Actor Networks and the Division of Knowledge in the University.

ERIC Educational Resources Information Center

Busch, Lawrence

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

Reassembling the Information Technology Innovation Process: An Actor Network Theory Method for Managing the Initiation, Production, and Diffusion of Innovations

NASA Astrophysics Data System (ADS)

Zendejas, Gerardo; Chiasson, Mike

This paper will propose and explore a method to enhance focal actors' abilities to enroll and control the many social and technical components interacting during the initiation, production, and diffusion of innovations. The reassembling and stabilizing of such components is the challenging goal of the focal actors involved in these processes. To address this possibility, a healthcare project involving the initiation, production, and diffusion of an IT-based innovation will be influenced by the researcher, using concepts from actor network theory (ANT), within an action research methodology (ARM). The experiences using this method, and the nature of enrolment and translation during its use, will highlight if and how ANT can provide a problem-solving method to help assemble the social and technical actants involved in the diffusion of an innovation. Finally, the paper will discuss the challenges and benefits of implementing such methods to attain widespread diffusion.

Exploring the Relational Efforts Making up a Curriculum Concept--An Actor-Network Theory Analysis of the Curriculum Concept of "Children's Interests"

ERIC Educational Resources Information Center

Moberg, Emilie

2018-01-01

This paper undertakes an investigation of the "life" of the curriculum concept of "children's interests" in a preschool practice. The concept of "children's interests" plays a vital role in the Swedish preschool curriculum text and in the preschool field. Strongly inspired by Actor-network theory readings, the paper…

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

Trail-Based Search for Efficient Event Report to Mobile Actors in Wireless Sensor and Actor Networks.

PubMed

Xu, Zhezhuang; Liu, Guanglun; Yan, Haotian; Cheng, Bin; Lin, Feilong

2017-10-27

In wireless sensor and actor networks, when an event is detected, the sensor node needs to transmit an event report to inform the actor. Since the actor moves in the network to execute missions, its location is always unavailable to the sensor nodes. A popular solution is the search strategy that can forward the data to a node without its location information. However, most existing works have not considered the mobility of the node, and thus generate significant energy consumption or transmission delay. In this paper, we propose the trail-based search (TS) strategy that takes advantage of actor's mobility to improve the search efficiency. The main idea of TS is that, when the actor moves in the network, it can leave its trail composed of continuous footprints. The search packet with the event report is transmitted in the network to search the actor or its footprints. Once an effective footprint is discovered, the packet will be forwarded along the trail until it is received by the actor. Moreover, we derive the condition to guarantee the trail connectivity, and propose the redundancy reduction scheme based on TS (TS-R) to reduce nontrivial transmission redundancy that is generated by the trail. The theoretical and numerical analysis is provided to prove the efficiency of TS. Compared with the well-known expanding ring search (ERS), TS significantly reduces the energy consumption and search delay.

Path scheduling for multiple mobile actors in wireless sensor network

NASA Astrophysics Data System (ADS)

Trapasiya, Samir D.; Soni, Himanshu B.

2017-05-01

In wireless sensor network (WSN), energy is the main constraint. In this work we have addressed this issue for single as well as multiple mobile sensor actor network. In this work, we have proposed Rendezvous Point Selection Scheme (RPSS) in which Rendezvous Nodes are selected by set covering problem approach and from that, Rendezvous Points are selected in a way to reduce the tour length. The mobile actors tour is scheduled to pass through those Rendezvous Points as per Travelling Salesman Problem (TSP). We have also proposed novel rendezvous node rotation scheme for fair utilisation of all the nodes. We have compared RPSS with Stationery Actor scheme as well as RD-VT, RD-VT-SMT and WRP-SMT for performance metrics like energy consumption, network lifetime, route length and found the better outcome in all the cases for single actor. We have also applied RPSS for multiple mobile actor case like Multi-Actor Single Depot (MASD) termination and Multi-Actor Multiple Depot (MAMD) termination and observed by extensive simulation that MAMD saves the network energy in optimised way and enhance network lifetime compared to all other schemes.

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

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

An actor-network theory analysis of policy innovation for smoke-free places: understanding change in complex systems.

PubMed

Young, David; Borland, Ron; Coghill, Ken

2010-07-01

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.

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…

("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…

Trail-Based Search for Efficient Event Report to Mobile Actors in Wireless Sensor and Actor Networks †

PubMed Central

Xu, Zhezhuang; Liu, Guanglun; Yan, Haotian; Cheng, Bin; Lin, Feilong

2017-01-01

In wireless sensor and actor networks, when an event is detected, the sensor node needs to transmit an event report to inform the actor. Since the actor moves in the network to execute missions, its location is always unavailable to the sensor nodes. A popular solution is the search strategy that can forward the data to a node without its location information. However, most existing works have not considered the mobility of the node, and thus generate significant energy consumption or transmission delay. In this paper, we propose the trail-based search (TS) strategy that takes advantage of actor’s mobility to improve the search efficiency. The main idea of TS is that, when the actor moves in the network, it can leave its trail composed of continuous footprints. The search packet with the event report is transmitted in the network to search the actor or its footprints. Once an effective footprint is discovered, the packet will be forwarded along the trail until it is received by the actor. Moreover, we derive the condition to guarantee the trail connectivity, and propose the redundancy reduction scheme based on TS (TS-R) to reduce nontrivial transmission redundancy that is generated by the trail. The theoretical and numerical analysis is provided to prove the efficiency of TS. Compared with the well-known expanding ring search (ERS), TS significantly reduces the energy consumption and search delay. PMID:29077017

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.

Network congestion control algorithm based on Actor-Critic reinforcement learning model

NASA Astrophysics Data System (ADS)

Xu, Tao; Gong, Lina; Zhang, Wei; Li, Xuhong; Wang, Xia; Pan, Wenwen

2018-04-01

Aiming at the network congestion control problem, a congestion control algorithm based on Actor-Critic reinforcement learning model is designed. Through the genetic algorithm in the congestion control strategy, the network congestion problems can be better found and prevented. According to Actor-Critic reinforcement learning, the simulation experiment of network congestion control algorithm is designed. The simulation experiments verify that the AQM controller can predict the dynamic characteristics of the network system. Moreover, the learning strategy is adopted to optimize the network performance, and the dropping probability of packets is adaptively adjusted so as to improve the network performance and avoid congestion. Based on the above finding, it is concluded that the network congestion control algorithm based on Actor-Critic reinforcement learning model can effectively avoid the occurrence of TCP network congestion.

Using attractiveness model for actors ranking in social media networks.

PubMed

Qasem, Ziyaad; Jansen, Marc; Hecking, Tobias; Hoppe, H Ulrich

2017-01-01

Influential actors detection in social media such as Twitter or Facebook can play a major role in gathering opinions on particular topics, improving the marketing efficiency, predicting the trends, etc. This work aims to extend our formally defined T measure to present a new measure aiming to recognize the actor's influence by the strength of attracting new important actors into a networked community. Therefore, we propose a model of the actor's influence based on the attractiveness of the actor in relation to the number of other attractors with whom he/she has established connections over time. Using an empirically collected social network for the underlying graph, we have applied the above-mentioned measure of influence in order to determine optimal seeds in a simulation of influence maximization. We study our extended measure in the context of information diffusion because this measure is based on a model of actors who attract others to be active members in a community. This corresponds to the idea of the IC simulation model which is used to identify the most important spreaders in a set of actors.

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…

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…

Defining the global health system and systematically mapping its network of actors.

PubMed

Hoffman, Steven J; Cole, Clarke B

2018-04-17

The global health system has faced significant expansion over the past few decades, including continued increase in both the number and diversity of actors operating within it. However, without a stronger understanding of what the global health system encompasses, coordination of actors and resources to address today's global health challenges will not be possible. This study presents a conceptually sound and operational definition of the global health system. Importantly, this definition can be applied in practice to facilitate analysis of the system. The study tested the analytical helpfulness of this definition through a network mapping exercise, whereby the interconnected nature of websites representing actors in the global health system was studied. Using a systematic methodology and related search functions, 203 global health actors were identified, representing the largest and most transparent list of its kind to date. Identified global health actors were characterized and the structure of their social network revealed intriguing patterns in relationships among actors. These findings provide a foundation for future inquiries into the global health system's structure and dynamics that are critical if we are to better coordinate system activities and ensure successful response to our most pressing global health challenges.

Following the moving and changing attachments and assemblages of 'addiction': Applying the actor network approach to autobiographies.

PubMed

Törrönen, Jukka; Tigerstedt, Christoffer

2018-04-01

The article applies actor network theory (ANT) to autobiographical data on alcohol dependence to explore what ANT can offer to the analysis of 'addiction stories'. By defining 'addiction' as a relational achievement, as the effect of elements acting together as a configuration of human and non-human actors, the article demonstrates how the moving and changing attachments of addiction can be dynamically analyzed with concepts of 'assemblage', 'mediator', 'tendency', 'translation', 'trajectory', 'immutable mobile', 'fluid' and 'bush fire'. The article shows how the reduction of alcohol dependence simply to genetic factors, neurobiological causes, personality disorders and self-medication constitutes an inadequate explanation. As 'meta theories', they illuminate addiction one-sidedly. Instead, as ANT pays attention to multiple heterogeneous mediators, it specifies in what way the causes identified in 'meta theories' may together with other actors participate in addiction assemblages. When following the development of addiction assemblages, we focus on situational sequences of action, in which human and non-human elements are linked to each other, and we trace how the relational shape of addiction changes from one sequence to another as a transforming assemblage of heterogeneous attachments that either maintain healthy subjectivities or destabilize them. The more attachments assemblages of addiction are able to make that are flexible and durable from one event to another, the stronger also the addiction-based subjectivities. Similarly, the fewer attachments that assemblages of addiction are able to keep in their various translations, the weaker the addiction-based subjectivities also become. An ANT-inspired analysis has a number of implications for the prevention and treatment of addiction: it suggests that in the prevention and treatment of addiction, the aim should hardly be to get rid of dependencies. Rather, the ambition should be the identification of attachments

Competing actors in the climate change arena in Mexico: A network analysis.

PubMed

Ortega Díaz, Araceli; Gutiérrez, Erika Casamadrid

2018-06-01

This paper analyzes the actors in the climate change arena and their influence in directing Mexico toward policies that decrease greenhouse gas emissions, such as the carbon tax and climate change law. The network analysis of the agreement of these laws and public policies in Mexico is a lesson for any country that is in the process of designing and adopting environmental laws. The research is performed using a network analysis that is derived from interviews with various main actors and a discourse analysis of the media. Results show that actors do not coordinate their efforts-they meet frequently but in different inter-ministerial commissions-and do not enforce the same policies. The actors in the industry have formed strong coalitions against the carbon tax and the General Law on Climate Change, whereas international institutions have formed coalitions that support these policies and laws. Copyright © 2018 Elsevier Ltd. All rights reserved.

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.

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.

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

PubMed

Lassa, Jonatan A

2015-07-01

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.

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…

Patterns of preference and practice: bridging actors in wildfire response networks in the American Northwest.

PubMed

Faas, A J; Velez, Anne-Lise K; FitzGerald, Clare; Nowell, Branda L; Steelman, Toddi A

2017-07-01

The roles of bridging actors in emergency response networks can be important to disaster response outcomes. This paper is based on an evaluation of wildfire preparedness and response networks in 21 large-scale wildfire events in the wildland-urban interface near national forests in the American Northwest. The study investigated how key individuals in responder networks anticipated seeking out specific people in perceived bridging roles prior to the occurrence of wildfires, and then captured who in fact assumed these roles during actual large-scale events. It examines two plausible, but contradictory, bodies of theory-similarity and dissimilarity-that suggest who people might seek out as bridgers and who they would really go to during a disaster. Roughly one-half of all pre-fire nominations were consistent with similarity. Yet, while similarity is a reliable indicator of how people expect to organise, it does not hold up for how they organise during the real incident. © 2017 The Author(s). Disasters © Overseas Development Institute, 2017.

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.

Finding The Limit: The Strategic Potential Of The Network Based Actor

DTIC Science & Technology

2016-12-01

6  E.  CASE STUDY SELECTION AND PROCESS .......................................6  1.  Selection of Baseline Case Studies: Pierre-Charles...Pathé and the Trust ..................................................................................7  2.  Selection of Test Case Studies...academic debate, which argues that non-state, network-based actors can have a strategic planning capacity. E. CASE STUDY SELECTION AND PROCESS This

Power structure among the actors of financial support to the poor to access health services: Social network analysis approach.

PubMed

Etemadi, Manal; Gorji, Hasan Abolghasem; Kangarani, Hannaneh Mohammadi; Ashtarian, Kioomars

2017-12-01

The extent of universal health coverage in terms of financial protection is worrisome in Iran. There are challenges in health policies to guarantee financial accessibility to health services, especially for poor people. Various institutions offer support to ensure that the poor have financial access to health services. The aim of this study is to investigate the relationship network among the institutions active in this field. This study is a policy document analysis. It evaluates the country's legal documents in the field of financial support to the poor for healthcare after the Islamic Revolution in Iran. The researchers looked for the documents on the related websites and referred to the related organizations. The social network analysis approach was chosen for the analysis of the documents. Block-modelling and multi-dimensional scaling (MDS) was used to determine the network structures. The UCINET software was employed to analyse the data. Most the main actors of this network are chosen from the government budget. There is no legal communication and cooperation among some of the actors because of their improper position in the network. Seven blocks have been clustered by CONCOR in terms of the actor's degree of similarity. The social distance among the actors of the seven blocks is very short. Power distribution in the field of financial support to the poor has a fragmented structure; however, it is mainly run by a dominant block consisting of The Supreme Council of Welfare and Social Security, Health Insurance Organization, and the Ministry of Health and Medical Education. The financial support for the poor network involves multiple actors. This variety has created a series of confusions in terms of the type, level, and scope of responsibilities among the actors. The weak presence legislative and regulatory institutions and also non-governmental institutions are the main weak points of this network. Copyright © 2017 Elsevier Ltd. All rights reserved.

Labeling Actors and Uncovering Causal Accounts of Their States in Social Networks and Social Media

ERIC Educational Resources Information Center

Bui, Ngot P.

2016-01-01

The emergence of social networks and social media has resulted in exponential increase in the amount of data that link diverse types of richly structured digital objects e.g., individuals, articles, images, videos, music, etc. Such data are naturally represented as heterogeneous networks with multiple types of objects e.g., actors, video,…

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.

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

PubMed

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

2016-09-01

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. 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. 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. More capacity building around strategic action-particularly in nonhealth sectors-is needed to support efforts in making widespread changes to community health.

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

PubMed Central

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

2017-01-01

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

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.

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

An Autonomous Connectivity Restoration Algorithm Based on Finite State Machine for Wireless Sensor-Actor Networks.

PubMed

Zhang, Ying; Wang, Jun; Hao, Guan

2018-01-08

With the development of autonomous unmanned intelligent systems, such as the unmanned boats, unmanned planes and autonomous underwater vehicles, studies on Wireless Sensor-Actor Networks (WSANs) have attracted more attention. Network connectivity algorithms play an important role in data exchange, collaborative detection and information fusion. Due to the harsh application environment, abnormal nodes often appear, and the network connectivity will be prone to be lost. Network self-healing mechanisms have become critical for these systems. In order to decrease the movement overhead of the sensor-actor nodes, an autonomous connectivity restoration algorithm based on finite state machine is proposed. The idea is to identify whether a node is a critical node by using a finite state machine, and update the connected dominating set in a timely way. If an abnormal node is a critical node, the nearest non-critical node will be relocated to replace the abnormal node. In the case of multiple node abnormality, a regional network restoration algorithm is introduced. It is designed to reduce the overhead of node movements while restoration happens. Simulation results indicate the proposed algorithm has better performance on the total moving distance and the number of total relocated nodes compared with some other representative restoration algorithms.

An Autonomous Connectivity Restoration Algorithm Based on Finite State Machine for Wireless Sensor-Actor Networks

PubMed Central

Zhang, Ying; Wang, Jun; Hao, Guan

2018-01-01

With the development of autonomous unmanned intelligent systems, such as the unmanned boats, unmanned planes and autonomous underwater vehicles, studies on Wireless Sensor-Actor Networks (WSANs) have attracted more attention. Network connectivity algorithms play an important role in data exchange, collaborative detection and information fusion. Due to the harsh application environment, abnormal nodes often appear, and the network connectivity will be prone to be lost. Network self-healing mechanisms have become critical for these systems. In order to decrease the movement overhead of the sensor-actor nodes, an autonomous connectivity restoration algorithm based on finite state machine is proposed. The idea is to identify whether a node is a critical node by using a finite state machine, and update the connected dominating set in a timely way. If an abnormal node is a critical node, the nearest non-critical node will be relocated to replace the abnormal node. In the case of multiple node abnormality, a regional network restoration algorithm is introduced. It is designed to reduce the overhead of node movements while restoration happens. Simulation results indicate the proposed algorithm has better performance on the total moving distance and the number of total relocated nodes compared with some other representative restoration algorithms. PMID:29316702

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.

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

2017-07-01

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.

Implementation of evidence-informed practice through central network actors; a case study of three public health units in Canada.

PubMed

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

2017-03-15

Workforce development is an important aspect of evidence-informed decision making (EIDM) interventions. The social position of individuals in formal and informal social networks, and the relevance of formal roles in relation to EIDM are important factors identifying key EIDM players in public health organizations. We assessed the role of central actors in information sharing networks in promoting the adoption of EIDM by the staff of three public health units in Canada, over a two-year period during which an organization-wide intervention was implemented. A multi-faceted and tailored intervention to train select staff applying research evidence in practice was implemented in three public health units in Canada from 2011 to 2013. Staff (n = 572) were asked to identify those in the health unit whom they turned to get help using research in practice, whom they considered as experts in EIDM, and friends. We developed multi-level linear regression models to predict the change in EIDM behavior scores predicted by being connected to peers who were central in networks and were engaged in the intervention. Only the group of highly engaged central actors who were connected to each other, and the staff who were not engaged in the intervention but were connected to highly engaged central actors significantly improved their EIDM behavior scores. Among the latter group, the staff who were also friends with their information sources showed a larger improvement in EIDM behavior. If engaged, central network actors use their formal and informal connections to promote EIDM. Central actors themselves are more likely to adopt EIDM if they communicate with each other. These social communications should be reinforced and supported through the implementation of training interventions as a means to promoting EIDM.

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…

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…

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.

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

PubMed Central

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

2013-01-01

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 were 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 were 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) were 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. PMID:24084068

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

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

PubMed

Hao, Chun; Liu, Hongjie

2015-06-01

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. 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. 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. 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. © The Author(s) 2014.

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. © 2013 American Academy of Forensic Sciences.

Understanding the complex relationships among actors involved in the implementation of public-private mix (PPM) for TB control in India, using social theory.

PubMed

Salve, Solomon; Harris, Kristine; Sheikh, Kabir; Porter, John D H

2018-06-07

Public Private Partnerships (PPP) are increasingly utilized as a public health strategy for strengthening health systems and have become a core component for the delivery of TB control services in India, as promoted through national policy. However, partnerships are complex systems that rely on relationships between a myriad of different actors with divergent agendas and backgrounds. Relationship is a crucial element of governance, and relationship building an important aspect of partnerships. To understand PPPs a multi-disciplinary perspective that draws on insights from social theory is needed. This paper demonstrates how social theory can aid the understanding of the complex relationships of actors involved in implementation of Public-Private Mix (PPM)-TB policy in India. Ethnographic research was conducted within a district in a Southern state of India over a 14 month period, combining participant observations, informal interactions and in-depth interviews with a wide range of respondents across public, private and non-government organisation (NGO) sectors. Drawing on the theoretical insights from Bourdieu's "theory of practice" this study explores the relationships between the different actors. The study found that programme managers, frontline TB workers, NGOs, and private practitioners all had a crucial role to play in TB partnerships. They were widely regarded as valued contributors with distinct social skills and capabilities within their organizations and professions. However, their potential contributions towards programme implementation tended to be unrecognized both at the top and bottom of the policy implementation chain. These actors constantly struggled for recognition and used different mechanisms to position themselves alongside other actors within the programme that further complicated the relationships between different actors. This paper demonstrates that applying social theory can enable a better understanding of the complex relationship

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…

Produsage in hybrid networks: sociotechnical skills in the case of Arduino

NASA Astrophysics Data System (ADS)

De Paoli, Stefano; Storni, Cristiano

2011-04-01

In 1this paper we investigate produsage using Actor-Network Theory with a focus on (produsage) skills, their development, and transformation. We argue that produsage is not a model that determines a change in the traditional consumption/production paradigm through a series of essential preconditions (such as open participation, peer-sharing, or common ownership). Rather, we explain produsage as the open-ended result of a series of heterogeneous actor-networking strategies. In this view, the so-called preconditions do not explain produsage but have to be explained along with its establishment as an actor-network. Drawing on this approach, we discuss a case study of an open hardware project: the Arduino board, and we develop a perspective that maps the skills of human and non-human entities in produsage actor-networks, showing how skills are symmetrical, relational, and circulating.

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…

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

ERIC Educational Resources Information Center

Gaskell, Jim; Hepburn, Gary

1998-01-01

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

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

Analysing barriers to service improvement using a multi-level theory of innovation: the case of glaucoma outpatient clinics.

PubMed

Turner, Simon; Vasilakis, Christos; Utley, Martin; Foster, Paul; Kotecha, Aachal; Fulop, Naomi J

2018-05-01

The development and implementation of innovation by healthcare providers is understood as a multi-determinant and multi-level process. Theories at different analytical levels (i.e. micro and organisational) are needed to capture the processes that influence innovation by providers. This article combines a micro theory of innovation, actor-network theory, with organisational level processes using the 'resource based view of the firm'. It examines the influence of, and interplay between, innovation-seeking teams (micro) and underlying organisational capabilities (meso) during innovation processes. We used ethnographic methods to study service innovations in relation to ophthalmology services run by a specialist English NHS Trust at multiple locations. Operational research techniques were used to support the ethnographic methods by mapping the care process in the existing and redesigned clinics. Deficiencies in organisational capabilities for supporting innovation were identified, including manager-clinician relations and organisation-wide resources. The article concludes that actor-network theory can be combined with the resource-based view to highlight the influence of organisational capabilities on the management of innovation. Equally, actor-network theory helps to address the lack of theory in the resource-based view on the micro practices of implementing change. © 2018 The Authors. Sociology of Health & Illness published by John Wiley & Sons Ltd on behalf of Foundation for SHIL.

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…

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…

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

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

PubMed Central

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

2015-01-01

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

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

PubMed

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

2015-05-01

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

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.

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…

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

PubMed

Green, Janet; Wyllie, Aileen; Jackson, Debra

2014-01-01

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

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).

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

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.

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.

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…

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.

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…

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.

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…

Nonlinear adaptive networks: A little theory, a few applications

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

Jones, R.D.; Qian, S.; Barnes, C.W.

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.

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.

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…

A theory-based model of translation practices in public health participatory research.

PubMed

Clavier, Carole; Sénéchal, Yan; Vibert, Stéphane; Potvin, Louise

2012-06-01

This article explores the innovative practices of actors specifically mandated to support interactions between academic researchers and their partners from the community during public health participatory research. Drawing on the concept of translation as developed in actor-network theory and found in the literature on knowledge transfer and the sociology of intermediate actors, we build a theory-based model of the translation practices developed by these actors at the interface between community and university. We refine this model by using it to analyse material from two focus groups comprising participants purposively selected because they work at the nexus between research and practice. Our model of translation practices includes cognitive (dealing with the contents of the research), strategic (geared to facilitating the research process and balancing power relationships among the partners) and logistic practices (the hands-on tasks of coordination). Combined, these three types of translation practices demonstrate that actors working at the interface in participatory research contribute to multidirectional exchanges and the co-construction of knowledge among research partners. Beyond the case of participatory research, theorising translation practices helps understand how knowledge is produced at the interface between academic and experiential (or lay) knowledge. © 2011 The Authors. Sociology of Health & Illness © 2011 Foundation for the Sociology of Health & Illness/Blackwell Publishing Ltd.

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.

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

Brain and Cognitive Reserve: Translation via Network Control Theory

PubMed Central

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

2017-01-01

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. PMID:28104411

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

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

Multi-actor involvement for integrating ecosystem services in strategic environmental assessment of spatial plans

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

Rozas-Vásquez, Daniel, E-mail: danielrozas@gmail.com; Laboratorio de Planificación Territorial, Universidad Católica de Temuco, Rudecindo ortega, 02950 Temuco; Fürst, Christine

Integrating an ecosystem services (ES) approach into Strategic Environmental Assessment (SEA) of spatial plans potentially enhances the consideration of the value of nature in decision making and policy processes. However, there is increasing concern about the institutional context and a lack of a common understanding of SEA and ecosystem services for adopting them as an integrated framework. This paper addresses this concern by analysing the current understanding and network relations in a multi-actor arrangement as a first step towards a successful integration of ES in SEA and spatial planning. Our analysis focuses on a case study in Chile, where wemore » administered a questionnaire survey to some of the main actors involved in the spatial planning process. The questionnaire focused on issues such as network relations among actors and on conceptual understanding, perceptions and challenges for integrating ES in SEA and spatial planning, knowledge on methodological approaches, and the connections and gaps in the science-policy interface. Our findings suggest that a common understanding of SEA and especially of ES in a context of multiple actors is still at an initial stage in Chile. Additionally, the lack of institutional guidelines and methodological support is considered the main challenge for integration. We conclude that preconditions exist in Chile for integrating ES in SEA for spatial planning, but they strongly depend on appropriate governance schemes that promote a close science-policy interaction, as well as collaborative work and learning. - Highlights: • Linking ecosystem services in SEA is an effective framework for sustainability. • Multi-actor understanding and networks in ecosystem services and SEA were analyzed. • Understanding of SEA and especially of ES is still in an initial stage in Chile. • A lack of institutional guidelines is one of the key challenges for this link.« less

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. Copyright © 2016 Elsevier Ltd. All rights reserved.

Zika in Twitter: Temporal Variations of Locations, Actors, and Concepts

PubMed Central

Vraga, Emily; Lamprianidis, Georgios; Radzikowski, Jacek; Delamater, Paul L; Jacobsen, Kathryn H; Pfoser, Dieter; Croitoru, Arie; Crooks, Andrew

2017-01-01

Background The recent Zika outbreak witnessed the disease evolving from a regional health concern to a global epidemic. During this process, different communities across the globe became involved in Twitter, discussing the disease and key issues associated with it. This paper presents a study of this discussion in Twitter, at the nexus of location, actors, and concepts. Objective Our objective in this study was to demonstrate the significance of 3 types of events: location related, actor related, and concept related, for understanding how a public health emergency of international concern plays out in social media, and Twitter in particular. Accordingly, the study contributes to research efforts toward gaining insights on the mechanisms that drive participation, contributions, and interaction in this social media platform during a disease outbreak. Methods We collected 6,249,626 tweets referring to the Zika outbreak over a period of 12 weeks early in the outbreak (December 2015 through March 2016). We analyzed this data corpus in terms of its geographical footprint, the actors participating in the discourse, and emerging concepts associated with the issue. Data were visualized and evaluated with spatiotemporal and network analysis tools to capture the evolution of interest on the topic and to reveal connections between locations, actors, and concepts in the form of interaction networks. Results The spatiotemporal analysis of Twitter contributions reflects the spread of interest in Zika from its original hotspot in South America to North America and then across the globe. The Centers for Disease Control and World Health Organization had a prominent presence in social media discussions. Tweets about pregnancy and abortion increased as more information about this emerging infectious disease was presented to the public and public figures became involved in this. Conclusions The results of this study show the utility of analyzing temporal variations in the analytic

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.

