then discuss applications to chaotic time series tidal prediction in Venice Lagoon, sonar transient detection, control of nonlinear processes, balancing a double inverted pendulum and design advice for free electron lasers. 26 refs., 23 figs.

  12. An anti-attack model based on complex network theory in P2P networks

    NASA Astrophysics Data System (ADS)

    Peng, Hao; Lu, Songnian; Zhao, Dandan; Zhang, Aixin; Li, Jianhua

    2012-04-01

    Complex network theory is a useful way to study many real systems. In this paper, an anti-attack model based on complex network theory is introduced. The mechanism of this model is based on a dynamic compensation process and a reverse percolation process in P2P networks. The main purpose of the paper is: (i) a dynamic compensation process can turn an attacked P2P network into a power-law (PL) network with exponential cutoff; (ii) a local healing process can restore the maximum degree of peers in an attacked P2P network to a normal level; (iii) a restoring process based on reverse percolation theory connects the fragmentary peers of an attacked P2P network together into a giant connected component. In this way, the model based on complex network theory can be effectively utilized for anti-attack and protection purposes in P2P networks.

  13. The Embedded Self: A Social Networks Approach to Identity Theory

    ERIC Educational Resources Information Center

    Walker, Mark H.; Lynn, Freda B.

    2013-01-01

    Despite the fact that key sociological theories of self and identity view the self as fundamentally rooted in networks of interpersonal relationships, empirical research investigating how personal network structure influences the self is conspicuously lacking. To address this gap, we examine links between network structure and role identity…

  14. Network anomaly detection system with optimized DS evidence theory.

    PubMed

    Liu, Yuan; Wang, Xiaofeng; Liu, Kaiyu

    2014-01-01

    Network anomaly detection has been focused on by more people with the fast development of computer network. Some researchers utilized fusion method and DS evidence theory to do network anomaly detection but with low performance, and they did not consider features of network-complicated and varied. To achieve high detection rate, we present a novel network anomaly detection system with optimized Dempster-Shafer evidence theory (ODS) and regression basic probability assignment (RBPA) function. In this model, we add weights for each sensor to optimize DS evidence theory according to its previous predict accuracy. And RBPA employs sensor's regression ability to address complex network. By four kinds of experiments, we find that our novel network anomaly detection model has a better detection rate, and RBPA as well as ODS optimization methods can improve system performance significantly. PMID:25254258

  15. Analysing collaboration among HIV agencies through combining network theory and relational coordination.

    PubMed

    Khosla, Nidhi; Marsteller, Jill Ann; Hsu, Yea Jen; Elliott, David L

    2016-02-01

    Agencies with different foci (e.g. nutrition, social, medical, housing) serve people living with HIV (PLHIV). Serving needs of PLHIV comprehensively requires a high degree of coordination among agencies which often benefits from more frequent communication. We combined Social Network theory and Relational Coordination theory to study coordination among HIV agencies in Baltimore. Social Network theory implies that actors (e.g., HIV agencies) establish linkages amongst themselves in order to access resources (e.g., information). Relational Coordination theory suggests that high quality coordination among agencies or teams relies on the seven dimensions of frequency, timeliness and accuracy of communication, problem-solving communication, knowledge of agencies' work, mutual respect and shared goals. We collected data on frequency of contact from 57 agencies using a roster method. Response options were ordinal ranging from 'not at all' to 'daily'. We analyzed data using social network measures. Next, we selected agencies with which at least one-third of the sample reported monthly or more frequent interaction. This yielded 11 agencies whom we surveyed on seven relational coordination dimensions with questions scored on a Likert scale of 1-5. Network density, defined as the proportion of existing connections to all possible connections, was 20% when considering monthly or higher interaction. Relational coordination scores from individual agencies to others ranged between 1.17 and 5.00 (maximum possible score 5). The average scores for different dimensions across all agencies ranged between 3.30 and 4.00. Shared goals (4.00) and mutual respect (3.91) scores were highest, while scores such as knowledge of each other's work and problem-solving communication were relatively lower. Combining theoretically driven analyses in this manner offers an innovative way to provide a comprehensive picture of inter-agency coordination and the quality of exchange that underlies

  16. Higher category theory as a paradigm for network applications

    NASA Astrophysics Data System (ADS)

    Bonick, James R.

    2006-05-01

    The importance of network science to the present and future military is unquestioned. Networks of some type pervade every aspect of military operations-a situation that is shared by civilian society. However, several aspects of militarily oriented network science must be considered unique or given significantly greater emphasis than their civilian counterparts. Military, especially battlespace, networks must be mobile and robust. They must utilize diverse sensors moving in and out of the network. They must be able to survive various modes of attack and the destruction of large segments of their structure. Nodes often must pass on classifications made locally while other nodes must serve as combined sensor/classifiers or information coordinators. They must be capable of forming fluidly and in an ad hoc manner. In this paper, it will be shown how category theory, higher category theory, and topos theory provide just the model required by military network science. Category theory is a well-developed mathematical field that views mathematical structures abstractly, often revealing previously unnoticed correspondences. It has been used in database and software modeling, and in sensor and data fusion. It provides an advantage over other modeling formalisms both in its generality and in its extensive theory. Higher category theory extends the insights of category theory into higher dimensions, enhancing robustness. Topos theory was developed, in part, through the application of category theory to logic, but it also has geometric aspects. The motivation behind including topos theory in network science is the idea that a mathematical theory fundamental to geometry and logic should be applicable to the study of systems of spatially distributed information and analysis flow. The structures presented in this paper will have profound and far-reaching applications to military networks.

  17. A Preliminary Theory of Dark Network Resilience

    ERIC Educational Resources Information Center

    Bakker, Rene M.; Raab, Jorg; Milward, H. Brinton

    2012-01-01

    A crucial contemporary policy question for governments across the globe is how to cope with international crime and terrorist networks. Many such "dark" networks--that is, networks that operate covertly and illegally--display a remarkable level of resilience when faced with shocks and attacks. Based on an in-depth study of three cases (MK, the…

  18. Reinforce Networking Theory with OPNET Simulation

    ERIC Educational Resources Information Center

    Guo, Jinhua; Xiang, Weidong; Wang, Shengquan

    2007-01-01

    As networking systems have become more complex and expensive, hands-on experiments based on networking simulation have become essential for teaching the key computer networking topics to students. The simulation approach is the most cost effective and highly useful because it provides a virtual environment for an assortment of desirable features…

  19. Network Anomaly Detection System with Optimized DS Evidence Theory

    PubMed Central

    Liu, Yuan; Wang, Xiaofeng; Liu, Kaiyu

    2014-01-01

    Network anomaly detection has been focused on by more people with the fast development of computer network. Some researchers utilized fusion method and DS evidence theory to do network anomaly detection but with low performance, and they did not consider features of network—complicated and varied. To achieve high detection rate, we present a novel network anomaly detection system with optimized Dempster-Shafer evidence theory (ODS) and regression basic probability assignment (RBPA) function. In this model, we add weights for each senor to optimize DS evidence theory according to its previous predict accuracy. And RBPA employs sensor's regression ability to address complex network. By four kinds of experiments, we find that our novel network anomaly detection model has a better detection rate, and RBPA as well as ODS optimization methods can improve system performance significantly. PMID:25254258

  20. Mean-field theory of echo state networks

    NASA Astrophysics Data System (ADS)

    Massar, Marc; Massar, Serge

    2013-04-01

    Dynamical systems driven by strong external signals are ubiquitous in nature and engineering. Here we study “echo state networks,” networks of a large number of randomly connected nodes, which represent a simple model of a neural network, and have important applications in machine learning. We develop a mean-field theory of echo state networks. The dynamics of the network is captured by the evolution law, similar to a logistic map, for a single collective variable. When the network is driven by many independent external signals, this collective variable reaches a steady state. But when the network is driven by a single external signal, the collective variable is non stationary but can be characterized by its time averaged distribution. The predictions of the mean-field theory, including the value of the largest Lyapunov exponent, are compared with the numerical integration of the equations of motion.

  1. Mean-field theory of echo state networks.

    PubMed

    Massar, Marc; Massar, Serge

    2013-04-01

    Dynamical systems driven by strong external signals are ubiquitous in nature and engineering. Here we study "echo state networks," networks of a large number of randomly connected nodes, which represent a simple model of a neural network, and have important applications in machine learning. We develop a mean-field theory of echo state networks. The dynamics of the network is captured by the evolution law, similar to a logistic map, for a single collective variable. When the network is driven by many independent external signals, this collective variable reaches a steady state. But when the network is driven by a single external signal, the collective variable is non stationary but can be characterized by its time averaged distribution. The predictions of the mean-field theory, including the value of the largest Lyapunov exponent, are compared with the numerical integration of the equations of motion. PMID:23679475

  2. The theory of pattern formation on directed networks

    NASA Astrophysics Data System (ADS)

    Asllani, Malbor; Challenger, Joseph D.; Pavone, Francesco Saverio; Sacconi, Leonardo; Fanelli, Duccio

    2014-07-01

    Dynamical processes on networks have generated widespread interest in recent years. The theory of pattern formation in reaction-diffusion systems defined on symmetric networks has often been investigated, due to its applications in a wide range of disciplines. Here we extend the theory to the case of directed networks, which are found in a number of different fields, such as neuroscience, computer networks and traffic systems. Owing to the structure of the network Laplacian, the dispersion relation has both real and imaginary parts, at variance with the case for a symmetric, undirected network. The homogeneous fixed point can become unstable due to the topology of the network, resulting in a new class of instabilities, which cannot be induced on undirected graphs. Results from a linear stability analysis allow the instability region to be analytically traced. Numerical simulations show travelling waves, or quasi-stationary patterns, depending on the characteristics of the underlying graph.

  3. Modern temporal network theory: a colloquium

    NASA Astrophysics Data System (ADS)

    Holme, Petter

    2015-09-01

    The power of any kind of network approach lies in the ability to simplify a complex system so that one can better understand its function as a whole. Sometimes it is beneficial, however, to include more information than in a simple graph of only nodes and links. Adding information about times of interactions can make predictions and mechanistic understanding more accurate. The drawback, however, is that there are not so many methods available, partly because temporal networks is a relatively young field, partly because it is more difficult to develop such methods compared to for static networks. In this colloquium, we review the methods to analyze and model temporal networks and processes taking place on them, focusing mainly on the last three years. This includes the spreading of infectious disease, opinions, rumors, in social networks; information packets in computer networks; various types of signaling in biology, and more. We also discuss future directions.

  4. Common cold outbreaks: A network theory approach

    NASA Astrophysics Data System (ADS)

    Vishkaie, Faranak Rajabi; Bakouie, Fatemeh; Gharibzadeh, Shahriar

    2014-11-01

    In this study, at first we evaluated the network structure in social encounters by which respiratory diseases can spread. We considered common-cold and recorded a sample of human population and actual encounters between them. Our results show that the database structure presents a great value of clustering. In the second step, we evaluated dynamics of disease spread with SIR model by assigning a function to each node of the structural network. The rate of disease spread in networks was observed to be inversely correlated with characteristic path length. Therefore, the shortcuts have a significant role in increasing spread rate. We conclude that the dynamics of social encounters' network stands between the random and the lattice in network spectrum. Although in this study we considered the period of common-cold disease for network dynamics, it seems that similar approaches may be useful for other airborne diseases such as SARS.

  5. Balanced Centrality of Networks.

    PubMed

    Debono, Mark; Lauri, Josef; Sciriha, Irene

    2014-01-01

    There is an age-old question in all branches of network analysis. What makes an actor in a network important, courted, or sought? Both Crossley and Bonacich contend that rather than its intrinsic wealth or value, an actor's status lies in the structures of its interactions with other actors. Since pairwise relation data in a network can be stored in a two-dimensional array or matrix, graph theory and linear algebra lend themselves as great tools to gauge the centrality (interpreted as importance, power, or popularity, depending on the purpose of the network) of each actor. We express known and new centralities in terms of only two matrices associated with the network. We show that derivations of these expressions can be handled exclusively through the main eigenvectors (not orthogonal to the all-one vector) associated with the adjacency matrix. We also propose a centrality vector (SWIPD) which is a linear combination of the square, walk, power, and degree centrality vectors with weightings of the various centralities depending on the purpose of the network. By comparing actors' scores for various weightings, a clear understanding of which actors are most central is obtained. Moreover, for threshold networks, the (SWIPD) measure turns out to be independent of the weightings. PMID:27437494

  6. Balanced Centrality of Networks

    PubMed Central

    Sciriha, Irene

    2014-01-01

    There is an age-old question in all branches of network analysis. What makes an actor in a network important, courted, or sought? Both Crossley and Bonacich contend that rather than its intrinsic wealth or value, an actor's status lies in the structures of its interactions with other actors. Since pairwise relation data in a network can be stored in a two-dimensional array or matrix, graph theory and linear algebra lend themselves as great tools to gauge the centrality (interpreted as importance, power, or popularity, depending on the purpose of the network) of each actor. We express known and new centralities in terms of only two matrices associated with the network. We show that derivations of these expressions can be handled exclusively through the main eigenvectors (not orthogonal to the all-one vector) associated with the adjacency matrix. We also propose a centrality vector (SWIPD) which is a linear combination of the square, walk, power, and degree centrality vectors with weightings of the various centralities depending on the purpose of the network. By comparing actors' scores for various weightings, a clear understanding of which actors are most central is obtained. Moreover, for threshold networks, the (SWIPD) measure turns out to be independent of the weightings.

  7. An Attractor Network in the Hippocampus: Theory and Neurophysiology

    ERIC Educational Resources Information Center

    Rolls, Edmund T.

    2007-01-01

    A quantitative computational theory of the operation of the CA3 system as an attractor or autoassociation network is described. Based on the proposal that CA3-CA3 autoassociative networks are important for episodic or event memory in which space is a component (place in rodents and spatial view in primates), it has been shown behaviorally that the…

  8. Network Strength Theory of Storage and Retrieval Dynamics

    ERIC Educational Resources Information Center

    Wickelgren, Wayne A.

    1976-01-01

    The notion of strength is defined in several alternative ways for chains of associations connected in series and in parallel. Network strength theory is extended to handle retrieval dynamics for a network of associations, in a manner that permits various degrees of serial versus parallel manner that permits various degrees of serial versus…

  9. Curriculum Theory Network [CTN 4: Winter 1969-70].

    ERIC Educational Resources Information Center

    Herbert, John, Ed.

    This issue of the journal of the "Curriculum Theory Network" contains four major articles on aspects of the curriculum. Karplus, using Science Curriculum Improvement Study as an example, presents three guidelines for developing elementary school science curricula: separate "experience" and "concept" goals; use developmental and learning theories;…

  10. Social Capital Theory: Implications for Women's Networking and Learning

    ERIC Educational Resources Information Center

    Alfred, Mary V.

    2009-01-01

    This chapter describes social capital theory as a framework for exploring women's networking and social capital resources. It presents the foundational assumptions of the theory, the benefits and risks of social capital engagement, a feminist critique of social capital, and the role of social capital in adult learning.

  11. Constructing Careers: Actor, Agent, and Author

    ERIC Educational Resources Information Center

    Savickas, Mark L.

    2011-01-01

    When individuals seek career counseling, they have stories to tell about their working lives. The aim of career construction theory is to be comprehensive in encouraging employment counselors to listen for a client's career story from the perspectives of actor, agent, and author. Taking multiple perspectives on career stories enables counselors to…

  12. Realizing Wisdom Theory in Complex Learning Networks

    ERIC Educational Resources Information Center

    Kok, Ayse

    2009-01-01

    The word "wisdom" is rarely seen in contemporary technology and learning discourse. This conceptual paper aims to provide some clear principles that answer the question: How can we establish wisdom in complex learning networks? By considering the nature of contemporary calls for wisdom the paper provides a metatheoretial framework to evaluate the…

  13. Unravelling the Social Network: Theory and Research

    ERIC Educational Resources Information Center

    Merchant, Guy

    2012-01-01

    Despite the widespread popularity of social networking sites (SNSs) amongst children and young people in compulsory education, relatively little scholarly work has explored the fundamental issues at stake. This paper makes an original contribution to the field by locating the study of this online activity within the broader terrain of social…

  14. Pathways, Networks, and Systems: Theory and Experiments

    SciTech Connect

    Joseph H. Nadeau; John D. Lambris

    2004-10-30

    The international conference provided a unique opportunity for theoreticians and experimenters to exchange ideas, strategies, problems, challenges, language and opportunities in both formal and informal settings. This dialog is an important step towards developing a deep and effective integration of theory and experiments in studies of systems biology in humans and model organisms.

  15. Spectral renormalization group theory on nonspatial networks

    NASA Astrophysics Data System (ADS)

    Tuncer, Asli; Erzan, Ayse

    We recently proposed a ``spectral renormalization group'' scheme, for non-spatial networks with no metric defined on them. We implemented the spectral renormalization group on two deterministic non-spatial networks without translational invariance, namely the Cayley tree and diamond lattice . The thermodynamic critical exponents for the Gaussian model are only functions of the spectral dimension, d ~. The Gaussian fixed point is stable with respect to a Ψ4 perturbation up to second order on these lattices with d ~ = 2 , the lower critical dimension for the Ising universality class. This is expected for the Cayley tree, but for the diamond lattice it is an indication that the perturbation expansion up to second order breaks down at d ~ = 2 , as it does for the Wilson scheme on the square lattice. On generalized diamond lattices, with 2 < d ~ < 4 , we find non-Gaussian fixed points with non-trivial exponents. For d ~ > 4 , the critical behavior is once again mean field.

  16. Biological impacts and context of network theory

    SciTech Connect

    Almaas, E

    2007-01-05

    Many complex systems can be represented and analyzed as networks, and examples that have benefited from this approach span the natural sciences. For instance, we now know that systems as disparate as the World-Wide Web, the Internet, scientific collaborations, food webs, protein interactions and metabolism all have common features in their organization, the most salient of which are their scale-free connectivity distributions and their small-world behavior. The recent availability of large scale datasets that span the proteome or metabolome of an organism have made it possible to elucidate some of the organizational principles and rules that govern their function, robustness and evolution. We expect that combining the currently separate layers of information from gene regulatory-, signal transduction-, protein interaction- and metabolic networks will dramatically enhance our understanding of cellular function and dynamics.

  17. Information theory and the ethylene genetic network.

    PubMed

    González-García, José S; Díaz, José

    2011-10-01

    The original aim of the Information Theory (IT) was to solve a purely technical problem: to increase the performance of communication systems, which are constantly affected by interferences that diminish the quality of the transmitted information. That is, the theory deals only with the problem of transmitting with the maximal precision the symbols constituting a message. In Shannon's theory messages are characterized only by their probabilities, regardless of their value or meaning. As for its present day status, it is generally acknowledged that Information Theory has solid mathematical foundations and has fruitful strong links with Physics in both theoretical and experimental areas. However, many applications of Information Theory to Biology are limited to using it as a technical tool to analyze biopolymers, such as DNA, RNA or protein sequences. The main point of discussion about the applicability of IT to explain the information flow in biological systems is that in a classic communication channel, the symbols that conform the coded message are transmitted one by one in an independent form through a noisy communication channel, and noise can alter each of the symbols, distorting the message; in contrast, in a genetic communication channel the coded messages are not transmitted in the form of symbols but signaling cascades transmit them. Consequently, the information flow from the emitter to the effector is due to a series of coupled physicochemical processes that must ensure the accurate transmission of the message. In this review we discussed a novel proposal to overcome this difficulty, which consists of the modeling of gene expression with a stochastic approach that allows Shannon entropy (H) to be directly used to measure the amount of uncertainty that the genetic machinery has in relation to the correct decoding of a message transmitted into the nucleus by a signaling pathway. From the value of H we can define a function I that measures the amount of

  18. Mean Field Theory for Nonequilibrium Network Reconstruction

    NASA Astrophysics Data System (ADS)

    Roudi, Yasser; Hertz, John

    2011-01-01

    There has been recent progress on inferring the structure of interactions in complex networks when they are in stationary states satisfying detailed balance, but little has been done for nonequilibrium systems. Here we introduce an approach to this problem, considering, as an example, the question of recovering the interactions in an asymmetrically coupled, synchronously updated Sherrington-Kirkpatrick model. We derive an exact iterative inversion algorithm and develop efficient approximations based on dynamical mean-field and Thouless-Anderson-Palmer equations that express the interactions in terms of equal-time and one-time-step-delayed correlation functions.

  19. Complex network theory, streamflow, and hydrometric monitoring system design

    NASA Astrophysics Data System (ADS)

    Halverson, M. J.; Fleming, S. W.

    2015-07-01

    Network theory is applied to an array of streamflow gauges located in the Coast Mountains of British Columbia (BC) and Yukon, Canada. The goal of the analysis is to assess whether insights from this branch of mathematical graph theory can be meaningfully applied to hydrometric data, and, more specifically, whether it may help guide decisions concerning stream gauge placement so that the full complexity of the regional hydrology is efficiently captured. The streamflow data, when represented as a complex network, have a global clustering coefficient and average shortest path length consistent with small-world networks, which are a class of stable and efficient networks common in nature, but the observed degree distribution did not clearly indicate a scale-free network. Stability helps ensure that the network is robust to the loss of nodes; in the context of a streamflow network, stability is interpreted as insensitivity to station removal at random. Community structure is also evident in the streamflow network. A network theoretic community detection algorithm identified separate communities, each of which appears to be defined by the combination of its median seasonal flow regime (pluvial, nival, hybrid, or glacial, which in this region in turn mainly reflects basin elevation) and geographic proximity to other communities (reflecting shared or different daily meteorological forcing). Furthermore, betweenness analyses suggest a handful of key stations which serve as bridges between communities and might be highly valued. We propose that an idealized sampling network should sample high-betweenness stations, small-membership communities which are by definition rare or undersampled relative to other communities, and index stations having large numbers of intracommunity links, while retaining some degree of redundancy to maintain network robustness.

  20. Social Network Theory in Engineering Education

    NASA Astrophysics Data System (ADS)

    Simon, Peter A.

    Collaborative groups are important both in the learning environment of engineering education and, in the real world, the business of engineering design. Selecting appropriate individuals to form an effective group and monitoring a group's progress are important aspects of successful task performance. This exploratory study looked at using the concepts of cognitive social structures, structural balance, and centrality from social network analysis as well as the measures of emotional intelligence. The concepts were used to analyze potential team members to examine if an individual's ability to perceive emotion in others and the self and to use, understand, and manage those emotions are a factor in a group's performance. The students from a capstone design course in computer engineering were used as volunteer subjects. They were formed into groups and assigned a design exercise to determine whether and which of the above-mentioned tools would be effective in both selecting teams and predicting the quality of the resultant design. The results were inconclusive with the exception of an individual's ability to accurately perceive emotions. The instruments that were successful were the Self-Monitoring scale and the accuracy scores derived from cognitive social structures and Level IV of network levels of analysis.

  1. Wireless network traffic modeling based on extreme value theory

    NASA Astrophysics Data System (ADS)

    Liu, Chunfeng; Shu, Yantai; Yang, Oliver W. W.; Liu, Jiakun; Dong, Linfang

    2006-10-01

    In this paper, Extreme Value Theory (EVT) is presented to analyze wireless network traffic. The role of EVT is to allow the development of procedures that are scientifically and statistically rational to estimate the extreme behavior of random processes. There are two primary methods for studying extremes: the Block Maximum (BM) method and the Points Over Threshold (POT) method. By taking limited traffic data that is greater than the threshold value, our experiment and analysis show the wireless network traffic model obtained with the EVT fits well with that of empirical distribution of traffic, thus illustrating that EVT has a good application foreground in the analysis of wireless network traffic.

  2. Percolation theory applied to measures of fragmentation in social networks

    NASA Astrophysics Data System (ADS)

    Chen, Yiping; Paul, Gerald; Cohen, Reuven; Havlin, Shlomo; Borgatti, Stephen P.; Liljeros, Fredrik; Stanley, H. Eugene

    2007-04-01

    We apply percolation theory to a recently proposed measure of fragmentation F for social networks. The measure F is defined as the ratio between the number of pairs of nodes that are not connected in the fragmented network after removing a fraction q of nodes and the total number of pairs in the original fully connected network. We compare F with the traditional measure used in percolation theory, P∞ , the fraction of nodes in the largest cluster relative to the total number of nodes. Using both analytical and numerical methods from percolation, we study Erdős-Rényi and scale-free networks under various types of node removal strategies. The removal strategies are random removal, high degree removal, and high betweenness centrality removal. We find that for a network obtained after removal (all strategies) of a fraction q of nodes above percolation threshold, P∞≈(1-F)1/2 . For fixed P∞ and close to percolation threshold (q=qc) , we show that 1-F better reflects the actual fragmentation. Close to qc , for a given P∞ , 1-F has a broad distribution and it is thus possible to improve the fragmentation of the network. We also study and compare the fragmentation measure F and the percolation measure P∞ for a real social network of workplaces linked by the households of the employees and find similar results.

  3. Percolation theory applied to measures of fragmentation in social networks.

    PubMed

    Chen, Yiping; Paul, Gerald; Cohen, Reuven; Havlin, Shlomo; Borgatti, Stephen P; Liljeros, Fredrik; Stanley, H Eugene

    2007-04-01

    We apply percolation theory to a recently proposed measure of fragmentation F for social networks. The measure F is defined as the ratio between the number of pairs of nodes that are not connected in the fragmented network after removing a fraction q of nodes and the total number of pairs in the original fully connected network. We compare F with the traditional measure used in percolation theory, P(infinity), the fraction of nodes in the largest cluster relative to the total number of nodes. Using both analytical and numerical methods from percolation, we study Erdos-Rényi and scale-free networks under various types of node removal strategies. The removal strategies are random removal, high degree removal, and high betweenness centrality removal. We find that for a network obtained after removal (all strategies) of a fraction q of nodes above percolation threshold, P(infinity) approximately (1-F)1/2. For fixed P(infinity) and close to percolation threshold (q=qc), we show that 1-F better reflects the actual fragmentation. Close to qc, for a given P(infinity), 1-F has a broad distribution and it is thus possible to improve the fragmentation of the network. We also study and compare the fragmentation measure F and the percolation measure P(infinity) for a real social network of workplaces linked by the households of the employees and find similar results. PMID:17500961

  4. Theory of interface: category theory, directed networks and evolution of biological networks.

    PubMed

    Haruna, Taichi

    2013-11-01

    Biological networks have two modes. The first mode is static: a network is a passage on which something flows. The second mode is dynamic: a network is a pattern constructed by gluing functions of entities constituting the network. In this paper, first we discuss that these two modes can be associated with the category theoretic duality (adjunction) and derive a natural network structure (a path notion) for each mode by appealing to the category theoretic universality. The path notion corresponding to the static mode is just the usual directed path. The path notion for the dynamic mode is called lateral path which is the alternating path considered on the set of arcs. Their general functionalities in a network are transport and coherence, respectively. Second, we introduce a betweenness centrality of arcs for each mode and see how the two modes are embedded in various real biological network data. We find that there is a trade-off relationship between the two centralities: if the value of one is large then the value of the other is small. This can be seen as a kind of division of labor in a network into transport on the network and coherence of the network. Finally, we propose an optimization model of networks based on a quality function involving intensities of the two modes in order to see how networks with the above trade-off relationship can emerge through evolution. We show that the trade-off relationship can be observed in the evolved networks only when the dynamic mode is dominant in the quality function by numerical simulations. We also show that the evolved networks have features qualitatively similar to real biological networks by standard complex network analysis. PMID:24012823

  5. Urban traffic-network performance: flow theory and simulation experiments

    SciTech Connect

    Williams, J.C.

    1986-01-01

    Performance models for urban street networks were developed to describe the response of a traffic network to given travel-demand levels. The three basic traffic flow variables, speed, flow, and concentration, are defined at the network level, and three model systems are proposed. Each system consists of a series of interrelated, consistent functions between the three basic traffic-flow variables as well as the fraction of stopped vehicles in the network. These models are subsequently compared with the results of microscopic simulation of a small test network. The sensitivity of one of the model systems to a variety of network features was also explored. Three categories of features were considered, with the specific features tested listed in parentheses: network topology (block length and street width), traffic control (traffic signal coordination), and traffic characteristics (level of inter-vehicular interaction). Finally, a fundamental issue concerning the estimation of two network-level parameters (from a nonlinear relation in the two-fluid theory) was examined. The principal concern was that of comparability of these parameters when estimated with information from a single vehicle (or small group of vehicles), as done in conjunction with previous field studies, and when estimated with network-level information (i.e., all the vehicles), as is possible with simulation.

  6. Network theory and its applications in economic systems

    NASA Astrophysics Data System (ADS)

    Huang, Xuqing

    This dissertation covers the two major parts of my Ph.D. research: i) developing theoretical framework of complex networks; and ii) applying complex networks models to quantitatively analyze economics systems. In part I, we focus on developing theories of interdependent networks, which includes two chapters: 1) We develop a mathematical framework to study the percolation of interdependent networks under targeted-attack and find that when the highly connected nodes are protected and have lower probability to fail, in contrast to single scale-free (SF) networks where the percolation threshold pc = 0, coupled SF networks are significantly more vulnerable with pc significantly larger than zero. 2) We analytically demonstrates that clustering, which quantifies the propensity for two neighbors of the same vertex to also be neighbors of each other, significantly increases the vulnerability of the system. In part II, we apply the complex networks models to study economics systems, which also includes two chapters: 1) We study the US corporate governance network, in which nodes representing directors and links between two directors representing their service on common company boards, and propose a quantitative measure of information and influence transformation in the network. Thus we are able to identify the most influential directors in the network. 2) We propose a bipartite networks model to simulate the risk propagation process among commercial banks during financial crisis. With empirical bank's balance sheet data in 2007 as input to the model, we find that our model efficiently identifies a significant portion of the actual failed banks reported by Federal Deposit Insurance Corporation during the financial crisis between 2008 and 2011. The results suggest that complex networks model could be useful for systemic risk stress testing for financial systems. The model also identifies that commercial rather than residential real estate assets are major culprits for the

  7. Evaluating Action Learning: A Critical Realist Complex Network Theory Approach

    ERIC Educational Resources Information Center

    Burgoyne, John G.

    2010-01-01

    This largely theoretical paper will argue the case for the usefulness of applying network and complex adaptive systems theory to an understanding of action learning and the challenge it is evaluating. This approach, it will be argued, is particularly helpful in the context of improving capability in dealing with wicked problems spread around…

  8. Theory VI. Computational Materials Sciences Network (CMSN)

    SciTech Connect

    Zhang, Z Y

    2008-06-25

    The Computational Materials Sciences Network (CMSN) is a virtual center consisting of scientists interested in working together, across organizational and disciplinary boundaries, to formulate and pursue projects that reflect challenging and relevant computational research in the materials sciences. The projects appropriate for this center involve those problems best pursued through broad cooperative efforts, rather than those key problems best tackled by single investigator groups. CMSN operates similarly to the DOE Center of Excellence for the Synthesis and Processing of Advanced Materials, coordinated by George Samara at Sandia. As in the Synthesis and Processing Center, the intent of the modest funding for CMSN is to foster partnering and collective activities. All CMSN proposals undergo external peer review and are judged foremost on the quality and timeliness of the science and also on criteria relevant to the objective of the center, especially concerning a strategy for partnering. More details about CMSN can be found on the CMSN webpages at: http://cmpweb.ameslab.gov/ccms/CMSN-homepage.html.

  9. Theory-independent limits on correlations from generalized Bayesian networks

    NASA Astrophysics Data System (ADS)

    Henson, Joe; Lal, Raymond; Pusey, Matthew F.

    2014-11-01

    Bayesian networks provide a powerful tool for reasoning about probabilistic causation, used in many areas of science. They are, however, intrinsically classical. In particular, Bayesian networks naturally yield the Bell inequalities. Inspired by this connection, we generalize the formalism of classical Bayesian networks in order to investigate non-classical correlations in arbitrary causal structures. Our framework of ‘generalized Bayesian networks’ replaces latent variables with the resources of any generalized probabilistic theory, most importantly quantum theory, but also, for example, Popescu-Rohrlich boxes. We obtain three main sets of results. Firstly, we prove that all of the observable conditional independences required by the classical theory also hold in our generalization; to obtain this, we extend the classical d-separation theorem to our setting. Secondly, we find that the theory-independent constraints on probabilities can go beyond these conditional independences. For example we find that no probabilistic theory predicts perfect correlation between three parties using only bipartite common causes. Finally, we begin a classification of those causal structures, such as the Bell scenario, that may yield a separation between classical, quantum and general-probabilistic correlations.

  10. Percolation theory and fragmentation measures in social networks

    NASA Astrophysics Data System (ADS)

    Chen, Yiping; Paul, Gerald; Cohen, Reuven; Havlin, Shlomo; Borgatti, Stephen P.; Liljeros, Fredrik; Eugene Stanley, H.

    2007-05-01

    We study the statistical properties of a recently proposed social networks measure of fragmentation F after removal of a fraction q of nodes or links from the network. The measure F is defined as the ratio of the number of pairs of nodes that are not connected in the fragmented network to the total number of pairs in the original fully connected network. We compare this measure with the one traditionally used in percolation theory, P∞, the fraction of nodes in the largest cluster relative to the total number of nodes. Using both analytical and numerical methods, we study Erdős-Rényi (ER) and scale-free (SF) networks under various node removal strategies. We find that for a network obtained after removal of a fraction q of nodes above criticality, P∞≈(1-F). For fixed P∞ and close to criticality, we show that 1-F better reflects the actual fragmentation. For a given P∞, 1-F has a broad distribution and thus one can improve significantly the fragmentation of the network. We also study and compare the fragmentation measure F and the percolation measure P∞ for a real national social network of workplaces linked by the households of the employees and find similar results.

  11. Towards a predictive theory for genetic regulatory networks

    NASA Astrophysics Data System (ADS)

    Tkacik, Gasper

    When cells respond to changes in the environment by regulating the expression levels of their genes, we often draw parallels between these biological processes and engineered information processing systems. One can go beyond this qualitative analogy, however, by analyzing information transmission in biochemical ``hardware'' using Shannon's information theory. Here, gene regulation is viewed as a transmission channel operating under restrictive constraints set by the resource costs and intracellular noise. We present a series of results demonstrating that a theory of information transmission in genetic regulatory circuits feasibly yields non-trivial, testable predictions. These predictions concern strategies by which individual gene regulatory elements, e.g., promoters or enhancers, read out their signals; as well as strategies by which small networks of genes, independently or in spatially coupled settings, respond to their inputs. These predictions can be quantitatively compared to the known regulatory networks and their function, and can elucidate how reproducible biological processes, such as embryonic development, can be orchestrated by networks built out of noisy components. Preliminary successes in the gap gene network of the fruit fly Drosophila indicate that a full ab initio theoretical prediction of a regulatory network is possible, a feat that has not yet been achieved for any real regulatory network. We end by describing open challenges on the path towards such a prediction.

  12. When More Power Makes Actors Worse off: Turning a Profit in the American Economy

    ERIC Educational Resources Information Center

    Piskorski, Mikolaj Jan; Casciaro, Tiziana

    2006-01-01

    We propose a theory which predicts that an increase in an actor's relative power reduces the actor's rewards in high mutual dependence dyads. Our argument is based on the premise that higher relative power gives the more powerful actor a greater share of surplus, but it also reduces dyadic exchange frequency, which lowers the expected magnitude of…

  13. Chemical reaction network approaches to Biochemical Systems Theory.

    PubMed

    Arceo, Carlene Perpetua P; Jose, Editha C; Marin-Sanguino, Alberto; Mendoza, Eduardo R

    2015-11-01

    This paper provides a framework to represent a Biochemical Systems Theory (BST) model (in either GMA or S-system form) as a chemical reaction network with power law kinetics. Using this representation, some basic properties and the application of recent results of Chemical Reaction Network Theory regarding steady states of such systems are shown. In particular, Injectivity Theory, including network concordance [36] and the Jacobian Determinant Criterion [43], a "Lifting Theorem" for steady states [26] and the comprehensive results of Müller and Regensburger [31] on complex balanced equilibria are discussed. A partial extension of a recent Emulation Theorem of Cardelli for mass action systems [3] is derived for a subclass of power law kinetic systems. However, it is also shown that the GMA and S-system models of human purine metabolism [10] do not display the reactant-determined kinetics assumed by Müller and Regensburger and hence only a subset of BST models can be handled with their approach. Moreover, since the reaction networks underlying many BST models are not weakly reversible, results for non-complex balanced equilibria are also needed. PMID:26363083

  14. Attributes and National Behavior, Part 2: Modern International Relations Monograph Series. Patterns of Cooperation: Relative Status-Field Theory, TU Actors.

    ERIC Educational Resources Information Center

    Vincent, Jack E.

    This monograph presents the computer printout of an analysis of data on international cooperation over a three-year period. Part of a large scale research project to test various theories with regard to their power in analyzing international relations, this monograph presents data on the application of discriminant function analysis to combined…

  15. Identifying influential nodes in weighted networks based on evidence theory

    NASA Astrophysics Data System (ADS)

    Wei, Daijun; Deng, Xinyang; Zhang, Xiaoge; Deng, Yong; Mahadevan, Sankaran

    2013-05-01

    The design of an effective ranking method to identify influential nodes is an important problem in the study of complex networks. In this paper, a new centrality measure is proposed based on the Dempster-Shafer evidence theory. The proposed measure trades off between the degree and strength of every node in a weighted network. The influences of both the degree and the strength of each node are represented by basic probability assignment (BPA). The proposed centrality measure is determined by the combination of these BPAs. Numerical examples are used to illustrate the effectiveness of the proposed method.

  16. Phase response theory extended to nonoscillatory network components

    NASA Astrophysics Data System (ADS)

    Sieling, Fred H.; Archila, Santiago; Hooper, Ryan; Canavier, Carmen C.; Prinz, Astrid A.

    2012-05-01

    New tools for analysis of oscillatory networks using phase response theory (PRT) under the assumption of pulsatile coupling have been developed steadily since the 1980s, but none have yet allowed for analysis of mixed systems containing nonoscillatory elements. This caveat has excluded the application of PRT to most real systems, which are often mixed. We show that a recently developed tool, the functional phase resetting curve (fPRC), provides a serendipitous benefit: it allows incorporation of nonoscillatory elements into systems of oscillators where PRT can be applied. We validate this method in a model system of neural oscillators and a biological system, the pyloric network of crustacean decapods.

  17. Actors: From Audience to Provider

    ERIC Educational Resources Information Center

    Charlier, Bernadette

    2011-01-01

    This article describes and analyzes actors' experiences of distance learning systems in a wide variety of cultural and organizational contexts. In line with the project of this special series of issues, results of research, much of which is longitudinal, allow us to suggest answers to the following questions: Who are the actors of distance…

  18. Surfactant self-assembly in oppositely charged polymer networks. Theory.

    PubMed

    Hansson, Per

    2009-10-01

    The interaction of ionic surfactants with polyion networks of opposite charge in an aqueous environment is analyzed theoretically by applying a recent theory of surfactant ion-polyion complex salts (J. Colloid. Int. Sci. 2009, 332, 183). The theory takes into account attractive and repulsive polyion-mediated interactions between the micelles, the deformation of the polymer network, the mixing of micelles, polyion chains, and simple ions with water, and the hydrophobic free energy at the micelle surface. The theory is used to calculate binding isotherms, swelling isotherms, surfactant aggregation numbers, compositions of complexes,and phase structure under various conditions. Factors controlling the gel volume transition and conditions for core/shell phase coexistence are investigated in detail, as well as the influence of salt. In particular, the interplay between electrostatic and elastic interactions is highlighted. Results from theory are compared with experimental data reported in the literature. The agreement is found to be semiquantitative or qualitative. The theory explains both the discrete volume transition observed in systems where the surfactant is in excess over the polyion and the core/shell phase coexistence in systems where the polyion is in excess. PMID:19728696

  19. On the genesis of the idiotypic network theory.

    PubMed

    Civello, Andrea

    2013-01-01

    The idiotypic network theory (INT) was conceived by the Danish immunologist Niels Kaj Jerne in 1973/1974. It proposes an overall view of the immune system as a network of lymphocytes and antibodies. The paper tries to offer a reconstruction of the genesis of the theory, now generally discarded and of mostly historical interest, first of all, by taking into account the context in which Jerne's theoretical proposal was advanced. It is argued the theory challenged, in a sense, the supremacy of the clonal selection theory (CST), this being regarded as the predominant paradigm in the immunological scenario. As CST found shortcomings in explaining certain phenomena, anomalies, one could view INT as a competing paradigm claiming to be able to make sense of such phenomena in its own conceptual framework. After a summary outline of the historical background and some relevant terminological elucidations, a narrative of the various phases of elaboration of the theory is proposed, up to its official public presentation. PMID:23207664

  20. Automata network theories in immunology: their utility and their underdetermination.

    PubMed

    Atlan, H

    1989-01-01

    Small networks of threshold automata are used to model complex interactions between populations of regulatory cells (helpers and suppressors, antigen specific and anti-idiotypic) which participate in the immune response. The models, being discrete and semiquantitative, are well adapted to the situation of incomplete information often encountered in vivo. However, the dynamics of many different network structures usually end up in the same attractor set. Thus, many different theories are equivalent in their explicative power for the same facts. This property, known as underdetermination of the theories by the facts, is given a quantitative estimate. It appears that such an underdetermination, as a kind of irreducible complexity, can be expected in many in vivo biological processes, even when the number of interacting and functionally coupled elements is relatively small. PMID:2924021

  1. Modelling mechanical characteristics of microbial biofilms by network theory

    PubMed Central

    Ehret, Alexander E.; Böl, Markus

    2013-01-01

    In this contribution, we present a constitutive model to describe the mechanical behaviour of microbial biofilms based on classical approaches in the continuum theory of polymer networks. Although the model is particularly developed for the well-studied biofilms formed by mucoid Pseudomonas aeruginosa strains, it could easily be adapted to other biofilms. The basic assumption behind the model is that the network of extracellular polymeric substances can be described as a superposition of worm-like chain networks, each connected by transient junctions of a certain lifetime. Several models that were applied to biofilms previously are included in the presented approach as special cases, and for small shear strains, the governing equations are those of four parallel Maxwell elements. Rheological data given in the literature are very adequately captured by the proposed model, and the simulated response for a series of compression tests at large strains is in good qualitative agreement with reported experimental behaviour. PMID:23034354

  2. Complex Network Theory Applied to the Growth of Kuala Lumpur's Public Urban Rail Transit Network.

    PubMed

    Ding, Rui; Ujang, Norsidah; Hamid, Hussain Bin; Wu, Jianjun

    2015-01-01

    Recently, the number of studies involving complex network applications in transportation has increased steadily as scholars from various fields analyze traffic networks. Nonetheless, research on rail network growth is relatively rare. This research examines the evolution of the Public Urban Rail Transit Networks of Kuala Lumpur (PURTNoKL) based on complex network theory and covers both the topological structure of the rail system and future trends in network growth. In addition, network performance when facing different attack strategies is also assessed. Three topological network characteristics are considered: connections, clustering and centrality. In PURTNoKL, we found that the total number of nodes and edges exhibit a linear relationship and that the average degree stays within the interval [2.0488, 2.6774] with heavy-tailed distributions. The evolutionary process shows that the cumulative probability distribution (CPD) of degree and the average shortest path length show good fit with exponential distribution and normal distribution, respectively. Moreover, PURTNoKL exhibits clear cluster characteristics; most of the nodes have a 2-core value, and the CPDs of the centrality's closeness and betweenness follow a normal distribution function and an exponential distribution, respectively. Finally, we discuss four different types of network growth styles and the line extension process, which reveal that the rail network's growth is likely based on the nodes with the biggest lengths of the shortest path and that network protection should emphasize those nodes with the largest degrees and the highest betweenness values. This research may enhance the networkability of the rail system and better shape the future growth of public rail networks. PMID:26448645

  3. Tensor Networks for Lattice Gauge Theories with Continuous Groups

    NASA Astrophysics Data System (ADS)

    Tagliacozzo, L.; Celi, A.; Lewenstein, M.

    2014-10-01

    We discuss how to formulate lattice gauge theories in the tensor-network language. In this way, we obtain both a consistent-truncation scheme of the Kogut-Susskind lattice gauge theories and a tensor-network variational ansatz for gauge-invariant states that can be used in actual numerical computations. Our construction is also applied to the simplest realization of the quantum link models or gauge magnets and provides a clear way to understand their microscopic relation with the Kogut-Susskind lattice gauge theories. We also introduce a new set of gauge-invariant operators that modify continuously Rokhsar-Kivelson wave functions and can be used to extend the phase diagrams of known models. As an example, we characterize the transition between the deconfined phase of the Z2 lattice gauge theory and the Rokhsar-Kivelson point of the U (1 ) gauge magnet in 2D in terms of entanglement entropy. The topological entropy serves as an order parameter for the transition but not the Schmidt gap.

  4. Game Theory for Wireless Sensor Networks: A Survey

    PubMed Central

    Shi, Hai-Yan; Wang, Wan-Liang; Kwok, Ngai-Ming; Chen, Sheng-Yong

    2012-01-01

    Game theory (GT) is a mathematical method that describes the phenomenon of conflict and cooperation between intelligent rational decision-makers. In particular, the theory has been proven very useful in the design of wireless sensor networks (WSNs). This article surveys the recent developments and findings of GT, its applications in WSNs, and provides the community a general view of this vibrant research area. We first introduce the typical formulation of GT in the WSN application domain. The roles of GT are described that include routing protocol design, topology control, power control and energy saving, packet forwarding, data collection, spectrum allocation, bandwidth allocation, quality of service control, coverage optimization, WSN security, and other sensor management tasks. Then, three variations of game theory are described, namely, the cooperative, non-cooperative, and repeated schemes. Finally, existing problems and future trends are identified for researchers and engineers in the field. PMID:23012533

  5. The Role of Vascular Actors in Two Dimensional Dialogue of Human Bone Marrow Stromal Cell and Endothelial Cell for Inducing Self-Assembled Network

    PubMed Central

    Li, Haiyan; Daculsi, Richard; Grellier, Maritie; Bareille, Reine; Bourget, Chantal; Remy, Murielle; Amedee, Joëlle

    2011-01-01

    Angiogenesis is very important for vascularized tissue engineering. In this study, we found that a two-dimensional co-culture of human bone marrow stromal cell (HBMSC) and human umbical vein endothelial cell (HUVEC) is able to stimulate the migration of co-cultured HUVEC and induce self-assembled network formation. During this process, expression of vascular endothelial growth factor (VEGF165) was upregulated in co-cultured HBMSC. Meanwhile, VEGF165-receptor2 (KDR) and urokinase-type plasminogen activator (uPA) were upregulated in co-cultured HUVEC. Functional studies show that neutralization of VEGF165 blocked the migration and the rearrangement of the cells and downregulated the expression of uPA and its receptor. Blocking of vascular endothelial-cadherin (VE-cad) did not affect the migration of co-cultured HUVEC but suppressed the self-assembled network formation. In conclusion, co-cultures upregulated the expression of VEGF165 in co-cultured HBMSC; VEGF165 then activated uPA in co-cultured HUVEC, which might be responsible for initiating the migration and the self-assembled network formation with the participation of VE-cad. All of these results indicated that only the direct contact of HBMSC and HUVEC and their respective dialogue are sufficient to stimulate secretion of soluble factors and to activate molecules that are critical for self-assembled network formation which show a great application potential for vascularization in tissue engineering. PMID:21304816

  6. Distributed Inference in Tree Networks Using Coding Theory

    NASA Astrophysics Data System (ADS)

    Kailkhura, Bhavya; Vempaty, Aditya; Varshney, Pramod K.

    2015-07-01

    In this paper, we consider the problem of distributed inference in tree based networks. In the framework considered in this paper, distributed nodes make a 1-bit local decision regarding a phenomenon before sending it to the fusion center (FC) via intermediate nodes. We propose the use of coding theory based techniques to solve this distributed inference problem in such structures. Data is progressively compressed as it moves towards the FC. The FC makes the global inference after receiving data from intermediate nodes. Data fusion at nodes as well as at the FC is implemented via error correcting codes. In this context, we analyze the performance for a given code matrix and also design the optimal code matrices at every level of the tree. We address the problems of distributed classification and distributed estimation separately and develop schemes to perform these tasks in tree networks. The proposed schemes are of practical significance due to their simple structure. We study the asymptotic inference performance of our schemes for two different classes of tree networks: fixed height tree networks, and fixed degree tree networks. We show that the proposed schemes are asymptotically optimal under certain conditions.

  7. Network theory and spatial rainfall connections: An interpretation

    NASA Astrophysics Data System (ADS)

    Jha, Sanjeev Kumar; Zhao, Honghan; Woldemeskel, Fitsum M.; Sivakumar, Bellie

    2015-08-01

    Adequate knowledge of spatial connections in rainfall is important for reliable modeling of catchment processes and water management. This study applies the ideas of network theory to examine and interpret the spatial connections in rainfall in Australian conditions. As case studies, monthly rainfall data across a network of raingages from two vastly different areas are studied: (1) Western Australia - data over a period of 67 years (1937-2003) from 57 raingages; and (2) Sydney catchment - data over a period of 114 years (1890-2003) from 47 monitoring stations. The spatial rainfall connections in the two networks are examined using clustering coefficient (CC), a popular network connectivity measure. The clustering coefficient measures the local density and quantifies the network's tendency to cluster. Different values of rainfall correlation threshold (CT) are used to measure the strength of connections in rainfall between different stations and, hence, to calculate CC. The clustering coefficient values are interpreted in terms of topographic factors (latitude, longitude, and elevation) and rainfall properties (mean, standard deviation, and coefficient of variation).

  8. A neural network theory of proportional analogy-making.

    PubMed

    Jani, N G; Levine, D S

    2000-03-01

    A neural network model that can simulate the learning of some simple proportional analogies is presented. These analogies include, for example, (a) red-square:red-circle :: yellow-square:?, (b) apple:red :: banana: ?, (c) a:b :: c:?. Underlying the development of this network is a theory for how the brain learns the nature of association between pairs of concepts. Traditional Hebbian learning of associations is necessary for this process but not sufficient. This is because it simply says, for example, that the concepts "apple" and "red" have been associated, but says nothing about the nature of this relationship. The types of context-dependent interlevel connections in the network suggest a semilocal type of learning that in some manner involves association among more than two nodes or neurons at once. Such connections have been called synaptic triads, and related to potential cell responses in the prefrontal cortex. Some additional types of connections are suggested by the problem of modeling analogies. These types of connections have not yet been verified by brain imaging, but the work herein suggests that they may occur and, possibly, be made and broken quickly in the course of working memory encoding. These working memory connections are referred to as differential, delayed and anti-Hebbian connections. In these connections, one can learn transitions such as "keep red the same"; "change red to yellow"; "turn off red"; "turn on yellow," and so forth. Also, included in the network is a kind of weight transport so that, for example, red to red can be transported to a different instance of color, such as yellow to yellow. The network instantiation developed here, based on common connectionist building blocks such as associative learning, competition, and adaptive resonance, along with additional principles suggested by analogy data, is a step toward a theory of interactions among several brain areas to develop and learn meaningful relationships between concepts

  9. Sharing, caring, and surveilling: an actor-partner interdependence model examination of Facebook relational maintenance strategies.

