DANGEROUS LIAISONS? DATING AND DRINKING DIFFUSION IN ADOLESCENT PEER NETWORKS*

PubMed Central

Kreager, Derek A.; Haynie, Dana L.

2014-01-01

The onset and escalation of alcohol consumption and romantic relationships are hallmarks of adolescence, yet only recently have these domains jointly been the focus of sociological inquiry. We extend this literature by connecting alcohol use, dating and peers to understand the diffusion of drinking behavior in school-based friendship networks. Drawing on Granovetter’s classic concept of weak ties, we argue that adolescent romantic partners are likely to be network bridges, or liaisons, connecting daters to new peer contexts which, in turn, promote changes in individual drinking behaviors and allow these behaviors to spread across peer networks. Using longitudinal data of 459 couples from the National Longitudinal Study of Adolescent Health, we estimate Actor-Partner Interdependence Models and identify the unique contributions of partners’ drinking, friends’ drinking, and friends-of-partners’ drinking to daters’ own future binge drinking and drinking frequency. Findings support the liaison hypothesis and suggest that friends-of-partners’ drinking have net associations with adolescent drinking patterns. Moreover, the coefficient for friends-of-partners drinking is larger than the coefficient for one’s own peers and generally immune to prior selection. Our findings suggest that romantic relationships are important mechanisms for understanding the diffusion of emergent problem behaviors in adolescent peer networks. PMID:25328162

Discovery of Information Diffusion Process in Social Networks

NASA Astrophysics Data System (ADS)

Kim, Kwanho; Jung, Jae-Yoon; Park, Jonghun

Information diffusion analysis in social networks is of significance since it enables us to deeply understand dynamic social interactions among users. In this paper, we introduce approaches to discovering information diffusion process in social networks based on process mining. Process mining techniques are applied from three perspectives: social network analysis, process discovery and community recognition. We then present experimental results by using a real-life social network data. The proposed techniques are expected to employ as new analytical tools in online social networks such as blog and wikis for company marketers, politicians, news reporters and online writers.

Directed Diffusion Modelling for Tesso Nilo National Parks Case Study

NASA Astrophysics Data System (ADS)

Yasri, Indra; Safrianti, Ery

2018-01-01

— Directed Diffusion (DD has ability to achieve energy efficiency in Wireless Sensor Network (WSN). This paper proposes Directed Diffusion (DD) modelling for Tesso Nilo National Parks (TNNP) case study. There are 4 stages of scenarios involved in this modelling. It’s started by appointing of sampling area through GPS coordinate. The sampling area is determined by optimization processes from 500m x 500m up to 1000m x 1000m with 100m increment in between. The next stage is sensor node placement. Sensor node is distributed in sampling area with three different quantities i.e. 20 nodes, 30 nodes and 40 nodes. One of those quantities is choose as an optimized sensor node placement. The third stage is to implement all scenarios in stages 1 and stages 2 on DD modelling. In the last stage, the evaluation process to achieve most energy efficient in the combination of optimized sampling area and optimized sensor node placement on Direct Diffusion (DD) routing protocol. The result shows combination between sampling area 500m x 500m and 20 nodes able to achieve energy efficient to support a forest preventive fire system at Tesso Nilo National Parks.

Group-based strategy diffusion in multiplex networks with weighted values

NASA Astrophysics Data System (ADS)

Yu, Jianyong; Jiang, J. C.; Xiang, Leijun

2017-03-01

The information diffusion of multiplex social networks has received increasing interests in recent years. Actually, the multiplex networks are made of many communities, and it should be gotten more attention for the influences of community level diffusion, besides of individual level interactions. In view of this, this work explores strategy interactions and diffusion processes in multiplex networks with weighted values from a new perspective. Two different groups consisting of some agents with different influential strength are firstly built in each layer network, the authority and non-authority groups. The strategy interactions between different groups in intralayer and interlayer networks are performed to explore community level diffusion, by playing two classical strategy games, Prisoner's Dilemma and Snowdrift Game. The impact forces from the different groups and the reactive forces from individual agents are simultaneously taken into account in intralayer and interlayer interactions. This paper reveals and explains the evolutions of cooperation diffusion and the influences of interlayer interaction tight degrees in multiplex networks with weighted values. Some thresholds of critical parameters of interaction degrees and games parameters settings are also discussed in group-based strategy diffusion.

Rewiring the network. What helps an innovation to diffuse?

NASA Astrophysics Data System (ADS)

Sznajd-Weron, Katarzyna; Szwabiński, Janusz; Weron, Rafał; Weron, Tomasz

2014-03-01

A fundamental question related to innovation diffusion is how the structure of the social network influences the process. Empirical evidence regarding real-world networks of influence is very limited. On the other hand, agent-based modeling literature reports different, and at times seemingly contradictory, results. In this paper we study innovation diffusion processes for a range of Watts-Strogatz networks in an attempt to shed more light on this problem. Using the so-called Sznajd model as the backbone of opinion dynamics, we find that the published results are in fact consistent and allow us to predict the role of network topology in various situations. In particular, the diffusion of innovation is easier on more regular graphs, i.e. with a higher clustering coefficient. Moreover, in the case of uncertainty—which is particularly high for innovations connected to public health programs or ecological campaigns—a more clustered network will help the diffusion. On the other hand, when social influence is less important (i.e. in the case of perfect information), a shorter path will help the innovation to spread in the society and—as a result—the diffusion will be easiest on a random graph.

Rumor diffusion model with spatio-temporal diffusion and uncertainty of behavior decision in complex social networks

NASA Astrophysics Data System (ADS)

Zhu, Liang; Wang, Youguo

2018-07-01

In this paper, a rumor diffusion model with uncertainty of human behavior under spatio-temporal diffusion framework is established. Take physical significance of spatial diffusion into account, a diffusion threshold is set under which the rumor is not a trend topic and only spreads along determined physical connections. Heterogeneity of degree distribution and distance distribution has also been considered in theoretical model at the same time. The global existence and uniqueness of classical solution are proved with a Lyapunov function and an approximate classical solution in form of infinite series is constructed with a system of eigenfunction. Simulations and numerical solutions both on Watts-Strogatz (WS) network and Barabási-Albert (BA) network display the variation of density of infected connections from spatial and temporal dimensions. Relevant results show that the density of infected connections is dominated by network topology and uncertainty of human behavior at threshold time. With increase of social capability, rumor diffuses to the steady state in a higher speed. And the variation trends of diffusion size with uncertainty are diverse on different artificial networks.

National Seminar on the Diffusion of New Instructional Materials and Practices. 5.0 Characteristics of the Communications Network: What are the Mechanisms Within the Diffusion System That Encourage or Discourage the Diffusion of Innovation?

ERIC Educational Resources Information Center

Social Science Education Consortium, Inc., Boulder, CO.

In this document conference participants consider characteristics of the communications network for diffusion of new instructional materials and practices. Responses to these questions are presented: What are the communication mechanisms within the diffusion system that encourage or discourage the diffusion of innovation? What role do journal…

Exposure, hazard, and survival analysis of diffusion on social networks.

PubMed

Wu, Jiacheng; Crawford, Forrest W; Kim, David A; Stafford, Derek; Christakis, Nicholas A

2018-04-29

Sociologists, economists, epidemiologists, and others recognize the importance of social networks in the diffusion of ideas and behaviors through human societies. To measure the flow of information on real-world networks, researchers often conduct comprehensive sociometric mapping of social links between individuals and then follow the spread of an "innovation" from reports of adoption or change in behavior over time. The innovation is introduced to a small number of individuals who may also be encouraged to spread it to their network contacts. In conjunction with the known social network, the pattern of adoptions gives researchers insight into the spread of the innovation in the population and factors associated with successful diffusion. Researchers have used widely varying statistical tools to estimate these quantities, and there is disagreement about how to analyze diffusion on fully observed networks. Here, we describe a framework for measuring features of diffusion processes on social networks using the epidemiological concepts of exposure and competing risks. Given a realization of a diffusion process on a fully observed network, we show that classical survival regression models can be adapted to estimate the rate of diffusion, and actor/edge attributes associated with successful transmission or adoption, while accounting for the topology of the social network. We illustrate these tools by applying them to a randomized network intervention trial conducted in Honduras to estimate the rate of adoption of 2 health-related interventions-multivitamins and chlorine bleach for water purification-and determine factors associated with successful social transmission. Copyright © 2018 John Wiley & Sons, Ltd.

The impact of network characteristics on the diffusion of innovations

NASA Astrophysics Data System (ADS)

Peres, Renana

2014-05-01

This paper studies the influence of network topology on the speed and reach of new product diffusion. While previous research has focused on comparing network types, this paper explores explicitly the relationship between topology and measurements of diffusion effectiveness. We study simultaneously the effect of three network metrics: the average degree, the relative degree of social hubs (i.e., the ratio of the average degree of highly-connected individuals to the average degree of the entire population), and the clustering coefficient. A novel network-generation procedure based on random graphs with a planted partition is used to generate 160 networks with a wide range of values for these topological metrics. Using an agent-based model, we simulate diffusion on these networks and check the dependence of the net present value (NPV) of the number of adopters over time on the network metrics. We find that the average degree and the relative degree of social hubs have a positive influence on diffusion. This result emphasizes the importance of high network connectivity and strong hubs. The clustering coefficient has a negative impact on diffusion, a finding that contributes to the ongoing controversy on the benefits and disadvantages of transitivity. These results hold for both monopolistic and duopolistic markets, and were also tested on a sample of 12 real networks.

Synchronization criteria for generalized reaction-diffusion neural networks via periodically intermittent control.

PubMed

Gan, Qintao; Lv, Tianshi; Fu, Zhenhua

2016-04-01

In this paper, the synchronization problem for a class of generalized neural networks with time-varying delays and reaction-diffusion terms is investigated concerning Neumann boundary conditions in terms of p-norm. The proposed generalized neural networks model includes reaction-diffusion local field neural networks and reaction-diffusion static neural networks as its special cases. By establishing a new inequality, some simple and useful conditions are obtained analytically to guarantee the global exponential synchronization of the addressed neural networks under the periodically intermittent control. According to the theoretical results, the influences of diffusion coefficients, diffusion space, and control rate on synchronization are analyzed. Finally, the feasibility and effectiveness of the proposed methods are shown by simulation examples, and by choosing different diffusion coefficients, diffusion spaces, and control rates, different controlled synchronization states can be obtained.

Restoration of rhythmicity in diffusively coupled dynamical networks.

PubMed

Zou, Wei; Senthilkumar, D V; Nagao, Raphael; Kiss, István Z; Tang, Yang; Koseska, Aneta; Duan, Jinqiao; Kurths, Jürgen

2015-07-15

Oscillatory behaviour is essential for proper functioning of various physical and biological processes. However, diffusive coupling is capable of suppressing intrinsic oscillations due to the manifestation of the phenomena of amplitude and oscillation deaths. Here we present a scheme to revoke these quenching states in diffusively coupled dynamical networks, and demonstrate the approach in experiments with an oscillatory chemical reaction. By introducing a simple feedback factor in the diffusive coupling, we show that the stable (in)homogeneous steady states can be effectively destabilized to restore dynamic behaviours of coupled systems. Even a feeble deviation from the normal diffusive coupling drastically shrinks the death regions in the parameter space. The generality of our method is corroborated in diverse non-linear systems of diffusively coupled paradigmatic models with various death scenarios. Our study provides a general framework to strengthen the robustness of dynamic activity in diffusively coupled dynamical networks.

Diffusion processes of fragmentary information on scale-free networks

NASA Astrophysics Data System (ADS)

Li, Xun; Cao, Lang

2016-05-01

Compartmental models of diffusion over contact networks have proven representative of real-life propagation phenomena among interacting individuals. However, there is a broad class of collective spreading mechanisms departing from compartmental representations, including those for diffusive objects capable of fragmentation and transmission unnecessarily as a whole. Here, we consider a continuous-state susceptible-infected-susceptible (SIS) model as an ideal limit-case of diffusion processes of fragmentary information on networks, where individuals possess fractions of the information content and update them by selectively exchanging messages with partners in the vicinity. Specifically, we incorporate local information, such as neighbors' node degrees and carried contents, into the individual partner choice, and examine the roles of a variety of such strategies in the information diffusion process, both qualitatively and quantitatively. Our method provides an effective and flexible route of modulating continuous-state diffusion dynamics on networks and has potential in a wide array of practical applications.

A Diffusive Homeostatic Signal Maintains Neural Heterogeneity and Responsiveness in Cortical Networks

PubMed Central

Sweeney, Yann; Hellgren Kotaleski, Jeanette; Hennig, Matthias H.

2015-01-01

Gaseous neurotransmitters such as nitric oxide (NO) provide a unique and often overlooked mechanism for neurons to communicate through diffusion within a network, independent of synaptic connectivity. NO provides homeostatic control of intrinsic excitability. Here we conduct a theoretical investigation of the distinguishing roles of NO-mediated diffusive homeostasis in comparison with canonical non-diffusive homeostasis in cortical networks. We find that both forms of homeostasis provide a robust mechanism for maintaining stable activity following perturbations. However, the resulting networks differ, with diffusive homeostasis maintaining substantial heterogeneity in activity levels of individual neurons, a feature disrupted in networks with non-diffusive homeostasis. This results in networks capable of representing input heterogeneity, and linearly responding over a broader range of inputs than those undergoing non-diffusive homeostasis. We further show that these properties are preserved when homeostatic and Hebbian plasticity are combined. These results suggest a mechanism for dynamically maintaining neural heterogeneity, and expose computational advantages of non-local homeostatic processes. PMID:26158556

Turing instability in reaction-diffusion models on complex networks

NASA Astrophysics Data System (ADS)

Ide, Yusuke; Izuhara, Hirofumi; Machida, Takuya

2016-09-01

In this paper, the Turing instability in reaction-diffusion models defined on complex networks is studied. Here, we focus on three types of models which generate complex networks, i.e. the Erdős-Rényi, the Watts-Strogatz, and the threshold network models. From analysis of the Laplacian matrices of graphs generated by these models, we numerically reveal that stable and unstable regions of a homogeneous steady state on the parameter space of two diffusion coefficients completely differ, depending on the network architecture. In addition, we theoretically discuss the stable and unstable regions in the cases of regular enhanced ring lattices which include regular circles, and networks generated by the threshold network model when the number of vertices is large enough.

