Network analysis of physics discussion forums and links to course success

NASA Astrophysics Data System (ADS)

Traxler, Adrienne; Gavrin, Andrew; Lindell, Rebecca

2017-01-01

Large introductory science courses tend to isolate students, with negative consequences for long-term retention in college. Many active learning courses build collaboration and community among students as an explicit goal, and social network analysis has been used to track the development and beneficial effects of these collaborations. Here we supplement such work by conducting network analysis of online course discussion forums in two semesters of an introductory physics class. Online forums provide a tool for engaging students with each other outside of class, and offer new opportunities to commuter or non-traditional students with limited on-campus time. We look for correlations between position in the forum network (centrality) and final course grades. Preliminary investigation has shown weak correlations in the very dense full-semester network, so we will consider reduced ''backbone'' networks that highlight the most consistent links between students. Future work and implications for instruction will also be discussed.

Crowdsourcing Physical Network Topology Mapping With Net.Tagger

DTIC Science & Technology

2016-03-01

backend server infrastructure . This in- cludes a full security audit, better web services handling, and integration with the OSM stack and dataset to...a novel approach to network infrastructure mapping that combines smartphone apps with crowdsourced collection to gather data for offline aggregation...and analysis. The project aims to build a map of physical network infrastructure such as fiber-optic cables, facilities, and access points. The

An Analysis of the Structure and Evolution of Networks

ERIC Educational Resources Information Center

Hua, Guangying

2011-01-01

As network research receives more and more attention from both academic researchers and practitioners, network analysis has become a fast growing field attracting many researchers from diverse fields such as physics, computer science, and sociology. This dissertation provides a review of theory and research on different real data sets from the…

Research Activity in Computational Physics utilizing High Performance Computing: Co-authorship Network Analysis

NASA Astrophysics Data System (ADS)

Ahn, Sul-Ah; Jung, Youngim

2016-10-01

The research activities of the computational physicists utilizing high performance computing are analyzed by bibliometirc approaches. This study aims at providing the computational physicists utilizing high-performance computing and policy planners with useful bibliometric results for an assessment of research activities. In order to achieve this purpose, we carried out a co-authorship network analysis of journal articles to assess the research activities of researchers for high-performance computational physics as a case study. For this study, we used journal articles of the Scopus database from Elsevier covering the time period of 2004-2013. We extracted the author rank in the physics field utilizing high-performance computing by the number of papers published during ten years from 2004. Finally, we drew the co-authorship network for 45 top-authors and their coauthors, and described some features of the co-authorship network in relation to the author rank. Suggestions for further studies are discussed.

Introduction to the Space Physics Analysis Network (SPAN)

NASA Technical Reports Server (NTRS)

Green, J. L. (Editor); Peters, D. J. (Editor)

1985-01-01

The Space Physics Analysis Network or SPAN is emerging as a viable method for solving an immediate communication problem for the space scientist. SPAN provides low-rate communication capability with co-investigators and colleagues, and access to space science data bases and computational facilities. The SPAN utilizes up-to-date hardware and software for computer-to-computer communications allowing binary file transfer and remote log-on capability to over 25 nationwide space science computer systems. SPAN is not discipline or mission dependent with participation from scientists in such fields as magnetospheric, ionospheric, planetary, and solar physics. Basic information on the network and its use are provided. It is anticipated that SPAN will grow rapidly over the next few years, not only from the standpoint of more network nodes, but as scientists become more proficient in the use of telescience, more capability will be needed to satisfy the demands.

Tailoring physical properties of transglutaminase-modified gelatin films by varying drying temperature

USDA-ARS?s Scientific Manuscript database

Gelatin films prepared with or without transglutaminase (TGase) and dried at 15, 25 and 35 °C were analyzed for polymeric network structure, chemical composition and physical properties. Differences in protein network structure were observed by optical microscopy analysis in freeze-dried film-formin...

Management of the Space Physics Analysis Network (SPAN)

NASA Technical Reports Server (NTRS)

Green, James L.; Thomas, Valerie L.; Butler, Todd F.; Peters, David J.; Sisson, Patricia L.

1990-01-01

Here, the purpose is to define the operational management structure and to delineate the responsibilities of key Space Physics Analysis Network (SPAN) individuals. The management structure must take into account the large NASA and ESA science research community by giving them a major voice in the operation of the system. Appropriate NASA and ESA interfaces must be provided so that there will be adequate communications facilities available when needed. Responsibilities are delineated for the Advisory Committee, the Steering Committee, the Project Scientist, the Project Manager, the SPAN Security Manager, the Internetwork Manager, the Network Operations Manager, the Remote Site Manager, and others.

A study of the electrical properties of complex resistor network based on NW model

NASA Astrophysics Data System (ADS)

Chang, Yunfeng; Li, Yunting; Yang, Liu; Guo, Lu; Liu, Gaochao

2015-04-01

The power and resistance of two-port complex resistor network based on NW small world network model are studied in this paper. Mainly, we study the dependence of the network power and resistance on the degree of port vertices, the connection probability and the shortest distance. Qualitative analysis and a simplified formula for network resistance are given out. Finally, we define a branching parameter and give out its physical meaning in the analysis of complex resistor network.

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.

Physical explosion analysis in heat exchanger network design

NASA Astrophysics Data System (ADS)

Pasha, M.; Zaini, D.; Shariff, A. M.

2016-06-01

The failure of shell and tube heat exchangers is being extensively experienced by the chemical process industries. This failure can create a loss of production for long time duration. Moreover, loss of containment through heat exchanger could potentially lead to a credible event such as fire, explosion and toxic release. There is a need to analyse the possible worst case effect originated from the loss of containment of the heat exchanger at the early design stage. Physical explosion analysis during the heat exchanger network design is presented in this work. Baker and Prugh explosion models are deployed for assessing the explosion effect. Microsoft Excel integrated with process design simulator through object linking and embedded (OLE) automation for this analysis. Aspen HYSYS V (8.0) used as a simulation platform in this work. A typical heat exchanger network of steam reforming and shift conversion process was presented as a case study. It is investigated from this analysis that overpressure generated from the physical explosion of each heat exchanger can be estimated in a more precise manner by using Prugh model. The present work could potentially assist the design engineer to identify the critical heat exchanger in the network at the preliminary design stage.

BioCichlid: central dogma-based 3D visualization system of time-course microarray data on a hierarchical biological network.

PubMed

Ishiwata, Ryosuke R; Morioka, Masaki S; Ogishima, Soichi; Tanaka, Hiroshi

2009-02-15

BioCichlid is a 3D visualization system of time-course microarray data on molecular networks, aiming at interpretation of gene expression data by transcriptional relationships based on the central dogma with physical and genetic interactions. BioCichlid visualizes both physical (protein) and genetic (regulatory) network layers, and provides animation of time-course gene expression data on the genetic network layer. Transcriptional regulations are represented to bridge the physical network (transcription factors) and genetic network (regulated genes) layers, thus integrating promoter analysis into the pathway mapping. BioCichlid enhances the interpretation of microarray data and allows for revealing the underlying mechanisms causing differential gene expressions. BioCichlid is freely available and can be accessed at http://newton.tmd.ac.jp/. Source codes for both biocichlid server and client are also available.

Network approach towards understanding the crazing in glassy amorphous polymers

NASA Astrophysics Data System (ADS)

Venkatesan, Sudarkodi; Vivek-Ananth, R. P.; Sreejith, R. P.; Mangalapandi, Pattulingam; Hassanali, Ali A.; Samal, Areejit

2018-04-01

We have used molecular dynamics to simulate an amorphous glassy polymer with long chains to study the deformation mechanism of crazing and associated void statistics. The Van der Waals interactions and the entanglements between chains constituting the polymer play a crucial role in crazing. Thus, we have reconstructed two underlying weighted networks, namely, the Van der Waals network and the entanglement network from polymer configurations extracted from the molecular dynamics simulation. Subsequently, we have performed graph-theoretic analysis of the two reconstructed networks to reveal the role played by them in the crazing of polymers. Our analysis captured various stages of crazing through specific trends in the network measures for Van der Waals networks and entanglement networks. To further corroborate the effectiveness of network analysis in unraveling the underlying physics of crazing in polymers, we have contrasted the trends in network measures for Van der Waals networks and entanglement networks in the light of stress-strain behaviour and voids statistics during deformation. We find that the Van der Waals network plays a crucial role in craze initiation and growth. Although, the entanglement network was found to maintain its structure during craze initiation stage, it was found to progressively weaken and undergo dynamic changes during the hardening and failure stages of crazing phenomena. Our work demonstrates the utility of network theory in quantifying the underlying physics of polymer crazing and widens the scope of applications of network science to characterization of deformation mechanisms in diverse polymers.

Molecular-level Analysis of Shock-wave Physics and Derivation of the Hugoniot Relations for Soda-lime Glass

DTIC Science & Technology

2011-06-17

based glasses like fused silica and soda - lime glass , the polyhedral central cation is silicon. In this case, each silicon is surrounded by four oxygen...to two network forming cations) oxygen atoms per network polyhedron. The equilibrium values for this parameter in fused silica and soda - lime glass ...Molecular-level analysis of shock-wave physics and derivation of the Hugoniot relations for soda - lime glass M. Grujicic • B. Pandurangan • W. C. Bell

A Qualitative Study to Examine Feasibility and Design of an Online Social Networking Intervention to Increase Physical Activity in Teenage Girls.

PubMed

Van Kessel, Gisela; Kavanagh, Madeleine; Maher, Carol

2016-01-01

Online social networks present wide-reaching and flexible platforms through which to deliver health interventions to targeted populations. This study used a social marketing approach to explore teenage girls' perceptions of physical activity and the potential use of online social networks to receive a physical activity intervention. Six focus groups were conducted with 19 Australian teenage girls (ages 13 to 18 years) with varying levels of physical activity and socioeconomic status. A semi-structured format was used, with groups discussion transcribed verbatim. Content analysis identified emergent themes, with triangulation and memos used to ensure accuracy. Physical activity was most appealing when it emphasised sport, exercise and fitness, along with opportunities for socialisation with friends and self-improvement. Participants were receptive to delivery of a physical activity intervention via online social networks, with Facebook the most widely reported site. Participants commonly accessed online social networks via mobile devices and particularly smartphones. Undesirable features included promotion of physical activity in terms of walking; use of cartoon imagery; use of humour; and promotion of the intervention via schools, each of which were considered "uncool". Participants noted that their parents were likely to be supportive of them using an online social networking physical activity intervention, particularly if not promoted as a weight loss intervention. This study identified key features likely to increase the feasibility and retention of an online social networking physical activity intervention for teenage girls. Guidelines for the design of interventions for teenage girls are provided for future applications.

A Qualitative Study to Examine Feasibility and Design of an Online Social Networking Intervention to Increase Physical Activity in Teenage Girls

PubMed Central

Van Kessel, Gisela; Kavanagh, Madeleine; Maher, Carol

2016-01-01

Background Online social networks present wide-reaching and flexible platforms through which to deliver health interventions to targeted populations. This study used a social marketing approach to explore teenage girls’ perceptions of physical activity and the potential use of online social networks to receive a physical activity intervention. Methods Six focus groups were conducted with 19 Australian teenage girls (ages 13 to 18 years) with varying levels of physical activity and socioeconomic status. A semi-structured format was used, with groups discussion transcribed verbatim. Content analysis identified emergent themes, with triangulation and memos used to ensure accuracy. Results Physical activity was most appealing when it emphasised sport, exercise and fitness, along with opportunities for socialisation with friends and self-improvement. Participants were receptive to delivery of a physical activity intervention via online social networks, with Facebook the most widely reported site. Participants commonly accessed online social networks via mobile devices and particularly smartphones. Undesirable features included promotion of physical activity in terms of walking; use of cartoon imagery; use of humour; and promotion of the intervention via schools, each of which were considered “uncool”. Participants noted that their parents were likely to be supportive of them using an online social networking physical activity intervention, particularly if not promoted as a weight loss intervention. Conclusion This study identified key features likely to increase the feasibility and retention of an online social networking physical activity intervention for teenage girls. Guidelines for the design of interventions for teenage girls are provided for future applications. PMID:26934191

Leaf Extraction and Analysis Framework Graphical User Interface: Segmenting and Analyzing the Structure of Leaf Veins and Areoles1[W][OA

PubMed Central

Price, Charles A.; Symonova, Olga; Mileyko, Yuriy; Hilley, Troy; Weitz, Joshua S.

2011-01-01

Interest in the structure and function of physical biological networks has spurred the development of a number of theoretical models that predict optimal network structures across a broad array of taxonomic groups, from mammals to plants. In many cases, direct tests of predicted network structure are impossible given the lack of suitable empirical methods to quantify physical network geometry with sufficient scope and resolution. There is a long history of empirical methods to quantify the network structure of plants, from roots, to xylem networks in shoots and within leaves. However, with few exceptions, current methods emphasize the analysis of portions of, rather than entire networks. Here, we introduce the Leaf Extraction and Analysis Framework Graphical User Interface (LEAF GUI), a user-assisted software tool that facilitates improved empirical understanding of leaf network structure. LEAF GUI takes images of leaves where veins have been enhanced relative to the background, and following a series of interactive thresholding and cleaning steps, returns a suite of statistics and information on the structure of leaf venation networks and areoles. Metrics include the dimensions, position, and connectivity of all network veins, and the dimensions, shape, and position of the areoles they surround. Available for free download, the LEAF GUI software promises to facilitate improved understanding of the adaptive and ecological significance of leaf vein network structure. PMID:21057114

Leaf extraction and analysis framework graphical user interface: segmenting and analyzing the structure of leaf veins and areoles.

PubMed

Price, Charles A; Symonova, Olga; Mileyko, Yuriy; Hilley, Troy; Weitz, Joshua S

2011-01-01

Interest in the structure and function of physical biological networks has spurred the development of a number of theoretical models that predict optimal network structures across a broad array of taxonomic groups, from mammals to plants. In many cases, direct tests of predicted network structure are impossible given the lack of suitable empirical methods to quantify physical network geometry with sufficient scope and resolution. There is a long history of empirical methods to quantify the network structure of plants, from roots, to xylem networks in shoots and within leaves. However, with few exceptions, current methods emphasize the analysis of portions of, rather than entire networks. Here, we introduce the Leaf Extraction and Analysis Framework Graphical User Interface (LEAF GUI), a user-assisted software tool that facilitates improved empirical understanding of leaf network structure. LEAF GUI takes images of leaves where veins have been enhanced relative to the background, and following a series of interactive thresholding and cleaning steps, returns a suite of statistics and information on the structure of leaf venation networks and areoles. Metrics include the dimensions, position, and connectivity of all network veins, and the dimensions, shape, and position of the areoles they surround. Available for free download, the LEAF GUI software promises to facilitate improved understanding of the adaptive and ecological significance of leaf vein network structure.

Differential C3NET reveals disease networks of direct physical interactions

PubMed Central

2011-01-01

Background Genes might have different gene interactions in different cell conditions, which might be mapped into different networks. Differential analysis of gene networks allows spotting condition-specific interactions that, for instance, form disease networks if the conditions are a disease, such as cancer, and normal. This could potentially allow developing better and subtly targeted drugs to cure cancer. Differential network analysis with direct physical gene interactions needs to be explored in this endeavour. Results C3NET is a recently introduced information theory based gene network inference algorithm that infers direct physical gene interactions from expression data, which was shown to give consistently higher inference performances over various networks than its competitors. In this paper, we present, DC3net, an approach to employ C3NET in inferring disease networks. We apply DC3net on a synthetic and real prostate cancer datasets, which show promising results. With loose cutoffs, we predicted 18583 interactions from tumor and normal samples in total. Although there are no reference interactions databases for the specific conditions of our samples in the literature, we found verifications for 54 of our predicted direct physical interactions from only four of the biological interaction databases. As an example, we predicted that RAD50 with TRF2 have prostate cancer specific interaction that turned out to be having validation from the literature. It is known that RAD50 complex associates with TRF2 in the S phase of cell cycle, which suggests that this predicted interaction may promote telomere maintenance in tumor cells in order to allow tumor cells to divide indefinitely. Our enrichment analysis suggests that the identified tumor specific gene interactions may be potentially important in driving the growth in prostate cancer. Additionally, we found that the highest connected subnetwork of our predicted tumor specific network is enriched for all proliferation genes, which further suggests that the genes in this network may serve in the process of oncogenesis. Conclusions Our approach reveals disease specific interactions. It may help to make experimental follow-up studies more cost and time efficient by prioritizing disease relevant parts of the global gene network. PMID:21777411

Local-Area-Network Simulator

NASA Technical Reports Server (NTRS)

Gibson, Jim; Jordan, Joe; Grant, Terry

1990-01-01

Local Area Network Extensible Simulator (LANES) computer program provides method for simulating performance of high-speed local-area-network (LAN) technology. Developed as design and analysis software tool for networking computers on board proposed Space Station. Load, network, link, and physical layers of layered network architecture all modeled. Mathematically models according to different lower-layer protocols: Fiber Distributed Data Interface (FDDI) and Star*Bus. Written in FORTRAN 77.

Pathway redundancy and protein essentiality revealed in the Saccharomyces cerevisiae interaction networks

PubMed Central

Ulitsky, Igor; Shamir, Ron

2007-01-01

The biological interpretation of genetic interactions is a major challenge. Recently, Kelley and Ideker proposed a method to analyze together genetic and physical networks, which explains many of the known genetic interactions as linking different pathways in the physical network. Here, we extend this method and devise novel analytic tools for interpreting genetic interactions in a physical context. Applying these tools on a large-scale Saccharomyces cerevisiae data set, our analysis reveals 140 between-pathway models that explain 3765 genetic interactions, roughly doubling those that were previously explained. Model genes tend to have short mRNA half-lives and many phosphorylation sites, suggesting that their stringent regulation is linked to pathway redundancy. We also identify ‘pivot' proteins that have many physical interactions with both pathways in our models, and show that pivots tend to be essential and highly conserved. Our analysis of models and pivots sheds light on the organization of the cellular machinery as well as on the roles of individual proteins. PMID:17437029

Sex Venue-Based Network Analysis to Identify HIV Prevention Dissemination Targets for Men Who Have Sex with Men.

PubMed

Patel, Rupa R; Luke, Douglas A; Proctor, Enola K; Powderly, William G; Chan, Philip A; Mayer, Kenneth H; Harrison, Laura C; Dhand, Amar

2018-01-01

The aim of this study was to identify sex venue-based networks among men who have sex with men (MSM) to inform HIV preexposure prophylaxis (PrEP) dissemination efforts. Using a cross-sectional design, we interviewed MSM about the venues where their recent sexual partners were found. Venues were organized into network matrices grouped by condom use and race. We examined network structure, central venues, and network subgroups. Among 49 participants, the median age was 27 years, 49% were Black and 86% reported condomless anal sex (ncAS). Analysis revealed a map of 54 virtual and physical venues with an overlap in the ncAS and with condom anal sex (cAS) venues. In the ncAS network, virtual and physical locations were more interconnected. The ncAS venues reported by Blacks were more diffusely organized than those reported by Whites. The network structures of sex venues for at-risk MSM differed by race. Network information can enhance HIV prevention dissemination efforts among subpopulations, including PrEP implementation.

Sex Venue-Based Network Analysis to Identify HIV Prevention Dissemination Targets for Men Who Have Sex with Men

PubMed Central

Luke, Douglas A.; Proctor, Enola K.; Powderly, William G.; Chan, Philip A.; Mayer, Kenneth H.; Harrison, Laura C.; Dhand, Amar

2018-01-01

Abstract Purpose: The aim of this study was to identify sex venue-based networks among men who have sex with men (MSM) to inform HIV preexposure prophylaxis (PrEP) dissemination efforts. Methods: Using a cross-sectional design, we interviewed MSM about the venues where their recent sexual partners were found. Venues were organized into network matrices grouped by condom use and race. We examined network structure, central venues, and network subgroups. Results: Among 49 participants, the median age was 27 years, 49% were Black and 86% reported condomless anal sex (ncAS). Analysis revealed a map of 54 virtual and physical venues with an overlap in the ncAS and with condom anal sex (cAS) venues. In the ncAS network, virtual and physical locations were more interconnected. The ncAS venues reported by Blacks were more diffusely organized than those reported by Whites. Conclusion: The network structures of sex venues for at-risk MSM differed by race. Network information can enhance HIV prevention dissemination efforts among subpopulations, including PrEP implementation. PMID:29324178

DSRC standards testing : 5MHz band-plan analysis, clustered system architecture and communication in emergency scenarios.

DOT National Transportation Integrated Search

2011-12-01

Researchers performed a system level technical study of physical layer and network layer performance of vehicular communication in a specially licensed Dedicated Short Range Communication (DSRC) 5.9 GHz frequency band. Physical layer analysis provide...

A Survey on Security and Privacy in Emerging Sensor Networks: From Viewpoint of Close-Loop.

PubMed

Zhang, Lifu; Zhang, Heng

2016-03-26

Nowadays, as the next generation sensor networks, Cyber-Physical Systems (CPSs) refer to the complex networked systems that have both physical subsystems and cyber components, and the information flow between different subsystems and components is across a communication network, which forms a closed-loop. New generation sensor networks are found in a growing number of applications and have received increasing attention from many inter-disciplines. Opportunities and challenges in the design, analysis, verification and validation of sensor networks co-exists, among which security and privacy are two important ingredients. This paper presents a survey on some recent results in the security and privacy aspects of emerging sensor networks from the viewpoint of the closed-loop. This paper also discusses several future research directions under these two umbrellas.

The role of interpersonal communication in the process of knowledge mobilization within a community-based organization: a network analysis.

PubMed

Gainforth, Heather L; Latimer-Cheung, Amy E; Athanasopoulos, Peter; Moore, Spencer; Ginis, Kathleen A Martin

2014-05-22

Diffusion of innovations theory has been widely used to explain knowledge mobilization of research findings. This theory posits that individuals who are more interpersonally connected within an organization may be more likely to adopt an innovation (e.g., research evidence) than individuals who are less interconnected. Research examining this tenet of diffusion of innovations theory in the knowledge mobilization literature is limited. The purpose of the present study was to use network analysis to examine the role of interpersonal communication in the adoption and mobilization of the physical activity guidelines for people with spinal cord injury (SCI) among staff in a community-based organization (CBO). The study used a cross-sectional, whole-network design. In total, 56 staff completed the network survey. Adoption of the guidelines was assessed using Rogers' innovation-decision process and interpersonal communication was assessed using an online network instrument. The patterns of densities observed within the network were indicative of a core-periphery structure revealing that interpersonal communication was greater within the core than between the core and periphery and within the periphery. Membership in the core, as opposed to membership in the periphery, was associated with greater knowledge of the evidence-based physical activity resources available and engagement in physical activity promotion behaviours (ps < 0.05). Greater in-degree centrality was associated with adoption of evidence-based behaviours (p < 0.05). Findings suggest that interpersonal communication is associated with knowledge mobilization and highlight how the network structure could be improved for further dissemination efforts. diffusion of innovations; network analysis; community-based organization; knowledge mobilization; knowledge translation, interpersonal communication.

Using Social Network Analysis to Better Understand Compulsive Exercise Behavior Among a Sample of Sorority Members.

PubMed

Patterson, Megan S; Goodson, Patricia

2017-05-01

Compulsive exercise, a form of unhealthy exercise often associated with prioritizing exercise and feeling guilty when exercise is missed, is a common precursor to and symptom of eating disorders. College-aged women are at high risk of exercising compulsively compared with other groups. Social network analysis (SNA) is a theoretical perspective and methodology allowing researchers to observe the effects of relational dynamics on the behaviors of people. SNA was used to assess the relationship between compulsive exercise and body dissatisfaction, physical activity, and network variables. Descriptive statistics were conducted using SPSS, and quadratic assignment procedure (QAP) analyses were conducted using UCINET. QAP regression analysis revealed a statistically significant model (R 2 = .375, P < .0001) predicting compulsive exercise behavior. Physical activity, body dissatisfaction, and network variables were statistically significant predictor variables in the QAP regression model. In our sample, women who are connected to "important" or "powerful" people in their network are likely to have higher compulsive exercise scores. This result provides healthcare practitioners key target points for intervention within similar groups of women. For scholars researching eating disorders and associated behaviors, this study supports looking into group dynamics and network structure in conjunction with body dissatisfaction and exercise frequency.

Health-Related Messages about Physical Activity Promotion: An Analysis of Photographs on Social Networking Sites of Universities

ERIC Educational Resources Information Center

Martínez-Bello, Vladimir E.; Martínez-Rojas, Ángela; Molina-García, Javier

2017-01-01

The main aim of this study was to examine how different physical activity domains are represented on the official social media sites of Spanish universities, through a content analysis of the photographs. Our results show that the representation of different physical activity domains is not balanced. While the analysed images do promote a message…

Persistent ISR: the social network analysis connection

NASA Astrophysics Data System (ADS)

Bowman, Elizabeth K.

2012-06-01

Persistent surveillance provides decision makers with unprecedented access to multisource data collected from humans and sensor assets around the globe, yet these data exist in the physical world and provide few overt clues to meaning behind actions. In this paper we explore the recent growth in online social networking and ask the questions: 1) can these sites provide value-added information to compliment physical sensing and 2) what are the mechanisms by which these data could inform situational awareness and decision making? In seeking these answers we consider the range of options provided by Social Network Analysis (SNA), and focus especially on the dynamic nature of these networks. In our discussion we focus on the wave of reform experienced by the North African nations in early 2011 known as the Arab Spring. Demonstrators made widespread use of social networking applications to coordinate, document, and publish material to aid their cause. Unlike members of covert social networks who hide their activity and associations, these demonstrators openly posted multimedia information to coordinate activity and stimulate global support. In this paper we provide a review of SNA approaches and consider how one might track network adaptations by capturing temporal and conceptual trends. We identify opportunities and challenges for merging SNA with physical sensor output, and conclude by addressing future challenges in the persistent ISR domain with respect to SNA.

Mapping University Students' Epistemic Framing of Computational Physics Using Network Analysis

ERIC Educational Resources Information Center

Bodin, Madelen

2012-01-01

Solving physics problem in university physics education using a computational approach requires knowledge and skills in several domains, for example, physics, mathematics, programming, and modeling. These competences are in turn related to students' beliefs about the domains as well as about learning. These knowledge and beliefs components are…

Unified Approach to Modeling and Simulation of Space Communication Networks and Systems

NASA Technical Reports Server (NTRS)

Barritt, Brian; Bhasin, Kul; Eddy, Wesley; Matthews, Seth

2010-01-01

Network simulator software tools are often used to model the behaviors and interactions of applications, protocols, packets, and data links in terrestrial communication networks. Other software tools that model the physics, orbital dynamics, and RF characteristics of space systems have matured to allow for rapid, detailed analysis of space communication links. However, the absence of a unified toolset that integrates the two modeling approaches has encumbered the systems engineers tasked with the design, architecture, and analysis of complex space communication networks and systems. This paper presents the unified approach and describes the motivation, challenges, and our solution - the customization of the network simulator to integrate with astronautical analysis software tools for high-fidelity end-to-end simulation. Keywords space; communication; systems; networking; simulation; modeling; QualNet; STK; integration; space networks

Adolescent Friendships, BMI, and Physical Activity: Untangling Selection and Influence Through Longitudinal Social Network Analysis

PubMed Central

Simpkins, Sandra D.; Schaefer, David R.; Price, Chara D.; Vest, Andrea E.

2012-01-01

Bioecological theory suggests that adolescents’ health is a result of selection and socialization processes occurring between adolescents and their microsettings. This study examines the association between adolescents’ friends and health using a social network model and data from the National Longitudinal Study of Adolescent Health (N = 1,896, mean age = 15.97 years). Results indicated evidence of friend influence on BMI and physical activity. Friendships were more likely among adolescents who engaged in greater physical activity and who were similar to one another in BMI and physical activity. These effects emerged after controlling for alternative friend selection factors, such as endogenous social network processes and propinquity through courses and activities. Some selection effects were moderated by gender, popularity, and reciprocity. PMID:24222971

INTERDISCIPLINARY PHYSICS AND RELATED AREAS OF SCIENCE AND TECHNOLOGY: Synchronization in Complex Networks with Multiple Connections

NASA Astrophysics Data System (ADS)

Wu, Qing-Chu; Fu, Xin-Chu; Sun, Wei-Gang

2010-01-01

In this paper a class of networks with multiple connections are discussed. The multiple connections include two different types of links between nodes in complex networks. For this new model, we give a simple generating procedure. Furthermore, we investigate dynamical synchronization behavior in a delayed two-layer network, giving corresponding theoretical analysis and numerical examples.

A Survey on Security and Privacy in Emerging Sensor Networks: From Viewpoint of Close-Loop

PubMed Central

Zhang, Lifu; Zhang, Heng

2016-01-01

Nowadays, as the next generation sensor networks, Cyber-Physical Systems (CPSs) refer to the complex networked systems that have both physical subsystems and cyber components, and the information flow between different subsystems and components is across a communication network, which forms a closed-loop. New generation sensor networks are found in a growing number of applications and have received increasing attention from many inter-disciplines. Opportunities and challenges in the design, analysis, verification and validation of sensor networks co-exists, among which security and privacy are two important ingredients. This paper presents a survey on some recent results in the security and privacy aspects of emerging sensor networks from the viewpoint of the closed-loop. This paper also discusses several future research directions under these two umbrellas. PMID:27023559

Network monitoring in the Tier2 site in Prague

NASA Astrophysics Data System (ADS)

Eliáš, Marek; Fiala, Lukáš; Horký, Jiří; Chudoba, Jiří; Kouba, Tomáš; Kundrát, Jan; Švec, Jan

2011-12-01

Network monitoring provides different types of view on the network traffic. It's output enables computing centre staff to make qualified decisions about changes in the organization of computing centre network and to spot possible problems. In this paper we present network monitoring framework used at Tier-2 in Prague in Institute of Physics (FZU). The framework consists of standard software and custom tools. We discuss our system for hardware failures detection using syslog logging and Nagios active checks, bandwidth monitoring of physical links and analysis of NetFlow exports from Cisco routers. We present tool for automatic detection of network layout based on SNMP. This tool also records topology changes into SVN repository. Adapted weathermap4rrd is used to visualize recorded data to get fast overview showing current bandwidth usage of links in network.

An Integrative Analysis of Preeclampsia Based on the Construction of an Extended Composite Network Featuring Protein-Protein Physical Interactions and Transcriptional Relationships

PubMed Central

Vaiman, Daniel; Miralles, Francisco

2016-01-01

Preeclampsia (PE) is a pregnancy disorder defined by hypertension and proteinuria. This disease remains a major cause of maternal and fetal morbidity and mortality. Defective placentation is generally described as being at the root of the disease. The characterization of the transcriptome signature of the preeclamptic placenta has allowed to identify differentially expressed genes (DEGs). However, we still lack a detailed knowledge on how these DEGs impact the function of the placenta. The tools of network biology offer a methodology to explore complex diseases at a systems level. In this study we performed a cross-platform meta-analysis of seven publically available gene expression datasets comparing non-pathological and preeclamptic placentas. Using the rank product algorithm we identified a total of 369 DEGs consistently modified in PE. The DEGs were used as seeds to build both an extended physical protein-protein interactions network and a transcription factors regulatory network. Topological and clustering analysis was conducted to analyze the connectivity properties of the networks. Finally both networks were merged into a composite network which presents an integrated view of the regulatory pathways involved in preeclampsia and the crosstalk between them. This network is a useful tool to explore the relationship between the DEGs and enable hypothesis generation for functional experimentation. PMID:27802351

Span graphics display utilities handbook, first edition

NASA Technical Reports Server (NTRS)

Gallagher, D. L.; Green, J. L.; Newman, R.

1985-01-01

The Space Physics Analysis Network (SPAN) is a computer network connecting scientific institutions throughout the United States. This network provides an avenue for timely, correlative research between investigators, in a multidisciplinary approach to space physics studies. An objective in the development of SPAN is to make available direct and simplified procedures that scientists can use, without specialized training, to exchange information over the network. Information exchanges include raw and processes data, analysis programs, correspondence, documents, and graphite images. This handbook details procedures that can be used to exchange graphic images over SPAN. The intent is to periodically update this handbook to reflect the constantly changing facilities available on SPAN. The utilities described within reflect an earnest attempt to provide useful descriptions of working utilities that can be used to transfer graphic images across the network. Whether graphic images are representative of satellite servations or theoretical modeling and whether graphics images are of device dependent or independent type, the SPAN graphics display utilities handbook will be the users guide to graphic image exchange.

Underwater Sensor Nodes and Networks

PubMed Central

Lloret, Jaime

2013-01-01

Sensor technology has matured enough to be used in any type of environment. The appearance of new physical sensors has increased the range of environmental parameters for gathering data. Because of the huge amount of unexploited resources in the ocean environment, there is a need of new research in the field of sensors and sensor networks. This special issue is focused on collecting recent advances on underwater sensors and underwater sensor networks in order to measure, monitor, surveillance of and control of underwater environments. On the one hand, from the sensor node perspective, we will see works related with the deployment of physical sensors, development of sensor nodes and transceivers for sensor nodes, sensor measurement analysis and several issues such as layer 1 and 2 protocols for underwater communication and sensor localization and positioning systems. On the other hand, from the sensor network perspective, we will see several architectures and protocols for underwater environments and analysis concerning sensor network measurements. Both sides will provide us a complete view of last scientific advances in this research field. PMID:24013489

The role of social networks in physical and relational aggression among young adolescents.

PubMed

Low, Sabina; Polanin, Joshua R; Espelage, Dorothy L

2013-07-01

Despite the veritable influence of the peer context on the elaboration of adolescent aggression, few studies of relational aggression have directly identified and measured peer groups, limiting our ability to draw formal conclusions about the level and nature of peer influence. The current study used a developmental framework to examine peer group influence on individual levels of physical and relational aggression over a year with 6th and 7th grade students (n = 346, 51 % female). A multilevel network approach was used in which peer groups were identified via social network analysis, and peer group influence was evaluated with hierarchical linear modeling (HLM). HLM analyses indicated that peer group aggression (physical and relational) at time 1 was predictive of individual aggression levels at time 2 after controlling for other peer group characteristics as well as other individual risk and protective factors. Although both forms of aggression were embedded in peer networks, findings suggest that physical aggression is relatively less endemic to peer networks, and is more likely to occur in smaller, predominantly male networks. The current study highlights the importance of understanding the influence of peer group membership on adolescent aggression and points to important implications for prevention.

High Energy Physics and Nuclear Physics Network Requirements

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

Dart, Eli; Bauerdick, Lothar; Bell, Greg

The Energy Sciences Network (ESnet) is the primary provider of network connectivity for the U.S. Department of Energy (DOE) Office of Science (SC), the single largest supporter of basic research in the physical sciences in the United States. In support of SC programs, ESnet regularly updates and refreshes its understanding of the networking requirements needed by instruments, facilities, scientists, and science programs that it serves. This focus has helped ESnet to be a highly successful enabler of scientific discovery for over 25 years. In August 2013, ESnet and the DOE SC Offices of High Energy Physics (HEP) and Nuclear Physicsmore » (NP) organized a review to characterize the networking requirements of the programs funded by the HEP and NP program offices. Several key findings resulted from the review. Among them: 1. The Large Hadron Collider?s ATLAS (A Toroidal LHC Apparatus) and CMS (Compact Muon Solenoid) experiments are adopting remote input/output (I/O) as a core component of their data analysis infrastructure. This will significantly increase their demands on the network from both a reliability perspective and a performance perspective. 2. The Large Hadron Collider (LHC) experiments (particularly ATLAS and CMS) are working to integrate network awareness into the workflow systems that manage the large number of daily analysis jobs (1 million analysis jobs per day for ATLAS), which are an integral part of the experiments. Collaboration with networking organizations such as ESnet, and the consumption of performance data (e.g., from perfSONAR [PERformance Service Oriented Network monitoring Architecture]) are critical to the success of these efforts. 3. The international aspects of HEP and NP collaborations continue to expand. This includes the LHC experiments, the Relativistic Heavy Ion Collider (RHIC) experiments, the Belle II Collaboration, the Large Synoptic Survey Telescope (LSST), and others. The international nature of these collaborations makes them heavily reliant on transoceanic connectivity, which is subject to longer term service disruptions than terrestrial connectivity. The network engineering aspects of undersea connectivity will continue to be a significant part of the planning, deployment, and operation of the data analysis infrastructure for HEP and NP experiments for the foreseeable future. Given their critical dependency on networking services, the experiments have expressed the need for tight integration (both technically and operationally) of the domestic and the transoceanic parts of the network infrastructure that supports the experiments. 4. The datasets associated with simulations continue to increase in size, and the need to move these datasets between analysis centers is placing ever-increasing demands on networks and on data management systems at the supercomputing centers. In addition, there is a need to harmonize cybersecurity practice with the data transfer performance requirements of the science. This report expands on these points, and addresses others as well. The report contains a findings section in addition to the text of the case studies discussed during the review.« less

Reliability analysis for the smart grid : from cyber control and communication to physical manifestations of failure.

DOT National Transportation Integrated Search

2010-01-01

The Smart Grid is a cyber-physical system comprised of physical components, such as transmission lines and generators, and a : network of embedded systems deployed for their cyber control. Our objective is to qualitatively and quantitatively analyze ...

Online social networks that connect users to physical activity partners: a review and descriptive analysis.

PubMed

Nakhasi, Atul; Shen, Album Xiaotian; Passarella, Ralph Joseph; Appel, Lawrence J; Anderson, Cheryl Am

2014-06-16

The US Centers for Disease Control and Prevention have identified a lack of encouragement, support, or companionship from family and friends as a major barrier to physical activity. To overcome this barrier, online social networks are now actively leveraging principles of companion social support in novel ways. The aim was to evaluate the functionality, features, and usability of existing online social networks which seek to increase physical activity and fitness among users by connecting them to physical activity partners, not just online, but also face-to-face. In September 2012, we used 3 major databases to identify the website addresses for relevant online social networks. We conducted a Google search using 8 unique keyword combinations: the common keyword "find" coupled with 1 of 4 prefix terms "health," "fitness," "workout," or "physical" coupled with 1 of 2 stem terms "activity partners" or "activity buddies." We also searched 2 prominent technology start-up news sites, TechCrunch and Y Combinator, using 2 unique keyword combinations: the common keyword "find" coupled with 1 of 2 stem terms "activity partners" and "activity buddies." Sites were defined as online social health activity networks if they had the ability to (1) actively find physical activity partners or activities for the user, (2) offer dynamic, real-time tracking or sharing of social activities, and (3) provide virtual profiles to users. We excluded from our analysis sites that were not Web-based, publicly available, in English, or free. Of the 360 initial search results, we identified 13 websites that met our complete criteria of an online social health activity network. Features such as physical activity creation (13/13, 100%) and private messaging (12/13, 92%) appeared almost universally among these websites. However, integration with Web 2.0 technologies such as Facebook and Twitter (9/13, 69%) and the option of direct event joining (8/13, 62%) were not as universally present. Largely absent were more sophisticated features that would enable greater usability, such as interactive engagement prompts (3/13, 23%) and system-created best fit activities (3/13, 23%). Several major online social networks that connect users to physical activity partners currently exist and use standardized features to achieve their goals. Future research is needed to better understand how users utilize these features and how helpful they truly are.

Network analysis of Bogotá's Ciclovía Recreativa, a self-organized multisectorial community program to promote physical activity in a middle-income country.

PubMed

Meisel, Jose D; Sarmiento, Olga L; Montes, Felipe; Martinez, Edwin O; Lemoine, Pablo D; Valdivia, Juan A; Brownson, Ross C; Zarama, Roberto

2014-01-01

Conduct a social network analysis of the health and non-health related organizations that participate in Bogotá's Ciclovía Recreativa (Ciclovía). Cross-sectional study. Ciclovía is a multisectoral community-based mass program in which streets are temporarily closed to motorized transport, allowing exclusive access to individuals for leisure activities and physical activity. Twenty-five organizations that participate in the Ciclovía. Seven variables were examined by using network analytic methods: relationship, link attributes (integration, contact, and importance), and node attributes (leadership, years in the program, and the sector of the organization). The network analytic methods were based on a visual descriptive analysis and an exponential random graph model. Analysis shows that the most central organizations in the network were outside of the Health sector and include Sports and Recreation, Government, and Security sectors. The organizations work in clusters formed by organizations of different sectors. Organization importance and structural predictors were positively related to integration, while the number of years working with Ciclovía was negatively associated with integration. Ciclovía is a network whose structure emerged as a self-organized complex system. Ciclovía of Bogotá is an example of a program with public health potential formed by organizations of multiple sectors with Sports and Recreation as the most central.

Applying traditional signal processing techniques to social media exploitation for situational understanding

NASA Astrophysics Data System (ADS)

Abdelzaher, Tarek; Roy, Heather; Wang, Shiguang; Giridhar, Prasanna; Al Amin, Md. Tanvir; Bowman, Elizabeth K.; Kolodny, Michael A.

2016-05-01

Signal processing techniques such as filtering, detection, estimation and frequency domain analysis have long been applied to extract information from noisy sensor data. This paper describes the exploitation of these signal processing techniques to extract information from social networks, such as Twitter and Instagram. Specifically, we view social networks as noisy sensors that report events in the physical world. We then present a data processing stack for detection, localization, tracking, and veracity analysis of reported events using social network data. We show using a controlled experiment that the behavior of social sources as information relays varies dramatically depending on context. In benign contexts, there is general agreement on events, whereas in conflict scenarios, a significant amount of collective filtering is introduced by conflicted groups, creating a large data distortion. We describe signal processing techniques that mitigate such distortion, resulting in meaningful approximations of actual ground truth, given noisy reported observations. Finally, we briefly present an implementation of the aforementioned social network data processing stack in a sensor network analysis toolkit, called Apollo. Experiences with Apollo show that our techniques are successful at identifying and tracking credible events in the physical world.

Using protein-protein interactions for refining gene networks estimated from microarray data by Bayesian networks.

PubMed

Nariai, N; Kim, S; Imoto, S; Miyano, S

2004-01-01

We propose a statistical method to estimate gene networks from DNA microarray data and protein-protein interactions. Because physical interactions between proteins or multiprotein complexes are likely to regulate biological processes, using only mRNA expression data is not sufficient for estimating a gene network accurately. Our method adds knowledge about protein-protein interactions to the estimation method of gene networks under a Bayesian statistical framework. In the estimated gene network, a protein complex is modeled as a virtual node based on principal component analysis. We show the effectiveness of the proposed method through the analysis of Saccharomyces cerevisiae cell cycle data. The proposed method improves the accuracy of the estimated gene networks, and successfully identifies some biological facts.

Multireceiver Acoustic Communications in Time-Varying Environments

DTIC Science & Technology

2014-06-01

Canberra, ACT, 2012, pp. 1–7. [7] W. Chen and F. Yanjun, “Physical layer design consideration for underwater acoustic sensor networks ,”3rd IEEE Int...analysis of underwater acoustic MIMO communications,”OCEANS, Sydney, NSW, 2010, pp. 1–8. [9] Wines lab (2013). Wireless networks and embedded... NETWORKS ......................................................................3 B. CHALLENGES OF UNDERWATER ACOUSTIC COMMUNICATIONS

SPAN: Astronomy and astrophysics

NASA Technical Reports Server (NTRS)

Thomas, Valerie L.; Green, James L.; Warren, Wayne H., Jr.; Lopez-Swafford, Brian

1987-01-01

The Space Physics Analysis Network (SPAN) is a multi-mission, correlative data comparison network which links science research and data analysis computers in the U.S., Canada, and Europe. The purpose of this document is to provide Astronomy and Astrophysics scientists, currently reachable on SPAN, with basic information and contacts for access to correlative data bases, star catalogs, and other astrophysic facilities accessible over SPAN.

Chaotic itinerancy within the coupled dynamics between a physical body and neural oscillator networks.

PubMed

Park, Jihoon; Mori, Hiroki; Okuyama, Yuji; Asada, Minoru

2017-01-01

Chaotic itinerancy is a phenomenon in which the state of a nonlinear dynamical system spontaneously explores and attracts certain states in a state space. From this perspective, the diverse behavior of animals and its spontaneous transitions lead to a complex coupled dynamical system, including a physical body and a brain. Herein, a series of simulations using different types of non-linear oscillator networks (i.e., regular, small-world, scale-free, random) with a musculoskeletal model (i.e., a snake-like robot) as a physical body are conducted to understand how the chaotic itinerancy of bodily behavior emerges from the coupled dynamics between the body and the brain. A behavior analysis (behavior clustering) and network analysis for the classified behavior are then applied. The former consists of feature vector extraction from the motions and classification of the movement patterns that emerged from the coupled dynamics. The network structures behind the classified movement patterns are revealed by estimating the "information networks" different from the given non-linear oscillator networks based on the transfer entropy which finds the information flow among neurons. The experimental results show that: (1) the number of movement patterns and their duration depend on the sensor ratio to control the balance of strength between the body and the brain dynamics and on the type of the given non-linear oscillator networks; and (2) two kinds of information networks are found behind two kinds movement patterns with different durations by utilizing the complex network measures, clustering coefficient and the shortest path length with a negative and a positive relationship with the duration periods of movement patterns. The current results seem promising for a future extension of the method to a more complicated body and environment. Several requirements are also discussed.

Static, Dynamic and Semantic Dimensions: Towards a Multidisciplinary Approach of Social Networks Analysis

NASA Astrophysics Data System (ADS)

Thovex, Christophe; Trichet, Francky

The objective of our work is to extend static and dynamic models of Social Networks Analysis (SNA), by taking conceptual aspects of enterprises and institutions social graph into account. The originality of our multidisciplinary work is to introduce abstract notions of electro-physic to define new measures in SNA, for new decision-making functions dedicated to Human Resource Management (HRM). This paper introduces a multidimensional system and new measures: (1) a tension measure for social network analysis, (2) an electrodynamic, predictive and semantic system for recommendations on social graphs evolutions and (3) a reactance measure used to evaluate the individual stress at work of the members of a social network.

Cyberinfrastructure for high energy physics in Korea

NASA Astrophysics Data System (ADS)

Cho, Kihyeon; Kim, Hyunwoo; Jeung, Minho; High Energy Physics Team

2010-04-01

We introduce the hierarchy of cyberinfrastructure which consists of infrastructure (supercomputing and networks), Grid, e-Science, community and physics from bottom layer to top layer. KISTI is the national headquarter of supercomputer, network, Grid and e-Science in Korea. Therefore, KISTI is the best place to for high energy physicists to use cyberinfrastructure. We explain this concept on the CDF and the ALICE experiments. In the meantime, the goal of e-Science is to study high energy physics anytime and anywhere even if we are not on-site of accelerator laboratories. The components are data production, data processing and data analysis. The data production is to take both on-line and off-line shifts remotely. The data processing is to run jobs anytime, anywhere using Grid farms. The data analysis is to work together to publish papers using collaborative environment such as EVO (Enabling Virtual Organization) system. We also present the global community activities of FKPPL (France-Korea Particle Physics Laboratory) and physics as top layer.

Social network analysis of a project-based introductory physics course

NASA Astrophysics Data System (ADS)

Oakley, Christopher

2016-03-01

Research suggests that students benefit from peer interaction and active engagement in the classroom. The quality, nature, effect of these interactions is currently being explored by Physics Education Researchers. Spelman College offers an introductory physics sequence that addresses content and research skills by engaging students in open-ended research projects, a form of Project-Based Learning. Students have been surveyed at regular intervals during the second semester of trigonometry-based course to determine the frequency of interactions in and out of class. These interactions can be with current or past students, tutors, and instructors. This line of inquiry focuses on metrics of Social Network analysis, such as centrality of participants as well as segmentation of groups. Further research will refine and highlight deeper questions regarding student performance in this pedagogy and course sequence.

Book Review:

NASA Astrophysics Data System (ADS)

Vespignani, A.

2004-09-01

Networks have been recently recognized as playing a central role in understanding a wide range of systems spanning diverse scientific domains such as physics and biology, economics, computer science and information technology. Specific examples run from the structure of the Internet and the World Wide Web to the interconnections of finance agents and ecological food webs. These networked systems are generally made by many components whose microscopic interactions give rise to global structures characterized by emergent collective behaviour and complex topological properties. In this context the statistical physics approach finds a natural application since it attempts to explain the various large-scale statistical properties of networks in terms of local interactions governing the dynamical evolution of the constituent elements of the system. It is not by chance then that many of the seminal papers in the field have been published in the physics literature, and have nevertheless made a considerable impact on other disciplines. Indeed, a truly interdisciplinary approach is required in order to understand each specific system of interest, leading to a very interesting cross-fertilization between different scientific areas defining the emergence of a new research field sometimes called network science. The book of Dorogovtsev and Mendes is the first comprehensive monograph on this new scientific field. It provides a thorough presentation of the forefront research activities in the area of complex networks, with an extensive sampling of the disciplines involved and the kinds of problems that form the subject of inquiry. The book starts with a short introduction to graphs and network theory that introduces the tools and mathematical background needed for the rest of the book. The following part is devoted to an extensive presentation of the empirical analysis of real-world networks. While for obvious reasons of space the authors cannot analyse in every detail all the various examples, they provide the reader with a general vista that makes clear the relevance of network science to a wide range of natural and man-made systems. Two chapters are then committed to the detailed exposition of the statistical physics approach to equilibrium and non-equilibrium networks. The authors are two leading players in the area of network theory and offer a very careful and complete presentation of the statistical physics theory of evolving networks. Finally, in the last two chapters, the authors focus on various consequences of network topology for dynamical and physical phenomena occurring in these kinds of structures. The book is completed by a very extensive bibliography and some useful appendices containing some technical points arising in the mathematical discussion and data analysis. The book's mathematical level is fairly advanced and allows a coherent and unified framework for the study of networked structure. The book is targeted at mathematicians, physicists and social scientists alike. It will be appreciated by everybody working in the network area, and especially by any researcher or student entering the field that would like to have a reference text on the latest developments in network science.

Talking and learning physics: Predicting future grades from network measures and Force Concept Inventory pretest scores

NASA Astrophysics Data System (ADS)

Bruun, Jesper; Brewe, Eric

2013-12-01

The role of student interactions in learning situations is a foundation of sociocultural learning theory, and social network analysis can be used to quantify student relations. We discuss how self-reported student interactions can be viewed as processes of meaning making and use this to understand how quantitative measures that describe the position in a network, called centrality measures, can be understood in terms of interactions that happen in the context of a university physics course. We apply this discussion to an empirical data set of self-reported student interactions. In a weekly administered survey, first year university students enrolled in an introductory physics course at a Danish university indicated with whom they remembered having communicated within different interaction categories. For three categories pertaining to (1) communication about how to solve physics problems in the course (called the PS category), (2) communications about the nature of physics concepts (called the CD category), and (3) social interactions that are not strictly related to the content of the physics classes (called the ICS category) in the introductory mechanics course, we use the survey data to create networks of student interaction. For each of these networks, we calculate centrality measures for each student and correlate these measures with grades from the introductory course, grades from two subsequent courses, and the pretest Force Concept Inventory (FCI) scores. We find highly significant correlations (p<0.001) between network centrality measures and grades in all networks. We find the highest correlations between network centrality measures and future grades. In the network composed of interactions regarding problem solving (the PS network), the centrality measures hide and PageRank show the highest correlations (r=-0.32 and r=0.33, respectively) with future grades. In the CD network, the network measure target entropy shows the highest correlation (r=0.45) with future grades. In the network composed solely of noncontent related social interactions, these patterns of correlation are maintained in the sense that these network measures show the highest correlations and maintain their internal ranking. Using hierarchical linear regression, we find that a linear model that adds the network measures hide and target entropy, calculated on the ICS network, significantly improves a base model that uses only the FCI pretest scores from the beginning of the semester. Though one should not infer causality from these results, they do point to how social interactions in class are intertwined with academic interactions. We interpret this as an integral part of learning, and suggest that physics is a robust example.

Understanding the structure of community collaboration: the case of one Canadian health promotion network.

PubMed

Barnes, Martha; Maclean, Joanne; Cousens, Laura

2010-06-01

In 2004, over 6.8 million Canadians were considered overweight, with an additional 2.4 million labeled clinically obese. Due to these escalating levels of obesity in Canada, physical activity is being championed by politicians, physicians, educators and community members as a means to address this health crisis. In doing so, many organizations are being called upon to provide essential physical activity services and programs to combat rising obesity rates. Yet, strategies for achieving these organizations' mandates, which invariably involve stretching already scarce resources, are difficult to implement and sustain. One strategy for improving the health and physical activity levels of people in communities has been the creation of inter-organizational networks of service providers. Yet, little is known about whether networks are effective in addressing policy issues in non-clinical health settings. The purpose of this investigation was 2-fold; to use whole network analysis to determine the structure of one health promotion network in Canada, and to identify the types of ties shared by actors in the health network. Findings revealed a network wherein information sharing constituted the basis for collaboration, whereas efforts related to sharing resources, marketing and/or fundraising endeavors were less evident.

Social network types among older Korean adults: Associations with subjective health.

PubMed

Sohn, Sung Yun; Joo, Won-Tak; Kim, Woo Jung; Kim, Se Joo; Youm, Yoosik; Kim, Hyeon Chang; Park, Yeong-Ran; Lee, Eun

2017-01-01

With population aging now a global phenomenon, the health of older adults is becoming an increasingly important issue. Because the Korean population is aging at an unprecedented rate, preparing for public health problems associated with old age is particularly salient in this country. As the physical and mental health of older adults is related to their social relationships, investigating the social networks of older adults and their relationship to health status is important for establishing public health policies. The aims of this study were to identify social network types among older adults in South Korea and to examine the relationship of these social network types with self-rated health and depression. Data from the Korean Social Life, Health, and Aging Project were analyzed. Model-based clustering using finite normal mixture modeling was conducted to identify the social network types based on ten criterion variables of social relationships and activities: marital status, number of children, number of close relatives, number of friends, frequency of attendance at religious services, attendance at organized group meetings, in-degree centrality, out-degree centrality, closeness centrality, and betweenness centrality. Multivariate regression analysis was conducted to examine associations between the identified social network types and self-rated health and depression. The model-based clustering analysis revealed that social networks clustered into five types: diverse, family, congregant, congregant-restricted, and restricted. Diverse or family social network types were significantly associated with more favorable subjective mental health, whereas the restricted network type was significantly associated with poorer ratings of mental and physical health. In addition, our analysis identified unique social network types related to religious activities. In summary, we developed a comprehensive social network typology for older Korean adults. Copyright © 2016 Elsevier Ltd. All rights reserved.

Effects of resistance training, endurance training and whole-body vibration on lean body mass, muscle strength and physical performance in older people: a systematic review and network meta-analysis.

PubMed

Lai, Chih-Chin; Tu, Yu-Kang; Wang, Tyng-Guey; Huang, Yi-Ting; Chien, Kuo-Liong

2018-05-01

A variety of different types of exercise are promoted to improve muscle strength and physical performance in older people. We aimed to determine the relative effects of resistance training, endurance training and whole-body vibration on lean body mass, muscle strength and physical performance in older people. A systematic review and network meta-analysis. Adults aged 60 and over. Evidence from randomised controlled trials of resistance training, endurance training and whole-body vibration were combined. The effects of exercise interventions on lean body mass, muscle strength and physical performance were evaluated by conducting a network meta-analysis to compare multiple interventions and usual care. Risk of bias of included studies was assessed using the Cochrane Collaboration's tool. A meta-regression was performed to assess potential effect modifiers. Data were obtained from 30 trials involving 1,405 participants (age range: 60-92 years). No significant differences were found between the effects of exercise or usual care on lean body mass. Resistance training (minimum 6 weeks duration) achieved greater muscle strength improvement than did usual care (12.8 kg; 95% confidence interval [CI]: 8.5-17.0 kg). Resistance training and whole-body vibration were associated with greater physical performance improvement compared with usual care (2.6 times greater [95% CI: 1.3-3.9] and 2.1 times greater [95% CI: 0.5-3.7], respectively). Resistance training is the most effect intervention to improve muscle strength and physical performance in older people. Our findings also suggest that whole-body vibration is beneficial for physical performance. However, none of the three exercise interventions examined had a significant effect on lean body mass.

Sustainable Revitalization in Cultural Heritage Kampong Kauman Surakarta Supported by Spatial Analysis

NASA Astrophysics Data System (ADS)

Musyawaroh, M.; Pitana, T. S.; Masykuri, M.; Nandariyah

2018-02-01

Revitalization is a much-needed for a historic kampong as a settlement, place of business, and as tourist destinations. The research was conducted in Kauman as one of the cultural heritage kampong which was formerly as a residence of abdidalemulamaKeraton who also work as batik entrepreneurs. This study aims to formulate a sustainable revitalization step based on the character of the area and the building. Aspects of sustainable revitalization that analyzed are the physical and non-physical condition of the environment. This research is an applied research with qualitative rationalistic approach supported with spatial distribution analysis through satellite imagery and Arch-GIS. The results revealed that sustainable revitalization for Kaumancan be done through: 1) Physical condition of the environment consists of land and building use, green open space, recreational park and sport activities, streets, drainage network, sewer network, the garbage disposal network; 2) Non-physical of the environment consists of economy, heritage socio-cultural, and the engagement of relevant stakeholders. The difference of this study with others is, this study is a continuation of the Kauman revitalization assistance program which involves community participation to produce a more appropriate solution for the problem of kampong.

Launch Control Network Engineer

NASA Technical Reports Server (NTRS)

Medeiros, Samantha

2017-01-01

The Spaceport Command and Control System (SCCS) is being built at the Kennedy Space Center in order to successfully launch NASA’s revolutionary vehicle that allows humans to explore further into space than ever before. During my internship, I worked with the Network, Firewall, and Hardware teams that are all contributing to the huge SCCS network project effort. I learned the SCCS network design and the several concepts that are running in the background. I also updated and designed documentation for physical networks that are part of SCCS. This includes being able to assist and build physical installations as well as configurations. I worked with the network design for vehicle telemetry interfaces to the Launch Control System (LCS); this allows the interface to interact with other systems at other NASA locations. This network design includes the Space Launch System (SLS), Interim Cryogenic Propulsion Stage (ICPS), and the Orion Multipurpose Crew Vehicle (MPCV). I worked on the network design and implementation in the Customer Avionics Interface Development and Analysis (CAIDA) lab.

Chaotic itinerancy within the coupled dynamics between a physical body and neural oscillator networks

PubMed Central

Mori, Hiroki; Okuyama, Yuji; Asada, Minoru

2017-01-01

Chaotic itinerancy is a phenomenon in which the state of a nonlinear dynamical system spontaneously explores and attracts certain states in a state space. From this perspective, the diverse behavior of animals and its spontaneous transitions lead to a complex coupled dynamical system, including a physical body and a brain. Herein, a series of simulations using different types of non-linear oscillator networks (i.e., regular, small-world, scale-free, random) with a musculoskeletal model (i.e., a snake-like robot) as a physical body are conducted to understand how the chaotic itinerancy of bodily behavior emerges from the coupled dynamics between the body and the brain. A behavior analysis (behavior clustering) and network analysis for the classified behavior are then applied. The former consists of feature vector extraction from the motions and classification of the movement patterns that emerged from the coupled dynamics. The network structures behind the classified movement patterns are revealed by estimating the “information networks” different from the given non-linear oscillator networks based on the transfer entropy which finds the information flow among neurons. The experimental results show that: (1) the number of movement patterns and their duration depend on the sensor ratio to control the balance of strength between the body and the brain dynamics and on the type of the given non-linear oscillator networks; and (2) two kinds of information networks are found behind two kinds movement patterns with different durations by utilizing the complex network measures, clustering coefficient and the shortest path length with a negative and a positive relationship with the duration periods of movement patterns. The current results seem promising for a future extension of the method to a more complicated body and environment. Several requirements are also discussed. PMID:28796797

Network analysis of inter-organizational relationships and policy use among active living organizations in Alberta, Canada.

PubMed

Loitz, Christina C; Stearns, Jodie A; Fraser, Shawn N; Storey, Kate; Spence, John C

2017-08-09

Coordinated partnerships and collaborations can optimize the efficiency and effectiveness of service and program delivery in organizational networks. However, the extent to which organizations are working together to promote physical activity, and use physical activity policies in Canada, is unknown. This project sought to provide a snapshot of the funding, coordination and partnership relationships among provincial active living organizations (ALOs) in Alberta, Canada. Additionally, the awareness, and use of the provincial policy and national strategy by the organizations was examined. Provincial ALOs (N = 27) answered questions regarding their funding, coordination and partnership connections with other ALOs in the network. Social network analysis was employed to examine network structure and position of each ALO. Discriminant function analysis determined the extent to which degree centrality was associated with the use of the Active Alberta (AA) policy and Active Canada 20/20 (AC 20/20) strategy. The funding network had a low density level (density = .20) and was centralized around Alberta Tourism Parks and Recreation (ATPR; degree centralization = 48.77%, betweenness centralization = 32.43%). The coordination network had a moderate density level (density = .31), and was low-to-moderately centralized around a few organizations (degree centralization = 45.37%, betweenness centrality = 19.92%). The partnership network had a low density level (density = .15), and was moderate-to-highly centralized around ATPR. Most organizations were aware of AA (89%) and AC 20/20 (78%), however more were using AA (67%) compared to AC 20/20 (33%). Central ALOs in the funding network were more likely to use AA and AC 20/20. Central ALOs in the coordination network were more likely to use AC 20/20, but not AA. Increasing formal and informal relationships between organizations and integrating disconnected or peripheral organizations could increase the capacity of the network to promote active living across Alberta. Uptake of the AA policy within the network is high and appears to be facilitated by the most central ALO. Promoting policy use through a central organization appeared to be an effective strategy for disseminating the province-level physical activity policy and could be considered as a policy-uptake strategy by other regions.

Unified functional network and nonlinear time series analysis for complex systems science: The pyunicorn package

NASA Astrophysics Data System (ADS)

Donges, Jonathan; Heitzig, Jobst; Beronov, Boyan; Wiedermann, Marc; Runge, Jakob; Feng, Qing Yi; Tupikina, Liubov; Stolbova, Veronika; Donner, Reik; Marwan, Norbert; Dijkstra, Henk; Kurths, Jürgen

2016-04-01

We introduce the pyunicorn (Pythonic unified complex network and recurrence analysis toolbox) open source software package for applying and combining modern methods of data analysis and modeling from complex network theory and nonlinear time series analysis. pyunicorn is a fully object-oriented and easily parallelizable package written in the language Python. It allows for the construction of functional networks such as climate networks in climatology or functional brain networks in neuroscience representing the structure of statistical interrelationships in large data sets of time series and, subsequently, investigating this structure using advanced methods of complex network theory such as measures and models for spatial networks, networks of interacting networks, node-weighted statistics, or network surrogates. Additionally, pyunicorn provides insights into the nonlinear dynamics of complex systems as recorded in uni- and multivariate time series from a non-traditional perspective by means of recurrence quantification analysis, recurrence networks, visibility graphs, and construction of surrogate time series. The range of possible applications of the library is outlined, drawing on several examples mainly from the field of climatology. pyunicorn is available online at https://github.com/pik-copan/pyunicorn. Reference: J.F. Donges, J. Heitzig, B. Beronov, M. Wiedermann, J. Runge, Q.-Y. Feng, L. Tupikina, V. Stolbova, R.V. Donner, N. Marwan, H.A. Dijkstra, and J. Kurths, Unified functional network and nonlinear time series analysis for complex systems science: The pyunicorn package, Chaos 25, 113101 (2015), DOI: 10.1063/1.4934554, Preprint: arxiv.org:1507.01571 [physics.data-an].

Techniques for the Detection of Faulty Packet Header Modifications

DTIC Science & Technology

2014-03-12

layer approaches to check if packets are being altered by middleboxes and were primarily developed as network neutrality analysis tools. Switzerland works...local and metropolitan area networks –specific requirements part 11: Wireless LAN medium access control (MAC) and physical layer (PHY) specifications...policy or position of the Department of Defense or the U.S. Government. Understanding, measuring, and debugging IP networks , particularly across

On Event-Triggered Adaptive Architectures for Decentralized and Distributed Control of Large-Scale Modular Systems

PubMed Central

Albattat, Ali; Gruenwald, Benjamin C.; Yucelen, Tansel

2016-01-01

The last decade has witnessed an increased interest in physical systems controlled over wireless networks (networked control systems). These systems allow the computation of control signals via processors that are not attached to the physical systems, and the feedback loops are closed over wireless networks. The contribution of this paper is to design and analyze event-triggered decentralized and distributed adaptive control architectures for uncertain networked large-scale modular systems; that is, systems consist of physically-interconnected modules controlled over wireless networks. Specifically, the proposed adaptive architectures guarantee overall system stability while reducing wireless network utilization and achieving a given system performance in the presence of system uncertainties that can result from modeling and degraded modes of operation of the modules and their interconnections between each other. In addition to the theoretical findings including rigorous system stability and the boundedness analysis of the closed-loop dynamical system, as well as the characterization of the effect of user-defined event-triggering thresholds and the design parameters of the proposed adaptive architectures on the overall system performance, an illustrative numerical example is further provided to demonstrate the efficacy of the proposed decentralized and distributed control approaches. PMID:27537894

On Event-Triggered Adaptive Architectures for Decentralized and Distributed Control of Large-Scale Modular Systems.

PubMed

Albattat, Ali; Gruenwald, Benjamin C; Yucelen, Tansel

2016-08-16

The last decade has witnessed an increased interest in physical systems controlled over wireless networks (networked control systems). These systems allow the computation of control signals via processors that are not attached to the physical systems, and the feedback loops are closed over wireless networks. The contribution of this paper is to design and analyze event-triggered decentralized and distributed adaptive control architectures for uncertain networked large-scale modular systems; that is, systems consist of physically-interconnected modules controlled over wireless networks. Specifically, the proposed adaptive architectures guarantee overall system stability while reducing wireless network utilization and achieving a given system performance in the presence of system uncertainties that can result from modeling and degraded modes of operation of the modules and their interconnections between each other. In addition to the theoretical findings including rigorous system stability and the boundedness analysis of the closed-loop dynamical system, as well as the characterization of the effect of user-defined event-triggering thresholds and the design parameters of the proposed adaptive architectures on the overall system performance, an illustrative numerical example is further provided to demonstrate the efficacy of the proposed decentralized and distributed control approaches.

Spectral stability of unitary network models

NASA Astrophysics Data System (ADS)

Asch, Joachim; Bourget, Olivier; Joye, Alain

2015-08-01

We review various unitary network models used in quantum computing, spectral analysis or condensed matter physics and establish relationships between them. We show that symmetric one-dimensional quantum walks are universal, as are CMV matrices. We prove spectral stability and propagation properties for general asymptotically uniform models by means of unitary Mourre theory.

Social influence and motivation to change health behaviors among Mexican origin adults: Implications for diet and physical activity

PubMed Central

Ashida, Sato; Wilkinson, Anna V.; Koehly, Laura M.

2011-01-01

Purpose To evaluate whether influence from social network members is associated with motivation to change dietary and physical activity behaviors. Design Baseline assessment followed by mailing of family health history-based personalized messages (2 weeks) and follow-up assessment (3 months). Setting Families from an ongoing population-based cohort in Houston, TX. Subjects 475 adults from 161 Mexican origin families. Out of 347 households contacted, 162 (47%) participated. Measures Family health history, social networks, and motivation to change behaviors. Analysis Two-level logistic regression modeling. Results Having at least one network member who encourages one to eat more fruits and vegetables (p=.010) and to engage in regular physical activity (p=.046) was associated with motivation to change the relevant behavior. About 40% of the participants did not have encouragers for these behaviors. Conclusions Identification of new encouragers within networks and targeting natural encouragers (e.g., children, spouses) may increase the efficacy of interventions to motivate behavioral changes among Mexican origin adults. PMID:22208416

Flory-Stockmayer analysis on reprocessable polymer networks

NASA Astrophysics Data System (ADS)

Li, Lingqiao; Chen, Xi; Jin, Kailong; Torkelson, John

Reprocessable polymer networks can undergo structure rearrangement through dynamic chemistries under proper conditions, making them a promising candidate for recyclable crosslinked materials, e.g. tires. This research field has been focusing on various chemistries. However, there has been lacking of an essential physical theory explaining the relationship between abundancy of dynamic linkages and reprocessability. Based on the classical Flory-Stockmayer analysis on network gelation, we developed a similar analysis on reprocessable polymer networks to quantitatively predict the critical condition for reprocessability. Our theory indicates that it is unnecessary for all bonds to be dynamic to make the resulting network reprocessable. As long as there is no percolated permanent network in the system, the material can fully rearrange. To experimentally validate our theory, we used a thiol-epoxy network model system with various dynamic linkage compositions. The stress relaxation behavior of resulting materials supports our theoretical prediction: only 50 % of linkages between crosslinks need to be dynamic for a tri-arm network to be reprocessable. Therefore, this analysis provides the first fundamental theoretical platform for designing and evaluating reprocessable polymer networks. We thank McCormick Research Catalyst Award Fund and ISEN cluster fellowship (L. L.) for funding support.