Ideas, actors and institutions: lessons from South Australian Health in All Policies on what encourages other sectors' involvement.

PubMed

Baum, Fran; Delany-Crowe, Toni; MacDougall, Colin; Lawless, Angela; van Eyk, Helen; Williams, Carmel

2017-10-16

This paper examines the extent to which actors from sectors other than health engaged with the South Australian Health in All Policies (HiAP) initiative, determines why they were prepared to do so and explains the mechanisms by which successful engagement happened. This examination applies theories of policy development and implementation. The paper draws on a five year study of the implementation of HiAP comprising document analysis, a log of key events, detailed interviews with 64 policy actors and two surveys of public servants. The findings are analysed within an institutional policy analysis framework and examine the extent to which ideas, institutional factors and actor agency influenced the willingness of actors from other sectors to work with Health sector staff under the HiAP initiative. In terms of ideas, there was wide acceptance of the role of social determinants in shaping health and the importance of action to promote health in all government agencies. The institutional environment was initially supportive, but support waned over the course of the study when the economy in South Australia became less buoyant and a health minister less supportive of health promotion took office. The existence of a HiAP Unit was very helpful for gaining support from other sectors. A new Public Health Act offered some promise of institutionalising the HiAP approach and ideas. The analysis concludes that a key factor was the operation of a supportive network of public servants who promoted HiAP, including some who were senior and influential. The South Australian case study demonstrates that despite institutional constraints and shifting political support within the health sector, HiAP gained traction in other sectors. The key factors that encouraged the commitment of others sectors to HiAP were the existence of a supportive, knowledgeable policy network, political support, institutionalisation of the ideas and approach, and balancing of the economic and social goals of

Renormalization group theory for percolation in time-varying networks.

PubMed

Karschau, Jens; Zimmerling, Marco; Friedrich, Benjamin M

2018-05-22

Motivated by multi-hop communication in unreliable wireless networks, we present a percolation theory for time-varying networks. We develop a renormalization group theory for a prototypical network on a regular grid, where individual links switch stochastically between active and inactive states. The question whether a given source node can communicate with a destination node along paths of active links is equivalent to a percolation problem. Our theory maps the temporal existence of multi-hop paths on an effective two-state Markov process. We show analytically how this Markov process converges towards a memoryless Bernoulli process as the hop distance between source and destination node increases. Our work extends classical percolation theory to the dynamic case and elucidates temporal correlations of message losses. Quantification of temporal correlations has implications for the design of wireless communication and control protocols, e.g. in cyber-physical systems such as self-organized swarms of drones or smart traffic networks.

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…

Actor Diversity and Interactions in the Development of Banana Hybrid Varieties in Uganda: Implications for Technology Uptake

ERIC Educational Resources Information Center

Sanya, Losira Nasirumbi; Sseguya, Haroon; Kyazze, Florence Birungi; Baguma, Yona; Kibwika, Paul

2018-01-01

Purpose: We examine the nature of networks through which new hybrid banana varieties (HBVs) in Uganda are developed, and how different actors engage in the technology development process. Design/methodology/approach: We collected the data through 20 key informant interviews and 5 focus group discussions with actors involved in the process. We…

Towards the Integration of Niche and Network Theories.

PubMed

Godoy, Oscar; Bartomeus, Ignasi; Rohr, Rudolf P; Saavedra, Serguei

2018-04-01

The quest for understanding how species interactions modulate diversity has progressed by theoretical and empirical advances following niche and network theories. Yet, niche studies have been limited to describe coexistence within tropic levels despite incorporating information about multi-trophic interactions. Network approaches could address this limitation, but they have ignored the structure of species interactions within trophic levels. Here we call for the integration of niche and network theories to reach new frontiers of knowledge exploring how interactions within and across trophic levels promote species coexistence. This integration is possible due to the strong parallelisms in the historical development, ecological concepts, and associated mathematical tools of both theories. We provide a guideline to integrate this framework with observational and experimental studies. Copyright © 2018 Elsevier Ltd. All rights reserved.

How Might Better Network Theories Support School Leadership Research?

ERIC Educational Resources Information Center

Hadfield, Mark; Jopling, Michael

2012-01-01

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

Why do policies change? Institutions, interests, ideas and networks in three cases of policy reform

PubMed Central

Shearer, Jessica C; Abelson, Julia; Kouyaté, Bocar; Lavis, John N; Walt, Gill

2016-01-01

Abstract Policy researchers have used various categories of variables to explain why policies change, including those related to institutions, interests and ideas. Recent research has paid growing attention to the role of policy networks—the actors involved in policy-making, their relationships with each other, and the structure formed by those relationships—in policy reform across settings and issues; however, this literature has largely ignored the theoretical integration of networks with other policy theories, including the ‘3Is’ of institutions, interests and ideas. This article proposes a conceptual framework integrating these variables and tests it on three cases of policy change in Burkina Faso, addressing the need for theoretical integration with networks as well as the broader aim of theory-driven health policy analysis research in low- and middle-income countries. We use historical process tracing, a type of comparative case study, to interpret and compare documents and in-depth interview data within and between cases. We found that while network changes were indeed associated with policy reform, this relationship was mediated by one or more of institutions, interests and ideas. In a context of high donor dependency, new donor rules affected the composition and structure of actors in the networks, which enabled the entry and dissemination of new ideas and shifts in the overall balance of interest power ultimately leading to policy change. The case of strategic networking occurred in only one case, by civil society actors, suggesting that network change is rarely the spark that initiates the process towards policy change. This analysis highlights the important role of changes in institutions and ideas to drive policymaking, but hints that network change is a necessary intermediate step in these processes. PMID:27233927

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…

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.

Zika in Twitter: Temporal Variations of Locations, Actors, and Concepts.

PubMed

Stefanidis, Anthony; Vraga, Emily; Lamprianidis, Georgios; Radzikowski, Jacek; Delamater, Paul L; Jacobsen, Kathryn H; Pfoser, Dieter; Croitoru, Arie; Crooks, Andrew

2017-04-20

The recent Zika outbreak witnessed the disease evolving from a regional health concern to a global epidemic. During this process, different communities across the globe became involved in Twitter, discussing the disease and key issues associated with it. This paper presents a study of this discussion in Twitter, at the nexus of location, actors, and concepts. Our objective in this study was to demonstrate the significance of 3 types of events: location related, actor related, and concept related, for understanding how a public health emergency of international concern plays out in social media, and Twitter in particular. Accordingly, the study contributes to research efforts toward gaining insights on the mechanisms that drive participation, contributions, and interaction in this social media platform during a disease outbreak. We collected 6,249,626 tweets referring to the Zika outbreak over a period of 12 weeks early in the outbreak (December 2015 through March 2016). We analyzed this data corpus in terms of its geographical footprint, the actors participating in the discourse, and emerging concepts associated with the issue. Data were visualized and evaluated with spatiotemporal and network analysis tools to capture the evolution of interest on the topic and to reveal connections between locations, actors, and concepts in the form of interaction networks. The spatiotemporal analysis of Twitter contributions reflects the spread of interest in Zika from its original hotspot in South America to North America and then across the globe. The Centers for Disease Control and World Health Organization had a prominent presence in social media discussions. Tweets about pregnancy and abortion increased as more information about this emerging infectious disease was presented to the public and public figures became involved in this. The results of this study show the utility of analyzing temporal variations in the analytic triad of locations, actors, and concepts. This

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.

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.

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

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.

Detection of network attacks based on adaptive resonance theory

NASA Astrophysics Data System (ADS)

Bukhanov, D. G.; Polyakov, V. M.

2018-05-01

The paper considers an approach to intrusion detection systems using a neural network of adaptive resonant theory. It suggests the structure of an intrusion detection system consisting of two types of program modules. The first module manages connections of user applications by preventing the undesirable ones. The second analyzes the incoming network traffic parameters to check potential network attacks. After attack detection, it notifies the required stations using a secure transmission channel. The paper describes the experiment on the detection and recognition of network attacks using the test selection. It also compares the obtained results with similar experiments carried out by other authors. It gives findings and conclusions on the sufficiency of the proposed approach. The obtained information confirms the sufficiency of applying the neural networks of adaptive resonant theory to analyze network traffic within the intrusion detection system.

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…

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

Scaling theory for information networks.

PubMed

Moses, Melanie E; Forrest, Stephanie; Davis, Alan L; Lodder, Mike A; Brown, James H

2008-12-06

Networks distribute energy, materials and information to the components of a variety of natural and human-engineered systems, including organisms, brains, the Internet and microprocessors. Distribution networks enable the integrated and coordinated functioning of these systems, and they also constrain their design. The similar hierarchical branching networks observed in organisms and microprocessors are striking, given that the structure of organisms has evolved via natural selection, while microprocessors are designed by engineers. Metabolic scaling theory (MST) shows that the rate at which networks deliver energy to an organism is proportional to its mass raised to the 3/4 power. We show that computational systems are also characterized by nonlinear network scaling and use MST principles to characterize how information networks scale, focusing on how MST predicts properties of clock distribution networks in microprocessors. The MST equations are modified to account for variation in the size and density of transistors and terminal wires in microprocessors. Based on the scaling of the clock distribution network, we predict a set of trade-offs and performance properties that scale with chip size and the number of transistors. However, there are systematic deviations between power requirements on microprocessors and predictions derived directly from MST. These deviations are addressed by augmenting the model to account for decentralized flow in some microprocessor networks (e.g. in logic networks). More generally, we hypothesize a set of constraints between the size, power and performance of networked information systems including transistors on chips, hosts on the Internet and neurons in the brain.

Why do policies change? Institutions, interests, ideas and networks in three cases of policy reform.

PubMed

Shearer, Jessica C; Abelson, Julia; Kouyaté, Bocar; Lavis, John N; Walt, Gill

2016-11-01

Policy researchers have used various categories of variables to explain why policies change, including those related to institutions, interests and ideas. Recent research has paid growing attention to the role of policy networks-the actors involved in policy-making, their relationships with each other, and the structure formed by those relationships-in policy reform across settings and issues; however, this literature has largely ignored the theoretical integration of networks with other policy theories, including the '3Is' of institutions, interests and ideas. This article proposes a conceptual framework integrating these variables and tests it on three cases of policy change in Burkina Faso, addressing the need for theoretical integration with networks as well as the broader aim of theory-driven health policy analysis research in low- and middle-income countries. We use historical process tracing, a type of comparative case study, to interpret and compare documents and in-depth interview data within and between cases. We found that while network changes were indeed associated with policy reform, this relationship was mediated by one or more of institutions, interests and ideas. In a context of high donor dependency, new donor rules affected the composition and structure of actors in the networks, which enabled the entry and dissemination of new ideas and shifts in the overall balance of interest power ultimately leading to policy change. The case of strategic networking occurred in only one case, by civil society actors, suggesting that network change is rarely the spark that initiates the process towards policy change. This analysis highlights the important role of changes in institutions and ideas to drive policymaking, but hints that network change is a necessary intermediate step in these processes. © The Author 2016. Published by Oxford University Press in association with The London School of Hygiene and Tropical Medicine. All rights reserved. For

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…

Quality of Care as an Emergent Phenomenon out of a Small-World Network of Relational Actors.

PubMed

Fiorini, Rodolfo; De Giacomo, Piero; Marconi, Pier Luigi; L'Abate, Luciano

2014-01-01

In Healthcare Decision Support System, the development and evaluation of effective "Quality of Care" (QOC) indicators, in simulation-based training, are key feature to develop resilient and antifragile organization scenarios. Is it possible to conceive of QOC not only as a result of a voluntary and rational decision, imposed or even not, but also as an overall system "emergent phenomenon" out of a small-world network of relational synthetic actors, endowed with their own personality profiles to simulate human behaviour (for short, called "subjects")? In order to answer this question and to observe the phenomena of real emergence we should use computational models of high complexity, with heavy computational load and extensive computational time. Nevertheless, De Giacomo's Elementary Pragmatic Model (EPM) intrinsic self-reflexive functional logical closure enables to run simulation examples to classify the outcomes grown out of a small-world network of relational subjects fast and effectively. Therefore, it is possible to take note and to learn of how much strategic systemic interventions can induce context conditions of QOC facilitation, which can improve the effectiveness of specific actions, which otherwise might be paradoxically counterproductive also. Early results are so encouraging to use EPM as basic block to start designing more powerful Evolutive Elementary Pragmatic Model (E2PM) for real emergence computational model, to cope with ontological uncertainty at system level.

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.

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

PubMed

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

2018-04-01

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.

Modeling Temporal Variation in Social Network: An Evolutionary Web Graph Approach

NASA Astrophysics Data System (ADS)

Mitra, Susanta; Bagchi, Aditya

A social network is a social structure between actors (individuals, organization or other social entities) and indicates the ways in which they are connected through various social relationships like friendships, kinships, professional, academic etc. Usually, a social network represents a social community, like a club and its members or a city and its citizens etc. or a research group communicating over Internet. In seventies Leinhardt [1] first proposed the idea of representing a social community by a digraph. Later, this idea became popular among other research workers like, network designers, web-service application developers and e-learning modelers. It gave rise to a rapid proliferation of research work in the area of social network analysis. Some of the notable structural properties of a social network are connectedness between actors, reachability between a source and a target actor, reciprocity or pair-wise connection between actors with bi-directional links, centrality of actors or the important actors having high degree or more connections and finally the division of actors into sub-structures or cliques or strongly-connected components. The cycles present in a social network may even be nested [2, 3]. The formal definition of these structural properties will be provided in Sect. 8.2.1. The division of actors into cliques or sub-groups can be a very important factor for understanding a social structure, particularly the degree of cohesiveness in a community. The number, size, and connections among the sub-groups in a network are useful in understanding how the network, as a whole, is likely to behave.

Finding influential nodes for integration in brain networks using optimal percolation theory.

PubMed

Del Ferraro, Gino; Moreno, Andrea; Min, Byungjoon; Morone, Flaviano; Pérez-Ramírez, Úrsula; Pérez-Cervera, Laura; Parra, Lucas C; Holodny, Andrei; Canals, Santiago; Makse, Hernán A

2018-06-11

Global integration of information in the brain results from complex interactions of segregated brain networks. Identifying the most influential neuronal populations that efficiently bind these networks is a fundamental problem of systems neuroscience. Here, we apply optimal percolation theory and pharmacogenetic interventions in vivo to predict and subsequently target nodes that are essential for global integration of a memory network in rodents. The theory predicts that integration in the memory network is mediated by a set of low-degree nodes located in the nucleus accumbens. This result is confirmed with pharmacogenetic inactivation of the nucleus accumbens, which eliminates the formation of the memory network, while inactivations of other brain areas leave the network intact. Thus, optimal percolation theory predicts essential nodes in brain networks. This could be used to identify targets of interventions to modulate brain function.

Education as networking: Rethinking the success of the harm reduction policy of Taiwan.

PubMed

Chen, Jia-shin

2015-05-01

The harm reduction policy of Taiwan has been considered a success. However, the HIV incidence among injection drug users declined before the nationwide needle and syringe program and drug substitution treatments were implemented. Thus, other factors in the policy might have contributed to its success. Some authors have suggested that education may have played a pivotal part. In this research, the purported significance of education in the success of the policy is conceptualized by reviewing the studies on harm reduction in Taiwan and reflecting upon my own fieldwork. Moreover, relevant literature is used as reference to reformulate this notion of education. This article shows that harm reduction education may be conducted in numerous forms, most of which are non-formal, improvisational, and contingent. Non-governmental organizations may play a role, but more actors, strategies, infrastructures, and interactions should be considered. This article draws from actor-network theory and refines the current thesis that attributes the policy success to education by utilizing three reflections, namely, appreciating materiality and spatiality, recognizing covert actors in the networking, and treating education as an outcome rather than a means. In conclusion, looking at education as a form of networking offers theoretical insight that increases understanding of its participants, mechanisms, processes, and permutations. © The Author(s) 2014.

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.

Bootstrapping disaster: The challenge of growing and maintaining a cross-sector collaborative network.

PubMed

Wachhaus, Aaron

This article examines the interaction of nonprofit and private actors with the traditional bureaucratic structures of government in central Pennsylvania&s recovery from hurricane Irene and tropical storm Lee. That effort relied heavily on private and nonprofit organizations as drivers of the response and recovery. The author maps the organizations involved in the recovery effort and explores the impact of the recovery effort on those organizations. A social network analysis was conducted and complemented with follow-up interviews with key actors. The network analysis reveals weak communication between sectors and a reliance on nonprofits to deliver services; interviews uncover the challenges of intersectoral collaboration. The author addresses the successes and limitations of the means by which a network of nonprofit efforts were coordinated with federal and state relief efforts and draw lessons for improving future practices. The author finds that this case deviates from theory in several ways that complicated community response and recovery. In particular, the challenges of developing and maintaining a recovery network while simultaneously delivering services placed great strain on several organizations, as well as on the fledgling network as a whole.

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

PubMed

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

2009-01-01

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

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…

Satisfaction with social networks: an examination of socioemotional selectivity theory across cohorts.

PubMed

Lansford, J E; Sherman, A M; Antonucci, T C

1998-12-01

This study examines L. L. Carstensen's (1993, 1995) socioemotional selectivity theory within and across three cohorts spanning 4 decades. Socioemotional selectivity theory predicts that as individuals age, they narrow their social networks to devote more emotional resources to fewer relationships with close friends and family. Data from 3 cohorts of nationally representative samples were analyzed to determine whether respondents' satisfaction with the size of their social networks differed by age, cohort, or both. Results support socioemotional selectivity theory: More older adults than younger adults were satisfied with the current size of their social networks rather than wanting larger networks. These findings are consistent across all cohorts. Results are discussed with respect to social relationships across the life course.

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

PubMed

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

2016-01-01

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

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. © The Author(s) 2015.

Structural integration and performance of inter-sectoral public health-related policy networks: An analysis across policy phases.

PubMed

Peters, D T J M; Raab, J; Grêaux, K M; Stronks, K; Harting, J

2017-12-01

Inter-sectoral policy networks may be effective in addressing environmental determinants of health with interventions. However, contradictory results are reported on relations between structural network characteristics (i.e., composition and integration) and network performance, such as addressing environmental determinants of health. This study examines these relations in different phases of the policy process. A multiple-case study was performed on four public health-related policy networks. Using a snowball method among network actors, overall and sub-networks per policy phase were identified and the policy sector of each actor was assigned. To operationalise the outcome variable, interventions were classified by the proportion of environmental determinants they addressed. In the overall networks, no relation was found between structural network characteristics and network performance. In most effective cases, the policy development sub-networks were characterised by integration with less interrelations between actors (low cohesion), more equally distributed distances between the actors (low closeness centralisation), and horizontal integration in inter-sectoral cliques. The most effective case had non-public health central actors with less connections in all sub-networks. The results suggest that, to address environmental determinants of health, sub-networks should be inter-sectorally composed in the policy development rather than in the intervention development and implementation phases, and that policy development actors should have the opportunity to connect with other actors, without strong direction from a central actor. Copyright © 2017 Elsevier B.V. All rights reserved.

Capacity to adapt to environmental change: evidence from a network of organizations concerned with increasing wildfire risk

Treesearch

A. Paige Fischer; Lorien Jasny

2017-01-01

Because wildfire size and frequency are expected to increase in many forested areas in the United States, organizations involved in forest and wildfire management could arguably benefit from working together and sharing information to develop strategies for how to adapt to this increasing risk. Social capital theory suggests that actors in cohesive networks are...

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…

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.

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.

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

PubMed Central

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

2010-01-01

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

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

PubMed

Li, Cai; Lowe, Robert; Ziemke, Tom

2013-01-01

The identification of learning mechanisms for locomotion has been the subject of much research for some time but many challenges remain. Dynamic systems theory (DST) offers a novel approach to humanoid learning through environmental interaction. Reinforcement learning (RL) has offered a promising method to adaptively link the dynamic system to the environment it interacts with via a reward-based value system. In this paper, we propose a model that integrates the above perspectives and applies it to the case of a humanoid (NAO) robot learning to walk the ability of which emerges from its value-based interaction with the environment. In the model, a simplified central pattern generator (CPG) architecture inspired by neuroscientific research and DST is integrated with an actor-critic approach to RL (cpg-actor-critic). In the cpg-actor-critic architecture, least-square-temporal-difference based learning converges to the optimal solution quickly by using natural gradient learning and balancing exploration and exploitation. Futhermore, rather than using a traditional (designer-specified) reward it uses a dynamic value function as a stability indicator that adapts to the environment. The results obtained are analyzed using a novel DST-based embodied cognition approach. Learning to walk, from this perspective, is a process of integrating levels of sensorimotor activity and value.

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

PubMed Central

Li, Cai; Lowe, Robert; Ziemke, Tom

2013-01-01

The identification of learning mechanisms for locomotion has been the subject of much research for some time but many challenges remain. Dynamic systems theory (DST) offers a novel approach to humanoid learning through environmental interaction. Reinforcement learning (RL) has offered a promising method to adaptively link the dynamic system to the environment it interacts with via a reward-based value system. In this paper, we propose a model that integrates the above perspectives and applies it to the case of a humanoid (NAO) robot learning to walk the ability of which emerges from its value-based interaction with the environment. In the model, a simplified central pattern generator (CPG) architecture inspired by neuroscientific research and DST is integrated with an actor-critic approach to RL (cpg-actor-critic). In the cpg-actor-critic architecture, least-square-temporal-difference based learning converges to the optimal solution quickly by using natural gradient learning and balancing exploration and exploitation. Futhermore, rather than using a traditional (designer-specified) reward it uses a dynamic value function as a stability indicator that adapts to the environment. The results obtained are analyzed using a novel DST-based embodied cognition approach. Learning to walk, from this perspective, is a process of integrating levels of sensorimotor activity and value. PMID:23675345

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.

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.

Student trajectories in physics: the need for analysis through a socio-cultural lens

NASA Astrophysics Data System (ADS)

Zapata, Mara

2010-09-01

An analysis of student connections through time and space relative to the core discipline of physics is attempted, as viewed through the lens of actor-network-theory, by Antonia Candela. Using lenses of cultural realities, networks, and perceived power in the discourse of one specific university in the capital city of Mexico and one undergraduate physics classroom, the trajectories and itineraries of students are analyzed, relative to a physics professor's pedagogical practices. This ethnographic study then yields comparisons between Mexican undergraduate students and students from the United States. Actor network theory recognizes that the symbiotic relationship existing between an actor and a continuum of space and time is defined by the symbiotic yet interdependent relationships and networks of practice (Lemke in Downward causation: Minds, bodies, and matter 2000). As part of this study and in line with actor-network-theory, human actors and non-human participants were viewed in relation to how subjects acted and were acted upon within networks of practice. Through this forum I reflect on this work with particular focus on the issues of situatedness of actors from a sociocultural perspective and how established networks viewed within this perspective frame and subsequently impact student trajectories and itineraries. In essence I argue for a need to look at a myriad of further complexities driving the symbiotic relationships being analyzed.

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.

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.

Business Model Design from an ANT Perspective: Contributions and Insights of an Open and Living Theory

NASA Astrophysics Data System (ADS)

Costa, Cristina Chuva; da Cunha, Paulo Rupino

The way the Internet has connected millions of users at negligible costs has changed playing field for companies. Several stakeholders can now come together in virtual networks to create innovative business models that would be unfeasible in the physical world. However, the more radical the departure from the established models of value creation, the bigger the complexity in ensuring the sustained interest of the involved parties and the stability of the bonds. To address this problem, we sought inspiration in the Actor-Network Theory (ANT), which is capable of providing insights into socio-technical settings where human and non-human agents interact. We describe how several of its principles, ideas, and concepts were adapted and embedded in our approach for complex business model design or analysis. A simple illustration is provided. Our iterative approach helps systematically scrutinize and tune the contributions and returns of the various actors, ensuring that all end up with an attractive value proposal, thus promoting the robustness of the network. Guidelines for the services that an underlying information system must provide are also derived from the results.

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.

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.

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.

Theory of correlation in a network with synaptic depression

NASA Astrophysics Data System (ADS)

Igarashi, Yasuhiko; Oizumi, Masafumi; Okada, Masato

2012-01-01

Synaptic depression affects not only the mean responses of neurons but also the correlation of response variability in neural populations. Although previous studies have constructed a theory of correlation in a spiking neuron model by using the mean-field theory framework, synaptic depression has not been taken into consideration. We expanded the previous theoretical framework in this study to spiking neuron models with short-term synaptic depression. On the basis of this theory we analytically calculated neural correlations in a ring attractor network with Mexican-hat-type connectivity, which was used as a model of the primary visual cortex. The results revealed that synaptic depression reduces neural correlation, which could be beneficial for sensory coding. Furthermore, our study opens the way for theoretical studies on the effect of interaction change on the linear response function in large stochastic networks.

Changing Power Actors in a Midwestern Community.

ERIC Educational Resources Information Center

Tait, John L.; And Others

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

Social Network Analysis Identifies Key Participants in Conservation Development.

PubMed

Farr, Cooper M; Reed, Sarah E; Pejchar, Liba

2018-05-01

Understanding patterns of participation in private lands conservation, which is often implemented voluntarily by individual citizens and private organizations, could improve its effectiveness at combating biodiversity loss. We used social network analysis (SNA) to examine participation in conservation development (CD), a private land conservation strategy that clusters houses in a small portion of a property while preserving the remaining land as protected open space. Using data from public records for six counties in Colorado, USA, we compared CD participation patterns among counties and identified actors that most often work with others to implement CDs. We found that social network characteristics differed among counties. The network density, or proportion of connections in the network, varied from fewer than 2 to nearly 15%, and was higher in counties with smaller populations and fewer CDs. Centralization, or the degree to which connections are held disproportionately by a few key actors, was not correlated strongly with any county characteristics. Network characteristics were not correlated with the prevalence of wildlife-friendly design features in CDs. The most highly connected actors were biological and geological consultants, surveyors, and engineers. Our work demonstrates a new application of SNA to land-use planning, in which CD network patterns are examined and key actors are identified. For better conservation outcomes of CD, we recommend using network patterns to guide strategies for outreach and information dissemination, and engaging with highly connected actor types to encourage widespread adoption of best practices for CD design and stewardship.

Building inhabitant feedback: Creating a reflective practice for environmental design using activity theory

NASA Astrophysics Data System (ADS)

Cunningham, Dara Suzanne

The way buildings are designed now, there is little feedback from use involved in the design process. Attempts to correct this problem have been made in the form of Post Occupancy Evaluations (POEs) for 50-years but have largely failed. POEs are the accepted method for environmental designers to collect feedback about buildings in use. They are infrequently conducted, after the building is built, in a one-time only evaluation, and not funded as part of the build process. Other products receive feedback about the design in use from online critiques. Online critiques could provide a platform for feedback from actors engaged with buildings in use for environmental designers to utilize in developing reflective design rationale to avoid adverse consequences in future designs or correct consequences in past and current designs. Since buildings constitute such a large part of the human environment, it's important to research the effects of buildings on their inhabitants. In order for environmental designers to act on feedback from situated use, designers need to have access to that feedback and all actors interacting with the building design need to have an easy, inexpensive, and accessible method to submit feedback. These needs can be addressed by utilizing modern networked and mobile computing to collect and access building feedback. The analysis presented in this dissertation is informed by a thorough evaluation of the theory of reflective practice, activity theory, environmental design, and cognitive science research. From this analysis, I developed the following contributions. First, I expanded Schon's reflective practice by combining his theory with a modified version of activity theory, using activity theory to enrich reflective practice and create Reflective Activity Systems Theory (RAST), which provides a new framework to develop design rationale based on feedback from use and a focus on the activity. Second, I suggest the design of an activity information system

Analyzing complex networks evolution through Information Theory quantifiers

NASA Astrophysics Data System (ADS)

Carpi, Laura C.; Rosso, Osvaldo A.; Saco, Patricia M.; Ravetti, Martín Gómez

2011-01-01

A methodology to analyze dynamical changes in complex networks based on Information Theory quantifiers is proposed. The square root of the Jensen-Shannon divergence, a measure of dissimilarity between two probability distributions, and the MPR Statistical Complexity are used to quantify states in the network evolution process. Three cases are analyzed, the Watts-Strogatz model, a gene network during the progression of Alzheimer's disease and a climate network for the Tropical Pacific region to study the El Niño/Southern Oscillation (ENSO) dynamic. We find that the proposed quantifiers are able not only to capture changes in the dynamics of the processes but also to quantify and compare states in their evolution.