Prediction of competitive diffusion on complex networks

NASA Astrophysics Data System (ADS)

Zhao, Jiuhua; Liu, Qipeng; Wang, Lin; Wang, Xiaofan

2018-10-01

In this paper, we study the prediction problem of diffusion process on complex networks in competitive circumstances. With this problem solved, the competitors could timely intervene the diffusion process if needed such that an expected outcome might be obtained. We consider a model with two groups of competitors spreading opposite opinions on a network. A prediction method based on the mutual influences among the agents is proposed, called Influence Matrix (IM for short), and simulations on real-world networks show that the proposed IM method has quite high accuracy on predicting both the preference of any normal agent and the final competition result. For comparison purpose, classic centrality measures are also used to predict the competition result. It is shown that PageRank, Degree, Katz Centrality, and the IM method are suitable for predicting the competition result. More precisely, in undirected networks, the IM method performs better than these centrality measures when the competing group contains more than one agent; in directed networks, the IM method performs only second to PageRank.

Cross-national diffusion of mental health policy

PubMed Central

Shen, Gordon C

2014-01-01

Background: Following the tenets of world polity and innovation diffusion theories, I focus on the coercive and mimetic forces that influence the diffusion of mental health policy across nations. International organizations’ mandates influence government behavior. Dependency on external resources, namely foreign aid, also affects governments’ formulation of national policy. And finally, mounting adoption in a region alters the risk, benefits, and information associated with a given policy. Methods: I use post-war, discrete time data spanning 1950 to 2011 and describing 193 nations’ mental health systems to test these diffusion mechanisms. Results: I find that the adoption of mental health policy is highly clustered temporally and spatially. Results provide support that membership in the World Health Organization (WHO), interdependence with neighbors and peers in regional blocs, national income status, and migrant sub-population are responsible for isomorphism. Aid, however, is an insufficient determinant of mental health policy adoption. Conclusion: This study examines the extent to which mental, neurological, and substance use disorder are addressed in national and international contexts through the lens of policy diffusion theory. It also adds to policy dialogues about non-communicable diseases as nascent items on the global health agenda. PMID:25337601

Reaction-diffusion processes and metapopulation models on duplex networks

NASA Astrophysics Data System (ADS)

Xuan, Qi; Du, Fang; Yu, Li; Chen, Guanrong

2013-03-01

Reaction-diffusion processes, used to model various spatially distributed dynamics such as epidemics, have been studied mostly on regular lattices or complex networks with simplex links that are identical and invariant in transferring different kinds of particles. However, in many self-organized systems, different particles may have their own private channels to keep their purities. Such division of links often significantly influences the underlying reaction-diffusion dynamics and thus needs to be carefully investigated. This article studies a special reaction-diffusion process, named susceptible-infected-susceptible (SIS) dynamics, given by the reaction steps β→α and α+β→2β, on duplex networks where links are classified into two groups: α and β links used to transfer α and β particles, which, along with the corresponding nodes, consist of an α subnetwork and a β subnetwork, respectively. It is found that the critical point of particle density to sustain reaction activity is independent of the network topology if there is no correlation between the degree sequences of the two subnetworks, and this critical value is suppressed or extended if the two degree sequences are positively or negatively correlated, respectively. Based on the obtained results, it is predicted that epidemic spreading may be promoted on positive correlated traffic networks but may be suppressed on networks with modules composed of different types of diffusion links.

Knowledge Diffusion on Networks through the Game Strategy

NASA Astrophysics Data System (ADS)

Sun, Shu; Wu, Jiangning; Xuan, Zhaoguo

In this paper, we develop a knowledge diffusion model in which agents determine to give their knowledge to others according to some exchange strategies. The typical network namely small-world network is used for modeling, on which agents with knowledge are viewed as the nodes of the network and the edges are viewed as the social relationships for knowledge transmission. Such agents are permitted to interact with their neighbors repeatedly who have direct connections with them and accordingly change their strategies by choosing the most beneficial neighbors to diffuse knowledge. Two kinds of knowledge transmission strategies are proposed for the theoretical model based on the game theory and thereafter used in different simulations to examine the effect of the network structure on the knowledge diffusion effect. By analyses, two main observations can be found: One is that the simulation results are contrary to our intuition which agents would like to only accept but not share, thus they will maximize their benefit; another one is that the number of the agents acquired knowledge and the corresponding knowledge stock turn out to be independent of the percentage of those agents who choose to contribute their knowledge.

Information Diffusion in Facebook-Like Social Networks Under Information Overload

NASA Astrophysics Data System (ADS)

Li, Pei; Xing, Kai; Wang, Dapeng; Zhang, Xin; Wang, Hui

2013-07-01

Research on social networks has received remarkable attention, since many people use social networks to broadcast information and stay connected with their friends. However, due to the information overload in social networks, it becomes increasingly difficult for users to find useful information. This paper takes Facebook-like social networks into account, and models the process of information diffusion under information overload. The term view scope is introduced to model the user information-processing capability under information overload, and the average number of times a message appears in view scopes after it is generated is proposed to characterize the information diffusion efficiency. Through theoretical analysis, we find that factors such as network structure and view scope number have no impact on the information diffusion efficiency, which is a surprising result. To verify the results, we conduct simulations and provide the simulation results, which are consistent with the theoretical analysis results perfectly.

Phase Transition in Opinion Diffusion in Social Networks

DTIC Science & Technology

2012-05-01

the opinions of social agents diffuse in a network under a so-called hard-interaction model, in which the agents inter- act more strongly with...gent behavior. Index Terms— opinion diffusion , opinion dynamics, social net- works, phase transition, herding. 1. INTRODUCTION The study of the

Locating multiple diffusion sources in time varying networks from sparse observations.

PubMed

Hu, Zhao-Long; Shen, Zhesi; Cao, Shinan; Podobnik, Boris; Yang, Huijie; Wang, Wen-Xu; Lai, Ying-Cheng

2018-02-08

Data based source localization in complex networks has a broad range of applications. Despite recent progress, locating multiple diffusion sources in time varying networks remains to be an outstanding problem. Bridging structural observability and sparse signal reconstruction theories, we develop a general framework to locate diffusion sources in time varying networks based solely on sparse data from a small set of messenger nodes. A general finding is that large degree nodes produce more valuable information than small degree nodes, a result that contrasts that for static networks. Choosing large degree nodes as the messengers, we find that sparse observations from a few such nodes are often sufficient for any number of diffusion sources to be located for a variety of model and empirical networks. Counterintuitively, sources in more rapidly varying networks can be identified more readily with fewer required messenger nodes.

Competitive diffusion in online social networks with heterogeneous users

NASA Astrophysics Data System (ADS)

Li, Pei; He, Su; Wang, Hui; Zhang, Xin

2014-06-01

Online social networks have attracted increasing attention since they provide various approaches for hundreds of millions of people to stay connected with their friends. However, most research on diffusion dynamics in epidemiology cannot be applied directly to characterize online social networks, where users are heterogeneous and may act differently according to their standpoints. In this paper, we propose models to characterize the competitive diffusion in online social networks with heterogeneous users. We classify messages into two types (i.e., positive and negative) and users into three types (i.e., positive, negative and neutral). We estimate the positive (negative) influence for a user generating a given type message, which is the number of times that positive (negative) messages are processed (i.e., read) incurred by this action. We then consider the diffusion threshold, above which the corresponding influence will approach infinity, and the effect threshold, above which the unexpected influence of generating a message will exceed the expected one. We verify all these results by simulations, which show the analysis results are perfectly consistent with the simulation results. These results are of importance in understanding the diffusion dynamics in online social networks, and also critical for advertisers in viral marketing where there are fans, haters and neutrals.

Knowledge diffusion in complex networks by considering time-varying information channels

NASA Astrophysics Data System (ADS)

Zhu, He; Ma, Jing

2018-03-01

In this article, based on a model of epidemic spreading, we explore the knowledge diffusion process with an innovative mechanism for complex networks by considering time-varying information channels. To cover the knowledge diffusion process in homogeneous and heterogeneous networks, two types of networks (the BA network and the ER network) are investigated. The mean-field theory is used to theoretically draw the knowledge diffusion threshold. Numerical simulation demonstrates that the knowledge diffusion threshold is almost linearly correlated with the mean of the activity rate. In addition, under the influence of the activity rate and distinct from the classic Susceptible-Infected-Susceptible (SIS) model, the density of knowers almost linearly grows with the spreading rate. Finally, in consideration of the ubiquitous mechanism of innovation, we further study the evolution of knowledge in our proposed model. The results suggest that compared with the effect of the spreading rate, the average knowledge version of the population is affected more by the innovation parameter and the mean of the activity rate. Furthermore, in the BA network, the average knowledge version of individuals with higher degree is always newer than those with lower degree.

A network model of knowledge accumulation through diffusion and upgrade

NASA Astrophysics Data System (ADS)

Zhuang, Enyu; Chen, Guanrong; Feng, Gang

2011-07-01

In this paper, we introduce a model to describe knowledge accumulation through knowledge diffusion and knowledge upgrade in a multi-agent network. Here, knowledge diffusion refers to the distribution of existing knowledge in the network, while knowledge upgrade means the discovery of new knowledge. It is found that the population of the network and the number of each agent’s neighbors affect the speed of knowledge accumulation. Four different policies for updating the neighboring agents are thus proposed, and their influence on the speed of knowledge accumulation and the topology evolution of the network are also studied.

Reconstruction of stochastic temporal networks through diffusive arrival times

NASA Astrophysics Data System (ADS)

Li, Xun; Li, Xiang

2017-06-01

Temporal networks have opened a new dimension in defining and quantification of complex interacting systems. Our ability to identify and reproduce time-resolved interaction patterns is, however, limited by the restricted access to empirical individual-level data. Here we propose an inverse modelling method based on first-arrival observations of the diffusion process taking place on temporal networks. We describe an efficient coordinate-ascent implementation for inferring stochastic temporal networks that builds in particular but not exclusively on the null model assumption of mutually independent interaction sequences at the dyadic level. The results of benchmark tests applied on both synthesized and empirical network data sets confirm the validity of our algorithm, showing the feasibility of statistically accurate inference of temporal networks only from moderate-sized samples of diffusion cascades. Our approach provides an effective and flexible scheme for the temporally augmented inverse problems of network reconstruction and has potential in a broad variety of applications.

Reconstruction of stochastic temporal networks through diffusive arrival times

PubMed Central

Li, Xun; Li, Xiang

2017-01-01

Temporal networks have opened a new dimension in defining and quantification of complex interacting systems. Our ability to identify and reproduce time-resolved interaction patterns is, however, limited by the restricted access to empirical individual-level data. Here we propose an inverse modelling method based on first-arrival observations of the diffusion process taking place on temporal networks. We describe an efficient coordinate-ascent implementation for inferring stochastic temporal networks that builds in particular but not exclusively on the null model assumption of mutually independent interaction sequences at the dyadic level. The results of benchmark tests applied on both synthesized and empirical network data sets confirm the validity of our algorithm, showing the feasibility of statistically accurate inference of temporal networks only from moderate-sized samples of diffusion cascades. Our approach provides an effective and flexible scheme for the temporally augmented inverse problems of network reconstruction and has potential in a broad variety of applications. PMID:28604687

Network diffusion accurately models the relationship between structural and functional brain connectivity networks

PubMed Central

Abdelnour, Farras; Voss, Henning U.; Raj, Ashish

2014-01-01

The relationship between anatomic connectivity of large-scale brain networks and their functional connectivity is of immense importance and an area of active research. Previous attempts have required complex simulations which model the dynamics of each cortical region, and explore the coupling between regions as derived by anatomic connections. While much insight is gained from these non-linear simulations, they can be computationally taxing tools for predicting functional from anatomic connectivities. Little attention has been paid to linear models. Here we show that a properly designed linear model appears to be superior to previous non-linear approaches in capturing the brain’s long-range second order correlation structure that governs the relationship between anatomic and functional connectivities. We derive a linear network of brain dynamics based on graph diffusion, whereby the diffusing quantity undergoes a random walk on a graph. We test our model using subjects who underwent diffusion MRI and resting state fMRI. The network diffusion model applied to the structural networks largely predicts the correlation structures derived from their fMRI data, to a greater extent than other approaches. The utility of the proposed approach is that it can routinely be used to infer functional correlation from anatomic connectivity. And since it is linear, anatomic connectivity can also be inferred from functional data. The success of our model confirms the linearity of ensemble average signals in the brain, and implies that their long-range correlation structure may percolate within the brain via purely mechanistic processes enacted on its structural connectivity pathways. PMID:24384152

Innovation diffusion on time-varying activity driven networks

NASA Astrophysics Data System (ADS)

Rizzo, Alessandro; Porfiri, Maurizio

2016-01-01

Since its introduction in the 1960s, the theory of innovation diffusion has contributed to the advancement of several research fields, such as marketing management and consumer behavior. The 1969 seminal paper by Bass [F.M. Bass, Manag. Sci. 15, 215 (1969)] introduced a model of product growth for consumer durables, which has been extensively used to predict innovation diffusion across a range of applications. Here, we propose a novel approach to study innovation diffusion, where interactions among individuals are mediated by the dynamics of a time-varying network. Our approach is based on the Bass' model, and overcomes key limitations of previous studies, which assumed timescale separation between the individual dynamics and the evolution of the connectivity patterns. Thus, we do not hypothesize homogeneous mixing among individuals or the existence of a fixed interaction network. We formulate our approach in the framework of activity driven networks to enable the analysis of the concurrent evolution of the interaction and individual dynamics. Numerical simulations offer a systematic analysis of the model behavior and highlight the role of individual activity on market penetration when targeted advertisement campaigns are designed, or a competition between two different products takes place.