Computer-Mediated Social Support for Physical Activity: A Content Analysis.

PubMed

Stragier, Jeroen; Mechant, Peter; De Marez, Lieven; Cardon, Greet

2018-02-01

Online fitness communities are a recent phenomenon experiencing growing user bases. They can be considered as online social networks in which recording, monitoring, and sharing of physical activity (PA) are the most prevalent practices. They have added a new dimension to the social experience of PA in which online peers function as virtual PA partners or supporters. However, research into seeking and receiving computer-mediated social support for PA is scarce. Our aim was to study to what extent using online fitness communities and sharing physical activities with online social networks results in receiving various types of online social support. Two databases, one containing physical activities logged with Strava and one containing physical activities logged with RunKeeper and shared on Twitter, were investigated for occurrence and type of social support, by means of a deductive content analysis. Results indicate that social support delivered through Twitter is not particularly extensive. On Strava, social support is significantly more prevalent. Especially esteem support, expressed as compliments for the accomplishment of an activity, is provided on both Strava and Twitter. The results demonstrate that social media have potential as a platform used for providing social support for PA, but differences among various social network sites can be substantial. Especially esteem support can be expected, in contrast to online health communities, where information support is more common.

Sensing network for electromagnetic fields generated by seismic activities

NASA Astrophysics Data System (ADS)

Gershenzon, Naum I.; Bambakidis, Gust; Ternovskiy, Igor V.

2014-06-01

The sensors network is becoming prolific and play now increasingly more important role in acquiring and processing information. Cyber-Physical Systems are focusing on investigation of integrated systems that includes sensing, networking, and computations. The physics of the seismic measurement and electromagnetic field measurement requires special consideration how to design electromagnetic field measurement networks for both research and detection earthquakes and explosions along with the seismic measurement networks. In addition, the electromagnetic sensor network itself could be designed and deployed, as a research tool with great deal of flexibility, the placement of the measuring nodes must be design based on systematic analysis of the seismic-electromagnetic interaction. In this article, we review the observations of the co-seismic electromagnetic field generated by earthquakes and man-made sources such as vibrations and explosions. The theoretical investigation allows the distribution of sensor nodes to be optimized and could be used to support existing geological networks. The placement of sensor nodes have to be determined based on physics of electromagnetic field distribution above the ground level. The results of theoretical investigations of seismo-electromagnetic phenomena are considered in Section I. First, we compare the relative contribution of various types of mechano-electromagnetic mechanisms and then analyze in detail the calculation of electromagnetic fields generated by piezomagnetic and electrokinetic effects.

Nondeducibility-Based Analysis of Cyber-Physical Systems

NASA Astrophysics Data System (ADS)

Gamage, Thoshitha; McMillin, Bruce

Controlling information flow in a cyber-physical system (CPS) is challenging because cyber domain decisions and actions manifest themselves as visible changes in the physical domain. This paper presents a nondeducibility-based observability analysis for CPSs. In many CPSs, the capacity of a low-level (LL) observer to deduce high-level (HL) actions ranges from limited to none. However, a collaborative set of observers strategically located in a network may be able to deduce all the HL actions. This paper models a distributed power electronics control device network using a simple DC circuit in order to understand the effect of multiple observers in a CPS. The analysis reveals that the number of observers required to deduce all the HL actions in a system increases linearly with the number of configurable units. A simple definition of nondeducibility based on the uniqueness of low-level projections is also presented. This definition is used to show that a system with two security domain levels could be considered “nondeducibility secure” if no unique LL projections exist.

Emulation Platform for Cyber Analysis of Wireless Communication Network Protocols

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

Van Leeuwen, Brian P.; Eldridge, John M.

Wireless networking and mobile communications is increasing around the world and in all sectors of our lives. With increasing use, the density and complexity of the systems increase with more base stations and advanced protocols to enable higher data throughputs. The security of data transported over wireless networks must also evolve with the advances in technologies enabling more capable wireless networks. However, means for analysis of the effectiveness of security approaches and implementations used on wireless networks are lacking. More specifically a capability to analyze the lower-layer protocols (i.e., Link and Physical layers) is a major challenge. An analysis approachmore » that incorporates protocol implementations without the need for RF emissions is necessary. In this research paper several emulation tools and custom extensions that enable an analysis platform to perform cyber security analysis of lower layer wireless networks is presented. A use case of a published exploit in the 802.11 (i.e., WiFi) protocol family is provided to demonstrate the effectiveness of the described emulation platform.« less

Epidemiologic research topics in Germany: a keyword network analysis of 2014 DGEpi conference presentations.

PubMed

Peter, Raphael Simon; Brehme, Torben; Völzke, Henry; Muche, Rainer; Rothenbacher, Dietrich; Büchele, Gisela

2016-06-01

Knowledge of epidemiologic research topics as well as trends is useful for scientific societies, researchers and funding agencies. In recent years researchers recognized the usefulness of keyword network analysis for visualizing and analyzing scientific research topics. Therefore, we applied keyword network analysis to present an overview of current epidemiologic research topics in Germany. Accepted submissions to the 9th annual congress of the German Society for Epidemiology (DGEpi) in 2014 were used as data source. Submitters had to choose one of 19 subject areas, and were ask to provide a title, structured abstract, names of authors along with their affiliations, and a list of freely selectable keywords. Keywords had been provided for 262 (82 %) submissions, 1030 keywords in total. Overall the most common keywords were: "migration" (18 times), "prevention" (15 times), followed by "children", "cohort study", "physical activity", and "secondary data analysis" (11 times each). Some keywords showed a certain concentration under one specific subject area, e.g. "migration" with 8 of 18 in social epidemiology or "breast cancer" with 4 of 7 in cancer epidemiology. While others like "physical activity" were equally distributed over multiple subject areas (cardiovascular & metabolic diseases, ageing, methods, paediatrics, prevention & health service research). This keyword network analysis demonstrated the high diversity of epidemiologic research topics with a large number of distinct keywords as presented at the annual conference of the DGEpi.

Restrictions of physical activity participation in older adults with disability: employing keyword network analysis.

PubMed

Koo, Kyo-Man; Kim, Chun-Jong; Park, Chae-Hee; Byeun, Jung-Kyun; Seo, Geon-Woo

2016-08-01

Older adults with disability might have been increasing due to the rapid aging of society. Many studies showed that physical activity is an essential part for improving quality of life in later lives. Regular physical activity is an efficient means that has roles of primary prevention and secondary prevention. However, there were few studies regarding older adults with disability and physical activity participation. The purpose of this current study was to investigate restriction factors to regularly participate older adults with disability in physical activity by employing keyword network analysis. Two hundred twenty-nine older adults with disability who were over 65 including aging with disability and disability with aging in type of physical disability and brain lesions defined by disabled person welfare law partook in the open questionnaire assessing barriers to participate in physical activity. The results showed that the keyword the most often used was 'Traffic' which was total of 21 times (3.47%) and the same proportion as in the 'personal' and 'economical'. Exercise was considered the most central keyword for participating in physical activity and keywords such as facility, physical activity, disabled, program, transportation, gym, discomfort, opportunity, and leisure activity were associated with exercise. In conclusion, it is necessary to educate older persons with disability about a true meaning of physical activity and providing more physical activity opportunities and decreasing inconvenience should be systematically structured in Korea.

Application of the device based on chirping of optical impulses for management of software-defined networks in dynamic mode

NASA Astrophysics Data System (ADS)

Vinogradova, Irina L.; Khasansin, Vadim R.; Andrianova, Anna V.; Yantilina, Liliya Z.; Vinogradov, Sergey L.

2016-03-01

The analysis of the influence of the physical layer concepts in optical networks on the performance of the whole network. It is concluded that the relevance of the search for new means of transmitting information on a physical level. It is proposed to use an optical chirp overhead transmission between controllers SDN. This article is devoted to research of a creation opportunity of optical neural switchboards controlled in addition by submitted optical radiation. It is supposed, that the managing radiation changes a parameter of refraction of optical environment of the device, and with it and length of a wave of information radiation. For the control by last is used multibeam interferometer. The brief estimation of technical aspects of construction of the device is carried out. The principle of using the device to an extensive network. Simulation of network performance parameters.

Methodology to model the energy and greenhouse gas emissions of electronic software distributions.

PubMed

Williams, Daniel R; Tang, Yinshan

2012-01-17

A new electronic software distribution (ESD) life cycle analysis (LCA) methodology and model structure were constructed to calculate energy consumption and greenhouse gas (GHG) emissions. In order to counteract the use of high level, top-down modeling efforts, and to increase result accuracy, a focus upon device details and data routes was taken. In order to compare ESD to a relevant physical distribution alternative, physical model boundaries and variables were described. The methodology was compiled from the analysis and operational data of a major online store which provides ESD and physical distribution options. The ESD method included the calculation of power consumption of data center server and networking devices. An in-depth method to calculate server efficiency and utilization was also included to account for virtualization and server efficiency features. Internet transfer power consumption was analyzed taking into account the number of data hops and networking devices used. The power consumed by online browsing and downloading was also factored into the model. The embedded CO(2)e of server and networking devices was proportioned to each ESD process. Three U.K.-based ESD scenarios were analyzed using the model which revealed potential CO(2)e savings of 83% when ESD was used over physical distribution. Results also highlighted the importance of server efficiency and utilization methods.

Use of annual physical examinations by aging Chinese Canadians.

PubMed

Lai, Daniel W L; Kalyniak, Sonya

2005-10-01

This study identified predictors of use of annual physical examination by aging Chinese Canadians. Data were collected from a random sample of 2,272 Chinese Canadians aged 55 and older. Based on the Andersen-Newman service utilization framework, hierarchical logistic regression analysis was used to examine the predictors of annual physical examination use. Predicting factors of annual physical health examination use were marital status, gender, length of residency in Canada, Chinese ethnic identity, social support, number of illnesses, dependency in instrumental activities of daily living (IADL), and depressive symptoms. Findings showed importance in targeting identified groups for preventive health education. Strengthened ethnic identity may serve to enhance one's social support network, which in turn facilitates the use of annual physical examinations. There may be awareness within the Chinese cultural network that builds education and attentiveness to preventive health care. The misconceptions about annual physical examinations were also discussed.

The SPAN cookbook: A practical guide to accessing SPAN

NASA Technical Reports Server (NTRS)

Mason, Stephanie; Tencati, Ronald D.; Stern, David M.; Capps, Kimberly D.; Dorman, Gary; Peters, David J.

1990-01-01

This is a manual for remote users who wish to send electronic mail messages from the Space Physics Analysis Network (SPAN) to scientific colleagues on other computer networks and vice versa. In several instances more than one gateway has been included for the same network. Users are provided with an introduction to each network listed with helpful details about accessing the system and mail syntax examples. Also included is information on file transfers, remote logins, and help telephone numbers.

The Use of Multi-Criteria Evaluation and Network Analysis in the Area Development Planning Process

DTIC Science & Technology

2013-03-01

layouts. The alternative layout scoring process, base in multi-criteria evaluation, returns a quantitative score for each alternative layout and a...The purpose of this research was to develop improvements to the area development planning process. These plans are used to improve operations within...an installation sub-section by altering the physical layout of facilities. One methodology was developed based on apply network analysis concepts to

An efficient management system for wireless sensor networks.

PubMed

Ma, Yi-Wei; Chen, Jiann-Liang; Huang, Yueh-Min; Lee, Mei-Yu

2010-01-01

Wireless sensor networks have garnered considerable attention recently. Networks typically have many sensor nodes, and are used in commercial, medical, scientific, and military applications for sensing and monitoring the physical world. Many researchers have attempted to improve wireless sensor network management efficiency. A Simple Network Management Protocol (SNMP)-based sensor network management system was developed that is a convenient and effective way for managers to monitor and control sensor network operations. This paper proposes a novel WSNManagement system that can show the connections stated of relationships among sensor nodes and can be used for monitoring, collecting, and analyzing information obtained by wireless sensor networks. The proposed network management system uses collected information for system configuration. The function of performance analysis facilitates convenient management of sensors. Experimental results show that the proposed method enhances the alive rate of an overall sensor node system, reduces the packet lost rate by roughly 5%, and reduces delay time by roughly 0.2 seconds. Performance analysis demonstrates that the proposed system is effective for wireless sensor network management.

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.

Heating value prediction for combustible fraction of municipal solid waste in Semarang using backpropagation neural network

NASA Astrophysics Data System (ADS)

Khuriati, Ainie; Setiabudi, Wahyu; Nur, Muhammad; Istadi, Istadi

2015-12-01

Backpropgation neural network was trained to predict of combustible fraction heating value of MSW from the physical composition. Waste-to-Energy (WtE) is a viable option for municipal solid waste (MSW) management. The influence of the heating value of municipal solid waste (MSW) is very important on the implementation of WtE systems. As MSW is heterogeneous material, direct heating value measurements are often not feasible. In this study an empirical model was developed to describe the heating value of the combustible fraction of municipal solid waste as a function of its physical composition of MSW using backpropagation neural network. Sampling process was carried out at Jatibarang landfill. The weight of each sorting sample taken from each discharged MSW vehicle load is 100 kg. The MSW physical components were grouped into paper wastes, absorbent hygiene product waste, styrofoam waste, HD plastic waste, plastic waste, rubber waste, textile waste, wood waste, yard wastes, kitchen waste, coco waste, and miscellaneous combustible waste. Network was trained by 24 datasets with 1200, 769, and 210 epochs. The results of this analysis showed that the correlation from the physical composition is better than multiple regression method .

Science and ethics meet: a mathematical view on one kind of violation of publication ethics

NASA Astrophysics Data System (ADS)

Shinyaeva, Taisiya S.; Tarasevich, Yuri Yu

2018-01-01

When a person who did not make a significant intellectual contribution to a published research is included into the co-author list, the person is called gift or guest author depending on the reason why the person has been added to the co-authors. Essential deviation of properties of a particular co-author network from typical values may evidenced that the network is artificial. Using network analysis, we have performed an attempt to characterize a typical co-author network. We performed analysis of the co-author networks using references in the thesis on Physics and Mathematics, Economics defended from 2012 to 2017 and planned to be defended in 2017 and 2018 in Russia. Properties of the co-author networks are expected to be a reference sample in future research.

A fully-automated neural network analysis of AFM force-distance curves for cancer tissue diagnosis

NASA Astrophysics Data System (ADS)

Minelli, Eleonora; Ciasca, Gabriele; Sassun, Tanya Enny; Antonelli, Manila; Palmieri, Valentina; Papi, Massimiliano; Maulucci, Giuseppe; Santoro, Antonio; Giangaspero, Felice; Delfini, Roberto; Campi, Gaetano; De Spirito, Marco

2017-10-01

Atomic Force Microscopy (AFM) has the unique capability of probing the nanoscale mechanical properties of biological systems that affect and are affected by the occurrence of many pathologies, including cancer. This capability has triggered growing interest in the translational process of AFM from physics laboratories to clinical practice. A factor still hindering the current use of AFM in diagnostics is related to the complexity of AFM data analysis, which is time-consuming and needs highly specialized personnel with a strong physical and mathematical background. In this work, we demonstrate an operator-independent neural-network approach for the analysis of surgically removed brain cancer tissues. This approach allowed us to distinguish—in a fully automated fashion—cancer from healthy tissues with high accuracy, also highlighting the presence and the location of infiltrating tumor cells.

Inferring hidden causal relations between pathway members using reduced Google matrix of directed biological networks

PubMed Central

2018-01-01

Signaling pathways represent parts of the global biological molecular network which connects them into a seamless whole through complex direct and indirect (hidden) crosstalk whose structure can change during development or in pathological conditions. We suggest a novel methodology, called Googlomics, for the structural analysis of directed biological networks using spectral analysis of their Google matrices, using parallels with quantum scattering theory, developed for nuclear and mesoscopic physics and quantum chaos. We introduce analytical “reduced Google matrix” method for the analysis of biological network structure. The method allows inferring hidden causal relations between the members of a signaling pathway or a functionally related group of genes. We investigate how the structure of hidden causal relations can be reprogrammed as a result of changes in the transcriptional network layer during cancerogenesis. The suggested Googlomics approach rigorously characterizes complex systemic changes in the wiring of large causal biological networks in a computationally efficient way. PMID:29370181

Complex networks as a unified framework for descriptive analysis and predictive modeling in climate

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

Steinhaeuser, Karsten J K; Chawla, Nitesh; Ganguly, Auroop R

The analysis of climate data has relied heavily on hypothesis-driven statistical methods, while projections of future climate are based primarily on physics-based computational models. However, in recent years a wealth of new datasets has become available. Therefore, we take a more data-centric approach and propose a unified framework for studying climate, with an aim towards characterizing observed phenomena as well as discovering new knowledge in the climate domain. Specifically, we posit that complex networks are well-suited for both descriptive analysis and predictive modeling tasks. We show that the structural properties of climate networks have useful interpretation within the domain. Further,more » we extract clusters from these networks and demonstrate their predictive power as climate indices. Our experimental results establish that the network clusters are statistically significantly better predictors than clusters derived using a more traditional clustering approach. Using complex networks as data representation thus enables the unique opportunity for descriptive and predictive modeling to inform each other.« less

The Citation Wake of Publications Detects Nobel Laureates' Papers

PubMed Central

Klosik, David F.; Bornholdt, Stefan

2014-01-01

For several decades, a leading paradigm of how to quantitatively assess scientific research has been the analysis of the aggregated citation information in a set of scientific publications. Although the representation of this information as a citation network has already been coined in the 1960s, it needed the systematic indexing of scientific literature to allow for impact metrics that actually made use of this network as a whole, improving on the then prevailing metrics that were almost exclusively based on the number of direct citations. However, besides focusing on the assignment of credit, the paper citation network can also be studied in terms of the proliferation of scientific ideas. Here we introduce a simple measure based on the shortest-paths in the paper's in-component or, simply speaking, on the shape and size of the wake of a paper within the citation network. Applied to a citation network containing Physical Review publications from more than a century, our approach is able to detect seminal articles which have introduced concepts of obvious importance to the further development of physics. We observe a large fraction of papers co-authored by Nobel Prize laureates in physics among the top-ranked publications. PMID:25437855

The citation wake of publications detects nobel laureates' papers.

PubMed

Klosik, David F; Bornholdt, Stefan

2014-01-01

For several decades, a leading paradigm of how to quantitatively assess scientific research has been the analysis of the aggregated citation information in a set of scientific publications. Although the representation of this information as a citation network has already been coined in the 1960s, it needed the systematic indexing of scientific literature to allow for impact metrics that actually made use of this network as a whole, improving on the then prevailing metrics that were almost exclusively based on the number of direct citations. However, besides focusing on the assignment of credit, the paper citation network can also be studied in terms of the proliferation of scientific ideas. Here we introduce a simple measure based on the shortest-paths in the paper's in-component or, simply speaking, on the shape and size of the wake of a paper within the citation network. Applied to a citation network containing Physical Review publications from more than a century, our approach is able to detect seminal articles which have introduced concepts of obvious importance to the further development of physics. We observe a large fraction of papers co-authored by Nobel Prize laureates in physics among the top-ranked publications.

Restrictions of physical activity participation in older adults with disability: employing keyword network analysis

PubMed Central

Koo, Kyo-Man; Kim, Chun-Jong; Park, Chae-Hee; Byeun, Jung-Kyun; Seo, Geon-Woo

2016-01-01

Older adults with disability might have been increasing due to the rapid aging of society. Many studies showed that physical activity is an essential part for improving quality of life in later lives. Regular physical activity is an efficient means that has roles of primary prevention and secondary prevention. However, there were few studies regarding older adults with disability and physical activity participation. The purpose of this current study was to investigate restriction factors to regularly participate older adults with disability in physical activity by employing keyword network analysis. Two hundred twenty-nine older adults with disability who were over 65 including aging with disability and disability with aging in type of physical disability and brain lesions defined by disabled person welfare law partook in the open questionnaire assessing barriers to participate in physical activity. The results showed that the keyword the most often used was ‘Traffic’ which was total of 21 times (3.47%) and the same proportion as in the ‘personal’ and ‘economical’. Exercise was considered the most central keyword for participating in physical activity and keywords such as facility, physical activity, disabled, program, transportation, gym, discomfort, opportunity, and leisure activity were associated with exercise. In conclusion, it is necessary to educate older persons with disability about a true meaning of physical activity and providing more physical activity opportunities and decreasing inconvenience should be systematically structured in Korea. PMID:27656637

Maximum entropy methods for extracting the learned features of deep neural networks.

PubMed

Finnegan, Alex; Song, Jun S

2017-10-01

New architectures of multilayer artificial neural networks and new methods for training them are rapidly revolutionizing the application of machine learning in diverse fields, including business, social science, physical sciences, and biology. Interpreting deep neural networks, however, currently remains elusive, and a critical challenge lies in understanding which meaningful features a network is actually learning. We present a general method for interpreting deep neural networks and extracting network-learned features from input data. We describe our algorithm in the context of biological sequence analysis. Our approach, based on ideas from statistical physics, samples from the maximum entropy distribution over possible sequences, anchored at an input sequence and subject to constraints implied by the empirical function learned by a network. Using our framework, we demonstrate that local transcription factor binding motifs can be identified from a network trained on ChIP-seq data and that nucleosome positioning signals are indeed learned by a network trained on chemical cleavage nucleosome maps. Imposing a further constraint on the maximum entropy distribution also allows us to probe whether a network is learning global sequence features, such as the high GC content in nucleosome-rich regions. This work thus provides valuable mathematical tools for interpreting and extracting learned features from feed-forward neural networks.

Fluxgate magnetorelaxometry for characterization of hydrogel polymerization kinetics and physical entrapment capacity.

PubMed

Heim, E; Harling, S; Ludwig, F; Menzel, H; Schilling, M

2008-05-21

Hydrogels have the potential for providing drug delivery systems with long release rates. The polymerization kinetics and the physical entrapment capacity of photo-cross-linked hydroxyethyl methacrylate hydroxyethylstarch hydrogels are investigated with a non-destructive method. For this purpose, superparamagnetic nanoparticles as replacements for biomolecules are used as probes. By analyzing their magnetic relaxation behavior, the amounts of physically entrapped and mobile nanoparticles can be determined. The hydrogels were loaded with five different concentrations of nanoparticles. Different methods of analysis of the relaxation curves and the influence of the microviscosity are discussed. This investigation allows one to optimize the UV light irradiation time and to determine the amount of physically entrapped nanoparticles in the hydrogel network. It was found that the polymerization kinetics is faster for decreasing nanoparticle concentration but not all nanoparticles can be physically entrapped in the network.

A convolutional neural network neutrino event classifier

DOE PAGES

Aurisano, A.; Radovic, A.; Rocco, D.; ...

2016-09-01

Here, convolutional neural networks (CNNs) have been widely applied in the computer vision community to solve complex problems in image recognition and analysis. We describe an application of the CNN technology to the problem of identifying particle interactions in sampling calorimeters used commonly in high energy physics and high energy neutrino physics in particular. Following a discussion of the core concepts of CNNs and recent innovations in CNN architectures related to the field of deep learning, we outline a specific application to the NOvA neutrino detector. This algorithm, CVN (Convolutional Visual Network) identifies neutrino interactions based on their topology withoutmore » the need for detailed reconstruction and outperforms algorithms currently in use by the NOvA collaboration.« less

A convolutional neural network neutrino event classifier

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

Aurisano, A.; Radovic, A.; Rocco, D.

Here, convolutional neural networks (CNNs) have been widely applied in the computer vision community to solve complex problems in image recognition and analysis. We describe an application of the CNN technology to the problem of identifying particle interactions in sampling calorimeters used commonly in high energy physics and high energy neutrino physics in particular. Following a discussion of the core concepts of CNNs and recent innovations in CNN architectures related to the field of deep learning, we outline a specific application to the NOvA neutrino detector. This algorithm, CVN (Convolutional Visual Network) identifies neutrino interactions based on their topology withoutmore » the need for detailed reconstruction and outperforms algorithms currently in use by the NOvA collaboration.« less

Students' network integration vs. persistence in introductory physics courses

NASA Astrophysics Data System (ADS)

Zwolak, Justyna; Brewe, Eric

2017-01-01

Society is constantly in flux, which demands the continuous development of our educational system to meet new challenges and impart the appropriate knowledge/skills to students. In order to improve student learning, among other things, the way we are teaching has significantly changed over the past few decades. We are moving away from traditional, lecture-based teaching towards more interactive, engagement-based strategies. A current, major challenge for universities is to increase student retention. While students' academic and social integration into an institution seems to be vital for student retention, research on the effect of interpersonal interactions is rare. I use of network analysis to investigate academic and social experiences of students in and beyond the classroom. In particular, there is a compelling case that transformed physics classes, such as Modeling Instruction (MI), promote persistence by the creation of learning communities that support the integration of students into the university. I will discuss recent results on pattern development in networks of MI students' interactions throughout the semester, as well as the effect of students' position within the network on their persistence in physics.

Reliability Analysis and Modeling of ZigBee Networks

NASA Astrophysics Data System (ADS)

Lin, Cheng-Min

The architecture of ZigBee networks focuses on developing low-cost, low-speed ubiquitous communication between devices. The ZigBee technique is based on IEEE 802.15.4, which specifies the physical layer and medium access control (MAC) for a low rate wireless personal area network (LR-WPAN). Currently, numerous wireless sensor networks have adapted the ZigBee open standard to develop various services to promote improved communication quality in our daily lives. The problem of system and network reliability in providing stable services has become more important because these services will be stopped if the system and network reliability is unstable. The ZigBee standard has three kinds of networks; star, tree and mesh. The paper models the ZigBee protocol stack from the physical layer to the application layer and analyzes these layer reliability and mean time to failure (MTTF). Channel resource usage, device role, network topology and application objects are used to evaluate reliability in the physical, medium access control, network, and application layers, respectively. In the star or tree networks, a series system and the reliability block diagram (RBD) technique can be used to solve their reliability problem. However, a division technology is applied here to overcome the problem because the network complexity is higher than that of the others. A mesh network using division technology is classified into several non-reducible series systems and edge parallel systems. Hence, the reliability of mesh networks is easily solved using series-parallel systems through our proposed scheme. The numerical results demonstrate that the reliability will increase for mesh networks when the number of edges in parallel systems increases while the reliability quickly drops when the number of edges and the number of nodes increase for all three networks. More use of resources is another factor impact on reliability decreasing. However, lower network reliability will occur due to network complexity, more resource usage and complex object relationship.

Statistical Analysis of Bus Networks in India

PubMed Central

2016-01-01

In this paper, we model the bus networks of six major Indian cities as graphs in L-space, and evaluate their various statistical properties. While airline and railway networks have been extensively studied, a comprehensive study on the structure and growth of bus networks is lacking. In India, where bus transport plays an important role in day-to-day commutation, it is of significant interest to analyze its topological structure and answer basic questions on its evolution, growth, robustness and resiliency. Although the common feature of small-world property is observed, our analysis reveals a wide spectrum of network topologies arising due to significant variation in the degree-distribution patterns in the networks. We also observe that these networks although, robust and resilient to random attacks are particularly degree-sensitive. Unlike real-world networks, such as Internet, WWW and airline, that are virtual, bus networks are physically constrained. Our findings therefore, throw light on the evolution of such geographically and constrained networks that will help us in designing more efficient bus networks in the future. PMID:27992590

Physics textbooks from the viewpoint of network structures

NASA Astrophysics Data System (ADS)

Králiková, Petra; Teleki, Aba

2017-01-01

We can observe self-organized networks all around us. These networks are, in general, scale invariant networks described by the Bianconi-Barabasi model. The self-organized networks (networks formed naturally when feedback acts on the system) show certain universality. These networks, in simplified models, have scale invariant distribution (Pareto distribution type I) and parameter α has value between 2 and 5. The textbooks are extremely important in the learning process and from this reason we studied physics textbook at the level of sentences and physics terms (bipartite network). The nodes represent physics terms, sentences, and pictures, tables, connected by links (by physics terms and transitional words and transitional phrases). We suppose that learning process are more robust and goes faster and easier if the physics textbook has a structure similar to structures of self-organized networks.

Associations between Aspects of Friendship Networks, Physical Activity, and Sedentary Behaviour among Adolescents

PubMed Central

McCormack, Gavin R.; Nettel-Aguirre, Alberto; Blackstaffe, Anita; Perry, Rosemary; Hawe, Penelope

2014-01-01

Background. Adolescent friendships have been linked to physical activity levels; however, network characteristics have not been broadly examined. Method. In a cross-sectional analysis of 1061 adolescents (11–15 years), achieving 60 minutes/day of moderate-to-vigorous physical activity (MVPA) and participating in over 2 hours/day of sedentary behaviour were determined based on friendship network characteristics (density; proportion of active/sedentary friends; betweenness centrality; popularity; clique membership) and perceived social support. Results. Adolescents with no friendship nominations participated in less MVPA. For boys and girls, a ten percent point increase in active friends was positively associated with achievement of 60 minutes/day of MVPA (OR 1.11; 95% CI 1.02–1.21, OR 1.14; 95% CI 1.02–1.27, resp.). For boys, higher social support from friends was negatively associated with achieving 60 minutes/day of MVPA (OR 0.63; 95% CI 0.42–0.96). Compared with low density networks, boys in higher density networks were more likely to participate in over 2 hours/day of sedentary behaviour (OR 2.93; 95% CI 1.32–6.49). Social support from friends also modified associations between network characteristics and MVPA and sedentary behaviour. Conclusion. Different network characteristics appeared to have different consequences. The proportion of active close friends was associated with MVPA, while network density was associated with sedentary behaviour. This poses challenges for intervention design. PMID:25328690

Micro-economic analysis of the physical constrained markets: game theory application to competitive electricity markets

NASA Astrophysics Data System (ADS)

Bompard, E.; Ma, Y. C.; Ragazzi, E.

2006-03-01

Competition has been introduced in the electricity markets with the goal of reducing prices and improving efficiency. The basic idea which stays behind this choice is that, in competitive markets, a greater quantity of the good is exchanged at a lower price, leading to higher market efficiency. Electricity markets are pretty different from other commodities mainly due to the physical constraints related to the network structure that may impact the market performance. The network structure of the system on which the economic transactions need to be undertaken poses strict physical and operational constraints. Strategic interactions among producers that game the market with the objective of maximizing their producer surplus must be taken into account when modeling competitive electricity markets. The physical constraints, specific of the electricity markets, provide additional opportunity of gaming to the market players. Game theory provides a tool to model such a context. This paper discussed the application of game theory to physical constrained electricity markets with the goal of providing tools for assessing the market performance and pinpointing the critical network constraints that may impact the market efficiency. The basic models of game theory specifically designed to represent the electricity markets will be presented. IEEE30 bus test system of the constrained electricity market will be discussed to show the network impacts on the market performances in presence of strategic bidding behavior of the producers.

Social Network and Content Analysis of the North American Carbon Program as a Scientific Community of Practice

NASA Technical Reports Server (NTRS)

Brown, Molly E.; Ihli, Monica; Hendrick, Oscar; Delgado-Arias, Sabrina; Escobar, Vanessa M.; Griffith, Peter

2015-01-01

The North American Carbon Program (NACP) was formed to further the scientific understanding of sources, sinks, and stocks of carbon in Earth's environment. Carbon cycle science integrates multidisciplinary research, providing decision-support information for managing climate and carbon-related change across multiple sectors of society. This investigation uses the conceptual framework of com-munities of practice (CoP) to explore the role that the NACP has played in connecting researchers into a carbon cycle knowledge network, and in enabling them to conduct physical science that includes ideas from social science. A CoP describes the communities formed when people consistently engage in shared communication and activities toward a common passion or learning goal. We apply the CoP model by using keyword analysis of abstracts from scientific publications to analyze the research outputs of the NACP in terms of its knowledge domain. We also construct a co-authorship network from the publications of core NACP members, describe the structure and social pathways within the community. Results of the content analysis indicate that the NACP community of practice has substantially expanded its research on human and social impacts on the carbon cycle, contributing to a better understanding of how human and physical processes interact with one another. Results of the co-authorship social network analysis demonstrate that the NACP has formed a tightly connected community with many social pathways through which knowledge may flow, and that it has also expanded its network of institutions involved in carbon cycle research over the past seven years.

Computer-Mediated Social Support for Physical Activity: A Content Analysis

ERIC Educational Resources Information Center

Stragier, Jeroen; Mechant, Peter; De Marez, Lieven; Cardon, Greet

2018-01-01

Purpose: Online fitness communities are a recent phenomenon experiencing growing user bases. They can be considered as online social networks in which recording, monitoring, and sharing of physical activity (PA) are the most prevalent practices. They have added a new dimension to the social experience of PA in which online peers function as…

The Elephant in the Schoolhouse: The Role of Propinquity in School Staff Interactions about Teaching

ERIC Educational Resources Information Center

Spillane, James P.; Shirrell, Matthew; Sweet, Tracy M.

2017-01-01

Although the physical arrangement of workspaces can both constrain and enable interactions among organizational members, sociological research in education has not extensively examined the role of physical proximity in determining work-related social ties among school staff. Using social network analysis, this article explores the relationship…

Revealing Fundamental Physics from the Daya Bay Neutrino Experiment Using Deep Neural Networks

DOE PAGES

Racah, Evan; Ko, Seyoon; Sadowski, Peter; ...

2017-02-02

Experiments in particle physics produce enormous quantities of data that must be analyzed and interpreted by teams of physicists. This analysis is often exploratory, where scientists are unable to enumerate the possible types of signal prior to performing the experiment. Thus, tools for summarizing, clustering, visualizing and classifying high-dimensional data are essential. Here in this work, we show that meaningful physical content can be revealed by transforming the raw data into a learned high-level representation using deep neural networks, with measurements taken at the Daya Bay Neutrino Experiment as a case study. We further show how convolutional deep neural networksmore » can provide an effective classification filter with greater than 97% accuracy across different classes of physics events, significantly better than other machine learning approaches.« less

Physical Attractiveness, Social Network Location, and Performance in the Military

DTIC Science & Technology

2008-03-01

PHYSICAL ATTRACTIVESS, SOCIAL NETWORK LOCATION, AND PERPORMANCE IN THE MILITARY THESIS...PHYSICAL ATTRACTIVESS, SOCIAL NETWORK LOCATION, AND PERFORMANCE IN THE MILITARY THESIS Presented to the Faculty Department of...PHYSICAL ATTRACTIVESS, SOCIAL NETWORK LOCATION, AND PERFORMANCE IN THE MILITARY Janell M. Lott, BS Second Lieutenant, USAF

Childhood Trauma, Social Networks, and the Mental Health of Adult Survivors.

PubMed

Schneider, F David; Loveland Cook, Cynthia A; Salas, Joanne; Scherrer, Jeffrey; Cleveland, Ivy N; Burge, Sandra K

2017-03-01

The purpose of this study was to investigate the relationship of childhood trauma to the quality of social networks and health outcomes later in adulthood. Data were obtained from a convenience sample of 254 adults seen in one of 10 primary care clinics in the state of Texas. Standardized measures of adverse childhood experiences (ACEs), stressful and supportive social relationships, medical conditions, anxiety, depression, and health-related quality of life were administered. Using latent class analysis, subjects were assigned to one of four ACE classes: (a) minimal childhood abuse (56%), (b) physical/verbal abuse of both child and mother with household alcohol abuse (13%), (c) verbal and physical abuse of child with household mental illness (12%), and (d) verbal abuse only (19%). Statistically significant differences across the four ACE classes were found for mental health outcomes in adulthood. Although respondents who were physically and verbally abused as children reported compromised mental health, this was particularly true for those who witnessed physical abuse of their mother. A similar relationship between ACE class and physical health was not found. The quality of adult social networks partly accounted for the relationship between ACE classes and mental health outcomes. Respondents exposed to ACEs with more supportive social networks as adults had diminished odds of reporting poor mental health. Conversely, increasing numbers of stressful social relationships contributed to adverse mental health outcomes. Although efforts to prevent childhood trauma remain a critical priority, the treatment of adult survivors needs to expand its focus on both strengthening social networks and decreasing the negative effects of stressful ones.

Interdependent Multi-Layer Networks: Modeling and Survivability Analysis with Applications to Space-Based Networks

PubMed Central

Castet, Jean-Francois; Saleh, Joseph H.

2013-01-01

This article develops a novel approach and algorithmic tools for the modeling and survivability analysis of networks with heterogeneous nodes, and examines their application to space-based networks. Space-based networks (SBNs) allow the sharing of spacecraft on-orbit resources, such as data storage, processing, and downlink. Each spacecraft in the network can have different subsystem composition and functionality, thus resulting in node heterogeneity. Most traditional survivability analyses of networks assume node homogeneity and as a result, are not suited for the analysis of SBNs. This work proposes that heterogeneous networks can be modeled as interdependent multi-layer networks, which enables their survivability analysis. The multi-layer aspect captures the breakdown of the network according to common functionalities across the different nodes, and it allows the emergence of homogeneous sub-networks, while the interdependency aspect constrains the network to capture the physical characteristics of each node. Definitions of primitives of failure propagation are devised. Formal characterization of interdependent multi-layer networks, as well as algorithmic tools for the analysis of failure propagation across the network are developed and illustrated with space applications. The SBN applications considered consist of several networked spacecraft that can tap into each other's Command and Data Handling subsystem, in case of failure of its own, including the Telemetry, Tracking and Command, the Control Processor, and the Data Handling sub-subsystems. Various design insights are derived and discussed, and the capability to perform trade-space analysis with the proposed approach for various network characteristics is indicated. The select results here shown quantify the incremental survivability gains (with respect to a particular class of threats) of the SBN over the traditional monolith spacecraft. Failure of the connectivity between nodes is also examined, and the results highlight the importance of the reliability of the wireless links between spacecraft (nodes) to enable any survivability improvements for space-based networks. PMID:23599835

Interdependent multi-layer networks: modeling and survivability analysis with applications to space-based networks.

PubMed

Castet, Jean-Francois; Saleh, Joseph H

2013-01-01

This article develops a novel approach and algorithmic tools for the modeling and survivability analysis of networks with heterogeneous nodes, and examines their application to space-based networks. Space-based networks (SBNs) allow the sharing of spacecraft on-orbit resources, such as data storage, processing, and downlink. Each spacecraft in the network can have different subsystem composition and functionality, thus resulting in node heterogeneity. Most traditional survivability analyses of networks assume node homogeneity and as a result, are not suited for the analysis of SBNs. This work proposes that heterogeneous networks can be modeled as interdependent multi-layer networks, which enables their survivability analysis. The multi-layer aspect captures the breakdown of the network according to common functionalities across the different nodes, and it allows the emergence of homogeneous sub-networks, while the interdependency aspect constrains the network to capture the physical characteristics of each node. Definitions of primitives of failure propagation are devised. Formal characterization of interdependent multi-layer networks, as well as algorithmic tools for the analysis of failure propagation across the network are developed and illustrated with space applications. The SBN applications considered consist of several networked spacecraft that can tap into each other's Command and Data Handling subsystem, in case of failure of its own, including the Telemetry, Tracking and Command, the Control Processor, and the Data Handling sub-subsystems. Various design insights are derived and discussed, and the capability to perform trade-space analysis with the proposed approach for various network characteristics is indicated. The select results here shown quantify the incremental survivability gains (with respect to a particular class of threats) of the SBN over the traditional monolith spacecraft. Failure of the connectivity between nodes is also examined, and the results highlight the importance of the reliability of the wireless links between spacecraft (nodes) to enable any survivability improvements for space-based networks.

Predicting Physical Interactions between Protein Complexes*

PubMed Central

Clancy, Trevor; Rødland, Einar Andreas; Nygard, Ståle; Hovig, Eivind

2013-01-01

Protein complexes enact most biochemical functions in the cell. Dynamic interactions between protein complexes are frequent in many cellular processes. As they are often of a transient nature, they may be difficult to detect using current genome-wide screens. Here, we describe a method to computationally predict physical interactions between protein complexes, applied to both humans and yeast. We integrated manually curated protein complexes and physical protein interaction networks, and we designed a statistical method to identify pairs of protein complexes where the number of protein interactions between a complex pair is due to an actual physical interaction between the complexes. An evaluation against manually curated physical complex-complex interactions in yeast revealed that 50% of these interactions could be predicted in this manner. A community network analysis of the highest scoring pairs revealed a biologically sensible organization of physical complex-complex interactions in the cell. Such analyses of proteomes may serve as a guide to the discovery of novel functional cellular relationships. PMID:23438732

Extensive cross-talk and global regulators identified from an analysis of the integrated transcriptional and signaling network in Escherichia coli.

PubMed

Antiqueira, Lucas; Janga, Sarath Chandra; Costa, Luciano da Fontoura

2012-11-01

To understand the regulatory dynamics of transcription factors (TFs) and their interplay with other cellular components we have integrated transcriptional, protein-protein and the allosteric or equivalent interactions which mediate the physiological activity of TFs in Escherichia coli. To study this integrated network we computed a set of network measurements followed by principal component analysis (PCA), investigated the correlations between network structure and dynamics, and carried out a procedure for motif detection. In particular, we show that outliers identified in the integrated network based on their network properties correspond to previously characterized global transcriptional regulators. Furthermore, outliers are highly and widely expressed across conditions, thus supporting their global nature in controlling many genes in the cell. Motifs revealed that TFs not only interact physically with each other but also obtain feedback from signals delivered by signaling proteins supporting the extensive cross-talk between different types of networks. Our analysis can lead to the development of a general framework for detecting and understanding global regulatory factors in regulatory networks and reinforces the importance of integrating multiple types of interactions in underpinning the interrelationships between them.

Molecular inspired models for prediction and control of directional FSO/RF wireless networks

NASA Astrophysics Data System (ADS)

Llorca, Jaime; Milner, Stuart D.; Davis, Christopher C.

2010-08-01

Directional wireless networks using FSO and RF transmissions provide wireless backbone support for mobile communications in dynamic environments. The heterogeneous and dynamic nature of such networks challenges their robustness and requires self-organization mechanisms to assure end-to-end broadband connectivity. We developed a framework based on the definition of a potential energy function to characterize robustness in communication networks and the study of first and second order variations of the potential energy to provide prediction and control strategies for network performance optimization. In this paper, we present non-convex molecular potentials such as the Morse Potential, used to describe the potential energy of bonds within molecules, for the characterization of communication links in the presence of physical constraints such as the power available at the network nodes. The inclusion of the Morse Potential translates into adaptive control strategies where forces on network nodes drive the release, retention or reconfiguration of communication links for network performance optimization. Simulation results show the effectiveness of our self-organized control mechanism, where the physical topology reorganizes to maximize the number of source to destination communicating pairs. Molecular Normal Mode Analysis (NMA) techniques for assessing network performance degradation in dynamic networks are also presented. Preliminary results show correlation between peaks in the eigenvalues of the Hessian of the network potential and network degradation.

Nursing work stress: the impacts of social network structure and organizational citizenship behavior.

PubMed

Tsang, Seng-Su; Chen, Tzu-Yin; Wang, Shih-Fong; Tai, Hsin-Ling

2012-03-01

The nursing workplace imposes significantly more stress on its employees than other workplace settings. Organizational resources, both physical and psychological, have been recognized in prior studies as important alleviators of nursing workplace stress. Whereas physical resources are less difficult to manipulate because of their tangibility, psychological resources, particularly psychological support from colleagues, are typically not deployed to greatest effect. This article investigated the alleviation of nursing work stress using resources already extant in coworker social networks. Researchers conducted a survey in a dialysis department at a medical center located in Taipei City, Taiwan. This survey measured nurse work stress, satisfaction, organizational citizenship behavior (OCB) and social network structures. Researchers employed UCINET to analyze the network structure data, which were in dyadic matrix format to estimate nurse network centralities and used partial least squares analysis to estimate research construct path coefficients and test extrapolated hypotheses. The level of OCB induced by nurse social ties was satisfactory and did not only directly increased work satisfaction but also alleviated work stress, which indirectly boosted work satisfaction. Findings suggest that managers may be able to use social network analysis to identify persons appropriate to conduct the distribution of organizational resources. Choosing those with multiple social connections can help distribute resources effectively and induce higher OCB levels within the organization. In addition, staff with strong friendship network connections may provide appropriate psychological resources (support) to coworkers. If those with high friendship network centrality receive proper counseling training, they should be in a good position to provide assistance when needed.

Analysis of wireless sensor network topology and estimation of optimal network deployment by deterministic radio channel characterization.

PubMed

Aguirre, Erik; Lopez-Iturri, Peio; Azpilicueta, Leire; Astrain, José Javier; Villadangos, Jesús; Falcone, Francisco

2015-02-05

One of the main challenges in the implementation and design of context-aware scenarios is the adequate deployment strategy for Wireless Sensor Networks (WSNs), mainly due to the strong dependence of the radiofrequency physical layer with the surrounding media, which can lead to non-optimal network designs. In this work, radioplanning analysis for WSN deployment is proposed by employing a deterministic 3D ray launching technique in order to provide insight into complex wireless channel behavior in context-aware indoor scenarios. The proposed radioplanning procedure is validated with a testbed implemented with a Mobile Ad Hoc Network WSN following a chain configuration, enabling the analysis and assessment of a rich variety of parameters, such as received signal level, signal quality and estimation of power consumption. The adoption of deterministic radio channel techniques allows the design and further deployment of WSNs in heterogeneous wireless scenarios with optimized behavior in terms of coverage, capacity, quality of service and energy consumption.

Multilayer motif analysis of brain networks

NASA Astrophysics Data System (ADS)

Battiston, Federico; Nicosia, Vincenzo; Chavez, Mario; Latora, Vito

2017-04-01

In the last decade, network science has shed new light both on the structural (anatomical) and on the functional (correlations in the activity) connectivity among the different areas of the human brain. The analysis of brain networks has made possible to detect the central areas of a neural system and to identify its building blocks by looking at overabundant small subgraphs, known as motifs. However, network analysis of the brain has so far mainly focused on anatomical and functional networks as separate entities. The recently developed mathematical framework of multi-layer networks allows us to perform an analysis of the human brain where the structural and functional layers are considered together. In this work, we describe how to classify the subgraphs of a multiplex network, and we extend the motif analysis to networks with an arbitrary number of layers. We then extract multi-layer motifs in brain networks of healthy subjects by considering networks with two layers, anatomical and functional, respectively, obtained from diffusion and functional magnetic resonance imaging. Results indicate that subgraphs in which the presence of a physical connection between brain areas (links at the structural layer) coexists with a non-trivial positive correlation in their activities are statistically overabundant. Finally, we investigate the existence of a reinforcement mechanism between the two layers by looking at how the probability to find a link in one layer depends on the intensity of the connection in the other one. Showing that functional connectivity is non-trivially constrained by the underlying anatomical network, our work contributes to a better understanding of the interplay between the structure and function in the human brain.

Talking and Learning Physics: Predicting Future Grades from Network Measures and Force Concept Inventory Pretest Scores

ERIC Educational Resources Information Center

Bruun, Jesper; Brewe, Eric

2013-01-01

The role of student interactions in learning situations is a foundation of sociocultural learning theory, and social network analysis can be used to quantify student relations. We discuss how self-reported student interactions can be viewed as processes of meaning making and use this to understand how quantitative measures that describe the…

SPAN: Ocean science

NASA Technical Reports Server (NTRS)

Thomas, Valerie L.; Koblinsky, Chester J.; Webster, Ferris; Zlotnicki, Victor; Green, James L.

1987-01-01

The Space Physics Analysis Network (SPAN) is a multi-mission, correlative data comparison network which links space and Earth science research and data analysis computers. It provides a common working environment for sharing computer resources, sharing computer peripherals, solving proprietary problems, and providing the potential for significant time and cost savings for correlative data analysis. This is one of a series of discipline-specific SPAN documents which are intended to complement the SPAN primer and SPAN Management documents. Their purpose is to provide the discipline scientists with a comprehensive set of documents to assist in the use of SPAN for discipline specific scientific research.

Investigating Student Communities with Network Analysis of Interactions in a Physics Learning Center

ERIC Educational Resources Information Center

Brewe, Eric; Kramer, Laird; Sawtelle, Vashti

2012-01-01

Developing a sense of community among students is one of the three pillars of an overall reform effort to increase participation in physics, and the sciences more broadly, at Florida International University. The emergence of a research and learning community, embedded within a course reform effort, has contributed to increased recruitment and…

Analysis of physical layer performance of hybrid optical-wireless access network

NASA Astrophysics Data System (ADS)

Shaddad, R. Q.; Mohammad, A. B.; Al-hetar, A. M.

2011-09-01

The hybrid optical-wireless access network (HOWAN) is a favorable architecture for next generation access network. It is an optimal combination of an optical backhaul and a wireless front-end for an efficient access network. In this paper, the HOWAN architecture is designed based on a wavelengths division multiplexing/time division multiplexing passive optical network (WDM/TDM PON) at the optical backhaul and a wireless fidelity (WiFi) technology at the wireless front-end. The HOWAN is proposed that can provide blanket coverage of broadband and flexible connection for end-users. Most of the existing works, based on performance evaluation are concerned on network layer aspects. This paper reports physical layer performance in terms of the bit error rate (BER), eye diagram, and signal-to-noise ratio (SNR) of the communication system. It accommodates 8 wavelength channels with 32 optical network unit/wireless access points (ONU/APs). It is demonstrated that downstream and upstream of 2 Gb/s can be achieved by optical backhaul for each wavelength channel along optical fiber length of 20 km and a data rate of 54 Mb/s per ONU/AP along a 50 m outdoor wireless link.

Pore network extraction from pore space images of various porous media systems

NASA Astrophysics Data System (ADS)

Yi, Zhixing; Lin, Mian; Jiang, Wenbin; Zhang, Zhaobin; Li, Haishan; Gao, Jian

2017-04-01

Pore network extraction, which is defined as the transformation from irregular pore space to a simplified network in the form of pores connected by throats, is significant to microstructure analysis and network modeling. A physically realistic pore network is not only a representation of the pore space in the sense of topology and morphology, but also a good tool for predicting transport properties accurately. We present a method to extract pore network by employing the centrally located medial axis to guide the construction of maximal-balls-like skeleton where the pores and throats are defined and parameterized. To validate our method, various rock samples including sand pack, sandstones, and carbonates were used to extract pore networks. The pore structures were compared quantitatively with the structures extracted by medial axis method or maximal ball method. The predicted absolute permeability and formation factor were verified against the theoretical solutions obtained by lattice Boltzmann method and finite volume method, respectively. The two-phase flow was simulated through the networks extracted from homogeneous sandstones, and the generated relative permeability curves were compared with the data obtained from experimental method and other numerical models. The results show that the accuracy of our network is higher than that of other networks for predicting transport properties, so the presented method is more reliable for extracting physically realistic pore network.

Anticipating flash-floods: Multi-scale aspects of the social response

NASA Astrophysics Data System (ADS)

Lutoff, Céline; Creutin, Jean-Dominique; Ruin, Isabelle; Borga, Marco

2016-10-01

This paper aims at exploring the anticipation phase before a flash flood, corresponding to the time between the first climatic signs and the peak-flow. We focus the analysis on people's behaviors observing how they use this period to organize themselves for facing the event. The analysis is made through the definition of three specific scales: the timeliness scale, an analytical scale of anticipatory actions and the scale of human response network. Using a cross-scale and cross level analysis enables to define different phases in the anticipation period where different kind of environmental precursors are mobilized by the actors in order to make sense of the situation and adapt. Three main points deserve attention at the end: firstly, the concepts of timeliness, anticipatory actions and crisis network scales enable to understand differently what happens both physically and socially during an extreme event; secondly, analyzing the precursors shows that each level of crisis network uses different kinds of signs for estimating the situation, organizing and reacting; thirdly, there is a potential for improvement in observation on both social and physical processes at different scales, for verifying the theory of the anticipatory phases.

Literature Review on Modeling Cyber Networks and Evaluating Cyber Risks.

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

Kelic, Andjelka; Campbell, Philip L

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

Hamiltonian dynamics for complex food webs

NASA Astrophysics Data System (ADS)

Kozlov, Vladimir; Vakulenko, Sergey; Wennergren, Uno

2016-03-01

We investigate stability and dynamics of large ecological networks by introducing classical methods of dynamical system theory from physics, including Hamiltonian and averaging methods. Our analysis exploits the topological structure of the network, namely the existence of strongly connected nodes (hubs) in the networks. We reveal new relations between topology, interaction structure, and network dynamics. We describe mechanisms of catastrophic phenomena leading to sharp changes of dynamics and hence completely altering the ecosystem. We also show how these phenomena depend on the structure of interaction between species. We can conclude that a Hamiltonian structure of biological interactions leads to stability and large biodiversity.

Network structure of multivariate time series.

PubMed

Lacasa, Lucas; Nicosia, Vincenzo; Latora, Vito

2015-10-21

Our understanding of a variety of phenomena in physics, biology and economics crucially depends on the analysis of multivariate time series. While a wide range tools and techniques for time series analysis already exist, the increasing availability of massive data structures calls for new approaches for multidimensional signal processing. We present here a non-parametric method to analyse multivariate time series, based on the mapping of a multidimensional time series into a multilayer network, which allows to extract information on a high dimensional dynamical system through the analysis of the structure of the associated multiplex network. The method is simple to implement, general, scalable, does not require ad hoc phase space partitioning, and is thus suitable for the analysis of large, heterogeneous and non-stationary time series. We show that simple structural descriptors of the associated multiplex networks allow to extract and quantify nontrivial properties of coupled chaotic maps, including the transition between different dynamical phases and the onset of various types of synchronization. As a concrete example we then study financial time series, showing that a multiplex network analysis can efficiently discriminate crises from periods of financial stability, where standard methods based on time-series symbolization often fail.

A Typology to Explain Changing Social Networks Post Stroke.

PubMed

Northcott, Sarah; Hirani, Shashivadan P; Hilari, Katerina

2018-05-08

Social network typologies have been used to classify the general population but have not previously been applied to the stroke population. This study investigated whether social network types remain stable following a stroke, and if not, why some people shift network type. We used a mixed methods design. Participants were recruited from two acute stroke units. They completed the Stroke Social Network Scale (SSNS) two weeks and six months post stroke and in-depth interviews 8-15 months following the stroke. Qualitative data was analysed using Framework Analysis; k-means cluster analysis was applied to the six-month data set. Eighty-seven participants were recruited, 71 were followed up at six months, and 29 completed in-depth interviews. It was possible to classify all 29 participants into one of the following network types both prestroke and post stroke: diverse; friends-based; family-based; restricted-supported; restricted-unsupported. The main shift that took place post stroke was participants moving out of a diverse network into a family-based one. The friends-based network type was relatively stable. Two network types became more populated post stroke: restricted-unsupported and family-based. Triangulatory evidence was provided by k-means cluster analysis, which produced a cluster solution (for n = 71) with comparable characteristics to the network types derived from qualitative analysis. Following a stroke, a person's social network is vulnerable to change. Explanatory factors for shifting network type included the physical and also psychological impact of having a stroke, as well as the tendency to lose contact with friends rather than family.

Assessing user engagement in a health promotion website using social networking.

PubMed

Tague, Rhys; Maeder, Anthony J; Vandelanotte, Corneel; Kolt, Gregory S; Caperchione, Cristina M; Rosenkranz, Richard R; Savage, Trevor N; Van Itallie, Anetta

2014-01-01

Remote provision of supportive mechanisms for preventive health is a fast-growing area in eHealth. Web-based interventions have been suggested as an effective way to increase adoption and maintenance of healthy lifestyle behaviours. This paper describes results obtained in the "Walk 2.0" trial to promote physical activity through a self-managed walking programme, using a social networking website that provided an online collaborative environment. Engagement of participants with the website was assessed by monitoring usage of the individual social networking functions (e.g. status post). The results demonstrate that users generally preferred contributing non-interactive public posts of information concerned with their individual physical activity levels, and more occasionally communicating privately to friends. Further analysis of topics within posts was done by classifying word usage frequencies. Results indicated that the dominant topics are well aligned with the social environment within which physical activity takes place. Topics centred around four main areas: description of the activity, timing of the activity, affective response to the activity, and context within which the activity occurs. These findings suggest that strong levels of user awareness and communication occur in the social networking setting, indicative of beneficial self-image and self-actualisation effects.

Overview of physical dosimetry methods for triage application integrated in the new European network RENEB.

PubMed

Trompier, François; Burbidge, Christopher; Bassinet, Céline; Baumann, Marion; Bortolin, Emanuela; De Angelis, Cinzia; Eakins, Jonathan; Della Monaca, Sara; Fattibene, Paola; Quattrini, Maria Cristina; Tanner, Rick; Wieser, Albrecht; Woda, Clemens

2017-01-01

In the EC-funded project RENEB (Realizing the European Network in Biodosimetry), physical methods applied to fortuitous dosimetric materials are used to complement biological dosimetry, to increase dose assessment capacity for large-scale radiation/nuclear accidents. This paper describes the work performed to implement Optically Stimulated Luminescence (OSL) and Electron Paramagnetic Resonance (EPR) dosimetry techniques. OSL is applied to electronic components and EPR to touch-screen glass from mobile phones. To implement these new approaches, several blind tests and inter-laboratory comparisons (ILC) were organized for each assay. OSL systems have shown good performances. EPR systems also show good performance in controlled conditions, but ILC have also demonstrated that post-irradiation exposure to sunlight increases the complexity of the EPR signal analysis. Physically-based dosimetry techniques present high capacity, new possibilities for accident dosimetry, especially in the case of large-scale events. Some of the techniques applied can be considered as operational (e.g. OSL on Surface Mounting Devices [SMD]) and provide a large increase of measurement capacity for existing networks. Other techniques and devices currently undergoing validation or development in Europe could lead to considerable increases in the capacity of the RENEB accident dosimetry network.

Scientific production on indoor air quality of environments used for physical exercise and sports practice: Bibliometric analysis.

PubMed

Andrade, Alexandro; Dominski, Fábio Hech; Coimbra, Danilo Reis

2017-07-01

In order to minimize adverse health effects and increase the benefits of physical activity, it is important to systematize indoor air quality study in environments used for physical exercise and sports. To investigate and analyze the scientific production related to indoor air quality of environments used for physical exercise and sports practice through a bibliometric analysis. The databases Scielo, Science Direct, Scopus, Lilacs, Medline via Pubmed, and SportDiscus were searched from their inception to March 2016. Bibliometric analysis was performed for authors, institutions, countries, and collaborative networks, in relation to publication year, theme, citation network, funding agency, and analysis of titles and keywords of publications. Country, area, and impact factor of the journals were analyzed. Of 1281 studies screened, 34 satisfied the inclusion criteria. The first publication occurred in 1975. An increase in publications was observed in the last 15 years. Most of the studies were performed by researchers in the USA, followed by Portugal and Italy. Seventeen different scientific journals have published studies on the subject, and most are in the area of Environmental Sciences. It was noted that the categories of author keywords associated with "Pollutants," "Sport Environment," and "Physical Exercise" were the most commonly used in most studies. A total of 68% of the studies had at least one funding agency, and 81% of studies published in the last decade had funding. Our results demonstrate that there is recent exponential growth, driven in the last decade by researchers in environmental science from European institutions. Copyright © 2017 Elsevier Ltd. All rights reserved.

Autonomous perception and decision making in cyber-physical systems

NASA Astrophysics Data System (ADS)

Sarkar, Soumik

2011-07-01

The cyber-physical system (CPS) is a relatively new interdisciplinary technology area that includes the general class of embedded and hybrid systems. CPSs require integration of computation and physical processes that involves the aspects of physical quantities such as time, energy and space during information processing and control. The physical space is the source of information and the cyber space makes use of the generated information to make decisions. This dissertation proposes an overall architecture of autonomous perception-based decision & control of complex cyber-physical systems. Perception involves the recently developed framework of Symbolic Dynamic Filtering for abstraction of physical world in the cyber space. For example, under this framework, sensor observations from a physical entity are discretized temporally and spatially to generate blocks of symbols, also called words that form a language. A grammar of a language is the set of rules that determine the relationships among words to build sentences. Subsequently, a physical system is conjectured to be a linguistic source that is capable of generating a specific language. The proposed technology is validated on various (experimental and simulated) case studies that include health monitoring of aircraft gas turbine engines, detection and estimation of fatigue damage in polycrystalline alloys, and parameter identification. Control of complex cyber-physical systems involve distributed sensing, computation, control as well as complexity analysis. A novel statistical mechanics-inspired complexity analysis approach is proposed in this dissertation. In such a scenario of networked physical systems, the distribution of physical entities determines the underlying network topology and the interaction among the entities forms the abstract cyber space. It is envisioned that the general contributions, made in this dissertation, will be useful for potential application areas such as smart power grids and buildings, distributed energy systems, advanced health care procedures and future ground and air transportation systems.

Design of pressure-driven microfluidic networks using electric circuit analogy.

PubMed

Oh, Kwang W; Lee, Kangsun; Ahn, Byungwook; Furlani, Edward P

2012-02-07

This article reviews the application of electric circuit methods for the analysis of pressure-driven microfluidic networks with an emphasis on concentration- and flow-dependent systems. The application of circuit methods to microfluidics is based on the analogous behaviour of hydraulic and electric circuits with correlations of pressure to voltage, volumetric flow rate to current, and hydraulic to electric resistance. Circuit analysis enables rapid predictions of pressure-driven laminar flow in microchannels and is very useful for designing complex microfluidic networks in advance of fabrication. This article provides a comprehensive overview of the physics of pressure-driven laminar flow, the formal analogy between electric and hydraulic circuits, applications of circuit theory to microfluidic network-based devices, recent development and applications of concentration- and flow-dependent microfluidic networks, and promising future applications. The lab-on-a-chip (LOC) and microfluidics community will gain insightful ideas and practical design strategies for developing unique microfluidic network-based devices to address a broad range of biological, chemical, pharmaceutical, and other scientific and technical challenges.

Graph modeling systems and methods

DOEpatents

Neergaard, Mike

2015-10-13

An apparatus and a method for vulnerability and reliability modeling are provided. The method generally includes constructing a graph model of a physical network using a computer, the graph model including a plurality of terminating vertices to represent nodes in the physical network, a plurality of edges to represent transmission paths in the physical network, and a non-terminating vertex to represent a non-nodal vulnerability along a transmission path in the physical network. The method additionally includes evaluating the vulnerability and reliability of the physical network using the constructed graph model, wherein the vulnerability and reliability evaluation includes a determination of whether each terminating and non-terminating vertex represents a critical point of failure. The method can be utilized to evaluate wide variety of networks, including power grid infrastructures, communication network topologies, and fluid distribution systems.

Student Agency: an Analysis of Students' Networked Relations Across the Informal and Formal Learning Domains

NASA Astrophysics Data System (ADS)

Rappa, Natasha Anne; Tang, Kok-Sing

2017-06-01

Agency is a construct facilitating our examination of when and how young people extend their own learning across contexts. However, little is known about the role played by adolescent learners' sense of agency. This paper reports two cases of students' agentively employing and developing science literacy practices—one in Singapore and the other in the USA. The paper illustrates how these two adolescent learners in different ways creatively accessed, navigated and integrated in-school and out-of-school discourses to support and nurture their learning of physics. Data were gleaned from students' work and interviews with students participating in a physics curricular programme in which they made linkages between their chosen out-of-school texts and several physics concepts learnt in school. The students' agentive moves were identified by means of situational mapping, which involved a relational analysis of the students' chosen artefacts and discourses across time and space. This relational analysis enabled us to address questions of student agency—how it can be effected, realised, construed and examined. It highlights possible ways to intervene in these networked relations to facilitate adolescents' agentive moves in their learning endeavours.

A Delay-Aware and Reliable Data Aggregation for Cyber-Physical Sensing

PubMed Central

Zhang, Jinhuan; Long, Jun; Zhang, Chengyuan; Zhao, Guihu

2017-01-01

Physical information sensed by various sensors in a cyber-physical system should be collected for further operation. In many applications, data aggregation should take reliability and delay into consideration. To address these problems, a novel Tiered Structure Routing-based Delay-Aware and Reliable Data Aggregation scheme named TSR-DARDA for spherical physical objects is proposed. By dividing the spherical network constructed by dispersed sensor nodes into circular tiers with specifically designed widths and cells, TSTR-DARDA tries to enable as many nodes as possible to transmit data simultaneously. In order to ensure transmission reliability, lost packets are retransmitted. Moreover, to minimize the latency while maintaining reliability for data collection, in-network aggregation and broadcast techniques are adopted to deal with the transmission between data collecting nodes in the outer layer and their parent data collecting nodes in the inner layer. Thus, the optimization problem is transformed to minimize the delay under reliability constraints by controlling the system parameters. To demonstrate the effectiveness of the proposed scheme, we have conducted extensive theoretical analysis and comparisons to evaluate the performance of TSR-DARDA. The analysis and simulations show that TSR-DARDA leads to lower delay with reliability satisfaction. PMID:28218668

UFMulti: A new parallel processing software system for HEP

NASA Astrophysics Data System (ADS)

Avery, Paul; White, Andrew

1989-12-01

UFMulti is a multiprocessing software package designed for general purpose high energy physics applications, including physics and detector simulation, data reduction and DST physics analysis. The system is particularly well suited for installations where several workstation or computers are connected through a local area network (LAN). The initial configuration of the software is currently running on VAX/VMS machines with a planned extension to ULTRIX, using the new RISC CPUs from Digital, in the near future.

Performance Analysis of Physical Layer Security of Opportunistic Scheduling in Multiuser Multirelay Cooperative Networks

PubMed Central

Shim, Kyusung; Do, Nhu Tri; An, Beongku

2017-01-01

In this paper, we study the physical layer security (PLS) of opportunistic scheduling for uplink scenarios of multiuser multirelay cooperative networks. To this end, we propose a low-complexity, yet comparable secrecy performance source relay selection scheme, called the proposed source relay selection (PSRS) scheme. Specifically, the PSRS scheme first selects the least vulnerable source and then selects the relay that maximizes the system secrecy capacity for the given selected source. Additionally, the maximal ratio combining (MRC) technique and the selection combining (SC) technique are considered at the eavesdropper, respectively. Investigating the system performance in terms of secrecy outage probability (SOP), closed-form expressions of the SOP are derived. The developed analysis is corroborated through Monte Carlo simulation. Numerical results show that the PSRS scheme significantly improves the secure ability of the system compared to that of the random source relay selection scheme, but does not outperform the optimal joint source relay selection (OJSRS) scheme. However, the PSRS scheme drastically reduces the required amount of channel state information (CSI) estimations compared to that required by the OJSRS scheme, specially in dense cooperative networks. PMID:28212286

The interaction of social networks and child obesity prevention program effects: the pathways trial.

PubMed

Shin, Hee-Sung; Valente, Thomas W; Riggs, Nathaniel R; Huh, Jimi; Spruijt-Metz, Donna; Chou, Chih-Ping; Ann Pentz, Mary

2014-06-01

Social network analysis was used to examine whether peer influence from one's social networks moderates obesity prevention program effects on obesity-related behaviors: healthful and unhealthful. Participants included 557 children residing in Southern California. The survey assessed health-promoting behaviors (i.e., physical activity at school, physical activity outside of school, and fruit and vegetable intake), as well as unhealthful behaviors (high-calorie, low-nutrient intake and sedentary activity), and peer exposure calculated from social network nominations as indicators of peer influence. Multilevel models were conducted separately on outcomes predicted by program participation, peer exposure, and program participation by peer exposure. Results indicated that peer exposure was positively associated with one's own healthful and unhealthful behaviors. Program participation effects were moderated by peer influence, but only when unhealthful peer influence was present. Results suggest that peer influence can diminish or amplify prevention programs Future interventions should consider peer-led components to promote healthful influence of peers on healthful and unhealthful behaviors, and programs should be mindful that their effects are moderated by social networks. Copyright © 2014 The Obesity Society.

