Science.gov

Sample records for actor network theory

  1. Up the ANTe: Understanding Entrepreneurial Leadership Learning through Actor-Network Theory

    ERIC Educational Resources Information Center

    Smith, Sue; Kempster, Steve; Barnes, Stewart

    2017-01-01

    This article explores the role of educators in supporting the development of entrepreneurial leadership learning by creating peer learning networks of owner-managers of small businesses. Using actor-network theory, the authors think through the process of constructing and maintaining a peer learning network (conceived of as an actor-network) and…

  2. 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

  3. 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…

  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. ("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…

  8. Putting Gino's lesson to work: Actor-network theory, enacted humanity, and rehabilitation.

    PubMed

    Abrams, Thomas; Gibson, Barbara E

    2016-02-01

    This article argues that rehabilitation enacts a particular understanding of "the human" throughout therapeutic assessment and treatment. Following Michel Callon and Vololona Rabeharisoa's "Gino's Lesson on Humanity," we suggest that this is not simply a top-down process, but is cultivated in the application and response to biomedical frameworks of human ability, competence, and responsibility. The emergence of the human is at once a materially contingent, moral, and interpersonal process. We begin the article by outlining the basics of the actor-network theory that underpins "Gino's Lesson on Humanity." Next, we elucidate its central thesis regarding how disabled personhood emerges through actor-network interactions. Section "Learning Gino's lesson" draws on two autobiographical examples, examining the emergence of humanity through rehabilitation, particularly assessment measures and the responses to them. We conclude by thinking about how rehabilitation and actor-network theory might take this lesson on humanity seriously.

  9. 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

  10. 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.

  11. Taking data seriously: the value of actor-network theory in rethinking patient experience data

    PubMed Central

    Zoccatelli, Giulia; Adams, Mary; Allen, Davina; Brearley, Sally; Rafferty, Anne Marie; Robert, Glenn; Donetto, Sara

    2017-01-01

    Hospitals are awash with patient experience data, much of it collected with the ostensible purpose of improving the quality of patient care. However, there has been comparatively little consideration of the nature and capacities of data itself. Using insights from actor-network theory, we propose that paying attention to patient experience data as having agency in particular hospital interactions allows us to better trace how and in what circumstances data lead (or fail to lead) to quality improvement. PMID:28429970

  12. [A non-classical approach to medical practices: Michel Foucault and Actor-Network Theory].

    PubMed

    Bińczyk, E

    2001-01-01

    The text presents an analysis of medical practices stemming from two sources: Michel Foucault's conception and the research of Annemarie Mol and John Law, representatives of a trend known as Actor-Network Theory. Both approaches reveal significant theoretical kinship: they can be successfully consigned to the framework of non-classical sociology of science. I initially refer to the cited conceptions as a version of non-classical sociology of medicine. The identity of non-classical sociology of medicine hinges on the fact that it undermines the possibility of objective definitions of disease, health and body. These are rather approached as variable social and historical phenomena, co-constituted by medical practices. To both Foucault and Mol the main object of interest was not medicine as such, but rather the network of medical practices. Mol and Law sketch a new theoretical perspective for the analysis of medical practices. They attempt to go beyond the dichotomous scheme of thinking about the human body as an object of medical research and the subject of private experience. Research on patients suffering blood-sugar deficiency provide the empirical background for the thesis of Actor-Network Theory representatives. Michel Foucault's conceptions are extremely critical of medical practices. The French researcher describes the processes of 'medicalising' Western society as the emergence of a new type of power. He attempts to sensitise the reader to the ethical dimension of the processes of medicalising society.

  13. 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.

  14. Beyond the Player: A User-Centered Approach to Analyzing Digital Games and Players Using Actor-Network Theory

    ERIC Educational Resources Information Center

    Hung, Aaron Chia Yuan

    2016-01-01

    The paper uses actor-network theory (ANT) to analyze the sociotechnical networks of three groups of adolescents who played online games in different physical and social contexts. These include: an internet café, which allowed the players to be co-present; a personal laptop, which gave the player more control over how he played; and at home through…

  15. Actor-Network Theory and methodology: Just what does it mean to say that nonhumans have agency?

    PubMed

    Sayes, Edwin

    2014-02-01

    Actor-Network Theory is a controversial social theory. In no respect is this more so than the role it 'gives' to nonhumans: nonhumans have agency, as Latour provocatively puts it. This article aims to interrogate the multiple layers of this declaration to understand what it means to assert with Actor-Network Theory that nonhumans exercise agency. The article surveys a wide corpus of statements by the position's leading figures and emphasizes the wider methodological framework in which these statements are embedded. With this work done, readers will then be better placed to reject or accept the Actor-Network position - understanding more precisely what exactly it is at stake in this decision.

  16. Unpacking complexity in public health interventions with the Actor-Network Theory.

    PubMed

    Bilodeau, Angèle; Potvin, Louise

    2016-08-04

    This article proposes a sociologically informed theoretical and methodological framework to address the complexity of public health interventions (PHI). It first proposes three arguments in favour of using the Actor-Network Theory (ANT) for the framework. ANT: (1) deals with systems made of human and non-human entities and proposes a relational view of action; (2) provides an understanding of the intervention-context interactions and (3) is a tool for opening the intervention's black box. Three principles derived from ANT addressing theoretical problems with conceptualisation of PHI as complex systems are proposed: (1) to focus on the process of connecting the network entities instead of their stabilised form; (2) both human and non-human entities composing networks have performative capacities and (3) network and intervention shape one another. Three methodological guidelines are further derived: (1) the researcher's task consists in documenting the events that transform the network and intervention; (2) events must be ordered chronologically to represent the intervention's evolution and (3) a broad range of data is needed to capture complex interventions' evolution. Using ANT as a guide, this paper helps reconcile technicist and social views of PHI and provides a mean to integrate process and effect studies of interventions.

  17. 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

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

    PubMed

    Cresswell, Kathrin M; Worth, Allison; Sheikh, Aziz

    2010-11-01

    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. 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. 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.

  19. 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.

  20. 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…

  1. 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…

  2. 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…

  3. 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…

  4. Rethinking agency and medical adherence technology: applying Actor Network Theory to the case study of Digital Pills.

    PubMed

    Hurtado-de-Mendoza, Alejandra; Cabling, Mark L; Sheppard, Vanessa B

    2015-12-01

    Much literature surrounding medical technology and adherence posits that technology is a mechanism for social control. This assumes that the medical establishment can take away patients' agency. Although power relationships and social control can play a key role, medical technology can also serve as an agentive tool to be utilized. We (1) offer the alternative framework of Actor Network Theory to view medical technology, (2) discuss the literature on medication adherence and technology, (3) delve into the ramifications of looking at adherence as a network and (4) use Digital Pills as a case study of dispersed agency.

  5. 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

  6. 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

  7. 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.

  8. The Changing Landscape of Literacy Curriculum in a Sino-Canada Transnational Education Programme: An Actor-Network Theory Informed Case Study

    ERIC Educational Resources Information Center

    Zhang, Zheng; Heydon, Rachel

    2016-01-01

    This paper concerns an exploratory and interpretive case study of the literacy curricula in a Canadian transnational education programme (Pseudonym: SCS) delivered in China where Ontario secondary school curricula were used at the same time as the Chinese national high school curricula. Using ethnographic tools and actor-network theory, the study…

  9. The Changing Landscape of Literacy Curriculum in a Sino-Canada Transnational Education Programme: An Actor-Network Theory Informed Case Study

    ERIC Educational Resources Information Center

    Zhang, Zheng; Heydon, Rachel

    2016-01-01

    This paper concerns an exploratory and interpretive case study of the literacy curricula in a Canadian transnational education programme (Pseudonym: SCS) delivered in China where Ontario secondary school curricula were used at the same time as the Chinese national high school curricula. Using ethnographic tools and actor-network theory, the study…

  10. Efficient Actor Recovery Paradigm for Wireless Sensor and Actor Networks

    PubMed Central

    Mahjoub, Reem K.; Elleithy, Khaled

    2017-01-01

    The actor nodes are the spine of wireless sensor and actor networks (WSANs) that collaborate to perform a specific task in an unverified and uneven environment. Thus, there is a possibility of high failure rate in such unfriendly scenarios due to several factors such as power consumption of devices, electronic circuit failure, software errors in nodes or physical impairment of the actor nodes and inter-actor connectivity problem. Therefore, it is extremely important to discover the failure of a cut-vertex actor and network-disjoint in order to improve the Quality-of-Service (QoS). In this paper, we propose an Efficient Actor Recovery (EAR) paradigm to guarantee the contention-free traffic-forwarding capacity. The EAR paradigm consists of a Node Monitoring and Critical Node Detection (NMCND) algorithm that monitors the activities of the nodes to determine the critical node. In addition, it replaces the critical node with backup node prior to complete node-failure which helps balancing the network performance. The packets are handled using Network Integration and Message Forwarding (NIMF) algorithm that determines the source of forwarding the packets; either from actor or sensor. This decision-making capability of the algorithm controls the packet forwarding rate to maintain the network for a longer time. Furthermore, for handling the proper routing strategy, Priority-Based Routing for Node Failure Avoidance (PRNFA) algorithm is deployed to decide the priority of the packets to be forwarded based on the significance of information available in the packet. To validate the effectiveness of the proposed EAR paradigm, the proposed algorithms were tested using OMNET++ simulation. PMID:28420102

  11. Efficient Actor Recovery Paradigm for Wireless Sensor and Actor Networks.

    PubMed

    Mahjoub, Reem K; Elleithy, Khaled

    2017-04-14

    The actor nodes are the spine of wireless sensor and actor networks (WSANs) that collaborate to perform a specific task in an unverified and uneven environment. Thus, there is a possibility of high failure rate in such unfriendly scenarios due to several factors such as power consumption of devices, electronic circuit failure, software errors in nodes or physical impairment of the actor nodes and inter-actor connectivity problem. Therefore, it is extremely important to discover the failure of a cut-vertex actor and network-disjoint in order to improve the Quality-of-Service (QoS). In this paper, we propose an Efficient Actor Recovery (EAR) paradigm to guarantee the contention-free traffic-forwarding capacity. The EAR paradigm consists of a Node Monitoring and Critical Node Detection (NMCND) algorithm that monitors the activities of the nodes to determine the critical node. In addition, it replaces the critical node with backup node prior to complete node-failure which helps balancing the network performance. The packets are handled using Network Integration and Message Forwarding (NIMF) algorithm that determines the source of forwarding the packets; either from actor or sensor. This decision-making capability of the algorithm controls the packet forwarding rate to maintain the network for a longer time. Furthermore, for handling the proper routing strategy, Priority-Based Routing for Node Failure Avoidance (PRNFA) algorithm is deployed to decide the priority of the packets to be forwarded based on the significance of information available in the packet. To validate the effectiveness of the proposed EAR paradigm, the proposed algorithms were tested using OMNET++ simulation.

  12. 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.

  13. 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.

  14. A New Mission for Business Schools: The Development of Actor-Network Leaders

    ERIC Educational Resources Information Center

    Sidle, C. Clinton; Warzynski, Chester C

    2003-01-01

    The lesson of actor-network theory is that to effect desired change, leaders must understand their place in the network and deploy strategies that forge new relationships and strengthen existing connections between individuals, groups, and other entities--both human and nonhuman. In this article, the authors use the Roy H. Park Leadership Fellows…

  15. 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…

  16. ("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…

  17. ("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…

  18. 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…

  19. 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.

  20. 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.)

  1. 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…

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

    PubMed

    Snijders, Tom A B; Steglich, Christian E G

    2015-05-01

    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.

  3. 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.

  4. Explaining How Political Actors Gain Strategic Positions: Predictors of Centrality in State Reading Policy Issue Networks

    ERIC Educational Resources Information Center

    Young, Tamara V.; Wang, Yuling; Lewis, Wayne D.

    2016-01-01

    Using data from interviews with 111 reading policy actors from California, Connecticut, Michigan, and Utah, this study explains how individuals acquire central positions in issue networks. Regression analyses showed that the greater a policy actor's reputed influence was and the more similar their preferences were to other members in the network,…

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

    ERIC Educational Resources Information Center

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

    2015-01-01

    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…

  6. Explaining How Political Actors Gain Strategic Positions: Predictors of Centrality in State Reading Policy Issue Networks

    ERIC Educational Resources Information Center

    Young, Tamara V.; Wang, Yuling; Lewis, Wayne D.

    2016-01-01

    Using data from interviews with 111 reading policy actors from California, Connecticut, Michigan, and Utah, this study explains how individuals acquire central positions in issue networks. Regression analyses showed that the greater a policy actor's reputed influence was and the more similar their preferences were to other members in the network,…

  7. 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.

  8. 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

  9. 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,…

  10. 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,…

  11. Interdependence theory and the actor-partner interdependence model: where theory and method converge.

    PubMed

    Wickham, Robert E; Knee, C Raymond

    2012-11-01

    This work describes an application of the actor-partner interdependence model (APIM) that allows researchers to test hypotheses in terms of interdependence theory (IT). The authors' goal is to move beyond the obvious similarities of these two frameworks by providing a detailed conceptual integration. This analysis demonstrates that aspects of APIM analysis reveal a useful perspective on interdependence not explicitly articulated by IT. They also expand on ideas presented by Kenny and Ledermann by exploring the relationship between their ratio parameter k and IT, and introducing two additional ratios (h and c) also suggested by IT. A complete worked example of APIM analysis from the perspective of IT, along with a SAS MACRO that produces confidence intervals for k, h, and c, is provided.

  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. Network Detection Theory

    NASA Astrophysics Data System (ADS)

    Ferry, James P.; Lo, Darren; Ahearn, Stephen T.; Phillips, Aaron M.

    Despite the breadth of modern network theory, it can be difficult to apply its results to the task of uncovering terrorist networks: the most useful network analyses are often low-tech, link-following approaches. In the traditional military domain, detection theory has a long history of finding stealthy targets such as submarines. We demonstrate how the detection theory framework leads to a variety of network analysis questions. Some solutions to these leverage existing theory; others require novel techniques - but in each case the solutions contribute to a principled methodology for solving network detection problems. This endeavor is difficult, and the work here represents only a beginning. However, the required mathematics is interesting, being the synthesis of two fields with little common history.

  14. Formal Specification and Validation of a Hybrid Connectivity Restoration Algorithm for Wireless Sensor and Actor Networks

    PubMed Central

    Imran, Muhammad; Zafar, Nazir Ahmad

    2012-01-01

    Maintaining inter-actor connectivity is extremely crucial in mission-critical applications of Wireless Sensor and Actor Networks (WSANs), as actors have to quickly plan optimal coordinated responses to detected events. Failure of a critical actor partitions the inter-actor network into disjoint segments besides leaving a coverage hole, and thus hinders the network operation. This paper presents a Partitioning detection and Connectivity Restoration (PCR) algorithm to tolerate critical actor failure. As part of pre-failure planning, PCR determines critical/non-critical actors based on localized information and designates each critical node with an appropriate backup (preferably non-critical). The pre-designated backup detects the failure of its primary actor and initiates a post-failure recovery process that may involve coordinated multi-actor relocation. To prove the correctness, we construct a formal specification of PCR using Z notation. We model WSAN topology as a dynamic graph and transform PCR to corresponding formal specification using Z notation. Formal specification is analyzed and validated using the Z Eves tool. Moreover, we simulate the specification to quantitatively analyze the efficiency of PCR. Simulation results confirm the effectiveness of PCR and the results shown that it outperforms contemporary schemes found in the literature.

  15. Mobilizing Workplaces: Actors, Discipline and Governmentality

    ERIC Educational Resources Information Center

    Edwards, Richard; Nicoll, Katherine

    2004-01-01

    Drawing on the work of Foucault, and to a lesser extent actor-network theory, this article examines some of their methodological and theoretical implications for conceptions of workplace learning. We suggest that workplaces need to be examined for the spatio-temporal ordering of practices and the actors drawn into them in order to move beyond the…

  16. Mobilizing Workplaces: Actors, Discipline and Governmentality

    ERIC Educational Resources Information Center

    Edwards, Richard; Nicoll, Katherine

    2004-01-01

    Drawing on the work of Foucault, and to a lesser extent actor-network theory, this article examines some of their methodological and theoretical implications for conceptions of workplace learning. We suggest that workplaces need to be examined for the spatio-temporal ordering of practices and the actors drawn into them in order to move beyond the…

  17. Finding The Most Important Actor in Online Crowd by Social Network Analysis

    NASA Astrophysics Data System (ADS)

    Yuliana, I.; Santosa, P. I.; Setiawan, N. A.; Sukirman

    2017-02-01

    Billion of people create trillions of connections through social media every single day. The increasing use of social media has led to dramatic changes in the of way science, government, healthcare, entertainment and enterprise operate. Large-scale participation in Technology-Mediated Social Participation (TMSP) system has opened up incredible new opportunities to deploy online crowd. This descriptive-correlational research used social network analysis (SNA) on data gathered from Fanpage Facebook of Greenpeace Indonesia related to important critical issues, the bushfires in 2015. SNA identifies relations on each member by sociometrics parameter such as three centrality (degree, closeness and betweenesse) for measuring and finding the most important actor in the online community. This paper use Fruchterman Rein-gold algorithm to visualize the online community in a graph, while Clauset-Newman-Moore is a technique to identify groups in community. As the result found 3735 vertices related to actors, 6927 edges as relation, 14 main actors in size order and 22 groups in Greenpeace Indonesia online community. This research contributes to organize some information for Greenpeace Indonesia managing their potency in online community to identify human behaviour.

  18. 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.

  19. Analysing animal social network dynamics: the potential of stochastic actor-oriented models.

    PubMed

    Fisher, David N; Ilany, Amiyaal; Silk, Matthew J; Tregenza, Tom

    2017-03-01

    Animals are embedded in dynamically changing networks of relationships with conspecifics. These dynamic networks are fundamental aspects of their environment, creating selection on behaviours and other traits. However, most social network-based approaches in ecology are constrained to considering networks as static, despite several calls for such analyses to become more dynamic. There are a number of statistical analyses developed in the social sciences that are increasingly being applied to animal networks, of which stochastic actor-oriented models (SAOMs) are a principal example. SAOMs are a class of individual-based models designed to model transitions in networks between discrete time points, as influenced by network structure and covariates. It is not clear, however, how useful such techniques are to ecologists, and whether they are suited to animal social networks. We review the recent applications of SAOMs to animal networks, outlining findings and assessing the strengths and weaknesses of SAOMs when applied to animal rather than human networks. We go on to highlight the types of ecological and evolutionary processes that SAOMs can be used to study. SAOMs can include effects and covariates for individuals, dyads and populations, which can be constant or variable. This allows for the examination of a wide range of questions of interest to ecologists. However, high-resolution data are required, meaning SAOMs will not be useable in all study systems. It remains unclear how robust SAOMs are to missing data and uncertainty around social relationships. Ultimately, we encourage the careful application of SAOMs in appropriate systems, with dynamic network analyses likely to prove highly informative. Researchers can then extend the basic method to tackle a range of existing questions in ecology and explore novel lines of questioning. © 2016 The Authors. Journal of Animal Ecology published by John Wiley & Sons Ltd on behalf of British Ecological Society.

  20. 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.

  1. Actor-Centered Social Work: Re-visioning "Person-in-Environment" through a Critical Theory Lens.

    ERIC Educational Resources Information Center

    Kondrat, Mary Ellen

    2002-01-01

    This article revisions the relationship between person and social environment through the lens of critical theory. Emphasizing distinctively human characteristics, arguments define human actors as coconstructors of their social environments. Although human behavior is shaped by society and its structures, those very structures are recursively…

  2. Actor-Centered Social Work: Re-visioning "Person-in-Environment" through a Critical Theory Lens.

    ERIC Educational Resources Information Center

    Kondrat, Mary Ellen

    2002-01-01

    This article revisions the relationship between person and social environment through the lens of critical theory. Emphasizing distinctively human characteristics, arguments define human actors as coconstructors of their social environments. Although human behavior is shaped by society and its structures, those very structures are recursively…

  3. 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…

  4. 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.

  5. Revealing the neural networks associated with processing of natural social interaction and the related effects of actor-orientation and face-visibility.

    PubMed

    Saggar, Manish; Shelly, Elizabeth Walter; Lepage, Jean-Francois; Hoeft, Fumiko; Reiss, Allan L

    2014-01-01

    Understanding the intentions and desires of those around us is vital for adapting to a dynamic social environment. In this paper, a novel event-related functional Magnetic Resonance Imaging (fMRI) paradigm with dynamic and natural stimuli (2s video clips) was developed to directly examine the neural networks associated with processing of gestures with social intent as compared to nonsocial intent. When comparing social to nonsocial gestures, increased activation in both the mentalizing (or theory of mind) and amygdala networks was found. As a secondary aim, a factor of actor-orientation was included in the paradigm to examine how the neural mechanisms differ with respect to personal engagement during a social interaction versus passively observing an interaction. Activity in the lateral occipital cortex and precentral gyrus was found sensitive to actor-orientation during social interactions. Lastly, by manipulating face-visibility we tested whether facial information alone is the primary driver of neural activation differences observed between social and nonsocial gestures. We discovered that activity in the posterior superior temporal sulcus (pSTS) and fusiform gyrus (FFG) was partially driven by observing facial expressions during social gestures. Altogether, using multiple factors associated with processing of natural social interaction, we conceptually advance our understanding of how social stimuli is processed in the brain and discuss the application of this paradigm to clinical populations where atypical social cognition is manifested as a key symptom. © 2013.

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

    PubMed

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

    2015-05-01

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

  7. Potential theory for directed networks.

    PubMed

    Zhang, Qian-Ming; Lü, Linyuan; Wang, Wen-Qiang; Zhu, Yu-Xiao; 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.

  8. 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

  9. Actor-network Procedures: Modeling Multi-factor Authentication, Device Pairing, Social Interactions

    DTIC Science & Technology

    2011-08-29

    computer networks are extended by nodes with physical sensors and controllers, including the humans , and interlaced with social networks, the engineering...heterogenous net- works of computers, humans and their devices, where these new procedures run; and we introduce Procedure Derivation Logic (PDL) as a...computer networks are extended by nodes with physical sensors and controllers, including the humans , and interlaced with social networks, the engineering

  10. 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

  11. 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.…

  12. 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.…

  13. 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

  14. 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…

  15. 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…

  16. 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.

  17. The tensor network theory library

    NASA Astrophysics Data System (ADS)

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

    2017-09-01

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

  18. 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

  19. 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

  20. An actor-based model of social network influence on adolescent body size, screen time, and playing sports.

    PubMed

    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.

  1. 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.

  2. Developing a grounded theory for interprofessional collaboration acquisition using facilitator and actor perspectives in simulated wilderness medical emergencies.

    PubMed

    Smith, Heather A; Reade, Maurianne; Marr, Marion; Jeeves, Nicholas

    2017-01-01

    Interprofessional collaboration is a complex process that has the potential to transform patient care for the better in urban, rural and remote healthcare settings. Simulation has been found to improve participants' interprofessional competencies, but the mechanisms by which interprofessionalism is learned have yet to be understood. A rural wilderness medicine conference (WildER Med) in northern Ontario, Canada with simulated medical scenarios has been demonstrated to be effective in improving participants' collaboration without formal interprofessional education (IPE) curriculum. Interprofessionalism may be taught through rural and remote medical simulation, as done in WildER Med where participants' interprofessional competencies improved without any formal IPE curriculum. This learning may be attributed to the informal and hidden curriculum. Understanding the mechanism by which this rural educational experience contributed to participants' learning to collaborate requires insight into the events before, during and after the simulations. The authors drew upon feedback from facilitators and patient actors in one-on-one interviews to develop a grounded theory for how collaboration is taught and learned. Sharing emerged as the core concept of a grounded theory to explain how team members acquired interprofessional collaboration competencies. Sharing was enacted through the strategies of developing common goals, sharing leadership, and developing mutual respect and understanding. Further analysis of the data and literature suggests that the social wilderness environment was foundational in enabling sharing to occur. Medical simulations in other rural and remote settings may offer an environment conducive to collaboration and be effective in teaching collaboration. When designing interprofessional education, health educators should consider using emergency response teams or rural community health teams to optimize the informal and hidden curriculum contributing to

  3. Design of Location Service for a Hybrid Network of Mobile Actors and Static Sensors

    DTIC Science & Technology

    2006-01-01

    the speed limit, v < p10th with the movement threshold r. In order to satisfy Eq. (17), we have need: 2ka−2ℓ+ D 5 ≤ D 2 . (18) So, approximately, ka...101. [2] The network simulator - ns-2. http://www.isi.edu/nsnam/ns/. [3] S. Basagni, I. Chalamtac, and V . R. Syrotiuk. A distance routing effect...Ottawa, 1999. [19] A. C. Viana , M. D. de Amorim, S. Fdida, Y. Viniotis, and J. F. de Rezende. Easily-managed and topology-independent location service

  4. Advances in the Theory of Complex Networks

    NASA Astrophysics Data System (ADS)

    Peruani, Fernando

    An exhaustive and comprehensive review on the theory of complex networks would imply nowadays a titanic task, and it would result in a lengthy work containing plenty of technical details of arguable relevance. Instead, this chapter addresses very briefly the ABC of complex network theory, visiting only the hallmarks of the theoretical founding, to finally focus on two of the most interesting and promising current research problems: the study of dynamical processes on transportation networks and the identification of communities in complex networks.