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…

A Low-cost System for Generating Near-realistic Virtual Actors

NASA Astrophysics Data System (ADS)

Afifi, Mahmoud; Hussain, Khaled F.; Ibrahim, Hosny M.; Omar, Nagwa M.

2015-06-01

Generating virtual actors is one of the most challenging fields in computer graphics. The reconstruction of a realistic virtual actor has been paid attention by the academic research and the film industry to generate human-like virtual actors. Many movies were acted by human-like virtual actors, where the audience cannot distinguish between real and virtual actors. The synthesis of realistic virtual actors is considered a complex process. Many techniques are used to generate a realistic virtual actor; however they usually require expensive hardware equipment. In this paper, a low-cost system that generates near-realistic virtual actors is presented. The facial features of the real actor are blended with a virtual head that is attached to the actor's body. Comparing with other techniques that generate virtual actors, the proposed system is considered a low-cost system that requires only one camera that records the scene without using any expensive hardware equipment. The results of our system show that the system generates good near-realistic virtual actors that can be used on many applications.

Dynamical Graph Theory Networks Methods for the Analysis of Sparse Functional Connectivity Networks and for Determining Pinning Observability in Brain Networks

PubMed Central

Meyer-Bäse, Anke; Roberts, Rodney G.; Illan, Ignacio A.; Meyer-Bäse, Uwe; Lobbes, Marc; Stadlbauer, Andreas; Pinker-Domenig, Katja

2017-01-01

Neuroimaging in combination with graph theory has been successful in analyzing the functional connectome. However almost all analysis are performed based on static graph theory. The derived quantitative graph measures can only describe a snap shot of the disease over time. Neurodegenerative disease evolution is poorly understood and treatment strategies are consequently only of limited efficiency. Fusing modern dynamic graph network theory techniques and modeling strategies at different time scales with pinning observability of complex brain networks will lay the foundation for a transformational paradigm in neurodegnerative diseases research regarding disease evolution at the patient level, treatment response evaluation and revealing some central mechanism in a network that drives alterations in these diseases. We model and analyze brain networks as two-time scale sparse dynamic graph networks with hubs (clusters) representing the fast sub-system and the interconnections between hubs the slow sub-system. Alterations in brain function as seen in dementia can be dynamically modeled by determining the clusters in which disturbance inputs have entered and the impact they have on the large-scale dementia dynamic system. Observing a small fraction of specific nodes in dementia networks such that the others can be recovered is accomplished by the novel concept of pinning observability. In addition, how to control this complex network seems to be crucial in understanding the progressive abnormal neural circuits in many neurodegenerative diseases. Detecting the controlling regions in the networks, which serve as key nodes to control the aberrant dynamics of the networks to a desired state and thus influence the progressive abnormal behavior, will have a huge impact in understanding and developing therapeutic solutions and also will provide useful information about the trajectory of the disease. In this paper, we present the theoretical framework and derive the necessary

Dynamical Graph Theory Networks Methods for the Analysis of Sparse Functional Connectivity Networks and for Determining Pinning Observability in Brain Networks.

PubMed

Meyer-Bäse, Anke; Roberts, Rodney G; Illan, Ignacio A; Meyer-Bäse, Uwe; Lobbes, Marc; Stadlbauer, Andreas; Pinker-Domenig, Katja

2017-01-01

Neuroimaging in combination with graph theory has been successful in analyzing the functional connectome. However almost all analysis are performed based on static graph theory. The derived quantitative graph measures can only describe a snap shot of the disease over time. Neurodegenerative disease evolution is poorly understood and treatment strategies are consequently only of limited efficiency. Fusing modern dynamic graph network theory techniques and modeling strategies at different time scales with pinning observability of complex brain networks will lay the foundation for a transformational paradigm in neurodegnerative diseases research regarding disease evolution at the patient level, treatment response evaluation and revealing some central mechanism in a network that drives alterations in these diseases. We model and analyze brain networks as two-time scale sparse dynamic graph networks with hubs (clusters) representing the fast sub-system and the interconnections between hubs the slow sub-system. Alterations in brain function as seen in dementia can be dynamically modeled by determining the clusters in which disturbance inputs have entered and the impact they have on the large-scale dementia dynamic system. Observing a small fraction of specific nodes in dementia networks such that the others can be recovered is accomplished by the novel concept of pinning observability. In addition, how to control this complex network seems to be crucial in understanding the progressive abnormal neural circuits in many neurodegenerative diseases. Detecting the controlling regions in the networks, which serve as key nodes to control the aberrant dynamics of the networks to a desired state and thus influence the progressive abnormal behavior, will have a huge impact in understanding and developing therapeutic solutions and also will provide useful information about the trajectory of the disease. In this paper, we present the theoretical framework and derive the necessary

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

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

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.

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…

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.

Teacher Educator Changing Perceptions of Theory

ERIC Educational Resources Information Center

Smith, Kim; Hodson, Elaine; Brown, Tony

2013-01-01

An alternative formulation of the actor in educational action research is shown to refresh notions of theory within initial teacher education. Methodologically, the actor is depicted as identifying with ongoing cultural adjustments through reflective data. Specifically, the paper considers the experience of mature trainee teachers in the United…

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

Use of actors as standardized psychiatric patients.

PubMed

Keltner, Norman L; Grant, Joan S; McLernon, Dennis

2011-05-01

Using actors in simulation provides opportunities for immersive, interactive, and reflective experiences to improve health care professionals' clinical expertise and practice. These experiences facilitate the development of enhanced critical thinking, problem-solving, and communication skills without risks to patients. This article discusses how to integrate actors and students into simulated experiences. Examples are provided using mental health simulations with actors as standardized psychiatric patients. Copyright 2011, SLACK Incorporated.

Voice disorders in actors.

PubMed

Lerner, Michael Z; Paskhover, Boris; Acton, Lynn; Young, Nwanmegha

2013-11-01

The purpose of this study was to investigate the prevalence of vocal pathology among first-year acting students. A retrospective review of 30 first-year graduate-level drama students between 2009 and 2011 was performed. Stroboscopy, Voice Handicap Index-10 questionnaires, and acoustic measures were analyzed. The prevalence of incomplete glottal closure, laryngeal hyperfunction, and decreased mucosal wave was 62%, 59%, and 55%, respectively. Laryngoscopic findings consistent with laryngopharyngeal reflux (LPR) were demonstrated in 48% of subjects. Subgroup analysis of laryngeal hyperfunctioning (HF) and nonhyperfunctioning drama students revealed an increased prevalence of all videostroboscopic abnormalities in the HF group. The increased prevalence of LPR stigmata in HF actors reached statistical significance (P = 0.04). The vocal demands of actors are unique, requiring the effective use of volume, pitch control, and endurance. This is the first study that systematically analyzes the prevalence of vocal pathology in actors. This study will continue throughout their education, anticipating that our feedback along with their vocal training will improve outcomes. Copyright © 2013 The Voice Foundation. Published by Mosby, Inc. All rights reserved.

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.

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…

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.

Environmental governance in China: Interactions between the state and "nonstate actors".

PubMed

Guttman, Dan; Young, Oran; Jing, Yijia; Bramble, Barbara; Bu, Maoliang; Chen, Carmen; Furst, Kathinka; Hu, Tao; Li, Yifei; Logan, Kate; Liu, Lingxuan; Price, Lydia; Spencer, Michael; Suh, Sangwon; Sun, Xiaopu; Tan, Bowen; Wang, Harold; Wang, Xin; Zhang, Juan; Zhang, Xinxin; Zeidan, Rodrigo

2018-08-15

In the West, limited government capacity to solve environmental problems has triggered the rise of a variety of "nonstate actors" to supplement government efforts or provide alternative mechanisms for addressing environmental issues. How does this development - along with our efforts to understand it - map onto environmental governance processes in China? China's efforts to address environmental issues reflect institutionalized governance processes that differ from parallel western processes in ways that have major consequences for domestic environmental governance practices and the governance of China "going abroad." China's governance processes blur the distinction between the state and other actors; the "shadow of the state" is a major factor in all efforts to address environmental issues. The space occupied by nonstate actors in western systems is occupied by shiye danwei ("public service units"), she hui tuanti ("social associations") and e-platforms, all of which have close links to the state. Meanwhile, international NGOs and multinational corporations are also significant players in China. As a result, the mechanisms of influence that produce effects in China differ in important ways from mechanisms familiar from the western experience. This conclusion has far-reaching implications for those seeking to address global environmental concerns, given the importance of China's growing economy and burgeoning network of trade relationships. Copyright © 2018 Elsevier Ltd. All rights reserved.

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.

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.

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.

Network Analysis in Community Psychology: Looking Back, Looking Forward.

PubMed

Neal, Zachary P; Neal, Jennifer Watling

2017-09-01

Network analysis holds promise for community psychology given the field's aim to understand the interplay between individuals and their social contexts. Indeed, because network analysis focuses explicitly on patterns of relationships between actors, its theories and methods are inherently extra-individual in nature and particularly well suited to characterizing social contexts. But, to what extent has community psychology taken advantage of this network analysis as a tool for capturing context? To answer these questions, this study provides a review of the use network analysis in articles published in American Journal of Community Psychology. Looking back, we describe and summarize the ways that network analysis has been employed in community psychology research to understand the range of ways community psychologists have found the technique helpful. Looking forward and paying particular attention to analytic issues identified in past applications, we provide some recommendations drawn from the network analysis literature to facilitate future applications of network analysis in community psychology. © 2017 The Authors. American Journal of Community Psychology published by Wiley Periodicals, Inc. on behalf of Society for Community Research and Action.

Endogenous Molecular-Cellular Network Cancer Theory: A Systems Biology Approach.

PubMed

Wang, Gaowei; Yuan, Ruoshi; Zhu, Xiaomei; Ao, Ping

2018-01-01

In light of ever apparent limitation of the current dominant cancer mutation theory, a quantitative hypothesis for cancer genesis and progression, endogenous molecular-cellular network hypothesis has been proposed from the systems biology perspective, now for more than 10 years. It was intended to include both the genetic and epigenetic causes to understand cancer. Its development enters the stage of meaningful interaction with experimental and clinical data and the limitation of the traditional cancer mutation theory becomes more evident. Under this endogenous network hypothesis, we established a core working network of hepatocellular carcinoma (HCC) according to the hypothesis and quantified the working network by a nonlinear dynamical system. We showed that the two stable states of the working network reproduce the main known features of normal liver and HCC at both the modular and molecular levels. Using endogenous network hypothesis and validated working network, we explored genetic mutation pattern in cancer and potential strategies to cure or relieve HCC from a totally new perspective. Patterns of genetic mutations have been traditionally analyzed by posteriori statistical association approaches in light of traditional cancer mutation theory. One may wonder the possibility of a priori determination of any mutation regularity. Here, we found that based on the endogenous network theory the features of genetic mutations in cancers may be predicted without any prior knowledge of mutation propensities. Normal hepatocyte and cancerous hepatocyte stable states, specified by distinct patterns of expressions or activities of proteins in the network, provide means to directly identify a set of most probable genetic mutations and their effects in HCC. As the key proteins and main interactions in the network are conserved through cell types in an organism, similar mutational features may also be found in other cancers. This analysis yielded straightforward and testable

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

Do People Use Their Implicit Theories of Creativity as General Theories?

ERIC Educational Resources Information Center

Lee, Hong; Kim, Jungsik; Ryu, Yeonjae; Song, Seokjong

2015-01-01

This study examines whether people use the general implicit theories of creativity or not when applying them to themselves and others. On the basis of the actor-observer asymmetry theory, the authors propose that conception of creativity would be differently constructed depending on the targets of attention: general, self, and other. Three studies…

Analytical transport network theory to guide the design of 3-D microstructural networks in energy materials: Part 1. Flow without reactions

NASA Astrophysics Data System (ADS)

Cocco, Alex P.; Nakajo, Arata; Chiu, Wilson K. S.

2017-12-01

We present a fully analytical, heuristic model - the "Analytical Transport Network Model" - for steady-state, diffusive, potential flow through a 3-D network. Employing a combination of graph theory, linear algebra, and geometry, the model explicitly relates a microstructural network's topology and the morphology of its channels to an effective material transport coefficient (a general term meant to encompass, e.g., conductivity or diffusion coefficient). The model's transport coefficient predictions agree well with those from electrochemical fin (ECF) theory and finite element analysis (FEA), but are computed 0.5-1.5 and 5-6 orders of magnitude faster, respectively. In addition, the theory explicitly relates a number of morphological and topological parameters directly to the transport coefficient, whereby the distributions that characterize the structure are readily available for further analysis. Furthermore, ATN's explicit development provides insight into the nature of the tortuosity factor and offers the potential to apply theory from network science and to consider the optimization of a network's effective resistance in a mathematically rigorous manner. The ATN model's speed and relative ease-of-use offer the potential to aid in accelerating the design (with respect to transport), and thus reducing the cost, of energy materials.

Cluster Analysis of Weighted Bipartite Networks: A New Copula-Based Approach

PubMed Central

Chessa, Alessandro; Crimaldi, Irene; Riccaboni, Massimo; Trapin, Luca

2014-01-01

In this work we are interested in identifying clusters of “positional equivalent” actors, i.e. actors who play a similar role in a system. In particular, we analyze weighted bipartite networks that describes the relationships between actors on one side and features or traits on the other, together with the intensity level to which actors show their features. We develop a methodological approach that takes into account the underlying multivariate dependence among groups of actors. The idea is that positions in a network could be defined on the basis of the similar intensity levels that the actors exhibit in expressing some features, instead of just considering relationships that actors hold with each others. Moreover, we propose a new clustering procedure that exploits the potentiality of copula functions, a mathematical instrument for the modelization of the stochastic dependence structure. Our clustering algorithm can be applied both to binary and real-valued matrices. We validate it with simulations and applications to real-world data. PMID:25303095

An Anatomy of Authority: The Bologna and ASEM Education Secretariats as Policy Actors and Region Builders

ERIC Educational Resources Information Center

Dang, Que Anh

2018-01-01

This paper examines the sources of authority behind the Bologna and ASEM secretariats' technocratic appearance and administrative routines, and argues that they are transnational policy actors in their own right. By drawing on principal-agent theory and the concept of "authority," it offers an alternative framework for understanding the…

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.)

Detection of strong attractors in social media networks.

PubMed

Qasem, Ziyaad; Jansen, Marc; Hecking, Tobias; Hoppe, H Ulrich

2016-01-01

Detection of influential actors in social media such as Twitter or Facebook plays an important role for improving the quality and efficiency of work and services in many fields such as education and marketing. The work described here aims to introduce a new approach that characterizes the influence of actors by the strength of attracting new active members into a networked community. We present a model of influence of an actor that is based on the attractiveness of the actor in terms of the number of other new actors with which he or she has established relations over time. We have used this concept and measure of influence to determine optimal seeds in a simulation of influence maximization using two empirically collected social networks for the underlying graphs. Our empirical results on the datasets demonstrate that our measure stands out as a useful measure to define the attractors comparing to the other influence measures.

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.

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.

Parallel Distributed Processing Theory in the Age of Deep Networks.

PubMed

Bowers, Jeffrey S

2017-12-01

Parallel distributed processing (PDP) models in psychology are the precursors of deep networks used in computer science. However, only PDP models are associated with two core psychological claims, namely that all knowledge is coded in a distributed format and cognition is mediated by non-symbolic computations. These claims have long been debated in cognitive science, and recent work with deep networks speaks to this debate. Specifically, single-unit recordings show that deep networks learn units that respond selectively to meaningful categories, and researchers are finding that deep networks need to be supplemented with symbolic systems to perform some tasks. Given the close links between PDP and deep networks, it is surprising that research with deep networks is challenging PDP theory. Copyright © 2017. Published by Elsevier Ltd.

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.

The Best of Both Worlds: The Benefits of Open-specialized and Closed-diverse Syndication Networks for New Ventures' Success.

PubMed

Ter Wal, Anne L J; Alexy, Oliver; Block, Jörn; Sandner, Philipp G

2016-09-01

Open networks give actors non-redundant information that is diverse, while closed networks offer redundant information that is easier to interpret. Integrating arguments about network structure and the similarity of actors' knowledge, we propose two types of network configurations that combine diversity and ease of interpretation. Closed-diverse networks offer diversity in actors' knowledge domains and shared third-party ties to help in interpreting that knowledge. In open-specialized networks, structural holes offer diversity, while shared interpretive schema and overlap between received information and actors' prior knowledge help in interpreting new information without the help of third parties. In contrast, actors in open-diverse networks suffer from information overload due to the lack of shared schema or overlapping prior knowledge for the interpretation of diverse information, and actors in closed-specialized networks suffer from overembeddedness because they cannot access diverse information. Using CrunchBase data on early-stage venture capital investments in the U.S. information technology sector, we test the effect of investors' social capital on the success of their portfolio ventures. We find that ventures have the highest chances of success if their syndicating investors have either open-specialized or closed-diverse networks. These effects are manifested beyond the direct effects of ventures' or investors' quality and are robust to controlling for the possibility that certain investors could have chosen more promising ventures at the time of first funding.

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.

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

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.

Compositional schedulability analysis of real-time actor-based systems.

PubMed

Jaghoori, Mohammad Mahdi; de Boer, Frank; Longuet, Delphine; Chothia, Tom; Sirjani, Marjan

2017-01-01

We present an extension of the actor model with real-time, including deadlines associated with messages, and explicit application-level scheduling policies, e.g.,"earliest deadline first" which can be associated with individual actors. Schedulability analysis in this setting amounts to checking whether, given a scheduling policy for each actor, every task is processed within its designated deadline. To check schedulability, we introduce a compositional automata-theoretic approach, based on maximal use of model checking combined with testing. Behavioral interfaces define what an actor expects from the environment, and the deadlines for messages given these assumptions. We use model checking to verify that actors match their behavioral interfaces. We extend timed automata refinement with the notion of deadlines and use it to define compatibility of actor environments with the behavioral interfaces. Model checking of compatibility is computationally hard, so we propose a special testing process. We show that the analyses are decidable and automate the process using the Uppaal model checker.

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

Implementing multiple intervention strategies in Dutch public health-related policy networks.

PubMed

Harting, Janneke; Peters, Dorothee; Grêaux, Kimberly; van Assema, Patricia; Verweij, Stefan; Stronks, Karien; Klijn, Erik-Hans

2017-10-13

Improving public health requires multiple intervention strategies. Implementing such an intervention mix is supposed to require a multisectoral policy network. As evidence to support this assumption is scarce, we examined under which conditions public health-related policy networks were able to implement an intervention mix. Data were collected (2009-14) from 29 Dutch public health policy networks. Surveys were used to identify the number of policy sectors, participation of actors, level of trust, networking by the project leader, and intervention strategies implemented. Conditions sufficient for an intervention mix (≥3 of 4 non-educational strategies present) were determined in a fuzzy-set qualitative comparative analysis. A multisectoral policy network (≥7 of 14 sectors present) was neither a necessary nor a sufficient condition. In multisectoral networks, additionally required was either the active participation of network actors (≥50% actively involved) or active networking by the project leader (≥monthly contacts with network actors). In policy networks that included few sectors, a high level of trust (positive perceptions of each other's intentions) was needed-in the absence though of any of the other conditions. If the network actors were also actively involved, an extra requirement was active networking by the project leader. We conclude that the multisectoral composition of policy networks can contribute to the implementation of a variety of intervention strategies, but not without additional efforts. However, policy networks that include only few sectors are also able to implement an intervention mix. Here, trust seems to be the most important condition. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

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.

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.

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

ACToR: Aggregated Computational Toxicology Resource (T)

EPA Science Inventory

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

Network Data: Statistical Theory and New Models

DTIC Science & Technology

2016-02-17

SECURITY CLASSIFICATION OF: During this period of review, Bin Yu worked on many thrusts of high-dimensional statistical theory and methodologies. Her...research covered a wide range of topics in statistics including analysis and methods for spectral clustering for sparse and structured networks...2,7,8,21], sparse modeling (e.g. Lasso) [4,10,11,17,18,19], statistical guarantees for the EM algorithm [3], statistical analysis of algorithm leveraging

Mining of the social network extraction

NASA Astrophysics Data System (ADS)

Nasution, M. K. M.; Hardi, M.; Syah, R.

2017-01-01

The use of Web as social media is steadily gaining ground in the study of social actor behaviour. However, information in Web can be interpreted in accordance with the ability of the method such as superficial methods for extracting social networks. Each method however has features and drawbacks: it cannot reveal the behaviour of social actors, but it has the hidden information about them. Therefore, this paper aims to reveal such information in the social networks mining. Social behaviour could be expressed through a set of words extracted from the list of snippets.

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.

Transient response of nonlinear polymer networks: A kinetic theory

NASA Astrophysics Data System (ADS)

Vernerey, Franck J.

2018-06-01

Dynamic networks are found in a majority of natural materials, but also in engineering materials, such as entangled polymers and physically cross-linked gels. Owing to their transient bond dynamics, these networks display a rich class of behaviors, from elasticity, rheology, self-healing, or growth. Although classical theories in rheology and mechanics have enabled us to characterize these materials, there is still a gap in our understanding on how individuals (i.e., the mechanics of each building blocks and its connection with others) affect the emerging response of the network. In this work, we introduce an alternative way to think about these networks from a statistical point of view. More specifically, a network is seen as a collection of individual polymer chains connected by weak bonds that can associate and dissociate over time. From the knowledge of these individual chains (elasticity, transient attachment, and detachment events), we construct a statistical description of the population and derive an evolution equation of their distribution based on applied deformation and their local interactions. We specifically concentrate on nonlinear elastic response that follows from the strain stiffening response of individual chains of finite size. Upon appropriate averaging operations and using a mean field approximation, we show that the distribution can be replaced by a so-called chain distribution tensor that is used to determine important macroscopic measures such as stress, energy storage and dissipation in the network. Prediction of the kinetic theory are then explored against known experimental measurement of polymer responses under uniaxial loading. It is found that even under the simplest assumptions of force-independent chain kinetics, the model is able to reproduce complex time-dependent behaviors of rubber and self-healing supramolecular polymers.

ACToR - Aggregated Computational Toxicology Resource

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

Judson, Richard; Richard, Ann; Dix, David

2008-11-15

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

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

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.

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

Efficient model learning methods for actor-critic control.

PubMed

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

2012-06-01

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

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

PubMed

Corner, Emily; Gill, Paul

2015-02-01

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

Networks, Netwar, and Information-Age Terrorism

DTIC Science & Technology

1999-01-01

intermediate nodes. • The star, hub, or wheel network, as in a franchise or a cartel structure where a set of actors is tied to a central node or actor...Aviv and Jerusalem. On March 21, a Hamas satchel bomb exploded at a Tel Aviv cafe , killing three persons and injuring 48; on July 30, two Hamas

[Social network analysis of interdisciplinary cooperation and networking in early prevention and intervention. A pilot study].

PubMed

Künster, A K; Knorr, C; Fegert, J M; Ziegenhain, U

2010-11-01

Child protection can only be successfully solved by interdisciplinary cooperation and networking. The individual, heterogeneous, and complex needs of families cannot be met sufficiently by one profession alone. To guarantee efficient interdisciplinary cooperation, there should not be any gaps in the network. In addition, each actor in the network should be placed at an optimal position regarding function, responsibilities, and skills. Actors that serve as allocators, such as pediatricians or youth welfare officers, should be in key player positions within the network. Furthermore, successful child protection is preventive and starts early. Social network analysis is an adequate technique to assess network structures and to plan interventions to improve networking. In addition, it is very useful to evaluate the effectiveness of interventions like round tables. We present data from our pilot project which was part of "Guter Start ins Kinderleben" ("a good start into a child's life"). Exemplary network data from one community show that networking is already quite effective with a satisfactory mean density throughout the network. There is potential for improvement in cooperation, especially at the interface between the child welfare and health systems.

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

Tolerance of practices by Muslim actors: an integrative social-developmental perspective.

PubMed

Gieling, Maike; Thijs, Jochem; Verkuyten, Maykel

2010-01-01

Using social-cognitive domain theory and social identity theory, tolerance judgments of practices by Muslim actors among Dutch adolescents (12-17) were investigated. The findings for Study 1 (N=180) demonstrated that participants evaluated 4 practices using different types of reasons: personal, social-conventional, and moral. In Study 2 (N=970), participants were more tolerant of acts considered to be a personal issue than of acts that pertained to moral issues (social-conventional acts were in the middle). Furthermore, participants were more tolerant of the particular practices than of campaigns for public support of co-Muslims for these practices. Level of education, in-group identification, and multiculturalism had much weaker effects in the moral than in the other domains. Age was negatively related to tolerance. © 2010 The Authors. Child Development © 2010 Society for Research in Child Development, Inc.

Impedance learning for robotic contact tasks using natural actor-critic algorithm.

PubMed

Kim, Byungchan; Park, Jooyoung; Park, Shinsuk; Kang, Sungchul

2010-04-01

Compared with their robotic counterparts, humans excel at various tasks by using their ability to adaptively modulate arm impedance parameters. This ability allows us to successfully perform contact tasks even in uncertain environments. This paper considers a learning strategy of motor skill for robotic contact tasks based on a human motor control theory and machine learning schemes. Our robot learning method employs impedance control based on the equilibrium point control theory and reinforcement learning to determine the impedance parameters for contact tasks. A recursive least-square filter-based episodic natural actor-critic algorithm is used to find the optimal impedance parameters. The effectiveness of the proposed method was tested through dynamic simulations of various contact tasks. The simulation results demonstrated that the proposed method optimizes the performance of the contact tasks in uncertain conditions of the environment.

Recollection and unitization in associating actors with extrinsic and intrinsic motions.

PubMed

Kersten, Alan W; Earles, Julie L; Berger, Johanna D

2015-04-01

Four experiments provide evidence for a distinction between 2 different kinds of motion representations. Extrinsic motions involve the path of an object with respect to an external frame of reference. Intrinsic motions involve the relative motions of the parts of an object. This research suggests that intrinsic motions are represented conjointly with information about the identities of the actors who perform them, whereas extrinsic motions are represented separately from identity information. Experiment 1 demonstrated that participants remembered which actor had performed a particular intrinsic motion better than they remembered which actor had performed a particular extrinsic motion. Experiment 2 replicated this effect with incidental encoding of actor information, suggesting that encoding intrinsic motions leads one to automatically encode identity information. The results of Experiments 3 and 4 were fit by Yonelinas's (1999) source-memory model to quantify the contributions of familiarity and recollection to memory for the actors who carried out the intrinsic and extrinsic motions. Successful performance with extrinsic motion items in Experiment 3 required participants to remember in which scene contexts an actor had appeared, whereas successful performance in Experiment 4 required participants to remember the exact path taken by an actor in each scene. In both experiments, discrimination of old and new combinations of actors and extrinsic motions relied strongly on recollection, suggesting independent but associated representations of actors and extrinsic motions. In contrast, participants discriminated old and new combinations of actors and intrinsic motions primarily on the basis of familiarity, suggesting unitized representations of actors and intrinsic motions. (c) 2015 APA, all rights reserved).