How to improve collaboration between the public health sector and other policy sectors to reduce health inequalities? - A study in sixteen municipalities in the Netherlands.

PubMed

Storm, Ilse; den Hertog, Frank; van Oers, Hans; Schuit, Albertine J

2016-06-22

The causes of health inequalities are complex. For the reduction of health inequalities, intersectoral collaboration between the public health sector and both social policy sectors (e.g. youth affairs, education) and physical policy sectors (e.g. housing, spatial planning) is essential, but in local practice difficult to realize. The aim of this study was to examine the collaboration between the sectors in question more closely and to identify opportunities for improvement. A qualitative descriptive analysis of five aspects of collaboration within sixteen Dutch municipalities was performed to examine the collaboration between the public health sector and other policy sectors: 1) involvement of the sectors in the public health policy network, 2) harmonisation of objectives, 3) use of policies by the relevant sectors, 4) formalised collaboration, and 5) previous experience. Empirical data on these collaboration aspects were collected based on document analysis, questionnaires and interviews. The study found that the policy workers of social sectors were more involved in the public health network and more frequently supported the objectives in the field of health inequality reduction. Both social policy sectors and physical policy sectors used policies and activities to reduce health inequalities. More is done to influence the determinants of health inequality through policies aimed at lifestyle and social setting than through policies aimed at socioeconomic factors and the physical environment. Where the physical policy sectors are involved in the public health network, the collaboration follows a very similar pattern as with the social policy sectors. All sectors recognise the importance of good relationships, positive experiences, a common interest in working together and coordinated mechanisms. This study shows that there is scope for improving collaboration in the field of health inequality reduction between the public health sector and both social policy sectors and physical policy sectors. Ways in which improvement could be realised include involving physical policy sectors in the network, pursuing widely supported policy goals, making balanced efforts to influence determinants of health inequalities, and increasing the emphasis on a programmatic approach.

Structural and functional social network attributes moderate the association of self-rated health with mental health in midlife and older adults.

PubMed

Windsor, Tim D; Rioseco, Pilar; Fiori, Katherine L; Curtis, Rachel G; Booth, Heather

2016-01-01

Social relationships are multifaceted, and different social network components can operate via different processes to influence well-being. This study examined associations of social network structure and relationship quality (positive and negative social exchanges) with mental health in midlife and older adults. The focus was on both direct associations of network structure and relationship quality with mental health, and whether these social network attributes moderated the association of self-rated health (SRH) with mental health. Analyses were based on survey data provided by 2001 (Mean age = 65, SD = 8.07) midlife and older adults. We used Latent Class Analysis (LCA) to classify participants into network types based on network structure (partner status, network size, contact frequency, and activity engagement), and used continuous measures of positive and negative social exchanges to operationalize relationship quality. Regression analysis was used to test moderation. LCA revealed network types generally consistent with those reported in previous studies. Participants in more diverse networks reported better mental health than those categorized into a restricted network type after adjustment for age, sex, education, and employment status. Analysis of moderation indicated that those with poorer SRH were less likely to report poorer mental health if they were classified into more diverse networks. A similar moderation effect was also evident for positive exchanges. The findings suggest that both quantity and quality of social relationships can play a role in buffering against the negative implications of physical health decline for mental health.

Analysis of white box test of cyber-physical system

NASA Astrophysics Data System (ADS)

Li, Bo; Zhang, Lichen

2017-05-01

The Cyber-Physical System is a complex system in which the information system is closely integrated with the physical system. Through the environment detection and the combination of computing, communication and control process, the physical real-time perception and dynamic control function are realized. CPS is another information revolution after the Internet, and his presence will change the way people interact with the physical world. In this paper, the concept of CPS and white box testing is introduced, and then the white box test for CPS hardware, software, network and system is discussed in detail. Finally, the research on CPS is prospected.

Stochastic lumping analysis for linear kinetics and its application to the fluctuation relations between hierarchical kinetic networks.

PubMed

Deng, De-Ming; Chang, Cheng-Hung

2015-05-14

Conventional studies of biomolecular behaviors rely largely on the construction of kinetic schemes. Since the selection of these networks is not unique, a concern is raised whether and under which conditions hierarchical schemes can reveal the same experimentally measured fluctuating behaviors and unique fluctuation related physical properties. To clarify these questions, we introduce stochasticity into the traditional lumping analysis, generalize it from rate equations to chemical master equations and stochastic differential equations, and extract the fluctuation relations between kinetically and thermodynamically equivalent networks under intrinsic and extrinsic noises. The results provide a theoretical basis for the legitimate use of low-dimensional models in the studies of macromolecular fluctuations and, more generally, for exploring stochastic features in different levels of contracted networks in chemical and biological kinetic systems.

Centrality in earthquake multiplex networks

NASA Astrophysics Data System (ADS)

Lotfi, Nastaran; Darooneh, Amir Hossein; Rodrigues, Francisco A.

2018-06-01

Seismic time series has been mapped as a complex network, where a geographical region is divided into square cells that represent the nodes and connections are defined according to the sequence of earthquakes. In this paper, we map a seismic time series to a temporal network, described by a multiplex network, and characterize the evolution of the network structure in terms of the eigenvector centrality measure. We generalize previous works that considered the single layer representation of earthquake networks. Our results suggest that the multiplex representation captures better earthquake activity than methods based on single layer networks. We also verify that the regions with highest seismological activities in Iran and California can be identified from the network centrality analysis. The temporal modeling of seismic data provided here may open new possibilities for a better comprehension of the physics of earthquakes.

Modeling the Internet.

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

Kelic, Andjelka; Mitchell, Michael David; Shirah, Donald N.

The National Infrastructure Simulations and Analysis Center (NISAC) has developed a nationwide model of the Internet to study the potential impact of the loss of physical facilities on the network and on other infrastructures that depend on the Internet for services. The model looks at the Internet from the perspective of Internet Service Providers (ISPs) and their connectivity and can be used to determine how the network connectivity could be modified to assist in mitigating an event. In addition the model could be used to explore how portions of the network could be made more resilient to disruptive events.

Smooth information flow in temperature climate network reflects mass transport

NASA Astrophysics Data System (ADS)

Hlinka, Jaroslav; Jajcay, Nikola; Hartman, David; Paluš, Milan

2017-03-01

A directed climate network is constructed by Granger causality analysis of air temperature time series from a regular grid covering the whole Earth. Using winner-takes-all network thresholding approach, a structure of a smooth information flow is revealed, hidden to previous studies. The relevance of this observation is confirmed by comparison with the air mass transfer defined by the wind field. Their close relation illustrates that although the information transferred due to the causal influence is not a physical quantity, the information transfer is tied to the transfer of mass and energy.

Analysis of citation networks as a new tool for scientific research

DOE PAGES

Vasudevan, R. K.; Ziatdinov, M.; Chen, C.; ...

2016-12-06

The rapid growth of scientific publications necessitates new methods to understand the direction of scientific research within fields of study, ascertain the importance of particular groups, authors, or institutions, compute metrics that can determine the importance (centrality) of particular seminal papers, and provide insight into the social (collaboration) networks that are present. We present one such method based on analysis of citation networks, using the freely available CiteSpace Program. We use citation network analysis on three examples, including a single material that has been widely explored in the last decade (BiFeO 3), two small subfields with a minimal number ofmore » authors (flexoelectricity and Kitaev physics), and a much wider field with thousands of publications pertaining to a single technique (scanning tunneling microscopy). Interpretation of the analysis and key insights into the fields, such as whether the fields are experiencing resurgence or stagnation, are discussed, and author or collaboration networks that are prominent are determined. Such methods represent a paradigm shift in our way of dealing with the large volume of scientific publications and could change the way literature searches and reviews are conducted, as well as how the impact of specific work is assessed.« less

Analysis of citation networks as a new tool for scientific research

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

Vasudevan, R. K.; Ziatdinov, M.; Chen, C.

The rapid growth of scientific publications necessitates new methods to understand the direction of scientific research within fields of study, ascertain the importance of particular groups, authors, or institutions, compute metrics that can determine the importance (centrality) of particular seminal papers, and provide insight into the social (collaboration) networks that are present. We present one such method based on analysis of citation networks, using the freely available CiteSpace Program. We use citation network analysis on three examples, including a single material that has been widely explored in the last decade (BiFeO 3), two small subfields with a minimal number ofmore » authors (flexoelectricity and Kitaev physics), and a much wider field with thousands of publications pertaining to a single technique (scanning tunneling microscopy). Interpretation of the analysis and key insights into the fields, such as whether the fields are experiencing resurgence or stagnation, are discussed, and author or collaboration networks that are prominent are determined. Such methods represent a paradigm shift in our way of dealing with the large volume of scientific publications and could change the way literature searches and reviews are conducted, as well as how the impact of specific work is assessed.« less

Physical and social activities mediate the associations between social network types and ventilatory function in Chinese older adults.

PubMed

Cheng, Sheung-Tak; Leung, Edward M F; Chan, Trista Wai Sze

2014-06-01

This study examined the associations between social network types and peak expiratory flow (PEF), and whether these associations were mediated by social and physical activities and mood. Nine hundred twenty-four community-dwelling Chinese older adults, who were classified into five network types (diverse, friend-focused, family-focused, distant family, and restricted), provided data on demographics, social and physical activities, mood, smoking, chronic diseases, and instrumental activities of daily living. PEF and biological covariates, including blood lipids and glucose, blood pressure, and height and weight, were assessed. Two measures of PEF were analyzed: the raw reading in L/min and the reading expressed as percentage of predicted normal value on the basis of age, sex, and height. Diverse, friend-focused, and distant family networks were hypothesized to have better PEF values compared with restricted networks, through higher physical and/or social activities. No relative advantage was predicted for family-focused networks because such networks tend to be associated with lower physical activity. Older adults with diverse, friend-focused, and distant family networks had significantly better PEF measures than those with restricted networks. The associations between diverse network and PEF measures were partially mediated by physical exercise and socializing activity. The associations between friend-focused network and PEF measures were partially mediated by socializing activity. No significant PEF differences between family-focused and restricted networks were found. Findings suggest that social network types are associated with PEF in older adults, and that network-type differences in physical and socializing activity is partly responsible for this relationship. PsycINFO Database Record (c) 2014 APA, all rights reserved.

Analysing efficiency of IPv6 packet transmission over 6LoWPAN network

NASA Astrophysics Data System (ADS)

Kozłowski, Adam; Sosnowski, Janusz

2017-08-01

Practical proliferation of Internet of Things (IoT) concept depends upon communication efficiency in the related network. In the paper we outline basic features of wireless communication protocols used in IoT and concentrate on analysing communication overheads. In particular, we discuss the impact of IPv6 packet length on 6LoWPAN network operation with physical and MAC layer defined by IEEE 802.15.4 standard. The presented analysis methodology is useful in estimation of the total goodput (throughput at the application level) and energy consumptions within the whole traffic model which are the crucial features of IoT networks.

Communications among data and science centers

NASA Technical Reports Server (NTRS)

Green, James L.

1990-01-01

The ability to electronically access and query the contents of remote computer archives is of singular importance in space and earth sciences; the present evaluation of such on-line information networks' development status foresees swift expansion of their data capabilities and complexity, in view of the volumes of data that will continue to be generated by NASA missions. The U.S.'s National Space Science Data Center (NSSDC) manages NASA's largest science computer network, the Space Physics Analysis Network; a comprehensive account is given of the structure of NSSDC international access through BITNET, and of connections to the NSSDC available in the Americas via the International X.25 network.

A communications model for an ISAS to NASA span link

NASA Technical Reports Server (NTRS)

Green, James L.; Mcguire, Robert E.; Lopez-Swafford, Brian

1987-01-01

The authors propose that an initial computer-to-computer communication link use the public packet switched networks (PPSN) Venus-P in Japan and TELENET in the U.S. When the traffic warrants it, this link would then be upgraded to a dedicated leased line that directly connects into the Space Physics Analysis Network (SPAN). The proposed system of hardware and software will easily support migration to such a dedicated link. It therefore provides a cost effective approach to the network problem. Once a dedicated line becomes operation it is suggested that the public networks link and continue to coexist, providing a backup capability.

Network testbed creation and validation

DOEpatents

Thai, Tan Q.; Urias, Vincent; Van Leeuwen, Brian P.; Watts, Kristopher K.; Sweeney, Andrew John

2017-03-21

Embodiments of network testbed creation and validation processes are described herein. A "network testbed" is a replicated environment used to validate a target network or an aspect of its design. Embodiments describe a network testbed that comprises virtual testbed nodes executed via a plurality of physical infrastructure nodes. The virtual testbed nodes utilize these hardware resources as a network "fabric," thereby enabling rapid configuration and reconfiguration of the virtual testbed nodes without requiring reconfiguration of the physical infrastructure nodes. Thus, in contrast to prior art solutions which require a tester manually build an emulated environment of physically connected network devices, embodiments receive or derive a target network description and build out a replica of this description using virtual testbed nodes executed via the physical infrastructure nodes. This process allows for the creation of very large (e.g., tens of thousands of network elements) and/or very topologically complex test networks.

Network testbed creation and validation

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

Thai, Tan Q.; Urias, Vincent; Van Leeuwen, Brian P.

Embodiments of network testbed creation and validation processes are described herein. A "network testbed" is a replicated environment used to validate a target network or an aspect of its design. Embodiments describe a network testbed that comprises virtual testbed nodes executed via a plurality of physical infrastructure nodes. The virtual testbed nodes utilize these hardware resources as a network "fabric," thereby enabling rapid configuration and reconfiguration of the virtual testbed nodes without requiring reconfiguration of the physical infrastructure nodes. Thus, in contrast to prior art solutions which require a tester manually build an emulated environment of physically connected network devices,more » embodiments receive or derive a target network description and build out a replica of this description using virtual testbed nodes executed via the physical infrastructure nodes. This process allows for the creation of very large (e.g., tens of thousands of network elements) and/or very topologically complex test networks.« less

Automated analysis of Physarum network structure and dynamics

NASA Astrophysics Data System (ADS)

Fricker, Mark D.; Akita, Dai; Heaton, Luke LM; Jones, Nick; Obara, Boguslaw; Nakagaki, Toshiyuki

2017-06-01

We evaluate different ridge-enhancement and segmentation methods to automatically extract the network architecture from time-series of Physarum plasmodia withdrawing from an arena via a single exit. Whilst all methods gave reasonable results, judged by precision-recall analysis against a ground-truth skeleton, the mean phase angle (Feature Type) from intensity-independent, phase-congruency edge enhancement and watershed segmentation was the most robust to variation in threshold parameters. The resultant single pixel-wide segmented skeleton was converted to a graph representation as a set of weighted adjacency matrices containing the physical dimensions of each vein, and the inter-vein regions. We encapsulate the complete image processing and network analysis pipeline in a downloadable software package, and provide an extensive set of metrics that characterise the network structure, including hierarchical loop decomposition to analyse the nested structure of the developing network. In addition, the change in volume for each vein and intervening plasmodial sheet was used to predict the net flow across the network. The scaling relationships between predicted current, speed and shear force with vein radius were consistent with predictions from Murray’s law. This work was presented at PhysNet 2015.

Social Networks and Participation with Others for Youth with Learning, Attention and Autism Spectrum Disorders

PubMed Central

Kreider, Consuelo M.; Bendixen, Roxanna M.; Young, Mary Ellen; Prudencio, Stephanie M.; McCarty, Christopher; Mann, William C.

2015-01-01

Background Social participation involves activities and roles providing interactions with others, including those within their social networks. Purpose Characterize social networks and participation with others for 36 adolescents, ages 11-16 years, with (n = 19) and without (n = 17) learning disability, attention disorder or high-functioning autism. Methods Social networks were measured using methods of personal network analysis. The Children's Assessment of Participation and Enjoyment With Whom dimension scores was used to measure participation with others. Youth from the clinical group were interviewed regarding their experiences within their social networks. Findings Group differences were observed for six social network variables and in the proportion of overall, physical, recreational, social and informal activities engaged with family and/or friends. Qualitative findings explicated strategies used in building, shaping and maintaining their social networks. Implications Social network factors should be considered when seeking to understand social participation. PMID:26755040

Unravelling networks in local public health policymaking in three European countries - a systems analysis.

PubMed

Spitters, Hilde P E M; Lau, Cathrine J; Sandu, Petru; Quanjel, Marcel; Dulf, Diana; Glümer, Charlotte; van Oers, Hans A M; van de Goor, Ien A M

2017-02-03

Facilitating and enhancing interaction between stakeholders involved in the policymaking process to stimulate collaboration and use of evidence, is important to foster the development of effective Health Enhancing Physical Activity (HEPA) policies. Performing an analysis of real-world policymaking processes will help reveal the complexity of a network of stakeholders. Therefore, the main objectives were to unravel the stakeholder network in the policy process by conducting three systems analyses, and to increase insight into the similarities and differences in the policy processes of these European country cases. A systems analysis of the local HEPA policymaking process was performed in three European countries involved in the 'REsearch into POlicy to enhance Physical Activity' (REPOPA) project, resulting in three schematic models showing the main stakeholders and their relationships. The models were used to compare the systems, focusing on implications with respect to collaboration and use of evidence in local HEPA policymaking. Policy documents and relevant webpages were examined and main stakeholders were interviewed. The systems analysis in each country identified the main stakeholders involved and their position and relations in the policymaking process. The Netherlands and Denmark were the most similar and both differed most from Romania, especially at the level of accountability of the local public authorities for local HEPA policymaking. The categories of driving forces underlying the relations between stakeholders were formal relations, informal interaction and knowledge exchange. A systems analysis providing detailed descriptions of positions and relations in the stakeholder network in local level HEPA policymaking is rather unique in this area. The analyses are useful when a need arises for increased interaction, collaboration and use of knowledge between stakeholders in the local HEPA network, as they provide an overview of the stakeholders involved and their mutual relations. This information can be an important starting point to enhance the uptake of evidence and build more effective public health policies.

Time and space: undergraduate Mexican physics in motion

NASA Astrophysics Data System (ADS)

Candela, Antonia

2010-09-01

This is an ethnographic study of the trajectories and itineraries of undergraduate physics students at a Mexican university. In this work learning is understood as being able to move oneself and, other things (cultural tools), through the space-time networks of a discipline (Nespor in Knowledge in motion: space, time and curriculum in undergraduate physics and management. Routledge Farmer, London, 1994). The potential of this socio-cultural perspective allows an analysis of how students are connected through extended spaces and times with an international core discipline as well as with cultural features related to local networks of power and construction. Through an example, I show that, from an actor-network-theory (Latour in Science in action. Harvard University Press, Cambridge, 1987), that in order to understand the complexities of undergraduate physics processes of learning you have to break classroom walls and take into account students' movements through complex spatial and temporal traces of the discipline of physics. Mexican professors do not give classes following one textbook but in a moment-to-moment open dynamism tending to include undergraduate students as actors in classroom events extending the teaching space-time of the classroom to the disciplinary research work of physics. I also find that Mexican undergraduate students show initiative and display some autonomy and power in the construction of their itineraries as they are encouraged to examine a variety of sources including contemporary research articles, unsolved physics problems, and even to participate in several physicists' spaces, as for example being speakers at the national congresses of physics. Their itineraries also open up new spaces of cultural and social practices, creating more extensive networks beyond those associated with a discipline. Some economic, historical and cultural contextual features of this school of sciences are analyzed in order to help understanding the particular way students are encouraged to develop their autonomy.

Modeling Psychological Attributes in Psychology – An Epistemological Discussion: Network Analysis vs. Latent Variables

PubMed Central

Guyon, Hervé; Falissard, Bruno; Kop, Jean-Luc

2017-01-01

Network Analysis is considered as a new method that challenges Latent Variable models in inferring psychological attributes. With Network Analysis, psychological attributes are derived from a complex system of components without the need to call on any latent variables. But the ontological status of psychological attributes is not adequately defined with Network Analysis, because a psychological attribute is both a complex system and a property emerging from this complex system. The aim of this article is to reappraise the legitimacy of latent variable models by engaging in an ontological and epistemological discussion on psychological attributes. Psychological attributes relate to the mental equilibrium of individuals embedded in their social interactions, as robust attractors within complex dynamic processes with emergent properties, distinct from physical entities located in precise areas of the brain. Latent variables thus possess legitimacy, because the emergent properties can be conceptualized and analyzed on the sole basis of their manifestations, without exploring the upstream complex system. However, in opposition with the usual Latent Variable models, this article is in favor of the integration of a dynamic system of manifestations. Latent Variables models and Network Analysis thus appear as complementary approaches. New approaches combining Latent Network Models and Network Residuals are certainly a promising new way to infer psychological attributes, placing psychological attributes in an inter-subjective dynamic approach. Pragmatism-realism appears as the epistemological framework required if we are to use latent variables as representations of psychological attributes. PMID:28572780

Atmospheric cloud physics thermal systems analysis

NASA Technical Reports Server (NTRS)

1977-01-01

Engineering analyses performed on the Atmospheric Cloud Physics (ACPL) Science Simulator expansion chamber and associated thermal control/conditioning system are reported. Analyses were made to develop a verified thermal model and to perform parametric thermal investigations to evaluate systems performance characteristics. Thermal network representations of solid components and the complete fluid conditioning system were solved simultaneously using the Systems Improved Numerical Differencing Analyzer (SINDA) computer program.

Proteins Encoded in Genomic Regions Associated with Immune-Mediated Disease Physically Interact and Suggest Underlying Biology

PubMed Central

Rossin, Elizabeth J.; Lage, Kasper; Raychaudhuri, Soumya; Xavier, Ramnik J.; Tatar, Diana; Benita, Yair

2011-01-01

Genome-wide association studies (GWAS) have defined over 150 genomic regions unequivocally containing variation predisposing to immune-mediated disease. Inferring disease biology from these observations, however, hinges on our ability to discover the molecular processes being perturbed by these risk variants. It has previously been observed that different genes harboring causal mutations for the same Mendelian disease often physically interact. We sought to evaluate the degree to which this is true of genes within strongly associated loci in complex disease. Using sets of loci defined in rheumatoid arthritis (RA) and Crohn's disease (CD) GWAS, we build protein–protein interaction (PPI) networks for genes within associated loci and find abundant physical interactions between protein products of associated genes. We apply multiple permutation approaches to show that these networks are more densely connected than chance expectation. To confirm biological relevance, we show that the components of the networks tend to be expressed in similar tissues relevant to the phenotypes in question, suggesting the network indicates common underlying processes perturbed by risk loci. Furthermore, we show that the RA and CD networks have predictive power by demonstrating that proteins in these networks, not encoded in the confirmed list of disease associated loci, are significantly enriched for association to the phenotypes in question in extended GWAS analysis. Finally, we test our method in 3 non-immune traits to assess its applicability to complex traits in general. We find that genes in loci associated to height and lipid levels assemble into significantly connected networks but did not detect excess connectivity among Type 2 Diabetes (T2D) loci beyond chance. Taken together, our results constitute evidence that, for many of the complex diseases studied here, common genetic associations implicate regions encoding proteins that physically interact in a preferential manner, in line with observations in Mendelian disease. PMID:21249183

Integrated situational awareness for cyber attack detection, analysis, and mitigation

NASA Astrophysics Data System (ADS)

Cheng, Yi; Sagduyu, Yalin; Deng, Julia; Li, Jason; Liu, Peng

2012-06-01

Real-time cyberspace situational awareness is critical for securing and protecting today's enterprise networks from various cyber threats. When a security incident occurs, network administrators and security analysts need to know what exactly has happened in the network, why it happened, and what actions or countermeasures should be taken to quickly mitigate the potential impacts. In this paper, we propose an integrated cyberspace situational awareness system for efficient cyber attack detection, analysis and mitigation in large-scale enterprise networks. Essentially, a cyberspace common operational picture will be developed, which is a multi-layer graphical model and can efficiently capture and represent the statuses, relationships, and interdependencies of various entities and elements within and among different levels of a network. Once shared among authorized users, this cyberspace common operational picture can provide an integrated view of the logical, physical, and cyber domains, and a unique visualization of disparate data sets to support decision makers. In addition, advanced analyses, such as Bayesian Network analysis, will be explored to address the information uncertainty, dynamic and complex cyber attack detection, and optimal impact mitigation issues. All the developed technologies will be further integrated into an automatic software toolkit to achieve near real-time cyberspace situational awareness and impact mitigation in large-scale computer networks.

Physical aging in graphite/epoxy composites

NASA Technical Reports Server (NTRS)

Kong, E. S. W.

1983-01-01

Sub-Tg annealing has been found to affect the properties of graphite/epoxy composites. The network epoxy studied was based on the chemistry of tetraglycidyl 4,4'-diamino-diphenyl methane (TGDDM) crosslinked by 4,4'-diamino-diphenyl sulfone (DDS). Differential scanning calorimetry, thermal mechanical analysis, and solid-state cross-polarized magic-angle-spinning nuclear magnetic resonance spectroscopy have been utilized in order to characterize this process of recovery towards thermodynamic equilibrium. The volume and enthalpy recovery as well as the 'thermoreversibility' aspects of the physical aging are discussed. This nonequilibrium and time-dependent behavior of network epoxies are considered in view of the increasingly wide applications of TGDDM-DDS epoxies as matrix materials of structural composites in the aerospace industry.

Workshop on Incomplete Network Data Held at Sandia National Labs – Livermore

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

Soundarajan, Sucheta; Wendt, Jeremy D.

2016-06-01

While network analysis is applied in a broad variety of scientific fields (including physics, computer science, biology, and the social sciences), how networks are constructed and the resulting bias and incompleteness have drawn more limited attention. For example, in biology, gene networks are typically developed via experiment -- many actual interactions are likely yet to be discovered. In addition to this incompleteness, the data-collection processes can introduce significant bias into the observed network datasets. For instance, if you observe part of the World Wide Web network through a classic random walk, then high degree nodes are more likely to bemore » found than if you had selected nodes at random. Unfortunately, such incomplete and biasing data collection methods must be often used.« less

Identification of Modules in Protein-Protein Interaction Networks

NASA Astrophysics Data System (ADS)

Erten, Sinan; Koyutürk, Mehmet

In biological systems, most processes are carried out through orchestration of multiple interacting molecules. These interactions are often abstracted using network models. A key feature of cellular networks is their modularity, which contributes significantly to the robustness, as well as adaptability of biological systems. Therefore, modularization of cellular networks is likely to be useful in obtaining insights into the working principles of cellular systems, as well as building tractable models of cellular organization and dynamics. A common, high-throughput source of data on molecular interactions is in the form of physical interactions between proteins, which are organized into protein-protein interaction (PPI) networks. This chapter provides an overview on identification and analysis of functional modules in PPI networks, which has been an active area of research in the last decade.

Pattern detection in stream networks: Quantifying spatialvariability in fish distribution

USGS Publications Warehouse

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

2004-01-01

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

Self-organized topology of recurrence-based complex networks

NASA Astrophysics Data System (ADS)

Yang, Hui; Liu, Gang

2013-12-01

With the rapid technological advancement, network is almost everywhere in our daily life. Network theory leads to a new way to investigate the dynamics of complex systems. As a result, many methods are proposed to construct a network from nonlinear time series, including the partition of state space, visibility graph, nearest neighbors, and recurrence approaches. However, most previous works focus on deriving the adjacency matrix to represent the complex network and extract new network-theoretic measures. Although the adjacency matrix provides connectivity information of nodes and edges, the network geometry can take variable forms. The research objective of this article is to develop a self-organizing approach to derive the steady geometric structure of a network from the adjacency matrix. We simulate the recurrence network as a physical system by treating the edges as springs and the nodes as electrically charged particles. Then, force-directed algorithms are developed to automatically organize the network geometry by minimizing the system energy. Further, a set of experiments were designed to investigate important factors (i.e., dynamical systems, network construction methods, force-model parameter, nonhomogeneous distribution) affecting this self-organizing process. Interestingly, experimental results show that the self-organized geometry recovers the attractor of a dynamical system that produced the adjacency matrix. This research addresses a question, i.e., "what is the self-organizing geometry of a recurrence network?" and provides a new way to reproduce the attractor or time series from the recurrence plot. As a result, novel network-theoretic measures (e.g., average path length and proximity ratio) can be achieved based on actual node-to-node distances in the self-organized network topology. The paper brings the physical models into the recurrence analysis and discloses the spatial geometry of recurrence networks.

Self-organized topology of recurrence-based complex networks.

PubMed

Yang, Hui; Liu, Gang

2013-12-01

With the rapid technological advancement, network is almost everywhere in our daily life. Network theory leads to a new way to investigate the dynamics of complex systems. As a result, many methods are proposed to construct a network from nonlinear time series, including the partition of state space, visibility graph, nearest neighbors, and recurrence approaches. However, most previous works focus on deriving the adjacency matrix to represent the complex network and extract new network-theoretic measures. Although the adjacency matrix provides connectivity information of nodes and edges, the network geometry can take variable forms. The research objective of this article is to develop a self-organizing approach to derive the steady geometric structure of a network from the adjacency matrix. We simulate the recurrence network as a physical system by treating the edges as springs and the nodes as electrically charged particles. Then, force-directed algorithms are developed to automatically organize the network geometry by minimizing the system energy. Further, a set of experiments were designed to investigate important factors (i.e., dynamical systems, network construction methods, force-model parameter, nonhomogeneous distribution) affecting this self-organizing process. Interestingly, experimental results show that the self-organized geometry recovers the attractor of a dynamical system that produced the adjacency matrix. This research addresses a question, i.e., "what is the self-organizing geometry of a recurrence network?" and provides a new way to reproduce the attractor or time series from the recurrence plot. As a result, novel network-theoretic measures (e.g., average path length and proximity ratio) can be achieved based on actual node-to-node distances in the self-organized network topology. The paper brings the physical models into the recurrence analysis and discloses the spatial geometry of recurrence networks.

Self-organized topology of recurrence-based complex networks

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

Yang, Hui, E-mail: huiyang@usf.edu; Liu, Gang

With the rapid technological advancement, network is almost everywhere in our daily life. Network theory leads to a new way to investigate the dynamics of complex systems. As a result, many methods are proposed to construct a network from nonlinear time series, including the partition of state space, visibility graph, nearest neighbors, and recurrence approaches. However, most previous works focus on deriving the adjacency matrix to represent the complex network and extract new network-theoretic measures. Although the adjacency matrix provides connectivity information of nodes and edges, the network geometry can take variable forms. The research objective of this article ismore » to develop a self-organizing approach to derive the steady geometric structure of a network from the adjacency matrix. We simulate the recurrence network as a physical system by treating the edges as springs and the nodes as electrically charged particles. Then, force-directed algorithms are developed to automatically organize the network geometry by minimizing the system energy. Further, a set of experiments were designed to investigate important factors (i.e., dynamical systems, network construction methods, force-model parameter, nonhomogeneous distribution) affecting this self-organizing process. Interestingly, experimental results show that the self-organized geometry recovers the attractor of a dynamical system that produced the adjacency matrix. This research addresses a question, i.e., “what is the self-organizing geometry of a recurrence network?” and provides a new way to reproduce the attractor or time series from the recurrence plot. As a result, novel network-theoretic measures (e.g., average path length and proximity ratio) can be achieved based on actual node-to-node distances in the self-organized network topology. The paper brings the physical models into the recurrence analysis and discloses the spatial geometry of recurrence networks.« less

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

Dykstra, Dave; Garzoglio, Gabriele; Kim, Hyunwoo

As of 2012, a number of US Department of Energy (DOE) National Laboratories have access to a 100 Gb/s wide-area network backbone. The ESnet Advanced Networking Initiative (ANI) project is intended to develop a prototype network, based on emerging 100 Gb/s Ethernet technology. The ANI network will support DOE's science research programs. A 100 Gb/s network test bed is a key component of the ANI project. The test bed offers the opportunity for early evaluation of 100Gb/s network infrastructure for supporting the high impact data movement typical of science collaborations and experiments. In order to make effective use of thismore » advanced infrastructure, the applications and middleware currently used by the distributed computing systems of large-scale science need to be adapted and tested within the new environment, with gaps in functionality identified and corrected. As a user of the ANI test bed, Fermilab aims to study the issues related to end-to-end integration and use of 100 Gb/s networks for the event simulation and analysis applications of physics experiments. In this paper we discuss our findings from evaluating existing HEP Physics middleware and application components, including GridFTP, Globus Online, etc. in the high-speed environment. These will include possible recommendations to the system administrators, application and middleware developers on changes that would make production use of the 100 Gb/s networks, including data storage, caching and wide area access.« less

Internet end-to-end performance monitoring for the High Energy Nuclear and Particle Physics community

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

Matthews, W.

2000-02-22

Modern High Energy Nuclear and Particle Physics (HENP) experiments at Laboratories around the world present a significant challenge to wide area networks. Petabytes (1015) or exabytes (1018) of data will be generated during the lifetime of the experiment. Much of this data will be distributed via the Internet to the experiment's collaborators at Universities and Institutes throughout the world for analysis. In order to assess the feasibility of the computing goals of these and future experiments, the HENP networking community is actively monitoring performance across a large part of the Internet used by its collaborators. Since 1995, the pingER projectmore » has been collecting data on ping packet loss and round trip times. In January 2000, there are 28 monitoring sites in 15 countries gathering data on over 2,000 end-to-end pairs. HENP labs such as SLAC, Fermi Lab and CERN are using Advanced Network's Surveyor project and monitoring performance from one-way delay of UDP packets. More recently several HENP sites have become involved with NLANR's active measurement program (AMP). In addition SLAC and CERN are part of the RIPE test-traffic project and SLAC is home for a NIMI machine. The large End-to-end performance monitoring infrastructure allows the HENP networking community to chart long term trends and closely examine short term glitches across a wide range of networks and connections. The different methodologies provide opportunities to compare results based on different protocols and statistical samples. Understanding agreement and discrepancies between results provides particular insight into the nature of the network. This paper will highlight the practical side of monitoring by reviewing the special needs of High Energy Nuclear and Particle Physics experiments and provide an overview of the experience of measuring performance across a large number of interconnected networks throughout the world with various methodologies. In particular, results from each project will be compared and disagreement will be analyzed. The goal is to address issues for improving understanding for gathering and analysis of accurate monitoring data, but the outlook for the computing goals of HENP will also be examined.« less

A multilevel layout algorithm for visualizing physical and genetic interaction networks, with emphasis on their modular organization.

PubMed

Tuikkala, Johannes; Vähämaa, Heidi; Salmela, Pekka; Nevalainen, Olli S; Aittokallio, Tero

2012-03-26

Graph drawing is an integral part of many systems biology studies, enabling visual exploration and mining of large-scale biological networks. While a number of layout algorithms are available in popular network analysis platforms, such as Cytoscape, it remains poorly understood how well their solutions reflect the underlying biological processes that give rise to the network connectivity structure. Moreover, visualizations obtained using conventional layout algorithms, such as those based on the force-directed drawing approach, may become uninformative when applied to larger networks with dense or clustered connectivity structure. We implemented a modified layout plug-in, named Multilevel Layout, which applies the conventional layout algorithms within a multilevel optimization framework to better capture the hierarchical modularity of many biological networks. Using a wide variety of real life biological networks, we carried out a systematic evaluation of the method in comparison with other layout algorithms in Cytoscape. The multilevel approach provided both biologically relevant and visually pleasant layout solutions in most network types, hence complementing the layout options available in Cytoscape. In particular, it could improve drawing of large-scale networks of yeast genetic interactions and human physical interactions. In more general terms, the biological evaluation framework developed here enables one to assess the layout solutions from any existing or future graph drawing algorithm as well as to optimize their performance for a given network type or structure. By making use of the multilevel modular organization when visualizing biological networks, together with the biological evaluation of the layout solutions, one can generate convenient visualizations for many network biology applications.

Analysis of linkage effects among industry sectors in China's stock market before and after the financial crisis

NASA Astrophysics Data System (ADS)

Yang, Rui; Li, Xiangyang; Zhang, Tong

2014-10-01

This paper uses two physics-derived techniques, the minimum spanning tree and the hierarchical tree, to investigate the networks formed by CITIC (China International Trust and Investment Corporation) industry indices in three periods from 2006 to 2013. The study demonstrates that obvious industry clustering effects exist in the networks, and Durable Consumer Goods, Industrial Products, Information Technology, Frequently Consumption and Financial Industry are the core nodes in the networks. We also use the rolling window technique to investigate the dynamic evolution of the networks' stability, by calculating the mean correlations and mean distances, as well as the variance of correlations and the distances of these indices. China's stock market is still immature and subject to administrative interventions. Therefore, through this analysis, regulators can focus on monitoring the core nodes to ensure the overall stability of the entire market, while investors can enhance their portfolio allocations or investment decision-making.

Diffusion Tensor Tractography Reveals Disrupted Structural Connectivity during Brain Aging

NASA Astrophysics Data System (ADS)

Lin, Lan; Tian, Miao; Wang, Qi; Wu, Shuicai

2017-10-01

Brain aging is one of the most crucial biological processes that entail many physical, biological, chemical, and psychological changes, and also a major risk factor for most common neurodegenerative diseases. To improve the quality of life for the elderly, it is important to understand how the brain is changed during the normal aging process. We compared diffusion tensor imaging (DTI)-based brain networks in a cohort of 75 healthy old subjects by using graph theory metrics to describe the anatomical networks and connectivity patterns, and network-based statistic (NBS) analysis was used to identify pairs of regions with altered structural connectivity. The NBS analysis revealed a significant network comprising nine distinct fiber bundles linking 10 different brain regions showed altered white matter structures in young-old group compare with middle-aged group (p < .05, family-wise error-corrected). Our results might guide future studies and help to gain a better understanding of brain aging.

General solution of the chemical master equation and modality of marginal distributions for hierarchic first-order reaction networks.

PubMed

Reis, Matthias; Kromer, Justus A; Klipp, Edda

2018-01-20

Multimodality is a phenomenon which complicates the analysis of statistical data based exclusively on mean and variance. Here, we present criteria for multimodality in hierarchic first-order reaction networks, consisting of catalytic and splitting reactions. Those networks are characterized by independent and dependent subnetworks. First, we prove the general solvability of the Chemical Master Equation (CME) for this type of reaction network and thereby extend the class of solvable CME's. Our general solution is analytical in the sense that it allows for a detailed analysis of its statistical properties. Given Poisson/deterministic initial conditions, we then prove the independent species to be Poisson/binomially distributed, while the dependent species exhibit generalized Poisson/Khatri Type B distributions. Generalized Poisson/Khatri Type B distributions are multimodal for an appropriate choice of parameters. We illustrate our criteria for multimodality by several basic models, as well as the well-known two-stage transcription-translation network and Bateman's model from nuclear physics. For both examples, multimodality was previously not reported.

Enzymatically cross-linked tilapia gelatin hydrogels: physical, chemical, and hybrid networks.

PubMed

Bode, Franziska; da Silva, Marcelo Alves; Drake, Alex F; Ross-Murphy, Simon B; Dreiss, Cécile A

2011-10-10

This Article investigates different types of networks formed from tilapia fish gelatin (10% w/w) in the presence and absence of the enzymatic cross-linker microbial transglutaminase. The influence of the temperature protocol and cross-linker concentration (0-55 U mTGase/g gelatin) was examined in physical, chemical, and hybrid gels, where physical gels arise from the formation of triple helices that act as junction points when the gels are cooled below the gelation point. A combination of rheology and optical rotation was used to study the evolution of the storage modulus (G') over time and the number of triple helices formed for each type of gel. We attempted to separate the final storage modulus of the gels into its chemical and physical contributions to examine the existence or otherwise of synergism between the two types of networks. Our experiments show that the gel characteristics vary widely with the thermal protocol. The final storage modulus in chemical gels increased with enzyme concentration, possibly due to the preferential formation of closed loops at low cross-linker amount. In chemical-physical gels, where the physical network (helices) was formed consecutively to the covalent one, we found that below a critical enzyme concentration the more extensive the chemical network is (as measured by G'), the weaker the final gel is. The storage modulus attributed to the physical network decreased exponentially as a function of G' from the chemical network, but both networks were found to be purely additive. Helices were not thermally stabilized. The simultaneous formation of physical and chemical networks (physical-co-chemical) resulted in G' values higher than the individual networks formed under the same conditions. Two regimes were distinguished: at low enzyme concentration (10-20 U mTGase/g gelatin), the networks were formed in series, but the storage modulus from the chemical network was higher in the presence of helices (compared to pure chemical gels); at higher enzyme concentration (30-40 U mTGase/g gelatin), strong synergistic effects were found as a large part of the covalent network became ineffective upon melting of the helices.

OSI in the NASA science internet: An analysis

NASA Technical Reports Server (NTRS)

Nitzan, Rebecca

1990-01-01

The Open Systems Interconnection (OSI) protocol suite is a result of a world-wide effort to develop international standards for networking. OSI is formalized through the International Organization for Standardization (ISO) and the International Electrotechnical Commission (IEC). The goal of OSI is to provide interoperability between network products without relying on one particular vendor, and to do so on a multinational basis. The National Institute for Standards and Technology (NIST) has developed a Government OSI Profile (GOSIP) that specified a subset of the OSI protocols as a Federal Information Processing Standard (FIPS 146). GOSIP compatibility has been adopted as the direction for all U.S. government networks. OSI is extremely diverse, and therefore adherence to a profile will facilitate interoperability within OSI networks. All major computer vendors have indicated current or future support of GOSIP-compliant OSI protocols in their products. The NASA Science Internet (NSI) is an operational network, serving user requirements under NASA's Office of Space Science and Applications. NSI consists of the Space Physics Analysis Network (SPAN) that uses the DECnet protocols and the NASA Science Network (NSN) that uses TCP/IP protocols. The NSI Project Office is currently working on an OSI integration analysis and strategy. A long-term goal is to integrate SPAN and NSN into one unified network service, using a full OSI protocol suite, which will support the OSSA user community.

Physical exercise increases involvement of motor networks as a compensatory mechanism during a cognitively challenging task.

PubMed

Ji, Lanxin; Pearlson, Godfrey D; Zhang, Xue; Steffens, David C; Ji, Xiaoqing; Guo, Hua; Wang, Lihong

2018-05-31

Neuroimaging studies suggest that older adults may compensate for declines in cognitive function through neural compensation and reorganization of neural resources. While neural compensation as a key component of cognitive reserve is an important factor that mediates cognitive decline, the field lacks a quantitative measure of neural compensatory ability, and little is known about factors that may modify compensation, such as physical exercise. Twenty-five healthy older adults participated in a 6-week dance training exercise program. Gait speed, cognitive function, and functional magnetic resonance imaging during a challenging memory task were measured before and after the exercise program. In this study, we used a newly proposed data-driven independent component analysis approach to measure neural compensatory ability and tested the effect of physical exercise on neural compensation through a longitudinal study. After the exercise program, participants showed significantly improved memory performance in Logical Memory Test (WMS(LM)) (P < .001) and Rey Auditory Verbal Learning Test (P = .001) and increased gait speed measured by the 6-minute walking test (P = .01). Among all identified neural networks, only the motor cortices and cerebellum showed greater involvement during the memory task after exercise. Importantly, subjects who activated the motor network only after exercise (but not before exercise) showed WMS(LM) increases. We conclude that physical exercise improved gait speed, cognitive function, and compensatory ability through increased involvement of motor-related networks. Copyright © 2018 John Wiley & Sons, Ltd.

The Interactions of Relationships, Interest, and Self-Efficacy in Undergraduate Physics

NASA Astrophysics Data System (ADS)

Dou, Remy

This collected papers dissertation explores students' academic interactions in an active learning, introductory physics settings as they relate to the development of physics self-efficacy and interest. The motivation for this work extends from the national call to increase participation of students in the pursuit of science, technology, engineering, and mathematics (STEM) careers. Self-efficacy and interest are factors that play prominent roles in popular, evidence-based, career theories, including the Social cognitive career theory (SCCT) and the identity framework. Understanding how these constructs develop in light of the most pervasive characteristic of the active learning introductory physics classroom (i.e., peer-to-peer interactions) has implications on how students learn in a variety of introductory STEM classrooms and settings structured after constructivist and sociocultural learning theories. I collected data related to students' in-class interactions using the tools of social network analysis (SNA). Social network analysis has recently been shown to be an effective and useful way to examine the structure of student relationships that develop in and out of STEM classrooms. This set of studies furthers the implementation of SNA as a tool to examine self-efficacy and interest formation in the active learning physics classroom. Here I represent a variety of statistical applications of SNA, including bootstrapped linear regression (Chapter 2), structural equation modeling (Chapter 3), and hierarchical linear modeling for longitudinal analyses (Chapter 4). Self-efficacy data were collected using the Sources of Self-Efficacy for Science Courses - Physics survey (SOSESC-P), and interest data were collected using the physics identity survey. Data for these studies came from the Modeling Instruction sections of Introductory Physics with Calculus offered at Florida International University in the fall of 2014 and 2015. Analyses support the idea that students' perceptions of one another impact the development of their social network centrality, which in turn affects their self-efficacy building experiences and their overall self-efficacy. It was shown that unlike career theories that emphasize causal relationships between the development of self-efficacy and the subsequent growth of student interest, in this context student interest takes precedence before the development of student self-efficacy. This outcome also has various implications for career theories.

[Influencing factors on HRQOL of physically disabled persons].

PubMed

Kim, Kye-Ha; Kim, Ok-Soo

2005-06-01

The purpose of this study was to investigate the influencing factors on health-related quality of life of physically disabled persons. Data was collected from 96 persons with a physical disability in three cities in Korea from June to September, 2003. Social support and depression were measured by a Social Support Questionnaire 6 (SSQ6) and Center for Epidemiologic Studies Depression questionnaire (CES-D). The Rosenberg Self-esteem Scale was used to measure self-esteem. Health-related quality of life (HRQOL) was measured using Smith Kline Beecham Quality of Life Scale (SBQOL). The SPSS WIN 11.0 version program was used for data analysis. There were significant differences of HRQOL according to monthly income and economic status. All subjects had a high level of depression and low self-esteem. The findings of this study show that self-esteem and the size of the social support network are significant influencing variables on HRQOL in physically disabled persons. Nursing intervention and counseling programs which improve self-esteem and increase the size of a social support network are needed to promote HRQOL in physically disabled persons.

#LancerHealth: Using Twitter and Instagram as a tool in a campus wide health promotion initiative.

PubMed

Santarossa, Sara; Woodruff, Sarah J

2018-02-05

The present study aimed to explore using popular technology that people already have/use as a health promotion tool, in a campus wide social media health promotion initiative, entitled #LancerHealth . During a two-week period the university community was asked to share photos on Twitter and Instagram of What does being healthy on campus look like to you ?, while tagging the image with #LancerHealth . All publically tagged media was collected using the Netlytic software and analysed. Text analysis (N=234 records, Twitter; N=141 records, Instagram) revealed that the majority of the conversation was positive and focused on health and the university. Social network analysis, based on five network properties, showed a small network with little interaction. Lastly, photo coding analysis (N=71 unique image) indicated that the majority of the shared images were of physical activity (52%) and on campus (80%). Further research into this area is warranted.

A Healthy Brain in a Healthy Body: Brain Network Correlates of Physical and Mental Fitness

PubMed Central

Douw, Linda; Nieboer, Dagmar; van Dijk, Bob W.; Stam, Cornelis J.; Twisk, Jos W. R.

2014-01-01

A healthy lifestyle is an important focus in today's society. The physical benefits of regular exercise are abundantly clear, but physical fitness is also associated with better cognitive performance. How these two factors together relate to characteristics of the brain is still incompletely understood. By applying mathematical concepts from ‘network theory’, insights in the organization and dynamics of brain functioning can be obtained. We test the hypothesis that neural network organization mediates the association between cardio respiratory fitness (i.e. VO2 max) and cognitive functioning. A healthy cohort was studied (n = 219, 113 women, age range 41–44 years). Subjects underwent resting-state eyes-closed magneto-encephalography (MEG). Five artifact-free epochs were analyzed and averaged in six frequency bands (delta-gamma). The phase lag index (PLI) was used as a measure of functional connectivity between all sensors. Modularity analysis was performed, and both within and between-module connectivity of each sensor was calculated. Subjects underwent a maximum oxygen uptake (VO2 max) measurement as an indicator of cardio respiratory fitness. All subjects were tested with a commonly used Dutch intelligence test. Intelligence quotient (IQ) was related to VO2 max. In addition, VO2 max was negatively associated with upper alpha and beta band modularity. Particularly increased intermodular connectivity in the beta band was associated with higher VO2 max and IQ, further indicating a benefit of more global network integration as opposed to local connections. Within-module connectivity showed a spatially varied pattern of correlation, while average connectivity did not show significant results. Mediation analysis was not significant. The occurrence of less modularity in the resting-state is associated with better cardio respiratory fitness, while having increased intermodular connectivity, as opposed to within-module connections, is related to better physical and mental fitness. PMID:24498438

Safety models incorporating graph theory based transit indicators.

PubMed

Quintero, Liliana; Sayed, Tarek; Wahba, Mohamed M

2013-01-01

There is a considerable need for tools to enable the evaluation of the safety of transit networks at the planning stage. One interesting approach for the planning of public transportation systems is the study of networks. Network techniques involve the analysis of systems by viewing them as a graph composed of a set of vertices (nodes) and edges (links). Once the transport system is visualized as a graph, various network properties can be evaluated based on the relationships between the network elements. Several indicators can be calculated including connectivity, coverage, directness and complexity, among others. The main objective of this study is to investigate the relationship between network-based transit indicators and safety. The study develops macro-level collision prediction models that explicitly incorporate transit physical and operational elements and transit network indicators as explanatory variables. Several macro-level (zonal) collision prediction models were developed using a generalized linear regression technique, assuming a negative binomial error structure. The models were grouped into four main themes: transit infrastructure, transit network topology, transit route design, and transit performance and operations. The safety models showed that collisions were significantly associated with transit network properties such as: connectivity, coverage, overlapping degree and the Local Index of Transit Availability. As well, the models showed a significant relationship between collisions and some transit physical and operational attributes such as the number of routes, frequency of routes, bus density, length of bus and 3+ priority lanes. Copyright © 2012 Elsevier Ltd. All rights reserved.

Comparison of Neural Network and Linear Regression Models in Statistically Predicting Mental and Physical Health Status of Breast Cancer Survivors

DTIC Science & Technology

2015-07-15

Long-term effects on cancer survivors’ quality of life of physical training versus physical training combined with cognitive-behavioral therapy ...COMPARISON OF NEURAL NETWORK AND LINEAR REGRESSION MODELS IN STATISTICALLY PREDICTING MENTAL AND PHYSICAL HEALTH STATUS OF BREAST...34Comparison of Neural Network and Linear Regression Models in Statistically Predicting Mental and Physical Health Status of Breast Cancer Survivors

Towards Interactive Medical Content Delivery Between Simulated Body Sensor Networks and Practical Data Center.

PubMed

Shi, Xiaobo; Li, Wei; Song, Jeungeun; Hossain, M Shamim; Mizanur Rahman, Sk Md; Alelaiwi, Abdulhameed

2016-10-01

With the development of IoT (Internet of Thing), big data analysis and cloud computing, traditional medical information system integrates with these new technologies. The establishment of cloud-based smart healthcare application gets more and more attention. In this paper, semi-physical simulation technology is applied to cloud-based smart healthcare system. The Body sensor network (BSN) of system transmit has two ways of data collection and transmission. The one is using practical BSN to collect data and transmitting it to the data center. The other is transmitting real medical data to practical data center by simulating BSN. In order to transmit real medical data to practical data center by simulating BSN under semi-physical simulation environment, this paper designs an OPNET packet structure, defines a gateway node model between simulating BSN and practical data center and builds a custom protocol stack. Moreover, this paper conducts a large amount of simulation on the real data transmission through simulation network connecting with practical network. The simulation result can provides a reference for parameter settings of fully practical network and reduces the cost of devices and personnel involved.

Investigating the Associations between Ethnic Networks, Community Social Capital, and Physical Health among Marriage Migrants in Korea.

PubMed

Kim, Harris Hyun-Soo

2018-01-17

This study examines factors associated with the physical health of Korea's growing immigrant population. Specifically, it focuses on the associations between ethnic networks, community social capital, and self-rated health (SRH) among female marriage migrants. For empirical testing, secondary analysis of a large nationally representative sample (NSMF 2009) is conducted. Given the clustered data structure (individuals nested in communities), a series of two-level random intercepts and slopes models are fitted to probe the relationships between SRH and interpersonal (bonding and bridging) networks among foreign-born wives in Korea. In addition to direct effects, cross-level interaction effects are investigated using hierarchical linear modeling. While adjusting for confounders, bridging (inter-ethnic) networks are significantly linked with better health. Bonding (co-ethnic) networks, to the contrary, are negatively associated with immigrant health. Net of individual-level covariates, living in a commuijnity with more aggregate bridging social capital is positively linked with health. Community-level bonding social capital, however, is not a significant predictor. Lastly, two cross-level interaction terms are found. First, the positive relationship between bridging network and health is stronger in residential contexts with more aggregate bridging social capital. Second, it is weaker in communities with more aggregate bonding social capital.

A new method for constructing networks from binary data

NASA Astrophysics Data System (ADS)

van Borkulo, Claudia D.; Borsboom, Denny; Epskamp, Sacha; Blanken, Tessa F.; Boschloo, Lynn; Schoevers, Robert A.; Waldorp, Lourens J.

2014-08-01

Network analysis is entering fields where network structures are unknown, such as psychology and the educational sciences. A crucial step in the application of network models lies in the assessment of network structure. Current methods either have serious drawbacks or are only suitable for Gaussian data. In the present paper, we present a method for assessing network structures from binary data. Although models for binary data are infamous for their computational intractability, we present a computationally efficient model for estimating network structures. The approach, which is based on Ising models as used in physics, combines logistic regression with model selection based on a Goodness-of-Fit measure to identify relevant relationships between variables that define connections in a network. A validation study shows that this method succeeds in revealing the most relevant features of a network for realistic sample sizes. We apply our proposed method to estimate the network of depression and anxiety symptoms from symptom scores of 1108 subjects. Possible extensions of the model are discussed.

Network analysis of Bogotá’s Ciclovía Recreativa, a self-organized multisectoral community program to promote physical activity in a middle-income country

PubMed Central

Meisel, Jose D; Sarmiento, Olga; Montes, Felipe; Martinez, Edwin O.; Lemoine, Pablo D; Valdivia, Juan A; Brownson, RC; Zarama, Robert

2016-01-01

Purpose Conduct a social network analysis of the health and non-health related organizations that participate in the Bogotá’s Ciclovía Recreativa (Ciclovía). Design Cross sectional study. Setting Ciclovía is a multisectoral community-based mass program in which streets are temporarily closed to motorized transport, allowing exclusive access to individuals for leisure activities and PA. Subjects 25 organizations that participate in the Ciclovía. Measures Seven variables were examined using network analytic methods: relationship, link attributes (integration, contact, and importance), and node attributes (leadership, years in the program, and the sector of the organization). Analysis The network analytic methods were based on a visual descriptive analysis and an exponential random graph model. Results Analysis shows that the most central organizations in the network were outside of the health sector and includes Sports and Recreation, Government, and Security sectors. The organizations work in clusters formed by organizations of different sectors. Organization importance and structural predictors were positively related to integration, while the number of years working with Ciclovía was negatively associated with integration. Conclusion Ciclovía is a network whose structure emerged as a self-organized complex system. Ciclovía of Bogotá is an example of a program with public health potential formed by organizations of multiple sectors with Sports and Recreation as the most central. PMID:23971523

A survey of social media data analysis for physical activity surveillance.

PubMed

Liu, Sam; Young, Sean D

2018-07-01

Social media data can provide valuable information regarding people's behaviors and health outcomes. Previous studies have shown that social media data can be extracted to monitor and predict infectious disease outbreaks. These same approaches can be applied to other fields including physical activity research and forensic science. Social media data have the potential to provide real-time monitoring and prediction of physical activity level in a given region. This tool can be valuable to public health organizations as it can overcome the time lag in the reporting of physical activity epidemiology data faced by traditional research methods (e.g. surveys, observational studies). As a result, this tool could help public health organizations better mobilize and target physical activity interventions. The first part of this paper aims to describe current approaches (e.g. topic modeling, sentiment analysis and social network analysis) that could be used to analyze social media data to provide real-time monitoring of physical activity level. The second aim of this paper was to discuss ways to apply social media analysis to other fields such as forensic sciences and provide recommendations to further social media research. Copyright © 2016 Elsevier Ltd and Faculty of Forensic and Legal Medicine. All rights reserved.

Using deep neural networks to augment NIF post-shot analysis

NASA Astrophysics Data System (ADS)

Humbird, Kelli; Peterson, Luc; McClarren, Ryan; Field, John; Gaffney, Jim; Kruse, Michael; Nora, Ryan; Spears, Brian

2017-10-01

Post-shot analysis of National Ignition Facility (NIF) experiments is the process of determining which simulation inputs yield results consistent with experimental observations. This analysis is typically accomplished by running suites of manually adjusted simulations, or Monte Carlo sampling surrogate models that approximate the response surfaces of the physics code. These approaches are expensive and often find simulations that match only a small subset of observables simultaneously. We demonstrate an alternative method for performing post-shot analysis using inverse models, which map directly from experimental observables to simulation inputs with quantified uncertainties. The models are created using a novel machine learning algorithm which automates the construction and initialization of deep neural networks to optimize predictive accuracy. We show how these neural networks, trained on large databases of post-shot simulations, can rigorously quantify the agreement between simulation and experiment. This work performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344.

Structural and functional networks in complex systems with delay.

PubMed

Eguíluz, Víctor M; Pérez, Toni; Borge-Holthoefer, Javier; Arenas, Alex

2011-05-01

Functional networks of complex systems are obtained from the analysis of the temporal activity of their components, and are often used to infer their unknown underlying connectivity. We obtain the equations relating topology and function in a system of diffusively delay-coupled elements in complex networks. We solve exactly the resulting equations in motifs (directed structures of three nodes) and in directed networks. The mean-field solution for directed uncorrelated networks shows that the clusterization of the activity is dominated by the in-degree of the nodes, and that the locking frequency decreases with increasing average degree. We find that the exponent of a power law degree distribution of the structural topology γ is related to the exponent of the associated functional network as α=(2-γ)(-1) for γ<2. © 2011 American Physical Society

Equipment Management for Sensor Networks: Linking Physical Infrastructure and Actions to Observational Data

NASA Astrophysics Data System (ADS)

Jones, A. S.; Horsburgh, J. S.; Matos, M.; Caraballo, J.

2015-12-01

Networks conducting long term monitoring using in situ sensors need the functionality to track physical equipment as well as deployments, calibrations, and other actions related to site and equipment maintenance. The observational data being generated by sensors are enhanced if direct linkages to equipment details and actions can be made. This type of information is typically recorded in field notebooks or in static files, which are rarely linked to observations in a way that could be used to interpret results. However, the record of field activities is often relevant to analysis or post-processing of the observational data. We have developed an underlying database schema and deployed a web interface for recording and retrieving information on physical infrastructure and related actions for observational networks. The database schema for equipment was designed as an extension to the Observations Data Model 2 (ODM2), a community-developed information model for spatially discrete, feature based earth observations. The core entities of ODM2 describe location, observed variable, and timing of observations, and the equipment extension contains entities to provide additional metadata specific to the inventory of physical infrastructure and associated actions. The schema is implemented in a relational database system for storage and management with an associated web interface. We designed the web-based tools for technicians to enter and query information on the physical equipment and actions such as site visits, equipment deployments, maintenance, and calibrations. These tools were implemented for the iUTAH (innovative Urban Transitions and Aridregion Hydrosustainability) ecohydrologic observatory, and we anticipate that they will be useful for similar large-scale monitoring networks desiring to link observing infrastructure to observational data to increase the quality of sensor-based data products.

Uncoordinated MAC for Adaptive Multi-Beam Directional Networks: Analysis and Evaluation

DTIC Science & Technology

2016-04-10

transmission times, hence traditional CSMA approaches are not appropriate. We first present our model of these multi-beamforming capa- bilities and the...resulting wireless interference. We then derive an upper bound on multi-access performance for an idealized version of this physical layer. We then present... transmissions and receptions in a mobile ad-hoc network has in practice led to very constrained topologies. As mentioned, one approach for system design is to de

The Core Symptoms of Bulimia Nervosa, Anxiety, and Depression: A Network Analysis

PubMed Central

Levinson, Cheri A.; Zerwas, Stephanie; Calebs, Benjamin; Forbush, Kelsie; Kordy, Hans; Watson, Hunna; Hofmeier, Sara; Levine, Michele; Crosby, Ross D.; Peat, Christine; Runfola, Cristin D.; Zimmer, Benjamin; Moesner, Markus; Marcus, Marsha D.; Bulik, Cynthia M.

2017-01-01

Bulimia nervosa (BN) is characterized by symptoms of binge eating and compensatory behavior, and overevaluation of weight and shape, which often co-occur with symptoms of anxiety and depression. However, there is little research identifying which specific BN symptoms maintain BN psychopathology and how they are associated with symptoms of depression and anxiety. Network analyses represent an emerging method in psychopathology research to examine how symptoms interact and may become self-reinforcing. In the current study of adults with a DSM-IV diagnosis of BN (N = 196), we used network analysis to identify the central symptoms of BN, as well as symptoms that may bridge the association between BN symptoms and anxiety and depression symptoms. Results showed that fear of weight gain was central to BN psychopathology, whereas binge eating, purging, and restriction were less central in the symptom network. Symptoms related to sensitivity to physical sensations (e.g., changes in appetite, feeling dizzy, wobbly) were identified as bridge symptoms between BN, and anxiety and depressive symptoms. We discuss our findings with respect to cognitive-behavioral treatment approaches for BN. These findings suggest that treatments for BN should focus on fear of weight gain, perhaps through exposure therapies. Further, interventions focusing on exposure to physical sensations may also address BN psychopathology, as well as co-occurring anxiety and depressive symptoms. PMID:28277735

The Impact of the Physical Activity Policy Research Network.

PubMed

Manteiga, Alicia M; Eyler, Amy A; Valko, Cheryl; Brownson, Ross C; Evenson, Kelly R; Schmid, Thomas

2017-03-01

Lack of physical activity is one of the greatest challenges of the 21st century. The Physical Activity Policy Research Network (PAPRN) is a thematic network established in 2004 to identify determinants, implementation, and outcomes of policies that are effective in increasing physical activity. The purpose of this study is to describe the products of PAPRN and make recommendations for future research and best practices. A mixed methods approach was used to obtain both quantitative and qualitative data on the network. First, in 2014, PAPRN's dissemination products from 2004 to 2014 were extracted and reviewed, including 57 publications and 56 presentations. Next, semi-structured qualitative interviews were conducted with 25 key network participants from 17 locations around the U.S. The transcripts were transcribed and coded. The results of the interviews indicated that the research network addressed several components of its mission, including the identification of physical activity policies, determinants of these policies, and the process of policy implementation. However, research focusing on physical activity policy outcomes was limited. Best practices included collaboration between researchers and practitioners and involvement of practitioners in research design, data collection, and dissemination of results. PAPRN is an example of a productive research network and has contributed to both the process and content of physical activity policy research over the past decade. Future research should emphasize physical activity policy outcomes. Additionally, increased partnerships with practitioners for collaborative, cross-sectoral physical activity policy research should be developed. Copyright © 2016 American Journal of Preventive Medicine. All rights reserved.

European health telematics networks for positron emission tomography

NASA Astrophysics Data System (ADS)

Kontaxakis, George; Pozo, Miguel Angel; Ohl, Roland; Visvikis, Dimitris; Sachpazidis, Ilias; Ortega, Fernando; Guerra, Pedro; Cheze-Le Rest, Catherine; Selby, Peter; Pan, Leyun; Diaz, Javier; Dimitrakopoulou-Strauss, Antonia; Santos, Andres; Strauss, Ludwig; Sakas, Georgios

2006-12-01

A pilot network of positron emission tomography centers across Europe has been setup employing telemedicine services. The primary aim is to bring all PET centers in Europe (and beyond) closer, by integrating advanced medical imaging technology and health telematics networks applications into a single, easy to operate health telematics platform, which allows secure transmission of medical data via a variety of telecommunications channels and fosters the cooperation between professionals in the field. The platform runs on PCs with Windows 2000/XP and incorporates advanced techniques for image visualization, analysis and fusion. The communication between two connected workstations is based on a TCP/IP connection secured by secure socket layers and virtual private network or jabber protocols. A teleconsultation can be online (with both physicians physically present) or offline (via transmission of messages which contain image data and other information). An interface sharing protocol enables online teleconsultations even over low bandwidth connections. This initiative promotes the cooperation and improved communication between nuclear medicine professionals, offering options for second opinion and training. It permits physicians to remotely consult patient data, even if they are away from the physical examination site.

Network approach to patterns in stratocumulus clouds

NASA Astrophysics Data System (ADS)

Glassmeier, Franziska; Feingold, Graham

2017-10-01

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

Network approach to patterns in stratocumulus clouds.

PubMed

Glassmeier, Franziska; Feingold, Graham

2017-10-03

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

Enlightening discriminative network functional modules behind Principal Component Analysis separation in differential-omic science studies

PubMed Central

Ciucci, Sara; Ge, Yan; Durán, Claudio; Palladini, Alessandra; Jiménez-Jiménez, Víctor; Martínez-Sánchez, Luisa María; Wang, Yuting; Sales, Susanne; Shevchenko, Andrej; Poser, Steven W.; Herbig, Maik; Otto, Oliver; Androutsellis-Theotokis, Andreas; Guck, Jochen; Gerl, Mathias J.; Cannistraci, Carlo Vittorio

2017-01-01

Omic science is rapidly growing and one of the most employed techniques to explore differential patterns in omic datasets is principal component analysis (PCA). However, a method to enlighten the network of omic features that mostly contribute to the sample separation obtained by PCA is missing. An alternative is to build correlation networks between univariately-selected significant omic features, but this neglects the multivariate unsupervised feature compression responsible for the PCA sample segregation. Biologists and medical researchers often prefer effective methods that offer an immediate interpretation to complicated algorithms that in principle promise an improvement but in practice are difficult to be applied and interpreted. Here we present PC-corr: a simple algorithm that associates to any PCA segregation a discriminative network of features. Such network can be inspected in search of functional modules useful in the definition of combinatorial and multiscale biomarkers from multifaceted omic data in systems and precision biomedicine. We offer proofs of PC-corr efficacy on lipidomic, metagenomic, developmental genomic, population genetic, cancer promoteromic and cancer stem-cell mechanomic data. Finally, PC-corr is a general functional network inference approach that can be easily adopted for big data exploration in computer science and analysis of complex systems in physics. PMID:28287094

Network approach to patterns in stratocumulus clouds

PubMed Central

Feingold, Graham

2017-01-01

Stratocumulus clouds (Sc) have a significant impact on the amount of sunlight reflected back to space, with important implications for Earth’s climate. Representing Sc and their radiative impact is one of the largest challenges for global climate models. Sc fields self-organize into cellular patterns and thus lend themselves to analysis and quantification in terms of natural cellular networks. Based on large-eddy simulations of Sc fields, we present a first analysis of the geometric structure and self-organization of Sc patterns from this network perspective. Our network analysis shows that the Sc pattern is scale-invariant as a consequence of entropy maximization that is known as Lewis’s Law (scaling parameter: 0.16) and is largely independent of the Sc regime (cloud-free vs. cloudy cell centers). Cells are, on average, hexagonal with a neighbor number variance of about 2, and larger cells tend to be surrounded by smaller cells, as described by an Aboav–Weaire parameter of 0.9. The network structure is neither completely random nor characteristic of natural convection. Instead, it emerges from Sc-specific versions of cell division and cell merging that are shaped by cell expansion. This is shown with a heuristic model of network dynamics that incorporates our physical understanding of cloud processes. PMID:28904097

Social networks help to infer causality in the tumor microenvironment.