  5. 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.

  6. Network of Interdependent Networks: Overview of Theory and Applications

    NASA Astrophysics Data System (ADS)

    Kenett, Dror Y.; Gao, Jianxi; Huang, Xuqing; Shao, Shuai; Vodenska, Irena; Buldyrev, Sergey V.; Paul, Gerald; Stanley, H. Eugene; Havlin, Shlomo

    Complex networks appear in almost every aspect of science and technology. Previous work in network theory has focused primarily on analyzing single networks that do not interact with other networks, despite the fact that many real-world networks interact with and depend on each other. Very recently an analytical framework for studying the percolation properties of interacting networks has been introduced. Here we review the analytical framework and the results for percolation laws for a network of networks (NON) formed by n interdependent random networks. The percolation properties of a network of networks differ greatly from those of single isolated networks. In particular, although networks with broad degree distributions, e.g., scale-free networks, are robust when analyzed as single networks, they become vulnerable in a NON. Moreover, because the constituent networks of a NON are connected by node dependencies, a NON is subject to cascading failure. When there is strong interdependent coupling between networks, the percolation transition is discontinuous (is a first-order transition), unlike the well-known continuous second-order transition in single isolated networks. We also review some possible real-world applications of NON theory.

  7. Complex Networks: from Graph Theory to Biology

    NASA Astrophysics Data System (ADS)

    Lesne, Annick

    2006-12-01

    The aim of this text is to show the central role played by networks in complex system science. A remarkable feature of network studies is to lie at the crossroads of different disciplines, from mathematics (graph theory, combinatorics, probability theory) to physics (statistical physics of networks) to computer science (network generating algorithms, combinatorial optimization) to biological issues (regulatory networks). New paradigms recently appeared, like that of ‘scale-free networks’ providing an alternative to the random graph model introduced long ago by Erdös and Renyi. With the notion of statistical ensemble and methods originally introduced for percolation networks, statistical physics is of high relevance to get a deep account of topological and statistical properties of a network. Then their consequences on the dynamics taking place in the network should be investigated. Impact of network theory is huge in all natural sciences, especially in biology with gene networks, metabolic networks, neural networks or food webs. I illustrate this brief overview with a recent work on the influence of network topology on the dynamics of coupled excitable units, and the insights it provides about network emerging features, robustness of network behaviors, and the notion of static or dynamic motif.

  8. 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.

  9. 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…

  10. 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…

  11. 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

  12. 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.

  13. Network susceptibilities: Theory and applications.

    PubMed

    Manik, Debsankha; Rohden, Martin; Ronellenfitsch, Henrik; Zhang, Xiaozhu; Hallerberg, Sarah; Witthaut, Dirk; Timme, Marc

    2017-01-01

    We introduce the concept of network susceptibilities quantifying the response of the collective dynamics of a network to small parameter changes. We distinguish two types of susceptibilities: vertex susceptibilities and edge susceptibilities, measuring the responses due to changes in the properties of units and their interactions, respectively. We derive explicit forms of network susceptibilities for oscillator networks close to steady states and offer example applications for Kuramoto-type phase-oscillator models, power grid models, and generic flow models. Focusing on the role of the network topology implies that these ideas can be easily generalized to other types of networks, in particular those characterizing flow, transport, or spreading phenomena. The concept of network susceptibilities is broadly applicable and may straightforwardly be transferred to all settings where networks responses of the collective dynamics to topological changes are essential.

  14. Mathematical Theory of Neural Networks

    DTIC Science & Technology

    1994-08-31

    This report provides a summary of the grant work by the principal investigators in the area of neural networks . The topics covered deal with...properties) for nets; and the use of neural networks for the control of nonlinear systems.

  15. Network susceptibilities: Theory and applications

    NASA Astrophysics Data System (ADS)

    Manik, Debsankha; Rohden, Martin; Ronellenfitsch, Henrik; Zhang, Xiaozhu; Hallerberg, Sarah; Witthaut, Dirk; Timme, Marc

    2017-01-01

    We introduce the concept of network susceptibilities quantifying the response of the collective dynamics of a network to small parameter changes. We distinguish two types of susceptibilities: vertex susceptibilities and edge susceptibilities, measuring the responses due to changes in the properties of units and their interactions, respectively. We derive explicit forms of network susceptibilities for oscillator networks close to steady states and offer example applications for Kuramoto-type phase-oscillator models, power grid models, and generic flow models. Focusing on the role of the network topology implies that these ideas can be easily generalized to other types of networks, in particular those characterizing flow, transport, or spreading phenomena. The concept of network susceptibilities is broadly applicable and may straightforwardly be transferred to all settings where networks responses of the collective dynamics to topological changes are essential.

  16. 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…

  17. A network theory of mental disorders

    PubMed Central

    Borsboom, Denny

    2017-01-01

    In recent years, the network approach to psychopathology has been advanced as an alternative way of conceptualizing mental disorders. In this approach, mental disorders arise from direct interactions between symptoms. Although the network approach has led to many novel methodologies and substantive applications, it has not yet been fully articulated as a scientific theory of mental disorders. The present paper aims to develop such a theory, by postulating a limited set of theoretical principles regarding the structure and dynamics of symptom networks. At the heart of the theory lies the notion that symptoms of psychopathology are causally connected through myriads of biological, psychological and societal mechanisms. If these causal relations are sufficiently strong, symptoms can generate a level of feedback that renders them self‐sustaining. In this case, the network can get stuck in a disorder state. The network theory holds that this is a general feature of mental disorders, which can therefore be understood as alternative stable states of strongly connected symptom networks. This idea naturally leads to a comprehensive model of psychopathology, encompassing a common explanatory model for mental disorders, as well as novel definitions of associated concepts such as mental health, resilience, vulnerability and liability. In addition, the network theory has direct implications for how to understand diagnosis and treatment, and suggests a clear agenda for future research in psychiatry and associated disciplines. PMID:28127906

  18. A Complexity Theory of Neural Networks

    DTIC Science & Technology

    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

  19. 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.

  20. 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.

  1. 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.

  2. 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).

  3. Research into Queueing Network Theory.

    DTIC Science & Technology

    1977-09-01

    aspects. Kleinrock [33] comments on this result, for example. In 1976, Burke [6] provided the first proof of some of what was occurring in the flow...server first passes through other servers (as for example in Jackson networks with loops) that item is delayed on its return. All current knowledge about...system simplification. A simplification is an operation on the system such that a new system is obtained subject to two requirements. First , the

  4. Operationalizing Network Theory for Ecosystem Service Assessments.

    PubMed

    Dee, Laura E; Allesina, Stefano; Bonn, Aletta; Eklöf, Anna; Gaines, Steven D; Hines, Jes; Jacob, Ute; McDonald-Madden, Eve; Possingham, Hugh; Schröter, Matthias; Thompson, Ross M

    2017-02-01

    Managing ecosystems to provide ecosystem services in the face of global change is a pressing challenge for policy and science. Predicting how alternative management actions and changing future conditions will alter services is complicated by interactions among components in ecological and socioeconomic systems. Failure to understand those interactions can lead to detrimental outcomes from management decisions. Network theory that integrates ecological and socioeconomic systems may provide a path to meeting this challenge. While network theory offers promising approaches to examine ecosystem services, few studies have identified how to operationalize networks for managing and assessing diverse ecosystem services. We propose a framework for how to use networks to assess how drivers and management actions will directly and indirectly alter ecosystem services.

  5. 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…

  6. An Actor-Network Theory Reading of Change for Children in Public Care

    ERIC Educational Resources Information Center

    Parker, Elisabeth

    2017-01-01

    The education of children in public, or Local Authority (LA), care, known in the United Kingdom (UK) as looked-after children (LAC), is supported by government initiatives to reduce the attainment gap that exists between LAC and their non-LAC peers. These children often find remaining in education a challenge, are twice as likely to be permanently…

  7. 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…

  8. 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…

  9. An Actor-Network Theory Reading of Change for Children in Public Care

    ERIC Educational Resources Information Center

    Parker, Elisabeth

    2017-01-01

    The education of children in public, or Local Authority (LA), care, known in the United Kingdom (UK) as looked-after children (LAC), is supported by government initiatives to reduce the attainment gap that exists between LAC and their non-LAC peers. These children often find remaining in education a challenge, are twice as likely to be permanently…

  10. Linear control theory for gene network modeling.

    PubMed

    Shin, Yong-Jun; Bleris, Leonidas

    2010-09-16

    Systems biology is an interdisciplinary field that aims at understanding complex interactions in cells. Here we demonstrate that linear control theory can provide valuable insight and practical tools for the characterization of complex biological networks. We provide the foundation for such analyses through the study of several case studies including cascade and parallel forms, feedback and feedforward loops. We reproduce experimental results and provide rational analysis of the observed behavior. We demonstrate that methods such as the transfer function (frequency domain) and linear state-space (time domain) can be used to predict reliably the properties and transient behavior of complex network topologies and point to specific design strategies for synthetic networks.

  11. Exploring network theory for mass drug administration.

    PubMed

    Chami, Goylette F; Molyneux, David H; Kontoleon, Andreas A; Dunne, David W

    2013-08-01

    Network theory is a well-established discipline that uses mathematical graphs to describe biological, physical, and social systems. The topologies across empirical networks display strikingly similar organizational properties. In particular, the characteristics of these networks allow computational analysis to contribute data unattainable from examining individual components in isolation. However, the interdisciplinary and quantitative nature of network analysis has yet to be exploited by public health initiatives to distribute preventive chemotherapies. One notable application is the 2012 World Health Organization (WHO) Roadmap for Neglected Tropical Diseases (NTDs) where there is a need to upscale distribution capacity and to target systematic noncompliers. An understanding of local networks for analysing the distributional properties of community-directed treatment may facilitate sustainable expansion of mass drug-administration (MDA) programs.

  12. Nonequilibrium landscape theory of neural networks.

    PubMed

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

    2013-11-05

    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.

  13. 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

  14. 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…

  15. Moving from theory to practice: A participatory social network mapping approach to address unmet need for family planning in Benin.

    PubMed

    Igras, Susan; Diakité, Mariam; Lundgren, Rebecka

    2016-03-07

    In West Africa, social factors influence whether couples with unmet need for family planning act on birth-spacing desires. Tékponon Jikuagou is testing a social network-based intervention to reduce social barriers by diffusing new ideas. Individuals and groups judged socially influential by their communities provide entrée to networks. A participatory social network mapping methodology was designed to identify these diffusion actors. Analysis of monitoring data, in-depth interviews, and evaluation reports assessed the methodology's acceptability to communities and staff and whether it produced valid, reliable data to identify influential individuals and groups who diffuse new ideas through their networks. Results indicated the methodology's acceptability. Communities were actively and equitably engaged. Staff appreciated its ability to yield timely, actionable information. The mapping methodology also provided valid and reliable information by enabling communities to identify highly connected and influential network actors. Consistent with social network theory, this methodology resulted in the selection of informal groups and individuals in both informal and formal positions. In-depth interview data suggest these actors were diffusing new ideas, further confirming their influence/connectivity. The participatory methodology generated insider knowledge of who has social influence, challenging commonly held assumptions. Collecting and displaying information fostered staff and community learning, laying groundwork for social change.

  16. 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.

  17. Network Theory Tools for RNA Modeling

    PubMed Central

    Kim, Namhee; Petingi, Louis; Schlick, Tamar

    2014-01-01

    An introduction into the usage of graph or network theory tools for the study of RNA molecules is presented. By using vertices and edges to define RNA secondary structures as tree and dual graphs, we can enumerate, predict, and design RNA topologies. Graph connectivity and associated Laplacian eigenvalues relate to biological properties of RNA and help understand RNA motifs as well as build, by computational design, various RNA target structures. Importantly, graph theoretical representations of RNAs reduce drastically the conformational space size and therefore simplify modeling and prediction tasks. Ongoing challenges remain regarding general RNA design, representation of RNA pseudoknots, and tertiary structure prediction. Thus, developments in network theory may help advance RNA biology. PMID:25414570

  18. Network Theory Tools for RNA Modeling.

    PubMed

    Kim, Namhee; Petingi, Louis; Schlick, Tamar

    2013-09-01

    An introduction into the usage of graph or network theory tools for the study of RNA molecules is presented. By using vertices and edges to define RNA secondary structures as tree and dual graphs, we can enumerate, predict, and design RNA topologies. Graph connectivity and associated Laplacian eigenvalues relate to biological properties of RNA and help understand RNA motifs as well as build, by computational design, various RNA target structures. Importantly, graph theoretical representations of RNAs reduce drastically the conformational space size and therefore simplify modeling and prediction tasks. Ongoing challenges remain regarding general RNA design, representation of RNA pseudoknots, and tertiary structure prediction. Thus, developments in network theory may help advance RNA biology.

  19. Using graph theory to analyze biological networks

    PubMed Central

    2011-01-01

    Understanding complex systems often requires a bottom-up analysis towards a systems biology approach. The need to investigate a system, not only as individual components but as a whole, emerges. This can be done by examining the elementary constituents individually and then how these are connected. The myriad components of a system and their interactions are best characterized as networks and they are mainly represented as graphs where thousands of nodes are connected with thousands of vertices. In this article we demonstrate approaches, models and methods from the graph theory universe and we discuss ways in which they can be used to reveal hidden properties and features of a network. This network profiling combined with knowledge extraction will help us to better understand the biological significance of the system. PMID:21527005

  20. The Rise of the Video-Recorder Teacher: The Sociomaterial Construction of an Educational Actor

    ERIC Educational Resources Information Center

    Perrotta, Carlo; Czerniewicz, Laura; Beetham, Helen

    2016-01-01

    This paper draws on actor-network theory and on the sociology of cultural consumption to examine the phenomenon of corporate Massive Open Online Courses. Through an analysis of texts available in the public domain, the paper argues that over a short period (between 2012 and 2013) digitisation technology became associated with the emergence of a…

  1. 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

  2. Reaction networks and evolutionary game theory.

    PubMed

    Veloz, Tomas; Razeto-Barry, Pablo; Dittrich, Peter; Fajardo, Alejandro

    2014-01-01

    The powerful mathematical tools developed for the study of large scale reaction networks have given rise to applications of this framework beyond the scope of biochemistry. Recently, reaction networks have been suggested as an alternative way to model social phenomena. In this "socio-chemical metaphor" molecular species play the role of agents' decisions and their outcomes, and chemical reactions play the role of interactions among these decisions. From here, it is possible to study the dynamical properties of social systems using standard tools of biochemical modelling. In this work we show how to use reaction networks to model systems that are usually studied via evolutionary game theory. We first illustrate our framework by modeling the repeated prisoners' dilemma. The model is built from the payoff matrix together with assumptions of the agents' memory and recognizability capacities. The model provides consistent results concerning the performance of the agents, and allows for the examination of the steady states of the system in a simple manner. We further develop a model considering the interaction among Tit for Tat and Defector agents. We produce analytical results concerning the performance of the strategies in different situations of agents' memory and recognizability. This approach unites two important theories and may produce new insights in classical problems such as the evolution of cooperation in large scale systems.

  3. Combing the Underworld: Identification of South East Asian Non-State Actor Proliferation Networks, Nodes, and Chokepoints

    DTIC Science & Technology

    2006-05-25

    major types of gambling in Thailand are sports betting, fish and cockfighting, illegal lotteries , and gambling dens. The state-run lottery is the...either directly or via the Malaysian provinces of Kelantan, Sarawak and Sabah.”68 However, the greatest requirement is in the nature of the types of...could be refined in Malaysian centrifuges, as was done by the AQ Khan network. This refined material could be used immediately by AQ affiliates such

  4. Moral actor, selfish agent.

    PubMed

    Frimer, Jeremy A; Schaefer, Nicola K; Oakes, Harrison

    2014-05-01

    People are motivated to behave selfishly while appearing moral. This tension gives rise to 2 divergently motivated selves. The actor-the watched self-tends to be moral; the agent-the self as executor-tends to be selfish. Three studies present direct evidence of the actor's and agent's distinct motives. To recruit the self-as-actor, we asked people to rate the importance of various goals. To recruit the self-as-agent, we asked people to describe their goals verbally. In Study 1, actors claimed their goals were equally about helping the self and others (viz., moral); agents claimed their goals were primarily about helping the self (viz., selfish). This disparity was evident in both individualist and collectivist cultures, attesting to the universality of the selfish agent. Study 2 compared actors' and agents' motives to those of people role-playing highly prosocial or selfish exemplars. In content (Study 2a) and in the impressions they made on an outside observer (Study 2b), actors' motives were similar to those of the prosocial role-players, whereas agents' motives were similar to those of the selfish role-players. Study 3 accounted for the difference between the actor and agent: Participants claimed that their agent's motives were the more realistic and that their actor's motives were the more idealistic. The selfish agent/moral actor duality may account for why implicit and explicit measures of the same construct diverge, and why feeling watched brings out the better angels of human nature.

  5. 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.

  6. Topological rubber elasticity theory. II. SCL networks

    NASA Astrophysics Data System (ADS)

    Iwata, Kazuyoshi

    1982-06-01

    The theory presented in part I [Iwata, J. Chem. Phys. 76, 6363 (1982)] is applied to networks having a simple-cubic-lattice (SCL) regular connection pattern, for which the projection matrix Γ* is computed easily. Derivatives of elastic free energies in regard to parameter λ for macroscopic deformation ∂F˜e/∂λ are computed numerically for isotropic deformations (swelling or deswelling) and for simple deformations (extension or contraction under swelling by α times). The initial arrangement of junction points r0 is assumed to be exactly SCL, and δ = d0/√νb is chosen as one of parameters in the calculation, where d0 is an end-to-end distance of the strands at the time of network formation, ν is a degree of polymerization in regard to the strands, and b is a statistical length per monomer. A repeating cell is chosen as a cube composed of 3×3×3 ( = 27) junction points and 3×27 ( = 81) strands. The following are found in this work. (1) Among four terms ∂F0,ph/∂λ, ∂F˜0,top/∂λ, ∂F˜1/∂λ, and ∂F˜2/∂λ of the derivative of the elastic free energy, the principal term is ∂F˜0,top/∂λ, which comes from the topological interaction among the strands; the phantom network term ∂F0,ph/∂λ is only a small correction to the net stress. (2) In isotropic deformations, the elastic free energy takes a minimum at λ0, a little below λ = 1; for compression below λ0, a strong postitive inner pressure, which comes from the topological repulsive forces among the strands, arises. (3) In simple deformations, the Mooney-Rivlin term appears for unswollen systems and it disappears as swelling of the network proceeds. Experimental plans are proposed which will reveal the existence of the topological repulsive interactions in the networks.

  7. An Outline for Actors.

    ERIC Educational Resources Information Center

    Jeffries, Charles

    1979-01-01

    Presents an outline of six basic preparation activities for student actors, including reading the play, doing historical research, elemental exercises, learning the part, creating the character, and exercises in movement and voice. (JMF)

  8. On the question of homosexuality in actors.

    PubMed

    Neuringer, C

    1989-12-01

    There is a belief that a high percentage of male actors are homosexual. The specific linking of actors and homosexuality seems to have first appeared in the Elizabethan Puritan condemnations of the theater. Psychoanalytic theory has tended to further promulgate the linkage between effeminacy, homosexuality, and acting. An analysis of the relevant existing empirical literature indicates that few studies have addressed themselves to evaluating this relationship. Those studies supporting the effeminacy-actor relationship were seriously flawed both in design (e.g., use of indirect measures to infer homosexuality) and interpretation of the data. Only one study used direct measures of sexual orientation. Even though that study had methodological problems, its results indicated that the percentage of homosexuality among actors was not verifiably greater than that found in the general population. It is felt that the current belief of greater homosexuality in actors, as compared to the general population, is a product of our Puritan heritage, the actor's unconventionality, and of public flaunting of the homoerotic behavior of that portion of actors that are homosexual.

  9. 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.

  10. 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.

  11. 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…

  12. 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.

  13. A Complexity Theory of Neural Networks

    DTIC Science & Technology

    1990-04-14

    Significant results have been obtained on the computation complexity of analog neural networks , and distribute voting. The computing power and...learning algorithms for limited precision analog neural networks have been investigated. Lower bounds for constant depth, polynomial size analog neural ... networks , and a limited version of discrete neural networks have been obtained. The work on distributed voting has important applications for distributed

  14. 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

  15. Application of random matrix theory to biological networks

    NASA Astrophysics Data System (ADS)

    Luo, Feng; Zhong, Jianxin; Yang, Yunfeng; Scheuermann, Richard H.; Zhou, Jizhong

    2006-09-01

    We show that spectral fluctuation of interaction matrices of a yeast protein protein interaction network and a yeast metabolic network follows the description of the Gaussian orthogonal ensemble (GOE) of random matrix theory (RMT). Furthermore, we demonstrate that while the global biological networks evaluated belong to GOE, removal of interactions between constituents transitions the networks to systems of isolated modules described by the Poisson distribution. Our results indicate that although biological networks are very different from other complex systems at the molecular level, they display the same statistical properties at network scale. The transition point provides a new objective approach for the identification of functional modules.

  16. 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

  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…

  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. 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…

  20. 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…

  1. Augmenting the theory of planned behaviour with the prototype/willingness model: predictive validity of actor versus abstainer prototypes for adolescents' health-protective and health-risk intentions.

    PubMed

    Rivis, Amanda; Sheeran, Paschal; Armitage, Christopher J

    2006-09-01

    The present research tested: (a) whether prototype perceptions and descriptive norms from the prototype/willingness model (PWM; Gibbons, Gerrard, Blanton, & Russell, 1998) enhance the prediction of adolescents' intentions to engage in health-protective and health-risk behaviours after variables from the theory of planned behaviour (TPB; Ajzen, 1991) and past behaviour have been taken into account and (b) whether images of the type of person who engages in a health behaviour (actor prototypes) and images of the type of person who does not engage in a health behaviour (abstainer prototypes) have equivalent predictive validity. An experimental design with a single between participants factor (actor versus abstainer prototype) was employed. Participants in this study were 247 school pupils who completed measures of TPB variables, PWM variables and past behaviour in relation to three health-protective and three health-risk behaviours. Findings indicated that PWM variables accounted for a significant proportion of the variance in behavioural intentions after TPB variables and past behaviour had been taken into account (Mean deltaR2=.05). Perceived similarity to prototypes was the most consistent additional predictor of intention. Actor and abstainer prototypes exhibited equivalent predictive validity. The present research suggests that variables from the PWM, especially prototype similarity, enhance the predictive validity of the TPB. The findings also provide new evidence that acquiring the characteristics of both health and risk images may be goals among adolescents and suggest that both healthy and risky prototypes constitute useful cognitive targets for interventions.

  2. Percolation theory on interdependent networks based on epidemic spreading

    NASA Astrophysics Data System (ADS)

    Son, Seung-Woo; Bizhani, Golnoosh; Christensen, Claire; Grassberger, Peter; Paczuski, Maya

    2012-01-01

    We consider percolation on interdependent locally treelike networks, recently introduced by Buldyrev S. V. et al., Nature, 464 (2010) 1025, and demonstrate that the problem can be simplified conceptually by deleting all references to cascades of failures. Such cascades do exist, but their explicit treatment just complicates the theory —which is a straightforward extension of the usual epidemic spreading theory on a single network. Our method has the added benefits that it is directly formulated in terms of an order parameter and its modular structure can be easily extended to other problems, e.g. to any number of interdependent networks, or to networks with dependency links.

  3. 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.

  4. The theory of pattern formation on directed networks.

    PubMed

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

    2014-07-31

    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.

  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.

  6. Brain and cognitive reserve: Translation via network control theory.

    PubMed

    Medaglia, John Dominic; Pasqualetti, Fabio; Hamilton, Roy H; Thompson-Schill, Sharon L; Bassett, Danielle S

    2017-04-01

    Traditional approaches to understanding the brain's resilience to neuropathology have identified neurophysiological variables, often described as brain or cognitive "reserve," associated with better outcomes. However, mechanisms of function and resilience in large-scale brain networks remain poorly understood. Dynamic network theory may provide a basis for substantive advances in understanding functional resilience in the human brain. In this perspective, we describe recent theoretical approaches from network control theory as a framework for investigating network level mechanisms underlying cognitive function and the dynamics of neuroplasticity in the human brain. We describe the theoretical opportunities offered by the application of network control theory at the level of the human connectome to understand cognitive resilience and inform translational intervention.

  7. Network Data: Statistical Theory and New Models

    DTIC Science & Technology

    2016-02-17

    research covered a wide range of topics in statistics including analysis and methods for spectral clustering for sparse and structured networks...signals, bootstrapping, Lasso+OLS, confidence interval, concise comparative summarization, EM algorithm, spectral clustering , aerosol retrieval...covered a wide range of topics in statistics including analysis and methods for spectral clustering for sparse and structured networks [2,7,8,21

  8. 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…

  9. 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…

  10. A Systems Theory View of Organizations as Communication Networks.

    ERIC Educational Resources Information Center

    Schwartz, Donald F.