Diffusion in random networks: Asymptotic properties, and numerical and engineering approximations

NASA Astrophysics Data System (ADS)

Padrino, Juan C.; Zhang, Duan Z.

2016-11-01

The ensemble phase averaging technique is applied to model mass transport by diffusion in random networks. The system consists of an ensemble of random networks, where each network is made of a set of pockets connected by tortuous channels. Inside a channel, we assume that fluid transport is governed by the one-dimensional diffusion equation. Mass balance leads to an integro-differential equation for the pores mass density. The so-called dual porosity model is found to be equivalent to the leading order approximation of the integration kernel when the diffusion time scale inside the channels is small compared to the macroscopic time scale. As a test problem, we consider the one-dimensional mass diffusion in a semi-infinite domain, whose solution is sought numerically. Because of the required time to establish the linear concentration profile inside a channel, for early times the similarity variable is xt- 1 / 4 rather than xt- 1 / 2 as in the traditional theory. This early time sub-diffusive similarity can be explained by random walk theory through the network. In addition, by applying concepts of fractional calculus, we show that, for small time, the governing equation reduces to a fractional diffusion equation with known solution. We recast this solution in terms of special functions easier to compute. Comparison of the numerical and exact solutions shows excellent agreement.

Diffusion models for innovation: s-curves, networks, power laws, catastrophes, and entropy.

PubMed

Jacobsen, Joseph J; Guastello, Stephen J

2011-04-01

This article considers models for the diffusion of innovation would be most relevant to the dynamics of early 21st century technologies. The article presents an overview of diffusion models and examines the adoption S-curve, network theories, difference models, influence models, geographical models, a cusp catastrophe model, and self-organizing dynamics that emanate from principles of network configuration and principles of heat diffusion. The diffusion dynamics that are relevant to information technologies and energy-efficient technologies are compared. Finally, principles of nonlinear dynamics for innovation diffusion that could be used to rehabilitate the global economic situation are discussed.

Effect of rich-club on diffusion in complex networks

NASA Astrophysics Data System (ADS)

Berahmand, Kamal; Samadi, Negin; Sheikholeslami, Seyed Mahmood

2018-05-01

One of the main issues in complex networks is the phenomenon of diffusion in which the goal is to find the nodes with the highest diffusing power. In diffusion, there is always a conflict between accuracy and efficiency time complexity; therefore, most of the recent studies have focused on finding new centralities to solve this problem and have offered new ones, but our approach is different. Using one of the complex networks’ features, namely the “rich-club”, its effect on diffusion in complex networks has been analyzed and it is demonstrated that in datasets which have a high rich-club, it is better to use the degree centrality for finding influential nodes because it has a linear time complexity and uses the local information; however, this rule does not apply to datasets which have a low rich-club. Next, real and artificial datasets with the high rich-club have been used in which degree centrality has been compared to famous centrality using the SIR standard.

Curation-Based Network Marketing: Strategies for Network Growth and Electronic Word-of-Mouth Diffusion

ERIC Educational Resources Information Center

Church, Earnie Mitchell, Jr.

2013-01-01

In the last couple of years, a new aspect of online social networking has emerged, in which the strength of social network connections is based not on social ties but mutually shared interests. This dissertation studies these "curation-based" online social networks (CBN) and their suitability for the diffusion of electronic word-of-mouth…

Influence Function Learning in Information Diffusion Networks.

PubMed

Du, Nan; Liang, Yingyu; Balcan, Maria-Florina; Song, Le

2014-06-01

Can we learn the influence of a set of people in a social network from cascades of information diffusion? This question is often addressed by a two-stage approach: first learn a diffusion model, and then calculate the influence based on the learned model. Thus, the success of this approach relies heavily on the correctness of the diffusion model which is hard to verify for real world data. In this paper, we exploit the insight that the influence functions in many diffusion models are coverage functions, and propose a novel parameterization of such functions using a convex combination of random basis functions. Moreover, we propose an efficient maximum likelihood based algorithm to learn such functions directly from cascade data, and hence bypass the need to specify a particular diffusion model in advance. We provide both theoretical and empirical analysis for our approach, showing that the proposed approach can provably learn the influence function with low sample complexity, be robust to the unknown diffusion models, and significantly outperform existing approaches in both synthetic and real world data.

Influence Function Learning in Information Diffusion Networks

PubMed Central

Du, Nan; Liang, Yingyu; Balcan, Maria-Florina; Song, Le

2015-01-01

Can we learn the influence of a set of people in a social network from cascades of information diffusion? This question is often addressed by a two-stage approach: first learn a diffusion model, and then calculate the influence based on the learned model. Thus, the success of this approach relies heavily on the correctness of the diffusion model which is hard to verify for real world data. In this paper, we exploit the insight that the influence functions in many diffusion models are coverage functions, and propose a novel parameterization of such functions using a convex combination of random basis functions. Moreover, we propose an efficient maximum likelihood based algorithm to learn such functions directly from cascade data, and hence bypass the need to specify a particular diffusion model in advance. We provide both theoretical and empirical analysis for our approach, showing that the proposed approach can provably learn the influence function with low sample complexity, be robust to the unknown diffusion models, and significantly outperform existing approaches in both synthetic and real world data. PMID:25973445

Modeling information diffusion in time-varying community networks

NASA Astrophysics Data System (ADS)

Cui, Xuelian; Zhao, Narisa

2017-12-01

Social networks are rarely static, and they typically have time-varying network topologies. A great number of studies have modeled temporal networks and explored social contagion processes within these models; however, few of these studies have considered community structure variations. In this paper, we present a study of how the time-varying property of a modular structure influences the information dissemination. First, we propose a continuous-time Markov model of information diffusion where two parameters, mobility rate and community attractiveness, are introduced to address the time-varying nature of the community structure. The basic reproduction number is derived, and the accuracy of this model is evaluated by comparing the simulation and theoretical results. Furthermore, numerical results illustrate that generally both the mobility rate and community attractiveness significantly promote the information diffusion process, especially in the initial outbreak stage. Moreover, the strength of this promotion effect is much stronger when the modularity is higher. Counterintuitively, it is found that when all communities have the same attractiveness, social mobility no longer accelerates the diffusion process. In addition, we show that the local spreading in the advantage group has been greatly enhanced due to the agglomeration effect caused by the social mobility and community attractiveness difference, which thus increases the global spreading.

On common noise-induced synchronization in complex networks with state-dependent noise diffusion processes

NASA Astrophysics Data System (ADS)

Russo, Giovanni; Shorten, Robert

2018-04-01

This paper is concerned with the study of common noise-induced synchronization phenomena in complex networks of diffusively coupled nonlinear systems. We consider the case where common noise propagation depends on the network state and, as a result, the noise diffusion process at the nodes depends on the state of the network. For such networks, we present an algebraic sufficient condition for the onset of synchronization, which depends on the network topology, the dynamics at the nodes, the coupling strength and the noise diffusion. Our result explicitly shows that certain noise diffusion processes can drive an unsynchronized network towards synchronization. In order to illustrate the effectiveness of our result, we consider two applications: collective decision processes and synchronization of chaotic systems. We explicitly show that, in the former application, a sufficiently large noise can drive a population towards a common decision, while, in the latter, we show how common noise can synchronize a network of Lorentz chaotic systems.

Anomalous diffusion on the Hanoi networks

NASA Astrophysics Data System (ADS)

Boettcher, S.; Gonçalves, B.

2008-11-01

Diffusion is modeled on the recently proposed Hanoi networks by studying the mean-square displacement of random walks with time, langr2rang~t2/dw. It is found that diffusion —the quintessential mode of transport throughout Nature— proceeds faster than ordinary, in one case with an exact, anomalous exponent dw=2- log2(phi)=1.30576... . It is an instance of a physical exponent containing the "golden ratio"\\phi=(1+\\sqrt{5})/2 that is intimately related to Fibonacci sequences and since Euclid's time has been found to be fundamental throughout geometry, architecture, art, and Nature itself. It originates from a singular renormalization group fixed point with a subtle boundary layer, for whose resolution phi is the main protagonist. The origin of this rare singularity is easily understood in terms of the physics of the process. Yet, the connection between network geometry and the emergence of phi in this context remains elusive. These results provide an accurate test of recently proposed universal scaling forms for first passage times.

Knowledge diffusion of dynamical network in terms of interaction frequency.

PubMed

Liu, Jian-Guo; Zhou, Qing; Guo, Qiang; Yang, Zhen-Hua; Xie, Fei; Han, Jing-Ti

2017-09-07

In this paper, we present a knowledge diffusion (SKD) model for dynamic networks by taking into account the interaction frequency which always used to measure the social closeness. A set of agents, which are initially interconnected to form a random network, either exchange knowledge with their neighbors or move toward a new location through an edge-rewiring procedure. The activity of knowledge exchange between agents is determined by a knowledge transfer rule that the target node would preferentially select one neighbor node to transfer knowledge with probability p according to their interaction frequency instead of the knowledge distance, otherwise, the target node would build a new link with its second-order neighbor preferentially or select one node in the system randomly with probability 1 - p. The simulation results show that, comparing with the Null model defined by the random selection mechanism and the traditional knowledge diffusion (TKD) model driven by knowledge distance, the knowledge would spread more fast based on SKD driven by interaction frequency. In particular, the network structure of SKD would evolve as an assortative one, which is a fundamental feature of social networks. This work would be helpful for deeply understanding the coevolution of the knowledge diffusion and network structure.

Network analysis of surgical innovation: Measuring value and the virality of diffusion in robotic surgery.

PubMed

Garas, George; Cingolani, Isabella; Panzarasa, Pietro; Darzi, Ara; Athanasiou, Thanos

2017-01-01

Existing surgical innovation frameworks suffer from a unifying limitation, their qualitative nature. A rigorous approach to measuring surgical innovation is needed that extends beyond detecting simply publication, citation, and patent counts and instead uncovers an implementation-based value from the structure of the entire adoption cascades produced over time by diffusion processes. Based on the principles of evidence-based medicine and existing surgical regulatory frameworks, the surgical innovation funnel is described. This illustrates the different stages through which innovation in surgery typically progresses. The aim is to propose a novel and quantitative network-based framework that will permit modeling and visualizing innovation diffusion cascades in surgery and measuring virality and value of innovations. Network analysis of constructed citation networks of all articles concerned with robotic surgery (n = 13,240, Scopus®) was performed (1974-2014). The virality of each cascade was measured as was innovation value (measured by the innovation index) derived from the evidence-based stage occupied by the corresponding seed article in the surgical innovation funnel. The network-based surgical innovation metrics were also validated against real world big data (National Inpatient Sample-NIS®). Rankings of surgical innovation across specialties by cascade size and structural virality (structural depth and width) were found to correlate closely with the ranking by innovation value (Spearman's rank correlation coefficient = 0.758 (p = 0.01), 0.782 (p = 0.008), 0.624 (p = 0.05), respectively) which in turn matches the ranking based on real world big data from the NIS® (Spearman's coefficient = 0.673;p = 0.033). Network analysis offers unique new opportunities for understanding, modeling and measuring surgical innovation, and ultimately for assessing and comparing generative value between different specialties. The novel surgical innovation metrics developed may

Event-triggered synchronization for reaction-diffusion complex networks via random sampling

NASA Astrophysics Data System (ADS)

Dong, Tao; Wang, Aijuan; Zhu, Huiyun; Liao, Xiaofeng

2018-04-01

In this paper, the synchronization problem of the reaction-diffusion complex networks (RDCNs) with Dirichlet boundary conditions is considered, where the data is sampled randomly. An event-triggered controller based on the sampled data is proposed, which can reduce the number of controller and the communication load. Under this strategy, the synchronization problem of the diffusion complex network is equivalently converted to the stability of a of reaction-diffusion complex dynamical systems with time delay. By using the matrix inequality technique and Lyapunov method, the synchronization conditions of the RDCNs are derived, which are dependent on the diffusion term. Moreover, it is found the proposed control strategy can get rid of the Zeno behavior naturally. Finally, a numerical example is given to verify the obtained results.

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

Detecting recurrent gene mutation in interaction network context using multi-scale graph diffusion.