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).

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.

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

Adaptive capacity of geographical clusters: Complexity science and network theory approach

NASA Astrophysics Data System (ADS)

Albino, Vito; Carbonara, Nunzia; Giannoccaro, Ilaria

This paper deals with the adaptive capacity of geographical clusters (GCs), that is a relevant topic in the literature. To address this topic, GC is considered as a complex adaptive system (CAS). Three theoretical propositions concerning the GC adaptive capacity are formulated by using complexity theory. First, we identify three main properties of CAS s that affect the adaptive capacity, namely the interconnectivity, the heterogeneity, and the level of control, and define how the value of these properties influence the adaptive capacity. Then, we associate these properties with specific GC characteristics so obtaining the key conditions of GCs that give them the adaptive capacity so assuring their competitive advantage. To test these theoretical propositions, a case study on two real GCs is carried out. The considered GCs are modeled as networks where firms are nodes and inter-firms relationships are links. Heterogeneity, interconnectivity, and level of control are considered as network properties and thus measured by using the methods of the network theory.

ACToR – Aggregated Computational Toxicology Resource ...

EPA Pesticide Factsheets

This presentation reviews the US EPAs reaction to the challenge of the NRC on the future of toxicity testing through the development of the ACTor Project and the ToxRef database. This presentation reviews the US EPAs reaction to the challenge of the NRC on the future of toxicity testing through the development of the ACTor Project and the ToxRef database.

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

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.

The use of nodes attributes in social network analysis with an application to an international trade network

NASA Astrophysics Data System (ADS)

de Andrade, Ricardo Lopes; Rêgo, Leandro Chaves

2018-02-01

The social network analysis (SNA) studies the interactions among actors in a network formed through some relationship (friendship, cooperation, trade, among others). The SNA is constantly approached from a binary point of view, i.e., it is only observed if a link between two actors is present or not regardless of the strength of this link. It is known that different information can be obtained in weighted and unweighted networks and that the information extracted from weighted networks is more accurate and detailed. Another rarely discussed approach in the SNA is related to the individual attributes of the actors (nodes), because such analysis is usually focused on the topological structure of networks. Features of the nodes are not incorporated in the SNA what implies that there is some loss or misperception of information in those analyze. This paper aims at exploring more precisely the complexities of a social network, initially developing a method that inserts the individual attributes in the topological structure of the network and then analyzing the network in four different ways: unweighted, edge-weighted and two methods for using both edge-weights and nodes' attributes. The international trade network was chosen in the application of this approach, where the nodes represent the countries, the links represent the cash flow in the trade transactions and countries' GDP were chosen as nodes' attributes. As a result, it is possible to observe which countries are most connected in the world economy and with higher cash flows, to point out the countries that are central to the intermediation of the wealth flow and those that are most benefited from being included in this network. We also made a principal component analysis to study which metrics are more influential in describing the data variability, which turn out to be mostly the weighted metrics which include the nodes' attributes.

Ordering theories: Typologies and conceptual frameworks for sociotechnical change.

PubMed

Sovacool, Benjamin K; Hess, David J

2017-10-01

What theories or concepts are most useful at explaining socio technical change? How can - or cannot - these be integrated? To provide an answer, this study presents the results from 35 semi-structured research interviews with social science experts who also shared more than two hundred articles, reports and books on the topic of the acceptance, adoption, use, or diffusion of technology. This material led to the identification of 96 theories and conceptual approaches spanning 22 identified disciplines. The article begins by explaining its research terms and methods before honing in on a combination of fourteen theories deemed most relevant and useful by the material. These are: Sociotechnical Transitions, Social Practice Theory, Discourse Theory, Domestication Theory, Large Technical Systems, Social Construction of Technology, Sociotechnical Imaginaries, Actor-Network Theory, Social Justice Theory, Sociology of Expectations, Sustainable Development, Values Beliefs Norms Theory, Lifestyle Theory, and the Unified Theory of Acceptance and Use of Technology. It then positions these theories in terms of two distinct typologies. Theories can be placed into five general categories of being centered on agency, structure, meaning, relations or norms. They can also be classified based on their assumptions and goals rooted in functionalism, interpretivism, humanism or conflict. The article lays out tips for research methodology before concluding with insights about technology itself, analytical processes associated with technology, and the framing and communication of results. An interdisciplinary theoretical and conceptual inventory has much to offer students, analysts and scholars wanting to study technological change and society.

Elastic Network Models For Biomolecular Dynamics: Theory and Application to Membrane Proteins and Viruses

NASA Astrophysics Data System (ADS)

Lezon, Timothy R.; Shrivastava, Indira H.; Yang, Zheng; Bahar, Ivet

The following sections are included: * Introduction * Theory and Assumptions * Statistical mechanical foundations * Anisotropic network models * Gaussian network model * Rigid block models * Treatment of perturbations * Langevin dynamics * Applications * Membrane proteins * Viruses * Conclusion * References

ACToR: Aggregated Computational Toxicology Resource (T) ...

EPA Pesticide Factsheets

The EPA Aggregated Computational Toxicology Resource (ACToR) is a set of databases compiling information on chemicals in the environment from a large number of public and in-house EPA sources. ACToR has 3 main goals: (1) The serve as a repository of public toxicology information on chemicals of interest to the EPA, and in particular to be a central source for the testing data on all chemicals regulated by all EPA programs; (2) To be a source of in vivo training data sets for building in vitro to in vivo computational models; (3) To serve as a central source of chemical structure and identity information for the ToxCastTM and Tox21 programs. There are 4 main databases, all linked through a common set of chemical information and a common structure linking chemicals to assay data: the public ACToR system (available at http://actor.epa.gov), the ToxMiner database holding ToxCast and Tox21 data, along with results form statistical analyses on these data; the Tox21 chemical repository which is managing the ordering and sample tracking process for the larger Tox21 project; and the public version of ToxRefDB. The public ACToR system contains information on ~500K compounds with toxicology, exposure and chemical property information from >400 public sources. The web site is visited by ~1,000 unique users per month and generates ~1,000 page requests per day on average. The databases are built on open source technology, which has allowed us to export them to a number of col

Being around and knowing the players: networks of influence in health policy.

PubMed

Lewis, Jenny M

2006-05-01

The accumulation and use of power is crucial to the health policy process. This paper examines the power of the medical profession in the health policy arena, by analysing which actors are perceived as influential, and how influence is structured in health policy. It combines an analysis of policy networks and social networks, to examine positional and personal influence in health policy in the state of Victoria, Australia. In the sub-graph of the influence network examined here, those most widely regarded as influential are academics, medically qualified and male. Positional actors (the top politician, political advisor and bureaucrat in health and the top nursing official) form part of a core group within this network structure. A second central group consists of medical influentials working in academia, research institutes and health-related NGOs. In this network locale overall, medical academics appear to combine positional and personal influence, and play significant intermediary roles across the network. While many claim that the medical profession has lost power in health policy and politics, this analysis yields few signs that the power of medicine to shape the health policy process has been greatly diminished in Victoria. Medical expertise is a potent embedded resource connecting actors through ties of association, making it difficult for actors with other resources and different knowledge to be considered influential. The network concepts and analytical techniques used here provide a novel means for uncovering different types of influence in health policy.

The Legitimation of Novel Technologies: The Case of Nanotechnology

NASA Astrophysics Data System (ADS)

Thyroff, Anastasia E.

Nanotechnology is the control, manipulation, and application of matter on an atomic and molecular level. The technology is complex and confusing to consumers, and its long-term safety and effect on the human body, as well as the environment, are unknown. However, for the past decade, nanotechnology has been used to develop consumer products and food with novel and attractive attributes. Since nanotechnology is still not well known, it is not legitimized; that is, it has not been deemed safe and accepted by society. However, the market for nanotechnology is in the legitimation process. It will take an entire network of key stakeholders playing a specific roles for nanotechnology to legitimize. Specifically, each key stakeholder will align with a certain cultural discourse to frame nanotechnology in a particular way that complements their values. In Essay 1, I follow previous market system dynamic's literature and combine Actor Network Theory (ANT), Foucault's Discourse on Power and Goffman's Frame analysis to theoretically explore what the actor network for nanotechnology looks like. Four dominate frames are identified: 1) Advancement (i.e., government), 2) Management (i.e., industry), 3) Development (i.e., academia/scientists), and 4) Informant (i.e., NGO). Essay 2 empirically explores each actor's perspective on the nanotechnology network through a total of 24 interviews. A hermeneutic approach is used to analyze the 208 page text and themes describing each actor's role from a self and other's perspective are discussed. Additionally, three overarching themes (i.e., contradiction, constance, and cutoff) emerge; these themes describe the degree of similarity in how actors view their role in the nanotechnology network compared to how other actor's view that actor's role. In Essay 3, I bring critical theory into market system's research to better contextualize market formation theories. Specifically, I discuss how critical theory can be used to supplement ANT. I

[Singing formant analysis of KunQu actors in their mutation and grown-up].

PubMed

Zhu, Mei; Zhang, Dao-Xing; Liu, Yong-Xiang; Yang, Xiao-ju

2005-04-01

To compare the singing formant differences between successful opera actors and non-successful opera actors during their adolescence period, and to compare the same index between adolescence and adult period of successful actors. From 1985 to 1986, the author had 21 adolescent actors' voice recorded, all of them were from Beijing KunQu opera troupe. In 2000, all the 21 subjects had their voice recorded and singing formant (Fs) analyzed by using computer and sound spectrograph, 7 of them had become adult actors, others quitted their actors career after adolescents period. Successful actors have obvious Fs, and stronger acoustic energy; successful actors had weaker Fs value during adolescence period than during adult period (t = 2. 9600, P < 0.05). Fs's presence and its acoustic energy were important to evaluate adolescent actors future locality potential.

Body height and occupational success for actors and actresses.

PubMed

Stieger, Stefan; Burger, Christoph

2010-08-01

The association of body height with occupational success has been frequently studied, with previous research mainly finding a positive effect among men and positive or null effects among women. Occupational success has almost exclusively been measured so far by short-term success variables (e.g., annual income). In the present study, the relationship of success and height was examined in a group of actors and actresses using a large online database about movies (Internet Movie Database) where heights of actors and actresses are stated. The number of roles played in movies and television series during each actor's lifetime was used as a measure of long-term occupational success. No height effect was found for male actors but a significant negative effect was found for actresses, even after controlling for possible confounding influences (age and birth year). Compared to the general population, actors and actresses were significantly taller; however, actresses who were shorter than average were more likely to achieve greater occupational success, in terms of being featured in more movies.

The moral sense of humanitarian actors: an empirical exploration.

PubMed

Rességuier, Anaïs

2018-01-01

This paper examines humanitarianism's moral positioning above private and political interests to save lives and alleviate suffering. It does not aim to assess the legitimacy of this stance, but rather to probe the way in which humanitarian actors relate to this moral dimension in their everyday work. It investigates empirically humanitarian ethics from the perspective of humanitarian actors, drawing on interviews conducted in Beirut, Lebanon, in 2014. As it is exploratory, three key conceptual innovations were required. The first of these is the introduction of the tools developed to consider a neglected reality: humanitarian actors' 'moral sense' vis-à-vis the humanitarian sector's 'moral culture'. Second, the study shows how the sector's moral culture is structured around the notion of 'concern for persons in need'. Third, it analyses the way in which the sector and its actors handle the asymmetrical relationships encountered daily. Ultimately this paper seeks to valorise humanitarian actors' creativity in their common practices and explore potential challenges to it. © 2018 The Author(s). Disasters © Overseas Development Institute, 2018.

Multilayer network decoding versatility and trust

NASA Astrophysics Data System (ADS)

Sarkar, Camellia; Yadav, Alok; Jalan, Sarika

2016-01-01

In the recent years, the multilayer networks have increasingly been realized as a more realistic framework to understand emergent physical phenomena in complex real-world systems. We analyze massive time-varying social data drawn from the largest film industry of the world under a multilayer network framework. The framework enables us to evaluate the versatility of actors, which turns out to be an intrinsic property of lead actors. Versatility in dimers suggests that working with different types of nodes are more beneficial than with similar ones. However, the triangles yield a different relation between type of co-actor and the success of lead nodes indicating the importance of higher-order motifs in understanding the properties of the underlying system. Furthermore, despite the degree-degree correlations of entire networks being neutral, multilayering picks up different values of correlation indicating positive connotations like trust, in the recent years. The analysis of weak ties of the industry uncovers nodes from a lower-degree regime being important in linking Bollywood clusters. The framework and the tools used herein may be used for unraveling the complexity of other real-world systems.

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.

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

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.

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

NASA Astrophysics Data System (ADS)

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

2007-02-01

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

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.

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.

European Schoolnet: Enabling School Networking

ERIC Educational Resources Information Center

Scimeca, Santi; Dumitru, Petru; Durando, Marc; Gilleran, Anne; Joyce, Alexa; Vuorikari, Riina

2009-01-01

School networking is increasingly important in a globalised world, where schools themselves can be actors on an international stage. This article builds on the activities and experience of the longest established European initiative in this area, European Schoolnet (EUN), a network of 31 Ministries of Education. First, we offer an introduction…

Care networking: a study of technical mediations in a home telecare service.

PubMed

Correa, Gonzalo; Domènech, Miquel

2013-07-22

This article examines the processes of technical mediation within familial care networks based on a study of home telecare targeted at older people. Supported by contributions from the actor-network theory as part of the social psychology of science and technology, these processes of technical mediation are analyzed using a qualitative approach. The data were gathered through six focus groups and four in-depth interviews; the participants in the study included users, relatives and formal carers. Thematic analysis techniques encompassing the information were used, revealing the effects on the patterns of caring relationships. The results show the interplay between presence-absence made possible by the devices; the two-way direction of care between the older people and the artifacts; and the process of sustaining care using the technology. We conclude that care should be seen as a socio-technical network where technology plays an active role in sustaining family relationships.

ACToR A Aggregated Computational Toxicology Resource ...

EPA Pesticide Factsheets

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

Actor-critic-based optimal tracking for partially unknown nonlinear discrete-time systems.

PubMed

Kiumarsi, Bahare; Lewis, Frank L

2015-01-01

This paper presents a partially model-free adaptive optimal control solution to the deterministic nonlinear discrete-time (DT) tracking control problem in the presence of input constraints. The tracking error dynamics and reference trajectory dynamics are first combined to form an augmented system. Then, a new discounted performance function based on the augmented system is presented for the optimal nonlinear tracking problem. In contrast to the standard solution, which finds the feedforward and feedback terms of the control input separately, the minimization of the proposed discounted performance function gives both feedback and feedforward parts of the control input simultaneously. This enables us to encode the input constraints into the optimization problem using a nonquadratic performance function. The DT tracking Bellman equation and tracking Hamilton-Jacobi-Bellman (HJB) are derived. An actor-critic-based reinforcement learning algorithm is used to learn the solution to the tracking HJB equation online without requiring knowledge of the system drift dynamics. That is, two neural networks (NNs), namely, actor NN and critic NN, are tuned online and simultaneously to generate the optimal bounded control policy. A simulation example is given to show the effectiveness of the proposed method.

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.

Influential Spheres: Examining Actors' Perceptions of Education Governance

ERIC Educational Resources Information Center

Thier, Michael; Smith, Joanna; Pitts, Christine; Anderson, Ross

2016-01-01

Many layers of education governance press upon U.S. schools, so we separated state actors into those internal to and those external to the system. In the process, we unpacked the traditional state-local dichotomy. Using interview data (n = 45) from six case-study states, we analyzed local leaders', state-internal actors', and state-external…

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…

The Mayaguez Incident: An Organizational Theory Analysis

DTIC Science & Technology

2006-09-01

actors, and its effectiveness is obtained. Applying organizational theory to the Mayaguez incident demonstrates that decision processes at the executive...theories to take to battle, an organizational theory tool to use on the lessons learned may prove effective . Though it is not feasible in the heat of...AND SUBTITLE: The Mayaguez Incident: An Organizational Theory Analysis 6. AUTHORS Edward J. Lengel, Shelley A. Rodriguez, Michael D. Tyynismaa and

Driving the brain towards creativity and intelligence: A network control theory analysis.

PubMed

Kenett, Yoed N; Medaglia, John D; Beaty, Roger E; Chen, Qunlin; Betzel, Richard F; Thompson-Schill, Sharon L; Qiu, Jiang

2018-01-04

High-level cognitive constructs, such as creativity and intelligence, entail complex and multiple processes, including cognitive control processes. Recent neurocognitive research on these constructs highlight the importance of dynamic interaction across neural network systems and the role of cognitive control processes in guiding such a dynamic interaction. How can we quantitatively examine the extent and ways in which cognitive control contributes to creativity and intelligence? To address this question, we apply a computational network control theory (NCT) approach to structural brain imaging data acquired via diffusion tensor imaging in a large sample of participants, to examine how NCT relates to individual differences in distinct measures of creative ability and intelligence. Recent application of this theory at the neural level is built on a model of brain dynamics, which mathematically models patterns of inter-region activity propagated along the structure of an underlying network. The strength of this approach is its ability to characterize the potential role of each brain region in regulating whole-brain network function based on its anatomical fingerprint and a simplified model of node dynamics. We find that intelligence is related to the ability to "drive" the brain system into easy to reach neural states by the right inferior parietal lobe and lower integration abilities in the left retrosplenial cortex. We also find that creativity is related to the ability to "drive" the brain system into difficult to reach states by the right dorsolateral prefrontal cortex (inferior frontal junction) and higher integration abilities in sensorimotor areas. Furthermore, we found that different facets of creativity-fluency, flexibility, and originality-relate to generally similar but not identical network controllability processes. We relate our findings to general theories on intelligence and creativity. Copyright © 2018 Elsevier Ltd. All rights reserved.

Dual-process models of health-related behaviour and cognition: a review of theory.

PubMed

Houlihan, S

2018-03-01

The aim of this review was to synthesise a spectrum of theories incorporating dual-process models of health-related behaviour. Review of theory, adapted loosely from Cochrane-style systematic review methodology. Inclusion criteria were specified to identify all relevant dual-process models that explain decision-making in the context of decisions made about human health. Data analysis took the form of iterative template analysis (adapted from the conceptual synthesis framework used in other reviews of theory), and in this way theories were synthesised on the basis of shared theoretical constructs and causal pathways. Analysis and synthesis proceeded in turn, instead of moving uni-directionally from analysis of individual theories to synthesis of multiple theories. Namely, the reviewer considered and reconsidered individual theories and theoretical components in generating the narrative synthesis' main findings. Drawing on systematic review methodology, 11 electronic databases were searched for relevant dual-process theories. After de-duplication, 12,198 records remained. Screening of title and abstract led to the exclusion of 12,036 records, after which 162 full-text records were assessed. Of those, 21 records were included in the review. Moving back and forth between analysis of individual theories and the synthesis of theories grouped on the basis of theme or focus yielded additional insights into the orientation of a theory to an individual. Theories could be grouped in part on their treatment of an individual as an irrational actor, as social actor, as actor in a physical environment or as a self-regulated actor. Synthesising identified theories into a general dual-process model of health-related behaviour indicated that such behaviour is the result of both propositional and unconscious reasoning driven by an individual's response to internal cues (such as heuristics, attitude and affect), physical cues (social and physical environmental stimuli) as well as

Ordering theories: Typologies and conceptual frameworks for sociotechnical change

PubMed Central

Sovacool, Benjamin K; Hess, David J

2017-01-01

What theories or concepts are most useful at explaining socio technical change? How can – or cannot – these be integrated? To provide an answer, this study presents the results from 35 semi-structured research interviews with social science experts who also shared more than two hundred articles, reports and books on the topic of the acceptance, adoption, use, or diffusion of technology. This material led to the identification of 96 theories and conceptual approaches spanning 22 identified disciplines. The article begins by explaining its research terms and methods before honing in on a combination of fourteen theories deemed most relevant and useful by the material. These are: Sociotechnical Transitions, Social Practice Theory, Discourse Theory, Domestication Theory, Large Technical Systems, Social Construction of Technology, Sociotechnical Imaginaries, Actor-Network Theory, Social Justice Theory, Sociology of Expectations, Sustainable Development, Values Beliefs Norms Theory, Lifestyle Theory, and the Unified Theory of Acceptance and Use of Technology. It then positions these theories in terms of two distinct typologies. Theories can be placed into five general categories of being centered on agency, structure, meaning, relations or norms. They can also be classified based on their assumptions and goals rooted in functionalism, interpretivism, humanism or conflict. The article lays out tips for research methodology before concluding with insights about technology itself, analytical processes associated with technology, and the framing and communication of results. An interdisciplinary theoretical and conceptual inventory has much to offer students, analysts and scholars wanting to study technological change and society. PMID:28641502

Network-based machine learning and graph theory algorithms for precision oncology.

PubMed

Zhang, Wei; Chien, Jeremy; Yong, Jeongsik; Kuang, Rui

2017-01-01

Network-based analytics plays an increasingly important role in precision oncology. Growing evidence in recent studies suggests that cancer can be better understood through mutated or dysregulated pathways or networks rather than individual mutations and that the efficacy of repositioned drugs can be inferred from disease modules in molecular networks. This article reviews network-based machine learning and graph theory algorithms for integrative analysis of personal genomic data and biomedical knowledge bases to identify tumor-specific molecular mechanisms, candidate targets and repositioned drugs for personalized treatment. The review focuses on the algorithmic design and mathematical formulation of these methods to facilitate applications and implementations of network-based analysis in the practice of precision oncology. We review the methods applied in three scenarios to integrate genomic data and network models in different analysis pipelines, and we examine three categories of network-based approaches for repositioning drugs in drug-disease-gene networks. In addition, we perform a comprehensive subnetwork/pathway analysis of mutations in 31 cancer genome projects in the Cancer Genome Atlas and present a detailed case study on ovarian cancer. Finally, we discuss interesting observations, potential pitfalls and future directions in network-based precision oncology.

Scattering theory of efficient quantum transport across finite networks

NASA Astrophysics Data System (ADS)

Walschaers, Mattia; Mulet, Roberto; Buchleitner, Andreas

2017-11-01

We present a scattering theory for the efficient transmission of an excitation across a finite network with designed disorder. We show that the presence of randomly positioned network sites allows significant acceleration of the excitation transfer processes as compared to a dimer structure, but only if the disordered Hamiltonians are constrained to be centrosymmetric and exhibit a dominant doublet in their spectrum. We identify the cause of this efficiency enhancement to be the constructive interplay between disorder-induced fluctuations of the dominant doublet’s splitting and the coupling strength between the input and output sites to the scattering channels. We find that the characteristic strength of these fluctuations together with the channel coupling fully control the transfer efficiency.

Acting discursively: the development of UK organic food and farming policy networks.

PubMed

TOMLINSON, Isobel Jane

2010-01-01

This paper documents the early evolution of UK organic food and farming policy networks and locates this empirical focus in a theoretical context concerned with understanding the contemporary policy-making process. While policy networks have emerged as a widely acknowledged empirical manifestation of governance, debate continues as to the concept's explanatory utility and usefulness in situations of network and policy transformation since, historically, policy networks have been applied to "static" circumstances. Recognizing this criticism, and in drawing on an interpretivist perspective, this paper sees policy networks as enacted by individual actors whose beliefs and actions construct the nature of the network. It seeks to make links between the characteristics of the policy network and the policy outcomes through the identification of discursively constructed "storylines" that form a tool for consensus building in networks. This study analyses the functioning of the organic policy networks through the discursive actions of policy-network actors.

Postdecisional counterfactual thinking by actors and readers.

PubMed

Girotto, Vittorio; Ferrante, Donatella; Pighin, Stefania; Gonzalez, Michel

2007-06-01

How do individuals think counterfactually about the outcomes of their decisions? Most previous studies have investigated how readers think about fictional stories, rather than how actors think about events they have actually experienced. We assumed that differences in individuals' roles (actor vs. reader) can make different information available, which in turn can affect counterfactual thinking. Hence, we predicted an effect of role on postdecisional counterfactual thinking. Reporting the results of eight studies, we show that readers undo the negative outcome of a story by undoing the protagonist's choice to tackle a given problem, rather than the protagonist's unsuccessful attempt to solve it. But actors who make the same choice and experience the same negative outcome as the protagonist undo this outcome by altering features of the problem. We also show that this effect does not depend on motivational factors. These results contradict current accounts of counterfactual thinking and demonstrate the necessity of investigating the counterfactual thoughts of individuals in varied roles.

Department of Defense Information Network (DODIN): A Study of Current Cyber Threats and Best Practices for Network Security

DTIC Science & Technology

2016-06-10

DODIN) is being threatened by state actors, non-state actors, and continuous hacking and cyber-attacks. These threats against the network come in a...variety of forms; physical attacks from radio jamming, logical cyber threats from hacking , or a combination of both physical and logical attacks. Each...year the number of hacking attacks is increasing. Corporations like Symantec publish annual reports on cyber threats and provide tips for best

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…

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

PubMed

Kim, Jinyoung

2017-12-01

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

Heath Sector Network Governance and State-building in South Kivu, Democratic Republic of Congo.

PubMed

Bwimana, Aembe

2017-12-01

Longstanding patterns of interaction exist between state and non-state actors seeking to improve public health in Democratic Republic of Congo (DRC). DRC is a weak state, and, in many cases, private actors have stepped in to fill the void created by the lack of state health care provision. However, the role of these interactions in creating a governance network in the health sector has been underexplored. Using data from 18 months of qualitative field research, this study aimed to explore governance networks in DRC's health sector, examining how multiple stakeholders work to manage the health system and how the resulting governance network has been relevant for the state-building process. The findings demonstrate that the health sector in South Kivu is emerging as an arena of networked governance based on active partnerships between state institutions and non-state actors. Interactions between state and non-state actors account for the persistence of the health sector in a setting characterized by state weakness. However, networked governance does not function optimally, because, although non-state interventions fill the void where the state falls short, the DRC state has faced the challenge of interacting with partners with fragmented and horizontally competing agendas. Although weak, the shadow of state authority is present in the arena of stakeholders' interactions, as the state plays a determining role by providing a regulatory framework. Overall, the findings show that the interactive engagement of non-state actors contributes to improving institutional capacity through these actors' engagement with state institutions for health system management and institutional development. However, although networked health sector governance does contribute to state capacity, it is difficult to assess the real influence of these interactions on the state-building process in a context of critical fragility, where coordination and alignment have been problematic. © The

Balancing influence between actors in healthcare decision making.