    Focusing on the analysis of communication networks within organizations with an eye toward implications for study of external communication, this paper (1) develops a systems theory/communication view of the nature of formal organizations, (2) illustrates the notion of holistic organizational communication networks in organizations which include…

  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. 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;…

  13. 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.

  14. 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.

  15. Applied Hypergame Theory for Network Defense

    DTIC Science & Technology

    2013-06-01

    research of game theory concepts. The most influential breakthrough would happen at the hands of a troubled genius , John F. Nash, Jr. 1.2.2 Nash...49] Vane, Russell R. “Hypergame Theory for DTGT Agents”. American Association for Artificial Intelligence, 2000. [50] Vane, Russell R., III. “Planning

  16. A theory that predicts behaviors of disordered cytoskeletal networks.

    PubMed

    Belmonte, Julio M; Leptin, Maria; Nédélec, François

    2017-09-27

    Morphogenesis in animal tissues is largely driven by actomyosin networks, through tensions generated by an active contractile process. Although the network components and their properties are known, and networks can be reconstituted in vitro, the requirements for contractility are still poorly understood. Here, we describe a theory that predicts whether an isotropic network will contract, expand, or conserve its dimensions. This analytical theory correctly predicts the behavior of simulated networks, consisting of filaments with varying combinations of connectors, and reveals conditions under which networks of rigid filaments are either contractile or expansile. Our results suggest that pulsatility is an intrinsic behavior of contractile networks if the filaments are not stable but turn over. The theory offers a unifying framework to think about mechanisms of contractions or expansion. It provides the foundation for studying a broad range of processes involving cytoskeletal networks and a basis for designing synthetic networks. © 2017 The Authors. Published under the terms of the CC BY 4.0 license.

  17. Network meta-analysis, electrical networks and graph theory.

    PubMed

    Rücker, Gerta

    2012-12-01

    Network meta-analysis is an active field of research in clinical biostatistics. It aims to combine information from all randomized comparisons among a set of treatments for a given medical condition. We show how graph-theoretical methods can be applied to network meta-analysis. A meta-analytic graph consists of vertices (treatments) and edges (randomized comparisons). We illustrate the correspondence between meta-analytic networks and electrical networks, where variance corresponds to resistance, treatment effects to voltage, and weighted treatment effects to current flows. Based thereon, we then show that graph-theoretical methods that have been routinely applied to electrical networks also work well in network meta-analysis. In more detail, the resulting consistent treatment effects induced in the edges can be estimated via the Moore-Penrose pseudoinverse of the Laplacian matrix. Moreover, the variances of the treatment effects are estimated in analogy to electrical effective resistances. It is shown that this method, being computationally simple, leads to the usual fixed effect model estimate when applied to pairwise meta-analysis and is consistent with published results when applied to network meta-analysis examples from the literature. Moreover, problems of heterogeneity and inconsistency, random effects modeling and including multi-armed trials are addressed. Copyright © 2012 John Wiley & Sons, Ltd. Copyright © 2012 John Wiley & Sons, Ltd.

  18. Quantum networks: General theory and applications

    NASA Astrophysics Data System (ADS)

    Bisio, A.; Chiribella, G.; D'Ariano, G. M.; Perinotti, P.

    2011-06-01

    In this work we present a general mathematical framework to deal with Quantum Networks, i.e. networks resulting from the interconnection of elementary quantum circuits. The cornerstone of our approach is a generalization of the Choi isomorphism that allows one to efficiently represent any given Quantum Network in terms of a single positive operator. Our formalism allows one to face and solve many quantum information processing problems that would be hardly manageable otherwise, the most relevant of which are reviewed in this work: quantum process tomography, quantum cloning and learning of transformations, inversion of a unitary gate, information-disturbance tradeoff in estimating a unitary transformation, cloning and learning of a measurement device.

  19. Genetic networks: between theory and experimentation

    NASA Astrophysics Data System (ADS)

    Bottani, Samuel; Mazurie, Aurélien

    Thanks to an increasing availability of data on cell components and progress in computers and computer science, a long awaited paradigm shift is running in biology from reductionism to holistic approaches. One of the consequences is the huge development of network-related representations of cell activity and an increasing involvement of researchers from computer science, physics and mathematics in their analysis. But what are the promises of these approaches for the biologist? What is the available biological data sustaining them and is it sufficient? After a presentation of the interaction network view of the cell, we shall focus on studies on gene network structure and dynamics. Then we shall discuss the difficulties of these approaches and their theoretical and practical usefulness for the biologist.

  20. Uncovering the Hidden Structure of Platoons: Formal and Emergent Leaders’ Perceptions of Organizational Networks

    DTIC Science & Technology

    2008-12-01

    of group-rated leadership ability. The theory of network homophily , or similarity- attraction theory (Byrne, 1971), predicts that individuals will... analysis . 1.1 Social Networks The term “social network” refers to a set of actors who are connected by a set of ties. Actors, often referred to as... interpersonal relationships is the structure of the dyadic ties found within the network. Ties are the medium through which interpersonal resources such

  1. 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.

  2. Assessing Connections Between Behavior Change Theories Using Network Analysis.

    PubMed

    Gainforth, Heather L; West, Robert; Michie, Susan

    2015-10-01

    A cross-disciplinary scoping review identified 83 of behavior change theories, with many similarities and overlapping constructs. Investigating the derivation of these theories may provide further understanding of their contribution and intended application. To develop and apply a method to describe the explicit derivation of theories of behavior change. A network analysis of the explicit "contributing to" relations between the 83 theories was conducted. Identification of relations involved textual analysis of primary theory sources. One hundred and twenty-two connections between the theories were identified amounting to 1.8% of the number possible. On average, theories contributed to one or two theories (mean = 1.47 ± 3.69 contributions) and were informed by one or two theories (mean = 1.47 ± 1.61 contributing theories). Most behavior change theories appear to be explicitly informed by few prior theories. If confirmed, this suggests a considerable dislocation between generations of theories which would be expected to undermine scientific progress.

  3. 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…

  4. 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…

  5. Complexity Theory and Network Centric Warfare

    DTIC Science & Technology

    2003-09-01

    Prediction ......................................... 60 Figure 3.4: 2nd Armoured Division– Neural Net Prediction...61 Figure 3.7: 9th Armoured Division– Neural Net Prediction........................................ 61 vi Figure 3.8...approach has been contrasted with three other prediction methodologies: a neural network; use of nonlinear prediction (a prediction is made by

  6. 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…

  7. 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.

  8. Actors and intentions in the development process of a mobile phone platform for self-management of hypertension.

    PubMed

    Ranerup, Agneta; Hallberg, Inger

    2014-06-24

    Aim: The aim of this study was to enhance the knowledge regarding actors and intentions in the development process of a mobile phone platform for self-management of hypertension. Methods: Our research approach was a 14-month longitudinal "real-time ethnography" method of description and analysis. Data were collected through focus groups with patients and providers, patient interviews, and design meetings with researchers and experts. The analysis was informed by the concepts of actors and inscriptions in actor-network theory (ANT). Results: Our study showed that laypersons, scientific actors, as well as technology itself, might influence development processes of support for self-management of hypertension. The intentions were inscribed into the technology design as well as the models of learning and treatment. Conclusions: The study highlighted important aspects of how actors and intentions feature in the development of the mobile phone platform to support self-management of hypertension. The study indicated the multifacetedness of the participating actors, including the prominent role of technology. The concrete results of such processes included questions in the self-report system, learning and treatment models.

  9. 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.

  10. Information theory and the ethylene genetic network

    PubMed Central

    González-García, José S

    2011-01-01

    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

  11. 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

  12. Composing Networks: Writing Practices on Mobile Devices

    ERIC Educational Resources Information Center

    Swarts, Jason

    2016-01-01

    This article is an investigation of composing practices through which people create networks with mobile phones. By looking through the lens of actor-network theory, the author portrays the networking activity of mobile phone users as translation, what Latour describes as an infralanguage to which different disciplinary perspectives can be…

  13. Composing Networks: Writing Practices on Mobile Devices

    ERIC Educational Resources Information Center

    Swarts, Jason

    2016-01-01

    This article is an investigation of composing practices through which people create networks with mobile phones. By looking through the lens of actor-network theory, the author portrays the networking activity of mobile phone users as translation, what Latour describes as an infralanguage to which different disciplinary perspectives can be…

  14. Graph theory network function in Parkinson's disease assessed with electroencephalography.

    PubMed

    Utianski, Rene L; Caviness, John N; van Straaten, Elisabeth C W; Beach, Thomas G; Dugger, Brittany N; Shill, Holly A; Driver-Dunckley, Erika D; Sabbagh, Marwan N; Mehta, Shyamal; Adler, Charles H; Hentz, Joseph G

    2016-05-01

    To determine what differences exist in graph theory network measures derived from electroencephalography (EEG), between Parkinson's disease (PD) patients who are cognitively normal (PD-CN) and matched healthy controls; and between PD-CN and PD dementia (PD-D). EEG recordings were analyzed via graph theory network analysis to quantify changes in global efficiency and local integration. This included minimal spanning tree analysis. T-tests and correlations were used to assess differences between groups and assess the relationship with cognitive performance. Network measures showed increased local integration across all frequency bands between control and PD-CN; in contrast, decreased local integration occurred in PD-D when compared to PD-CN in the alpha1 frequency band. Differences found in PD-MCI mirrored PD-D. Correlations were found between network measures and assessments of global cognitive performance in PD. Our results reveal distinct patterns of band and network measure type alteration and breakdown for PD, as well as with cognitive decline in PD. These patterns suggest specific ways that interaction between cortical areas becomes abnormal and contributes to PD symptoms at various stages. Graph theory analysis by EEG suggests that network alteration and breakdown are robust attributes of PD cortical dysfunction pathophysiology. Copyright © 2016 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

  15. 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.

  16. 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.

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

    ERIC Educational Resources Information Center

    Vincent, Jack E.

    This monograph presents findings from 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 reports on the testing of relative status field theory on WEIS conflict data for 1966-1969…

  18. 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.

  19. Application of Ecological Network Theory to the Human Microbiome

    PubMed Central

    Foster, James A.; Krone, Stephen M.; Forney, Larry J.

    2008-01-01

    In healthy humans, many microbial consortia constitute rich ecosystems with dozens to hundreds of species, finely tuned to functions relevant to human health. Medical interventions, lifestyle changes, and the normal rhythms of life sometimes upset the balance in microbial ecosystems, facilitating pathogen invasions or causing other clinically relevant problems. Some diseases, such as bacterial vaginosis, have exactly this sort of community etiology. Mathematical network theory is ideal for studying the ecological networks of interacting species that comprise the human microbiome. Theoretical networks require little consortia specific data to provide insight into both normal and disturbed microbial community functions, but it is easy to incorporate additional empirical data as it becomes available. We argue that understanding some diseases, such as bacterial vaginosis, requires a shift of focus from individual bacteria to (mathematical) networks of interacting populations, and that known emergent properties of these networks will provide insights that would be otherwise elusive. PMID:19259330

  20. 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.

  1. Dimension theory of graphs and networks

    NASA Astrophysics Data System (ADS)

    Nowotny, Thomas; Requardt, Manfred

    1998-03-01

    Starting from the working hypothesis that both physics and the corresponding mathematics have to be described by means of discrete concepts on the Planck scale, one of the many problems one has to face in this enterprise is to find the discrete protoforms of the building blocks of continuum physics and mathematics. A core concept is the notion of dimension. In the following we develop such a notion for irregular structures such as (large) graphs and networks and derive a number of its properties. Among other things we show its stability under a wide class of perturbations which is important if one has ` dimensional phase transitions' in mind. Furthermore we systematically construct graphs with almost arbitrary ` fractal dimension' which may be of some use in the context of ` dimensional renormalization' or statistical mechanics on irregular sets.

  2. 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.

  3. 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…

  4. 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

  5. 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.

  6. 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…

  7. 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…

  8. 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.

  9. How Fast Can Networks Synchronize? A Random Matrix Theory Approach

    NASA Astrophysics Data System (ADS)

    Timme, Marc; Wolf, Fred; Geisel, Theo

    2004-03-01

    Pulse-coupled oscillators constitute a paradigmatic class of dynamical systems interacting on networks because they model a variety of biological systems including flashing fireflies and chirping crickets as well as pacemaker cells of the heart and neural networks. Synchronization is one of the most simple and most prevailing kinds of collective dynamics on such networks. Here we study collective synchronization [1] of pulse-coupled oscillators interacting on asymmetric random networks. Using random matrix theory we analytically determine the speed of synchronization in such networks in dependence on the dynamical and network parameters [2]. The speed of synchronization increases with increasing coupling strengths. Surprisingly, however, it stays finite even for infinitely strong interactions. The results indicate that the speed of synchronization is limited by the connectivity of the network. We discuss the relevance of our findings to general equilibration processes on complex networks. [5mm] [1] M. Timme, F. Wolf, T. Geisel, Phys. Rev. Lett. 89:258701 (2002). [2] M. Timme, F. Wolf, T. Geisel, cond-mat/0306512 (2003).

  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. Attributes and National Behavior, Part 2: Modern International Relations Monograph Series. Relative Status-Field Theory, Results for Cooperation, UT Actors, 1966-1969, An Inventory of Findings.

    ERIC Educational Resources Information Center

    Vincent, Jack E.

    This monograph is a computer printout which presents findings from 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 ability to analyze international relations, this monograph presents the computer printout of data on the application of…

  12. Attributes and National Behavior, Part 2: Modern International Relations Monograph Series. Relative Status-Field Theory, Results for Cooperation, TU Actors, 1966-1969, An Inventory of Findings.

    ERIC Educational Resources Information Center

    Vincent, Jack E.

    This monograph is a computer printout which presents findings from an analysis of data on international cooperation over a three-year period. The document is part of a large scale research project to test various theories with regard to their ability to analyze international relations. In this monograph, data are analyzed according to relative…

  13. Attributes and National Behavior, Part 2: Modern International Relations Monograph Series. Relative Status-Field Theory, Results for Conflict, UT Actors, 1966-1969, An Inventory of Findings.

    ERIC Educational Resources Information Center

    Vincent, Jack E.

    This monograph is a computer printout which presents findings from an analysis of data on international conflict over a three-year period. Part of a large scale research project to test various theories with regard to their ability to analyze international relations, this monograph presents the computer printout of data on the application of…

  14. Attributes and National Behavior, Part 2: Modern International Relations Monograph Series. Relative Status-Field Theory, Results for Conflict, TT Actors, 1966-69, An Inventory of Findings.

    ERIC Educational Resources Information Center

    Vincent, Jack E.

    This monograph presents findings on international conflict 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 a computer printout of data regarding 'topdog' behavior among nations with regard to economic development and…

  15. Attributes and National Behavior, Part 2: Modern International Relations Monograph Series. Relative Status-Field Theory, Results for Conflict, TU Actors, 1966-1969, An Inventory of Findings.

    ERIC Educational Resources Information Center

    Vincent, Jack E.

    This monograph presents findings from an analysis of data on international conflict 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 the computer printout of data on the application of discriminant function analysis of…

  16. 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…

  17. 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…

  18. Attributes and National Behavior, Part 2: Modern International Relations Monograph Series. Patterns of Conflict: 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 conflict 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…

  19. Attributes and National Behavior, Part 2: Modern International Relations Monograph Series. Patterns of Conflict: Relative Status-Field Theory, TT Actors.

    ERIC Educational Resources Information Center

    Vincent, Jack E.

    This monograph presents the computer printout of an analysis of data on international conflict 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 'topdog'…

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

    ERIC Educational Resources Information Center

    Vincent, Jack E.

    This monograph presents 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 the computer printout of data on the application of second stage factor analysis of 'underdog'…

  1. Attributes and National Behavior, Part 2: Modern International Relations Monograph Series. Relative Status-Field Theory, Results for Cooperation, UU Actors, 1966-1969, An Inventory of Findings.

    ERIC Educational Resources Information Center

    Vincent, Jack E.

    This monograph presents findings from 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 the computer printout of data on the application of discriminant function analysis…

  2. Attributes and National Behavior, Part 2: Modern International Relations Monograph Series. Relative Status-Field Theory, Results for Conflict, UU Actors, 1966-1969, An Inventory of Findings.

    ERIC Educational Resources Information Center

    Vincent, Jack E.

    This monograph is a computer printout which presents findings from an analysis of data on international conflict over a three-year period. Part of a large scale research project to test various theories with regard to their ability to analyze international relations, this monograph presents the computer printout of data on the application of…

  3. Attributes and National Behavior, Part 2: Modern International Relations Monograph Series. Patterns of Conflict: Relative Status-Field Theory, UU Actors.

    ERIC Educational Resources Information Center

    Vincent, Jack E.

    This monograph presents the computer printout of an analysis of data on international conflict 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 of 'underdog'…

  4. 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. Copyright © 2015 Elsevier Inc. All rights reserved.

  5. Nonlinear effective-medium theory of disordered spring networks.

    PubMed

    Sheinman, M; Broedersz, C P; MacKintosh, F C

    2012-02-01

    Disordered soft materials, such as fibrous networks in biological contexts, exhibit a nonlinear elastic response. We study such nonlinear behavior with a minimal model for networks on lattice geometries with simple Hookian elements with disordered spring constant. By developing a mean-field approach to calculate the differential elastic bulk modulus for the macroscopic network response of such networks under large isotropic deformations, we provide insight into the origins of the strain stiffening and softening behavior of these systems. We find that the nonlinear mechanics depends only weakly on the lattice geometry and is governed by the average network connectivity. In particular, the nonlinear response is controlled by the isostatic connectivity, which depends strongly on the applied strain. Our predictions for the strain dependence of the isostatic point as well as the strain-dependent differential bulk modulus agree well with numerical results in both two and three dimensions. In addition, by using a mapping between the disordered network and a regular network with random forces, we calculate the nonaffine fluctuations of the deformation field and compare them to the numerical results. Finally, we discuss the limitations and implications of the developed theory.

  6. 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…

  7. Recent developments in quantitative graph theory: information inequalities for networks.

    PubMed

    Dehmer, Matthias; Sivakumar, Lavanya

    2012-01-01

    In this article, we tackle a challenging problem in quantitative graph theory. We establish relations between graph entropy measures representing the structural information content of networks. In particular, we prove formal relations between quantitative network measures based on Shannon's entropy to study the relatedness of those measures. In order to establish such information inequalities for graphs, we focus on graph entropy measures based on information functionals. To prove such relations, we use known graph classes whose instances have been proven useful in various scientific areas. Our results extend the foregoing work on information inequalities for graphs.

  8. Phase response theory extended to nonoscillatory network components

    PubMed Central

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

    2012-01-01

    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. PMID:23004844

  9. Recent Developments in Quantitative Graph Theory: Information Inequalities for Networks

    PubMed Central

    Dehmer, Matthias; Sivakumar, Lavanya

    2012-01-01

    In this article, we tackle a challenging problem in quantitative graph theory. We establish relations between graph entropy measures representing the structural information content of networks. In particular, we prove formal relations between quantitative network measures based on Shannon's entropy to study the relatedness of those measures. In order to establish such information inequalities for graphs, we focus on graph entropy measures based on information functionals. To prove such relations, we use known graph classes whose instances have been proven useful in various scientific areas. Our results extend the foregoing work on information inequalities for graphs. PMID:22355362

  10. 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.

  11. Dynamical graph theory networks techniques for the analysis of sparse connectivity networks in dementia

    NASA Astrophysics Data System (ADS)

    Tahmassebi, Amirhessam; Pinker-Domenig, Katja; Wengert, Georg; Lobbes, Marc; Stadlbauer, Andreas; Romero, Francisco J.; Morales, Diego P.; Castillo, Encarnacion; Garcia, Antonio; Botella, Guillermo; Meyer-Bäse, Anke

    2017-05-01

    Graph network models in dementia have become an important computational technique in neuroscience to study fundamental organizational principles of brain structure and function of neurodegenerative diseases such as dementia. The graph connectivity is reflected in the connectome, the complete set of structural and functional connections of the graph network, which is mostly based on simple Pearson correlation links. In contrast to simple Pearson correlation networks, the partial correlations (PC) only identify direct correlations while indirect associations are eliminated. In addition to this, the state-of-the-art techniques in brain research are based on static graph theory, which is unable to capture the dynamic behavior of the brain connectivity, as it alters with disease evolution. We propose a new research avenue in neuroimaging connectomics based on combining dynamic graph network theory and modeling strategies at different time scales. We present the theoretical framework for area aggregation and time-scale modeling in brain networks as they pertain to disease evolution in dementia. This novel paradigm is extremely powerful, since we can derive both static parameters pertaining to node and area parameters, as well as dynamic parameters, such as system's eigenvalues. By implementing and analyzing dynamically both disease driven PC-networks and regular concentration networks, we reveal differences in the structure of these network that play an important role in the temporal evolution of this disease. The described research is key to advance biomedical research on novel disease prediction trajectories and dementia therapies.

  12. Animal Social Network Theory Can Help Wildlife Conservation.

    PubMed

    Snijders, Lysanne; Blumstein, Daniel T; Stanley, Christina R; Franks, Daniel W

    2017-08-01

    Many animals preferentially associate with certain other individuals. This social structuring can influence how populations respond to changes to their environment, thus making network analysis a promising technique for understanding, predicting, and potentially manipulating population dynamics. Various network statistics can correlate with individual fitness components and key population-level processes, yet the logical role and formal application of animal social network theory for conservation and management have not been well articulated. We outline how understanding of direct and indirect relationships between animals can be profitably applied by wildlife managers and conservationists. By doing so, we aim to stimulate the development and implementation of practical tools for wildlife conservation and management and to inspire novel behavioral research in this field. Copyright © 2017 Elsevier Ltd. All rights reserved.

  13. 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

  14. Topological analysis of metabolic networks based on petri net theory.

    PubMed

    Zevedei-Oancea, Ionela; Schuster, Stefan

    2011-01-01

    Petri net concepts provide additional tools for the modelling of metabolic networks. Here, the similarities between the counterparts in traditional biochemical modelling and Petri net theory are discussed. For example the stoichiometry matrix of a metabolic network corresponds to the incidence matrix of the Petri net. The flux modes and conservation relations have the T-invariants, respectively, P-invariants as counterparts. We reveal the biological meaning of some notions specific to the Petri net framework (traps, siphons, deadlocks, liveness). We focus on the topological analysis rather than on the analysis of the dynamic behaviour. The treatment of external metabolites is discussed. Some simple theoretical examples are presented for illustration. Also the Petri nets corresponding to some biochemical networks are built to support our results. For example, the role of triose phosphate isomerase (TPI) in Trypanosoma brucei metabolism is evaluated by detecting siphons and traps. All Petri net properties treated in this contribution are exemplified on a system extracted from nucleotide metabolism.

  15. Network thermodynamics and complexity: a transition to relational systems theory.

    PubMed

    Mikulecky, D C

    2001-07-01

    Most systems of interest in today's world are highly structured and highly interactive. They cannot be reduced to simple components without losing a great deal of their system identity. Network thermodynamics is a marriage of classical and non-equilibrium thermodynamics along with network theory and kinetics to provide a practical framework for handling these systems. The ultimate result of any network thermodynamic model is still a set of state vector equations. But these equations are built in a new informative way so that information about the organization of the system is identifiable in the structure of the equations. The domain of network thermodynamics is all of physical systems theory. By using the powerful circuit simulator, the Simulation Program with Integrated Circuit Emphasis (SPICE), as a general systems simulator, any highly non-linear stiff system can be simulated. Furthermore, the theoretical findings of network thermodynamics are important new contributions. The contribution of a metric structure to thermodynamics compliments and goes beyond other recent work in this area. The application of topological reasoning through Tellegen's theorem shows that a mathematical structure exists into which all physical systems can be represented canonically. The old results in non-equilibrium thermodynamics due to Onsager can be reinterpreted and extended using these new, more holistic concepts about systems. Some examples are given. These are but a few of the many applications of network thermodynamics that have been proven to extend our capacity for handling the highly interactive, non-linear systems that populate both biology and chemistry. The presentation is carried out in the context of the recent growth of the field of complexity science. In particular, the context used for this discussion derives from the work of the mathematical biologist, Robert Rosen.

  16. Network theory to understand microarray studies of complex diseases.

    PubMed

    Benson, Mikael; Breitling, Rainer

    2006-09-01

    Complex diseases, such as allergy, diabetes and obesity depend on altered interactions between multiple genes, rather than changes in a single causal gene. DNA microarray studies of a complex disease often implicate hundreds of genes in the pathogenesis. This indicates that many different mechanisms and pathways are involved. How can we understand such complexity? How can hypotheses be formulated and tested? One approach is to organize the data in network models and to analyze these in a top-down manner. Globally, networks in nature are often characterized by a small number of highly connected nodes, while the majority of nodes have few connections. The highly connected nodes serve as hubs that affect many other nodes. Such hubs have key roles in the network. In yeast cells, for example, deletion of highly connected proteins is associated with increased lethality, compared to deletion of less connected proteins. This suggests the biological relevance of networks. Moving down in the network structure, there may be sub-networks or modules with specific functions. These modules may be further dissected to analyze individual nodes. In the context of DNA microarray studies of complex diseases, gene-interaction networks may contain modules of co-regulated or interacting genes that have distinct biological functions. Such modules may be linked to specific gene polymorphisms, transcription factors, cellular functions and disease mechanisms. Genes that are reliably active only in the context of their modules can be considered markers for the activity of the modules and may thus be promising candidates for biomarkers or therapeutic targets. This review aims to give an introduction to network theory and how it can be applied to microarray studies of complex diseases.