PubMed

Babaei, Sepideh; Hulsman, Marc; Reinders, Marcel; de Ridder, Jeroen

2013-01-23

Delineating the molecular drivers of cancer, i.e. determining cancer genes and the pathways which they deregulate, is an important challenge in cancer research. In this study, we aim to identify pathways of frequently mutated genes by exploiting their network neighborhood encoded in the protein-protein interaction network. To this end, we introduce a multi-scale diffusion kernel and apply it to a large collection of murine retroviral insertional mutagenesis data. The diffusion strength plays the role of scale parameter, determining the size of the network neighborhood that is taken into account. As a result, in addition to detecting genes with frequent mutations in their genomic vicinity, we find genes that harbor frequent mutations in their interaction network context. We identify densely connected components of known and putatively novel cancer genes and demonstrate that they are strongly enriched for cancer related pathways across the diffusion scales. Moreover, the mutations in the clusters exhibit a significant pattern of mutual exclusion, supporting the conjecture that such genes are functionally linked. Using multi-scale diffusion kernel, various infrequently mutated genes are found to harbor significant numbers of mutations in their interaction network neighborhood. Many of them are well-known cancer genes. The results demonstrate the importance of defining recurrent mutations while taking into account the interaction network context. Importantly, the putative cancer genes and networks detected in this study are found to be significant at different diffusion scales, confirming the necessity of a multi-scale analysis.

High-throughput mathematical analysis identifies Turing networks for patterning with equally diffusing signals.

PubMed

Marcon, Luciano; Diego, Xavier; Sharpe, James; Müller, Patrick

2016-04-08

The Turing reaction-diffusion model explains how identical cells can self-organize to form spatial patterns. It has been suggested that extracellular signaling molecules with different diffusion coefficients underlie this model, but the contribution of cell-autonomous signaling components is largely unknown. We developed an automated mathematical analysis to derive a catalog of realistic Turing networks. This analysis reveals that in the presence of cell-autonomous factors, networks can form a pattern with equally diffusing signals and even for any combination of diffusion coefficients. We provide a software (available at http://www.RDNets.com) to explore these networks and to constrain topologies with qualitative and quantitative experimental data. We use the software to examine the self-organizing networks that control embryonic axis specification and digit patterning. Finally, we demonstrate how existing synthetic circuits can be extended with additional feedbacks to form Turing reaction-diffusion systems. Our study offers a new theoretical framework to understand multicellular pattern formation and enables the wide-spread use of mathematical biology to engineer synthetic patterning systems.

Emotion shapes the diffusion of moralized content in social networks.

PubMed

Brady, William J; Wills, Julian A; Jost, John T; Tucker, Joshua A; Van Bavel, Jay J

2017-07-11

Political debate concerning moralized issues is increasingly common in online social networks. However, moral psychology has yet to incorporate the study of social networks to investigate processes by which some moral ideas spread more rapidly or broadly than others. Here, we show that the expression of moral emotion is key for the spread of moral and political ideas in online social networks, a process we call "moral contagion." Using a large sample of social media communications about three polarizing moral/political issues ( n = 563,312), we observed that the presence of moral-emotional words in messages increased their diffusion by a factor of 20% for each additional word. Furthermore, we found that moral contagion was bounded by group membership; moral-emotional language increased diffusion more strongly within liberal and conservative networks, and less between them. Our results highlight the importance of emotion in the social transmission of moral ideas and also demonstrate the utility of social network methods for studying morality. These findings offer insights into how people are exposed to moral and political ideas through social networks, thus expanding models of social influence and group polarization as people become increasingly immersed in social media networks.

High-throughput mathematical analysis identifies Turing networks for patterning with equally diffusing signals

PubMed Central

Marcon, Luciano; Diego, Xavier; Sharpe, James; Müller, Patrick

2016-01-01

The Turing reaction-diffusion model explains how identical cells can self-organize to form spatial patterns. It has been suggested that extracellular signaling molecules with different diffusion coefficients underlie this model, but the contribution of cell-autonomous signaling components is largely unknown. We developed an automated mathematical analysis to derive a catalog of realistic Turing networks. This analysis reveals that in the presence of cell-autonomous factors, networks can form a pattern with equally diffusing signals and even for any combination of diffusion coefficients. We provide a software (available at http://www.RDNets.com) to explore these networks and to constrain topologies with qualitative and quantitative experimental data. We use the software to examine the self-organizing networks that control embryonic axis specification and digit patterning. Finally, we demonstrate how existing synthetic circuits can be extended with additional feedbacks to form Turing reaction-diffusion systems. Our study offers a new theoretical framework to understand multicellular pattern formation and enables the wide-spread use of mathematical biology to engineer synthetic patterning systems. DOI: http://dx.doi.org/10.7554/eLife.14022.001 PMID:27058171

Synchronization of Reaction-Diffusion Neural Networks With Dirichlet Boundary Conditions and Infinite Delays.

PubMed

Sheng, Yin; Zhang, Hao; Zeng, Zhigang

2017-10-01

This paper is concerned with synchronization for a class of reaction-diffusion neural networks with Dirichlet boundary conditions and infinite discrete time-varying delays. By utilizing theories of partial differential equations, Green's formula, inequality techniques, and the concept of comparison, algebraic criteria are presented to guarantee master-slave synchronization of the underlying reaction-diffusion neural networks via a designed controller. Additionally, sufficient conditions on exponential synchronization of reaction-diffusion neural networks with finite time-varying delays are established. The proposed criteria herein enhance and generalize some published ones. Three numerical examples are presented to substantiate the validity and merits of the obtained theoretical results.

Diffusion Dynamics of Energy Saving Practices in Large Heterogeneous Online Networks

PubMed Central

Mohammadi, Neda; Wang, Qi; Taylor, John E.

2016-01-01

Online social networks are today’s fastest growing communications channel and a popular source of information for many, so understanding their contribution to building awareness and shaping public perceptions of climate change is of utmost importance. Today’s online social networks are composed of complex combinations of entities and communication channels and it is not clear which communicators are the most influential, what the patterns of communication flow are, or even whether the widely accepted two-step flow of communication model applies in this new arena. This study examines the diffusion of energy saving practices in a large online social network across organizations, opinion leaders, and the public by tracking 108,771 communications on energy saving practices among 1,084 communicators, then analyzing the flow of information and influence over a 28 day period. Our findings suggest that diffusion networks of messages advocating energy saving practices are predominantly led by the activities of dedicated organizations but their attempts do not result in substantial public awareness, as most of these communications are effectively trapped in organizational loops in which messages are simply shared between organizations. Despite their comparably significant influential values, opinion leaders played a weak role in diffusing energy saving practices to a wider audience. Thus, the two-step flow of communication model does not appear to describe the sharing of energy conservation practices in large online heterogeneous networks. These results shed new light on the underlying mechanisms driving the diffusion of important societal issues such as energy efficiency, particularly in the context of large online social media outlets. PMID:27736912

Diffusion Dynamics of Energy Saving Practices in Large Heterogeneous Online Networks.

PubMed

Mohammadi, Neda; Wang, Qi; Taylor, John E

2016-01-01

Online social networks are today's fastest growing communications channel and a popular source of information for many, so understanding their contribution to building awareness and shaping public perceptions of climate change is of utmost importance. Today's online social networks are composed of complex combinations of entities and communication channels and it is not clear which communicators are the most influential, what the patterns of communication flow are, or even whether the widely accepted two-step flow of communication model applies in this new arena. This study examines the diffusion of energy saving practices in a large online social network across organizations, opinion leaders, and the public by tracking 108,771 communications on energy saving practices among 1,084 communicators, then analyzing the flow of information and influence over a 28 day period. Our findings suggest that diffusion networks of messages advocating energy saving practices are predominantly led by the activities of dedicated organizations but their attempts do not result in substantial public awareness, as most of these communications are effectively trapped in organizational loops in which messages are simply shared between organizations. Despite their comparably significant influential values, opinion leaders played a weak role in diffusing energy saving practices to a wider audience. Thus, the two-step flow of communication model does not appear to describe the sharing of energy conservation practices in large online heterogeneous networks. These results shed new light on the underlying mechanisms driving the diffusion of important societal issues such as energy efficiency, particularly in the context of large online social media outlets.

A study on ?-dissipative synchronisation of coupled reaction-diffusion neural networks with time-varying delays

NASA Astrophysics Data System (ADS)

Ali, M. Syed; Zhu, Quanxin; Pavithra, S.; Gunasekaran, N.

2018-03-01

This study examines the problem of dissipative synchronisation of coupled reaction-diffusion neural networks with time-varying delays. This paper proposes a complex dynamical network consisting of N linearly and diffusively coupled identical reaction-diffusion neural networks. By constructing a suitable Lyapunov-Krasovskii functional (LKF), utilisation of Jensen's inequality and reciprocally convex combination (RCC) approach, strictly ?-dissipative conditions of the addressed systems are derived. Finally, a numerical example is given to show the effectiveness of the theoretical results.

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.

Emotion shapes the diffusion of moralized content in social networks

PubMed Central

Wills, Julian A.; Jost, John T.; Tucker, Joshua A.; Van Bavel, Jay J.

2017-01-01

Political debate concerning moralized issues is increasingly common in online social networks. However, moral psychology has yet to incorporate the study of social networks to investigate processes by which some moral ideas spread more rapidly or broadly than others. Here, we show that the expression of moral emotion is key for the spread of moral and political ideas in online social networks, a process we call “moral contagion.” Using a large sample of social media communications about three polarizing moral/political issues (n = 563,312), we observed that the presence of moral-emotional words in messages increased their diffusion by a factor of 20% for each additional word. Furthermore, we found that moral contagion was bounded by group membership; moral-emotional language increased diffusion more strongly within liberal and conservative networks, and less between them. Our results highlight the importance of emotion in the social transmission of moral ideas and also demonstrate the utility of social network methods for studying morality. These findings offer insights into how people are exposed to moral and political ideas through social networks, thus expanding models of social influence and group polarization as people become increasingly immersed in social media networks. PMID:28652356

Network analysis of surgical innovation: Measuring value and the virality of diffusion in robotic surgery

PubMed Central

Cingolani, Isabella; Panzarasa, Pietro; Darzi, Ara; Athanasiou, Thanos

2017-01-01

Background Existing surgical innovation frameworks suffer from a unifying limitation, their qualitative nature. A rigorous approach to measuring surgical innovation is needed that extends beyond detecting simply publication, citation, and patent counts and instead uncovers an implementation-based value from the structure of the entire adoption cascades produced over time by diffusion processes. Based on the principles of evidence-based medicine and existing surgical regulatory frameworks, the surgical innovation funnel is described. This illustrates the different stages through which innovation in surgery typically progresses. The aim is to propose a novel and quantitative network-based framework that will permit modeling and visualizing innovation diffusion cascades in surgery and measuring virality and value of innovations. Materials and methods Network analysis of constructed citation networks of all articles concerned with robotic surgery (n = 13,240, Scopus®) was performed (1974–2014). The virality of each cascade was measured as was innovation value (measured by the innovation index) derived from the evidence-based stage occupied by the corresponding seed article in the surgical innovation funnel. The network-based surgical innovation metrics were also validated against real world big data (National Inpatient Sample–NIS®). Results Rankings of surgical innovation across specialties by cascade size and structural virality (structural depth and width) were found to correlate closely with the ranking by innovation value (Spearman’s rank correlation coefficient = 0.758 (p = 0.01), 0.782 (p = 0.008), 0.624 (p = 0.05), respectively) which in turn matches the ranking based on real world big data from the NIS® (Spearman’s coefficient = 0.673;p = 0.033). Conclusion Network analysis offers unique new opportunities for understanding, modeling and measuring surgical innovation, and ultimately for assessing and comparing generative value between different

National networks of Healthy Cities in Europe.

PubMed

Janss Lafond, Leah; Heritage, Zoë

2009-11-01

National networks of Healthy Cities emerged in the late 1980s as a spontaneous reaction to a great demand by cities to participate in the Healthy Cities movement. Today, they engage at least 1300 cities in the European region and form the backbone of the Healthy Cities movement. This article provides an analysis of the results of the regular surveys of national networks that have been carried out principally since 1997. The main functions and achievements of national networks are presented alongside some of their most pressing challenges. Although networks have differing priorities and organizational characteristics, they do share common goals and strategic directions based on the Healthy Cities model (see other articles in this special edition of HPI). Therefore, it has been possible to identify a set of organizational and strategic factors that contribute to the success of networks. These factors form the basis of a set of accreditation criteria for national networks and provide guidance for the establishment of new national networks. Although national networks have made substantial achievements, they continue to face a number of dilemmas that are discussed in the article. Problems a national network must deal with include how to obtain sustainable funding, how to raise the standard of work in cities without creating exclusive participation criteria and how to balance the need to provide direct support to cities with its role as a national player. These dilemmas are similar to other public sector networks. During the last 15 years, the pooling of practical expertise in urban health has made Healthy Cities networks an important resource for national as well as local governments. Not only do they provide valuable support to their members but they often advise ministries and other national institutions on effective models to promote sustainable urban health development.

Nanotechnology knowledge diffusion: measuring the impact of the research networking and a strategy for improvement

NASA Astrophysics Data System (ADS)

Liu, Xuan; Jiang, Shan; Chen, Hsinchun; Larson, Catherine A.; Roco, Mihail C.

2014-09-01

Given the global increase in public funding for nanotechnology research and development, it is even more important to support projects with promising return on investment. A main return is the benefit to other researchers and to the entire field through knowledge diffusion, invention, and innovation. The social network of researchers is one of the channels through which this happens. This study considers the scientific publication network in the field of nanotechnology, and evaluates how knowledge diffusion through coauthorship and citations is affected in large institutions by the location and connectivity of individual researchers in the network. The relative position and connectivity of a researcher is measured by various social network metrics, including degree centrality, Bonacich Power centrality, structural holes, and betweenness centrality. Leveraging the Cox regression model, we analyzed the temporal relationships between knowledge diffusion and social network measures of researchers in five leading universities in the United States using papers published from 2000 to 2010. The results showed that the most significant effects on knowledge diffusion in the field of nanotechnology were from the structural holes of the network and the degree centrality of individual researchers. The data suggest that a researcher has potential to perform better in knowledge creation and diffusion on boundary-spanning positions between different communities and when he or she has a high level of connectivity in the knowledge network. These observations may lead to improved strategies in planning, conducting, and evaluating multidisciplinary nanotechnology research. The paper also identifies the researchers who made most significant contributions to nanotechnology knowledge diffusion in the networks of five leading U.S. universities.