    PubMed

    McEwan, Bree

    2013-12-01

    Abstract Relational maintenance is connected to high quality friendships. Friendship maintenance behaviors may occur online via social networking sites. This study utilized an Actor-Partner Interdependence Model to examine how Facebook maintenance and surveillance affect friendship quality. Bryant and Marmo's (2012) Facebook maintenance scale was evaluated, revealing two factors: sharing and caring. Facebook surveillance was also measured. For friendship satisfaction and liking, significant positive actor and partner effects emerged for caring; significant negative actor, partner, and interaction effects emerged for sharing; and significant positive actor effects emerged for surveillance. For friendship closeness, significant positive actor effects emerged for caring and surveillance. PMID:23962125

  10. The Sociotechnical Networks of Scholarly Communication.

    ERIC Educational Resources Information Center

    Beagle, Donald

    2001-01-01

    Discusses the state of flux in scholarly communications and publishing, explains the Actor-Network Theory that offers an interdisciplinary approach to understanding the impact on libraries, provides an overview of the evolution of scholarly communications sociotechnical networks, and analyzes the strategy of the Scholarly Publishing and Academic…

  11. Bridging disparate symptoms of schizophrenia: a triple network dysfunction theory.

    PubMed

    Nekovarova, Tereza; Fajnerova, Iveta; Horacek, Jiri; Spaniel, Filip

    2014-01-01

    Schizophrenia is a complex neuropsychiatric disorder with variable symptomatology, traditionally divided into positive and negative symptoms, and cognitive deficits. However, the etiology of this disorder has yet to be fully understood. Recent findings suggest that alteration of the basic sense of self-awareness may be an essential distortion of schizophrenia spectrum disorders. In addition, extensive research of social and mentalizing abilities has stressed the role of distortion of social skills in schizophrenia.This article aims to propose and support a concept of a triple brain network model of the dysfunctional switching between default mode and central executive network (CEN) related to the aberrant activity of the salience network. This model could represent a unitary mechanism of a wide array of symptom domains present in schizophrenia including the deficit of self (self-awareness and self-representation) and theory of mind (ToM) dysfunctions along with the traditional positive, negative and cognitive domains. We review previous studies which document the dysfunctions of self and ToM in schizophrenia together with neuroimaging data that support the triple brain network model as a common neuronal substrate of this dysfunction. PMID:24910597

  12. Bridging disparate symptoms of schizophrenia: a triple network dysfunction theory

    PubMed Central

    Nekovarova, Tereza; Fajnerova, Iveta; Horacek, Jiri; Spaniel, Filip

    2014-01-01

    Schizophrenia is a complex neuropsychiatric disorder with variable symptomatology, traditionally divided into positive and negative symptoms, and cognitive deficits. However, the etiology of this disorder has yet to be fully understood. Recent findings suggest that alteration of the basic sense of self-awareness may be an essential distortion of schizophrenia spectrum disorders. In addition, extensive research of social and mentalizing abilities has stressed the role of distortion of social skills in schizophrenia.This article aims to propose and support a concept of a triple brain network model of the dysfunctional switching between default mode and central executive network (CEN) related to the aberrant activity of the salience network. This model could represent a unitary mechanism of a wide array of symptom domains present in schizophrenia including the deficit of self (self-awareness and self-representation) and theory of mind (ToM) dysfunctions along with the traditional positive, negative and cognitive domains. We review previous studies which document the dysfunctions of self and ToM in schizophrenia together with neuroimaging data that support the triple brain network model as a common neuronal substrate of this dysfunction. PMID:24910597

  13. Modeling network traffic with the extreme value theory

    NASA Astrophysics Data System (ADS)

    Liu, Jiakun; Shu, Yantai; Yang, Oliver W. W.; Gao, Deyun

    2003-08-01

    This paper introduced the Extreme Value Theory (EVT) for analysis of network traffic. The role of EVT is to allow the development of procedures that are scientifically and statistically rational to estimate the extreme behavior of random processes. In this paper, we propose an EVT_based procedure to fit a model to the traffic trace. We have performed some simulation experiments on real-traffic traces such as video data to study the feasibility of our proposed method. Our experiments showed that the EVT method can be applied to statistical analysis of real traffic. Furthermore, since only the data greater than the threshold are processed, the computation overhead is reduced greatly. It indicates that EVT method could be applied to real time network control.

  14. Advances on tensor network theory: symmetries, fermions, entanglement, and holography

    NASA Astrophysics Data System (ADS)

    Orús, Román

    2014-11-01

    This is a short review on selected theory developments on tensor network (TN) states for strongly correlated systems. Specifically, we briefly review the effect of symmetries in TN states, fermionic TNs, the calculation of entanglement Hamiltonians from projected entangled pair states (PEPS), and the relation between the multi-scale entanglement renormalization ansatz (MERA) and the AdS/CFT or gauge/gravity duality. We stress the role played by entanglement in the emergence of several physical properties and objects through the TN language. Some recent results along these lines are also discussed.

  15. Stochastical modeling for Viral Disease: Statistical Mechanics and Network Theory

    NASA Astrophysics Data System (ADS)

    Zhou, Hao; Deem, Michael

    2007-04-01

    Theoretical methods of statistical mechanics are developed and applied to study the immunological response against viral disease, such as dengue. We use this theory to show how the immune response to four different dengue serotypes may be sculpted. It is the ability of avian influenza, to change and to mix, that has given rise to the fear of a new human flu pandemic. Here we propose to utilize a scale free network based stochastic model to investigate the mitigation strategies and analyze the risk.

  16. A Danger-Theory-Based Immune Network Optimization Algorithm

    PubMed Central

    Li, Tao; Xiao, Xin; Shi, Yuanquan

    2013-01-01

    Existing artificial immune optimization algorithms reflect a number of shortcomings, such as premature convergence and poor local search ability. This paper proposes a danger-theory-based immune network optimization algorithm, named dt-aiNet. The danger theory emphasizes that danger signals generated from changes of environments will guide different levels of immune responses, and the areas around danger signals are called danger zones. By defining the danger zone to calculate danger signals for each antibody, the algorithm adjusts antibodies' concentrations through its own danger signals and then triggers immune responses of self-regulation. So the population diversity can be maintained. Experimental results show that the algorithm has more advantages in the solution quality and diversity of the population. Compared with influential optimization algorithms, CLONALG, opt-aiNet, and dopt-aiNet, the algorithm has smaller error values and higher success rates and can find solutions to meet the accuracies within the specified function evaluation times. PMID:23483853

  17. Transportation and dynamic networks: Models, theory, and applications to supply chains, electric power, and financial networks

    NASA Astrophysics Data System (ADS)

    Liu, Zugang

    Network systems, including transportation and logistic systems, electric power generation and distribution networks as well as financial networks, provide the critical infrastructure for the functioning of our societies and economies. The understanding of the dynamic behavior of such systems is also crucial to national security and prosperity. The identification of new connections between distinct network systems is the inspiration for the research in this dissertation. In particular, I answer two questions raised by Beckmann, McGuire, and Winsten (1956) and Copeland (1952) over half a century ago, which are, respectively, how are electric power flows related to transportation flows and does money flow like water or electricity? In addition, in this dissertation, I achieve the following: (1) I establish the relationships between transportation networks and three other classes of complex network systems: supply chain networks, electric power generation and transmission networks, and financial networks with intermediation. The establishment of such connections provides novel theoretical insights as well as new pricing mechanisms, and efficient computational methods. (2) I develop new modeling frameworks based on evolutionary variational inequality theory that capture the dynamics of such network systems in terms of the time-varying flows and incurred costs, prices, and, where applicable, profits. This dissertation studies the dynamics of such network systems by addressing both internal competition and/or cooperation, and external changes, such as varying costs and demands. (3) I focus, in depth, on electric power supply chains. By exploiting the relationships between transportation networks and electric power supply chains, I develop a large-scale network model that integrates electric power supply chains and fuel supply markets. The model captures both the economic transactions as well as the physical transmission constraints. The model is then applied to the New

  18. You're a What? Voice Actor

    ERIC Educational Resources Information Center

    Liming, Drew

    2009-01-01

    This article talks about voice actors and features Tony Oliver, a professional voice actor. Voice actors help to bring one's favorite cartoon and video game characters to life. They also do voice-overs for radio and television commercials and movie trailers. These actors use the sound of their voice to sell a character's emotions--or an advertised…

  19. Morphological brain network assessed using graph theory and network filtration in deaf adults.

    PubMed

    Kim, Eunkyung; Kang, Hyejin; Lee, Hyekyoung; Lee, Hyo-Jeong; Suh, Myung-Whan; Song, Jae-Jin; Oh, Seung-Ha; Lee, Dong Soo

    2014-09-01

    Prolonged deprivation of auditory input can change brain networks in pre- and postlingual deaf adults by brain-wide reorganization. To investigate morphological changes in these brains voxel-based morphometry, voxel-wise correlation with the primary auditory cortex, and whole brain network analyses using morphological covariance were performed in eight prelingual deaf, eleven postlingual deaf, and eleven hearing adults. Network characteristics based on graph theory and network filtration based on persistent homology were examined. Gray matter density in the primary auditor cortex was preserved in prelingual deafness, while it tended to decrease in postlingual deafness. Unlike postlingual, prelingual deafness showed increased bilateral temporal connectivity of the primary auditory cortex compared to the hearing adults. Of the graph theory-based characteristics, clustering coefficient, betweenness centrality, and nodal efficiency all increased in prelingual deafness, while all the parameters of postlingual deafness were similar to the hearing adults. Patterns of connected components changing during network filtration were different between prelingual deafness and hearing adults according to the barcode, dendrogram, and single linkage matrix representations, while these were the same in postlingual deafness. Nodes in fronto-limbic and left temporal components were closely coupled, and nodes in the temporo-parietal component were loosely coupled, in prelingual deafness. Patterns of connected components changing in postlingual deafness were the same as hearing adults. We propose that the preserved density of auditory cortex associated with increased connectivity in prelingual deafness, and closer coupling between certain brain areas, represent distinctive reorganization of auditory and related cortices compared with hearing or postlingual deaf adults. The differential network reorganization in the prelingual deaf adults could be related to the absence of auditory speech

  20. Multicultural Monologues for Young Actors. The Young Actors Series.

    ERIC Educational Resources Information Center

    Slaight, Craig, Ed.; Sharrar, Jack, Ed.

    This book presents 62 monologue selections from diverse cultures for young actors to perform. The book's selections offer "quality literature by significant writers." Some of the writers represented in the book are George C. Wolfe, Miguel Pinero, Lorraine Hansberry, Amiri Baraka (LeRoi Jones), John M. Synge, Yukio Mishima, Reynolds Price, and John…

  1. The Actor and His Body.

    ERIC Educational Resources Information Center

    Rubin, Lucille S., Ed.

    Fourteen brief articles deal with training actors to use their bodies effectively on stage. The articles discuss the following topics: the concept of succession-sequential movement (movement that passes through the body joint by joint); learning physical action through staged fight sequences; techniques of empty-handed combat; protecting students…

  2. The Course as Token: A Construction of/by Networks.

    ERIC Educational Resources Information Center

    Gaskell, Jim; Hepburn, Gary

    1998-01-01

    Describes the way in which a new applied-physics course introduced in British Columbia as part of a program in applied academics can be seen to construct different networks in different contexts. Employs actor network theory (ANT). Contains 20 references. (DDR)

  3. Construal level and free will beliefs shape perceptions of actors' proximal and distal intent.

    PubMed

    Plaks, Jason E; Robinson, Jeffrey S

    2015-01-01

    Two components of lay observers' calculus of moral judgment are proximal intent (the actor's mind is focused on performing the action) and distal intent (the actor's mind is focused on the broader goal). What causes observers to prioritize one form of intent over the other? The authors observed whether construal level (Studies 1-2) and beliefs about free will (Studies 3-4) would influence participants' sensitivity to the actor's proximal vs. distal intent. In four studies, participants read scenarios in which the actor's proximal and distal intent were independently manipulated. In Study 1, when only distal intent was present in the actor's mind, participants rated the psychologically distant actor more responsible than the psychologically near actor. In Study 2, when only distal intent was in the actor's mind, participants with a chronic high level of action identification rated the actor more responsible than did those with a low level of action identification. In both studies, when only proximal intent was in the actor's mind, construal level did not predict judgments of responsibility. In Study 3, when only proximal intent was present in the actor's mind, the more participants believed in free will, the more they rated the actor responsible. When only distal intent was in the actor's mind, free will belief did not influence ratings of responsibility. In Study 4, the same pattern emerged when free will/determinism beliefs were manipulated and the actor performed a positive (life-saving) act. The authors discuss how these results shed new light on the literatures on moral reasoning and psycho-legal theory. PMID:26106352

  4. Construal level and free will beliefs shape perceptions of actors' proximal and distal intent

    PubMed Central

    Plaks, Jason E.; Robinson, Jeffrey S.

    2015-01-01

    Two components of lay observers' calculus of moral judgment are proximal intent (the actor's mind is focused on performing the action) and distal intent (the actor's mind is focused on the broader goal). What causes observers to prioritize one form of intent over the other? The authors observed whether construal level (Studies 1–2) and beliefs about free will (Studies 3–4) would influence participants' sensitivity to the actor's proximal vs. distal intent. In four studies, participants read scenarios in which the actor's proximal and distal intent were independently manipulated. In Study 1, when only distal intent was present in the actor's mind, participants rated the psychologically distant actor more responsible than the psychologically near actor. In Study 2, when only distal intent was in the actor's mind, participants with a chronic high level of action identification rated the actor more responsible than did those with a low level of action identification. In both studies, when only proximal intent was in the actor's mind, construal level did not predict judgments of responsibility. In Study 3, when only proximal intent was present in the actor's mind, the more participants believed in free will, the more they rated the actor responsible. When only distal intent was in the actor's mind, free will belief did not influence ratings of responsibility. In Study 4, the same pattern emerged when free will/determinism beliefs were manipulated and the actor performed a positive (life-saving) act. The authors discuss how these results shed new light on the literatures on moral reasoning and psycho-legal theory. PMID:26106352

  5. Attachment-dissociation network: some thoughts about a modern complex theory.

    PubMed

    Bovensiepen, Gustav

    2006-06-01

    The paper revises the complex theory in the light of modern infant research, neurosciences and object relation theory. The author takes up Jean Knox's idea to understand complexes as analogies to the internal working models of attachment theory. The author proposes to understand complexes as dissociated sub-networks out of the network structure of the psyche; these sub-networks contain the internal working models, the characteristic affects and unconscious expectation phantasies. With this network model one can try to understand severe defensive organizations in some patients as a pathological organization of different complexes. This is illustrated by a clinical example. PMID:16712687

  6. Transnational corporations as 'keystone actors' in marine ecosystems.

    PubMed

    Österblom, Henrik; Jouffray, Jean-Baptiste; Folke, Carl; Crona, Beatrice; Troell, Max; Merrie, Andrew; Rockström, Johan

    2015-01-01

    Keystone species have a disproportionate influence on the structure and function of ecosystems. Here we analyze whether a keystone-like pattern can be observed in the relationship between transnational corporations and marine ecosystems globally. We show how thirteen corporations control 11-16% of the global marine catch (9-13 million tons) and 19-40% of the largest and most valuable stocks, including species that play important roles in their respective ecosystem. They dominate all segments of seafood production, operate through an extensive global network of subsidiaries and are profoundly involved in fisheries and aquaculture decision-making. Based on our findings, we define these companies as keystone actors of the Anthropocene. The phenomenon of keystone actors represents an increasingly important feature of the human-dominated world. Sustainable leadership by keystone actors could result in cascading effects throughout the entire seafood industry and enable a critical transition towards improved management of marine living resources and ecosystems. PMID:26017777

  7. Unified-theory-of-reinforcement neural networks do not simulate the blocking effect.

    PubMed

    Calvin, Nicholas T; J McDowell, J

    2015-11-01

    For the last 20 years the unified theory of reinforcement (Donahoe et al., 1993) has been used to develop computer simulations to evaluate its plausibility as an account for behavior. The unified theory of reinforcement states that operant and respondent learning occurs via the same neural mechanisms. As part of a larger project to evaluate the operant behavior predicted by the theory, this project was the first replication of neural network models based on the unified theory of reinforcement. In the process of replicating these neural network models it became apparent that a previously published finding, namely, that the networks simulate the blocking phenomenon (Donahoe et al., 1993), was a misinterpretation of the data. We show that the apparent blocking produced by these networks is an artifact of the inability of these networks to generate the same conditioned response to multiple stimuli. The piecemeal approach to evaluate the unified theory of reinforcement via simulation is critiqued and alternatives are discussed. PMID:26319369

  8. Changing Power Actors in a Midwestern Community.

    ERIC Educational Resources Information Center

    Tait, John L.; And Others

    A longitudinal study was made of Prairie City, Iowa wherein the personal and social characteristics of the 1962 power actor pool were compared with characteristics of the 1973 power actor pool to test the hypothesis that: the personal and social characteristics of power actors will not change significantly over time. Procedures for identifying…

  9. Privileged Emotion Managers: The Case of Actors

    ERIC Educational Resources Information Center

    Orzechowicz, David

    2008-01-01

    Theatre provides a unique set of conditions for the management of emotions. Drawing on participant observation from one repertory theater, three university productions, and interviews with stage actors, directors, and acting instructors, I conceptualize actors as privileged emotion managers. Actors access structural resources that enable their…

  10. Networking for Teacher Learning: Toward a Theory of Effective Design.

    ERIC Educational Resources Information Center

    McDonald, Joseph P.; Klein, Emily J.

    2003-01-01

    Examines how teacher networks design for teacher learning, describing several dynamic tensions inherent in the designs of a sample of teacher networks and assessing the relationships of these tensions to teacher learning. The paper illustrates these design concepts with reference to the work of seven networks that aim to revamp teacher' knowledge…

  11. Entropy measures for networks: toward an information theory of complex topologies.

    PubMed

    Anand, Kartik; Bianconi, Ginestra

    2009-10-01

    The quantification of the complexity of networks is, today, a fundamental problem in the physics of complex systems. A possible roadmap to solve the problem is via extending key concepts of information theory to networks. In this Rapid Communication we propose how to define the Shannon entropy of a network ensemble and how it relates to the Gibbs and von Neumann entropies of network ensembles. The quantities we introduce here will play a crucial role for the formulation of null models of networks through maximum-entropy arguments and will contribute to inference problems emerging in the field of complex networks. PMID:19905379

  12. Reliability theory for diffusion processes on interconnected networks

    NASA Astrophysics Data System (ADS)

    Khorramzadeh, Yasamin; Youssef, Mina; Eubank, Stephen

    2014-03-01

    We present the concept of network reliability as a framework to study diffusion dynamics in interdependent networks. We illustrate how different outcomes of diffusion processes, such as cascading failure, can be studied by estimating the reliability polynomial under different reliability rules. As an example, we investigate the effect of structural properties on diffusion dynamics for a few different topologies of two coupled networks. We evaluate the effect of varying the probability of failure propagating along the edges, both within a single network as well as between the networks. We exhibit the sensitivity of interdependent network reliability and connectivity to edge failures in each topology. Network Dynamics and Simulation Science Laboratory, Virginia Bioinformatics Institute, Virginia Tech, Blacksburg, Virginia 24061, USA.

  13. Why Universities Join Cross-Sector Social Partnerships: Theory and Evidence

    ERIC Educational Resources Information Center

    Siegel, David J.

    2010-01-01

    Cross-sector partnerships are an increasingly popular mode of organizing to address intractable social problems, yet theory and research have virtually ignored university involvement in such activity. This article attempts to ascertain the reasons universities join networks of other social actors to support a common cause. Theories on the…

  14. Theory of rumour spreading in complex social networks

    NASA Astrophysics Data System (ADS)

    Nekovee, M.; Moreno, Y.; Bianconi, G.; Marsili, M.

    2007-01-01

    We introduce a general stochastic model for the spread of rumours, and derive mean-field equations that describe the dynamics of the model on complex social networks (in particular, those mediated by the Internet). We use analytical and numerical solutions of these equations to examine the threshold behaviour and dynamics of the model on several models of such networks: random graphs, uncorrelated scale-free networks and scale-free networks with assortative degree correlations. We show that in both homogeneous networks and random graphs the model exhibits a critical threshold in the rumour spreading rate below which a rumour cannot propagate in the system. In the case of scale-free networks, on the other hand, this threshold becomes vanishingly small in the limit of infinite system size. We find that the initial rate at which a rumour spreads is much higher in scale-free networks than in random graphs, and that the rate at which the spreading proceeds on scale-free networks is further increased when assortative degree correlations are introduced. The impact of degree correlations on the final fraction of nodes that ever hears a rumour, however, depends on the interplay between network topology and the rumour spreading rate. Our results show that scale-free social networks are prone to the spreading of rumours, just as they are to the spreading of infections. They are relevant to the spreading dynamics of chain emails, viral advertising and large-scale information dissemination algorithms on the Internet.

  15. A social network model for the development of a 'Theory of Mind'

    NASA Astrophysics Data System (ADS)

    Harré, Michael S.

    2013-02-01

    A "Theory of Mind" is one of the most important skills we as humans have developed; It enables us to infer the mental states and intentions of others, build stable networks of relationships and it plays a central role in our psychological make-up and development. Findings published earlier this year have also shown that we as a species as well as each of us individually benefit from the enlargement of the underlying neuro-anatomical regions that support our social networks, mediated by our Theory of Mind that stabilises these networks. On the basis of such progress and that of earlier work, this paper draws together several different strands from psychology, behavioural economics and network theory in order to generate a novel theoretical representation of the development of our social-cognition and how subsequent larger social networks enables much of our cultural development but at the increased risk of mental disorders.

  16. Functional Organization of the Action Observation Network in Autism: A Graph Theory Approach

    PubMed Central

    Alaerts, Kaat; Geerlings, Franca; Herremans, Lynn; Swinnen, Stephan P.; Verhoeven, Judith; Sunaert, Stefan; Wenderoth, Nicole

    2015-01-01

    Background The ability to recognize, understand and interpret other’s actions and emotions has been linked to the mirror system or action-observation-network (AON). Although variations in these abilities are prevalent in the neuro-typical population, persons diagnosed with autism spectrum disorders (ASD) have deficits in the social domain and exhibit alterations in this neural network. Method Here, we examined functional network properties of the AON using graph theory measures and region-to-region functional connectivity analyses of resting-state fMRI-data from adolescents and young adults with ASD and typical controls (TC). Results Overall, our graph theory analyses provided convergent evidence that the network integrity of the AON is altered in ASD, and that reductions in network efficiency relate to reductions in overall network density (i.e., decreased overall connection strength). Compared to TC, individuals with ASD showed significant reductions in network efficiency and increased shortest path lengths and centrality. Importantly, when adjusting for overall differences in network density between ASD and TC groups, participants with ASD continued to display reductions in network integrity, suggesting that also network-level organizational properties of the AON are altered in ASD. Conclusion While differences in empirical connectivity contributed to reductions in network integrity, graph theoretical analyses provided indications that also changes in the high-level network organization reduced integrity of the AON. PMID:26317222

  17. Insights into the organization of biochemical regulatory networks using graph theory analyses.

    PubMed

    Ma'ayan, Avi

    2009-02-27

    Graph theory has been a valuable mathematical modeling tool to gain insights into the topological organization of biochemical networks. There are two types of insights that may be obtained by graph theory analyses. The first provides an overview of the global organization of biochemical networks; the second uses prior knowledge to place results from multivariate experiments, such as microarray data sets, in the context of known pathways and networks to infer regulation. Using graph analyses, biochemical networks are found to be scale-free and small-world, indicating that these networks contain hubs, which are proteins that interact with many other molecules. These hubs may interact with many different types of proteins at the same time and location or at different times and locations, resulting in diverse biological responses. Groups of components in networks are organized in recurring patterns termed network motifs such as feedback and feed-forward loops. Graph analysis revealed that negative feedback loops are less common and are present mostly in proximity to the membrane, whereas positive feedback loops are highly nested in an architecture that promotes dynamical stability. Cell signaling networks have multiple pathways from some input receptors and few from others. Such topology is reminiscent of a classification system. Signaling networks display a bow-tie structure indicative of funneling information from extracellular signals and then dispatching information from a few specific central intracellular signaling nexuses. These insights show that graph theory is a valuable tool for gaining an understanding of global regulatory features of biochemical networks. PMID:18940806

  18. The network perspective: an integration of attachment and family systems theories.

    PubMed

    Kozlowska, Kasia; Hanney, Lesley

    2002-01-01

    In this article we discuss the network paradigm as a useful base from which to integrate attachment and family systems theories. The network perspective refers to the application of general systems theory to living systems, and provides a framework that conceptualizes the dyadic and family systems as simultaneously distinct and interconnected. Network thinking requires that the clinician holds multiple perspectives in mind, considers each system level as both a part and a whole, and shifts the focus of attention between levels as required. Key epistemological issues that have hindered the integration of the theories are discussed. These include inconsistencies within attachment theory itself and confusion surrounding the theoretical conceptualizations of the relationship between attachment and family systems theories. Detailed information about attachment categories is provided using the Dynamic Maturational model. Case vignettes illustrating work with young children and their families explore the clinical implications of integrating attachment data into family therapy practice. PMID:12395561

  19. Information theory in systems biology. Part I: Gene regulatory and metabolic networks.

    PubMed

    Mousavian, Zaynab; Kavousi, Kaveh; Masoudi-Nejad, Ali

    2016-03-01

    "A Mathematical Theory of Communication", was published in 1948 by Claude Shannon to establish a framework that is now known as information theory. In recent decades, information theory has gained much attention in the area of systems biology. The aim of this paper is to provide a systematic review of those contributions that have applied information theory in inferring or understanding of biological systems. Based on the type of system components and the interactions between them, we classify the biological systems into 4 main classes: gene regulatory, metabolic, protein-protein interaction and signaling networks. In the first part of this review, we attempt to introduce most of the existing studies on two types of biological networks, including gene regulatory and metabolic networks, which are founded on the concepts of information theory. PMID:26701126

  20. A brief historical introduction to Euler's formula for polyhedra, topology, graph theory and networks

    NASA Astrophysics Data System (ADS)

    Debnath, Lokenath

    2010-09-01

    This article is essentially devoted to a brief historical introduction to Euler's formula for polyhedra, topology, theory of graphs and networks with many examples from the real-world. Celebrated Königsberg seven-bridge problem and some of the basic properties of graphs and networks for some understanding of the macroscopic behaviour of real physical systems are included. We also mention some important and modern applications of graph theory or network problems from transportation to telecommunications. Graphs or networks are effectively used as powerful tools in industrial, electrical and civil engineering, communication networks in the planning of business and industry. Graph theory and combinatorics can be used to understand the changes that occur in many large and complex scientific, technical and medical systems. With the advent of fast large computers and the ubiquitous Internet consisting of a very large network of computers, large-scale complex optimization problems can be modelled in terms of graphs or networks and then solved by algorithms available in graph theory. Many large and more complex combinatorial problems dealing with the possible arrangements of situations of various kinds, and computing the number and properties of such arrangements can be formulated in terms of networks. The Knight's tour problem, Hamilton's tour problem, problem of magic squares, the Euler Graeco-Latin squares problem and their modern developments in the twentieth century are also included.

  1. Untangling Word Webs: Graph Theory and the Notion of Density in Second Language Word Association Networks.

    ERIC Educational Resources Information Center

    Wilks, Clarissa; Meara, Paul

    2002-01-01

    Examines the implications of the metaphor of the vocabulary network. Takes a formal approach to the exploration of this metaphor by applying the principles of graph theory to word association data to compare the relative densities of the first language and second language lexical networks. (Author/VWL)

  2. A Social Network Perspective on Teacher Collaboration in Schools: Theory, Methodology, and Applications

    ERIC Educational Resources Information Center

    Moolenaar, Nienke M.

    2012-01-01

    An emerging trend in educational research is the use of social network theory and methodology to understand how teacher collaboration can support or constrain teaching, learning, and educational change. This article provides a critical synthesis of educational literature on school social networks among educators to advance our understanding of the…

  3. A Brief Historical Introduction to Euler's Formula for Polyhedra, Topology, Graph Theory and Networks

    ERIC Educational Resources Information Center

    Debnath, Lokenath

    2010-01-01

    This article is essentially devoted to a brief historical introduction to Euler's formula for polyhedra, topology, theory of graphs and networks with many examples from the real-world. Celebrated Konigsberg seven-bridge problem and some of the basic properties of graphs and networks for some understanding of the macroscopic behaviour of real…

  4. Small-World Network Spectra in Mean-Field Theory

    NASA Astrophysics Data System (ADS)

    Grabow, Carsten; Grosskinsky, Stefan; Timme, Marc

    2012-05-01

    Collective dynamics on small-world networks emerge in a broad range of systems with their spectra characterizing fundamental asymptotic features. Here we derive analytic mean-field predictions for the spectra of small-world models that systematically interpolate between regular and random topologies by varying their randomness. These theoretical predictions agree well with the actual spectra (obtained by numerical diagonalization) for undirected and directed networks and from fully regular to strongly random topologies. These results may provide analytical insights to empirically found features of dynamics on small-world networks from various research fields, including biology, physics, engineering, and social science.

  5. Guest editorial. Body sensor networks: from theory to emerging applications.

    PubMed

    Jovanov, Emil; Poon, Carmen C Y; Yang, Guang-Zhong; Zhang, Y T

    2009-11-01

    The use of sensor networks for healthcare, well-being, and working in extreme environments has long roots in the engineering sector in medicine and biology community. With the maturity of wireless sensor networks, body area networks (BANs), and wireless BANs (WBANs), recent efforts in promoting the concept of body sensor networks (BSNs) aim to move beyond sensor connectivity to adopt a system-level approach to address issues related to biosensor design, interfacing, and embodiment, as well as ultralow-power processing/communication, power scavenging, autonomic sensing, data mining, inferencing, and integrated wireless sensor microsystems. As a result, the system architecture based on WBAN and BSN is becoming a widely accepted method of organization for ambulatory and ubiquitous monitoring systems. This editorial paper presents a snapshot of the current research and emerging applications and addresses some of the challenges and implementation issues. PMID:19887307

  6. The network and the remodeling theories of aging: historical background and new perspectives.

    PubMed

    Franceschi, C; Valensin, S; Bonafè, M; Paolisso, G; Yashin, A I; Monti, D; De Benedictis, G

    2000-09-01

    Two general theories, i.e. "the network theory of aging" (1989) and "the remodeling theory of aging" (1995), as well as their implications, new developments, and perspectives are reviewed and discussed. Particular attention has been paid to illustrate: (i) how the network theory of aging fits with recent data on aging and longevity in unicellular organisms (yeast), multicellular organisms (worms), and mammals (mice and humans); (ii) the evolutionary and experimental basis of the remodeling theory of aging (immunological, genetic, and metabolic data in healthy centenarians, and studies on the evolution of the immune response, stress and inflammation) and its recent development (the concepts of "immunological space" and "inflamm-aging"); (iii) the profound relationship between these two theories and the data which suggest that aging and longevity are related, in a complex way, to the capability to cope with a variety of stressors. PMID:11053678

  7. Leveraging percolation theory to single out influential spreaders in networks

    NASA Astrophysics Data System (ADS)

    Radicchi, Filippo; Castellano, Claudio

    2016-06-01

    Among the consequences of the disordered interaction topology underlying many social, technological, and biological systems, a particularly important one is that some nodes, just because of their position in the network, may have a disproportionate effect on dynamical processes mediated by the complex interaction pattern. For example, the early adoption of a commercial product by an opinion leader in a social network may change its fate or just a few superspreaders may determine the virality of a meme in social media. Despite many recent efforts, the formulation of an accurate method to optimally identify influential nodes in complex network topologies remains an unsolved challenge. Here, we present the exact solution of the problem for the specific, but highly relevant, case of the susceptible-infected-removed (SIR) model for epidemic spreading at criticality. By exploiting the mapping between bond percolation and the static properties of the SIR model, we prove that the recently introduced nonbacktracking centrality is the optimal criterion for the identification of influential spreaders in locally tree-like networks at criticality. By means of simulations on synthetic networks and on a very extensive set of real-world networks, we show that the nonbacktracking centrality is a highly reliable metric to identify top influential spreaders also in generic graphs not embedded in space and for noncritical spreading.

  8. Leveraging percolation theory to single out influential spreaders in networks.

    PubMed

    Radicchi, Filippo; Castellano, Claudio

    2016-06-01

    Among the consequences of the disordered interaction topology underlying many social, technological, and biological systems, a particularly important one is that some nodes, just because of their position in the network, may have a disproportionate effect on dynamical processes mediated by the complex interaction pattern. For example, the early adoption of a commercial product by an opinion leader in a social network may change its fate or just a few superspreaders may determine the virality of a meme in social media. Despite many recent efforts, the formulation of an accurate method to optimally identify influential nodes in complex network topologies remains an unsolved challenge. Here, we present the exact solution of the problem for the specific, but highly relevant, case of the susceptible-infected-removed (SIR) model for epidemic spreading at criticality. By exploiting the mapping between bond percolation and the static properties of the SIR model, we prove that the recently introduced nonbacktracking centrality is the optimal criterion for the identification of influential spreaders in locally tree-like networks at criticality. By means of simulations on synthetic networks and on a very extensive set of real-world networks, we show that the nonbacktracking centrality is a highly reliable metric to identify top influential spreaders also in generic graphs not embedded in space and for noncritical spreading. PMID:27415287

  9. Non-fragile H∞ synchronization of memristor-based neural networks using passivity theory.

    PubMed

    Mathiyalagan, K; Anbuvithya, R; Sakthivel, R; Park, Ju H; Prakash, P

    2016-02-01

    In this paper, we formulate and investigate the mixed H∞ and passivity based synchronization criteria for memristor-based recurrent neural networks with time-varying delays. Some sufficient conditions are obtained to guarantee the synchronization of the considered neural network based on the master-slave concept, differential inclusions theory and Lyapunov-Krasovskii stability theory. Also, the memristive neural network is considered with two different types of memductance functions and two types of gain variations. The results for non-fragile observer-based synchronization are derived in terms of linear matrix inequalities (LMIs). Finally, the effectiveness of the proposed criterion is demonstrated through numerical examples. PMID:26655373

  10. [Attachment theory and baby slings/carriers: technological network formation].

    PubMed

    Lu, Zxy-Yann Jane; Lin, Wan-Shiuan

    2011-12-01

    Healthcare providers recognize the important role played by attachment theory in explaining the close relationship between mental health and social behavior in mothers and their children. This paper uses attachment theory in a socio-cultural context to ascertain the mechanism by which baby slings/carriers, a new technology, produced and reproduced the scientific motherhood. It further applies a social history of technology perspective to understand how baby carriers and attachment theory are socially constructed and historically contingent on three major transformations. These transformations include the use of attachment theory-based baby carriers to further scientific motherhood; the use of baby slings/carriers to further the medicalization of breastfeeding and enhance mother-infant attachment; and the use of baby slings/carriers to transform woman's identities by integrating scientific motherhood, independence and fashion. Implications for nursing clinical policy are suggested. PMID:22113629

  11. Complex Network Theory Applied to the Growth of Kuala Lumpur’s Public Urban Rail Transit Network

    PubMed Central

    Ding, Rui; Ujang, Norsidah; Hamid, Hussain bin; Wu, Jianjun

    2015-01-01

    Recently, the number of studies involving complex network applications in transportation has increased steadily as scholars from various fields analyze traffic networks. Nonetheless, research on rail network growth is relatively rare. This research examines the evolution of the Public Urban Rail Transit Networks of Kuala Lumpur (PURTNoKL) based on complex network theory and covers both the topological structure of the rail system and future trends in network growth. In addition, network performance when facing different attack strategies is also assessed. Three topological network characteristics are considered: connections, clustering and centrality. In PURTNoKL, we found that the total number of nodes and edges exhibit a linear relationship and that the average degree stays within the interval [2.0488, 2.6774] with heavy-tailed distributions. The evolutionary process shows that the cumulative probability distribution (CPD) of degree and the average shortest path length show good fit with exponential distribution and normal distribution, respectively. Moreover, PURTNoKL exhibits clear cluster characteristics; most of the nodes have a 2-core value, and the CPDs of the centrality’s closeness and betweenness follow a normal distribution function and an exponential distribution, respectively. Finally, we discuss four different types of network growth styles and the line extension process, which reveal that the rail network’s growth is likely based on the nodes with the biggest lengths of the shortest path and that network protection should emphasize those nodes with the largest degrees and the highest betweenness values. This research may enhance the networkability of the rail system and better shape the future growth of public rail networks. PMID:26448645

  12. Topics in the theory of quantum and classical networks

    NASA Astrophysics Data System (ADS)

    Almaas, Eivind

    We study both quantum and classical networks. The quantum networks consist of 1D and 2D arrays of Josephson junctions coupled to a resonant cavity. We derive dynamical equations for these arrays by applying the Heisenberg equations of motion to a model Hamiltonian. By means of a canonical transformation, we also show that, in the absence of an applied current and dissipation, our model reduces to one used to describe coupled qubits, and that the cavity-junction coupling corresponds to a capacitive coupling between the array and the cavity mode. From extensive numerical solutions of the model in both 1D and 2D, we find that the array locks into a coherent, periodic state above a critical number of active junctions, that the current-voltage characteristics of the array have self-induced resonant steps (SIRS's), that when N a active junctions are synchronized on a SIRS, the energy emitted into the resonant cavity is quadratic in Na, and that when a fixed number of junctions is biased on a SIRS, the energy is linear in the input power. All these results are in agreement with recent experiments. We conclude that most of the experimental data can be understood from classical equations of motion. Our study of classical networks is divided into two parts. In the first, we study the structural properties of 'small-world' networks (SWN)---networks that display properties of both regular and random graphs. We generalize the model for generating such networks that was first introduced by Watts and Strogatz. For this model, we study the distribution function for minimal paths, derive its general form and also discuss its scaling properties. Using this distribution function, we derive exact expressions for several network properties, like the average minimal distance, ℓ¯ and its variance, sigma2. These exact relations are independent of the 'degree distribution', i.e. the distribution of nearest-neighbor connections. In the second, we study how the structure of the network

  13. Bombing alone: tracing the motivations and antecedent behaviors of lone-actor terrorists,.

    PubMed

    Gill, Paul; Horgan, John; Deckert, Paige

    2014-03-01

    This article analyzes the sociodemographic network characteristics and antecedent behaviors of 119 lone-actor terrorists. This marks a departure from existing analyses by largely focusing upon behavioral aspects of each offender. This article also examines whether lone-actor terrorists differ based on their ideologies or network connectivity. The analysis leads to seven conclusions. There was no uniform profile identified. In the time leading up to most lone-actor terrorist events, other people generally knew about the offender's grievance, extremist ideology, views, and/or intent to engage in violence. A wide range of activities and experiences preceded lone actors' plots or events. Many but not all lone-actor terrorists were socially isolated. Lone-actor terrorists regularly engaged in a detectable and observable range of activities with a wider pressure group, social movement, or terrorist organization. Lone-actor terrorist events were rarely sudden and impulsive. There were distinguishable behavioral differences between subgroups. The implications for policy conclude this article. PMID:24313297

  14. Extended Network Generalized Entanglement Theory: therapeutic mechanisms, empirical predictions, and investigations.

    PubMed

    Hyland, Michael E

    2003-12-01

    Extended Network Generalized Entanglement Theory (Entanglement Theory for short) combines two earlier theories based on complexity theory and quantum mechanics. The theory's assumptions are: the body is a complex, self-organizing system (the extended network) that self-organizes so as to achieve genetically defined patterns (where patterns include morphologic as well as lifestyle patterns). These pattern-specifying genes require feedback that is provided by generalized quantum entanglement. Additionally, generalized entanglement has evolved as a form of communication between people (and animals) and can be used in healing. Entanglement Theory suggests that several processes are involved in complementary and alternative medicine (CAM). Direct subtle therapy creates network change either through lifestyle management, some manual therapies, and psychologically mediated effects of therapy. Indirect subtle therapy is a process of entanglement with other people or physical entities (e.g., remedies, healing sites). Both types of subtle therapy create two kinds of information within the network--either that the network is more disregulated than it is and the network then compensates for this error, or as a guide for network change leading to healing. Most CAM therapies involve a combination of indirect and direct therapies, making empirical evaluation complex. Empirical predictions from this theory are contrasted with those from two other possible mechanisms of healing: (1) psychologic processes and (2) mechanisms involving electromagnetic influence between people (biofield/energy medicine). Topics for empirical study include a hyperfast communication system, the phenomenology of entanglement, predictors of outcome in naturally occurring clinical settings, and the importance of therapist and patient characteristics to outcome. PMID:14736363

  15. An Energy-Efficient Game-Theory-Based Spectrum Decision Scheme for Cognitive Radio Sensor Networks.

    PubMed

    Salim, Shelly; Moh, Sangman

    2016-01-01

    A cognitive radio sensor network (CRSN) is a wireless sensor network in which sensor nodes are equipped with cognitive radio. In this paper, we propose an energy-efficient game-theory-based spectrum decision (EGSD) scheme for CRSNs to prolong the network lifetime. Note that energy efficiency is the most important design consideration in CRSNs because it determines the network lifetime. The central part of the EGSD scheme consists of two spectrum selection algorithms: random selection and game-theory-based selection. The EGSD scheme also includes a clustering algorithm, spectrum characterization with a Markov chain, and cluster member coordination. Our performance study shows that EGSD outperforms the existing popular framework in terms of network lifetime and coordination overhead. PMID:27376290

  16. Decorated tensor network renormalization for lattice gauge theories and spin foam models

    NASA Astrophysics Data System (ADS)

    Dittrich, Bianca; Mizera, Sebastian; Steinhaus, Sebastian

    2016-05-01

    Tensor network techniques have proved to be powerful tools that can be employed to explore the large scale dynamics of lattice systems. Nonetheless, the redundancy of degrees of freedom in lattice gauge theories (and related models) poses a challenge for standard tensor network algorithms. We accommodate for such systems by introducing an additional structure decorating the tensor network. This allows to explicitly preserve the gauge symmetry of the system under coarse graining and straightforwardly interpret the fixed point tensors. We propose and test (for models with finite Abelian groups) a coarse graining algorithm for lattice gauge theories based on decorated tensor networks. We also point out that decorated tensor networks are applicable to other models as well, where they provide the advantage to give immediate access to certain expectation values and correlation functions.

  17. An Energy-Efficient Game-Theory-Based Spectrum Decision Scheme for Cognitive Radio Sensor Networks

    PubMed Central

    Salim, Shelly; Moh, Sangman

    2016-01-01

    A cognitive radio sensor network (CRSN) is a wireless sensor network in which sensor nodes are equipped with cognitive radio. In this paper, we propose an energy-efficient game-theory-based spectrum decision (EGSD) scheme for CRSNs to prolong the network lifetime. Note that energy efficiency is the most important design consideration in CRSNs because it determines the network lifetime. The central part of the EGSD scheme consists of two spectrum selection algorithms: random selection and game-theory-based selection. The EGSD scheme also includes a clustering algorithm, spectrum characterization with a Markov chain, and cluster member coordination. Our performance study shows that EGSD outperforms the existing popular framework in terms of network lifetime and coordination overhead. PMID:27376290

  18. Automatic theory generation from analyst text files using coherence networks

    NASA Astrophysics Data System (ADS)

    Shaffer, Steven C.

    2014-05-01

    This paper describes a three-phase process of extracting knowledge from analyst textual reports. Phase 1 involves performing natural language processing on the source text to extract subject-predicate-object triples. In phase 2, these triples are then fed into a coherence network analysis process, using a genetic algorithm optimization. Finally, the highest-value sub networks are processed into a semantic network graph for display. Initial work on a well- known data set (a Wikipedia article on Abraham Lincoln) has shown excellent results without any specific tuning. Next, we ran the process on the SYNthetic Counter-INsurgency (SYNCOIN) data set, developed at Penn State, yielding interesting and potentially useful results.

  19. Mean field theory for scale-free random networks

    NASA Astrophysics Data System (ADS)

    Barabási, Albert-László; Albert, Réka; Jeong, Hawoong

    1999-10-01

    Random networks with complex topology are common in Nature, describing systems as diverse as the world wide web or social and business networks. Recently, it has been demonstrated that most large networks for which topological information is available display scale-free features. Here we study the scaling properties of the recently introduced scale-free model, that can account for the observed power-law distribution of the connectivities. We develop a mean-field method to predict the growth dynamics of the individual vertices, and use this to calculate analytically the connectivity distribution and the scaling exponents. The mean-field method can be used to address the properties of two variants of the scale-free model, that do not display power-law scaling.

  20. Statistical theory of designed quantum transport across disordered networks.

    PubMed

    Walschaers, Mattia; Mulet, Roberto; Wellens, Thomas; Buchleitner, Andreas

    2015-04-01

    We explain how centrosymmetry, together with a dominant doublet of energy eigenstates in the local density of states, can guarantee interference-assisted, strongly enhanced, strictly coherent quantum excitation transport between two predefined sites of a random network of two-level systems. Starting from a generalization of the chaos-assisted tunnelling mechanism, we formulate a random matrix theoretical framework for the analytical prediction of the transfer time distribution, of lower bounds of the transfer efficiency, and of the scaling behavior of characteristic statistical properties with the size of the network. We show that these analytical predictions compare well to numerical simulations, using Hamiltonians sampled from the Gaussian orthogonal ensemble. PMID:25974468

  1. Statistical theory of designed quantum transport across disordered networks

    NASA Astrophysics Data System (ADS)

    Walschaers, Mattia; Mulet, Roberto; Wellens, Thomas; Buchleitner, Andreas

    2015-04-01

    We explain how centrosymmetry, together with a dominant doublet of energy eigenstates in the local density of states, can guarantee interference-assisted, strongly enhanced, strictly coherent quantum excitation transport between two predefined sites of a random network of two-level systems. Starting from a generalization of the chaos-assisted tunnelling mechanism, we formulate a random matrix theoretical framework for the analytical prediction of the transfer time distribution, of lower bounds of the transfer efficiency, and of the scaling behavior of characteristic statistical properties with the size of the network. We show that these analytical predictions compare well to numerical simulations, using Hamiltonians sampled from the Gaussian orthogonal ensemble.

  2. Identification and description of coverage holes in a wireless sensor network using graph theory and homology

    NASA Astrophysics Data System (ADS)

    Uribe Peláez, Simon

    2010-04-01

    Identifying coverage holes makes an important topic for optimization of quality service for wireless sensor network hosts. This paper introduces a new way to identify and describe how is the network's structure, its number of holes and its components, assuming there's a sensor covering an area where a network communication exists. The simplicial complex method and algebraic graph theory will be applied. Betti numbers and Euler characteristics will be used for a sensor network represented by a simplicial complex, and the Tutte polynomial will be used for describing visual graphs algebraically, for a complete identification.

  3. Tuning RED parameters in satellite networks using control theory

    NASA Astrophysics Data System (ADS)

    Sridharan, Mukundan; Durresi, Arjan; Chellappan, Sriram; Ozbay, Hitay; Jain, Raj

    2003-08-01

    Congestion in the Internet results in wasted bandwidth and also stands in the way of guaranteeing QoS. The effect of congestion is multiplied many fold in Satellite networks, where the resources are very expensive. Thus congestion control has a special significance in the performance of Satellite networks. In today's Internet, congestion control is implemented mostly using some form of the de facto standard, RED. But tuning of parameters in RED has been a major problem throughout. Achieving high throughput with corresponding low delays is the main goal in parameter setting. It is also desired to keep the oscillations in the queue low to reduce jitter, so that the QoS guarantees can be improved. In this paper, we use a previously linearized fluid flow model of TCP-RED to study the performance and stability of the Queue in the router. We use classical control tools like Tracking Error minimization and Delay Margin to study the performance, stability of the system. We use the above-mentioned tools to provide guidelines for setting the parameters in RED, such that the throughput, delay and jitter of the system are optimized. Thus we provide guidelines for optimizing satellite IP networks. We apply our results exclusively for optimizing the performance of satellite networks, where the effects of congestion are much pronounced and need for optimization is much important. We use ns simulator to validate our results to support our analysis.

  4. Feedback Theory through the Lens of Social Networking

    ERIC Educational Resources Information Center

    Kio, Su Iong

    2015-01-01

    Feedback has long been utilised as an effective tool to enhance learning. Between students and teachers; students and students; students and schools, feedback provides a channel of communication between all parties within an education system. With the emergence and development of social networking sites (SNSs) over the past decade, it has become…

  5. Graph theory and stability analysis of protein complex interaction networks.

    PubMed

    Huang, Chien-Hung; Chen, Teng-Hung; Ng, Ka-Lok

    2016-04-01

    Protein complexes play an essential role in many biological processes. Complexes can interact with other complexes to form protein complex interaction network (PCIN) that involves in important cellular processes. There are relatively few studies on examining the interaction topology among protein complexes; and little is known about the stability of PCIN under perturbations. We employed graph theoretical approach to reveal hidden properties and features of four species PCINs. Two main issues are addressed, (i) the global and local network topological properties, and (ii) the stability of the networks under 12 types of perturbations. According to the topological parameter classification, we identified some critical protein complexes and validated that the topological analysis approach could provide meaningful biological interpretations of the protein complex systems. Through the Kolmogorov-Smimov test, we showed that local topological parameters are good indicators to characterise the structure of PCINs. We further demonstrated the effectiveness of the current approach by performing the scalability and data normalization tests. To measure the robustness of PCINs, we proposed to consider eight topological-based perturbations, which are specifically applicable in scenarios of targeted, sustained attacks. We found that the degree-based, betweenness-based and brokering-coefficient-based perturbations have the largest effect on network stability. PMID:26997661

  6. Intra- Versus Intersex Aggression: Testing Theories of Sex Differences Using Aggression Networks.

    PubMed

    Wölfer, Ralf; Hewstone, Miles

    2015-08-01

    Two theories offer competing explanations of sex differences in aggressive behavior: sexual-selection theory and social-role theory. While each theory has specific strengths and limitations depending on the victim's sex, research hardly differentiates between intrasex and intersex aggression. In the present study, 11,307 students (mean age = 14.96 years; 50% girls, 50% boys) from 597 school classes provided social-network data (aggression and friendship networks) as well as physical (body mass index) and psychosocial (gender and masculinity norms) information. Aggression networks were used to disentangle intra- and intersex aggression, whereas their class-aggregated sex differences were analyzed using contextual predictors derived from sexual-selection and social-role theories. As expected, results revealed that sexual-selection theory predicted male-biased sex differences in intrasex aggression, whereas social-role theory predicted male-biased sex differences in intersex aggression. Findings suggest the value of explaining sex differences separately for intra- and intersex aggression with a dual-theory framework covering both evolutionary and normative components. PMID:26158924

  7. 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…

  8. Learning Networks and the Journey of "Becoming Doctor"

    ERIC Educational Resources Information Center

    Barnacle, Robyn; Mewburn, Inger

    2010-01-01

    Scholars such as Kamler and Thompson argue that identity formation has a key role to play in doctoral learning, particularly the process of thesis writing. This article builds on these insights to address other sites in which scholarly identity is performed within doctoral candidature. Drawing on actor-network theory, the authors examine the role…

  9. A unified data representation theory for network visualization, ordering and coarse-graining

    NASA Astrophysics Data System (ADS)

    Kovács, István A.; Mizsei, Réka; Csermely, Péter

    2015-09-01

    Representation of large data sets became a key question of many scientific disciplines in the last decade. Several approaches for network visualization, data ordering and coarse-graining accomplished this goal. However, there was no underlying theoretical framework linking these problems. Here we show an elegant, information theoretic data representation approach as a unified solution of network visualization, data ordering and coarse-graining. The optimal representation is the hardest to distinguish from the original data matrix, measured by the relative entropy. The representation of network nodes as probability distributions provides an efficient visualization method and, in one dimension, an ordering of network nodes and edges. Coarse-grained representations of the input network enable both efficient data compression and hierarchical visualization to achieve high quality representations of larger data sets. Our unified data representation theory will help the analysis of extensive data sets, by revealing the large-scale structure of complex networks in a comprehensible form.

  10. Expert system for heart function based on artificial neural networks and fuzzy theory

    NASA Astrophysics Data System (ADS)

    Yu, Wei; Li, Xiaoying; Yu, Daoyin; Mao, Yi; Hua, Qi

    1998-09-01

    In this paper, a computer-aided diagnosis system for heart function based on artificial neural networks and fuzzy logic is introduced. Typical parameters reflecting heart function, provided by echocardiography, were used as input of neural networks and their corresponding heart functions as output. To obtain an analytic and discrimination model closer to brain, we combined fuzzy theory with neural network technology, and input parameters are fuzzily treated. During distinguishing morbid style, we used fuzzy interval, fuzzy number and its related possibility distribution concepts, and selected appropriate operator, and so get its corresponding membership, meanwhile membership was put out of interval of linguistic to consist with language expression. The network selected was BP, and back- propagation algorithm was used to train the network. After studying the result evaluated by expert, the neural network was used to appreciate 150 testees' heart function, of which 90.7% was consistent with experts' diagnosis.

  11. A unified data representation theory for network visualization, ordering and coarse-graining

    PubMed Central

    Kovács, István A.; Mizsei, Réka; Csermely, Péter

    2015-01-01

    Representation of large data sets became a key question of many scientific disciplines in the last decade. Several approaches for network visualization, data ordering and coarse-graining accomplished this goal. However, there was no underlying theoretical framework linking these problems. Here we show an elegant, information theoretic data representation approach as a unified solution of network visualization, data ordering and coarse-graining. The optimal representation is the hardest to distinguish from the original data matrix, measured by the relative entropy. The representation of network nodes as probability distributions provides an efficient visualization method and, in one dimension, an ordering of network nodes and edges. Coarse-grained representations of the input network enable both efficient data compression and hierarchical visualization to achieve high quality representations of larger data sets. Our unified data representation theory will help the analysis of extensive data sets, by revealing the large-scale structure of complex networks in a comprehensible form. PMID:26348923

  12. Social contagion theory: examining dynamic social networks and human behavior.

    PubMed

    Christakis, Nicholas A; Fowler, James H

    2013-02-20

    Here, we review the research we have conducted on social contagion. We describe the methods we have employed (and the assumptions they have entailed) to examine several datasets with complementary strengths and weaknesses, including the Framingham Heart Study, the National Longitudinal Study of Adolescent Health, and other observational and experimental datasets that we and others have collected. We describe the regularities that led us to propose that human social networks may exhibit a 'three degrees of influence' property, and we review statistical approaches we have used to characterize interpersonal influence with respect to phenomena as diverse as obesity, smoking, cooperation, and happiness. We do not claim that this work is the final word, but we do believe that it provides some novel, informative, and stimulating evidence regarding social contagion in longitudinally followed networks. Along with other scholars, we are working to develop new methods for identifying causal effects using social network data, and we believe that this area is ripe for statistical development as current methods have known and often unavoidable limitations. PMID:22711416

  13. Social contagion theory: examining dynamic social networks and human behavior

    PubMed Central

    Christakis, Nicholas A.; Fowler, James H.