PubMed

Kaplan, Robert M; Babad, Yair M

2011-04-19

Healthcare costs in most developed countries are not clearly linked to better patient and public health outcomes, but are rather associated with service delivery orientation. In the U.S. this has resulted in large variation in healthcare availability and use, increased cost, reduced employer participation in health insurance programs, and reduced overall population health outcomes. Recent U.S. healthcare reform legislation addresses only some of these issues. Other countries face similar healthcare issues. A major goal of healthcare is to enhance patient health outcomes. This objective is not realized in many countries because incentives and structures are currently not aligned for maximizing population health. The misalignment occurs because of the competing interests between "actors" in healthcare. In a simplified model these are individuals motivated to enhance their own health; enterprises (including a mix of nonprofit, for profit and government providers, payers, and suppliers, etc.) motivated by profit, political, organizational and other forces; and government which often acts in the conflicting roles of a healthcare payer and provider in addition to its role as the representative and protector of the people. An imbalance exists between the actors, due to the resources and information control of the enterprise and government actors relative to the individual and the public. Failure to use effective preventive interventions is perhaps the best example of the misalignment of incentives. We consider the current Pareto efficient balance between the actors in relation to the Pareto frontier, and show that a significant change in the healthcare market requires major changes in the utilities of the enterprise and government actors. A variety of actions are necessary for maximizing population health within the constraints of available resources and the current balance between the actors. These actions include improved transparency of all aspects of medical decision

Balancing influence between actors in healthcare decision making

PubMed Central

2011-01-01

Background Healthcare costs in most developed countries are not clearly linked to better patient and public health outcomes, but are rather associated with service delivery orientation. In the U.S. this has resulted in large variation in healthcare availability and use, increased cost, reduced employer participation in health insurance programs, and reduced overall population health outcomes. Recent U.S. healthcare reform legislation addresses only some of these issues. Other countries face similar healthcare issues. Discussion A major goal of healthcare is to enhance patient health outcomes. This objective is not realized in many countries because incentives and structures are currently not aligned for maximizing population health. The misalignment occurs because of the competing interests between "actors" in healthcare. In a simplified model these are individuals motivated to enhance their own health; enterprises (including a mix of nonprofit, for profit and government providers, payers, and suppliers, etc.) motivated by profit, political, organizational and other forces; and government which often acts in the conflicting roles of a healthcare payer and provider in addition to its role as the representative and protector of the people. An imbalance exists between the actors, due to the resources and information control of the enterprise and government actors relative to the individual and the public. Failure to use effective preventive interventions is perhaps the best example of the misalignment of incentives. We consider the current Pareto efficient balance between the actors in relation to the Pareto frontier, and show that a significant change in the healthcare market requires major changes in the utilities of the enterprise and government actors. Summary A variety of actions are necessary for maximizing population health within the constraints of available resources and the current balance between the actors. These actions include improved transparency of

[Be in role. Examination of dissociative experiences of theatrical actors].

PubMed

Docsa, Viktória Pálma; Szemán-Nagy, Anita

2012-01-01

In spite of the fact that acting makes great demands on the personality, there is lack of research dealing with the psychological status of actors. Resulted from their profession actors often experience dissociation, since absorption and changing of their identity is a routine task for them. They are acting on the stage, and they are acting in private. 36 theatrical actors completed the DISQ-H version of the Dissociation Questionnaire measuring four subscales: Identity Confusion, Amnesia, Loss of Control and Absorption. In order to understand their experiences deeper, nine actors were interviewed. The sample consisted of 21 men and 15 women and their ages ranged from 23 to 60. Higher ages implied longer career as an actor, thus the youngest subject had been working for 2 years, while the oldest one had been working for 39 years. DISQ-H total score results of the actors were significantly higher compared to the Hungarian standard scores. As we expected, the two non-pathological subscales (Loss of Control and Absorption) showed significant differences compared to the standard scores of the subscales. In the case of Identity Confusion subscale we found no significant differences, however the results indicate that the tendency observed emphasizes the importance of further research of this phenomenon. To sum up, dissociative experiences proved to be important elements of acting.

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.

Analyzing Collaborative Governance Through Social Network Analysis: A Case Study of River Management Along the Waal River in The Netherlands.

PubMed

Fliervoet, J M; Geerling, G W; Mostert, E; Smits, A J M

2016-02-01

Until recently, governmental organizations played a dominant and decisive role in natural resource management. However, an increasing number of studies indicate that this dominant role is developing towards a more facilitating role as equal partner to improve efficiency and create a leaner state. This approach is characterized by complex collaborative relationships between various actors and sectors on multiple levels. To understand this complexity in the field of environmental management, we conducted a social network analysis of floodplain management in the Dutch Rhine delta. We charted the current interorganizational relationships between 43 organizations involved in flood protection (blue network) and nature management (green network) and explored the consequences of abolishing the central actor in these networks. The discontinuation of this actor will decrease the connectedness of actors within the blue and green network and may therefore have a large impact on the exchange of ideas and decision-making processes. Furthermore, our research shows the dependence of non-governmental actors on the main governmental organizations. It seems that the Dutch governmental organizations still have a dominant and controlling role in floodplain management. This challenges the alleged shift from a dominant government towards collaborative governance and calls for detailed analysis of actual governance.

Analyzing Collaborative Governance Through Social Network Analysis: A Case Study of River Management Along the Waal River in The Netherlands

NASA Astrophysics Data System (ADS)

Fliervoet, J. M.; Geerling, G. W.; Mostert, E.; Smits, A. J. M.

2016-02-01

Until recently, governmental organizations played a dominant and decisive role in natural resource management. However, an increasing number of studies indicate that this dominant role is developing towards a more facilitating role as equal partner to improve efficiency and create a leaner state. This approach is characterized by complex collaborative relationships between various actors and sectors on multiple levels. To understand this complexity in the field of environmental management, we conducted a social network analysis of floodplain management in the Dutch Rhine delta. We charted the current interorganizational relationships between 43 organizations involved in flood protection (blue network) and nature management (green network) and explored the consequences of abolishing the central actor in these networks. The discontinuation of this actor will decrease the connectedness of actors within the blue and green network and may therefore have a large impact on the exchange of ideas and decision-making processes. Furthermore, our research shows the dependence of non-governmental actors on the main governmental organizations. It seems that the Dutch governmental organizations still have a dominant and controlling role in floodplain management. This challenges the alleged shift from a dominant government towards collaborative governance and calls for detailed analysis of actual governance.

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

DTIC Science & Technology

2008-12-01

perceptions of formal and emergent leaders differ from those of non-leaders, and if so, how. We approach this topic through the lens of social network...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...the structure of any social system can be defined as a set of relations between all pairs of individuals who are members of the network (Krackhardt

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

PubMed

Valente, Thomas W; Pitts, Stephanie R

2017-03-20

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.

Intelligent policy making? Key actors' perspectives on the development and implementation of an early years' initiative in Scotland's public health arena.

PubMed

Deas, L; Mattu, L; Gnich, W

2013-11-01

Increased political enthusiasm for evidence-based policy and action has re-ignited interest in the use of evidence within political and practitioner networks. Theories of evidence-based policy making and practice are being re-considered in an attempt to better understand the processes through which knowledge translation occurs. Understanding how policy develops, and practice results, has the potential to facilitate effective evidence use. Further knowledge of the factors which shape healthcare delivery and their influence in different contexts is needed. This paper explores the processes involved in the development of a complex intervention in Scotland's National Health Service (NHS). It uses a national oral health programme for children (Childsmile) as a case study, drawing upon key actors' perceptions of the influence of different drivers (research evidence, practitioner knowledge and values, policy, and political and local context) to programme development. Framework analysis is used to analyse stakeholder accounts from in-depth interviews. Documentary review is also undertaken. Findings suggest that Childsmile can be described as an 'evidence-informed' intervention, blending available research evidence with knowledge from practitioner experience and continual learning through evaluation, to plan delivery. The importance of context was underscored, in terms of the need to align with prevailing political ideology and in the facilitative strength of networks within the relatively small public health community in Scotland. Respondents' perceptions support several existing theoretical models of translation, however no single theory offered a comprehensive framework covering all aspects of the complex processes reported. Childsmile's use of best available evidence and on-going contribution to knowledge suggest that the programme is an example of intelligent policy making with international relevance. Copyright © 2013 Elsevier Ltd. All rights reserved.

Developing physical activity interventions for adults with spinal cord injury. Part 1: a comparison of social cognitions across actors, intenders, and nonintenders.

PubMed

Ginis, Kathleen A Martin; Tomasone, Jennifer R; Latimer-Cheung, Amy E; Arbour-Nicitopoulos, Kelly P; Bassett-Gunter, Rebecca L; Wolfe, Dalton L

2013-08-01

This article is the first in a three-part series focused on designing theory-based interventions to increase leisure time physical activity (LTPA) in persons with spinal cord injury (SCI). The purpose of this first study was to compare social cognitions for LTPA between people classified as LTPA actors, intenders, and nonintenders, as per Schwarzer's Health Action Process Approach (HAPA) model. Participants were 238 men and women living with a SCI (M age = 44.14, SD = 12.74; 44.5% paraplegic) who were subsequently classified as LTPA actors (n = 105), intenders (n = 73), or nonintenders (n = 60). Participants completed a questionnaire that assessed the following HAPA constructs: LTPA outcome expectancies, self-efficacy, intentions, planning, and action control. A MANCOVA revealed significant between-groups differences for all variables (ps < .001). For all of the measures, actors scored significantly higher than intenders who, in turn, scored significantly higher than nonintenders. It is both theoretically and practically important to distinguish between LTPA nonintenders, intenders, and actors when developing LTPA-enhancing interventions for people with SCI. These distinctions inform the design and testing of the interventions reported in the two accompanying articles. (c) 2013 APA, all rights reserved.

Effects of Network Characteristics on Reaching the Payoff-Dominant Equilibrium in Coordination Games: A Simulation study.

PubMed

Buskens, Vincent; Snijders, Chris

2016-01-01

We study how payoffs and network structure affect reaching the payoff-dominant equilibrium in a [Formula: see text] coordination game that actors play with their neighbors in a network. Using an extensive simulation analysis of over 100,000 networks with 2-25 actors, we show that the importance of network characteristics is restricted to a limited part of the payoff space. In this part, we conclude that the payoff-dominant equilibrium is chosen more often if network density is larger, the network is more centralized, and segmentation of the network is smaller. Moreover, it is more likely that heterogeneity in behavior persists if the network is more segmented and less centralized. Persistence of heterogeneous behavior is not related to network density.

Bridging online and offline social networks: Multiplex analysis

NASA Astrophysics Data System (ADS)

Filiposka, Sonja; Gajduk, Andrej; Dimitrova, Tamara; Kocarev, Ljupco

2017-04-01

We show that three basic actor characteristics, namely normalized reciprocity, three cycles, and triplets, can be expressed using an unified framework that is based on computing the similarity index between two sets associated with the actor: the set of her/his friends and the set of those considering her/him as a friend. These metrics are extended to multiplex networks and then computed for two friendship networks generated by collecting data from two groups of undergraduate students. We found that in offline communication strong and weak ties are (almost) equally presented, while in online communication weak ties are dominant. Moreover, weak ties are much less reciprocal than strong ties. However, across different layers of the multiplex network reciprocities are preserved, while triads (measured with normalized three cycles and triplets) are not significant.

ACToR A Aggregated Computational Toxicology Resource (S) ...

EPA Pesticide Factsheets

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

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.

Exploring the use of grounded theory as a methodological approach to examine the 'black box' of network leadership in the national quality forum.

PubMed

Hoflund, A Bryce

2013-01-01

This paper describes how grounded theory was used to investigate the "black box" of network leadership in the creation of the National Quality Forum. Scholars are beginning to recognize the importance of network organizations and are in the embryonic stages of collecting and analyzing data about network leadership processes. Grounded theory, with its focus on deriving theory from empirical data, offers researchers a distinctive way of studying little-known phenomena and is therefore well suited to exploring network leadership processes. Specifically, this paper provides an overview of grounded theory, a discussion of the appropriateness of grounded theory to investigating network phenomena, a description of how the research was conducted, and a discussion of the limitations and lessons learned from using this approach.

Application of the actor model to large scale NDE data analysis

NASA Astrophysics Data System (ADS)

Coughlin, Chris

2018-03-01

The Actor model of concurrent computation discretizes a problem into a series of independent units or actors that interact only through the exchange of messages. Without direct coupling between individual components, an Actor-based system is inherently concurrent and fault-tolerant. These traits lend themselves to so-called "Big Data" applications in which the volume of data to analyze requires a distributed multi-system design. For a practical demonstration of the Actor computational model, a system was developed to assist with the automated analysis of Nondestructive Evaluation (NDE) datasets using the open source Myriad Data Reduction Framework. A machine learning model trained to detect damage in two-dimensional slices of C-Scan data was deployed in a streaming data processing pipeline. To demonstrate the flexibility of the Actor model, the pipeline was deployed on a local system and re-deployed as a distributed system without recompiling, reconfiguring, or restarting the running application.

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…

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…

Simulating drinking in social networks to inform alcohol prevention and treatment efforts.

PubMed

Hallgren, Kevin A; McCrady, Barbara S; Caudell, Thomas P; Witkiewitz, Katie; Tonigan, J Scott

2017-11-01

Adolescent drinking influences, and is influenced by, peer alcohol use. Several efficacious adolescent alcohol interventions include elements aimed at reducing susceptibility to peer influence. Modeling these interventions within dynamically changing social networks may improve our understanding of how such interventions work and for whom they work best. We used stochastic actor-based models to simulate longitudinal drinking and friendship formation within social networks using parameters obtained from a meta-analysis of real-world 10th grade adolescent social networks. Levels of social influence (i.e., friends affecting changes in one's drinking) and social selection (i.e., drinking affecting changes in one's friendships) were manipulated at several levels, which directly impacted the degree of clustering in friendships based on similarity in drinking behavior. Midway through each simulation, one randomly selected heavy-drinking actor from each network received an "intervention" that either (a) reduced their susceptibility to social influence, (b) reduced their susceptibility to social selection, (c) eliminated a friendship with a heavy drinker, or (d) initiated a friendship with a nondrinker. Only the intervention that eliminated targeted actors' susceptibility to social influence consistently reduced that actor's drinking. Moreover, this was only effective in networks with social influence and social selection that were at higher levels than what was found in the real-world reference study. Social influence and social selection are dynamic processes that can lead to complex systems that may moderate the effectiveness of network-based interventions. Interventions that reduce susceptibility to social influence may be most effective among adolescents with high susceptibility to social influence and heavier-drinking friends. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

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

PubMed Central

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

2015-01-01

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

ACToR Chemical Structure processing using Open Source ...

EPA Pesticide Factsheets

ACToR (Aggregated Computational Toxicology Resource) is a centralized database repository developed by the National Center for Computational Toxicology (NCCT) at the U.S. Environmental Protection Agency (EPA). Free and open source tools were used to compile toxicity data from over 1,950 public sources. ACToR contains chemical structure information and toxicological data for over 558,000 unique chemicals. The database primarily includes data from NCCT research programs, in vivo toxicity data from ToxRef, human exposure data from ExpoCast, high-throughput screening data from ToxCast and high quality chemical structure information from the EPA DSSTox program. The DSSTox database is a chemical structure inventory for the NCCT programs and currently has about 16,000 unique structures. Included are also data from PubChem, ChemSpider, USDA, FDA, NIH and several other public data sources. ACToR has been a resource to various international and national research groups. Most of our recent efforts on ACToR are focused on improving the structural identifiers and Physico-Chemical properties of the chemicals in the database. Organizing this huge collection of data and improving the chemical structure quality of the database has posed some major challenges. Workflows have been developed to process structures, calculate chemical properties and identify relationships between CAS numbers. The Structure processing workflow integrates web services (PubChem and NIH NCI Cactus) to d

Power-law behavior in complex organizational communication networks during crisis

NASA Astrophysics Data System (ADS)

Uddin, Shahadat; Murshed, Shahriar Tanvir Hasan; Hossain, Liaquat

2011-08-01

Communication networks can be described as patterns of contacts which are created due to the flow of messages and information shared among participating actors. Contemporary organizations are now commonly viewed as dynamic systems of adaptation and evolution containing several parts, which interact with one another both in internal and in external environment. Although there is limited consensus among researchers on the precise definition of organizational crisis, there is evidence of shared meaning: crisis produces individual crisis, crisis can be associated with positive or negative conditions, crises can be situations having been precipitated quickly or suddenly or situations that have developed over time and are predictable etc. In this research, we study the power-law behavior of an organizational email communication network during crisis from complexity perspective. Power law simply describes that, the probability that a randomly selected node has k links (i.e. degree k) follows P(k)∼k, where γ is the degree exponent. We used social network analysis tools and techniques to analyze the email communication dataset. We tested two propositions: (1) as organization goes through crisis, a few actors, who are prominent or more active, will become central, and (2) the daily communication network as well as the actors in the communication network exhibit power-law behavior. Our preliminary results support these two propositions. The outcome of this study may provide significant advancement in exploring organizational communication network behavior during crisis.

Professional Actors in the University Classroom

ERIC Educational Resources Information Center

Sharpham, John R.; Pritner, Calvin Lee

1973-01-01

A company of professional actors perform scenes from history, act in plays, and do improvisations and poetry readings in university classrooms. Describes Illinois State University's unique program for enlivening the humanities. (Author/JF)

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…

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.

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.

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

Lone Actor Terrorist Attack Planning and Preparation: A Data-Driven Analysis.

PubMed

Schuurman, Bart; Bakker, Edwin; Gill, Paul; Bouhana, Noémie

2017-10-23

This article provides an in-depth assessment of lone actor terrorists' attack planning and preparation. A codebook of 198 variables related to different aspects of pre-attack behavior is applied to a sample of 55 lone actor terrorists. Data were drawn from open-source materials and complemented where possible with primary sources. Most lone actors are not highly lethal or surreptitious attackers. They are generally poor at maintaining operational security, leak their motivations and capabilities in numerous ways, and generally do so months and even years before an attack. Moreover, the "loneness" thought to define this type of terrorism is generally absent; most lone actors uphold social ties that are crucial to their adoption and maintenance of the motivation and capability to commit terrorist violence. The results offer concrete input for those working to detect and prevent this form of terrorism and argue for a re-evaluation of the "lone actor" concept. © 2017 The Authors. Journal of Forensic Sciences published by Wiley Periodicals, Inc. on behalf of American Academy of Forensic Sciences.

Matching safety to access: global actors and pharmacogovernance in Kenya- a case study.

PubMed

Moscou, Kathy; Kohler, Jillian C

2017-03-23

The Kenyan government has sought to address inadequacies in its National Pharmaceutical Policy and the Pharmacy and Poisons Board's (PPB) medicines governance by engaging with global actors (e.g. the World Health Organization). Policy actors have influenced the way pharmacovigilance is defined, how challenges are understood and which norms are requisite to address drug safety issues. In this paper, we investigate the relationship between specific modes of engagement among global (exogenous) and domestic actors at the national and sub-national level to identify the positive or negative effect on pharmacovigilance and pharmacogovernance in Kenya. Pharmacogovernance is defined as the manner in which governing structures; policy instruments; institutional authority (e.g., ability to act, implement and enforce norms, policies and processes) and resources are managed to promote societal interests for patient safety and protection from adverse drug reactions (ADRs). Qualitative research methods that included key informant interviews and document analysis, were employed to investigate the relationship between global actors' patterns of engagement with national actors and pharmacogovernance in Kenya. Global actors' influence on pharmacogovernance and pharmacovigilance priorities in Kenya (e.g., legislation and adverse drug reaction surveillance) was positively perceived by key informants. We found that global actors' engagement with state actors produced positive and negative outcomes. Engagement with the PPB and Ministry of Health (MOH) that was characterized as dependent (advocacy, empowerment, delegated) or interdependent (collaborative, cooperative, consultative) was mostly associated with positive outcomes e.g., capacity building; strengthening legislation and stakeholder coordination. Fragmentation (independent engagement) hindered risk communication between public, private, and NGO health programs. A framework for assessing pharmacogovernance would support policy

Analysing published global Ebola Virus Disease research using social network analysis.

PubMed

Hagel, Christiane; Weidemann, Felix; Gauch, Stephan; Edwards, Suzanne; Tinnemann, Peter

2017-10-01

The 2014/2015 West African Ebola Virus Disease (EVD) outbreak attracted global attention. Numerous opinions claimed that the global response was impaired, in part because, the EVD research was neglected, although quantitative or qualitative studies did not exist. Our objective was to analyse how the EVD research landscape evolved by exploring the existing research network and its communities before and during the outbreak in West Africa. Social network analysis (SNA) was used to analyse collaborations between institutions named by co-authors as affiliations in publications on EVD. Bibliometric data of publications on EVD between 1976 and 2015 was collected from Thomson Reuters' Web of Science Core Collection (WoS). Freely available software was used for network analysis at a global-level and for 10-year periods. The networks are presented as undirected-weighted graphs. Rankings by degree and betweenness were calculated to identify central and powerful network positions; modularity function was used to identify research communities. Overall 4,587 publications were identified, of which 2,528 were original research articles. Those yielded 1,644 authors' affiliated institutions and 9,907 connections for co-authorship network construction. The majority of institutions were from the USA, Canada and Europe. Collaborations with research partners on the African continent did exist, but less frequently. Around six highly connected organisations in the network were identified with powerful and broker positions. Network characteristics varied widely among the 10-year periods and evolved from 30 to 1,489 institutions and 60 to 9,176 connections respectively. Most influential actors are from public or governmental institutions whereas private sector actors, in particular the pharmaceutical industry, are largely absent. Research output on EVD has increased over time and surged during the 2014/2015 outbreak. The overall EVD research network is organised around a few key actors

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

ERIC Educational Resources Information Center

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

2015-01-01

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

Training students with patient actors improves communication: a pilot study.

PubMed

Anderson, Heather A; Young, Jack; Marrelli, Danica; Black, Rudolph; Lambreghts, Kimberly; Twa, Michael D

2014-01-01

Effective patient communication is correlated with better health outcomes and patient satisfaction, but is challenging to train, particularly with difficult clinical scenarios such as loss of sight. In this pilot study, we evaluated the use of simulated patient encounters with actors to train optometric students. Students were recorded during encounters with actors and assigned to an enrichment group performing five interactions with instructor feedback (n = 6) or a no-enrichment group performing two interactions without feedback (n = 4). Student performance on first and last encounters was scored with (1) subjective rating of performance change using a visual analog scale (anchors: much worse/much better), (2) yes/no response: Would you recommend this doctor to a friend/relative?, and (3) average score on questions from the American Board of Internal Medicine (ABIM) assessment of doctor communication skills. Three clinical instructors, masked to student group assignments and the order of patient encounters they viewed, provided scores in addition to self-evaluation by students and patient-actors. Using the visual analog scale, students who received enrichment were rated more improved than the no-enrichment group by masked examiners (+18 vs. -11% p = 0.04) and self-evaluation (+79 vs. +27% p = 0.009), but not by actors (+31 vs. +43%). The proportion of students recommended significantly increased following enrichment for masked examiners (61% vs. 94%; p < 0.001), but not actors (100 vs. 83%). Average ABIM assessment scores were not significantly different by any rating group: masked instructors, actors, or self-ratings. The findings of this study suggest five simulated patient encounters with feedback result in measurable improvement in student-patient communication skills as rated by masked examiners.

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.

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

World Health Organization and the search for accountability: a critical analysis of the new framework of engagement with non-state actors.

PubMed

Rached, Danielle Hanna; Ventura, Deisy de Freitas Lima

2017-07-03

The article probes the origins and content of the Framework of Engagement with Non-State Actors (FENSA) of the World Health Organization (WHO), approved on May 28, 2016, at the 69th World Health Assembly, which established different rules of collaboration to four categories of actors: nongovernmental organizations (NGOs), private sector entities, philanthropic foundations, and academic institutions. Applying the findings of International Legal Theory and based on extensive documentary research, we sought to determine whether FENSA is an appropriate accountability mechanism according to four functions of accountability: constitutional, democratic, epistemic, and populist. The article concludes that there is a risk of the prevalence of the populist function at the expense of the accountability potential that could result from the better use of the other three accountability functions.

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

PubMed

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

2016-01-01

Digital Health Social Networks (DHSNs) are common; however, there are few metrics that can be used to identify participation inequality. The objective of this study was to investigate whether the Gini coefficient, an economic measure of statistical dispersion traditionally used to measure income inequality, could be employed to measure DHSN inequality. Quarterly Gini coefficients were derived from four long-standing DHSNs. The combined data set included 625,736 posts that were generated from 15,181 actors over 18,671 days. The range of actors (8-2323), posts (29-28,684), and Gini coefficients (0.15-0.37) varied. Pearson correlations indicated statistically significant associations between number of actors and number of posts (0.527-0.835, p  < .001), and Gini coefficients and number of posts (0.342-0.725, p  < .001). However, the association between Gini coefficient and number of actors was only statistically significant for the addiction networks (0.619 and 0.276, p  < .036). Linear regression models had positive but mixed R 2 results (0.333-0.527). In all four regression models, the association between Gini coefficient and posts was statistically significant ( t  = 3.346-7.381, p  < .002). However, unlike the Pearson correlations, the association between Gini coefficient and number of actors was only statistically significant in the two mental health networks ( t  = -4.305 and -5.934, p  < .000). The Gini coefficient is helpful in measuring shifts in DHSN inequality. However, as a standalone metric, the Gini coefficient does not indicate optimal numbers or ratios of actors to posts, or effective network engagement. Further, mixed-methods research investigating quantitative performance metrics is required.

Associations between perceived HIV stigma and quality of life at the dyadic level: the actor-partner interdependence model.

PubMed

Liu, Hongjie; Xu, Yongfang; Lin, Xinjin; Shi, Jian; Chen, Shiyi

2013-01-01

Few studies have investigated the relationship between HIV-related stigma and quality life at the dyadic level. The objective of this study was to examine the actor and partner effects of stigma that was perceived by people living with HIV/AIDS (PLWHAs) and caregivers on quality of life at the dyadic level. A survey was conducted among 148 dyads consisting of one PLWHA and one caregiver (296 participants) in Nanning, China. The interdependent relationship between a pair of dyadic members that influences the associations between stigma and quality of life was analyzed, using an innovative dyadic analysis technique: the Actor-Partner Interdependence Model (APIM). We found in this dyadic analysis that (1) PLWHAs compared to their caregivers exhibited a higher level of perceived HIV stigma and lower level of quality of life measured in four domains; (2) both PLWHAs' and caregivers' perceived HIV stigma influenced their own quality of life; (3) The quality of life was not substantially influenced by their partners' perceived stigma; and (4) Both actor and partner effects of stigma on quality of life were similar among PLWHAs and their caregivers. As HIV stigma and quality of life are complex phenomena rooted in cultures, intervention programs should be carefully planned based on social or cognitive theories and should be culturally adopted.

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.

Topological analysis of metabolic networks based on Petri net theory.

PubMed

Zevedei-Oancea, Ionela; Schuster, Stefan

2003-01-01

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.

'The biggest legal battle in UK casino history': Processes and politics of 'cheating' in sociotechnical networks.

PubMed

Johnson, Mark R

2018-04-01

Previous literature on cheating has focused on defining the concept, assigning responsibility to individual players, collaborative social processes or technical faults in a game's rules. By contrast, this paper applies an actor-network perspective to understanding 'cheating' in games, and explores how the concept is rhetorically effective in sociotechnical controversies. The article identifies human and nonhuman actors whose interests and properties were translated in a case study of 'edge sorting' - identifying minor but crucial differences in tessellated patterns on the backs of playing cards, and using these to estimate their values. In the ensuing legal controversy, the defending actors - casinos - retranslated the interests of actors to position edge sorting as cheating. This allowed the casinos to emerge victorious in a legal battle over almost twenty million dollars. Analyzing this dispute shows that cheating is both sociotechnically complex as an act and an extremely powerful rhetorical tool for actors seeking to prevent changes to previously-established networks. Science and Technology Studies (STS) offers a rich toolkit for examining cheating, but in addition the cheating discourse may be valuable to STS, enlarging our repertoire of actor strategies relevant to sociotechnical disputes.

The role of policy actors and contextual factors in policy agenda setting and formulation: maternal fee exemption policies in Ghana over four and a half decades.