The role of organizational affiliations and research networks in the diffusion of breast cancer treatment innovation.

PubMed

Carpenter, William R; Reeder-Hayes, Katherine; Bainbridge, John; Meyer, Anne-Marie; Amos, Keith D; Weiner, Bryan J; Godley, Paul A

2011-02-01

The National Institutes of Health (NIH) sees provider-based research networks and other organizational linkages between academic researchers and community practitioners as promising vehicles for accelerating the translation of research into practice. This study examines whether organizational research affiliations and teaching affiliations are associated with accelerated diffusion of sentinel lymph node biopsy (SLNB), an innovation in the treatment of early-stage breast cancer. Surveillance Epidemiology and End Results-Medicare data were used to examine the diffusion of SLNB for treatment of early-stage breast cancer among women aged 65 years and older diagnosed between 2000 and 2002, shortly after Medicare approved and began reimbursing for the procedure. In this population, patients treated at an organization affiliated with a research network--the American College of Surgeons Oncology Group (ACOSOG) or other National Cancer Institute (NCI) cooperative groups--were more likely to receive the innovative treatment (SLNB) than patients treated at unaffiliated organizations (odds ratio: 2.70, 95% confidence interval: 1.77-4.12; odds ratio: 1.84, 95% confidence interval: 1.26-2.69, respectively). Neither hospital teaching status nor surgical volume was significantly associated with differences in SLNB use. Patients who receive cancer treatment at organizations affiliated with cancer research networks have an enhanced probability of receiving SLNB, an innovative procedure that offers the promise of improved patient outcomes. Study findings support the NIH Roadmap and programs such as the NCI's Community Clinical Oncology Program, as they seek to accelerate the translation of research into practice by simultaneously accelerating and broadening cancer research in the community.

Random walks and diffusion on networks

NASA Astrophysics Data System (ADS)

Masuda, Naoki; Porter, Mason A.; Lambiotte, Renaud

2017-11-01

Random walks are ubiquitous in the sciences, and they are interesting from both theoretical and practical perspectives. They are one of the most fundamental types of stochastic processes; can be used to model numerous phenomena, including diffusion, interactions, and opinions among humans and animals; and can be used to extract information about important entities or dense groups of entities in a network. Random walks have been studied for many decades on both regular lattices and (especially in the last couple of decades) on networks with a variety of structures. In the present article, we survey the theory and applications of random walks on networks, restricting ourselves to simple cases of single and non-adaptive random walkers. We distinguish three main types of random walks: discrete-time random walks, node-centric continuous-time random walks, and edge-centric continuous-time random walks. We first briefly survey random walks on a line, and then we consider random walks on various types of networks. We extensively discuss applications of random walks, including ranking of nodes (e.g., PageRank), community detection, respondent-driven sampling, and opinion models such as voter models.

23 CFR 658.21 - Identification of National Network.

Code of Federal Regulations, 2011 CFR

2011-04-01

... 23 Highways 1 2011-04-01 2011-04-01 false Identification of National Network. 658.21 Section 658... Identification of National Network. (a) To identify the National Network, a State may sign the routes or provide maps of lists of highways describing the National Network. (b) Exceptional local conditions on the...

23 CFR 658.21 - Identification of National Network.

Code of Federal Regulations, 2010 CFR

2010-04-01

... 23 Highways 1 2010-04-01 2010-04-01 false Identification of National Network. 658.21 Section 658... Identification of National Network. (a) To identify the National Network, a State may sign the routes or provide maps of lists of highways describing the National Network. (b) Exceptional local conditions on the...

Network confinement and heterogeneity slows nanoparticle diffusion in polymer gels

NASA Astrophysics Data System (ADS)

Parrish, Emmabeth; Caporizzo, Matthew A.; Composto, Russell J.

2017-05-01

Nanoparticle (NP) diffusion was measured in polyacrylamide gels (PAGs) with a mesh size comparable to the NP size, 21 nm. The confinement ratio (CR), NP diameter/mesh size, increased from 0.4 to 3.8 by increasing crosslinker density and from 0.4 to 2.1 by adding acetone, which collapsed the PAGs. In all gels, NPs either became localized, moving less than 200 nm, diffused microns, or exhibited a combination of these behaviors, as measured by single particle tracking. Mean squared displacements (MSDs) of mobile NPs decreased as CR increased. In collapsed gels, the localized NP population increased and MSD of mobile NPs decreased compared to crosslinked PAGs. For all CRs, van Hove distributions exhibited non-Gaussian displacements, consistent with intermittent localization of NPs. The non-Gaussian parameter increased from a maximum of 1.5 for crosslinked PAG to 5 for collapsed PAG, consistent with greater network heterogeneity in these gels. Diffusion coefficients decreased exponentially as CR increased for crosslinked gels; however, in collapsed gels, the diffusion coefficients decreased more strongly, which was attributed to network heterogeneity. Collapsing the gel resulted in an increasingly tortuous pathway for NPs, slowing diffusion at a given CR. Understanding how gel structure affects NP mobility will allow the design and enhanced performance of gels that separate and release molecules in membranes and drug delivery platforms.

Consume, Modify, Share (CMS): The Interplay between Individual Decisions and Structural Network Properties in the Diffusion of Information.

PubMed

Koren, Hila; Kaminer, Ido; Raban, Daphne Ruth

2016-01-01

Widely used information diffusion models such as Independent Cascade Model, Susceptible Infected Recovered (SIR) and others fail to acknowledge that information is constantly subject to modification. Some aspects of information diffusion are best explained by network structural characteristics while in some cases strong influence comes from individual decisions. We introduce reinvention, the ability to modify information, as an individual level decision that affects the diffusion process as a whole. Based on a combination of constructs from the Diffusion of Innovations and the Critical Mass Theories, the present study advances the CMS (consume, modify, share) model which accounts for the interplay between network structure and human behavior and interactions. The model's building blocks include processes leading up to and following the formation of a critical mass of information adopters and disseminators. We examine the formation of an inflection point, information reach, sustainability of the diffusion process and collective value creation. The CMS model is tested on two directed networks and one undirected network, assuming weak or strong ties and applying constant and relative modification schemes. While all three networks are designed for disseminating new knowledge they differ in structural properties. Our findings suggest that modification enhances the diffusion of information in networks that support undirected connections and carries the biggest effect when information is shared via weak ties. Rogers' diffusion model and traditional information contagion models are fine tuned. Our results show that modifications not only contribute to a sustainable diffusion process, but also aid information in reaching remote areas of the network. The results point to the importance of cultivating weak ties, allowing reciprocal interaction among nodes and supporting the modification of information in promoting diffusion processes. These results have theoretical and

Consume, Modify, Share (CMS): The Interplay between Individual Decisions and Structural Network Properties in the Diffusion of Information

PubMed Central

Koren, Hila; Kaminer, Ido

2016-01-01

Widely used information diffusion models such as Independent Cascade Model, Susceptible Infected Recovered (SIR) and others fail to acknowledge that information is constantly subject to modification. Some aspects of information diffusion are best explained by network structural characteristics while in some cases strong influence comes from individual decisions. We introduce reinvention, the ability to modify information, as an individual level decision that affects the diffusion process as a whole. Based on a combination of constructs from the Diffusion of Innovations and the Critical Mass Theories, the present study advances the CMS (consume, modify, share) model which accounts for the interplay between network structure and human behavior and interactions. The model's building blocks include processes leading up to and following the formation of a critical mass of information adopters and disseminators. We examine the formation of an inflection point, information reach, sustainability of the diffusion process and collective value creation. The CMS model is tested on two directed networks and one undirected network, assuming weak or strong ties and applying constant and relative modification schemes. While all three networks are designed for disseminating new knowledge they differ in structural properties. Our findings suggest that modification enhances the diffusion of information in networks that support undirected connections and carries the biggest effect when information is shared via weak ties. Rogers' diffusion model and traditional information contagion models are fine tuned. Our results show that modifications not only contribute to a sustainable diffusion process, but also aid information in reaching remote areas of the network. The results point to the importance of cultivating weak ties, allowing reciprocal interaction among nodes and supporting the modification of information in promoting diffusion processes. These results have theoretical and

Impulsive synchronization of stochastic reaction-diffusion neural networks with mixed time delays.

PubMed

Sheng, Yin; Zeng, Zhigang

2018-07-01

This paper discusses impulsive synchronization of stochastic reaction-diffusion neural networks with Dirichlet boundary conditions and hybrid time delays. By virtue of inequality techniques, theories of stochastic analysis, linear matrix inequalities, and the contradiction method, sufficient criteria are proposed to ensure exponential synchronization of the addressed stochastic reaction-diffusion neural networks with mixed time delays via a designed impulsive controller. Compared with some recent studies, the neural network models herein are more general, some restrictions are relaxed, and the obtained conditions enhance and generalize some published ones. Finally, two numerical simulations are performed to substantiate the validity and merits of the developed theoretical analysis. Copyright © 2018 Elsevier Ltd. All rights reserved.

Localization of diffusion sources in complex networks with sparse observations

NASA Astrophysics Data System (ADS)

Hu, Zhao-Long; Shen, Zhesi; Tang, Chang-Bing; Xie, Bin-Bin; Lu, Jian-Feng

2018-04-01

Locating sources in a large network is of paramount importance to reduce the spreading of disruptive behavior. Based on the backward diffusion-based method and integer programming, we propose an efficient approach to locate sources in complex networks with limited observers. The results on model networks and empirical networks demonstrate that, for a certain fraction of observers, the accuracy of our method for source localization will improve as the increase of network size. Besides, compared with the previous method (the maximum-minimum method), the performance of our method is much better with a small fraction of observers, especially in heterogeneous networks. Furthermore, our method is more robust against noise environments and strategies of choosing observers.

Interests diffusion in social networks

NASA Astrophysics Data System (ADS)

D'Agostino, Gregorio; D'Antonio, Fulvio; De Nicola, Antonio; Tucci, Salvatore

2015-10-01

We provide a model for diffusion of interests in Social Networks (SNs). We demonstrate that the topology of the SN plays a crucial role in the dynamics of the individual interests. Understanding cultural phenomena on SNs and exploiting the implicit knowledge about their members is attracting the interest of different research communities both from the academic and the business side. The community of complexity science is devoting significant efforts to define laws, models, and theories, which, based on acquired knowledge, are able to predict future observations (e.g. success of a product). In the mean time, the semantic web community aims at engineering a new generation of advanced services by defining constructs, models and methods, adding a semantic layer to SNs. In this context, a leapfrog is expected to come from a hybrid approach merging the disciplines above. Along this line, this work focuses on the propagation of individual interests in social networks. The proposed framework consists of the following main components: a method to gather information about the members of the social networks; methods to perform some semantic analysis of the Domain of Interest; a procedure to infer members' interests; and an interests evolution theory to predict how the interests propagate in the network. As a result, one achieves an analytic tool to measure individual features, such as members' susceptibilities and authorities. Although the approach applies to any type of social network, here it is has been tested against the computer science research community. The DBLP (Digital Bibliography and Library Project) database has been elected as test-case since it provides the most comprehensive list of scientific production in this field.

Transnational networks, diffusion dynamics, and electoral revolutions in the postcommunist world

NASA Astrophysics Data System (ADS)

Bunce, Valerie; Wolchik, Sharon L.

2007-05-01

Since 1996, eight elections have taken place in postcommunist Europe and Eurasia that have replaced illiberal with liberal governments. There is ample evidence that these “electoral revolutions” reflected the cross-national diffusion of a distinctive model of regime change that was developed elsewhere and that was designed to promote democratization in authoritarian political contexts featuring semi-competitive elections. This electoral model spread throughout the postcommunist region because of both shared perceptions by opposition groups of similar local conditions and the existence of transnational democracy promotion networks that included local, regional and American participants. As these revolutions spread, however, they were less successful in carrying through democratic change-in part because local conditions were less supportive and in part because authoritarian leaders and their international allies were both forewarned and forearmed.

Building Capacity: The National Network for Ocean and Climate Change Interpretation

NASA Astrophysics Data System (ADS)

Spitzer, W.

2014-12-01

In the US, more than 1,500 informal science venues (science centers, museums, aquariums, zoos, nature centers, national parks) are visited annually by 61% of the population. Research shows that these visitors are receptive to learning about climate change, and expect these institutions to provide reliable information about environmental issues and solutions. These informal science venues play a critical role in shaping public understanding. Since 2007, the New England Aquarium has led a national effort to increase the capacity of informal science venues to effectively communicate about climate change. We are now leading the NSF-funded National Network for Ocean and Climate Change Interpretation (NNOCCI), partnering with the Association of Zoos and Aquariums, FrameWorks Institute, Woods Hole Oceanographic Institution, Monterey Bay Aquarium, and National Aquarium, with evaluation conducted by the New Knowledge Organization, Pennsylvania State University, and Ohio State University. After two years of project implementation, key findings include: 1. Importance of adaptive management - We continue to make ongoing changes in training format, content, and roles of facilitators and participants. 2. Impacts on interpreters - We have multiple lines of evidence for changes in knowledge, skills, attitudes, and behaviors. 3. Social radiation - Trained interpreters have a significant influence on their friends, family and colleagues. 4. Visitor impacts - "Exposure to "strategically framed" interpretation does change visitors' perceptions about climate change. 5. Community of practice - We are seeing evidence of growing participation, leadership, and sustainability. 6. Diffusion of innovation - Peer networks are facilitating dissemination throughout the informal science education community. Over the next five years, NNOCCI will achieve a systemic national impact across the ISE community, embed its work within multiple ongoing regional and national climate change education

Building A National Network for Ocean and Climate Change Interpretation (Invited)

NASA Astrophysics Data System (ADS)

Spitzer, W.; Anderson, J.