  17. 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.

  18. 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.

  19. Game theory for Wireless Sensor Networks: a survey.

    PubMed

    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.

  20. 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

  1. 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.

  2. Actors', partners', and observers' perceptions of sarcasm.

    PubMed

    Rockwell, P

    2000-10-01

    This study compared actors', partners', and observers' perceptions of the amount of sarcasm used by participants (n = 80) in videotaped conversations. Significant differences were found among perceptions of actors, partners, and observers. Of the three perspectives, actors perceived themselves as using the greatest amount of sarcasm, followed by partners' perceptions of actors. Observers perceived actors as using the least amount of sarcasm. Correlations conducted to assess whether partners and observers recognized actors' individual attempts at sarcasm during the conversations were generally low.

  3. 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…

  4. The role of vascular actors in two dimensional dialogue of human bone marrow stromal cell and endothelial cell for inducing self-assembled network.

    PubMed

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

    2011-02-03

    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.

  5. 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.

  6. Defeating Violent Nonstate Actors

    DTIC Science & Technology

    2013-01-01

    systems, vehicles, and support elements operating on land to accomplish assigned missions and tasks.” 2 Boots-on-the-ground integrated into Brigade...2011), http://www.foreignpolicy.com/articles/2011/02/22/ it_takes_a_network. 2 Via JP 3-31. See Joint Chiefs of Staff, Department of Defense...failing to comply with a collection of information if it does not display a currently valid OMB control number. 1. REPORT DATE 2013 2 . REPORT TYPE

  7. Theory of liquid crystal elastomers and polymer networks : Connection between neoclassical theory and differential geometry.

    PubMed

    Nguyen, Thanh-Son; Selinger, Jonathan V

    2017-09-01

    In liquid crystal elastomers and polymer networks, the orientational order of liquid crystals is coupled with elastic distortions of crosslinked polymers. Previous theoretical research has described these materials through two different approaches: a neoclassical theory based on the liquid crystal director and the deformation gradient tensor, and a geometric elasticity theory based on the difference between the actual metric tensor and a reference metric. Here, we connect those two approaches using a formalism based on differential geometry. Through this connection, we determine how both the director and the geometry respond to a change of temperature.

  8. Understanding Knowledge Network, Learning and Connectivism

    ERIC Educational Resources Information Center

    AlDahdouh, Alaa A.; Osório, António J.; Caires, Susana

    2015-01-01

    Behaviorism, Cognitivism, Constructivism and other growing theories such as Actor-Network and Connectivism are circulating in the educational field. For each, there are allies who stand behind research evidence and consistency of observation. Meantime, those existing theories dominate the field until the background is changed or new concrete…

  9. 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

  10. 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.

  11. 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.

  12. 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

  13. Understanding actors and object-goals in the human brain.

    PubMed

    Ramsey, Richard; Hamilton, Antonia F de C

    2010-04-15

    When another person takes 10 pounds from your hand, it matters if they are a shopkeeper or a robber. That is, the meaning of a simple, goal-directed action can vary depending on the identity of the actors involved. Research examining action understanding has identified an action observation network (AON) that encodes action features such as goals and kinematics. However, it is not yet known how or where the brain links actor identity to action goal. In the present paper, we used a repetition suppression paradigm during functional magnetic resonance imaging (fMRI) to examine the neural representation of actor identity within the context of object-directed actions. Participants watched video clips of two different actors with two different object-goals. Repeated presentation of the same actor suppressed the blood oxygen level-dependent (BOLD) response in fusiform gyrus and occipitotemporal cortex. In contrast, repeated presentation of an action with the same object-goal suppressed the BOLD response throughout the AON. Our data reveal an extended brain network for understanding other people and their everyday actions that go beyond the traditional action observation network.

  14. 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…

  15. 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

  16. Proteins as networks: usefulness of graph theory in protein science.

    PubMed

    Krishnan, Arun; Zbilut, Joseph P; Tomita, Masaru; Giuliani, Alessandro

    2008-02-01

    The network paradigm is based on the derivation of emerging properties of studied systems by their representation as oriented graphs: any system is traced back to a set of nodes (its constituent elements) linked by edges (arcs) correspondent to the relations existing between the nodes. This allows for a straightforward quantitative formalization of systems by means of the computation of mathematical descriptors of such graphs (graph theory). The network paradigm is particularly useful when it is clear which elements of the modelled system must play the role of nodes and arcs respectively, and when topological constraints have a major role with respect to kinetic ones. In this review we demonstrate how nodes and arcs of protein topology are characterized at different levels of definition: 1. Recurrence matrix of hydrophobicity patterns along the sequence 2. Contact matrix of alpha carbons of 3D structures 3. Correlation matrix of motions of different portion of the molecule in molecular dynamics. These three conditions represent different but potentially correlated reticular systems that can be profitably analysed by means of network analysis tools.

  17. Mean-field theory of assortative networks of phase oscillators

    NASA Astrophysics Data System (ADS)

    Restrepo, Juan G.; Ott, Edward

    2014-09-01

    Employing the Kuramoto model as an illustrative example, we show how the use of the mean-field approximation can be applied to large networks of phase oscillators with assortativity. We then use the ansatz of Ott and Antonsen (Chaos, 19 (2008) 037113) to reduce the mean-field kinetic equations to a system of ordinary differential equations. The resulting formulation is illustrated by application to a network Kuramoto problem with degree assortativity and correlation between the node degrees and the natural oscillation frequencies. Good agreement is found between the solutions of the reduced set of ordinary differential equations obtained from our theory and full simulations of the system. These results highlight the ability of our method to capture all the phase transitions (bifurcations) and system attractors. One interesting result is that degree assortativity can induce transitions from a steady macroscopic state to a temporally oscillating macroscopic state through both (presumed) Hopf and SNIPER (saddle-node, infinite period) bifurcations. Possible use of these techniques to a broad class of phase oscillator network problems is discussed.

  18. 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…

  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. Imperishable Networks: Complexity Theory and Communication Networking-Bridging the Gap Between Algorithmic Information Theory and Communication Networking

    DTIC Science & Technology

    2003-04-01

    resources. This idea can be extended to optimize or prevent adverse effects from critical resources in addition to band- width and CPU. Memory , time of...tolerance. Active networks form an ideal environment in which to study the effects of trade-offs in algorithmic and static information representation...39 The effect of a partition on MML . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 40 Symbol

  1. Reading: Tales for Two Actors.

    ERIC Educational Resources Information Center

    Slattery, Judith M.

    1979-01-01

    The author explains how she changes folk tales into simple two-actor plays geared to the oral reading ability of her remedial reading students. Two of her plays are included in this article: "A Halloween Tale" and "The Three Wishes." (SJL)

  2. 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…

  3. 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…

  4. Reading: Tales for Two Actors.

    ERIC Educational Resources Information Center

    Slattery, Judith M.

    1979-01-01

    The author explains how she changes folk tales into simple two-actor plays geared to the oral reading ability of her remedial reading students. Two of her plays are included in this article: "A Halloween Tale" and "The Three Wishes." (SJL)

  5. Application of Game Theory Approaches in Routing Protocols for Wireless Networks

    NASA Astrophysics Data System (ADS)

    Javidi, Mohammad M.; Aliahmadipour, Laya

    2011-09-01

    An important and essential issue for wireless networks is routing protocol design that is a major technical challenge due to the function of the network. Game theory is a powerful mathematical tool that analyzes the strategic interactions among multiple decision makers and the results of researches show that applied game theory in routing protocol lead to improvement the network performance through reduce overhead and motivates selfish nodes to collaborate in the network. This paper presents a review and comparison for typical representatives of routing protocols designed that applied game theory approaches for various wireless networks such as ad hoc networks, mobile ad hoc networks and sensor networks that all of them lead to improve the network performance.

  6. Methods of information theory and algorithmic complexity for network biology.

    PubMed

    Zenil, Hector; Kiani, Narsis A; Tegnér, Jesper

    2016-03-01

    We survey and introduce concepts and tools located at the intersection of information theory and network biology. We show that Shannon's information entropy, compressibility and algorithmic complexity quantify different local and global aspects of synthetic and biological data. We show examples such as the emergence of giant components in Erdös-Rényi random graphs, and the recovery of topological properties from numerical kinetic properties simulating gene expression data. We provide exact theoretical calculations, numerical approximations and error estimations of entropy, algorithmic probability and Kolmogorov complexity for different types of graphs, characterizing their variant and invariant properties. We introduce formal definitions of complexity for both labeled and unlabeled graphs and prove that the Kolmogorov complexity of a labeled graph is a good approximation of its unlabeled Kolmogorov complexity and thus a robust definition of graph complexity. Copyright © 2016 Elsevier Ltd. All rights reserved.

  7. Nuclear charge radii: density functional theory meets Bayesian neural networks

    NASA Astrophysics Data System (ADS)

    Utama, R.; Chen, Wei-Chia; Piekarewicz, J.

    2016-11-01

    The distribution of electric charge in atomic nuclei is fundamental to our understanding of the complex nuclear dynamics and a quintessential observable to validate nuclear structure models. The aim of this study is to explore a novel approach that combines sophisticated models of nuclear structure with Bayesian neural networks (BNN) to generate predictions for the charge radii of thousands of nuclei throughout the nuclear chart. A class of relativistic energy density functionals is used to provide robust predictions for nuclear charge radii. In turn, these predictions are refined through Bayesian learning for a neural network that is trained using residuals between theoretical predictions and the experimental data. Although predictions obtained with density functional theory provide a fairly good description of experiment, our results show significant improvement (better than 40%) after BNN refinement. Moreover, these improved results for nuclear charge radii are supplemented with theoretical error bars. We have successfully demonstrated the ability of the BNN approach to significantly increase the accuracy of nuclear models in the predictions of nuclear charge radii. However, as many before us, we failed to uncover the underlying physics behind the intriguing behavior of charge radii along the calcium isotopic chain.

  8. 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

  9. 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.

  10. 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…

  11. An approach to design long-term monitoring and evaluation frameworks in multi-actor systems--a case in water management.

    PubMed

    Hermans, Leon M; Naber, Arienne C; Enserink, Bert

    2012-11-01

    Learning-by-doing and adaptive management require careful monitoring and evaluation of the outcomes of environmental policies and programs under implementation. Selecting relevant indicators is difficult, especially when monitoring over a longer period of time. Further challenges arise when policies are developed as a collaborative effort among multiple actors. This paper discusses an approach to design frameworks for long-term monitoring and evaluation in multi-actor systems. It uses Dynamic Actor Network Analysis (DANA) as an actor-sensitive method to reconstruct program theories. This is combined with elements of assumption-based planning to identify critical assumptions and associated indicators to incorporate the dynamic aspects related to long-term monitoring. An application of this approach is described for a case of water management in the Netherlands. Here, mapping multiple perspectives and identifying critical assumptions helped to broaden the scope of monitoring in important ways. Identifying associated indicators and expectations on their development in response to policy implementation proved more difficult. From this case, it can be concluded that the approach is feasible, useful, but also demanding. However, with continuing trends of networked governance and adaptive management, additional efforts to reflect these trends in monitoring and evaluation, through this and similar approaches, are needed.

  12. 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…

  13. 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…

  14. 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…

  15. 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.

  16. 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.

  17. Self-similarity and scaling theory of complex networks

    NASA Astrophysics Data System (ADS)

    Song, Chaoming

    Scale-free networks have been studied extensively due to their relevance to many real systems as diverse as the World Wide Web (WWW), the Internet, biological and social networks. We present a novel approach to the analysis of scale-free networks, revealing that their structure is self-similar. This result is achieved by the application of a renormalization procedure which coarse-grains the system into boxes containing nodes within a given "size". Concurrently, we identify a power-law relation between the number of boxes needed to cover the network and the size of the box defining a self-similar exponent, which classifies fractal and non-fractal networks. By using the concept of renormalization as a mechanism for the growth of fractal and non-fractal modular networks, we show that the key principle that gives rise to the fractal architecture of networks is a strong effective "repulsion" between the most connected nodes (hubs) on all length scales, rendering them very dispersed. We show that a robust network comprised of functional modules, such as a cellular network, necessitates a fractal topology, suggestive of a evolutionary drive for their existence. These fundamental properties help to understand the emergence of the scale-free property in complex networks.

  18. Asymptotic theory of time varying networks with burstiness and heterogeneous activation patterns

    NASA Astrophysics Data System (ADS)

    Burioni, Raffaella; Ubaldi, Enrico; Vezzani, Alessandro

    2017-05-01

    The recent availability of large-scale, time-resolved and high quality digital datasets has allowed for a deeper understanding of the structure and properties of many real-world networks. The empirical evidence of a temporal dimension prompted the switch of paradigm from a static representation of networks to a time varying one. In this work we briefly review the framework of time-varying-networks in real world social systems, especially focusing on the activity-driven paradigm. We develop a framework that allows for the encoding of three generative mechanisms that seem to play a central role in the social networks’ evolution: the individual’s propensity to engage in social interactions, its strategy in allocate these interactions among its alters and the burstiness of interactions amongst social actors. The functional forms and probability distributions encoding these mechanisms are typically data driven. A natural question arises if different classes of strategies and burstiness distributions, with different local scale behavior and analogous asymptotics can lead to the same long time and large scale structure of the evolving networks. We consider the problem in its full generality, by investigating and solving the system dynamics in the asymptotic limit, for general classes of ties allocation mechanisms and waiting time probability distributions. We show that the asymptotic network evolution is driven by a few characteristics of these functional forms, that can be extracted from direct measurements on large datasets.

  19. Synchronization in networks with random interactions: Theory and applications

    NASA Astrophysics Data System (ADS)

    Feng, Jianfeng; Jirsa, Viktor K.; Ding, Mingzhou

    2006-03-01

    Synchronization is an emergent property in networks of interacting dynamical elements. Here we review some recent results on synchronization in randomly coupled networks. Asymptotical behavior of random matrices is summarized and its impact on the synchronization of network dynamics is presented. Robert May's results on the stability of equilibrium points in linear dynamics are first extended to systems with time delayed coupling and then nonlinear systems where the synchronized dynamics can be periodic or chaotic. Finally, applications of our results to neuroscience, in particular, networks of Hodgkin-Huxley neurons, are included.

  20. 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.

  1. 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

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

    PubMed

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

    2015-01-01

    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. 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). 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. 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.

  3. 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.

  4. 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.

  5. 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. Copyright © 2015 Elsevier Ltd. All rights reserved.

  6. Applications of small-world network theory in alcohol epidemiology.

    PubMed

    Braun, Richard J; Wilson, Robert A; Pelesko, John A; Buchanan, J Robert; Gleeson, James P

    2006-07-01

    This study develops a mathematical model of alcohol abuse in structured populations, such as communities and college campuses. The study employs a network model that has the capacity to incorporate a variety of forms of connectivity membership besides personal acquaintance, such as geographic proximity and common organizations. The model also incorporates a resilience dimension that indicates the susceptibility of each individual in a network to alcohol abuse. The model has the capacity to simulate the effect of moving alcohol abusers into networks of nonabusers, either as the result of treatment or membership in self-help organizations. The study employs a small-world model. A cubic equation for each person (vertex on a graph) governs the evolution of an individual's state between 0 and 1 with regard to alcohol dependence, with 1 indicating absolute certainty of alcohol dependence. The simulations are dependent on initial conditions, the structure of the network, and the resilience distribution of the network. The simulations incorporate multiple realizations of social networks, showing the effect of different network structures. The model suggests that the prevalence of alcohol abuse can be minimized by treating a relatively small percentage of the study population. In the small populations that we studied, the critical point was 10% or less of the study population, but we emphasize that this is within the limitations and assumptions of this model. The use of a simple model that incorporates the influence of the social network neighbors in structured populations shows promise for helping to inform treatment and prevention policy.

  7. Branching Network Theory and Application in Geosciences (Invited)

    NASA Astrophysics Data System (ADS)

    Waymire, E. C.

    2009-12-01

    This talk will provide a partial overview of the mathematical development of various aspects of branching networks at the heart of a wide variety of geophysical and environmental applications. In addition some recently emerging mathematical structures will be described in this framework to address dispersion and transport phenomena in river networks.

  8. Networking Theories on Giftedness--What We Can Learn from Synthesizing Renzulli's Domain General and Krutetskii's Mathematics-Specific Theory

    ERIC Educational Resources Information Center

    Schindler, Maike; Rott, Benjamin

    2017-01-01

    Giftedness is an increasingly important research topic in educational sciences and mathematics education in particular. In this paper, we contribute to further theorizing mathematical giftedness through illustrating how networking processes can be conducted and illustrating their potential benefits. The paper focuses on two theories: Renzulli's…

  9. The Altered Triple Networks Interaction in Depression under Resting State Based on Graph Theory

    PubMed Central

    Xu, Lele; Xie, Fufang; Guo, Xiaojuan; Zhang, Jiacai; Yao, Li; Wu, Xia

    2015-01-01

    The triple network model (Menon, 2011) has been proposed, which helps with finding a common framework for understanding the dysfunction in core neurocognitive network across multiple disorders. The alteration of the triple networks in the major depression disorder (MDD) is not clear. In our study, the altered interaction of the triple networks, which include default model network (DMN), central executive network (CEN), and salience network (SN), was examined in the MDD by graph theory method. The results showed that the connectivity degree of right anterior insula (rAI) significantly increased in MDD compared with healthy control (HC), and the connectivity degree between DMN and CEN significantly decreased in MDD. These results not only supported the proposal of the triple network model, but also prompted us to understand the dysfunction of neural mechanism in MDD. PMID:26180798

  10. The Altered Triple Networks Interaction in Depression under Resting State Based on Graph Theory.

    PubMed

    Zheng, Hongna; Xu, Lele; Xie, Fufang; Guo, Xiaojuan; Zhang, Jiacai; Yao, Li; Wu, Xia

    2015-01-01

    The triple network model (Menon, 2011) has been proposed, which helps with finding a common framework for understanding the dysfunction in core neurocognitive network across multiple disorders. The alteration of the triple networks in the major depression disorder (MDD) is not clear. In our study, the altered interaction of the triple networks, which include default model network (DMN), central executive network (CEN), and salience network (SN), was examined in the MDD by graph theory method. The results showed that the connectivity degree of right anterior insula (rAI) significantly increased in MDD compared with healthy control (HC), and the connectivity degree between DMN and CEN significantly decreased in MDD. These results not only supported the proposal of the triple network model, but also prompted us to understand the dysfunction of neural mechanism in MDD.

  11. 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.

  12. 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…

  13. 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)

  14. 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…

  15. 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…

  16. Ninter-Networked Interaction: Theory-based Cases in Teaching and Learning.

    ERIC Educational Resources Information Center

    Saarenkunnas, Maarit; Jarvela, Sanna; Hakkinen, Paivi; Kuure, Leena; Taalas, Peppi; Kunelius, Esa

    2000-01-01

    Describes the pedagogical framework of an interdisciplinary, international project entitled NINTER (Networked Interaction: Theory-Based Cases in Teaching and Learning). Discusses a pedagogical model for teacher and staff development programs in a networked environment; distributed cognition; cognitive apprenticeship; challenges for educational…

  17. 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)

  18. 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…

  19. Cyberspace Assurance Metrics: Utilizing Models of Networks, Complex Systems Theory, Multidimensional Wavelet Analysis, and Generalized Entrophy Measures

    DTIC Science & Technology

    2005-04-01

    the topological specification of a network in the form of a connection matrix and the branches of mathematics known as continuous group theory and...Connection Matrix . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .3 2.2 Dynamical Network Changes...essential aspects of the network into just a few metrics (functions of the network matrix values). It is well known that a network is characterized

  20. Network Theory Analysis of Antibody-Antigen Reactivity Data: The Immune Trees at Birth and Adulthood

    PubMed Central

    Bransburg-Zabary, Sharron; Merbl, Yifat; Quintana, Francisco J.; Tauber, Alfred I.; Cohen, Irun R.; Ben-Jacob, Eshel

    2011-01-01

    Motivation New antigen microarray technology enables parallel recording of antibody reactivities with hundreds of antigens. Such data affords system level analysis of the immune system's organization using methods and approaches from network theory. Here we measured the reactivity of 290 antigens (for both the IgG and IgM isotypes) of 10 healthy mothers and their term newborns. We constructed antigen correlation networks (or immune networks) whose nodes are the antigens and the edges are the antigen-antigen reactivity correlations, and we also computed their corresponding minimum spanning trees (MST) – maximal information reduced sub-graphs. We quantify the network organization (topology) in terms of the network theory divergence rate measure and rank the antigen importance in the full antigen correlation networks by the eigen-value centrality measure. This analysis makes possible the characterization and comparison of the IgG and IgM immune networks at birth (newborns) and adulthood (mothers) in terms of topology and node importance. Results Comparison of the immune network topology at birth and adulthood revealed partial conservation of the IgG immune network topology, and significant reorganization of the IgM immune networks. Inspection of the antigen importance revealed some dominant (in terms of high centrality) antigens in the IgG and IgM networks at birth, which retain their importance at adulthood. PMID:21408156

  1. Voting procedures from the perspective of theory of neural networks

    NASA Astrophysics Data System (ADS)

    Suleimenov, Ibragim; Panchenko, Sergey; Gabrielyan, Oleg; Pak, Ivan

    2016-11-01

    It is shown that voting procedure in any authority can be treated as Hopfield neural network analogue. It was revealed that weight coefficients of neural network which has discrete outputs -1 and 1 can be replaced by coefficients of a discrete set (-1, 0, 1). This gives us the opportunity to qualitatively analyze the voting procedure on the basis of limited data about mutual influence of members. It also proves that result of voting procedure is actually taken by network formed by voting members.

  2. Small-world network spectra in mean-field theory.

    PubMed

    Grabow, Carsten; Grosskinsky, Stefan; Timme, Marc

    2012-05-25

    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.

  3. 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.

  4. A Practical Theory of Micro-Solar Power Sensor Networks

    DTIC Science & Technology

    2009-04-20

    candidate. The deployment is evaluated by analyzing the effects of different solar profiles across the network. The analysis from the deployment can be...analyzing the effects of different solar profiles across the network. The analysis from the deployment can be used to refine the next system-design...radiation for solar panel at operating point and MPP with a Trio node. . . . . 34 3.6 Current consumption of a Trio node with radio duty-cycle of 1.56

  5. Predicting Networked Strategic Behavior via Machine Learning and Game Theory

    DTIC Science & Technology

    2015-01-13

    The funding for this project was used to develop basic models, methodology and algorithms for the application of machine learning and related tools to settings in which strategic behavior is central. Among the topics studied was the development of simple behavioral models explaining and predicting human subject behavior in networked strategic experiments from prior work. These included experiments in biased voting and networked trading, among others.

  6. Traditional Chinese medicine network pharmacology: theory, methodology and application.

    PubMed

    Li, Shao; Zhang, Bo

    2013-03-01

    Traditional Chinese medicine (TCM) has a long history of viewing an individual or patient as a system with different statuses, and has accumulated numerous herbal formulae. The holistic philosophy of TCM shares much with the key ideas of emerging network pharmacology and network biology, and meets the requirements of overcoming complex diseases, such as cancer, in a systematic manner. To discover TCM from a systems perspective and at the molecular level, a novel TCM network pharmacology approach was established by updating the research paradigm from the current "one target, one drug" mode to a new "network target, multi-components" mode. Subsequently, a set of TCM network pharmacology methods were created to prioritize disease-associated genes, to predict the target profiles and pharmacological actions of herbal compounds, to reveal drug-gene-disease co-module associations, to screen synergistic multi-compounds from herbal formulae in a high-throughput manner, and to interpret the combinatorial rules and network regulation effects of herbal formulae. The effectiveness of the network-based methods was demonstrated for the discovery of bioactive compounds and for the elucidation of the mechanisms of action of herbal formulae, such as Qing-Luo-Yin and the Liu-Wei-Di-Huang pill. The studies suggest that the TCM network pharmacology approach provides a new research paradigm for translating TCM from an experience-based medicine to an evidence-based medicine system, which will accelerate TCM drug discovery, and also improve current drug discovery strategies. Copyright © 2013 China Pharmaceutical University. Published by Elsevier B.V. All rights reserved.

  7. Actors in Academia--Roles Professors Play

    ERIC Educational Resources Information Center

    Minter, Mary Kennedy

    2009-01-01

    In order to set the stage for the "actors in academia," the author suggests that the following roles and responsibilities are the most significant ones for the college/university professor, including some for students: (1) Actor; (2) Communicator; (3) Facilitator; (4) Trainer/Coach; (5) Craftsman (craft of teaching); and (6) Manager. After 40…

  8. 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.