    2013-01-01

    Here, we review the research we have conducted on social contagion. We describe the methods we have employed (and the assumptions they have entailed) to examine several datasets with complementary strengths and weaknesses, including the Framingham Heart Study, the National Longitudinal Study of Adolescent Health, and other observational and experimental datasets that we and others have collected. We describe the regularities that led us to propose that human social networks may exhibit a ‘three degrees of influence’ property, and we review statistical approaches we have used to characterize interpersonal influence with respect to phenomena as diverse as obesity, smoking, cooperation, and happiness. We do not claim that this work is the final word, but we do believe that it provides some novel, informative, and stimulating evidence regarding social contagion in longitudinally followed networks. Along with other scholars, we are working to develop new methods for identifying causal effects using social network data, and we believe that this area is ripe for statistical development as current methods have known and often unavoidable limitations. PMID:22711416

  14. Capturing dissipation and adhesion using transient network theory

    NASA Astrophysics Data System (ADS)

    Sing, Michelle; McKinley, Gareth; Olsen, Bradley

    Associative networks are prevalent in many fields and are of interest for applications where it is important that these materials are capable of adhering to their surroundings and/or provide a mechanism for dissipating energy in high-impact systems. However, little is known about the particular molecular behavior that differentiates these materials from their non-dissipative and non- adhesive associative counterparts. Here, we modify our previous work using the Smoluchowski equation to model the full network chain end-to-end distance distribution while tracking the population of individual chain conformations for chains that undergo multiple reaction intermediate steps. Thus, instead of the binary associated/dissociated states traditionally studied, we incorporate the ability for chains to partially dissociate and associate. This partial association/dissociation results in stress relaxation due to chain extension. In steady shear and start-up of steady shear, dissipation within the network becomes a function of both the elastically stored energy and the bond energy released during dissociation events.

  15. Allocation of computer ports within a terminal switching network: an application of queuing theory to gandalf port contenders

    SciTech Connect

    Vahle, M.O.

    1982-03-01

    Queuing theory is applied to the problem of assigning computer ports within a terminal switching network to maximize the likelihood of instant connect. A brief background of the network is included to focus on the statement of the problem.

  16. Information theory in systems biology. Part II: protein-protein interaction and signaling networks.

    PubMed

    Mousavian, Zaynab; Díaz, José; Masoudi-Nejad, Ali

    2016-03-01

    By the development of information theory in 1948 by Claude Shannon to address the problems in the field of data storage and data communication over (noisy) communication channel, it has been successfully applied in many other research areas such as bioinformatics and systems biology. In this manuscript, we attempt to review some of the existing literatures in systems biology, which are using the information theory measures in their calculations. As we have reviewed most of the existing information-theoretic methods in gene regulatory and metabolic networks in the first part of the review, so in the second part of our study, the application of information theory in other types of biological networks including protein-protein interaction and signaling networks will be surveyed. PMID:26691180

  17. On the correspondence between three nodes W states in quantum network theory and the oriented links in knot theory

    NASA Astrophysics Data System (ADS)

    Gu, Zhi-Yu; Qian, Shang-Wu

    2015-04-01

    The GHZ states and W states are two fundamental types of three qubits quantum entangled states. For finding the knotted pictures of three nodes W states, on the one side, we empty any one node, thus obtaining three degenerated two-node W states, then we find the nonzero submatrix of the corresponding covariance correlation tensor in quantum network theory. On the other side, excepting the linkage 41 corresponding to Bell bases, we conjecture that the another one possible oriented link (which is composed of two-component knots entangled with each other and has four crossings) would be the required knotted pictures of the two nodes W states, thence obtain the nonzero submatrix of the Alexander relation matrix in the theory of knot crystals for these knotted pictures. The equality of the two nonzero submatrices of different kinds thus verify the exactness of our conjecture. The superposition of three knotted pictures of two-node W states from different choices of the emptied node gives the knotted pictures of three-node W states, thus shows the correspondence between three-node W states in quantum network theory and the oriented links in knot theory. Finally we point out that there is an intimate and simple relationship between the knotted pictures of GHZ states and W states.

  18. Massive-Scale Gene Co-Expression Network Construction and Robustness Testing Using Random Matrix Theory

    PubMed Central

    Isaacson, Sven; Luo, Feng; Feltus, Frank A.; Smith, Melissa C.

    2013-01-01

    The study of gene relationships and their effect on biological function and phenotype is a focal point in systems biology. Gene co-expression networks built using microarray expression profiles are one technique for discovering and interpreting gene relationships. A knowledge-independent thresholding technique, such as Random Matrix Theory (RMT), is useful for identifying meaningful relationships. Highly connected genes in the thresholded network are then grouped into modules that provide insight into their collective functionality. While it has been shown that co-expression networks are biologically relevant, it has not been determined to what extent any given network is functionally robust given perturbations in the input sample set. For such a test, hundreds of networks are needed and hence a tool to rapidly construct these networks. To examine functional robustness of networks with varying input, we enhanced an existing RMT implementation for improved scalability and tested functional robustness of human (Homo sapiens), rice (Oryza sativa) and budding yeast (Saccharomyces cerevisiae). We demonstrate dramatic decrease in network construction time and computational requirements and show that despite some variation in global properties between networks, functional similarity remains high. Moreover, the biological function captured by co-expression networks thresholded by RMT is highly robust. PMID:23409071

  19. Lithofacies identification using multiple adaptive resonance theory neural networks and group decision expert system

    USGS Publications Warehouse

    Chang, H.-C.; Kopaska-Merkel, D. C.; Chen, H.-C.; Rocky, Durrans S.

    2000-01-01

    Lithofacies identification supplies qualitative information about rocks. Lithofacies represent rock textures and are important components of hydrocarbon reservoir description. Traditional techniques of lithofacies identification from core data are costly and different geologists may provide different interpretations. In this paper, we present a low-cost intelligent system consisting of three adaptive resonance theory neural networks and a rule-based expert system to consistently and objectively identify lithofacies from well-log data. The input data are altered into different forms representing different perspectives of observation of lithofacies. Each form of input is processed by a different adaptive resonance theory neural network. Among these three adaptive resonance theory neural networks, one neural network processes the raw continuous data, another processes categorial data, and the third processes fuzzy-set data. Outputs from these three networks are then combined by the expert system using fuzzy inference to determine to which facies the input data should be assigned. Rules are prioritized to emphasize the importance of firing order. This new approach combines the learning ability of neural networks, the adaptability of fuzzy logic, and the expertise of geologists to infer facies of the rocks. This approach is applied to the Appleton Field, an oil field located in Escambia County, Alabama. The hybrid intelligence system predicts lithofacies identity from log data with 87.6% accuracy. This prediction is more accurate than those of single adaptive resonance theory networks, 79.3%, 68.0% and 66.0%, using raw, fuzzy-set, and categorical data, respectively, and by an error-backpropagation neural network, 57.3%. (C) 2000 Published by Elsevier Science Ltd. All rights reserved.

  20. Lithofacies identification using multiple adaptive resonance theory neural networks and group decision expert system

    NASA Astrophysics Data System (ADS)

    Chang, Hsien-cheng; Kopaska-Merkel, David C.; Chen, Hui-Chuan; Durrans, S. Rocky

    2000-06-01

    Lithofacies identification supplies qualitative information about rocks. Lithofacies represent rock textures and are important components of hydrocarbon reservoir description. Traditional techniques of lithofacies identification from core data are costly and different geologists may provide different interpretations. In this paper, we present a low-cost intelligent system consisting of three adaptive resonance theory neural networks and a rule-based expert system to consistently and objectively identify lithofacies from well-log data. The input data are altered into different forms representing different perspectives of observation of lithofacies. Each form of input is processed by a different adaptive resonance theory neural network. Among these three adaptive resonance theory neural networks, one neural network processes the raw continuous data, another processes categorical data, and the third processes fuzzy-set data. Outputs from these three networks are then combined by the expert system using fuzzy inference to determine to which facies the input data should be assigned. Rules are prioritized to emphasize the importance of firing order. This new approach combines the learning ability of neural networks, the adaptability of fuzzy logic, and the expertise of geologists to infer facies of the rocks. This approach is applied to the Appleton Field, an oil field located in Escambia County, Alabama. The hybrid intelligence system predicts lithofacies identity from log data with 87.6% accuracy. This prediction is more accurate than those of single adaptive resonance theory networks, 79.3%, 68.0% and 66.0%, using raw, fuzzy-set, and categorical data, respectively, and by an error-backpropagation neural network, 57.3%.

  1. Extending unified-theory-of-reinforcement neural networks to steady-state operant behavior.

    PubMed

    Calvin, Olivia L; McDowell, J J

    2016-06-01

    The unified theory of reinforcement has been used to develop models of behavior over the last 20 years (Donahoe et al., 1993). Previous research has focused on the theory's concordance with the respondent behavior of humans and animals. In this experiment, neural networks were developed from the theory to extend the unified theory of reinforcement to operant behavior on single-alternative variable-interval schedules. This area of operant research was selected because previously developed neural networks could be applied to it without significant alteration. Previous research with humans and animals indicates that the pattern of their steady-state behavior is hyperbolic when plotted against the obtained rate of reinforcement (Herrnstein, 1970). A genetic algorithm was used in the first part of the experiment to determine parameter values for the neural networks, because values that were used in previous research did not result in a hyperbolic pattern of behavior. After finding these parameters, hyperbolic and other similar functions were fitted to the behavior produced by the neural networks. The form of the neural network's behavior was best described by an exponentiated hyperbola (McDowell, 1986; McLean and White, 1983; Wearden, 1981), which was derived from the generalized matching law (Baum, 1974). In post-hoc analyses the addition of a baseline rate of behavior significantly improved the fit of the exponentiated hyperbola and removed systematic residuals. The form of this function was consistent with human and animal behavior, but the estimated parameter values were not. PMID:27018201

  2. Exploring the Combination of Dempster-Shafer Theory and Neural Network for Predicting Trust and Distrust.

    PubMed

    Wang, Xin; Wang, Ying; Sun, Hongbin

    2016-01-01

    In social media, trust and distrust among users are important factors in helping users make decisions, dissect information, and receive recommendations. However, the sparsity and imbalance of social relations bring great difficulties and challenges in predicting trust and distrust. Meanwhile, there are numerous inducing factors to determine trust and distrust relations. The relationship among inducing factors may be dependency, independence, and conflicting. Dempster-Shafer theory and neural network are effective and efficient strategies to deal with these difficulties and challenges. In this paper, we study trust and distrust prediction based on the combination of Dempster-Shafer theory and neural network. We firstly analyze the inducing factors about trust and distrust, namely, homophily, status theory, and emotion tendency. Then, we quantify inducing factors of trust and distrust, take these features as evidences, and construct evidence prototype as input nodes of multilayer neural network. Finally, we propose a framework of predicting trust and distrust which uses multilayer neural network to model the implementing process of Dempster-Shafer theory in different hidden layers, aiming to overcome the disadvantage of Dempster-Shafer theory without optimization method. Experimental results on a real-world dataset demonstrate the effectiveness of the proposed framework. PMID:27034651

  3. Exploring the Combination of Dempster-Shafer Theory and Neural Network for Predicting Trust and Distrust

    PubMed Central

    Wang, Xin; Wang, Ying; Sun, Hongbin

    2016-01-01

    In social media, trust and distrust among users are important factors in helping users make decisions, dissect information, and receive recommendations. However, the sparsity and imbalance of social relations bring great difficulties and challenges in predicting trust and distrust. Meanwhile, there are numerous inducing factors to determine trust and distrust relations. The relationship among inducing factors may be dependency, independence, and conflicting. Dempster-Shafer theory and neural network are effective and efficient strategies to deal with these difficulties and challenges. In this paper, we study trust and distrust prediction based on the combination of Dempster-Shafer theory and neural network. We firstly analyze the inducing factors about trust and distrust, namely, homophily, status theory, and emotion tendency. Then, we quantify inducing factors of trust and distrust, take these features as evidences, and construct evidence prototype as input nodes of multilayer neural network. Finally, we propose a framework of predicting trust and distrust which uses multilayer neural network to model the implementing process of Dempster-Shafer theory in different hidden layers, aiming to overcome the disadvantage of Dempster-Shafer theory without optimization method. Experimental results on a real-world dataset demonstrate the effectiveness of the proposed framework. PMID:27034651

  4. Dynamical influence processes on networks: general theory and applications to social contagion.

    PubMed

    Harris, Kameron Decker; Danforth, Christopher M; Dodds, Peter Sheridan

    2013-08-01

    We study binary state dynamics on a network where each node acts in response to the average state of its neighborhood. By allowing varying amounts of stochasticity in both the network and node responses, we find different outcomes in random and deterministic versions of the model. In the limit of a large, dense network, however, we show that these dynamics coincide. We construct a general mean-field theory for random networks and show this predicts that the dynamics on the network is a smoothed version of the average response function dynamics. Thus, the behavior of the system can range from steady state to chaotic depending on the response functions, network connectivity, and update synchronicity. As a specific example, we model the competing tendencies of imitation and nonconformity by incorporating an off-threshold into standard threshold models of social contagion. In this way, we attempt to capture important aspects of fashions and societal trends. We compare our theory to extensive simulations of this "limited imitation contagion" model on Poisson random graphs, finding agreement between the mean-field theory and stochastic simulations. PMID:24032892

  5. Dynamical influence processes on networks: General theory and applications to social contagion

    NASA Astrophysics Data System (ADS)

    Harris, Kameron Decker; Danforth, Christopher M.; Dodds, Peter Sheridan

    2013-08-01

    We study binary state dynamics on a network where each node acts in response to the average state of its neighborhood. By allowing varying amounts of stochasticity in both the network and node responses, we find different outcomes in random and deterministic versions of the model. In the limit of a large, dense network, however, we show that these dynamics coincide. We construct a general mean-field theory for random networks and show this predicts that the dynamics on the network is a smoothed version of the average response function dynamics. Thus, the behavior of the system can range from steady state to chaotic depending on the response functions, network connectivity, and update synchronicity. As a specific example, we model the competing tendencies of imitation and nonconformity by incorporating an off-threshold into standard threshold models of social contagion. In this way, we attempt to capture important aspects of fashions and societal trends. We compare our theory to extensive simulations of this “limited imitation contagion” model on Poisson random graphs, finding agreement between the mean-field theory and stochastic simulations.

  6. A network theory approach for a better understanding of overland flow connectivity

    NASA Astrophysics Data System (ADS)

    Masselink, Rens; Heckmann, Tobias; Temme, Arnaud; Anders, Niels; Keesstra, Saskia

    2016-04-01

    Hydrological connectivity describes the physical coupling, or linkages of different elements within a landscape regarding (sub)surface flows. A firm understanding of hydrological connectivity is important for catchment management applications, for e.g. habitat and species protection, and for flood resistance and resilience improvement. Thinking about (geomorphological) systems as networks can lead to new insights, which has been recognised within the scientific community as well, seeing the recent increase in the use of network (graph) theory within the geosciences. Network theory supports the analysis and understanding of complex systems by providing data structures for modelling objects and their linkages, and a versatile toolbox to quantitatively appraise network structure and properties. The objective of this study was to characterise overland flow connectivity dynamics on hillslopes in a humid sub-Mediterranean environment by using a combination of high-resolution digital-terrain models, overland flow sensors and a network approach. Results showed that there are significant differences between overland flow on agricultural areas and semi-natural shrubs areas. Positive correlations between connectivity and precipitation characteristics were found, while negative correlations between connectivity and soil moisture were found, probably due to soil water repellency. The combination of a structural network to determine potential connectivity with dynamic networks to determine the actual connectivity proved a powerful tool in analysing overland flow connectivity.

  7. Finite state model and compatibility theory - New analysis tools for permutation networks

    NASA Technical Reports Server (NTRS)

    Huang, S.-T.; Tripathi, S. K.

    1986-01-01

    A simple model to describe the fundamental operation theory of shuffle-exchange-type permutation networks, the finite permutation machine (FPM), is described, and theorems which transform the control matrix result to a continuous compatible vector result are developed. It is found that only 2n-1 shuffle exchange passes are necessary, and that 3n-3 passes are sufficient, to realize all permutations, reducing the sufficient number of passes by two from previous results. The flexibility of the approach is demonstrated by the description of a stack permutation machine (SPM) which can realize all permutations, and by showing that the FPM corresponding to the Benes (1965) network belongs to the SPM. The FPM corresponding to the network with two cascaded reverse-exchange networks is found to realize all permutations, and a simple mechanism to verify several equivalence relationships of various permutation networks is discussed.

  8. Dissolved oxygen prediction using a possibility theory based fuzzy neural network

    NASA Astrophysics Data System (ADS)

    Khan, Usman T.; Valeo, Caterina

    2016-06-01

    A new fuzzy neural network method to predict minimum dissolved oxygen (DO) concentration in a highly urbanised riverine environment (in Calgary, Canada) is proposed. The method uses abiotic factors (non-living, physical and chemical attributes) as inputs to the model, since the physical mechanisms governing DO in the river are largely unknown. A new two-step method to construct fuzzy numbers using observations is proposed. Then an existing fuzzy neural network is modified to account for fuzzy number inputs and also uses possibility theory based intervals to train the network. Results demonstrate that the method is particularly well suited to predicting low DO events in the Bow River. Model performance is compared with a fuzzy neural network with crisp inputs, as well as with a traditional neural network. Model output and a defuzzification technique are used to estimate the risk of low DO so that water resource managers can implement strategies to prevent the occurrence of low DO.

  9. Material Matters for Learning in Virtual Networks: A Case Study of a Professional Learning Programme Hosted in a Google+ Online Community

    ERIC Educational Resources Information Center

    Ackland, Aileen; Swinney, Ann

    2015-01-01

    In this paper, we draw on Actor-Network Theories (ANT) to explore how material components functioned to create gateways and barriers to a virtual learning network in the context of a professional development module in higher education. Students were practitioners engaged in family learning in different professional roles and contexts. The data…

  10. Bombing Alone: Tracing the Motivations and Antecedent Behaviors of Lone-Actor Terrorists*,†,‡

    PubMed Central

    Gill, Paul; Horgan, John; Deckert, Paige

    2014-01-01

    This article analyzes the sociodemographic network characteristics and antecedent behaviors of 119 lone-actor terrorists. This marks a departure from existing analyses by largely focusing upon behavioral aspects of each offender. This article also examines whether lone-actor terrorists differ based on their ideologies or network connectivity. The analysis leads to seven conclusions. There was no uniform profile identified. In the time leading up to most lone-actor terrorist events, other people generally knew about the offender’s grievance, extremist ideology, views, and/or intent to engage in violence. A wide range of activities and experiences preceded lone actors’ plots or events. Many but not all lone-actor terrorists were socially isolated. Lone-actor terrorists regularly engaged in a detectable and observable range of activities with a wider pressure group, social movement, or terrorist organization. Lone-actor terrorist events were rarely sudden and impulsive. There were distinguishable behavioral differences between subgroups. The implications for policy conclude this article. PMID:24313297

  11. Development of Novel Random Network Theory-Based Approaches to Identify Network Interactions among Nitrifying Bacteria

    SciTech Connect

    Shi, Cindy

    2015-07-17

    The interactions among different microbial populations in a community could play more important roles in determining ecosystem functioning than species numbers and their abundances, but very little is known about such network interactions at a community level. The goal of this project is to develop novel framework approaches and associated software tools to characterize the network interactions in microbial communities based on high throughput, large scale high-throughput metagenomics data and apply these approaches to understand the impacts of environmental changes (e.g., climate change, contamination) on network interactions among different nitrifying populations and associated microbial communities.

  12. Finite state model and compatibility theory: New analysis tools for permutation networks

    SciTech Connect

    Huang, S.T.; Fripathi, S.K.

    1986-07-01

    In this paper, the authors present a new model, finite permutation machine (FPM), to describe the permutation networks. A set of theorems are developed to capture the theory of operations for the permutation networks. Using this new framework, an interesting problem is attacked: are 2n-1 passes of shuffle exchange necessary and sufficient to realize all permutations. where n=log/sub 2/N and N is the number of inputs and outputs interconnected by the network. They prove that to realize all permutations, 2n-1 passes of shuffle exchange are necessary and that 3n-3 passes are sufficient. This reduces the sufficient number of passes by 2 from the best-known result. Benes network is the most well-known network that can realize all permutations. To show the flexibility of the approach, the authors describe a general class of FPM, stack permutation machine (SPM), which can realize all permutations, and show that FPM corresponding to Benes network belongs to SPM. They also show that FPM corresponding to the network with 2 cascaded reverse-exchange networks can realize all permutations. To show the simplicity of the approach, they also present a very simple mechanism to verify several equivalence relationships of various permutation networks.

  13. Investigating the topology of interacting networks. Theory and application to coupled climate subnetworks

    NASA Astrophysics Data System (ADS)

    Donges, J. F.; Schultz, H. C. H.; Marwan, N.; Zou, Y.; Kurths, J.

    2011-12-01

    Network theory provides various tools for investigating the structural or functional topology of many complex systems found in nature, technology and society. Nevertheless, it has recently been realised that a considerable number of systems of interest should be treated, more appropriately, as interacting networks or networks of networks. Here we introduce a novel graph-theoretical framework for studying the interaction structure between subnetworks embedded within a complex network of networks. This framework allows us to quantify the structural role of single vertices or whole subnetworks with respect to the interaction of a pair of subnetworks on local, mesoscopic and global topological scales. Climate networks have recently been shown to be a powerful tool for the analysis of climatological data. Applying the general framework for studying interacting networks, we introduce coupled climate subnetworks to represent and investigate the topology of statistical relationships between the fields of distinct climatological variables. Using coupled climate subnetworks to investigate the terrestrial atmosphere's three-dimensional geopotential height field uncovers known as well as interesting novel features of the atmosphere's vertical stratification and general circulation. Specifically, the new measure "cross-betweenness" identifies regions which are particularly important for mediating vertical wind field interactions. The promising results obtained by following the coupled climate subnetwork approach present a first step towards an improved understanding of the Earth system and its complex interacting components from a network perspective.

  14. Tolerance of Practices by Muslim Actors: An Integrative Social-Developmental Perspective

    ERIC Educational Resources Information Center

    Gieling, Maike; Thijs, Jochem; Verkuyten, Maykel

    2010-01-01

    Using social-cognitive domain theory and social identity theory, tolerance judgments of practices by Muslim actors among Dutch adolescents (12-17) were investigated. The findings for Study 1 (N = 180) demonstrated that participants evaluated 4 practices using different types of reasons: personal, social-conventional, and moral. In Study 2 (N =…

  15. Functional brain networks contributing to the Parieto-Frontal Integration Theory of Intelligence.

    PubMed

    Vakhtin, Andrei A; Ryman, Sephira G; Flores, Ranee A; Jung, Rex E

    2014-12-01

    The refinement of localization of intelligence in the human brain is converging onto a distributed network that broadly conforms to the Parieto-Frontal Integration Theory (P-FIT). While this theory has received support in the neuroimaging literature, no functional magnetic resonance imaging study to date has conducted a whole-brain network-wise examination of the changes during engagement in tasks that are reliable measures of general intelligence (e.g., Raven's Progressive Matrices Test; RPM). Seventy-nine healthy subjects were scanned while solving RPM problems and during rest. Functional networks were extracted from the RPM and resting state data using Independent Component Analysis. Twenty-nine networks were identified, 26 of which were detected in both conditions. Fourteen networks were significantly correlated with the RPM task. The networks' spatial maps and functional connectivity measures at 3 frequency levels (low, medium, & high) were compared between the RPM and rest conditions. The regions involved in the networks that were found to be task related were consistent with the P-FIT, localizing to the bilateral medial frontal and parietal regions, right superior frontal lobule, and the right cingulate gyrus. Functional connectivity in multiple component pairs was differentially affected across all frequency levels during the RPM task. Our findings demonstrate that functional brain networks are more stable than previously thought, and maintain their general features across resting state and engagement in a complex cognitive task. The described spatial and functional connectivity alterations that such components undergo during fluid reasoning provide a network-wise framework of the P-FIT that can be valuable for further, network based, neuroimaging inquiries regarding the neural underpinnings of intelligence. PMID:25284305

  16. Modeling and dynamical topology properties of VANET based on complex networks theory

    NASA Astrophysics Data System (ADS)

    Zhang, Hong; Li, Jie

    2015-01-01

    Vehicular Ad hoc Network (VANET) is a special subset of multi-hop Mobile Ad hoc Networks in which vehicles can not only communicate with each other but also with the fixed equipments along the roads through wireless interfaces. Recently, it has been discovered that essential systems in real world share similar properties. When they are regarded as networks, among which the dynamic topology structure of VANET system is an important issue. Many real world networks are actually growing with preferential attachment like Internet, transportation system and telephone network. Those phenomena have brought great possibility in finding a strategy to calibrate and control the topology parameters which can help find VANET topology change regulation to relieve traffic jam, prevent traffic accident and improve traffic safety. VANET is a typical complex network which has its basic characteristics. In this paper, we focus on the macroscopic Vehicle-to-Infrastructure (V2I) and Vehicle-to-Vehicle (V2V) inter-vehicle communication network with complex network theory. In particular, this paper is the first one to propose a method analyzing the topological structure and performance of VANET and present the communications in VANET from a new perspective. Accordingly, we propose degree distribution, clustering coefficient and the short path length of complex network to implement our strategy by numerical example and simulation. All the results demonstrate that VANET shows small world network features and is characterized by a truncated scale-free degree distribution with power-law degree distribution. The average path length of the network is simulated numerically, which indicates that the network shows small-world property and is rarely affected by the randomness. What's more, we carry out extensive simulations of information propagation and mathematically prove the power law property when γ > 2. The results of this study provide useful information for VANET optimization from a

  17. Modeling and dynamical topology properties of VANET based on complex networks theory

    SciTech Connect

    Zhang, Hong; Li, Jie

    2015-01-15

    Vehicular Ad hoc Network (VANET) is a special subset of multi-hop Mobile Ad hoc Networks in which vehicles can not only communicate with each other but also with the fixed equipments along the roads through wireless interfaces. Recently, it has been discovered that essential systems in real world share similar properties. When they are regarded as networks, among which the dynamic topology structure of VANET system is an important issue. Many real world networks are actually growing with preferential attachment like Internet, transportation system and telephone network. Those phenomena have brought great possibility in finding a strategy to calibrate and control the topology parameters which can help find VANET topology change regulation to relieve traffic jam, prevent traffic accident and improve traffic safety. VANET is a typical complex network which has its basic characteristics. In this paper, we focus on the macroscopic Vehicle-to-Infrastructure (V2I) and Vehicle-to-Vehicle (V2V) inter-vehicle communication network with complex network theory. In particular, this paper is the first one to propose a method analyzing the topological structure and performance of VANET and present the communications in VANET from a new perspective. Accordingly, we propose degree distribution, clustering coefficient and the short path length of complex network to implement our strategy by numerical example and simulation. All the results demonstrate that VANET shows small world network features and is characterized by a truncated scale-free degree distribution with power-law degree distribution. The average path length of the network is simulated numerically, which indicates that the network shows small-world property and is rarely affected by the randomness. What’s more, we carry out extensive simulations of information propagation and mathematically prove the power law property when γ > 2. The results of this study provide useful information for VANET optimization from a

  18. A Computer-Based Education Approach to Electrical Network Theory: Lesson Development, Use and Evaluation.

    ERIC Educational Resources Information Center

    Grossel, Roger Louis

    This study investigated the use of the PLATO III computer assisted instruction (CAI) system to assist in the teaching of an electrical network theory course. It sought to: 1) identify the topics and teaching strategies most amenable to CAI system; 2) develop computer programs needed to teach those topics; 3) use, evaluate and service the programs;…

  19. Faculty Social Networking Interactions: Using Social Domain Theory to Assess Student Views

    ERIC Educational Resources Information Center

    Nemetz, Patricia L.

    2012-01-01

    As educators consider using social networking sites, like Facebook, for educational innovations, they must be aware of possible vulnerabilities associated with the blurring of social and professional boundaries. This research uses social domain theory to examine how students rate the appropriateness of various faculty postings, behaviors, and…

  20. Time dependent mechanical modeling for polymers based on network theory

    NASA Astrophysics Data System (ADS)

    Billon, Noëlle

    2016-05-01

    Despite of a lot of attempts during recent years, complex mechanical behaviour of polymers remains incompletely modelled, making industrial design of structures under complex, cyclic and hard loadings not totally reliable. The non linear and dissipative viscoelastic, viscoplastic behaviour of those materials impose to take into account non linear and combined effects of mechanical and thermal phenomena. In this view, a visco-hyperelastic, viscoplastic model, based on network description of the material has recently been developed and designed in a complete thermodynamic frame in order to take into account those main thermo-mechanical couplings. Also, a way to account for coupled effects of strain-rate and temperature was suggested. First experimental validations conducted in the 1D limit on amorphous rubbery like PMMA in isothermal conditions led to pretty goods results. In this paper a more complete formalism is presented and validated in the case of a semi crystalline polymer, a PA66 and a PET (either amorphous or semi crystalline) are used. Protocol for identification of constitutive parameters is described. It is concluded that this new approach should be the route to accurately model thermo-mechanical behaviour of polymers using a reduced number of parameters of some physicl meaning.

  1. Partial Synchronization in Pulse-Coupled Oscillator Networks I: Theory

    NASA Astrophysics Data System (ADS)

    Engelbrecht, Jan; Chen, Bolun; Mirollo, Renato

    We study N identical integrate and fire model neurons coupled in an all to all network through α-function pulses, weighted by a parameter K. Studies of the dynamics of this system often focus on the stability of the fully synchronous and the fully asynchronous splay states, that naturally depend on the sign of K, i.e. excitation vs inhibition. We find that for finite N there is a rich set of other partially synchronized attractors, such as (N - 1 , 1) fixed states and partially synchronized splay states. Our framework exploits the neutrality of the dynamics for K = 0 which allows us to implement a dimensional reduction strategy that replaces the discrete pulses with a continuous flow, with the sign of K determining the flow direction. This framework naturally incorporates a hierarchy of partially synchronized subspaces in which the new states lie. For N = 2 , 3 , 4 , we completely describe the sequence of bifurcations and the stability of all fixed points and limit cycles. Work Supported by NSF DMS 1413020.

  2. A game theory approach to target tracking in sensor networks.

    PubMed

    Gu, Dongbing

    2011-02-01

    In this paper, we investigate a moving-target tracking problem with sensor networks. Each sensor node has a sensor to observe the target and a processor to estimate the target position. It also has wireless communication capability but with limited range and can only communicate with neighbors. The moving target is assumed to be an intelligent agent, which is "smart" enough to escape from the detection by maximizing the estimation error. This adversary behavior makes the target tracking problem more difficult. We formulate this target estimation problem as a zero-sum game in this paper and use a minimax filter to estimate the target position. The minimax filter is a robust filter that minimizes the estimation error by considering the worst case noise. Furthermore, we develop a distributed version of the minimax filter for multiple sensor nodes. The distributed computation is implemented via modeling the information received from neighbors as measurements in the minimax filter. The simulation results show that the target tracking algorithm proposed in this paper provides a satisfactory result. PMID:20194057

  3. Network Theory: A Primer and Questions for Air Transportation Systems Applications

    NASA Technical Reports Server (NTRS)

    Holmes, Bruce J.

    2004-01-01

    A new understanding (with potential applications to air transportation systems) has emerged in the past five years in the scientific field of networks. This development emerges in large part because we now have a new laboratory for developing theories about complex networks: The Internet. The premise of this new understanding is that most complex networks of interest, both of nature and of human contrivance, exhibit a fundamentally different behavior than thought for over two hundred years under classical graph theory. Classical theory held that networks exhibited random behavior, characterized by normal, (e.g., Gaussian or Poisson) degree distributions of the connectivity between nodes by links. The new understanding turns this idea on its head: networks of interest exhibit scale-free (or small world) degree distributions of connectivity, characterized by power law distributions. The implications of scale-free behavior for air transportation systems include the potential that some behaviors of complex system architectures might be analyzed through relatively simple approximations of local elements of the system. For air transportation applications, this presentation proposes a framework for constructing topologies (architectures) that represent the relationships between mobility, flight operations, aircraft requirements, and airspace capacity, and the related externalities in airspace procedures and architectures. The proposed architectures or topologies may serve as a framework for posing comparative and combinative analyses of performance, cost, security, environmental, and related metrics.

  4. Delinquency, Social Skills and the Structure of Peer Relations: Assessing Criminological Theories by Social Network Theory

    ERIC Educational Resources Information Center

    Smangs, Mattias

    2010-01-01

    This article explores the plausibility of the conflicting theoretical assumptions underlying the main criminological perspectives on juvenile delinquents, their peer relations and social skills: the social ability model, represented by Sutherland's theory of differential associations, and the social disability model, represented by Hirschi's…

  5. Game Theory Meets Wireless Sensor Networks Security Requirements and Threats Mitigation: A Survey

    PubMed Central

    Abdalzaher, Mohamed S.; Seddik, Karim; Elsabrouty, Maha; Muta, Osamu; Furukawa, Hiroshi; Abdel-Rahman, Adel

    2016-01-01

    We present a study of using game theory for protecting wireless sensor networks (WSNs) from selfish behavior or malicious nodes. Due to scalability, low complexity and disseminated nature of WSNs, malicious attacks can be modeled effectively using game theory. In this study, we survey the different game-theoretic defense strategies for WSNs. We present a taxonomy of the game theory approaches based on the nature of the attack, whether it is caused by an external attacker or it is the result of an internal node acting selfishly or maliciously. We also present a general trust model using game theory for decision making. We, finally, identify the significant role of evolutionary games for WSNs security against intelligent attacks; then, we list several prospect applications of game theory to enhance the data trustworthiness and node cooperation in different WSNs. PMID:27367700

  6. Game Theory Meets Wireless Sensor Networks Security Requirements and Threats Mitigation: A Survey.

    PubMed

    Abdalzaher, Mohamed S; Seddik, Karim; Elsabrouty, Maha; Muta, Osamu; Furukawa, Hiroshi; Abdel-Rahman, Adel

    2016-01-01

    We present a study of using game theory for protecting wireless sensor networks (WSNs) from selfish behavior or malicious nodes. Due to scalability, low complexity and disseminated nature of WSNs, malicious attacks can be modeled effectively using game theory. In this study, we survey the different game-theoretic defense strategies for WSNs. We present a taxonomy of the game theory approaches based on the nature of the attack, whether it is caused by an external attacker or it is the result of an internal node acting selfishly or maliciously. We also present a general trust model using game theory for decision making. We, finally, identify the significant role of evolutionary games for WSNs security against intelligent attacks; then, we list several prospect applications of game theory to enhance the data trustworthiness and node cooperation in different WSNs. PMID:27367700

  7. Neural networks, field theory, directed percolation, and critical branching

    NASA Astrophysics Data System (ADS)

    Buice, Michael A.

    We describe the dynamics of neural activity using field-theoretic methods for non-equilibrium statistical processes. Using a Markov assumption, we introduce the "spike model". The spike model permits a characterization of both neural fluctuations and response, presenting a tractable way to extend the mean field (Wilson-Cowan) equations used in much of theoretical and computational neuroscience. We also demonstrate the formalism's application to the Cowan models, one of which is equivalent to the forest fire model with immune trees. We argue that neural activity under mild conditions exhibits a dynamical phase transition which is in the universality class of directed percolation (DP). Owing to the spatial extent of neural interactions, there is a region in which the critical behavior is that of a branching process before crossing over into the DP region, consistent with measurements in cortical slice preparations. From the perspective of theoretical neuroscience, a principal contribution of this work is the connection of the problem of non-linear, non-Gaussian systems with the problem of dealing with infrared singularities in field theory. This work suggests a general characterization of epilepsy as a manifestation of a directed percolation phase transition.

  8. Fragmentation network of doubly charged methionine: Interpretation using graph theory.

    PubMed

    Ha, D T; Yamazaki, K; Wang, Y; Alcamí, M; Maeda, S; Kono, H; Martín, F; Kukk, E

    2016-09-01

    The fragmentation of doubly charged gas-phase methionine (HO2CCH(NH2)CH2CH2SCH3) is systematically studied using the self-consistent charge density functional tight-binding molecular dynamics (MD) simulation method. We applied graph theory to analyze the large number of the calculated MD trajectories, which appears to be a highly effective and convenient means of extracting versatile information from the large data. The present theoretical results strongly concur with the earlier studied experimental ones. Essentially, the dication dissociates into acidic group CO2H and basic group C4NSH10. The former may carry a single or no charge and stays intact in most cases, whereas the latter may hold either a single or a double charge and tends to dissociate into smaller fragments. The decay of the basic group is observed to follow the Arrhenius law. The dissociation pathways to CO2H and C4NSH10 and subsequent fragmentations are also supported by ab initio calculations. PMID:27608997

  9. Review of uses of network and graph theory concepts within proteomics.

    PubMed

    Grindrod, Peter; Kibble, Milla

    2004-08-01

    The size and nature of data collected on gene and protein interactions has led to a rapid growth of interest in graph theory and modern techniques for describing, characterizing and comparing networks. Simultaneously, this is a field of growth within mathematics and theoretical physics, where the global properties, and emergent behavior of networks, as a function of the local properties has long been studied. In this review, a number of approaches for exploiting modern network theory to help describe and analyze different data sets and problems associated with proteomic data are considered. This review aims to help biologists find their way towards useful ideas and references, yet may also help scientists from a mathematics and physics background to understand where they may apply their expertise. PMID:15966817

  10. Modeling and training emotional talking faces of virtual actors in synthetic movies

    NASA Astrophysics Data System (ADS)

    Karunaratne, Savant; Yan, Hong

    2000-05-01

    This paper presents an overview of a virtual actor system composed of several subsystems designed to automate some of these animation tasks. Our emphasis is on the facial animation of virtual actors. The paper specifically details the situations processor component of the framework, which is a major building block in the automatic virtual actor system. An expert system using a fuzzy knowledge-based control system is used to realize the automated system. Fuzzy linguistic rules are used to train virtual actors to know the appropriate emotions and gestures to use in different situations of a synthetic movie, the higher level parameters of which are provided by human directors. Theories of emotion, personality, dialogue, and acting, as well as empirical evidence is incorporated into our framework and knowledge bases to produce promising results.

  11. Speed of synchronization in complex networks of neural oscillators: Analytic results based on Random Matrix Theory

    NASA Astrophysics Data System (ADS)

    Timme, Marc; Geisel, Theo; Wolf, Fred

    2006-03-01

    We analyze the dynamics of networks of spiking neural oscillators. First, we present an exact linear stability theory of the synchronous state for networks of arbitrary connectivity. For general neuron rise functions, stability is determined by multiple operators, for which standard analysis is not suitable. We describe a general nonstandard solution to the multioperator problem. Subsequently, we derive a class of neuronal rise functions for which all stability operators become degenerate and standard eigenvalue analysis becomes a suitable tool. Interestingly, this class is found to consist of networks of leaky integrate-and-fire neurons. For random networks of inhibitory integrate-and-fire neurons, we then develop an analytical approach, based on the theory of random matrices, to precisely determine the eigenvalue distributions of the stability operators. This yields the asymptotic relaxation time for perturbations to the synchronous state which provides the characteristic time scale on which neurons can coordinate their activity in such networks. For networks with finite in-degree, i.e., finite number of presynaptic inputs per neuron, we find a speed limit to coordinating spiking activity. Even with arbitrarily strong interaction strengths neurons cannot synchronize faster than at a certain maximal speed determined by the typical in-degree.

  12. Bad Actors Criticality Assessment for Pipeline system

    NASA Astrophysics Data System (ADS)

    Nasir, Meseret; Chong, Kit wee; Osman, Sabtuni; Siaw Khur, Wee

    2015-04-01

    Failure of a pipeline system could bring huge economic loss. In order to mitigate such catastrophic loss, it is required to evaluate and rank the impact of each bad actor of the pipeline system. In this study, bad actors are known as the root causes or any potential factor leading to the system downtime. Fault Tree Analysis (FTA) is used to analyze the probability of occurrence for each bad actor. Bimbaum's Importance and criticality measure (BICM) is also employed to rank the impact of each bad actor on the pipeline system failure. The results demonstrate that internal corrosion; external corrosion and construction damage are critical and highly contribute to the pipeline system failure with 48.0%, 12.4% and 6.0% respectively. Thus, a minor improvement in internal corrosion; external corrosion and construction damage would bring significant changes in the pipeline system performance and reliability. These results could also be useful to develop efficient maintenance strategy by identifying the critical bad actors.

  13. Appia, Craig and the Actor: A New Look.

    ERIC Educational Resources Information Center

    Hubbard, Oliver F., Jr.

    Despite the amount of attention paid Adolphe Appia and Edward Gordon Craig, a misconception persists with regard to their ideas concerning the actor; namely, that Appia had the actor dominate all the elements of staging, and that Craig considered the actor less essential. However, to both, the actor was both essential and nonessential to the…

  14. Strengthening Prevention Program Theories and Evaluations: Contributions from Social Network Analysis

    PubMed Central

    Gest, Scott D.; Osgood, D. Wayne; Feinberg, Mark; Bierman, Karen L.; Moody, James

    2011-01-01

    A majority of school-based prevention programs target the modification of setting-level social dynamics, either explicitly (e.g., by changing schools’ organizational, cultural or instructional systems that influence children’s relationships), or implicitly (e.g., by altering behavioral norms designed to influence children’s social affiliations and interactions). Yet, in outcome analyses of these programs, the rich and complicated set of peer network dynamics is often reduced to an aggregation of individual characteristics or assessed with methods that do not account for the interdependencies of network data. In this paper, we present concepts and analytic methods from the field of social network analysis and illustrate their great value to prevention science – both as a source of tools for refining program theories and as methods that enable more sophisticated and focused tests of intervention effects. An additional goal is to inform discussions of the broader implications of social network analysis for public health efforts. PMID:21728069

  15. Strengthening prevention program theories and evaluations: contributions from social network analysis.

    PubMed

    Gest, Scott D; Osgood, D Wayne; Feinberg, Mark E; Bierman, Karen L; Moody, James

    2011-12-01

    A majority of school-based prevention programs target the modification of setting-level social dynamics, either explicitly (e.g., by changing schools' organizational, cultural or instructional systems that influence children's relationships), or implicitly (e.g., by altering behavioral norms designed to influence children's social affiliations and interactions). Yet, in outcome analyses of these programs, the rich and complicated set of peer network dynamics is often reduced to an aggregation of individual characteristics or assessed with methods that do not account for the interdependencies of network data. In this paper, we present concepts and analytic methods from the field of social network analysis and illustrate their great value to prevention science--both as a source of tools for refining program theories and as methods that enable more sophisticated and focused tests of intervention effects. An additional goal is to inform discussions of the broader implications of social network analysis for public health efforts. PMID:21728069

  16. Complexity theory of neural networks. Final technical report, 15 Sep-14 Apr 91

    SciTech Connect

    Berman, P.; Schnitger, G.; Parberry, I.

    1991-08-09

    Significant progress has been made in laying the foundations of a complexity theory of neural networks. The fundamental complexity classes have been identified and studied. The class of problems solvable by small, shallow neural networks has been found to be the same class even if (1) probabilistic behaviour (2)Multi-valued logic, and (3)analog behaviour, are allowed (subject to certain resonable technical assumptions). Neural networks can be made provably fault-tolerant by physically separating the summation units from the thresholding units. New results have also been obtained on the complexity of approximation, communication complexity, the complexity of learning from examples and counterexamples, learning with multi-valued neurons, exponential lower bounds for restricted neural networks, and fault tolerance in distributed computation.

  17. Game Theory and Extremal Optimization for Community Detection in Complex Dynamic Networks

    PubMed Central

    Lung, Rodica Ioana; Chira, Camelia; Andreica, Anca

    2014-01-01

    The detection of evolving communities in dynamic complex networks is a challenging problem that recently received attention from the research community. Dynamics clearly add another complexity dimension to the difficult task of community detection. Methods should be able to detect changes in the network structure and produce a set of community structures corresponding to different timestamps and reflecting the evolution in time of network data. We propose a novel approach based on game theory elements and extremal optimization to address dynamic communities detection. Thus, the problem is formulated as a mathematical game in which nodes take the role of players that seek to choose a community that maximizes their profit viewed as a fitness function. Numerical results obtained for both synthetic and real-world networks illustrate the competitive performance of this game theoretical approach. PMID:24586257

  18. Using Social Network Theory to Influence the Development of State and Local Primary Prevention Capacity-Building Teams

    ERIC Educational Resources Information Center

    Cook-Craig, Patricia G.

    2010-01-01

    This article examines the role that social network theory and social network analysis has played in assessing and developing effective primary prevention networks across a southeastern state. In 2004 the state began an effort to develop a strategic plan for the primary prevention of violence working with local communities across the state. The…

  19. Indications of marine bioinvasion from network theory. An analysis of the global cargo ship network

    NASA Astrophysics Data System (ADS)

    Kölzsch, A.; Blasius, B.

    2011-12-01

    The transport of huge amounts of small aquatic organisms in the ballast tanks and at the hull of large cargo ships leads to ever increasing rates of marine bioinvasion. In this study, we apply a network theoretic approach to examine the introduction of invasive species into new ports by global shipping. This is the first stage of the invasion process where it is still possible to intervene with regulating measures. We compile a selection of widely used and newly developed network properties and apply these to analyse the structure and spread characteristics of the directed and weighted global cargo ship network (GCSN). Our results reveal that the GCSN is highly efficient, shows small world characteristics and is positive assortative, indicating that quick spread of invasive organisms between ports is likely. The GCSN shows strong community structure and contains two large communities, the Atlantic and Pacific trading groups. Ports that appear as connector hubs and are of high centralities are the Suez and Panama Canal, Singapore and Shanghai. Furthermore, from robustness analyses and the network's percolation behaviour, we evaluate differences of onboard and in-port ballast water treatment, set them into context with previous studies and advise bioinvasion management strategies.

  20. ACToR - Aggregated Computational Toxicology Resource

    SciTech Connect

    Judson, Richard Richard, Ann; Dix, David; Houck, Keith; Elloumi, Fathi; Martin, Matthew; Cathey, Tommy; Transue, Thomas R.; Spencer, Richard; Wolf, Maritja

    2008-11-15

    ACToR (Aggregated Computational Toxicology Resource) is a database and set of software applications that bring into one central location many types and sources of data on environmental chemicals. Currently, the ACToR chemical database contains information on chemical structure, in vitro bioassays and in vivo toxicology assays derived from more than 150 sources including the U.S. Environmental Protection Agency (EPA), Centers for Disease Control (CDC), U.S. Food and Drug Administration (FDA), National Institutes of Health (NIH), state agencies, corresponding government agencies in Canada, Europe and Japan, universities, the World Health Organization (WHO) and non-governmental organizations (NGOs). At the EPA National Center for Computational Toxicology, ACToR helps manage large data sets being used in a high-throughput environmental chemical screening and prioritization program called ToxCast{sup TM}.

  1. Microscopic theory of the glassy dynamics of passive and active network materials

    NASA Astrophysics Data System (ADS)

    Wang, Shenshen; Wolynes, Peter G.

    2013-03-01

    Signatures of glassy dynamics have been identified experimentally for a rich variety of materials in which molecular networks provide rigidity. Here we present a theoretical framework to study the glassy behavior of both passive and active network materials. We construct a general microscopic network model that incorporates nonlinear elasticity of individual filaments and steric constraints due to crowding. Based on constructive analogies between structural glass forming liquids and random field Ising magnets implemented using a heterogeneous self-consistent phonon method, our scheme provides a microscopic approach to determine the mismatch surface tension and the configurational entropy, which compete in determining the barrier for structural rearrangements within the random first order transition theory of escape from a local energy minimum. The influence of crosslinking on the fragility of inorganic network glass formers is recapitulated by the model. For active network materials, the mapping, which correlates the glassy characteristics to the network architecture and properties of nonequilibrium motor processes, is shown to capture several key experimental observations on the cytoskeleton of living cells: Highly connected tense networks behave as strong glass formers; intense motor action promotes reconfiguration. The fact that our model assuming a negative motor susceptibility predicts the latter suggests that on average the motorized processes in living cells do resist the imposed mechanical load. Our calculations also identify a spinodal point where simultaneously the mismatch penalty vanishes and the mechanical stability of amorphous packing disappears.

  2. Microscopic theory of the glassy dynamics of passive and active network materials.

    PubMed

    Wang, Shenshen; Wolynes, Peter G

    2013-03-28

    Signatures of glassy dynamics have been identified experimentally for a rich variety of materials in which molecular networks provide rigidity. Here we present a theoretical framework to study the glassy behavior of both passive and active network materials. We construct a general microscopic network model that incorporates nonlinear elasticity of individual filaments and steric constraints due to crowding. Based on constructive analogies between structural glass forming liquids and random field Ising magnets implemented using a heterogeneous self-consistent phonon method, our scheme provides a microscopic approach to determine the mismatch surface tension and the configurational entropy, which compete in determining the barrier for structural rearrangements within the random first order transition theory of escape from a local energy minimum. The influence of crosslinking on the fragility of inorganic network glass formers is recapitulated by the model. For active network materials, the mapping, which correlates the glassy characteristics to the network architecture and properties of nonequilibrium motor processes, is shown to capture several key experimental observations on the cytoskeleton of living cells: Highly connected tense networks behave as strong glass formers; intense motor action promotes reconfiguration. The fact that our model assuming a negative motor susceptibility predicts the latter suggests that on average the motorized processes in living cells do resist the imposed mechanical load. Our calculations also identify a spinodal point where simultaneously the mismatch penalty vanishes and the mechanical stability of amorphous packing disappears. PMID:23556772

  3. Network analysis for a network disorder: The emerging role of graph theory in the study of epilepsy.

    PubMed

    Bernhardt, Boris C; Bonilha, Leonardo; Gross, Donald W

    2015-09-01

    Recent years have witnessed a paradigm shift in the study and conceptualization of epilepsy, which is increasingly understood as a network-level disorder. An emblematic case is temporal lobe epilepsy (TLE), the most common drug-resistant epilepsy that is electroclinically defined as a focal epilepsy and pathologically associated with hippocampal sclerosis. In this review, we will summarize histopathological, electrophysiological, and neuroimaging evidence supporting the concept that the substrate of TLE is not limited to the hippocampus alone, but rather is broadly distributed across multiple brain regions and interconnecting white matter pathways. We will introduce basic concepts of graph theory, a formalism to quantify topological properties of complex systems that has recently been widely applied to study networks derived from brain imaging and electrophysiology. We will discuss converging graph theoretical evidence indicating that networks in TLE show marked shifts in their overall topology, providing insight into the neurobiology of TLE as a network-level disorder. Our review will conclude by discussing methodological challenges and future clinical applications of this powerful analytical approach. PMID:26159729

  4. Song Perception by Professional Singers and Actors: An MEG Study.

    PubMed

    Rosslau, Ken; Herholz, Sibylle C; Knief, Arne; Ortmann, Magdalene; Deuster, Dirk; Schmidt, Claus-Michael; Zehnhoff-Dinnesen, Antoinetteam; Pantev, Christo; Dobel, Christian

    2016-01-01

    The cortical correlates of speech and music perception are essentially overlapping, and the specific effects of different types of training on these networks remain unknown. We compared two groups of vocally trained professionals for music and speech, singers and actors, using recited and sung rhyme sequences from German art songs with semantic and/ or prosodic/melodic violations (i.e. violations of pitch) of the last word, in order to measure the evoked activation in a magnetoencephalographic (MEG) experiment. MEG data confirmed the existence of intertwined networks for the sung and spoken modality in an early time window after word violation. In essence for this early response, higher activity was measured after melodic/prosodic than semantic violations in predominantly right temporal areas. For singers as well as for actors, modality-specific effects were evident in predominantly left-temporal lateralized activity after semantic expectancy violations in the spoken modality, and right-dominant temporal activity in response to melodic violations in the sung modality. As an indication of a special group-dependent audiation process, higher neuronal activity for singers appeared in a late time window in right temporal and left parietal areas, both after the recited and the sung sequences. PMID:26863437

  5. Song Perception by Professional Singers and Actors: An MEG Study

    PubMed Central

    Rosslau, Ken; Herholz, Sibylle C.; Knief, Arne; Ortmann, Magdalene; Deuster, Dirk; Schmidt, Claus-Michael; Zehnhoff-Dinnesen, Antoinetteam; Pantev, Christo; Dobel, Christian

    2016-01-01

    The cortical correlates of speech and music perception are essentially overlapping, and the specific effects of different types of training on these networks remain unknown. We compared two groups of vocally trained professionals for music and speech, singers and actors, using recited and sung rhyme sequences from German art songs with semantic and/ or prosodic/melodic violations (i.e. violations of pitch) of the last word, in order to measure the evoked activation in a magnetoencephalographic (MEG) experiment. MEG data confirmed the existence of intertwined networks for the sung and spoken modality in an early time window after word violation. In essence for this early response, higher activity was measured after melodic/prosodic than semantic violations in predominantly right temporal areas. For singers as well as for actors, modality-specific effects were evident in predominantly left-temporal lateralized activity after semantic expectancy violations in the spoken modality, and right-dominant temporal activity in response to melodic violations in the sung modality. As an indication of a special group-dependent audiation process, higher neuronal activity for singers appeared in a late time window in right temporal and left parietal areas, both after the recited and the sung sequences. PMID:26863437

  6. Numerical methods for solving moment equations in kinetic theory of neuronal network dynamics

    NASA Astrophysics Data System (ADS)

    Rangan, Aaditya V.; Cai, David; Tao, Louis

    2007-02-01

    Recently developed kinetic theory and related closures for neuronal network dynamics have been demonstrated to be a powerful theoretical framework for investigating coarse-grained dynamical properties of neuronal networks. The moment equations arising from the kinetic theory are a system of (1 + 1)-dimensional nonlinear partial differential equations (PDE) on a bounded domain with nonlinear boundary conditions. The PDEs themselves are self-consistently specified by parameters which are functions of the boundary values of the solution. The moment equations can be stiff in space and time. Numerical methods are presented here for efficiently and accurately solving these moment equations. The essential ingredients in our numerical methods include: (i) the system is discretized in time with an implicit Euler method within a spectral deferred correction framework, therefore, the PDEs of the kinetic theory are reduced to a sequence, in time, of boundary value problems (BVPs) with nonlinear boundary conditions; (ii) a set of auxiliary parameters is introduced to recast the original BVP with nonlinear boundary conditions as BVPs with linear boundary conditions - with additional algebraic constraints on the auxiliary parameters; (iii) a careful combination of two Newton's iterates for the nonlinear BVP with linear boundary condition, interlaced with a Newton's iterate for solving the associated algebraic constraints is constructed to achieve quadratic convergence for obtaining the solutions with self-consistent parameters. It is shown that a simple fixed-point iteration can only achieve a linear convergence for the self-consistent parameters. The practicability and efficiency of our numerical methods for solving the moment equations of the kinetic theory are illustrated with numerical examples. It is further demonstrated that the moment equations derived from the kinetic theory of neuronal network dynamics can very well capture the coarse-grained dynamical properties of

  7. GTRF: A Game Theory Approach for Regulating Node Behavior in Real-Time Wireless Sensor Networks

    PubMed Central

    Lin, Chi; Wu, Guowei; Pirozmand, Poria

    2015-01-01

    The selfish behaviors of nodes (or selfish nodes) cause packet loss, network congestion or even void regions in real-time wireless sensor networks, which greatly decrease the network performance. Previous methods have focused on detecting selfish nodes or avoiding selfish behavior, but little attention has been paid to regulating selfish behavior. In this paper, a Game Theory-based Real-time & Fault-tolerant (GTRF) routing protocol is proposed. GTRF is composed of two stages. In the first stage, a game theory model named VA is developed to regulate nodes’ behaviors and meanwhile balance energy cost. In the second stage, a jumping transmission method is adopted, which ensures that real-time packets can be successfully delivered to the sink before a specific deadline. We prove that GTRF theoretically meets real-time requirements with low energy cost. Finally, extensive simulations are conducted to demonstrate the performance of our scheme. Simulation results show that GTRF not only balances the energy cost of the network, but also prolongs network lifetime. PMID:26053745

  8. GTRF: a game theory approach for regulating node behavior in real-time wireless sensor networks.

    PubMed

    Lin, Chi; Wu, Guowei; Pirozmand, Poria

    2015-01-01

    The selfish behaviors of nodes (or selfish nodes) cause packet loss, network congestion or even void regions in real-time wireless sensor networks, which greatly decrease the network performance. Previous methods have focused on detecting selfish nodes or avoiding selfish behavior, but little attention has been paid to regulating selfish behavior. In this paper, a Game Theory-based Real-time & Fault-tolerant (GTRF) routing protocol is proposed. GTRF is composed of two stages. In the first stage, a game theory model named VA is developed to regulate nodes' behaviors and meanwhile balance energy cost. In the second stage, a jumping transmission method is adopted, which ensures that real-time packets can be successfully delivered to the sink before a specific deadline. We prove that GTRF theoretically meets real-time requirements with low energy cost. Finally, extensive simulations are conducted to demonstrate the performance of our scheme. Simulation results show that GTRF not only balances the energy cost of the network, but also prolongs network lifetime. PMID:26053745

  9. Optimization of flow modeling in fractured media with discrete fracture network via percolation theory

    NASA Astrophysics Data System (ADS)

    Donado-Garzon, L. D.; Pardo, Y.