2013-12-01

In the US, more than 1,500 informal science venues (science centers, museums, aquariums, zoos, nature centers, national parks) are visited annually by 61% of the population. Research shows that these visitors are receptive to learning about climate change, and expect these institutions to provide reliable information about environmental issues and solutions. Given that we spend less than 5% of our lifetime in a classroom, informal science venues play a critical role in shaping public understanding. Since 2007, the New England Aquarium (NEAq) has led a national effort to increase the capacity of informal science education institutions (ISEIs) to effectively communicate about the impacts of climate change on the oceans. NEAq is now leading the NSF-funded National Network for Ocean and Climate Change Interpretation (NNOCCI), partnering with the Association of Zoos and Aquariums, FrameWorks Institute, Woods Hole Oceanographic Institution, Monterey Bay Aquarium, and National Aquarium, with evaluation conducted by the New Knowledge Organization, Pennsylvania State University, and Ohio State University. NNOCCI's design is based on best practices in informal science learning, cognitive/social psychology, community and network building: Interpreters as Communication Strategists - Interpreters can serve not merely as educators disseminating information, but can also be leaders in influencing public perceptions, given their high level of commitment, knowledge, public trust, social networks, and visitor contact. Communities of Practice - Learning is a social activity that is created through engagement in a supportive community context. Social support is particularly important in addressing a complex, contentious and distressing subject. Diffusion of Innovation - Peer networks are of primary importance in spreading innovations. Leaders serve as 'early adopters' and influence others to achieve a critical mass of implementation. Over the next five years, NNOCCI will achieve a

Beyond Economy: Impact of National Cultural Values on Nationwide Broadband Internet Diffusion

ERIC Educational Resources Information Center

Joo, Sung-Hee

2010-01-01

This study examines how the non-conventional factors of national cultural values and government involvement affect the diffusion of broadband Internet technologies in various nations around the world. An innovative element of the study was the examination of the influence patterns at different stages of diffusion, which was measured by the number…

The influence of ionic strength on DNA diffusion in gel networks

NASA Astrophysics Data System (ADS)

Fu, Yuanxi; Jee, Ah-Young; Kim, Hyeong-Ju; Granick, Steve

Cations are known to reduce the rigidity of the DNA molecules by screening the negative charge along the sugar phosphate backbone. This was established by optical tweezer pulling experiment of immobilized DNA strands. However, little is known regarding the influence of ions on the motion of DNA molecules as they thread through network meshes. We imaged in real time the Brownian diffusion of fluorescent labeled lambda-DNA in an agarose gel network in the presence of salt with monovalent or multivalent cations. Each movie was analyzed using home-written program to yield a trajectory of center of the mass and the accompanying history of the shape fluctuations. One preliminary finding is that ionic strength has a profound influence on the slope of the trace of mean square displacement (MSD) versus time. The influence of ionic strength on DNA diffusion in gel networks.

Modeling of information diffusion in Twitter-like social networks under information overload.

PubMed

Li, Pei; Li, Wei; Wang, Hui; Zhang, Xin

2014-01-01

Due to the existence of information overload in social networks, it becomes increasingly difficult for users to find useful information according to their interests. This paper takes Twitter-like social networks into account and proposes models to characterize the process of information diffusion under information overload. Users are classified into different types according to their in-degrees and out-degrees, and user behaviors are generalized into two categories: generating and forwarding. View scope is introduced to model the user information-processing capability under information overload, and the average number of times a message appears in view scopes after it is generated by a given type user is adopted to characterize the information diffusion efficiency, which is calculated theoretically. To verify the accuracy of theoretical analysis results, we conduct simulations and provide the simulation results, which are consistent with the theoretical analysis results perfectly. These results are of importance to understand the diffusion dynamics in social networks, and this analysis framework can be extended to consider more realistic situations.

Modeling of Information Diffusion in Twitter-Like Social Networks under Information Overload

PubMed Central

Li, Wei

2014-01-01

Due to the existence of information overload in social networks, it becomes increasingly difficult for users to find useful information according to their interests. This paper takes Twitter-like social networks into account and proposes models to characterize the process of information diffusion under information overload. Users are classified into different types according to their in-degrees and out-degrees, and user behaviors are generalized into two categories: generating and forwarding. View scope is introduced to model the user information-processing capability under information overload, and the average number of times a message appears in view scopes after it is generated by a given type user is adopted to characterize the information diffusion efficiency, which is calculated theoretically. To verify the accuracy of theoretical analysis results, we conduct simulations and provide the simulation results, which are consistent with the theoretical analysis results perfectly. These results are of importance to understand the diffusion dynamics in social networks, and this analysis framework can be extended to consider more realistic situations. PMID:24795541

Network diffusion-based analysis of high-throughput data for the detection of differentially enriched modules

PubMed Central

Bersanelli, Matteo; Mosca, Ettore; Remondini, Daniel; Castellani, Gastone; Milanesi, Luciano

2016-01-01

A relation exists between network proximity of molecular entities in interaction networks, functional similarity and association with diseases. The identification of network regions associated with biological functions and pathologies is a major goal in systems biology. We describe a network diffusion-based pipeline for the interpretation of different types of omics in the context of molecular interaction networks. We introduce the network smoothing index, a network-based quantity that allows to jointly quantify the amount of omics information in genes and in their network neighbourhood, using network diffusion to define network proximity. The approach is applicable to both descriptive and inferential statistics calculated on omics data. We also show that network resampling, applied to gene lists ranked by quantities derived from the network smoothing index, indicates the presence of significantly connected genes. As a proof of principle, we identified gene modules enriched in somatic mutations and transcriptional variations observed in samples of prostate adenocarcinoma (PRAD). In line with the local hypothesis, network smoothing index and network resampling underlined the existence of a connected component of genes harbouring molecular alterations in PRAD. PMID:27731320

Diffusion on social networks: Survey data from rural villages in central China.

PubMed

Xiong, Hang; Wang, Puqing; Zhu, Yueji

2016-06-01

Empirical studies on social diffusions are often restricted by the access to data of diffusion and social relations on the same objects. We present a set of first-hand data that we collected in ten rural villages in central China through household surveys. The dataset contains detailed and comprehensive data of the diffusion of an innovation, the major social relationships and the household level demographic characteristics in these villages. The data have been used to study peer effects in social diffusion using simulation models, "Peer Effects and Social Network: The Case of Rural Diffusion in Central China" [1]. They can also be used to estimate spatial econometric models. Data are supplied with this article.

Modeling the diffusion of complex innovations as a process of opinion formation through social networks.

PubMed

Assenova, Valentina A

2018-01-01

Complex innovations- ideas, practices, and technologies that hold uncertain benefits for potential adopters-often vary in their ability to diffuse in different communities over time. To explain why, I develop a model of innovation adoption in which agents engage in naïve (DeGroot) learning about the value of an innovation within their social networks. Using simulations on Bernoulli random graphs, I examine how adoption varies with network properties and with the distribution of initial opinions and adoption thresholds. The results show that: (i) low-density and high-asymmetry networks produce polarization in influence to adopt an innovation over time, (ii) increasing network density and asymmetry promote adoption under a variety of opinion and threshold distributions, and (iii) the optimal levels of density and asymmetry in networks depend on the distribution of thresholds: networks with high density (>0.25) and high asymmetry (>0.50) are optimal for maximizing diffusion when adoption thresholds are right-skewed (i.e., barriers to adoption are low), but networks with low density (<0.01) and low asymmetry (<0.25) are optimal when thresholds are left-skewed. I draw on data from a diffusion field experiment to predict adoption over time and compare the results to observed outcomes.

Modelling cointegration and Granger causality network to detect long-term equilibrium and diffusion paths in the financial system.

PubMed

Gao, Xiangyun; Huang, Shupei; Sun, Xiaoqi; Hao, Xiaoqing; An, Feng

2018-03-01

Microscopic factors are the basis of macroscopic phenomena. We proposed a network analysis paradigm to study the macroscopic financial system from a microstructure perspective. We built the cointegration network model and the Granger causality network model based on econometrics and complex network theory and chose stock price time series of the real estate industry and its upstream and downstream industries as empirical sample data. Then, we analysed the cointegration network for understanding the steady long-term equilibrium relationships and analysed the Granger causality network for identifying the diffusion paths of the potential risks in the system. The results showed that the influence from a few key stocks can spread conveniently in the system. The cointegration network and Granger causality network are helpful to detect the diffusion path between the industries. We can also identify and intervene in the transmission medium to curb risk diffusion.

Modelling cointegration and Granger causality network to detect long-term equilibrium and diffusion paths in the financial system

PubMed Central

Huang, Shupei; Sun, Xiaoqi; Hao, Xiaoqing; An, Feng

2018-01-01

Microscopic factors are the basis of macroscopic phenomena. We proposed a network analysis paradigm to study the macroscopic financial system from a microstructure perspective. We built the cointegration network model and the Granger causality network model based on econometrics and complex network theory and chose stock price time series of the real estate industry and its upstream and downstream industries as empirical sample data. Then, we analysed the cointegration network for understanding the steady long-term equilibrium relationships and analysed the Granger causality network for identifying the diffusion paths of the potential risks in the system. The results showed that the influence from a few key stocks can spread conveniently in the system. The cointegration network and Granger causality network are helpful to detect the diffusion path between the industries. We can also identify and intervene in the transmission medium to curb risk diffusion. PMID:29657804

An evolutionary game for the diffusion of rumor in complex networks

NASA Astrophysics Data System (ADS)

Li, Dandan; Ma, Jing; Tian, Zihao; Zhu, Hengmin

2015-09-01

In this paper, we investigate the rumor diffusion process according to the evolutionary game framework. By using three real social network datasets, we find that increasing the judgment ability of individuals could curb the diffusion of rumor effectively. Under the same level of punishment cost, there are more spreaders in the network that has larger average degree. Moreover, the punishment fraction has more significant impact than the risk coefficient on the controlling of rumor diffusion. There exist some optimal risk coefficients and punishment fractions that could help more people refusing to spread rumor. In addition, the effect of the tie strength on the final fraction of spreaders is investigated. The results indicate that the rumor can be suppressed soon if the individuals preferentially select the neighbor either weaker or stronger ties persistently to update their strategy. However, choosing neighbor blindly may promote the spread of rumor. Finally, by comparing three kinds of punishment mechanisms, we show that taking the lead in punishing the higher degree nodes is the most effective measure to reduce the coverage of rumor.

Fostering diffusion of scientific contents of National Society Cardiovascular Journals: The new ESC search engine.

PubMed

Alfonso, Fernando; Gonçalves, Lino; Pinto, Fausto; Timmis, Adam; Ector, Hugo; Ambrosio, Giuseppe; Vardas, Panos

2015-05-01

European Society of Cardiology (ESC) National Society Cardiovascular Journals (NSCJs) are high-quality biomedical journals focused on cardiovascular diseases. The Editors' Network of the ESC devises editorial initiatives aimed at improving the scientific quality and diffusion of NSCJ. In this article we will discuss on the importance of the Internet, electronic editions and open access strategies on scientific publishing. Finally, we will propose a new editorial initiative based on a novel electronic tool on the ESC web-page that may further help to increase the dissemination of contents and visibility of NSCJs. Copyright © 2013 Sociedade Portuguesa de Cardiologia. Published by Elsevier España. All rights reserved.

National law enforcement telecommunications network

NASA Technical Reports Server (NTRS)

Reilly, N. B.; Garrison, G. W.; Sohn, R. L.; Gallop, D. L.; Goldstein, B. L.

1975-01-01

Alternative approaches are analyzed to a National Law Enforcement Telecommunications Network (NALECOM) designed to service all state-to-state and state-to-national criminal justice communications traffic needs in the United States. Network topology options were analyzed, and equipment and personnel requirements for each option were defined in accordance with NALECOM functional specifications and design guidelines. Evaluation criteria were developed and applied to each of the options leading to specific conclusions. Detailed treatments of methods for determining traffic requirements, communication line costs, switcher configurations and costs, microwave costs, satellite system configurations and costs, facilities, operations and engineering costs, network delay analysis and network availability analysis are presented. It is concluded that a single regional switcher configuration is the optimum choice based on cost and technical factors. A two-region configuration is competitive. Multiple-region configurations are less competitive due to increasing costs without attending benefits.

Transport through a network of capillaries from ultrametric diffusion equation with quadratic nonlinearity

NASA Astrophysics Data System (ADS)

Oleschko, K.; Khrennikov, A.

2017-10-01

This paper is about a novel mathematical framework to model transport (of, e.g., fluid or gas) through networks of capillaries. This framework takes into account the tree structure of the networks of capillaries. (Roughly speaking, we use the tree-like system of coordinates.) As is well known, tree-geometry can be topologically described as the geometry of an ultrametric space, i.e., a metric space in which the metric satisfies the strong triangle inequality: in each triangle, the third side is less than or equal to the maximum of two other sides. Thus transport (e.g., of oil or emulsion of oil and water in porous media, or blood and air in biological organisms) through networks of capillaries can be mathematically modelled as ultrametric diffusion. Such modelling was performed in a series of recently published papers of the authors. However, the process of transport through capillaries can be only approximately described by the linear diffusion, because the concentration of, e.g., oil droplets, in a capillary can essentially modify the dynamics. Therefore nonlinear dynamical equations provide a more adequate model of transport in a network of capillaries. We consider a nonlinear ultrametric diffusion equation with quadratic nonlinearity - to model transport in such a network. Here, as in the linear case, we apply the theory of ultrametric wavelets. The paper also contains a simple introduction to theory of ultrametric spaces and analysis on them.