  9. 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.

  10. Graph Theory-Based Pinning Synchronization of Stochastic Complex Dynamical Networks.

    PubMed

    Li, Xiao-Jian; Yang, Guang-Hong

    2017-02-01

    This paper is concerned with the adaptive pinning synchronization problem of stochastic complex dynamical networks (CDNs). Based on algebraic graph theory and Lyapunov theory, pinning controller design conditions are derived, and the rigorous convergence analysis of synchronization errors in the probability sense is also conducted. Compared with the existing results, the topology structures of stochastic CDN are allowed to be unknown due to the use of graph theory. In particular, it is shown that the selection of nodes for pinning depends on the unknown lower bounds of coupling strengths. Finally, an example on a Chua's circuit network is given to validate the effectiveness of the theoretical results.

  11. 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.

  12. 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

  13. 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.

  14. [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.

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

    PubMed

    Salim, Shelly; Moh, Sangman

    2016-06-30

    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.

  16. 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

  17. 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.

  18. Neural networks for perceptual processing: from simulation tools to theories.

    PubMed

    Gurney, Kevin

    2007-03-29

    Neural networks are modelling tools that are, in principle, able to capture the input-output behaviour of arbitrary systems that may include the dynamics of animal populations or brain circuits. While a neural network model is useful if it captures phenomenologically the behaviour of the target system in this way, its utility is amplified if key mechanisms of the model can be discovered, and identified with those of the underlying system. In this review, we first describe, at a fairly high level with minimal mathematics, some of the tools used in constructing neural network models. We then go on to discuss the implications of network models for our understanding of the system they are supposed to describe, paying special attention to those models that deal with neural circuits and brain systems. We propose that neural nets are useful for brain modelling if they are viewed in a wider computational framework originally devised by Marr. Here, neural networks are viewed as an intermediate mechanistic abstraction between 'algorithm' and 'implementation', which can provide insights into biological neural representations and their putative supporting architectures.

  19. Increased segregation of brain networks in focal epilepsy: An fMRI graph theory finding

    PubMed Central

    Pedersen, Mangor; Omidvarnia, Amir H.; Walz, Jennifer M.; Jackson, Graeme D.

    2015-01-01

    Focal epilepsy is conceived of as activating local areas of the brain as well as engaging regional brain networks. Graph theory represents a powerful quantitative framework for investigation of brain networks. Here we investigate whether functional network changes are present in extratemporal focal epilepsy. Task-free functional magnetic resonance imaging data from 15 subjects with extratemporal epilepsy and 26 age and gender matched healthy controls were used for analysis. Local network properties were calculated using local efficiency, clustering coefficient and modularity metrics. Global network properties were assessed with global efficiency and betweenness centrality metrics. Cost-efficiency of the networks at both local and global levels was evaluated by estimating the physical distance between functionally connected nodes, in addition to the overall numbers of connections in the network. Clustering coefficient, local efficiency and modularity were significantly higher in individuals with focal epilepsy than healthy control subjects, while global efficiency and betweenness centrality were not significantly different between the two groups. Local network properties were also highly efficient, at low cost, in focal epilepsy subjects compared to healthy controls. Our results show that functional networks in focal epilepsy are altered in a way that the nodes of the network are more isolated. We postulate that network regularity, or segregation of the nodes of the networks, may be an adaptation that inhibits the conversion of the interictal state to seizures. It remains possible that this may be part of the epileptogenic process or an effect of medications. PMID:26110111

  20. Increased segregation of brain networks in focal epilepsy: An fMRI graph theory finding.

    PubMed

    Pedersen, Mangor; Omidvarnia, Amir H; Walz, Jennifer M; Jackson, Graeme D

    2015-01-01

    Focal epilepsy is conceived of as activating local areas of the brain as well as engaging regional brain networks. Graph theory represents a powerful quantitative framework for investigation of brain networks. Here we investigate whether functional network changes are present in extratemporal focal epilepsy. Task-free functional magnetic resonance imaging data from 15 subjects with extratemporal epilepsy and 26 age and gender matched healthy controls were used for analysis. Local network properties were calculated using local efficiency, clustering coefficient and modularity metrics. Global network properties were assessed with global efficiency and betweenness centrality metrics. Cost-efficiency of the networks at both local and global levels was evaluated by estimating the physical distance between functionally connected nodes, in addition to the overall numbers of connections in the network. Clustering coefficient, local efficiency and modularity were significantly higher in individuals with focal epilepsy than healthy control subjects, while global efficiency and betweenness centrality were not significantly different between the two groups. Local network properties were also highly efficient, at low cost, in focal epilepsy subjects compared to healthy controls. Our results show that functional networks in focal epilepsy are altered in a way that the nodes of the network are more isolated. We postulate that network regularity, or segregation of the nodes of the networks, may be an adaptation that inhibits the conversion of the interictal state to seizures. It remains possible that this may be part of the epileptogenic process or an effect of medications.

  1. 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.

  2. 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…

  3. Subjects, Networks and Positions: Thinking Educational Guidance Differently

    ERIC Educational Resources Information Center

    Usher, Robin; Edwards, Richard G.

    2005-01-01

    This article explores the ways in which framings drawn from post-structuralism can help to inform the understanding of guidance practices. In particular, it draws upon the later work of Foucault and Actor-Network Theory to question the centrality of the humanistic subject predominant within discourses of contemporary guidance and raise issues of…

  4. 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…

  5. 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…

  6. 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…

  7. 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.

  8. 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.

  9. 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.

  10. Theory of resistor networks: the two-point resistance

    NASA Astrophysics Data System (ADS)

    Wu, F. Y.

    2004-07-01

    The resistance between two arbitrary nodes in a resistor network is obtained in terms of the eigenvalues and eigenfunctions of the Laplacian matrix associated with the network. Explicit formulae for two-point resistances are deduced for regular lattices in one, two and three dimensions under various boundary conditions including that of a Möbius strip and a Klein bottle. The emphasis is on lattices of finite sizes. We also deduce summation and product identities which can be used to analyse large-size expansions in two and higher dimensions.

  11. 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.

  12. Workshop: Theory an Applications of Coupled Cell Networks

    DTIC Science & Technology

    2006-03-22

    Economia and Centro de Matematica, Universidade do Porto) Application of coupled cell systems have been made to a wide range of problems in the physical and...the propagation of perturbations across the optical spectrum. Minimal coupled cell networks M. Aguiar (Faculdade de Economia do Porto), A.P.S. Dias

  13. 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…

  14. 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.

  15. Discretized kinetic theory on scale-free networks

    NASA Astrophysics Data System (ADS)

    Bertotti, Maria Letizia; Modanese, Giovanni

    2016-10-01

    The network of interpersonal connections is one of the possible heterogeneous factors which affect the income distribution emerging from micro-to-macro economic models. In this paper we equip our model discussed in [1, 2] with a network structure. The model is based on a system of n differential equations of the kinetic discretized-Boltzmann kind. The network structure is incorporated in a probabilistic way, through the introduction of a link density P(α) and of correlation coefficients P(β|α), which give the conditioned probability that an individual with α links is connected to one with β links. We study the properties of the equations and give analytical results concerning the existence, normalization and positivity of the solutions. For a fixed network with P(α) = c/α q , we investigate numerically the dependence of the detailed and marginal equilibrium distributions on the initial conditions and on the exponent q. Our results are compatible with those obtained from the Bouchaud-Mezard model and from agent-based simulations, and provide additional information about the dependence of the individual income on the level of connectivity.

  16. 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. Copyright © 2015 Elsevier B.V. All rights reserved.

  17. Brain Network Theory Can Predict Whether Neuropsychological Outcomes Will Differ from Clinical Expectations.

    PubMed

    Warren, David E; Denburg, Natalie L; Power, Jonathan D; Bruss, Joel; Waldron, Eric J; Sun, Haoxin; Petersen, Steve E; Tranel, Daniel

    2017-02-01

    Theories of brain-network organization based on neuroimaging data have burgeoned in recent years, but the predictive power of such theories for cognition and behavior has only rarely been examined. Here, predictions from clinical neuropsychologists about the cognitive profiles of patients with focal brain lesions were used to evaluate a brain-network theory (Warren et al., 2014). Neuropsychologists made predictions regarding the neuropsychological profiles of a neurological patient sample (N = 30) based on lesion location. The neuropsychologists then rated the congruence of their predictions with observed neuropsychological outcomes, in regard to the "severity" of neuropsychological deficits and the "focality" of neuropsychological deficits. Based on the network theory, two types of lesion locations were identified: "target" locations (putative hubs in a brain-wide network) and "control" locations (hypothesized to play limited roles in network function). We found that patients with lesions of target locations (N = 19) had deficits of greater than expected severity that were more widespread than expected, whereas patients with lesions of control locations (N = 11) showed milder, circumscribed deficits that were more congruent with expectations. The findings for the target brain locations suggest that prevailing views of brain-behavior relationships may be sharpened and refined by integrating recently proposed network-oriented perspectives. © The Author 2016. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

  18. The Application of Queueing Theory to Communications Networks -- A Review,

    DTIC Science & Technology

    1984-03-01

    chains 3.4.3 Inhomogeneous Markov chains 3.5 Continuous-time Narkov chains 3.6 Birth -death processes 3.6.1 The Chapman-Kolmogorov equations 3.6.2 Poisson...34 The BIRTH -DEATH PROCESS is a special case of a Markov chain where transitions may only take place to the current state or neighbouring states. A...by IT Q -o 1 (38) ---- --- * 15 3.6 Birth -death processes 3.6.1 The Chapman-Kolmogorov equations Elementary queueing theory is built upon the theory

  19. Network organization is globally atypical in autism: A graph theory study of intrinsic functional connectivity.

    PubMed

    Keown, Christopher L; Datko, Michael C; Chen, Colleen P; Maximo, José Omar; Jahedi, Afrooz; Müller, Ralph-Axel

    2017-01-01

    Despite abundant evidence of brain network anomalies in autism spectrum disorder (ASD), findings have varied from broad functional underconnectivity to broad overconnectivity. Rather than pursuing overly simplifying general hypotheses ('under' vs. 'over'), we tested the hypothesis of atypical network distribution in ASD (i.e., participation of unusual loci in distributed functional networks). We used a selective high-quality data subset from the ABIDE datashare (including 111 ASD and 174 typically developing [TD] participants) and several graph theory metrics. Resting state functional MRI data were preprocessed and analyzed for detection of low-frequency intrinsic signal correlations. Groups were tightly matched for available demographics and head motion. As hypothesized, the Rand Index (reflecting how similar network organization was to a normative set of networks) was significantly lower in ASD than TD participants. This was accounted for by globally reduced cohesion and density, but increased dispersion of networks. While differences in hub architecture did not survive correction, rich club connectivity (among the hubs) was increased in the ASD group. Our findings support the model of reduced network integration (connectivity with networks) and differentiation (or segregation; based on connectivity outside network boundaries) in ASD. While the findings applied at the global level, they were not equally robust across all networks and in one case (greater cohesion within ventral attention network in ASD) even reversed.

  20. Some characteristics of supernetworks based on unified hybrid network theory framework

    NASA Astrophysics Data System (ADS)

    Liu, Qiang; Fang, Jin-Qing; Li, Yong

    Comparing with single complex networks, supernetworks are more close to the real world in some ways, and have become the newest research hot spot in the network science recently. Some progresses have been made in the research of supernetworks, but the theoretical research method and complex network characteristics of supernetwork models are still needed to further explore. In this paper, we propose three kinds of supernetwork models with three layers based on the unified hybrid network theory framework (UHNTF), and introduce preferential and random linking, respectively, between the upper and lower layers. Then we compared the topological characteristics of the single networks with the supernetwork models. In order to analyze the influence of the interlayer edges on network characteristics, the cross-degree is defined as a new important parameter. Then some interesting new phenomena are found, the results imply this supernetwork model has reference value and application potential.

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

    PubMed

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

    2015-09-08

    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.

  2. 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.

  3. 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

  4. 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.

  5. 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. Copyright © 2015 Elsevier Ltd. All rights reserved.

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

    PubMed

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

    2015-06-01

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

  7. The use of network theory to model disparate ship design information

    NASA Astrophysics Data System (ADS)

    Rigterink, Douglas; Piks, Rebecca; Singer, David J.

    2014-06-01

    This paper introduces the use of network theory to model and analyze disparate ship design information. This work will focus on a ship's distributed systems and their intra- and intersystem structures and interactions. The three system to be analyzed are: a passageway system, an electrical system, and a fire fighting system. These systems will be analyzed individually using common network metrics to glean information regarding their structures and attributes. The systems will also be subjected to community detection algorithms both separately and as a multiplex network to compare their similarities, differences, and interactions. Network theory will be shown to be useful in the early design stage due to its simplicity and ability to model any shipboard system.

  8. Functional neural networks of honesty and dishonesty in children: Evidence from graph theory analysis.

    PubMed

    Ding, Xiao Pan; Wu, Si Jia; Liu, Jiangang; Fu, Genyue; Lee, Kang

    2017-09-21

    The present study examined how different brain regions interact with each other during spontaneous honest vs. dishonest communication. More specifically, we took a complex network approach based on the graph-theory to analyze neural response data when children are spontaneously engaged in honest or dishonest acts. Fifty-nine right-handed children between 7 and 12 years of age participated in the study. They lied or told the truth out of their own volition. We found that lying decreased both the global and local efficiencies of children's functional neural network. This finding, for the first time, suggests that lying disrupts the efficiency of children's cortical network functioning. Further, it suggests that the graph theory based network analysis is a viable approach to study the neural development of deception.

  9. Parameter Networks: Towards a Theory of Low-level Vision,

    DTIC Science & Technology

    1981-04-01

    8217Iels suc(h ,-s thiose shown in 1ligure 7 to reorganize origami wo.d- figures. Figoure?7. 1’o show an example In detail, Kender’s techn!Ciue for...Compuiter Science Dept, Carnegie-.Mcllon U., October 1979. Kanade, Tl., "A theory of Origami world," CMU-CS-78-144, Computer Science Dept, Carnegie

  10. Lone-Actor Terrorist Target Choice.

    PubMed

    Gill, Paul; Corner, Emily

    2016-09-01

    Lone-actor terrorist attacks have risen to the forefront of the public's consciousness in the past few years. Some of these attacks were conducted against public officials. The rise of hard-to-detect, low-tech attacks may lead to more public officials being targeted. This paper explores whether different behavioral traits are apparent within a sample of lone-actor terrorists who plotted against high-value targets (including public officials) than within a sample of lone actors who plotted against members of the public. Utilizing a unique dataset of 111 lone-actor terrorists, we test a series of hypotheses related to attack capability and operational security. The results indicate that very little differentiates those who attack high-value targets from those who attack members of the public. We conclude with a series of illustrations to theorize why this may be the case. Copyright © 2016 John Wiley & Sons, Ltd.

  11. 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.

  12. 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

  13. Massive-scale gene co-expression network construction and robustness testing using random matrix theory.

    PubMed

    Gibson, Scott M; Ficklin, Stephen P; 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.

  14. 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.

  15. 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

  16. 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…

  17. 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…

  18. 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.

  19. Associative nature of event participation dynamics: A network theory approach

    PubMed Central

    Smiljanić, Jelena; Mitrović Dankulov, Marija

    2017-01-01

    The affiliation with various social groups can be a critical factor when it comes to quality of life of each individual, making such groups an essential element of every society. The group dynamics, longevity and effectiveness strongly depend on group’s ability to attract new members and keep them engaged in group activities. It was shown that high heterogeneity of scientist’s engagement in conference activities of the specific scientific community depends on the balance between the numbers of previous attendances and non-attendances and is directly related to scientist’s association with that community. Here we show that the same holds for leisure groups of the Meetup website and further quantify individual members’ association with the group. We examine how structure of personal social networks is evolving with the event attendance. Our results show that member’s increasing engagement in the group activities is primarily associated with the strengthening of already existing ties and increase in the bonding social capital. We also show that Meetup social networks mostly grow trough big events, while small events contribute to the groups cohesiveness. PMID:28166305

  20. Power system cascading risk assessment based on complex network theory

    NASA Astrophysics Data System (ADS)

    Wang, Zhuoyang; Hill, David J.; Chen, Guo; Dong, Zhao Yang

    2017-09-01

    When a single failure occurs in a vulnerable part of a power system, this may cause a large area cascading event. Therefore, an advanced method that can assess the risks during cascading events is needed. In this paper, an improved complex network model for power system risk assessment is proposed. Risk is defined by consequence and probability of the failures in this model, which are affected by both power factors and network structure. Compared with existing risk assessment models, the proposed one can evaluate the risk of the system comprehensively during a cascading event by combining the topological and electrical information. A new cascading event simulation module is adopted to identify the power grid cascading chain from a system-level view. In addition, simulations are investigated on the IEEE 14 bus system and IEEE 39 bus system respectively to illustrate the performance of the proposed module. The simulation results demonstrate that the proposed method is effective in a power grid risk assessment during cascading event.

  1. 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

  2. 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.

  3. The Psychological Self as Actor, Agent, and Author.

    PubMed

    McAdams, Dan P

    2013-05-01

    The psychological self may be construed as a reflexive arrangement of the subjective "I" and the constructed "Me," evolving and expanding over the human life course. The psychological self begins life as a social actor, construed in terms of performance traits and social roles. By the end of childhood, the self has become a motivated agent, too, as personal goals, motives, values, and envisioned projects for the future become central features of how the I conceives of the Me. A third layer of selfhood begins to form in the adolescent and emerging adulthood years, when the self as autobiographical author aims to construct a story of the Me, to provide adult life with broad purpose and a dynamic sense of temporal continuity. An integrative theory that envisions the psychological self as a developing I-Me configuration of actor, agent, and author helps to synthesize a wide range of conceptions and findings on the self from social, personality, cognitive, cultural, and developmental psychology and from sociology and other social sciences. The actor-agent-author framework also sheds new light on studies of self-regulation, self-esteem, self-continuity, and the relationship between self and culture.

  4. Can We Control Contaminant Transport In Hydrologic Networks? Application Of Control Theory Concepts To Watershed Management

    NASA Astrophysics Data System (ADS)

    Yeghiazarian, L.; Riasi, M. S.

    2016-12-01

    Although controlling the level of contamination everywhere in the surface water network may not be feasible, it is vital to maintain safe water quality levels in specific areas, e.g. recreational waters. The question then is "what is the most efficient way to fully/partially control water quality in surface water networks?". This can be posed as a control problem where the goal is to efficiently drive the system to a desired state by manipulating few input variables. Such problems reduce to (1) finding the best control locations in the network to influence the state of the system; and (2) choosing the time-variant inputs at the control locations to achieve the desired state of the system with minimum effort. We demonstrate that the optimal solution to control the level of contamination in the network can be found through application of control theory concepts to transport in dendritic surface water networks.

  5. Optimal networks of nature reserves can be found through eigenvalue perturbation theory of the connectivity matrix.

    PubMed

    Jacobi, Martin Nilsson; Jonsson, Per R

    2011-07-01

    Conservation and management of natural resources and biodiversity need improved criteria to select functional networks of protected areas. The connectivity within networks due to dispersal is rarely considered, partly because it is unclear how connectivity information can be included in the selection of protected areas. We present a novel and general method that applies eigenvalue perturbation theory (EPT) to select optimum networks of protected areas based on connectivity. At low population densities, characteristic of threatened populations, this procedure selects networks that maximize the growth rate of the overall network. This method offers an improved link between connectivity and metapopulation dynamics. Our framework is applied to connectivities estimated for marine larvae and demonstrates that, for open populations, the best strategy is to protect areas acting as both strong donors and recipients of recruits. It should be possible to implement an EPT framework for connectivity analysis into existing holistic tools for design of protected areas.

  6. 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.

  7. Multi/infinite dimensional neural networks, multi/infinite dimensional logic theory.

    PubMed

    Murthy, Garimella Rama

    2005-06-01

    A mathematical model of an arbitrary multi-dimensional neural network is developed and a convergence theorem for an arbitrary multi-dimensional neural network represented by a fully symmetric tensor is stated and proved. The input and output signal states of a multi-dimensional neural network/logic gate are related through an energy function, defined over the fully symmetric tensor (representing the connection structure of a multi-dimensional neural network). The inputs and outputs are related such that the minimum/maximum energy states correspond to the output states of the logic gate/neural network realizing a logic function. Similarly, a logic circuit consisting of the interconnection of logic gates, represented by a block symmetric tensor, is associated with a quadratic/higher degree energy function. Infinite dimensional logic theory is discussed through the utilization of infinite dimension/order tensors.

  8. 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.

  9. 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.

  10. 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. Published by Elsevier Inc.

  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. Wilson punctured network defects in 2D q-deformed Yang-Mills theory

    NASA Astrophysics Data System (ADS)

    Watanabe, Noriaki

    2016-12-01

    In the context of class S theories and 4D/2D duality relations there, we discuss the skein relations of general topological defects on the 2D side which are expected to be counterparts of composite surface-line operators in 4D class S theory. Such defects are geometrically interpreted as networks in a three dimensional space. We also propose a conjectural computational procedure for such defects in two dimensional SU( N ) topological q-deformed Yang-Mills theory by interpreting it as a statistical mechanical system associated with ideal triangulations.

  13. 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.

  14. 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;…

  15. 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…

  16. "Living" Theory: A Pedagogical Framework for Process Support in Networked Learning

    ERIC Educational Resources Information Center

    Levy, Philipa

    2006-01-01

    This paper focuses on the broad outcome of an action research project in which practical theory was developed in the field of networked learning through case-study analysis of learners' experiences and critical evaluation of educational practice. It begins by briefly discussing the pedagogical approach adopted for the case-study course and the…

  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. 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

  19. Hydrogen bond network topology in liquid water and methanol: a graph theory approach.

    PubMed

    Bakó, Imre; Bencsura, Akos; Hermannson, Kersti; Bálint, Szabolcs; Grósz, Tamás; Chihaia, Viorel; Oláh, Julianna

    2013-09-28

    Networks are increasingly recognized as important building blocks of various systems in nature and society. Water is known to possess an extended hydrogen bond network, in which the individual bonds are broken in the sub-picosecond range and still the network structure remains intact. We investigated and compared the topological properties of liquid water and methanol at various temperatures using concepts derived within the framework of graph and network theory (neighbour number and cycle size distribution, the distribution of local cyclic and local bonding coefficients, Laplacian spectra of the network, inverse participation ratio distribution of the eigenvalues and average localization distribution of a node) and compared them to small world and Erdős-Rényi random networks. Various characteristic properties (e.g. the local cyclic and bonding coefficients) of the network in liquid water could be reproduced by small world and/or Erdős-Rényi networks, but the ring size distribution of water is unique and none of the studied graph models could describe it. Using the inverse participation ratio of the Laplacian eigenvectors we characterized the network inhomogeneities found in water and showed that similar phenomena can be observed in Erdős-Rényi and small world graphs. We demonstrated that the topological properties of the hydrogen bond network found in liquid water systematically change with the temperature and that increasing temperature leads to a broader ring size distribution. We applied the studied topological indices to the network of water molecules with four hydrogen bonds, and showed that at low temperature (250 K) these molecules form a percolated or nearly-percolated network, while at ambient or high temperatures only small clusters of four-hydrogen bonded water molecules exist.

  20. 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.

  1. 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

    2016-06-29

    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.

  2. 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

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

    SciTech Connect

    Billon, Noëlle

    2016-05-18

    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 physical meaning.

  4. 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.

  5. Protein Signaling Networks from Single Cell Fluctuations and Information Theory Profiling

    PubMed Central

    Shin, Young Shik; Remacle, F.; Fan, Rong; Hwang, Kiwook; Wei, Wei; Ahmad, Habib; Levine, R.D.; Heath, James R.

    2011-01-01

    Protein signaling networks among cells play critical roles in a host of pathophysiological processes, from inflammation to tumorigenesis. We report on an approach that integrates microfluidic cell handling, in situ protein secretion profiling, and information theory to determine an extracellular protein-signaling network and the role of perturbations. We assayed 12 proteins secreted from human macrophages that were subjected to lipopolysaccharide challenge, which emulates the macrophage-based innate immune responses against Gram-negative bacteria. We characterize the fluctuations in protein secretion of single cells, and of small cell colonies (n = 2, 3,···), as a function of colony size. Measuring the fluctuations permits a validation of the conditions required for the application of a quantitative version of the Le Chatelier's principle, as derived using information theory. This principle provides a quantitative prediction of the role of perturbations and allows a characterization of a protein-protein interaction network. PMID:21575571

  6. Protein signaling networks from single cell fluctuations and information theory profiling.

    PubMed

    Shin, Young Shik; Remacle, F; Fan, Rong; Hwang, Kiwook; Wei, Wei; Ahmad, Habib; Levine, R D; Heath, James R

    2011-05-18

    Protein signaling networks among cells play critical roles in a host of pathophysiological processes, from inflammation to tumorigenesis. We report on an approach that integrates microfluidic cell handling, in situ protein secretion profiling, and information theory to determine an extracellular protein-signaling network and the role of perturbations. We assayed 12 proteins secreted from human macrophages that were subjected to lipopolysaccharide challenge, which emulates the macrophage-based innate immune responses against Gram-negative bacteria. We characterize the fluctuations in protein secretion of single cells, and of small cell colonies (n = 2, 3,···), as a function of colony size. Measuring the fluctuations permits a validation of the conditions required for the application of a quantitative version of the Le Chatelier's principle, as derived using information theory. This principle provides a quantitative prediction of the role of perturbations and allows a characterization of a protein-protein interaction network.