    2013-12-01

    Fractured media are very heterogeneous systems where occur complex physical and chemical processes to model. One of the possible approaches to conceptualize this type of massifs is the Discrete Fracture Network (DFN). Donado et al., modeled flow and transport in a granitic batholith based on this approach and found good fitting with hydraulic and tracer tests, but the computational cost was excessive due to a gigantic amount of elements to model. We present in this work a methodology based on percolation theory for reducing the number of elements and in consequence, to reduce the bandwidth of the conductance matrix and the execution time of each network. DFN poses as an excellent representation of all the set of fractures of the media, but not all the fractures of the media are part of the conductive network. Percolation theory is used to identify which nodes or fractures are not conductive, based on the occupation probability or percolation threshold. In a fractured system, connectivity determines the flow pattern in the fractured rock mass. This volume of fluid is driven through connection paths formed by the fractures, when the permeability of the rock is negligible compared to the fractures. In a population of distributed fractures, each of this that has no intersection with any connected fracture do not contribute to generate a flow field. This algorithm also permits us to erase these elements however they are water conducting and hence, refine even more the backbone of the network. We used 100 different generations of DFN that were optimized in this study using percolation theory. In each of the networks calibrate hydrodynamic parameters as hydraulic conductivity and specific storage coefficient, for each of the five families of fractures, yielding a total of 10 parameters to estimate, at each generation. Since the effects of the distribution of fault orientation changes the value of the percolation threshold, but not the universal laws of classical

  10. Maximum-entropy closures for kinetic theories of neuronal network dynamics.

    PubMed

    Rangan, Aaditya V; Cai, David

    2006-05-01

    We analyze (1 + 1)D kinetic equations for neuronal network dynamics, which are derived via an intuitive closure from a Boltzmann-like equation governing the evolution of a one-particle (i.e., one-neuron) probability density function. We demonstrate that this intuitive closure is a generalization of moment closures based on the maximum-entropy principle. By invoking maximum-entropy closures, we show how to systematically extend this kinetic theory to obtain higher-order, kinetic equations and to include coupled networks of both excitatory and inhibitory neurons. PMID:16712338

  11. The Construction of Higher Education Entrepreneur Services Network System a Research Based on Ecological Systems Theory

    NASA Astrophysics Data System (ADS)

    Xue, Jingxin

    The article aims to completely, systematically and objectively analyze the current situation of Entrepreneurship Education in China with Ecological Systems Theory. From this perspective, the author discusses the structure, function and its basic features of higher education entrepreneur services network system, and puts forward the opinion that every entrepreneurship organization in higher education institution does not limited to only one platform. Different functional supporting platforms should be combined closed through composite functional organization to form an integrated network system, in which each unit would impels others' development.

  12. Writing Programs as Distributed Networks: A Materialist Approach to University-Community Digital Media Literacy

    ERIC Educational Resources Information Center

    Comstock, Michelle

    2006-01-01

    This article addresses how community-university digital media literacy projects are redefining literacy, literate practices, and institutions. Using Actor-Network Theory (ANT), which emphasizes the organizing process itself, I analyze the shifting definitions of literacy within one particular university-community collaboration. My analysis…

  13. Virtual Learning Environments as Sociomaterial Agents in the Network of Teaching Practice

    ERIC Educational Resources Information Center

    Johannesen, Monica; Erstad, Ola; Habib, Laurence

    2012-01-01

    This article presents findings related to the sociomaterial agency of educators and their practice in Norwegian education. Using actor-network theory, we ask how Virtual Learning Environments (VLEs) negotiate the agency of educators and how they shape their teaching practice. Since the same kinds of VLE tools have been widely implemented…

  14. Contextualized Network Analysis: Theory and Methods for Networks with Node Covariates

    NASA Astrophysics Data System (ADS)

    Binkiewicz, Norbert M.

    Biological and social systems consist of myriad interacting units. The interactions can be intuitively represented in the form of a graph or network. Measurements of these graphs can reveal the underlying structure of these interactions, which provides insight into the systems that generated the graphs. Moreover, in applications such as neuroconnectomics, social networks, and genomics, graph data is accompanied by contextualizing measures on each node. We leverage these node covariates to help uncover latent communities, using a modification of spectral clustering. Statistical guarantees are provided under a joint mixture model called the node contextualized stochastic blockmodel, including a bound on the mis-clustering rate. For most simulated conditions, covariate assisted spectral clustering yields superior results relative to both regularized spectral clustering without node covariates and an adaptation of canonical correlation analysis. We apply covariate assisted spectral clustering to large brain graphs derived from diffusion MRI, using the node locations or neurological regions as covariates. In both cases, covariate assisted spectral clustering yields clusters that are easier to interpret neurologically. A low rank update algorithm is developed to reduce the computational cost of determining the tuning parameter for covariate assisted spectral clustering. As simulations demonstrate, the low rank update algorithm increases the speed of covariate assisted spectral clustering up to ten-fold, while practically matching the clustering performance of the standard algorithm. Graphs with node attributes are sometimes accompanied by ground truth labels that align closely with the latent communities in the graph. We consider the example of a mouse retina neuron network accompanied by the neuron spatial location and neuronal cell types. In this example, the neuronal cell type is considered a ground truth label. Current approaches for defining neuronal cell type vary

  15. Reinforcement learning using a continuous time actor-critic framework with spiking neurons.

    PubMed

    Frémaux, Nicolas; Sprekeler, Henning; Gerstner, Wulfram

    2013-04-01

    Animals repeat rewarded behaviors, but the physiological basis of reward-based learning has only been partially elucidated. On one hand, experimental evidence shows that the neuromodulator dopamine carries information about rewards and affects synaptic plasticity. On the other hand, the theory of reinforcement learning provides a framework for reward-based learning. Recent models of reward-modulated spike-timing-dependent plasticity have made first steps towards bridging the gap between the two approaches, but faced two problems. First, reinforcement learning is typically formulated in a discrete framework, ill-adapted to the description of natural situations. Second, biologically plausible models of reward-modulated spike-timing-dependent plasticity require precise calculation of the reward prediction error, yet it remains to be shown how this can be computed by neurons. Here we propose a solution to these problems by extending the continuous temporal difference (TD) learning of Doya (2000) to the case of spiking neurons in an actor-critic network operating in continuous time, and with continuous state and action representations. In our model, the critic learns to predict expected future rewards in real time. Its activity, together with actual rewards, conditions the delivery of a neuromodulatory TD signal to itself and to the actor, which is responsible for action choice. In simulations, we show that such an architecture can solve a Morris water-maze-like navigation task, in a number of trials consistent with reported animal performance. We also use our model to solve the acrobot and the cartpole problems, two complex motor control tasks. Our model provides a plausible way of computing reward prediction error in the brain. Moreover, the analytically derived learning rule is consistent with experimental evidence for dopamine-modulated spike-timing-dependent plasticity. PMID:23592970

  16. Reinforcement Learning Using a Continuous Time Actor-Critic Framework with Spiking Neurons

    PubMed Central

    Frémaux, Nicolas; Sprekeler, Henning; Gerstner, Wulfram

    2013-01-01

    Animals repeat rewarded behaviors, but the physiological basis of reward-based learning has only been partially elucidated. On one hand, experimental evidence shows that the neuromodulator dopamine carries information about rewards and affects synaptic plasticity. On the other hand, the theory of reinforcement learning provides a framework for reward-based learning. Recent models of reward-modulated spike-timing-dependent plasticity have made first steps towards bridging the gap between the two approaches, but faced two problems. First, reinforcement learning is typically formulated in a discrete framework, ill-adapted to the description of natural situations. Second, biologically plausible models of reward-modulated spike-timing-dependent plasticity require precise calculation of the reward prediction error, yet it remains to be shown how this can be computed by neurons. Here we propose a solution to these problems by extending the continuous temporal difference (TD) learning of Doya (2000) to the case of spiking neurons in an actor-critic network operating in continuous time, and with continuous state and action representations. In our model, the critic learns to predict expected future rewards in real time. Its activity, together with actual rewards, conditions the delivery of a neuromodulatory TD signal to itself and to the actor, which is responsible for action choice. In simulations, we show that such an architecture can solve a Morris water-maze-like navigation task, in a number of trials consistent with reported animal performance. We also use our model to solve the acrobot and the cartpole problems, two complex motor control tasks. Our model provides a plausible way of computing reward prediction error in the brain. Moreover, the analytically derived learning rule is consistent with experimental evidence for dopamine-modulated spike-timing-dependent plasticity. PMID:23592970

  17. A quantitative theory of the functions of the hippocampal CA3 network in memory

    PubMed Central

    Rolls, Edmund T.

    2013-01-01

    A quantitative computational theory of the operation of the hippocampal CA3 system as an autoassociation or attractor network used in episodic memory system is described. In this theory, the CA3 system operates as a single attractor or autoassociation network to enable rapid, one-trial, associations between any spatial location (place in rodents, or spatial view in primates) and an object or reward, and to provide for completion of the whole memory during recall from any part. The theory is extended to associations between time and object or reward to implement temporal order memory, also important in episodic memory. The dentate gyrus (DG) performs pattern separation by competitive learning to produce sparse representations suitable for setting up new representations in CA3 during learning, producing for example neurons with place-like fields from entorhinal cortex grid cells. The dentate granule cells produce by the very small number of mossy fiber (MF) connections to CA3 a randomizing pattern separation effect important during learning but not recall that separates out the patterns represented by CA3 firing to be very different from each other, which is optimal for an unstructured episodic memory system in which each memory must be kept distinct from other memories. The direct perforant path (pp) input to CA3 is quantitatively appropriate to provide the cue for recall in CA3, but not for learning. Tests of the theory including hippocampal subregion analyses and hippocampal NMDA receptor knockouts are described, and support the theory. PMID:23805074

  18. A quantitative theory of the functions of the hippocampal CA3 network in memory.

    PubMed

    Rolls, Edmund T

    2013-01-01

    A quantitative computational theory of the operation of the hippocampal CA3 system as an autoassociation or attractor network used in episodic memory system is described. In this theory, the CA3 system operates as a single attractor or autoassociation network to enable rapid, one-trial, associations between any spatial location (place in rodents, or spatial view in primates) and an object or reward, and to provide for completion of the whole memory during recall from any part. The theory is extended to associations between time and object or reward to implement temporal order memory, also important in episodic memory. The dentate gyrus (DG) performs pattern separation by competitive learning to produce sparse representations suitable for setting up new representations in CA3 during learning, producing for example neurons with place-like fields from entorhinal cortex grid cells. The dentate granule cells produce by the very small number of mossy fiber (MF) connections to CA3 a randomizing pattern separation effect important during learning but not recall that separates out the patterns represented by CA3 firing to be very different from each other, which is optimal for an unstructured episodic memory system in which each memory must be kept distinct from other memories. The direct perforant path (pp) input to CA3 is quantitatively appropriate to provide the cue for recall in CA3, but not for learning. Tests of the theory including hippocampal subregion analyses and hippocampal NMDA receptor knockouts are described, and support the theory. PMID:23805074

  19. Risk Assessment of Communication Network of Power Company Based on Rough Set Theory and Multiclass SVM

    NASA Astrophysics Data System (ADS)

    He, Xi; Wang, Wei; Liu, Xinyu; Ji, Yong

    This paper proposes a new risk assessment method based on the attribute reduction theory of rough set and multiclass SVM classification. Rough set theory is introduced for data attribute reduction and multiclass SVM is used for automatic assessment of risk levels. Redundant features of data are deleted that can reduce the computation complexity of multiclass SVM and improve the learning and the generalization ability. Multiclass SVM trained with the empirical data can predict the risk level. Experiment shows that the predict result has relatively high precision, and the method is validity for power network risk assessment.

  20. False recollection of the role played by an actor in an event.

    PubMed

    Kersten, Alan W; Earles, Julie L; Upshaw, Christin

    2013-11-01

    Two experiments demonstrated that eyewitnesses more frequently associate an actor with the actions of another person when those two people had appeared together in the same event, rather than in different events. This greater likelihood of binding an actor with the actions of another person from the same event was associated with high-confidence recognition judgments and "remember" responses in a remember-know task, suggesting that viewing an actor together with the actions of another person led participants to falsely recollect having seen that actor perform those actions. An analysis of age differences provided evidence that familiarity also contributed to false recognition independently of a false-recollection mechanism. In particular, older adults were more likely than young adults to falsely recognize a novel conjunction of a familiar actor and action, regardless of whether that actor and action were from the same or from different events. Older adults' elevated rate of false recognition was associated with intermediate confidence levels, suggesting that it stemmed from increased reliance on familiarity rather than from false recollection. The implications of these results are discussed for theories of conjunction errors in memory and of unconscious transference in eyewitness testimony. PMID:23722927

  1. False recollection of the role played by an actor in an event

    PubMed Central

    Earles, Julie L.; Upshaw, Christin

    2013-01-01

    Two experiments demonstrated that eyewitnesses more frequently associate an actor with the actions of another person when those two people had appeared together in the same event, rather than in different events. This greater likelihood of binding an actor with the actions of another person from the same event was associated with high-confidence recognition judgments and “remember” responses in a remember–know task, suggesting that viewing an actor together with the actions of another person led participants to falsely recollect having seen that actor perform those actions. An analysis of age differences provided evidence that familiarity also contributed to false recognition independently of a false-recollection mechanism. In particular, older adults were more likely than young adults to falsely recognize a novel conjunction of a familiar actor and action, regardless of whether that actor and action were from the same or from different events. Older adults’ elevated rate of false recognition was associated with intermediate confidence levels, suggesting that it stemmed from increased reliance on familiarity rather than from false recollection. The implications of these results are discussed for theories of conjunction errors in memory and of unconscious transference in eyewitness testimony. PMID:23722927

  2. Altered Brain Network in Amyotrophic Lateral Sclerosis: A Resting Graph Theory-Based Network Study at Voxel-Wise Level.

    PubMed

    Zhou, Chaoyang; Hu, Xiaofei; Hu, Jun; Liang, Minglong; Yin, Xuntao; Chen, Lin; Zhang, Jiuquan; Wang, Jian

    2016-01-01

    Amyotrophic lateral sclerosis (ALS) is a rare degenerative disorder characterized by loss of upper and lower motor neurons. Neuroimaging has provided noticeable evidence that ALS is a complex disease, and shown that anatomical and functional lesions extend beyond precentral cortices and corticospinal tracts, to include the corpus callosum; frontal, sensory, and premotor cortices; thalamus; and midbrain. The aim of this study is to investigate graph theory-based functional network abnormalities at voxel-wise level in ALS patients on a whole brain scale. Forty-three ALS patients and 44 age- and sex-matched healthy volunteers were enrolled. The voxel-wise network degree centrality (DC), a commonly employed graph-based measure of network organization, was used to characterize the alteration of whole brain functional network. Compared with the controls, the ALS patients showed significant increase of DC in the left cerebellum posterior lobes, bilateral cerebellum crus, bilateral occipital poles, right orbital frontal lobe, and bilateral prefrontal lobes; significant decrease of DC in the bilateral primary motor cortex, bilateral sensory motor region, right prefrontal lobe, left bilateral precuneus, bilateral lateral temporal lobes, left cingulate cortex, and bilateral visual processing cortex. The DC's z-scores of right inferior occipital gyrus were significant negative correlated with the ALSFRS-r scores. Our findings confirm that the regions with abnormal network DC in ALS patients were located in multiple brain regions including primary motor, somatosensory and extra-motor areas, supporting the concept that ALS is a multisystem disorder. Specifically, our study found that DC in the visual areas was altered and ALS patients with higher DC in right inferior occipital gyrus have more severity of disease. The result demonstrated that the altered DC value in this region can probably be used to assess severity of ALS. PMID:27242409

  3. Altered Brain Network in Amyotrophic Lateral Sclerosis: A Resting Graph Theory-Based Network Study at Voxel-Wise Level

    PubMed Central

    Zhou, Chaoyang; Hu, Xiaofei; Hu, Jun; Liang, Minglong; Yin, Xuntao; Chen, Lin; Zhang, Jiuquan; Wang, Jian

    2016-01-01

    Amyotrophic lateral sclerosis (ALS) is a rare degenerative disorder characterized by loss of upper and lower motor neurons. Neuroimaging has provided noticeable evidence that ALS is a complex disease, and shown that anatomical and functional lesions extend beyond precentral cortices and corticospinal tracts, to include the corpus callosum; frontal, sensory, and premotor cortices; thalamus; and midbrain. The aim of this study is to investigate graph theory-based functional network abnormalities at voxel-wise level in ALS patients on a whole brain scale. Forty-three ALS patients and 44 age- and sex-matched healthy volunteers were enrolled. The voxel-wise network degree centrality (DC), a commonly employed graph-based measure of network organization, was used to characterize the alteration of whole brain functional network. Compared with the controls, the ALS patients showed significant increase of DC in the left cerebellum posterior lobes, bilateral cerebellum crus, bilateral occipital poles, right orbital frontal lobe, and bilateral prefrontal lobes; significant decrease of DC in the bilateral primary motor cortex, bilateral sensory motor region, right prefrontal lobe, left bilateral precuneus, bilateral lateral temporal lobes, left cingulate cortex, and bilateral visual processing cortex. The DC's z-scores of right inferior occipital gyrus were significant negative correlated with the ALSFRS-r scores. Our findings confirm that the regions with abnormal network DC in ALS patients were located in multiple brain regions including primary motor, somatosensory and extra-motor areas, supporting the concept that ALS is a multisystem disorder. Specifically, our study found that DC in the visual areas was altered and ALS patients with higher DC in right inferior occipital gyrus have more severity of disease. The result demonstrated that the altered DC value in this region can probably be used to assess severity of ALS. PMID:27242409

  4. Analysis of Online Social Networks to Understand Information Sharing Behaviors Through Social Cognitive Theory

    SciTech Connect

    Yoon, Hong-Jun; Tourassi, Georgia

    2014-01-01

    Analyzing the contents of online social networks is an effective process for monitoring and understanding peoples behaviors. Since the nature of conversation and information propagation is similar to traditional conversation and learning, one of the popular socio-cognitive methods, social cognitive theory was applied to online social networks to. Two major news topics about colon cancer were chosen to monitor traffic of Twitter messages. The activity of leaders on the issue (i.e., news companies or people will prior Twitter activity on topics related to colon cancer) was monitored. In addition, the activity of followers , people who never discussed the topics before, but replied to the discussions was also monitored. Topics that produce tangible benefits such as positive outcomes from appropriate preventive actions received dramatically more attention and online social media traffic. Such characteristics can be explained with social cognitive theory and thus present opportunities for effective health campaigns.

  5. Policy Actors: Doing Policy Work in Schools

    ERIC Educational Resources Information Center

    Ball, Stephen J.; Maguire, Meg; Braun, Annette; Hoskins, Kate

    2011-01-01

    This paper considers the "policy work" of teacher actors in schools. It focuses on the "problem of meaning" and offers a typology of roles and positions through which teachers engage with policy and with which policies get "enacted". It argues that "policy work" is made up of a set of complex and differentiated activities which involve both…

  6. Public Policies and Strategies of Actors

    ERIC Educational Resources Information Center

    Loiret, Pierre-Jean

    2011-01-01

    The synthesis "Public Policies and Strategies of Actors" concerns the same theme as Part 4 of the "Handbook of Distance Education" (Moore 2007), which deals with policies, administration, and management. Eleven articles illustrate the theme. Three articles are studies about the experience in France between 2000 and 2003 of the digital campuses.…

  7. [Reliability theory based on quality risk network analysis for Chinese medicine injection].

    PubMed

    Li, Zheng; Kang, Li-Yuan; Fan, Xiao-Hui

    2014-08-01

    A new risk analysis method based upon reliability theory was introduced in this paper for the quality risk management of Chinese medicine injection manufacturing plants. The risk events including both cause and effect ones were derived in the framework as nodes with a Bayesian network analysis approach. It thus transforms the risk analysis results from failure mode and effect analysis (FMEA) into a Bayesian network platform. With its structure and parameters determined, the network can be used to evaluate the system reliability quantitatively with probabilistic analytical appraoches. Using network analysis tools such as GeNie and AgenaRisk, we are able to find the nodes that are most critical to influence the system reliability. The importance of each node to the system can be quantitatively evaluated by calculating the effect of the node on the overall risk, and minimization plan can be determined accordingly to reduce their influences and improve the system reliability. Using the Shengmai injection manufacturing plant of SZYY Ltd as a user case, we analyzed the quality risk with both static FMEA analysis and dynamic Bayesian Network analysis. The potential risk factors for the quality of Shengmai injection manufacturing were identified with the network analysis platform. Quality assurance actions were further defined to reduce the risk and improve the product quality. PMID:25509315

  8. Mean field theory for biology inspired duplication-divergence network model.

    PubMed

    Cai, Shuiming; Liu, Zengrong; Lee, H C

    2015-08-01

    The duplication-divergence network model is generally thought to incorporate key ingredients underlying the growth and evolution of protein-protein interaction networks. Properties of the model have been elucidated through numerous simulation studies. However, a comprehensive theoretical study of the model is lacking. Here, we derived analytic expressions for quantities describing key characteristics of the network-the average degree, the degree distribution, the clustering coefficient, and the neighbor connectivity-in the mean-field, large-N limit of an extended version of the model, duplication-divergence complemented with heterodimerization and addition. We carried out extensive simulations and verified excellent agreement between simulation and theory except for one partial case. All four quantities obeyed power-laws even at moderate network size ( N∼10(4)), except the degree distribution, which had an additional exponential factor observed to obey power-law. It is shown that our network model can lead to the emergence of scale-free property and hierarchical modularity simultaneously, reproducing the important topological properties of real protein-protein interaction networks. PMID:26328557

  9. Efficiency of a seismic network from the viewpoint of mathematical information theory: application to the Andalucia (Spain) seismic network

    NASA Astrophysics Data System (ADS)

    Lana, X.; Martínez, M. D.; Miguel, F. De

    1990-05-01

    Concepts of information theory applied to data from the Andalucia (Spain) seismic network permit the discussion of whether data are correctly used in determining epicentres. The elementary definition of Shannon's information allows a discussion of the coverage of the epicentres in terms of azimuths and distances to the seismic stations. The contributions of all the stations of the network to the coverage is also investigated. Data were obtained from 13 seismic stations and 765 epicentral determinations corresponding to the seismic activity of the years 1983-84 and some months of 1985 in the Central Belies area (Southern Spain). Information theory concepts were applied to the data after a distribution of epicentres according to their mo values and hypocentral depths. The obtained results show a better treatment of very shallow earthquakes, especially of those with values of mb less than or equal to 2.5. No significant different coverages were obtained for the sets of earthquakes classified according to their hypocentral depths and mb values.

  10. Theory of electromagnetic transmission structures. I - Relativistic foundation and network formalisms

    NASA Technical Reports Server (NTRS)

    Gabriel, G. J.

    1980-01-01

    A new theorem on a class of four-dimensional skew-symmetric tensors is demonstrated. Coupled with the relativistic covariant form of Maxwell's equations, this theorem consolidates the classifications of guided waves by combining the three types - TE, TM, TEM - under a uniform condition applied to the generating four-potential which is Lorentz invariant. Each type corresponds to a potential of which a pair of the four components vanishes in a particular frame. Through appropriate normalization conditions, the resulting time-domain equations for the field amplitudes are readily reduced to modified telegraphist equations, which in turn lead to distributed network representations for each of the three types. The ambiguity of distributed network formalisms in general is elucidated and the concept of network parameter densities such as traditionally employed in TEM transmission line theory is questioned.

  11. Biogeography revisited with network theory: retracing the history of hydrothermal vent communities.

    PubMed

    Moalic, Yann; Desbruyères, Daniel; Duarte, Carlos M; Rozenfeld, Alejandro F; Bachraty, Charleyne; Arnaud-Haond, Sophie

    2012-01-01

    Defining biogeographic provinces to understand the history and evolution of communities associated with a given kind of ecosystem is challenging and usually requires a priori assumptions to be made. We applied network theory, a holistic and exploratory method, to the most complete database of faunal distribution available on oceanic hydrothermal vents, environments which support fragmented and unstable ecosystems, to infer the processes driving their worldwide biogeography. Besides the identification of robust provinces, the network topology allowed us to identify preferential pathways that had hitherto been overlooked. These pathways are consistent with the previously proposed hypothesis of a role of plate tectonics in the biogeographical history of hydrothermal vent communities. A possible ancestral position of the Western Pacific is also suggested for the first time. Finally, this work provides an innovative example of the potential of network tools to unravel the biogeographic history of faunal assemblages and to supply comprehensive information for the conservation and management of biodiversity. PMID:21856628

  12. Dissolved oxygen prediction using a possibility-theory based fuzzy neural network

    NASA Astrophysics Data System (ADS)

    Khan, U. T.; Valeo, C.

    2015-11-01

    A new fuzzy neural network method to predict minimum dissolved oxygen (DO) concentration in a highly urbanised riverine environment (in Calgary, Canada) is proposed. The method uses abiotic (non-living, physical and chemical attributes) as inputs to the model, since the physical mechanisms governing DO in the river are largely unknown. A new two-step method to construct fuzzy numbers using observations is proposed. Then an existing fuzzy neural network is modified to account for fuzzy number inputs and also uses possibility-theory based intervals to train the network. Results demonstrate that the method is particularly well suited to predict low DO events in the Bow River. Model output and a defuzzification technique is used to estimate the risk of low DO so that water resource managers can implement strategies to prevent the occurrence of low DO.

  13. The Elastic Behaviour of Sintered Metallic Fibre Networks: A Finite Element Study by Beam Theory

    PubMed Central

    Bosbach, Wolfram A.

    2015-01-01

    Background The finite element method has complimented research in the field of network mechanics in the past years in numerous studies about various materials. Numerical predictions and the planning efficiency of experimental procedures are two of the motivational aspects for these numerical studies. The widespread availability of high performance computing facilities has been the enabler for the simulation of sufficiently large systems. Objectives and Motivation In the present study, finite element models were built for sintered, metallic fibre networks and validated by previously published experimental stiffness measurements. The validated models were the basis for predictions about so far unknown properties. Materials and Methods The finite element models were built by transferring previously published skeletons of fibre networks into finite element models. Beam theory was applied as simplification method. Results and Conclusions The obtained material stiffness isn’t a constant but rather a function of variables such as sample size and boundary conditions. Beam theory offers an efficient finite element method for the simulated fibre networks. The experimental results can be approximated by the simulated systems. Two worthwhile aspects for future work will be the influence of size and shape and the mechanical interaction with matrix materials. PMID:26569603

  14. Analytical theory of polymer-network-mediated interaction between colloidal particles

    PubMed Central

    Di Michele, Lorenzo; Zaccone, Alessio; Eiser, Erika

    2012-01-01

    Nanostructured materials based on colloidal particles embedded in a polymer network are used in a variety of applications ranging from nanocomposite rubbers to organic-inorganic hybrid solar cells. Further, polymer-network-mediated colloidal interactions are highly relevant to biological studies whereby polymer hydrogels are commonly employed to probe the mechanical response of living cells, which can determine their biological function in physiological environments. The performance of nanomaterials crucially relies upon the spatial organization of the colloidal particles within the polymer network that depends, in turn, on the effective interactions between the particles in the medium. Existing models based on nonlocal equilibrium thermodynamics fail to clarify the nature of these interactions, precluding the way toward the rational design of polymer-composite materials. In this article, we present a predictive analytical theory of these interactions based on a coarse-grained model for polymer networks. We apply the theory to the case of colloids partially embedded in cross-linked polymer substrates and clarify the origin of attractive interactions recently observed experimentally. Monte Carlo simulation results that quantitatively confirm the theoretical predictions are also presented. PMID:22679289

  15. Visibility graph analysis on quarterly macroeconomic series of China based on complex network theory

    NASA Astrophysics Data System (ADS)

    Wang, Na; Li, Dong; Wang, Qiwen

    2012-12-01

    The visibility graph approach and complex network theory provide a new insight into time series analysis. The inheritance of the visibility graph from the original time series was further explored in the paper. We found that degree distributions of visibility graphs extracted from Pseudo Brownian Motion series obtained by the Frequency Domain algorithm exhibit exponential behaviors, in which the exponential exponent is a binomial function of the Hurst index inherited in the time series. Our simulations presented that the quantitative relations between the Hurst indexes and the exponents of degree distribution function are different for different series and the visibility graph inherits some important features of the original time series. Further, we convert some quarterly macroeconomic series including the growth rates of value-added of three industry series and the growth rates of Gross Domestic Product series of China to graphs by the visibility algorithm and explore the topological properties of graphs associated from the four macroeconomic series, namely, the degree distribution and correlations, the clustering coefficient, the average path length, and community structure. Based on complex network analysis we find degree distributions of associated networks from the growth rates of value-added of three industry series are almost exponential and the degree distributions of associated networks from the growth rates of GDP series are scale free. We also discussed the assortativity and disassortativity of the four associated networks as they are related to the evolutionary process of the original macroeconomic series. All the constructed networks have “small-world” features. The community structures of associated networks suggest dynamic changes of the original macroeconomic series. We also detected the relationship among government policy changes, community structures of associated networks and macroeconomic dynamics. We find great influences of government

  16. Theory of light-induced deformation of azobenzene elastomers: Influence of network structure

    NASA Astrophysics Data System (ADS)

    Toshchevikov, V. P.; Saphiannikova, M.; Heinrich, G.

    2012-07-01

    Azobenzene elastomers have been extensively explored in the last decade as photo-deformable smart materials which are able to transform light energy into mechanical stress. Presently, there is a great need for theoretical approaches to accurately predict the quantitative response of these materials based on their microscopic structure. Recently, we proposed a theory of light-induced deformation of azobenzene elastomers using a simple regular cubic network model [V. Toshchevikov, M. Saphiannikova, and G. Heinrich, J. Phys. Chem. B 116, 913 (2012), 10.1021/jp206323h]. In the present study, we extend the previous theory using more realistic network models which take into account the random orientation of end-to-end vectors of network strands as well as the molecular weight distribution of the strands. Interaction of the chromophores with the linearly polarized light is described by an effective orientation potential which orients the chromophores perpendicular to the polarization direction. We show that both monodisperse and polydisperse azobenzene elastomers can demonstrate either a uniaxial expansion or contraction along the polarization direction. The sign of deformation (expansion/contraction) depends on the orientation distribution of chromophores with respect to the main chains which is defined by the chemical structure and by the lengths of spacers. The degree of cross-linking and the polydispersity of network strands do not affect the sign of deformation but influence the magnitude of light-induced deformation. We demonstrate that photo-mechanical properties of mono- and poly-disperse azobenzene elastomers with random spatial distribution of network strands can be described in a very good approximation by a regular cubic network model with an appropriately chosen length of the strands.

  17. Mean field theory for biology inspired duplication-divergence network model

    NASA Astrophysics Data System (ADS)

    Cai, Shuiming; Liu, Zengrong; Lee, H. C.

    2015-08-01

    The duplication-divergence network model is generally thought to incorporate key ingredients underlying the growth and evolution of protein-protein interaction networks. Properties of the model have been elucidated through numerous simulation studies. However, a comprehensive theoretical study of the model is lacking. Here, we derived analytic expressions for quantities describing key characteristics of the network—the average degree, the degree distribution, the clustering coefficient, and the neighbor connectivity—in the mean-field, large-N limit of an extended version of the model, duplication-divergence complemented with heterodimerization and addition. We carried out extensive simulations and verified excellent agreement between simulation and theory except for one partial case. All four quantities obeyed power-laws even at moderate network size ( N ˜104 ), except the degree distribution, which had an additional exponential factor observed to obey power-law. It is shown that our network model can lead to the emergence of scale-free property and hierarchical modularity simultaneously, reproducing the important topological properties of real protein-protein interaction networks.

  18. Learning Science in a Virtual Reality Application: The Impacts of Animated-Virtual Actors' Visual Complexity

    ERIC Educational Resources Information Center

    Kartiko, Iwan; Kavakli, Manolya; Cheng, Ken

    2010-01-01

    As the technology in computer graphics advances, Animated-Virtual Actors (AVAs) in Virtual Reality (VR) applications become increasingly rich and complex. Cognitive Theory of Multimedia Learning (CTML) suggests that complex visual materials could hinder novice learners from attending to the lesson properly. On the other hand, previous studies have…

  19. Reading Theatre, Parents as Actors: Movie Production in a Family Literacy Workshop

    ERIC Educational Resources Information Center

    Huang, Grace; Dolejs, Barbara

    2007-01-01

    The goal of the family literacy workshop "Reading Theatre, Parents as Actors: Movie production in a Family Literacy Workshop" is to empower and motivate parents to learn various storytelling strategies through theatrical production experiences and apply them at home. This is a theory-based family literacy practice supported by McClelland's…

  20. Temporal Effects of Performance on Causal Attributions in Actors and Observers.

    ERIC Educational Resources Information Center

    Bryant, Fred B.

    Although understanding how causal attributions for performance develop is important to attribution theory, little research has been done on this topic. To explore changes in attributions during task performance for both actors and observers, 90 female undergraduates participated in a procedure in which they received either 80 percent or 20 percent…

  1. Comparing Brain Networks of Different Size and Connectivity Density Using Graph Theory

    PubMed Central

    van Wijk, Bernadette C. M.; Stam, Cornelis J.; Daffertshofer, Andreas

    2010-01-01

    Graph theory is a valuable framework to study the organization of functional and anatomical connections in the brain. Its use for comparing network topologies, however, is not without difficulties. Graph measures may be influenced by the number of nodes (N) and the average degree (k) of the network. The explicit form of that influence depends on the type of network topology, which is usually unknown for experimental data. Direct comparisons of graph measures between empirical networks with different N and/or k can therefore yield spurious results. We list benefits and pitfalls of various approaches that intend to overcome these difficulties. We discuss the initial graph definition of unweighted graphs via fixed thresholds, average degrees or edge densities, and the use of weighted graphs. For instance, choosing a threshold to fix N and k does eliminate size and density effects but may lead to modifications of the network by enforcing (ignoring) non-significant (significant) connections. Opposed to fixing N and k, graph measures are often normalized via random surrogates but, in fact, this may even increase the sensitivity to differences in N and k for the commonly used clustering coefficient and small-world index. To avoid such a bias we tried to estimate the N,k-dependence for empirical networks, which can serve to correct for size effects, if successful. We also add a number of methods used in social sciences that build on statistics of local network structures including exponential random graph models and motif counting. We show that none of the here-investigated methods allows for a reliable and fully unbiased comparison, but some perform better than others. PMID:21060892

  2. Exploring empowerment in settings: mapping distributions of network power.

    PubMed

    Neal, Jennifer Watling

    2014-06-01

    This paper brings together two trends in the empowerment literature-understanding empowerment in settings and understanding empowerment as relational-by examining what makes settings empowering from a social network perspective. Specifically, extending Neal and Neal's (Am J Community Psychol 48(3/4):157-167, 2011) conception of network power, an empowering setting is defined as one in which (1) actors have existing relationships that allow for the exchange of resources and (2) the distribution of network power among actors in the setting is roughly equal. The paper includes a description of how researchers can examine distributions of network power in settings. Next, this process is illustrated in both an abstract example and using empirical data on early adolescents' peer relationships in urban classrooms. Finally, implications for theory, methods, and intervention related to understanding empowering settings are explored. PMID:24213301

  3. Sculpting the Immunological Response against Viral Disease: Statistical Mechanics and Network Theory

    NASA Astrophysics Data System (ADS)

    Zhou, Hao; Deem, Michael

    2007-03-01

    The twin challenges of immunodominance and heterologous immunity have hampered discovery of an effective vaccine against all four dengue viruses. Here we develop a generalized NK, or spin glass, theory of T cell original antigenic sin and immunodominance. The theory we develop predicts dengue vaccine clinical trial data well. From the insights that we gain by this theory, we propose two new ideas for design of epitope-based T cell vaccines against dengue. The H5N1 strain of avian influenza first appeared in Hong Kong in 1997. Since then, it has spread to at least eight other Asian countries, Romania, and Russia, and it is widely expected to enter the rest of Europe through migratory birds. Various countries around the world have started to create stockpiles of avian influenza vaccines. However, since the avian influenza is mutating, how many and which strains should be stockpiled? Here we use a combination of statistical physics and network theory to simulate the bird flu transmission and evolution. From the insights that we gain by the theory, we propose new strategies to improve the vaccine efficacy.

  4. A theory for species migration in a finitely strained solid with application to polymer network swelling

    NASA Astrophysics Data System (ADS)

    Duda, Fernando P.; Souza, Angela C.; Fried, Eliot

    2010-04-01

    We present a theory for the behavior of a solid undergoing two interdependent processes, a macroscopic or mechanical process due to the deformation of the solid and a microscopic or chemical process due to the migration of a chemical species through the solid. The principle of virtual power is invoked to deduce the basic balances of the theory, namely the mechanical force balance and the transport balance for the chemical species. In combination with thermodynamically consistent constitutive relations, these balances generate the basic equations of the theory. Keeping in mind applications involving the swelling of polymer networks by liquids, a specialization of the theory is presented and applied to study the influences of mechanical and chemical interactions on equilibrium states and diffusive dynamical processes. It is shown that the possibility of a mechanically induced phase transition is governed by two parameters: the Flory interaction parameter and a parameter given by the product between the number of cross-linked units per unit reference volume and the molecular volume of the liquid molecule. As for diffusion, it is shown that the theory is able to describe the pressure-induced diffusion in swollen membranes.

  5. Understanding Health Information Seeking from an Actor-Centric Perspective.

    PubMed

    Batchelor, Simon; Waldman, Linda; Bloom, Gerry; Rasheed, Sabrina; Scott, Nigel; Ahmed, Tanvir; Khan, Nazib Uz Zaman; Sharmin, Tamanna

    2015-07-01

    This paper presents a conceptual approach for discussing health information seeking among poor households in Africa and Asia. This approach is part of a larger research endeavor aimed at understanding how health systems are adapting; with possibilities and constraints emerging. These health systems can be found in a context of the changing relationships between states, markets and civil society in low and middle income countries. The paper starts from an understanding of the health sector as a "health knowledge economy", organized to provide people with access to knowledge and advice. The use of the term "health knowledge economy" draws attention to the ways the health sector is part of a broader knowledge economy changing the way individuals and households obtain and use specialist information. The paper integrates an actor centric approach with the theory of planned behavior. It seeks to identify the actors engaged in the health knowledge economy as a precursor to longer term studies on the uptake of innovations integrating health services with mobile phones, commonly designated as mHealth, contributing to an understanding of the potential vulnerabilities of poor people, and highlighting possible dangers if providers of health information and advice are strongly influenced by interest groups. PMID:26184275

  6. Understanding Health Information Seeking from an Actor-Centric Perspective

    PubMed Central

    Batchelor, Simon; Waldman, Linda; Bloom, Gerry; Rasheed, Sabrina; Scott, Nigel; Ahmed, Tanvir; Uz Zaman Khan, Nazib; Sharmin, Tamanna

    2015-01-01

    This paper presents a conceptual approach for discussing health information seeking among poor households in Africa and Asia. This approach is part of a larger research endeavor aimed at understanding how health systems are adapting; with possibilities and constraints emerging. These health systems can be found in a context of the changing relationships between states, markets and civil society in low and middle income countries. The paper starts from an understanding of the health sector as a “health knowledge economy”, organized to provide people with access to knowledge and advice. The use of the term “health knowledge economy” draws attention to the ways the health sector is part of a broader knowledge economy changing the way individuals and households obtain and use specialist information. The paper integrates an actor centric approach with the theory of planned behavior. It seeks to identify the actors engaged in the health knowledge economy as a precursor to longer term studies on the uptake of innovations integrating health services with mobile phones, commonly designated as mHealth, contributing to an understanding of the potential vulnerabilities of poor people, and highlighting possible dangers if providers of health information and advice are strongly influenced by interest groups. PMID:26184275

  7. An examination of network position and childhood relational aggression: integrating resource control and social exchange theories.

    PubMed

    Neal, Jennifer Watling; Cappella, Elise

    2012-01-01

    Applying resource control theory and social exchange theory, we examined the social network conditions under which elementary age children were likely to engage in relational aggression. Data on classroom peer networks and peer-nominated behaviors were collected on 671 second- through fourth-grade children in 34 urban, low-income classrooms. Nested regression models with robust cluster standard errors demonstrated that the association between children's number of relationships and their levels of relational aggression was moderated by the number of relationships that their affiliates had. Children with more peer relationships (i.e., higher network centrality) exhibited higher levels of relational aggression, but only when these relationships were with peers who had fewer connections themselves (i.e., poorly connected peers). This finding remained significant even when controlling for common predictors of relational aggression including gender, overt aggression, prosocial behavior, victimization, social preference, and perceived popularity. Results are discussed in terms of their implications for advancing the literature on childhood relational aggression and their practical applications for identifying children at risk for these behaviors. PMID:25363638

  8. Large-Scale Transportation Network Congestion Evolution Prediction Using Deep Learning Theory

    PubMed Central

    Ma, Xiaolei; Yu, Haiyang; Wang, Yunpeng; Wang, Yinhai

    2015-01-01

    Understanding how congestion at one location can cause ripples throughout large-scale transportation network is vital for transportation researchers and practitioners to pinpoint traffic bottlenecks for congestion mitigation. Traditional studies rely on either mathematical equations or simulation techniques to model traffic congestion dynamics. However, most of the approaches have limitations, largely due to unrealistic assumptions and cumbersome parameter calibration process. With the development of Intelligent Transportation Systems (ITS) and Internet of Things (IoT), transportation data become more and more ubiquitous. This triggers a series of data-driven research to investigate transportation phenomena. Among them, deep learning theory is considered one of the most promising techniques to tackle tremendous high-dimensional data. This study attempts to extend deep learning theory into large-scale transportation network analysis. A deep Restricted Boltzmann Machine and Recurrent Neural Network architecture is utilized to model and predict traffic congestion evolution based on Global Positioning System (GPS) data from taxi. A numerical study in Ningbo, China is conducted to validate the effectiveness and efficiency of the proposed method. Results show that the prediction accuracy can achieve as high as 88% within less than 6 minutes when the model is implemented in a Graphic Processing Unit (GPU)-based parallel computing environment. The predicted congestion evolution patterns can be visualized temporally and spatially through a map-based platform to identify the vulnerable links for proactive congestion mitigation. PMID:25780910

  9. Large-scale transportation network congestion evolution prediction using deep learning theory.

    PubMed

    Ma, Xiaolei; Yu, Haiyang; Wang, Yunpeng; Wang, Yinhai

    2015-01-01

    Understanding how congestion at one location can cause ripples throughout large-scale transportation network is vital for transportation researchers and practitioners to pinpoint traffic bottlenecks for congestion mitigation. Traditional studies rely on either mathematical equations or simulation techniques to model traffic congestion dynamics. However, most of the approaches have limitations, largely due to unrealistic assumptions and cumbersome parameter calibration process. With the development of Intelligent Transportation Systems (ITS) and Internet of Things (IoT), transportation data become more and more ubiquitous. This triggers a series of data-driven research to investigate transportation phenomena. Among them, deep learning theory is considered one of the most promising techniques to tackle tremendous high-dimensional data. This study attempts to extend deep learning theory into large-scale transportation network analysis. A deep Restricted Boltzmann Machine and Recurrent Neural Network architecture is utilized to model and predict traffic congestion evolution based on Global Positioning System (GPS) data from taxi. A numerical study in Ningbo, China is conducted to validate the effectiveness and efficiency of the proposed method. Results show that the prediction accuracy can achieve as high as 88% within less than 6 minutes when the model is implemented in a Graphic Processing Unit (GPU)-based parallel computing environment. The predicted congestion evolution patterns can be visualized temporally and spatially through a map-based platform to identify the vulnerable links for proactive congestion mitigation. PMID:25780910

  10. Application of the Actor-Critic Architecture to Functional Electrical Stimulation Control of a Human Arm.

    PubMed

    Thomas, Philip; Branicky, Michael; van den Bogert, Antonie; Jagodnik, Kathleen

    2009-01-01

    Clinical tests have shown that the dynamics of a human arm, controlled using Functional Electrical Stimulation (FES), can vary significantly between and during trials. In this paper, we study the application of the actor-critic architecture, with neural networks for the both the actor and the critic, as a controller that can adapt to these changing dynamics of a human arm. Development and tests were done in simulation using a planar arm model and Hill-based muscle dynamics. We begin by training it using a Proportional Derivative (PD) controller as a supervisor. We then make clinically relevant changes to the dynamics of the arm and test the actor-critic's ability to adapt without supervision in a reasonable number of episodes. Finally, we devise methods for achieving both rapid learning and long-term stability. PMID:20689654

  11. Feasibility Evaluation of an On-site Generator Network by the Cooperative Game Theory

    NASA Astrophysics Data System (ADS)

    Komiyama, Ryoichi; Hayashi, Taketo; Fujii, Yasumasa; Yamaji, Kenji

    On-site generator, such as CGS (cogeneration system), is allegedly considered to be an effective end-use energy system in order to accomplish primary energy conservation, CO2 emission mitigation and system cost reduction, which characteristics eventually improve the whole performance of an existing energy system for the future. Considering the drawback of installing an end-use CGS into the customer with small or middle scale floor space, however, it is difficult to achieve those distinctive features because the thermal-electricity ratio of CGS does not always be in agreement with that of customer energy demand. In order to overcome that matching deficiency, it is hence better to organize an on-site generator network based on mutual electricity and heating transmission. But focusing on some cogenerators underlying their behaviors on maximizing their own profits, this on-site network, which situation corresponds to a grand coalition, is not necessarily established because of each cogenerator’s motivation to form a partial coalition and acquire its own profit as much as possible. In this paper, we attempt to analyze the optimal operation of an on-site generator network and identify by applying the nucleolus of the cooperative game theory the optimal benefit allocation strategy in order for the cogenerators to construct the network. Regarding the installation site of this network, the center of Tokyo area is assumed, which locational information includes floor space and so forth through a GIS (geographic information system) database. The results from the nucleolus suggest that all districts should impartially obtain the benefit from organizing network for the purpose of jointly attaining the system total cost reduction.

  12. Applications of network theory to frustrated spin systems and transitions in models of disease spread

    NASA Astrophysics Data System (ADS)

    Stone, Thomas E., Jr.

    This study of network structure and phase transitions focuses on three systems with different dynamical rules: the Ising model with competing ferromagnetic and antiferromagnetic interactions on a 2D triangular lattice, the susceptible-infected-recovered (SIR) epidemic model on an adaptive small-world network, and the SIR model on the Saramaki-Kaski dynamic small-world network. In the Ising model with competing interactions, we employ a novel network construction using the individual spins as nodes and links occurring between two nodes if their spin-spin correlation function exceeds a set threshold. This construction yields the emergence of multiple networks of correlated fluctuations. In the spin-glass-like phase, we find spatially non-contiguous networks of correlated fluctuations, as had been previously predicted by chaotic renormalization-group trajectory arguments, but not confirmed. In the second part of this thesis we turn to a dynamical process, disease spreading, on an adaptive small-world network. The adaptive nature of the contact network means that the social connections can evolve in time, in response to the current states of the individual nodes, creating a feedback mechanism. Unlike previous work, we introduce a method by which this adaptive rewiring is included while maintaining the underlying community structure. This more realistic method can have significant effects on the final size of an outbreak. We also develop a mean-field theory to verify our simulation results in certain limits based on master equation considerations. The third part of this thesis treats a dynamic small-world network, in order to utilize its computational advantages to study the critical phenomena of the disease-free to epidemic phase transition. We solve the dynamical equations for the predicted critical point, and verify this point via finite size scaling arguments. The associated critical exponents are found in a similar manner, which show this model to be in a new

  13. Securing Mobile Ad Hoc Networks Using Danger Theory-Based Artificial Immune Algorithm

    PubMed Central

    2015-01-01

    A mobile ad hoc network (MANET) is a set of mobile, decentralized, and self-organizing nodes that are used in special cases, such as in the military. MANET properties render the environment of this network vulnerable to different types of attacks, including black hole, wormhole and flooding-based attacks. Flooding-based attacks are one of the most dangerous attacks that aim to consume all network resources and thus paralyze the functionality of the whole network. Therefore, the objective of this paper is to investigate the capability of a danger theory-based artificial immune algorithm called the mobile dendritic cell algorithm (MDCA) to detect flooding-based attacks in MANETs. The MDCA applies the dendritic cell algorithm (DCA) to secure the MANET with additional improvements. The MDCA is tested and validated using Qualnet v7.1 simulation tool. This work also introduces a new simulation module for a flooding attack called the resource consumption attack (RCA) using Qualnet v7.1. The results highlight the high efficiency of the MDCA in detecting RCAs in MANETs. PMID:25946001

  14. Securing mobile ad hoc networks using danger theory-based artificial immune algorithm.

    PubMed

    Abdelhaq, Maha; Alsaqour, Raed; Abdelhaq, Shawkat

    2015-01-01

    A mobile ad hoc network (MANET) is a set of mobile, decentralized, and self-organizing nodes that are used in special cases, such as in the military. MANET properties render the environment of this network vulnerable to different types of attacks, including black hole, wormhole and flooding-based attacks. Flooding-based attacks are one of the most dangerous attacks that aim to consume all network resources and thus paralyze the functionality of the whole network. Therefore, the objective of this paper is to investigate the capability of a danger theory-based artificial immune algorithm called the mobile dendritic cell algorithm (MDCA) to detect flooding-based attacks in MANETs. The MDCA applies the dendritic cell algorithm (DCA) to secure the MANET with additional improvements. The MDCA is tested and validated using Qualnet v7.1 simulation tool. This work also introduces a new simulation module for a flooding attack called the resource consumption attack (RCA) using Qualnet v7.1. The results highlight the high efficiency of the MDCA in detecting RCAs in MANETs. PMID:25946001

  15. On a theory of stability for nonlinear stochastic chemical reaction networks

    NASA Astrophysics Data System (ADS)

    Smadbeck, Patrick; Kaznessis, Yiannis N.