PubMed

Crespo, Isaac; Doucey, Marie-Agnès; Xenarios, Ioannis

2016-03-15

Networks have become a popular way to conceptualize a system of interacting elements, such as electronic circuits, social communication, metabolism or gene regulation. Network inference, analysis, and modeling techniques have been developed in different areas of science and technology, such as computer science, mathematics, physics, and biology, with an active interdisciplinary exchange of concepts and approaches. However, some concepts seem to belong to a specific field without a clear transferability to other domains. At the same time, it is increasingly recognized that within some biological systems--such as the tumor microenvironment--where different types of resident and infiltrating cells interact to carry out their functions, the complexity of the system demands a theoretical framework, such as statistical inference, graph analysis and dynamical models, in order to asses and study the information derived from high-throughput experimental technologies. In this article we propose to adopt and adapt the concepts of influence and investment from the world of social network analysis to biological problems, and in particular to apply this approach to infer causality in the tumor microenvironment. We showed that constructing a bidirectional network of influence between cell and cell communication molecules allowed us to determine the direction of inferred regulations at the expression level and correctly recapitulate cause-effect relationships described in literature. This work constitutes an example of a transfer of knowledge and concepts from the world of social network analysis to biomedical research, in particular to infer network causality in biological networks. This causality elucidation is essential to model the homeostatic response of biological systems to internal and external factors, such as environmental conditions, pathogens or treatments.

Associations of a social network typology with physical and mental health risks among older adults in South Korea.

PubMed

Park, N S; Jang, Y; Lee, B S; Chiriboga, D A; Chang, S; Kim, S Y

2018-05-01

The objectives of this study were to (1) develop an empirical typology of social networks in older Koreans; and (2) examine its effect on physical and mental health. A sample of 6900 community-dwelling older adults in South Korea was drawn from the 2014 Korean National Elderly Survey. Latent profile analysis (LPA) was conducted to derive social network types using eight common social network characteristics (marital status, living arrangement, the number and frequency of contact with close family/relatives, the number and frequency of contact with close friends, frequency of participation in social activities, and frequency of having visitors at home). The identified typologies were then regressed on self-rated health and depressive symptoms to explore the health risks posed by the group membership. The LPA identified a model with five types of social network as being most optimal (BIC = 153,848.34, entropy = .90). The groups were named diverse/family (enriched networks with more engagement with family), diverse/friend (enriched networks with more engagement with friends), friend-focused (high engagement with friends), distant (structurally disengaged), and restricted (structurally engaged but disengaged in family/friends networks). A series of regression analyses showed that membership in the restricted type was associated with more health and mental health risks than all types of social networks except the distant type. Findings demonstrate the importance of family and friends as a source of social network and call attention to not only structural but also non-structural aspects of social isolation. Findings and implications are discussed in cultural contexts.

A system of networks and continuing education for physical therapists in rheumatology: a feasibility study

PubMed Central

Verhoef, J.; Oosterveld, F.G.J.; Hoekman, R.; Munneke, M.; Boonman, D.C.G.; Bakker, M.; Otten, W.; Rasker, J.J.; de Vries-vander Zwan, H.M.; Vliet Vlieland, T.P.M.

2004-01-01

Abstract Purpose To evaluate the feasibility of regional physical therapy networks including continuing education in rheumatology. The aim of these networks was to improve care provided by primary care physical therapists by improving specific knowledge, technical and communicative skills and the collaboration with rheumatologists. Methods In two regions in The Netherlands continuing education (CE) programmes, consisting of a 5-day postgraduate training course followed by bimonthly workshops and teaching practices, were organised simultaneously. Network activities included consultations, newsletters and the development of a communication guideline. Endpoint measures included the participation rate, compliance, quality of the CE programme, teaching practices, knowledge, network activities, communication, number of patients treated and patient satisfaction. Results Sixty-three physical therapists out of 193 practices (33%) participated in the project. They all completed the education programmes and were formally registered. All evaluations of the education programmes showed positive scores. Knowledge scores increased significantly directly after the training course and at 18 months. A draft guideline on communication between physical therapists and rheumatologists was developed, and 4 newsletters were distributed. A substantial proportion of physical therapists and rheumatologists reported improved communication at 18 months. The mean number of patients treated by physical therapists participating in the networks increased significantly. Patients' satisfaction scores within the networks were significantly higher than those from outside the networks at 18 months. Conclusions Setting up a system of networks for continuing education for physical therapists regarding the treatment of patients with rheumatic diseases is feasible. Further research will focus on the effectiveness of the system and its implementation on a larger scale. PMID:16773150

A multilevel layout algorithm for visualizing physical and genetic interaction networks, with emphasis on their modular organization

PubMed Central

2012-01-01

Background Graph drawing is an integral part of many systems biology studies, enabling visual exploration and mining of large-scale biological networks. While a number of layout algorithms are available in popular network analysis platforms, such as Cytoscape, it remains poorly understood how well their solutions reflect the underlying biological processes that give rise to the network connectivity structure. Moreover, visualizations obtained using conventional layout algorithms, such as those based on the force-directed drawing approach, may become uninformative when applied to larger networks with dense or clustered connectivity structure. Methods We implemented a modified layout plug-in, named Multilevel Layout, which applies the conventional layout algorithms within a multilevel optimization framework to better capture the hierarchical modularity of many biological networks. Using a wide variety of real life biological networks, we carried out a systematic evaluation of the method in comparison with other layout algorithms in Cytoscape. Results The multilevel approach provided both biologically relevant and visually pleasant layout solutions in most network types, hence complementing the layout options available in Cytoscape. In particular, it could improve drawing of large-scale networks of yeast genetic interactions and human physical interactions. In more general terms, the biological evaluation framework developed here enables one to assess the layout solutions from any existing or future graph drawing algorithm as well as to optimize their performance for a given network type or structure. Conclusions By making use of the multilevel modular organization when visualizing biological networks, together with the biological evaluation of the layout solutions, one can generate convenient visualizations for many network biology applications. PMID:22448851

Discriminative Cooperative Networks for Detecting Phase Transitions

NASA Astrophysics Data System (ADS)

Liu, Ye-Hua; van Nieuwenburg, Evert P. L.

2018-04-01

The classification of states of matter and their corresponding phase transitions is a special kind of machine-learning task, where physical data allow for the analysis of new algorithms, which have not been considered in the general computer-science setting so far. Here we introduce an unsupervised machine-learning scheme for detecting phase transitions with a pair of discriminative cooperative networks (DCNs). In this scheme, a guesser network and a learner network cooperate to detect phase transitions from fully unlabeled data. The new scheme is efficient enough for dealing with phase diagrams in two-dimensional parameter spaces, where we can utilize an active contour model—the snake—from computer vision to host the two networks. The snake, with a DCN "brain," moves and learns actively in the parameter space, and locates phase boundaries automatically.

Network access to PCDS (SPAN, ESN, SESNET, ARPANET)

NASA Technical Reports Server (NTRS)

Green, J.

1986-01-01

One of the major goals of the National Space Science Data Center is to increase access to NASA data systems by enhancing networking activities. The activities are centered around three basic networking systems: the Space Physics Analysis Network (SPAN); the Earth Science Network (ESN); and the NASA Packet Switched System (NPSS). Each system is described, linkages among systems are explained, and future plans are announced. The inclusion of several new climate nodes on SPAN or ESN are also mentioned. Presently, the Pilot Climate Data System is accessible through SPAN and will be accessible through NPSS by summer and ESN by the end of 1986. Ambitious plans for implementation are underway. The implementation of these plans will represent a major advance in the utilization and accessibility of data worldwide.

Semianalytic calculation of cosmic microwave background anisotropies from wiggly and superconducting cosmic strings

NASA Astrophysics Data System (ADS)

Rybak, I. Yu.; Avgoustidis, A.; Martins, C. J. A. P.

2017-11-01

We study how the presence of world-sheet currents affects the evolution of cosmic string networks, and their impact on predictions for the cosmic microwave background (CMB) anisotropies generated by these networks. We provide a general description of string networks with currents and explicitly investigate in detail two physically motivated examples: wiggly and superconducting cosmic string networks. By using a modified version of the CMBact code, we show quantitatively how the relevant network parameters in both of these cases influence the predicted CMB signal. Our analysis suggests that previous studies have overestimated the amplitude of the anisotropies for wiggly strings. For superconducting strings the amplitude of the anisotropies depends on parameters which presently are not well known—but which can be measured in future high-resolution numerical simulations.

Influence of fracture network physical properties on stability criteria of density-driven flow in a dual-porosity system

NASA Astrophysics Data System (ADS)

Hassanzadeh, H.; Jafari Raad, S. M.

2017-12-01

Linear stability analysis is conducted to study the onset of buoyancy-driven convection involved in solubility trapping of CO2 into deep fractured aquifers. In this study, the effect of fracture network physical properties on the stability criteria in a brine-rich fractured porous layer is investigated using dual porosity concept for both single and variable matrix block size distributions. Linear stability analysis results show that both fracture interporosity flow and fracture storativity factors play an important role in the stability behavior of the system. It is shown that a diffusive boundary layer under the gravity field in a fractured rock with lower fracture storativity and/or higher fracture interporosity flow coefficient is more stable. We present scaling relations that relate the onset of convective instability in fractured aquifers. These findings improve our understanding of buoyancy driven flow in fractured aquifers and are particularly important in estimation of potential storage capacity, risk assessment, and storage sites characterization and screening.Keywords: CO2 sequestration; fractured rock; buoyancy-driven convection; stability analysis

Computation and Communication Evaluation of an Authentication Mechanism for Time-Triggered Networked Control Systems

PubMed Central

Martins, Goncalo; Moondra, Arul; Dubey, Abhishek; Bhattacharjee, Anirban; Koutsoukos, Xenofon D.

2016-01-01

In modern networked control applications, confidentiality and integrity are important features to address in order to prevent against attacks. Moreover, network control systems are a fundamental part of the communication components of current cyber-physical systems (e.g., automotive communications). Many networked control systems employ Time-Triggered (TT) architectures that provide mechanisms enabling the exchange of precise and synchronous messages. TT systems have computation and communication constraints, and with the aim to enable secure communications in the network, it is important to evaluate the computational and communication overhead of implementing secure communication mechanisms. This paper presents a comprehensive analysis and evaluation of the effects of adding a Hash-based Message Authentication (HMAC) to TT networked control systems. The contributions of the paper include (1) the analysis and experimental validation of the communication overhead, as well as a scalability analysis that utilizes the experimental result for both wired and wireless platforms and (2) an experimental evaluation of the computational overhead of HMAC based on a kernel-level Linux implementation. An automotive application is used as an example, and the results show that it is feasible to implement a secure communication mechanism without interfering with the existing automotive controller execution times. The methods and results of the paper can be used for evaluating the performance impact of security mechanisms and, thus, for the design of secure wired and wireless TT networked control systems. PMID:27463718

Computation and Communication Evaluation of an Authentication Mechanism for Time-Triggered Networked Control Systems.

PubMed

Martins, Goncalo; Moondra, Arul; Dubey, Abhishek; Bhattacharjee, Anirban; Koutsoukos, Xenofon D

2016-07-25

In modern networked control applications, confidentiality and integrity are important features to address in order to prevent against attacks. Moreover, network control systems are a fundamental part of the communication components of current cyber-physical systems (e.g., automotive communications). Many networked control systems employ Time-Triggered (TT) architectures that provide mechanisms enabling the exchange of precise and synchronous messages. TT systems have computation and communication constraints, and with the aim to enable secure communications in the network, it is important to evaluate the computational and communication overhead of implementing secure communication mechanisms. This paper presents a comprehensive analysis and evaluation of the effects of adding a Hash-based Message Authentication (HMAC) to TT networked control systems. The contributions of the paper include (1) the analysis and experimental validation of the communication overhead, as well as a scalability analysis that utilizes the experimental result for both wired and wireless platforms and (2) an experimental evaluation of the computational overhead of HMAC based on a kernel-level Linux implementation. An automotive application is used as an example, and the results show that it is feasible to implement a secure communication mechanism without interfering with the existing automotive controller execution times. The methods and results of the paper can be used for evaluating the performance impact of security mechanisms and, thus, for the design of secure wired and wireless TT networked control systems.

Space physics analysis network node directory (The Yellow Pages): Fourth edition

NASA Technical Reports Server (NTRS)

Peters, David J.; Sisson, Patricia L.; Green, James L.; Thomas, Valerie L.

1989-01-01

The Space Physics Analysis Network (SPAN) is a component of the global DECnet Internet, which has over 17,000 host computers. The growth of SPAN from its implementation in 1981 to its present size of well over 2,500 registered SPAN host computers, has created a need for users to acquire timely information about the network through a central source. The SPAN Network Information Center (SPAN-NIC) an online facility managed by the National Space Science Data Center (NSSDC) was developed to meet this need for SPAN-wide information. The remote node descriptive information in this document is not currently contained in the SPAN-NIC database, but will be incorporated in the near future. Access to this information is also available to non-DECnet users over a variety of networks such as Telenet, the NASA Packet Switched System (NPSS), and the TCP/IP Internet. This publication serves as the Yellow Pages for SPAN node information. The document also provides key information concerning other computer networks connected to SPAN, nodes associated with each SPAN routing center, science discipline nodes, contacts for primary SPAN nodes, and SPAN reference information. A section on DECnet Internetworking discusses SPAN connections with other wide-area DECnet networks (many with thousands of nodes each). Another section lists node names and their disciplines, countries, and institutions in the SPAN Network Information Center Online Data Base System. All remote sites connected to US-SPAN and European-SPAN (E-SPAN) are indexed. Also provided is information on the SPAN tail circuits, i.e., those remote nodes connected directly to a SPAN routing center, which is the local point of contact for resolving SPAN-related problems. Reference material is included for those who wish to know more about SPAN. Because of the rapid growth of SPAN, the SPAN Yellow Pages is reissued periodically.

Dynamics of subway networks based on vehicles operation timetable

NASA Astrophysics Data System (ADS)

Xiao, Xue-mei; Jia, Li-min; Wang, Yan-hui

2017-05-01

In this paper, a subway network is represented as a dynamic, directed and weighted graph, in which vertices represent subway stations and weights of edges represent the number of vehicles passing through the edges by considering vehicles operation timetable. Meanwhile the definitions of static and dynamic metrics which can represent vertices' and edges' local and global attributes are proposed. Based on the model and metrics, standard deviation is further introduced to study the dynamic properties (heterogeneity and vulnerability) of subway networks. Through a detailed analysis of the Beijing subway network, we conclude that with the existing network structure, the heterogeneity and vulnerability of the Beijing subway network varies over time when the vehicle operation timetable is taken into consideration, and the distribution of edge weights affects the performance of the network. In other words, although the vehicles operation timetable is restrained by the physical structure of the network, it determines the performances and properties of the Beijing subway network.

Network inference reveals novel connections in pathways regulating growth and defense in the yeast salt response.

PubMed

MacGilvray, Matthew E; Shishkova, Evgenia; Chasman, Deborah; Place, Michael; Gitter, Anthony; Coon, Joshua J; Gasch, Audrey P

2018-05-01

Cells respond to stressful conditions by coordinating a complex, multi-faceted response that spans many levels of physiology. Much of the response is coordinated by changes in protein phosphorylation. Although the regulators of transcriptome changes during stress are well characterized in Saccharomyces cerevisiae, the upstream regulatory network controlling protein phosphorylation is less well dissected. Here, we developed a computational approach to infer the signaling network that regulates phosphorylation changes in response to salt stress. We developed an approach to link predicted regulators to groups of likely co-regulated phospho-peptides responding to stress, thereby creating new edges in a background protein interaction network. We then use integer linear programming (ILP) to integrate wild type and mutant phospho-proteomic data and predict the network controlling stress-activated phospho-proteomic changes. The network we inferred predicted new regulatory connections between stress-activated and growth-regulating pathways and suggested mechanisms coordinating metabolism, cell-cycle progression, and growth during stress. We confirmed several network predictions with co-immunoprecipitations coupled with mass-spectrometry protein identification and mutant phospho-proteomic analysis. Results show that the cAMP-phosphodiesterase Pde2 physically interacts with many stress-regulated transcription factors targeted by PKA, and that reduced phosphorylation of those factors during stress requires the Rck2 kinase that we show physically interacts with Pde2. Together, our work shows how a high-quality computational network model can facilitate discovery of new pathway interactions during osmotic stress.

Hippocampal microRNA-mRNA regulatory network is affected by physical exercise.

PubMed

Fernandes, Jansen; Vieira, Andre Schwambach; Kramer-Soares, Juliana Carlota; Da Silva, Eduardo Alves; Lee, Kil Sun; Lopes-Cendes, Iscia; Arida, Ricardo Mario

2018-05-08

It is widely known that physical activity positively affects the overall health and brain function. Recently, microRNAs (miRNAs) have emerged as potential regulators of numerous biological processes within the brain. These molecules modulate gene expression post-transcriptionally by inducing mRNA degradation and inhibiting the translation of target mRNAs. To verify whether the procognitive effects of physical exercise are accompanied by changes in the activity of miRNA-mRNA network in the brain, differential expression analysis was performed in the hippocampus of control (CTL) and exercised (Ex) rats subjected to 4 weeks of treadmill exercise. Cognition was evaluated by a multiple trial inhibitory avoidance (MTIA) task and Illumina next-generation sequencing (NGS) was used for miRNA and mRNA profiling. Exercise improved memory retention but not acquisition in the MTIA task. It was observed that 4 miRNAs and 54 mRNAs were significantly altered in the hippocampus of Ex2 (euthanized 2 h after the last exercise bout) group when compared to CTL group. Bioinformatic analysis showed an inverse correlation between 3 miRNAs and 6 target mRNAs. The miRNAs miR-129-1-3p and miR-144-5p were inversely correlated to the Igfbp5 and Itm2a, respectively, and the miR-708-5p presented an inverse correlation with Cdkn1a, Per2, Rt1-a2. The exercise-induced memory improvements are accompanied by changes in hippocampal miRNA-mRNA regulatory network. Physical exercise can affect brain function through modulation of epigenetics mechanisms involving miRNA regulation. Copyright © 2018 Elsevier B.V. All rights reserved.

Optical transmission testing based on asynchronous sampling techniques: images analysis containing chromatic dispersion using convolutional neural network

NASA Astrophysics Data System (ADS)

Mrozek, T.; Perlicki, K.; Tajmajer, T.; Wasilewski, P.

2017-08-01

The article presents an image analysis method, obtained from an asynchronous delay tap sampling (ADTS) technique, which is used for simultaneous monitoring of various impairments occurring in the physical layer of the optical network. The ADTS method enables the visualization of the optical signal in the form of characteristics (so called phase portraits) that change their shape under the influence of impairments such as chromatic dispersion, polarization mode dispersion and ASE noise. Using this method, a simulation model was built with OptSim 4.0. After the simulation study, data were obtained in the form of images that were further analyzed using the convolutional neural network algorithm. The main goal of the study was to train a convolutional neural network to recognize the selected impairment (distortion); then to test its accuracy and estimate the impairment for the selected set of test images. The input data consisted of processed binary images in the form of two-dimensional matrices, with the position of the pixel. This article focuses only on the analysis of images containing chromatic dispersion.

Protein complexes, big data, machine learning and integrative proteomics: lessons learned over a decade of systematic analysis of protein interaction networks.

PubMed

Havugimana, Pierre C; Hu, Pingzhao; Emili, Andrew

2017-10-01

Elucidation of the networks of physical (functional) interactions present in cells and tissues is fundamental for understanding the molecular organization of biological systems, the mechanistic basis of essential and disease-related processes, and for functional annotation of previously uncharacterized proteins (via guilt-by-association or -correlation). After a decade in the field, we felt it timely to document our own experiences in the systematic analysis of protein interaction networks. Areas covered: Researchers worldwide have contributed innovative experimental and computational approaches that have driven the rapidly evolving field of 'functional proteomics'. These include mass spectrometry-based methods to characterize macromolecular complexes on a global-scale and sophisticated data analysis tools - most notably machine learning - that allow for the generation of high-quality protein association maps. Expert commentary: Here, we recount some key lessons learned, with an emphasis on successful workflows, and challenges, arising from our own and other groups' ongoing efforts to generate, interpret and report proteome-scale interaction networks in increasingly diverse biological contexts.

Macro-Econophysics

NASA Astrophysics Data System (ADS)

Aoyama, Hideaki; Fujiwara, Yoshi; Ikeda, Yuichi; Iyetomi, Hiroshi; Souma, Wataru; Yoshikawa, Hiroshi

2017-07-01

Preface; Foreword, Acknowledgements, List of tables; List of figures, prologue, 1. Introduction: reconstructing macroeconomics; 2. Basic concepts in statistical physics and stochastic models; 3. Income and firm-size distributions; 4. Productivity distribution and related topics; 5. Multivariate time-series analysis; 6. Business cycles; 7. Price dynamics and inflation/deflation; 8. Complex network, community analysis, visualization; 9. Systemic risks; Appendix A: computer program for beginners; Epilogue; Bibliography; Index.

Fitness, but not physical activity, is related to functional integrity of brain networks associated with aging.

PubMed

Voss, Michelle W; Weng, Timothy B; Burzynska, Agnieszka Z; Wong, Chelsea N; Cooke, Gillian E; Clark, Rachel; Fanning, Jason; Awick, Elizabeth; Gothe, Neha P; Olson, Erin A; McAuley, Edward; Kramer, Arthur F

2016-05-01

Greater physical activity and cardiorespiratory fitness are associated with reduced age-related cognitive decline and lower risk for dementia. However, significant gaps remain in the understanding of how physical activity and fitness protect the brain from adverse effects of brain aging. The primary goal of the current study was to empirically evaluate the independent relationships between physical activity and fitness with functional brain health among healthy older adults, as measured by the functional connectivity of cognitively and clinically relevant resting state networks. To build context for fitness and physical activity associations in older adults, we first demonstrate that young adults have greater within-network functional connectivity across a broad range of cortical association networks. Based on these results and previous research, we predicted that individual differences in fitness and physical activity would be most strongly associated with functional integrity of the networks most sensitive to aging. Consistent with this prediction, and extending on previous research, we showed that cardiorespiratory fitness has a positive relationship with functional connectivity of several cortical networks associated with age-related decline, and effects were strongest in the default mode network (DMN). Furthermore, our results suggest that the positive association of fitness with brain function can occur independent of habitual physical activity. Overall, our findings provide further support that cardiorespiratory fitness is an important factor in moderating the adverse effects of aging on cognitively and clinically relevant functional brain networks. Copyright © 2015 Elsevier Inc. All rights reserved.

Fitness, but not physical activity, is related to functional integrity of brain networks associated with aging

PubMed Central

Voss, Michelle W.; Weng, Timothy B.; Burzynska, Agnieszka Z.; Wong, Chelsea N.; Cooke, Gillian E.; Clark, Rachel; Fanning, Jason; Awick, Elizabeth; Gothe, Neha P.; Olson, Erin A.; McAuley, Edward; Kramer, Arthur F.

2015-01-01

Greater physical activity and cardiorespiratory fitness are associated with reduced age-related cognitive decline and lower risk for dementia. However, significant gaps remain in the understanding of how physical activity and fitness protect the brain from adverse effects of brain aging. The primary goal of the current study was to empirically evaluate the independent relationships between physical activity and fitness with functional brain health among healthy older adults, as measured by the functional connectivity of cognitively and clinically relevant resting state networks. To build context for fitness and physical activity associations in older adults, we first demonstrate that young adults have greater within-network functional connectivity across a broad range of cortical association networks. Based on these results and previous research, we predicted that individual differences in fitness and physical activity would be most strongly associated with functional integrity of the networks most sensitive to aging. Consistent with this prediction, and extending on previous research, we showed that cardiorespiratory fitness has a positive relationship with functional connectivity of several cortical networks associated with age-related decline, and effects were strongest in the Default Mode Network (DMN). Furthermore, our results suggest that the positive association of fitness with brain function can occur independent of habitual physical activity. Overall, our findings provide further support that cardiorespiratory fitness is an important factor in moderating the adverse effects of aging on cognitively and clinically relevant functional brain networks. PMID:26493108

Physical activity discrimination improvement using accelerometers and wireless sensor network localization - biomed 2013.

PubMed

Bashford, Gregory R; Burnfield, Judith M; Perez, Lance C

2013-01-01

Automating documentation of physical activity data (e.g., duration and speed of walking or propelling a wheelchair) into the electronic medical record (EMR) offers promise for improving efficiency of documentation and understanding of best practices in the rehabilitation and home health settings. Commercially available devices which could be used to automate documentation of physical activities are either cumbersome to wear or lack the specificity required to differentiate activities. We have designed a novel system to differentiate and quantify physical activities, using inexpensive accelerometer-based biomechanical data technology and wireless sensor networks, a technology combination that has not been used in a rehabilitation setting to date. As a first step, a feasibility study was performed where 14 healthy young adults (mean age = 22.6 ± 2.5 years, mean height = 173 ± 10.0 cm, mean mass = 70.7 ± 11.3 kg) carried out eight different activities while wearing a biaxial accelerometer sensor. Activities were performed at each participant’s self-selected pace during a single testing session in a controlled environment. Linear discriminant analysis was performed by extracting spectral parameters from the subjects’ accelerometer patterns. It is shown that physical activity classification alone results in an average accuracy of 49.5%, but when combined with rule-based constraints using a wireless sensor network with localization capabilities in an in silico simulated room, accuracy improves to 99.3%. When fully implemented, our technology package is expected to improve goal setting, treatment interventions and patient outcomes by enhancing clinicians’ understanding of patients’ physical performance within a day and across the rehabilitation program.

Students' network integration as a predictor of persistence in introductory physics courses

NASA Astrophysics Data System (ADS)

Zwolak, Justyna P.; Dou, Remy; Williams, Eric A.; Brewe, Eric

2017-06-01

Increasing student retention (successfully finishing a particular course) and persistence (continuing through a sequence of courses or the major area of study) is currently a major challenge for universities. While students' academic and social integration into an institution seems to be vital for student retention, research into the effect of interpersonal interactions is rare. We use network analysis as an approach to investigate academic and social experiences of students in the classroom. In particular, centrality measures identify patterns of interaction that contribute to integration into the university. Using these measures, we analyze how position within a social network in a Modeling Instruction (MI) course—an introductory physics course that strongly emphasizes interactive learning—predicts their persistence in taking a subsequent physics course. Students with higher centrality at the end of the first semester of MI are more likely to enroll in a second semester of MI. Moreover, we found that chances of successfully predicting individual student's persistence based on centrality measures are fairly high—up to 75%, making the centrality a good predictor of persistence. These findings suggest that increasing student social integration may help in improving persistence in science, technology, engineering, and mathematics fields.

Effects in the network topology due to node aggregation: Empirical evidence from the domestic maritime transportation in Greece

NASA Astrophysics Data System (ADS)

Tsiotas, Dimitrios; Polyzos, Serafeim

2018-02-01

This article studies the topological consistency of spatial networks due to node aggregation, examining the changes captured between different network representations that result from nodes' grouping and they refer to the same socioeconomic system. The main purpose of this study is to evaluate what kind of topological information remains unalterable due to node aggregation and, further, to develop a framework for linking the data of an empirical network with data of its socioeconomic environment, when the latter are available for hierarchically higher levels of aggregation, in an effort to promote the interdisciplinary research in the field of complex network analysis. The research question is empirically tested on topological and socioeconomic data extracted from the Greek Maritime Network (GMN) that is modeled as a non-directed multilayer (bilayer) graph consisting of a port-layer, where nodes represent ports, and a prefecture-layer, where nodes represent coastal and insular prefectural groups of ports. The analysis highlights that the connectivity (degree) of the GMN is the most consistent aspect of this multilayer network, which preserves both the topological and the socioeconomic information through node aggregation. In terms of spatial analysis and regional science, such effects illustrate the effectiveness of the prefectural administrative division for the functionality of the Greek maritime transportation system. Overall, this approach proposes a methodological framework that can enjoy further applications about the grouping effects induced on the network topology, providing physical, technical, socioeconomic, strategic or political insights.

The application of complex network time series analysis in turbulent heated jets

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

Charakopoulos, A. K.; Karakasidis, T. E., E-mail: thkarak@uth.gr; Liakopoulos, A.

In the present study, we applied the methodology of the complex network-based time series analysis to experimental temperature time series from a vertical turbulent heated jet. More specifically, we approach the hydrodynamic problem of discriminating time series corresponding to various regions relative to the jet axis, i.e., time series corresponding to regions that are close to the jet axis from time series originating at regions with a different dynamical regime based on the constructed network properties. Applying the transformation phase space method (k nearest neighbors) and also the visibility algorithm, we transformed time series into networks and evaluated the topologicalmore » properties of the networks such as degree distribution, average path length, diameter, modularity, and clustering coefficient. The results show that the complex network approach allows distinguishing, identifying, and exploring in detail various dynamical regions of the jet flow, and associate it to the corresponding physical behavior. In addition, in order to reject the hypothesis that the studied networks originate from a stochastic process, we generated random network and we compared their statistical properties with that originating from the experimental data. As far as the efficiency of the two methods for network construction is concerned, we conclude that both methodologies lead to network properties that present almost the same qualitative behavior and allow us to reveal the underlying system dynamics.« less

The application of complex network time series analysis in turbulent heated jets

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

Charakopoulos, A. K.; Karakasidis, T. E., E-mail: thkarak@uth.gr; Liakopoulos, A.

2014-06-15

In the present study, we applied the methodology of the complex network-based time series analysis to experimental temperature time series from a vertical turbulent heated jet. More specifically, we approach the hydrodynamic problem of discriminating time series corresponding to various regions relative to the jet axis, i.e., time series corresponding to regions that are close to the jet axis from time series originating at regions with a different dynamical regime based on the constructed network properties. Applying the transformation phase space method (k nearest neighbors) and also the visibility algorithm, we transformed time series into networks and evaluated the topologicalmore » properties of the networks such as degree distribution, average path length, diameter, modularity, and clustering coefficient. The results show that the complex network approach allows distinguishing, identifying, and exploring in detail various dynamical regions of the jet flow, and associate it to the corresponding physical behavior. In addition, in order to reject the hypothesis that the studied networks originate from a stochastic process, we generated random network and we compared their statistical properties with that originating from the experimental data. As far as the efficiency of the two methods for network construction is concerned, we conclude that both methodologies lead to network properties that present almost the same qualitative behavior and allow us to reveal the underlying system dynamics.« less

Application of Artificial Neural Network to Predict Colour Change, Shrinkage and Texture of Osmotically Dehydrated Pumpkin

NASA Astrophysics Data System (ADS)

Tang, S. Y.; Lee, J. S.; Loh, S. P.; Tham, H. J.

2017-06-01

The objectives of this study were to use Artificial Neural Network (ANN) to predict colour change, shrinkage and texture of osmotically dehydrated pumpkin slices. The effects of process variables such as concentration of osmotic solution, immersion temperature and immersion time on the above mentioned physical properties were studied. The colour of the samples was measured using a colorimeter and the net colour difference changes, ΔE were determined. The texture was measured in terms of hardness by using a Texture Analyzer. As for the shrinkage, displacement of volume method was applied and percentage of shrinkage was obtained in terms of volume changes. A feed-forward backpropagation network with sigmoidal function was developed and best network configuration was chosen based on the highest correlation coefficients between the experimental values versus predicted values. As a comparison, Response Surface Methodology (RSM) statistical analysis was also employed. The performances of both RSM and ANN modelling were evaluated based on absolute average deviation (AAD), correlation of determination (R2) and root mean square error (RMSE). The results showed that ANN has higher prediction capability as compared to RSM. The relative importance of the variables on the physical properties were also determined by using connection weight approach in ANN. It was found that solution concentration showed the highest influence on all three physical properties.

Beyond performance metrics: Examining a decrease in students' physics self-efficacy through a social networks lens

NASA Astrophysics Data System (ADS)

Dou, Remy; Brewe, Eric; Zwolak, Justyna P.; Potvin, Geoff; Williams, Eric A.; Kramer, Laird H.

2016-12-01

The Modeling Instruction (MI) approach to introductory physics manifests significant increases in student conceptual understanding and attitudes toward physics. In light of these findings, we investigated changes in student self-efficacy while considering the construct's contribution to the career-decision making process. Students in the Fall 2014 and 2015 MI courses at Florida International University exhibited a decrease on each of the sources of self-efficacy and overall self-efficacy (N =147 ) as measured by the Sources of Self-Efficacy in Science Courses-Physics (SOSESC-P) survey. This held true regardless of student gender or ethnic group. Given the highly interactive nature of the MI course and the drops observed on the SOSESC-P, we chose to further explore students' changes in self-efficacy as a function of three centrality measures (i.e., relational positions in the classroom social network): inDegree, outDegree, and PageRank. We collected social network data by periodically asking students to list the names of peers with whom they had meaningful interactions. While controlling for PRE scores on the SOSESC-P, bootstrapped linear regressions revealed post-self-efficacy scores to be predicted by PageRank centrality. When disaggregated by the sources of self-efficacy, PageRank centrality was shown to be directly related to students' sense of mastery experiences. InDegree was associated with verbal persuasion experiences, and outDegree with both verbal persuasion and vicarious learning experiences. We posit that analysis of social networks in active learning classrooms helps to reveal nuances in self-efficacy development.

Mapping the historical development of physical activity and health research: A structured literature review and citation network analysis.

PubMed

Varela, Andrea Ramirez; Pratt, Michael; Harris, Jenine; Lecy, Jesse; Salvo, Deborah; Brownson, Ross C; Hallal, Pedro C

2018-06-01

Little has been published about the historical development of scientific evidence in the physical activity (PA) and public health research field. The study aimed to examine the evolution of knowledge in this field. A structured literature review using formal citation network analysis methods was conducted in June-2016. Using a list of influential PA publications identified by domain experts, a snowball sampling technique was used to build a compact citation network of 141 publications that represents the backbone of the field. Articles were coded by study type and research team characteristics, then analyzed by visualizing the citation network and identifying research clusters to trace the evolution of the field. The field started in the 1950s, with a health sciences focus and strong North American and European leadership. Health outcome studies appeared most frequently in the network and policy and interventions least. Critical articles on objective measurement and public policy have influenced the progress from an emphasis on health outcomes research at early stages in the field to the more recent emerging built environment and global monitoring foci. There is only modest cross-citation across types of study. To our knowledge, this paper is the first to systematically describe the development of research on PA and public health. The key publications include fundamental ideas that remain citable over time, but notable research and dissemination gaps exist and should be addressed. Increasing collaboration and communication between study areas, encouraging female researchers, and increasing studies on interventions, evaluation of interventions and policy are recommended. Copyright © 2017 Elsevier Inc. All rights reserved.

MO-DE-BRA-05: Developing Effective Medical Physics Knowledge Structures: Models and Methods

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

Sprawls, P

Purpose: Develop a method and supporting online resources to be used by medical physics educators for teaching medical imaging professionals and trainees so they develop highly-effective physics knowledge structures that can contribute to improved diagnostic image quality on a global basis. Methods: The different types of mental knowledge structures were analyzed and modeled with respect to both the learning and teaching process for their development and the functions or tasks that can be performed with the knowledge. While symbolic verbal and mathematical knowledge structures are very important in medical physics for many purposes, the tasks of applying physics in clinicalmore » imaging--especially to optimize image quality and diagnostic accuracy--requires a sensory conceptual knowledge structure, specifically, an interconnected network of visually based concepts. This type of knowledge supports tasks such as analysis, evaluation, problem solving, interacting, and creating solutions. Traditional educational methods including lectures, online modules, and many texts are serial procedures and limited with respect to developing interconnected conceptual networks. A method consisting of the synergistic combination of on-site medical physics teachers and the online resource, CONET (Concept network developer), has been developed and made available for the topic Radiographic Image Quality. This was selected as the inaugural topic, others to follow, because it can be used by medical physicists teaching the large population of medical imaging professionals, such as radiology residents, who can apply the knowledge. Results: Tutorials for medical physics educators on developing effective knowledge structures are being presented and published and CONET is available with open access for all to use. Conclusion: An adjunct to traditional medical physics educational methods with the added focus on sensory concept development provides opportunities for medical physics teachers to share their knowledge and experience at a higher cognitive level and produce medical professionals with the enhanced ability to apply physics to clinical procedures.« less

Friendship networks and physical activity and sedentary behavior among youth: a systematized review.

PubMed

Sawka, Keri Jo; McCormack, Gavin R; Nettel-Aguirre, Alberto; Hawe, Penelope; Doyle-Baker, Patricia K

2013-12-01

Low levels of physical activity and increased participation in sedentary leisure-time activities are two important obesity-risk behaviors that impact the health of today's youth. Friend's health behaviors have been shown to influence individual health behaviors; however, current evidence on the specific role of friendship networks in relation to levels of physical activity and sedentary behavior is limited. The purpose of this review was to summarize evidence on friendship networks and both physical activity and sedentary behavior among children and adolescents. After a search of seven scientific databases and reference scans, a total of thirteen articles were eligible for inclusion. All assessed the association between friendship networks and physical activity, while three also assessed sedentary behavior. Overall, higher levels of physical activity among friends are associated with higher levels of physical activity of the individual. Longitudinal studies reveal that an individual's level of physical activity changes to reflect his/her friends' higher level of physical activity. Boys tend to be influenced by their friendship network to a greater extent than girls. There is mixed evidence surrounding a friend's sedentary behavior and individual sedentary behavior. Friends' physical activity level appears to have a significant influence on individual's physical activity level. Evidence surrounding sedentary behavior is limited and mixed. Results from this review could inform effective public health interventions that harness the influence of friends to increase physical activity levels among children and adolescents.

Physical security and IT convergence: Managing the cyber-related risks.

PubMed

McCreight, Tim; Leece, Doug

The convergence of physical security devices into the corporate network is increasing, due to the perceived economic benefits and efficiencies gained from using one enterprise network. Bringing these two networks together is not without risk. Physical devices like closed circuit television cameras (CCTV), card access readers, and heating, ventilation and air conditioning controllers (HVAC) are typically not secured to the standards we expect for corporate computer networks. These devices can pose significant risks to the corporate network by creating new avenues to exploit vulnerabilities in less-than-secure implementations of physical systems. The ASIS Information Technology Security Council (ITSC) developed a white paper describing steps organisations can take to reduce the risks this convergence can pose, and presented these concepts at the 2015 ASIS/ISC2 Congress in Anaheim, California. 1 This paper expands upon the six characteristics described by ITSC, and provides business continuity planners with information on how to apply these recommendations to physical security devices that use the corporate network.

AccessMod 3.0: computing geographic coverage and accessibility to health care services using anisotropic movement of patients

PubMed Central

Ray, Nicolas; Ebener, Steeve

2008-01-01

Background Access to health care can be described along four dimensions: geographic accessibility, availability, financial accessibility and acceptability. Geographic accessibility measures how physically accessible resources are for the population, while availability reflects what resources are available and in what amount. Combining these two types of measure into a single index provides a measure of geographic (or spatial) coverage, which is an important measure for assessing the degree of accessibility of a health care network. Results This paper describes the latest version of AccessMod, an extension to the Geographical Information System ArcView 3.×, and provides an example of application of this tool. AccessMod 3 allows one to compute geographic coverage to health care using terrain information and population distribution. Four major types of analysis are available in AccessMod: (1) modeling the coverage of catchment areas linked to an existing health facility network based on travel time, to provide a measure of physical accessibility to health care; (2) modeling geographic coverage according to the availability of services; (3) projecting the coverage of a scaling-up of an existing network; (4) providing information for cost effectiveness analysis when little information about the existing network is available. In addition to integrating travelling time, population distribution and the population coverage capacity specific to each health facility in the network, AccessMod can incorporate the influence of landscape components (e.g. topography, river and road networks, vegetation) that impact travelling time to and from facilities. Topographical constraints can be taken into account through an anisotropic analysis that considers the direction of movement. We provide an example of the application of AccessMod in the southern part of Malawi that shows the influences of the landscape constraints and of the modes of transportation on geographic coverage. Conclusion By incorporating the demand (population) and the supply (capacities of heath care centers), AccessMod provides a unifying tool to efficiently assess the geographic coverage of a network of health care facilities. This tool should be of particular interest to developing countries that have a relatively good geographic information on population distribution, terrain, and health facility locations. PMID:19087277

Nuclear Physics Science Network Requirements Workshop, May 2008 - Final Report

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

Tierney, Ed., Brian L; Dart, Ed., Eli; Carlson, Rich

2008-11-10

The Energy Sciences Network (ESnet) is the primary provider of network connectivity for the US Department of Energy Office of Science, the single largest supporter of basic research in the physical sciences in the United States of America. In support of the Office of Science programs, ESnet regularly updates and refreshes its understanding of the networking requirements of the instruments, facilities, scientists, and science programs that it serves. This focus has helped ESnet to be a highly successful enabler of scientific discovery for over 20 years. In May 2008, ESnet and the Nuclear Physics (NP) Program Office of the DOEmore » Office of Science organized a workshop to characterize the networking requirements of the science programs funded by the NP Program Office. Most of the key DOE sites for NP related work will require significant increases in network bandwidth in the 5 year time frame. This includes roughly 40 Gbps for BNL, and 20 Gbps for NERSC. Total transatlantic requirements are on the order of 40 Gbps, and transpacific requirements are on the order of 30 Gbps. Other key sites are Vanderbilt University and MIT, which will need on the order of 20 Gbps bandwidth to support data transfers for the CMS Heavy Ion program. In addition to bandwidth requirements, the workshop emphasized several points in regard to science process and collaboration. One key point is the heavy reliance on Grid tools and infrastructure (both PKI and tools such as GridFTP) by the NP community. The reliance on Grid software is expected to increase in the future. Therefore, continued development and support of Grid software is very important to the NP science community. Another key finding is that scientific productivity is greatly enhanced by easy researcher-local access to instrument data. This is driving the creation of distributed repositories for instrument data at collaborating institutions, along with a corresponding increase in demand for network-based data transfers and the tools to manage those transfers effectively. Network reliability is also becoming more important as there is often a narrow window between data collection and data archiving when transfer and analysis can be done. The instruments do not stop producing data, so extended network outages can result in data loss due to analysis pipeline stalls. Finally, as the scope of collaboration continues to increase, collaboration tools such as audio and video conferencing are becoming ever more critical to the productivity of scientific collaborations.« less

How to Identify Success Among Networks That Promote Active Living.

PubMed

Litt, Jill; Varda, Danielle; Reed, Hannah; Retrum, Jessica; Tabak, Rachel; Gustat, Jeanette; O'Hara Tompkins, Nancy

2015-11-01

We evaluated organization- and network-level factors that influence organizations' perceived success. This is important for managing interorganizational networks, which can mobilize communities to address complex health issues such as physical activity, and for achieving change. In 2011, we used structured interview and network survey data from 22 states in the United States to estimate multilevel random-intercept models to understand organization- and network-level factors that explain perceived network success. A total of 53 of 59 "whole networks" met the criteria for inclusion in the analysis (89.8%). Coordinators identified 559 organizations, with 3 to 12 organizations from each network taking the online survey (response rate = 69.7%; range = 33%-100%). Occupying a leadership position (P < .01), the amount of time with the network (P < .05), and support from community leaders (P < .05) emerged as correlates of perceived success. Organizations' perceptions of success can influence decisions about continuing involvement and investment in networks designed to promote environment and policy change for active living. Understanding these factors can help leaders manage complex networks that involve diverse memberships, varied interests, and competing community-level priorities.

Optimization of analytical laboratory work using computer networking and databasing

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

Upp, D.L.; Metcalf, R.A.

1996-06-01

The Health Physics Analysis Laboratory (HPAL) performs around 600,000 analyses for radioactive nuclides each year at Los Alamos National Laboratory (LANL). Analysis matrices vary from nasal swipes, air filters, work area swipes, liquids, to the bottoms of shoes and cat litter. HPAL uses 8 liquid scintillation counters, 8 gas proportional counters, and 9 high purity germanium detectors in 5 laboratories to perform these analyses. HPAL has developed a computer network between the labs and software to produce analysis results. The software and hardware package includes barcode sample tracking, log-in, chain of custody, analysis calculations, analysis result printing, and utility programs.more » All data are written to a database, mirrored on a central server, and eventually written to CD-ROM to provide for online historical results. This system has greatly reduced the work required to provide for analysis results as well as improving the quality of the work performed.« less

Identifying emerging research collaborations and networks: method development.

PubMed

Dozier, Ann M; Martina, Camille A; O'Dell, Nicole L; Fogg, Thomas T; Lurie, Stephen J; Rubinstein, Eric P; Pearson, Thomas A

2014-03-01

Clinical and translational research is a multidisciplinary, collaborative team process. To evaluate this process, we developed a method to document emerging research networks and collaborations in our medical center to describe their productivity and viability over time. Using an e-mail survey, sent to 1,620 clinical and basic science full- and part-time faculty members, respondents identified their research collaborators. Initial analyses, using Pajek software, assessed the feasibility of using social network analysis (SNA) methods with these data. Nearly 400 respondents identified 1,594 collaborators across 28 medical center departments resulting in 309 networks with 5 or more collaborators. This low-burden approach yielded a rich data set useful for evaluation using SNA to: (a) assess networks at several levels of the organization, including intrapersonal (individuals), interpersonal (social), organizational/institutional leadership (tenure and promotion), and physical/environmental (spatial proximity) and (b) link with other data to assess the evolution of these networks.

Stability and synchronization analysis of inertial memristive neural networks with time delays.

PubMed

Rakkiyappan, R; Premalatha, S; Chandrasekar, A; Cao, Jinde

2016-10-01

This paper is concerned with the problem of stability and pinning synchronization of a class of inertial memristive neural networks with time delay. In contrast to general inertial neural networks, inertial memristive neural networks is applied to exhibit the synchronization and stability behaviors due to the physical properties of memristors and the differential inclusion theory. By choosing an appropriate variable transmission, the original system can be transformed into first order differential equations. Then, several sufficient conditions for the stability of inertial memristive neural networks by using matrix measure and Halanay inequality are derived. These obtained criteria are capable of reducing computational burden in the theoretical part. In addition, the evaluation is done on pinning synchronization for an array of linearly coupled inertial memristive neural networks, to derive the condition using matrix measure strategy. Finally, the two numerical simulations are presented to show the effectiveness of acquired theoretical results.

A neural-network-based model for the dynamic simulation of the tire/suspension system while traversing road irregularities.

PubMed

Guarneri, Paolo; Rocca, Gianpiero; Gobbi, Massimiliano

2008-09-01

This paper deals with the simulation of the tire/suspension dynamics by using recurrent neural networks (RNNs). RNNs are derived from the multilayer feedforward neural networks, by adding feedback connections between output and input layers. The optimal network architecture derives from a parametric analysis based on the optimal tradeoff between network accuracy and size. The neural network can be trained with experimental data obtained in the laboratory from simulated road profiles (cleats). The results obtained from the neural network demonstrate good agreement with the experimental results over a wide range of operation conditions. The NN model can be effectively applied as a part of vehicle system model to accurately predict elastic bushings and tire dynamics behavior. Although the neural network model, as a black-box model, does not provide a good insight of the physical behavior of the tire/suspension system, it is a useful tool for assessing vehicle ride and noise, vibration, harshness (NVH) performance due to its good computational efficiency and accuracy.

Weighted complex network analysis of the Beijing subway system: Train and passenger flows

NASA Astrophysics Data System (ADS)

Feng, Jia; Li, Xiamiao; Mao, Baohua; Xu, Qi; Bai, Yun

2017-05-01

In recent years, complex network theory has become an important approach to the study of the structure and dynamics of traffic networks. However, because traffic data is difficult to collect, previous studies have usually focused on the physical topology of subway systems, whereas few studies have considered the characteristics of traffic flows through the network. Therefore, in this paper, we present a multi-layer model to analyze traffic flow patterns in subway networks, based on trip data and an operation timetable obtained from the Beijing Subway System. We characterize the patterns in terms of the spatiotemporal flow size distributions of both the train flow network and the passenger flow network. In addition, we describe the essential interactions between these two networks based on statistical analyses. The results of this study suggest that layered models of transportation systems can elucidate fundamental differences between the coexisting traffic flows and can also clarify the mechanism that causes these differences.

BESIU Physical Analysis on Hadoop Platform

NASA Astrophysics Data System (ADS)

Huo, Jing; Zang, Dongsong; Lei, Xiaofeng; Li, Qiang; Sun, Gongxing

2014-06-01

In the past 20 years, computing cluster has been widely used for High Energy Physics data processing. The jobs running on the traditional cluster with a Data-to-Computing structure, have to read large volumes of data via the network to the computing nodes for analysis, thereby making the I/O latency become a bottleneck of the whole system. The new distributed computing technology based on the MapReduce programming model has many advantages, such as high concurrency, high scalability and high fault tolerance, and it can benefit us in dealing with Big Data. This paper brings the idea of using MapReduce model to do BESIII physical analysis, and presents a new data analysis system structure based on Hadoop platform, which not only greatly improve the efficiency of data analysis, but also reduces the cost of system building. Moreover, this paper establishes an event pre-selection system based on the event level metadata(TAGs) database to optimize the data analyzing procedure.

Artificial neural networks in biology and chemistry: the evolution of a new analytical tool.

PubMed

Cartwright, Hugh M

2008-01-01

Once regarded as an eccentric and unpromising algorithm for the analysis of scientific data, the neural network has been developed in the last decade into a powerful computational tool. Its use now spans all areas of science, from the physical sciences and engineering to the life sciences and allied subjects. Applications range from the assessment of epidemiological data or the deconvolution of spectra to highly practical applications, such as the electronic nose. This introductory chapter considers briefly the growth in the use of neural networks and provides some general background in preparation for the more detailed chapters that follow.

Wellness partners: design and evaluation of a web-based physical activity diary with social gaming features for adults.

PubMed

Gotsis, Marientina; Wang, Hua; Spruijt-Metz, Donna; Jordan-Marsh, Maryalice; Valente, Thomas William

2013-02-01

The United States is currently in an age of obesity and inactivity despite increasing public awareness and scientific knowledge of detrimental long-term health effects of this lifestyle. Behavior-tracking diaries offer an effective strategy for physical activity adherence and weight management. Furthermore, Web-based physical activity diaries can engage meaningful partners in people's social networks through fun online gaming interactions and generate motivational mechanisms for effective behavioral change and positive health outcomes. Wellness Partners (WP) is a Web-based intervention in the form of a physical activity diary with social networking and game features. Two versions were designed and developed for the purpose of this study-"Diary" only and "Diary+Game". The objectives of this study included pilot testing the research process of this intervention design, implementation, evaluation, and exploring the effectiveness of social gaming features on adult participants' physical activity and anthropometric measures. We conducted a field experiment with randomized crossover design. Assessments occurred at baseline, first follow-up (FU, 5-8 weeks after using one version of WP), and second FU (5-8 weeks of using the other version of WP). In the control condition, participants started with the "Diary" version of WP while in the experimental condition, participants started with the "Diary+Game" version of WP. A total of 54 adults (egos) ages 44-88, and their family and friends (alters) ages 17-69 participated in the study in ego-network groups. Both egos and their alters completed online surveys about their exercise habits. In addition, egos completed anthropometric measurements of BMI, fat percentage, and fat mass by bioimpedance. From October 2009 to May 2010, flyers, emails, and Web advertisements yielded 335 volunteers who were screened. Rolling recruitment resulted in enrollment of 142 qualified participants in 54 ego-network groups, which were randomly assigned to a study condition. The final analytic sample included 87 individuals from 41 groups. Data were collected from December 2009 to August 2010, and data analysis was completed in 2011. Overall, the participants were given access to the intervention for 10-13 weeks. Statistical analysis suggested an increase in self-reported exercise frequency (mean days per week) from baseline (2.57, SD 1.92) to first FU (3.21, SD 1.74) in both conditions. Stronger effects were seen in the condition where Diary+Game was played first, especially in network groups with larger age variation between the alters and egos. Overall, the decrease in egos' BMI was statistically significant from baseline to first FU, with greater decrease for those in the Diary+Game first condition (-0.26 vs -0.16 in the Diary first condition). The Wellness Partners program increased physical activity among participants and resulted in health benefits among the egos. Web-based diary interventions designed with social gaming features hold potential to promote active lifestyles for middle-age adults and people in their social networks.

A Model-Based Approach for Bridging Virtual and Physical Sensor Nodes in a Hybrid Simulation Framework

PubMed Central

Mozumdar, Mohammad; Song, Zhen Yu; Lavagno, Luciano; Sangiovanni-Vincentelli, Alberto L.

2014-01-01

The Model Based Design (MBD) approach is a popular trend to speed up application development of embedded systems, which uses high-level abstractions to capture functional requirements in an executable manner, and which automates implementation code generation. Wireless Sensor Networks (WSNs) are an emerging very promising application area for embedded systems. However, there is a lack of tools in this area, which would allow an application developer to model a WSN application by using high level abstractions, simulate it mapped to a multi-node scenario for functional analysis, and finally use the refined model to automatically generate code for different WSN platforms. Motivated by this idea, in this paper we present a hybrid simulation framework that not only follows the MBD approach for WSN application development, but also interconnects a simulated sub-network with a physical sub-network and then allows one to co-simulate them, which is also known as Hardware-In-the-Loop (HIL) simulation. PMID:24960083

The association between active participation in a sports club, physical activity and social network on the development of lung cancer in smokers: a case-control study.

PubMed

Schmidt, Anna; Jung, Julia; Ernstmann, Nicole; Driller, Elke; Neumann, Melanie; Staratschek-Jox, Andrea; Schneider, Christian; Wolf, Jürgen; Pfaff, Holger

2012-01-04

This study analyses the effect of active participation in a sports club, physical activity and social networks on the development of lung cancer in patients who smoke. Our hypothesis is that study participants who lack social networks and do not actively participate in a sports club are at a greater risk for lung cancer than those who do. Data for the study were taken from the Cologne Smoking Study (CoSmoS), a retrospective case-control study examining potential psychosocial risk factors for the development of lung cancer. Our sample consisted of n = 158 participants who had suffered lung cancer (diagnosis in the patient document) and n = 144 control group participants. Both groups had a history of smoking.Data on social networks were collected by asking participants whether they participated in a sports club and about the number of friends and relatives in their social environment. In addition, sociodemographic data (gender, age, education, marital status, residence and religion), physical activity and data on pack years (the cumulative number of cigarettes smoked by an individual, calculated by multiplying the number of cigarettes smoked per day by the number of years the person has smoked divided by 20) were collected to control for potential confounders. Logistic regression was used for the statistical analysis. The results reveal that participants who are physically active are at a lower risk of lung cancer than those who are not (adjusted OR = 0.53*; CI = 0.29-0.97). Older age and lower education seem also to be risk factors for the development of lung cancer. The extent of smoking, furthermore, measured by pack years is statistically significant. Active participation in a sports club, number of friends and relatives had no statistically significant influence on the development of the cancer. The results of the study suggest that there is a lower risk for physically active participants to develop lung cancer. In the study sample, physical activity seemed to have a greater protective effect than participation in a sports club or social network of friends and relatives. Further studies have to investigate in more detail physical activity and other club participations.

SYNCHRONIZATION OF HETEROGENEOUS OSCILLATORS UNDER NETWORK MODIFICATIONS: PERTURBATION AND OPTIMIZATION OF THE SYNCHRONY ALIGNMENT FUNCTION

PubMed Central

Taylor, Dane; Skardal, Per Sebastian; Sun, Jie

2016-01-01

Synchronization is central to many complex systems in engineering physics (e.g., the power-grid, Josephson junction circuits, and electro-chemical oscillators) and biology (e.g., neuronal, circadian, and cardiac rhythms). Despite these widespread applications—for which proper functionality depends sensitively on the extent of synchronization—there remains a lack of understanding for how systems can best evolve and adapt to enhance or inhibit synchronization. We study how network modifications affect the synchronization properties of network-coupled dynamical systems that have heterogeneous node dynamics (e.g., phase oscillators with non-identical frequencies), which is often the case for real-world systems. Our approach relies on a synchrony alignment function (SAF) that quantifies the interplay between heterogeneity of the network and of the oscillators and provides an objective measure for a system’s ability to synchronize. We conduct a spectral perturbation analysis of the SAF for structural network modifications including the addition and removal of edges, which subsequently ranks the edges according to their importance to synchronization. Based on this analysis, we develop gradient-descent algorithms to efficiently solve optimization problems that aim to maximize phase synchronization via network modifications. We support these and other results with numerical experiments. PMID:27872501

Attenuation correction for brain PET imaging using deep neural network based on dixon and ZTE MR images.

PubMed

Gong, Kuang; Yang, Jaewon; Kim, Kyungsang; El Fakhri, Georges; Seo, Youngho; Li, Quanzheng

2018-05-23

Positron Emission Tomography (PET) is a functional imaging modality widely used in neuroscience studies. To obtain meaningful quantitative results from PET images, attenuation correction is necessary during image reconstruction. For PET/MR hybrid systems, PET attenuation is challenging as Magnetic Resonance (MR) images do not reflect attenuation coefficients directly. To address this issue, we present deep neural network methods to derive the continuous attenuation coefficients for brain PET imaging from MR images. With only Dixon MR images as the network input, the existing U-net structure was adopted and analysis using forty patient data sets shows it is superior than other Dixon based methods. When both Dixon and zero echo time (ZTE) images are available, we have proposed a modified U-net structure, named GroupU-net, to efficiently make use of both Dixon and ZTE information through group convolution modules when the network goes deeper. Quantitative analysis based on fourteen real patient data sets demonstrates that both network approaches can perform better than the standard methods, and the proposed network structure can further reduce the PET quantification error compared to the U-net structure. © 2018 Institute of Physics and Engineering in Medicine.

Fast Two-Dimensional Bubble Analysis of Biopolymer Filamentous Networks Pore Size from Confocal Microscopy Thin Data Stacks

PubMed Central

Molteni, Matteo; Magatti, Davide; Cardinali, Barbara; Rocco, Mattia; Ferri, Fabio

2013-01-01

The average pore size ξ0 of filamentous networks assembled from biological macromolecules is one of the most important physical parameters affecting their biological functions. Modern optical methods, such as confocal microscopy, can noninvasively image such networks, but extracting a quantitative estimate of ξ0 is a nontrivial task. We present here a fast and simple method based on a two-dimensional bubble approach, which works by analyzing one by one the (thresholded) images of a series of three-dimensional thin data stacks. No skeletonization or reconstruction of the full geometry of the entire network is required. The method was validated by using many isotropic in silico generated networks of different structures, morphologies, and concentrations. For each type of network, the method provides accurate estimates (a few percent) of the average and the standard deviation of the three-dimensional distribution of the pore sizes, defined as the diameters of the largest spheres that can be fit into the pore zones of the entire gel volume. When applied to the analysis of real confocal microscopy images taken on fibrin gels, the method provides an estimate of ξ0 consistent with results from elastic light scattering data. PMID:23473499

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

PubMed

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

2017-08-01

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

PatterNet: a system to learn compact physical design pattern representations for pattern-based analytics

NASA Astrophysics Data System (ADS)

Lutich, Andrey

2017-07-01

This research considers the problem of generating compact vector representations of physical design patterns for analytics purposes in semiconductor patterning domain. PatterNet uses a deep artificial neural network to learn mapping of physical design patterns to a compact Euclidean hyperspace. Distances among mapped patterns in this space correspond to dissimilarities among patterns defined at the time of the network training. Once the mapping network has been trained, PatterNet embeddings can be used as feature vectors with standard machine learning algorithms, and pattern search, comparison, and clustering become trivial problems. PatterNet is inspired by the concepts developed within the framework of generative adversarial networks as well as the FaceNet. Our method facilitates a deep neural network (DNN) to learn directly the compact representation by supplying it with pairs of design patterns and dissimilarity among these patterns defined by a user. In the simplest case, the dissimilarity is represented by an area of the XOR of two patterns. Important to realize that our PatterNet approach is very different to the methods developed for deep learning on image data. In contrast to "conventional" pictures, the patterns in the CAD world are the lists of polygon vertex coordinates. The method solely relies on the promise of deep learning to discover internal structure of the incoming data and learn its hierarchical representations. Artificial intelligence arising from the combination of PatterNet and clustering analysis very precisely follows intuition of patterning/optical proximity correction experts paving the way toward human-like and human-friendly engineering tools.

Integrating physical and genetic maps: from genomes to interaction networks

PubMed Central

Beyer, Andreas; Bandyopadhyay, Sourav; Ideker, Trey

2009-01-01

Physical and genetic mapping data have become as important to network biology as they once were to the Human Genome Project. Integrating physical and genetic networks currently faces several challenges: increasing the coverage of each type of network; establishing methods to assemble individual interaction measurements into contiguous pathway models; and annotating these pathways with detailed functional information. A particular challenge involves reconciling the wide variety of interaction types that are currently available. For this purpose, recent studies have sought to classify genetic and physical interactions along several complementary dimensions, such as ordered versus unordered, alleviating versus aggravating, and first versus second degree. PMID:17703239

Optimizing targeted vaccination across cyber-physical networks: an empirically based mathematical simulation study.

PubMed

Mones, Enys; Stopczynski, Arkadiusz; Pentland, Alex 'Sandy'; Hupert, Nathaniel; Lehmann, Sune

2018-01-01

Targeted vaccination, whether to minimize the forward transmission of infectious diseases or their clinical impact, is one of the 'holy grails' of modern infectious disease outbreak response, yet it is difficult to achieve in practice due to the challenge of identifying optimal targets in real time. If interruption of disease transmission is the goal, targeting requires knowledge of underlying person-to-person contact networks. Digital communication networks may reflect not only virtual but also physical interactions that could result in disease transmission, but the precise overlap between these cyber and physical networks has never been empirically explored in real-life settings. Here, we study the digital communication activity of more than 500 individuals along with their person-to-person contacts at a 5-min temporal resolution. We then simulate different disease transmission scenarios on the person-to-person physical contact network to determine whether cyber communication networks can be harnessed to advance the goal of targeted vaccination for a disease spreading on the network of physical proximity. We show that individuals selected on the basis of their closeness centrality within cyber networks (what we call 'cyber-directed vaccination') can enhance vaccination campaigns against diseases with short-range (but not full-range) modes of transmission. © 2018 The Author(s).

Friendship networks and physical activity and sedentary behavior among youth: a systematized review

PubMed Central

2013-01-01

Background Low levels of physical activity and increased participation in sedentary leisure-time activities are two important obesity-risk behaviors that impact the health of today’s youth. Friend’s health behaviors have been shown to influence individual health behaviors; however, current evidence on the specific role of friendship networks in relation to levels of physical activity and sedentary behavior is limited. The purpose of this review was to summarize evidence on friendship networks and both physical activity and sedentary behavior among children and adolescents. Method After a search of seven scientific databases and reference scans, a total of thirteen articles were eligible for inclusion. All assessed the association between friendship networks and physical activity, while three also assessed sedentary behavior. Results Overall, higher levels of physical activity among friends are associated with higher levels of physical activity of the individual. Longitudinal studies reveal that an individual’s level of physical activity changes to reflect his/her friends’ higher level of physical activity. Boys tend to be influenced by their friendship network to a greater extent than girls. There is mixed evidence surrounding a friend’s sedentary behavior and individual sedentary behavior. Conclusion Friends’ physical activity level appears to have a significant influence on individual’s physical activity level. Evidence surrounding sedentary behavior is limited and mixed. Results from this review could inform effective public health interventions that harness the influence of friends to increase physical activity levels among children and adolescents. PMID:24289113

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

Cyber-physical networking for wireless mesh infrastructures

NASA Astrophysics Data System (ADS)

Mannweiler, C.; Lottermann, C.; Klein, A.; Schneider, J.; Schotten, H. D.

2012-09-01

This paper presents a novel approach for cyber-physical network control. "Cyber-physical" refers to the inclusion of different parameters and information sources, ranging from physical sensors (e.g. energy, temperature, light) to conventional network information (bandwidth, delay, jitter, etc.) to logical data providers (inference systems, user profiles, spectrum usage databases). For a consistent processing, collected data is represented in a uniform way, analyzed, and provided to dedicated network management functions and network services, both internally and, through an according API, to third party services. Specifically, in this work, we outline the design of sophisticated energy management functionalities for a hybrid wireless mesh network (WLAN for both backhaul traffic and access, GSM for access only), disposing of autonomous energy supply, in this case solar power. Energy consumption is optimized under the presumption of fluctuating power availability and considerable storage constraints, thus influencing, among others, handover and routing decisions. Moreover, advanced situation-aware auto-configuration and self-adaptation mechanisms are introduced for an autonomous operation of the network. The overall objective is to deploy a robust wireless access and backbone infrastructure with minimal operational cost and effective, cyber-physical control mechanisms, especially dedicated for rural or developing regions.

The core symptoms of bulimia nervosa, anxiety, and depression: A network analysis.

PubMed

Levinson, Cheri A; Zerwas, Stephanie; Calebs, Benjamin; Forbush, Kelsie; Kordy, Hans; Watson, Hunna; Hofmeier, Sara; Levine, Michele; Crosby, Ross D; Peat, Christine; Runfola, Cristin D; Zimmer, Benjamin; Moesner, Markus; Marcus, Marsha D; Bulik, Cynthia M

2017-04-01

Bulimia nervosa (BN) is characterized by symptoms of binge eating and compensatory behavior, and overevaluation of weight and shape, which often co-occur with symptoms of anxiety and depression. However, there is little research identifying which specific BN symptoms maintain BN psychopathology and how they are associated with symptoms of depression and anxiety. Network analyses represent an emerging method in psychopathology research to examine how symptoms interact and may become self-reinforcing. In the current study of adults with a Diagnostic and Statistical Manual for Mental Disorders-Fourth Edition ( DSM-IV ) diagnosis of BN (N = 196), we used network analysis to identify the central symptoms of BN, as well as symptoms that may bridge the association between BN symptoms and anxiety and depression symptoms. Results showed that fear of weight gain was central to BN psychopathology, whereas binge eating, purging, and restriction were less central in the symptom network. Symptoms related to sensitivity to physical sensations (e.g., changes in appetite, feeling dizzy, and wobbly) were identified as bridge symptoms between BN, and anxiety and depressive symptoms. We discuss our findings with respect to cognitive-behavioral treatment approaches for BN. These findings suggest that treatments for BN should focus on fear of weight gain, perhaps through exposure therapies. Further, interventions focusing on exposure to physical sensations may also address BN psychopathology, as well as co-occurring anxiety and depressive symptoms. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

A Statistical Approach to Characterize and Detect degradation Within the Barabasi-Albert Network

DTIC Science & Technology

2016-09-01

Astrophysics Collaborations 16046 932.11 0.4948 520.10|6 57 High-Energy Physics Theory Collaborations 7610 251.54 0.9481 -16.27|6 22 High-Energy Physics ...social, physical , and biological phenomena [6, 70, 16, 107]. The Barabási-Albert network exhibits the scale-free property and is highly desired for...It was noted that there has also been considerable effort in applying various types of graph entropies in the field of network physics . Mowshowitz and

Network analysis of named entity co-occurrences in written texts

NASA Astrophysics Data System (ADS)

Amancio, Diego Raphael

2016-06-01

The use of methods borrowed from statistics and physics to analyze written texts has allowed the discovery of unprecedent patterns of human behavior and cognition by establishing links between models features and language structure. While current models have been useful to unveil patterns via analysis of syntactical and semantical networks, only a few works have probed the relevance of investigating the structure arising from the relationship between relevant entities such as characters, locations and organizations. In this study, we represent entities appearing in the same context as a co-occurrence network, where links are established according to a null model based on random, shuffled texts. Computational simulations performed in novels revealed that the proposed model displays interesting topological features, such as the small world feature, characterized by high values of clustering coefficient. The effectiveness of our model was verified in a practical pattern recognition task in real networks. When compared with traditional word adjacency networks, our model displayed optimized results in identifying unknown references in texts. Because the proposed representation plays a complementary role in characterizing unstructured documents via topological analysis of named entities, we believe that it could be useful to improve the characterization of written texts (and related systems), specially if combined with traditional approaches based on statistical and deeper paradigms.

Social grooming network in captive chimpanzees: does the wild or captive origin of group members affect sociality?