PubMed

Koduah, Augustina; van Dijk, Han; Agyepong, Irene Akua

2015-05-30

Development of health policy is a complex process that does not necessarily follow a particular format and a predictable trajectory. Therefore, agenda setting and selecting of alternatives are critical processes of policy development and can give insights into how and why policies are made. Understanding why some policy issues remain and are maintained whiles others drop off the agenda is an important enquiry. This paper aims to advance understanding of health policy agenda setting and formulation in Ghana, a lower middle-income country, by exploring how and why the maternal (antenatal, delivery and postnatal) fee exemption policy agenda in the health sector has been maintained over the four and half decades since a 'free antenatal care in government facilities' policy was first introduced in October 1963. A mix of historical and contemporary qualitative case studies of nine policy agenda setting and formulation processes was used. Data collection methods involved reviews of archival materials, contemporary records, media content, in-depth interviews, and participant observation. Data was analysed drawing on a combination of policy analysis theories and frameworks. Contextual factors, acting in an interrelating manner, shaped how policy actors acted in a timely manner and closely linked policy content to the intended agenda. Contextual factors that served as bases for the policymaking process were: political ideology, economic crisis, data about health outcomes, historical events, social unrest, change in government, election year, austerity measures, and international agendas. Nkrumah's socialist ideology first set the agenda for free antenatal service in 1963. This policy trajectory taken in 1963 was not reversed by subsequent policy actors because contextual factors and policy actors created a network of influence to maintain this issue on the agenda. Politicians over the years participated in the process to direct and approve the agenda. Donors increasingly

[Social actors in HIV/AIDS prevention: opposition and interests in educational policy in Mexico, 1994-2000].

PubMed

Granados-Cosme, José Arturo; Nasaiya, Kittipong; Brambila, Alberto Torres

2007-03-01

Studies and recommendations by health agencies have emphasized the importance of education in HIV-AIDS prevention. Mexico has included topics on sexuality and HIV-AIDS in school programs, triggering resistance by some social actors. The current study seeks to clarify the various positions and interests and their influence on the textbook content. A literature search was conducted on the period during which the last educational reform was implemented in Mexico. The discourse analysis focused on the ethnography of communication, which identified: the various actors' positions, arguments, actions, economic and political power, and relations to others. The results show that those who oppose the inclusion of these themes in the school curriculum base their position on tradition, contrary to modernization and secularization of social life, and that their positions range from refusal to raising conditions. Networks have been formed that provide such groups with significant economic and political power. Government has given in to some demands by partially modifying the textbook contents. The current analysis proposes to reflect on the potential repercussions of such actions on the control of the epidemic.

The Role of the Theory-of-Mind Cortical Network in the Comprehension of Narratives

PubMed Central

Mason, Robert A.; Just, Marcel Adam

2009-01-01

Narrative comprehension rests on the ability to understand the intentions and perceptions of various agents in a story who interact with respect to some goal or problem. Reasoning about the state of mind of another person, real or fictional, has been referred to as Theory of Mind processing. While Theory of Mind Processing was first postulated prior to the existence of neuroimaging research, fMRI studies make it possible to characterize this processing in some detail. We propose that narrative comprehension makes use of some of the neural substrate of Theory of Mind reasoning, evoking what is referred to as a protagonist perspective network. The main cortical components of this protagonist-based network are the dorsomedial prefrontal cortex and the right temporo-parietal junction. The article discusses how these two cortical centers interact in narrative comprehension but still play distinguishable roles, and how the interaction between the two centers is disrupted in individuals with autism. PMID:19809575

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

Social Dynamics in Adult and Community Education Networks: Insights from a Case Study

ERIC Educational Resources Information Center

Dollhausen, Karin; Alke, Matthias

2014-01-01

Implementing network type structures has become a widely appreciated strategy to promote actor-relationships in the field of adult and community education and to coordinate them purposefully. However, there is still a lack of knowledge on how a "successful" coordination of actor-relationships can actually be achieved. This paper offers…

Emotional labor actors: a latent profile analysis of emotional labor strategies.

PubMed

Gabriel, Allison S; Daniels, Michael A; Diefendorff, James M; Greguras, Gary J

2015-05-01

Research on emotional labor focuses on how employees utilize 2 main regulation strategies-surface acting (i.e., faking one's felt emotions) and deep acting (i.e., attempting to feel required emotions)-to adhere to emotional expectations of their jobs. To date, researchers largely have considered how each strategy functions to predict outcomes in isolation. However, this variable-centered perspective ignores the possibility that there are subpopulations of employees who may differ in their combined use of surface and deep acting. To address this issue, we conducted 2 studies that examined surface acting and deep acting from a person-centered perspective. Using latent profile analysis, we identified 5 emotional labor profiles-non-actors, low actors, surface actors, deep actors, and regulators-and found that these actor profiles were distinguished by several emotional labor antecedents (positive affectivity, negative affectivity, display rules, customer orientation, and emotion demands-abilities fit) and differentially predicted employee outcomes (emotional exhaustion, job satisfaction, and felt inauthenticity). Our results reveal new insights into the nature of emotion regulation in emotional labor contexts and how different employees may characteristically use distinct combinations of emotion regulation strategies to manage their emotional expressions at work. (c) 2015 APA, all rights reserved.

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…

The Discourse of Interculturality and Its Transnational Migration: Towards a Comparative Analysis of Its Appropriation by Academic and Political Actors in the State of Veracruz

ERIC Educational Resources Information Center

Cortes, Laura Selene Mateos

2009-01-01

This paper analyses the ways in which social and educational networks are being configured around the actors participating in the increasingly transnational field of intercultural education both at the Universidad Veracruzana Intercultural and the Veracruz State Ministry of Education. It starts by defining the notion of discursive migration as…

Two-actor conflict with time delay: A dynamical model

NASA Astrophysics Data System (ADS)

Qubbaj, Murad R.; Muneepeerakul, Rachata

2012-11-01

Recent mathematical dynamical models of the conflict between two different actors, be they nations, groups, or individuals, have been developed that are capable of predicting various outcomes depending on the chosen feedback strategies, initial conditions, and the previous states of the actors. In addition to these factors, this paper examines the effect of time delayed feedback on the conflict dynamics. Our analysis shows that under certain initial and feedback conditions, a stable neutral equilibrium of conflict may destabilize for some critical values of time delay, and the two actors may evolve to new emotional states. We investigate the results by constructing critical delay surfaces for different sets of parameters and analyzing results from numerical simulations. These results provide new insights regarding conflict and conflict resolution and may help planners in adjusting and assessing their strategic decisions.

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…

Neural basis of understanding communicative actions: Changes associated with knowing the actor's intention and the meanings of the actions.

PubMed

Möttönen, Riikka; Farmer, Harry; Watkins, Kate E

2016-01-29

People can communicate by using hand actions, e.g., signs. Understanding communicative actions requires that the observer knows that the actor has an intention to communicate and the meanings of the actions. Here, we investigated how this prior knowledge affects processing of observed actions. We used functional MRI to determine changes in action processing when non-signers were told that the observed actions are communicative (i.e., signs) and learned the meanings of half of the actions. Processing of hand actions activated the left and right inferior frontal gyrus (IFG, BA 44 and 45) when the communicative intention of the actor was known, even when the meanings of the actions remained unknown. These regions were not active when the observers did not know about the communicative nature of the hand actions. These findings suggest that the left and right IFG play a role in understanding the intention of the actor, but do not process visuospatial features of the communicative actions. Knowing the meanings of the hand actions further enhanced activity in the anterior part of the IFG (BA 45), the inferior parietal lobule and posterior inferior and middle temporal gyri in the left hemisphere. These left-hemisphere language regions could provide a link between meanings and observed actions. In sum, the findings provide evidence for the segregation of the networks involved in the neural processing of visuospatial features of communicative hand actions and those involved in understanding the actor's intention and the meanings of the actions. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

[Local public health networks. Apropos of an experience].

PubMed

Guix, Joan; Bocio, Ana; Ferràs, Joaquim; Margalef, Jordi; Osanz, Anna C; Serrano, Mónica; Sentenà, Anna

2013-01-01

Public health action on a territory is complex and requires the involvement of multiple actors, who do not always act coordinately. Networks of organizations structures including the whole of the local actors facilitate the generation of synergies and enable greater effectiveness and efficiency of the joint action from the different actors on a same landscape. We present 3 years experience of four Public Health Committees in a region of Catalonia (Spain), composed by the main actors in public health planning. Each of the committees is organized on a plenary and working groups on issues arising from the regional health diagnosis, and coincident with the Health Plan of the Region. Coordination in no case implies the loss or dilution of the firm of the actor generator of intervention initiative in public health, but their empowerment and collaboration by the other actors. In conclusion welcomes the creation of a culture of collaboration and synergies between the different organizations concerned. Lack of specificity is observed in establishing operational objectives, and the need for greater coordination and involvement of the components of the various working groups. Copyright © 2012 SESPAS. Published by Elsevier Espana. All rights reserved.

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.…

Breaking into the Business: Experiences of Actors with Disabilities in the Entertainment Industry

ERIC Educational Resources Information Center

Raynor, Olivia; Hayward, Katharine

2009-01-01

The pursuit of an acting career is a difficult one for anybody. However, studies have yet to factor how disability affects casting opportunities. This study describes the employment of actors with disabilities, along with the unique barriers they encounter in the audition and casting process. Actors with disabilities from the Screen Actors Guild…

Group field theory and tensor networks: towards a Ryu–Takayanagi formula in full quantum gravity

NASA Astrophysics Data System (ADS)

Chirco, Goffredo; Oriti, Daniele; Zhang, Mingyi

2018-06-01

We establish a dictionary between group field theory (thus, spin networks and random tensors) states and generalized random tensor networks. Then, we use this dictionary to compute the Rényi entropy of such states and recover the Ryu–Takayanagi formula, in two different cases corresponding to two different truncations/approximations, suggested by the established correspondence.

Uncovering Influence through Social Network Analysis: The Role of Schools in Education for Sustainable Development

ERIC Educational Resources Information Center

Kolleck, Nina

2016-01-01

This paper examines the implementation of Education for Sustainable Development (ESD) in Germany and explores the possibilities of Social Network Analysis (SNA) for uncovering influential actors in educational policy innovation processes. From the theoretical perspective, an actor's influence is inferred from its relative position within…

The Development of the International Baccalaureate in Spanish Speaking Countries: A Global Comparative Approach

ERIC Educational Resources Information Center

Resnik, Julia

2016-01-01

This paper compares the development of International Baccalaureate (IB) schools in four different settings: Argentine, Chile, Spain and Ecuador. The global comparative approach used in this study, based on actor-network theory (ANT), allows us to analyse the connections and interactions between global actors and the plurality of national,…

A social network's changing statistical properties and the quality of human innovation

NASA Astrophysics Data System (ADS)

Uzzi, Brian

2008-06-01

We examined the entire network of creative artists that made Broadway musicals, in the post-War period, a collaboration network of international acclaim and influence, with an eye to investigating how the network's structural features condition the relationship between individual artistic talent and the success of their musicals. Our findings show that some of the evolving topographical qualities of degree distributions, path lengths and assortativity are relatively stable with time even as collaboration patterns shift, which suggests their changes are only minimally associated with the ebb and flux of the success of new productions. In contrast, the clustering coefficient changed substantially over time and we found that it had a nonlinear association with the production of financially and artistically successful shows. When the clustering coefficient ratio is low or high, the financial and artistic success of the industry is low, while an intermediate level of clustering is associated with successful shows. We supported these findings with sociological theory on the relationship between social structure and collaboration and with tests of statistical inference. Our discussion focuses on connecting the statistical properties of social networks to their performance and the performance of the actors embedded within them.

Validation of Networks Derived from Snowball Sampling of Municipal Science Education Actors

ERIC Educational Resources Information Center

von der Fehr, Ane; Sølberg, Jan; Bruun, Jesper

2018-01-01

Social network analysis (SNA) has been used in many educational studies in the past decade, but what these studies have in common is that the populations in question in most cases are defined and known to the researchers studying the networks. Snowball sampling is an SNA methodology most often used to study hidden populations, for example, groups…

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.

Modelling the evolution of a bi-partite network Peer referral in interlocking directorates*

PubMed Central

Edling, Christofer

2010-01-01

A central part of relational ties between social actors are constituted by shared affiliations and events. The action of joint participation reinforces personal ties between social actors as well as mutually shared values and norms that in turn perpetuate the patterns of social action that define groups. Therefore the study of bipartite networks is central to social science. Furthermore, the dynamics of these processes suggests that bipartite networks should not be considered static structures but rather be studied over time. In order to model the evolution of bipartite networks empirically we introduce a class of models and a Bayesian inference scheme that extends previous stochastic actor-oriented models for unimodal graphs. Contemporary research on interlocking directorates provides an area of research in which it seems reasonable to apply the model. Specifically, we address the question of how tie formation, i.e. director recruitment, contributes to the structural properties of the interlocking directorate network. For boards of directors on the Stockholm stock exchange we propose that a prolific mechanism in tie formation is that of peer referral. The results indicate that such a mechanism is present, generating multiple interlocks between boards. PMID:24944435

Sacred Shock: Student Actors on Anti-Bullying Improvisation and Impact of Self-Rehearsal

ERIC Educational Resources Information Center

Gilman, Sharlene Elinor

2017-01-01

This article describes responses of a group of adolescent student actors and actor alumni involved in anti-bullying skits arising from a critical case study of the Tolerance Troupe from a small rural and suburban borough in Pennsylvania. Seventeen active members and 19 actor alumni participated in semi-structured interviews focusing on what the…

Partnership in Knowledge Creation: Lessons Learned from a Researcher-Policy Actor Partnership to Co-Produce a Rapid Appraisal Case Study of South Australia's Social Inclusion Initiative

ERIC Educational Resources Information Center

Newman, Lareen; Biedrzycki, Kate; Patterson, Jan; Baum, Fran

2011-01-01

This paper describes a partnership between researchers and policy actors that was developed within a short timeframe to produce a rapid appraisal case study of a government policy initiative--South Australia's "Social Inclusion Initiative"--for the Social Exclusion Knowledge Network of the international Commission on Social Determinants…

A model for the multiplex dynamics of two-mode and one-mode networks, with an application to employment preference, friendship, and advice

PubMed Central

Snijders, Tom A.B.; Lomi, Alessandro; Torló, Vanina Jasmine

2012-01-01

We propose a new stochastic actor-oriented model for the co-evolution of two-mode and one-mode networks. The model posits that activities of a set of actors, represented in the two-mode network, co-evolve with exchanges and interactions between the actors, as represented in the one-mode network. The model assumes that the actors, not the activities, have agency. The empirical value of the model is demonstrated by examining how employment preferences co-evolve with friendship and advice relations in a group of seventy-five MBA students. The analysis shows that activity in the two-mode network, as expressed by number of employment preferences, is related to activity in the friendship network, as expressed by outdegrees. Further, advice ties between students lead to agreement with respect to employment preferences. In addition, considering the multiplexity of advice and friendship ties yields a better understanding of the dynamics of the advice relation: tendencies to reciprocation and homophily in advice relations are mediated to an important extent by friendship relations. The discussion pays attention to the implications of this study in the broader context of current efforts to model the co-evolutionary dynamics of social networks and individual behavior. PMID:23690653

Networking expertise: discursive coalitions and collaborative networks of experts in a public creationism controversy in the UK.

PubMed

Allgaier, Joachim

2012-04-01

Experts do play a particular role in public socio-scientific debates, even more so if they form heterogeneous coalition with other actors and experts. A case study about a public science education controversy surrounding the teaching of evolution/creationism in the UK press is used to investigate in detail how connections and coalitions between experts and other actors involved in the controversy emerged and played out. The research focuses on the question of what role collaborative and other networks of experts played in terms of influence, visibility, credibility, consensus and weight of argument. Issues that are considered in the research are the status of the members of the coalitions forming during the debate and how it is displayed in media representations and letters and petitions, and also how these networks and coalitions of experts perform in relation to each other.

Networking expertise: Discursive coalitions and collaborative networks of experts in a public creationism controversy in the UK

PubMed Central

Allgaier, Joachim

2012-01-01

Experts do play a particular role in public socio-scientific debates, even more so if they form heterogeneous coalition with other actors and experts. A case study about a public science education controversy surrounding the teaching of evolution/creationism in the UK press is used to investigate in detail how connections and coalitions between experts and other actors involved in the controversy emerged and played out. The research focuses on the question of what role collaborative and other networks of experts played in terms of influence, visibility, credibility, consensus and weight of argument. Issues that are considered in the research are the status of the members of the coalitions forming during the debate and how it is displayed in media representations and letters and petitions, and also how these networks and coalitions of experts perform in relation to each other. PMID:23045882

Body area network--a key infrastructure element for patient-centered telemedicine.

PubMed

Norgall, Thomas; Schmidt, Robert; von der Grün, Thomas

2004-01-01

The Body Area Network (BAN) extends the range of existing wireless network technologies by an ultra-low range, ultra-low power network solution optimised for long-term or continuous healthcare applications. It enables wireless radio communication between several miniaturised, intelligent Body Sensor (or actor) Units (BSU) and a single Body Central Unit (BCU) worn at the human body. A separate wireless transmission link from the BCU to a network access point--using different technology--provides for online access to BAN components via usual network infrastructure. The BAN network protocol maintains dynamic ad-hoc network configuration scenarios and co-existence of multiple networks.BAN is expected to become a basic infrastructure element for electronic health services: By integrating patient-attached sensors and mobile actor units, distributed information and data processing systems, the range of medical workflow can be extended to include applications like wireless multi-parameter patient monitoring and therapy support. Beyond clinical use and professional disease management environments, private personal health assistance scenarios (without financial reimbursement by health agencies / insurance companies) enable a wide range of applications and services in future pervasive computing and networking environments.

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)

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.

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

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.

A network approach for researching political feasibility of healthcare reform: the case of universal healthcare system in Taiwan.

PubMed

Wang, Guang-Xu

2012-12-01

This study evaluates the political feasibility of healthcare reform taking place in Taiwan in the past decade. Since Taiwan adopted National Health Insurance (NHI) in 1995, it has provided coverage for virtually all of the island's citizens. However, the imbalance between expenditure and revenue has resulted in a cycle of unsustainable spending which has necessitated financial reforms and political confrontations. By applying social network analysis, this paper examines multiple types of ties between policy elites and power distribution that have evolved in crucial policy events of the NHI's financial reforms between 1998 and 2010. Data sources include official documents and 62 social network interviews that were held with government officials and related unofficial policy participants. Blockmodeling and multidimensional scaling (MDS) are used to determine the major participants and network structures in the NHI domain, as well as the influential policy actors, based on information transmission, resource exchange, reputation attribution and action-set coalition networks in Taiwan's current political situation. The results show that although both public actors and all medical associations are the leading actors in the NHI reform, without good communication with societal actors, the promotion of reform proposals ends in failure. As a tool of political feasibility evaluation, social network analysis can map the political conflict between policy stakeholders systematically when policy makers pursue the result of policy adoption. Copyright © 2012 Elsevier Ltd. All rights reserved.

Laser dynamics: The system dynamics and network theory of optoelectronic integrated circuit design

NASA Astrophysics Data System (ADS)

Tarng, Tom Shinming-T. K.

Laser dynamics is the system dynamics, communication and network theory for the design of opto-electronic integrated circuit (OEIC). Combining the optical network theory and optical communication theory, the system analysis and design for the OEIC fundamental building blocks is considered. These building blocks include the direct current modulation, inject light modulation, wideband filter, super-gain optical amplifier, E/O and O/O optical bistability and current-controlled optical oscillator. Based on the rate equations, the phase diagram and phase portrait analysis is applied to the theoretical studies and numerical simulation. The OEIC system design methodologies are developed for the OEIC design. Stimulating-field-dependent rate equations are used to model the line-width narrowing/broadening mechanism for the CW mode and frequency chirp of semiconductor lasers. The momentary spectra are carrier-density-dependent. Furthermore, the phase portrait analysis and the nonlinear refractive index is used to simulate the single mode frequency chirp. The average spectra of chaos, period doubling, period pulsing, multi-loops and analog modulation are generated and analyzed. The bifurcation-chirp design chart with modulation depth and modulation frequency as parameters is provided for design purpose.

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

PubMed Central

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

2016-01-01

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

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

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

Transnationalisation within School Education:The Interconnection between Actors, Structures and Mechanisms

ERIC Educational Resources Information Center

Schneider, Claudia

2017-01-01

The current literature of school education, transnationalisation and migration explores actors, structures and social mechanisms, however, tends to focus on these analytical levels separately. This article advocates a more explicit analysis of the interconnections of structures, actors and mechanisms within and across schools and wider national…

Functional network-based statistics in depression: Theory of mind subnetwork and importance of parietal region.

PubMed

Lai, Chien-Han; Wu, Yu-Te; Hou, Yuh-Ming

2017-08-01

The functional network analysis of whole brain is an emerging field for research in depression. We initiated this study to investigate which subnetwork is significantly altered within the functional connectome in major depressive disorder (MDD). The study enrolled 52 first-episode medication-naïve patients with MDD and 40 controls for functional network analysis. All participants received the resting-state functional imaging using a 3-Tesla magnetic resonance scanner. After preprocessing, we calculated the connectivity matrix of functional connectivity in whole brain for each subject. The network-based statistics of connectome was used to perform group comparisons between patients and controls. The correlations between functional connectivity and clinical parameters were also performed. MDD patients had significant alterations in the network involving "theory of mind" regions, such as the left precentral gyrus, left angular gyrus, bilateral rolandic operculums and left inferior frontal gyrus. The center node of significant network was the left angular gyrus. No significant correlations of functional connectivity within the subnetwork and clinical parameters were noted. Functional connectivity of "theory of mind" subnetwork may be the core issue for pathophysiology in MDD. In addition, the center role of parietal region should be emphasized in future study. Copyright © 2017. Published by Elsevier B.V.

Statistically Validated Networks in Bipartite Complex Systems

PubMed Central

Tumminello, Michele; Miccichè, Salvatore; Lillo, Fabrizio; Piilo, Jyrki; Mantegna, Rosario N.

2011-01-01

Many complex systems present an intrinsic bipartite structure where elements of one set link to elements of the second set. In these complex systems, such as the system of actors and movies, elements of one set are qualitatively different than elements of the other set. The properties of these complex systems are typically investigated by constructing and analyzing a projected network on one of the two sets (for example the actor network or the movie network). Complex systems are often very heterogeneous in the number of relationships that the elements of one set establish with the elements of the other set, and this heterogeneity makes it very difficult to discriminate links of the projected network that are just reflecting system's heterogeneity from links relevant to unveil the properties of the system. Here we introduce an unsupervised method to statistically validate each link of a projected network against a null hypothesis that takes into account system heterogeneity. We apply the method to a biological, an economic and a social complex system. The method we propose is able to detect network structures which are very informative about the organization and specialization of the investigated systems, and identifies those relationships between elements of the projected network that cannot be explained simply by system heterogeneity. We also show that our method applies to bipartite systems in which different relationships might have different qualitative nature, generating statistically validated networks in which such difference is preserved. PMID:21483858

Combining network analysis with Cognitive Work Analysis: insights into social organisational and cooperation analysis.

PubMed

Houghton, Robert J; Baber, Chris; Stanton, Neville A; Jenkins, Daniel P; Revell, Kirsten

2015-01-01

Cognitive Work Analysis (CWA) allows complex, sociotechnical systems to be explored in terms of their potential configurations. However, CWA does not explicitly analyse the manner in which person-to-person communication is performed in these configurations. Consequently, the combination of CWA with Social Network Analysis provides a means by which CWA output can be analysed to consider communication structure. The approach is illustrated through a case study of a military planning team. The case study shows how actor-to-actor and actor-to-function mapping can be analysed, in terms of centrality, to produce metrics of system structure under different operating conditions. In this paper, a technique for building social network diagrams from CWA is demonstrated.The approach allows analysts to appreciate the potential impact of organisational structure on a command system.

Information theory-based decision support system for integrated design of multivariable hydrometric networks

NASA Astrophysics Data System (ADS)

Keum, Jongho; Coulibaly, Paulin

2017-07-01

Adequate and accurate hydrologic information from optimal hydrometric networks is an essential part of effective water resources management. Although the key hydrologic processes in the water cycle are interconnected, hydrometric networks (e.g., streamflow, precipitation, groundwater level) have been routinely designed individually. A decision support framework is proposed for integrated design of multivariable hydrometric networks. The proposed method is applied to design optimal precipitation and streamflow networks simultaneously. The epsilon-dominance hierarchical Bayesian optimization algorithm was combined with Shannon entropy of information theory to design and evaluate hydrometric networks. Specifically, the joint entropy from the combined networks was maximized to provide the most information, and the total correlation was minimized to reduce redundant information. To further optimize the efficiency between the networks, they were designed by maximizing the conditional entropy of the streamflow network given the information of the precipitation network. Compared to the traditional individual variable design approach, the integrated multivariable design method was able to determine more efficient optimal networks by avoiding the redundant stations. Additionally, four quantization cases were compared to evaluate their effects on the entropy calculations and the determination of the optimal networks. The evaluation results indicate that the quantization methods should be selected after careful consideration for each design problem since the station rankings and the optimal networks can change accordingly.

Analysing published global Ebola Virus Disease research using social network analysis

PubMed Central

Hagel, Christiane; Weidemann, Felix; Gauch, Stephan; Edwards, Suzanne

2017-01-01

Introduction The 2014/2015 West African Ebola Virus Disease (EVD) outbreak attracted global attention. Numerous opinions claimed that the global response was impaired, in part because, the EVD research was neglected, although quantitative or qualitative studies did not exist. Our objective was to analyse how the EVD research landscape evolved by exploring the existing research network and its communities before and during the outbreak in West Africa. Methods/ Principal findings Social network analysis (SNA) was used to analyse collaborations between institutions named by co-authors as affiliations in publications on EVD. Bibliometric data of publications on EVD between 1976 and 2015 was collected from Thomson Reuters’ Web of Science Core Collection (WoS). Freely available software was used for network analysis at a global-level and for 10-year periods. The networks are presented as undirected-weighted graphs. Rankings by degree and betweenness were calculated to identify central and powerful network positions; modularity function was used to identify research communities. Overall 4,587 publications were identified, of which 2,528 were original research articles. Those yielded 1,644 authors’ affiliated institutions and 9,907 connections for co-authorship network construction. The majority of institutions were from the USA, Canada and Europe. Collaborations with research partners on the African continent did exist, but less frequently. Around six highly connected organisations in the network were identified with powerful and broker positions. Network characteristics varied widely among the 10-year periods and evolved from 30 to 1,489 institutions and 60 to 9,176 connections respectively. Most influential actors are from public or governmental institutions whereas private sector actors, in particular the pharmaceutical industry, are largely absent. Conclusion/ Significance Research output on EVD has increased over time and surged during the 2014/2015 outbreak. The

Theory of networked minority games based on strategy pattern dynamics.

PubMed

Lo, T S; Chan, H Y; Hui, P M; Johnson, N F

2004-11-01

We formulate a theory of agent-based models in which agents compete to be in a winning group. The agents may be part of a network or not, and the winning group may be a minority group or not. An important feature of the present formalism is its focus on the dynamical pattern of strategy rankings, and its careful treatment of the strategy ties which arise during the system's temporal evolution. We apply it to the minority game with connected populations. Expressions for the mean success rate among the agents and for the mean success rate for agents with k neighbors are derived. We also use the theory to estimate the value of connectivity p above which the binary-agent-resource system with high resource levels makes the transition into the high-connectivity state.

Construction of multi-agent mobile robots control system in the problem of persecution with using a modified reinforcement learning method based on neural networks

NASA Astrophysics Data System (ADS)

Patkin, M. L.; Rogachev, G. N.

2018-02-01

A method for constructing a multi-agent control system for mobile robots based on training with reinforcement using deep neural networks is considered. Synthesis of the management system is proposed to be carried out with reinforcement training and the modified Actor-Critic method, in which the Actor module is divided into Action Actor and Communication Actor in order to simultaneously manage mobile robots and communicate with partners. Communication is carried out by sending partners at each step a vector of real numbers that are added to the observation vector and affect the behaviour. Functions of Actors and Critic are approximated by deep neural networks. The Critics value function is trained by using the TD-error method and the Actor’s function by using DDPG. The Communication Actor’s neural network is trained through gradients received from partner agents. An environment in which a cooperative multi-agent interaction is present was developed, computer simulation of the application of this method in the control problem of two robots pursuing two goals was carried out.