    2015-05-01

    We present elements of a stability theory for small, stochastic, nonlinear chemical reaction networks. Steady state probability distributions are computed with zero-information (ZI) closure, a closure algorithm that solves chemical master equations of small arbitrary nonlinear reactions. Stochastic models can be linearized around the steady state with ZI-closure, and the eigenvalues of the Jacobian matrix can be readily computed. Eigenvalues govern the relaxation of fluctuation autocorrelation functions at steady state. Autocorrelation functions reveal the time scales of phenomena underlying the dynamics of nonlinear reaction networks. In accord with the fluctuation-dissipation theorem, these functions are found to be congruent to response functions to small perturbations. Significant differences are observed in the stability of nonlinear reacting systems between deterministic and stochastic modeling formalisms.

  16. On a theory of stability for nonlinear stochastic chemical reaction networks

    SciTech Connect

    Smadbeck, Patrick; Kaznessis, Yiannis N.

    2015-05-14

    We present elements of a stability theory for small, stochastic, nonlinear chemical reaction networks. Steady state probability distributions are computed with zero-information (ZI) closure, a closure algorithm that solves chemical master equations of small arbitrary nonlinear reactions. Stochastic models can be linearized around the steady state with ZI-closure, and the eigenvalues of the Jacobian matrix can be readily computed. Eigenvalues govern the relaxation of fluctuation autocorrelation functions at steady state. Autocorrelation functions reveal the time scales of phenomena underlying the dynamics of nonlinear reaction networks. In accord with the fluctuation-dissipation theorem, these functions are found to be congruent to response functions to small perturbations. Significant differences are observed in the stability of nonlinear reacting systems between deterministic and stochastic modeling formalisms.

  17. HBNG: Graph theory based visualization of hydrogen bond networks in protein structures

    PubMed Central

    Tiwari, Abhishek; Tiwari, Vivek

    2007-01-01

    HBNG is a graph theory based tool for visualization of hydrogen bond network in 2D. Digraphs generated by HBNG facilitate visualization of cooperativity and anticooperativity chains and rings in protein structures. HBNG takes hydrogen bonds list files (output from HBAT, HBEXPLORE, HBPLUS and STRIDE) as input and generates a DOT language script and constructs digraphs using freeware AT and T Graphviz tool. HBNG is useful in the enumeration of favorable topologies of hydrogen bond networks in protein structures and determining the effect of cooperativity and anticooperativity on protein stability and folding. HBNG can be applied to protein structure comparison and in the identification of secondary structural regions in protein structures. Availability Program is available from the authors for non-commercial purposes. PMID:18084648

  18. Optimal design of hydrometric monitoring networks with dynamic components based on Information Theory

    NASA Astrophysics Data System (ADS)

    Alfonso, Leonardo; Chacon, Juan; Solomatine, Dimitri

    2016-04-01

    The EC-FP7 WeSenseIt project proposes the development of a Citizen Observatory of Water, aiming at enhancing environmental monitoring and forecasting with the help of citizens equipped with low-cost sensors and personal devices such as smartphones and smart umbrellas. In this regard, Citizen Observatories may complement the limited data availability in terms of spatial and temporal density, which is of interest, among other areas, to improve hydraulic and hydrological models. At this point, the following question arises: how can citizens, who are part of a citizen observatory, be optimally guided so that the data they collect and send is useful to improve modelling and water management? This research proposes a new methodology to identify the optimal location and timing of potential observations coming from moving sensors of hydrological variables. The methodology is based on Information Theory, which has been widely used in hydrometric monitoring design [1-4]. In particular, the concepts of Joint Entropy, as a measure of the amount of information that is contained in a set of random variables, which, in our case, correspond to the time series of hydrological variables captured at given locations in a catchment. The methodology presented is a step forward in the state of the art because it solves the multiobjective optimisation problem of getting simultaneously the minimum number of informative and non-redundant sensors needed for a given time, so that the best configuration of monitoring sites is found at every particular moment in time. To this end, the existing algorithms have been improved to make them efficient. The method is applied to cases in The Netherlands, UK and Italy and proves to have a great potential to complement the existing in-situ monitoring networks. [1] Alfonso, L., A. Lobbrecht, and R. Price (2010a), Information theory-based approach for location of monitoring water level gauges in polders, Water Resour. Res., 46(3), W03528 [2] Alfonso, L., A

  19. Real-Time Dynamics in U(1) Lattice Gauge Theories with Tensor Networks

    NASA Astrophysics Data System (ADS)

    Pichler, T.; Dalmonte, M.; Rico, E.; Zoller, P.; Montangero, S.

    2016-01-01

    Tensor network algorithms provide a suitable route for tackling real-time-dependent problems in lattice gauge theories, enabling the investigation of out-of-equilibrium dynamics. We analyze a U(1) lattice gauge theory in (1 +1 ) dimensions in the presence of dynamical matter for different mass and electric-field couplings, a theory akin to quantum electrodynamics in one dimension, which displays string breaking: The confining string between charges can spontaneously break during quench experiments, giving rise to charge-anticharge pairs according to the Schwinger mechanism. We study the real-time spreading of excitations in the system by means of electric-field and particle fluctuations. We determine a dynamical state diagram for string breaking and quantitatively evaluate the time scales for mass production. We also show that the time evolution of the quantum correlations can be detected via bipartite von Neumann entropies, thus demonstrating that the Schwinger mechanism is tightly linked to entanglement spreading. To present a variety of possible applications of this simulation platform, we show how one could follow the real-time scattering processes between mesons and the creation of entanglement during scattering processes. Finally, we test the quality of quantum simulations of these dynamics, quantifying the role of possible imperfections in cold atoms, trapped ions, and superconducting circuit systems. Our results demonstrate how entanglement properties can be used to deepen our understanding of basic phenomena in the real-time dynamics of gauge theories such as string breaking and collisions.

  20. Extraction of business relationships in supply networks using statistical learning theory.

    PubMed

    Zuo, Yi; Kajikawa, Yuya; Mori, Junichiro

    2016-06-01

    Supply chain management represents one of the most important scientific streams of operations research. The supply of energy, materials, products, and services involves millions of transactions conducted among national and local business enterprises. To deliver efficient and effective support for supply chain design and management, structural analyses and predictive models of customer-supplier relationships are expected to clarify current enterprise business conditions and to help enterprises identify innovative business partners for future success. This article presents the outcomes of a recent structural investigation concerning a supply network in the central area of Japan. We investigated the effectiveness of statistical learning theory to express the individual differences of a supply chain of enterprises within a certain business community using social network analysis. In the experiments, we employ support vector machine to train a customer-supplier relationship model on one of the main communities extracted from a supply network in the central area of Japan. The prediction results reveal an F-value of approximately 70% when the model is built by using network-based features, and an F-value of approximately 77% when the model is built by using attribute-based features. When we build the model based on both, F-values are improved to approximately 82%. The results of this research can help to dispel the implicit design space concerning customer-supplier relationships, which can be explored and refined from detailed topological information provided by network structures rather than from traditional and attribute-related enterprise profiles. We also investigate and discuss differences in the predictive accuracy of the model for different sizes of enterprises and types of business communities. PMID:27441294

  1. Parametric sensitivity analysis for biochemical reaction networks based on pathwise information theory

    PubMed Central

    2013-01-01

    Background Stochastic modeling and simulation provide powerful predictive methods for the intrinsic understanding of fundamental mechanisms in complex biochemical networks. Typically, such mathematical models involve networks of coupled jump stochastic processes with a large number of parameters that need to be suitably calibrated against experimental data. In this direction, the parameter sensitivity analysis of reaction networks is an essential mathematical and computational tool, yielding information regarding the robustness and the identifiability of model parameters. However, existing sensitivity analysis approaches such as variants of the finite difference method can have an overwhelming computational cost in models with a high-dimensional parameter space. Results We develop a sensitivity analysis methodology suitable for complex stochastic reaction networks with a large number of parameters. The proposed approach is based on Information Theory methods and relies on the quantification of information loss due to parameter perturbations between time-series distributions. For this reason, we need to work on path-space, i.e., the set consisting of all stochastic trajectories, hence the proposed approach is referred to as “pathwise”. The pathwise sensitivity analysis method is realized by employing the rigorously-derived Relative Entropy Rate, which is directly computable from the propensity functions. A key aspect of the method is that an associated pathwise Fisher Information Matrix (FIM) is defined, which in turn constitutes a gradient-free approach to quantifying parameter sensitivities. The structure of the FIM turns out to be block-diagonal, revealing hidden parameter dependencies and sensitivities in reaction networks. Conclusions As a gradient-free method, the proposed sensitivity analysis provides a significant advantage when dealing with complex stochastic systems with a large number of parameters. In addition, the knowledge of the structure of the

  2. Information theory and signal transduction systems: from molecular information processing to network inference.

    PubMed

    Mc Mahon, Siobhan S; Sim, Aaron; Filippi, Sarah; Johnson, Robert; Liepe, Juliane; Smith, Dominic; Stumpf, Michael P H

    2014-11-01

    Sensing and responding to the environment are two essential functions that all biological organisms need to master for survival and successful reproduction. Developmental processes are marshalled by a diverse set of signalling and control systems, ranging from systems with simple chemical inputs and outputs to complex molecular and cellular networks with non-linear dynamics. Information theory provides a powerful and convenient framework in which such systems can be studied; but it also provides the means to reconstruct the structure and dynamics of molecular interaction networks underlying physiological and developmental processes. Here we supply a brief description of its basic concepts and introduce some useful tools for systems and developmental biologists. Along with a brief but thorough theoretical primer, we demonstrate the wide applicability and biological application-specific nuances by way of different illustrative vignettes. In particular, we focus on the characterisation of biological information processing efficiency, examining cell-fate decision making processes, gene regulatory network reconstruction, and efficient signal transduction experimental design. PMID:24953199

  3. Design of a universal two-layered neural network derived from the PLI theory

    NASA Astrophysics Data System (ADS)

    Hu, Chia-Lun J.

    2004-05-01

    The if-and-only-if (IFF) condition that a set of M analog-to-digital vector-mapping relations can be learned by a one-layered-feed-forward neural network (OLNN) is that all the input analog vectors dichotomized by the i-th output bit must be positively, linearly independent, or PLI. If they are not PLI, then the OLNN just cannot learn no matter what learning rules is employed because the solution of the connection matrix does not exist mathematically. However, in this case, one can still design a parallel-cascaded, two-layered, perceptron (PCTLP) to acheive this general mapping goal. The design principle of this "universal" neural network is derived from the major mathematical properties of the PLI theory - changing the output bits of the dependent relations existing among the dichotomized input vectors to make the PLD relations PLI. Then with a vector concatenation technique, the required mapping can still be learned by this PCTLP system with very high efficiency. This paper will report in detail the mathematical derivation of the general design principle and the design procedures of the PCTLP neural network system. It then will be verified in general by a practical numerical example.

  4. Localizing Pain Matrix and Theory of Mind networks with both verbal and non-verbal stimuli.

    PubMed

    Jacoby, Nir; Bruneau, Emile; Koster-Hale, Jorie; Saxe, Rebecca

    2016-02-01

    Functional localizer tasks allow researchers to identify brain regions in each individual's brain, using a combination of anatomical and functional constraints. In this study, we compare three social cognitive localizer tasks, designed to efficiently identify regions in the "Pain Matrix," recruited in response to a person's physical pain, and the "Theory of Mind network," recruited in response to a person's mental states (i.e. beliefs and emotions). Participants performed three tasks: first, the verbal false-belief stories task; second, a verbal task including stories describing physical pain versus emotional suffering; and third, passively viewing a non-verbal animated movie, which included segments depicting physical pain and beliefs and emotions. All three localizers were efficient in identifying replicable, stable networks in individual subjects. The consistency across tasks makes all three tasks viable localizers. Nevertheless, there were small reliable differences in the location of the regions and the pattern of activity within regions, hinting at more specific representations. The new localizers go beyond those currently available: first, they simultaneously identify two functional networks with no additional scan time, and second, the non-verbal task extends the populations in whom functional localizers can be applied. These localizers will be made publicly available. PMID:26589334

  5. A game theory-based obstacle avoidance routing protocol for wireless sensor networks.

    PubMed

    Guan, Xin; Wu, Huayang; Bi, Shujun

    2011-01-01

    The obstacle avoidance problem in geographic forwarding is an important issue for location-based routing in wireless sensor networks. The presence of an obstacle leads to several geographic routing problems such as excessive energy consumption and data congestion. Obstacles are hard to avoid in realistic environments. To bypass obstacles, most routing protocols tend to forward packets along the obstacle boundaries. This leads to a situation where the nodes at the boundaries exhaust their energy rapidly and the obstacle area is diffused. In this paper, we introduce a novel routing algorithm to solve the obstacle problem in wireless sensor networks based on a game-theory model. Our algorithm forms a concave region that cannot forward packets to achieve the aim of improving the transmission success rate and decreasing packet transmission delays. We consider the residual energy, out-degree and forwarding angle to determine the forwarding probability and payoff function of forwarding candidates. This achieves the aim of load balance and reduces network energy consumption. Simulation results show that based on the average delivery delay, energy consumption and packet delivery ratio performances our protocol is superior to other traditional schemes. PMID:22163698

  6. Multiple-scale theory of topology-driven patterns on directed networks.

    PubMed

    Contemori, Silvia; Di Patti, Francesca; Fanelli, Duccio; Miele, Filippo

    2016-03-01

    Dynamical processes on networks are currently being considered in different domains of cross-disciplinary interest. Reaction-diffusion systems hosted on directed graphs are in particular relevant for their widespread applications, from computer networks to traffic systems. Due to the peculiar spectrum of the discrete Laplacian operator, homogeneous fixed points can turn unstable, on a directed support, because of the topology of the network, a phenomenon which cannot be induced on undirected graphs. A linear analysis can be performed to single out the conditions that underly the instability. The complete characterization of the patterns, which are eventually attained beyond the linear regime of exponential growth, calls instead for a full nonlinear treatment. By performing a multiple time scale perturbative calculation, we here derive an effective equation for the nonlinear evolution of the amplitude of the most unstable mode, close to the threshold of criticality. This is a Stuart-Landau equation the complex coefficients of which appear to depend on the topological features of the embedding directed graph. The theory proves adequate versus simulations, as confirmed by operating with a paradigmatic reaction-diffusion model. PMID:27078376

  7. Multiple-scale theory of topology-driven patterns on directed networks

    NASA Astrophysics Data System (ADS)

    Contemori, Silvia; Di Patti, Francesca; Fanelli, Duccio; Miele, Filippo

    2016-03-01

    Dynamical processes on networks are currently being considered in different domains of cross-disciplinary interest. Reaction-diffusion systems hosted on directed graphs are in particular relevant for their widespread applications, from computer networks to traffic systems. Due to the peculiar spectrum of the discrete Laplacian operator, homogeneous fixed points can turn unstable, on a directed support, because of the topology of the network, a phenomenon which cannot be induced on undirected graphs. A linear analysis can be performed to single out the conditions that underly the instability. The complete characterization of the patterns, which are eventually attained beyond the linear regime of exponential growth, calls instead for a full nonlinear treatment. By performing a multiple time scale perturbative calculation, we here derive an effective equation for the nonlinear evolution of the amplitude of the most unstable mode, close to the threshold of criticality. This is a Stuart-Landau equation the complex coefficients of which appear to depend on the topological features of the embedding directed graph. The theory proves adequate versus simulations, as confirmed by operating with a paradigmatic reaction-diffusion model.

  8. Testing Foundations of Biological Scaling Theory Using Automated Measurements of Vascular Networks.

    PubMed

    Newberry, Mitchell G; Ennis, Daniel B; Savage, Van M

    2015-08-01

    Scientists have long sought to understand how vascular networks supply blood and oxygen to cells throughout the body. Recent work focuses on principles that constrain how vessel size changes through branching generations from the aorta to capillaries and uses scaling exponents to quantify these changes. Prominent scaling theories predict that combinations of these exponents explain how metabolic, growth, and other biological rates vary with body size. Nevertheless, direct measurements of individual vessel segments have been limited because existing techniques for measuring vasculature are invasive, time consuming, and technically difficult. We developed software that extracts the length, radius, and connectivity of in vivo vessels from contrast-enhanced 3D Magnetic Resonance Angiography. Using data from 20 human subjects, we calculated scaling exponents by four methods-two derived from local properties of branching junctions and two from whole-network properties. Although these methods are often used interchangeably in the literature, we do not find general agreement between these methods, particularly for vessel lengths. Measurements for length of vessels also diverge from theoretical values, but those for radius show stronger agreement. Our results demonstrate that vascular network models cannot ignore certain complexities of real vascular systems and indicate the need to discover new principles regarding vessel lengths. PMID:26317654

  9. A Game Theory-Based Obstacle Avoidance Routing Protocol for Wireless Sensor Networks

    PubMed Central

    Guan, Xin; Wu, Huayang; Bi, Shujun

    2011-01-01

    The obstacle avoidance problem in geographic forwarding is an important issue for location-based routing in wireless sensor networks. The presence of an obstacle leads to several geographic routing problems such as excessive energy consumption and data congestion. Obstacles are hard to avoid in realistic environments. To bypass obstacles, most routing protocols tend to forward packets along the obstacle boundaries. This leads to a situation where the nodes at the boundaries exhaust their energy rapidly and the obstacle area is diffused. In this paper, we introduce a novel routing algorithm to solve the obstacle problem in wireless sensor networks based on a game-theory model. Our algorithm forms a concave region that cannot forward packets to achieve the aim of improving the transmission success rate and decreasing packet transmission delays. We consider the residual energy, out-degree and forwarding angle to determine the forwarding probability and payoff function of forwarding candidates. This achieves the aim of load balance and reduces network energy consumption. Simulation results show that based on the average delivery delay, energy consumption and packet delivery ratio performances our protocol is superior to other traditional schemes. PMID:22163698

  10. Testing Foundations of Biological Scaling Theory Using Automated Measurements of Vascular Networks

    PubMed Central

    Newberry, Mitchell G; Ennis, Daniel B; Savage, Van M

    2015-01-01

    Scientists have long sought to understand how vascular networks supply blood and oxygen to cells throughout the body. Recent work focuses on principles that constrain how vessel size changes through branching generations from the aorta to capillaries and uses scaling exponents to quantify these changes. Prominent scaling theories predict that combinations of these exponents explain how metabolic, growth, and other biological rates vary with body size. Nevertheless, direct measurements of individual vessel segments have been limited because existing techniques for measuring vasculature are invasive, time consuming, and technically difficult. We developed software that extracts the length, radius, and connectivity of in vivo vessels from contrast-enhanced 3D Magnetic Resonance Angiography. Using data from 20 human subjects, we calculated scaling exponents by four methods—two derived from local properties of branching junctions and two from whole-network properties. Although these methods are often used interchangeably in the literature, we do not find general agreement between these methods, particularly for vessel lengths. Measurements for length of vessels also diverge from theoretical values, but those for radius show stronger agreement. Our results demonstrate that vascular network models cannot ignore certain complexities of real vascular systems and indicate the need to discover new principles regarding vessel lengths. PMID:26317654

  11. Transition modes in Ising networks: an approximate theory for macromolecular recognition.

    PubMed Central

    Keating, S; Di Cera, E

    1993-01-01

    For a statistical lattice, or Ising network, composed of N identical units existing in two possible states, 0 and 1, and interacting according to a given geometry, a set of values can be found for the mean free energy of the 0-->1 transition of a single unit. Each value defines a transition mode in an ensemble of nu N = 3N - 2N possible values and reflects the role played by intermediate states in shaping the energetics of the system as a whole. The distribution of transition modes has a number of intriguing properties. Some of them apply quite generally to any Ising network, regardless of its dimension, while others are specific for each interaction geometry and dimensional embedding and bear on fundamental aspects of analytical number theory. The landscape of transition modes encapsulates all of the important thermodynamic properties of the network. The free energy terms defining the partition function of the system can be derived from the modes by simple transformations. Classical mean-field expressions can be obtained from consideration of the properties of transition modes in a rather straightforward way. The results obtained in the analysis of the transition mode distributions have been used to develop an approximate treatment of the problem of macromolecular recognition. This phenomenon is modeled as a cooperative process that involves a number of recognition subsites across an interface generated by the binding of two macromolecular components. The distribution of allowed binding free energies for the system is shown to be a superposition of Gaussian terms with mean and variance determined a priori by the theory. Application to the analysis of the biologically interaction of thrombin with hirudin has provided some useful information on basic aspects of the interaction, such as the number of recognition subsites involved and the energy balance for binding and cooperative coupling among them. Our results agree quite well with information derived independently

  12. Combining Flux Balance and Energy Balance Analysis for Large-Scale Metabolic Network: Biochemical Circuit Theory for Analysis of Large-Scale Metabolic Networks

    NASA Technical Reports Server (NTRS)

    Beard, Daniel A.; Liang, Shou-Dan; Qian, Hong; Biegel, Bryan (Technical Monitor)

    2001-01-01

    Predicting behavior of large-scale biochemical metabolic networks represents one of the greatest challenges of bioinformatics and computational biology. Approaches, such as flux balance analysis (FBA), that account for the known stoichiometry of the reaction network while avoiding implementation of detailed reaction kinetics are perhaps the most promising tools for the analysis of large complex networks. As a step towards building a complete theory of biochemical circuit analysis, we introduce energy balance analysis (EBA), which compliments the FBA approach by introducing fundamental constraints based on the first and second laws of thermodynamics. Fluxes obtained with EBA are thermodynamically feasible and provide valuable insight into the activation and suppression of biochemical pathways.

  13. Application of Percolation Theory to Complex Interconnected Networks in Advanced Functional Composites

    NASA Astrophysics Data System (ADS)

    Hing, P.

    2011-11-01

    Percolation theory deals with the behaviour of connected clusters in a system. Originally developed for studying the flow of liquid in a porous body, the percolation theory has been extended to quantum computation and communication, entanglement percolation in quantum networks, cosmology, chaotic situations, properties of disordered solids, pandemics, petroleum industry, finance, control of traffic and so on. In this paper, the application of various models of the percolation theory to predict and explain the properties of a specially developed family of dense sintered and highly refractory Al2O3-W composites for potential application in high intensity discharge light sources such as high pressure sodium lamps and ceramic metal halide lamps are presented and discussed. The low cost, core-shell concept can be extended to develop functional composite materials with unusual dielectric, electrical, magnetic, superconducting, and piezoelectric properties starting from a classical insulator. The core shell concept can also be applied to develop catalysts with high specific surface areas with minimal amount of expensive platinium, palladium or rare earth nano structured materials for light harvesting, replicating natural photosynthesis, in synthetic zeolite composites for the cracking and separation of crude oil. There is also possibility of developing micron and nanosize Faraday cages for quantum devices, nano electronics and spintronics. The possibilities are limitless.

  14. The effect of inter-particle contact time in granular flows -- A network theory

    SciTech Connect

    Zhang, D.Z.; Rauenzahn, R.M.

    1996-12-31

    In a kinetic theory, it is usually assumed that the time duration of particle collision is vanishingly small and only binary collisions are considered. The validity of these assumptions depends on the ratio of collision time to mean free flight time. If this ratio is small, the kinetic theory description is appropriate. In a dense system, however, this ratio is usually large, and the dynamics of the multi-particle interactions have to be considered. For instance, during a collision, the contacting pair usually has a relative tangential velocity that causes a change in the direction of rebound. This implies a dependence of the granular stress on the vorticity of the mean flows field. Due to the inherent energy dissipation in a particle collision, and the consistent rearrangement of particles, there are relaxation times associated with them. In a binary collision, this energy dissipation is represented by coefficient of restitution. In a dense granular system, multi-particle interactions occur frequently. The energy dissipation and system relaxation have to be studied by the consideration of the dynamics in the duration of particle interaction and cannot be represented by a single coefficient of restitution. In this case, the relaxation times must be introduced explicitly. By modification of the network theory for rubber material, a constitutive model for dense granular material is developed based on the dynamics of multi-particle interaction. The finite particle interaction time and system relaxation times are considered.

  15. Governance of Health Systems Comment on “A Network Based Theory of Health Systems and Cycles of Well-Being”

    PubMed Central

    Blanchet, Karl

    2013-01-01

    Health systems research aims to understand the governance of health systems (i.e. how health systems function and perform and how their actors interact with each other). This can be achieved by applying innovative methodologies and concepts that are going to capture the complexity and dynamics of health systems when they are affected by shocks. The capacity of health systems to adapt to shocks (i.e. the resilience of health systems) is a new area of investigation. Social network analysis is a great avenue that can help measure the properties of systems and analyse the relationships between its actors and between the structure of a health system and the performance of a health system. A new conceptual framework is presented to define the governance of health systems using a resilience perspective. PMID:24596859

  16. Assessment on knowledge network sharing capability of industrial cluster based on dempster-shafer theory of evidence.

    PubMed

    Dai, Shengli; Zhang, Hailin

    2014-01-01

    Based on Theory of Evidence and reviewing research papers concerned, a concept model of knowledge sharing network among industrial cluster firms, which can be applied to assess knowledge sharing capacity, has been built. Next, the authors create a set of assessment index systems including twelve subindexes under four principle indexes. In this study, ten experts in the same field were invited to score all the indexes of knowledge sharing capacity concerning one certain industrial cluster. The research result shows relatively high knowledge network sharing capacity among the certain industrial cluster firms. Another conclusion is that the assessment method with Theory of Evidence is feasible to conduct such a research. PMID:24795540

  17. Assessment on Knowledge Network Sharing Capability of Industrial Cluster Based on Dempster-Shafer Theory of Evidence

    PubMed Central

    Zhang, Hailin

    2014-01-01

    Based on Theory of Evidence and reviewing research papers concerned, a concept model of knowledge sharing network among industrial cluster firms, which can be applied to assess knowledge sharing capacity, has been built. Next, the authors create a set of assessment index systems including twelve subindexes under four principle indexes. In this study, ten experts in the same field were invited to score all the indexes of knowledge sharing capacity concerning one certain industrial cluster. The research result shows relatively high knowledge network sharing capacity among the certain industrial cluster firms. Another conclusion is that the assessment method with Theory of Evidence is feasible to conduct such a research. PMID:24795540

  18. Note: Network random walk model of two-state protein folding: Test of the theory

    NASA Astrophysics Data System (ADS)

    Berezhkovskii, Alexander M.; Murphy, Ronan D.; Buchete, Nicolae-Viorel

    2013-01-01

    We study two-state protein folding in the framework of a toy model of protein dynamics. This model has an important advantage: it allows for an analytical solution for the sum of folding and unfolding rate constants [A. M. Berezhkovskii, F. Tofoleanu, and N.-V. Buchete, J. Chem. Theory Comput. 7, 2370 (2011), 10.1021/ct200281d] and hence for the reactive flux at equilibrium. We use the model to test the Kramers-type formula for the reactive flux, which was derived assuming that the protein dynamics is described by a Markov random walk on a network of complex connectivity [A. Berezhkovskii, G. Hummer, and A. Szabo, J. Chem. Phys. 130, 205102 (2009), 10.1063/1.3139063]. It is shown that the Kramers-type formula leads to the same result for the reactive flux as the sum of the rate constants.

  19. Truncated Wigner theory of coherent Ising machines based on degenerate optical parametric oscillator network

    NASA Astrophysics Data System (ADS)

    Maruo, Daiki; Utsunomiya, Shoko; Yamamoto, Yoshihisa

    2016-08-01

    We present the quantum theory of coherent Ising machines based on networks of degenerate optical parametric oscillators (DOPOs). In a simple model consisting of two coupled DOPOs, both positive-P representation and truncated Wigner representation predict quantum correlation and inseparability between the two DOPOs in spite of the open-dissipative nature of the system. Here, we apply the truncated Wigner representation method to coherent Ising machines with thermal, vacuum, and squeezed reservoir fields. We find that the probability of finding the ground state of a one-dimensional Ising model increases substantially as a result of reducing excess thermal noise and squeezing the incident vacuum fluctuation on the out-coupling port.

  20. Electromagnetic game modeling through Tensor Analysis of Networks and Game Theory

    NASA Astrophysics Data System (ADS)

    Maurice, Olivier; Reineix, Alain; Lalléchère, Sébastien

    2014-10-01

    A complex system involves events coming from natural behaviors. Whatever is the complicated face of machines, they are still far from the complexity of natural systems. Currently, economy is one of the rare science trying to find out some ways to model human behavior. These attempts involve game theory and psychology. Our purpose is to develop a formalism able to take in charge both game and hardware modeling. We first present the Tensorial Analysis of Networks, used for the material part of the system. Then, we detail the mathematical objects defined in order to describe the evolution of the system and its gaming side. To illustrate the discussion we consider the case of a drone whose electronic can be disturbed by a radar field, but this drone must fly as near as possible close to this radar.

  1. STICAP: A linear circuit analysis program with stiff systems capability. Volume 1: Theory manual. [network analysis

    NASA Technical Reports Server (NTRS)

    Cooke, C. H.

    1975-01-01

    STICAP (Stiff Circuit Analysis Program) is a FORTRAN 4 computer program written for the CDC-6400-6600 computer series and SCOPE 3.0 operating system. It provides the circuit analyst a tool for automatically computing the transient responses and frequency responses of large linear time invariant networks, both stiff and nonstiff (algorithms and numerical integration techniques are described). The circuit description and user's program input language is engineer-oriented, making simple the task of using the program. Engineering theories underlying STICAP are examined. A user's manual is included which explains user interaction with the program and gives results of typical circuit design applications. Also, the program structure from a systems programmer's viewpoint is depicted and flow charts and other software documentation are given.

  2. Lay theories of successful aging after the death of a spouse: a network text analysis of bereavement advice.

    PubMed

    Bergstrom, M J; Holmes, M E

    2000-01-01

    Social theories of successful aging attempt to explain how individuals adapt to changes characteristically associated with aging and to predict whether older adults' adaptations will lead to successful aging. The death of a spouse and the accompanying bereavement process entail dramatic changes to personal networks and experience to which individuals must adapt to age successfully. Network text analysis (including word frequencies, cluster analysis, and multidimensional scaling) of advice for adjusting to, and coping with, the loss of a spouse given by a sample of 60 bereaved spouses (mean age = 68) at 6 points in time after the death of their marital partner (3-4 weeks to 24 months) reveal respondents' lay theories of successful aging. Thematic clusters address social positioning and qualifiers, activity, communication, time, and spousal characteristics. Results indicate respondents frame their advice as unique to their context of social relationships while providing support for activity theory and negatively addressing disengagement theory. PMID:11063287

  3. Explaining the Stellar Initial Mass Function with the Theory of Spatial Networks

    NASA Astrophysics Data System (ADS)

    Klishin, Andrei A.; Chilingarian, Igor

    2016-06-01

    The distributions of stars and prestellar cores by mass (initial and dense core mass functions, IMF/DCMF) are among the key factors regulating star formation and are the subject of detailed theoretical and observational studies. Results from numerical simulations of star formation qualitatively resemble an observed mass function, a scale-free power law with a sharp decline at low masses. However, most analytic IMF theories critically depend on the empirically chosen input spectrum of mass fluctuations which evolve into dense cores and, subsequently, stars, and on the scaling relation between the amplitude and mass of a fluctuation. Here we propose a new approach exploiting techniques from the field of network science. We represent a system of dense cores accreting gas from the surrounding diffuse interstellar medium (ISM) as a spatial network growing by preferential attachment and assume that the ISM density has a self-similar fractal distribution following the Kolmogorov turbulence theory. We effectively combine gravoturbulent and competitive accretion approaches and predict the accretion rate to be proportional to the dense core mass: {dM}/{dt}\\propto M. Then we describe the dense core growth and demonstrate that the power-law core mass function emerges independently of the initial distribution of density fluctuations by mass. Our model yields a power law solely defined by the fractal dimensionalities of the ISM and accreting gas. With a proper choice of the low-mass cut-off, it reproduces observations over three decades in mass. We also rule out a low-mass star dominated “bottom-heavy” IMF in a single star-forming region.

  4. Integrating actors into a simulation program: a primer.

    PubMed

    Pascucci, Robert C; Weinstock, Peter H; O'Connor, Brigid E; Fancy, Kristina M; Meyer, Elaine C

    2014-04-01

    We describe our more than 10 years' experience working with actors and provide a "how-to" guide to recruiting, auditioning, hiring, training, and mentoring actors for work as simulated patients in simulation programs. We contend that trained actors add great realism, richness, and depth to simulation-based training programs. The actors experience satisfaction from their contributions, and their skill and improvisational talent allow programs to offer ethical and relational training, customized to a wide range of practitioners and adapted across a variety of health care conversations. Such learning opportunities can directly address Accreditation Council for Graduate Medical Education core competencies in preparing capable, confident, and empathic health care practitioners. PMID:24096918

  5. Game Theory Based Security in Wireless Body Area Network with Stackelberg Security Equilibrium.

    PubMed

    Somasundaram, M; Sivakumar, R

    2015-01-01

    Wireless Body Area Network (WBAN) is effectively used in healthcare to increase the value of the patient's life and also the value of healthcare services. The biosensor based approach in medical care system makes it difficult to respond to the patients with minimal response time. The medical care unit does not deploy the accessing of ubiquitous broadband connections full time and hence the level of security will not be high always. The security issue also arises in monitoring the user body function records. Most of the systems on the Wireless Body Area Network are not effective in facing the security deployment issues. To access the patient's information with higher security on WBAN, Game Theory with Stackelberg Security Equilibrium (GTSSE) is proposed in this paper. GTSSE mechanism takes all the players into account. The patients are monitored by placing the power position authority initially. The position authority in GTSSE is the organizer and all the other players react to the organizer decision. Based on our proposed approach, experiment has been conducted on factors such as security ratio based on patient's health information, system flexibility level, energy consumption rate, and information loss rate. Stackelberg Security considerably improves the strength of solution with higher security. PMID:26759829

  6. Spreading Effect in Industrial Complex Network Based on Revised Structural Holes Theory

    PubMed Central

    Ye, Qing; Guan, Jun

    2016-01-01

    This paper analyzed the spreading effect of industrial sectors with complex network model under perspective of econophysics. Input-output analysis, as an important research tool, focuses more on static analysis. However, the fundamental aim of industry analysis is to figure out how interaction between different industries makes impacts on economic development, which turns out to be a dynamic process. Thus, industrial complex network based on input-output tables from WIOD is proposed to be a bridge connecting accurate static quantitative analysis and comparable dynamic one. With application of revised structural holes theory, flow betweenness and random walk centrality were respectively chosen to evaluate industrial sectors’ long-term and short-term spreading effect process in this paper. It shows that industries with higher flow betweenness or random walk centrality would bring about more intensive industrial spreading effect to the industrial chains they stands in, because value stream transmission of industrial sectors depends on how many products or services it can get from the other ones, and they are regarded as brokers with bigger information superiority and more intermediate interests. PMID:27218468

  7. Neural network approach to quantum-chemistry data: Accurate prediction of density functional theory energies

    NASA Astrophysics Data System (ADS)

    Balabin, Roman M.; Lomakina, Ekaterina I.

    2009-08-01

    Artificial neural network (ANN) approach has been applied to estimate the density functional theory (DFT) energy with large basis set using lower-level energy values and molecular descriptors. A total of 208 different molecules were used for the ANN training, cross validation, and testing by applying BLYP, B3LYP, and BMK density functionals. Hartree-Fock results were reported for comparison. Furthermore, constitutional molecular descriptor (CD) and quantum-chemical molecular descriptor (QD) were used for building the calibration model. The neural network structure optimization, leading to four to five hidden neurons, was also carried out. The usage of several low-level energy values was found to greatly reduce the prediction error. An expected error, mean absolute deviation, for ANN approximation to DFT energies was 0.6±0.2 kcal mol-1. In addition, the comparison of the different density functionals with the basis sets and the comparison of multiple linear regression results were also provided. The CDs were found to overcome limitation of the QD. Furthermore, the effective ANN model for DFT/6-311G(3df,3pd) and DFT/6-311G(2df,2pd) energy estimation was developed, and the benchmark results were provided.

  8. Circuit Design and Simulation of AN Augmented Adaptive Resonance Theory (aart) Neural Network.

    NASA Astrophysics Data System (ADS)

    Ho, Ching-Sung

    This dissertation presents circuit implementations for an binary-input adaptive resonance theory neural network architecture, called the augmented ART-1 neural network (AART1-NN). The AART1-NN is a modification of the popular ART1-NN, developed by Carpenter and Grossberg, and it exhibits the same behavior as the ART1-NN. The AART1-NN is a real -time model, and has the ability to classify an arbitrary set of binary input patterns into different clusters. The design of the AART1-NN circuit is based on a set of coupled nonlinear differential equations that constitute the AART1 -NN model. Various ways are examined to implement an efficient and practical AART1-NN in electronic hardware. They include designing circuits of AART1-NN by means of discrete electronic components, such as operational amplifiers, capacitors, and resistors, digital VLSI circuit, and mixed analog/digital VLSI circuit. The implemented circuit prototypes are verified using the PSpice circuit simulator, running on Sun workstations. Results obtained from PSpice circuit simulations are also compared with results obtained by solving the coupled differential equations numerically. The prototype systems developed in this work can be used as building blocks for larger AART1-NN architectures, as well as for other types of ART architectures that involve the AART1-NN model.

  9. Analog circuit design and implementation of an adaptive resonance theory (ART) neural network architecture

    NASA Astrophysics Data System (ADS)

    Ho, Ching S.; Liou, Juin J.; Georgiopoulos, Michael; Heileman, Gregory L.; Christodoulou, Christos G.

    1993-09-01

    This paper presents an analog circuit implementation for an adaptive resonance theory neural network architecture, called the augmented ART-1 neural network (AART1-NN). The AART1-NN is a modification of the popular ART1-NN, developed by Carpenter and Grossberg, and it exhibits the same behavior as the ART1-NN. The AART1-NN is a real-time model, and has the ability to classify an arbitrary set of binary input patterns into different clusters. The design of the AART1-NN model. The circuit is implemented by utilizing analog electronic components, such as, operational amplifiers, transistors, capacitors, and resistors. The implemented circuit is verified using the PSpice circuit simulator, running on Sun workstations. Results obtained from the PSpice circuit simulation compare favorably with simulation results produced by solving the differential equations numerically. The prototype system developed here can be used as a building block for larger AART1-NN architectures, as well as for other types of ART architectures that involve the AART1-NN model.

  10. Assessment of the Instantaneous Unit Hydrograph Derived From the Theory of Topologically Random Networks

    NASA Astrophysics Data System (ADS)

    Karlinger, M. R.; Troutman, B. M.

    1985-11-01

    An instantaneous unit hydrograph (iuh) based on the theory of topologically random networks (topological iuh) is evaluated in terms of sets of basin characteristics and hydraulic parameters. Hydrographs were computed using two linear routing methods for each of two drainage basins in the southeastern United States and are the basis of comparison for the topological iuh's. Elements in the sets of basin characteristics for the topological iuh's are the number of first-order streams only, (N), or the nuber of sources together with the number of channel links in the topological diameter (N, D); the hydraulic parameters are values of the celerity and diffusivity constant. Sensitivity analyses indicate that the mean celerity of the internal links in the network is the critical hydraulic parameter for determining the shape of the topological iuh, while the diffusivity constant has minimal effect on the topological iuh. Asymptotic results (source-only) indicate the number of sources need not be large to approximate the topological iuh with the Weibull probability density function.

  11. Load reduction test method of similarity theory and BP neural networks of large cranes

    NASA Astrophysics Data System (ADS)

    Yang, Ruigang; Duan, Zhibin; Lu, Yi; Wang, Lei; Xu, Gening

    2016-01-01

    Static load tests are an important means of supervising and detecting a crane's lift capacity. Due to space restrictions, however, there are difficulties and potential danger when testing large bridge cranes. To solve the loading problems of large-tonnage cranes during testing, an equivalency test is proposed based on the similarity theory and BP neural networks. The maximum stress and displacement of a large bridge crane is tested in small loads, combined with the training neural network of a similar structure crane through stress and displacement data which is collected by a physics simulation progressively loaded to a static load test load within the material scope of work. The maximum stress and displacement of a crane under a static load test load can be predicted through the relationship of stress, displacement, and load. By measuring the stress and displacement of small tonnage weights, the stress and displacement of large loads can be predicted, such as the maximum load capacity, which is 1.25 times the rated capacity. Experimental study shows that the load reduction test method can reflect the lift capacity of large bridge cranes. The load shedding predictive analysis for Sanxia 1200 t bridge crane test data indicates that when the load is 1.25 times the rated lifting capacity, the predicted displacement and actual displacement error is zero. The method solves the problem that lifting capacities are difficult to obtain and testing accidents are easily possible when 1.25 times related weight loads are tested for large tonnage cranes.

  12. Spreading Effect in Industrial Complex Network Based on Revised Structural Holes Theory.

    PubMed

    Xing, Lizhi; Ye, Qing; Guan, Jun

    2016-01-01

    This paper analyzed the spreading effect of industrial sectors with complex network model under perspective of econophysics. Input-output analysis, as an important research tool, focuses more on static analysis. However, the fundamental aim of industry analysis is to figure out how interaction between different industries makes impacts on economic development, which turns out to be a dynamic process. Thus, industrial complex network based on input-output tables from WIOD is proposed to be a bridge connecting accurate static quantitative analysis and comparable dynamic one. With application of revised structural holes theory, flow betweenness and random walk centrality were respectively chosen to evaluate industrial sectors' long-term and short-term spreading effect process in this paper. It shows that industries with higher flow betweenness or random walk centrality would bring about more intensive industrial spreading effect to the industrial chains they stands in, because value stream transmission of industrial sectors depends on how many products or services it can get from the other ones, and they are regarded as brokers with bigger information superiority and more intermediate interests. PMID:27218468

  13. Game Theory Based Security in Wireless Body Area Network with Stackelberg Security Equilibrium

    PubMed Central

    Somasundaram, M.; Sivakumar, R.

    2015-01-01

    Wireless Body Area Network (WBAN) is effectively used in healthcare to increase the value of the patient's life and also the value of healthcare services. The biosensor based approach in medical care system makes it difficult to respond to the patients with minimal response time. The medical care unit does not deploy the accessing of ubiquitous broadband connections full time and hence the level of security will not be high always. The security issue also arises in monitoring the user body function records. Most of the systems on the Wireless Body Area Network are not effective in facing the security deployment issues. To access the patient's information with higher security on WBAN, Game Theory with Stackelberg Security Equilibrium (GTSSE) is proposed in this paper. GTSSE mechanism takes all the players into account. The patients are monitored by placing the power position authority initially. The position authority in GTSSE is the organizer and all the other players react to the organizer decision. Based on our proposed approach, experiment has been conducted on factors such as security ratio based on patient's health information, system flexibility level, energy consumption rate, and information loss rate. Stackelberg Security considerably improves the strength of solution with higher security. PMID:26759829

  14. Network Reconstruction Based on Proteomic Data and Prior Knowledge of Protein Connectivity Using Graph Theory

    PubMed Central

    Stavrakas, Vassilis; Alexopoulos, Leonidas G.

    2015-01-01

    Modeling of signal transduction pathways is instrumental for understanding cells’ function. People have been tackling modeling of signaling pathways in order to accurately represent the signaling events inside cells’ biochemical microenvironment in a way meaningful for scientists in a biological field. In this article, we propose a method to interrogate such pathways in order to produce cell-specific signaling models. We integrate available prior knowledge of protein connectivity, in a form of a Prior Knowledge Network (PKN) with phosphoproteomic data to construct predictive models of the protein connectivity of the interrogated cell type. Several computational methodologies focusing on pathways’ logic modeling using optimization formulations or machine learning algorithms have been published on this front over the past few years. Here, we introduce a light and fast approach that uses a breadth-first traversal of the graph to identify the shortest pathways and score proteins in the PKN, fitting the dependencies extracted from the experimental design. The pathways are then combined through a heuristic formulation to produce a final topology handling inconsistencies between the PKN and the experimental scenarios. Our results show that the algorithm we developed is efficient and accurate for the construction of medium and large scale signaling networks. We demonstrate the applicability of the proposed approach by interrogating a manually curated interaction graph model of EGF/TNFA stimulation against made up experimental data. To avoid the possibility of erroneous predictions, we performed a cross-validation analysis. Finally, we validate that the introduced approach generates predictive topologies, comparable to the ILP formulation. Overall, an efficient approach based on graph theory is presented herein to interrogate protein–protein interaction networks and to provide meaningful biological insights. PMID:26020784

  15. Network reconstruction based on proteomic data and prior knowledge of protein connectivity using graph theory.

    PubMed

    Stavrakas, Vassilis; Melas, Ioannis N; Sakellaropoulos, Theodore; Alexopoulos, Leonidas G

    2015-01-01

    Modeling of signal transduction pathways is instrumental for understanding cells' function. People have been tackling modeling of signaling pathways in order to accurately represent the signaling events inside cells' biochemical microenvironment in a way meaningful for scientists in a biological field. In this article, we propose a method to interrogate such pathways in order to produce cell-specific signaling models. We integrate available prior knowledge of protein connectivity, in a form of a Prior Knowledge Network (PKN) with phosphoproteomic data to construct predictive models of the protein connectivity of the interrogated cell type. Several computational methodologies focusing on pathways' logic modeling using optimization formulations or machine learning algorithms have been published on this front over the past few years. Here, we introduce a light and fast approach that uses a breadth-first traversal of the graph to identify the shortest pathways and score proteins in the PKN, fitting the dependencies extracted from the experimental design. The pathways are then combined through a heuristic formulation to produce a final topology handling inconsistencies between the PKN and the experimental scenarios. Our results show that the algorithm we developed is efficient and accurate for the construction of medium and large scale signaling networks. We demonstrate the applicability of the proposed approach by interrogating a manually curated interaction graph model of EGF/TNFA stimulation against made up experimental data. To avoid the possibility of erroneous predictions, we performed a cross-validation analysis. Finally, we validate that the introduced approach generates predictive topologies, comparable to the ILP formulation. Overall, an efficient approach based on graph theory is presented herein to interrogate protein-protein interaction networks and to provide meaningful biological insights. PMID:26020784

  16. Social networking for nurse education: Possibilities, perils and pitfalls.

    PubMed

    Green, Janet; Wyllie, Aileen; Jackson, Debra

    2014-01-01

    Abstract In this paper, we consider the potential and implications of using social networking sites such as Facebook® in nurse education. The concept of social networking and the use of Facebook will be explored, as will the theoretical constructs specific to the use of online technology and Web 2.0 tools. Theories around Communities of Inquiry (Garrison, Anderson, & Archer, 2000), Communities of Practice (Wenger, 1998), Activity Theory (Daniels, Cole, & Wertsch, 2007) and Actor-Network theory (Latour, 1997) will be briefly explored, as will the work of Vygotsky (1978), as applies to the social aspects of learning. Boundary issues, such as if and how faculty and students should or could be connected via social networking sites will also be explored. PMID:25267140

  17. Social networking for nurse education: Possibilities, perils and pitfalls.

    PubMed

    Green, Janet; Wyllie, Aileen; Jackson, Debra

    2014-03-11

    Abstract In this paper, we consider the potential and implications of using social networking sites such as Facebook® in nurse education. The concept of social networking and the use of Facebook will be explored, as will the theoretical constructs specific to the use of online technology and web 2.0 tools. Theories around Communities of Inquiry (Garrison, Anderson & Archer 2000), Communities of Practice (Wenger 1998), Activity Theory (Daniels, Cole & Wertsch 2007) and Actor Network Theory (Latour 1997) will be briefly explored, as will the work of Vygotsky (1978), as applies to the social aspects of learning. Boundary issues, such as if and how faculty and students should or could be connected via social networking sites will also be explored. PMID:24611647

  18. Coarse-Grained Models Reveal Functional Dynamics - I. Elastic Network Models – Theories, Comparisons and Perspectives

    PubMed Central

    Yang, Lee-Wei; Chng, Choon-Peng

    2008-01-01

    In this review, we summarize the progress on coarse-grained elastic network models (CG-ENMs) in the past decade. Theories were formulated to allow study of conformational dynamics in time/space frames of biological interest. Several highlighted models and their underlined hypotheses are introduced in physical depth. Important ENM offshoots, motivated to reproduce experimental data as well as to address the slow-mode-encoded configurational transitions, are also introduced. With the theoretical developments, computational cost is significantly reduced due to simplified potentials and coarse-grained schemes. Accumulating wealth of data suggest that ENMs agree equally well with experiment in describing equilibrium dynamics despite their distinct potentials and levels of coarse-graining. They however do differ in the slowest motional components that are essential to address large conformational changes of functional significance. The difference stems from the dissimilar curvatures of the harmonic energy wells described for each model. We also provide our views on the predictability of ‘open to close’ (open→close) transitions of biomolecules on the basis of conformational selection theory. Lastly, we address the limitations of the ENM formalism which are partially alleviated by the complementary CG-MD approach, to be introduced in the second paper of this two-part series. PMID:19812764

  19. An analytic explanation of the stellar initial mass function from the theory of spatial networks

    NASA Astrophysics Data System (ADS)

    Klishin, Andrei; Chilingarian, Igor

    2015-08-01

    The distribution of stars by mass or the stellar initial mass function (IMF) that has been intensively studied in the Milky Way and other galaxies is the key property regulating star formation and galaxy evolution. The mass function of prestellar dense cores (DCMF) is an IMF precursor that has a similar shape, a broken power law with a sharp decline at low masses, but offset to higher masses. Results from numerical simulations of star formation qualitatively resemble an observed IMF/DCMF, however, most analytic IMF theories critically depend on the empirically chosen input spectrum of mass fluctuations which evolve into dense cores and, subsequently, stars. Here we propose an analytic approach by representing a system of dense cores accreting gas from the surrounding diffuse interstellar medium (ISM) as a spatial network growing by preferential attachment and assuming that the ISM density has a self-similar fractal distribution following the Kolmogorov turbulence theory. We obtain a scale free power law with the exponent that is not related to the input fluctuation mass spectrum but depends only on the fractal distribution dimensionalities of infalling gas (Dp) and turbulent ISM (Dm=2.35). It can be as steep as -3.24 (uniform volume density Dp=3) and becomes Salpeter (α=-2.35) for Dp=2.5 that corresponds to a variety of Brownian processes in physics. Our theory reproduces the observed DCMF shape over three orders of magnitude in mass, and it rules out a low mass star dominated "bottom-heavy" IMF shape unless the same steep slope holds at the higher masses.

  20. [Status quo and potential of health services research: the perspective of Bavarian actors].

    PubMed

    Hollederer, A; Voigtländer, S; Wildner, M; Zapf, A; Zellner, A

    2015-03-01

    In 2011, the Bavarian Parliament decided to advance health services research (HSR) in Bavaria by bundling scientific competencies in a State Working Group and integrating other actors in it. The establishment of such a State Working Group "Health Services Research" -(LAGeV) together with members from science, health care and politics followed in 2012. The objective of this study is to identify the status quo of HSR in Bavaria including its determinants and potential for development based on the actors' perspective.After the inaugural meeting a semi-structured questionnaire was sent to all 36 members from 28 organisations. Items comprise information on the respondent's background as well as status quo, future topics and potential for development of HSR in Bavaria.27 members took part in the survey, resulting in a response rate of 75.0%. Satisfaction of actors with the status quo of HSR is rather low, especially regarding the effectiveness of policy advice. Researchers and health care providers are also not much satisfied with the HSR environment. For the future of HSR, respondents prioritise the topics interface and networking research, followed by innovative care concepts, care for patients with multiple or chronic conditions as well as evaluation of innovations, processes and technologies. Potential for development and thus improvement of care is primarily seen in the abolishment of existing constraints by an overall HSR concept (including selective research promotion), networking and cooperation, research funding as well as improving the interface between politics and science. Respondents assess the benefit of an increased networking within the LAGeV as high.Status quo of HSR in Bavaria is not very satisfactory. The survey reveals important constraints as well as promoting factors based on the viewpoints of different groups of actors. It also prioritises future HSR topics and identifies potential for development, which are important for the LAGeV. The findings

  1. Blogs and Social Network Sites as Activity Systems: Exploring Adult Informal Learning Process through Activity Theory Framework

    ERIC Educational Resources Information Center

    Heo, Gyeong Mi; Lee, Romee

    2013-01-01

    This paper uses an Activity Theory framework to explore adult user activities and informal learning processes as reflected in their blogs and social network sites (SNS). Using the assumption that a web-based space is an activity system in which learning occurs, typical features of the components were investigated and each activity system then…

  2. A Theory of Self-Learning in a Networked Human and IT Environment: Implications for Education Reforms.

    ERIC Educational Resources Information Center

    Mok, Magdalena Mo Ching; Cheng, Yin Cheong

    2001-01-01

    Discusses a theoretical model that can be used to deepen understanding of the nature and process of self-learning, and to facilitate students in becoming highly motivated and effective self-learners with the support of a networked human and information technology (IT) environment. Explores how the theory's implications can contribute to…

  3. Understanding the Employment of Actors. Research Division Report #3.

    ERIC Educational Resources Information Center

    National Endowment for the Arts, Washington, DC. Research Div.