PubMed

Levé, Marine; Sueur, Cédric; Petit, Odile; Matsuzawa, Tetsuro; Hirata, Satoshi

2016-01-01

Many chimpanzees throughout the world are housed in captivity, and there is an increasing effort to recreate social groups by mixing individuals with captive origins with those with wild origins. Captive origins may entail restricted rearing conditions during early infant life, including, for example, no maternal rearing and a limited social life. Early rearing conditions have been linked with differences in tool-use behavior between captive- and wild-born chimpanzees. If physical cognition can be impaired by non-natural rearing, what might be the consequences for social capacities? This study describes the results of network analysis based on grooming interactions in chimpanzees with wild and captive origins living in the Kumamoto Sanctuary in Kumamoto, Japan. Grooming is a complex social activity occupying up to 25% of chimpanzees' waking hours and plays a role in the emergence and maintenance of social relationships. We assessed whether the social centralities and roles of chimpanzees might be affected by their origin (captive vs wild). We found that captive- and wild-origin chimpanzees did not differ in their grooming behavior, but that theoretical removal of individuals from the network had differing impacts depending on the origin of the individual. Contrary to findings that non-natural early rearing has long-term effects on physical cognition, living in social groups seems to compensate for the negative effects of non-natural early rearing. Social network analysis (SNA) and, in particular, theoretical removal analysis, were able to highlight differences between individuals that would have been impossible to show using classical methods. The social environment of captive animals is important to their well-being, and we are only beginning to understand how SNA might help to enhance animal welfare.

National Space Science Data Center and World Data Center A for Rockets and Satellites - Ionospheric data holdings and services

NASA Technical Reports Server (NTRS)

Bilitza, D.; King, J. H.

1988-01-01

The activities and services of the National Space Science data Center (NSSDC) and the World Data Center A for Rockets and Satellites (WDC-A-R and S) are described with special emphasis on ionospheric physics. The present catalog/archive system is explained and future developments are indicated. In addition to the basic data acquisition, archiving, and dissemination functions, ongoing activities include the Central Online Data Directory (CODD), the Coordinated Data Analysis Workshopps (CDAW), the Space Physics Analysis Network (SPAN), advanced data management systems (CD/DIS, NCDS, PLDS), and publication of the NSSDC News, the SPACEWARN Bulletin, and several NSSD reports.

SISSY: An example of a multi-threaded, networked, object-oriented databased application

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

Scipioni, B.; Liu, D.; Song, T.

1993-05-01

The Systems Integration Support SYstem (SISSY) is presented and its capabilities and techniques are discussed. It is fully automated data collection and analysis system supporting the SSCL`s systems analysis activities as they relate to the Physics Detector and Simulation Facility (PDSF). SISSY itself is a paradigm of effective computing on the PDSF. It uses home-grown code (C++), network programming (RPC, SNMP), relational (SYBASE) and object-oriented (ObjectStore) DBMSs, UNIX operating system services (IRIX threads, cron, system utilities, shells scripts, etc.), and third party software applications (NetCentral Station, Wingz, DataLink) all of which act together as a single application to monitor andmore » analyze the PDSF.« less

A Study of LoRa: Long Range & Low Power Networks for the Internet of Things

PubMed Central

Augustin, Aloÿs; Yi, Jiazi; Clausen, Thomas; Townsley, William Mark

2016-01-01

LoRa is a long-range, low-power, low-bitrate, wireless telecommunications system, promoted as an infrastructure solution for the Internet of Things: end-devices use LoRa across a single wireless hop to communicate to gateway(s), connected to the Internet and which act as transparent bridges and relay messages between these end-devices and a central network server. This paper provides an overview of LoRa and an in-depth analysis of its functional components. The physical and data link layer performance is evaluated by field tests and simulations. Based on the analysis and evaluations, some possible solutions for performance enhancements are proposed. PMID:27618064

A Study of LoRa: Long Range & Low Power Networks for the Internet of Things.

PubMed

Augustin, Aloÿs; Yi, Jiazi; Clausen, Thomas; Townsley, William Mark

2016-09-09

LoRa is a long-range, low-power, low-bitrate, wireless telecommunications system, promoted as an infrastructure solution for the Internet of Things: end-devices use LoRa across a single wireless hop to communicate to gateway(s), connected to the Internet and which act as transparent bridges and relay messages between these end-devices and a central network server. This paper provides an overview of LoRa and an in-depth analysis of its functional components. The physical and data link layer performance is evaluated by field tests and simulations. Based on the analysis and evaluations, some possible solutions for performance enhancements are proposed.

Experiments in clustered neuronal networks: A paradigm for complex modular dynamics

NASA Astrophysics Data System (ADS)

Teller, Sara; Soriano, Jordi

2016-06-01

Uncovering the interplay activity-connectivity is one of the major challenges in neuroscience. To deepen in the understanding of how a neuronal circuit shapes network dynamics, neuronal cultures have emerged as remarkable systems given their accessibility and easy manipulation. An attractive configuration of these in vitro systems consists in an ensemble of interconnected clusters of neurons. Using calcium fluorescence imaging to monitor spontaneous activity in these clustered neuronal networks, we were able to draw functional maps and reveal their topological features. We also observed that these networks exhibit a hierarchical modular dynamics, in which clusters fire in small groups that shape characteristic communities in the network. The structure and stability of these communities is sensitive to chemical or physical action, and therefore their analysis may serve as a proxy for network health. Indeed, the combination of all these approaches is helping to develop models to quantify damage upon network degradation, with promising applications for the study of neurological disorders in vitro.

Finding Multi-scale Connectivity in Our Geospace Observational System: A New Perspective for Total Electron Content Data Through Network Analysis

NASA Astrophysics Data System (ADS)

McGranaghan, R. M.; Mannucci, A. J.; Verkhoglyadova, O. P.; Malik, N.

2017-12-01

How do we evolve beyond current traditional methods in order to innovate into the future? In what disruptive innovations will the next frontier of space physics and aeronomy (SPA) be grounded? We believe the answer to these compelling, yet equally challenging, questions lies in a shift of focus: from a narrow, field-specific view to a radically inclusive, interdisciplinary new modus operandi at the intersection of SPA and the information and data sciences. Concretely addressing these broader themes, we present results from a novel technique for knowledge discovery in the magnetosphere-ionosphere-thermosphere (MIT) system: complex network analysis (NA). We share findings from the first NA of ionospheric total electron content (TEC) data, including hemispheric and interplanetary magnetic field clock angle dependencies [1]. Our work shows that NA complements more traditional approaches for the investigation of TEC structure and dynamics, by both reaffirming well-established understanding, giving credence to the method, and identifying new connections, illustrating the exciting potential. We contextualize these new results through a discussion of the potential of data-driven discovery in the MIT system when innovative data science techniques are embraced. We address implications and potentially disruptive data analysis approaches for SPA in terms of: 1) the future of the geospace observational system; 2) understanding multi-scale phenomena; and 3) machine learning. [1] McGranaghan, R. M., A. J. Mannucci, O. Verkhoglyadova, and N. Malik (2017), Finding multiscale connectivity in our geospace observational system: Network analysis of total electron content, J. Geophys. Res. Space Physics, 122, doi:10.1002/2017JA024202.

A Cluster Analysis of Support Networks of Older People with Severe Intellectual Impairment.

ERIC Educational Resources Information Center

Moss, Steve; Hogg, James

1989-01-01

The report describes a demographic survey of 122 people with severe intellectual impairment over 50 years of age in a British community. Seven relatively independent clusters were identified: contact with relatives, community activities, community independence, friendship, service pathways, geriatrics/mobility, and physical treatment. (Author/DB)

Network analysis: a new tool for resource managers

Treesearch

Ruth H. Allen

1980-01-01

Resource managers manipulate ecosystems for direct or indirect human uses. Examples of relatively well studied resource management issues include familiar biological products such as: forests, ranges, fish and wildlife; or physical products such as air, water and soil. Until very recently, urban environments received much less scholarly attention. However, as Spurr (...

Combining the Finite Element Method with Structural Connectome-based Analysis for Modeling Neurotrauma: Connectome Neurotrauma Mechanics

PubMed Central

Kraft, Reuben H.; Mckee, Phillip Justin; Dagro, Amy M.; Grafton, Scott T.

2012-01-01

This article presents the integration of brain injury biomechanics and graph theoretical analysis of neuronal connections, or connectomics, to form a neurocomputational model that captures spatiotemporal characteristics of trauma. We relate localized mechanical brain damage predicted from biofidelic finite element simulations of the human head subjected to impact with degradation in the structural connectome for a single individual. The finite element model incorporates various length scales into the full head simulations by including anisotropic constitutive laws informed by diffusion tensor imaging. Coupling between the finite element analysis and network-based tools is established through experimentally-based cellular injury thresholds for white matter regions. Once edges are degraded, graph theoretical measures are computed on the “damaged” network. For a frontal impact, the simulations predict that the temporal and occipital regions undergo the most axonal strain and strain rate at short times (less than 24 hrs), which leads to cellular death initiation, which results in damage that shows dependence on angle of impact and underlying microstructure of brain tissue. The monotonic cellular death relationships predict a spatiotemporal change of structural damage. Interestingly, at 96 hrs post-impact, computations predict no network nodes were completely disconnected from the network, despite significant damage to network edges. At early times () network measures of global and local efficiency were degraded little; however, as time increased to 96 hrs the network properties were significantly reduced. In the future, this computational framework could help inform functional networks from physics-based structural brain biomechanics to obtain not only a biomechanics-based understanding of injury, but also neurophysiological insight. PMID:22915997

Network Analysis of Protein Adaptation: Modeling the Functional Impact of Multiple Mutations

PubMed Central

Beleva Guthrie, Violeta; Masica, David L; Fraser, Andrew; Federico, Joseph; Fan, Yunfan; Camps, Manel; Karchin, Rachel

2018-01-01

Abstract The evolution of new biochemical activities frequently involves complex dependencies between mutations and rapid evolutionary radiation. Mutation co-occurrence and covariation have previously been used to identify compensating mutations that are the result of physical contacts and preserve protein function and fold. Here, we model pairwise functional dependencies and higher order interactions that enable evolution of new protein functions. We use a network model to find complex dependencies between mutations resulting from evolutionary trade-offs and pleiotropic effects. We present a method to construct these networks and to identify functionally interacting mutations in both extant and reconstructed ancestral sequences (Network Analysis of Protein Adaptation). The time ordering of mutations can be incorporated into the networks through phylogenetic reconstruction. We apply NAPA to three distantly homologous β-lactamase protein clusters (TEM, CTX-M-3, and OXA-51), each of which has experienced recent evolutionary radiation under substantially different selective pressures. By analyzing the network properties of each protein cluster, we identify key adaptive mutations, positive pairwise interactions, different adaptive solutions to the same selective pressure, and complex evolutionary trajectories likely to increase protein fitness. We also present evidence that incorporating information from phylogenetic reconstruction and ancestral sequence inference can reduce the number of spurious links in the network, whereas preserving overall network community structure. The analysis does not require structural or biochemical data. In contrast to function-preserving mutation dependencies, which are frequently from structural contacts, gain-of-function mutation dependencies are most commonly between residues distal in protein structure. PMID:29522102

Effects of social networks on physical health among people with serious mental illness.

PubMed

Lee, Sungkyu; Wong, Yin-Ling Irene; Rothbard, Aileen

2014-12-01

This study examined the effects of social network characteristics on physical health among people with serious mental illness using social transactions that are reciprocal, and the combination of objective and subjective health measures. The sample consisted of a probability sample of 231 adults with serious mental illness who resided in permanent supportive housing in Philadelphia, Pennsylvania. Path analyses were conducted to examine the relationships between social network characteristics and two aspects of medical comorbidity, objective health and subjective health. Bivariate statistics showed that individuals with medical comorbidity were more likely to have contact with their network members and had a higher level of reciprocal positive tangible support when compared to those who did not have medical comorbidity. The results of the path analyses revealed that none of the social network characteristics were associated with better physical health. The lack of a significant relationship between social networks and better physical health is contrary to prior research findings. However, this is the first study to include both types of social transactions simultaneously as predictors of better physical health for individuals with serious mental illness. A longitudinal study would provide more insight into the temporal relationship of social networks and physical health conditions of people with serious mental illness. Furthermore, the transactional nature of social relationships, particularly for those with mental health issues, requires greater exploration.

Computer Network Resources for Physical Geography Instruction.

ERIC Educational Resources Information Center

Bishop, Michael P.; And Others

1993-01-01

Asserts that the use of computer networks provides an important and effective resource for geography instruction. Describes the use of the Internet network in physical geography instruction. Provides an example of the use of Internet resources in a climatology/meteorology course. (CFR)

Finding community structure in very large networks

NASA Astrophysics Data System (ADS)

Clauset, Aaron; Newman, M. E. J.; Moore, Cristopher

2004-12-01

The discovery and analysis of community structure in networks is a topic of considerable recent interest within the physics community, but most methods proposed so far are unsuitable for very large networks because of their computational cost. Here we present a hierarchical agglomeration algorithm for detecting community structure which is faster than many competing algorithms: its running time on a network with n vertices and m edges is O(mdlogn) where d is the depth of the dendrogram describing the community structure. Many real-world networks are sparse and hierarchical, with mtilde n and dtilde logn , in which case our algorithm runs in essentially linear time, O(nlog2n) . As an example of the application of this algorithm we use it to analyze a network of items for sale on the web site of a large on-line retailer, items in the network being linked if they are frequently purchased by the same buyer. The network has more than 400 000 vertices and 2×106 edges. We show that our algorithm can extract meaningful communities from this network, revealing large-scale patterns present in the purchasing habits of customers.

Investigation with respect to content and general properties of physics 10 textbook in accordance with the 2013 secondary school physics curriculum

NASA Astrophysics Data System (ADS)

Kavcar, Nevzat; Korkmaz, Cihan

2017-02-01

Purpose of this work is to determine the physics teacher candidates' views on Physics 10 textbook' content and general properties suitable to the 2013 Secondary School Physics Curriculum. 23 teacher candidates at 2014-2015 school year constituted the sampling of the study in which scanning model based on qualitative research technique was used by performing document analysis. Data collection tool of the research was the files prepared with 51 and nine open ended questions including the subject content and general properties of the textbook. It was concluded that the textbook was sufficient for being life context -based, language, activity-based and student-centered approximation, development of social and inquiry skills, and was insufficient for referring educational gains of the Curriculum, involving activities, projects and homework about application. Activities and applications about affective area, such tools for assessment and evaluation practices as concept map, concept network and semantic analysis table may be involved in the textbook.

Network Analysis of Students' Use of Representations in Problem Solving

NASA Astrophysics Data System (ADS)

McPadden, Daryl; Brewe, Eric

2016-03-01

We present the preliminary results of a study on student use of representations in problem solving within the Modeling Instruction - Electricity and Magnetism (MI-E&M) course. Representational competence is a critical skill needed for students to develop a sophisticated understanding of college science topics and to succeed in their science courses. In this study, 70 students from the MI-E&M, calculus-based course were given a survey of 25 physics problem statements both pre- and post- instruction, covering both Newtonian Mechanics and Electricity and Magnetism (E&M). For each problem statement, students were asked which representations they would use in that given situation. We analyze the survey results through network analysis, identifying which representations are linked together in which contexts. We also compare the representation networks for those students who had already taken the first-semester Modeling Instruction Mechanics course and those students who had taken a non-Modeling Mechanics course.

A dedicated network for social interaction processing in the primate brain.

PubMed

Sliwa, J; Freiwald, W A

2017-05-19

Primate cognition requires interaction processing. Interactions can reveal otherwise hidden properties of intentional agents, such as thoughts and feelings, and of inanimate objects, such as mass and material. Where and how interaction analyses are implemented in the brain is unknown. Using whole-brain functional magnetic resonance imaging in macaque monkeys, we discovered a network centered in the medial and ventrolateral prefrontal cortex that is exclusively engaged in social interaction analysis. Exclusivity of specialization was found for no other function anywhere in the brain. Two additional networks, a parieto-premotor and a temporal one, exhibited both social and physical interaction preference, which, in the temporal lobe, mapped onto a fine-grain pattern of object, body, and face selectivity. Extent and location of a dedicated system for social interaction analysis suggest that this function is an evolutionary forerunner of human mind-reading capabilities. Copyright © 2017, American Association for the Advancement of Science.

Finite-time synchronization for memristor-based neural networks with time-varying delays.

PubMed

Abdurahman, Abdujelil; Jiang, Haijun; Teng, Zhidong

2015-09-01

Memristive network exhibits state-dependent switching behaviors due to the physical properties of memristor, which is an ideal tool to mimic the functionalities of the human brain. In this paper, finite-time synchronization is considered for a class of memristor-based neural networks with time-varying delays. Based on the theory of differential equations with discontinuous right-hand side, several new sufficient conditions ensuring the finite-time synchronization of memristor-based chaotic neural networks are obtained by using analysis technique, finite time stability theorem and adding a suitable feedback controller. Besides, the upper bounds of the settling time of synchronization are estimated. Finally, a numerical example is given to show the effectiveness and feasibility of the obtained results. Copyright © 2015 Elsevier Ltd. All rights reserved.

Analysis of remote synchronization in complex networks

NASA Astrophysics Data System (ADS)

Gambuzza, Lucia Valentina; Cardillo, Alessio; Fiasconaro, Alessandro; Fortuna, Luigi; Gómez-Gardeñes, Jesus; Frasca, Mattia

2013-12-01

A novel regime of synchronization, called remote synchronization, where the peripheral nodes form a phase synchronized cluster not including the hub, was recently observed in star motifs [Bergner et al., Phys. Rev. E 85, 026208 (2012)]. We show the existence of a more general dynamical state of remote synchronization in arbitrary networks of coupled oscillators. This state is characterized by the synchronization of pairs of nodes that are not directly connected via a physical link or any sequence of synchronized nodes. This phenomenon is almost negligible in networks of phase oscillators as its underlying mechanism is the modulation of the amplitude of those intermediary nodes between the remotely synchronized units. Our findings thus show the ubiquity and robustness of these states and bridge the gap from their recent observation in simple toy graphs to complex networks.

CROSS-DISCIPLINARY PHYSICS AND RELATED AREAS OF SCIENCE AND TECHNOLOGY: Worldwide Marine Transportation Network: Efficiency and Container Throughput

NASA Astrophysics Data System (ADS)

Deng, Wei-Bing; Guo, Long; Li, Wei; Cai, Xu

2009-11-01

Through empirical analysis of the global structure of the Worldwide Marine Transportation Network (WMTN), we find that the WMTN, a small-world network, exhibits an exponential-like degree distribution. We hereby investigate the efficiency of the WMTN by employing a simple definition. Compared with many other transportation networks, the WMTN possesses relatively low efficiency. Furthermore, by exploring the relationship between the topological structure and the container throughput, we find that strong correlations exist among the container throughout the degree and the clustering coefficient. Also, considering the navigational process that a ship travels in a real shipping line, we obtain that the weight of a seaport is proportional to the total probability contributed by all the passing shipping lines.

Layer 1 VPN services in distributed next-generation SONET/SDH networks with inverse multiplexing

NASA Astrophysics Data System (ADS)

Ghani, N.; Muthalaly, M. V.; Benhaddou, D.; Alanqar, W.

2006-05-01

Advances in next-generation SONET/SDH along with GMPLS control architectures have enabled many new service provisioning capabilities. In particular, a key services paradigm is the emergent Layer 1 virtual private network (L1 VPN) framework, which allows multiple clients to utilize a common physical infrastructure and provision their own 'virtualized' circuit-switched networks. This precludes expensive infrastructure builds and increases resource utilization for carriers. Along these lines, a novel L1 VPN services resource management scheme for next-generation SONET/SDH networks is proposed that fully leverages advanced virtual concatenation and inverse multiplexing features. Additionally, both centralized and distributed GMPLS-based implementations are also tabled to support the proposed L1 VPN services model. Detailed performance analysis results are presented along with avenues for future research.

Near real-time traffic routing

NASA Technical Reports Server (NTRS)

Yang, Chaowei (Inventor); Xie, Jibo (Inventor); Zhou, Bin (Inventor); Cao, Ying (Inventor)

2012-01-01

A near real-time physical transportation network routing system comprising: a traffic simulation computing grid and a dynamic traffic routing service computing grid. The traffic simulator produces traffic network travel time predictions for a physical transportation network using a traffic simulation model and common input data. The physical transportation network is divided into a multiple sections. Each section has a primary zone and a buffer zone. The traffic simulation computing grid includes multiple of traffic simulation computing nodes. The common input data includes static network characteristics, an origin-destination data table, dynamic traffic information data and historical traffic data. The dynamic traffic routing service computing grid includes multiple dynamic traffic routing computing nodes and generates traffic route(s) using the traffic network travel time predictions.

A Physics-driven Neural Networks-based Simulation System (PhyNNeSS) for multimodal interactive virtual environments involving nonlinear deformable objects

PubMed Central

De, Suvranu; Deo, Dhannanjay; Sankaranarayanan, Ganesh; Arikatla, Venkata S.

2012-01-01

Background While an update rate of 30 Hz is considered adequate for real time graphics, a much higher update rate of about 1 kHz is necessary for haptics. Physics-based modeling of deformable objects, especially when large nonlinear deformations and complex nonlinear material properties are involved, at these very high rates is one of the most challenging tasks in the development of real time simulation systems. While some specialized solutions exist, there is no general solution for arbitrary nonlinearities. Methods In this work we present PhyNNeSS - a Physics-driven Neural Networks-based Simulation System - to address this long-standing technical challenge. The first step is an off-line pre-computation step in which a database is generated by applying carefully prescribed displacements to each node of the finite element models of the deformable objects. In the next step, the data is condensed into a set of coefficients describing neurons of a Radial Basis Function network (RBFN). During real-time computation, these neural networks are used to reconstruct the deformation fields as well as the interaction forces. Results We present realistic simulation examples from interactive surgical simulation with real time force feedback. As an example, we have developed a deformable human stomach model and a Penrose-drain model used in the Fundamentals of Laparoscopic Surgery (FLS) training tool box. Conclusions A unique computational modeling system has been developed that is capable of simulating the response of nonlinear deformable objects in real time. The method distinguishes itself from previous efforts in that a systematic physics-based pre-computational step allows training of neural networks which may be used in real time simulations. We show, through careful error analysis, that the scheme is scalable, with the accuracy being controlled by the number of neurons used in the simulation. PhyNNeSS has been integrated into SoFMIS (Software Framework for Multimodal Interactive Simulation) for general use. PMID:22629108

Integrative Analysis of the Physical Transport Network into Australia.

PubMed

Cope, Robert C; Ross, Joshua V; Wittmann, Talia A; Prowse, Thomas A A; Cassey, Phillip

2016-01-01

Effective biosecurity is necessary to protect nations and their citizens from a variety of threats, including emerging infectious diseases, agricultural or environmental pests and pathogens, and illegal wildlife trade. The physical pathways by which these threats are transported internationally, predominantly shipping and air traffic, have undergone significant growth and changes in spatial distributions in recent decades. An understanding of the specific pathways and donor-traffic hotspots created by this integrated physical transport network is vital for the development of effective biosecurity strategies into the future. In this study, we analysed the physical transport network into Australia over the period 1999-2012. Seaborne and air traffic were weighted to calculate a "weighted cumulative impact" score for each source region worldwide, each year. High risk source regions, and those source regions that underwent substantial changes in risk over the study period, were determined. An overall risk ranking was calculated by integrating across all possible weighting combinations. The source regions having greatest overall physical connectedness with Australia were Singapore, which is a global transport hub, and the North Island of New Zealand, a close regional trading partner with Australia. Both those regions with large amounts of traffic across multiple vectors (e.g., Hong Kong), and those with high levels of traffic of only one type (e.g., Bali, Indonesia with respect to passenger flights), were represented among high risk source regions. These data provide a baseline model for the transport of individuals and commodities against which the effectiveness of biosecurity controls may be assessed, and are a valuable tool in the development of future biosecurity policy.

Integrative Analysis of the Physical Transport Network into Australia

PubMed Central

Cope, Robert C.; Ross, Joshua V.; Wittmann, Talia A.; Prowse, Thomas A. A.; Cassey, Phillip

2016-01-01

Effective biosecurity is necessary to protect nations and their citizens from a variety of threats, including emerging infectious diseases, agricultural or environmental pests and pathogens, and illegal wildlife trade. The physical pathways by which these threats are transported internationally, predominantly shipping and air traffic, have undergone significant growth and changes in spatial distributions in recent decades. An understanding of the specific pathways and donor-traffic hotspots created by this integrated physical transport network is vital for the development of effective biosecurity strategies into the future. In this study, we analysed the physical transport network into Australia over the period 1999–2012. Seaborne and air traffic were weighted to calculate a “weighted cumulative impact” score for each source region worldwide, each year. High risk source regions, and those source regions that underwent substantial changes in risk over the study period, were determined. An overall risk ranking was calculated by integrating across all possible weighting combinations. The source regions having greatest overall physical connectedness with Australia were Singapore, which is a global transport hub, and the North Island of New Zealand, a close regional trading partner with Australia. Both those regions with large amounts of traffic across multiple vectors (e.g., Hong Kong), and those with high levels of traffic of only one type (e.g., Bali, Indonesia with respect to passenger flights), were represented among high risk source regions. These data provide a baseline model for the transport of individuals and commodities against which the effectiveness of biosecurity controls may be assessed, and are a valuable tool in the development of future biosecurity policy. PMID:26881782

Recent Advances in Atmospheric, Solar-Terrestrial Physics and Space Weather From a North-South network of scientists [2006-2016] PART B : Results and Capacity Building

NASA Astrophysics Data System (ADS)

Amory-Mazaudier, C.; Fleury, R.; Petitdidier, M.; Soula, S.; Masson, F.; Davila, J.; Doherty, P.; Elias, A.; Gadimova, S.; Makela, J.; Nava, B.; Radicella, S.; Richardson, J.; Touzani, A.; Girgea Team

2017-12-01

This paper reviews scientific advances achieved by a North-South network between 2006 and 2016. These scientific advances concern solar terrestrial physics, atmospheric physics and space weather. This part B is devoted to the results and capacity building. Our network began in 1991, in solar terrestrial physics, by our participation in the two projects: International Equatorial Electrojet Year IEEY [1992-1993] and International Heliophysical Year IHY [2007-2009]. These two projects were mainly focused on the equatorial ionosphere in Africa. In Atmospheric physics our research focused on gravity waves in the framework of the African Multidisciplinary Monsoon Analysis project n°1 [2005-2009 ], on hydrology in the Congo river basin and on lightning in Central Africa, the most lightning part of the world. In Vietnam the study of a broad climate data base highlighted global warming. In space weather, our results essentially concern the impact of solar events on global navigation satellite system GNSS and on the effects of solar events on the circulation of electric currents in the earth (GIC). This research began in the framework of the international space weather initiative project ISWI [2010-2012]. Finally, all these scientific projects have enabled young scientists from the South to publish original results and to obtain positions in their countries. These projects have also crossed disciplinary boundaries and defined a more diversified education which led to the training of specialists in a specific field with knowledge of related scientific fields.

Systems-level analysis of risk genes reveals the modular nature of schizophrenia.

PubMed

Liu, Jiewei; Li, Ming; Luo, Xiong-Jian; Su, Bing

2018-05-19

Schizophrenia (SCZ) is a complex mental disorder with high heritability. Genetic studies (especially recent genome-wide association studies) have identified many risk genes for schizophrenia. However, the physical interactions among the proteins encoded by schizophrenia risk genes remain elusive and it is not known whether the identified risk genes converge on common molecular networks or pathways. Here we systematically investigated the network characteristics of schizophrenia risk genes using the high-confidence protein-protein interactions (PPI) from the human interactome. We found that schizophrenia risk genes encode a densely interconnected PPI network (P = 4.15 × 10 -31 ). Compared with the background genes, the schizophrenia risk genes in the interactome have significantly higher degree (P = 5.39 × 10 -11 ), closeness centrality (P = 7.56 × 10 -11 ), betweeness centrality (P = 1.29 × 10 -11 ), clustering coefficient (P = 2.22 × 10 -2 ), and shorter average shortest path length (P = 7.56 × 10 -11 ). Based on the densely interconnected PPI network, we identified 48 hub genes and 4 modules formed by highly interconnected schizophrenia genes. We showed that the proteins encoded by schizophrenia hub genes have significantly more direct physical interactions. Gene ontology (GO) analysis revealed that cell adhesion, cell cycle, immune system response, and GABR-receptor complex categories were enriched in the modules formed by highly interconnected schizophrenia risk genes. Our study reveals that schizophrenia risk genes encode a densely interconnected molecular network and demonstrates the modular nature of schizophrenia. Copyright © 2018 Elsevier B.V. All rights reserved.

Topic-Aware Physical Activity Propagation in a Health Social Network

PubMed Central

Phan, Nhathai; Ebrahimi, Javid; Kil, Dave; Piniewski, Brigitte; Dou, Dejing

2016-01-01

Modeling physical activity propagation, such as physical exercise level and intensity, is the key to preventing the conduct that can lead to obesity; it can also help spread wellness behavior in a social network. PMID:27087794

What Motivates Young Adults to Talk About Physical Activity on Social Network Sites?

PubMed Central

Campo, Shelly; Yang, Jingzhen; Eckler, Petya; Snetselaar, Linda; Janz, Kathleen; Leary, Emily

2017-01-01

Background Electronic word-of-mouth on social network sites has been used successfully in marketing. In social marketing, electronic word-of-mouth about products as health behaviors has the potential to be more effective and reach more young adults than health education through traditional mass media. However, little is known about what motivates people to actively initiate electronic word-of-mouth about health behaviors on their personal pages or profiles on social network sites, thus potentially reaching all their contacts on those sites. Objective This study filled the gap by applying a marketing theoretical model to explore the factors associated with electronic word-of-mouth on social network sites about leisure-time physical activity. Methods A Web survey link was sent to undergraduate students at one of the Midwestern universities and 439 of them completed the survey. Results The average age of the 439 participants was 19 years (SD=1 year, range: 18-24). Results suggested that emotional engagement with leisure-time physical activity (ie, affective involvement in leisure-time physical activity) predicted providing relevant opinions or information on social network sites. Social network site users who perceived stronger ties with all their contacts were more likely to provide and seek leisure-time physical activity opinions and information. People who provided leisure-time physical activity opinions and information were more likely to seek opinions and information, and people who forwarded information about leisure-time physical activity were more likely to chat about it. Conclusions This study shed light on the application of the electronic word-of-mouth theoretical framework in promoting health behaviors. The findings can also guide the development of future social marketing interventions using social network sites to promote leisure-time physical activity. PMID:28642215

Detailed temporal structure of communication networks in groups of songbirds.

PubMed

Stowell, Dan; Gill, Lisa; Clayton, David

2016-06-01

Animals in groups often exchange calls, in patterns whose temporal structure may be influenced by contextual factors such as physical location and the social network structure of the group. We introduce a model-based analysis for temporal patterns of animal call timing, originally developed for networks of firing neurons. This has advantages over cross-correlation analysis in that it can correctly handle common-cause confounds and provides a generative model of call patterns with explicit parameters for the influences between individuals. It also has advantages over standard Markovian analysis in that it incorporates detailed temporal interactions which affect timing as well as sequencing of calls. Further, a fitted model can be used to generate novel synthetic call sequences. We apply the method to calls recorded from groups of domesticated zebra finch (Taeniopygia guttata) individuals. We find that the communication network in these groups has stable structure that persists from one day to the next, and that 'kernels' reflecting the temporal range of influence have a characteristic structure for a calling individual's effect on itself, its partner and on others in the group. We further find characteristic patterns of influences by call type as well as by individual. © 2016 The Authors.

Analysis of surface-water data network in Kansas for effectiveness in providing regional streamflow information; with a section on theory and application of generalized least squares

USGS Publications Warehouse

Medina, K.D.; Tasker, Gary D.

1987-01-01

This report documents the results of an analysis of the surface-water data network in Kansas for its effectiveness in providing regional streamflow information. The network was analyzed using generalized least squares regression. The correlation and time-sampling error of the streamflow characteristic are considered in the generalized least squares method. Unregulated medium-, low-, and high-flow characteristics were selected to be representative of the regional information that can be obtained from streamflow-gaging-station records for use in evaluating the effectiveness of continuing the present network stations, discontinuing some stations, and (or) adding new stations. The analysis used streamflow records for all currently operated stations that were not affected by regulation and for discontinued stations for which unregulated flow characteristics, as well as physical and climatic characteristics, were available. The State was divided into three network areas, western, northeastern, and southeastern Kansas, and analysis was made for the three streamflow characteristics in each area, using three planning horizons. The analysis showed that the maximum reduction of sampling mean-square error for each cost level could be obtained by adding new stations and discontinuing some current network stations. Large reductions in sampling mean-square error for low-flow information could be achieved in all three network areas, the reduction in western Kansas being the most dramatic. The addition of new stations would be most beneficial for mean-flow information in western Kansas. The reduction of sampling mean-square error for high-flow information would benefit most from the addition of new stations in western Kansas. Southeastern Kansas showed the smallest error reduction in high-flow information. A comparison among all three network areas indicated that funding resources could be most effectively used by discontinuing more stations in northeastern and southeastern Kansas and establishing more new stations in western Kansas.

News Competition: Physics Olympiad hits Thailand Report: Institute carries out survey into maths in physics at university Event: A day for everyone teaching physics Conference: Welsh conference celebrates birthday Schools: Researchers in Residence scheme set to close Teachers: A day for new physics teachers Social: Network combines fun and physics Forthcoming events

NASA Astrophysics Data System (ADS)

2011-09-01

Competition: Physics Olympiad hits Thailand Report: Institute carries out survey into maths in physics at university Event: A day for everyone teaching physics Conference: Welsh conference celebrates birthday Schools: Researchers in Residence scheme set to close Teachers: A day for new physics teachers Social: Network combines fun and physics Forthcoming events

Resolution-Enhanced Harmonic and Interharmonic Measurement for Power Quality Analysis in Cyber-Physical Energy System.

PubMed

Liu, Yanchi; Wang, Xue; Liu, Youda; Cui, Sujin

2016-06-27

Power quality analysis issues, especially the measurement of harmonic and interharmonic in cyber-physical energy systems, are addressed in this paper. As new situations are introduced to the power system, the impact of electric vehicles, distributed generation and renewable energy has introduced extra demands to distributed sensors, waveform-level information and power quality data analytics. Harmonics and interharmonics, as the most significant disturbances, require carefully designed detection methods for an accurate measurement of electric loads whose information is crucial to subsequent analyzing and control. This paper gives a detailed description of the power quality analysis framework in networked environment and presents a fast and resolution-enhanced method for harmonic and interharmonic measurement. The proposed method first extracts harmonic and interharmonic components efficiently using the single-channel version of Robust Independent Component Analysis (RobustICA), then estimates the high-resolution frequency from three discrete Fourier transform (DFT) samples with little additional computation, and finally computes the amplitudes and phases with the adaptive linear neuron network. The experiments show that the proposed method is time-efficient and leads to a better accuracy of the simulated and experimental signals in the presence of noise and fundamental frequency deviation, thus providing a deeper insight into the (inter)harmonic sources or even the whole system.

Resolution-Enhanced Harmonic and Interharmonic Measurement for Power Quality Analysis in Cyber-Physical Energy System

PubMed Central

Liu, Yanchi; Wang, Xue; Liu, Youda; Cui, Sujin

2016-01-01

Power quality analysis issues, especially the measurement of harmonic and interharmonic in cyber-physical energy systems, are addressed in this paper. As new situations are introduced to the power system, the impact of electric vehicles, distributed generation and renewable energy has introduced extra demands to distributed sensors, waveform-level information and power quality data analytics. Harmonics and interharmonics, as the most significant disturbances, require carefully designed detection methods for an accurate measurement of electric loads whose information is crucial to subsequent analyzing and control. This paper gives a detailed description of the power quality analysis framework in networked environment and presents a fast and resolution-enhanced method for harmonic and interharmonic measurement. The proposed method first extracts harmonic and interharmonic components efficiently using the single-channel version of Robust Independent Component Analysis (RobustICA), then estimates the high-resolution frequency from three discrete Fourier transform (DFT) samples with little additional computation, and finally computes the amplitudes and phases with the adaptive linear neuron network. The experiments show that the proposed method is time-efficient and leads to a better accuracy of the simulated and experimental signals in the presence of noise and fundamental frequency deviation, thus providing a deeper insight into the (inter)harmonic sources or even the whole system. PMID:27355946

Noncoherent Physical-Layer Network Coding with FSK Modulation: Relay Receiver Design Issues

DTIC Science & Technology

2011-03-01

222 IEEE TRANSACTIONS ON COMMUNICATIONS, VOL. 59, NO. 9, SEPTEMBER 2011 2595 Noncoherent Physical-Layer Network Coding with FSK Modulation: Relay... noncoherent reception, channel estima- tion. I. INTRODUCTION IN the two-way relay channel (TWRC), a pair of sourceterminals exchange information...2011 4. TITLE AND SUBTITLE Noncoherent Physical-Layer Network Coding with FSK Modulation:Relay Receiver Design Issues 5a. CONTRACT NUMBER 5b

Delay Analysis of Car-to-Car Reliable Data Delivery Strategies Based on Data Mulling with Network Coding

NASA Astrophysics Data System (ADS)

Park, Joon-Sang; Lee, Uichin; Oh, Soon Young; Gerla, Mario; Lun, Desmond Siumen; Ro, Won Woo; Park, Joonseok

Vehicular ad hoc networks (VANET) aims to enhance vehicle navigation safety by providing an early warning system: any chance of accidents is informed through the wireless communication between vehicles. For the warning system to work, it is crucial that safety messages be reliably delivered to the target vehicles in a timely manner and thus reliable and timely data dissemination service is the key building block of VANET. Data mulling technique combined with three strategies, network codeing, erasure coding and repetition coding, is proposed for the reliable and timely data dissemination service. Particularly, vehicles in the opposite direction on a highway are exploited as data mules, mobile nodes physically delivering data to destinations, to overcome intermittent network connectivity cause by sparse vehicle traffic. Using analytic models, we show that in such a highway data mulling scenario the network coding based strategy outperforms erasure coding and repetition based strategies.

Universal properties of mythological networks

NASA Astrophysics Data System (ADS)

Mac Carron, Pádraig; Kenna, Ralph

2012-07-01

As in statistical physics, the concept of universality plays an important, albeit qualitative, role in the field of comparative mythology. Here we apply statistical mechanical tools to analyse the networks underlying three iconic mythological narratives with a view to identifying common and distinguishing quantitative features. Of the three narratives, an Anglo-Saxon and a Greek text are mostly believed by antiquarians to be partly historically based while the third, an Irish epic, is often considered to be fictional. Here we use network analysis in an attempt to discriminate real from imaginary social networks and place mythological narratives on the spectrum between them. This suggests that the perceived artificiality of the Irish narrative can be traced back to anomalous features associated with six characters. Speculating that these are amalgams of several entities or proxies, renders the plausibility of the Irish text comparable to the others from a network-theoretic point of view.

SNM-DAT: Simulation of a heterogeneous network for nuclear border security

NASA Astrophysics Data System (ADS)

Nemzek, R.; Kenyon, G.; Koehler, A.; Lee, D. M.; Priedhorsky, W.; Raby, E. Y.

2007-08-01

We approach the problem of detecting Special Nuclear Material (SNM) smuggling across open borders by modeling a heterogeneous sensor network using an agent-based simulation. Our simulation SNM Data Analysis Tool (SNM-DAT) combines fixed seismic, metal, and radiation detectors with a mobile gamma spectrometer. Decision making within the simulation determines threat levels by combined signatures. The spectrometer is a limited-availability asset, and is only deployed for substantial threats. "Crossers" can be benign or carrying shielded SNM. Signatures and sensors are physics based, allowing us to model realistic sensor networks. The heterogeneous network provides great gains in detection efficiency compared to a radiation-only system. We can improve the simulation through better sensor and terrain models, additional signatures, and crossers that mimic actual trans-border traffic. We expect further gains in our ability to design sensor networks as we learn the emergent properties of heterogeneous detection, and potential adversary responses.

Women in physics in France

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

Pierron-Bohnes, Véronique

We present six associations and entities working in France on issues of women in physics: the Women and Physics Commission, French Physical Society; Women in Nuclear (WiN) France; Women and Science Association; Mission for the Place of Women at CNRS; Parity, Diversity, and Women Network, CEA; and the Network of University Equality-Diversity Representatives.

Brown spider monkeys (Ateles hybridus): a model for differentiating the role of social networks and physical contact on parasite transmission dynamics

PubMed Central

Rimbach, Rebecca; Bisanzio, Donal; Galvis, Nelson; Link, Andrés; Di Fiore, Anthony; Gillespie, Thomas R.

2015-01-01

Elevated risk of disease transmission is considered a major cost of sociality, although empirical evidence supporting this idea remains scant. Variation in spatial cohesion and the occurrence of social interactions may have profound implications for patterns of interindividual parasite transmission. We used a social network approach to shed light on the importance of different aspects of group-living (i.e. within-group associations versus physical contact) on patterns of parasitism in a neotropical primate, the brown spider monkey (Ateles hybridus), which exhibits a high degree of fission–fusion subgrouping. We used daily subgroup composition records to create a ‘proximity’ network, and built a separate ‘contact’ network using social interactions involving physical contact. In the proximity network, connectivity between individuals was homogeneous, whereas the contact network highlighted high between-individual variation in the extent to which animals had physical contact with others, which correlated with an individual's age and sex. The gastrointestinal parasite species richness of highly connected individuals was greater than that of less connected individuals in the contact network, but not in the proximity network. Our findings suggest that among brown spider monkeys, physical contact impacts the spread of several common parasites and supports the idea that pathogen transmission is one cost associated with social contact. PMID:25870396

Brown spider monkeys (Ateles hybridus): a model for differentiating the role of social networks and physical contact on parasite transmission dynamics.

PubMed

Rimbach, Rebecca; Bisanzio, Donal; Galvis, Nelson; Link, Andrés; Di Fiore, Anthony; Gillespie, Thomas R

2015-05-26

Elevated risk of disease transmission is considered a major cost of sociality, although empirical evidence supporting this idea remains scant. Variation in spatial cohesion and the occurrence of social interactions may have profound implications for patterns of interindividual parasite transmission. We used a social network approach to shed light on the importance of different aspects of group-living (i.e. within-group associations versus physical contact) on patterns of parasitism in a neotropical primate, the brown spider monkey (Ateles hybridus), which exhibits a high degree of fission-fusion subgrouping. We used daily subgroup composition records to create a 'proximity' network, and built a separate 'contact' network using social interactions involving physical contact. In the proximity network, connectivity between individuals was homogeneous, whereas the contact network highlighted high between-individual variation in the extent to which animals had physical contact with others, which correlated with an individual's age and sex. The gastrointestinal parasite species richness of highly connected individuals was greater than that of less connected individuals in the contact network, but not in the proximity network. Our findings suggest that among brown spider monkeys, physical contact impacts the spread of several common parasites and supports the idea that pathogen transmission is one cost associated with social contact. © 2015 The Author(s) Published by the Royal Society. All rights reserved.

#LancerHealth: Using Twitter and Instagram as a tool in a campus wide health promotion initiative

PubMed Central

Santarossa, Sara; Woodruff, Sarah J.

2018-01-01

The present study aimed to explore using popular technology that people already have/use as a health promotion tool, in a campus wide social media health promotion initiative, entitled #LancerHealth. During a two-week period the university community was asked to share photos on Twitter and Instagram of What does being healthy on campus look like to you?, while tagging the image with #LancerHealth. All publically tagged media was collected using the Netlytic software and analysed. Text analysis (N=234 records, Twitter; N=141 records, Instagram) revealed that the majority of the conversation was positive and focused on health and the university. Social network analysis, based on five network properties, showed a small network with little interaction. Lastly, photo coding analysis (N=71 unique image) indicated that the majority of the shared images were of physical activity (52%) and on campus (80%). Further research into this area is warranted. Significance for public healthAs digital media continues to become a popular tool among both public health organizations and those in academia, it is important to understand how, why, and which platforms individuals are using in regards to their health. This campus wide, social media health promotion initiative found that people will use popular social networking sites like Twitter and Instagram to share their healthy behaviours. Online social networks, created through social networking sites, can play a role in social diffusion of public health information and health behaviours. In this study, however, social network analysis revealed that there needs to be influential and highly connected individuals sharing information to generate social diffusion. This study can help guide future public health research in the area of social media and its potential influence on health promotion. PMID:29780763

Engineering Online and In-person Social Networks for Physical Activity: A Randomized Trial

PubMed Central

Rovniak, Liza S.; Kong, Lan; Hovell, Melbourne F.; Ding, Ding; Sallis, James F.; Ray, Chester A.; Kraschnewski, Jennifer L.; Matthews, Stephen A.; Kiser, Elizabeth; Chinchilli, Vernon M.; George, Daniel R.; Sciamanna, Christopher N.

2016-01-01

Background Social networks can influence physical activity, but little is known about how best to engineer online and in-person social networks to increase activity. Purpose To conduct a randomized trial based on the Social Networks for Activity Promotion model to assess the incremental contributions of different procedures for building social networks on objectively-measured outcomes. Methods Physically inactive adults (n = 308, age, 50.3 (SD = 8.3) years, 38.3% male, 83.4% overweight/obese) were randomized to 1 of 3 groups. The Promotion group evaluated the effects of weekly emailed tips emphasizing social network interactions for walking (e.g., encouragement, informational support); the Activity group evaluated the incremental effect of adding an evidence-based online fitness walking intervention to the weekly tips; and the Social Networks group evaluated the additional incremental effect of providing access to an online networking site for walking, and prompting walking/activity across diverse settings. The primary outcome was mean change in accelerometer-measured moderate-to-vigorous physical activity (MVPA), assessed at 3 and 9 months from baseline. Results Participants increased their MVPA by 21.0 mins/week, 95% CI [5.9, 36.1], p = .005, at 3 months, and this change was sustained at 9 months, with no between-group differences. Conclusions Although the structure of procedures for targeting social networks varied across intervention groups, the functional effect of these procedures on physical activity was similar. Future research should evaluate if more powerful reinforcers improve the effects of social network interventions. Trial Registration Number NCT01142804 PMID:27405724

Optimal information dissemination strategy to promote preventive behaviors in multilayer epidemic networks.

PubMed

Shakeri, Heman; Sahneh, Faryad Darabi; Scoglio, Caterina; Poggi-Corradini, Pietro; Preciado, Victor M

2015-06-01

Launching a prevention campaign to contain the spread of infection requires substantial financial investments; therefore, a trade-off exists between suppressing the epidemic and containing costs. Information exchange among individuals can occur as physical contacts (e.g., word of mouth, gatherings), which provide inherent possibilities of disease transmission, and non-physical contacts (e.g., email, social networks), through which information can be transmitted but the infection cannot be transmitted. Contact network (CN) incorporates physical contacts, and the information dissemination network (IDN) represents non-physical contacts, thereby generating a multilayer network structure. Inherent differences between these two layers cause alerting through CN to be more effective but more expensive than IDN. The constraint for an epidemic to die out derived from a nonlinear Perron-Frobenius problem that was transformed into a semi-definite matrix inequality and served as a constraint for a convex optimization problem. This method guarantees a dying-out epidemic by choosing the best nodes for adopting preventive behaviors with minimum monetary resources. Various numerical simulations with network models and a real-world social network validate our method.

Revealing physical interaction networks from statistics of collective dynamics

PubMed Central

Nitzan, Mor; Casadiego, Jose; Timme, Marc

2017-01-01

Revealing physical interactions in complex systems from observed collective dynamics constitutes a fundamental inverse problem in science. Current reconstruction methods require access to a system’s model or dynamical data at a level of detail often not available. We exploit changes in invariant measures, in particular distributions of sampled states of the system in response to driving signals, and use compressed sensing to reveal physical interaction networks. Dynamical observations following driving suffice to infer physical connectivity even if they are temporally disordered, are acquired at large sampling intervals, and stem from different experiments. Testing various nonlinear dynamic processes emerging on artificial and real network topologies indicates high reconstruction quality for existence as well as type of interactions. These results advance our ability to reveal physical interaction networks in complex synthetic and natural systems. PMID:28246630

Networking—a statistical physics perspective

NASA Astrophysics Data System (ADS)

Yeung, Chi Ho; Saad, David

2013-03-01

Networking encompasses a variety of tasks related to the communication of information on networks; it has a substantial economic and societal impact on a broad range of areas including transportation systems, wired and wireless communications and a range of Internet applications. As transportation and communication networks become increasingly more complex, the ever increasing demand for congestion control, higher traffic capacity, quality of service, robustness and reduced energy consumption requires new tools and methods to meet these conflicting requirements. The new methodology should serve for gaining better understanding of the properties of networking systems at the macroscopic level, as well as for the development of new principled optimization and management algorithms at the microscopic level. Methods of statistical physics seem best placed to provide new approaches as they have been developed specifically to deal with nonlinear large-scale systems. This review aims at presenting an overview of tools and methods that have been developed within the statistical physics community and that can be readily applied to address the emerging problems in networking. These include diffusion processes, methods from disordered systems and polymer physics, probabilistic inference, which have direct relevance to network routing, file and frequency distribution, the exploration of network structures and vulnerability, and various other practical networking applications.

Extending Topological Approaches to Microseismic-Derived 3D Fracture Networks

NASA Astrophysics Data System (ADS)

Urbancic, T.; Bosman, K.; Baig, A.; Ardakani, E. P.

2017-12-01

Fracture topology is important for determining the fluid-flow characteristics of a fracture network. In most unconventional petroleum applications, flow through subsurface fracture networks is the primary source of production, as matrix permeability is often in the nanodarcy range. Typical models of reservoir discrete fracture networks (DFNs) are constructed using fracture orientation and average spacing, without consideration of how the connectivity of the fracture network aids the percolation of hydrocarbons back to the wellbore. Topological approaches to DFN characterization have been developed and extensively used in analysis of outcrop data and aerial photography. Such study of the surface expression of fracture networks is straight-forward, and the physical form of the observed fractures is directly reflected in the parameters used to describe the topology. However, this analysis largely ignores the three-dimensional nature of natural fracture networks, which is difficult to define accurately in geological studies. SMTI analysis of microseismic event distributions can produce DFNs, where each event is represented by a penny-shaped crack with radius and orientation determined from the frequency content of the waveforms and assessment of the slip instability of the potential fracture planes, respectively. Analysis of the geometric relationships between a set of fractures can provide details of intersections between fractures, and thus the topological characteristics of the fracture network. Extension of existing 2D topology approaches to 3D fracture networks is non-trivial. In the 2D case, a fracture intersection is a single point (node), and branches connect adjacent nodes along fractures. For the 3D case, intersection "nodes" become lines, and connecting nodes to find branches becomes more complicated. There are several parameters defined in 2D topology to quantify the connectivity of the fracture network. Equivalent quantities must be defined and calibrated for the 3D case to provide a meaningful measurement of fracture network connectivity. We have developed an approach to analyze the topology of 3D fracture networks derived from microseismic moment tensors. We illustrate the utility of the approach with applications to example datasets from hydraulic fracturing completions.

Mapping the Evolution of Scientific Fields

PubMed Central

Herrera, Mark; Roberts, David C.; Gulbahce, Natali

2010-01-01

Despite the apparent cross-disciplinary interactions among scientific fields, a formal description of their evolution is lacking. Here we describe a novel approach to study the dynamics and evolution of scientific fields using a network-based analysis. We build an idea network consisting of American Physical Society Physics and Astronomy Classification Scheme (PACS) numbers as nodes representing scientific concepts. Two PACS numbers are linked if there exist publications that reference them simultaneously. We locate scientific fields using a community finding algorithm, and describe the time evolution of these fields over the course of 1985–2006. The communities we identify map to known scientific fields, and their age depends on their size and activity. We expect our approach to quantifying the evolution of ideas to be relevant for making predictions about the future of science and thus help to guide its development. PMID:20463949

Mapping the evolution of scientific fields.

PubMed

Herrera, Mark; Roberts, David C; Gulbahce, Natali

2010-05-04

Despite the apparent cross-disciplinary interactions among scientific fields, a formal description of their evolution is lacking. Here we describe a novel approach to study the dynamics and evolution of scientific fields using a network-based analysis. We build an idea network consisting of American Physical Society Physics and Astronomy Classification Scheme (PACS) numbers as nodes representing scientific concepts. Two PACS numbers are linked if there exist publications that reference them simultaneously. We locate scientific fields using a community finding algorithm, and describe the time evolution of these fields over the course of 1985-2006. The communities we identify map to known scientific fields, and their age depends on their size and activity. We expect our approach to quantifying the evolution of ideas to be relevant for making predictions about the future of science and thus help to guide its development.

CCSDS Advanced Orbiting Systems Virtual Channel Access Service for QoS MACHETE Model

NASA Technical Reports Server (NTRS)

Jennings, Esther H.; Segui, John S.

2011-01-01

To support various communications requirements imposed by different missions, interplanetary communication protocols need to be designed, validated, and evaluated carefully. Multimission Advanced Communications Hybrid Environment for Test and Evaluation (MACHETE), described in "Simulator of Space Communication Networks" (NPO-41373), NASA Tech Briefs, Vol. 29, No. 8 (August 2005), p. 44, combines various tools for simulation and performance analysis of space networks. The MACHETE environment supports orbital analysis, link budget analysis, communications network simulations, and hardware-in-the-loop testing. By building abstract behavioral models of network protocols, one can validate performance after identifying the appropriate metrics of interest. The innovators have extended the MACHETE model library to include a generic link-layer Virtual Channel (VC) model supporting quality-of-service (QoS) controls based on IP streams. The main purpose of this generic Virtual Channel model addition was to interface fine-grain flow-based QoS (quality of service) between the network and MAC layers of the QualNet simulator, a commercial component of MACHETE. This software model adds the capability of mapping IP streams, based on header fields, to virtual channel numbers, allowing extended QoS handling at link layer. This feature further refines the QoS v existing at the network layer. QoS at the network layer (e.g. diffserv) supports few QoS classes, so data from one class will be aggregated together; differentiating between flows internal to a class/priority is not supported. By adding QoS classification capability between network and MAC layers through VC, one maps multiple VCs onto the same physical link. Users then specify different VC weights, and different queuing and scheduling policies at the link layer. This VC model supports system performance analysis of various virtual channel link-layer QoS queuing schemes independent of the network-layer QoS systems.

A Scalable Approach for Discovering Conserved Active Subnetworks across Species

PubMed Central

Verfaillie, Catherine M.; Hu, Wei-Shou; Myers, Chad L.

2010-01-01

Overlaying differential changes in gene expression on protein interaction networks has proven to be a useful approach to interpreting the cell's dynamic response to a changing environment. Despite successes in finding active subnetworks in the context of a single species, the idea of overlaying lists of differentially expressed genes on networks has not yet been extended to support the analysis of multiple species' interaction networks. To address this problem, we designed a scalable, cross-species network search algorithm, neXus (Network - cross(X)-species - Search), that discovers conserved, active subnetworks based on parallel differential expression studies in multiple species. Our approach leverages functional linkage networks, which provide more comprehensive coverage of functional relationships than physical interaction networks by combining heterogeneous types of genomic data. We applied our cross-species approach to identify conserved modules that are differentially active in stem cells relative to differentiated cells based on parallel gene expression studies and functional linkage networks from mouse and human. We find hundreds of conserved active subnetworks enriched for stem cell-associated functions such as cell cycle, DNA repair, and chromatin modification processes. Using a variation of this approach, we also find a number of species-specific networks, which likely reflect mechanisms of stem cell function that have diverged between mouse and human. We assess the statistical significance of the subnetworks by comparing them with subnetworks discovered on random permutations of the differential expression data. We also describe several case examples that illustrate the utility of comparative analysis of active subnetworks. PMID:21170309

Geographies of an Online Social Network.

PubMed

Lengyel, Balázs; Varga, Attila; Ságvári, Bence; Jakobi, Ákos; Kertész, János

2015-01-01

How is online social media activity structured in the geographical space? Recent studies have shown that in spite of earlier visions about the "death of distance", physical proximity is still a major factor in social tie formation and maintenance in virtual social networks. Yet, it is unclear, what are the characteristics of the distance dependence in online social networks. In order to explore this issue the complete network of the former major Hungarian online social network is analyzed. We find that the distance dependence is weaker for the online social network ties than what was found earlier for phone communication networks. For a further analysis we introduced a coarser granularity: We identified the settlements with the nodes of a network and assigned two kinds of weights to the links between them. When the weights are proportional to the number of contacts we observed weakly formed, but spatially based modules resemble to the borders of macro-regions, the highest level of regional administration in the country. If the weights are defined relative to an uncorrelated null model, the next level of administrative regions, counties are reflected.

Geographies of an Online Social Network

PubMed Central

Lengyel, Balázs; Varga, Attila; Ságvári, Bence; Jakobi, Ákos; Kertész, János

2015-01-01

How is online social media activity structured in the geographical space? Recent studies have shown that in spite of earlier visions about the “death of distance”, physical proximity is still a major factor in social tie formation and maintenance in virtual social networks. Yet, it is unclear, what are the characteristics of the distance dependence in online social networks. In order to explore this issue the complete network of the former major Hungarian online social network is analyzed. We find that the distance dependence is weaker for the online social network ties than what was found earlier for phone communication networks. For a further analysis we introduced a coarser granularity: We identified the settlements with the nodes of a network and assigned two kinds of weights to the links between them. When the weights are proportional to the number of contacts we observed weakly formed, but spatially based modules resemble to the borders of macro-regions, the highest level of regional administration in the country. If the weights are defined relative to an uncorrelated null model, the next level of administrative regions, counties are reflected. PMID:26359668

Security Analysis of Smart Grid Cyber Physical Infrastructures Using Modeling and Game Theoretic Simulation

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

Abercrombie, Robert K; Sheldon, Frederick T.

Cyber physical computing infrastructures typically consist of a number of sites are interconnected. Its operation critically depends both on cyber components and physical components. Both types of components are subject to attacks of different kinds and frequencies, which must be accounted for the initial provisioning and subsequent operation of the infrastructure via information security analysis. Information security analysis can be performed using game theory implemented in dynamic Agent Based Game Theoretic (ABGT) simulations. Such simulations can be verified with the results from game theory analysis and further used to explore larger scale, real world scenarios involving multiple attackers, defenders, andmore » information assets. We concentrated our analysis on the electric sector failure scenarios and impact analyses by the NESCOR Working Group Study, From the Section 5 electric sector representative failure scenarios; we extracted the four generic failure scenarios and grouped them into three specific threat categories (confidentiality, integrity, and availability) to the system. These specific failure scenarios serve as a demonstration of our simulation. The analysis using our ABGT simulation demonstrates how to model the electric sector functional domain using a set of rationalized game theoretic rules decomposed from the failure scenarios in terms of how those scenarios might impact the cyber physical infrastructure network with respect to CIA.« less

Anatomy of triply-periodic network assemblies: characterizing skeletal and inter-domain surface geometry of block copolymer gyroids.

PubMed

Prasad, Ishan; Jinnai, Hiroshi; Ho, Rong-Ming; Thomas, Edwin L; Grason, Gregory M

2018-05-09

Triply-periodic networks (TPNs), like the well-known gyroid and diamond network phases, abound in soft matter assemblies, from block copolymers (BCPs), lyotropic liquid crystals and surfactants to functional architectures in biology. While TPNs are, in reality, volume-filling patterns of spatially-varying molecular composition, physical and structural models most often reduce their structure to lower-dimensional geometric objects: the 2D interfaces between chemical domains; and the 1D skeletons that thread through inter-connected, tubular domains. These lower-dimensional structures provide a useful basis of comparison to idealized geometries based on triply-periodic minimal, or constant-mean curvature surfaces, and shed important light on the spatially heterogeneous packing of molecular constituents that form the networks. Here, we propose a simple, efficient and flexible method to extract a 1D skeleton from 3D volume composition data of self-assembled networks. We apply this method to both self-consistent field theory predictions as well as experimental electron microtomography reconstructions of the double-gyroid phase of an ABA triblock copolymer. We further demonstrate how the analysis of 1D skeleton, 2D inter-domain surfaces, and combinations therefore, provide physical and structural insight into TPNs, across multiple length scales. Specifically, we propose and compare simple measures of network chirality as well as domain thickness, and analyze their spatial and statistical distributions in both ideal (theoretical) and non-ideal (experimental) double gyroid assemblies.

Wellness Partners: Design and Evaluation of a Web-Based Physical Activity Diary with Social Gaming Features for Adults

PubMed Central

Wang, Hua; Spruijt-Metz, Donna; Jordan-Marsh, Maryalice; Valente, Thomas William

2013-01-01

Background The United States is currently in an age of obesity and inactivity despite increasing public awareness and scientific knowledge of detrimental long-term health effects of this lifestyle. Behavior-tracking diaries offer an effective strategy for physical activity adherence and weight management. Furthermore, Web-based physical activity diaries can engage meaningful partners in people’s social networks through fun online gaming interactions and generate motivational mechanisms for effective behavioral change and positive health outcomes. Objective Wellness Partners (WP) is a Web-based intervention in the form of a physical activity diary with social networking and game features. Two versions were designed and developed for the purpose of this study—“Diary” only and “Diary+Game”. The objectives of this study included pilot testing the research process of this intervention design, implementation, evaluation, and exploring the effectiveness of social gaming features on adult participants’ physical activity and anthropometric measures. Methods We conducted a field experiment with randomized crossover design. Assessments occurred at baseline, first follow-up (FU, 5-8 weeks after using one version of WP), and second FU (5-8 weeks of using the other version of WP). In the control condition, participants started with the “Diary” version of WP while in the experimental condition, participants started with the “Diary+Game” version of WP. A total of 54 adults (egos) ages 44-88, and their family and friends (alters) ages 17-69 participated in the study in ego-network groups. Both egos and their alters completed online surveys about their exercise habits. In addition, egos completed anthropometric measurements of BMI, fat percentage, and fat mass by bioimpedance. Results From October 2009 to May 2010, flyers, emails, and Web advertisements yielded 335 volunteers who were screened. Rolling recruitment resulted in enrollment of 142 qualified participants in 54 ego-network groups, which were randomly assigned to a study condition. The final analytic sample included 87 individuals from 41 groups. Data were collected from December 2009 to August 2010, and data analysis was completed in 2011. Overall, the participants were given access to the intervention for 10-13 weeks. Statistical analysis suggested an increase in self-reported exercise frequency (mean days per week) from baseline (2.57, SD 1.92) to first FU (3.21, SD 1.74) in both conditions. Stronger effects were seen in the condition where Diary+Game was played first, especially in network groups with larger age variation between the alters and egos. Overall, the decrease in egos’ BMI was statistically significant from baseline to first FU, with greater decrease for those in the Diary+Game first condition (-0.26 vs -0.16 in the Diary first condition). Conclusions The Wellness Partners program increased physical activity among participants and resulted in health benefits among the egos. Web-based diary interventions designed with social gaming features hold potential to promote active lifestyles for middle-age adults and people in their social networks. PMID:23611986

Building a Prototype of LHC Analysis Oriented Computing Centers

NASA Astrophysics Data System (ADS)

Bagliesi, G.; Boccali, T.; Della Ricca, G.; Donvito, G.; Paganoni, M.

2012-12-01

A Consortium between four LHC Computing Centers (Bari, Milano, Pisa and Trieste) has been formed in 2010 to prototype Analysis-oriented facilities for CMS data analysis, profiting from a grant from the Italian Ministry of Research. The Consortium aims to realize an ad-hoc infrastructure to ease the analysis activities on the huge data set collected at the LHC Collider. While “Tier2” Computing Centres, specialized in organized processing tasks like Monte Carlo simulation, are nowadays a well established concept, with years of running experience, site specialized towards end user chaotic analysis activities do not yet have a defacto standard implementation. In our effort, we focus on all the aspects that can make the analysis tasks easier for a physics user not expert in computing. On the storage side, we are experimenting on storage techniques allowing for remote data access and on storage optimization on the typical analysis access patterns. On the networking side, we are studying the differences between flat and tiered LAN architecture, also using virtual partitioning of the same physical networking for the different use patterns. Finally, on the user side, we are developing tools and instruments to allow for an exhaustive monitoring of their processes at the site, and for an efficient support system in case of problems. We will report about the results of the test executed on different subsystem and give a description of the layout of the infrastructure in place at the site participating to the consortium.

Physical Activity After Stroke Is Associated With Increased Interhemispheric Connectivity of the Dorsal Attention Network.

PubMed

Veldsman, Michele; Churilov, Leonid; Werden, Emilio; Li, Qi; Cumming, Toby; Brodtmann, Amy

2017-02-01

Attention is frequently impaired after stroke, and its impairment is associated with poor quality of life. Physical activity benefits attention in healthy populations and has also been associated with recovery after brain injury. We investigated the relationship between objectively measured daily physical activity, attention network connectivity, and attention task performance after stroke. We hypothesized that increased daily physical activity would be associated with improved attention network function. Stroke patients (n = 62; mean age = 67 years, SD = 12.6 years) and healthy controls (n = 27; mean age = 68 years, SD = 6 years) underwent cognitive testing and 7 minutes of functional magnetic resonance imaging in the resting-state. Patients were tested 3 months after ischemic stroke. Physical activity was monitored with an electronic armband worn for 7 days. Dorsal and ventral attention network function was examined using seed-based connectivity analyses. Greater daily physical activity was associated with increased interhemispheric connectivity of the superior parietal lobule in the dorsal attention network (DAN; P < .05, false discovery rate corrected). This relationship was not explained by stroke lesion volume. Importantly, stronger connectivity in this region was related to faster reaction time in 3 attention tasks, as revealed by robust linear regression. The relationship remained after adjusting for age, gray matter volume, and white matter hyperintensity load. Daily physical activity was associated with increased resting interhemispheric connectivity of the DAN. Increased connectivity was associated with faster attention performance, suggesting a cognitive correlate to increased network connectivity. Attentional modulation by physical activity represents a key focus for intervention studies.

Towards understanding the behavior of physical systems using information theory

NASA Astrophysics Data System (ADS)

Quax, Rick; Apolloni, Andrea; Sloot, Peter M. A.

2013-09-01

One of the goals of complex network analysis is to identify the most influential nodes, i.e., the nodes that dictate the dynamics of other nodes. In the case of autonomous systems or transportation networks, highly connected hubs play a preeminent role in diffusing the flow of information and viruses; in contrast, in language evolution most linguistic norms come from the peripheral nodes who have only few contacts. Clearly a topological analysis of the interactions alone is not sufficient to identify the nodes that drive the state of the network. Here we show how information theory can be used to quantify how the dynamics of individual nodes propagate through a system. We interpret the state of a node as a storage of information about the state of other nodes, which is quantified in terms of Shannon information. This information is transferred through interactions and lost due to noise, and we calculate how far it can travel through a network. We apply this concept to a model of opinion formation in a complex social network to calculate the impact of each node by measuring how long its opinion is remembered by the network. Counter-intuitively we find that the dynamics of opinions are not determined by the hubs or peripheral nodes, but rather by nodes with an intermediate connectivity.

Conditions for addressing environmental determinants of health behavior in intersectoral policy networks: A fuzzy set Qualitative Comparative Analysis.

PubMed

Peters, D T J M; Verweij, S; Grêaux, K; Stronks, K; Harting, J

2017-12-01

Improving health requires changes in the social, physical, economic and political determinants of health behavior. For the realization of policies that address these environmental determinants, intersectoral policy networks are considered necessary for the pooling of resources to implement different policy instruments. However, such network diversity may increase network complexity and therefore hamper network performance. Network complexity may be reduced by network management and the provision of financial resources. This study examined whether network diversity - amidst the other conditions - is indeed needed to address environmental determinants of health behavior. We included 25 intersectoral policy networks in Dutch municipalities aimed at reducing overweight, smoking, and alcohol/drugs abuse. For our fuzzy set Qualitative Comparative Analysis we used data from three web-based surveys among (a) project leaders regarding network diversity and size (n = 38); (b) project leaders and project partners regarding management (n = 278); and (c) implementation professionals regarding types of environmental determinants addressed (n = 137). Data on budgets were retrieved from project application forms. Contrary to their intentions, most policy networks typically addressed personal determinants. If the environment was addressed too, it was mostly the social environment. To address environmental determinants of health behavior, network diversity (>50% of the actors are non-public health) was necessary in networks that were either small (<16 actors) or had small budgets (<€183,172), when both were intensively managed. Irrespective of network diversity, environmental determinants also were addressed by small networks with large budgets, and by large networks with small budgets, when both provided network management. We conclude that network diversity is important - although not necessary - for resource pooling to address environmental determinants of health behavior, but only effective in the presence of network management. Our findings may support intersectoral policy networks in improving health behaviors by addressing a variety of environmental determinants. Copyright © 2017. Published by Elsevier Ltd.

A computer tool to support in design of industrial Ethernet.