The 1% Rule in Four Digital Health Social Networks: An Observational Study

PubMed Central

2014-01-01

Background In recent years, cyberculture has informally reported a phenomenon named the 1% rule, or 90-9-1 principle, which seeks to explain participatory patterns and network effects within Internet communities. The rule states that 90% of actors observe and do not participate, 9% contribute sparingly, and 1% of actors create the vast majority of new content. This 90%, 9%, and 1% are also known as Lurkers, Contributors, and Superusers, respectively. To date, very little empirical research has been conducted to verify the 1% rule. Objective The 1% rule is widely accepted in digital marketing. Our goal was to determine if the 1% rule applies to moderated Digital Health Social Networks (DHSNs) designed to facilitate behavior change. Methods To help gain insight into participatory patterns, descriptive data were extracted from four long-standing DHSNs: the AlcoholHelpCenter, DepressionCenter, PanicCenter, and StopSmokingCenter sites. Results During the study period, 63,990 actors created 578,349 posts. Less than 25% of actors made one or more posts. The applicability of the 1% rule was confirmed as Lurkers, Contributors, and Superusers accounted for a weighted average of 1.3% (n=4668), 24.0% (n=88,732), and 74.7% (n=276,034) of content. Conclusions The 1% rule was consistent across the four DHSNs. As social network sustainability requires fresh content and timely interactions, these results are important for organizations actively promoting and managing Internet communities. Superusers generate the vast majority of traffic and create value, so their recruitment and retention is imperative for long-term success. Although Lurkers may benefit from observing interactions between Superusers and Contributors, they generate limited or no network value. The results of this study indicate that DHSNs may be optimized to produce network effects, positive externalities, and bandwagon effects. Further research in the development and expansion of DHSNs is required. PMID:24496109

The 1% rule in four digital health social networks: an observational study.

PubMed

van Mierlo, Trevor

2014-02-04

In recent years, cyberculture has informally reported a phenomenon named the 1% rule, or 90-9-1 principle, which seeks to explain participatory patterns and network effects within Internet communities. The rule states that 90% of actors observe and do not participate, 9% contribute sparingly, and 1% of actors create the vast majority of new content. This 90%, 9%, and 1% are also known as Lurkers, Contributors, and Superusers, respectively. To date, very little empirical research has been conducted to verify the 1% rule. The 1% rule is widely accepted in digital marketing. Our goal was to determine if the 1% rule applies to moderated Digital Health Social Networks (DHSNs) designed to facilitate behavior change. To help gain insight into participatory patterns, descriptive data were extracted from four long-standing DHSNs: the AlcoholHelpCenter, DepressionCenter, PanicCenter, and StopSmokingCenter sites. During the study period, 63,990 actors created 578,349 posts. Less than 25% of actors made one or more posts. The applicability of the 1% rule was confirmed as Lurkers, Contributors, and Superusers accounted for a weighted average of 1.3% (n=4668), 24.0% (n=88,732), and 74.7% (n=276,034) of content. The 1% rule was consistent across the four DHSNs. As social network sustainability requires fresh content and timely interactions, these results are important for organizations actively promoting and managing Internet communities. Superusers generate the vast majority of traffic and create value, so their recruitment and retention is imperative for long-term success. Although Lurkers may benefit from observing interactions between Superusers and Contributors, they generate limited or no network value. The results of this study indicate that DHSNs may be optimized to produce network effects, positive externalities, and bandwagon effects. Further research in the development and expansion of DHSNs is required.

An object recognition method based on fuzzy theory and BP networks

NASA Astrophysics Data System (ADS)

Wu, Chuan; Zhu, Ming; Yang, Dong

2006-01-01

It is difficult to choose eigenvectors when neural network recognizes object. It is possible that the different object eigenvectors is similar or the same object eigenvectors is different under scaling, shifting, rotation if eigenvectors can not be chosen appropriately. In order to solve this problem, the image is edged, the membership function is reconstructed and a new threshold segmentation method based on fuzzy theory is proposed to get the binary image. Moment invariant of binary image is extracted and normalized. Some time moment invariant is too small to calculate effectively so logarithm of moment invariant is taken as input eigenvectors of BP network. The experimental results demonstrate that the proposed approach could recognize the object effectively, correctly and quickly.

Associations between Perceived HIV Stigma and Quality of Life at the Dyadic Lvel: The Actor-Partner Interdependence Model

PubMed Central

Liu, Hongjie; Xu, Yongfang; Lin, Xinjin; Shi, Jian; Chen, Shiyi

2013-01-01

Background Few studies have investigated the relationship between HIV-related stigma and quality life at the dyadic level. The objective of this study was to examine the actor and partner effects of stigma that was perceived by people living with HIV/AIDS (PLWHAs) and caregivers on quality of life at the dyadic level. Method A survey was conducted among 148 dyads consisting of one PLWHA and one caregiver (296 participants) in Nanning, China. The interdependent relationship between a pair of dyadic members that influences the associations between stigma and quality of life was analyzed, using an innovative dyadic analysis technique: the Actor-Partner Interdependence Model (APIM). Results We found in this dyadic analysis that (1) PLWHAs compared to their caregivers exhibited a higher level of perceived HIV stigma and lower level of quality of life measured in four domains; (2) both PLWHAs' and caregivers' perceived HIV stigma influenced their own quality of life; (3) The quality of life was not substantially influenced by their partners' perceived stigma; and (4) Both actor and partner effects of stigma on quality of life were similar among PLWHAs and their caregivers. Conclusion As HIV stigma and quality of life are complex phenomena rooted in cultures, intervention programs should be carefully planned based on social or cognitive theories and should be culturally adopted. PMID:23383343

Social Network Analysis and Qualitative Interviews for Assessing Geographic Characteristics of Tourism Business Networks.

PubMed

Kelman, Ilan; Luthe, Tobias; Wyss, Romano; Tørnblad, Silje H; Evers, Yvette; Curran, Marina Martin; Williams, Richard J; Berlow, Eric L

2016-01-01

This study integrates quantitative social network analysis (SNA) and qualitative interviews for understanding tourism business links in isolated communities through analysing spatial characteristics. Two case studies are used, the Surselva-Gotthard region in the Swiss Alps and Longyearbyen in the Arctic archipelago of Svalbard, to test the spatial characteristics of physical proximity, isolation, and smallness for understanding tourism business links. In the larger Surselva-Gotthard region, we found a strong relationship between geographic separation of the three communities on compartmentalization of the collaboration network. A small set of businesses played a central role in steering collaborative decisions for this community, while a group of structurally 'peripheral' actors were less influential. By contrast, the business community in Svalbard showed compartmentalization that was independent of geographic distance between actors. Within towns of similar size and governance scale, Svalbard is more compartmentalized, and those compartments are not driven by geographic separation of the collaboration clusters. This compartmentalization in Svalbard was reflected in a lower density of formal business collaboration ties compared to the communities of the Alps. We infer that the difference is due to Svalbard having higher cultural diversity and population turnover than the Alps communities. We propose that integrating quantitative network analysis from simple surveys with qualitative interviews targeted from the network results is an efficient general approach to identify regionally specific constraints and opportunities for effective governance.

Social Network Analysis and Qualitative Interviews for Assessing Geographic Characteristics of Tourism Business Networks

PubMed Central

Luthe, Tobias; Wyss, Romano; Tørnblad, Silje H.; Evers, Yvette; Curran, Marina Martin; Williams, Richard J.; Berlow, Eric L.

2016-01-01

This study integrates quantitative social network analysis (SNA) and qualitative interviews for understanding tourism business links in isolated communities through analysing spatial characteristics. Two case studies are used, the Surselva-Gotthard region in the Swiss Alps and Longyearbyen in the Arctic archipelago of Svalbard, to test the spatial characteristics of physical proximity, isolation, and smallness for understanding tourism business links. In the larger Surselva-Gotthard region, we found a strong relationship between geographic separation of the three communities on compartmentalization of the collaboration network. A small set of businesses played a central role in steering collaborative decisions for this community, while a group of structurally ‘peripheral’ actors were less influential. By contrast, the business community in Svalbard showed compartmentalization that was independent of geographic distance between actors. Within towns of similar size and governance scale, Svalbard is more compartmentalized, and those compartments are not driven by geographic separation of the collaboration clusters. This compartmentalization in Svalbard was reflected in a lower density of formal business collaboration ties compared to the communities of the Alps. We infer that the difference is due to Svalbard having higher cultural diversity and population turnover than the Alps communities. We propose that integrating quantitative network analysis from simple surveys with qualitative interviews targeted from the network results is an efficient general approach to identify regionally specific constraints and opportunities for effective governance. PMID:27258007

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.

Who Needs What? Some Thoughts on the Possibility of Using Psychology in Actor Training.

ERIC Educational Resources Information Center

Vulova, Marina

2001-01-01

Contends that the aim of professional actor training is to reveal and develop an actor's individuality. Proposes that the responsibility of drama teachers is to lead training in such away that students feel accepted, understood, and respected. Proposes that psychodrama is the most appropriate method for student and professional actors' personal…

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

Understanding complex interactions using social network analysis.

PubMed

Pow, Janette; Gayen, Kaberi; Elliott, Lawrie; Raeside, Robert

2012-10-01

The aim of this paper is to raise the awareness of social network analysis as a method to facilitate research in nursing research. The application of social network analysis in assessing network properties has allowed greater insight to be gained in many areas including sociology, politics, business organisation and health care. However, the use of social networks in nursing has not received sufficient attention. Review of literature and illustration of the application of the method of social network analysis using research examples. First, the value of social networks will be discussed. Then by using illustrative examples, the value of social network analysis to nursing will be demonstrated. The method of social network analysis is found to give greater insights into social situations involving interactions between individuals and has particular application to the study of interactions between nurses and between nurses and patients and other actors. Social networks are systems in which people interact. Two quantitative techniques help our understanding of these networks. The first is visualisation of the network. The second is centrality. Individuals with high centrality are key communicators in a network. Applying social network analysis to nursing provides a simple method that helps gain an understanding of human interaction and how this might influence various health outcomes. It allows influential individuals (actors) to be identified. Their influence on the formation of social norms and communication can determine the extent to which new interventions or ways of thinking are accepted by a group. Thus, working with key individuals in a network could be critical to the success and sustainability of an intervention. Social network analysis can also help to assess the effectiveness of such interventions for the recipient and the service provider. © 2012 Blackwell Publishing Ltd.

Neuroimaging of the joint Simon effect with believed biological and non-biological co-actors.

PubMed

Wen, Tanya; Hsieh, Shulan

2015-01-01

Performing a task alone or together with another agent can produce different outcomes. The current study used event-related functional magnetic resonance imaging (fMRI) to investigate the neural underpinnings when participants performed a Go/Nogo task alone or complementarily with another co-actor (unseen), whom was believed to be another human or a computer. During both complementary tasks, reaction time data suggested that participants integrated the potential action of their co-actor in their own action planning. Compared to the single-actor task, increased parietal and precentral activity during complementary tasks as shown in the fMRI data further suggested representation of the co-actor's response. The superior frontal gyrus of the medial prefrontal cortex was differentially activated in the human co-actor condition compared to the computer co-actor condition. The medial prefrontal cortex, involved thinking about the beliefs and intentions of other people, possibly reflects a social-cognitive aspect or self-other discrimination during the joint task when believing a biological co-actor is present. Our results suggest that action co-representation can occur even offline with any agent type given a priori information that they are co-acting; however, additional regions are recruited when participants believe they are task-sharing with another human.

Applications of Social Network Analysis

NASA Astrophysics Data System (ADS)

Thilagam, P. Santhi

A social network [2] is a description of the social structure between actors, mostly persons, groups or organizations. It indicates the ways in which they are connected with each other by some relationship such as friendship, kinship, finance exchange etc. In a nutshell, when the person uses already known/unknown people to create new contacts, it forms social networking. The social network is not a new concept rather it can be formed when similar people interact with each other directly or indirectly to perform particular task. Examples of social networks include a friendship networks, collaboration networks, co-authorship networks, and co-employees networks which depict the direct interaction among the people. There are also other forms of social networks, such as entertainment networks, business Networks, citation networks, and hyperlink networks, in which interaction among the people is indirect. Generally, social networks operate on many levels, from families up to the level of nations and assists in improving interactive knowledge sharing, interoperability and collaboration.

The influence of socio cultural dynamics on convergence communication of aquaculture agribusiness actors

NASA Astrophysics Data System (ADS)

Oktavia, Y.

2018-03-01

This research aims to: (1) Analyze the level of socio-cultural dynamics of agibusiness aquaculture actors. (2) Analyze the influence of socio-cultural dynamics on convergence communication of capacity development of aquaculture agribusiness actors.Data was collected by questionnaire and interview of group members on agribusiness. Data analyze was done by descriptive and inferential statistics with using SEM method. The result of descriptive statistics on 284 agribusiness members showed that: Socio-cultural dynamics of agibusiness aquaculture actors was in low category, as shown by lack of the role of customary institutions and quality of local leadership.The communication convergence is significantly and positively influenced by the communication behavior of agribusiness actors in access information.

Local energy governance in vermont: an analysis of energy system transition strategies and actor capacity

NASA Astrophysics Data System (ADS)

Rowse, Tarah

and financial stimulus are essential if Vermont hopes to increase strategic energy planning alignment and spur whole-scale energy system change. Study 2 examined local energy actors to assess their ability to develop and sustain energy action on the local level. A survey of 120 municipalities collected statewide baseline data covering the structures, processes, and activities of local energy actors. The analysis examined the role that various forms of capacity play in local energy activity. The results show that towns with higher incomes are more likely to have local energy actors and towns with higher populations have higher aggregate energy activity levels. Structurally, energy actors that had both an energy coordinator and an energy committee were more active, and municipal committees were more active than independent committees. Access to a budget and volunteer engagement were both associated with higher activity levels. The network of local energy actors in Vermont consists of committed and knowledgeable volunteers. Yet, the capacity of these local energy actors to implement sustainable energy change is limited due to resource constraints of time and money. In most cases, the scope of municipal energy planning strategy is modest. Prioritization of strategy and action at the central and local levels, along with increased interaction and coordination, is necessary to increase the regional compatibility and pace of energy system transformation.

A Hockey Night in Canada: An Imagined Conversation between Theorists

ERIC Educational Resources Information Center

Fogel, Curtis

2010-01-01

In this paper, various methodological issues surrounding the sociological study of sport are explored. Through an imagined dialogue between two graduate students at a hockey game, this work brings together three divergent approaches to social enquiry: Positivist Grounded Theory, Constructivist Grounded Theory, and Actor-Network Theory. This paper…

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.

Language and Tools for Networkers

ERIC Educational Resources Information Center

Wielinga, Eelke; Vrolijk, Maarten

2009-01-01

The network society has a major impact on knowledge systems, and in agricultural and rural development. It has changed relationships between actors such as farmers, extension workers, researchers, policy-makers, businessmen and consumers. These changes require different language, concepts and tools compared to the time that it was thought that…

ACToR A Aggregated Computational Toxicology Resource

EPA Science Inventory

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

Locally excitatory, globally inhibitory oscillator networks: theory and application to scene segmentation

NASA Astrophysics Data System (ADS)

Wang, DeLiang; Terman, David

1995-01-01

A novel class of locally excitatory, globally inhibitory oscillator networks (LEGION) is proposed and investigated analytically and by computer simulation. The model of each oscillator corresponds to a standard relaxation oscillator with two time scales. The network exhibits a mechanism of selective gating, whereby an oscillator jumping up to its active phase rapidly recruits the oscillators stimulated by the same pattern, while preventing other oscillators from jumping up. We show analytically that with the selective gating mechanism the network rapidly achieves both synchronization within blocks of oscillators that are stimulated by connected regions and desynchronization between different blocks. Computer simulations demonstrate LEGION's promising ability for segmenting multiple input patterns in real time. This model lays a physical foundation for the oscillatory correlation theory of feature binding, and may provide an effective computational framework for scene segmentation and figure/ground segregation.

[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.

Educational Theories, Cultures and Learning: A Critical Perspective. Critical Perspectives on Education

ERIC Educational Resources Information Center

Daniels, Harry, Ed.; Lauder, Hugh, Ed.; Porter, Jill, Ed.

2011-01-01

"Educational Theories, Cultures and Learning" focuses on how education is understood in different cultures, the theories and related assumptions we make about learners and students and how we think about them, and how we can understand the principle actors in education--learners and teachers. Within this volume, internationally renowned…

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.

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

Applying network theory to animal movements to identify properties of landscape space use.

PubMed

Bastille-Rousseau, Guillaume; Douglas-Hamilton, Iain; Blake, Stephen; Northrup, Joseph M; Wittemyer, George

2018-04-01

Network (graph) theory is a popular analytical framework to characterize the structure and dynamics among discrete objects and is particularly effective at identifying critical hubs and patterns of connectivity. The identification of such attributes is a fundamental objective of animal movement research, yet network theory has rarely been applied directly to animal relocation data. We develop an approach that allows the analysis of movement data using network theory by defining occupied pixels as nodes and connection among these pixels as edges. We first quantify node-level (local) metrics and graph-level (system) metrics on simulated movement trajectories to assess the ability of these metrics to pull out known properties in movement paths. We then apply our framework to empirical data from African elephants (Loxodonta africana), giant Galapagos tortoises (Chelonoidis spp.), and mule deer (Odocoileous hemionus). Our results indicate that certain node-level metrics, namely degree, weight, and betweenness, perform well in capturing local patterns of space use, such as the definition of core areas and paths used for inter-patch movement. These metrics were generally applicable across data sets, indicating their robustness to assumptions structuring analysis or strategies of movement. Other metrics capture local patterns effectively, but were sensitive to specified graph properties, indicating case specific applications. Our analysis indicates that graph-level metrics are unlikely to outperform other approaches for the categorization of general movement strategies (central place foraging, migration, nomadism). By identifying critical nodes, our approach provides a robust quantitative framework to identify local properties of space use that can be used to evaluate the effect of the loss of specific nodes on range wide connectivity. Our network approach is intuitive, and can be implemented across imperfectly sampled or large-scale data sets efficiently, providing a

Action adaptation during natural unfolding social scenes influences action recognition and inferences made about actor beliefs.

PubMed

Keefe, Bruce D; Wincenciak, Joanna; Jellema, Tjeerd; Ward, James W; Barraclough, Nick E

2016-07-01

When observing another individual's actions, we can both recognize their actions and infer their beliefs concerning the physical and social environment. The extent to which visual adaptation influences action recognition and conceptually later stages of processing involved in deriving the belief state of the actor remains unknown. To explore this we used virtual reality (life-size photorealistic actors presented in stereoscopic three dimensions) to see how visual adaptation influences the perception of individuals in naturally unfolding social scenes at increasingly higher levels of action understanding. We presented scenes in which one actor picked up boxes (of varying number and weight), after which a second actor picked up a single box. Adaptation to the first actor's behavior systematically changed perception of the second actor. Aftereffects increased with the duration of the first actor's behavior, declined exponentially over time, and were independent of view direction. Inferences about the second actor's expectation of box weight were also distorted by adaptation to the first actor. Distortions in action recognition and actor expectations did not, however, extend across different actions, indicating that adaptation is not acting at an action-independent abstract level but rather at an action-dependent level. We conclude that although adaptation influences more complex inferences about belief states of individuals, this is likely to be a result of adaptation at an earlier action recognition stage rather than adaptation operating at a higher, more abstract level in mentalizing or simulation systems.

Characteristics of pornography film actors: self-report versus perceptions of college students.

PubMed

Griffith, James D; Hayworth, Michelle; Adams, Lea T; Mitchell, Sharon; Hart, Christian

2013-05-01

The assumed characteristics of individuals in the adult entertainment industry have been used to advocate positions for and against pornography. Although prior studies have investigated perceptions of porn actors, no data on the actual characteristics of this group exist. The present study compared the self-reports of 105 male and 177 female porn actors to the perceptions of 399 college students on childhood sexual abuse (CSA), self-esteem, work and non-work sexual behaviors, and safe sex issues. College students were asked to identify the characteristics associated with either a male or female porn star. College students provided underestimates for both female and male porn actors on self-esteem, age of first intercourse, lifetime number of partners outside of work, ideal experience in a romantic partner, concerns regarding sexually transmitted diseases (STDs), enjoyment of sex, and condom use during a first time sexual encounter, but overestimated earnings. Additional differences among male porn stars included an underestimate of the number of partners at work. For female porn stars, college students underestimated their enjoyment of work, the probability of catching an STD, and having unprotected sex. Although there were no significant differences on perceived rates of childhood abuse of porn actors, the incidence of CSA among the porn actor participants were within the ranges of the general population. The majority of college student stereotypes were not supported regarding the perceptions of porn actors. These findings were discussed within the context of attributing unfounded characteristics of individuals to an entire industry.

A Collaboration Network Model Of Cytokine-Protein Network

NASA Astrophysics Data System (ADS)

Zou, Sheng-Rong; Zhou, Ta; Peng, Yu-Jing; Guo, Zhong-Wei; Gu, Chang-Gui; He, Da-Ren

2008-03-01

Complex networks provide us a new view for investigation of immune systems. We collect data through STRING database and present a network description with cooperation network model. The cytokine-protein network model we consider is constituted by two kinds of nodes, one is immune cytokine types which can be regarded as collaboration acts, the other one is protein type which can be regarded as collaboration actors. From act degree distribution that can be well described by typical SPL (shifted power law) functions [1], we find that HRAS, TNFRSF13C, S100A8, S100A1, MAPK8, S100A7, LIF, CCL4, CXCL13 are highly collaborated with other proteins. It reveals that these mediators are important in cytokine-protein network to regulate immune activity. Dyad in the collaboration networks can be defined as two proteins and they appear in one cytokine collaboration relationship. The dyad act degree distribution can also be well described by typical SPL functions. [1] Assortativity and act degree distribution of some collaboration networks, Hui Chang, Bei-Bei Su, Yue-Ping Zhou, Daren He, Physica A, 383 (2007) 687-702

A Network Analysis of Social Balance in Conflict in the Maghreb

DTIC Science & Technology

2013-03-01

relationships from Table 6 shown in graph form. Graph by author using Pajek ( Batagelj & Mrvar , 1996 ...author using Pajek ( Batagelj & Mrvar , 1996 )................................................................................................ 4-17 Figure...negative and black is positive. By author using Pajek ( Batagelj & Mrvar , 1996 ). ..... 4-21 Figure 23: Network Graph of 10 Actor Network (Post-French

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.

Practicing Technology Implementation: The Case of an Enterprise System

ERIC Educational Resources Information Center

Awazu, Yukika

2013-01-01

Drawing on four theories of practice--Communities of Practice (CoP), Bourdieu's theory of practice, Pickering's mangle of practice, and Actor Network Theory (ANT), the study provides an in-depth understanding about technology implementation practice. Analysis of an Enterprise System implementation project in a software manufacturing…

From conflict management to reward-based decision making: actors and critics in primate medial frontal cortex.

PubMed

Silvetti, Massimo; Alexander, William; Verguts, Tom; Brown, Joshua W

2014-10-01

The role of the medial prefrontal cortex (mPFC) and especially the anterior cingulate cortex has been the subject of intense debate for the last decade. A number of theories have been proposed to account for its function. Broadly speaking, some emphasize cognitive control, whereas others emphasize value processing; specific theories concern reward processing, conflict detection, error monitoring, and volatility detection, among others. Here we survey and evaluate them relative to experimental results from neurophysiological, anatomical, and cognitive studies. We argue for a new conceptualization of mPFC, arising from recent computational modeling work. Based on reinforcement learning theory, these new models propose that mPFC is an Actor-Critic system. This system is aimed to predict future events including rewards, to evaluate errors in those predictions, and finally, to implement optimal skeletal-motor and visceromotor commands to obtain reward. This framework provides a comprehensive account of mPFC function, accounting for and predicting empirical results across different levels of analysis, including monkey neurophysiology, human ERP, human neuroimaging, and human behavior. Copyright © 2013 Elsevier Ltd. All rights reserved.

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

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

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

Zhang, Hong; Li, Jie, E-mail: prof.li@foxmail.com

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 andmore » 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

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.

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

"Too Many Actors and Too Few Jobs": A Case for Curriculum Extension in UK Vocational Actor Training

ERIC Educational Resources Information Center

Wilkie, Ian

2015-01-01

This article questions the current situation for vocational acting training (VAT) in the UK. It aims to provide an update on the report into burgeoning provision of acting training (and the attempt to address subsequent high rates of actor unemployment) that was originally undertaken by the Calouste Gulbenkian Foundation (CGF, 1975) in their…

Kevin Bacon and Graph Theory

ERIC Educational Resources Information Center

Hopkins, Brian

2004-01-01

The interconnected world of actors and movies is a familiar, rich example for graph theory. This paper gives the history of the "Kevin Bacon Game" and makes extensive use of a Web site to analyze the underlying graph. The main content is the classroom development of the weighted average to determine the best choice of "center" for the graph. The…

Economic Feasibility of Wireless Sensor Network-Based Service Provision in a Duopoly Setting with a Monopolist Operator.

PubMed

Sanchis-Cano, Angel; Romero, Julián; Sacoto-Cabrera, Erwin J; Guijarro, Luis

2017-11-25

We analyze the feasibility of providing Wireless Sensor Network-data-based services in an Internet of Things scenario from an economical point of view. The scenario has two competing service providers with their own private sensor networks, a network operator and final users. The scenario is analyzed as two games using game theory. In the first game, sensors decide to subscribe or not to the network operator to upload the collected sensing-data, based on a utility function related to the mean service time and the price charged by the operator. In the second game, users decide to subscribe or not to the sensor-data-based service of the service providers based on a Logit discrete choice model related to the quality of the data collected and the subscription price. The sinks and users subscription stages are analyzed using population games and discrete choice models, while network operator and service providers pricing stages are analyzed using optimization and Nash equilibrium concepts respectively. The model is shown feasible from an economic point of view for all the actors if there are enough interested final users and opens the possibility of developing more efficient models with different types of services.

Identity theory and personality theory: mutual relevance.

PubMed

Stryker, Sheldon

2007-12-01

Some personality psychologists have found a structural symbolic interactionist frame and identity theory relevant to their work. This frame and theory, developed in sociology, are first reviewed. Emphasized in the review are a multiple identity conception of self, identities as internalized expectations derived from roles embedded in organized networks of social interaction, and a view of social structures as facilitators in bringing people into networks or constraints in keeping them out, subsequently, attention turns to a discussion of the mutual relevance of structural symbolic interactionism/identity theory and personality theory, looking to extensions of the current literature on these topics.

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.

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

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.

Toward multidomain integrated network management for ATM and SDH networks

NASA Astrophysics Data System (ADS)

Galis, Alex; Gantenbein, Dieter; Covaci, Stefan; Bianza, Carlo; Karayannis, Fotis; Mykoniatis, George

1996-12-01

ACTS Project AC080 MISA has embarked upon the task of realizing and validating via European field trials integrated end-to-end management of hybrid SDH and ATM networks in the framework of open network provision. This paper reflects the initial work of the project and gives an overview of the proposed MISA system architecture and initial design. We describe our understanding of the underlying enterprise model in the network management context, including the concept of the MISA Global Broadband Connectivity Management service. It supports Integrated Broadband Communication by defining an end-to-end broadband connection service in a multi-domain business environment. Its implementation by the MISA consortium within trials across Europe aims for an efficient management of network resources of the SDH and ATM infrastructure, considering optimum end-to-end quality of service and the needs of a number of telecommunication actors: customers, value-added service providers, and network providers.