    Focusing on actors' employment problems, part 1 of this report describes data collected by Actor's Equity primarily in terms of: (1) membership files; (2) the organization's contract department; (3) pension and welfare funds; and (4) employment statistics. Part 2 analyzes these data sets in relation to employment, unemployment, risk factors for…

  4. ACToR: Aggregated Computational Toxicology Resource (T)

    EPA Science Inventory

    The EPA Aggregated Computational Toxicology Resource (ACToR) is a set of databases compiling information on chemicals in the environment from a large number of public and in-house EPA sources. ACToR has 3 main goals: (1) The serve as a repository of public toxicology information ...

  5. Teaching, Learning, and Leading: Preparing Teachers as Educational Policy Actors

    ERIC Educational Resources Information Center

    Heineke, Amy J.; Ryan, Ann Marie; Tocci, Charles

    2015-01-01

    Within the current federal, state, and local contexts of educational reform, teachers must be recognized as central actors in policy work, but rarely do we explicitly consider preparing teachers to become policy actors. Understanding these implications for teacher education, we investigate teacher candidates' learning of the complexity and…

  6. Metacommunity theory as a multispecies, multiscale framework for studying the influence of river network structure on riverine communities and ecosystems

    USGS Publications Warehouse

    Brown, B.L.; Swan, C.M.; Auerbach, D.A.; Campbell, Grant E.H.; Hitt, N.P.; Maloney, K.O.; Patrick, C.

    2011-01-01

    Explaining the mechanisms underlying patterns of species diversity and composition in riverine networks is challenging. Historically, community ecologists have conceived of communities as largely isolated entities and have focused on local environmental factors and interspecific interactions as the major forces determining species composition. However, stream ecologists have long embraced a multiscale approach to studying riverine ecosystems and have studied both local factors and larger-scale regional factors, such as dispersal and disturbance. River networks exhibit a dendritic spatial structure that can constrain aquatic organisms when their dispersal is influenced by or confined to the river network. We contend that the principles of metacommunity theory would help stream ecologists to understand how the complex spatial structure of river networks mediates the relative influences of local and regional control on species composition. From a basic ecological perspective, the concept is attractive because new evidence suggests that the importance of regional processes (dispersal) depends on spatial structure of habitat and on connection to the regional species pool. The role of local factors relative to regional factors will vary with spatial position in a river network. From an applied perspective, the long-standing view in ecology that local community composition is an indicator of habitat quality may not be uniformly applicable across a river network, but the strength of such bioassessment approaches probably will depend on spatial position in the network. The principles of metacommunity theory are broadly applicable across taxa and systems but seem of particular consequence to stream ecology given the unique spatial structure of riverine systems. By explicitly embracing processes at multiple spatial scales, metacommunity theory provides a foundation on which to build a richer understanding of stream communities.

  7. Actor-critic models of the basal ganglia: new anatomical and computational perspectives.

    PubMed

    Joel, Daphna; Niv, Yael; Ruppin, Eytan

    2002-01-01

    A large number of computational models of information processing in the basal ganglia have been developed in recent years. Prominent in these are actor-critic models of basal ganglia functioning, which build on the strong resemblance between dopamine neuron activity and the temporal difference prediction error signal in the critic, and between dopamine-dependent long-term synaptic plasticity in the striatum and learning guided by a prediction error signal in the actor. We selectively review several actor-critic models of the basal ganglia with an emphasis on two important aspects: the way in which models of the critic reproduce the temporal dynamics of dopamine firing, and the extent to which models of the actor take into account known basal ganglia anatomy and physiology. To complement the efforts to relate basal ganglia mechanisms to reinforcement learning (RL), we introduce an alternative approach to modeling a critic network, which uses Evolutionary Computation techniques to 'evolve' an optimal RL mechanism, and relate the evolved mechanism to the basic model of the critic. We conclude our discussion of models of the critic by a critical discussion of the anatomical plausibility of implementations of a critic in basal ganglia circuitry, and conclude that such implementations build on assumptions that are inconsistent with the known anatomy of the basal ganglia. We return to the actor component of the actor-critic model, which is usually modeled at the striatal level with very little detail. We describe an alternative model of the basal ganglia which takes into account several important, and previously neglected, anatomical and physiological characteristics of basal ganglia-thalamocortical connectivity and suggests that the basal ganglia performs reinforcement-biased dimensionality reduction of cortical inputs. We further suggest that since such selective encoding may bias the representation at the level of the frontal cortex towards the selection of rewarded

  8. Transcriptional regulatory network refinement and quantification through kinetic modeling, gene expression microarray data and information theory

    PubMed Central

    Sayyed-Ahmad, Abdallah; Tuncay, Kagan; Ortoleva, Peter J

    2007-01-01

    Background Gene expression microarray and other multiplex data hold promise for addressing the challenges of cellular complexity, refined diagnoses and the discovery of well-targeted treatments. A new approach to the construction and quantification of transcriptional regulatory networks (TRNs) is presented that integrates gene expression microarray data and cell modeling through information theory. Given a partial TRN and time series data, a probability density is constructed that is a functional of the time course of transcription factor (TF) thermodynamic activities at the site of gene control, and is a function of mRNA degradation and transcription rate coefficients, and equilibrium constants for TF/gene binding. Results Our approach yields more physicochemical information that compliments the results of network structure delineation methods, and thereby can serve as an element of a comprehensive TRN discovery/quantification system. The most probable TF time courses and values of the aforementioned parameters are obtained by maximizing the probability obtained through entropy maximization. Observed time delays between mRNA expression and activity are accounted for implicitly since the time course of the activity of a TF is coupled by probability functional maximization, and is not assumed to be proportional to expression level of the mRNA type that translates into the TF. This allows one to investigate post-translational and TF activation mechanisms of gene regulation. Accuracy and robustness of the method are evaluated. A kinetic formulation is used to facilitate the analysis of phenomena with a strongly dynamical character while a physically-motivated regularization of the TF time course is found to overcome difficulties due to omnipresent noise and data sparsity that plague other methods of gene expression data analysis. An application to Escherichia coli is presented. Conclusion Multiplex time series data can be used for the construction of the network of

  9. The theory-of-mind network in support of action verb comprehension: evidence from an fMRI study.

    PubMed

    Lin, Nan; Bi, Yanchao; Zhao, Ying; Luo, Chunming; Li, Xingshan

    2015-02-01

    The theory-of-mind (ToM) network refers to a specific group of brain regions implicated in the thinking of people's mental states. It remains unclear how this network contributes to verb comprehension. In the present study, we compared brain activations evoked by verbs that refer to social actions, private actions, and nonhuman events. All classic regions of the ToM network, including the posterior superior temporal sulcus (pSTS) whose activation during word comprehension is typically interpreted as the processing of motion properties, showed stronger activations to social action verbs than the others. These findings indicate that the ToM network is involved in the processing of social/mental knowledge of verb meanings. Furthermore, the activation of the pSTS during word comprehension mainly reflects the processing of social/mental properties but not that of biological-motion properties. PMID:25498409

  10. Vaccinomics, adversomics, and the immune response network theory: Individualized vaccinology in the 21st century

    PubMed Central

    Poland, Gregory A.; Kennedy, Richard B.; McKinney, Brett A.; Ovsyannikova, Inna G.; Lambert, Nathaniel D.; Jacobson, Robert M.; Oberg, Ann L.

    2013-01-01

    Vaccines, like drugs and medical procedures, are increasingly amenable to individualization or personalization, often based on novel data resulting from high throughput “omics” technologies. As a result of these technologies, 21st century vaccinology will increasingly see the abandonment of a “one size fits all” approach to vaccine dosing and delivery, as well as the abandonment of the empiric “isolate–inactivate–inject” paradigm for vaccine development. In this review, we discuss the immune response network theory and its application to the new field of vaccinomics and adversomics, and illustrate how vaccinomics can lead to new vaccine candidates, new understandings of how vaccines stimulate immune responses, new biomarkers for vaccine response, and facilitate the understanding of what genetic and other factors might be responsible for rare side effects due to vaccines. Perhaps most exciting will be the ability, at a systems biology level, to integrate increasingly complex high throughput data into descriptive and predictive equations for immune responses to vaccines. Herein, we discuss the above with a view toward the future of vaccinology. PMID:23755893

  11. Multiresolution transmission of the correlation modes between bivariate time series based on complex network theory

    NASA Astrophysics Data System (ADS)

    Huang, Xuan; An, Haizhong; Gao, Xiangyun; Hao, Xiaoqing; Liu, Pengpeng

    2015-06-01

    This study introduces an approach to study the multiscale transmission characteristics of the correlation modes between bivariate time series. The correlation between the bivariate time series fluctuates over time. The transmission among the correlation modes exhibits a multiscale phenomenon, which provides richer information. To investigate the multiscale transmission of the correlation modes, this paper describes a hybrid model integrating wavelet analysis and complex network theory to decompose and reconstruct the original bivariate time series into sequences in a joint time-frequency domain and defined the correlation modes at each time-frequency domain. We chose the crude oil spot and futures prices as the sample data. The empirical results indicate that the main duration of volatility (32-64 days) for the strongly positive correlation between the crude oil spot price and the futures price provides more useful information for investors. Moreover, the weighted degree, weighted indegree and weighted outdegree of the correlation modes follow power-law distributions. The correlation fluctuation strengthens the extent of persistence over the long term, whereas persistence weakens over the short and medium term. The primary correlation modes dominating the transmission process and the major intermediary modes in the transmission process are clustered both in the short and long term.

  12. Theory of mind network activity is altered in subjects with familial liability for schizophrenia.

    PubMed

    Mohnke, Sebastian; Erk, Susanne; Schnell, Knut; Romanczuk-Seiferth, Nina; Schmierer, Phöbe; Romund, Lydia; Garbusow, Maria; Wackerhagen, Carolin; Ripke, Stephan; Grimm, Oliver; Haller, Leila; Witt, Stephanie H; Degenhardt, Franziska; Tost, Heike; Heinz, Andreas; Meyer-Lindenberg, Andreas; Walter, Henrik

    2016-02-01

    As evidenced by a multitude of studies, abnormalities in Theory of Mind (ToM) and its neural processing might constitute an intermediate phenotype of schizophrenia. If so, neural alterations during ToM should be observable in unaffected relatives of patients as well, since they share a considerable amount of genetic risk. While behaviorally, impaired ToM function is confirmed meta-analytically in relatives, evidence on aberrant function of the neural ToM network is sparse and inconclusive. The present study therefore aimed to further explore the neural correlates of ToM in relatives of schizophrenia. About 297 controls and 63 unaffected first-degree relatives of patients with schizophrenia performed a ToM task during functional magnetic resonance imaging. Consistent with the literature relatives exhibited decreased activity of the medial prefrontal cortex. Additionally, increased recruitment of the right middle temporal gyrus and posterior cingulate cortex was found, which was related to subclinical paranoid symptoms in relatives. These results further support decreased medial prefrontal activation during ToM as an intermediate phenotype of genetic risk for schizophrenia. Enhanced recruitment of posterior ToM areas in relatives might indicate inefficiency mechanisms in the presence of genetic risk. PMID:26341902

  13. The theory of planned behavior applied to young people's use of social networking Web sites.

    PubMed

    Pelling, Emma L; White, Katherine M

    2009-12-01

    Despite the increasing popularity of social networking Web sites (SNWs), very little is known about the psychosocial variables that predict people's use of these Web sites. The present study used an extended model of the theory of planned behavior (TPB), including the additional variables of self-identity and belongingness, to predict high-level SNW use intentions and behavior in a sample of young people ages 17 to 24 years. Additional analyses examined the impact of self-identity and belongingness on young people's addictive tendencies toward SNWs. University students (N = 233) completed measures of the standard TPB constructs (attitude, subjective norm, and perceived behavioral control), the additional predictor variables (self-identity and belongingness), demographic variables (age, gender, and past behavior), and addictive tendencies. One week later, they reported their engagement in high-level SNW use during the previous week. Regression analyses partially supported the TPB: attitude and subjective norm significantly predicted intentions to engage in high-level SNW use with intention significantly predicting behavior. Self-identity, but not belongingness, significantly contributed to the prediction of intention and, unexpectedly, behavior. Past behavior also significantly predicted intention and behavior. Self-identity and belongingness significantly predicted addictive tendencies toward SNWs. Overall, the present study revealed that high-level SNW use is influenced by attitudinal, normative, and self-identity factors, findings that can be used to inform strategies that aim to modify young people's high levels of use or addictive tendencies for SNWs. PMID:19788377

  14. A Game Theory Algorithm for Intra-Cluster Data Aggregation in a Vehicular Ad Hoc Network.

    PubMed

    Chen, Yuzhong; Weng, Shining; Guo, Wenzhong; Xiong, Naixue

    2016-01-01

    Vehicular ad hoc networks (VANETs) have an important role in urban management and planning. The effective integration of vehicle information in VANETs is critical to traffic analysis, large-scale vehicle route planning and intelligent transportation scheduling. However, given the limitations in the precision of the output information of a single sensor and the difficulty of information sharing among various sensors in a highly dynamic VANET, effectively performing data aggregation in VANETs remains a challenge. Moreover, current studies have mainly focused on data aggregation in large-scale environments but have rarely discussed the issue of intra-cluster data aggregation in VANETs. In this study, we propose a multi-player game theory algorithm for intra-cluster data aggregation in VANETs by analyzing the competitive and cooperative relationships among sensor nodes. Several sensor-centric metrics are proposed to measure the data redundancy and stability of a cluster. We then study the utility function to achieve efficient intra-cluster data aggregation by considering both data redundancy and cluster stability. In particular, we prove the existence of a unique Nash equilibrium in the game model, and conduct extensive experiments to validate the proposed algorithm. Results demonstrate that the proposed algorithm has advantages over typical data aggregation algorithms in both accuracy and efficiency. PMID:26907272

  15. A Game Theory Algorithm for Intra-Cluster Data Aggregation in a Vehicular Ad Hoc Network

    PubMed Central

    Chen, Yuzhong; Weng, Shining; Guo, Wenzhong; Xiong, Naixue

    2016-01-01

    Vehicular ad hoc networks (VANETs) have an important role in urban management and planning. The effective integration of vehicle information in VANETs is critical to traffic analysis, large-scale vehicle route planning and intelligent transportation scheduling. However, given the limitations in the precision of the output information of a single sensor and the difficulty of information sharing among various sensors in a highly dynamic VANET, effectively performing data aggregation in VANETs remains a challenge. Moreover, current studies have mainly focused on data aggregation in large-scale environments but have rarely discussed the issue of intra-cluster data aggregation in VANETs. In this study, we propose a multi-player game theory algorithm for intra-cluster data aggregation in VANETs by analyzing the competitive and cooperative relationships among sensor nodes. Several sensor-centric metrics are proposed to measure the data redundancy and stability of a cluster. We then study the utility function to achieve efficient intra-cluster data aggregation by considering both data redundancy and cluster stability. In particular, we prove the existence of a unique Nash equilibrium in the game model, and conduct extensive experiments to validate the proposed algorithm. Results demonstrate that the proposed algorithm has advantages over typical data aggregation algorithms in both accuracy and efficiency. PMID:26907272

  16. Network theory approach for data evaluation in the dynamic force spectroscopy of biomolecular interactions

    NASA Astrophysics Data System (ADS)

    Živković, J.; Mitrović, M.; Janssen, L.; Heus, H. A.; Tadić, B.; Speller, S.

    2010-03-01

    Investigations of bonds between single molecules and molecular complexes by dynamic force spectroscopy are subject to large fluctuations at nanoscale and possible aspecific binding, which mask the experimental output. Big efforts are devoted to develop methods for the effective selection of the relevant experimental data, before the quantitative analysis of bond parameters. Here we present a methodology which is based on the application of graph theory. The force-distance curves corresponding to repeated pulling events are mapped onto their correlation network (mathematical graph). On these graphs the groups of similar curves appear as topological modules, which are identified using the spectral analysis of graphs. We demonstrate the approach by analyzing a large ensemble of the force-distance curves measured on: ssDNA-ssDNA, peptide-RNA (from HIV1), and peptide-Au surface systems. Within our data sets the methodology systematically separates subgroups of curves which are related to different types of intermolecular interactions and to spatial arrangements in which the molecules are brought together and/or pulling speeds. This demonstrates the sensitivity of the method to the spatial degrees of freedom, suggesting potential applications in the case of large molecular complexes and situations with multiple binding sites.

  17. A false dichotomy? Mental illness and lone-actor terrorism.

    PubMed

    Corner, Emily; Gill, Paul

    2015-02-01

    We test whether significant differences in mental illness exist in a matched sample of lone- and group-based terrorists. We then test whether there are distinct behavioral differences between lone-actor terrorists with and without mental illness. We then stratify our sample across a range of diagnoses and again test whether significant differences exist. We conduct a series of bivariate, multivariate, and multinomial statistical tests using a unique dataset of 119 lone-actor terrorists and a matched sample of group-based terrorists. The odds of a lone-actor terrorist having a mental illness is 13.49 times higher than the odds of a group actor having a mental illness. Lone actors who were mentally ill were 18.07 times more likely to have a spouse or partner who was involved in a wider movement than those without a history of mental illness. Those with a mental illness were more likely to have a proximate upcoming life change, more likely to have been a recent victim of prejudice, and experienced proximate and chronic stress. The results identify behaviors and traits that security agencies can utilize to monitor and prevent lone-actor terrorism events. The correlated behaviors provide an image of how risk can crystalize within the individual offender and that our understanding of lone-actor terrorism should be multivariate in nature. PMID:25133916

  18. [The emergence and institutionalization of sexology in Portugal: processes, actors, and specificities].

    PubMed

    Alarcão, Violeta; Machado, Fernando Luís; Giami, Alain

    2016-01-01

    Based on Bourdieu's field theory, this article analyzes the emergence and institutionalization of sexology as a science and profession in Portugal, identifying relevant institutions, actors, and professional practices and discussing its relations and specificities. The analysis begins by contextualizing the emergence of modern Western sexology in order to comprehend the Portuguese case in the international sexology context. The second section describes the social, cultural, and institutional factors that have driven the professionalization of sexology. The third section describes the emergence of Portuguese sexology and its principal historical milestones, institutions, and actors. Finally, the article discusses some implications of this process for the role of sexology as a science and profession. The study reveals the dynamics of national and international processes in the field, in the transition from a holistic perspective of sexology to the hegemony of sexual medicine, and sheds light on its mechanisms of legitimation as a transdisciplinary science of sexuality, suggesting future perspectives. PMID:27598015

  19. Computer generation of symbolic network functions - A new theory and implementation.

    NASA Technical Reports Server (NTRS)

    Alderson, G. E.; Lin, P.-M.

    1972-01-01

    A new method is presented for obtaining network functions in which some, none, or all of the network elements are represented by symbolic parameters (i.e., symbolic network functions). Unlike the topological tree enumeration or signal flow graph methods generally used to derive symbolic network functions, the proposed procedure employs fast, efficient, numerical-type algorithms to determine the contribution of those network branches that are not represented by symbolic parameters. A computer program called NAPPE (for Network Analysis Program using Parameter Extractions) and incorporating all of the concepts discussed has been written. Several examples illustrating the usefulness and efficiency of NAPPE are presented.

  20. Analyzing the evolutionary mechanisms of the Air Transportation System-of-Systems using network theory and machine learning algorithms

    NASA Astrophysics Data System (ADS)

    Kotegawa, Tatsuya

    Complexity in the Air Transportation System (ATS) arises from the intermingling of many independent physical resources, operational paradigms, and stakeholder interests, as well as the dynamic variation of these interactions over time. Currently, trade-offs and cost benefit analyses of new ATS concepts are carried out on system-wide evaluation simulations driven by air traffic forecasts that assume fixed airline routes. However, this does not well reflect reality as airlines regularly add and remove routes. A airline service route network evolution model that projects route addition and removal was created and combined with state-of-the-art air traffic forecast methods to better reflect the dynamic properties of the ATS in system-wide simulations. Guided by a system-of-systems framework, network theory metrics and machine learning algorithms were applied to develop the route network evolution models based on patterns extracted from historical data. Constructing the route addition section of the model posed the greatest challenge due to the large pool of new link candidates compared to the actual number of routes historically added to the network. Of the models explored, algorithms based on logistic regression, random forests, and support vector machines showed best route addition and removal forecast accuracies at approximately 20% and 40%, respectively, when validated with historical data. The combination of network evolution models and a system-wide evaluation tool quantified the impact of airline route network evolution on air traffic delay. The expected delay minutes when considering network evolution increased approximately 5% for a forecasted schedule on 3/19/2020. Performance trade-off studies between several airline route network topologies from the perspectives of passenger travel efficiency, fuel burn, and robustness were also conducted to provide bounds that could serve as targets for ATS transformation efforts. The series of analysis revealed that high

  1. Whose Journey Is It? A Critic's Plea to Actors.

    ERIC Educational Resources Information Center

    Lasser, Michael

    1999-01-01

    Laments the narcissism that the author sees in too many contemporary approaches to acting and directing. Argues that actors must focus on the world outside themselves, where the play and the audience most need them to be. (SR)

  2. Efficient model learning methods for actor-critic control.

    PubMed

    Grondman, Ivo; Vaandrager, Maarten; Buşoniu, Lucian; Babuska, Robert; Schuitema, Erik

    2012-06-01

    We propose two new actor-critic algorithms for reinforcement learning. Both algorithms use local linear regression (LLR) to learn approximations of the functions involved. A crucial feature of the algorithms is that they also learn a process model, and this, in combination with LLR, provides an efficient policy update for faster learning. The first algorithm uses a novel model-based update rule for the actor parameters. The second algorithm does not use an explicit actor but learns a reference model which represents a desired behavior, from which desired control actions can be calculated using the inverse of the learned process model. The two novel methods and a standard actor-critic algorithm are applied to the pendulum swing-up problem, in which the novel methods achieve faster learning than the standard algorithm. PMID:22156998

  3. ACToR A Aggregated Computational Toxicology Resource

    EPA Science Inventory

    We are developing the ACToR system (Aggregated Computational Toxicology Resource) to serve as a repository for a variety of types of chemical, biological and toxicological data that can be used for predictive modeling of chemical toxicology.

  4. 29 CFR 570.125 - Actors and performers.

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ... an actor or performer in motion pictures or theatrical productions, or in radio or television... definition will be helpful in determining whether a child qualifies as a “* * * performer in motion...

  5. ACToR A Aggregated Computational Toxicology Resource (S)

    EPA Science Inventory

    We are developing the ACToR system (Aggregated Computational Toxicology Resource) to serve as a repository for a variety of types of chemical, biological and toxicological data that can be used for predictive modeling of chemical toxicology.

  6. Some problems of the qualitative Sturm-Liouville theory on a spatial network

    NASA Astrophysics Data System (ADS)

    Pokornyi, Yu V.; Pryadiev, V. L.

    2004-06-01

    An analogue of the Sturm oscillation theory of the distribution of the zeros of eigenfunctions is constructed for the problem \\displaystyle Lu\\overset{\\text{def}}{=}-\\frac d{d\\Gamma}(pu')+qu=\\lambda mu, \\qquadu\\big\\vert _{\\partial\\Gamma}=0(*) on a spatial network \\Gamma (in other terms, \\Gamma is a metric graph, a CW complex, a stratified locally one-dimensional manifold, a branching space, a quantum graph, and so on), where \\partial\\Gamma is the family of boundary vertices of \\Gamma. At interior points of the edges of \\Gamma the quasi-derivative \\displaystyle\\frac d{d\\Gamma}(pu') has the classical form (pu')', and at interior nodes it is assumed that \\displaystyle \\frac d{d\\Gamma}(pu')=-\\sum_\\gamma\\alpha_\\gamma(a)u'_\\gamma(a), where the summation is taken over the edges \\gamma incident to the node a and, for an edge \\gamma, u'_\\gamma (a) stands for the `endpoint' derivative of the restriction u_\\gamma (x) of the function u\\colon\\Gamma\\to\\mathbb R to \\gamma. Despite the branching argument, which is a kind of intermediate type between the one-dimensional and multidimensional cases, the outward form of the results turns out to be quite classical. The classical nature of the operator L is clarified, and exact analogues of the maximum principle and of the Sturm theorem on alternation of zeros are established, together with the sign-regular oscillation properties of the spectrum of the problem (*) (including the simplicity and positivity of the points of the spectrum and also the number of zeros and their alternation for the eigenfunctions).

  7. Reconsidering Stanislavsky: Feeling, Feminism, and the Actor.

    ERIC Educational Resources Information Center

    Blair, Rhonda

    2002-01-01

    Comments on the mistrustful attitude toward feeling and the biological body in feminist theories of performance. Proposes that recent developments in cognitive neuroscience and neurophysiology can provide a way to reengage issues of feeling, consciousness and performance. Calls for feminists to reconsider not only Stanislavsky-based approaches to…

  8. Structure and role of metal clusters in a metal-organic coordination network determined by density functional theory

    NASA Astrophysics Data System (ADS)

    Svane, K. L.; Linderoth, T. R.; Hammer, B.

    2016-02-01

    We present a comprehensive theoretical investigation of the structures formed by self-assembly of tetrahydroxybenzene (THB)-derivatives on Cu(111). The THB molecule is known to dehydrogenate completely during annealing, forming a reactive radical which assembles into a close-packed structure or a porous metal-coordinated network depending on the coverage of the system. Here, we present details on how the structures are determined by density functional theory calculations, using scanning tunneling microscopy-derived information on the periodicity. The porous network is based on adatom trimers. By analysing the charge distribution of the structure, it is found that this unusual coordination motif is preferred because it simultaneously provides a good coordination of all oxygen atoms and allows for the formation of a two-dimensional network on the surface.

  9. Current Understanding of the Formation and Adaptation of Metabolic Systems Based on Network Theory

    PubMed Central

    Takemoto, Kazuhiro

    2012-01-01

    Formation and adaptation of metabolic networks has been a long-standing question in biology. With recent developments in biotechnology and bioinformatics, the understanding of metabolism is progressively becoming clearer from a network perspective. This review introduces the comprehensive metabolic world that has been revealed by a wide range of data analyses and theoretical studies; in particular, it illustrates the role of evolutionary events, such as gene duplication and horizontal gene transfer, and environmental factors, such as nutrient availability and growth conditions, in evolution of the metabolic network. Furthermore, the mathematical models for the formation and adaptation of metabolic networks have also been described, according to the current understanding from a perspective of metabolic networks. These recent findings are helpful in not only understanding the formation of metabolic networks and their adaptation, but also metabolic engineering. PMID:24957641

  10. Humanoids Learning to Walk: A Natural CPG-Actor-Critic Architecture.

    PubMed

    Li, Cai; Lowe, Robert; Ziemke, Tom

    2013-01-01

    The identification of learning mechanisms for locomotion has been the subject of much research for some time but many challenges remain. Dynamic systems theory (DST) offers a novel approach to humanoid learning through environmental interaction. Reinforcement learning (RL) has offered a promising method to adaptively link the dynamic system to the environment it interacts with via a reward-based value system. In this paper, we propose a model that integrates the above perspectives and applies it to the case of a humanoid (NAO) robot learning to walk the ability of which emerges from its value-based interaction with the environment. In the model, a simplified central pattern generator (CPG) architecture inspired by neuroscientific research and DST is integrated with an actor-critic approach to RL (cpg-actor-critic). In the cpg-actor-critic architecture, least-square-temporal-difference based learning converges to the optimal solution quickly by using natural gradient learning and balancing exploration and exploitation. Futhermore, rather than using a traditional (designer-specified) reward it uses a dynamic value function as a stability indicator that adapts to the environment. The results obtained are analyzed using a novel DST-based embodied cognition approach. Learning to walk, from this perspective, is a process of integrating levels of sensorimotor activity and value. PMID:23675345

  11. Humanoids Learning to Walk: A Natural CPG-Actor-Critic Architecture

    PubMed Central

    Li, Cai; Lowe, Robert; Ziemke, Tom

    2013-01-01

    The identification of learning mechanisms for locomotion has been the subject of much research for some time but many challenges remain. Dynamic systems theory (DST) offers a novel approach to humanoid learning through environmental interaction. Reinforcement learning (RL) has offered a promising method to adaptively link the dynamic system to the environment it interacts with via a reward-based value system. In this paper, we propose a model that integrates the above perspectives and applies it to the case of a humanoid (NAO) robot learning to walk the ability of which emerges from its value-based interaction with the environment. In the model, a simplified central pattern generator (CPG) architecture inspired by neuroscientific research and DST is integrated with an actor-critic approach to RL (cpg-actor-critic). In the cpg-actor-critic architecture, least-square-temporal-difference based learning converges to the optimal solution quickly by using natural gradient learning and balancing exploration and exploitation. Futhermore, rather than using a traditional (designer-specified) reward it uses a dynamic value function as a stability indicator that adapts to the environment. The results obtained are analyzed using a novel DST-based embodied cognition approach. Learning to walk, from this perspective, is a process of integrating levels of sensorimotor activity and value. PMID:23675345

  12. A Perron-Frobenius theory for block matrices associated to a multiplex network

    NASA Astrophysics Data System (ADS)

    Romance, Miguel; Solá, Luis; Flores, Julio; García, Esther; García del Amo, Alejandro; Criado, Regino

    2015-03-01

    The uniqueness of the Perron vector of a nonnegative block matrix associated to a multiplex network is discussed. The conclusions come from the relationships between the irreducibility of some nonnegative block matrix associated to a multiplex network and the irreducibility of the corresponding matrices to each layer as well as the irreducibility of the adjacency matrix of the projection network. In addition the computation of that Perron vector in terms of the Perron vectors of the blocks is also addressed. Finally we present the precise relations that allow to express the Perron eigenvector of the multiplex network in terms of the Perron eigenvectors of its layers.

  13. The Application of Imperialist Competitive Algorithm based on Chaos Theory in Perceptron Neural Network

    NASA Astrophysics Data System (ADS)

    Zhang, Xiuping

    In this paper, the weights of a Neural Network using Chaotic Imperialist Competitive Algorithm are updated. A three-layered Perseptron Neural Network applied for prediction of the maximum worth of the stocks changed in TEHRAN's bourse market. We trained this neural network with CICA, ICA, PSO and GA algorithms and compared the results with each other. The consideration of the results showed that the training and test error of the network trained by the CICA algorithm has been reduced in comparison to the other three methods.

  14. The Role of Social Networking Services in eParticipation

    NASA Astrophysics Data System (ADS)

    Sæbø, Øystein; Rose, Jeremy; Nyvang, Tom

    A serious problem in eParticipation projects is citizen engagement - citizens do not necessarily become more willing to participate simply because net-services are provided for them. Most forms of eParticipation in democratic contexts are, however, dependent on citizen engagement, interaction and social networking because democratic systems favour the interests of larger groups of citizens - the more voices behind a political proposition, the greater its chances of success. In this context of challenges the study of social networking on the internet and social network theory offers valuable insights into the practices and theories of citizen engagement. Social network theory focuses on the chains of relationships that social actors communicate and act within. Some social networking services on the internet attract large numbers of users, and apparently sustain a great deal of interaction, content-generation and the development of loosely-coupled communities. They provide the forum for much discussion and interaction. In this respect social networking could contribute to solve some of the problems of engaging their users that eParticipation services often struggle with. This paper investigates the potential of Social Networking Services for the eParticipation area by defining social networking services, introducing the driving forces behind their advance, and discusses the potential use of social networking software in the eParticipation context.

  15. Food-web structure and network theory: The role of connectance and size

    NASA Astrophysics Data System (ADS)

    Dunne, Jennifer A.; Williams, Richard J.; Martinez, Neo D.

    2002-10-01

    Networks from a wide range of physical, biological, and social systems have been recently described as "small-world" and "scale-free." However, studies disagree whether ecological networks called food webs possess the characteristic path lengths, clustering coefficients, and degree distributions required for membership in these classes of networks. Our analysis suggests that the disagreements are based on selective use of relatively few food webs, as well as analytical decisions that obscure important variability in the data. We analyze a broad range of 16 high-quality food webs, with 25-172 nodes, from a variety of aquatic and terrestrial ecosystems. Food webs generally have much higher complexity, measured as connectance (the fraction of all possible links that are realized in a network), and much smaller size than other networks studied, which have important implications for network topology. Our results resolve prior conflicts by demonstrating that although some food webs have small-world and scale-free structure, most do not if they exceed a relatively low level of connectance. Although food-web degree distributions do not display a universal functional form, observed distributions are systematically related to network connectance and size. Also, although food webs often lack small-world structure because of low clustering, we identify a continuum of real-world networks including food webs whose ratios of observed to random clustering coefficients increase as a power-law function of network size over 7 orders of magnitude. Although food webs are generally not small-world, scale-free networks, food-web topology is consistent with patterns found within those classes of networks.

  16. Construction of citrus gene coexpression networks from microarray data using random matrix theory.

    PubMed

    Du, Dongliang; Rawat, Nidhi; Deng, Zhanao; Gmitter, Fred G

    2015-01-01

    After the sequencing of citrus genomes, gene function annotation is becoming a new challenge. Gene coexpression analysis can be employed for function annotation using publicly available microarray data sets. In this study, 230 sweet orange (Citrus sinensis) microarrays were used to construct seven coexpression networks, including one condition-independent and six condition-dependent (Citrus canker, Huanglongbing, leaves, flavedo, albedo, and flesh) networks. In total, these networks contain 37 633 edges among 6256 nodes (genes), which accounts for 52.11% measurable genes of the citrus microarray. Then, these networks were partitioned into functional modules using the Markov Cluster Algorithm. Significantly enriched Gene Ontology biological process terms and KEGG pathway terms were detected for 343 and 60 modules, respectively. Finally, independent verification of these networks was performed using another expression data of 371 genes. This study provides new targets for further functional analyses in citrus. PMID:26504573

  17. Combining Partial Directed Coherence and Graph Theory to Analyse Effective Brain Networks of Different Mental Tasks

    PubMed Central

    Huang, Dengfeng; Ren, Aifeng; Shang, Jing; Lei, Qiao; Zhang, Yun; Yin, Zhongliang; Li, Jun; von Deneen, Karen M.; Huang, Liyu

    2016-01-01

    Purpose: The aim of this study is to qualify the network properties of the brain networks between two different mental tasks (play task or rest task) in a healthy population. Methods and Materials: EEG signals were recorded from 19 healthy subjects when performing different mental tasks. Partial directed coherence (PDC) analysis, based on Granger causality (GC), was used to assess the effective brain networks during the different mental tasks. Moreover, the network measures, including degree, degree distribution, local and global efficiency in delta, theta, alpha, and beta rhythms were calculated and analyzed. Results: The local efficiency is higher in the beta frequency and lower in the theta frequency during play task whereas the global efficiency is higher in the theta frequency and lower in the beta frequency in the rest task. Significance: This study reveals the network measures during different mental states and efficiency measures may be used as characteristic quantities for improvement in attentional performance. PMID:27242495

  18. Metabolic reconstruction, constraint-based analysis and game theory to probe genome-scale metabolic networks.

    PubMed

    Ruppin, Eytan; Papin, Jason A; de Figueiredo, Luis F; Schuster, Stefan

    2010-08-01

    With the advent of modern omics technologies, it has become feasible to reconstruct (quasi-) whole-cell metabolic networks and characterize them in more and more detail. Computer simulations of the dynamic behavior of such networks are difficult due to a lack of kinetic data and to computational limitations. In contrast, network analysis based on appropriate constraints such as the steady-state condition (constraint-based analysis) is feasible and allows one to derive conclusions about the system's metabolic capabilities. Here, we review methods for the reconstruction of metabolic networks, modeling techniques such as flux balance analysis and elementary flux modes and current progress in their development and applications. Game-theoretical methods for studying metabolic networks are discussed as well. PMID:20692823

  19. Construction of citrus gene coexpression networks from microarray data using random matrix theory

    PubMed Central

    Du, Dongliang; Rawat, Nidhi; Deng, Zhanao; Gmitter, Fred G.

    2015-01-01

    After the sequencing of citrus genomes, gene function annotation is becoming a new challenge. Gene coexpression analysis can be employed for function annotation using publicly available microarray data sets. In this study, 230 sweet orange (Citrus sinensis) microarrays were used to construct seven coexpression networks, including one condition-independent and six condition-dependent (Citrus canker, Huanglongbing, leaves, flavedo, albedo, and flesh) networks. In total, these networks contain 37 633 edges among 6256 nodes (genes), which accounts for 52.11% measurable genes of the citrus microarray. Then, these networks were partitioned into functional modules using the Markov Cluster Algorithm. Significantly enriched Gene Ontology biological process terms and KEGG pathway terms were detected for 343 and 60 modules, respectively. Finally, independent verification of these networks was performed using another expression data of 371 genes. This study provides new targets for further functional analyses in citrus. PMID:26504573

  20. Hybrid protection algorithms based on game theory in multi-domain optical networks

    NASA Astrophysics Data System (ADS)

    Guo, Lei; Wu, Jingjing; Hou, Weigang; Liu, Yejun; Zhang, Lincong; Li, Hongming

    2011-12-01

    With the network size increasing, the optical backbone is divided into multiple domains and each domain has its own network operator and management policy. At the same time, the failures in optical network may lead to a huge data loss since each wavelength carries a lot of traffic. Therefore, the survivability in multi-domain optical network is very important. However, existing survivable algorithms can achieve only the unilateral optimization for profit of either users or network operators. Then, they cannot well find the double-win optimal solution with considering economic factors for both users and network operators. Thus, in this paper we develop the multi-domain network model with involving multiple Quality of Service (QoS) parameters. After presenting the link evaluation approach based on fuzzy mathematics, we propose the game model to find the optimal solution to maximize the user's utility, the network operator's utility, and the joint utility of user and network operator. Since the problem of finding double-win optimal solution is NP-complete, we propose two new hybrid protection algorithms, Intra-domain Sub-path Protection (ISP) algorithm and Inter-domain End-to-end Protection (IEP) algorithm. In ISP and IEP, the hybrid protection means that the intelligent algorithm based on Bacterial Colony Optimization (BCO) and the heuristic algorithm are used to solve the survivability in intra-domain routing and inter-domain routing, respectively. Simulation results show that ISP and IEP have the similar comprehensive utility. In addition, ISP has better resource utilization efficiency, lower blocking probability, and higher network operator's utility, while IEP has better user's utility.

  1. Semantic network mapping of religious material: testing multi-agent computer models of social theories against real-world data.

    PubMed

    Lane, Justin E

    2015-11-01

    Agent-based modeling allows researchers to investigate theories of complex social phenomena and subsequently use the model to generate new hypotheses that can then be compared to real-world data. However, computer modeling has been underutilized in regard to the understanding of religious systems, which often require very complex theories with multiple interacting variables (Braxton et al. in Method Theory Study Relig 24(3):267-290, 2012. doi: 10.1163/157006812X635709 ; Lane in J Cogn Sci Relig 1(2):161-180, 2013). This paper presents an example of how computer modeling can be used to explore, test, and further understand religious systems, specifically looking at one prominent theory of religious ritual. The process is continuous: theory building, hypothesis generation, testing against real-world data, and improving the model. In this example, the output of an agent-based model of religious behavior is compared against real-world religious sermons and texts using semantic network analysis. It finds that most religious materials exhibit unique scale-free small-world properties and that a concept's centrality in a religious schema best predicts its frequency of presentation. These results reveal that there adjustments need to be made to existing models of religious ritual systems and provide parameters for future models. The paper ends with a discussion of implications for a new multi-agent model of doctrinal ritual behaviors as well as propositions for further interdisciplinary research concerning the multi-agent modeling of religious ritual behaviors. PMID:25851082

  2. A finite-size ergodic theory of stable chaos for quantifying information processing in balanced state networks of spiking neurons

    NASA Astrophysics Data System (ADS)

    Puelma Touzel, Maximilian; Monteforte, Michael; Wolf, Fred

    2015-03-01

    The stability of a dynamics constrains its ability to process information, a notion intended to be captured by the ergodic theory of chaos and one likely to be important for neuroscience. Asynchronous, irregular network activity can be produced by models in which excitatory and inhibitory inputs are balanced. For negative and sharply pulsed interactions, these networks turn out to be stable. The coexistence of aperiodic activity and stability is called stable chaos. This stability to perturbations only exists up to some finite average strength beyond which they are unstable. This finite-size instability produces entropy not captured by conventional ergodic theory. We derive and use the probability of divergence as a function of perturbation strength to give an expression for a finite-sized analogue of the Kolmolgorov-Sinai (KS) entropy that scales with the perturbation strength, and thus deviates from the conventional KS entropy value of 0. This work provides a foundation for understanding the information processing capacity of networks in the fast synapse, fast action potential onset, and inhibition-dominated regime.

  3. A trust evaluation algorithm for wireless sensor networks based on node behaviors and D-S evidence theory.

    PubMed

    Feng, Renjian; Xu, Xiaofeng; Zhou, Xiang; Wan, Jiangwen

    2011-01-01

    For wireless sensor networks (WSNs), many factors, such as mutual interference of wireless links, battlefield applications and nodes exposed to the environment without good physical protection, result in the sensor nodes being more vulnerable to be attacked and compromised. In order to address this network security problem, a novel trust evaluation algorithm defined as NBBTE (Node Behavioral Strategies Banding Belief Theory of the Trust Evaluation Algorithm) is proposed, which integrates the approach of nodes behavioral strategies and modified evidence theory. According to the behaviors of sensor nodes, a variety of trust factors and coefficients related to the network application are established to obtain direct and indirect trust values through calculating weighted average of trust factors. Meanwhile, the fuzzy set method is applied to form the basic input vector of evidence. On this basis, the evidence difference is calculated between the indirect and direct trust values, which link the revised D-S evidence combination rule to finally synthesize integrated trust value of nodes. The simulation results show that NBBTE can effectively identify malicious nodes and reflects the characteristic of trust value that 'hard to acquire and easy to lose'. Furthermore, it is obvious that the proposed scheme has an outstanding advantage in terms of illustrating the real contribution of different nodes to trust evaluation. PMID:22319355

  4. A Trust Evaluation Algorithm for Wireless Sensor Networks Based on Node Behaviors and D-S Evidence Theory

    PubMed Central

    Feng, Renjian; Xu, Xiaofeng; Zhou, Xiang; Wan, Jiangwen

    2011-01-01

    For wireless sensor networks (WSNs), many factors, such as mutual interference of wireless links, battlefield applications and nodes exposed to the environment without good physical protection, result in the sensor nodes being more vulnerable to be attacked and compromised. In order to address this network security problem, a novel trust evaluation algorithm defined as NBBTE (Node Behavioral Strategies Banding Belief Theory of the Trust Evaluation Algorithm) is proposed, which integrates the approach of nodes behavioral strategies and modified evidence theory. According to the behaviors of sensor nodes, a variety of trust factors and coefficients related to the network application are established to obtain direct and indirect trust values through calculating weighted average of trust factors. Meanwhile, the fuzzy set method is applied to form the basic input vector of evidence. On this basis, the evidence difference is calculated between the indirect and direct trust values, which link the revised D-S evidence combination rule to finally synthesize integrated trust value of nodes. The simulation results show that NBBTE can effectively identify malicious nodes and reflects the characteristic of trust value that ‘hard to acquire and easy to lose’. Furthermore, it is obvious that the proposed scheme has an outstanding advantage in terms of illustrating the real contribution of different nodes to trust evaluation. PMID:22319355

  5. Applying the Uses and Gratifications Theory to Compare Higher Education Students' Motivation for Using Social Networking Sites: Experiences from Iran, Malaysia, United Kingdom, and South Africa

    ERIC Educational Resources Information Center

    Karimi, Leila; Khodabandelou, Rouhollah; Ehsani, Maryam; Ahmad, Muhammad

    2014-01-01

    Drawing from the Uses and Gratifications Theory, this study examined the Gratification Sought and the Gratification Obtained from using Social Networking Sites among Iranian, Malaysian, British, and South African higher education students. This comparison allowed to drawing conclusions about how social networking sites fulfill users' needs with…

  6. First principles and effective theory approaches to dynamics of complex networks

    NASA Astrophysics Data System (ADS)

    Dehmamy, Nima

    This dissertation concerns modeling two aspects of dynamics of complex networks: (1) response dynamics and (2) growth and formation. A particularly challenging class of networks are ones in which both nodes and links are evolving over time -- the most prominent example is a financial network. In the first part of the dissertation we present a model for the response dynamics in networks near a metastable point. We start with a Landau-Ginzburg approach and show that the most general lowest order Lagrangians for dynamical weighted networks can be used to derive conditions for stability under external shocks. Using a closely related model, which is easier to solve numerically, we propose a powerful and intuitive set of equations for response dynamics of financial networks. We find the stability conditions of the model and find two phases: "calm" phase , in which changes are sub-exponential and where the system moves to a new, close-by equilibrium; "frantic" phase, where changes are exponential, with negative blows resulting in crashes and positive ones leading to formation of "bubbles". We empirically verify these claims by analyzing data from Eurozone crisis of 2009-2012 and stock markets. We show that the model correctly identifies the time-line of the Eurozone crisis, and in the stock market data it correctly reproduces the auto-correlations and phases observed in the data. The second half of the dissertation addresses the following question: Do networks that form due to local interactions (local in real space, or in an abstract parameter space) have characteristics different from networks formed of random or non-local interactions? Using interacting fields obeying Fokker-Planck equations we show that many network characteristics such as degree distribution, degree-degree correlation and clustering can either be derived analytically or there are analytical bounds on their behaviour. In particular, we derive recursive equations for all powers of the ensemble average

  7. Performance evaluation of a simulated data-flow computer with low-resolution actors

    SciTech Connect

    Gaudiot, J.L.; Ercegovac, M.D.

    1985-11-01

    In the ambition to go beyond a single-processor architecture, to enhance programmability, and to take advantage of the power brought by VLSI devices, data-flow systems and languages were devised. Indeed, due to their functional semantics, these languages offer promise in the area of multiprocessor systems design and will possibly enable the development of computers comprising large numbers of processors with a corresponding increase in performance. Several important design problems have to be surmounted and are described here. The authors thus present a ''variable-resolution'' scheme, where the level of primitives can be selected so that the overhead due to the data-flow mode of operation is reduced. A deterministic simulation of a data-flow machine with a variable number of processing elements was undertaken and is described here. The tests were performed using various program structures such as directed acyclic graphs, vector operations, and array handling. The performance results observed confirm the advantage of actors with variable size and indicate the presence of a trade-off between overhead control and the need to control parallelism in the program. The authors also look at some of the communication issues and examine the effect of several interconnection networks (dual counter-rotating rings, daisy chain, and optimal double loop network) on the performance. It is shown how increasing communication costs induce a performance degradation that can be masked when the size of the basic data-flow actor is increased. The associative memory cycle time is also changed with similar conclusions. Finally, the lower-resolution scheme is applied to the array handling case; the observations confirm the advantage of a more complex actor at the array level.

  8. Network science and the human brain: Using graph theory to understand the brain and one of its hubs, the amygdala, in health and disease.

    PubMed

    Mears, David; Pollard, Harvey B

    2016-06-01

    Over the past 15 years, the emerging field of network science has revealed the key features of brain networks, which include small-world topology, the presence of highly connected hubs, and hierarchical modularity. The value of network studies of the brain is underscored by the range of network alterations that have been identified in neurological and psychiatric disorders, including epilepsy, depression, Alzheimer's disease, schizophrenia, and many others. Here we briefly summarize the concepts of graph theory that are used to quantify network properties and describe common experimental approaches for analysis of brain networks of structural and functional connectivity. These range from tract tracing to functional magnetic resonance imaging, diffusion tensor imaging, electroencephalography, and magnetoencephalography. We then summarize the major findings from the application of graph theory to nervous systems ranging from Caenorhabditis elegans to more complex primate brains, including man. Focusing, then, on studies involving the amygdala, a brain region that has attracted intense interest as a center for emotional processing, fear, and motivation, we discuss the features of the amygdala in brain networks for fear conditioning and emotional perception. Finally, to highlight the utility of graph theory for studying dysfunction of the amygdala in mental illness, we review data with regard to changes in the hub properties of the amygdala in brain networks of patients with depression. We suggest that network studies of the human brain may serve to focus attention on regions and connections that act as principal drivers and controllers of brain function in health and disease. PMID:26771046

  9. Two-actor conflict with time delay: A dynamical model

    NASA Astrophysics Data System (ADS)

    Qubbaj, Murad R.; Muneepeerakul, Rachata

    2012-11-01

    Recent mathematical dynamical models of the conflict between two different actors, be they nations, groups, or individuals, have been developed that are capable of predicting various outcomes depending on the chosen feedback strategies, initial conditions, and the previous states of the actors. In addition to these factors, this paper examines the effect of time delayed feedback on the conflict dynamics. Our analysis shows that under certain initial and feedback conditions, a stable neutral equilibrium of conflict may destabilize for some critical values of time delay, and the two actors may evolve to new emotional states. We investigate the results by constructing critical delay surfaces for different sets of parameters and analyzing results from numerical simulations. These results provide new insights regarding conflict and conflict resolution and may help planners in adjusting and assessing their strategic decisions.

  10. Queuing Theory Based Co-Channel Interference Analysis Approach for High-Density Wireless Local Area Networks.

    PubMed

    Zhang, Jie; Han, Guangjie; Qian, Yujie

    2016-01-01

    Increased co-channel interference (CCI) in wireless local area networks (WLANs) is bringing serious resource constraints to today's high-density wireless environments. CCI in IEEE 802.11-based networks is inevitable due to the nature of the carrier sensing mechanism however can be reduced by resource optimization approaches. That means the CCI analysis is basic, but also crucial for an efficient resource management. In this article, we present a novel CCI analysis approach based on the queuing theory, which considers the randomness of end users' behavior and the irregularity and complexity of network traffic in high-density WLANs that adopts the M/M/c queuing model for CCI analysis. Most of the CCIs occur when multiple networks overlap and trigger channel contentions; therefore, we use the ratio of signal-overlapped areas to signal coverage as a probabilistic factor to the queuing model to analyze the CCI impacts in highly overlapped WLANs. With the queuing model, we perform simulations to see how the CCI influences the quality of service (QoS) in high-density WLANs. PMID:27563896

  11. Principal curves for lumen center extraction and flow channel width estimation in 3-D arterial networks: theory, algorithm, and validation.

    PubMed

    Wong, Wilbur C K; So, Ronald W K; Chung, Albert C S

    2012-04-01

    We present an energy-minimization-based framework for locating the centerline and estimating the width of tubelike objects from their structural network with a nonparametric model. The nonparametric representation promotes simple modeling of nested branches and n -way furcations, i.e., structures that abound in an arterial network, e.g., a cerebrovascular circulation. Our method is capable of extracting the entire vascular tree from an angiogram in a single execution with a proper initialization. A succinct initial model from the user with arterial network inlets, outlets, and branching points is sufficient for complex vasculature. The novel method is based upon the theory of principal curves. In this paper, theoretical extension to grayscale angiography is discussed, and an algorithm to find an arterial network as principal curves is also described. Quantitative validation on a number of simulated data sets, synthetic volumes of 19 BrainWeb vascular models, and 32 Rotterdam Coronary Artery volumes was conducted. We compared the algorithm to a state-of-the-art method and further tested it on two clinical data sets. Our algorithmic outputs-lumen centers and flow channel widths-are important to various medical and clinical applications, e.g., vasculature segmentation, registration and visualization, virtual angioscopy, and vascular atlas formation and population study. PMID:22167625

  12. A Lagrangian Formulation of Neural Networks I: Theory and Analog Dynamics

    NASA Technical Reports Server (NTRS)

    Mjolsness, Eric; Miranker, Willard L.

    1997-01-01

    We expand the mathematicla apparatus for relaxation networks, which conventionally consists of an objective function E and a dynamics given by a system of differenctial equations along whose trajectories E is diminished.

  13. Modelling and analysis of gene regulatory network using feedback control theory

    NASA Astrophysics Data System (ADS)

    El-Samad, H.; Khammash, M.

    2010-01-01

    Molecular pathways are a part of a remarkable hierarchy of regulatory networks that operate at all levels of organisation. These regulatory networks are responsible for much of the biological complexity within the cell. The dynamic character of these pathways and the prevalence of feedback regulation strategies in their operation make them amenable to systematic mathematical analysis using the same tools that have been used with success in analysing and designing engineering control systems. In this article, we aim at establishing this strong connection through various examples where the behaviour exhibited by gene networks is explained in terms of their underlying control strategies. We complement our analysis by a survey of mathematical techniques commonly used to model gene regulatory networks and analyse their dynamic behaviour.