  7. 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…

  8. 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…

  9. 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

    2016-09-07

    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.

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

    PubMed

    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.

  11. Team Sports Performance Analysed Through the Lens of Social Network Theory: Implications for Research and Practice.

    PubMed

    Ribeiro, João; Silva, Pedro; Duarte, Ricardo; Davids, Keith; Garganta, Júlio

    2017-02-15

    This paper discusses how social network analyses and graph theory can be implemented in team sports performance analyses to evaluate individual (micro) and collective (macro) performance data, and how to use this information for designing practice tasks. Moreover, we briefly outline possible limitations of social network studies and provide suggestions for future research. Instead of cataloguing discrete events or player actions, it has been argued that researchers need to consider the synergistic interpersonal processes emerging between teammates in competitive performance environments. Theoretical assumptions on team coordination prompted the emergence of innovative, theoretically driven methods for assessing collective team sport behaviours. Here, we contribute to this theoretical and practical debate by re-conceptualising sports teams as complex social networks. From this perspective, players are viewed as network nodes, connected through relevant information variables (e.g. a ball-passing action), sustaining complex patterns of interaction between teammates (e.g. a ball-passing network). Specialised tools and metrics related to graph theory could be applied to evaluate structural and topological properties of interpersonal interactions of teammates, complementing more traditional analysis methods. This innovative methodology moves beyond the use of common notation analysis methods, providing a richer understanding of the complexity of interpersonal interactions sustaining collective team sports performance. The proposed approach provides practical applications for coaches, performance analysts, practitioners and researchers by establishing social network analyses as a useful approach for capturing the emergent properties of interactions between players in sports teams.

  12. Actor training for surgical team simulations.

    PubMed

    Kassab, Eva S; King, Dominic; Hull, Louise M; Arora, Sonal; Sevdalis, Nick; Kneebone, Roger L; Nestel, Debra

    2010-01-01

    Immersive simulations can enable surgeons to learn complex sets of skills required for safe surgical practice without risk to patients. However, recruiting healthcare professionals to support surgeons training as members of an operating theatre (OT) team is challenging and resource intensive. We developed a training programme for actors to take on the role of an OT team to support validation studies in a simulated environment. This article describes the evaluation of the programme. The programme comprised of written materials, video discussion and experiential activities. Evaluation methods consisted of post-simulation interviews and questionnaires with actors and surgeons. Participants were recruited by convenience sampling. Quantitative data were analysed using descriptive statistics and interviews were analysed using thematic extraction. Three actors participated in the programme. Twelve surgeons completed simulations. All data suggest that the training was successful. Actors were perceived as realistic. Suggestions were made to improve training. After a brief training, actors can realistically portray members of an OT team in simulations designed to support surgeon training. This article highlights factors that contributed to success and suggests improvements. Although there are limitations with the study, its findings have relevance to training and assessment that focuses on individual clinician's functioning as a member of an OT team.

  13. 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.

  14. 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…

  15. 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…

  16. Study on node importance evaluation of the high-speed passenger traffic complex network based on the Structural Hole Theory

    NASA Astrophysics Data System (ADS)

    Zhang, Xu; Chen, Bingzhi

    2017-03-01

    Complex Network Theory can analyze the reliability of high-speed passenger traffic networks and also evaluate node importance. This paper conducts a systematic and in-depth research of importance of various nodes in the high-speed passenger traffic network so as to improve the high-speed passenger traffic network level. To study importance of network nodes can contribute to an in-depth understanding of the network structure. Therefore, the complex network is introduced and the node importance is evaluated. The characteristics of the complex network are briefly analyzed. In order to study the high-speed passenger traffic nodes, the network restraint coefficient, the network scale, the efficiency, the grade level, the partial clustering coefficient of degree and structural hole. Besides, the algorithm to calculate node importance is designed. Through analysis of the high-speed passenger network, the accuracy and practicability of the Complex Network Theory in evaluating node importance are pointed out. It is also proved that Complex Network Theory can help optimize high-speed passenger traffic networks and improve traffic efficiency.

  17. Beyond the actor's traits: forming impressions of actors, targets, and relationships from social behaviors.

    PubMed

    Frey, K P; Smith, E R

    1993-09-01

    Perceivers who observe social behaviors may form impressions not only of actors' traits but also of people as targets and of interpersonal relationships. In Study 1, Ss read about 4 individuals' behaviors under instructions to form actor-, target-, and relationship-based impressions. Ss then read additional behavioral information that they later tried to recall. Ss accurately perceived actor, target, and relationship effects in the presented information, and they better recalled subsequent behaviors that were consistent with all 3 types of impressions. In Study 2, Ss thought of 4 people they knew and judged how much each liked the other 3. These ratings revealed actor, target, and relationship effects as well as individual and dyadic reciprocity. Perceivers can form relatively accurate impressions of people as actors and as targets and accurate impressions of relationships between people, and these impressions influence memory for further behaviors.

  18. Acoustic characteristics [correction of characeristics] of adolescent actors' and non-actors' voices.

    PubMed

    Kovacić, Gordana; Budanovac, Aleksandar

    2002-01-01

    The aim of the present study was to investigate differences in the acoustic characteristics of the voice between adolescent actors and non-actors. The experimental sample consisted of 10 actresses and 10 actors while the control sample included 13 girls and 14 boys. Phonation of the vowel /a/, spontaneous speaking and oral reading provided a set of acoustic variables (fundamental frequency, jitter, shimmer, speaking and reading ranges); t test showed statistically significant differences between actresses and non-actresses in speaking range, reading F(0) maximum, and reading range, whereas between actors and non-actors the difference was found in reading range only. The results showed that drama in education without systematic voice training had no effects in terms of acoustic characteristics of the voice. Copyright 2002 S. Karger AG, Basel

  19. New morphometric properties for channel network classification using the graph theory and DEM

    NASA Astrophysics Data System (ADS)

    Moussa, R.; Colin, F.; Rabotin, M.; A; Crabit

    2012-04-01

    The channel network controls the spatial pattern of hydrological processes within a catchment. Hence the identification of key hydrological features characterising the channel network can contribute to a rational classification of catchments. This presentation aims to investigate morphometric properties of the channel network derived from DEM using the graph theory, and estimate whether these properties can be used as similarity indices for the classification of channel networks. The graph theory was used in order to represent the contributing drainage area which has properties of a scale free network, and was subsequently characterised by highly connected nodes called hubs. The method involves ranking the hubs of a channel network according to the contributing drainage area and the distance to the outlet. The hubs' characteristics can be considered as morphometric descriptors of the channel network and are used to compare and classify channel network. Applications were conducted on 788 French catchments with the same area (between 100 and 105 km2) and on 18 catchments having an area between 43 and 116450 km2. First, we present some newly found invariance properties of headwater subcatchments and show that some invariant morphometric properties characterize only natural channel networks verifying Optimal Channel Networks (OCN) properties, but are not verified for non-OCN (Moussa et al., 2011, Water Resources Research, 47, W08518). A new empirical model based on self-affine properties was developed in order to calculate the number N and the total headwater area H as a function of the cutoff area S used to extract the channel network from DEM. Results show that H(S) / S0 (S0 being the catchment area) is independent from S and seems constant (0.29 +/- 0.03) for various shapes and sizes of channel networks, and consequently can be considered as invariant general descriptor of natural channel networks. On the contrary, this is not the case when the approach is applied

  20. 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…

  1. 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…

  2. 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.

  3. Game theory and extremal optimization for community detection in complex dynamic networks.

    PubMed

    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.

  4. Graph Theory-Based Analysis of the Lymph Node Fibroblastic Reticular Cell Network.

    PubMed

    Novkovic, Mario; Onder, Lucas; Bocharov, Gennady; Ludewig, Burkhard

    2017-01-01

    Secondary lymphoid organs have developed segregated niches that are able to initiate and maintain effective immune responses. Such global organization requires tight control of diverse cellular components, specifically those that regulate lymphocyte trafficking. Fibroblastic reticular cells (FRCs) form a densely interconnected network in lymph nodes and provide key factors necessary for T cell migration and retention, and foster subsequent interactions between T cells and dendritic cells. Development of integrative systems biology approaches has made it possible to elucidate this multilevel complexity of the immune system. Here, we present a graph theory-based analysis of the FRC network in murine lymph nodes, where generation of the network topology is performed using high-resolution confocal microscopy and 3D reconstruction. This approach facilitates the analysis of physical cell-to-cell connectivity, and estimation of topological robustness and global behavior of the network when it is subjected to perturbation in silico.

  5. Graph Theory Data Objects Applied to Stream Flow Network Representation in an Integrated Hydrological Model

    NASA Astrophysics Data System (ADS)

    Park, J.; Obeysekera, J.; Vanzee, R.

    2005-05-01

    The Management Simulation Engine (MSE) component of the Regional Simulation Model (RSM) incorporates a multi-level hierarchical control architecture which emphasizes the decoupling of hydrological state information from the management information processing applied to the states. A crucial aspect of effectively storing and accessing state information for water resource management purposes is the maintenance of an efficient storage mechanism which associates hydrological state information with the proper managerial abstractions. In the RSM this is done by storing hydrological and managerial information relevant to a water control unit (WCU) in a data storage object defined in the MSE Network. The MSE Network is an abstraction of the stream flow network and control structures suited to the needs of water resource routing and decisions. It is based on a standard graph theory representation of a flow network comprised of arcs and nodes. The MSE Network data objects serve as state and process information repositories for management processes. They maintain appropriately filtered state information, parameter storage relevant to WCU or hydraulic structure managerial constraints and variables, and serve as an integrated data source for any MSE algorithm. It also provides a mathematical representation of a constrained, interconnected flow network which facilitates efficient graph theory solutions of network connectivity and flow algorithms. This paper describes the MSE Network implementation in the RSM, an integrated hydrological computation engine aimed at meeting the needs for comprehensive integration of management features in coupled hydrological models [1]. [1] Belaineh, G., Peralta, R. C., Hughes, T. C., Simulation/ Optimization Modeling for Water Resources Management, ASCE Journal Water Resources Planning Management, 125(3), p 154-61, 1999

  6. 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

  7. Working on gender issues with partners and other actors.

    PubMed

    1996-06-01

    Discussions at the workshop centered around the Oxfam UK/1 program work on gender with its partners and other actors. Gender issues have been part of the program since 1985. Around 80% of the program involves mixed partners (men and women), while around 15% involves women-only groups. Strategies for working with partners include training, ongoing dialogue, involvement in planning, networking, lobbying, advocacy work, sectoral interventions, and research to highlight issues. Improving the gender work of existing counterparts and building new relationships are the goals of the Oxfam UK/1 program. Gender awareness should be used as a criterion in choosing those with whom work is done. Time-bound strategies are needed to persuade partners to respond to the gender-related needs of target groups. Resources are needed to enhance the capacity skills of willing partners. The workshop produced the following recommendations: 1) program managers must take conscious steps to invest time and resources in seeking out new relationships with new potential actors; 2) local culture should be analyzed to develop a locally appropriate approach to gender discrimination, and strategies have to synchronize policy directives with what is happening on the ground; 3) in seeking new relationships, centers of positive energy, which can create a domino effect and break down resistance, should be identified; and 4) networking should be broadened to outside the current universe of counterparts.

  8. 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.

  9. 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.

  10. Documentation of Education for Teenagers in Residential Care: A Network of Blame and Critique

    ERIC Educational Resources Information Center

    Severinsson, Susanne

    2017-01-01

    This article presents analyses of documents from special schools in Sweden for students in the care of social welfare who have been assessed with social, emotional and behavioural difficulties. The aim is to use actor-network theory to analyse how blame and critique are handled in individual educational plans, and how responsibilities are produced…

  11. 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…

  12. 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…

  13. Further evidence of alerted default network connectivity and association with theory of mind ability in schizophrenia.

    PubMed

    Mothersill, Omar; Tangney, Noreen; Morris, Derek W; McCarthy, Hazel; Frodl, Thomas; Gill, Michael; Corvin, Aiden; Donohoe, Gary

    2017-06-01

    Resting-state functional magnetic resonance imaging (rs-fMRI) has repeatedly shown evidence of altered functional connectivity of large-scale networks in schizophrenia. The relationship between these connectivity changes and behaviour (e.g. symptoms, neuropsychological performance) remains unclear. Functional connectivity in 27 patients with schizophrenia or schizoaffective disorder, and 25 age and gender matched healthy controls was examined using rs-fMRI. Based on seed regions from previous studies, we examined functional connectivity of the default, cognitive control, affective and attention networks. Effects of symptom severity and theory of mind performance on functional connectivity were also examined. Patients showed increased connectivity between key nodes of the default network including the precuneus and medial prefrontal cortex compared to controls (p<0.01, FWE-corrected). Increasing positive symptoms and increasing theory of mind performance were both associated with altered connectivity of default regions within the patient group (p<0.01, FWE-corrected). This study confirms previous findings of default hyper-connectivity in schizophrenia spectrum patients and reveals an association between altered default connectivity and positive symptom severity. As a novel find, this study also shows that default connectivity is correlated to and predictive of theory of mind performance. Extending these findings by examining the effects of emerging social cognition treatments on both default connectivity and theory of mind performance is now an important goal for research. Copyright © 2016 Elsevier B.V. All rights reserved.

  14. Connectomics and graph theory analyses: Novel insights into network abnormalities in epilepsy.

    PubMed

    Gleichgerrcht, Ezequiel; Kocher, Madison; Bonilha, Leonardo

    2015-11-01

    The assessment of neural networks in epilepsy has become increasingly relevant in the context of translational research, given that localized forms of epilepsy are more likely to be related to abnormal function within specific brain networks, as opposed to isolated focal brain pathology. It is notable that variability in clinical outcomes from epilepsy treatment may be a reflection of individual patterns of network abnormalities. As such, network endophenotypes may be important biomarkers for the diagnosis and treatment of epilepsy. Despite its exceptional potential, measuring abnormal networks in translational research has been thus far constrained by methodologic limitations. Fortunately, recent advancements in neuroscience, particularly in the field of connectomics, permit a detailed assessment of network organization, dynamics, and function at an individual level. Data from the personal connectome can be assessed using principled forms of network analyses based on graph theory, which may disclose patterns of organization that are prone to abnormal dynamics and epileptogenesis. Although the field of connectomics is relatively new, there is already a rapidly growing body of evidence to suggest that it can elucidate several important and fundamental aspects of abnormal networks to epilepsy. In this article, we provide a review of the emerging evidence from connectomics research regarding neural network architecture, dynamics, and function related to epilepsy. We discuss how connectomics may bring together pathophysiologic hypotheses from conceptual and basic models of epilepsy and in vivo biomarkers for clinical translational research. By providing neural network information unique to each individual, the field of connectomics may help to elucidate variability in clinical outcomes and open opportunities for personalized medicine approaches to epilepsy. Connectomics involves complex and rich data from each subject, thus collaborative efforts to enable the

  15. 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. Copyright © 2016 Elsevier B.V. All rights reserved.

  16. Evaluation of neural network robust reliability using information-gap theory.

    PubMed

    Pierce, S Gareth; Ben-Haim, Yakov; Worden, Keith; Manson, Graeme

    2006-11-01

    A novel technique for the evaluation of neural network robustness against uncertainty using a nonprobabilistic approach is presented. Conventional optimization techniques were employed to train multilayer perceptron (MLP) networks, which were then probed with an uncertainty analysis using an information-gap model to quantify the network response to uncertainty in the input data. It is demonstrated that the best performing network on data with low uncertainty is not in general the optimal network on data with a higher degree of input uncertainty. Using the concepts of information-gap theory, this paper develops a theoretical framework for information-gap uncertainty applied to neural networks, and explores the practical application of the procedure to three sample cases. The first consists of a simple two-dimensional (2-D) classification network operating on a known Gaussian distribution, the second a nine-lass vibration classification problem from an aircraft wing, and the third a two-class example from a database of breast cancer incidence.

  17. 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. Copyright © 2015 Elsevier Inc. All rights reserved.

  18. 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.

  19. 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

  20. An Appraisal of Social Network Theory and Analysis as Applied to Public Health: Challenges and Opportunities.

    PubMed

    Valente, Thomas W; Pitts, Stephanie R

    2016-12-15

    The use of social network theory and analysis methods as applied to public health has expanded greatly in the past decade, yielding a significant academic literature that spans almost every conceivable health issue. This review identifies several important theoretical challenges that confront the field but also provides opportunities for new research. These challenges include (a) measuring network influences, (b) identifying appropriate influence mechanisms, (c) the impact of social media and computerized communications, (d) the role of networks in evaluating public health interventions, and (e) ethics. Next steps for the field are outlined and the need for funding is emphasized. Recently developed network analysis techniques, technological innovations in communication, and changes in theoretical perspectives to include a focus on social and environmental behavioral influences have created opportunities for new theory and ever broader application of social networks to public health topics. Expected final online publication date for the Annual Review of Public Health Volume 38 is March 20, 2017. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

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

    PubMed

    Lin, Chi; Wu, Guowei; Pirozmand, Poria

    2015-06-04

    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.

  2. 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

  3. Cartographic generalization of urban street networks based on gravitational field theory

    NASA Astrophysics Data System (ADS)

    Liu, Gang; Li, Yongshu; Li, Zheng; Guo, Jiawei

    2014-05-01

    The automatic generalization of urban street networks is a constant and important aspect of geographical information science. Previous studies show that the dual graph for street-street relationships more accurately reflects the overall morphological properties and importance of streets than do other methods. In this study, we construct a dual graph to represent street-street relationship and propose an approach to generalize street networks based on gravitational field theory. We retain the global structural properties and topological connectivity of an original street network and borrow from gravitational field theory to define the gravitational force between nodes. The concept of multi-order neighbors is introduced and the gravitational force is taken as the measure of the importance contribution between nodes. The importance of a node is defined as the result of the interaction between a given node and its multi-order neighbors. Degree distribution is used to evaluate the level of maintaining the global structure and topological characteristics of a street network and to illustrate the efficiency of the suggested method. Experimental results indicate that the proposed approach can be used in generalizing street networks and retaining their density characteristics, connectivity and global structure.

  4. 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

  5. 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.

  6. 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

  7. 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.

  8. 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

  9. More than just wires : applying complexity theory to communications network assurance.

    SciTech Connect

    North, M.; Macal, C.; Thomas, W. H.; Miller, D.; Peerenboom, J.

    2002-09-05

    Complexity Theory is the study of order within otherwise chaotic systems (Holland, 1999). Complexity Theory often focuses on Complex Adaptive Systems (CAS). A CAS is a system of components that interact and reproduce while adapting to their environment. A CAS consists of large numbers of components that are diverse in both form and capability. A CAS exhibits unstable coherence in spite of constant disruptions and a lack of central planning. Large-scale, interconnected infrastructures such as communication networks are CAS. These infrastructures are vastly more dynamic than their predecessors. Such infrastructures consist of a large number of components and participants that are diverse in both form and capability. Furthermore, these infrastructures exhibit unstable coherence in spite of constant disruptions and a lack of central planning. Viewing large-scale, interconnected infrastructures with complex physical architectures, such as communication networks, as CAS can provide many new insights (Bower and Bunn, 2000; North, 2000a, 2000b, and 2001). The CAS approach emphasizes the specific evolution of integrated infrastructures and their participants' behavior, not just simple trends or end states. The adaptation of the infrastructure participants to changing conditions is paramount. Also, the effects of random events and uncertainty are explicitly considered. One powerful computational approach to understanding CAS is agent-based modeling and simulation (ABMS). Applying ABMS to communication networks and the infrastructures upon which they depend may allow such networks to be understood as more than just wires. Communication networks may then be electronically managed as complete, dynamic systems. An example is the integrated, systems-level computational perspective ABMS has provided to electrical and natural gas infrastructure research (North, 2001). This holistic computational perspective may allow both the physical and human dimensions of complex systems such as

  10. On the Contributions of a Network Approach to Personality Theory and Research.

    PubMed

    Furr, R Michael; Fleeson, William; Anderson, Michelle; Arnold, Elizabeth Mayfield

    2012-07-01

    Understanding personality structure and processes is one of the most fundamental goals in personality psychology. The network approach presented by Cramer et al. represents a useful path toward this goal, and we address two facets of their approach. First, we examine the possibility that it solves the problem of breadth, which has inhibited the integration of trait theory with social cognitive theory. Second, we evaluate the value and usability of their proposed method (qgraph), doing so by conducting idiographic analyses of the symptom structure of Borderline Personality Disorder.

  11. Constructing gene co-expression networks and predicting functions of unknown genes by random matrix theory

    PubMed Central

    Luo, Feng; Yang, Yunfeng; Zhong, Jianxin; Gao, Haichun; Khan, Latifur; Thompson, Dorothea K; Zhou, Jizhong

    2007-01-01

    Background Large-scale sequencing of entire genomes has ushered in a new age in biology. One of the next grand challenges is to dissect the cellular networks consisting of many individual functional modules. Defining co-expression networks without ambiguity based on genome-wide microarray data is difficult and current methods are not robust and consistent with different data sets. This is particularly problematic for little understood organisms since not much existing biological knowledge can be exploited for determining the threshold to differentiate true correlation from random noise. Random matrix theory (RMT), which has been widely and successfully used in physics, is a powerful approach to distinguish system-specific, non-random properties embedded in complex systems from random noise. Here, we have hypothesized that the universal predictions of RMT are also applicable to biological systems and the correlation threshold can be determined by characterizing the correlation matrix of microarray profiles using random matrix theory. Results Application of random matrix theory to microarray data of S. oneidensis, E. coli, yeast, A. thaliana, Drosophila, mouse and human indicates that there is a sharp transition of nearest neighbour spacing distribution (NNSD) of correlation matrix after gradually removing certain elements insider the matrix. Testing on an in silico modular model has demonstrated that this transition can be used to determine the correlation threshold for revealing modular co-expression networks. The co-expression network derived from yeast cell cycling microarray data is supported by gene annotation. The topological properties of the resulting co-expression network agree well with the general properties of biological networks. Computational evaluations have showed that RMT approach is sensitive and robust. Furthermore, evaluation on sampled expression data of an in silico modular gene system has showed that under-sampled expressions do not affect the

  12. 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

  13. 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…

  14. 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…

  15. 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…

  16. 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.

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

    PubMed Central

    Yoon, Hong-Jun; Tourassi, Georgia

    2015-01-01

    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. PMID:25973446

  18. [Study on signal transmission characteristics of meridian based on electrical network theory and experiments].

    PubMed

    Wang, Zhi-Gong; Lü, Xiao-Ying; Gao, Jian-Yun; Wang, Yu-Hang; Huang, Cen-Yu; Chen, Yue-Lin; Xing, Li-Yang; Wang, Gui-Ying

    2011-08-01

    Study on features of acupoints with resistance test in the past half century is reviewed in this article. Mechanism and technology of the method are introduced as well as its shortcomings. The determination method of signal transmission along meridians with the combination of electrical network theories and practice is advanced. And the result of a series experiments on one meridian at the superficial part of the body are given as well. Thus, it is concluded that the signals of the point-in/point-out and the signals along a non-meridian path with the same distance are significantly different, which gives a verification of the feasibility of the method by using electrical network theories to set out characteristics of signal transmission along meridians dynamically.

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

    PubMed

    Yoon, Hong-Jun; Tourassi, Georgia

    2014-05-01

    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.

  20. 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.

  1. Random matrix theory for analyzing the brain functional network in attention deficit hyperactivity disorder

    NASA Astrophysics Data System (ADS)

    Wang, Rong; Wang, Li; Yang, Yong; Li, Jiajia; Wu, Ying; Lin, Pan

    2016-11-01

    Attention deficit hyperactivity disorder (ADHD) is the most common childhood neuropsychiatric disorder and affects approximately 6 -7 % of children worldwide. Here, we investigate the statistical properties of undirected and directed brain functional networks in ADHD patients based on random matrix theory (RMT), in which the undirected functional connectivity is constructed based on correlation coefficient and the directed functional connectivity is measured based on cross-correlation coefficient and mutual information. We first analyze the functional connectivity and the eigenvalues of the brain functional network. We find that ADHD patients have increased undirected functional connectivity, reflecting a higher degree of linear dependence between regions, and increased directed functional connectivity, indicating stronger causality and more transmission of information among brain regions. More importantly, we explore the randomness of the undirected and directed functional networks using RMT. We find that for ADHD patients, the undirected functional network is more orderly than that for normal subjects, which indicates an abnormal increase in undirected functional connectivity. In addition, we find that the directed functional networks are more random, which reveals greater disorder in causality and more chaotic information flow among brain regions in ADHD patients. Our results not only further confirm the efficacy of RMT in characterizing the intrinsic properties of brain functional networks but also provide insights into the possibilities RMT offers for improving clinical diagnoses and treatment evaluations for ADHD patients.