Effects of awareness diffusion and self-initiated awareness behavior on epidemic spreading - An approach based on multiplex networks

NASA Astrophysics Data System (ADS)

Kan, Jia-Qian; Zhang, Hai-Feng

2017-03-01

In this paper, we study the interplay between the epidemic spreading and the diffusion of awareness in multiplex networks. In the model, an infectious disease can spread in one network representing the paths of epidemic spreading (contact network), leading to the diffusion of awareness in the other network (information network), and then the diffusion of awareness will cause individuals to take social distances, which in turn affects the epidemic spreading. As for the diffusion of awareness, we assume that, on the one hand, individuals can be informed by other aware neighbors in information network, on the other hand, the susceptible individuals can be self-awareness induced by the infected neighbors in the contact networks (local information) or mass media (global information). Through Markov chain approach and numerical computations, we find that the density of infected individuals and the epidemic threshold can be affected by the structures of the two networks and the effective transmission rate of the awareness. However, we prove that though the introduction of the self-awareness can lower the density of infection, which cannot increase the epidemic threshold no matter of the local information or global information. Our finding is remarkably different to many previous results on single-layer network: local information based behavioral response can alter the epidemic threshold. Furthermore, our results indicate that the nodes with more neighbors (hub nodes) in information networks are easier to be informed, as a result, their risk of infection in contact networks can be effectively reduced.

Dynamic node immunization for restraint of harmful information diffusion in social networks

NASA Astrophysics Data System (ADS)

Yang, Dingda; Liao, Xiangwen; Shen, Huawei; Cheng, Xueqi; Chen, Guolong

2018-08-01

To restrain the spread of harmful information is crucial for the healthy and sustainable development of social networks. We address the problem of restraining the spread of harmful information by immunizing nodes in the networks. Previous works have developed methods based on the network topology or studied how to immunize nodes in the presence of initial infected nodes. These static methods, in which nodes are immunized at once, may have poor performance in the certain situation due to the dynamics of diffusion. To tackle this problem, we introduce a new dynamic immunization problem of immunizing nodes during the process of the diffusion in this paper. We formulate the problem and propose a novel heuristic algorithm by dealing with two sub-problems: (1) how to select a node to achieve the best immunization effect at the present time? (2) whether the selected node should be immunized right now? Finally, we demonstrate the effectiveness of our algorithm through extensive experiments on various real datasets.

Predicting the future trend of popularity by network diffusion.

PubMed

Zeng, An; Yeung, Chi Ho

2016-06-01

Conventional approaches to predict the future popularity of products are mainly based on extrapolation of their current popularity, which overlooks the hidden microscopic information under the macroscopic trend. Here, we study diffusion processes on consumer-product and citation networks to exploit the hidden microscopic information and connect consumers to their potential purchase, publications to their potential citers to obtain a prediction for future item popularity. By using the data obtained from the largest online retailers including Netflix and Amazon as well as the American Physical Society citation networks, we found that our method outperforms the accurate short-term extrapolation and identifies the potentially popular items long before they become prominent.

Predicting the future trend of popularity by network diffusion

NASA Astrophysics Data System (ADS)

Zeng, An; Yeung, Chi Ho

2016-06-01

Conventional approaches to predict the future popularity of products are mainly based on extrapolation of their current popularity, which overlooks the hidden microscopic information under the macroscopic trend. Here, we study diffusion processes on consumer-product and citation networks to exploit the hidden microscopic information and connect consumers to their potential purchase, publications to their potential citers to obtain a prediction for future item popularity. By using the data obtained from the largest online retailers including Netflix and Amazon as well as the American Physical Society citation networks, we found that our method outperforms the accurate short-term extrapolation and identifies the potentially popular items long before they become prominent.

Dangerous Liaisons? Dating and Drinking Diffusion in Adolescent Peer Networks

ERIC Educational Resources Information Center

Kreager, Derek A.; Haynie, Dana L.

2011-01-01

The onset and escalation of alcohol consumption and romantic relationships are hallmarks of adolescence. Yet only recently have these domains jointly been the focus of sociological inquiry. We extend this literature by connecting alcohol use, dating, and peers to understand the diffusion of drinking behavior in school-based friendship networks.…

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

PubMed

Séror, Ann C

2006-01-27

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

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

PubMed Central

2006-01-01

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

Design of a national distributed health data network.

PubMed

Maro, Judith C; Platt, Richard; Holmes, John H; Strom, Brian L; Hennessy, Sean; Lazarus, Ross; Brown, Jeffrey S

2009-09-01

A distributed health data network is a system that allows secure remote analysis of separate data sets, each comprising a different medical organization's or health plan's records. Distributed health data networks are currently being planned that could cover millions of people, permitting studies of comparative clinical effectiveness, best practices, diffusion of medical technologies, and quality of care. These networks could also support assessment of medical product safety and other public health needs. Distributed network technologies allow data holders to control all uses of their data, which overcomes many practical obstacles related to confidentiality, regulation, and proprietary interests. Some of the challenges and potential methods of operation of a multipurpose, multi-institutional distributed health data network are described.

A diffusion perspective on temporal networks: A case study on a supermarket

NASA Astrophysics Data System (ADS)

Deng, Shiguo; Qiu, Lu; Yang, Yue; Yang, Huijie

2016-01-01

From a large amount of records, one can extract behavioral characteristics of a social system at different scales. Theoretically, it can help us to know how the global behavior of a social system is formed from individual activities. Practically, it can be used to optimize and even to control the social system. Complicated relationships between the individuals form a network, which evolves with time. The behavior of the system can be accordingly understood in the framework of temporal network. In the present paper, instead of focusing on microscopic structures, we develop a framework to investigate temporal networks from the viewpoint of diffusion process, in which each snapshot network is divided into groups and the ID number of the group a node belongs to is used to measure its state. By this way trajectories of the nodes form an ensemble of realizations of a stochastic process. As an illustration, we investigate the diffusion behavior of a supermarket. One can find that with the increase of time the customers cluster and separate into different groups. Meanwhile, the system evolves in a significant order way, instead of a complete random one.

A Component-Based Diffusion Model With Structural Diversity for Social Networks.

PubMed

Qing Bao; Cheung, William K; Yu Zhang; Jiming Liu

2017-04-01

Diffusion on social networks refers to the process where opinions are spread via the connected nodes. Given a set of observed information cascades, one can infer the underlying diffusion process for social network analysis. The independent cascade model (IC model) is a widely adopted diffusion model where a node is assumed to be activated independently by any one of its neighbors. In reality, how a node will be activated also depends on how its neighbors are connected and activated. For instance, the opinions from the neighbors of the same social group are often similar and thus redundant. In this paper, we extend the IC model by considering that: 1) the information coming from the connected neighbors are similar and 2) the underlying redundancy can be modeled using a dynamic structural diversity measure of the neighbors. Our proposed model assumes each node to be activated independently by different communities (or components) of its parent nodes, each weighted by its effective size. An expectation maximization algorithm is derived to infer the model parameters. We compare the performance of the proposed model with the basic IC model and its variants using both synthetic data sets and a real-world data set containing news stories and Web blogs. Our empirical results show that incorporating the community structure of neighbors and the structural diversity measure into the diffusion model significantly improves the accuracy of the model, at the expense of only a reasonable increase in run-time.

Dispersion in Rectangular Networks: Effective Diffusivity and Large-Deviation Rate Function

NASA Astrophysics Data System (ADS)

Tzella, Alexandra; Vanneste, Jacques

2016-09-01

The dispersion of a diffusive scalar in a fluid flowing through a network has many applications including to biological flows, porous media, water supply, and urban pollution. Motivated by this, we develop a large-deviation theory that predicts the evolution of the concentration of a scalar released in a rectangular network in the limit of large time t ≫1 . This theory provides an approximation for the concentration that remains valid for large distances from the center of mass, specifically for distances up to O (t ) and thus much beyond the O (t1 /2) range where a standard Gaussian approximation holds. A byproduct of the approach is a closed-form expression for the effective diffusivity tensor that governs this Gaussian approximation. Monte Carlo simulations of Brownian particles confirm the large-deviation results and demonstrate their effectiveness in describing the scalar distribution when t is only moderately large.

The Bass diffusion model on networks with correlations and inhomogeneous advertising

NASA Astrophysics Data System (ADS)

Bertotti, M. L.; Brunner, J.; Modanese, G.

2016-09-01

The Bass model, which is an effective forecasting tool for innovation diffusion based on large collections of empirical data, assumes an homogeneous diffusion process. We introduce a network structure into this model and we investigate numerically the dynamics in the case of networks with link density $P(k)=c/k^\\gamma$, where $k=1, \\ldots , N$. The resulting curve of the total adoptions in time is qualitatively similar to the homogeneous Bass curve corresponding to a case with the same average number of connections. The peak of the adoptions, however, tends to occur earlier, particularly when $\\gamma$ and $N$ are large (i.e., when there are few hubs with a large maximum number of connections). Most interestingly, the adoption curve of the hubs anticipates the total adoption curve in a predictable way, with peak times which can be, for instance when $N=100$, between 10% and 60% of the total adoptions peak. This may allow to monitor the hubs for forecasting purposes. We also consider the case of networks with assortative and disassortative correlations and a case of inhomogeneous advertising where the publicity terms are "targeted" on the hubs while maintaining their total cost constant.

Online Networks and the Diffusion of Protests

NASA Astrophysics Data System (ADS)

Moreno, Yamir

2013-03-01

Undoubtedly, online social networks have an enormous impact on opinions and cultural trends. Also, these platforms have revealed as a fundamental organizing mechanism in country-wide social movements. Recent events in the Middle East and North Africa (the wave of protests in the Arab world), across Europe (in the form of anti-cuts demonstrations or riots) and United States (the OWS movement) have generated much discussion on how digital media is connected to the diffusion of protests. In this talk, we investigate the mechanisms driving the emergence, development and stabilization of unrest movements in Spain and the USA by analyzing data from Twitter. Messages related to the protests are analyzed at both static and dynamic levels. We show that the online trace of the protests provides a unique opportunity to tackle central issues like recruitment patterns, information cascades and their spatiotemporal dynamics. Our findings shed light on the connection between online networks and social movements, and offer an empirical test to elusive sociological questions about collective action.

Optimal resource diffusion for suppressing disease spreading in multiplex networks

NASA Astrophysics Data System (ADS)

Chen, Xiaolong; Wang, Wei; Cai, Shimin; Stanley, H. Eugene; Braunstein, Lidia A.

2018-05-01

Resource diffusion is a ubiquitous phenomenon, but how it impacts epidemic spreading has received little study. We propose a model that couples epidemic spreading and resource diffusion in multiplex networks. The spread of disease in a physical contact layer and the recovery of the infected nodes are both strongly dependent upon resources supplied by their counterparts in the social layer. The generation and diffusion of resources in the social layer are in turn strongly dependent upon the state of the nodes in the physical contact layer. Resources diffuse preferentially or randomly in this model. To quantify the degree of preferential diffusion, a bias parameter that controls the resource diffusion is proposed. We conduct extensive simulations and find that the preferential resource diffusion can change phase transition type of the fraction of infected nodes. When the degree of interlayer correlation is below a critical value, increasing the bias parameter changes the phase transition from double continuous to single continuous. When the degree of interlayer correlation is above a critical value, the phase transition changes from multiple continuous to first discontinuous and then to hybrid. We find hysteresis loops in the phase transition. We also find that there is an optimal resource strategy at each fixed degree of interlayer correlation under which the threshold reaches a maximum and the disease can be maximally suppressed. In addition, the optimal controlling parameter increases as the degree of inter-layer correlation increases.

Diffusion of Polymers through Periodic Networks of Lipid-Based Nanochannels.

PubMed

Ghanbari, Reza; Assenza, Salvatore; Saha, Abhijit; Mezzenga, Raffaele

2017-04-11

We present an experimental investigation of the diffusion of unfolded polymers in the triply-periodic water-channel network of inverse bicontinuous cubic phases. Depending on the chain size, our results indicate the presence of two different dynamical regimes corresponding to Zimm and Rouse diffusion. We support our findings by scaling arguments based on a combination of blob and effective-medium theories and suggest the presence of a third regime where dynamics is driven by reptation. Our experimental results also show an increasing behavior of the partition coefficient as a function of the polymer molecular weight, indicative of a reduction in the conformational degrees of freedom induced by the confinement.