  14. Generalized synchronization in the complex network: theory and applications to epileptic brain

    NASA Astrophysics Data System (ADS)

    Moskalenko, Olga I.; Pivovarov, Anatoly A.; Pavlov, Alexey N.; Koronovskii, Alexey A.; Khramova, Marina V.; Hramov, Alexander E.

    2016-04-01

    Generalized synchronization in complex networks with chaotic dynamical systems being in their nodes has been studied. The synchronous regime is shown to be detected by the sign-change of the second positive Lyapunov exponent of the network or by the nearest neighbor method. The same method is shown to be applied for the detection of the synchronous regime between the different fields of epileptic brain.

  15. Using theories of action to guide national program evaluation and local strategy in the community care network demonstration.

    PubMed

    Sofaer, Shoshanna; Bazzoli, Gloria J; Alexander, Jeffrey A; Conrad, Douglas A; Hasnain-Wynia, Romana; Shortell, Stephen M; Margolin, Frances; Pittman, Mary; Casey, Elizabeth; Ladenheim, Kala; Mauery, D Richard; Zukoski, Ann P

    2003-12-01

    Evaluations of multisite community-based projects are notoriously difficult to conceptualize and conduct. Projects may share an overarching vision but operate in varying contexts and pursue different initiatives. One tool that can assist evaluators facing these challenges is to develop a "theory of action" (TOA) that identifies critical assumptions regarding how a program expects to achieve its goals. Community Care Network (CCN) evaluators used the TOA to refine research questions, define key variables, relate questions to each other, and identify when we might realistically expect to observe answers. In this article, the authors present their national-level CCN TOA. They also worked with sites to help them "surface" their local TOA; the article analyzes the results to determine the content, clarity, extent of evidence base, and strategic orientation of theories articulated by different sites. PMID:14687428

  16. Working the network: Initiating a new science and technology course

    NASA Astrophysics Data System (ADS)

    Hepburn, Gary Roy

    1997-12-01

    This study explores the introduction of a new applied physics course into a British Columbia high school during the 1994-1995 school year. The course was part of a provincial effort aimed at making science and technology education more responsive to the workplace. Data collection took place during the first year the applied physics course was being piloted at the school and focused on the pilot teacher and the applied physics classes, but also involved others inside and outside the school who had a connection to the course. A variety of methods were used in data collection including interviews, observation, and document analysis. Using actor-network theory and sociocultural theory, the focus of the research is on the networks that were constructed at the pilot school and at the provincial level where the course was conceptualized and developed. The research describes how the teacher and other network builders attempted to enroll various human and nonhuman actors into the networks they were constructing in support of the course. They did this by convincing the actors that the course was compatible with their interests. The types of actors that were enrolled, the sociocultural communities they belonged to, and what it took to convince them to support the course are shown to shape the way that the course was enacted in the classroom. In addition, it is demonstrated that the network that was constructed at the provincial level had only a minor connection to the one the teacher was constructing at the school level. The lack of contact between the two networks meant that the interests of those who were involved in organizing the applied physics pilots at the provincial level were seldom taken into account in the course at the school. Fourteen conclusions are drawn about the networks that were constructed and the network building process at both the school and provincial levels. These conclusions have implications for policy in educational change initiatives and for

  17. Teacher Educator Changing Perceptions of Theory

    ERIC Educational Resources Information Center

    Smith, Kim; Hodson, Elaine; Brown, Tony

    2013-01-01

    An alternative formulation of the actor in educational action research is shown to refresh notions of theory within initial teacher education. Methodologically, the actor is depicted as identifying with ongoing cultural adjustments through reflective data. Specifically, the paper considers the experience of mature trainee teachers in the United…

  18. Neural basis of understanding communicative actions: Changes associated with knowing the actor's intention and the meanings of the actions.

    PubMed

    Möttönen, Riikka; Farmer, Harry; Watkins, Kate E

    2016-01-29

    People can communicate by using hand actions, e.g., signs. Understanding communicative actions requires that the observer knows that the actor has an intention to communicate and the meanings of the actions. Here, we investigated how this prior knowledge affects processing of observed actions. We used functional MRI to determine changes in action processing when non-signers were told that the observed actions are communicative (i.e., signs) and learned the meanings of half of the actions. Processing of hand actions activated the left and right inferior frontal gyrus (IFG, BA 44 and 45) when the communicative intention of the actor was known, even when the meanings of the actions remained unknown. These regions were not active when the observers did not know about the communicative nature of the hand actions. These findings suggest that the left and right IFG play a role in understanding the intention of the actor, but do not process visuospatial features of the communicative actions. Knowing the meanings of the hand actions further enhanced activity in the anterior part of the IFG (BA 45), the inferior parietal lobule and posterior inferior and middle temporal gyri in the left hemisphere. These left-hemisphere language regions could provide a link between meanings and observed actions. In sum, the findings provide evidence for the segregation of the networks involved in the neural processing of visuospatial features of communicative hand actions and those involved in understanding the actor's intention and the meanings of the actions. PMID:26752450

  19. Breaking news dissemination in the media via propagation behavior based on complex network theory

    NASA Astrophysics Data System (ADS)

    Liu, Nairong; An, Haizhong; Gao, Xiangyun; Li, Huajiao; Hao, Xiaoqing

    2016-07-01

    The diffusion of breaking news largely relies on propagation behaviors in the media. The tremendous and intricate propagation relationships in the media form a complex network. An improved understanding of breaking news diffusion characteristics can be obtained through the complex network research. Drawing on the news data of Bohai Gulf oil spill event from June 2011 to May 2014, we constructed a weighted and directed complex network in which media are set as nodes, the propagation relationships as edges and the propagation times as the weight of the edges. The primary results show (1) the propagation network presents small world feature, which means relations among media are close and breaking news originating from any node can spread rapidly; (2) traditional media and official websites are the typical sources for news propagation, while business portals are news collectors and spreaders; (3) the propagation network is assortative and the group of core media facilities the spread of breaking news faster; (4) for online media, news originality factor become less important to propagation behaviors. This study offers a new insight to explore information dissemination from the perspective of statistical physics and is beneficial for utilizing the public opinion in a positive way.

  20. Identifying essential pairwise interactions in elastic network model using the alpha shape theory.

    PubMed

    Xia, Fei; Tong, Dudu; Yang, Lifeng; Wang, Dayong; Hoi, Steven C H; Koehl, Patrice; Lu, Lanyuan

    2014-06-01

    Elastic network models (ENM) are based on the idea that the geometry of a protein structure provides enough information for computing its fluctuations around its equilibrium conformation. This geometry is represented as an elastic network (EN) that is, a network of links between residues. A spring is associated with each of these links. The normal modes of the protein are then identified with the normal modes of the corresponding network of springs. Standard approaches for generating ENs rely on a cutoff distance. There is no consensus on how to choose this cutoff. In this work, we propose instead to filter the set of all residue pairs in a protein using the concept of alpha shapes. The main alpha shape we considered is based on the Delaunay triangulation of the Cα positions; we referred to the corresponding EN as EN(∞). We have shown that heterogeneous anisotropic network models, called αHANMs, that are based on EN(∞) reproduce experimental B-factors very well, with correlation coefficients above 0.99 and root-mean-square deviations below 0.1 Å(2) for a large set of high resolution protein structures. The construction of EN(∞) is simple to implement and may be used automatically for generating ENs for all types of ENMs. PMID:24648309

  1. Dynamical complex network theory applied to the therapeutics of brain malignancies

    NASA Astrophysics Data System (ADS)

    Meyer-Bäse, Anke; Fratte, Daniel; Barbu, Adrian; Pinker-Domenig, Katja

    2015-05-01

    An important problem in modern therapeutics at the metabolomic, transcriptomic or phosphoproteomic level remains to identify therapeutic targets in a plentitude of high-throughput data from experiments relevant to a variety of diseases. This paper presents the application of novel graph algorithms and modern control solutions applied to the graph networks resulting from specific experiments to discover disease-related pathways and drug targets in glioma cancer stem cells (GSCs). The theoretical frameworks provides us with the minimal number of "driver nodes" necessary to determine the full control over the obtained graph network in order to provide a change in the network's dynamics from an initial state (disease) to a desired state (non-disease). The achieved results will provide biochemists with techniques to identify more metabolic regions and biological pathways for complex diseases, and design and test novel therapeutic solutions.

  2. Networks.

    ERIC Educational Resources Information Center

    Maughan, George R.; Petitto, Karen R.; McLaughlin, Don

    2001-01-01

    Describes the connectivity features and options of modern campus communication and information system networks, including signal transmission (wire-based and wireless), signal switching, convergence of networks, and network assessment variables, to enable campus leaders to make sound future-oriented decisions. (EV)

  3. Simulations on the number of entanglements of a polymer network using knot theory.

    PubMed

    Michalke, W; Lang, M; Kreitmeier, S; Göritz, D

    2001-07-01

    Polymer networks, created on the computer using the Bond-Fluctuation-Algorithm, offer the possibility to count the number of entanglements. We generated networks consisting of 5000 chains that were cross linked at their end groups via tetra-functional cross linkers. The analysis of the topology was performed by computing the Homfly polynomial of the entanglements offering a much more precise determination of the knot and entanglement type than the Gaussian linking number. It also allows us to determine the influence of Brunnian links. Results concerning the connection between the chain length and the number of entanglements are shown. PMID:11461310

  4. Local energy governance in vermont: an analysis of energy system transition strategies and actor capacity

    NASA Astrophysics Data System (ADS)

    Rowse, Tarah

    and financial stimulus are essential if Vermont hopes to increase strategic energy planning alignment and spur whole-scale energy system change. Study 2 examined local energy actors to assess their ability to develop and sustain energy action on the local level. A survey of 120 municipalities collected statewide baseline data covering the structures, processes, and activities of local energy actors. The analysis examined the role that various forms of capacity play in local energy activity. The results show that towns with higher incomes are more likely to have local energy actors and towns with higher populations have higher aggregate energy activity levels. Structurally, energy actors that had both an energy coordinator and an energy committee were more active, and municipal committees were more active than independent committees. Access to a budget and volunteer engagement were both associated with higher activity levels. The network of local energy actors in Vermont consists of committed and knowledgeable volunteers. Yet, the capacity of these local energy actors to implement sustainable energy change is limited due to resource constraints of time and money. In most cases, the scope of municipal energy planning strategy is modest. Prioritization of strategy and action at the central and local levels, along with increased interaction and coordination, is necessary to increase the regional compatibility and pace of energy system transformation.

  5. Educational Judgment: Linking the Actor and the Spectator.

    ERIC Educational Resources Information Center

    Coulter, David; Wiens, John R.

    2002-01-01

    Recommends moving from debates between spectators and actors about knowledge and practice to discussions about how all educators can foster good judgment, outlining Aristotle's and Kant's accounts of judgment, which ultimately privilege spectators, and introducing Arendt's work. Arendt linked thinking and acting without privileging either in her…

  6. Researching the Habitus of Global Policy Actors in Education

    ERIC Educational Resources Information Center

    Lingard, Bob; Sellar, Sam; Baroutsis, Aspa

    2015-01-01

    This paper reprises the argument for the emergence of a global education policy field and then focuses on the shared habitus of global and national policy actors and technicians. It is argued that this shared habitus is constituted as a reflection of and a contribution to the creation of the global education policy field. Bourdieu's approach…

  7. Hugh Grant's Image Restoration Discourse: An Actor Apologizes.

    ERIC Educational Resources Information Center

    Benoit, William L.

    1997-01-01

    Examines the strategies used by actor Hugh Grant (in his appearances on talk shows) to help restore his reputation after he was arrested for lewd behavior with a prostitute. Uses this case as a springboard to contrast entertainment image repair with political and corporate image repair, arguing that important situational differences can be…

  8. Lifelong Learning in the EU: Changing Conceptualisations, Actors, and Policies

    ERIC Educational Resources Information Center

    Volles, Nina

    2016-01-01

    This paper explores the changing conceptualisations, actors, and policies of lifelong learning (LLL) in the European Union (EU) from the time the topic first emerged and was promoted by international organisations in the 1960s. The author uses Kingdon's Multiple Streams Framework to analyse how the LLL discourse became an important part of the EU…

  9. Children's Recognition of Plans in the Behavior of Other Actors.

    ERIC Educational Resources Information Center

    Walton, Marsha D.; Sedlak, Andrea J.

    An investigation of children's tendencies to infer planfulness from the behavior of other actors revealed systematic differences in the responses of kindergarten and second-grade children to questions about the motives, goals, and knowledge of story characters. Participating in the study were 13 boys and 13 girls attending public school (15…

  10. Comparative analysis of collaboration networks

    SciTech Connect

    Progulova, Tatiana; Gadjiev, Bahruz

    2011-03-14

    In this paper we carry out a comparative analysis of the word network as the collaboration network based on the novel by M. Bulgakov 'Master and Margarita', the synonym network of the Russian language as well as the Russian movie actor network. We have constructed one-mode projections of these networks, defined degree distributions for them and have calculated main characteristics. In the paper a generation algorithm of collaboration networks has been offered which allows one to generate networks statistically equivalent to the studied ones. It lets us reveal a structural correlation between word network, synonym network and movie actor network. We show that the degree distributions of all analyzable networks are described by the distribution of q-type.

  11. On the biological plausibility of grandmother cells: implications for neural network theories in psychology and neuroscience.

    PubMed

    Bowers, Jeffrey S

    2009-01-01

    A fundamental claim associated with parallel distributed processing (PDP) theories of cognition is that knowledge is coded in a distributed manner in mind and brain. This approach rejects the claim that knowledge is coded in a localist fashion, with words, objects, and simple concepts (e.g. "dog"), that is, coded with their own dedicated representations. One of the putative advantages of this approach is that the theories are biologically plausible. Indeed, advocates of the PDP approach often highlight the close parallels between distributed representations learned in connectionist models and neural coding in brain and often dismiss localist (grandmother cell) theories as biologically implausible. The author reviews a range a data that strongly challenge this claim and shows that localist models provide a better account of single-cell recording studies. The author also contrast local and alternative distributed coding schemes (sparse and coarse coding) and argues that common rejection of grandmother cell theories in neuroscience is due to a misunderstanding about how localist models behave. The author concludes that the localist representations embedded in theories of perception and cognition are consistent with neuroscience; biology only calls into question the distributed representations often learned in PDP models. PMID:19159155

  12. Intervening in Partner Violence against Women: A Grounded Theory Exploration of Informal Network Members' Experiences

    ERIC Educational Resources Information Center

    Latta, Rachel E.; Goodman, Lisa A.

    2011-01-01

    A large body of cross-sectional and longitudinal research demonstrates the important contribution of informal social networks to the well-being and safety of female survivors of intimate partner violence (IPV). Most survivors turn to family and friends before, during, and after their involvement with formal services; and many rely solely on…

  13. A network theory for resource exchange between rivers and their watersheds

    NASA Astrophysics Data System (ADS)

    Sabo, John L.; Hagen, Elizabeth M.

    2012-04-01

    Watersheds are drained by river networks, which route materials and energy from headwaters to terminal water bodies. River networks likewise perfuse the terrestrial portion of watershed ecosystems and reroute some of these materials upslope via material exchange between rivers and land. Here we develop a model of resource exchange between rivers and watersheds to predict the spatial extent of material and nutrient fluxes from aquatic portions of watershed ecosystems. The model is based on a geomorphic template that includes river network structure, topography, and channel sinuosity as well as important biological attributes (productivity and dispersal ability). Analysis of this model suggests that the geomorphic template strongly influences the spatial extent of resource flows in watershed ecosystems. The geomorphic template also predicts the location of areas of concentrated resource exchange, typically at ridge crests, in meander bends, and tributary junctions. We contend that these areas represent hotspots of foraging activity for terrestrial consumers, especially those at the reach scale (meander bends). More generally, our model suggests that the spatial extent of aquatic resource flow equal in magnitude to 20% or greater of terrestrial production may encompass as much as 20%-50% of terrestrial portions of watersheds. Resource flow from rivers to terrestrial ecosystems is not merely an edge effect. Instead, the river network may reroute a substantial flux of materials into watershed ecosystems.

  14. A Review of Verb Network Strengthening Treatment: Theory, Methods, Results, and Clinical Implications

    ERIC Educational Resources Information Center

    Edmonds, Lisa A.

    2016-01-01

    This article examines Verb Network Strengthening Treatment (VNeST), a relatively new treatment approach for anomia in people with aphasia. The VNeST protocol aims to promote generalization to increased lexical retrieval of untrained words across a hierarchy of linguistic tasks, including single-word naming of nouns and verbs, sentence production,…

  15. Using Pattern Languages to Mediate Theory-Praxis Conversations in Design for Networked Learning

    ERIC Educational Resources Information Center

    Goodyear, Peter; de Laat, Maarten; Lally, Vic

    2006-01-01

    Educational design for networked learning is becoming more complex but also more inclusive, with teachers and learners playing more active roles in the design of tasks and of the learning environment. This paper connects emerging research on the use of design patterns and pattern languages with a conception of educational design as a conversation…

  16. Network representation of protein interactions: Theory of graph description and analysis.

    PubMed

    Kurzbach, Dennis

    2016-09-01

    A methodological framework is presented for the graph theoretical interpretation of NMR data of protein interactions. The proposed analysis generalizes the idea of network representations of protein structures by expanding it to protein interactions. This approach is based on regularization of residue-resolved NMR relaxation times and chemical shift data and subsequent construction of an adjacency matrix that represents the underlying protein interaction as a graph or network. The network nodes represent protein residues. Two nodes are connected if two residues are functionally correlated during the protein interaction event. The analysis of the resulting network enables the quantification of the importance of each amino acid of a protein for its interactions. Furthermore, the determination of the pattern of correlations between residues yields insights into the functional architecture of an interaction. This is of special interest for intrinsically disordered proteins, since the structural (three-dimensional) architecture of these proteins and their complexes is difficult to determine. The power of the proposed methodology is demonstrated at the example of the interaction between the intrinsically disordered protein osteopontin and its natural ligand heparin. PMID:27272236

  17. Use of formative research and social network theory to develop a group walking intervention: Sumter County on the Move!

    PubMed

    Forthofer, Melinda; Burroughs-Girardi, Ericka; Stoisor-Olsson, Liliana; Wilcox, Sara; Sharpe, Patricia A; Pekuri, Linda M

    2016-10-01

    Although social support is a frequently cited enabler of physical activity, few studies have examined how to harness social support in interventions. This paper describes community-based formative research to design a walking program for mobilizing naturally occurring social networks to support increases in walking behavior. Focus group methods were used to engage community members in discussions about desired walking program features. The research was conducted with underserved communities in Sumter County, South Carolina. The majority of focus group participants were women (76%) and African American (92%). Several important themes emerged from the focus group results regarding attitudes toward walking, facilitators of and barriers to walking, ideal walking program characteristics, and strategies for encouraging community members to walk. Most noteably, the role of existing social networks as a supportive influence on physical activity was a recurring theme in our formative research and a gap in the existing evidence base. The resulting walking program focused on strategies for mobilizing, supporting and reinforcing existing social networks as mechanisms for increasing walking. Our approach to linking theory, empirical evidence and community-based formative research for the development of a walking intervention offers an example for practitioners developing intervention strategies for a wide range of behaviors. PMID:27268867

  18. Abnormal functional resting-state networks in ADHD: graph theory and pattern recognition analysis of fMRI data.

    PubMed

    dos Santos Siqueira, Anderson; Biazoli Junior, Claudinei Eduardo; Comfort, William Edgar; Rohde, Luis Augusto; Sato, João Ricardo

    2014-01-01

    The framework of graph theory provides useful tools for investigating the neural substrates of neuropsychiatric disorders. Graph description measures may be useful as predictor variables in classification procedures. Here, we consider several centrality measures as predictor features in a classification algorithm to identify nodes of resting-state networks containing predictive information that can discriminate between typical developing children and patients with attention-deficit/hyperactivity disorder (ADHD). The prediction was based on a support vector machines classifier. The analyses were performed in a multisite and publicly available resting-state fMRI dataset of healthy children and ADHD patients: the ADHD-200 database. Network centrality measures contained little predictive information for the discrimination between ADHD patients and healthy subjects. However, the classification between inattentive and combined ADHD subtypes was more promising, achieving accuracies higher than 65% (balance between sensitivity and specificity) in some sites. Finally, brain regions were ranked according to the amount of discriminant information and the most relevant were mapped. As hypothesized, we found that brain regions in motor, frontoparietal, and default mode networks contained the most predictive information. We concluded that the functional connectivity estimations are strongly dependent on the sample characteristics. Thus different acquisition protocols and clinical heterogeneity decrease the predictive values of the graph descriptors. PMID:25309910

  19. The Discourse of Interculturality and Its Transnational Migration: Towards a Comparative Analysis of Its Appropriation by Academic and Political Actors in the State of Veracruz

    ERIC Educational Resources Information Center

    Cortes, Laura Selene Mateos

    2009-01-01

    This paper analyses the ways in which social and educational networks are being configured around the actors participating in the increasingly transnational field of intercultural education both at the Universidad Veracruzana Intercultural and the Veracruz State Ministry of Education. It starts by defining the notion of discursive migration as…

  20. VR/IS Lab Virtual Actor research overview

    SciTech Connect

    Shawver, D.M.; Stansfield, S.

    1995-06-22

    This overview presents current research at Sandia National Laboratories in the Virtual Reality and Intelligent Simulation Lab. Into an existing distributed VR environment which we have been developing, and which provides shared immersion for multiple users, we are adding virtual actor support. The virtual actor support we are adding to this environment is intended to provide semi-autonomous actors, with oversight and high-level guiding control by a director/user, and to allow the overall action to be driven by a scenario. We present an overview of the environment into which our virtual actors will be added in Section 3, and discuss the direction of the Virtual Actor research itself in Section 4. We will briefly review related work in Section 2. First however we need to place the research in the context of what motivates it. The motivation for our construction of this environment, and the line of research associated with it, is based on a long-term program of providing support, through simulation, for situational training, by which we mean a type of training in which students learn to handle multiple situations or scenarios. In these situations, the student may encounter events ranging from the routine occurance to the rare emergency. Indeed, the appeal of such training systems is that they could allow the student to experience and develop effective responses for situations they would otherwise have no opportunity to practice, until they happened to encounter an actual occurance. Examples of the type of students for this kind of training would be security forces or emergency response forces. An example of the type of training scenario we would like to support is given in Section 4.2.

  1. A Network Based Theory of Health Systems and Cycles of Well-being.

    PubMed

    Rhodes, Michael Grant

    2013-06-01

    There are two dominant approaches to describe and understand the anatomy of complete health and well-being systems internationally. Yet, neither approach has been able to either predict or explain occasional but dramatic crises in health and well-being systems around the world and in developed emerging market or developing country contexts. As the impacts of such events can be measured not simply in terms of their social and economic consequences but also public health crises, there is a clear need to look for and formulate an alternative approach. This paper examines multi-disciplinary theoretical evidence to suggest that health systems exhibit natural and observable systemic and long cycle characteristics that can be modelled. A health and well-being system model of two slowly evolving anthropological network sub-systems is defined. The first network sub-system consists of organised professional networks of exclusive suppliers of health and well-being services. The second network sub-system consists of communities organising themselves to resource those exclusive services. Together these two network sub-systems interact to form the specific (sovereign) health and well-being systems we know today. But the core of a truly 'complex adaptive system' can also be identified and a simplified two sub-system model of recurring Lotka-Volterra predator-prey cycles is specified. The implications of such an adaptive and evolving model of system anatomy for effective public health, social security insurance and well-being systems governance could be considerable. PMID:24596831

  2. A Network Based Theory of Health Systems and Cycles of Well-being

    PubMed Central

    Rhodes, Michael Grant

    2013-01-01

    There are two dominant approaches to describe and understand the anatomy of complete health and well-being systems internationally. Yet, neither approach has been able to either predict or explain occasional but dramatic crises in health and well-being systems around the world and in developed emerging market or developing country contexts. As the impacts of such events can be measured not simply in terms of their social and economic consequences but also public health crises, there is a clear need to look for and formulate an alternative approach. This paper examines multi-disciplinary theoretical evidence to suggest that health systems exhibit natural and observable systemic and long cycle characteristics that can be modelled. A health and well-being system model of two slowly evolving anthropological network sub-systems is defined. The first network sub-system consists of organised professional networks of exclusive suppliers of health and well-being services. The second network sub-system consists of communities organising themselves to resource those exclusive services. Together these two network sub-systems interact to form the specific (sovereign) health and well-being systems we know today. But the core of a truly ‘complex adaptive system’ can also be identified and a simplified two sub-system model of recurring Lotka-Volterra predator-prey cycles is specified. The implications of such an adaptive and evolving model of system anatomy for effective public health, social security insurance and well-being systems governance could be considerable. PMID:24596831

  3. Impedance learning for robotic contact tasks using natural actor-critic algorithm.

    PubMed

    Kim, Byungchan; Park, Jooyoung; Park, Shinsuk; Kang, Sungchul

    2010-04-01

    Compared with their robotic counterparts, humans excel at various tasks by using their ability to adaptively modulate arm impedance parameters. This ability allows us to successfully perform contact tasks even in uncertain environments. This paper considers a learning strategy of motor skill for robotic contact tasks based on a human motor control theory and machine learning schemes. Our robot learning method employs impedance control based on the equilibrium point control theory and reinforcement learning to determine the impedance parameters for contact tasks. A recursive least-square filter-based episodic natural actor-critic algorithm is used to find the optimal impedance parameters. The effectiveness of the proposed method was tested through dynamic simulations of various contact tasks. The simulation results demonstrated that the proposed method optimizes the performance of the contact tasks in uncertain conditions of the environment. PMID:19696001

  4. Multiple actor-critic structures for continuous-time optimal control using input-output data.

    PubMed

    Song, Ruizhuo; Lewis, Frank; Wei, Qinglai; Zhang, Hua-Guang; Jiang, Zhong-Ping; Levine, Dan

    2015-04-01

    In industrial process control, there may be multiple performance objectives, depending on salient features of the input-output data. Aiming at this situation, this paper proposes multiple actor-critic structures to obtain the optimal control via input-output data for unknown nonlinear systems. The shunting inhibitory artificial neural network (SIANN) is used to classify the input-output data into one of several categories. Different performance measure functions may be defined for disparate categories. The approximate dynamic programming algorithm, which contains model module, critic network, and action network, is used to establish the optimal control in each category. A recurrent neural network (RNN) model is used to reconstruct the unknown system dynamics using input-output data. NNs are used to approximate the critic and action networks, respectively. It is proven that the model error and the closed unknown system are uniformly ultimately bounded. Simulation results demonstrate the performance of the proposed optimal control scheme for the unknown nonlinear system. PMID:25730830

  5. Assessing and accounting for time heterogeneity in stochastic actor oriented models

    PubMed Central

    Schweinberger, Michael; Snijders, Tom A. B.; Ripley, Ruth M.

    2011-01-01

    This paper explores time heterogeneity in stochastic actor oriented models (SAOM) proposed by Snijders (Sociological Methodology. Blackwell, Boston, pp 361–395, 2001) which are meant to study the evolution of networks. SAOMs model social networks as directed graphs with nodes representing people, organizations, etc., and dichotomous relations representing underlying relationships of friendship, advice, etc. We illustrate several reasons why heterogeneity should be statistically tested and provide a fast, convenient method for assessment and model correction. SAOMs provide a flexible framework for network dynamics which allow a researcher to test selection, influence, behavioral, and structural properties in network data over time. We show how the forward-selecting, score type test proposed by Schweinberger (Chapter 4: Statistical modeling of network panel data: goodness of fit. PhD thesis, University of Groningen 2007) can be employed to quickly assess heterogeneity at almost no additional computational cost. One step estimates are used to assess the magnitude of the heterogeneity. Simulation studies are conducted to support the validity of this approach. The ASSIST dataset (Campbell et al. Lancet 371(9624):1595–1602, 2008) is reanalyzed with the score type test, one step estimators, and a full estimation for illustration. These tools are implemented in the RSiena package, and a brief walkthrough is provided. PMID:22003370

  6. Assessing and accounting for time heterogeneity in stochastic actor oriented models.

    PubMed

    Lospinoso, Joshua A; Schweinberger, Michael; Snijders, Tom A B; Ripley, Ruth M

    2011-07-01

    This paper explores time heterogeneity in stochastic actor oriented models (SAOM) proposed by Snijders (Sociological Methodology. Blackwell, Boston, pp 361-395, 2001) which are meant to study the evolution of networks. SAOMs model social networks as directed graphs with nodes representing people, organizations, etc., and dichotomous relations representing underlying relationships of friendship, advice, etc. We illustrate several reasons why heterogeneity should be statistically tested and provide a fast, convenient method for assessment and model correction. SAOMs provide a flexible framework for network dynamics which allow a researcher to test selection, influence, behavioral, and structural properties in network data over time. We show how the forward-selecting, score type test proposed by Schweinberger (Chapter 4: Statistical modeling of network panel data: goodness of fit. PhD thesis, University of Groningen 2007) can be employed to quickly assess heterogeneity at almost no additional computational cost. One step estimates are used to assess the magnitude of the heterogeneity. Simulation studies are conducted to support the validity of this approach. The ASSIST dataset (Campbell et al. Lancet 371(9624):1595-1602, 2008) is reanalyzed with the score type test, one step estimators, and a full estimation for illustration. These tools are implemented in the RSiena package, and a brief walkthrough is provided. PMID:22003370

  7. An Activity Theory Exegesis on Conflict and Contradictions in Networked Discussions and Feedback Exchanges

    ERIC Educational Resources Information Center

    Hadjistassou, Stella K.

    2012-01-01

    The goal of this study was to investigate the culturally afforded contradictions that ten advanced English as a Second Language (ESL) learner encountered when they posted their paper topics and exchanged feedback strategies online and contextualized some of these strategies to draft their papers. Using Cultural-Historical Activity Theory (CHAT),…

  8. On the Biological Plausibility of Grandmother Cells: Implications for Neural Network Theories in Psychology and Neuroscience

    ERIC Educational Resources Information Center

    Bowers, Jeffrey S.

    2009-01-01

    A fundamental claim associated with parallel distributed processing (PDP) theories of cognition is that knowledge is coded in a distributed manner in mind and brain. This approach rejects the claim that knowledge is coded in a localist fashion, with words, objects, and simple concepts (e.g. "dog"), that is, coded with their own dedicated…

  9. Geographic Theories of Educational Development: Innovation Diffusion Within Informal Interpersonal Networks.

    ERIC Educational Resources Information Center

    Berry, Brian J. L.

    An examination of geographic theories of social change clarifies how and why Torsten Haagerstrand's ideas have revolutionized geographic thinking, particularly regarding educational change and development, and provides the background for analyzing his models in detail. Haagerstrand developed the first formal geoqraphic model of diffusion…

  10. Fitting Multidimensional Amotivation into the Self-Determination Theory Nomological Network: Application in School Physical Education

    ERIC Educational Resources Information Center

    Vlachopoulos, Symeon P.; Katartzi, Ermioni S.; Kontou, Maria G.

    2013-01-01

    The present study investigated the nomological validity of the Amotivation Inventory-Physical Education (Shen, Wingert, Li, Sun, & Rukavina, 2010b) scores by examining the associations of ability, effort, value, and task characteristics amotivation beliefs with self-determination theory variables. Data were collected from 401 fifth- and…

  11. Modeling discrete combinatorial systems as alphabetic bipartite networks: Theory and applications

    NASA Astrophysics Data System (ADS)

    Choudhury, Monojit; Ganguly, Niloy; Maiti, Abyayananda; Mukherjee, Animesh; Brusch, Lutz; Deutsch, Andreas; Peruani, Fernando

    2010-03-01

    Genes and human languages are discrete combinatorial systems (DCSs), in which the basic building blocks are finite sets of elementary units: nucleotides or codons in a DNA sequence, and letters or words in a language. Different combinations of these finite units give rise to potentially infinite numbers of genes or sentences. This type of DCSs can be represented as an alphabetic bipartite network (ABN) where there are two kinds of nodes, one type represents the elementary units while the other type represents their combinations. Here, we extend and generalize recent analytical findings for ABNs derived in [Peruani , Europhys. Lett. 79, 28001 (2007)] and empirically investigate two real world systems in terms of ABNs, the codon gene and the phoneme-language network. The one-mode projections onto the elementary basic units are also studied theoretically as well as in real world ABNs. We propose the use of ABNs as a means for inferring the mechanisms underlying the growth of real world DCSs.

  12. The social contagion hypothesis: comment on 'Social contagion theory: examining dynamic social networks and human behavior'.

    PubMed

    Thomas, A C

    2013-02-20

    I reflect on the statistical methods of the Christakis-Fowler studies on network-based contagion of traits by checking the sensitivity of these kinds of results to various alternate specifications and generative mechanisms. Despite the honest efforts of all involved, I remain pessimistic about establishing whether binary health outcomes or product adoptions are contagious if the evidence comes from simultaneously observed data. PMID:23341080

  13. Application of neural networks and information theory to the identification of E. coli transcriptional promoters

    SciTech Connect

    Abremski, K. . Experimental Station); Sirotkin, K. ); Lapedes, A. )

    1991-01-01

    The Humane Genome Project has as its eventual goal the determination of the entire DNA sequence of man, which comprises approximately 3 billion base pairs. An important aspect of this project will be the analysis of the sequence to locate regions of biological importance. New computer methods will be needed to automate and facilitate this task. In this paper, we have investigated use of neural networks for the recognition of functional patterns in biological sequences. The prediction of Escherichia coli transcriptional promoters was chosen as a model system for these studies. Two approaches were employed. In the fist method, a mutual information analysis of promoter and nonpromoter sequences was carried out to demonstrate the informative base positions that help to distinguish promoter sequences from non-promoter sequences. These base positions were than used to train a Perceptron to predict new promoter sequences. In the second method, the experimental knowledge of promoters was used to indicate the important base positions in the sequence. These base positions were used to train a back propagation network with hidden units which represented regions of sequence conservation found in promoters. With both types of networks, prediction of new promoter sequences was greater than 96.9%. 12 refs., 1 fig., 4 tabs.

  14. Optimizing Natural Gas Networks through Dynamic Manifold Theory and a Decentralized Algorithm: Belgium Case Study

    NASA Astrophysics Data System (ADS)

    Koch, Caleb; Winfrey, Leigh

    2014-10-01

    Natural Gas is a major energy source in Europe, yet political instabilities have the potential to disrupt access and supply. Energy resilience is an increasingly essential construct and begins with transmission network design. This study proposes a new way of thinking about modelling natural gas flow. Rather than relying on classical economic models, this problem is cast into a time-dependent Hamiltonian dynamics discussion. Traditional Natural Gas constraints, including inelastic demand and maximum/minimum pipe flows, are portrayed as energy functions and built into the dynamics of each pipe flow. Doing so allows the constraints to be built into the dynamics of each pipeline. As time progresses in the model, natural gas flow rates find the minimum energy, thus the optimal gas flow rates. The most important result of this study is using dynamical principles to ensure the output of natural gas at demand nodes remains constant, which is important for country to country natural gas transmission. Another important step in this study is building the dynamics of each flow in a decentralized algorithm format. Decentralized regulation has solved congestion problems for internet data flow, traffic flow, epidemiology, and as demonstrated in this study can solve the problem of Natural Gas congestion. A mathematical description is provided for how decentralized regulation leads to globally optimized network flow. Furthermore, the dynamical principles and decentralized algorithm are applied to a case study of the Fluxys Belgium Natural Gas Network.

  15. Development of flow network analysis code for block type VHTR core by linear theory method

    SciTech Connect

    Lee, J. H.; Yoon, S. J.; Park, J. W.; Park, G. C.

    2012-07-01

    VHTR (Very High Temperature Reactor) is high-efficiency nuclear reactor which is capable of generating hydrogen with high temperature of coolant. PMR (Prismatic Modular Reactor) type reactor consists of hexagonal prismatic fuel blocks and reflector blocks. The flow paths in the prismatic VHTR core consist of coolant holes, bypass gaps and cross gaps. Complicated flow paths are formed in the core since the coolant holes and bypass gap are connected by the cross gap. Distributed coolant was mixed in the core through the cross gap so that the flow characteristics could not be modeled as a simple parallel pipe system. It requires lot of effort and takes very long time to analyze the core flow with CFD analysis. Hence, it is important to develop the code for VHTR core flow which can predict the core flow distribution fast and accurate. In this study, steady state flow network analysis code is developed using flow network algorithm. Developed flow network analysis code was named as FLASH code and it was validated with the experimental data and CFD simulation results. (authors)

  16. Balancing influence between actors in healthcare decision making

    PubMed Central

    2011-01-01

    Background Healthcare costs in most developed countries are not clearly linked to better patient and public health outcomes, but are rather associated with service delivery orientation. In the U.S. this has resulted in large variation in healthcare availability and use, increased cost, reduced employer participation in health insurance programs, and reduced overall population health outcomes. Recent U.S. healthcare reform legislation addresses only some of these issues. Other countries face similar healthcare issues. Discussion A major goal of healthcare is to enhance patient health outcomes. This objective is not realized in many countries because incentives and structures are currently not aligned for maximizing population health. The misalignment occurs because of the competing interests between "actors" in healthcare. In a simplified model these are individuals motivated to enhance their own health; enterprises (including a mix of nonprofit, for profit and government providers, payers, and suppliers, etc.) motivated by profit, political, organizational and other forces; and government which often acts in the conflicting roles of a healthcare payer and provider in addition to its role as the representative and protector of the people. An imbalance exists between the actors, due to the resources and information control of the enterprise and government actors relative to the individual and the public. Failure to use effective preventive interventions is perhaps the best example of the misalignment of incentives. We consider the current Pareto efficient balance between the actors in relation to the Pareto frontier, and show that a significant change in the healthcare market requires major changes in the utilities of the enterprise and government actors. Summary A variety of actions are necessary for maximizing population health within the constraints of available resources and the current balance between the actors. These actions include improved transparency of

  17. Actor-critic-based optimal tracking for partially unknown nonlinear discrete-time systems.

    PubMed

    Kiumarsi, Bahare; Lewis, Frank L

    2015-01-01

    This paper presents a partially model-free adaptive optimal control solution to the deterministic nonlinear discrete-time (DT) tracking control problem in the presence of input constraints. The tracking error dynamics and reference trajectory dynamics are first combined to form an augmented system. Then, a new discounted performance function based on the augmented system is presented for the optimal nonlinear tracking problem. In contrast to the standard solution, which finds the feedforward and feedback terms of the control input separately, the minimization of the proposed discounted performance function gives both feedback and feedforward parts of the control input simultaneously. This enables us to encode the input constraints into the optimization problem using a nonquadratic performance function. The DT tracking Bellman equation and tracking Hamilton-Jacobi-Bellman (HJB) are derived. An actor-critic-based reinforcement learning algorithm is used to learn the solution to the tracking HJB equation online without requiring knowledge of the system drift dynamics. That is, two neural networks (NNs), namely, actor NN and critic NN, are tuned online and simultaneously to generate the optimal bounded control policy. A simulation example is given to show the effectiveness of the proposed method. PMID:25312944

  18. Networking.

    ERIC Educational Resources Information Center

    Duvall, Betty

    Networking is an information giving and receiving system, a support system, and a means whereby women can get ahead in careers--either in new jobs or in current positions. Networking information can create many opportunities: women can talk about how other women handle situations and tasks, and previously established contacts can be used in…

  19. Graph Theory Analysis of Functional Brain Networks and Mobility Disability in Older Adults

    PubMed Central

    Burdette, Jonathan H.; Morgan, Ashley R.; Williamson, Jeff D.; Kritchevsky, Stephen B.; Laurienti, Paul J.

    2014-01-01

    Background. The brain’s structural integrity is associated with mobility function in older adults. Changes in function may be evident earlier than changes in structure and may be more directly related to mobility. Therefore, we assessed whether functional brain networks varied with mobility function in older adults. Methods. Short Physical Performance Battery (SPPB) and resting state functional magnetic resonance imaging were collected on 24 young (mean age = 26.4±5.1) and 48 older (mean age = 72.04±5.1) participants. Older participants were divided into three groups by SPPB score: Low SPPB (score = 7–9), Mid SPPB (score = 10), High SPPB (score = 11–12).Graph theory–based methods were used to characterize and compare brain network organization. Results. Connectivity in the somatomotor cortex distinguished between groups based on SPPB score. The community structure of the somatomotor cortex was significantly less consistent in the Low SPPB group (mean = 0.097±0.05) compared with Young (mean = 0.163±0.09, p = .03) SPPB group. Striking differences were evident in second-order connections between somatomotor cortex and superior temporal gyrus and insula that reached statistical significance. The Low SPPB group (mean = 140.87±109.30) had a significantly higher number of connections than Young (mean = 45.05±33.79, p = .0003) or High (mean = 49.61±35.31, p = .002) SPPB group. Conclusions. Older adults with poorer mobility function exhibited reduced consistency of somatomotor community structure and a greater number of secondary connections with vestibular and multisensory regions of the brain. Further study is needed to fully interpret these effects, but analysis of functional brain networks adds new insights to the contribution of the brain to mobility. PMID:24717331

  20. Spectral renormalization group for the Gaussian model and ψ4 theory on nonspatial networks

    NASA Astrophysics Data System (ADS)

    Tuncer, Aslı; Erzan, Ayşe

    2015-08-01

    We implement the spectral renormalization group on different deterministic nonspatial networks without translational invariance. We calculate the thermodynamic critical exponents for the Gaussian model on the Cayley tree and the diamond lattice and find that they are functions of the spectral dimension, d ˜. The results are shown to be consistent with those from exact summation and finite-size scaling approaches. At d ˜=2 , the lower critical dimension for the Ising universality class, the Gaussian fixed point is stable with respect to a ψ4 perturbation up to second order. However, on generalized diamond lattices, non-Gaussian fixed points arise for 2

  1. Performance Analysis of an Actor-Based Distributed Simulation

    NASA Technical Reports Server (NTRS)

    Schoeffler, James D.

    1998-01-01

    Object-oriented design of simulation programs appears to be very attractive because of the natural association of components in the simulated system with objects. There is great potential in distributing the simulation across several computers for the purpose of parallel computation and its consequent handling of larger problems in less elapsed time. One approach to such a design is to use "actors", that is, active objects with their own thread of control. Because these objects execute concurrently, communication is via messages. This is in contrast to an object-oriented design using passive objects where communication between objects is via method calls (direct calls when they are in the same address space and remote procedure calls when they are in different address spaces or different machines). This paper describes a performance analysis program for the evaluation of a design for distributed simulations based upon actors.

  2. Teachers as Actors: The Implications of Acting on Physics Teaching

    NASA Astrophysics Data System (ADS)

    Milner-Bolotin, Marina

    2007-10-01

    In the spring of 2006, a rather unusual advertisement by the Centre of Teaching and Academic Growth at UBC (http://www.tag.ubc.ca) came to my attention. Faculty members were invited to take part in a workshop entitled "All the World's a Stage: Teachers as Actors," offered by a zoology instructor and an amateur actor, Greg Bole: Teaching can be seen as creating an interpersonal relationship and hence uses many of the same skills as acting. The investigation and use of acting skills in teacher preparation can allow a greater facility with diverse methods, increase skill at adapting to change in the classroom or lecture hall, and an increased ability to quickly form positive relationships with students. (Greg Bole: http://www.tag.ubc.ca/programs/series-detail.php?series_id=249 )

  3. Deformation theory of an electro-conductive composite composed of entangled network of carbon nanotubes embedded in elastic polyurethane

    NASA Astrophysics Data System (ADS)

    Slobodian, Petr; Riha, Pavel; Olejnik, Robert; Saha, Petr

    2013-04-01

    A strain sensing polymer composite consisting of a network of entangled multi-walled carbon nanotubes in a thermoplastic polyurethane elastomer is tested by tensile and bending deformation. The composite is prepared by taking a non-woven polyurethane filter membrane, enmeshing it with carbon nanotubes and melding them together. The testing has shown that the material can be elongated as much as 400% during which the electrical resistance is increased more than 270 times. To describe the composite strain dependent resistance, a rheological model is proposed which takes into account a decrease of local contact forces between nanotubes as well as the reduction of number of contacts with deformation. The theory is used for description of sensing element deformation and resistance when simple elongation and repeated bending is exerted.

  4. Intelligent policy making? Key actors' perspectives on the development and implementation of an early years' initiative in Scotland's public health arena.

    PubMed

    Deas, L; Mattu, L; Gnich, W

    2013-11-01

    Increased political enthusiasm for evidence-based policy and action has re-ignited interest in the use of evidence within political and practitioner networks. Theories of evidence-based policy making and practice are being re-considered in an attempt to better understand the processes through which knowledge translation occurs. Understanding how policy develops, and practice results, has the potential to facilitate effective evidence use. Further knowledge of the factors which shape healthcare delivery and their influence in different contexts is needed. This paper explores the processes involved in the development of a complex intervention in Scotland's National Health Service (NHS). It uses a national oral health programme for children (Childsmile) as a case study, drawing upon key actors' perceptions of the influence of different drivers (research evidence, practitioner knowledge and values, policy, and political and local context) to programme development. Framework analysis is used to analyse stakeholder accounts from in-depth interviews. Documentary review is also undertaken. Findings suggest that Childsmile can be described as an 'evidence-informed' intervention, blending available research evidence with knowledge from practitioner experience and continual learning through evaluation, to plan delivery. The importance of context was underscored, in terms of the need to align with prevailing political ideology and in the facilitative strength of networks within the relatively small public health community in Scotland. Respondents' perceptions support several existing theoretical models of translation, however no single theory offered a comprehensive framework covering all aspects of the complex processes reported. Childsmile's use of best available evidence and on-going contribution to knowledge suggest that the programme is an example of intelligent policy making with international relevance. PMID:24034945

  5. Extended Generalized Blockmodeling for Compound Communities and External Actors

    NASA Astrophysics Data System (ADS)

    Brendel, Radoslaw; Krawczyk, Henryk

    Some social communities evident their own unique internal structure. In this chapter, we consider social communities composed of several cohesive subgroups which we call compound communities. For such communities, an extended generalized blockmodeling is proposed, taking into account the structure of compound communities and their relations with external actors. Using the extension, the community protection approach is proposed and used in detection of spam directed toward an e-mail local society.

  6. A Novel Optimal Joint Resource Allocation Method in Cooperative Multicarrier Networks: Theory and Practice

    PubMed Central

    Gao, Yuan; Zhou, Weigui; Ao, Hong; Chu, Jian; Zhou, Quan; Zhou, Bo; Wang, Kang; Li, Yi; Xue, Peng

    2016-01-01

    With the increasing demands for better transmission speed and robust quality of service (QoS), the capacity constrained backhaul gradually becomes a bottleneck in cooperative wireless networks, e.g., in the Internet of Things (IoT) scenario in joint processing mode of LTE-Advanced Pro. This paper focuses on resource allocation within capacity constrained backhaul in uplink cooperative wireless networks, where two base stations (BSs) equipped with single antennae serve multiple single-antennae users via multi-carrier transmission mode. In this work, we propose a novel cooperative transmission scheme based on compress-and-forward with user pairing to solve the joint mixed integer programming problem. To maximize the system capacity under the limited backhaul, we formulate the joint optimization problem of user sorting, subcarrier mapping and backhaul resource sharing among different pairs (subcarriers for users). A novel robust and efficient centralized algorithm based on alternating optimization strategy and perfect mapping is proposed. Simulations show that our novel method can improve the system capacity significantly under the constraint of the backhaul resource compared with the blind alternatives. PMID:27077865

  7. A Novel Optimal Joint Resource Allocation Method in Cooperative Multicarrier Networks: Theory and Practice.

    PubMed

    Gao, Yuan; Zhou, Weigui; Ao, Hong; Chu, Jian; Zhou, Quan; Zhou, Bo; Wang, Kang; Li, Yi; Xue, Peng

    2016-01-01

    With the increasing demands for better transmission speed and robust quality of service (QoS), the capacity constrained backhaul gradually becomes a bottleneck in cooperative wireless networks, e.g., in the Internet of Things (IoT) scenario in joint processing mode of LTE-Advanced Pro. This paper focuses on resource allocation within capacity constrained backhaul in uplink cooperative wireless networks, where two base stations (BSs) equipped with single antennae serve multiple single-antennae users via multi-carrier transmission mode. In this work, we propose a novel cooperative transmission scheme based on compress-and-forward with user pairing to solve the joint mixed integer programming problem. To maximize the system capacity under the limited backhaul, we formulate the joint optimization problem of user sorting, subcarrier mapping and backhaul resource sharing among different pairs (subcarriers for users). A novel robust and efficient centralized algorithm based on alternating optimization strategy and perfect mapping is proposed. Simulations show that our novel method can improve the system capacity significantly under the constraint of the backhaul resource compared with the blind alternatives. PMID:27077865

  8. Multispecies networks: visualizing the psychological research of the Committee for Research in Problems of Sex.

    PubMed

    Pettit, Michael; Serykh, Darya; Green, Christopher D

    2015-03-01

    In our current moment, there is considerable interest in networks, in how people and things are connected. This essay outlines one approach that brings together insights from actor-network theory, social network analysis, and digital history to interpret past scientific activity. Multispecies network analysis (MNA) is a means of understanding the historical interactions among scientists, institutions, and preferred experimental animals. A reexamination of studies of sexual behavior funded by the Committee for Research in Problems of Sex between the 1920s and the 1940s demonstrates the applicability of MNA to clarifying the relations that sustained this area of psychology. The measures of weighted degree and betweenness can highlight which nodes (whether organisms or institutions) were particularly "central" to this network. Rats featured as the animals most widely studied during this period, but the analysis also reveals distinct institutional and disciplinary cultures where different species were favored as either surrogates for humans or representatives of more general biological groups. PMID:26027310

  9. Shared and nonshared neural networks of cognitive and affective theory-of-mind: a neuroimaging study using cartoon picture stories.

    PubMed

    Schlaffke, Lara; Lissek, Silke; Lenz, Melanie; Juckel, Georg; Schultz, Thomas; Tegenthoff, Martin; Schmidt-Wilcke, Tobias; Brüne, Martin

    2015-01-01

    Theory of mind (ToM) refers to the ability to represent one's own and others' cognitive and affective mental states. Recent imaging studies have aimed to disentangle the neural networks involved in cognitive as opposed to affective ToM, based on clinical observations that the two can functionally dissociate. Due to large differences in stimulus material and task complexity findings are, however, inconclusive. Here, we investigated the neural correlates of cognitive and affective ToM in psychologically healthy male participants (n = 39) using functional brain imaging, whereby the same set of stimuli was presented for all conditions (affective, cognitive and control), but associated with different questions prompting either a cognitive or affective ToM inference. Direct contrasts of cognitive versus affective ToM showed that cognitive ToM recruited the precuneus and cuneus, as well as regions in the temporal lobes bilaterally. Affective ToM, in contrast, involved a neural network comprising prefrontal cortical structures, as well as smaller regions in the posterior cingulate cortex and the basal ganglia. Notably, these results were complemented by a multivariate pattern analysis (leave one study subject out), yielding a classifier with an accuracy rate of more than 85% in distinguishing between the two ToM-conditions. The regions contributing most to successful classification corresponded to those found in the univariate analyses. The study contributes to the differentiation of neural patterns involved in the representation of cognitive and affective mental states of others. PMID:25131828

  10. Education as networking: Rethinking the success of the harm reduction policy of Taiwan.

    PubMed

    Chen, Jia-shin

    2015-05-01

    The harm reduction policy of Taiwan has been considered a success. However, the HIV incidence among injection drug users declined before the nationwide needle and syringe program and drug substitution treatments were implemented. Thus, other factors in the policy might have contributed to its success. Some authors have suggested that education may have played a pivotal part. In this research, the purported significance of education in the success of the policy is conceptualized by reviewing the studies on harm reduction in Taiwan and reflecting upon my own fieldwork. Moreover, relevant literature is used as reference to reformulate this notion of education. This article shows that harm reduction education may be conducted in numerous forms, most of which are non-formal, improvisational, and contingent. Non-governmental organizations may play a role, but more actors, strategies, infrastructures, and interactions should be considered. This article draws from actor-network theory and refines the current thesis that attributes the policy success to education by utilizing three reflections, namely, appreciating materiality and spatiality, recognizing covert actors in the networking, and treating education as an outcome rather than a means. In conclusion, looking at education as a form of networking offers theoretical insight that increases understanding of its participants, mechanisms, processes, and permutations. PMID:25139870

  11. Structural Variability within Frontoparietal Networks and Individual Differences in Attentional Functions: An Approach Using the Theory of Visual Attention

    PubMed Central

    Gillebert, Celine R.; Vangkilde, Signe A.; Petersen, Anders; Humphreys, Glyn W.