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.

Media actors' perceptions of their roles in reporting food incidents.

PubMed

Wilson, Annabelle M; Henderson, Julie; Coveney, John; Meyer, Samantha B; Webb, Trevor; Calnan, Michael; Caraher, Martin; Lloyd, Sue; McCullum, Dean; Elliott, Anthony; Ward, Paul R

2014-12-18

Previous research has shown that the media can play a role in shaping consumer perceptions during a public health crisis. In order for public health professionals to communicate well-informed health information to the media, it is important that they understand how media view their role in transmitting public health information to consumers and decide what information to present. This paper reports the perceptions of media actors from three countries about their role in reporting information during a food incident. This information is used to present ideas and suggestions for public health professionals working with media during food incidents. Thirty three semi-structured interviews with media actors from Australia, New Zealand and the United Kingdom were conducted and analysed thematically. Media actors were recruited via purposive sampling using a sampling strategy, from a variety of formats including newspaper, television, radio and online. Media actors said that during a food incident, they play two roles. First, they play a role in communicating information to consumers by acting as a conduit for information between the public and the relevant authorities. Second, they play a role as investigators by acting as a public watchdog. Media actors are an important source of consumer information during food incidents. Public health professionals can work with media by actively approaching them with information about food incidents; promoting to media that as public health professionals, they are best placed to provide the facts about food incidents; and by providing angles for further investigation and directing media to relevant and correct information to inform such investigations. Public health professionals who adapt how they work with media are more likely to influence media to portray messages that fit what they would like the public to know and that are in line with public health recommendations and enable consumers to engage in safe and health promoting

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.

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

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

Reframing clinical workplace learning using the theory of distributed cognition.

PubMed

Pimmer, Christoph; Pachler, Norbert; Genewein, Urs

2013-09-01

In medicine, knowledge is embodied and socially, temporally, spatially, and culturally distributed between actors and their environment. In addition, clinicians increasingly are using technology in their daily work to gain and share knowledge. Despite these characteristics, surprisingly few studies have incorporated the theory of distributed cognition (DCog), which emphasizes how cognition is distributed in a wider system in the form of multimodal representations (e.g., clinical images, speech, gazes, and gestures) between social actors (e.g., doctors and patients) in the physical environment (e.g., with technological instruments and computers). In this article, the authors provide an example of an interaction between medical actors. Using that example, they then introduce the important concepts of the DCog theory, identifying five characteristics of clinical representations-that they are interwoven, co-constructed, redundantly accessed, intersubjectively shared, and substantiated-and discuss their value for learning. By contrasting these DCog perspectives with studies from the field of medical education, the authors argue that researchers should focus future medical education scholarship on the ways in which medical actors use and connect speech, bodily movements (e.g., gestures), and the visual and haptic structures of their own bodies and of artifacts, such as technological instruments and computers, to construct complex, multimodal representations. They also argue that future scholarship should "zoom in" on detailed, moment-by-moment analysis and, at the same time, "zoom out" following the distribution of cognition through an overall system to develop a more integrated view of clinical workplace learning.

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.

Body Area Network BAN--a key infrastructure element for patient-centered medical applications.

PubMed

Schmidt, Robert; Norgall, Thomas; Mörsdorf, Joachim; Bernhard, Josef; von der Grün, Thomas

2002-01-01

The Body Area Network (BAN) concept enables wireless communication between several miniaturized, intelligent Body Sensor (or actor) Units (BSU) and a single Body Central Unit (BCU) worn at the human body. A separate wireless transmission link from the BCU to a network access point--using different technology--provides for online access to BAN data via usual network infrastructure. BAN is expected to become a basic infrastructure element for service-based electronic health assistance: By integrating patient-attached sensors and control of mobile dedicated actor units, the range of medical workflow can be extended by wireless patient monitoring and therapy support. Beyond clinical use, professional disease management environments, and private personal health assistance scenarios (without financial reimbursement by health agencies/insurance companies), BAN enables a wide range of health care applications and related services.

Quebec mental health services networks: models and implementation

PubMed Central

Fleury, Marie-Josée

2005-01-01

Abstract Purpose In the transformation of health care systems, the introduction of integrated service networks is considered to be one of the main solutions for enhancing efficiency. In the last few years, a wealth of literature has emerged on the topic of services integration. However, the question of how integrated service networks should be modelled to suit different implementation contexts has barely been touched. To fill that gap, this article presents four models for the organization of mental health integrated networks. Data sources The proposed models are drawn from three recently published studies on mental health integrated services in the province of Quebec (Canada) with the author as principal investigator. Description Following an explanation of the concept of integrated service network and a description of the Quebec context for mental health networks, the models, applicable in all settings: rural, urban or semi-urban, and metropolitan, and summarized in four figures, are presented. Discussion and conclusion To apply the models successfully, the necessity of rallying all the actors of a system, from the strategic, tactical and operational levels, according to the type of integration involved: functional/administrative, clinical and physician-system is highlighted. The importance of formalizing activities among organizations and actors in a network and reinforcing the governing mechanisms at the local level is also underlined. Finally, a number of integration strategies and key conditions of success to operationalize integrated service networks are suggested. PMID:16773157

[Participation, knowledge production, and evaluative research: participation by different actors in a mental health study].

PubMed

Furtado, Juarez Pereira; Campos, Rosana Onocko

2008-11-01

This article reflects on the interrelations between participation, knowledge production, and public policy evaluation in light of issues from our own experience with evaluative research on a municipal network of Psychosocial Care Centers (CAPS) in Brazil. The article discusses the coordination of the complex process and the potentials and limits of partnerships for conducting qualitative evaluative studies in mental health with participation by different social actors. The authors conclude that qualitative evaluative research aligned with the perspective of including different points of view representing various segments is the best approach for understanding the numerous spin-offs from the implementation of services linked to the Brazilian psychiatric reform movement, given the inherent specificities of the mental health field.

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.

Adaptive Actor-Critic Design-Based Integral Sliding-Mode Control for Partially Unknown Nonlinear Systems With Input Disturbances.

PubMed

Fan, Quan-Yong; Yang, Guang-Hong

2016-01-01

This paper is concerned with the problem of integral sliding-mode control for a class of nonlinear systems with input disturbances and unknown nonlinear terms through the adaptive actor-critic (AC) control method. The main objective is to design a sliding-mode control methodology based on the adaptive dynamic programming (ADP) method, so that the closed-loop system with time-varying disturbances is stable and the nearly optimal performance of the sliding-mode dynamics can be guaranteed. In the first step, a neural network (NN)-based observer and a disturbance observer are designed to approximate the unknown nonlinear terms and estimate the input disturbances, respectively. Based on the NN approximations and disturbance estimations, the discontinuous part of the sliding-mode control is constructed to eliminate the effect of the disturbances and attain the expected equivalent sliding-mode dynamics. Then, the ADP method with AC structure is presented to learn the optimal control for the sliding-mode dynamics online. Reconstructed tuning laws are developed to guarantee the stability of the sliding-mode dynamics and the convergence of the weights of critic and actor NNs. Finally, the simulation results are presented to illustrate the effectiveness of the proposed method.

Pioneering topological methods for network-based drug-target prediction by exploiting a brain-network self-organization theory.

PubMed

Durán, Claudio; Daminelli, Simone; Thomas, Josephine M; Haupt, V Joachim; Schroeder, Michael; Cannistraci, Carlo Vittorio

2017-04-26

The bipartite network representation of the drug-target interactions (DTIs) in a biosystem enhances understanding of the drugs' multifaceted action modes, suggests therapeutic switching for approved drugs and unveils possible side effects. As experimental testing of DTIs is costly and time-consuming, computational predictors are of great aid. Here, for the first time, state-of-the-art DTI supervised predictors custom-made in network biology were compared-using standard and innovative validation frameworks-with unsupervised pure topological-based models designed for general-purpose link prediction in bipartite networks. Surprisingly, our results show that the bipartite topology alone, if adequately exploited by means of the recently proposed local-community-paradigm (LCP) theory-initially detected in brain-network topological self-organization and afterwards generalized to any complex network-is able to suggest highly reliable predictions, with comparable performance with the state-of-the-art-supervised methods that exploit additional (non-topological, for instance biochemical) DTI knowledge. Furthermore, a detailed analysis of the novel predictions revealed that each class of methods prioritizes distinct true interactions; hence, combining methodologies based on diverse principles represents a promising strategy to improve drug-target discovery. To conclude, this study promotes the power of bio-inspired computing, demonstrating that simple unsupervised rules inspired by principles of topological self-organization and adaptiveness arising during learning in living intelligent systems (like the brain) can efficiently equal perform complicated algorithms based on advanced, supervised and knowledge-based engineering. © The Author 2017. Published by Oxford University Press.

Review of game theory applications for situation awareness

NASA Astrophysics Data System (ADS)

Blasch, Erik; Shen, Dan; Pham, Khanh D.; Chen, Genshe

2015-05-01

Game theoretical methods have been used for spectral awareness, space situational awareness (SSA), cyber situational awareness (CSA), and Intelligence, Surveillance, and Reconnaissance situation awareness (ISA). Each of these cases, awareness is supported by sensor estimation for assessment and the situation is determined from the actions of multiple players. Game theory assumes rational actors in a defined scenario; however, variations in social, cultural and behavioral factors include the dynamic nature of the context. In a dynamic data-driven application system (DDDAS), modeling must include both the measurements but also how models are used by different actors with different priorities. In this paper, we highlight the applications of game theory by reviewing the literature to determine the current state of the art and future needs. Future developments would include building towards knowledge awareness with information technology (e.g., data aggregation, access, indexing); multiscale analysis (e.g., space, time, and frequency), and software methods (e.g., architectures, cloud computing, protocols).

Ontology-based Vaccine and Drug Adverse Event Representation and Theory-guided Systematic Causal Network Analysis toward Integrative Pharmacovigilance Research

PubMed Central

He, Yongqun

2016-01-01

Compared with controlled terminologies (e.g., MedDRA, CTCAE, and WHO-ART), the community-based Ontology of AEs (OAE) has many advantages in adverse event (AE) classifications. The OAE-derived Ontology of Vaccine AEs (OVAE) and Ontology of Drug Neuropathy AEs (ODNAE) serve as AE knowledge bases and support data integration and analysis. The Immune Response Gene Network Theory explains molecular mechanisms of vaccine-related AEs. The OneNet Theory of Life treats the whole process of a life of an organism as a single complex and dynamic network (i.e., OneNet). A new “OneNet effectiveness” tenet is proposed here to expand the OneNet theory. Derived from the OneNet theory, the author hypothesizes that one human uses one single genotype-rooted mechanism to respond to different vaccinations and drug treatments, and experimentally identified mechanisms are manifestations of the OneNet blueprint mechanism under specific conditions. The theories and ontologies interact together as semantic frameworks to support integrative pharmacovigilance research. PMID:27458549

Ontology-based Vaccine and Drug Adverse Event Representation and Theory-guided Systematic Causal Network Analysis toward Integrative Pharmacovigilance Research.

PubMed

He, Yongqun

2016-06-01

Compared with controlled terminologies ( e.g. , MedDRA, CTCAE, and WHO-ART), the community-based Ontology of AEs (OAE) has many advantages in adverse event (AE) classifications. The OAE-derived Ontology of Vaccine AEs (OVAE) and Ontology of Drug Neuropathy AEs (ODNAE) serve as AE knowledge bases and support data integration and analysis. The Immune Response Gene Network Theory explains molecular mechanisms of vaccine-related AEs. The OneNet Theory of Life treats the whole process of a life of an organism as a single complex and dynamic network ( i.e. , OneNet). A new "OneNet effectiveness" tenet is proposed here to expand the OneNet theory. Derived from the OneNet theory, the author hypothesizes that one human uses one single genotype-rooted mechanism to respond to different vaccinations and drug treatments, and experimentally identified mechanisms are manifestations of the OneNet blueprint mechanism under specific conditions. The theories and ontologies interact together as semantic frameworks to support integrative pharmacovigilance research.

Linear analysis near a steady-state of biochemical networks: control analysis, correlation metrics and circuit theory.

PubMed

Heuett, William J; Beard, Daniel A; Qian, Hong

2008-05-15

Several approaches, including metabolic control analysis (MCA), flux balance analysis (FBA), correlation metric construction (CMC), and biochemical circuit theory (BCT), have been developed for the quantitative analysis of complex biochemical networks. Here, we present a comprehensive theory of linear analysis for nonequilibrium steady-state (NESS) biochemical reaction networks that unites these disparate approaches in a common mathematical framework and thermodynamic basis. In this theory a number of relationships between key matrices are introduced: the matrix A obtained in the standard, linear-dynamic-stability analysis of the steady-state can be decomposed as A = SRT where R and S are directly related to the elasticity-coefficient matrix for the fluxes and chemical potentials in MCA, respectively; the control-coefficients for the fluxes and chemical potentials can be written in terms of RTBS and STBS respectively where matrix B is the inverse of A; the matrix S is precisely the stoichiometric matrix in FBA; and the matrix eAt plays a central role in CMC. One key finding that emerges from this analysis is that the well-known summation theorems in MCA take different forms depending on whether metabolic steady-state is maintained by flux injection or concentration clamping. We demonstrate that if rate-limiting steps exist in a biochemical pathway, they are the steps with smallest biochemical conductances and largest flux control-coefficients. We hypothesize that biochemical networks for cellular signaling have a different strategy for minimizing energy waste and being efficient than do biochemical networks for biosynthesis. We also discuss the intimate relationship between MCA and biochemical systems analysis (BSA).

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

Neuroimaging of the joint Simon effect with believed biological and non-biological co-actors

PubMed Central

Wen, Tanya; Hsieh, Shulan

2015-01-01

Performing a task alone or together with another agent can produce different outcomes. The current study used event-related functional magnetic resonance imaging (fMRI) to investigate the neural underpinnings when participants performed a Go/Nogo task alone or complementarily with another co-actor (unseen), whom was believed to be another human or a computer. During both complementary tasks, reaction time data suggested that participants integrated the potential action of their co-actor in their own action planning. Compared to the single-actor task, increased parietal and precentral activity during complementary tasks as shown in the fMRI data further suggested representation of the co-actor’s response. The superior frontal gyrus of the medial prefrontal cortex was differentially activated in the human co-actor condition compared to the computer co-actor condition. The medial prefrontal cortex, involved thinking about the beliefs and intentions of other people, possibly reflects a social-cognitive aspect or self-other discrimination during the joint task when believing a biological co-actor is present. Our results suggest that action co-representation can occur even offline with any agent type given a priori information that they are co-acting; however, additional regions are recruited when participants believe they are task-sharing with another human. PMID:26388760

Effect of Acting Experience on Emotion Expression and Recognition in Voice: Non-Actors Provide Better Stimuli than Expected.

PubMed

Jürgens, Rebecca; Grass, Annika; Drolet, Matthis; Fischer, Julia

Both in the performative arts and in emotion research, professional actors are assumed to be capable of delivering emotions comparable to spontaneous emotional expressions. This study examines the effects of acting training on vocal emotion depiction and recognition. We predicted that professional actors express emotions in a more realistic fashion than non-professional actors. However, professional acting training may lead to a particular speech pattern; this might account for vocal expressions by actors that are less comparable to authentic samples than the ones by non-professional actors. We compared 80 emotional speech tokens from radio interviews with 80 re-enactments by professional and inexperienced actors, respectively. We analyzed recognition accuracies for emotion and authenticity ratings and compared the acoustic structure of the speech tokens. Both play-acted conditions yielded similar recognition accuracies and possessed more variable pitch contours than the spontaneous recordings. However, professional actors exhibited signs of different articulation patterns compared to non-trained speakers. Our results indicate that for emotion research, emotional expressions by professional actors are not better suited than those from non-actors.

Contact Trees: Network Visualization beyond Nodes and Edges

PubMed Central

Sallaberry, Arnaud; Fu, Yang-chih; Ho, Hwai-Chung; Ma, Kwan-Liu

2016-01-01

Node-Link diagrams make it possible to take a quick glance at how nodes (or actors) in a network are connected by edges (or ties). A conventional network diagram of a “contact tree” maps out a root and branches that represent the structure of nodes and edges, often without further specifying leaves or fruits that would have grown from small branches. By furnishing such a network structure with leaves and fruits, we reveal details about “contacts” in our ContactTrees upon which ties and relationships are constructed. Our elegant design employs a bottom-up approach that resembles a recent attempt to understand subjective well-being by means of a series of emotions. Such a bottom-up approach to social-network studies decomposes each tie into a series of interactions or contacts, which can help deepen our understanding of the complexity embedded in a network structure. Unlike previous network visualizations, ContactTrees highlight how relationships form and change based upon interactions among actors, as well as how relationships and networks vary by contact attributes. Based on a botanical tree metaphor, the design is easy to construct and the resulting tree-like visualization can display many properties at both tie and contact levels, thus recapturing a key ingredient missing from conventional techniques of network visualization. We demonstrate ContactTrees using data sets consisting of up to three waves of 3-month contact diaries over the 2004-2012 period, and discuss how this design can be applied to other types of datasets. PMID:26784350

The key role of supply chain actors in groundwater irrigation development in North Africa

NASA Astrophysics Data System (ADS)

Lejars, Caroline; Daoudi, Ali; Amichi, Hichem

2017-09-01

The role played by supply chain actors in the rapid development of groundwater-based irrigated agriculture is analyzed. Agricultural groundwater use has increased tremendously in the past 50 years, leading to the decline of water tables. Groundwater use has enabled intensification of existing farming systems and ensured economic growth. This "groundwater economy" has been growing rapidly due to the initiative of farmers and the involvement of a wide range of supply chain actors, including suppliers of equipment, inputs retailers, and distributors of irrigated agricultural products. In North Africa, the actors in irrigated production chains often operate at the margin of public policies and are usually described as "informal", "unstructured", and as participating in "groundwater anarchy". This paper underlines the crucial role of supply chain actors in the development of groundwater irrigation, a role largely ignored by public policies and rarely studied. The analysis is based on three case studies in Morocco, Tunisia and Algeria, and focuses on the horticultural sub-sector, in particular on onions and tomatoes, which are irrigated high value crops. The study demonstrates that although supply chain actors are catalyzers of the expansion of groundwater irrigation, they could also become actors in adaptation to the declining water tables. Through their informal activities, they help reduce market risks, facilitate credit and access to subsidies, and disseminate innovation. The interest associated with making these actors visible to agricultural institutions is discussed, along with methods of getting them involved in the management of the resource on which they depend.

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

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

Yoon, Hong-Jun; Tourassi, Georgia

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 topicsmore » 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.« less

Seeing through Transparency in Education Reform: Illuminating the "Local"

ERIC Educational Resources Information Center

Koyama, Jill; Kania, Brian

2016-01-01

Utilizing "assemblage," a notion associated with Actor-Network Theory (ANT), we explore what discourses of transparency can, and cannot, accomplish in a network of education reform that includes schools, government agencies, and community organizations. Drawing on data collected between July 2011 and March 2013 in an…

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…

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

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.

Actor-specific contributions to the deforestation slowdown in the Brazilian Amazon.

PubMed

Godar, Javier; Gardner, Toby A; Tizado, E Jorge; Pacheco, Pablo

2014-10-28

Annual deforestation rates in the Brazilian Amazon fell by 77% between 2004 and 2011, yet have stabilized since 2009 at 5,000-7,000 km(2). We provide the first submunicipality assessment, to our knowledge, of actor-specific contributions to the deforestation slowdown by linking agricultural census and remote-sensing data on deforestation and forest degradation. Almost half (36,158 km(2)) of the deforestation between 2004 and 2011 occurred in areas dominated by larger properties (>500 ha), whereas only 12% (9,720 km(2)) occurred in areas dominated by smallholder properties (<100 ha). In addition, forests in areas dominated by smallholders tend to be less fragmented and less degraded. However, although annual deforestation rates fell during this period by 68-85% for all actors, the contribution of the largest landholders (>2,500 ha) to annual deforestation decreased over time (63% decrease between 2005 and 2011), whereas that of smallholders went up by a similar amount (69%) during the same period. In addition, the deforestation share attributable to remote areas increased by 88% between 2009 and 2011. These observations are consistent across the Brazilian Amazon, regardless of geographical differences in actor dominance or socioenvironmental context. Our findings suggest that deforestation policies to date, which have been particularly focused on command and control measures on larger properties in deforestation hotspots, may be increasingly limited in their effectiveness and fail to address all actors equally. Further reductions in deforestation are likely to be increasingly costly and require actor-tailored approaches, including better monitoring to detect small-scale deforestation and a shift toward more incentive-based conservation policies.

Actor-specific contributions to the deforestation slowdown in the Brazilian Amazon

PubMed Central

Godar, Javier; Gardner, Toby A.; Tizado, E. Jorge

2014-01-01

Annual deforestation rates in the Brazilian Amazon fell by 77% between 2004 and 2011, yet have stabilized since 2009 at 5,000–7,000 km2. We provide the first submunicipality assessment, to our knowledge, of actor-specific contributions to the deforestation slowdown by linking agricultural census and remote-sensing data on deforestation and forest degradation. Almost half (36,158 km2) of the deforestation between 2004 and 2011 occurred in areas dominated by larger properties (>500 ha), whereas only 12% (9,720 km2) occurred in areas dominated by smallholder properties (<100 ha). In addition, forests in areas dominated by smallholders tend to be less fragmented and less degraded. However, although annual deforestation rates fell during this period by 68–85% for all actors, the contribution of the largest landholders (>2,500 ha) to annual deforestation decreased over time (63% decrease between 2005 and 2011), whereas that of smallholders went up by a similar amount (69%) during the same period. In addition, the deforestation share attributable to remote areas increased by 88% between 2009 and 2011. These observations are consistent across the Brazilian Amazon, regardless of geographical differences in actor dominance or socioenvironmental context. Our findings suggest that deforestation policies to date, which have been particularly focused on command and control measures on larger properties in deforestation hotspots, may be increasingly limited in their effectiveness and fail to address all actors equally. Further reductions in deforestation are likely to be increasingly costly and require actor-tailored approaches, including better monitoring to detect small-scale deforestation and a shift toward more incentive-based conservation policies. PMID:25313087

Intelligent Control via Wireless Sensor Networks for Advanced Coal Combustion Systems

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

Aman Behal; Sunil Kumar; Goodarz Ahmadi

2007-08-05

Numerical Modeling of Solid Gas Flow, System Identification for purposes of modeling and control, and Wireless Sensor and Actor Network design were pursued as part of this project. Time series input-output data was obtained from NETL's Morgantown CFB facility courtesy of Dr. Lawrence Shadle. It was run through a nonlinear kernel estimator and nonparametric models were obtained for the system. Linear and first-order nonlinear kernels were then utilized to obtain a state-space description of the system. Neural networks were trained that performed better at capturing the plant dynamics. It is possible to use these networks to find a plant modelmore » and the inversion of this model can be used to control the system. These models allow one to compare with physics based models whose parameters can then be determined by comparing them against the available data based model. On a parallel track, Dr. Kumar designed an energy-efficient and reliable transport protocol for wireless sensor and actor networks, where the sensors could be different types of wireless sensors used in CFB based coal combustion systems and actors are more powerful wireless nodes to set up a communication network while avoiding the data congestion. Dr. Ahmadi's group studied gas solid flow in a duct. It was seen that particle concentration clearly shows a preferential distribution. The particles strongly interact with the turbulence eddies and are concentrated in narrow bands that are evolving with time. It is believed that observed preferential concentration is due to the fact that these particles are flung out of eddies by centrifugal force.« less

A network approach to policy framing: A case study of the National Aboriginal and Torres Strait Islander Health Plan.

PubMed

Browne, Jennifer; de Leeuw, Evelyne; Gleeson, Deborah; Adams, Karen; Atkinson, Petah; Hayes, Rick

2017-01-01

Aboriginal health policy in Australia represents a unique policy subsystem comprising a diverse network of Aboriginal-specific and "mainstream" organisations, often with competing interests. This paper describes the network structure of organisations attempting to influence national Aboriginal health policy and examines how the different subgroups within the network approached the policy discourse. Public submissions made as part of a policy development process for the National Aboriginal and Torres Strait Islander Health Plan were analysed using a novel combination of network analysis and qualitative framing analysis. Other organisational actors in the network in each submission were identified, and relationships between them determined; these were used to generate a network map depicting the ties between actors. A qualitative framing analysis was undertaken, using inductive coding of the policy discourses in the submissions. The frames were overlaid with the network map to identify the relationship between the structure of the network and the way in which organisations framed Aboriginal health problems. Aboriginal organisations were central to the network and strongly connected with each other. The network consisted of several densely connected subgroups, whose central nodes were closely connected to one another. Each subgroup deployed a particular policy frame, with a frame of "system dysfunction" also adopted by all but one subgroup. Analysis of submissions revealed that many of the stakeholders in Aboriginal health policy actors are connected to one another. These connections help to drive the policy discourse. The combination of network and framing analysis illuminates competing interests within a network, and can assist advocacy organisations to identify which network members are most influential. Copyright © 2016 Elsevier Ltd. All rights reserved.

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

PubMed

Tiwari, Abhishek; Tiwari, Vivek

2007-07-09

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

Neuromuscular control of the point to point and oscillatory movements of a sagittal arm with the actor-critic reinforcement learning method.

PubMed

Golkhou, Vahid; Parnianpour, Mohamad; Lucas, Caro

2005-04-01

In this study, we have used a single link system with a pair of muscles that are excited with alpha and gamma signals to achieve both point to point and oscillatory movements with variable amplitude and frequency.The system is highly nonlinear in all its physical and physiological attributes. The major physiological characteristics of this system are simultaneous activation of a pair of nonlinear muscle-like-actuators for control purposes, existence of nonlinear spindle-like sensors and Golgi tendon organ-like sensor, actions of gravity and external loading. Transmission delays are included in the afferent and efferent neural paths to account for a more accurate representation of the reflex loops.A reinforcement learning method with an actor-critic (AC) architecture instead of middle and low level of central nervous system (CNS), is used to track a desired trajectory. The actor in this structure is a two layer feedforward neural network and the critic is a model of the cerebellum. The critic is trained by state-action-reward-state-action (SARSA) method. The critic will train the actor by supervisory learning based on the prior experiences. Simulation studies of oscillatory movements based on the proposed algorithm demonstrate excellent tracking capability and after 280 epochs the RMS error for position and velocity profiles were 0.02, 0.04 rad and rad/s, respectively.

Game Theory-Based Cooperation for Underwater Acoustic Sensor Networks: Taxonomy, Review, Research Challenges and Directions

PubMed Central

Muhammed, Dalhatu; Anisi, Mohammad Hossein; Vargas-Rosales, Cesar; Khan, Anwar

2018-01-01

Exploring and monitoring the underwater world using underwater sensors is drawing a lot of attention these days. In this field cooperation between acoustic sensor nodes has been a critical problem due to the challenging features such as acoustic channel failure (sound signal), long propagation delay of acoustic signal, limited bandwidth and loss of connectivity. There are several proposed methods to improve cooperation between the nodes by incorporating information/game theory in the node’s cooperation. However, there is a need to classify the existing works and demonstrate their performance in addressing the cooperation issue. In this paper, we have conducted a review to investigate various factors affecting cooperation in underwater acoustic sensor networks. We study various cooperation techniques used for underwater acoustic sensor networks from different perspectives, with a concentration on communication reliability, energy consumption, and security and present a taxonomy for underwater cooperation. Moreover, we further review how the game theory can be applied to make the nodes cooperate with each other. We further analyze different cooperative game methods, where their performance on different metrics is compared. Finally, open issues and future research direction in underwater acoustic sensor networks are highlighted. PMID:29389874