PubMed

Lugli, Alexandre Baratella; Santos, Max Mauro Dias; Franco, Lucia Regina Horta Rodrigues

2009-04-01

This paper presents a computer tool to support in the project and development of an industrial Ethernet network, verifying the physical layer (cables-resistance and capacitance, scan time, network power supply-POE's concept "Power Over Ethernet" and wireless), and occupation rate (amount of information transmitted to the network versus the controller network scan time). These functions are accomplished without a single physical element installed in the network, using only simulation. The computer tool has a software that presents a detailed vision of the network to the user, besides showing some possible problems in the network, and having an extremely friendly environment.

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.

Proceedings 3rd NASA/IEEE Workshop on Formal Approaches to Agent-Based Systems (FAABS-III)

NASA Technical Reports Server (NTRS)

Hinchey, Michael (Editor); Rash, James (Editor); Truszkowski, Walt (Editor); Rouff, Christopher (Editor)

2004-01-01

These preceedings contain 18 papers and 4 poster presentation, covering topics such as: multi-agent systems, agent-based control, formalism, norms, as well as physical and biological models of agent-based systems. Some applications presented in the proceedings include systems analysis, software engineering, computer networks and robot control.

Coupled disease-behavior dynamics on complex networks: A review

NASA Astrophysics Data System (ADS)

Wang, Zhen; Andrews, Michael A.; Wu, Zhi-Xi; Wang, Lin; Bauch, Chris T.

2015-12-01

It is increasingly recognized that a key component of successful infection control efforts is understanding the complex, two-way interaction between disease dynamics and human behavioral and social dynamics. Human behavior such as contact precautions and social distancing clearly influence disease prevalence, but disease prevalence can in turn alter human behavior, forming a coupled, nonlinear system. Moreover, in many cases, the spatial structure of the population cannot be ignored, such that social and behavioral processes and/or transmission of infection must be represented with complex networks. Research on studying coupled disease-behavior dynamics in complex networks in particular is growing rapidly, and frequently makes use of analysis methods and concepts from statistical physics. Here, we review some of the growing literature in this area. We contrast network-based approaches to homogeneous-mixing approaches, point out how their predictions differ, and describe the rich and often surprising behavior of disease-behavior dynamics on complex networks, and compare them to processes in statistical physics. We discuss how these models can capture the dynamics that characterize many real-world scenarios, thereby suggesting ways that policy makers can better design effective prevention strategies. We also describe the growing sources of digital data that are facilitating research in this area. Finally, we suggest pitfalls which might be faced by researchers in the field, and we suggest several ways in which the field could move forward in the coming years.

Role of Graph Architecture in Controlling Dynamical Networks with Applications to Neural Systems.

PubMed

Kim, Jason Z; Soffer, Jonathan M; Kahn, Ari E; Vettel, Jean M; Pasqualetti, Fabio; Bassett, Danielle S

2018-01-01

Networked systems display complex patterns of interactions between components. In physical networks, these interactions often occur along structural connections that link components in a hard-wired connection topology, supporting a variety of system-wide dynamical behaviors such as synchronization. While descriptions of these behaviors are important, they are only a first step towards understanding and harnessing the relationship between network topology and system behavior. Here, we use linear network control theory to derive accurate closed-form expressions that relate the connectivity of a subset of structural connections (those linking driver nodes to non-driver nodes) to the minimum energy required to control networked systems. To illustrate the utility of the mathematics, we apply this approach to high-resolution connectomes recently reconstructed from Drosophila, mouse, and human brains. We use these principles to suggest an advantage of the human brain in supporting diverse network dynamics with small energetic costs while remaining robust to perturbations, and to perform clinically accessible targeted manipulation of the brain's control performance by removing single edges in the network. Generally, our results ground the expectation of a control system's behavior in its network architecture, and directly inspire new directions in network analysis and design via distributed control.

Role of graph architecture in controlling dynamical networks with applications to neural systems

NASA Astrophysics Data System (ADS)

Kim, Jason Z.; Soffer, Jonathan M.; Kahn, Ari E.; Vettel, Jean M.; Pasqualetti, Fabio; Bassett, Danielle S.

2018-01-01

Networked systems display complex patterns of interactions between components. In physical networks, these interactions often occur along structural connections that link components in a hard-wired connection topology, supporting a variety of system-wide dynamical behaviours such as synchronization. Although descriptions of these behaviours are important, they are only a first step towards understanding and harnessing the relationship between network topology and system behaviour. Here, we use linear network control theory to derive accurate closed-form expressions that relate the connectivity of a subset of structural connections (those linking driver nodes to non-driver nodes) to the minimum energy required to control networked systems. To illustrate the utility of the mathematics, we apply this approach to high-resolution connectomes recently reconstructed from Drosophila, mouse, and human brains. We use these principles to suggest an advantage of the human brain in supporting diverse network dynamics with small energetic costs while remaining robust to perturbations, and to perform clinically accessible targeted manipulation of the brain's control performance by removing single edges in the network. Generally, our results ground the expectation of a control system's behaviour in its network architecture, and directly inspire new directions in network analysis and design via distributed control.

How to Identify Success Among Networks That Promote Active Living

PubMed Central

Varda, Danielle; Reed, Hannah; Retrum, Jessica; Tabak, Rachel; Gustat, Jeanette; O'Hara Tompkins, Nancy

2015-01-01

Objectives. We evaluated organization- and network-level factors that influence organizations’ perceived success. This is important for managing interorganizational networks, which can mobilize communities to address complex health issues such as physical activity, and for achieving change. Methods. In 2011, we used structured interview and network survey data from 22 states in the United States to estimate multilevel random-intercept models to understand organization- and network-level factors that explain perceived network success. Results. A total of 53 of 59 “whole networks” met the criteria for inclusion in the analysis (89.8%). Coordinators identified 559 organizations, with 3 to 12 organizations from each network taking the online survey (response rate = 69.7%; range = 33%–100%). Occupying a leadership position (P < .01), the amount of time with the network (P < .05), and support from community leaders (P < .05) emerged as correlates of perceived success. Conclusions. Organizations’ perceptions of success can influence decisions about continuing involvement and investment in networks designed to promote environment and policy change for active living. Understanding these factors can help leaders manage complex networks that involve diverse memberships, varied interests, and competing community-level priorities. PMID:26378863

Cyber-physical approach to the network-centric robotics control task

NASA Astrophysics Data System (ADS)

Muliukha, Vladimir; Ilyashenko, Alexander; Zaborovsky, Vladimir; Lukashin, Alexey

2016-10-01

Complex engineering tasks concerning control for groups of mobile robots are developed poorly. In our work for their formalization we use cyber-physical approach, which extends the range of engineering and physical methods for a design of complex technical objects by researching the informational aspects of communication and interaction between objects and with an external environment [1]. The paper analyzes network-centric methods for control of cyber-physical objects. Robots or cyber-physical objects interact with each other by transmitting information via computer networks using preemptive queueing system and randomized push-out mechanism [2],[3]. The main field of application for the results of our work is space robotics. The selection of cyber-physical systems as a special class of designed objects is due to the necessity of integrating various components responsible for computing, communications and control processes. Network-centric solutions allow using universal means for the organization of information exchange to integrate different technologies for the control system.

Promoting the Swedish method of physical education throughout France for the benefit of public health (1868-1954).

PubMed

Bazoge, N; Saint-Martin, J; Attali, M

2013-03-01

This article examines the cultural and public health challenges associated with the dissemination of the Swedish approach and methods of physical education throughout France and illustrates the two main methods of influence, both direct through research and study visits and indirect through the creation of an international network entitled the International Federation of Physical Education. More particularly, it studies the roles of Philippe Tissié in 1898 and Pierre Seurin in 1946, and shows how these two major players of French physical education contributed actively to strengthening Swedish influence throughout France. It also highlights their equally essential role in the successful implementation of a pro-Swedish network in France, intended to serve their public health aims. This analysis forms part of the geopolitical and socio-cultural history of foreign physical education models, whose exemplarity was mainly dependent on Franco-Swedish relations and the models' social representations. Using archives from the French Physical Education League, travel logs and the Revue des jeux scolaires et d'hygiène sociale (Journal for School Games and Social Hygiene), it has been shown why the myth of the Swedish Eldorado contributed to creating, in France, "a work of art and of science that was, at the same time, both national and practical." © 2011 John Wiley & Sons A/S.

Local Spatial Obesity Analysis and Estimation Using Online Social Network Sensors.

PubMed

Sun, Qindong; Wang, Nan; Li, Shancang; Zhou, Hongyi

2018-03-15

Recently, the online social networks (OSNs) have received considerable attentions as a revolutionary platform to offer users massive social interaction among users that enables users to be more involved in their own healthcare. The OSNs have also promoted increasing interests in the generation of analytical, data models in health informatics. This paper aims at developing an obesity identification, analysis, and estimation model, in which each individual user is regarded as an online social network 'sensor' that can provide valuable health information. The OSN-based obesity analytic model requires each sensor node in an OSN to provide associated features, including dietary habit, physical activity, integral/incidental emotions, and self-consciousness. Based on the detailed measurements on the correlation of obesity and proposed features, the OSN obesity analytic model is able to estimate the obesity rate in certain urban areas and the experimental results demonstrate a high success estimation rate. The measurements and estimation experimental findings created by the proposed obesity analytic model show that the online social networks could be used in analyzing the local spatial obesity problems effectively. Copyright © 2018. Published by Elsevier Inc.

Graph-based unsupervised segmentation algorithm for cultured neuronal networks' structure characterization and modeling.

PubMed

de Santos-Sierra, Daniel; Sendiña-Nadal, Irene; Leyva, Inmaculada; Almendral, Juan A; Ayali, Amir; Anava, Sarit; Sánchez-Ávila, Carmen; Boccaletti, Stefano

2015-06-01

Large scale phase-contrast images taken at high resolution through the life of a cultured neuronal network are analyzed by a graph-based unsupervised segmentation algorithm with a very low computational cost, scaling linearly with the image size. The processing automatically retrieves the whole network structure, an object whose mathematical representation is a matrix in which nodes are identified neurons or neurons' clusters, and links are the reconstructed connections between them. The algorithm is also able to extract any other relevant morphological information characterizing neurons and neurites. More importantly, and at variance with other segmentation methods that require fluorescence imaging from immunocytochemistry techniques, our non invasive measures entitle us to perform a longitudinal analysis during the maturation of a single culture. Such an analysis furnishes the way of individuating the main physical processes underlying the self-organization of the neurons' ensemble into a complex network, and drives the formulation of a phenomenological model yet able to describe qualitatively the overall scenario observed during the culture growth. © 2014 International Society for Advancement of Cytometry.

The power of social networks and social support in promotion of physical activity and body mass index among African American adults.

PubMed

Flórez, Karen R; Richardson, Andrea S; Ghosh-Dastidar, Madhumita Bonnie; Troxel, Wendy; DeSantis, Amy; Colabianchi, Natalie; Dubowitz, Tamara

2018-04-01

Social support and social networks can elucidate important structural and functional aspects of social relationships that are associated with health-promoting behaviors, including Physical Activity (PA) and weight. A growing number of studies have investigated the relationship between social support, social networks, PA and obesity specifically among African Americans; however, the evidence is mixed and many studies focus exclusively on African American women. Most studies have also focused on either functional or structural aspects of social relationships (but not both) and few have objectively measured moderate-to-vigorous physical activity (MVPA) and body mass index (BMI). Cross-sectional surveys of adult African American men and women living in two low-income predominantly African American neighborhoods in Pittsburgh, PA (N = 799) measured numerous structural features as well as functional aspects of social relationships. Specifically, structural features included social isolation, and social network size and diversity. Functional aspects included perceptions of social support for physical activity from the social network in general as well as from family and friends specifically. Height, weight, and PA were objectively measured. From these, we derived Body Mass Index (BMI) and moderate-to-vigorous physical activity (MVPA). All regression models were stratified by gender, and included age, income, education, employment, marital status, physical limitations, and a neighborhood indicator. Greater social isolation was a significant predictor of lower BMI among men only. Among women only, social isolation was significantly associated with increased MVPA whereas, network diversity was significantly associated with reduced MVPA. Future research would benefit from in-depth qualitative investigations to understand how social networks may act to influence different types of physical activity among African Americans, as well as understand how they can be possible levers for health promotion and prevention.

Engineering Online and In-Person Social Networks for Physical Activity: A Randomized Trial.

PubMed

Rovniak, Liza S; Kong, Lan; Hovell, Melbourne F; Ding, Ding; Sallis, James F; Ray, Chester A; Kraschnewski, Jennifer L; Matthews, Stephen A; Kiser, Elizabeth; Chinchilli, Vernon M; George, Daniel R; Sciamanna, Christopher N

2016-12-01

Social networks can influence physical activity, but little is known about how best to engineer online and in-person social networks to increase activity. The purpose of this study was to conduct a randomized trial based on the Social Networks for Activity Promotion model to assess the incremental contributions of different procedures for building social networks on objectively measured outcomes. Physically inactive adults (n = 308, age, 50.3 (SD = 8.3) years, 38.3 % male, 83.4 % overweight/obese) were randomized to one of three groups. The Promotion group evaluated the effects of weekly emailed tips emphasizing social network interactions for walking (e.g., encouragement, informational support); the Activity group evaluated the incremental effect of adding an evidence-based online fitness walking intervention to the weekly tips; and the Social Networks group evaluated the additional incremental effect of providing access to an online networking site for walking as well as prompting walking/activity across diverse settings. The primary outcome was mean change in accelerometer-measured moderate-to-vigorous physical activity (MVPA), assessed at 3 and 9 months from baseline. Participants increased their MVPA by 21.0 min/week, 95 % CI [5.9, 36.1], p = .005, at 3 months, and this change was sustained at 9 months, with no between-group differences. Although the structure of procedures for targeting social networks varied across intervention groups, the functional effect of these procedures on physical activity was similar. Future research should evaluate if more powerful reinforcers improve the effects of social network interventions. The trial was registered with the ClinicalTrials.gov (NCT01142804).

Does a network structure exist in molecular liquid SnI4 and GeI4?

NASA Astrophysics Data System (ADS)

Sakagami, Takahiro; Fuchizaki, Kazuhiro

2017-04-01

The existence of a network structure consisting of electrically neutral tetrahedral molecules in liquid SnI4 and GeI4 at ambient pressure was examined. The liquid structures employed for the examination were obtained from a reverse Monte Carlo analysis. The structures were physically interpreted by introducing an appropriate intermolecular interaction. A ‘bond’ was then defined as an intermolecular connection that minimizes the energy of intermolecular interaction. However, their ‘bond’ energy is too weak for the ‘bond’ and the resulting network structure to be defined statically. The vertex-to-edge orientation between the nearest molecules is so ubiquitous that almost all of the molecules in the system can take part in the network, which is reflected in the appearance of a prepeak in the structure factor.

Physical-Layer Network Coding for VPN in TDM-PON

NASA Astrophysics Data System (ADS)

Wang, Qike; Tse, Kam-Hon; Chen, Lian-Kuan; Liew, Soung-Chang

2012-12-01

We experimentally demonstrate a novel optical physical-layer network coding (PNC) scheme over time-division multiplexing (TDM) passive optical network (PON). Full-duplex error-free communications between optical network units (ONUs) at 2.5 Gb/s are shown for all-optical virtual private network (VPN) applications. Compared to the conventional half-duplex communications set-up, our scheme can increase the capacity by 100% with power penalty smaller than 3 dB. Synchronization of two ONUs is not required for the proposed VPN scheme

Missed connections: A case study of the social networks of physics doctoral students in a single department

NASA Astrophysics Data System (ADS)

Knaub, Alexis Victoria

Gender disparity is an issue among the many science, technology, engineering, and mathematics (STEM) fields. Although many previous studies examine gender issues in STEM as an aggregate discipline, there are unique issues to each of the fields that are considered STEM fields. Some fields, such as physics, have fewer women graduating with degrees than other fields. This suggests that women's experiences vary by STEM field. The majority of previous research also examines gender and other disparities at either the nationwide or individual level. This project entailed social network analysis through survey and interview data to examine a single physics department's doctoral students in order to provide a comprehensive look at student social experiences. In addition to examining gender, other demographic variables were studied to see if the results are truly associated with gender; these variables include race/ethnicity, year in program, student type, relationship status, research type, undergraduate institute, and subfield. Data were examined to determine if there are relationships to social connections and outcome variables such as persistence in completing the degree and the time to degree. Data collected on faculty were used to rank faculty members; data such as h-indices and number of students graduate over the past 5 years were collected. Fifty-five (55) of 110 possible participants completed the survey; forty-three are male, and twelve are female. Twenty-eight of the fifty-five survey participants were interview; twenty-three are male, and five are female. Findings for peer networks include that peer networks are established during the first year and do not change drastically as one progresses in the program. Geographic location within the campus affects socializing with peers. Connections to fellow students are not necessarily reciprocated; the maximum percentage of reciprocated connections is 60%. The number of connections one has varies by network purpose, with students having more connections for the more social purposes. Students are isolated when working on their research, even in their early years. Research discussion does not occur, unless one is providing casual updates to a peer. Findings for student-faculty networks indicate that these relationships are important but complicated. Advisor selection is often done casually, even when one is switching advisors. Faculty have a lot of influence on the doctoral students such as motivating research collaborations among students or aiding in the job search. Most doctoral students feel as though there is a power dynamic that hinders them from socializing with faculty and thus, are not close to the faculty. Opportunities to develop stronger relationships and for professional development are often missed. The total number of peer and faculty ties has significant relationships to whether a student considers leaving the program. Analyzing the qualitative and quantitative data through demographic variables showed how complex these experiences are. All demographic variables indicated there are statistically significant differences in social experience among the groups, though the extent varies. The year in program variable showed the most differences among cohort years, primarily with those in the fifth year. While gender showed few differences, women tended to have more homophilous peer networks than men and women tended to have more connections to higher prestige faculty. The race/ethnicity, student type, undergraduate institute, subfield, and relationship status variables produced few statistically significant results. Peer networks have statistically significant differences in homophily when examining research type. The regression model suggests that being female, having a higher year in the program, and/or completing undergraduate studies from a liberal arts college increases the time to degree. Being in a relationship (dating or married) and/or working on experimental research decreases the time to degree. Only research peer network and departmental information network variables remain in this model. Suggestions for further research for both physics/STEM education and social network analysis are included. Suggestions for ways in which the Jonas University physics department can improve its climate are also included. Although these suggestions are written based upon the Jonas University data, they may be applicable to other physics/STEM graduate programs.

Evaluation of Yogurt Microstructure Using Confocal Laser Scanning Microscopy and Image Analysis.

PubMed

Skytte, Jacob L; Ghita, Ovidiu; Whelan, Paul F; Andersen, Ulf; Møller, Flemming; Dahl, Anders B; Larsen, Rasmus

2015-06-01

The microstructure of protein networks in yogurts defines important physical properties of the yogurt and hereby partly its quality. Imaging this protein network using confocal scanning laser microscopy (CSLM) has shown good results, and CSLM has become a standard measuring technique for fermented dairy products. When studying such networks, hundreds of images can be obtained, and here image analysis methods are essential for using the images in statistical analysis. Previously, methods including gray level co-occurrence matrix analysis and fractal analysis have been used with success. However, a range of other image texture characterization methods exists. These methods describe an image by a frequency distribution of predefined image features (denoted textons). Our contribution is an investigation of the choice of image analysis methods by performing a comparative study of 7 major approaches to image texture description. Here, CSLM images from a yogurt fermentation study are investigated, where production factors including fat content, protein content, heat treatment, and incubation temperature are varied. The descriptors are evaluated through nearest neighbor classification, variance analysis, and cluster analysis. Our investigation suggests that the texton-based descriptors provide a fuller description of the images compared to gray-level co-occurrence matrix descriptors and fractal analysis, while still being as applicable and in some cases as easy to tune. © 2015 Institute of Food Technologists®

Artificial Intelligence in planetary spectroscopy

NASA Astrophysics Data System (ADS)

Waldmann, Ingo

2017-10-01

The field of exoplanetary spectroscopy is as fast moving as it is new. Analysing currently available observations of exoplanetary atmospheres often invoke large and correlated parameter spaces that can be difficult to map or constrain. This is true for both: the data analysis of observations as well as the theoretical modelling of their atmospheres.Issues of low signal-to-noise data and large, non-linear parameter spaces are nothing new and commonly found in many fields of engineering and the physical sciences. Recent years have seen vast improvements in statistical data analysis and machine learning that have revolutionised fields as diverse as telecommunication, pattern recognition, medical physics and cosmology.In many aspects, data mining and non-linearity challenges encountered in other data intensive fields are directly transferable to the field of extrasolar planets. In this conference, I will discuss how deep neural networks can be designed to facilitate solving said issues both in exoplanet atmospheres as well as for atmospheres in our own solar system. I will present a deep belief network, RobERt (Robotic Exoplanet Recognition), able to learn to recognise exoplanetary spectra and provide artificial intelligences to state-of-the-art atmospheric retrieval algorithms. Furthermore, I will present a new deep convolutional network that is able to map planetary surface compositions using hyper-spectral imaging and demonstrate its uses on Cassini-VIMS data of Saturn.

[Study of building quantitative analysis model for chlorophyll in winter wheat with reflective spectrum using MSC-ANN algorithm].

PubMed

Liang, Xue; Ji, Hai-yan; Wang, Peng-xin; Rao, Zhen-hong; Shen, Bing-hui

2010-01-01

Preprocess method of multiplicative scatter correction (MSC) was used to reject noises in the original spectra produced by the environmental physical factor effectively, then the principal components of near-infrared spectroscopy were calculated by nonlinear iterative partial least squares (NIPALS) before building the back propagation artificial neural networks method (BP-ANN), and the numbers of principal components were calculated by the method of cross validation. The calculated principal components were used as the inputs of the artificial neural networks model, and the artificial neural networks model was used to find the relation between chlorophyll in winter wheat and reflective spectrum, which can predict the content of chlorophyll in winter wheat. The correlation coefficient (r) of calibration set was 0.9604, while the standard deviation (SD) and relative standard deviation (RSD) was 0.187 and 5.18% respectively. The correlation coefficient (r) of predicted set was 0.9600, and the standard deviation (SD) and relative standard deviation (RSD) was 0.145 and 4.21% respectively. It means that the MSC-ANN algorithm can reject noises in the original spectra produced by the environmental physical factor effectively and set up an exact model to predict the contents of chlorophyll in living leaves veraciously to replace the classical method and meet the needs of fast analysis of agricultural products.

Multilayer modeling and analysis of human brain networks

PubMed Central

2017-01-01

Abstract Understanding how the human brain is structured, and how its architecture is related to function, is of paramount importance for a variety of applications, including but not limited to new ways to prevent, deal with, and cure brain diseases, such as Alzheimer’s or Parkinson’s, and psychiatric disorders, such as schizophrenia. The recent advances in structural and functional neuroimaging, together with the increasing attitude toward interdisciplinary approaches involving computer science, mathematics, and physics, are fostering interesting results from computational neuroscience that are quite often based on the analysis of complex network representation of the human brain. In recent years, this representation experienced a theoretical and computational revolution that is breaching neuroscience, allowing us to cope with the increasing complexity of the human brain across multiple scales and in multiple dimensions and to model structural and functional connectivity from new perspectives, often combined with each other. In this work, we will review the main achievements obtained from interdisciplinary research based on magnetic resonance imaging and establish de facto, the birth of multilayer network analysis and modeling of the human brain. PMID:28327916

A graph-based computational framework for simulation and optimisation of coupled infrastructure networks

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

Jalving, Jordan; Abhyankar, Shrirang; Kim, Kibaek

Here, we present a computational framework that facilitates the construction, instantiation, and analysis of large-scale optimization and simulation applications of coupled energy networks. The framework integrates the optimization modeling package PLASMO and the simulation package DMNetwork (built around PETSc). These tools use a common graphbased abstraction that enables us to achieve compatibility between data structures and to build applications that use network models of different physical fidelity. We also describe how to embed these tools within complex computational workflows using SWIFT, which is a tool that facilitates parallel execution of multiple simulation runs and management of input and output data.more » We discuss how to use these capabilities to target coupled natural gas and electricity systems.« less

A graph-based computational framework for simulation and optimisation of coupled infrastructure networks

DOE PAGES

Jalving, Jordan; Abhyankar, Shrirang; Kim, Kibaek; ...

2017-04-24

Here, we present a computational framework that facilitates the construction, instantiation, and analysis of large-scale optimization and simulation applications of coupled energy networks. The framework integrates the optimization modeling package PLASMO and the simulation package DMNetwork (built around PETSc). These tools use a common graphbased abstraction that enables us to achieve compatibility between data structures and to build applications that use network models of different physical fidelity. We also describe how to embed these tools within complex computational workflows using SWIFT, which is a tool that facilitates parallel execution of multiple simulation runs and management of input and output data.more » We discuss how to use these capabilities to target coupled natural gas and electricity systems.« less

LHCNet: Wide Area Networking and Collaborative Systems for HEP

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

Newman, H.B,

2007-08-20

This proposal presents the status and progress in 2006-7, and the technical and financial plans for 2008-2010 for the US LHCNet transatlantic network supporting U.S. participation in the LHC physics program. US LHCNet provides transatlantic connections of the Tier1 computing facilities at Fermilab and Brookhaven with the Tier0 and Tier1 facilities at CERN as well as Tier1s elsewhere in Europe and Asia. Together with ESnet, Internet2, the GEANT pan-European network, and NSF’s UltraLight project, US LHCNet also supports connections between the Tier2 centers (where most of the analysis of the data will take place, starting this year) and the Tier1smore » as needed.See report« less

Impulse-induced localized control of chaos in starlike networks.

PubMed

Chacón, Ricardo; Palmero, Faustino; Cuevas-Maraver, Jesús

2016-06-01

Locally decreasing the impulse transmitted by periodic pulses is shown to be a reliable method of taming chaos in starlike networks of dissipative nonlinear oscillators, leading to both synchronous periodic states and equilibria (oscillation death). Specifically, the paradigmatic model of damped kicked rotators is studied in which it is assumed that when the rotators are driven synchronously, i.e., all driving pulses transmit the same impulse, the networks display chaotic dynamics. It is found that the taming effect of decreasing the impulse transmitted by the pulses acting on particular nodes strongly depends on their number and degree of connectivity. A theoretical analysis is given explaining the basic physical mechanism as well as the main features of the chaos-control scenario.

Markov Task Network: A Framework for Service Composition under Uncertainty in Cyber-Physical Systems.

PubMed

Mohammed, Abdul-Wahid; Xu, Yang; Hu, Haixiao; Agyemang, Brighter

2016-09-21

In novel collaborative systems, cooperative entities collaborate services to achieve local and global objectives. With the growing pervasiveness of cyber-physical systems, however, such collaboration is hampered by differences in the operations of the cyber and physical objects, and the need for the dynamic formation of collaborative functionality given high-level system goals has become practical. In this paper, we propose a cross-layer automation and management model for cyber-physical systems. This models the dynamic formation of collaborative services pursuing laid-down system goals as an ontology-oriented hierarchical task network. Ontological intelligence provides the semantic technology of this model, and through semantic reasoning, primitive tasks can be dynamically composed from high-level system goals. In dealing with uncertainty, we further propose a novel bridge between hierarchical task networks and Markov logic networks, called the Markov task network. This leverages the efficient inference algorithms of Markov logic networks to reduce both computational and inferential loads in task decomposition. From the results of our experiments, high-precision service composition under uncertainty can be achieved using this approach.

The evolution of cost-efficiency in neural networks during recovery from traumatic brain injury.

PubMed

Roy, Arnab; Bernier, Rachel A; Wang, Jianli; Benson, Monica; French, Jerry J; Good, David C; Hillary, Frank G

2017-01-01

A somewhat perplexing finding in the systems neuroscience has been the observation that physical injury to neural systems may result in enhanced functional connectivity (i.e., hyperconnectivity) relative to the typical network response. The consequences of local or global enhancement of functional connectivity remain uncertain and this is particularly true for the overall metabolic cost of the network. We examine the hyperconnectivity hypothesis in a sample of 14 individuals with TBI with data collected at approximately 3, 6, and 12 months following moderate and severe TBI. As anticipated, individuals with TBI showed increased network strength and cost early after injury, but by one-year post injury hyperconnectivity was more circumscribed to frontal DMN and temporal-parietal attentional control regions. Cost in these subregions was a significant predictor of cognitive performance. Cost-efficiency analysis in the Power 264 data parcellation suggested that at 6 months post injury the network requires higher cost connections to achieve high efficiency as compared to the network 12 months post injury. These results demonstrate that networks self-organize to re-establish connectivity while balancing cost-efficiency trade-offs.

The evolution of cost-efficiency in neural networks during recovery from traumatic brain injury

PubMed Central

Roy, Arnab; Bernier, Rachel A.; Wang, Jianli; Benson, Monica; French, Jerry J.; Good, David C.; Hillary, Frank G.

2017-01-01

A somewhat perplexing finding in the systems neuroscience has been the observation that physical injury to neural systems may result in enhanced functional connectivity (i.e., hyperconnectivity) relative to the typical network response. The consequences of local or global enhancement of functional connectivity remain uncertain and this is particularly true for the overall metabolic cost of the network. We examine the hyperconnectivity hypothesis in a sample of 14 individuals with TBI with data collected at approximately 3, 6, and 12 months following moderate and severe TBI. As anticipated, individuals with TBI showed increased network strength and cost early after injury, but by one-year post injury hyperconnectivity was more circumscribed to frontal DMN and temporal-parietal attentional control regions. Cost in these subregions was a significant predictor of cognitive performance. Cost-efficiency analysis in the Power 264 data parcellation suggested that at 6 months post injury the network requires higher cost connections to achieve high efficiency as compared to the network 12 months post injury. These results demonstrate that networks self-organize to re-establish connectivity while balancing cost-efficiency trade-offs. PMID:28422992

High-accuracy local positioning network for the alignment of the Mu2e experiment.

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

Hejdukova, Jana B.

This Diploma thesis describes the establishment of a high-precision local positioning network and accelerator alignment for the Mu2e physics experiment. The process of establishing new network consists of few steps: design of the network, pre-analysis, installation works, measurements of the network and making adjustments. Adjustments were performed using two approaches. First is a geodetic approach of taking into account the Earth’s curvature and the metrological approach of a pure 3D Cartesian system on the other side. The comparison of those two approaches is performed and evaluated in the results and compared with expected differences. The effect of the Earth’s curvaturemore » was found to be significant for this kind of network and should not be neglected. The measurements were obtained with Absolute Tracker AT401, leveling instrument Leica DNA03 and gyrotheodolite DMT Gyromat 2000. The coordinates of the points of the reference network were determined by the Least Square Meth od and the overall view is attached as Annexes.« less

Diffany: an ontology-driven framework to infer, visualise and analyse differential molecular networks.

PubMed

Van Landeghem, Sofie; Van Parys, Thomas; Dubois, Marieke; Inzé, Dirk; Van de Peer, Yves

2016-01-05

Differential networks have recently been introduced as a powerful way to study the dynamic rewiring capabilities of an interactome in response to changing environmental conditions or stimuli. Currently, such differential networks are generated and visualised using ad hoc methods, and are often limited to the analysis of only one condition-specific response or one interaction type at a time. In this work, we present a generic, ontology-driven framework to infer, visualise and analyse an arbitrary set of condition-specific responses against one reference network. To this end, we have implemented novel ontology-based algorithms that can process highly heterogeneous networks, accounting for both physical interactions and regulatory associations, symmetric and directed edges, edge weights and negation. We propose this integrative framework as a standardised methodology that allows a unified view on differential networks and promotes comparability between differential network studies. As an illustrative application, we demonstrate its usefulness on a plant abiotic stress study and we experimentally confirmed a predicted regulator. Diffany is freely available as open-source java library and Cytoscape plugin from http://bioinformatics.psb.ugent.be/supplementary_data/solan/diffany/.

Unraveling spurious properties of interaction networks with tailored random networks.

PubMed

Bialonski, Stephan; Wendler, Martin; Lehnertz, Klaus

2011-01-01

We investigate interaction networks that we derive from multivariate time series with methods frequently employed in diverse scientific fields such as biology, quantitative finance, physics, earth and climate sciences, and the neurosciences. Mimicking experimental situations, we generate time series with finite length and varying frequency content but from independent stochastic processes. Using the correlation coefficient and the maximum cross-correlation, we estimate interdependencies between these time series. With clustering coefficient and average shortest path length, we observe unweighted interaction networks, derived via thresholding the values of interdependence, to possess non-trivial topologies as compared to Erdös-Rényi networks, which would indicate small-world characteristics. These topologies reflect the mostly unavoidable finiteness of the data, which limits the reliability of typically used estimators of signal interdependence. We propose random networks that are tailored to the way interaction networks are derived from empirical data. Through an exemplary investigation of multichannel electroencephalographic recordings of epileptic seizures--known for their complex spatial and temporal dynamics--we show that such random networks help to distinguish network properties of interdependence structures related to seizure dynamics from those spuriously induced by the applied methods of analysis.

Unraveling Spurious Properties of Interaction Networks with Tailored Random Networks

PubMed Central

Bialonski, Stephan; Wendler, Martin; Lehnertz, Klaus

2011-01-01

We investigate interaction networks that we derive from multivariate time series with methods frequently employed in diverse scientific fields such as biology, quantitative finance, physics, earth and climate sciences, and the neurosciences. Mimicking experimental situations, we generate time series with finite length and varying frequency content but from independent stochastic processes. Using the correlation coefficient and the maximum cross-correlation, we estimate interdependencies between these time series. With clustering coefficient and average shortest path length, we observe unweighted interaction networks, derived via thresholding the values of interdependence, to possess non-trivial topologies as compared to Erdös-Rényi networks, which would indicate small-world characteristics. These topologies reflect the mostly unavoidable finiteness of the data, which limits the reliability of typically used estimators of signal interdependence. We propose random networks that are tailored to the way interaction networks are derived from empirical data. Through an exemplary investigation of multichannel electroencephalographic recordings of epileptic seizures – known for their complex spatial and temporal dynamics – we show that such random networks help to distinguish network properties of interdependence structures related to seizure dynamics from those spuriously induced by the applied methods of analysis. PMID:21850239

What Motivates Young Adults to Talk About Physical Activity on Social Network Sites?

PubMed

Zhang, Ni; Campo, Shelly; Yang, Jingzhen; Eckler, Petya; Snetselaar, Linda; Janz, Kathleen; Leary, Emily

2017-06-22

Electronic word-of-mouth on social network sites has been used successfully in marketing. In social marketing, electronic word-of-mouth about products as health behaviors has the potential to be more effective and reach more young adults than health education through traditional mass media. However, little is known about what motivates people to actively initiate electronic word-of-mouth about health behaviors on their personal pages or profiles on social network sites, thus potentially reaching all their contacts on those sites. This study filled the gap by applying a marketing theoretical model to explore the factors associated with electronic word-of-mouth on social network sites about leisure-time physical activity. A Web survey link was sent to undergraduate students at one of the Midwestern universities and 439 of them completed the survey. The average age of the 439 participants was 19 years (SD=1 year, range: 18-24). Results suggested that emotional engagement with leisure-time physical activity (ie, affective involvement in leisure-time physical activity) predicted providing relevant opinions or information on social network sites. Social network site users who perceived stronger ties with all their contacts were more likely to provide and seek leisure-time physical activity opinions and information. People who provided leisure-time physical activity opinions and information were more likely to seek opinions and information, and people who forwarded information about leisure-time physical activity were more likely to chat about it. This study shed light on the application of the electronic word-of-mouth theoretical framework in promoting health behaviors. The findings can also guide the development of future social marketing interventions using social network sites to promote leisure-time physical activity. ©Ni Zhang, Shelly Campo, Jingzhen Yang, Petya Eckler, Linda Snetselaar, Kathleen Janz, Emily Leary. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 22.06.2017.

Comparison of home and away-from-home physical activity using accelerometers and cellular network-based tracking devices.

PubMed

Ramulu, Pradeep Y; Chan, Emilie S; Loyd, Tara L; Ferrucci, Luigi; Friedman, David S

2012-08-01

Measuring physical at home and away from home is essential for assessing health and well-being, and could help design interventions to increase physical activity. Here, we describe how physical activity at home and away from home can be quantified by combining information from cellular network-based tracking devices and accelerometers. Thirty-five working adults wore a cellular network-based tracking device and an accelerometer for 6 consecutive days and logged their travel away from home. Performance of the tracking device was determined using the travel log for reference. Tracking device and accelerometer data were merged to compare physical activity at home and away from home. The tracking device detected 98.6% of all away-from-home excursions, accurately measured time away from home and demonstrated few prolonged signal drop-out periods. Most physical activity took place away from home on weekdays, but not on weekends. Subjects were more physically active per unit of time while away from home, particularly on weekends. Cellular network-based tracking devices represent an alternative to global positioning systems for tracking location, and provide information easily integrated with accelerometers to determine where physical activity takes place. Promoting greater time spent away from home may increase physical activity.

Driving factors of interactions between the exchange rate market and the commodity market: A wavelet-based complex network perspective

NASA Astrophysics Data System (ADS)

Wen, Shaobo; An, Haizhong; Chen, Zhihua; Liu, Xueyong

2017-08-01

In traditional econometrics, a time series must be in a stationary sequence. However, it usually shows time-varying fluctuations, and it remains a challenge to execute a multiscale analysis of the data and discover the topological characteristics of conduction in different scales. Wavelet analysis and complex networks in physical statistics have special advantages in solving these problems. We select the exchange rate variable from the Chinese market and the commodity price index variable from the world market as the time series of our study. We explore the driving factors behind the behavior of the two markets and their topological characteristics in three steps. First, we use the Kalman filter to find the optimal estimation of the relationship between the two markets. Second, wavelet analysis is used to extract the scales of the relationship that are driven by different frequency wavelets. Meanwhile, we search for the actual economic variables corresponding to different frequency wavelets. Finally, a complex network is used to search for the transfer characteristics of the combination of states driven by different frequency wavelets. The results show that statistical physics have a unique advantage over traditional econometrics. The Chinese market has time-varying impacts on the world market: it has greater influence when the world economy is stable and less influence in times of turmoil. The process of forming the state combination is random. Transitions between state combinations have a clustering feature. Based on these characteristics, we can effectively reduce the information burden on investors and correctly respond to the government's policy mix.

Optical network democratization.

PubMed

Nejabati, Reza; Peng, Shuping; Simeonidou, Dimitra

2016-03-06

The current Internet infrastructure is not able to support independent evolution and innovation at physical and network layer functionalities, protocols and services, while at same time supporting the increasing bandwidth demands of evolving and heterogeneous applications. This paper addresses this problem by proposing a completely democratized optical network infrastructure. It introduces the novel concepts of the optical white box and bare metal optical switch as key technology enablers for democratizing optical networks. These are programmable optical switches whose hardware is loosely connected internally and is completely separated from their control software. To alleviate their complexity, a multi-dimensional abstraction mechanism using software-defined network technology is proposed. It creates a universal model of the proposed switches without exposing their technological details. It also enables a conventional network programmer to develop network applications for control of the optical network without specific technical knowledge of the physical layer. Furthermore, a novel optical network virtualization mechanism is proposed, enabling the composition and operation of multiple coexisting and application-specific virtual optical networks sharing the same physical infrastructure. Finally, the optical white box and the abstraction mechanism are experimentally evaluated, while the virtualization mechanism is evaluated with simulation. © 2016 The Author(s).

Student Modeling in Orthopedic Surgery Training: Exploiting Symbiosis between Temporal Bayesian Networks and Fine-Grained Didactic Analysis

ERIC Educational Resources Information Center

Chieu, Vu Minh; Luengo, Vanda; Vadcard, Lucile; Tonetti, Jerome

2010-01-01

Cognitive approaches have been used for student modeling in intelligent tutoring systems (ITSs). Many of those systems have tackled fundamental subjects such as mathematics, physics, and computer programming. The change of the student's cognitive behavior over time, however, has not been considered and modeled systematically. Furthermore, the…

Physical Attractiveness Stereotyping on American Television Programs: A Content Analysis.

ERIC Educational Resources Information Center

Downs, A. Chris; Harrison, Sheila K.

The frequencies of specific types of verbal attractiveness stereotypes portrayed on television commercials and regular programs were determined in two studies. In the first, the 4,294 commercials aired between 8 and 10 p.m. on the 3 major networks were observed during a 7-day period in the spring of 1982. Statements related to attractiveness were…

Differences between Peer Victimization in Cyber and Physical Settings and Associated Psychosocial Adjustment in Early Adolescence

ERIC Educational Resources Information Center

Dempsey, Allison G.; Sulkowski, Michael L.; Nichols, Rebecca; Storch, Eric A.

2009-01-01

The increasing use of cyberspace as a social networking forum creates a new medium for youth to become victims of peer aggression. This study used factor analysis techniques to confirm whether survey questions about frequency of cyber victimization formed a distinct latent construct from questions about relational and overt victimization…

Social Influences, Social Context, and Health Behaviors among Working-Class, Multi-Ethnic Adults

ERIC Educational Resources Information Center

Emmons, Karen M.; Barbeau, Elizabeth M.; Gutheil, Caitlin; Stryker, Jo Ellen; Stoddard, Anne M.

2007-01-01

Little research has explored the relationship between social influences (e.g., social networks, social support, social norms) and health as related to modifying factors that may contribute to health disparities. This is a cross-sectional analysis of fruit and vegetable intake and physical activity, using baseline data from two cancer prevention…

Cyber Intelligence Threat Prioritization

DTIC Science & Technology

2014-10-01

platform that allows anyone to make their organization more visible to threat actors. Online Presence Extracurricular Activities Motive Risk...intelligence • The acquisition and analysis of information to identify, track, and predict cyber capabilities, intentions, and activities to offer courses of...access can significantly aid in identifying the risk to employees. Physical and Network-Based Access Position Abnormal Activity Infrastructure

Childhood Physical and Sexual Abuse and Social Network Patterns on Social Media: Associations With Alcohol Use and Problems Among Young Adult Women

PubMed Central

Oshri, Assaf; Himelboim, Itai; Kwon, Josephine A.; Sutton, Tara E.; Mackillop, James

2015-01-01

Objective: The aim of the present study was to examine the links between severities of child abuse (physical vs. sexual), and alcohol use versus problems via social media (Facebook) peer connection structures. Method: A total of 318 undergraduate female students at a public university in the United States reported severity of child abuse experiences and current alcohol use and problems. Social network data were obtained directly from the individuals’ Facebook network. Results: Severity of childhood physical abuse was positively linked to alcohol use and problems via eigenvector centrality, whereas severity of childhood sexual abuse was negatively linked to alcohol use and problems via clustering coefficient. Conclusions: Childhood physical and sexual abuse were linked positively and negatively, respectively, to online social network patterns associated with alcohol use and problems. The study suggests the potential utility of these online network patterns as risk indices and ultimately using social media as a platform for targeted preventive interventions. PMID:26562592

Childhood Physical and Sexual Abuse and Social Network Patterns on Social Media: Associations With Alcohol Use and Problems Among Young Adult Women.

PubMed

Oshri, Assaf; Himelboim, Itai; Kwon, Josephine A; Sutton, Tara E; Mackillop, James

2015-11-01

The aim of the present study was to examine the links between severities of child abuse (physical vs. sexual), and alcohol use versus problems via social media (Facebook) peer connection structures. A total of 318 undergraduate female students at a public university in the United States reported severity of child abuse experiences and current alcohol use and problems. Social network data were obtained directly from the individuals' Facebook network. Severity of childhood physical abuse was positively linked to alcohol use and problems via eigenvector centrality, whereas severity of childhood sexual abuse was negatively linked to alcohol use and problems via clustering coefficient. Childhood physical and sexual abuse were linked positively and negatively, respectively, to online social network patterns associated with alcohol use and problems. The study suggests the potential utility of these online network patterns as risk indices and ultimately using social media as a platform for targeted preventive interventions.

Integrating atomistic molecular dynamics simulations, experiments, and network analysis to study protein dynamics: strength in unity.

PubMed

Papaleo, Elena

2015-01-01

In the last years, we have been observing remarkable improvements in the field of protein dynamics. Indeed, we can now study protein dynamics in atomistic details over several timescales with a rich portfolio of experimental and computational techniques. On one side, this provides us with the possibility to validate simulation methods and physical models against a broad range of experimental observables. On the other side, it also allows a complementary and comprehensive view on protein structure and dynamics. What is needed now is a better understanding of the link between the dynamic properties that we observe and the functional properties of these important cellular machines. To make progresses in this direction, we need to improve the physical models used to describe proteins and solvent in molecular dynamics, as well as to strengthen the integration of experiments and simulations to overcome their own limitations. Moreover, now that we have the means to study protein dynamics in great details, we need new tools to understand the information embedded in the protein ensembles and in their dynamic signature. With this aim in mind, we should enrich the current tools for analysis of biomolecular simulations with attention to the effects that can be propagated over long distances and are often associated to important biological functions. In this context, approaches inspired by network analysis can make an important contribution to the analysis of molecular dynamics simulations.

Physical-layer network coding for passive optical interconnect in datacenter networks.

PubMed

Lin, Rui; Cheng, Yuxin; Guan, Xun; Tang, Ming; Liu, Deming; Chan, Chun-Kit; Chen, Jiajia

2017-07-24

We introduce physical-layer network coding (PLNC) technique in a passive optical interconnect (POI) architecture for datacenter networks. The implementation of the PLNC in the POI at 2.5 Gb/s and 10Gb/s have been experimentally validated while the gains in terms of network layer performances have been investigated by simulation. The results reveal that in order to realize negligible packet drop, the wavelengths usage can be reduced by half while a significant improvement in packet delay especially under high traffic load can be achieved by employing PLNC over POI.

Statistical physics of interacting neural networks

NASA Astrophysics Data System (ADS)

Kinzel, Wolfgang; Metzler, Richard; Kanter, Ido

2001-12-01

Recent results on the statistical physics of time series generation and prediction are presented. A neural network is trained on quasi-periodic and chaotic sequences and overlaps to the sequence generator as well as the prediction errors are calculated numerically. For each network there exists a sequence for which it completely fails to make predictions. Two interacting networks show a transition to perfect synchronization. A pool of interacting networks shows good coordination in the minority game-a model of competition in a closed market. Finally, as a demonstration, a perceptron predicts bit sequences produced by human beings.

Physical and Cross-Layer Security Enhancement and Resource Allocation for Wireless Networks

ERIC Educational Resources Information Center

Bashar, Muhammad Shafi Al

2011-01-01

In this dissertation, we present novel physical (PHY) and cross-layer design guidelines and resource adaptation algorithms to improve the security and user experience in the future wireless networks. Physical and cross-layer wireless security measures can provide stronger overall security with high efficiency and can also provide better…

IP Infrastructure Geolocation

DTIC Science & Technology

2015-03-01

unlimited 13. ABSTRACT (maximum 200 words) Physical network maps are important to critical infrastructure defense and planning. Current state-of...the-art network infrastructure geolocation relies on Domain Name System (DNS) inferences. However, not only is using the DNS relatively inaccurate for...INTENTIONALLY LEFT BLANK iv ABSTRACT Physical network maps are important to critical infrastructure defense and planning. Cur- rent state-of-the-art

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

NASA Astrophysics Data System (ADS)

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

2015-11-01

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

Ranking Causal Anomalies via Temporal and Dynamical Analysis on Vanishing Correlations.

PubMed

Cheng, Wei; Zhang, Kai; Chen, Haifeng; Jiang, Guofei; Chen, Zhengzhang; Wang, Wei

2016-08-01

Modern world has witnessed a dramatic increase in our ability to collect, transmit and distribute real-time monitoring and surveillance data from large-scale information systems and cyber-physical systems. Detecting system anomalies thus attracts significant amount of interest in many fields such as security, fault management, and industrial optimization. Recently, invariant network has shown to be a powerful way in characterizing complex system behaviours. In the invariant network, a node represents a system component and an edge indicates a stable, significant interaction between two components. Structures and evolutions of the invariance network, in particular the vanishing correlations, can shed important light on locating causal anomalies and performing diagnosis. However, existing approaches to detect causal anomalies with the invariant network often use the percentage of vanishing correlations to rank possible casual components, which have several limitations: 1) fault propagation in the network is ignored; 2) the root casual anomalies may not always be the nodes with a high-percentage of vanishing correlations; 3) temporal patterns of vanishing correlations are not exploited for robust detection. To address these limitations, in this paper we propose a network diffusion based framework to identify significant causal anomalies and rank them. Our approach can effectively model fault propagation over the entire invariant network, and can perform joint inference on both the structural, and the time-evolving broken invariance patterns. As a result, it can locate high-confidence anomalies that are truly responsible for the vanishing correlations, and can compensate for unstructured measurement noise in the system. Extensive experiments on synthetic datasets, bank information system datasets, and coal plant cyber-physical system datasets demonstrate the effectiveness of our approach.

Perceived influence and college students' diet and physical activity behaviors: an examination of ego-centric social networks.

PubMed

Harmon, Brook E; Forthofer, Melinda; Bantum, Erin O; Nigg, Claudio R

2016-06-06

Obesity is partially a social phenomenon, with college students particularly vulnerable to changes in social networks and obesity-related behaviors. Currently, little is known about the structure of social networks among college students and their potential influence on diet and physical activity behaviors. The purpose of the study was to examine social influences impacting college students' diet and physical activity behaviors, including sources of influence, comparisons between sources' and students' behaviors, and associations with meeting diet and physical activity recommendations. Data was collected from 40 students attending college in Hawaii. Participants completed diet and physical activity questionnaires and a name generator. Participants rated nominees' influence on their diet and physical activity behaviors as well as compared nominees' behaviors to their own. Descriptive statistics were used to look at perceptions of influence across network groups. Logistic regression models were used to examine associations between network variables and odds of meeting recommendations. A total of 325 nominations were made and included: family (n = 116), college friends (n = 104), high school friends (n = 87), and significant others (n = 18). Nearly half of participants were not from Hawaii. Significant others of non-Hawaii students were perceived to be the most influential (M(SD) = 9(1.07)) and high school friends the least influential (M(SD) = 1.31(.42)) network. Overall, perceived influence was highest for diet compared to physical activity, but varied based on comparisons with nominees' behaviors. Significant others were most often perceived has having similar (44 %) or worse (39 %) eating behaviors than participants, and those with similar eating behaviors were perceived as most influential (M(SD) = 9.25(1.04)). Few associations were seen between network variables and odds of meeting recommendations. Among the groups nominated, high school friends were perceived as least influential, especially among students who moved a long distance for college. Intervention strategies addressing perceived norms and using peer leaders may help promote physical activity among college students, while diet interventions may need to involve significant others in order to be successful. Testing of these types of intervention strategies and continued examination of social networks and their influences on diet and physical activity behaviors are needed.

Interference Mitigation for Cyber-Physical Wireless Body Area Network System Using Social Networks.

PubMed

Zhang, Zhaoyang; Wang, Honggang; Wang, Chonggang; Fang, Hua

2013-06-01

Wireless body area networks (WBANs) are cyber-physical systems (CPS) that have emerged as a key technology to provide real-time health monitoring and ubiquitous healthcare services. WBANs could operate in dense environments such as in a hospital and lead to a high mutual communication interference in many application scenarios. The excessive interferences will significantly degrade the network performance including depleting the energy of WBAN nodes more quickly, and even eventually jeopardize people's lives due to unreliable (caused by the interference) healthcare data collections. Therefore, It is critical to mitigate the interference among WBANs to increase the reliability of the WBAN system while minimizing the system power consumption. Many existing approaches can deal with communication interference mitigation in general wireless networks but are not suitable for WBANs due to their ignoring the social nature of WBANs. Unlike the previous research, we for the first time propose a power game based approach to mitigate the communication interferences for WBANs based on the people's social interaction information. Our major contributions include: (1) model the inter-WBANs interference, and determine the distance distribution of the interference through both theoretical analysis and Monte Carlo simulations; (2) develop social interaction detection and prediction algorithms for people carrying WBANs; (3) develop a power control game based on the social interaction information to maximize the system's utility while minimize the energy consumption of WBANs system. The extensive simulation results show the effectiveness of the power control game for inter-WBAN interference mitigation using social interaction information. Our research opens a new research vista of WBANs using social networks.

Interference Mitigation for Cyber-Physical Wireless Body Area Network System Using Social Networks

PubMed Central

Zhang, Zhaoyang; Wang, Honggang; Wang, Chonggang; Fang, Hua

2014-01-01

Wireless body area networks (WBANs) are cyber-physical systems (CPS) that have emerged as a key technology to provide real-time health monitoring and ubiquitous healthcare services. WBANs could operate in dense environments such as in a hospital and lead to a high mutual communication interference in many application scenarios. The excessive interferences will significantly degrade the network performance including depleting the energy of WBAN nodes more quickly, and even eventually jeopardize people’s lives due to unreliable (caused by the interference) healthcare data collections. Therefore, It is critical to mitigate the interference among WBANs to increase the reliability of the WBAN system while minimizing the system power consumption. Many existing approaches can deal with communication interference mitigation in general wireless networks but are not suitable for WBANs due to their ignoring the social nature of WBANs. Unlike the previous research, we for the first time propose a power game based approach to mitigate the communication interferences for WBANs based on the people’s social interaction information. Our major contributions include: (1) model the inter-WBANs interference, and determine the distance distribution of the interference through both theoretical analysis and Monte Carlo simulations; (2) develop social interaction detection and prediction algorithms for people carrying WBANs; (3) develop a power control game based on the social interaction information to maximize the system’s utility while minimize the energy consumption of WBANs system. The extensive simulation results show the effectiveness of the power control game for inter-WBAN interference mitigation using social interaction information. Our research opens a new research vista of WBANs using social networks. PMID:25436180

Statistical mechanics of complex neural systems and high dimensional data

NASA Astrophysics Data System (ADS)

Advani, Madhu; Lahiri, Subhaneil; Ganguli, Surya

2013-03-01

Recent experimental advances in neuroscience have opened new vistas into the immense complexity of neuronal networks. This proliferation of data challenges us on two parallel fronts. First, how can we form adequate theoretical frameworks for understanding how dynamical network processes cooperate across widely disparate spatiotemporal scales to solve important computational problems? Second, how can we extract meaningful models of neuronal systems from high dimensional datasets? To aid in these challenges, we give a pedagogical review of a collection of ideas and theoretical methods arising at the intersection of statistical physics, computer science and neurobiology. We introduce the interrelated replica and cavity methods, which originated in statistical physics as powerful ways to quantitatively analyze large highly heterogeneous systems of many interacting degrees of freedom. We also introduce the closely related notion of message passing in graphical models, which originated in computer science as a distributed algorithm capable of solving large inference and optimization problems involving many coupled variables. We then show how both the statistical physics and computer science perspectives can be applied in a wide diversity of contexts to problems arising in theoretical neuroscience and data analysis. Along the way we discuss spin glasses, learning theory, illusions of structure in noise, random matrices, dimensionality reduction and compressed sensing, all within the unified formalism of the replica method. Moreover, we review recent conceptual connections between message passing in graphical models, and neural computation and learning. Overall, these ideas illustrate how statistical physics and computer science might provide a lens through which we can uncover emergent computational functions buried deep within the dynamical complexities of neuronal networks.

Cyber-Physical Test Platform for Microgrids: Combining Hardware, Hardware-in-the-Loop, and Network-Simulator-in-the-Loop

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

Nelson, Austin; Chakraborty, Sudipta; Wang, Dexin

This paper presents a cyber-physical testbed, developed to investigate the complex interactions between emerging microgrid technologies such as grid-interactive power sources, control systems, and a wide variety of communication platforms and bandwidths. The cyber-physical testbed consists of three major components for testing and validation: real time models of a distribution feeder model with microgrid assets that are integrated into the National Renewable Energy Laboratory's (NREL) power hardware-in-the-loop (PHIL) platform; real-time capable network-simulator-in-the-loop (NSIL) models; and physical hardware including inverters and a simple system controller. Several load profiles and microgrid configurations were tested to examine the effect on system performance withmore » increasing channel delays and router processing delays in the network simulator. Testing demonstrated that the controller's ability to maintain a target grid import power band was severely diminished with increasing network delays and laid the foundation for future testing of more complex cyber-physical systems.« less

Model-Driven Safety Analysis of Closed-Loop Medical Systems

PubMed Central

Pajic, Miroslav; Mangharam, Rahul; Sokolsky, Oleg; Arney, David; Goldman, Julian; Lee, Insup

2013-01-01

In modern hospitals, patients are treated using a wide array of medical devices that are increasingly interacting with each other over the network, thus offering a perfect example of a cyber-physical system. We study the safety of a medical device system for the physiologic closed-loop control of drug infusion. The main contribution of the paper is the verification approach for the safety properties of closed-loop medical device systems. We demonstrate, using a case study, that the approach can be applied to a system of clinical importance. Our method combines simulation-based analysis of a detailed model of the system that contains continuous patient dynamics with model checking of a more abstract timed automata model. We show that the relationship between the two models preserves the crucial aspect of the timing behavior that ensures the conservativeness of the safety analysis. We also describe system design that can provide open-loop safety under network failure. PMID:24177176

Model-Driven Safety Analysis of Closed-Loop Medical Systems.

PubMed

Pajic, Miroslav; Mangharam, Rahul; Sokolsky, Oleg; Arney, David; Goldman, Julian; Lee, Insup

2012-10-26

In modern hospitals, patients are treated using a wide array of medical devices that are increasingly interacting with each other over the network, thus offering a perfect example of a cyber-physical system. We study the safety of a medical device system for the physiologic closed-loop control of drug infusion. The main contribution of the paper is the verification approach for the safety properties of closed-loop medical device systems. We demonstrate, using a case study, that the approach can be applied to a system of clinical importance. Our method combines simulation-based analysis of a detailed model of the system that contains continuous patient dynamics with model checking of a more abstract timed automata model. We show that the relationship between the two models preserves the crucial aspect of the timing behavior that ensures the conservativeness of the safety analysis. We also describe system design that can provide open-loop safety under network failure.

Neural signal registration and analysis of axons grown in microchannels

NASA Astrophysics Data System (ADS)

Pigareva, Y.; Malishev, E.; Gladkov, A.; Kolpakov, V.; Bukatin, A.; Mukhina, I.; Kazantsev, V.; Pimashkin, A.

2016-08-01

Registration of neuronal bioelectrical signals remains one of the main physical tools to study fundamental mechanisms of signal processing in the brain. Neurons generate spiking patterns which propagate through complex map of neural network connectivity. Extracellular recording of isolated axons grown in microchannels provides amplification of the signal for detailed study of spike propagation. In this study we used neuronal hippocampal cultures grown in microfluidic devices combined with microelectrode arrays to investigate a changes of electrical activity during neural network development. We found that after 5 days in vitro after culture plating the spiking activity appears first in microchannels and on the next 2-3 days appears on the electrodes of overall neural network. We conclude that such approach provides a convenient method to study neural signal processing and functional structure development on a single cell and network level of the neuronal culture.

Overarching framework for data-based modelling

NASA Astrophysics Data System (ADS)

Schelter, Björn; Mader, Malenka; Mader, Wolfgang; Sommerlade, Linda; Platt, Bettina; Lai, Ying-Cheng; Grebogi, Celso; Thiel, Marco

2014-02-01

One of the main modelling paradigms for complex physical systems are networks. When estimating the network structure from measured signals, typically several assumptions such as stationarity are made in the estimation process. Violating these assumptions renders standard analysis techniques fruitless. We here propose a framework to estimate the network structure from measurements of arbitrary non-linear, non-stationary, stochastic processes. To this end, we propose a rigorous mathematical theory that underlies this framework. Based on this theory, we present a highly efficient algorithm and the corresponding statistics that are immediately sensibly applicable to measured signals. We demonstrate its performance in a simulation study. In experiments of transitions between vigilance stages in rodents, we infer small network structures with complex, time-dependent interactions; this suggests biomarkers for such transitions, the key to understand and diagnose numerous diseases such as dementia. We argue that the suggested framework combines features that other approaches followed so far lack.

Multilayer Network Analysis of Nuclear Reactions

NASA Astrophysics Data System (ADS)

Zhu, Liang; Ma, Yu-Gang; Chen, Qu; Han, Ding-Ding

2016-08-01

The nuclear reaction network is usually studied via precise calculation of differential equation sets, and much research interest has been focused on the characteristics of nuclides, such as half-life and size limit. In this paper, however, we adopt the methods from both multilayer and reaction networks, and obtain a distinctive view by mapping all the nuclear reactions in JINA REACLIB database into a directed network with 4 layers: neutron, proton, 4He and the remainder. The layer names correspond to reaction types decided by the currency particles consumed. This combined approach reveals that, in the remainder layer, the β-stability has high correlation with node degree difference and overlapping coefficient. Moreover, when reaction rates are considered as node strength, we find that, at lower temperatures, nuclide half-life scales reciprocally with its out-strength. The connection between physical properties and topological characteristics may help to explore the boundary of the nuclide chart.

Parallel discrete-event simulation of FCFS stochastic queueing networks

NASA Technical Reports Server (NTRS)

Nicol, David M.

1988-01-01

Physical systems are inherently parallel. Intuition suggests that simulations of these systems may be amenable to parallel execution. The parallel execution of a discrete-event simulation requires careful synchronization of processes in order to ensure the execution's correctness; this synchronization can degrade performance. Largely negative results were recently reported in a study which used a well-known synchronization method on queueing network simulations. Discussed here is a synchronization method (appointments), which has proven itself to be effective on simulations of FCFS queueing networks. The key concept behind appointments is the provision of lookahead. Lookahead is a prediction on a processor's future behavior, based on an analysis of the processor's simulation state. It is shown how lookahead can be computed for FCFS queueing network simulations, give performance data that demonstrates the method's effectiveness under moderate to heavy loads, and discuss performance tradeoffs between the quality of lookahead, and the cost of computing lookahead.

Physical inactivity mediates the association between the perceived exercising behavior of social network members and obesity: a cross-sectional study.

PubMed

Leroux, Janette S; Moore, Spencer; Richard, Lucie; Gauvin, Lise

2012-01-01

Social networks influence the spread of depression, health behaviors, and obesity. The social networks of older urban-dwelling adults were examined to assess whether physical inactivity mediated the association between social networks and obesity. Data come from the Montreal Neighborhood Networks and Healthy Aging study (n=2707). Self-reported height and weight were used to calculate body mass index (BMI) with obesity defined as a BMI ≥ 30. A name generator/interpreter instrument was used to elicit participants' core ties (i.e., alters), and assess whether alters exercised regularly and resided in participants' neighborhoods. The International Physical Activity Questionnaire was used to measure physical inactivity. Separate multilevel logistic regression analyses were conducted for younger (18-54 years) and older (55 years plus) age groups to examine the association between the exercising behavior of alters and obesity. Ancillary analyses examined whether the residential location of alters was associated with obesity. Mediation analyses assessed whether physical inactivity mediated the association between alter exercising behavior and obesity. Models adjusted for participant socio-demographic and -economic characteristics. Among the older age stratum (55 years plus), physically inactive individuals were more likely obese (OR 2.14; 95% CIs: 1.48-3.10); participants who had more exercising alters were less likely obese (OR: 0.85; 95% CIs: 0.72-0.99). Physical inactivity mediated the association between exercising alters and obesity. Ancillary analyses showed that having exercising alters in the neighborhood compared to other locations tended to reduce the odds of obesity. This work demonstrates the importance of social networks among older adults in facilitating a physically active lifestyle and reducing the odds of obesity. Such findings can inform the design of public health interventions that seek to improve the environmental conditions supporting the physical activity of older adults.

A macrochip interconnection network enabled by silicon nanophotonic devices.

PubMed

Zheng, Xuezhe; Cunningham, John E; Koka, Pranay; Schwetman, Herb; Lexau, Jon; Ho, Ron; Shubin, Ivan; Krishnamoorthy, Ashok V; Yao, Jin; Mekis, Attila; Pinguet, Thierry

2010-03-01

We present an advanced wavelength-division multiplexing point-to-point network enabled by silicon nanophotonic devices. This network offers strictly non-blocking all-to-all connectivity while maximizing bisection bandwidth, making it ideal for multi-core and multi-processor interconnections. We introduce one of the key components, the nanophotonic grating coupler, and discuss, for the first time, how this device can be useful for practical implementations of the wavelength-division multiplexing network using optical proximity communications. Finite difference time-domain simulation of the nanophotonic grating coupler device indicates that it can be made compact (20 microm x 50 microm), low loss (3.8 dB), and broadband (100 nm). These couplers require subwavelength material modulation at the nanoscale to achieve the desired functionality. We show that optical proximity communication provides unmatched optical I/O bandwidth density to electrical chips, which enables the application of wavelength-division multiplexing point-to-point network in macrochip with unprecedented bandwidth-density. The envisioned physical implementation is discussed. The benefits of such an interconnect network include a 5-6x improvement in latency when compared to a purely electronic implementation. Performance analysis shows that the wavelength-division multiplexing point-to-point network offers better overall performance over other optical network architectures.

Network model of bilateral power markets based on complex networks

NASA Astrophysics Data System (ADS)

Wu, Yang; Liu, Junyong; Li, Furong; Yan, Zhanxin; Zhang, Li

2014-06-01

The bilateral power transaction (BPT) mode becomes a typical market organization with the restructuring of electric power industry, the proper model which could capture its characteristics is in urgent need. However, the model is lacking because of this market organization's complexity. As a promising approach to modeling complex systems, complex networks could provide a sound theoretical framework for developing proper simulation model. In this paper, a complex network model of the BPT market is proposed. In this model, price advantage mechanism is a precondition. Unlike other general commodity transactions, both of the financial layer and the physical layer are considered in the model. Through simulation analysis, the feasibility and validity of the model are verified. At same time, some typical statistical features of BPT network are identified. Namely, the degree distribution follows the power law, the clustering coefficient is low and the average path length is a bit long. Moreover, the topological stability of the BPT network is tested. The results show that the network displays a topological robustness to random market member's failures while it is fragile against deliberate attacks, and the network could resist cascading failure to some extent. These features are helpful for making decisions and risk management in BPT markets.

Design and Analysis of a Data Fusion Scheme in Mobile Wireless Sensor Networks Based on Multi-Protocol Mobile Agents

PubMed Central

Wu, Chunxue; Wu, Wenliang; Wan, Caihua

2017-01-01

Sensors are increasingly used in mobile environments with wireless network connections. Multiple sensor types measure distinct aspects of the same event. Their measurements are then combined to produce integrated, reliable results. As the number of sensors in networks increases, low energy requirements and changing network connections complicate event detection and measurement. We present a data fusion scheme for use in mobile wireless sensor networks with high energy efficiency and low network delays, that still produces reliable results. In the first phase, we used a network simulation where mobile agents dynamically select the next hop migration node based on the stability parameter of the link, and perform the data fusion at the migration node. Agents use the fusion results to decide if it should return the fusion results to the processing center or continue to collect more data. In the second phase. The feasibility of data fusion at the node level is confirmed by an experimental design where fused data from color sensors show near-identical results to actual physical temperatures. These results are potentially important for new large-scale sensor network applications. PMID:29099793

Multi-criteria robustness analysis of metro networks

NASA Astrophysics Data System (ADS)

Wang, Xiangrong; Koç, Yakup; Derrible, Sybil; Ahmad, Sk Nasir; Pino, Willem J. A.; Kooij, Robert E.

2017-05-01

Metros (heavy rail transit systems) are integral parts of urban transportation systems. Failures in their operations can have serious impacts on urban mobility, and measuring their robustness is therefore critical. Moreover, as physical networks, metros can be viewed as topological entities, and as such they possess measurable network properties. In this article, by using network science and graph theory, we investigate ten theoretical and four numerical robustness metrics and their performance in quantifying the robustness of 33 metro networks under random failures or targeted attacks. We find that the ten theoretical metrics capture two distinct aspects of robustness of metro networks. First, several metrics place an emphasis on alternative paths. Second, other metrics place an emphasis on the length of the paths. To account for all aspects, we standardize all ten indicators and plot them on radar diagrams to assess the overall robustness for metro networks. Overall, we find that Tokyo and Rome are the most robust networks. Rome benefits from short transferring and Tokyo has a significant number of transfer stations, both in the city center and in the peripheral area of the city, promoting both a higher number of alternative paths and overall relatively short path-lengths.

Joint physical and numerical modeling of water distribution networks.

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

Zimmerman, Adam; O'Hern, Timothy John; Orear, Leslie Jr.