    2015-01-01

    Visuospatial attention allows us to select and act upon a subset of behaviorally relevant visual stimuli while ignoring distraction. Bundesen's theory of visual attention (TVA) (Bundesen, 1990) offers a quantitative analysis of the different facets of attention within a unitary model and provides a powerful analytic framework for understanding individual differences in attentional functions. Visuospatial attention is contingent upon large networks, distributed across both hemispheres, consisting of several cortical areas interconnected by long-association frontoparietal pathways, including three branches of the superior longitudinal fasciculus (SLF I-III) and the inferior fronto-occipital fasciculus (IFOF). Here we examine whether structural variability within human frontoparietal networks mediates differences in attention abilities as assessed by the TVA. Structural measures were based on spherical deconvolution and tractography-derived indices of tract volume and hindrance-modulated orientational anisotropy (HMOA). Individual differences in visual short-term memory (VSTM) were linked to variability in the microstructure (HMOA) of SLF II, SLF III, and IFOF within the right hemisphere. Moreover, VSTM and speed of information processing were linked to hemispheric lateralization within the IFOF. Differences in spatial bias were mediated by both variability in microstructure and volume of the right SLF II. Our data indicate that the microstructural and macrostrucutral organization of white matter pathways differentially contributes to both the anatomical lateralization of frontoparietal attentional networks and to individual differences in attentional functions. We conclude that individual differences in VSTM capacity, processing speed, and spatial bias, as assessed by TVA, link to variability in structural organization within frontoparietal pathways. PMID:26224851

  12. Structural Variability within Frontoparietal Networks and Individual Differences in Attentional Functions: An Approach Using the Theory of Visual Attention.

    PubMed

    Chechlacz, Magdalena; Gillebert, Celine R; Vangkilde, Signe A; Petersen, Anders; Humphreys, Glyn W

    2015-07-29

    Visuospatial attention allows us to select and act upon a subset of behaviorally relevant visual stimuli while ignoring distraction. Bundesen's theory of visual attention (TVA) (Bundesen, 1990) offers a quantitative analysis of the different facets of attention within a unitary model and provides a powerful analytic framework for understanding individual differences in attentional functions. Visuospatial attention is contingent upon large networks, distributed across both hemispheres, consisting of several cortical areas interconnected by long-association frontoparietal pathways, including three branches of the superior longitudinal fasciculus (SLF I-III) and the inferior fronto-occipital fasciculus (IFOF). Here we examine whether structural variability within human frontoparietal networks mediates differences in attention abilities as assessed by the TVA. Structural measures were based on spherical deconvolution and tractography-derived indices of tract volume and hindrance-modulated orientational anisotropy (HMOA). Individual differences in visual short-term memory (VSTM) were linked to variability in the microstructure (HMOA) of SLF II, SLF III, and IFOF within the right hemisphere. Moreover, VSTM and speed of information processing were linked to hemispheric lateralization within the IFOF. Differences in spatial bias were mediated by both variability in microstructure and volume of the right SLF II. Our data indicate that the microstructural and macrostrucutral organization of white matter pathways differentially contributes to both the anatomical lateralization of frontoparietal attentional networks and to individual differences in attentional functions. We conclude that individual differences in VSTM capacity, processing speed, and spatial bias, as assessed by TVA, link to variability in structural organization within frontoparietal pathways. PMID:26224851

  13. Optimal Observation Network Design for Model Discrimination using Information Theory and Bayesian Model Averaging

    NASA Astrophysics Data System (ADS)

    Pham, H. V.; Tsai, F. T. C.

    2014-12-01

    Groundwater systems are complex and subject to multiple interpretations and conceptualizations due to a lack of sufficient information. As a result, multiple conceptual models are often developed and their mean predictions are preferably used to avoid biased predictions from using a single conceptual model. Yet considering too many conceptual models may lead to high prediction uncertainty and may lose the purpose of model development. In order to reduce the number of models, an optimal observation network design is proposed based on maximizing the Kullback-Leibler (KL) information to discriminate competing models. The KL discrimination function derived by Box and Hill [1967] for one additional observation datum at a time is expanded to account for multiple independent spatiotemporal observations. The Bayesian model averaging (BMA) method is used to incorporate existing data and quantify future observation uncertainty arising from conceptual and parametric uncertainties in the discrimination function. To consider the future observation uncertainty, the Monte Carlo realizations of BMA predicted future observations are used to calculate the mean and variance of posterior model probabilities of the competing models. The goal of the optimal observation network design is to find the number and location of observation wells and sampling rounds such that the highest posterior model probability of a model is larger than a desired probability criterion (e.g., 95%). The optimal observation network design is implemented to a groundwater study in the Baton Rouge area, Louisiana to collect new groundwater heads from USGS wells. The considered sources of uncertainty that create multiple groundwater models are the geological architecture, the boundary condition, and the fault permeability architecture. All possible design solutions are enumerated using high performance computing systems. Results show that total model variance (the sum of within-model variance and between

  14. Coarse-grained models reveal functional dynamics--I. Elastic network models--theories, comparisons and perspectives.

    PubMed

    Yang, Lee-Wei; Chng, Choon-Peng

    2008-01-01

    In this review, we summarize the progress on coarse-grained elastic network models (CG-ENMs) in the past decade. Theories were formulated to allow study of conformational dynamics in time/space frames of biological interest. Several highlighted models and their underlined hypotheses are introduced in physical depth. Important ENM offshoots, motivated to reproduce experimental data as well as to address the slow-mode-encoded configurational transitions, are also introduced. With the theoretical developments, computational cost is significantly reduced due to simplified potentials and coarse-grained schemes. Accumulating wealth of data suggest that ENMs agree equally well with experiment in describing equilibrium dynamics despite their distinct potentials and levels of coarse-graining. They however do differ in the slowest motional components that are essential to address large conformational changes of functional significance. The difference stems from the dissimilar curvatures of the harmonic energy wells described for each model. We also provide our views on the predictability of 'open to close' (open-->close) transitions of biomolecules on the basis of conformational selection theory. Lastly, we address the limitations of the ENM formalism which are partially alleviated by the complementary CG-MD approach, to be introduced in the second paper of this two-part series. PMID:19812764

  15. Mathematics of small stochastic reaction networks: A boundary layer theory for eigenstate analysis

    PubMed Central

    Mjolsness, Eric; Prasad, Upendra

    2013-01-01

    We study and analyze the stochastic dynamics of a reversible bimolecular reaction A + B ↔ C called the “trivalent reaction.” This reaction is of a fundamental nature and is part of many biochemical reaction networks. The stochastic dynamics is given by the stochastic master equation, which is difficult to solve except when the equilibrium state solution is desired. We present a novel way of finding the eigenstates of this system of difference-differential equations, using perturbation analysis of ordinary differential equations arising from approximation of the difference equations. The time evolution of the state probabilities can then be expressed in terms of the eigenvalues and the eigenvectors. PMID:23514469

  16. A Low-cost System for Generating Near-realistic Virtual Actors

    NASA Astrophysics Data System (ADS)

    Afifi, Mahmoud; Hussain, Khaled F.; Ibrahim, Hosny M.; Omar, Nagwa M.

    2015-06-01

    Generating virtual actors is one of the most challenging fields in computer graphics. The reconstruction of a realistic virtual actor has been paid attention by the academic research and the film industry to generate human-like virtual actors. Many movies were acted by human-like virtual actors, where the audience cannot distinguish between real and virtual actors. The synthesis of realistic virtual actors is considered a complex process. Many techniques are used to generate a realistic virtual actor; however they usually require expensive hardware equipment. In this paper, a low-cost system that generates near-realistic virtual actors is presented. The facial features of the real actor are blended with a virtual head that is attached to the actor's body. Comparing with other techniques that generate virtual actors, the proposed system is considered a low-cost system that requires only one camera that records the scene without using any expensive hardware equipment. The results of our system show that the system generates good near-realistic virtual actors that can be used on many applications.

  17. Who Needs What? Some Thoughts on the Possibility of Using Psychology in Actor Training.

    ERIC Educational Resources Information Center

    Vulova, Marina

    2001-01-01

    Contends that the aim of professional actor training is to reveal and develop an actor's individuality. Proposes that the responsibility of drama teachers is to lead training in such away that students feel accepted, understood, and respected. Proposes that psychodrama is the most appropriate method for student and professional actors' personal…

  18. Breaking into the Business: Experiences of Actors with Disabilities in the Entertainment Industry

    ERIC Educational Resources Information Center

    Raynor, Olivia; Hayward, Katharine

    2009-01-01

    The pursuit of an acting career is a difficult one for anybody. However, studies have yet to factor how disability affects casting opportunities. This study describes the employment of actors with disabilities, along with the unique barriers they encounter in the audition and casting process. Actors with disabilities from the Screen Actors Guild…

  19. Entropy theory based multi-criteria resampling of rain gauge networks for hydrological modelling - A case study of humid area in southern China

    NASA Astrophysics Data System (ADS)

    Xu, Hongliang; Xu, Chong-Yu; Sælthun, Nils Roar; Xu, Youpeng; Zhou, Bin; Chen, Hua

    2015-06-01

    Rain gauge networks are used to provide estimates of area average, spatial variability and point rainfalls at catchment scale and provide the most important input for hydrological models. Therefore, it is desired to design the optimal rain gauge networks with a minimal number of rain gauges to provide reliable data with both areal mean values and spatial-temporal variability. Based on a dense rain gauge network of 185 rain gauges in Xiangjiang River Basin, southern China, this study used an entropy theory based multi-criteria method which simultaneously considers the information derived from rainfall series, minimize the bias of areal mean rainfall as well as minimize the information overlapped by different gauges to resample the rain gauge networks with different gauge densities. The optimal networks were examined using two hydrological models: The lumped Xinanjiang Model and the distributed SWAT Model. The results indicate that the performances of the lumped model using different optimal networks are stable while the performances of the distributed model keep on improving as the number of rain gauges increases. The results reveal that the entropy theory based multi-criteria strategy provides an optimal design of rain gauge network which is of vital importance in regional hydrological study and water resources management.

  20. A source-initiated on-demand routing algorithm based on the Thorup-Zwick theory for mobile wireless sensor networks.

    PubMed

    Mao, Yuxin; Zhu, Ping

    2013-01-01

    The unreliability and dynamics of mobile wireless sensor networks make it hard to perform end-to-end communications. This paper presents a novel source-initiated on-demand routing mechanism for efficient data transmission in mobile wireless sensor networks. It explores the Thorup-Zwick theory to achieve source-initiated on-demand routing with time efficiency. It is able to find out shortest routing path between source and target in a network and transfer data in linear time. The algorithm is easy to be implemented and performed in resource-constrained mobile wireless sensor networks. We also evaluate the approach by analyzing its cost in detail. It can be seen that the approach is efficient to support data transmission in mobile wireless sensor networks. PMID:24453826

  1. Performance evaluation of a simulated data-flow computer with low-resolution actors

    NASA Technical Reports Server (NTRS)

    Gaudiot, J. L.; Ercegovac, M. D.

    1985-01-01

    Basic problems related to the exploitation of parallelism in a program include sequencing of the instructions and communication of the data. It is pointed out that the data-flow approach offers an elegant solution to the sequencing problem, since all data dependencies are automatically handled and only instructions with ready input sets are activated. It is shown that a change in the level of subcomputations (actors) affects communications costs. The concept of variable resolution is discussed, and the testbed environment is examined. Attention is given to the architecture of the processing elements, the communication network, and the simulators. A description of the analytical model is also provided. Simulation and results are discussed, taking into account test programs and allocation, the variation of the number of processing elements, the variation of the resolution in directed acyclic graphs, performance in processing loops, and array handling.

  2. Graph theory analysis of complex brain networks: new concepts in brain mapping applied to neurosurgery.

    PubMed

    Hart, Michael G; Ypma, Rolf J F; Romero-Garcia, Rafael; Price, Stephen J; Suckling, John

    2016-06-01

    Neuroanatomy has entered a new era, culminating in the search for the connectome, otherwise known as the brain's wiring diagram. While this approach has led to landmark discoveries in neuroscience, potential neurosurgical applications and collaborations have been lagging. In this article, the authors describe the ideas and concepts behind the connectome and its analysis with graph theory. Following this they then describe how to form a connectome using resting state functional MRI data as an example. Next they highlight selected insights into healthy brain function that have been derived from connectome analysis and illustrate how studies into normal development, cognitive function, and the effects of synthetic lesioning can be relevant to neurosurgery. Finally, they provide a précis of early applications of the connectome and related techniques to traumatic brain injury, functional neurosurgery, and neurooncology. PMID:26544769

  3. Similarities and Dissimilarities in Coauthorship Networks: Gestalt Theory as Explanation for Well-Ordered Collaboration Structures and Production of Scientific Literature.

    ERIC Educational Resources Information Center

    Kretschmer, Hildrun

    2002-01-01

    Based on Gestalt theory, the author assumes the existence of a field-force equilibrium to explain how, according to the conciseness principle, mathematically precise gestalts could exist in coauthorship networks. Develops a mathematical function to describe these gestalts in scientific literature and discusses structural characteristics of…

  4. An MPS-BNS Mixed Strategy Based on Game Theory for Wireless Mesh Networks

    PubMed Central

    Huang, S. Q.; Wang, G. C.; Zhen, H. H.; Zhang, Z.

    2013-01-01

    To achieve a valid effect of wireless mesh networks against selfish nodes and selfish behaviors in the packets forwarding, an approach named mixed MPS-BNS strategy is proposed in this paper. The proposed strategy is based on the Maximum Payoff Strategy (MPS) and the Best Neighbor Strategy (BNS). In this strategy, every node plays a packet forwarding game with its neighbors and records the total payoff of the game. After one round of play, each player chooses the MPS or BNS strategy for certain probabilities and updates the strategy accordingly. In MPS strategy, each node chooses a strategy that will get the maximum payoff according to its neighbor's strategy. In BNS strategy, each node follows the strategy of its neighbor with the maximum total payoff and then enters the next round of play. The simulation analysis has shown that MPS-BNS strategy is able to evolve to the maximum expected level of average payoff with faster speed than the pure BNS strategy, especially in the packets forwarding beginning with a low cooperation level. It is concluded that MPS-BNS strategy is effective in fighting against selfishness in different levels and can achieve a preferable performance. PMID:23401672

  5. THEORIZING HYBRIDITY: INSTITUTIONAL LOGICS, COMPLEX ORGANIZATIONS, AND ACTOR IDENTITIES: THE CASE OF NONPROFITS

    PubMed Central

    SKELCHER, CHRIS; SMITH, STEVEN RATHGEB

    2015-01-01

    We propose a novel approach to theorizing hybridity in public and nonprofit organizations. The concept of hybridity is widely used to describe organizational responses to changes in governance, but the literature seldom explains how hybrids arise or what forms they take. Transaction cost and organizational design literatures offer some solutions, but lack a theory of agency. We use the institutional logics approach to theorize hybrids as entities that face a plurality of normative frames. Logics provide symbolic and material elements that structure organizational legitimacy and actor identities. Contradictions between institutional logics offer space for them to be elaborated and creatively reconstructed by situated agents. We propose five types of organizational hybridity – segmented, segregated, assimilated, blended, and blocked. Each type is theoretically derived from empirically observed variations in organizational responses to institutional plurality. We develop propositions to show how our approach to hybridity adds value to academic and policy-maker audiences. PMID:26640298

  6. Identifying emergent social networks at a federally qualified health center-based farmers' market.

    PubMed

    Alia, Kassandra A; Freedman, Darcy A; Brandt, Heather M; Browne, Teri

    2014-06-01

    Identifying potential mechanisms connecting farmers' market interventions with health, economic, and community outcomes could inform strategies for addressing health disparities. The present study used social network theory to guide the in-depth examination of naturally occurring social interactions at a farmers' market located at a federally qualified health center located in a rural, low-income community. Trained observers recorded 61 observation logs at the market over 18 weeks. Thematic analysis revealed a range of actors and nonhuman facilitators instrumental to the farmers' market context. These actors connected with one another for communication and relationship development, economic and financial exchange, education, resource sharing, community ownership of the farmers' market, and conflict resolution. These interactions provided opportunities for social networks to develop among attendees, which may have facilitated the acquisition of social supports related to improved health, economic and community outcomes. Results provide insight into the role social networks may play in mediating the relationship between a farmers' market intervention and individual benefits. Findings also contribute to defining the typology of social networks, which may further disentangle the complex relationships between social networks and health outcomes. Future research should identify strategies for purposefully targeting social networks as a way to reduce diet-related health disparities. PMID:24352510

  7. A water quality monitoring network design using fuzzy theory and multiple criteria analysis.

    PubMed

    Chang, Chia-Ling; Lin, You-Tze

    2014-10-01

    A proper water quality monitoring design is required in a watershed, particularly in a water resource protected area. As numerous factors can influence the water quality monitoring design, this study applies multiple criteria analysis to evaluate the suitability of the water quality monitoring design in the Taipei Water Resource Domain (TWRD) in northern Taiwan. Seven criteria, which comprise percentage of farmland area, percentage of built-up area, amount of non-point source pollution, green cover ratio, landslide area ratio, ratio of over-utilization on hillsides, and density of water quality monitoring stations, are selected in the multiple criteria analysis. The criteria are normalized and weighted. The weighted method is applied to score the subbasins. The density of water quality stations needs to be increased in priority in the subbasins with a higher score. The fuzzy theory is utilized to prioritize the need for a higher density of water quality monitoring stations. The results show that the need for more water quality stations in subbasin 2 in the Bei-Shih Creek Basin is much higher than those in the other subbasins. Furthermore, the existing water quality station in subbasin 2 requires maintenance. It is recommended that new water quality stations be built in subbasin 2. PMID:24974234

  8. Direct gaze elicits atypical activation of the theory-of-mind network in autism spectrum conditions.

    PubMed

    von dem Hagen, Elisabeth A H; Stoyanova, Raliza S; Rowe, James B; Baron-Cohen, Simon; Calder, Andrew J

    2014-06-01

    Eye contact plays a key role in social interaction and is frequently reported to be atypical in individuals with autism spectrum conditions (ASCs). Despite the importance of direct gaze, previous functional magnetic resonance imaging in ASC has generally focused on paradigms using averted gaze. The current study sought to determine the neural processing of faces displaying direct and averted gaze in 18 males with ASC and 23 matched controls. Controls showed an increased response to direct gaze in brain areas implicated in theory-of-mind and gaze perception, including medial prefrontal cortex, temporoparietal junction, posterior superior temporal sulcus region, and amygdala. In contrast, the same regions showed an increased response to averted gaze in individuals with an ASC. This difference was confirmed by a significant gaze direction × group interaction. Relative to controls, participants with ASC also showed reduced functional connectivity between these regions. We suggest that, in the typical brain, perceiving another person gazing directly at you triggers spontaneous attributions of mental states (e.g. he is "interested" in me), and that such mental state attributions to direct gaze may be reduced or absent in the autistic brain. PMID:23324559

  9. Dissociable prefrontal networks for cognitive and affective theory of mind: a lesion study.

    PubMed

    Shamay-Tsoory, Simone G; Aharon-Peretz, Judith

    2007-10-01

    The underlying mechanisms and neuroanatomical correlates of theory of mind (ToM), the ability to make inferences on others' mental states, remain largely unknown. While numerous studies have implicated the ventromedial (VM) frontal lobes in ToM, recent findings have questioned the role of the prefrontal cortex. We designed two novel tasks that examined the hypothesis that affective ToM processing is distinct from that related to cognitive ToM and depends in part on separate anatomical substrates. The performance of patients with localized lesions in the VM was compared to responses of patients with dorsolateral lesions, mixed prefrontal lesions, and posterior lesions and with healthy control subjects. While controls made fewer errors on affective as compared to cognitive ToM conditions in both tasks, patients with VM damage showed a different trend. Furthermore, while affective ToM was mostly impaired by VM damage, cognitive ToM was mostly impaired by extensive prefrontal damage, suggesting that cognitive and affective mentalizing abilities are partly dissociable. By introducing the concept of 'affective ToM' to the study of social cognition, these results offer new insights into the mediating role of the VM in the affective facets of social behavior that may underlie the behavioral disturbances observed in these patients. PMID:17640690

  10. Functional brain networks and white matter underlying theory-of-mind in autism.

    PubMed

    Kana, Rajesh K; Libero, Lauren E; Hu, Christi P; Deshpande, Hrishikesh D; Colburn, Jeffrey S

    2014-01-01

    Human beings constantly engage in attributing causal explanations to one's own and to others' actions, and theory-of-mind (ToM) is critical in making such inferences. Although children learn causal attribution early in development, children with autism spectrum disorders (ASDs) are known to have impairments in the development of intentional causality. This functional magnetic resonance imaging (fMRI) and diffusion tensor imaging (DTI) study investigated the neural correlates of physical and intentional causal attribution in people with ASDs. In the fMRI scanner, 15 adolescents and adults with ASDs and 15 age- and IQ-matched typically developing peers made causal judgments about comic strips presented randomly in an event-related design. All participants showed robust activation in bilateral posterior superior temporal sulcus at the temporo-parietal junction (TPJ) in response to intentional causality. Participants with ASDs showed lower activation in TPJ, right inferior frontal gyrus and left premotor cortex. Significantly weaker functional connectivity was also found in the ASD group between TPJ and motor areas during intentional causality. DTI data revealed significantly reduced fractional anisotropy in ASD participants in white matter underlying the temporal lobe. In addition to underscoring the role of TPJ in ToM, this study found an interaction between motor simulation and mentalizing systems in intentional causal attribution and its possible discord in autism. PMID:22977198

  11. PRODIAG: Combined expert system/neural network for process fault diagnosis. Volume 1, Theory

    SciTech Connect

    Reifman, J.; Wei, T.Y.C.; Vitela, J.E.

    1995-09-01

    The function of the PRODIAG code is to diagnose on-line the root cause of a thermal-hydraulic (T-H) system transient with trace back to the identification of the malfunctioning component using the T-H instrumentation signals exclusively. The code methodology is based on the Al techniques of automated reasoning/expert systems (ES) and artificial neural networks (ANN). The research and development objective is to develop a generic code methodology which would be plant- and T-H-system-independent. For the ES part the only plant or T-H system specific code requirements would be implemented through input only and at that only through a Piping and Instrumentation Diagram (PID) database. For the ANN part the only plant or T-H system specific code requirements would be through the ANN training data for normal component characteristics and the same PID database information. PRODIAG would, therefore, be generic and portable from T-H system to T-H system and from plant to plant without requiring any code-related modifications except for the PID database and the ANN training with the normal component characteristics. This would give PRODIAG the generic feature which numerical simulation plant codes such as TRAC or RELAP5 have. As the code is applied to different plants and different T-H systems, only the connectivity information, the operating conditions and the normal component characteristics are changed, and the changes are made entirely through input. Verification and validation of PRODIAG would, be T-H system independent and would be performed only ``once``.

  12. Production of intoxication states by actors: perception by lay listeners.

    PubMed

    Hollien, H; DeJong, G; Martin, C A

    1998-11-01

    The effects of ingesting ethanol have been shown to be somewhat variable in humans; there appear to be but few universals. Yet, questions about intoxication often are asked by law enforcement personnel (especially relative to DUI), clinicians and various individuals in social settings. A key question: Is it possible to determine if a person is intoxicated by observing them in some manner? A closely associated one: Can speech be used for that purpose? Two of the many issues related to the second of these questions involve the possibility that (1) speakers, especially actors, can effectively mimic the speech of intoxicated individuals, and (2) they may be able to volitionally reduce any speech degradation which results from intoxication. The approach used to test these two questions tasked auditors to determine if these simulations were possible. To this end, young, healthy actors chosen on the basis of a large number of selection criteria were asked to produce several types of controlled utterances (1) during a learning phase, (2) when sober, (3) at three simulated levels of intoxication (mildly, legally and severely drunk), (4) during actual, and parallel, levels of intoxication, and (5) at the highest intoxication level attained but when attempting to sound completely sober. Two aural-perceptual studies were conducted; both involved counterbalanced ABX procedures where each subject was paired with him/herself. Listeners were normally hearing university students drawn from undergraduate phonetics and linguistics courses. In the first study, they rated the actors as being more intoxicated--when they actually were sober but simulating drunkenness--88% more often than when they actually were intoxicated. In the second study, they were judged as sounding less inebriated when attempting to sound sober (than they actually were) 61% of the time. These relationships would appear to impact a number of situations; one of special importance would be the detection of

  13. Macro-actor execution on multilevel data-driven architectures

    SciTech Connect

    Gaudiot, J.L.; Najjar, W.

    1988-12-31

    The data-flow model of computation brings to multiprocessors high programmability at the expense of increased overhead. Applying the model at a higher level leads to better performance but also introduces loss of parallelism. We demonstrate here syntax directed program decomposition methods for the creation of large macro-actors in numerical algorithms. In order to alleviate some of the problems introduced by the lower resolution interpretation, we describe a multi-level of resolution and analyze the requirements for its actual hardware and software integration.

  14. The dynamic consequences of cooperation and competition in small-world networks.

    PubMed

    Fernández-Rosales, Iván Y; Liebovitch, Larry S; Guzmán-Vargas, Lev

    2015-01-01

    We present a study of the social dynamics among cooperative and competitive actors interacting on a complex network that has a small-world topology. In this model, the state of each actor depends on its previous state in time, its inertia to change, and the influence of its neighboring actors. Using numerical simulations, we determine how the distribution of final states of the actors and measures of the distances between the values of the actors at local and global levels, depend on the number of cooperative to competitive actors and the connectivity of the actors in the network. We find that similar numbers of cooperative and competitive actors yield the lowest values for the local and global measures of the distances between the values of the actors. On the other hand, when the number of either cooperative or competitive actors dominate the system, then the divergence is largest between the values of the actors. Our findings make new testable predictions on how the dynamics of a conflict depends on the strategies chosen by groups of actors and also have implications for the evolution of behaviors. PMID:25927995

  15. The Dynamic Consequences of Cooperation and Competition in Small-World Networks

    PubMed Central

    Fernández-Rosales, Iván Y.; Liebovitch, Larry S.; Guzmán-Vargas, Lev

    2015-01-01

    We present a study of the social dynamics among cooperative and competitive actors interacting on a complex network that has a small-world topology. In this model, the state of each actor depends on its previous state in time, its inertia to change, and the influence of its neighboring actors. Using numerical simulations, we determine how the distribution of final states of the actors and measures of the distances between the values of the actors at local and global levels, depend on the number of cooperative to competitive actors and the connectivity of the actors in the network. We find that similar numbers of cooperative and competitive actors yield the lowest values for the local and global measures of the distances between the values of the actors. On the other hand, when the number of either cooperative or competitive actors dominate the system, then the divergence is largest between the values of the actors. Our findings make new testable predictions on how the dynamics of a conflict depends on the strategies chosen by groups of actors and also have implications for the evolution of behaviors. PMID:25927995

  16. Associations between Perceived HIV Stigma and Quality of Life at the Dyadic Lvel: The Actor-Partner Interdependence Model

    PubMed Central

    Liu, Hongjie; Xu, Yongfang; Lin, Xinjin; Shi, Jian; Chen, Shiyi

    2013-01-01

    Background Few studies have investigated the relationship between HIV-related stigma and quality life at the dyadic level. The objective of this study was to examine the actor and partner effects of stigma that was perceived by people living with HIV/AIDS (PLWHAs) and caregivers on quality of life at the dyadic level. Method A survey was conducted among 148 dyads consisting of one PLWHA and one caregiver (296 participants) in Nanning, China. The interdependent relationship between a pair of dyadic members that influences the associations between stigma and quality of life was analyzed, using an innovative dyadic analysis technique: the Actor-Partner Interdependence Model (APIM). Results We found in this dyadic analysis that (1) PLWHAs compared to their caregivers exhibited a higher level of perceived HIV stigma and lower level of quality of life measured in four domains; (2) both PLWHAs' and caregivers' perceived HIV stigma influenced their own quality of life; (3) The quality of life was not substantially influenced by their partners' perceived stigma; and (4) Both actor and partner effects of stigma on quality of life were similar among PLWHAs and their caregivers. Conclusion As HIV stigma and quality of life are complex phenomena rooted in cultures, intervention programs should be carefully planned based on social or cognitive theories and should be culturally adopted. PMID:23383343

  17. European Schoolnet: Enabling School Networking

    ERIC Educational Resources Information Center

    Scimeca, Santi; Dumitru, Petru; Durando, Marc; Gilleran, Anne; Joyce, Alexa; Vuorikari, Riina

    2009-01-01

    School networking is increasingly important in a globalised world, where schools themselves can be actors on an international stage. This article builds on the activities and experience of the longest established European initiative in this area, European Schoolnet (EUN), a network of 31 Ministries of Education. First, we offer an introduction…

  18. What about the "actor's formant" in actresses' voices?

    PubMed

    Master, Suely; De Biase, Noemi Grigolleto; Madureira, Sandra

    2012-05-01

    Spectrographic analysis of male actors' voices showed a cluster, the "actor's formant" (AF), which is related to the perception of good and projected voice quality. To date, similar phenomena have not been described in the voices of actresses. Therefore, the objective of the current investigation was to compare actresses' and nonactresses' voices through acoustic analysis to verify the existence of the "AF" cluster or the strategies used to produce the performing voice. Thirty actresses and 30 nonactresses volunteered as subjects in the present study. All subjects read a 40-second text at both habitual and loud levels. Praat (v.5.1) was then used to analyze equivalent sound pressure level (Leq), speaking fundamental frequency (SFF), and in the long-term average spectrum window, the difference between the amplitude level of the fundamental frequency and first formant (L1-L0), the spectral tilt (alpha ratio), and the amplitude and frequency of the "AF" region. Significant differences between the groups, in both levels, were observed for SFF and L1-L0, with actresses presenting lower values. There were no significant differences between groups for Leq or alpha ratio at either level. There was no evidence of an "AF" cluster in the actresses' voices. Voice projection for this group of actresses seemed to be mainly a result of a laryngeal setting instead of vocal tract resonances. PMID:21376530

  19. Effects of Social Support About Physical Activity on Social Networking Sites: Applying the Theory of Planned Behavior.

    PubMed

    Zhang, Ni; Campo, Shelly; Yang, Jingzhen; Janz, Kathleen F; Snetselaar, Linda G; Eckler, Petya

    2015-01-01

    Despite the physical and mental health benefits of leisure-time physical activity (LTPA), only about half of college students participate in the recommended amount of LTPA. While college students are avid users of social network sites (SNSs), whether SNSs would be an effective channel for promoting LTPA through peer social support is unclear. The aim of this study was to explore the effects of social support from students' contacts on SNSs on their intention to participate in LTPA, applying the Theory of Planned Behavior. Participants were recruited through a mass e-mail sent to undergraduate students at a large Midwestern university in fall 2011. In total, 439 surveys were analyzed. Descriptive analyses and analysis for mediating effects were conducted. Social support about LTPA from contacts on SNSs has indirect effect on intention through affective attitude, instrumental attitude, and perceived behavioral control (PBC). The results indicate that social support about LTPA from contacts on SNSs might not be effective to change students' intention unless attitudes and PBC are changed. Future interventions aiming to promote students' intention to participate in LTPA by increasing support from contacts on SNSs should increase affective attitude, instrumental attitude, and PBC at the same time. PMID:26086237

  20. Combined Computational Approach Based on Density Functional Theory and Artificial Neural Networks for Predicting The Solubility Parameters of Fullerenes.

    PubMed

    Perea, J Darío; Langner, Stefan; Salvador, Michael; Kontos, Janos; Jarvas, Gabor; Winkler, Florian; Machui, Florian; Görling, Andreas; Dallos, Andras; Ameri, Tayebeh; Brabec, Christoph J

    2016-05-19

    The solubility of organic semiconductors in environmentally benign solvents is an important prerequisite for the widespread adoption of organic electronic appliances. Solubility can be determined by considering the cohesive forces in a liquid via Hansen solubility parameters (HSP). We report a numerical approach to determine the HSP of fullerenes using a mathematical tool based on artificial neural networks (ANN). ANN transforms the molecular surface charge density distribution (σ-profile) as determined by density functional theory (DFT) calculations within the framework of a continuum solvation model into solubility parameters. We validate our model with experimentally determined HSP of the fullerenes C60, PC61BM, bisPC61BM, ICMA, ICBA, and PC71BM and through comparison with previously reported molecular dynamics calculations. Most excitingly, the ANN is able to correctly predict the dispersive contributions to the solubility parameters of the fullerenes although no explicit information on the van der Waals forces is present in the σ-profile. The presented theoretical DFT calculation in combination with the ANN mathematical tool can be easily extended to other π-conjugated, electronic material classes and offers a fast and reliable toolbox for future pathways that may include the design of green ink formulations for solution-processed optoelectronic devices. PMID:27070101

  1. Novel paradigm for constructing masses in Dempster-Shafer evidence theory for wireless sensor network's multisource data fusion.

    PubMed

    Zhang, Zhenjiang; Liu, Tonghuan; Zhang, Wenyu

    2014-01-01

    Dempster-Shafer evidence theory (DSET) is a flexible and popular paradigm for multisource data fusion in wireless sensor networks (WSNs). This paper presents a novel and easy implementing method computing masses from the hundreds of pieces of data collected by a WSN. The transfer model is based on the Mahalanobis distance (MD), which is an effective method to measure the similarity between an object and a sample. Compared to the existing methods, the proposed method concerns the statistical features of the observed data and it is good at transferring multi-dimensional data to belief assignment correctly and effectively. The main processes of the proposed method, which include the calculation of the intersection classes of the power set and the algorithm mapping MDs to masses, are described in detail. Experimental results in transformer fault diagnosis show that the proposed method has a high accuracy in constructing masses from multidimensional data for DSET. Additionally, the results also prove that higher dimensional data brings higher accuracy in transferring data to mass. PMID:24759109

  2. Novel Paradigm for Constructing Masses in Dempster-Shafer Evidence Theory for Wireless Sensor Network's Multisource Data Fusion

    PubMed Central

    Zhang, Zhenjiang; Liu, Tonghuan; Zhang, Wenyu

    2014-01-01

    Dempster-Shafer evidence theory (DSET) is a flexible and popular paradigm for multisource data fusion in wireless sensor networks (WSNs). This paper presents a novel and easy implementing method computing masses from the hundreds of pieces of data collected by a WSN. The transfer model is based on the Mahalanobis distance (MD), which is an effective method to measure the similarity between an object and a sample. Compared to the existing methods, the proposed method concerns the statistical features of the observed data and it is good at transferring multi-dimensional data to belief assignment correctly and effectively. The main processes of the proposed method, which include the calculation of the intersection classes of the power set and the algorithm mapping MDs to masses, are described in detail. Experimental results in transformer fault diagnosis show that the proposed method has a high accuracy in constructing masses from multidimensional data for DSET. Additionally, the results also prove that higher dimensional data brings higher accuracy in transferring data to mass. PMID:24759109

  3. Trigonometrical sums connected with the chiral Potts model, Verlinde dimension formula, two-dimensional resistor network, and number theory

    SciTech Connect

    Chair, Noureddine

    2014-02-15

    We have recently developed methods for obtaining exact two-point resistance of the complete graph minus N edges. We use these methods to obtain closed formulas of certain trigonometrical sums that arise in connection with one-dimensional lattice, in proving Scott’s conjecture on permanent of Cauchy matrix, and in the perturbative chiral Potts model. The generalized trigonometrical sums of the chiral Potts model are shown to satisfy recursion formulas that are transparent and direct, and differ from those of Gervois and Mehta. By making a change of variables in these recursion formulas, the dimension of the space of conformal blocks of SU(2) and SO(3) WZW models may be computed recursively. Our methods are then extended to compute the corner-to-corner resistance, and the Kirchhoff index of the first non-trivial two-dimensional resistor network, 2×N. Finally, we obtain new closed formulas for variant of trigonometrical sums, some of which appear in connection with number theory. -- Highlights: • Alternative derivation of certain trigonometrical sums of the chiral Potts model are given. • Generalization of these trigonometrical sums satisfy recursion formulas. • The dimension of the space of conformal blocks may be computed from these recursions. • Exact corner-to-corner resistance, the Kirchhoff index of 2×N are given.

  4. Visions of the Future - the Changing Role of Actors in Data-Intensive Science

    NASA Astrophysics Data System (ADS)

    Schäfer, L.; Klump, J. F.

    2013-12-01

    ? This gives rise to the question of what tools are required to locate and pursue the correct course in a networked world. One tool from the area of innovation management is the scenario technique. This poster will outline visions of the future as possible developments of the scientific world in 2020 (or later). The scenarios presented will show possible developments - both positive and negative. It is up then to the actors themselves to define their own position in this context, to rethink it and consider steps that can achieve a positive development for the future.

  5. Action adaptation during natural unfolding social scenes influences action recognition and inferences made about actor beliefs.

    PubMed

    Keefe, Bruce D; Wincenciak, Joanna; Jellema, Tjeerd; Ward, James W; Barraclough, Nick E

    2016-07-01

    When observing another individual's actions, we can both recognize their actions and infer their beliefs concerning the physical and social environment. The extent to which visual adaptation influences action recognition and conceptually later stages of processing involved in deriving the belief state of the actor remains unknown. To explore this we used virtual reality (life-size photorealistic actors presented in stereoscopic three dimensions) to see how visual adaptation influences the perception of individuals in naturally unfolding social scenes at increasingly higher levels of action understanding. We presented scenes in which one actor picked up boxes (of varying number and weight), after which a second actor picked up a single box. Adaptation to the first actor's behavior systematically changed perception of the second actor. Aftereffects increased with the duration of the first actor's behavior, declined exponentially over time, and were independent of view direction. Inferences about the second actor's expectation of box weight were also distorted by adaptation to the first actor. Distortions in action recognition and actor expectations did not, however, extend across different actions, indicating that adaptation is not acting at an action-independent abstract level but rather at an action-dependent level. We conclude that although adaptation influences more complex inferences about belief states of individuals, this is likely to be a result of adaptation at an earlier action recognition stage rather than adaptation operating at a higher, more abstract level in mentalizing or simulation systems. PMID:27472496

  6. The actor as context for social judgments: effects of prior impressions and stereotypes.

    PubMed

    Stewart, T L; Doan, K A; Gingrich, B E; Smith, E R

    1998-11-01

    Three experiments identified conditions under which trait judgments made about a behavior were more likely to influence later judgments of the behavior. In Experiment 1, participants made trait judgments about numerous behaviors presented with photos of actors. Some behaviors were repeated, paired with the same or a different actor. All repeated behaviors were judged faster than new behaviors. Facilitation was greatest when repeated behaviors were paired with the same actor, suggesting greater influence of prior judgments in this condition. Experiments 2 and 3 replicated this effect, and the pattern of response times (RTs) suggested a stronger association between the actor and behavior when a prior impression of the actor had been formed (Experiment 2) and when the behavior was stereotypic of the actor's group (Experiment 3). Level of prejudice moderated RT patterns in Experiment 3. Implications for context effects, the nature of trait inferences, and stereotype change are discussed. PMID:9866181

  7. Mesenchymal Stem Cells after Polytrauma: Actor and Target.

    PubMed

    Huber-Lang, Markus; Wiegner, Rebecca; Lampl, Lorenz; Brenner, Rolf E

    2016-01-01

    Mesenchymal stem cells (MSCs) are multipotent cells that are considered indispensable in regeneration processes after tissue trauma. MSCs are recruited to damaged areas via several chemoattractant pathways where they function as "actors" in the healing process by the secretion of manifold pro- and anti-inflammatory, antimicrobial, pro- and anticoagulatory, and trophic/angiogenic factors, but also by proliferation and differentiation into the required cells. On the other hand, MSCs represent "targets" during the pathophysiological conditions after severe trauma, when excessively generated inflammatory mediators, complement activation factors, and damage- and pathogen-associated molecular patterns challenge MSCs and alter their functionality. This in turn leads to complement opsonization, lysis, clearance by macrophages, and reduced migratory and regenerative abilities which culminate in impaired tissue repair. We summarize relevant cellular and signaling mechanisms and provide an up-to-date overview about promising future therapeutic MSC strategies in the context of severe tissue trauma. PMID:27340408

  8. Role of Actors and Gender Factor in Disaster Management

    NASA Astrophysics Data System (ADS)

    Gundogdu, Oguz; Isik, Ozden; Ozcep, Ferhat; Goksu, Goksel

    2014-05-01

    In Turkey, the discussions in the modern sense about disaster management begun after the 1992 Erzincan and the 1995 Dinar earthquakes, faulting in terms of features and effects. These earthquakes are "Urban Earthquakes'' with effects and faulting charectristics, and have led to radical changes in terms of disaster and disaster management. Disaster Management, to become a science in the world, but with the 1999 Izmit and Duzce earthquakes in Turkey has begun to take seriously on the agenda. Firstly, such as Civil Defense and Red Crescent organizations, by transforming its own, have entered into a new organizing effort. By these earthquakes, NGO's have contributed the search-rescue efforts in the field and to the process of normalization of life. Because "the authority and responsibilities" of NGO's could not be determined, and could not be in planning and scenario studies, we faced the problems. Thus, to the citizens of our country-specific "voluntary" has not benefited enough from the property. The most important development in disaster management in 2009, the Disaster and Emergency Management Presidency (AFAD) has been the establishment. However, in terms of coordination and accreditation to the target point has been reached yet. Another important issue in disaster management (need to be addressed along with disaster actors) is the role of women in disasters. After the Golcuk Earthquake, successful field works of women and women's victimization has attracted attention in two different directions. Gender-sensitive policies should be noted by the all disaster actors due to the importance of the mitigation, and these policies should take place in laws, regulations and planning.

  9. Modeling the low-cycle fatigue behavior of visco-hyperelastic elastomeric materials using a new network alteration theory: Application to styrene-butadiene rubber

    NASA Astrophysics Data System (ADS)

    Ayoub, G.; Zaïri, F.; Naït-Abdelaziz, M.; Gloaguen, J. M.

    2011-02-01

    Although several theories were more or less recently proposed to describe the Mullins effect, i.e. the stress-softening after the first load, the nonlinear equilibrium and non-equilibrium material response as well as the continuous stress-softening during fatigue loading need to be included in the analysis to propose a reliable design of rubber structures. This contribution presents for the first time a network alteration theory, based on physical interpretations of the stress-softening phenomenon, to capture the time-dependent mechanical response of elastomeric materials under fatigue loading, and this until failure. A successful physically based visco-hyperelastic model is revisited by introducing an evolution law for the physical material parameters affected by the network alteration. The general form of the model can be basically represented by two parallel networks: a nonlinear equilibrium response and a time-dependent deviation from equilibrium, in which the network parameters become functions of the damage rate (defined as the ratio of the applied cycle over the applied cycle to failure). The mechanical behavior of styrene-butadiene rubber was experimentally investigated, and the main features of the constitutive response under fatigue loading are highlighted. The experimental results demonstrate that the evolution of the normalized maximum stress only depends on the damage rate endured by the material during the fatigue loading history. The average chain length and the average chain density are then taken as functions of the damage rate in the proposed network alteration theory. The new model is found to adequately capture the important features of the observed stress-strain curves under loading-unloading for a large spectrum of strain and damage levels. The model capabilities to predict variable amplitude tests are critically discussed by comparisons with experiments.

  10. Epistemology and Networking Theories

    ERIC Educational Resources Information Center

    Kidron, Ivy

    2016-01-01

    A theoretical reflection on epistemology is presented. The important role of epistemological analysis in research in mathematics education is discussed. I analyze the epistemological evolution as a consequence of the changes in the mathematical culture and demonstrate how the epistemological analysis is tightly linked to the cultural dimension.…

  11. The role of multisensor data fusion in neuromuscular control of a sagittal arm with a pair of muscles using actor-critic reinforcement learning method.

    PubMed

    Golkhou, V; Parnianpour, M; Lucas, C

    2004-01-01

    In this study, we consider the role of multisensor data fusion in neuromuscular control using an actor-critic reinforcement learning method. The model we use is a single link system actuated by a pair of muscles that are excited with alpha and gamma signals. Various physiological sensor information such as proprioception, spindle sensors, and Golgi tendon organs have been integrated to achieve an oscillatory movement with variable amplitude and frequency, while achieving a stable movement with minimum metabolic cost and coactivation. The system is highly nonlinear in all its physical and physiological attributes. Transmission delays are included in the afferent and efferent neural paths to account for a more accurate representation of the reflex loops. This paper proposes a reinforcement learning method with an Actor-Critic architecture instead of middle and low level of central nervous system (CNS). The Actor in this structure is a two layer feedforward neural network and the Critic is a model of the cerebellum. The Critic is trained by the State-Action-Reward-State-Action (SARSA) method. The Critic will train the Actor by supervisory learning based on previous experiences. The reinforcement signal in SARSA is evaluated based on available alternatives concerning the concept of multisensor data fusion. The effectiveness and the biological plausibility of the present model are demonstrated by several simulations. The system showed excellent tracking capability when we integrated the available sensor information. Addition of a penalty for activation of muscles resulted in much lower muscle coactivation while keeping the movement stable. PMID:15671597

  12. Description of earthquake sequences using complex network theory: the cases of Italy (L'Aquila, 2009) and Southern California (Baja, 2010)

    NASA Astrophysics Data System (ADS)

    Daskalaki, E.; Papadopoulos, G. A.; Minadakis, G.; Spiliotis, K.; Siettos, C.

    2013-12-01

    Complex networks pertain to the structure of many real-world systems influencing their dynamics. Earthquakes are a highly complex natural process that develops in the space-time-size domains given that the state of the seismogenic layer of the Earth is characterized by self-organized criticality. Over the last years, complex network theory was tested as a tool to quantify the topological characteristics of seismic activity aiming to investigate possible correlation patterns between earthquakes. With the aid of complex network theory, we have analyzed foreshock and aftershock sequences associated with the mainshocks of L'Aquila (Italy), 6th April 2009, Mw=6.3, and of Baja (Southern California) 4th April 2010, Mw=7.2. After testing the catalogues for data completeness on the basis of the magnitude-frequency relationship, we selected magnitude cut-off of 1.3 and 1.0, respectively. We constructed the underlying network that describes the evolution of the two sequences in space and extracted the statistical properties of the underlying topology resulting in characteristic scale-free and small-world structures. We found that the corresponding earthquake networks form a scale-free degree distribution and we computed their basic statistical measures, such as the Average Clustering Coefficient, Mean Path Length and Entropy. Taking into account a spatio-temporal sensitivity analysis, we found that the statistical measures of the two networks change considerably before and after the two main shocks, thus underlying the space-time clustering of the sequences. Our findings are in agreement with the ones obtained by using well established classical methods of statistical seismology. Thus, we believe that the proposed approach has the potential to serve as a supplementary or stand-alone methodology towards the better assessment of seismicity clusters

  13. Digital Ecology: Coexistence and Domination among Interacting Networks

    PubMed Central

    Kleineberg, Kaj-Kolja; Boguñá, Marián

    2015-01-01

    The overwhelming success of Web 2.0, within which online social networks are key actors, has induced a paradigm shift in the nature of human interactions. The user-driven character of Web 2.0 services has allowed researchers to quantify large-scale social patterns for the first time. However, the mechanisms that determine the fate of networks at the system level are still poorly understood. For instance, the simultaneous existence of multiple digital services naturally raises questions concerning which conditions these services can coexist under. Analogously to the case of population dynamics, the digital world forms a complex ecosystem of interacting networks. The fitness of each network depends on its capacity to attract and maintain users’ attention, which constitutes a limited resource. In this paper, we introduce an ecological theory of the digital world which exhibits stable coexistence of several networks as well as the dominance of an individual one, in contrast to the competitive exclusion principle. Interestingly, our theory also predicts that the most probable outcome is the coexistence of a moderate number of services, in agreement with empirical observations. PMID:25988318

  14. Digital Ecology: Coexistence and Domination among Interacting Networks

    NASA Astrophysics Data System (ADS)

    Kleineberg, Kaj-Kolja; Boguñá, Marián

    2015-05-01

    The overwhelming success of Web 2.0, within which online social networks are key actors, has induced a paradigm shift in the nature of human interactions. The user-driven character of Web 2.0 services has allowed researchers to quantify large-scale social patterns for the first time. However, the mechanisms that determine the fate of networks at the system level are still poorly understood. For instance, the simultaneous existence of multiple digital services naturally raises questions concerning which conditions these services can coexist under. Analogously to the case of population dynamics, the digital world forms a complex ecosystem of interacting networks. The fitness of each network depends on its capacity to attract and maintain users’ attention, which constitutes a limited resource. In this paper, we introduce an ecological theory of the digital world which exhibits stable coexistence of several networks as well as the dominance of an individual one, in contrast to the competitive exclusion principle. Interestingly, our theory also predicts that the most probable outcome is the coexistence of a moderate number of services, in agreement with empirical observations.

  15. Kevin Bacon and Graph Theory

    ERIC Educational Resources Information Center

    Hopkins, Brian

    2004-01-01

    The interconnected world of actors and movies is a familiar, rich example for graph theory. This paper gives the history of the "Kevin Bacon Game" and makes extensive use of a Web site to analyze the underlying graph. The main content is the classroom development of the weighted average to determine the best choice of "center" for the graph. The…

  16. Dissecting the social brain: Introducing the EmpaToM to reveal distinct neural networks and brain-behavior relations for empathy and Theory of Mind.

    PubMed

    Kanske, Philipp; Böckler, Anne; Trautwein, Fynn-Mathis; Singer, Tania

    2015-11-15

    Successful social interactions require both affect sharing (empathy) and understanding others' mental states (Theory of Mind, ToM). As these two functions have mostly been investigated in isolation, the specificity of the underlying neural networks and the relation of these networks to the respective behavioral indices could not be tested. Here, we present a novel fMRI paradigm (EmpaToM) that independently manipulates both empathy and ToM. Experiments 1a/b (N=90) validated the task with established empathy and ToM paradigms on a behavioral and neural level. Experiment 2 (N=178) employed the EmpaToM and revealed clearly separable neural networks including anterior insula for empathy and ventral temporoparietal junction for ToM. These distinct networks could be replicated in task-free resting state functional connectivity. Importantly, brain activity in these two networks specifically predicted the respective behavioral indices, that is, inter-individual differences in ToM related brain activity predicted inter-individual differences in ToM performance, but not empathic responding, and vice versa. Taken together, the validated EmpaToM allows separation of affective and cognitive routes to understanding others. It may thus benefit future clinical, developmental, and intervention studies on identifying selective impairments and improvement in specific components of social cognition. PMID:26254589

  17. Discriminating micropathogen lineages and their reticulate evolution through graph theory-based network analysis: the case of Trypanosoma cruzi, the agent of Chagas disease.

    PubMed

    Arnaud-Haond, Sophie; Moalic, Yann; Barnabé, Christian; Ayala, Francisco José; Tibayrenc, Michel

    2014-01-01

    Micropathogens (viruses, bacteria, fungi, parasitic protozoa) share a common trait, which is partial clonality, with wide variance in the respective influence of clonality and sexual recombination on the dynamics and evolution of taxa. The discrimination of distinct lineages and the reconstruction of their phylogenetic history are key information to infer their biomedical properties. However, the phylogenetic picture is often clouded by occasional events of recombination across divergent lineages, limiting the relevance of classical phylogenetic analysis and dichotomic trees. We have applied a network analysis based on graph theory to illustrate the relationships among genotypes of Trypanosoma cruzi, the parasitic protozoan responsible for Chagas disease, to identify major lineages and to unravel their past history of divergence and possible recombination events. At the scale of T. cruzi subspecific diversity, graph theory-based networks applied to 22 isoenzyme loci (262 distinct Multi-Locus-Enzyme-Electrophoresis -MLEE) and 19 microsatellite loci (66 Multi-Locus-Genotypes -MLG) fully confirms the high clustering of genotypes into major lineages or "near-clades". The release of the dichotomic constraint associated with phylogenetic reconstruction usually applied to Multilocus data allows identifying putative hybrids and their parental lineages. Reticulate topology suggests a slightly different history for some of the main "near-clades", and a possibly more complex origin for the putative hybrids than hitherto proposed. Finally the sub-network of the near-clade T. cruzi I (28 MLG) shows a clustering subdivision into three differentiated lesser near-clades ("Russian doll pattern"), which confirms the hypothesis recently proposed by other investigators. The present study broadens and clarifies the hypotheses previously obtained from classical markers on the same sets of data, which demonstrates the added value of this approach. This underlines the potential of graph

  18. Commercial Actors and the Governing of Education: The Case of Academy School Sponsors in England

    ERIC Educational Resources Information Center

    Papanastasiou, Natalie

    2013-01-01

    This article explores the ways in which commercial actors are operating in state education by focusing on the case study of England's academies policy. First of all the discussion outlines the development of academies over time and the way in which the policy has provided opportunities for private actors to become involved in the state…

  19. West Side Silence: Producing "West Side Story" with Deaf and Hearing Actors.

    ERIC Educational Resources Information Center

    Brewer, Diane

    2002-01-01

    Details a collaborative production of "West Side Story" with hearing actors from MacMurray College and deaf actors from the Illinois School for the Deaf. Explores some of the practical dilemmas encountered as the distinctions between the Deaf and hearing communities were negotiated. Explains that the show explored the ways in which sign language…

  20. Managing the Bologna Process at the European Level: Institution and Actor Dynamics

    ERIC Educational Resources Information Center

    Lazetic, Predrag

    2010-01-01

    This article analyses the work of the Bologna Follow Up Group as the main institution of the Bologna Process and the perceptions of the policy actors involved concerning the character of the process in terms of its functioning in contrast to similar multi-level multi-actor European processes, its modes of communication and consensus seeking, as…