  2. GENERAL: Mean-field Theory for Some Bus Transport Networks with Random Overlapping Clique Structure

    NASA Astrophysics Data System (ADS)

    Yang, Xu-Hua; Sun, Bao; Wang, Bo; Sun, You-Xian

    2010-04-01

    Transport networks, such as railway networks and airport networks, are a kind of random network with complex topology. Recently, more and more scholars paid attention to various kinds of transport networks and try to explore their inherent characteristics. Here we study the exponential properties of a recently introduced Bus Transport Networks (BTNs) evolution model with random overlapping clique structure, which gives a possible explanation for the observed exponential distribution of the connectivities of some BTNs of three major cities in China. Applying mean-field theory, we analyze the BTNs model and prove that this model has the character of exponential distribution of the connectivities, and develop a method to predict the growth dynamics of the individual vertices, and use this to calculate analytically the connectivity distribution and the exponents. By comparing mean-field based theoretic results with the statistical data of real BTNs, we observe that, as a whole, both of their data show similar character of exponential distribution of the connectivities, and their exponents have same order of magnitude, which show the availability of the analytical result of this paper.

  3. Network modeling of resting state connectivity points towards the bottom up theories of schizophrenia.

    PubMed

    Orliac, François; Delamillieure, Pascal; Delcroix, Nicolas; Naveau, Mikael; Brazo, Perrine; Razafimandimby, Annick; Dollfus, Sonia; Joliot, Marc

    2017-08-30

    The dysconnectivity theory of schizophrenia proposes that schizophrenia symptoms arise from abnormalities in neuronal synchrony. Resting-state Functional Connectivity (FC) techniques allow us to highlight synchronization of large-scale networks, the Resting-state Networks (RNs). A large body of work suggests that disruption of RN synchronization could give rise to specific schizophrenia symptoms. The present study aimed to explore within- and between-network FC strength of 34 RNs in 29 patients suffering from schizophrenia, and their relationships with schizophrenia symptoms. Resting-state data were analyzed using independent component analysis and dual-regression techniques. Our results showed that both within-RN and between-RN FC were disrupted in patients with schizophrenia, with a global trend toward weaker FC. This decrease affected more particularly visual, auditory and crossmodal binding networks. These alterations were correlated with negative symptoms, positive symptoms and hallucinations, indicating abnormalities in visual processing and crossmodal binding in schizophrenia. Moreover, we stressed an anomalous synchronization between a visual network and a network thought to be engaged in mental imaging processes, correlated with delusions and hallucinations. Altogether, our results supported the assumption that some schizophrenia symptoms may be related to low-order sensory alterations impacting higher-order cognitive processes, i.e. the "bottom-up" hypothesis of schizophrenia symptoms. Copyright © 2017. Published by Elsevier B.V.

  4. Analysing human mobility patterns of hiking activities through complex network theory

    PubMed Central

    Pérez, Toni; Guerrero, Carlos; Eguíluz, Víctor M.; Juiz, Carlos

    2017-01-01

    The exploitation of high volume of geolocalized data from social sport tracking applications of outdoor activities can be useful for natural resource planning and to understand the human mobility patterns during leisure activities. This geolocalized data represents the selection of hike activities according to subjective and objective factors such as personal goals, personal abilities, trail conditions or weather conditions. In our approach, human mobility patterns are analysed from trajectories which are generated by hikers. We propose the generation of the trail network identifying special points in the overlap of trajectories. Trail crossings and trailheads define our network and shape topological features. We analyse the trail network of Balearic Islands, as a case of study, using complex weighted network theory. The analysis is divided into the four seasons of the year to observe the impact of weather conditions on the network topology. The number of visited places does not decrease despite the large difference in the number of samples of the two seasons with larger and lower activity. It is in summer season where it is produced the most significant variation in the frequency and localization of activities from inland regions to coastal areas. Finally, we compare our model with other related studies where the network possesses a different purpose. One finding of our approach is the detection of regions with relevant importance where landscape interventions can be applied in function of the communities. PMID:28542280

  5. Random matrix theory for analyzing the brain functional network in attention deficit hyperactivity disorder.

    PubMed

    Wang, Rong; Wang, Li; Yang, Yong; Li, Jiajia; Wu, Ying; Lin, Pan

    2016-11-01

    Attention deficit hyperactivity disorder (ADHD) is the most common childhood neuropsychiatric disorder and affects approximately 6-7% of children worldwide. Here, we investigate the statistical properties of undirected and directed brain functional networks in ADHD patients based on random matrix theory (RMT), in which the undirected functional connectivity is constructed based on correlation coefficient and the directed functional connectivity is measured based on cross-correlation coefficient and mutual information. We first analyze the functional connectivity and the eigenvalues of the brain functional network. We find that ADHD patients have increased undirected functional connectivity, reflecting a higher degree of linear dependence between regions, and increased directed functional connectivity, indicating stronger causality and more transmission of information among brain regions. More importantly, we explore the randomness of the undirected and directed functional networks using RMT. We find that for ADHD patients, the undirected functional network is more orderly than that for normal subjects, which indicates an abnormal increase in undirected functional connectivity. In addition, we find that the directed functional networks are more random, which reveals greater disorder in causality and more chaotic information flow among brain regions in ADHD patients. Our results not only further confirm the efficacy of RMT in characterizing the intrinsic properties of brain functional networks but also provide insights into the possibilities RMT offers for improving clinical diagnoses and treatment evaluations for ADHD patients.

  6. Analysing human mobility patterns of hiking activities through complex network theory.

    PubMed

    Lera, Isaac; Pérez, Toni; Guerrero, Carlos; Eguíluz, Víctor M; Juiz, Carlos

    2017-01-01

    The exploitation of high volume of geolocalized data from social sport tracking applications of outdoor activities can be useful for natural resource planning and to understand the human mobility patterns during leisure activities. This geolocalized data represents the selection of hike activities according to subjective and objective factors such as personal goals, personal abilities, trail conditions or weather conditions. In our approach, human mobility patterns are analysed from trajectories which are generated by hikers. We propose the generation of the trail network identifying special points in the overlap of trajectories. Trail crossings and trailheads define our network and shape topological features. We analyse the trail network of Balearic Islands, as a case of study, using complex weighted network theory. The analysis is divided into the four seasons of the year to observe the impact of weather conditions on the network topology. The number of visited places does not decrease despite the large difference in the number of samples of the two seasons with larger and lower activity. It is in summer season where it is produced the most significant variation in the frequency and localization of activities from inland regions to coastal areas. Finally, we compare our model with other related studies where the network possesses a different purpose. One finding of our approach is the detection of regions with relevant importance where landscape interventions can be applied in function of the communities.

  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.

  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.

  9. A Network Neuroscience of Human Learning: Potential to Inform Quantitative Theories of Brain and Behavior.

    PubMed

    Bassett, Danielle S; Mattar, Marcelo G

    2017-04-01

    Humans adapt their behavior to their external environment in a process often facilitated by learning. Efforts to describe learning empirically can be complemented by quantitative theories that map changes in neurophysiology to changes in behavior. In this review we highlight recent advances in network science that offer a sets of tools and a general perspective that may be particularly useful in understanding types of learning that are supported by distributed neural circuits. We describe recent applications of these tools to neuroimaging data that provide unique insights into adaptive neural processes, the attainment of knowledge, and the acquisition of new skills, forming a network neuroscience of human learning. While promising, the tools have yet to be linked to the well-formulated models of behavior that are commonly utilized in cognitive psychology. We argue that continued progress will require the explicit marriage of network approaches to neuroimaging data and quantitative models of behavior.

  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. 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

  12. 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

  13. Understanding cancer complexome using networks, spectral graph theory and multilayer framework

    NASA Astrophysics Data System (ADS)

    Rai, Aparna; Pradhan, Priodyuti; Nagraj, Jyothi; Lohitesh, K.; Chowdhury, Rajdeep; Jalan, Sarika

    2017-02-01

    Cancer complexome comprises a heterogeneous and multifactorial milieu that varies in cytology, physiology, signaling mechanisms and response to therapy. The combined framework of network theory and spectral graph theory along with the multilayer analysis provides a comprehensive approach to analyze the proteomic data of seven different cancers, namely, breast, oral, ovarian, cervical, lung, colon and prostate. Our analysis demonstrates that the protein-protein interaction networks of the normal and the cancerous tissues associated with the seven cancers have overall similar structural and spectral properties. However, few of these properties implicate unsystematic changes from the normal to the disease networks depicting difference in the interactions and highlighting changes in the complexity of different cancers. Importantly, analysis of common proteins of all the cancer networks reveals few proteins namely the sensors, which not only occupy significant position in all the layers but also have direct involvement in causing cancer. The prediction and analysis of miRNAs targeting these sensor proteins hint towards the possible role of these proteins in tumorigenesis. This novel approach helps in understanding cancer at the fundamental level and provides a clue to develop promising and nascent concept of single drug therapy for multiple diseases as well as personalized medicine.

  14. Understanding cancer complexome using networks, spectral graph theory and multilayer framework

    PubMed Central

    Rai, Aparna; Pradhan, Priodyuti; Nagraj, Jyothi; Lohitesh, K.; Chowdhury, Rajdeep; Jalan, Sarika

    2017-01-01

    Cancer complexome comprises a heterogeneous and multifactorial milieu that varies in cytology, physiology, signaling mechanisms and response to therapy. The combined framework of network theory and spectral graph theory along with the multilayer analysis provides a comprehensive approach to analyze the proteomic data of seven different cancers, namely, breast, oral, ovarian, cervical, lung, colon and prostate. Our analysis demonstrates that the protein-protein interaction networks of the normal and the cancerous tissues associated with the seven cancers have overall similar structural and spectral properties. However, few of these properties implicate unsystematic changes from the normal to the disease networks depicting difference in the interactions and highlighting changes in the complexity of different cancers. Importantly, analysis of common proteins of all the cancer networks reveals few proteins namely the sensors, which not only occupy significant position in all the layers but also have direct involvement in causing cancer. The prediction and analysis of miRNAs targeting these sensor proteins hint towards the possible role of these proteins in tumorigenesis. This novel approach helps in understanding cancer at the fundamental level and provides a clue to develop promising and nascent concept of single drug therapy for multiple diseases as well as personalized medicine. PMID:28155908

  15. A new adaptive backpropagation algorithm based on Lyapunov stability theory for neural networks.

    PubMed

    Man, Zhihong; Wu, Hong Ren; Liu, Sophie; Yu, Xinghuo

    2006-11-01

    A new adaptive backpropagation (BP) algorithm based on Lyapunov stability theory for neural networks is developed in this paper. It is shown that the candidate of a Lyapunov function V(k) of the tracking error between the output of a neural network and the desired reference signal is chosen first, and the weights of the neural network are then updated, from the output layer to the input layer, in the sense that deltaV(k) = V(k) - V(k - 1) < 0. The output tracking error can then asymptotically converge to zero according to Lyapunov stability theory. Unlike gradient-based BP training algorithms, the new Lyapunov adaptive BP algorithm in this paper is not used for searching the global minimum point along the cost-function surface in the weight space, but it is aimed at constructing an energy surface with a single global minimum point through the adaptive adjustment of the weights as the time goes to infinity. Although a neural network may have bounded input disturbances, the effects of the disturbances can be eliminated, and asymptotic error convergence can be obtained. The new Lyapunov adaptive BP algorithm is then applied to the design of an adaptive filter in the simulation example to show the fast error convergence and strong robustness with respect to large bounded input disturbances.

  16. Understanding cancer complexome using networks, spectral graph theory and multilayer framework.

    PubMed

    Rai, Aparna; Pradhan, Priodyuti; Nagraj, Jyothi; Lohitesh, K; Chowdhury, Rajdeep; Jalan, Sarika

    2017-02-03

    Cancer complexome comprises a heterogeneous and multifactorial milieu that varies in cytology, physiology, signaling mechanisms and response to therapy. The combined framework of network theory and spectral graph theory along with the multilayer analysis provides a comprehensive approach to analyze the proteomic data of seven different cancers, namely, breast, oral, ovarian, cervical, lung, colon and prostate. Our analysis demonstrates that the protein-protein interaction networks of the normal and the cancerous tissues associated with the seven cancers have overall similar structural and spectral properties. However, few of these properties implicate unsystematic changes from the normal to the disease networks depicting difference in the interactions and highlighting changes in the complexity of different cancers. Importantly, analysis of common proteins of all the cancer networks reveals few proteins namely the sensors, which not only occupy significant position in all the layers but also have direct involvement in causing cancer. The prediction and analysis of miRNAs targeting these sensor proteins hint towards the possible role of these proteins in tumorigenesis. This novel approach helps in understanding cancer at the fundamental level and provides a clue to develop promising and nascent concept of single drug therapy for multiple diseases as well as personalized medicine.

  17. 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.

  18. 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

  19. Categorizing "Others": The Segmentation of Other Actors for "Faith in Others' Efficacy (FIO)"

    ERIC Educational Resources Information Center

    Ng, Chi Kwan; D'Souza, Clare

    2016-01-01

    This conceptual paper provides an innovative categorization of "others" for the variable of "faith in others (FIO)". Adopted by pro-environmental and sustainability literature, FIO refers to faith in the efficacy of other actors. Examination and integration of theories on sustainable pro-environmental behavior leads to the…

  20. 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…

  1. 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…

  2. A Conceptual Framework for Understanding Armed Non State Actors (ANSAs): Strategic Roles and Operational Dynamics

    DTIC Science & Technology

    This is the Final Report of the Technology Investment Fund (TIF) Project entitled A Conceptual Framework for Understanding Armed Non-state Actors...Cmap. The generic ANSA Cmap is a high-level conceptual framework grounded in both multidisciplinary theory and mixed methods practice that distills our

  3. 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…

  4. 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…

  5. 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.

  6. A generalized equivalent circuit theory for the electric and magnetic resonances of metallic wire networks

    NASA Astrophysics Data System (ADS)

    Zhang, Weiyi; Chui, S. T.

    2009-06-01

    We generalize Kirchoff's law for multiply connected wire networks to finite frequencies. We focus on the boundary conditions not present in the conventional Kirchoff's law at joints when more than three wires come together, which is absent in our previous "circuit theory" for the finite frequency properties of metallic wire networks for singly connected structures. These boundary conditions at the joints involve introducing localized boundary electric fields, in addition to the electric fields of inductive and capacitive origins. The boundary fields act as natural "Lagrange multipliers" for imposing the boundary conditions on the circuit currents. In this way the number of equations is the same as the number of unknowns. The eigenmodes determine not only the circuit current and charge profiles, but also the boundary electric fields which supplement such profiles. The application to T- and H-shape metallic wire networks suggests that the basic types of resonances are mainly controlled by the symmetry and the wire dimensions of the networks. The low frequency modes form along the longest connected paths of the wire network while the high frequency modes can be generated via succeedingly adding more nodes along these various wire paths. The characteristic behavior of the electric and magnetic responses can be inferred from the circuit current profile of a given mode, which offers a simple physical picture on circuit design with particular electromagnetic parameters.

  7. The topology and dynamics of protein complexes: insights from intra- molecular network theory.

    PubMed

    Hu, Guang; Zhou, Jianhong; Yan, Wenying; Chen, Jiajia; Shen, Bairong

    2013-03-01

    Intra-molecular interactions within complex systems play a pivotal role in the biological function. They form a major challenge to computational structural proteomics. The network paradigm treats any system as a set of nodes linked by edges corresponding to the relations existing between the nodes. It offers a computationally efficient tool to meet this challenge. Here, we review the recent advances in the use of network theory to study the topology and dynamics of protein- ligand and protein-nucleic acid complexes. The study of protein complexes networks not only involves the topological classification in term of network parameters, but also reveals the consistent picture of intrinsic functional dynamics. Current dynamical analysis focuses on a plethora of functional phenomena: the process of allosteric communication, the binding induced conformational changes, prediction and identification of binding sites of protein complexes, which will give insights into intra-protein complexes interactions. Furthermore, such computational results may elucidate a variety of known biological processes and experimental data, and thereby demonstrate a huge potential for applications such as drug design and functional genomics. Finally we describe some web-based resources for protein complexes, as well as protein network servers and related bioinformatics tools.

  8. 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

  9. Comparing brain networks of different size and connectivity density using graph theory.

    PubMed

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

    2010-10-28

    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.

  10. Actor modelling and its contribution to the development of integrative strategies for management of pharmaceuticals in drinking water.

    PubMed

    Titz, Alexandra; Döll, Petra

    2009-02-01

    Widespread presence of human pharmaceuticals in water resources across the globe is documented. While some, but certainly not enough, research on the occurrence, fate and effect of pharmaceuticals in water resources has been carried out, a holistic risk management strategy is missing. The transdisciplinary research project "start" aimed to develop an integrative strategy by the participation of experts representing key actors in the problem field "pharmaceuticals in drinking water". In this paper, we describe a novel modelling method, actor modelling with the semi-quantitative software DANA (Dynamic Actor Network Analysis), and its application in support of identifying an integrative risk management strategy. Based on the individual perceptions of different actors, the approach allows the identification of optimal strategies. Actors' perceptions were elicited by participatory model building and interviews, and were then modelled in perception graphs. Actor modelling indicated that an integrative strategy that targets environmentally-responsible prescription, therapy, and disposal of pharmaceuticals on one hand, and the development of environmentally-friendly pharmaceuticals on the other hand, will likely be most effective for reducing the occurrence of pharmaceuticals in drinking water (at least in Germany where the study was performed). However, unlike most other actors, the pharmaceutical industry itself does not perceive that the production of environmentally-friendly pharmaceuticals is an action that helps to achieve its goals, but contends that continued development of highly active pharmaceutical ingredients will help to reduce the occurrence of pharmaceuticals in the water cycle. Investment in advanced waste or drinking water treatment is opposed by both the wastewater treatment company and the drinking water supplier, and is not mentioned as appropriate by the other actors. According to our experience, actor modelling is a useful method to suggest effective

  11. 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

  12. 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

    2015-07-15

    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.

  13. Non-compliant Actors (NONCAS) Handbook

    DTIC Science & Technology

    2010-07-23

    being rather friendly. The colour terminology is borrowed from the operational planning and/or wargaming domains, where actors are classified...according to colours . NONCAS-Handbook, 23 July 2010 Page 5 identified which are helpful to classify and evaluate NC/NONCAS and which have direct... stereotyping , strong conformity pressure, illusion of unanimity, self-appointed mind-guards (see ―What motivates potential adversaries?‖: p. 16

  14. Inference and Analysis of Population Structure Using Genetic Data and Network Theory.

    PubMed

    Greenbaum, Gili; Templeton, Alan R; Bar-David, Shirli

    2016-04-01

    Clustering individuals to subpopulations based on genetic data has become commonplace in many genetic studies. Inference about population structure is most often done by applying model-based approaches, aided by visualization using distance-based approaches such as multidimensional scaling. While existing distance-based approaches suffer from a lack of statistical rigor, model-based approaches entail assumptions of prior conditions such as that the subpopulations are at Hardy-Weinberg equilibria. Here we present a distance-based approach for inference about population structure using genetic data by defining population structure using network theory terminology and methods. A network is constructed from a pairwise genetic-similarity matrix of all sampled individuals. The community partition, a partition of a network to dense subgraphs, is equated with population structure, a partition of the population to genetically related groups. Community-detection algorithms are used to partition the network into communities, interpreted as a partition of the population to subpopulations. The statistical significance of the structure can be estimated by using permutation tests to evaluate the significance of the partition's modularity, a network theory measure indicating the quality of community partitions. To further characterize population structure, a new measure of the strength of association (SA) for an individual to its assigned community is presented. The strength of association distribution (SAD) of the communities is analyzed to provide additional population structure characteristics, such as the relative amount of gene flow experienced by the different subpopulations and identification of hybrid individuals. Human genetic data and simulations are used to demonstrate the applicability of the analyses. The approach presented here provides a novel, computationally efficient model-free method for inference about population structure that does not entail assumption of

  15. 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.

  16. 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

  17. 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.

  18. 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.

  19. Quantization-Based Adaptive Actor-Critic Tracking Control With Tracking Error Constraints.

    PubMed

    Fan, Quan-Yong; Yang, Guang-Hong; Ye, Dan

    2017-02-01

    In this paper, the problem of adaptive actor-critic (AC) tracking control is investigated for a class of continuous-time nonlinear systems with unknown nonlinearities and quantized inputs. Different from the existing results based on reinforcement learning, the tracking error constraints are considered and new critic functions are constructed to improve the performance further. To ensure that the tracking errors keep within the predefined time-varying boundaries, a tracking error transformation technique is used to constitute an augmented error system. Specific critic functions, rather than the long-term cost function, are introduced to supervise the tracking performance and tune the weights of the AC neural networks (NNs). A novel adaptive controller with a special structure is designed to reduce the effect of the NN reconstruction errors, input quantization, and disturbances. Based on the Lyapunov stability theory, the boundedness of the closed-loop signals and the desired tracking performance can be guaranteed. Finally, simulations on two connected inverted pendulums are given to illustrate the effectiveness of the proposed method.

  20. [Study about target-network of anti-cerebral infarction neuropathy based on theory of neurovascular unit and network pharmacology].

    PubMed

    Liu, Qingshan; Fang, Liang; Wang, Weiqun; Zhang, Ziqian; Yang, Hongjun

    2012-01-01

    Potention drug-targets on anti-neuropathy of stroke were summarized, and it will provide materials for developing innovation components traditional Chinese medicine on anti-cerebral infarction neuropathy. This article had done a series of researching work about neurovascular unit which includes three kinds of cells: neuron, gliacyte,brain microvascular endothelial cell, then signal mechanism of cell death or apoptosis of each section of stroke neuropathy was analysised by the historical documents. There are five important pathways: inflammatory factor-MMPs pathway- Caspases, Ca2+ -mitochondrial pathway-Caspases, Ca2+ -Phospholipase-PI-3K/AK pathway, Ca2+ -radical-MAPK pathway, Ca2+ -NO-protease pathway, among all the nodes, Caspases, Ca2+, NO were the most important ones. Developing the multi-mechanism and multilevel of traditional chinese medicine under the guidance of the theories of network pharmacology and neurovascular unit will play an important role in studying the key links of signal-network of stroke neuropathy.

  1. Social network theory applied to resting-state fMRI connectivity data in the identification of epilepsy networks with iterative feature selection.

    PubMed

    Zhang, Xiaohui; Tokoglu, Fuyuze; Negishi, Michiro; Arora, Jagriti; Winstanley, Scott; Spencer, Dennis D; Constable, R Todd

    2011-07-15

    Epilepsy is a brain disorder usually associated with abnormal cortical and/or subcortical functional networks. Exploration of the abnormal network properties and localization of the brain regions involved in human epilepsy networks are critical for both the understanding of the epilepsy networks and planning therapeutic strategies. Currently, most localization of seizure networks come from ictal EEG observations. Functional MRI provides high spatial resolution together with more complete anatomical coverage compared with EEG and may have advantages if it can be used to identify the network(s) associated with seizure onset and propagation. Epilepsy networks are believed to be present with detectable abnormal signatures even during the interictal state. In this study, epilepsy networks were investigated using resting-state fMRI acquired with the subjects in the interictal state. We tested the hypothesis that social network theory applied to resting-state fMRI data could reveal abnormal network properties at the group level. Using network data as input to a classification algorithm allowed separation of medial temporal lobe epilepsy (MTLE) patients from normal control subjects indicating the potential value of such network analyses in epilepsy. Five local network properties obtained from 36 anatomically defined ROIs were input as features to the classifier. An iterative feature selection strategy based on the classification efficiency that can avoid 'over-fitting' is proposed to further improve the classification accuracy. An average sensitivity of 77.2% and specificity of 83.86% were achieved via 'leave one out' cross validation. This finding of significantly abnormal network properties in group level data confirmed our initial hypothesis and provides motivation for further investigation of the epilepsy process at the network level.

  2. 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.

  3. 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

  4. 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

  5. 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.

  6. Brain network connectivity in women exposed to intimate partner violence: a graph theory analysis study.

    PubMed

    Roos, Annerine; Fouche, Jean-Paul; Stein, Dan J

    2016-10-18

    Evidence suggests that women who suffer from intimate partner violence (IPV) and posttraumatic stress disorder (PTSD) have structural and functional alterations in specific brain regions. Yet, little is known about how brain connectivity may be altered in individuals with IPV, but without PTSD. Women exposed to IPV (n = 18) and healthy controls (n = 18) underwent structural brain imaging using a Siemens 3T MRI. Global and regional brain network connectivity measures were determined, using graph theory analyses. Structural covariance networks were created using volumetric and cortical thickness data after controlling for intracranial volume, age and alcohol use. Nonparametric permutation tests were used to investigate group differences. Findings revealed altered connectivity on a global and regional level in the IPV group of regions involved in cognitive-emotional control, with principal involvement of the caudal anterior cingulate, the middle temporal gyrus, left amygdala and ventral diencephalon that includes the thalamus. To our knowledge, this is the first evidence showing different brain network connectivity in global and regional networks in women exposed to IPV, and without PTSD. Altered cognitive-emotional control in IPV may underlie adaptive neural mechanisms in environments characterized by potentially dangerous cues.