2009-01-01

This report summarizes the experimental and modeling effort undertaken to understand solute mixing in a water distribution network conducted during the last year of a 3-year project. The experimental effort involves measurement of extent of mixing within different configurations of pipe networks, measurement of dynamic mixing in a single mixing tank, and measurement of dynamic solute mixing in a combined network-tank configuration. High resolution analysis of turbulence mixing is carried out via high speed photography as well as 3D finite-volume based Large Eddy Simulation turbulence models. Macroscopic mixing rules based on flow momentum balance are also explored, and in somemore » cases, implemented in EPANET. A new version EPANET code was developed to yield better mixing predictions. The impact of a storage tank on pipe mixing in a combined pipe-tank network during diurnal fill-and-drain cycles is assessed. Preliminary comparison between dynamic pilot data and EPANET-BAM is also reported.« less

Measuring accessibility of sustainable transportation using space syntax in Bojonggede area

NASA Astrophysics Data System (ADS)

Suryawinata, B. A.; Mariana, Y.; Wijaksono, S.

2017-12-01

Changes in the physical structure of regional space as a result of the increase of planned and unplanned settlements in the Bojonggede area have an impact on the road network pattern system. Changes in road network patterns will have an impact on the permeability of the area. Permeability measures the extent to which road network patterns provide an option in traveling. If the permeability increases the travel distance decreases and the route of travel choice increases, permeability like this can create an easy access system and physically integrated. This study aims to identify the relationship of physical characteristics of residential area and road network pattern to the level of space permeability in Bojonggede area. By conducting this research can be a reference for the arrangement of circulation, accessibility, and land use in the vicinity of Bojonggede. This research uses quantitative method and space syntax method to see global integration and local integration on the region which become the parameter of permeability level. The results showed that the level of permeability globally and locally high in Bojonggede physical area is the physical characteristics of the area that has a grid pattern of road network grid.

[Role of the social support network which influences age of death and physical function of elderly people: study of trends in and outside of Japan and future problems].

PubMed

Kishi, Reiko; Horikawa, Naoko

2004-02-01

Concerning associations between the social support network and physical health of the elderly, longitudinal studies have been conducted using various measurement indexes. The studies indicated that the support network influences on physical function and life expectancy. In this study we compared research papers from Japan and elsewhere that appeared after 1980, from the viewpoint of 1) social support effects, and 2) social network effects, to examine potential problems in the future. The main knowledge obtained was that the receipt of emotional support, wide network size, and participation in social activities reduced the risk of early death and decrease in physical function of elderly people. Sex differences were indicated, and in many cases, the effects were more remarkable in men than women. In addition the positive influence of receiving help from a support network, a major subject of conventional research, the effects of offering help to others and negative findings were also examined. It has been indicated that participation in volunteer groups and offer of support to other people can prevent decrease in physical function or early death. As negative effects, improper instrumental support rather disturbs the mental and physical independence of elderly people. As future issues, it is necessary to focus on both positive/negative and receipt/offer effects of support network, and to clarify how to provide example which best match the life of elderly people by comparing sexes and regions. It is also important to actually apply the knowledge gained from observational studies to prevent the elderly from becoming a condition requiring care, and to develop intervention studies which can increase the social contacts of elderly people at the same time as conducting health education and medical treatment.

Comparison of classical statistical methods and artificial neural network in traffic noise prediction

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

Nedic, Vladimir, E-mail: vnedic@kg.ac.rs; Despotovic, Danijela, E-mail: ddespotovic@kg.ac.rs; Cvetanovic, Slobodan, E-mail: slobodan.cvetanovic@eknfak.ni.ac.rs

2014-11-15

Traffic is the main source of noise in urban environments and significantly affects human mental and physical health and labor productivity. Therefore it is very important to model the noise produced by various vehicles. Techniques for traffic noise prediction are mainly based on regression analysis, which generally is not good enough to describe the trends of noise. In this paper the application of artificial neural networks (ANNs) for the prediction of traffic noise is presented. As input variables of the neural network, the proposed structure of the traffic flow and the average speed of the traffic flow are chosen. Themore » output variable of the network is the equivalent noise level in the given time period L{sub eq}. Based on these parameters, the network is modeled, trained and tested through a comparative analysis of the calculated values and measured levels of traffic noise using the originally developed user friendly software package. It is shown that the artificial neural networks can be a useful tool for the prediction of noise with sufficient accuracy. In addition, the measured values were also used to calculate equivalent noise level by means of classical methods, and comparative analysis is given. The results clearly show that ANN approach is superior in traffic noise level prediction to any other statistical method. - Highlights: • We proposed an ANN model for prediction of traffic noise. • We developed originally designed user friendly software package. • The results are compared with classical statistical methods. • The results are much better predictive capabilities of ANN model.« less

Modeling socio-cultural processes in network-centric environments

NASA Astrophysics Data System (ADS)

Santos, Eunice E.; Santos, Eugene, Jr.; Korah, John; George, Riya; Gu, Qi; Kim, Keumjoo; Li, Deqing; Russell, Jacob; Subramanian, Suresh

2012-05-01

The major focus in the field of modeling & simulation for network centric environments has been on the physical layer while making simplifications for the human-in-the-loop. However, the human element has a big impact on the capabilities of network centric systems. Taking into account the socio-behavioral aspects of processes such as team building, group decision-making, etc. are critical to realistically modeling and analyzing system performance. Modeling socio-cultural processes is a challenge because of the complexity of the networks, dynamism in the physical and social layers, feedback loops and uncertainty in the modeling data. We propose an overarching framework to represent, model and analyze various socio-cultural processes within network centric environments. The key innovation in our methodology is to simultaneously model the dynamism in both the physical and social layers while providing functional mappings between them. We represent socio-cultural information such as friendships, professional relationships and temperament by leveraging the Culturally Infused Social Network (CISN) framework. The notion of intent is used to relate the underlying socio-cultural factors to observed behavior. We will model intent using Bayesian Knowledge Bases (BKBs), a probabilistic reasoning network, which can represent incomplete and uncertain socio-cultural information. We will leverage previous work on a network performance modeling framework called Network-Centric Operations Performance and Prediction (N-COPP) to incorporate dynamism in various aspects of the physical layer such as node mobility, transmission parameters, etc. We validate our framework by simulating a suitable scenario, incorporating relevant factors and providing analyses of the results.

Interfacing a General Purpose Fluid Network Flow Program with the SINDA/G Thermal Analysis Program

NASA Technical Reports Server (NTRS)

Schallhorn, Paul; Popok, Daniel

1999-01-01

A general purpose, one dimensional fluid flow code is currently being interfaced with the thermal analysis program Systems Improved Numerical Differencing Analyzer/Gaski (SINDA/G). The flow code, Generalized Fluid System Simulation Program (GFSSP), is capable of analyzing steady state and transient flow in a complex network. The flow code is capable of modeling several physical phenomena including compressibility effects, phase changes, body forces (such as gravity and centrifugal) and mixture thermodynamics for multiple species. The addition of GFSSP to SINDA/G provides a significant improvement in convective heat transfer modeling for SINDA/G. The interface development is conducted in multiple phases. This paper describes the first phase of the interface which allows for steady and quasi-steady (unsteady solid, steady fluid) conjugate heat transfer modeling.

Real-Time Joint Streaming Data Processing from Social and Physical Sensors

NASA Astrophysics Data System (ADS)

Kropivnitskaya, Y. Y.; Qin, J.; Tiampo, K. F.; Bauer, M.

2014-12-01

The results of the technological breakthroughs in computing that have taken place over the last few decades makes it possible to achieve emergency management objectives that focus on saving human lives and decreasing economic effects. In particular, the integration of a wide variety of information sources, including observations from spatially-referenced physical sensors and new social media sources, enables better real-time seismic hazard analysis through distributed computing networks. The main goal of this work is to utilize innovative computational algorithms for better real-time seismic risk analysis by integrating different data sources and processing tools into streaming and cloud computing applications. The Geological Survey of Canada operates the Canadian National Seismograph Network (CNSN) with over 100 high-gain instruments and 60 low-gain or strong motion seismographs. The processing of the continuous data streams from each station of the CNSN provides the opportunity to detect possible earthquakes in near real-time. The information from physical sources is combined to calculate a location and magnitude for an earthquake. The automatically calculated results are not always sufficiently precise and prompt that can significantly reduce the response time to a felt or damaging earthquake. Social sensors, here represented as Twitter users, can provide information earlier to the general public and more rapidly to the emergency planning and disaster relief agencies. We introduce joint streaming data processing from social and physical sensors in real-time based on the idea that social media observations serve as proxies for physical sensors. By using the streams of data in the form of Twitter messages, each of which has an associated time and location, we can extract information related to a target event and perform enhanced analysis by combining it with physical sensor data. Results of this work suggest that the use of data from social media, in conjunction with the development of innovative computing algorithms, when combined with sensor data can provide a new paradigm for real-time earthquake detection in order to facilitate rapid and inexpensive natural risk reduction.

The “Picardie en Forme” Network: Federating Regional Health-enhancing Sports Resources

PubMed

Weissland, Thierry; Passavant, Éric; Allal, Aziz; Amiard, Valérie; Antczak, Boris; Manzo, Julie

2016-06-08

Initiated by the Regional Olympic and Sports Committee and the Regional Directorate of Youth, Sports and Social Cohesion, the “Picardie en Forme” network has been working since 2011 in favour of adults of all ages, with chronic noncommunicable or similar diseases, to encourage a gradual return to reassuring and perennial regular physical activity,. A first step consisted of organizing a care pathway based on two principles: inform general practitioners so that they can encourage their patients to be physically active by referring them to the network, develop a range of local sports by accrediting certain clubs with sports instructors who have been trained in the management of this specific population. In 2013, 121 users entered the network at the request of 61 doctors. 48 sports instructors were trained and 20 associations obtained the Picardie en Forme label. Comparison of the results of tests performed on entry in the network and then eight months later shows a general physical reconditioning of users, increasing their motivation and perceived physical value. However, despite these encouraging results, the network has difficulty retaining users, and maintaining the involvement of general practitioners and certain local partners. This article discusses the relevance of initial approaches and describes the changes made to sustain this regional network, which, for the first time, links sport, health and users.

The feasibility of measuring social networks among older adults in assisted living and dementia special care units.

PubMed

Abbott, Katherine M; Bettger, Janet Prvu; Hampton, Keith N; Kohler, Hans-Peter

2015-03-01

Studies indicate that social integration has a significant influence on physical and mental health. Older adults experience an increased risk of social isolation as their social networks decline with fewer traditional opportunities to add new social relationships. Deaths of similar aged friends, cognitive and functional impairments, and relocating to a nursing home (NH) or assisted-living (AL) facility contribute to difficulties in maintaining one's social network. Due to the paucity of research examining the social networks of people residing in AL and NH, this study was designed to develop and test the feasibility of using a combination of methodological approaches to capture social network data among older adults living in AL and a dementia special care unit NH. Social network analysis of both egocentric and sociocentric networks was conducted to visualize the social networks of 15 residents of an AL neighborhood and 12 residents of a dementia special care unit NH and to calculate measures network size, centrality, and reciprocity. The combined egocentric and sociocentric method was feasible and provided a robust indicator of resident social networks highlighting individuals who were socially integrated as well as isolated. © The Author(s) 2013 Reprints and permissions: sagepub.co.uk/journalsPermissions.nav.

Coupled disease-behavior dynamics on complex networks: A review.

PubMed

Wang, Zhen; Andrews, Michael A; Wu, Zhi-Xi; Wang, Lin; Bauch, Chris T

2015-12-01

It is increasingly recognized that a key component of successful infection control efforts is understanding the complex, two-way interaction between disease dynamics and human behavioral and social dynamics. Human behavior such as contact precautions and social distancing clearly influence disease prevalence, but disease prevalence can in turn alter human behavior, forming a coupled, nonlinear system. Moreover, in many cases, the spatial structure of the population cannot be ignored, such that social and behavioral processes and/or transmission of infection must be represented with complex networks. Research on studying coupled disease-behavior dynamics in complex networks in particular is growing rapidly, and frequently makes use of analysis methods and concepts from statistical physics. Here, we review some of the growing literature in this area. We contrast network-based approaches to homogeneous-mixing approaches, point out how their predictions differ, and describe the rich and often surprising behavior of disease-behavior dynamics on complex networks, and compare them to processes in statistical physics. We discuss how these models can capture the dynamics that characterize many real-world scenarios, thereby suggesting ways that policy makers can better design effective prevention strategies. We also describe the growing sources of digital data that are facilitating research in this area. Finally, we suggest pitfalls which might be faced by researchers in the field, and we suggest several ways in which the field could move forward in the coming years. Copyright © 2015 Elsevier B.V. All rights reserved.

Connectomic Insights into Topologically Centralized Network Edges and Relevant Motifs in the Human Brain

PubMed Central

Xia, Mingrui; Lin, Qixiang; Bi, Yanchao; He, Yong

2016-01-01

White matter (WM) tracts serve as important material substrates for information transfer across brain regions. However, the topological roles of WM tracts in global brain communications and their underlying microstructural basis remain poorly understood. Here, we employed diffusion magnetic resonance imaging and graph-theoretical approaches to identify the pivotal WM connections in human whole-brain networks and further investigated their wiring substrates (including WM microstructural organization and physical consumption) and topological contributions to the brain's network backbone. We found that the pivotal WM connections with highly topological-edge centrality were primarily distributed in several long-range cortico-cortical connections (including the corpus callosum, cingulum and inferior fronto-occipital fasciculus) and some projection tracts linking subcortical regions. These pivotal WM connections exhibited high levels of microstructural organization indicated by diffusion measures (the fractional anisotropy, the mean diffusivity and the axial diffusivity) and greater physical consumption indicated by streamline lengths, and contributed significantly to the brain's hubs and the rich-club structure. Network motif analysis further revealed their heavy participations in the organization of communication blocks, especially in routes involving inter-hemispheric heterotopic and extremely remote intra-hemispheric systems. Computational simulation models indicated the sharp decrease of global network integrity when attacking these highly centralized edges. Together, our results demonstrated high building-cost consumption and substantial communication capacity contributions for pivotal WM connections, which deepens our understanding of the topological mechanisms that govern the organization of human connectomes. PMID:27148015

Connectomic Insights into Topologically Centralized Network Edges and Relevant Motifs in the Human Brain.

PubMed

Xia, Mingrui; Lin, Qixiang; Bi, Yanchao; He, Yong

2016-01-01

White matter (WM) tracts serve as important material substrates for information transfer across brain regions. However, the topological roles of WM tracts in global brain communications and their underlying microstructural basis remain poorly understood. Here, we employed diffusion magnetic resonance imaging and graph-theoretical approaches to identify the pivotal WM connections in human whole-brain networks and further investigated their wiring substrates (including WM microstructural organization and physical consumption) and topological contributions to the brain's network backbone. We found that the pivotal WM connections with highly topological-edge centrality were primarily distributed in several long-range cortico-cortical connections (including the corpus callosum, cingulum and inferior fronto-occipital fasciculus) and some projection tracts linking subcortical regions. These pivotal WM connections exhibited high levels of microstructural organization indicated by diffusion measures (the fractional anisotropy, the mean diffusivity and the axial diffusivity) and greater physical consumption indicated by streamline lengths, and contributed significantly to the brain's hubs and the rich-club structure. Network motif analysis further revealed their heavy participations in the organization of communication blocks, especially in routes involving inter-hemispheric heterotopic and extremely remote intra-hemispheric systems. Computational simulation models indicated the sharp decrease of global network integrity when attacking these highly centralized edges. Together, our results demonstrated high building-cost consumption and substantial communication capacity contributions for pivotal WM connections, which deepens our understanding of the topological mechanisms that govern the organization of human connectomes.

Sociospace: A smart social framework based on the IP Multimedia Subsystem

NASA Astrophysics Data System (ADS)

Hasswa, Ahmed

Advances in smart technologies, wireless networking, and increased interest in contextual services have led to the emergence of ubiquitous and pervasive computing as one of the most promising areas of computing in recent years. Smart Spaces, in particular, have gained significant interest within the research community. Currently, most Smart Spaces rely on physical components, such as sensors, to acquire information about the real-world environment. Although current sensor networks can acquire some useful contextual information from the physical environment, their information resources are often limited, and the data acquired is often unreliable. We argue that by introducing social network information into such systems, smarter and more adaptive spaces can be created. Social networks have recently become extremely popular, and are now an integral part of millions of people's daily lives. Through social networks, users create profiles, build relationships, and join groups, forming intermingled sets and communities. Social Networks contain a wealth of information, which, if exploited properly, can lead to a whole new level of smart contextual services. A mechanism is therefore needed to extract data from heterogeneous social networks, to link profiles across different networks, and to aggregate the data obtained. We therefore propose the design and implementation of a Smart Spaces framework that utilizes the social context. In order to manage services and sessions, we integrate our system with the IP Multimedia Subsystem. Our system, which we call SocioSpace, includes full design and implementation of all components, including the central server, the location management system, the social network interfacing system, the service delivery platform, and user agents. We have built a prototype for proof of concept and carried out exhaustive performance analysis; the results show that SocioSpace is scalable, extensible, and fault-tolerant. It is capable of creating Smart Spaces that can truly deliver adaptive services that enhance the users' overall experience, increase their satisfaction, and make the surroundings more beneficial and interesting to them.

Computationally efficient characterization of potential energy surfaces based on fingerprint distances

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

Schaefer, Bastian; Goedecker, Stefan, E-mail: stefan.goedecker@unibas.ch

2016-07-21

An analysis of the network defined by the potential energy minima of multi-atomic systems and their connectivity via reaction pathways that go through transition states allows us to understand important characteristics like thermodynamic, dynamic, and structural properties. Unfortunately computing the transition states and reaction pathways in addition to the significant energetically low-lying local minima is a computationally demanding task. We here introduce a computationally efficient method that is based on a combination of the minima hopping global optimization method and the insight that uphill barriers tend to increase with increasing structural distances of the educt and product states. This methodmore » allows us to replace the exact connectivity information and transition state energies with alternative and approximate concepts. Without adding any significant additional cost to the minima hopping global optimization approach, this method allows us to generate an approximate network of the minima, their connectivity, and a rough measure for the energy needed for their interconversion. This can be used to obtain a first qualitative idea on important physical and chemical properties by means of a disconnectivity graph analysis. Besides the physical insight obtained by such an analysis, the gained knowledge can be used to make a decision if it is worthwhile or not to invest computational resources for an exact computation of the transition states and the reaction pathways. Furthermore it is demonstrated that the here presented method can be used for finding physically reasonable interconversion pathways that are promising input pathways for methods like transition path sampling or discrete path sampling.« less

Scale-free networks which are highly assortative but not small world

NASA Astrophysics Data System (ADS)

Small, Michael; Xu, Xiaoke; Zhou, Jin; Zhang, Jie; Sun, Junfeng; Lu, Jun-An

2008-06-01

Uncorrelated scale-free networks are necessarily small world (and, in fact, smaller than small world). Nonetheless, for scale-free networks with correlated degree distribution this may not be the case. We describe a mechanism to generate highly assortative scale-free networks which are not small world. We show that it is possible to generate scale-free networks, with arbitrary degree exponent γ>1 , such that the average distance between nodes in the network is large. To achieve this, nodes are not added to the network with preferential attachment. Instead, we greedily optimize the assortativity of the network. The network generation scheme is physically motivated, and we show that the recently observed global network of Avian Influenza outbreaks arises through a mechanism similar to what we present here. Simulations show that this network exhibits very similar physical characteristics (very high assortativity, clustering, and path length).

Automated method for the systematic interpretation of resonance peaks in spectrum data

DOEpatents

Damiano, B.; Wood, R.T.

1997-04-22

A method is described for spectral signature interpretation. The method includes the creation of a mathematical model of a system or process. A neural network training set is then developed based upon the mathematical model. The neural network training set is developed by using the mathematical model to generate measurable phenomena of the system or process based upon model input parameter that correspond to the physical condition of the system or process. The neural network training set is then used to adjust internal parameters of a neural network. The physical condition of an actual system or process represented by the mathematical model is then monitored by extracting spectral features from measured spectra of the actual process or system. The spectral features are then input into said neural network to determine the physical condition of the system or process represented by the mathematical model. More specifically, the neural network correlates the spectral features (i.e. measurable phenomena) of the actual process or system with the corresponding model input parameters. The model input parameters relate to specific components of the system or process, and, consequently, correspond to the physical condition of the process or system. 1 fig.

Automated method for the systematic interpretation of resonance peaks in spectrum data

DOEpatents

Damiano, Brian; Wood, Richard T.

1997-01-01

A method for spectral signature interpretation. The method includes the creation of a mathematical model of a system or process. A neural network training set is then developed based upon the mathematical model. The neural network training set is developed by using the mathematical model to generate measurable phenomena of the system or process based upon model input parameter that correspond to the physical condition of the system or process. The neural network training set is then used to adjust internal parameters of a neural network. The physical condition of an actual system or process represented by the mathematical model is then monitored by extracting spectral features from measured spectra of the actual process or system. The spectral features are then input into said neural network to determine the physical condition of the system or process represented by the mathematical. More specifically, the neural network correlates the spectral features (i.e. measurable phenomena) of the actual process or system with the corresponding model input parameters. The model input parameters relate to specific components of the system or process, and, consequently, correspond to the physical condition of the process or system.

Veterans with recent substance use and aggression: PTSD, substance use, and social network behaviors.

PubMed

Sexton, Minden B; Davis, Alan K; Buchholz, Katherine R; Winters, Jamie J; Rauch, Sheila A M; Yzquibell, Maegan; Bonar, Erin E; Friday, Steven; Chermack, Stephen T

2018-04-23

Violence is a salient concern among veterans, yet relationships between psychiatric comorbidity, social networks, and aggression are poorly understood. We examined associations between biopsychosocial factors (substance use, posttraumatic stress disorder [PTSD], and social network behaviors) with aggression. We recruited veterans endorsing past-year aggression and substance use (N = 180) from Department of Veterans Affairs outpatient treatment clinics. Main and interaction effects between probable PTSD, substance use, social network violence and substance use, and veteran violence were examined with negative binomial regressions-specifically, physical aggression toward a relationship partner (PA-P), physical injury of a partner (PI-P), physical aggression toward nonpartners (PA-NP), and physical injury of nonpartners (PI-NP). Alcohol use yielded consistent main effects. PTSD and social network violence demonstrated main effects for PA-NP and PI-NP. PTSD and social network violence interacted to predict PA-P such that social network violence appeared salient only in the context of PTSD. PTSD was associated with PI-P, PA-NP, and PI-NP in social network substance use models. In the PA-P model including social network substance use, veterans with PTSD reported greater PA-P in the context of greater social network substance use, whereas veterans without PTSD endorsed PA-P concurrent with greater alcohol frequency. For PI-P, PTSD interacted with alcohol to predict a greater likelihood of partner injury in the context of social network substance use. Investigated variables demonstrated unique associations within the context of specific relationships and the severity of behaviors. Overall, the findings underscore the importance of biopsychosocial models for understanding veteran violence. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

International comparison of observation-specific spatial buffers: maximizing the ability to estimate physical activity.

PubMed

Frank, Lawrence D; Fox, Eric H; Ulmer, Jared M; Chapman, James E; Kershaw, Suzanne E; Sallis, James F; Conway, Terry L; Cerin, Ester; Cain, Kelli L; Adams, Marc A; Smith, Graham R; Hinckson, Erica; Mavoa, Suzanne; Christiansen, Lars B; Hino, Adriano Akira F; Lopes, Adalberto A S; Schipperijn, Jasper

2017-01-23

Advancements in geographic information systems over the past two decades have increased the specificity by which an individual's neighborhood environment may be spatially defined for physical activity and health research. This study investigated how different types of street network buffering methods compared in measuring a set of commonly used built environment measures (BEMs) and tested their performance on associations with physical activity outcomes. An internationally-developed set of objective BEMs using three different spatial buffering techniques were used to evaluate the relative differences in resulting explanatory power on self-reported physical activity outcomes. BEMs were developed in five countries using 'sausage,' 'detailed-trimmed,' and 'detailed,' network buffers at a distance of 1 km around participant household addresses (n = 5883). BEM values were significantly different (p < 0.05) for 96% of sausage versus detailed-trimmed buffer comparisons and 89% of sausage versus detailed network buffer comparisons. Results showed that BEM coefficients in physical activity models did not differ significantly across buffering methods, and in most cases BEM associations with physical activity outcomes had the same level of statistical significance across buffer types. However, BEM coefficients differed in significance for 9% of the sausage versus detailed models, which may warrant further investigation. Results of this study inform the selection of spatial buffering methods to estimate physical activity outcomes using an internationally consistent set of BEMs. Using three different network-based buffering methods, the findings indicate significant variation among BEM values, however associations with physical activity outcomes were similar across each buffering technique. The study advances knowledge by presenting consistently assessed relationships between three different network buffer types and utilitarian travel, sedentary behavior, and leisure-oriented physical activity outcomes.

Role of physical and mental training in brain network configuration

PubMed Central

Foster, Philip P.

2015-01-01

It is hypothesized that the topology of brain networks is constructed by connecting nodes which may be continuously remodeled by appropriate training. Efficiency of physical and/or mental training on the brain relies on the flexibility of networks' architecture molded by local remodeling of proteins and synapses of excitatory neurons producing transformations in network topology. Continuous remodeling of proteins of excitatory neurons is fine-tuning the scaling and strength of excitatory synapses up or down via regulation of intra-cellular metabolic and regulatory networks of the genome-transcriptome-proteome interface. Alzheimer's disease is a model of “energy cost-driven small-world network disorder” with dysfunction of high-energy cost wiring as the network global efficiency is impaired by the deposition of an informed agent, the amyloid-β, selectively targeting high-degree nodes. In schizophrenia, the interconnectivity and density of rich-club networks are significantly reduced. Training-induced homeostatic synaptogenesis-enhancement, presumably via reconfiguration of brain networks into greater small-worldness, appears essential in learning, memory, and executive functions. A macroscopic cartography of creation-removal of synaptic connections in a macro-network, and at the intra-cellular scale, micro-networks regulate the physiological mechanisms for the preferential attachment of synapses. The strongest molecular relationship of exercise and functional connectivity was identified for brain-derived neurotrophic factor (BDNF). The allele variant, rs7294919, also shows a powerful relationship with the hippocampal volume. How the brain achieves this unique quest of reconfiguration remains a puzzle. What are the underlying mechanisms of synaptogenesis promoting communications brain ↔ muscle and brain ↔ brain in such trainings? What is the respective role of independent mental, physical, or combined-mental-physical trainings? Physical practice seems to be playing an instrumental role in the cognitive enhancement (brain ↔ muscle com.). However, mental training, meditation or virtual reality (films, games) require only minimal motor activity and cardio-respiratory stimulation. Therefore, other potential paths (brain ↔ brain com.) molding brain networks are nonetheless essential. Patients with motor neuron disease/injury (e.g., amyotrophic lateral sclerosis, traumatism) also achieve successful cognitive enhancement albeit they may only elicit mental practice. PMID:26157387

Role of physical and mental training in brain network configuration.

PubMed

Foster, Philip P

2015-01-01

It is hypothesized that the topology of brain networks is constructed by connecting nodes which may be continuously remodeled by appropriate training. Efficiency of physical and/or mental training on the brain relies on the flexibility of networks' architecture molded by local remodeling of proteins and synapses of excitatory neurons producing transformations in network topology. Continuous remodeling of proteins of excitatory neurons is fine-tuning the scaling and strength of excitatory synapses up or down via regulation of intra-cellular metabolic and regulatory networks of the genome-transcriptome-proteome interface. Alzheimer's disease is a model of "energy cost-driven small-world network disorder" with dysfunction of high-energy cost wiring as the network global efficiency is impaired by the deposition of an informed agent, the amyloid-β, selectively targeting high-degree nodes. In schizophrenia, the interconnectivity and density of rich-club networks are significantly reduced. Training-induced homeostatic synaptogenesis-enhancement, presumably via reconfiguration of brain networks into greater small-worldness, appears essential in learning, memory, and executive functions. A macroscopic cartography of creation-removal of synaptic connections in a macro-network, and at the intra-cellular scale, micro-networks regulate the physiological mechanisms for the preferential attachment of synapses. The strongest molecular relationship of exercise and functional connectivity was identified for brain-derived neurotrophic factor (BDNF). The allele variant, rs7294919, also shows a powerful relationship with the hippocampal volume. How the brain achieves this unique quest of reconfiguration remains a puzzle. What are the underlying mechanisms of synaptogenesis promoting communications brain ↔ muscle and brain ↔ brain in such trainings? What is the respective role of independent mental, physical, or combined-mental-physical trainings? Physical practice seems to be playing an instrumental role in the cognitive enhancement (brain ↔ muscle com.). However, mental training, meditation or virtual reality (films, games) require only minimal motor activity and cardio-respiratory stimulation. Therefore, other potential paths (brain ↔ brain com.) molding brain networks are nonetheless essential. Patients with motor neuron disease/injury (e.g., amyotrophic lateral sclerosis, traumatism) also achieve successful cognitive enhancement albeit they may only elicit mental practice.

Physical Heterogeneity and Aquatic Community Function in River Networks

EPA Science Inventory

The geomorphological character of a river network provides the template upon which evolution acts to create unique biological communities. Deciphering commonly observed patterns and processes within riverine landscapes resulting from the interplay between physical and biological...

3 CFR 13652 - Executive Order 13652 of September 30, 2013. Continuance of Certain Federal Advisory Committees

Code of Federal Regulations, 2014 CFR

2014-01-01

... sectors and their functional systems, physical assets, and cyber networks. “(a) Membership. The NIAC shall... critical infrastructure and their supporting functional systems, physical assets, and cyber networks, and...

Cytoprophet: a Cytoscape plug-in for protein and domain interaction networks inference.

PubMed

Morcos, Faruck; Lamanna, Charles; Sikora, Marcin; Izaguirre, Jesús

2008-10-01

Cytoprophet is a software tool that allows prediction and visualization of protein and domain interaction networks. It is implemented as a plug-in of Cytoscape, an open source software framework for analysis and visualization of molecular networks. Cytoprophet implements three algorithms that predict new potential physical interactions using the domain composition of proteins and experimental assays. The algorithms for protein and domain interaction inference include maximum likelihood estimation (MLE) using expectation maximization (EM); the set cover approach maximum specificity set cover (MSSC) and the sum-product algorithm (SPA). After accepting an input set of proteins with Uniprot ID/Accession numbers and a selected prediction algorithm, Cytoprophet draws a network of potential interactions with probability scores and GO distances as edge attributes. A network of domain interactions between the domains of the initial protein list can also be generated. Cytoprophet was designed to take advantage of the visual capabilities of Cytoscape and be simple to use. An example of inference in a signaling network of myxobacterium Myxococcus xanthus is presented and available at Cytoprophet's website. http://cytoprophet.cse.nd.edu.

Large Scale Environmental Monitoring through Integration of Sensor and Mesh Networks.

PubMed

Jurdak, Raja; Nafaa, Abdelhamid; Barbirato, Alessio

2008-11-24

Monitoring outdoor environments through networks of wireless sensors has received interest for collecting physical and chemical samples at high spatial and temporal scales. A central challenge to environmental monitoring applications of sensor networks is the short communication range of the sensor nodes, which increases the complexity and cost of monitoring commodities that are located in geographically spread areas. To address this issue, we propose a new communication architecture that integrates sensor networks with medium range wireless mesh networks, and provides users with an advanced web portal for managing sensed information in an integrated manner. Our architecture adopts a holistic approach targeted at improving the user experience by optimizing the system performance for handling data that originates at the sensors, traverses the mesh network, and resides at the server for user consumption. This holistic approach enables users to set high level policies that can adapt the resolution of information collected at the sensors, set the preferred performance targets for their application, and run a wide range of queries and analysis on both real-time and historical data. All system components and processes will be described in this paper.

Analysis of surface-water data network in Kansas for effectiveness in providing regional streamflow information

USGS Publications Warehouse

Medina, K.D.; Tasker, Gary D.

1985-01-01

The surface water data network in Kansas was analyzed using generalized least squares regression for its effectiveness in providing regional streamflow information. The correlation and time-sampling error of the streamflow characteristic are considered in the generalized least squares method. Unregulated medium-flow, low-flow and high-flow characteristics were selected to be representative of the regional information that can be obtained from streamflow gaging station records for use in evaluating the effectiveness of continuing the present network stations, discontinuing some stations; and/or adding new stations. The analysis used streamflow records for all currently operated stations that were not affected by regulation and discontinued stations for which unregulated flow characteristics , as well as physical and climatic characteristics, were available. The state was divided into three network areas, western, northeastern, and southeastern Kansas, and analysis was made for three streamflow characteristics in each area, using three planning horizons. The analysis showed that the maximum reduction of sampling mean square error for each cost level could be obtained by adding new stations and discontinuing some of the present network stations. Large reductions in sampling mean square error for low-flow information could be accomplished in all three network areas, with western Kansas having the most dramatic reduction. The addition of new stations would be most beneficial for man- flow information in western Kansas, and to lesser degrees in the other two areas. The reduction of sampling mean square error for high-flow information would benefit most from the addition of new stations in western Kansas, and the effect diminishes to lesser degrees in the other two areas. Southeastern Kansas showed the smallest error reduction in high-flow information. A comparison among all three network areas indicated that funding resources could be most effectively used by discontinuing more stations in northeastern and southeastern Kansas and establishing more new stations in western Kansas. (Author 's abstract)

Clustering of worry appraisals among college students.

PubMed

Schwab, Nicholas G; Cullum, Jerry C; Harton, Helen C

2016-01-01

The present study investigated the potential clustering of worry appraisals within college social networks. Participants living in campus residence buildings responded to online surveys across the course of several months. Worry appraisals were measured 10 weeks into the fall semester and again approximately 6 months later. Analysis of sociometric data suggests that the majority of participants' social interactions occurred within their respective residence building floors, indicating that proximity strongly influenced the development of social network ties and sources of social influence. Further, significant clustering of worry appraisals occurred across time, and more importantly, within residence building floors. The present findings compliment previous work suggesting that several physical and psychological states appear to spread and cluster within social networks. Implications for the study of emotional appraisals and future research are discussed.

Association of childhood abuse with homeless women's social networks.

PubMed

Green, Harold D; Tucker, Joan S; Wenzel, Suzanne L; Golinelli, Daniela; Kennedy, David P; Ryan, Gery W; Zhou, Annie J

2012-01-01

Childhood abuse has been linked to negative sequelae for women later in life including drug and alcohol use and violence as victim or perpetrator and may also affect the development of women's social networks. Childhood abuse is prevalent among at-risk populations of women (such as the homeless) and thus may have a stronger impact on their social networks. We conducted a study to: (a) develop a typology of sheltered homeless women's social networks; (b) determine whether childhood abuse was associated with the social networks of sheltered homeless women; and (c) determine whether those associations remained after accounting for past-year substance abuse and recent intimate partner abuse. A probability sample of 428 homeless women from temporary shelter settings in Los Angeles County completed a personal network survey that provided respondent information as well as information about their network members' demographics and level of interaction with each other. Cluster analyses identified groups of women who shared specific social network characteristics. Multinomial logistic regressions revealed variables associated with group membership. We identified three groups of women with differing social network characteristics: low-risk networks, densely connected risky networks (dense, risky), and sparsely connected risky networks (sparse, risky). Multinomial logistic regressions indicated that membership in the sparse, risky network group, when compared to the low-risk group, was associated with history of childhood physical abuse (but not sexual or emotional abuse). Recent drug abuse was associated with membership in both risky network groups; however, the association of childhood physical abuse with sparse, risky network group membership remained. Although these findings support theories proposing that the experience of childhood abuse can shape women's social networks, they suggest that it may be childhood physical abuse that has the most impact among homeless women. The effects of childhood physical abuse should be more actively investigated in clinical settings, especially those frequented by homeless women, particularly with respect to the formation of social networks in social contexts that may expose these women to greater risks. Copyright © 2012. Published by Elsevier Ltd.

Optimal Performance Monitoring of Hybrid Mid-Infrared Wavelength MIMO Free Space Optical and RF Wireless Networks in Fading Channels

NASA Astrophysics Data System (ADS)

Schmidt, Barnet Michael

An optimal performance monitoring metric for a hybrid free space optical and radio-frequency (RF) wireless network, the Outage Capacity Objective Function, is analytically developed and studied. Current and traditional methods of performance monitoring of both optical and RF wireless networks are centered on measurement of physical layer parameters, the most common being signal-to-noise ratio, error rate, Q factor, and eye diagrams, occasionally combined with link-layer measurements such as data throughput, retransmission rate, and/or lost packet rate. Network management systems frequently attempt to predict or forestall network failures by observing degradations of these parameters and to attempt mitigation (such as offloading traffic, increasing transmitter power, reducing the data rate, or combinations thereof) prior to the failure. These methods are limited by the frequent low sensitivity of the physical layer parameters to the atmospheric optical conditions (measured by optical signal-to-noise ratio) and the radio frequency fading channel conditions (measured by signal-to-interference ratio). As a result of low sensitivity, measurements of this type frequently are unable to predict impending failures sufficiently in advance for the network management system to take corrective action prior to the failure. We derive and apply an optimal measure of hybrid network performance based on the outage capacity of the hybrid optical and RF channel, the outage capacity objective function. The objective function provides high sensitivity and reliable failure prediction, and considers both the effects of atmospheric optical impairments on the performance of the free space optical segment as well as the effect of RF channel impairments on the radio frequency segment. The radio frequency segment analysis considers the three most common RF channel fading statistics: Rayleigh, Ricean, and Nakagami-m. The novel application of information theory to the underlying physics of the gamma-gamma optical channel and radio fading channels in determining the joint hybrid channel outage capacity provides the best performance estimate under any given set of operating conditions. It is shown that, unlike traditional physical layer performance monitoring techniques, the objective function based upon the outage capacity of the hybrid channel at any combination of OSNR and SIR, is able to predict channel degradation and failure well in advance of the actual outage. An outage in the information-theoretic definition occurs when the offered load exceeds the outage capacity under the current conditions of OSNR and SIR. The optical channel is operated at the "long" mid-infrared wavelength of 10000 nm. which provides improved resistance to scattering compared to shorter wavelengths such as 1550 nm.

Review of Supervisory Control and Data Acquisition (SCADA) Systems

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

Reva Nickelson; Briam Johnson; Ken Barnes

2004-01-01

A review using open source information was performed to obtain data related to Supervisory Control and Data Acquisition (SCADA) systems used to supervise and control domestic electric power generation, transmission, and distribution. This report provides the technical details for the types of systems used, system disposal, cyber and physical security measures, network connections, and a gap analysis of SCADA security holes.

Chapter 2: Stream and riparian habitat analysis and monitoring with a high-resolution terrestrial-aquatic LiDAR

Treesearch

Jim McKean; Dan Isaak; Wayne Wright

2009-01-01

Management of aquatic habitat in streams requires description of conditions and processes both inside the channels and in the adjacent riparian zones. Biological and physical processes in these environments operate over a range of spatial scales from microhabitat to whole river networks. Limitations of previous survey technologies have focused management and research...

Interorganizational Relationships in the Heart and Stroke Foundation's Spark Together for Healthy Kids™: Insights from Using Network Analysis

ERIC Educational Resources Information Center

Yessis, Jennifer; Riley, Barbara; Stockton, Lisa; Brodovsky, Sharon; Von Sychowski, Shirley

2013-01-01

The Heart and Stroke Foundation's Spark Together for Healthy Kids™ (Spark) is a multiyear initiative in Ontario, Canada, that takes a population approach to obesity prevention. It focuses on creating healthy environments by improving access to healthy foods and physical activity, with an emphasis on strengthening the advocacy capacity of…

Training Knowledge Bots for Physics-Based Simulations Using Artificial Neural Networks

NASA Technical Reports Server (NTRS)

Samareh, Jamshid A.; Wong, Jay Ming

2014-01-01

Millions of complex physics-based simulations are required for design of an aerospace vehicle. These simulations are usually performed by highly trained and skilled analysts, who execute, monitor, and steer each simulation. Analysts rely heavily on their broad experience that may have taken 20-30 years to accumulate. In addition, the simulation software is complex in nature, requiring significant computational resources. Simulations of system of systems become even more complex and are beyond human capacity to effectively learn their behavior. IBM has developed machines that can learn and compete successfully with a chess grandmaster and most successful jeopardy contestants. These machines are capable of learning some complex problems much faster than humans can learn. In this paper, we propose using artificial neural network to train knowledge bots to identify the idiosyncrasies of simulation software and recognize patterns that can lead to successful simulations. We examine the use of knowledge bots for applications of computational fluid dynamics (CFD), trajectory analysis, commercial finite-element analysis software, and slosh propellant dynamics. We will show that machine learning algorithms can be used to learn the idiosyncrasies of computational simulations and identify regions of instability without including any additional information about their mathematical form or applied discretization approaches.

CardioNet: a human metabolic network suited for the study of cardiomyocyte metabolism.

PubMed

Karlstädt, Anja; Fliegner, Daniela; Kararigas, Georgios; Ruderisch, Hugo Sanchez; Regitz-Zagrosek, Vera; Holzhütter, Hermann-Georg

2012-08-29

Availability of oxygen and nutrients in the coronary circulation is a crucial determinant of cardiac performance. Nutrient composition of coronary blood may significantly vary in specific physiological and pathological conditions, for example, administration of special diets, long-term starvation, physical exercise or diabetes. Quantitative analysis of cardiac metabolism from a systems biology perspective may help to a better understanding of the relationship between nutrient supply and efficiency of metabolic processes required for an adequate cardiac output. Here we present CardioNet, the first large-scale reconstruction of the metabolic network of the human cardiomyocyte comprising 1793 metabolic reactions, including 560 transport processes in six compartments. We use flux-balance analysis to demonstrate the capability of the network to accomplish a set of 368 metabolic functions required for maintaining the structural and functional integrity of the cell. Taking the maintenance of ATP, biosynthesis of ceramide, cardiolipin and further important phospholipids as examples, we analyse how a changed supply of glucose, lactate, fatty acids and ketone bodies may influence the efficiency of these essential processes. CardioNet is a functionally validated metabolic network of the human cardiomyocyte that enables theorectical studies of cellular metabolic processes crucial for the accomplishment of an adequate cardiac output.

Impact detection and analysis/health monitoring system for composites

NASA Astrophysics Data System (ADS)

Child, James E.; Kumar, Amrita; Beard, Shawn; Qing, Peter; Paslay, Don G.

2006-05-01

This manuscript includes information from test evaluations and development of a smart event detection system for use in monitoring composite rocket motor cases for damaging impacts. The primary purpose of the system as a sentry for case impact event logging is accomplished through; implementation of a passive network of miniaturized piezoelectric sensors, logger with pre-determined force threshold levels, and analysis software. Empirical approaches to structural characterizations and network calibrations along with implementation techniques were successfully evaluated, testing was performed on both unloaded (less propellants) as well as loaded rocket motors with the cylindrical areas being of primary focus. The logged test impact data with known physical network parameters provided for impact location as well as force determination, typically within 3 inches of actual impact location using a 4 foot network grid and force accuracy within 25%of an actual impact force. The simplistic empirical characterization approach along with the robust / flexible sensor grids and battery operated portable logger show promise of a system that can increase confidence in composite integrity for both new assets progressing through manufacturing processes as well as existing assets that may be in storage or transportation.

Integration of new biological and physical retrospective dosimetry methods into EU emergency response plans - joint RENEB and EURADOS inter-laboratory comparisons.

PubMed

Ainsbury, Elizabeth; Badie, Christophe; Barnard, Stephen; Manning, Grainne; Moquet, Jayne; Abend, Michael; Antunes, Ana Catarina; Barrios, Lleonard; Bassinet, Celine; Beinke, Christina; Bortolin, Emanuela; Bossin, Lily; Bricknell, Clare; Brzoska, Kamil; Buraczewska, Iwona; Castaño, Carlos Huertas; Čemusová, Zina; Christiansson, Maria; Cordero, Santiago Mateos; Cosler, Guillaume; Monaca, Sara Della; Desangles, François; Discher, Michael; Dominguez, Inmaculada; Doucha-Senf, Sven; Eakins, Jon; Fattibene, Paola; Filippi, Silvia; Frenzel, Monika; Georgieva, Dimka; Gregoire, Eric; Guogyte, Kamile; Hadjidekova, Valeria; Hadjiiska, Ljubomira; Hristova, Rositsa; Karakosta, Maria; Kis, Enikő; Kriehuber, Ralf; Lee, Jungil; Lloyd, David; Lumniczky, Katalin; Lyng, Fiona; Macaeva, Ellina; Majewski, Matthaeus; Vanda Martins, S; McKeever, Stephen W S; Meade, Aidan; Medipally, Dinesh; Meschini, Roberta; M'kacher, Radhia; Gil, Octávia Monteiro; Montero, Alegria; Moreno, Mercedes; Noditi, Mihaela; Oestreicher, Ursula; Oskamp, Dominik; Palitti, Fabrizio; Palma, Valentina; Pantelias, Gabriel; Pateux, Jerome; Patrono, Clarice; Pepe, Gaetano; Port, Matthias; Prieto, María Jesús; Quattrini, Maria Cristina; Quintens, Roel; Ricoul, Michelle; Roy, Laurence; Sabatier, Laure; Sebastià, Natividad; Sholom, Sergey; Sommer, Sylwester; Staynova, Albena; Strunz, Sonja; Terzoudi, Georgia; Testa, Antonella; Trompier, Francois; Valente, Marco; Hoey, Olivier Van; Veronese, Ivan; Wojcik, Andrzej; Woda, Clemens

2017-01-01

RENEB, 'Realising the European Network of Biodosimetry and Physical Retrospective Dosimetry,' is a network for research and emergency response mutual assistance in biodosimetry within the EU. Within this extremely active network, a number of new dosimetry methods have recently been proposed or developed. There is a requirement to test and/or validate these candidate techniques and inter-comparison exercises are a well-established method for such validation. The authors present details of inter-comparisons of four such new methods: dicentric chromosome analysis including telomere and centromere staining; the gene expression assay carried out in whole blood; Raman spectroscopy on blood lymphocytes, and detection of radiation-induced thermoluminescent signals in glass screens taken from mobile phones. In general the results show good agreement between the laboratories and methods within the expected levels of uncertainty, and thus demonstrate that there is a lot of potential for each of the candidate techniques. Further work is required before the new methods can be included within the suite of reliable dosimetry methods for use by RENEB partners and others in routine and emergency response scenarios.

Hybrid network modeling and the effect of image resolution on digitally-obtained petrophysical and two-phase flow properties

NASA Astrophysics Data System (ADS)

Aghaei, A.

2017-12-01

Digital imaging and modeling of rocks and subsequent simulation of physical phenomena in digitally-constructed rock models are becoming an integral part of core analysis workflows. One of the inherent limitations of image-based analysis, at any given scale, is image resolution. This limitation becomes more evident when the rock has multiple scales of porosity such as in carbonates and tight sandstones. Multi-scale imaging and constructions of hybrid models that encompass images acquired at multiple scales and resolutions are proposed as a solution to this problem. In this study, we investigate the effect of image resolution and unresolved porosity on petrophysical and two-phase flow properties calculated based on images. A helical X-ray micro-CT scanner with a high cone-angle is used to acquire digital rock images that are free of geometric distortion. To remove subjectivity from the analyses, a semi-automated image processing technique is used to process and segment the acquired data into multiple phases. Direct and pore network based models are used to simulate physical phenomena and obtain absolute permeability, formation factor and two-phase flow properties such as relative permeability and capillary pressure. The effect of image resolution on each property is investigated. Finally a hybrid network model incorporating images at multiple resolutions is built and used for simulations. The results from the hybrid model are compared against results from the model built at the highest resolution and those from laboratory tests.

The physical therapy clinical research network (PTClinResNet): methods, efficacy, and benefits of a rehabilitation research network.

PubMed

Winstein, Carolee; Pate, Patricia; Ge, Tingting; Ervin, Carolyn; Baurley, James; Sullivan, Katherine J; Underwood, Samantha J; Fowler, Eileen G; Mulroy, Sara; Brown, David A; Kulig, Kornelia; Gordon, James; Azen, Stanley P

2008-11-01

This article describes the vision, methods, and implementation strategies used in building the infrastructure for PTClinResNet, a clinical research network designed to assess outcomes for health-related mobility associated with evidence-based physical therapy interventions across and within four different disability groups. Specific aims were to (1) create the infrastructure necessary to develop and sustain clinical trials research in rehabilitation, (2) generate evidence to evaluate the efficacy of resistance exercise-based physical interventions designed to improve muscle performance and movement skills, and (3) provide education and training opportunities for present and future clinician-researchers and for the rehabilitation community at-large in its support of evidence-based practice. We present the network's infrastructure, development, and several examples that highlight the benefits of a clinical research network. We suggest that the network structure is ideal for building research capacity and fostering multisite, multiinvestigator clinical research projects designed to generate evidence for the efficacy of rehabilitation interventions.

Cognitive control in the self-regulation of physical activity and sedentary behavior

PubMed Central

Buckley, Jude; Cohen, Jason D.; Kramer, Arthur F.; McAuley, Edward; Mullen, Sean P.

2014-01-01

Cognitive control of physical activity and sedentary behavior is receiving increased attention in the neuroscientific and behavioral medicine literature as a means of better understanding and improving the self-regulation of physical activity. Enhancing individuals’ cognitive control capacities may provide a means to increase physical activity and reduce sedentary behavior. First, this paper reviews emerging evidence of the antecedence of cognitive control abilities in successful self-regulation of physical activity, and in precipitating self-regulation failure that predisposes to sedentary behavior. We then highlight the brain networks that may underpin the cognitive control and self-regulation of physical activity, including the default mode network, prefrontal cortical networks and brain regions and pathways associated with reward. We then discuss research on cognitive training interventions that document improved cognitive control and that suggest promise of influencing physical activity regulation. Key cognitive training components likely to be the most effective at improving self-regulation are also highlighted. The review concludes with suggestions for future research. PMID:25324754

Social Networks and Health: Understanding the Nuances of Healthcare Access between Urban and Rural Populations.

PubMed

Amoah, Padmore Adusei; Edusei, Joseph; Amuzu, David

2018-05-13

Communities and individuals in many sub-Saharan African countries often face limited access to healthcare. Hence, many rely on social networks to enhance their chances for adequate health care. While this knowledge is well-established, little is known about the nuances of how different population groups activate these networks to improve access to healthcare. This paper examines how rural and urban dwellers in the Ashanti Region in Ghana distinctively and systematically activate their social networks to enhance access to healthcare. It uses a qualitative cross-sectional design, with in-depth interviews of 79 primary participants (28 urban and 51 rural residents) in addition to the views of eight community leaders and eight health personnel. It was discovered that both intimate and distanced social networks for healthcare are activated at different periods by rural and urban residents. Four main stages of social networks activation, comprising different individuals and groups were observed among rural and urban dwellers. Among both groups, physical proximity, privacy, trust and sense of fairness, socio-cultural meaning attached to health problems, and perceived knowledge and other resources (mainly money) held in specific networks inherently influenced social network activation. The paper posits that a critical analysis of social networks may help to tailor policy contents to individuals and groups with limited access to healthcare.

MIANN models in medicinal, physical and organic chemistry.

PubMed

González-Díaz, Humberto; Arrasate, Sonia; Sotomayor, Nuria; Lete, Esther; Munteanu, Cristian R; Pazos, Alejandro; Besada-Porto, Lina; Ruso, Juan M

2013-01-01

Reducing costs in terms of time, animal sacrifice, and material resources with computational methods has become a promising goal in Medicinal, Biological, Physical and Organic Chemistry. There are many computational techniques that can be used in this sense. In any case, almost all these methods focus on few fundamental aspects including: type (1) methods to quantify the molecular structure, type (2) methods to link the structure with the biological activity, and others. In particular, MARCH-INSIDE (MI), acronym for Markov Chain Invariants for Networks Simulation and Design, is a well-known method for QSAR analysis useful in step (1). In addition, the bio-inspired Artificial-Intelligence (AI) algorithms called Artificial Neural Networks (ANNs) are among the most powerful type (2) methods. We can combine MI with ANNs in order to seek QSAR models, a strategy which is called herein MIANN (MI & ANN models). One of the first applications of the MIANN strategy was in the development of new QSAR models for drug discovery. MIANN strategy has been expanded to the QSAR study of proteins, protein-drug interactions, and protein-protein interaction networks. In this paper, we review for the first time many interesting aspects of the MIANN strategy including theoretical basis, implementation in web servers, and examples of applications in Medicinal and Biological chemistry. We also report new applications of the MIANN strategy in Medicinal chemistry and the first examples in Physical and Organic Chemistry, as well. In so doing, we developed new MIANN models for several self-assembly physicochemical properties of surfactants and large reaction networks in organic synthesis. In some of the new examples we also present experimental results which were not published up to date.

Two Web-Based Laboratories of the FisL@bs Network: Hooke's and Snell's Laws

ERIC Educational Resources Information Center

de la Torre, L.; Sanchez, J.; Dormido, S.; Sanchez, J. P.; Yuste, M.; Carreras, C.

2011-01-01

FisL@bs is a network of remote and virtual laboratories for physics university education via the Internet that offers students the possibility of performing hands-on experiments in different fields of physics in two ways: simulation and real remote operation. This paper gives a detailed account of a novel way in physics in which distance learning…

Mathematical Modeling and Evaluation of Human Motions in Physical Therapy Using Mixture Density Neural Networks

PubMed Central

Vakanski, A; Ferguson, JM; Lee, S

2016-01-01

Objective The objective of the proposed research is to develop a methodology for modeling and evaluation of human motions, which will potentially benefit patients undertaking a physical rehabilitation therapy (e.g., following a stroke or due to other medical conditions). The ultimate aim is to allow patients to perform home-based rehabilitation exercises using a sensory system for capturing the motions, where an algorithm will retrieve the trajectories of a patient’s exercises, will perform data analysis by comparing the performed motions to a reference model of prescribed motions, and will send the analysis results to the patient’s physician with recommendations for improvement. Methods The modeling approach employs an artificial neural network, consisting of layers of recurrent neuron units and layers of neuron units for estimating a mixture density function over the spatio-temporal dependencies within the human motion sequences. Input data are sequences of motions related to a prescribed exercise by a physiotherapist to a patient, and recorded with a motion capture system. An autoencoder subnet is employed for reducing the dimensionality of captured sequences of human motions, complemented with a mixture density subnet for probabilistic modeling of the motion data using a mixture of Gaussian distributions. Results The proposed neural network architecture produced a model for sets of human motions represented with a mixture of Gaussian density functions. The mean log-likelihood of observed sequences was employed as a performance metric in evaluating the consistency of a subject’s performance relative to the reference dataset of motions. A publically available dataset of human motions captured with Microsoft Kinect was used for validation of the proposed method. Conclusion The article presents a novel approach for modeling and evaluation of human motions with a potential application in home-based physical therapy and rehabilitation. The described approach employs the recent progress in the field of machine learning and neural networks in developing a parametric model of human motions, by exploiting the representational power of these algorithms to encode nonlinear input-output dependencies over long temporal horizons. PMID:28111643

Mathematical Modeling and Evaluation of Human Motions in Physical Therapy Using Mixture Density Neural Networks.

PubMed

Vakanski, A; Ferguson, J M; Lee, S

2016-12-01

The objective of the proposed research is to develop a methodology for modeling and evaluation of human motions, which will potentially benefit patients undertaking a physical rehabilitation therapy (e.g., following a stroke or due to other medical conditions). The ultimate aim is to allow patients to perform home-based rehabilitation exercises using a sensory system for capturing the motions, where an algorithm will retrieve the trajectories of a patient's exercises, will perform data analysis by comparing the performed motions to a reference model of prescribed motions, and will send the analysis results to the patient's physician with recommendations for improvement. The modeling approach employs an artificial neural network, consisting of layers of recurrent neuron units and layers of neuron units for estimating a mixture density function over the spatio-temporal dependencies within the human motion sequences. Input data are sequences of motions related to a prescribed exercise by a physiotherapist to a patient, and recorded with a motion capture system. An autoencoder subnet is employed for reducing the dimensionality of captured sequences of human motions, complemented with a mixture density subnet for probabilistic modeling of the motion data using a mixture of Gaussian distributions. The proposed neural network architecture produced a model for sets of human motions represented with a mixture of Gaussian density functions. The mean log-likelihood of observed sequences was employed as a performance metric in evaluating the consistency of a subject's performance relative to the reference dataset of motions. A publically available dataset of human motions captured with Microsoft Kinect was used for validation of the proposed method. The article presents a novel approach for modeling and evaluation of human motions with a potential application in home-based physical therapy and rehabilitation. The described approach employs the recent progress in the field of machine learning and neural networks in developing a parametric model of human motions, by exploiting the representational power of these algorithms to encode nonlinear input-output dependencies over long temporal horizons.

A neural network for real-time retrievals of PWV and LWP from Arctic millimeter-wave ground-based observations.

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

Cadeddu, M. P.; Turner, D. D.; Liljegren, J. C.

2009-07-01

This paper presents a new neural network (NN) algorithm for real-time retrievals of low amounts of precipitable water vapor (PWV) and integrated liquid water from millimeter-wave ground-based observations. Measurements are collected by the 183.3-GHz G-band vapor radiometer (GVR) operating at the Atmospheric Radiation Measurement (ARM) Program Climate Research Facility, Barrow, AK. The NN provides the means to explore the nonlinear regime of the measurements and investigate the physical boundaries of the operability of the instrument. A methodology to compute individual error bars associated with the NN output is developed, and a detailed error analysis of the network output is provided.more » Through the error analysis, it is possible to isolate several components contributing to the overall retrieval errors and to analyze the dependence of the errors on the inputs. The network outputs and associated errors are then compared with results from a physical retrieval and with the ARM two-channel microwave radiometer (MWR) statistical retrieval. When the NN is trained with a seasonal training data set, the retrievals of water vapor yield results that are comparable to those obtained from a traditional physical retrieval, with a retrieval error percentage of {approx}5% when the PWV is between 2 and 10 mm, but with the advantages that the NN algorithm does not require vertical profiles of temperature and humidity as input and is significantly faster computationally. Liquid water path (LWP) retrievals from the NN have a significantly improved clear-sky bias (mean of {approx}2.4 g/m{sup 2}) and a retrieval error varying from 1 to about 10 g/m{sup 2} when the PWV amount is between 1 and 10 mm. As an independent validation of the LWP retrieval, the longwave downwelling surface flux was computed and compared with observations. The comparison shows a significant improvement with respect to the MWR statistical retrievals, particularly for LWP amounts of less than 60 g/m{sup 2}.« less

An Embedded Multi-Agent Systems Based Industrial Wireless Sensor Network

PubMed Central

Brennan, Robert W.

2017-01-01

With the emergence of cyber-physical systems, there has been a growing interest in network-connected devices. One of the key requirements of a cyber-physical device is the ability to sense its environment. Wireless sensor networks are a widely-accepted solution for this requirement. In this study, an embedded multi-agent systems-managed wireless sensor network is presented. A novel architecture is proposed, along with a novel wireless sensor network architecture. Active and passive wireless sensor node types are defined, along with their communication protocols, and two application-specific examples are presented. A series of three experiments is conducted to evaluate the performance of the agent-embedded wireless sensor network. PMID:28906452

An Embedded Multi-Agent Systems Based Industrial Wireless Sensor Network.

PubMed

Taboun, Mohammed S; Brennan, Robert W

2017-09-14

With the emergence of cyber-physical systems, there has been a growing interest in network-connected devices. One of the key requirements of a cyber-physical device is the ability to sense its environment. Wireless sensor networks are a widely-accepted solution for this requirement. In this study, an embedded multi-agent systems-managed wireless sensor network is presented. A novel architecture is proposed, along with a novel wireless sensor network architecture. Active and passive wireless sensor node types are defined, along with their communication protocols, and two application-specific examples are presented. A series of three experiments is conducted to evaluate the performance of the agent-embedded wireless sensor network.

Development and Validation of a Deep Neural Network Model for Prediction of Postoperative In-hospital Mortality.

PubMed

Lee, Christine K; Hofer, Ira; Gabel, Eilon; Baldi, Pierre; Cannesson, Maxime

2018-04-17

The authors tested the hypothesis that deep neural networks trained on intraoperative features can predict postoperative in-hospital mortality. The data used to train and validate the algorithm consists of 59,985 patients with 87 features extracted at the end of surgery. Feed-forward networks with a logistic output were trained using stochastic gradient descent with momentum. The deep neural networks were trained on 80% of the data, with 20% reserved for testing. The authors assessed improvement of the deep neural network by adding American Society of Anesthesiologists (ASA) Physical Status Classification and robustness of the deep neural network to a reduced feature set. The networks were then compared to ASA Physical Status, logistic regression, and other published clinical scores including the Surgical Apgar, Preoperative Score to Predict Postoperative Mortality, Risk Quantification Index, and the Risk Stratification Index. In-hospital mortality in the training and test sets were 0.81% and 0.73%. The deep neural network with a reduced feature set and ASA Physical Status classification had the highest area under the receiver operating characteristics curve, 0.91 (95% CI, 0.88 to 0.93). The highest logistic regression area under the curve was found with a reduced feature set and ASA Physical Status (0.90, 95% CI, 0.87 to 0.93). The Risk Stratification Index had the highest area under the receiver operating characteristics curve, at 0.97 (95% CI, 0.94 to 0.99). Deep neural networks can predict in-hospital mortality based on automatically extractable intraoperative data, but are not (yet) superior to existing methods.

Use of a mobile social networking intervention for weight management: a mixed-methods study protocol

PubMed Central

Lau, Annie Y S; Martin, Paige; Tong, Huong Ly; Coiera, Enrico

2017-01-01

Introduction Obesity and physical inactivity are major societal challenges and significant contributors to the global burden of disease and healthcare costs. Information and communication technologies are increasingly being used in interventions to promote behaviour change in diet and physical activity. In particular, social networking platforms seem promising for the delivery of weight control interventions. We intend to pilot test an intervention involving the use of a social networking mobile application and tracking devices (Fitbit Flex 2 and Fitbit Aria scale) to promote the social comparison of weight and physical activity, in order to evaluate whether mechanisms of social influence lead to changes in those outcomes over the course of the study. Methods and analysis Mixed-methods study involving semi-structured interviews and a pre–post quasi-experimental pilot with one arm, where healthy participants in different body mass index (BMI) categories, aged between 19 and 35 years old, will be subjected to a social networking intervention over a 6-month period. The primary outcome is the average difference in weight before and after the intervention. Secondary outcomes include BMI, number of steps per day, engagement with the intervention, social support and system usability. Semi-structured interviews will assess participants’ expectations and perceptions regarding the intervention. Ethics and dissemination Ethics approval was granted by Macquarie University’s Human Research Ethics Committee for Medical Sciences on 3 November 2016 (ethics reference number 5201600716). The social network will be moderated by a researcher with clinical expertise, who will monitor and respond to concerns raised by participants. Monitoring will involve daily observation of measures collected by the fitness tracker and the wireless scale, as well as continuous supervision of forum interactions and posts. Additionally, a protocol is in place to monitor for participant misbehaviour and direct participants-in-need to appropriate sources of help. PMID:28706104

MaxEnt analysis of a water distribution network in Canberra, ACT, Australia

NASA Astrophysics Data System (ADS)

Waldrip, Steven H.; Niven, Robert K.; Abel, Markus; Schlegel, Michael; Noack, Bernd R.

2015-01-01

A maximum entropy (MaxEnt) method is developed to infer the state of a pipe flow network, for situations in which there is insufficient information to form a closed equation set. This approach substantially extends existing deterministic methods for the analysis of engineered flow networks (e.g. Newton's method or the Hardy Cross scheme). The network is represented as an undirected graph structure, in which the uncertainty is represented by a continuous relative entropy on the space of internal and external flow rates. The head losses (potential differences) on the network are treated as dependent variables, using specified pipe-flow resistance functions. The entropy is maximised subject to "observable" constraints on the mean values of certain flow rates and/or potential differences, and also "physical" constraints arising from the frictional properties of each pipe and from Kirchhoff's nodal and loop laws. A numerical method is developed in Matlab for solution of the integral equation system, based on multidimensional quadrature. Several nonlinear resistance functions (e.g. power-law and Colebrook) are investigated, necessitating numerical solution of the implicit Lagrangian by a double iteration scheme. The method is applied to a 1123-node, 1140-pipe water distribution network for the suburb of Torrens in the Australian Capital Territory, Australia, using network data supplied by water authority ACTEW Corporation Limited. A number of different assumptions are explored, including various network geometric representations, prior probabilities and constraint settings, yielding useful predictions of network demand and performance. We also propose this methodology be used in conjunction with in-flow monitoring systems, to obtain better inferences of user consumption without large investments in monitoring equipment and maintenance.

Source and Size of Emotional and Financial-Related Social Support Network on Physical Activity Behavior Among Older Adults.

PubMed

Loprinzi, Paul D; Joyner, Chelsea

2016-07-01

To examine the association of source of emotional- and financial-related social support and size of social support network on physical activity behavior among older adults. Data from the 1999-2006 NHANES were used (N = 5616; 60 to 85 yrs). Physical activity and emotional- and financial-related social support were assessed via self-report. Older adults with perceived having emotional social support had a 41% increased odds of meeting physical activity guidelines (OR = 1.41; 95% CI: 1.01-1.97). The only specific sources of social support that were associated with meeting physical activity guidelines was friend emotional support (OR = 1.19; 95% CI: 1.01-1.41) and financial support (OR = 1.28; 95% CI: 1.09-1.49). With regard to size of social support network, a dose-response relationship was observed. Compared with those with 0 close friends, those with 1 to 2, 3 to 4, 5, and 6+ close friends, respectively, had a 1.70-, 2.38-, 2.57-, and 2.71-fold increased odds of meeting physical activity guidelines. There was some evidence of gender- and age-specific associations between social support and physical activity. Emotional- and financial-related social support and size of social support network are associated with higher odds of meeting physical activity guidelines among older adults.

Medical cyber-physical systems: A survey.

PubMed

Dey, Nilanjan; Ashour, Amira S; Shi, Fuqian; Fong, Simon James; Tavares, João Manuel R S

2018-03-10

Medical cyber-physical systems (MCPS) are healthcare critical integration of a network of medical devices. These systems are progressively used in hospitals to achieve a continuous high-quality healthcare. The MCPS design faces numerous challenges, including inoperability, security/privacy, and high assurance in the system software. In the current work, the infrastructure of the cyber-physical systems (CPS) are reviewed and discussed. This article enriched the researches of the networked Medical Device (MD) systems to increase the efficiency and safety of the healthcare. It also can assist the specialists of medical device to overcome crucial issues related to medical devices, and the challenges facing the design of the medical device's network. The concept of the social networking and its security along with the concept of the wireless sensor networks (WSNs) are addressed. Afterward, the CPS systems and platforms have been established, where more focus was directed toward CPS-based healthcare. The big data framework of CPSs is also included.

A review and guidance for pattern selection in spatiotemporal system

NASA Astrophysics Data System (ADS)

Wang, Chunni; Ma, Jun

2018-03-01

Pattern estimation and selection in media can give important clues to understand the collective response to external stimulus by detecting the observable variables. Both reaction-diffusion systems (RDs) and neuronal networks can be treated as multi-agent systems from molecular level, intrinsic cooperation, competition. An external stimulus or attack can cause collapse of spatial order and distribution, while appropriate noise can enhance the consensus in the spatiotemporal systems. Pattern formation and synchronization stability can bridge isolated oscillators and the network by coupling these nodes with appropriate connection types. As a result, the dynamical behaviors can be detected and discussed by developing different spatial patterns and realizing network synchronization. Indeed, the collective response of network and multi-agent system depends on the local kinetics of nodes and cells. It is better to know the standard bifurcation analysis and stability control schemes before dealing with network problems. In this review, dynamics discussion and synchronization control on low-dimensional systems, pattern formation and synchronization stability on network, wave stability in RDs and neuronal network are summarized. Finally, possible guidance is presented when some physical effects such as polarization field and electromagnetic induction are considered.

An overview of mesoscale aerosol processes, comparisons, and validation studies from DRAGON networks

NASA Astrophysics Data System (ADS)

Holben, Brent N.; Kim, Jhoon; Sano, Itaru; Mukai, Sonoyo; Eck, Thomas F.; Giles, David M.; Schafer, Joel S.; Sinyuk, Aliaksandr; Slutsker, Ilya; Smirnov, Alexander; Sorokin, Mikhail; Anderson, Bruce E.; Che, Huizheng; Choi, Myungje; Crawford, James H.; Ferrare, Richard A.; Garay, Michael J.; Jeong, Ukkyo; Kim, Mijin; Kim, Woogyung; Knox, Nichola; Li, Zhengqiang; Lim, Hwee S.; Liu, Yang; Maring, Hal; Nakata, Makiko; Pickering, Kenneth E.; Piketh, Stuart; Redemann, Jens; Reid, Jeffrey S.; Salinas, Santo; Seo, Sora; Tan, Fuyi; Tripathi, Sachchida N.; Toon, Owen B.; Xiao, Qingyang

2018-01-01

Over the past 24 years, the AErosol RObotic NETwork (AERONET) program has provided highly accurate remote-sensing characterization of aerosol optical and physical properties for an increasingly extensive geographic distribution including all continents and many oceanic island and coastal sites. The measurements and retrievals from the AERONET global network have addressed satellite and model validation needs very well, but there have been challenges in making comparisons to similar parameters from in situ surface and airborne measurements. Additionally, with improved spatial and temporal satellite remote sensing of aerosols, there is a need for higher spatial-resolution ground-based remote-sensing networks. An effort to address these needs resulted in a number of field campaign networks called Distributed Regional Aerosol Gridded Observation Networks (DRAGONs) that were designed to provide a database for in situ and remote-sensing comparison and analysis of local to mesoscale variability in aerosol properties. This paper describes the DRAGON deployments that will continue to contribute to the growing body of research related to meso- and microscale aerosol features and processes. The research presented in this special issue illustrates the diversity of topics that has resulted from the application of data from these networks.

Spectral Entropies as Information-Theoretic Tools for Complex Network Comparison

NASA Astrophysics Data System (ADS)

De Domenico, Manlio; Biamonte, Jacob

2016-10-01

Any physical system can be viewed from the perspective that information is implicitly represented in its state. However, the quantification of this information when it comes to complex networks has remained largely elusive. In this work, we use techniques inspired by quantum statistical mechanics to define an entropy measure for complex networks and to develop a set of information-theoretic tools, based on network spectral properties, such as Rényi q entropy, generalized Kullback-Leibler and Jensen-Shannon divergences, the latter allowing us to define a natural distance measure between complex networks. First, we show that by minimizing the Kullback-Leibler divergence between an observed network and a parametric network model, inference of model parameter(s) by means of maximum-likelihood estimation can be achieved and model selection can be performed with appropriate information criteria. Second, we show that the information-theoretic metric quantifies the distance between pairs of networks and we can use it, for instance, to cluster the layers of a multilayer system. By applying this framework to networks corresponding to sites of the human microbiome, we perform hierarchical cluster analysis and recover with high accuracy existing community-based associations. Our results imply that spectral-based statistical inference in complex networks results in demonstrably superior performance as well as a conceptual backbone, filling a gap towards a network information theory.

Social and cultural environment factors influencing physical activity among african-american adolescents.

PubMed

Baskin, Monica L; Dulin-Keita, Akilah; Thind, Herpreet; Godsey, Emily

2015-05-01

African-American youth are at high risk for physical inactivity. This study explored social and cultural environment facilitators of physical activity among 12- to 14-year-old African-American adolescents living in a metropolitan area in the Southeast. Youth (n = 51; 45% male) participated in brainstorming focus groups responding to the prompt, "What about your family, friends, and community, encourages you to be physically active?" In a second meeting, participants (n = 56; 37.5% male) sorted statements (n = 84) based on similarity in meaning and rated statements on relative importance. Statement groups and ratings were entered into Concept Systems software where multidimensional scaling and hierarchical cluster analysis were used to create graphical representation of ideas. Finally, researchers named clusters according to the gestalt of grouped statements. The total sample included 28.9% of youth with household incomes ≤$30,000 (area median income = $30,701), 29% who perceived themselves as overweight, and 14.5% who reported being active for 60+ minutes everyday. Nine clusters, in rank order, emerged as follows: access/availability of physical activity resources; family and friend support; physical activity with friends; physical activity with family members; inspiration to/from others; parental reinforcement; opportunities in daily routine; pressure from social networks; and seeing consequences of activity/inactivity. Themes analyzed by gender were very similar (r = .90); however, "pressure from social networks" was more important for girls than boys (r = .10). Clear patterns of social and cultural facilitators of physical activity are perceived by African-American adolescents. Interventions targeting this group may benefit by incorporating these themes. Copyright © 2015 Society for Adolescent Health and Medicine. Published by Elsevier Inc. All rights reserved.

Understanding patient outcomes after acute respiratory distress syndrome: identifying subtypes of physical, cognitive and mental health outcomes.

PubMed

Brown, Samuel M; Wilson, Emily L; Presson, Angela P; Dinglas, Victor D; Greene, Tom; Hopkins, Ramona O; Needham, Dale M

2017-12-01

With improving short-term mortality in acute respiratory distress syndrome (ARDS), understanding survivors' posthospitalisation outcomes is increasingly important. However, little is known regarding associations among physical, cognitive and mental health outcomes. Identification of outcome subtypes may advance understanding of post-ARDS morbidities. We analysed baseline variables and 6-month health status for participants in the ARDS Network Long-Term Outcomes Study. After division into derivation and validation datasets, we used weighted network analysis to identify subtypes from predictors and outcomes in the derivation dataset. We then used recursive partitioning to develop a subtype classification rule and assessed adequacy of the classification rule using a kappa statistic with the validation dataset. Among 645 ARDS survivors, 430 were in the derivation and 215 in the validation datasets. Physical and mental health status, but not cognitive status, were closely associated. Four distinct subtypes were apparent (percentages in the derivation cohort): (1) mildly impaired physical and mental health (22% of patients), (2) moderately impaired physical and mental health (39%), (3) severely impaired physical health with moderately impaired mental health (15%) and (4) severely impaired physical and mental health (24%). The classification rule had high agreement (kappa=0.89 in validation dataset). Female Latino smokers had the poorest status, while male, non-Latino non-smokers had the best status. We identified four post-ARDS outcome subtypes that were predicted by sex, ethnicity, pre-ARDS smoking status and other baseline factors. These subtypes may help develop tailored rehabilitation strategies, including investigation of combined physical and mental health interventions, and distinct interventions to improve cognitive outcomes. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Statistical mechanics of broadcast channels using low-density parity-check codes.

PubMed

Nakamura, Kazutaka; Kabashima, Yoshiyuki; Morelos-Zaragoza, Robert; Saad, David

2003-03-01

We investigate the use of Gallager's low-density parity-check (LDPC) codes in a degraded broadcast channel, one of the fundamental models in network information theory. Combining linear codes is a standard technique in practical network communication schemes and is known to provide better performance than simple time sharing methods when algebraic codes are used. The statistical physics based analysis shows that the practical performance of the suggested method, achieved by employing the belief propagation algorithm, is superior to that of LDPC based time sharing codes while the best performance, when received transmissions are optimally decoded, is bounded by the time sharing limit.

Crafting a Social Context for Medical Informatics Networks

NASA Astrophysics Data System (ADS)

Patel, Salil H.

Effective healthcare delivery is increasingly predicated upon the availability, accuracy, and integrity of personal health information. Tracking and analysis of medical information throughout its lifeeycle may be viewed through the lenses of both physical network architecture and the broader social context in which such information is gathered and applied. As information technology and evidence-based practice models evolve in tandem, the development of interlinked multimodal and multidimensional databases has shown great promise for improving public health. To this end. providers, regulators, payers, and individual patients each share rights and responsibilities in creating a milieu which both, fosters and protects the practice and promise of medical information.

A study of the status of women in physics in Nagpur

NASA Astrophysics Data System (ADS)

Darisi, Sridevi; Ubale, Seema

2015-12-01

Networking plays an important role in ensuring that women participate equally in science and technology. In Nagpur, India, a growing city in the center of the country, a small and local network called Women in Physics in Nagpur was launched in July 2013 with about 10-15 members. A Google group of the same name was also launched. The main aim of the network was to set collective goals towards a vision for Indian women physicists. This paper reports on one of our early activities, a survey of women in Nagpur who have a physics background, and suggests future activities.

Efficient evaluation of wireless real-time control networks.

PubMed

Horvath, Peter; Yampolskiy, Mark; Koutsoukos, Xenofon

2015-02-11

In this paper, we present a system simulation framework for the design and performance evaluation of complex wireless cyber-physical systems. We describe the simulator architecture and the specific developments that are required to simulate cyber-physical systems relying on multi-channel, multihop mesh networks. We introduce realistic and efficient physical layer models and a system simulation methodology, which provides statistically significant performance evaluation results with low computational complexity. The capabilities of the proposed framework are illustrated in the example of WirelessHART, a centralized, real-time, multi-hop mesh network designed for industrial control and monitor applications.

[Association of the physical activity of community-dwelling older adults with transportation modes, depression and social networks].

PubMed

Tsunoda, Kenji; Mitsuishi, Yasuhiro; Tsuji, Taishi; Yoon, Ji-Yeong; Muraki, Toshiaki; Hotta, Kazushi; Okura, Tomohiro

2011-01-01

The purpose of this study was to cross-sectionally examine the relationships among leisure, household and occupational physical activity with the frequency of going out by various transportation modes, depression and social networks in older adults. We randomly selected a total of 2,100 community-dwelling adults aged 65 to 85 years of age from the Basic Resident Register. Of these, 340 people were the subjects of this study. The scales of measurement used were the Physical Activity Scale for the Elderly, the Lubben Social Network Scale (LSNS) and the Geriatric Depression Scale (GDS). In a regression model, leisure-time physical activity significantly correlated with frequency of going out by bicycle (β=0.17) and LSNS score (β=0.17). Household physical activity and occupational physical activity were significantly correlated with LSNS score (β=0.21) and frequency of going out by motor vehicle (β=0.25), respectively. For total physical activity, in the 3 above-mentioned activities a significant correlation was observed among frequency of going out by bicycle (β=0.10), by motor vehicle (β=0.23), GDS score (β=-0.16) and LSNS score (β=0.23). These results indicate that the frequency of going out by bicycle and by motor vehicle were significant factors to predict leisure and occupational physical activity. Furthermore, social networks appear to be important determiners in leisure and household physical activity in community-dwelling older adults.

Tools and Models for Integrating Multiple Cellular Networks

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

Gerstein, Mark

2015-11-06

In this grant, we have systematically investigated the integrated networks, which are responsible for the coordination of activity between metabolic pathways in prokaryotes. We have developed several computational tools to analyze the topology of the integrated networks consisting of metabolic, regulatory, and physical interaction networks. The tools are all open-source, and they are available to download from Github, and can be incorporated in the Knowledgebase. Here, we summarize our work as follow. Understanding the topology of the integrated networks is the first step toward understanding its dynamics and evolution. For Aim 1 of this grant, we have developed a novelmore » algorithm to determine and measure the hierarchical structure of transcriptional regulatory networks [1]. The hierarchy captures the direction of information flow in the network. The algorithm is generally applicable to regulatory networks in prokaryotes, yeast and higher organisms. Integrated datasets are extremely beneficial in understanding the biology of a system in a compact manner due to the conflation of multiple layers of information. Therefore for Aim 2 of this grant, we have developed several tools and carried out analysis for integrating system-wide genomic information. To make use of the structural data, we have developed DynaSIN for protein-protein interactions networks with various dynamical interfaces [2]. We then examined the association between network topology with phenotypic effects such as gene essentiality. In particular, we have organized E. coli and S. cerevisiae transcriptional regulatory networks into hierarchies. We then correlated gene phenotypic effects by tinkering with different layers to elucidate which layers were more tolerant to perturbations [3]. In the context of evolution, we also developed a workflow to guide the comparison between different types of biological networks across various species using the concept of rewiring [4], and Furthermore, we have developed CRIT for correlation analysis in systems biology [5]. For Aim 3, we have further investigated the scaling relationship that the number of Transcription Factors (TFs) in a genome is proportional to the square of the total number of genes. We have extended the analysis from transcription factors to various classes of functional categories, and from individual categories to joint distribution [6]. By introducing a new analytical framework, we have generalized the original toolbox model to take into account of metabolic network with arbitrary network topology [7].« less

Technological Networks

NASA Astrophysics Data System (ADS)

Mitra, Bivas

The study of networks in the form of mathematical graph theory is one of the fundamental pillars of discrete mathematics. However, recent years have witnessed a substantial new movement in network research. The focus of the research is shifting away from the analysis of small graphs and the properties of individual vertices or edges to consideration of statistical properties of large scale networks. This new approach has been driven largely by the availability of technological networks like the Internet [12], World Wide Web network [2], etc. that allow us to gather and analyze data on a scale far larger than previously possible. At the same time, technological networks have evolved as a socio-technological system, as the concepts of social systems that are based on self-organization theory have become unified in technological networks [13]. In today’s society, we have a simple and universal access to great amounts of information and services. These information services are based upon the infrastructure of the Internet and the World Wide Web. The Internet is the system composed of ‘computers’ connected by cables or some other form of physical connections. Over this physical network, it is possible to exchange e-mails, transfer files, etc. On the other hand, the World Wide Web (commonly shortened to the Web) is a system of interlinked hypertext documents accessed via the Internet where nodes represent web pages and links represent hyperlinks between the pages. Peer-to-peer (P2P) networks [26] also have recently become a popular medium through which huge amounts of data can be shared. P2P file sharing systems, where files are searched and downloaded among peers without the help of central servers, have emerged as a major component of Internet traffic. An important advantage in P2P networks is that all clients provide resources, including bandwidth, storage space, and computing power. In this chapter, we discuss these technological networks in detail. The review is organized as follows. Section 2 presents an introduction to the Internet and different protocols related to it. This section also specifies the socio-technological properties of the Internet, like scale invariance, the small-world property, network resilience, etc. Section 3 describes the P2P networks, their categorization, and other related issues like search, stability, etc. Section 4 concludes the chapter.

Space physics education via examples in the undergraduate physics curriculum

NASA Astrophysics Data System (ADS)

Martin, R.; Holland, D. L.

2011-12-01

The field of space physics is rich with examples of basic physics and analysis techniques, yet it is rarely seen in physics courses or textbooks. As space physicists in an undergraduate physics department we like to use research to inform teaching, and we find that students respond well to examples from magnetospheric science. While we integrate examples into general education courses as well, this talk will focus on physics major courses. Space physics examples are typically selected to illustrate a particular concept or method taught in the course. Four examples will be discussed, from an introductory electricity and magnetism course, a mechanics/nonlinear dynamics course, a computational physics course, and a plasma physics course. Space physics provides examples of many concepts from introductory E&M, including the application of Faraday's law to terrestrial magnetic storm effects and the use of the basic motion of charged particles as a springboard to discussion of the inner magnetosphere and the aurora. In the mechanics and nonlinear dynamics courses, the motion of charged particles in a magnetotail current sheet magnetic field is treated as a Newtonian dynamical system, illustrating the Poincaré surface-of-section technique, the partitioning of phase space, and the KAM theorem. Neural network time series analysis of AE data is used as an example in the computational physics course. Finally, among several examples, current sheet particle dynamics is utilized in the plasma physics course to illustrate the notion of adiabatic/guiding center motion and the breakdown of the adiabatic approximation. We will present short descriptions of our pedagogy and student assignments in this "backdoor" method of space physics education.

Accessibility assessment of Houston's roadway network during Harvey through integration of observed flood impacts and hydrologic modeling

NASA Astrophysics Data System (ADS)

Gidaris, I.; Gori, A.; Panakkal, P.; Padgett, J.; Bedient, P. B.

2017-12-01

The record-breaking rainfall produced over the Houston region by Hurricane Harvey resulted in catastrophic and unprecedented impacts on the region's infrastructure. Notably, Houston's transportation network was crippled, with almost every major highway flooded during the five-day event. Entire neighborhoods and subdivisions were inundated, rendering them completely inaccessible to rescue crews and emergency services. Harvey has tragically highlighted the vulnerability of major thoroughfares, as well as neighborhood roads, to severe inundation during extreme precipitation events. Furthermore, it has emphasized the need for detailed accessibility characterization of road networks under extreme event scenarios in order to determine which areas of the city are most vulnerable. This analysis assesses and tracks the accessibility of Houston's major highways during Harvey's evolution by utilizing road flood/closure data from the Texas DOT. In the absence of flooded/closure data for local roads, a hybrid approach is adopted that utilizes a physics-based hydrologic model to produce high-resolution inundation estimates for selected urban watersheds in the Houston area. In particular, hydrologic output in the form of inundation depths is used to estimate the operability of local roads. Ultimately, integration of hydrologic-based estimation of road conditions with observed data from DOT supports a network accessibility analysis of selected urban neighborhoods. This accessibility analysis can identify operable routes for emergency response (rescue crews, medical services, etc.) during the storm event.

European network for promoting the physical health of residents in psychiatric and social care facilities (HELPS): background, aims and methods

PubMed Central

Weiser, Prisca; Becker, Thomas; Losert, Carolin; Alptekin, Köksal; Berti, Loretta; Burti, Lorenzo; Burton, Alexandra; Dernovsek, Mojca; Dragomirecka, Eva; Freidl, Marion; Friedrich, Fabian; Genova, Aneta; Germanavicius, Arunas; Halis, Ulaş; Henderson, John; Hjorth, Peter; Lai, Taavi; Larsen, Jens Ivar; Lech, Katarzyna; Lucas, Ramona; Marginean, Roxana; McDaid, David; Mladenova, Maya; Munk-Jørgensen, Povl; Paziuc, Alexandru; Paziuc, Petronela; Priebe, Stefan; Prot-Klinger, Katarzyna; Wancata, Johannes; Kilian, Reinhold

2009-01-01

Background People with mental disorders have a higher prevalence of physical illnesses and reduced life expectancy as compared with the general population. However, there is a lack of knowledge across Europe concerning interventions that aim at reducing somatic morbidity and excess mortality by promoting behaviour-based and/or environment-based interventions. Methods and design HELPS is an interdisciplinary European network that aims at (i) gathering relevant knowledge on physical illness in people with mental illness, (ii) identifying health promotion initiatives in European countries that meet country-specific needs, and (iii) at identifying best practice across Europe. Criteria for best practice will include evidence on the efficacy of physical health interventions and of their effectiveness in routine care, cost implications and feasibility for adaptation and implementation of interventions across different settings in Europe. HELPS will develop and implement a "physical health promotion toolkit". The toolkit will provide information to empower residents and staff to identify the most relevant risk factors in their specific context and to select the most appropriate action out of a range of defined health promoting interventions. The key methods are (a) stakeholder analysis, (b) international literature reviews, (c) Delphi rounds with experts from participating centres, and (d) focus groups with staff and residents of mental health care facilities. Meanwhile a multi-disciplinary network consisting of 15 European countries has been established and took up the work. As one main result of the project they expect that a widespread use of the HELPS toolkit could have a significant positive effect on the physical health status of residents of mental health and social care facilities, as well as to hold resonance for community dwelling people with mental health problems. Discussion A general strategy on health promotion for people with mental disorders must take into account behavioural, environmental and iatrogenic health risks. A European health promotion toolkit needs to consider heterogeneity of mental disorders, the multitude of physical health problems, health-relevant behaviour, health-related attitudes, health-relevant living conditions, and resource levels in mental health and social care facilities. PMID:19715560

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

Racah, Evan; Ko, Seyoon; Sadowski, Peter

Experiments in particle physics produce enormous quantities of data that must be analyzed and interpreted by teams of physicists. This analysis is often exploratory, where scientists are unable to enumerate the possible types of signal prior to performing the experiment. Thus, tools for summarizing, clustering, visualizing and classifying high-dimensional data are essential. Here in this work, we show that meaningful physical content can be revealed by transforming the raw data into a learned high-level representation using deep neural networks, with measurements taken at the Daya Bay Neutrino Experiment as a case study. We further show how convolutional deep neural networksmore » can provide an effective classification filter with greater than 97% accuracy across different classes of physics events, significantly better than other machine learning approaches.« less

Physics in ;Real Life;: Accelerator-based Research with Undergraduates

NASA Astrophysics Data System (ADS)

Klay, J. L.

All undergraduates in physics and astronomy should have access to significant research experiences. When given the opportunity to tackle challenging open-ended problems outside the classroom, students build their problem-solving skills in ways that better prepare them for the workplace or future research in graduate school. Accelerator-based research on fundamental nuclear and particle physics can provide a myriad of opportunities for undergraduate involvement in hardware and software development as well as ;big data; analysis. The collaborative nature of large experiments exposes students to scientists of every culture and helps them begin to build their professional network even before they graduate. This paper presents an overview of my experiences - the good, the bad, and the ugly - engaging undergraduates in particle and nuclear physics research at the CERN Large Hadron Collider and the Los Alamos Neutron Science Center.

Performance evaluation of complete data transfer of physical layer according to IEEE 802.15.4 standard

NASA Astrophysics Data System (ADS)

Raju, Kota Solomon; Merugu, Naresh Babu; Neetu, Babu, E. Ram

2016-03-01

ZigBee is well-accepted industrial standard for wireless sensor networks based on IEEE 802.15.4 standard. Wireless Sensor Networks is the major concern of communication these days. These Wireless Sensor Networks investigate the properties of networks of small battery-powered sensors with wireless communication. The communication between any two wireless nodes of wireless sensor networks is carried out through a protocol stack. This protocol stack has been designed by different vendors in various ways. Every custom vendor possesses his own protocol stack and algorithms especially at the MAC layer. But, many applications require modifications in their algorithms at various layers as per their requirements, especially energy efficient protocols at MAC layer that are simulated in Wireless sensor Network Simulators which are not being tested in real time systems because vendors do not allow the programmability of each layer in their protocol stack. This problem can be quoted as Vendor-Interoperability. The solution is to develop the programmable protocol stack where we can design our own application as required. As a part of the task first we tried implementing physical layer and transmission of data using physical layer. This paper describes about the transmission of the total number of bytes of Frame according to the IEEE 802.15.4 standard using Physical Layer.

Impact of interprofessional education about psychological and medical comorbidities on practitioners' knowledge and collaborative practice: mixed method evaluation of a national program.

PubMed

Phillips, Christine B; Hall, Sally; Irving, Michelle

2016-09-02

Many patients with chronic physical illnesses have co-morbid psychological illnesses, which may respond to interprofessional collaborative care. Continuing education programs frequently focus on skills and knowledge relevant for individual illnesses, and unidisciplinary care. This study evaluates the impact of "Mind the Gap", an Australian interprofessional continuing education program about management of dual illnesses, on practitioners' knowledge, use of psychological strategies and collaborative practice. A 6-h module addressing knowledge and skills needed for patients with physical and psychological co-morbid illnesses was delivered to 837 practitioners from mixed health professional backgrounds, through locally-facilitated workshops at 45 Australian sites. We conducted a mixed-methods evaluation, incorporating observation, surveys and network analysis using data collected, before, immediately after, and three months after training. Six hundred forty-five participants enrolled in the evaluation (58 % GPs, 17 % nurses, 15 % mental health professionals, response rate 76 %). Participants' knowledge and confidence to manage patients with psychological and physical illnesses improved immediately. Among the subset surveyed at three months (response rate 24 %), referral networks had increased across seven disciplines, improvements in confidence and knowledge were sustained, and doctors, but no other disciplines, reported an increase in use of motivational interviewing (85.9 % to 96.8 %) and mindfulness (58.6 % to 74 %). Interprofessional workshops had an immediate impact on the stated knowledge and confidence of participants to manage patients with physical and psychological comorbidities, which appears to have been sustained. For some attendees, there was a sustained improvement in the size of their referral networks and their use of some psychological strategies.

Gross anatomy of network security

NASA Technical Reports Server (NTRS)

Siu, Thomas J.

2002-01-01

Information security involves many branches of effort, including information assurance, host level security, physical security, and network security. Computer network security methods and implementations are given a top-down description to permit a medically focused audience to anchor this information to their daily practice. The depth of detail of network functionality and security measures, like that of the study of human anatomy, can be highly involved. Presented at the level of major gross anatomical systems, this paper will focus on network backbone implementation and perimeter defenses, then diagnostic tools, and finally the user practices (the human element). Physical security measures, though significant, have been defined as beyond the scope of this presentation.

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.

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

Individual and social network predictors of physical bullying: a longitudinal study of Taiwanese early adolescents.

PubMed

Wei, Hsi-Sheng; Lee, Wonjae

2014-01-01

This study followed 125 7th-grade students in Taiwan for the entire school year and analyzed the individual and social network factors predicting their involvement in physical bullying over 5 waves of data. Using self-reports of bullying experiences, 20 classroom-level networks of bullying and friendship were constructed for 4 classrooms and 5 temporal points, from which 4 individual-level network measures were calculated. They included bully and victim centrality, popularity, and embeddedness in friendship networks. A series of mixed models for repeated measures were constructed to predict students' bully and victim centrality in bullying network at time t + 1. Compared to girls, boys were more likely to be both the bullies and victims. Lower self-esteem and higher family economic status contributed to victim centrality. Having parents married and living together predicted lower bully centrality. Higher educational level of parents predicted lower victim and bully centrality. Regarding the social network factors, students' bully centrality at t positively predicted their bully centrality at t + 1, whereas victim centrality predicted their subsequent victim centrality. Interaction effects between friendship network and bullying network were observed. Embeddedness in friendship network reduced victim centrality at t + 1 except for those students with low victim centrality at t. For those with high victim centrality at t, popularity increased their risk of physical victimization over time. Implications for research and practice are discussed.

Coincidence and coherent data analysis methods for gravitational wave bursts in a network of interferometric detectors

NASA Astrophysics Data System (ADS)

Arnaud, Nicolas; Barsuglia, Matteo; Bizouard, Marie-Anne; Brisson, Violette; Cavalier, Fabien; Davier, Michel; Hello, Patrice; Kreckelbergh, Stephane; Porter, Edward K.

2003-11-01

Network data analysis methods are the only way to properly separate real gravitational wave (GW) transient events from detector noise. They can be divided into two generic classes: the coincidence method and the coherent analysis. The former uses lists of selected events provided by each interferometer belonging to the network and tries to correlate them in time to identify a physical signal. Instead of this binary treatment of detector outputs (signal present or absent), the latter method involves first the merging of the interferometer data and looks for a common pattern, consistent with an assumed GW waveform and a given source location in the sky. The thresholds are only applied later, to validate or not the hypothesis made. As coherent algorithms use more complete information than coincidence methods, they are expected to provide better detection performances, but at a higher computational cost. An efficient filter must yield a good compromise between a low false alarm rate (hence triggering on data at a manageable rate) and a high detection efficiency. Therefore, the comparison of the two approaches is achieved using so-called receiving operating characteristics (ROC), giving the relationship between the false alarm rate and the detection efficiency for a given method. This paper investigates this question via Monte Carlo simulations, using the network model developed in a previous article. Its main conclusions are the following. First, a three-interferometer network such as Virgo-LIGO is found to be too small to reach good detection efficiencies at low false alarm rates: larger configurations are suitable to reach a confidence level high enough to validate as true GW a detected event. In addition, an efficient network must contain interferometers with comparable sensitivities: studying the three-interferometer LIGO network shows that the 2-km interferometer with half sensitivity leads to a strong reduction of performances as compared to a network of three interferometers with full sensitivity. Finally, it is shown that coherent analyses are feasible for burst searches and are clearly more efficient than coincidence strategies. Therefore, developing such methods should be an important goal of a worldwide collaborative data analysis.

Effects of Social Support About Physical Activity on Social Networking Sites: Applying the Theory of Planned Behavior.

PubMed

Zhang, Ni; Campo, Shelly; Yang, Jingzhen; Janz, Kathleen F; Snetselaar, Linda G; Eckler, Petya

2015-01-01

Despite the physical and mental health benefits of leisure-time physical activity (LTPA), only about half of college students participate in the recommended amount of LTPA. While college students are avid users of social network sites (SNSs), whether SNSs would be an effective channel for promoting LTPA through peer social support is unclear. The aim of this study was to explore the effects of social support from students' contacts on SNSs on their intention to participate in LTPA, applying the Theory of Planned Behavior. Participants were recruited through a mass e-mail sent to undergraduate students at a large Midwestern university in fall 2011. In total, 439 surveys were analyzed. Descriptive analyses and analysis for mediating effects were conducted. Social support about LTPA from contacts on SNSs has indirect effect on intention through affective attitude, instrumental attitude, and perceived behavioral control (PBC). The results indicate that social support about LTPA from contacts on SNSs might not be effective to change students' intention unless attitudes and PBC are changed. Future interventions aiming to promote students' intention to participate in LTPA by increasing support from contacts on SNSs should increase affective attitude, instrumental attitude, and PBC at the same time.

Knowledge evolution in physics research: An analysis of bibliographic coupling networks.

PubMed

Liu, Wenyuan; Nanetti, Andrea; Cheong, Siew Ann

2017-01-01

Even as we advance the frontiers of physics knowledge, our understanding of how this knowledge evolves remains at the descriptive levels of Popper and Kuhn. Using the American Physical Society (APS) publications data sets, we ask in this paper how new knowledge is built upon old knowledge. We do so by constructing year-to-year bibliographic coupling networks, and identify in them validated communities that represent different research fields. We then visualize their evolutionary relationships in the form of alluvial diagrams, and show how they remain intact through APS journal splits. Quantitatively, we see that most fields undergo weak Popperian mixing, and it is rare for a field to remain isolated/undergo strong mixing. The sizes of fields obey a simple linear growth with recombination. We can also reliably predict the merging between two fields, but not for the considerably more complex splitting. Finally, we report a case study of two fields that underwent repeated merging and splitting around 1995, and how these Kuhnian events are correlated with breakthroughs on Bose-Einstein condensation (BEC), quantum teleportation, and slow light. This impact showed up quantitatively in the citations of the BEC field as a larger proportion of references from during and shortly after these events.

Interface Control Document for the EMPACT Module that Estimates Electric Power Transmission System Response to EMP-Caused Damage

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

Werley, Kenneth Alan; Mccown, Andrew William

The EPREP code is designed to evaluate the effects of an Electro-Magnetic Pulse (EMP) on the electric power transmission system. The EPREP code embodies an umbrella framework that allows a user to set up analysis conditions and to examine analysis results. The code links to three major physics/engineering modules. The first module describes the EM wave in space and time. The second module evaluates the damage caused by the wave on specific electric power (EP) transmission system components. The third module evaluates the consequence of the damaged network on its (reduced) ability to provide electric power to meet demand. Thismore » third module is the focus of the present paper. The EMPACT code serves as the third module. The EMPACT name denotes EMP effects on Alternating Current Transmission systems. The EMPACT algorithms compute electric power transmission network flow solutions under severely damaged network conditions. Initial solutions are often characterized by unacceptible network conditions including line overloads and bad voltages. The EMPACT code contains algorithms to adjust optimally network parameters to eliminate network problems while minimizing outages. System adjustments include automatically adjusting control equipment (generator V control, variable transformers, and variable shunts), as well as non-automatic control of generator power settings and minimal load shedding. The goal is to evaluate the minimal loss of customer load under equilibrium (steady-state) conditions during peak demand.« less

Appplication of statistical mechanical methods to the modeling of social networks

NASA Astrophysics Data System (ADS)

Strathman, Anthony Robert

With the recent availability of large-scale social data sets, social networks have become open to quantitative analysis via the methods of statistical physics. We examine the statistical properties of a real large-scale social network, generated from cellular phone call-trace logs. We find this network, like many other social networks to be assortative (r = 0.31) and clustered (i.e., strongly transitive, C = 0.21). We measure fluctuation scaling to identify the presence of internal structure in the network and find that structural inhomogeneity effectively disappears at the scale of a few hundred nodes, though there is no sharp cutoff. We introduce an agent-based model of social behavior, designed to model the formation and dissolution of social ties. The model is a modified Metropolis algorithm containing agents operating under the basic sociological constraints of reciprocity, communication need and transitivity. The model introduces the concept of a social temperature. We go on to show that this simple model reproduces the global statistical network features (incl. assortativity, connected fraction, mean degree, clustering, and mean shortest path length) of the real network data and undergoes two phase transitions, one being from a "gas" to a "liquid" state and the second from a liquid to a glassy state as function of this social temperature.

Parameter diagnostics of phases and phase transition learning by neural networks

NASA Astrophysics Data System (ADS)

Suchsland, Philippe; Wessel, Stefan

2018-05-01

We present an analysis of neural network-based machine learning schemes for phases and phase transitions in theoretical condensed matter research, focusing on neural networks with a single hidden layer. Such shallow neural networks were previously found to be efficient in classifying phases and locating phase transitions of various basic model systems. In order to rationalize the emergence of the classification process and for identifying any underlying physical quantities, it is feasible to examine the weight matrices and the convolutional filter kernels that result from the learning process of such shallow networks. Furthermore, we demonstrate how the learning-by-confusing scheme can be used, in combination with a simple threshold-value classification method, to diagnose the learning parameters of neural networks. In particular, we study the classification process of both fully-connected and convolutional neural networks for the two-dimensional Ising model with extended domain wall configurations included in the low-temperature regime. Moreover, we consider the two-dimensional XY model and contrast the performance of the learning-by-confusing scheme and convolutional neural networks trained on bare spin configurations to the case of preprocessed samples with respect to vortex configurations. We discuss these findings in relation to similar recent investigations and possible further applications.

Identifying group discriminative and age regressive sub-networks from DTI-based connectivity via a unified framework of non-negative matrix factorization and graph embedding

PubMed Central

Ghanbari, Yasser; Smith, Alex R.; Schultz, Robert T.; Verma, Ragini

2014-01-01

Diffusion tensor imaging (DTI) offers rich insights into the physical characteristics of white matter (WM) fiber tracts and their development in the brain, facilitating a network representation of brain’s traffic pathways. Such a network representation of brain connectivity has provided a novel means of investigating brain changes arising from pathology, development or aging. The high dimensionality of these connectivity networks necessitates the development of methods that identify the connectivity building blocks or sub-network components that characterize the underlying variation in the population. In addition, the projection of the subject networks into the basis set provides a low dimensional representation of it, that teases apart different sources of variation in the sample, facilitating variation-specific statistical analysis. We propose a unified framework of non-negative matrix factorization and graph embedding for learning sub-network patterns of connectivity by their projective non-negative decomposition into a reconstructive basis set, as well as, additional basis sets representing variational sources in the population like age and pathology. The proposed framework is applied to a study of diffusion-based connectivity in subjects with autism that shows localized sparse sub-networks which mostly capture the changes related to pathology and developmental variations. PMID:25037933

PREFACE: Algebra, Geometry, and Mathematical Physics 2010

NASA Astrophysics Data System (ADS)

Stolin, A.; Abramov, V.; Fuchs, J.; Paal, E.; Shestopalov, Y.; Silvestrov, S.

2012-02-01

This proceedings volume presents results obtained by the participants of the 6th Baltic-Nordic workshop 'Algebra, Geometry, and Mathematical Physics (AGMP-6)' held at the Sven Lovén Centre for Marine Sciences in Tjärnö, Sweden on October 25-30, 2010. The Baltic-Nordic Network AGMP 'Algebra, Geometry, and Mathematical Physics' http://www.agmp.eu was created in 2005 on the initiative of two Estonian universities and two Swedish universities: Tallinn University of Technology represented by Eugen Paal (coordinator of the network), Tartu University represented by Viktor Abramov, Lund University represented by Sergei Silvestrov, and Chalmers University of Technology and the University of Gothenburg represented by Alexander Stolin. The goal was to promote international and interdisciplinary cooperation between scientists and research groups in the countries of the Baltic-Nordic region in mathematics and mathematical physics, with special emphasis on the important role played by algebra and geometry in modern physics, engineering and technologies. The main activities of the AGMP network consist of a series of regular annual international workshops, conferences and research schools. The AGMP network also constitutes an important educational forum for scientific exchange and dissimilation of research results for PhD students and Postdocs. The network has expanded since its creation, and nowadays its activities extend beyond countries in the Baltic-Nordic region to universities in other European countries and participants from elsewhere in the world. As one of the important research-dissimilation outcomes of its activities, the network has a tradition of producing high-quality research proceedings volumes after network events, publishing them with various international publishers. The PDF also contains the following: List of AGMP workshops and other AGMP activities Main topics discussed at AGMP-6 Review of AGMP-6 proceedings Acknowledgments List of Conference Participants

Loads Bias Genetic and Signaling Switches in Synthetic and Natural Systems

PubMed Central

Medford, June; Prasad, Ashok

2014-01-01

Biological protein interactions networks such as signal transduction or gene transcription networks are often treated as modular, allowing motifs to be analyzed in isolation from the rest of the network. Modularity is also a key assumption in synthetic biology, where it is similarly expected that when network motifs are combined together, they do not lose their essential characteristics. However, the interactions that a network module has with downstream elements change the dynamical equations describing the upstream module and thus may change the dynamic and static properties of the upstream circuit even without explicit feedback. In this work we analyze the behavior of a ubiquitous motif in gene transcription and signal transduction circuits: the switch. We show that adding an additional downstream component to the simple genetic toggle switch changes its dynamical properties by changing the underlying potential energy landscape, and skewing it in favor of the unloaded side, and in some situations adding loads to the genetic switch can also abrogate bistable behavior. We find that an additional positive feedback motif found in naturally occurring toggle switches could tune the potential energy landscape in a desirable manner. We also analyze autocatalytic signal transduction switches and show that a ubiquitous positive feedback switch can lose its switch-like properties when connected to a downstream load. Our analysis underscores the necessity of incorporating the effects of downstream components when understanding the physics of biochemical network motifs, and raises the question as to how these effects are managed in real biological systems. This analysis is particularly important when scaling synthetic networks to more complex organisms. PMID:24676102

Efficient Allocation of Resources for Defense of Spatially Distributed Networks Using Agent-Based Simulation.

PubMed

Kroshl, William M; Sarkani, Shahram; Mazzuchi, Thomas A

2015-09-01

This article presents ongoing research that focuses on efficient allocation of defense resources to minimize the damage inflicted on a spatially distributed physical network such as a pipeline, water system, or power distribution system from an attack by an active adversary, recognizing the fundamental difference between preparing for natural disasters such as hurricanes, earthquakes, or even accidental systems failures and the problem of allocating resources to defend against an opponent who is aware of, and anticipating, the defender's efforts to mitigate the threat. Our approach is to utilize a combination of integer programming and agent-based modeling to allocate the defensive resources. We conceptualize the problem as a Stackelberg "leader follower" game where the defender first places his assets to defend key areas of the network, and the attacker then seeks to inflict the maximum damage possible within the constraints of resources and network structure. The criticality of arcs in the network is estimated by a deterministic network interdiction formulation, which then informs an evolutionary agent-based simulation. The evolutionary agent-based simulation is used to determine the allocation of resources for attackers and defenders that results in evolutionary stable strategies, where actions by either side alone cannot increase its share of victories. We demonstrate these techniques on an example network, comparing the evolutionary agent-based results to a more traditional, probabilistic risk analysis (PRA) approach. Our results show that the agent-based approach results in a greater percentage of defender victories than does the PRA-based approach. © 2015 Society for Risk Analysis.

The SEVAN Worldwide network of particle detectors: 10 years of operation

NASA Astrophysics Data System (ADS)

Chilingarian, A.; Babayan, V.; Karapetyan, T.; Mailyan, B.; Sargsyan, B.; Zazyan, M.

2018-05-01

The Space Environment Viewing and Analysis Network (SEVAN) aims to improve the fundamental research on particle acceleration in the vicinity of the sun, on space weather effects and on high-energy physics in the atmosphere and lightning initiation. This new type of a particle detector setup simultaneously measures fluxes of most species of secondary cosmic rays, thus being a powerful integrated device for exploration of solar modulation effects and electron acceleration in the thunderstorm atmosphere. The SEVAN modules are operating at the Aragats Space Environmental Center (ASEC) in Armenia, in Croatia, Bulgaria, Slovakia, the Czech Republic (from 2017) and in India. In this paper, we present the most interesting results of the SEVAN network operation during the last decade. We present this review on the occasion of the 10th anniversary of the International Heliophysical Year in 2007.

Engineering online and in-person social networks to sustain physical activity: application of a conceptual model.

PubMed

Rovniak, Liza S; Sallis, James F; Kraschnewski, Jennifer L; Sciamanna, Christopher N; Kiser, Elizabeth J; Ray, Chester A; Chinchilli, Vernon M; Ding, Ding; Matthews, Stephen A; Bopp, Melissa; George, Daniel R; Hovell, Melbourne F

2013-08-14

High rates of physical inactivity compromise the health status of populations globally. Social networks have been shown to influence physical activity (PA), but little is known about how best to engineer social networks to sustain PA. To improve procedures for building networks that shape PA as a normative behavior, there is a need for more specific hypotheses about how social variables influence PA. There is also a need to integrate concepts from network science with ecological concepts that often guide the design of in-person and electronically-mediated interventions. Therefore, this paper: (1) proposes a conceptual model that integrates principles from network science and ecology across in-person and electronically-mediated intervention modes; and (2) illustrates the application of this model to the design and evaluation of a social network intervention for PA. A conceptual model for engineering social networks was developed based on a scoping literature review of modifiable social influences on PA. The model guided the design of a cluster randomized controlled trial in which 308 sedentary adults were randomly assigned to three groups: WalkLink+: prompted and provided feedback on participants' online and in-person social-network interactions to expand networks for PA, plus provided evidence-based online walking program and weekly walking tips; WalkLink: evidence-based online walking program and weekly tips only; Minimal Treatment Control: weekly tips only. The effects of these treatment conditions were assessed at baseline, post-program, and 6-month follow-up. The primary outcome was accelerometer-measured PA. Secondary outcomes included objectively-measured aerobic fitness, body mass index, waist circumference, blood pressure, and neighborhood walkability; and self-reported measures of the physical environment, social network environment, and social network interactions. The differential effects of the three treatment conditions on primary and secondary outcomes will be analyzed using general linear modeling (GLM), or generalized linear modeling if the assumptions for GLM cannot be met. Results will contribute to greater understanding of how to conceptualize and implement social networks to support long-term PA. Establishing social networks for PA across multiple life settings could contribute to cultural norms that sustain active living. ClinicalTrials.gov NCT01142804.

Relative impacts of the fragmentation and spatial structure of habitats on freshwater fish distributions: application on French watersheds (Invited)

NASA Astrophysics Data System (ADS)

Le Pichon, C.; Belliard, J.; Talès, E.; Gorges, G.; Clément, F.

2009-12-01

Most of the rivers of the Ile de France region, intimately linked with the megalopolis of Paris, are severely altered and freshwater fishes are exposed to habitat alteration, reduced connectivity and pollution. Several species thus present fragmented distributions and decreasing densities. In this context, the European Water Framework Directive (2000) has goals of hydrosystems rehabilitation and no further damage. In particular, the preservation and restoration of ecological connectivity of river networks is a key element for fish populations. These goals require the identification of natural and anthropological factors which influence the spatial distribution of species. We have proposed a riverscape approach, based on landscape ecology concepts, combined with a set of spatial analysis methods to assess the multiscale relationships between the spatial pattern of fish habitats and processes depending on fish movements. In particular, we used this approach to test the relative roles of spatial arrangement of fish habitats and the presence of physical barriers in explaining fish spatial distributions in a small rural watershed (106 km2). We performed a spatially continuous analysis of fish-habitat relationships. Fish habitats and physical barriers were mapped along the river network (33 km) with a GPS and imported into a GIS. In parallel, a longitudinal electrofishing survey of the distribution and abundance of fishes was made using a point abundance sampling scheme. Longitudinal arrangement of fish habitats were evaluated using spatial analysis methods: patch/distance metrics and moving window analysis. Explanatory models were developed to test the relative contribution of local environmental variables and spatial context in explaining fish presence. We have recorded about 100 physical barriers, on average one every 330 meters; most artificial barriers were road pipe culverts, falls associated with ponds and sluice gates. Contrasted fish communities and densities were observed in the different areas of the watershed, related to various land use (riparian forest or agriculture). The first results of fish-habitat association analysis on a 5 km stream are that longitudinal distribution of fish species was mainly impacted by falls associated with ponds. The impact was both due to the barrier effect and to the modification of aquatic habitats. Abundance distribution of Salmo trutta and Cottus gobio was particularly affected. Spatially continuous analysis of fish-habitat relationships allowed us to identify the relative impacts of habitat alteration and presence of physical barriers to fish movements. These techniques could help prioritize preservation and restoration policies in human-impacted watersheds, in particular, identifying the key physical barriers to remove.

A physically based catchment partitioning method for hydrological analysis

NASA Astrophysics Data System (ADS)

Menduni, Giovanni; Riboni, Vittoria

2000-07-01

We propose a partitioning method for the topographic surface, which is particularly suitable for hydrological distributed modelling and shallow-landslide distributed modelling. The model provides variable mesh size and appears to be a natural evolution of contour-based digital terrain models. The proposed method allows the drainage network to be derived from the contour lines. The single channels are calculated via a search for the steepest downslope lines. Then, for each network node, the contributing area is determined by means of a search for both steepest upslope and downslope lines. This leads to the basin being partitioned into physically based finite elements delimited by irregular polygons. In particular, the distributed computation of local geomorphological parameters (i.e. aspect, average slope and elevation, main stream length, concentration time, etc.) can be performed easily for each single element. The contributing area system, together with the information on the distribution of geomorphological parameters provide a useful tool for distributed hydrological modelling and simulation of environmental processes such as erosion, sediment transport and shallow landslides.

Non-canonical Wnt signalling modulates the endothelial shear stress flow sensor in vascular remodelling

PubMed Central

Franco, Claudio A; Jones, Martin L; Bernabeu, Miguel O; Vion, Anne-Clemence; Barbacena, Pedro; Fan, Jieqing; Mathivet, Thomas; Fonseca, Catarina G; Ragab, Anan; Yamaguchi, Terry P; Coveney, Peter V; Lang, Richard A; Gerhardt, Holger

2016-01-01

Endothelial cells respond to molecular and physical forces in development and vascular homeostasis. Deregulation of endothelial responses to flow-induced shear is believed to contribute to many aspects of cardiovascular diseases including atherosclerosis. However, how molecular signals and shear-mediated physical forces integrate to regulate vascular patterning is poorly understood. Here we show that endothelial non-canonical Wnt signalling regulates endothelial sensitivity to shear forces. Loss of Wnt5a/Wnt11 renders endothelial cells more sensitive to shear, resulting in axial polarization and migration against flow at lower shear levels. Integration of flow modelling and polarity analysis in entire vascular networks demonstrates that polarization against flow is achieved differentially in artery, vein, capillaries and the primitive sprouting front. Collectively our data suggest that non-canonical Wnt signalling stabilizes forming vascular networks by reducing endothelial shear sensitivity, thus keeping vessels open under low flow conditions that prevail in the primitive plexus. DOI: http://dx.doi.org/10.7554/eLife.07727.001 PMID:26845523

Physical Model of the Genotype-to-Phenotype Map of Proteins

NASA Astrophysics Data System (ADS)

Tlusty, Tsvi; Libchaber, Albert; Eckmann, Jean-Pierre

2017-04-01

How DNA is mapped to functional proteins is a basic question of living matter. We introduce and study a physical model of protein evolution which suggests a mechanical basis for this map. Many proteins rely on large-scale motion to function. We therefore treat protein as learning amorphous matter that evolves towards such a mechanical function: Genes are binary sequences that encode the connectivity of the amino acid network that makes a protein. The gene is evolved until the network forms a shear band across the protein, which allows for long-range, soft modes required for protein function. The evolution reduces the high-dimensional sequence space to a low-dimensional space of mechanical modes, in accord with the observed dimensional reduction between genotype and phenotype of proteins. Spectral analysis of the space of 1 06 solutions shows a strong correspondence between localization around the shear band of both mechanical modes and the sequence structure. Specifically, our model shows how mutations are correlated among amino acids whose interactions determine the functional mode.

The impact of targeted Rheumatoid Arthritis pharmacological treatment on mental health: A systematic review and network meta-analysis.

PubMed

Matcham, Faith; Galloway, James; Hotopf, Matthew; Roberts, Emmert; Scott, Ian C; Steer, Sophia; Norton, Sam

2018-06-06

Rheumatoid Arthritis (RA) pharmacotherapy may impact mental health (MH) outcomes by improving pain and stiffness; and potentially via targeting inflammatory processes common to RA and depression. The objectives of this review were to i) ascertain the frequency of MH assessment in RA pharmacotherapy trials; ii) quantify the efficacy of RA pharmacotherapy efficacy on MH outcomes; iii) explore the clinical and demographic factors related to MH outcomes. CENTRAL, PsychINFO, Web of Science, Medline, Embase and CINAHL were systematically searched from inception to March 2017 for randomised trials of disease-modifying anti-rheumatic drugs (DMARDs) in adult RA patients. The primary outcome was MH; self-reported physical health was extracted as a secondary outcome. Pairwise meta-analysis (PMA) created pooled effect sizes and 95%CIs for comparisons of all treatments versus comparators (active or placebo). Network meta-analysis (NMA) provided effect size estimates of targeted biologic DMARDs (bDMARDs) versus conventional synthetic DMARDs (csDMARDs) using indirect comparisons of different treatment modalities. 71 eligible studies were identified. 57 studies were included in the PMA, representing 23,535 patients. bDMARDs showed small effects on MH (standardised mean difference (SMD) versus csDMARDs = 0.19 to 0.30), and moderate effects on self-reported physical health (SMD versus csDMARDs = 0.46 to 0.50), with NMA determining no significant differences in effectiveness between bDMARD mode of action on either outcome. Effective pharmacotherapy alone is unlikely to substantially improve MH outcomes for most RA patients. Integrated MH care provided within routine clinical practice is essential to optimise mental and physical health outcomes. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

Physical approach to quantum networks with massive particles

NASA Astrophysics Data System (ADS)

Andersen, Molte Emil Strange; Zinner, Nikolaj Thomas

2018-04-01

Assembling large-scale quantum networks is a key goal of modern physics research with applications in quantum information and computation. Quantum wires and waveguides in which massive particles propagate in tailored confinement is one promising platform for realizing a quantum network. In the literature, such networks are often treated as quantum graphs, that is, the wave functions are taken to live on graphs of one-dimensional edges meeting in vertices. Hitherto, it has been unclear what boundary conditions on the vertices produce the physical states one finds in nature. This paper treats a quantum network from a physical approach, explicitly finds the physical eigenstates and compares them to the quantum-graph description. The basic building block of a quantum network is an X-shaped potential well made by crossing two quantum wires, and we consider a massive particle in such an X well. The system is analyzed using a variational method based on an expansion into modes with fast convergence and it provides a very clear intuition for the physics of the problem. The particle is found to have a ground state that is exponentially localized to the center of the X well, and the other symmetric solutions are formed so to be orthogonal to the ground state. This is in contrast to the predictions of the conventionally used so-called Kirchoff boundary conditions in quantum graph theory that predict a different sequence of symmetric solutions that cannot be physically realized. Numerical methods have previously been the only source of information on the ground-state wave function and our results provide a different perspective with strong analytical insights. The ground-state wave function has a spatial profile that looks very similar to the shape of a solitonic solution to a nonlinear Schrödinger equation, enabling an analytical prediction of the wave number. When combining multiple X wells into a network or grid, each site supports a solitonlike localized state. These localized solutions only couple to each other and are able to jump from one site to another as if they were trapped in a discrete lattice.

Do Israeli health promoting schools contribute to students' healthy eating and physical activity habits?

PubMed

Hayek, Samah; Tessler, Riki; Bord, Shiran; Endevelt, Ronit; Satran, Carmit; Livne, Irit; Khatib, Mohammed; Harel-Fisch, Yosi; Baron-Epel, Orna

2017-10-04

The Israeli Health Promoting School Network (HPSN) is actively committed to enhancing a healthy lifestyle for the entire school population. This study aimed to explore the contribution of school participation in the HPSN and students' individual characteristics to healthy eating and physical activity habits among Israeli school children aged 10-12 years. A cross-sectional survey was conducted among 4166 students in grades 4-6 from 28 schools. The schools were selected from a sample of HPSN affiliated and non-HPSN schools. The contribution of individual characteristics (grade, gender and subjective self-reported health education activities at school) and school characteristics (school type, population group, deprivation score) to healthy eating and physical activity habits was analyzed using multi-level hierarchical models. Multi-level analysis indicated that student's individual characteristic was significantly associated with healthy eating and physical activity habits. The subjective self-reported health education received at school was statistically significant factor associated with students' health behaviors. The school's affiliation with the HPSN was not associated with higher healthy eating and physical activity scores after adjusting for individual factors. These findings suggest that Israeli HPSN schools do not contribute to children's health behaviors more than other schools. Therefore, health promoting activities in HPSN schools need to be improved to justify their recognition as members of the HPS network and to fulfill their mission. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Neighborhood social capital and infant physical abuse: a population-based study in Japan.

PubMed

Fujiwara, Takeo; Yamaoka, Yui; Kawachi, Ichiro

2016-01-01

We sought to investigate the relationship between neighborhood social capital and infant physical abuse using a population-based sample of women with 4-month-old infants in Japan. A questionnaire was administered to women who participated in a 4-month health checkup program (n = 1277; valid response rate, 80 %). We inquired about their perceptions of the level of trust in their neighborhood (an indicator of "social capital") as well as the availability of support from their personal social networks. Infant physical abuse during the past month was assessed by self-reports of spanking, shaking or smothering. The prevalence of infant physical abuse at 4 months of age was 9.0 % (95 % confidence interval [CI], 7.6-10.7 %). Women living in trusting neighborhoods were less likely to report infant physical abuse compared to those living in areas with low neighborhood trust (odds ratio [OR] 0.25, 95 % CI 0.06-0.97). In addition, women with supportive social networks were less likely to report infant physical abuse (OR 0.59, 95 % CI 0.36-0.99). In addition to one's personal social network, social trust in the neighborhood was independently associated with lowered risk of infant physical abuse. To prevent infant abuse, interventions should consider strengthening community social bonds in addition to strengthening the social network of isolated mothers.

Review of complex networks application in hydroclimatic extremes with an implementation to characterize spatio-temporal drought propagation in continental USA

NASA Astrophysics Data System (ADS)

Konapala, Goutam; Mishra, Ashok

2017-12-01

The quantification of spatio-temporal hydroclimatic extreme events is a key variable in water resources planning, disaster mitigation, and preparing climate resilient society. However, quantification of these extreme events has always been a great challenge, which is further compounded by climate variability and change. Recently complex network theory was applied in earth science community to investigate spatial connections among hydrologic fluxes (e.g., rainfall and streamflow) in water cycle. However, there are limited applications of complex network theory for investigating hydroclimatic extreme events. This article attempts to provide an overview of complex networks and extreme events, event synchronization method, construction of networks, their statistical significance and the associated network evaluation metrics. For illustration purpose, we apply the complex network approach to study the spatio-temporal evolution of droughts in Continental USA (CONUS). A different drought threshold leads to a new drought event as well as different socio-economic implications. Therefore, it would be interesting to explore the role of thresholds on spatio-temporal evolution of drought through network analysis. In this study, long term (1900-2016) Palmer drought severity index (PDSI) was selected for spatio-temporal drought analysis using three network-based metrics (i.e., strength, direction and distance). The results indicate that the drought events propagate differently at different thresholds associated with initiation of drought events. The direction metrics indicated that onset of mild drought events usually propagate in a more spatially clustered and uniform approach compared to onsets of moderate droughts. The distance metric shows that the drought events propagate for longer distance in western part compared to eastern part of CONUS. We believe that the network-aided metrics utilized in this study can be an important tool in advancing our knowledge on drought propagation as well as other hydroclimatic extreme events. Although the propagation of droughts is investigated using the network approach, however process (physics) based approaches is essential to further understand the dynamics of hydroclimatic extreme events.

Virtual optical network mapping and core allocation in elastic optical networks using multi-core fibers

NASA Astrophysics Data System (ADS)

Xuan, Hejun; Wang, Yuping; Xu, Zhanqi; Hao, Shanshan; Wang, Xiaoli

2017-11-01

Virtualization technology can greatly improve the efficiency of the networks by allowing the virtual optical networks to share the resources of the physical networks. However, it will face some challenges, such as finding the efficient strategies for virtual nodes mapping, virtual links mapping and spectrum assignment. It is even more complex and challenging when the physical elastic optical networks using multi-core fibers. To tackle these challenges, we establish a constrained optimization model to determine the optimal schemes of optical network mapping, core allocation and spectrum assignment. To solve the model efficiently, tailor-made encoding scheme, crossover and mutation operators are designed. Based on these, an efficient genetic algorithm is proposed to obtain the optimal schemes of the virtual nodes mapping, virtual links mapping, core allocation. The simulation experiments are conducted on three widely used networks, and the experimental results show the effectiveness of the proposed model and algorithm.

Time-resolved microrheology of actively remodeling actomyosin networks

NASA Astrophysics Data System (ADS)

Silva, Marina Soares e.; Stuhrmann, Björn; Betz, Timo; Koenderink, Gijsje H.

2014-07-01

Living cells constitute an extraordinary state of matter since they are inherently out of thermal equilibrium due to internal metabolic processes. Indeed, measurements of particle motion in the cytoplasm of animal cells have revealed clear signatures of nonthermal fluctuations superposed on passive thermal motion. However, it has been difficult to pinpoint the exact molecular origin of this activity. Here, we employ time-resolved microrheology based on particle tracking to measure nonequilibrium fluctuations produced by myosin motor proteins in a minimal model system composed of purified actin filaments and myosin motors. We show that the motors generate spatially heterogeneous contractile fluctuations, which become less frequent with time as a consequence of motor-driven network remodeling. We analyze the particle tracking data on different length scales, combining particle image velocimetry, an ensemble analysis of the particle trajectories, and finally a kymograph analysis of individual particle trajectories to quantify the length and time scales associated with active particle displacements. All analyses show clear signatures of nonequilibrium activity: the particles exhibit random motion with an enhanced amplitude compared to passive samples, and they exhibit sporadic contractile fluctuations with ballistic motion over large (up to 30 μm) distances. This nonequilibrium activity diminishes with sample age, even though the adenosine triphosphate level is held constant. We propose that network coarsening concentrates motors in large clusters and depletes them from the network, thus reducing the occurrence of contractile fluctuations. Our data provide valuable insight into the physical processes underlying stress generation within motor-driven actin networks and the analysis framework may prove useful for future microrheology studies in cells and model organisms.

Maximizing Information Diffusion in the Cyber-physical Integrated Network †

PubMed Central

Lu, Hongliang; Lv, Shaohe; Jiao, Xianlong; Wang, Xiaodong; Liu, Juan

2015-01-01

Nowadays, our living environment has been embedded with smart objects, such as smart sensors, smart watches and smart phones. They make cyberspace and physical space integrated by their abundant abilities of sensing, communication and computation, forming a cyber-physical integrated network. In order to maximize information diffusion in such a network, a group of objects are selected as the forwarding points. To optimize the selection, a minimum connected dominating set (CDS) strategy is adopted. However, existing approaches focus on minimizing the size of the CDS, neglecting an important factor: the weight of links. In this paper, we propose a distributed maximizing the probability of information diffusion (DMPID) algorithm in the cyber-physical integrated network. Unlike previous approaches that only consider the size of CDS selection, DMPID also considers the information spread probability that depends on the weight of links. To weaken the effects of excessively-weighted links, we also present an optimization strategy that can properly balance the two factors. The results of extensive simulation show that DMPID can nearly double the information diffusion probability, while keeping a reasonable size of selection with low overhead in different distributed networks. PMID:26569254

Social support network, mental health and quality of life: a cross-sectional study in primary care.

PubMed

Portugal, Flávia Batista; Campos, Mônica Rodrigues; Correia, Celina Ragoni; Gonçalves, Daniel Almeida; Ballester, Dinarte; Tófoli, Luis Fernando; Mari, Jair de Jesus; Gask, Linda; Dowrick, Christopher; Bower, Peter; Fortes, Sandra

2016-12-22

The objective of this study was to identify the association between emotional distress and social support networks with quality of life in primary care patients. This was a cross-sectional study involving 1,466 patients in the cities of São Paulo and Rio de Janeiro, Brazil, in 2009/2010. The General Health Questionnaire, the Hospital Anxiety and Depression Scale and the brief version of the World Health Organization Quality of Life Instrument were used. The Social Support Network Index classified patients with the highest and lowest index as socially integrated or isolated. A bivariate analysis and four multiple linear regressions were conducted for each quality of life outcome. The means scores for the physical, psychological, social relations, and environment domains were, respectively, 64.7; 64.2; 68.5 and 49.1. In the multivariate analysis, the psychological domain was negatively associated with isolation, whereas the social relations and environment domains were positively associated with integration. Integration and isolation proved to be important factors for those in emotional distress as they minimize or maximize negative effects on quality of life.

Developing an Intelligent System for Diagnosis of Asthma Based on Artificial Neural Network.

PubMed

Alizadeh, Behrouz; Safdari, Reza; Zolnoori, Maryam; Bashiri, Azadeh

2015-08-01

Lack of proper diagnosis and inadequate treatment of asthma, leads to physical and financial complications. This study aimed to use data mining techniques and creating a neural network intelligent system for diagnosis of asthma. The study population is the patients who had visited one of the Lung Clinics in Tehran. Data were analyzed using the SPSS statistical tool and the chi-square Pearson's coefficient was the basis of decision making for data ranking. The considered neural network is trained using back propagation learning technique. According to the analysis performed by means of SPSS to select the top factors, 13 effective factors were selected, in different performances, data was mixed in various forms, so the different modes was made for training the data and testing networks and in all different modes, the network was able to predict correctly 100% of all cases. Using data mining methods before the design structure of system, aimed to reduce the data dimension and the optimum choice of the data, will lead to a more accurate system. So considering the data mining approaches due to the nature of medical data is necessary.

A network of discrete events for the representation and analysis of diffusion dynamics.

PubMed

Pintus, Alberto M; Pazzona, Federico G; Demontis, Pierfranco; Suffritti, Giuseppe B

2015-11-14

We developed a coarse-grained description of the phenomenology of diffusive processes, in terms of a space of discrete events and its representation as a network. Once a proper classification of the discrete events underlying the diffusive process is carried out, their transition matrix is calculated on the basis of molecular dynamics data. This matrix can be represented as a directed, weighted network where nodes represent discrete events, and the weight of edges is given by the probability that one follows the other. The structure of this network reflects dynamical properties of the process of interest in such features as its modularity and the entropy rate of nodes. As an example of the applicability of this conceptual framework, we discuss here the physics of diffusion of small non-polar molecules in a microporous material, in terms of the structure of the corresponding network of events, and explain on this basis the diffusivity trends observed. A quantitative account of these trends is obtained by considering the contribution of the various events to the displacement autocorrelation function.

A cloud-based forensics tracking scheme for online social network clients.

PubMed

Lin, Feng-Yu; Huang, Chien-Cheng; Chang, Pei-Ying

2015-10-01

In recent years, with significant changes in the communication modes, most users are diverted to cloud-based applications, especially online social networks (OSNs), which applications are mostly hosted on the outside and available to criminals, enabling them to impede criminal investigations and intelligence gathering. In the virtual world, how the Law Enforcement Agency (LEA) identifies the "actual" identity of criminal suspects, and their geolocation in social networks, is a major challenge to current digital investigation. In view of this, this paper proposes a scheme, based on the concepts of IP location and network forensics, which aims to develop forensics tracking on OSNs. According to our empirical analysis, the proposed mechanism can instantly trace the "physical location" of a targeted service resource identifier (SRI), when the target client is using online social network applications (Facebook, Twitter, etc.), and can analyze the probable target client "identity" associatively. To the best of our knowledge, this is the first individualized location method and architecture developed and evaluated in OSNs. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

The NASA Fireball Network

NASA Technical Reports Server (NTRS)

Cooke, William J.

2013-01-01

In the summer of 2008, the NASA Meteoroid Environments Office (MEO) began to establish a video fireball network, based on the following objectives: (1) determine the speed distribution of cm size meteoroids, (2) determine the major sources of cm size meteoroids (showers/sporadic sources), (3) characterize meteor showers (numbers, magnitudes, trajectories, orbits), (4) determine the size at which showers dominate the meteor flux, (5) discriminate between re-entering space debris and meteors, and 6) locate meteorite falls. In order to achieve the above with the limited resources available to the MEO, it was necessary that the network function almost fully autonomously, with very little required from humans in the areas of upkeep or analysis. With this in mind, the camera design and, most importantly, the ASGARD meteor detection software were adopted from the University of Western Ontario's Southern Ontario Meteor Network (SOMN), as NASA has a cooperative agreement with Western's Meteor Physics Group. 15 cameras have been built, and the network now consists of 8 operational cameras, with at least 4 more slated for deployment in calendar year 2013. The goal is to have 15 systems, distributed in two or more groups east of automatic analysis; every morning, this server also automatically generates an email and a web page (http://fireballs.ndc.nasa.gov) containing an automated analysis of the previous night's events. This analysis provides the following for each meteor: UTC date and time, speed, start and end locations (longitude, latitude, altitude), radiant, shower identification, light curve (meteor absolute magnitude as a function of time), photometric mass, orbital elements, and Tisserand parameter. Radiant/orbital plots and various histograms (number versus speed, time, etc) are also produced. After more than four years of operation, over 5,000 multi-station fireballs have been observed, 3 of which potentially dropped meteorites. A database containing data on all these events, including the videos and calibration information, has been developed and is being modified to include data from the SOMN and other camera networks.

Inference of directed climate networks: role of instability of causality estimation methods

NASA Astrophysics Data System (ADS)

Hlinka, Jaroslav; Hartman, David; Vejmelka, Martin; Paluš, Milan

2013-04-01

Climate data are increasingly analyzed by complex network analysis methods, including graph-theoretical approaches [1]. For such analysis, links between localized nodes of climate network are typically quantified by some statistical measures of dependence (connectivity) between measured variables of interest. To obtain information on the directionality of the interactions in the networks, a wide range of methods exists. These can be broadly divided into linear and nonlinear methods, with some of the latter having the theoretical advantage of being model-free, and principally a generalization of the former [2]. However, as a trade-off, this generality comes together with lower accuracy - in particular if the system was close to linear. In an overall stationary system, this may potentially lead to higher variability in the nonlinear network estimates. Therefore, with the same control of false alarms, this may lead to lower sensitivity for detection of real changes in the network structure. These problems are discussed on the example of daily SAT and SLP data from the NCEP/NCAR reanalysis dataset. We first reduce the dimensionality of data using PCA with VARIMAX rotation to detect several dozens of components that together explain most of the data variability. We further construct directed climate networks applying a selection of most widely used methods - variants of linear Granger causality and conditional mutual information. Finally, we assess the stability of the detected directed climate networks by computing them in sliding time windows. To understand the origin of the observed instabilities and their range, we also apply the same procedure to two types of surrogate data: either with non-stationarity in network structure removed, or imposed in a controlled way. In general, the linear methods show stable results in terms of overall similarity of directed climate networks inferred. For instance, for different decades of SAT data, the Spearman correlation of edge weights in the networks is ~ 0.6. The networks constructed using nonlinear measures were in general less stable both in real data and stationarized surrogates. Interestingly, when the nonlinear method parameters are optimized with respect to temporal stability of the networks, the networks seem to converge close to those detected by linear Granger causality. This provides further evidence for the hypothesis of overall sparsity and weakness of nonlinear coupling in climate networks on this spatial and temporal scale [3] and sufficient support for the use of linear methods in this context, unless specific clearly detectable nonlinear phenomena are targeted. Acknowledgement: This study is supported by the Czech Science Foundation, Project No. P103/11/J068. [1] Boccaletti, S.; Latora, V.; Moreno, Y.; Chavez, M. & Hwang, D. U.: Complex networks: Structure and dynamics, Physics Reports, 2006, 424, 175-308 [2] Barnett, L.; Barrett, A. B. & Seth, A. K.: Granger Causality and Transfer Entropy Are Equivalent for Gaussian Variables, Physical Review Letters, 2009, 103, 238701 [3] Hlinka, J.; Hartman, D.; Vejmelka, M.; Novotná, D.; Paluš, M.: Non-linear dependence and teleconnections in climate data: sources, relevance, nonstationarity, submitted preprint (http://arxiv.org/abs/1211.6688)