  7. Molecular epidemiology of tuberculosis transmission: Contextualizing the evidence through social network theory.

    PubMed

    Hollm-Delgado, Maria-Graciela

    2009-09-01

    Despite a long-standing recognition that factors such as age, gender, and socioeconomic status play a fundamental role in tuberculosis transmission and susceptibility, few molecular epidemiological studies have fully elucidated the etiological mechanisms by which each of these social factors may influence transmission of the disease. In this paper, we propose that in order to achieve this goal, molecular epidemiology must move towards a more holistic approach for disease transmission, thus enabling social theory to be integrated into molecular epidemiological studies on tuberculosis. We then present a social network model to illustrate how molecular and social epidemiology can be combined to study disease transmission patterns, and provide preliminary molecular epidemiological evidence to support the role of social networks in tuberculosis transmission.

  8. A Statistical Test of Walrasian Equilibrium by Means of Complex Networks Theory

    NASA Astrophysics Data System (ADS)

    Bargigli, Leonardo; Viaggiu, Stefano; Lionetto, Andrea

    2016-10-01

    We represent an exchange economy in terms of statistical ensembles for complex networks by introducing the concept of market configuration. This is defined as a sequence of nonnegative discrete random variables {w_{ij}} describing the flow of a given commodity from agent i to agent j. This sequence can be arranged in a nonnegative matrix W which we can regard as the representation of a weighted and directed network or digraph G. Our main result consists in showing that general equilibrium theory imposes highly restrictive conditions upon market configurations, which are in most cases not fulfilled by real markets. An explicit example with reference to the e-MID interbank credit market is provided.

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

    PubMed Central

    Smadbeck, Patrick; Kaznessis, Yiannis N.

    2015-01-01

    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. PMID:25978877

  10. Small Pure Carbon Molecules with Small-World Networks Using Density Functional Theory Simulations

    NASA Astrophysics Data System (ADS)

    Yancey, Jeremy A.; Novotny, M. A.; Gwaltney, Steven R.

    The possible existence of small, pure carbon molecules based on small-world networks is addressed using density functional theory simulations. A ring of atoms with one or more small-world connections between pairs of non-nearest-neighbor sites was chosen for the network topology. The small-world connections are made with and without additional carbon atoms placed along the link. The energy per atom of these small-world carbon systems is compared with benchmark molecules such as the C20 ring, bowl, and cage isomers, the C60 Buckyball, monocyclic pure carbon rings ranging from C4 to C60, bare linear carbon chains ranging from C2 to C36, and various graphitic fragments without hydrogens. The results of the energy per atom for some of these small-world clusters provide an indication that such pure carbon molecules are reasonable for real world synthesis.

  11. 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.

  12. Can Humans Fly Action Understanding with Multiple Classes of Actors

    DTIC Science & Technology

    2015-06-08

    formulation jointly captures the actor-action tuples as unique entities but cannot model the common actor and action behaviors among different tu- ples as...tionships in the individual actor and action spaces as well as Model Actor Action <A, A> Actor Action <A, A> Naïve Bayes 70.51 74.40 56.17 76.85 78.29... model them. This phenomenon occurs in all of our experiments. Finally, the trilayer model outperforms the other two mod- els in terms of both individual

  13. 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

  14. Effective-medium theory of elastic waves in random networks of rods.

    PubMed

    Katz, J I; Hoffman, J J; Conradi, M S; Miller, J G

    2012-06-01

    We formulate an effective medium (mean field) theory of a material consisting of randomly distributed nodes connected by straight slender rods, hinged at the nodes. Defining wavelength-dependent effective elastic moduli, we calculate both the static moduli and the dispersion relations of ultrasonic longitudinal and transverse elastic waves. At finite wave vector k the waves are dispersive, with phase and group velocities decreasing with increasing wave vector. These results are directly applicable to networks with empty pore space. They also describe the solid matrix in two-component (Biot) theories of fluid-filled porous media. We suggest the possibility of low density materials with higher ratios of stiffness and strength to density than those of foams, aerogels, or trabecular bone.

  15. Recent advances on techniques and theories of feedforward networks with supervised learning

    NASA Astrophysics Data System (ADS)

    Xu, Lei; Klasa, Stan

    1992-07-01

    The rediscovery and popularization of the back propagation training technique for multilayer perceptrons as well as the invention of the Boltzmann Machine learning algorithm has given a new boost to the study of supervised learning networks. In recent years, besides the widely spread applications and the various further improvements of the classical back propagation technique, many new supervised learning models, techniques as well as theories, have also been proposed in a vast number of publications. This paper tries to give a rather systematical review on the recent advances on supervised learning techniques and theories for static feedforward networks. We summarize a great number of developments into four aspects: (1) Various improvements and variants made on the classical back propagation techniques for multilayer (static) perceptron nets, for speeding up training, avoiding local minima, increasing the generalization ability, as well as for many other interesting purposes. (2) A number of other learning methods for training multilayer (static) perceptron, such as derivative estimation by perturbation, direct weight update by perturbation, genetic algorithms, recursive least square estimate and extended Kalman filter, linear programming, the policy of fixing one layer while updating another, constructing networks by converting decision tree classifiers, and others. (3) Various other feedforward models which are also able to implement function approximation, probability density estimation and classification, including various models of basis function expansion (e.g., radial basis functions, restricted coulomb energy, multivariate adaptive regression splines, trigonometric and polynomial bases, projection pursuit, basis function tree, and may others), and several other supervised learning models. (4) Models with complex structures, e.g., modular architecture, hierarchy architecture, and others. (5) A number of theoretical issues involving the universal

  16. Graph Theory-Based Approach for Stability Analysis of Stochastic Coupled Systems With Lévy Noise on Networks.

    PubMed

    Zhang, Chunmei; Li, Wenxue; Wang, Ke

    2015-08-01

    In this paper, a novel class of stochastic coupled systems with Lévy noise on networks (SCSLNNs) is presented. Both white noise and Lévy noise are considered in the networks. By exploiting graph theory and Lyapunov stability theory, criteria ensuring p th moment exponential stability and stability in probability of these SCSLNNs are established, respectively. These principles are closely related to the topology of the network and the perturbation intensity of white noise and Lévy noise. Moreover, to verify the theoretical results, stochastic coupled oscillators with Lévy noise on a network and stochastic Volterra predator-prey system with Lévy noise are performed. Finally, a numerical example about oscillators' network is provided to illustrate the feasibility of our analytical results.

  17. 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.

  18. An efficient graph theory based method to identify every minimal reaction set in a metabolic network

    PubMed Central

    2014-01-01

    Background Development of cells with minimal metabolic functionality is gaining importance due to their efficiency in producing chemicals and fuels. Existing computational methods to identify minimal reaction sets in metabolic networks are computationally expensive. Further, they identify only one of the several possible minimal reaction sets. Results In this paper, we propose an efficient graph theory based recursive optimization approach to identify all minimal reaction sets. Graph theoretical insights offer systematic methods to not only reduce the number of variables in math programming and increase its computational efficiency, but also provide efficient ways to find multiple optimal solutions. The efficacy of the proposed approach is demonstrated using case studies from Escherichia coli and Saccharomyces cerevisiae. In case study 1, the proposed method identified three minimal reaction sets each containing 38 reactions in Escherichia coli central metabolic network with 77 reactions. Analysis of these three minimal reaction sets revealed that one of them is more suitable for developing minimal metabolism cell compared to other two due to practically achievable internal flux distribution. In case study 2, the proposed method identified 256 minimal reaction sets from the Saccharomyces cerevisiae genome scale metabolic network with 620 reactions. The proposed method required only 4.5 hours to identify all the 256 minimal reaction sets and has shown a significant reduction (approximately 80%) in the solution time when compared to the existing methods for finding minimal reaction set. Conclusions Identification of all minimal reactions sets in metabolic networks is essential since different minimal reaction sets have different properties that effect the bioprocess development. The proposed method correctly identified all minimal reaction sets in a both the case studies. The proposed method is computationally efficient compared to other methods for finding minimal

  19. External control of the GAL network in S. cerevisiae: a view from control theory.

    PubMed

    Yang, Ruoting; Lenaghan, Scott C; Wikswo, John P; Zhang, Mingjun

    2011-04-29

    While there is a vast literature on the control systems that cells utilize to regulate their own state, there is little published work on the formal application of control theory to the external regulation of cellular functions. This paper chooses the GAL network in S. cerevisiae as a well understood benchmark example to demonstrate how control theory can be employed to regulate intracellular mRNA levels via extracellular galactose. Based on a mathematical model reduced from the GAL network, we have demonstrated that a galactose dose necessary to drive and maintain the desired GAL genes' mRNA levels can be calculated in an analytic form. And thus, a proportional feedback control can be designed to precisely regulate the level of mRNA. The benefits of the proposed feedback control are extensively investigated in terms of stability and parameter sensitivity. This paper demonstrates that feedback control can both significantly accelerate the process to precisely regulate mRNA levels and enhance the robustness of the overall cellular control system.

  20. Synthesizing animal and human behavior research via neural network learning theory.

    PubMed

    Tryon, W W

    1995-12-01

    Animal and human research have been "divorced" since approximately 1968. Several recent articles have tried to persuade behavior therapists of the merits of animal research. Three reasons are given concerning why disinterest in animal research is so widespread: (1) functional explanations are given for animals, and cognitive explanations are given for humans; (2) serial symbol manipulating models are used to explain human behavior; and (3) human learning was assumed, thereby removing it as something to be explained. Brain-inspired connectionist neural networks, collectively referred to as neural network learning theory (NNLT), are briefly described, and a spectrum of their accomplishments from simple conditioning through speech is outlined. Five benefits that behavior therapists can derive from NNLT are described. They include (a) enhanced professional identity derived from a comprehensive learning theory, (b) improved interdisciplinary collaboration both clinically and scientifically, (c) renewed perceived relevance of animal research, (d) access to plausible proximal causal mechanisms capable of explaining operant conditioning, and (e) an inherently developmental perspective.

  1. Disrupted theory of mind network processing in response to idea of reference evocation in schizophrenia.

    PubMed

    Park, I H; Ku, J; Lee, H; Kim, S Y; Kim, S I; Yoon, K J; Kim, J-J

    2011-01-01

    This study examined the neural pathophysiology of the theory of mind network by eliciting self-referential processing during an idea of reference evocating situation in patients with schizophrenia. Functional MRI was conducted on 14 schizophrenic in-patients with the idea of reference and 15 healthy participants while viewing video vignettes of referential conversations, non-referential conversations or no conversations between two people, which were filmed at varying distances of 1, 5 or 10 m. The patient group did not show normal patterns of superior temporal sulcus activation to conversational context, and reciprocal deactivation and activation of the ventromedial and dorsomedial prefrontal cortex to referential conversational context. Instead, the patient group showed overall greater ventromedial prefrontal activities across different conversational contexts and inverse correlation between superior temporal sulcus activity and delusional severity. Differential activations of the temporal pole and its posterior extension to varying distances were observed in the control group but not in the patient group. The present study demonstrates that theory of mind-related responses of the medial prefrontal-superior temporal network are attenuated during the self-referential processing in patients with schizophrenia and that these abnormalities may be related to the formation of their referential or persecutory delusion. © 2010 John Wiley & Sons A/S.

  2. Real-time flood forecasts & risk assessment using a possibility-theory based fuzzy neural network

    NASA Astrophysics Data System (ADS)

    Khan, U. T.

    2016-12-01

    Globally floods are one of the most devastating natural disasters and improved flood forecasting methods are essential for better flood protection in urban areas. Given the availability of high resolution real-time datasets for flood variables (e.g. streamflow and precipitation) in many urban areas, data-driven models have been effectively used to predict peak flow rates in river; however, the selection of input parameters for these types of models is often subjective. Additionally, the inherit uncertainty associated with data models along with errors in extreme event observations means that uncertainty quantification is essential. Addressing these concerns will enable improved flood forecasting methods and provide more accurate flood risk assessments. In this research, a new type of data-driven model, a quasi-real-time updating fuzzy neural network is developed to predict peak flow rates in urban riverine watersheds. A possibility-to-probability transformation is first used to convert observed data into fuzzy numbers. A possibility theory based training regime is them used to construct the fuzzy parameters and the outputs. A new entropy-based optimisation criterion is used to train the network. Two existing methods to select the optimum input parameters are modified to account for fuzzy number inputs, and compared. These methods are: Entropy-Wavelet-based Artificial Neural Network (EWANN) and Combined Neural Pathway Strength Analysis (CNPSA). Finally, an automated algorithm design to select the optimum structure of the neural network is implemented. The overall impact of each component of training this network is to replace the traditional ad hoc network configuration methods, with one based on objective criteria. Ten years of data from the Bow River in Calgary, Canada (including two major floods in 2005 and 2013) are used to calibrate and test the network. The EWANN method selected lagged peak flow as a candidate input, whereas the CNPSA method selected lagged

  3. 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

  4. 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

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

    PubMed

    Keating, S; Di Cera, E

    1993-07-01

    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

  6. Mapping the neuropsychological profile of temporal lobe epilepsy using cognitive network topology and graph theory.

    PubMed

    Kellermann, Tanja S; Bonilha, Leonardo; Eskandari, Ramin; Garcia-Ramos, Camille; Lin, Jack J; Hermann, Bruce P

    2016-10-01

    Normal cognitive function is defined by harmonious interaction among multiple neuropsychological domains. Epilepsy has a disruptive effect on cognition, but how diverse cognitive abilities differentially interact with one another compared with healthy controls (HC) is unclear. This study used graph theory to analyze the community structure of cognitive networks in adults with temporal lobe epilepsy (TLE) compared with that in HC. Neuropsychological assessment was performed in 100 patients with TLE and 82 HC. For each group, an adjacency matrix was constructed representing pair-wise correlation coefficients between raw scores obtained in each possible test combination. For each cognitive network, each node corresponded to a cognitive test; each link corresponded to the correlation coefficient between tests. Global network structure, community structure, and node-wise graph theory properties were qualitatively assessed. The community structure in patients with TLE was composed of fewer, larger, more mixed modules, characterizing three main modules representing close relationships between the following: 1) aspects of executive function (EF), verbal and visual memory, 2) speed and fluency, and 3) speed, EF, perception, language, intelligence, and nonverbal memory. Conversely, controls exhibited a relative division between cognitive functions, segregating into more numerous, smaller modules consisting of the following: 1) verbal memory, 2) language, perception, and intelligence, 3) speed and fluency, and 4) visual memory and EF. Overall node-wise clustering coefficient and efficiency were increased in TLE. Adults with TLE demonstrate a less clear and poorly structured segregation between multiple cognitive domains. This panorama suggests a higher degree of interdependency across multiple cognitive domains in TLE, possibly indicating compensatory mechanisms to overcome functional impairments. Copyright © 2016 Elsevier Inc. All rights reserved.

  7. 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.

  8. Spatial assessment and redesign of a groundwater quality monitoring network using entropy theory, Gaza Strip, Palestine

    NASA Astrophysics Data System (ADS)

    Mogheir, Y.; Singh, V. P.; de Lima, J. L. M. P.

    2006-06-01

    Using entropy theory, a methodology was developed for the evaluation and redesign of groundwater quality monitoring wells in the Gaza Strip in Palestine. Essential to the methodology is the development of a Transinformation Model (TM) which yields the amount of information transfer and the dependency between the wells as a function of distance. The TM parameters, such as the minimum transinformation and the range, were employed for evaluating the network which revealed that most of the distances between wells were less than the range. It also indicated that a high percentage of redundant information existed in the network. Therefore, the network was reduced by superimposing a square pattern over the monitored area and selecting one well per square block in a stratified pattern. The methodology was tested using the chloride data collected from 1972 2000 from 417 groundwater quality monitoring wells in the Gaza Strip. The number of the groundwater quality monitoring wells in the Gaza Strip was reduced by 53%, while there was 26% redundant information based on the minimum existing distance between wells. This methodology is meant to help monitor the groundwater quality (salinity) in the Gaza Strip.

  9. Dysregulation between emotion and theory of mind networks in borderline personality disorder.

    PubMed

    O'Neill, Aisling; D'Souza, Arun; Samson, Andrea C; Carballedo, Angela; Kerskens, Christian; Frodl, Thomas

    2015-01-30

    Individuals with borderline personality disorder (BPD) commonly display deficits in emotion regulation, but findings in the area of social cognitive (e.g., theory of mind, ToM) capacities have been heterogeneous. The aims of the current study were to investigate differences between patients with BPD and controls in functional connectivity (1) between the emotion and ToM network and (2) in the default mode network (DMN). Functional magnetic resonance imaging was used to investigate 19 healthy controls and 17 patients with BPD at rest and during ToM processing. Functional coupling was analysed. Significantly decreased functional connectivity was found for patients compared with controls between anterior cingulate cortex and three brain areas involved in ToM processes: the left superior temporal lobe, right supramarginal/inferior parietal lobes, and right middle cingulate cortex. Increased functional connectivity was found in patients compared with controls between the precuneus as the DMN seed and the left inferior frontal lobe, left precentral/middle frontal, and left middle occipital/superior parietal lobes during rest. Reduced functional coupling between the emotional and the ToM network during ToM processing is in line with emotion-regulation dysfunctions in BPD. The increased connectivity between precuneus and frontal regions during rest might be related to extensive processing of internal thoughts and self-referential information in BPD.

  10. Asymptotic Analysis of Large Cooperative Relay Networks Using Random Matrix Theory

    NASA Astrophysics Data System (ADS)

    Li, Husheng; Han, Z.; Poor, H.

    2008-12-01

    Cooperative transmission is an emerging communication technology that takes advantage of the broadcast nature of wireless channels. In cooperative transmission, the use of relays can create a virtual antenna array so that multiple-input/multiple-output (MIMO) techniques can be employed. Most existing work in this area has focused on the situation in which there are a small number of sources and relays and a destination. In this paper, cooperative relay networks with large numbers of nodes are analyzed, and in particular the asymptotic performance improvement of cooperative transmission over direction transmission and relay transmission is analyzed using random matrix theory. The key idea is to investigate the eigenvalue distributions related to channel capacity and to analyze the moments of this distribution in large wireless networks. A performance upper bound is derived, the performance in the low signal-to-noise-ratio regime is analyzed, and two approximations are obtained for high and low relay-to-destination link qualities, respectively. Finally, simulations are provided to validate the accuracy of the analytical results. The analysis in this paper provides important tools for the understanding and the design of large cooperative wireless networks.

  11. 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.

  12. A new measure based on degree distribution that links information theory and network graph analysis

    PubMed Central

    2012-01-01

    Background Detailed connection maps of human and nonhuman brains are being generated with new technologies, and graph metrics have been instrumental in understanding the general organizational features of these structures. Neural networks appear to have small world properties: they have clustered regions, while maintaining integrative features such as short average pathlengths. Results We captured the structural characteristics of clustered networks with short average pathlengths through our own variable, System Difference (SD), which is computationally simple and calculable for larger graph systems. SD is a Jaccardian measure generated by averaging all of the differences in the connection patterns between any two nodes of a system. We calculated SD over large random samples of matrices and found that high SD matrices have a low average pathlength and a larger number of clustered structures. SD is a measure of degree distribution with high SD matrices maximizing entropic properties. Phi (Φ), an information theory metric that assesses a system’s capacity to integrate information, correlated well with SD - with SD explaining over 90% of the variance in systems above 11 nodes (tested for 4 to 13 nodes). However, newer versions of Φ do not correlate well with the SD metric. Conclusions The new network measure, SD, provides a link between high entropic structures and degree distributions as related to small world properties. PMID:22726594

  13. Adaptive Resonance Theory Neural Networks for Astronomical Region of Interest Detection and Noise Characterization

    NASA Astrophysics Data System (ADS)

    Young, R. J.; Ritthaler, M. Healy, M.; Caudell, T. P. Zimmer, P.; McGraw, J.

    2007-10-01

    While learning algorithms have been used for astronomical data analysis, the vast majority of those algorithms have used supervised learning. We examine the use of two types of Adaptive Resonance Theory (ART) (Carpenter & Grossberg 1987) neural networks which use unsupervised learning for this task. Using synthetic astronomical data from SkyMaker which was designed to mimic the dynamic range of the CTI-II telescope, we compared the ability of the ART-1 neural network and the ART-1 neural network with a category theoretic modification to detect regions of interest and to characterize noise. We use the program SExtractor to pinpoint clusters that contain either many or no object hits. We then show that there are more targets in the clusters with many SExtractor hits than SExtractor finds. We also show that ART clusters together input regions that are dominated by noise that can be used to characterize the noise in an image. The results provided show that unsupervised learning algorithms should not be overlooked for astronomical data analysis.

  14. 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. Copyright © 2014 Elsevier Ltd. All rights reserved.

  15. Optimization of hydrometric monitoring network in urban drainage systems using information theory.

    PubMed

    Yazdi, J

    2017-10-01

    Regular and continuous monitoring of urban runoff in both quality and quantity aspects is of great importance for controlling and managing surface runoff. Due to the considerable costs of establishing new gauges, optimization of the monitoring network is essential. This research proposes an approach for site selection of new discharge stations in urban areas, based on entropy theory in conjunction with multi-objective optimization tools and numerical models. The modeling framework provides an optimal trade-off between the maximum possible information content and the minimum shared information among stations. This approach was applied to the main surface-water collection system in Tehran to determine new optimal monitoring points under the cost considerations. Experimental results on this drainage network show that the obtained cost-effective designs noticeably outperform the consulting engineers' proposal in terms of both information contents and shared information. The research also determined the highly frequent sites at the Pareto front which might be important for decision makers to give a priority for gauge installation on those locations of the network.

  16. 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.

  17. The actor-observer effect in virtual reality presentations.

    PubMed

    Larsson, P; Västfjäll, D; Kleiner, M

    2001-04-01

    The use of virtual reality (VR) presentations are becoming a more and more frequent means of communicating information and displaying data to large groups of viewers. VR presentations put heavy demands on reproduction of visual, aural, and tactile information. A common situation in VR presentations is that one actor acts in the virtual environment (VE), while a group of people observes the actors actions in the VE, often from the perspective of the actor. The current paper aims to study actors' (participants actively interacting with the VE) and observers' (participants passively observing the actors' interaction with the VE) evaluations of the VR presentation. In an experiment, 16 actors and 16 observers either acted in or observed a VE and performed ratings of the quality of the presentation. The results showed that actors experienced higher presence and realism, and enjoyed the VR experience more than observers did. Observers, on the other hand, experienced that external events distracted their attention more than actors did. Finally, actors experienced more symptoms of simulation sickness. However, no differences between actors and observers were found for ratings of audio quality.

  18. 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.

  19. The educational value of improvisational actors to teach communication and relational skills: perspectives of interprofessional learners, faculty, and actors.

    PubMed

    Bell, Sigall K; Pascucci, Robert; Fancy, Kristina; Coleman, Kelliann; Zurakowski, David; Meyer, Elaine C

    2014-09-01

    To assess the educational value of improvisational actors in difficult conversation simulations to teach communication and relational skills to interprofessional learners. Surveys of 192 interprofessional health care professionals, and 33 teaching faculty, and semi-structured interviews of 10 actors. Descriptive statistics, Fisher's exact test and chi-square test were used for quantitative analyses, and the Crabtree and Miller approach was used for qualitative analyses. 191/192 (99.5%) interprofessional learners (L), and 31/33 (94%) teaching faculty (F) responded to surveys. All 10/10 actors completed interviews. Nearly all participants found the actors realistic (98%L, 96%F), and valuable to the learning (97%L, 100%F). Most felt that role-play with another clinician would not have been as valuable as learning with actors (80%L, 97%F). There were no statistically significant differences in perceived value between learners who participated in the simulations (47%) versus those who observed (53%), or between doctors, nurses, or psychosocial professionals. Qualitative assessment yielded five actor value themes: Realism, Actor Feedback, Layperson Perspective, Depth of Emotion, and Role of Improvisation in Education. Actors independently identified similar themes as goals of their work. The value attributed to actors was nearly universal among interprofessional learners and faculty, and independent of enactment participation versus observation. Authenticity, feedback from actors, patient/family perspectives, emotion, and improvisation were key educational elements. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

  20. Perturbation waves in proteins and protein networks: applications of percolation and game theories in signaling and drug design.

    PubMed

    Antal, Miklós A; Böde, Csaba; Csermely, Peter

    2009-04-01

    The network paradigm is increasingly used to describe the dynamics of complex systems. Here we review the current results and propose future development areas in the assessment of perturbation waves, i.e. propagating structural changes in amino acid networks building individual protein molecules and in protein-protein interaction networks (interactomes). We assess the possibilities and critically review the initial attempts for the application of game theory to the often rather complicated process, when two protein molecules approach each other, mutually adjust their conformations via multiple communication steps and finally, bind to each other. We also summarize available data on the application of percolation theory for the prediction of amino acid network- and interactome-dynamics. Furthermore, we give an overview of the dissection of signals and noise in the cellular context of various perturbations. Finally, we propose possible applications of the reviewed methodologies in drug design.