Network Confinement and Heterogeneity Slows Nanoparticle Diffusion in Polymer Gels

NASA Astrophysics Data System (ADS)

Parrish, Emmabeth; Caporizzo, Matthew; Composto, Russell

Nanoparticle (NP) diffusion was measured in polyacrylamide gels (PAG) with a mesh size comparable to NP size, 20nm. The confinement ratio (CR), NP diameter/mesh, increased from 0.4 to 3.8 by increasing crosslinker density and 0.4 to 2 by adding acetone, which collapsed PAG. In all gels, NPs either became localized (<200nm) or diffused microns, as measured by single particle tracking. Mean squared displacements (MSD) of mobile NPs decreased as CR increased. In collapsed gels, the localized NP population increased and MSD of mobile NPs decreased compared to crosslinked PAG. For all CRs, van Hove distributions exhibited non-Gaussian displacements consistent with intermittent localization of NPs. The non-Gaussian parameter increased from a maximum of 1.5 for crosslinked PAG to 5 for collapsed PAG, consistent with greater network heterogeneity. Diffusion coefficients, D, decreased exponentially as CR increased for crosslinked gels, but in collapsed gels D decreased more strongly, suggesting CR alone was insufficient to capture diffusion. Collapsing the gel resulted in an increasingly tortuous pathway for NPs, slowing diffusion at a given CR. Understanding how gel structure affects NP mobility will allow the design of gels with improved ability to separate and release molecules. ACS/PRF 54028-ND7, NSF/MWN DMR-1210379.

NCI National Clinical Trials Network Structure

Cancer.gov

Learn about how the National Clinical Trials Network (NCTN) is structured. The NCTN is a program of the National Cancer Institute that gives funds and other support to cancer research organizations to conduct cancer clinical trials.

National research and education network

NASA Technical Reports Server (NTRS)

Villasenor, Tony

1991-01-01

Some goals of this network are as follows: Extend U.S. technological leadership in high performance computing and computer communications; Provide wide dissemination and application of the technologies both to the speed and the pace of innovation and to serve the national economy, national security, education, and the global environment; and Spur gains in the U.S. productivity and industrial competitiveness by making high performance computing and networking technologies an integral part of the design and production process. Strategies for achieving these goals are as follows: Support solutions to important scientific and technical challenges through a vigorous R and D effort; Reduce the uncertainties to industry for R and D and use of this technology through increased cooperation between government, industry, and universities and by the continued use of government and government funded facilities as a prototype user for early commercial HPCC products; and Support underlying research, network, and computational infrastructures on which U.S. high performance computing technology is based.

Global exponential stability of BAM neural networks with time-varying delays and diffusion terms

NASA Astrophysics Data System (ADS)

Wan, Li; Zhou, Qinghua

2007-11-01

The stability property of bidirectional associate memory (BAM) neural networks with time-varying delays and diffusion terms are considered. By using the method of variation parameter and inequality technique, the delay-independent sufficient conditions to guarantee the uniqueness and global exponential stability of the equilibrium solution of such networks are established.

Study of car-sharing diffusion criticality conditions based on human traveling network

NASA Astrophysics Data System (ADS)

Xu, Yan; Ji, Xuehong

Car-sharing program, like Car2go, is an innovative urban transportation mode where the car-sharing company provides a car fleet to offer people with the short-term access of car traveling. As a new traveling service, car-sharing platforms have been struggling hard to trigger initial users and speed up their diffusion process. Unlike new product spreading via geographical proximity people, car-sharing users usually drive sharing cars to different destinations and influence people there, and potential user decision also depends on previous user activity at all their destinations. Car-sharing user connections are mainly affected by their traveling behaviors. The influence of user traveling network on new service/product spreading process has been rarely studied before. Here, we find that the infective rate between users with the same destination is critical to the minimum user base of car-sharing diffusion. Moreover, a city with central user network is more appropriate for car-sharing. It leads to a small critical infective rate for diffusion, and a large stable market size of car-sharing service. Our study can impact car-sharing market strategies ranging from market expansion in one city to optimal market selection among different cities.

Master stability functions reveal diffusion-driven pattern formation in networks

NASA Astrophysics Data System (ADS)

Brechtel, Andreas; Gramlich, Philipp; Ritterskamp, Daniel; Drossel, Barbara; Gross, Thilo

2018-03-01

We study diffusion-driven pattern formation in networks of networks, a class of multilayer systems, where different layers have the same topology, but different internal dynamics. Agents are assumed to disperse within a layer by undergoing random walks, while they can be created or destroyed by reactions between or within a layer. We show that the stability of homogeneous steady states can be analyzed with a master stability function approach that reveals a deep analogy between pattern formation in networks and pattern formation in continuous space. For illustration, we consider a generalized model of ecological meta-food webs. This fairly complex model describes the dispersal of many different species across a region consisting of a network of individual habitats while subject to realistic, nonlinear predator-prey interactions. In this example, the method reveals the intricate dependence of the dynamics on the spatial structure. The ability of the proposed approach to deal with this fairly complex system highlights it as a promising tool for ecology and other applications.

The National Biomedical Communications Network as a Developing Structure *

PubMed Central

Davis, Ruth M.

1971-01-01

The National Biomedical Communications Network has evolved both from a set of conceptual recommendations over the last twelve years and an accumulation of needs manifesting themselves in the requests of members of the medical community. With a short history of three years this network and its developing structure have exhibited most of the stresses of technology interfacing with customer groups, and of a structure attempting to build itself upon many existing fragmentary unconnected segments of a potentially viable resourcesharing capability. In addition to addressing these topics, the paper treats a design appropriate to any network devoted to information transfer in a special interest user community. It discusses fundamentals of network design, highlighting that network structure most appropriate to a national information network. Examples are given of cost analyses of information services and certain conjectures are offered concerning the roles of national networks. PMID:5542912

United States National seismograph network

USGS Publications Warehouse

Masse, R.P.; Filson, J.R.; Murphy, A.

1989-01-01

The USGS National Earthquake Information Center (NEIC) has planned and is developing a broadband digital seismograph network for the United States. The network will consist of approximately 150 seismograph stations distributed across the contiguous 48 states and across Alaska, Hawaii, Puerto Rico and the Virgin Islands. Data transmission will be via two-way satellite telemetry from the network sites to a central recording facility at the NEIC in Golden, Colorado. The design goal for the network is the on-scale recording by at least five well-distributed stations of any seismic event of magnitude 2.5 or greater in all areas of the United States except possibly part of Alaska. All event data from the network will be distributed to the scientific community on compact disc with read-only memory (CD-ROM). ?? 1989.

A network model of successive partitioning-limited solute diffusion through the stratum corneum.

PubMed

Schumm, Phillip; Scoglio, Caterina M; van der Merwe, Deon

2010-02-07

As the most exposed point of contact with the external environment, the skin is an important barrier to many chemical exposures, including medications, potentially toxic chemicals and cosmetics. Traditional dermal absorption models treat the stratum corneum lipids as a homogenous medium through which solutes diffuse according to Fick's first law of diffusion. This approach does not explain non-linear absorption and irregular distribution patterns within the stratum corneum lipids as observed in experimental data. A network model, based on successive partitioning-limited solute diffusion through the stratum corneum, where the lipid structure is represented by a large, sparse, and regular network where nodes have variable characteristics, offers an alternative, efficient, and flexible approach to dermal absorption modeling that simulates non-linear absorption data patterns. Four model versions are presented: two linear models, which have unlimited node capacities, and two non-linear models, which have limited node capacities. The non-linear model outputs produce absorption to dose relationships that can be best characterized quantitatively by using power equations, similar to the equations used to describe non-linear experimental data.

SPIR: The potential spreaders involved SIR model for information diffusion in social networks

NASA Astrophysics Data System (ADS)

Rui, Xiaobin; Meng, Fanrong; Wang, Zhixiao; Yuan, Guan; Du, Changjiang

2018-09-01

The Susceptible-Infective-Removed (SIR) model is one of the most widely used models for the information diffusion research in social networks. Many researchers have devoted themselves to improving the classic SIR model in different aspects. However, on the one hand, the equations of these improved models are regarded as continuous functions, while the corresponding simulation experiments use discrete time, leading to the mismatch between numerical solutions got from mathematical method and experimental results obtained by simulating the spreading behaviour of each node. On the other hand, if the equations of these improved models are solved discretely, susceptible nodes will be calculated repeatedly, resulting in a big deviation from the actual value. In order to solve the above problem, this paper proposes a Susceptible-Potential-Infective-Removed (SPIR) model that analyses the diffusion process based on the discrete time according to simulation. Besides, this model also introduces a potential spreader set which solve the problem of repeated calculation effectively. To test the SPIR model, various experiments have been carried out from different angles on both artificial networks and real world networks. The Pearson correlation coefficient between numerical solutions of our SPIR equations and corresponding simulation results is mostly bigger than 0.95, which reveals that the proposed SPIR model is able to depict the information diffusion process with high accuracy.

Designs on a National Research Network.

ERIC Educational Resources Information Center

Walsh, John

1988-01-01

Discusses the addition of the National Aeronautics and Space Administration database to the National Science Foundation's NSFnet data communication network. Outlines the history of databases in the United States and enumerates proposed upgrades from a new Office of Science and Technology policy report. (TW)

Slow-down or speed-up of inter- and intra-cluster diffusion of controversial knowledge in stubborn communities based on a small world network

NASA Astrophysics Data System (ADS)

Ausloos, Marcel

2015-06-01

Diffusion of knowledge is expected to be huge when agents are open minded. The report concerns a more difficult diffusion case when communities are made of stubborn agents. Communities having markedly different opinions are for example the Neocreationist and Intelligent Design Proponents (IDP), on one hand, and the Darwinian Evolution Defenders (DED), on the other hand. The case of knowledge diffusion within such communities is studied here on a network based on an adjacency matrix built from time ordered selected quotations of agents, whence for inter- and intra-communities. The network is intrinsically directed and not necessarily reciprocal. Thus, the adjacency matrices have complex eigenvalues; the eigenvectors present complex components. A quantification of the slow-down or speed-up effects of information diffusion in such temporal networks, with non-Markovian contact sequences, can be made by comparing the real time dependent (directed) network to its counterpart, the time aggregated (undirected) network, - which has real eigenvalues. In order to do so, small world networks which both contain an odd number of nodes are studied and compared to similar networks with an even number of nodes. It is found that (i) the diffusion of knowledge is more difficult on the largest networks; (ii) the network size influences the slowing-down or speeding-up diffusion process. Interestingly, it is observed that (iii) the diffusion of knowledge is slower in IDP and faster in DED communities. It is suggested that the finding can be "rationalized", if some "scientific quality" and "publication habit" is attributed to the agents, as common sense would guess. This finding offers some opening discussion toward tying scientific knowledge to belief.

Locating the source of diffusion in complex networks by time-reversal backward spreading.

PubMed

Shen, Zhesi; Cao, Shinan; Wang, Wen-Xu; Di, Zengru; Stanley, H Eugene

2016-03-01

Locating the source that triggers a dynamical process is a fundamental but challenging problem in complex networks, ranging from epidemic spreading in society and on the Internet to cancer metastasis in the human body. An accurate localization of the source is inherently limited by our ability to simultaneously access the information of all nodes in a large-scale complex network. This thus raises two critical questions: how do we locate the source from incomplete information and can we achieve full localization of sources at any possible location from a given set of observable nodes. Here we develop a time-reversal backward spreading algorithm to locate the source of a diffusion-like process efficiently and propose a general locatability condition. We test the algorithm by employing epidemic spreading and consensus dynamics as typical dynamical processes and apply it to the H1N1 pandemic in China. We find that the sources can be precisely located in arbitrary networks insofar as the locatability condition is assured. Our tools greatly improve our ability to locate the source of diffusion in complex networks based on limited accessibility of nodal information. Moreover, they have implications for controlling a variety of dynamical processes taking place on complex networks, such as inhibiting epidemics, slowing the spread of rumors, pollution control, and environmental protection.

Locating the source of diffusion in complex networks by time-reversal backward spreading

NASA Astrophysics Data System (ADS)

Shen, Zhesi; Cao, Shinan; Wang, Wen-Xu; Di, Zengru; Stanley, H. Eugene

2016-03-01

Locating the source that triggers a dynamical process is a fundamental but challenging problem in complex networks, ranging from epidemic spreading in society and on the Internet to cancer metastasis in the human body. An accurate localization of the source is inherently limited by our ability to simultaneously access the information of all nodes in a large-scale complex network. This thus raises two critical questions: how do we locate the source from incomplete information and can we achieve full localization of sources at any possible location from a given set of observable nodes. Here we develop a time-reversal backward spreading algorithm to locate the source of a diffusion-like process efficiently and propose a general locatability condition. We test the algorithm by employing epidemic spreading and consensus dynamics as typical dynamical processes and apply it to the H1N1 pandemic in China. We find that the sources can be precisely located in arbitrary networks insofar as the locatability condition is assured. Our tools greatly improve our ability to locate the source of diffusion in complex networks based on limited accessibility of nodal information. Moreover, they have implications for controlling a variety of dynamical processes taking place on complex networks, such as inhibiting epidemics, slowing the spread of rumors, pollution control, and environmental protection.

Delineating interpersonal communication networks: a study of the diffusion of an intervention among female entertainment workers in Shanghai, China.

PubMed

Chen, Yiyun; Latkin, Carl; Celentano, David D; Yang, Xiushi; Li, Xiaoming; Xia, Guomei; Miao, Jia; Surkan, Pamela J

2012-10-01

Diffusion of innovation (DOI) is widely cited in the HIV behavior change literature; however there is a dearth of research on the application of DOI in interventions for sex workers. Following a randomized-controlled trial of HIV risk reduction among female entertainment workers (FEWs) in Shanghai, China, we used qualitative approaches to delineate potential interpersonal communication networks and contributing factors that promote diffusion of information in entertainment venues. Results showed that top-down communication networks from the venue owners to the FEWs were efficient for diffusion of information. Mammies/madams, who act as intermediaries between FEWs and clients form an essential part of FEWs' social networks but do not function as information disseminators due to a conflict of interest between safer sex and maximizing profits. Diffusion of information in large venues tended to rely more on aspects of the physical environment to create intimacy and on pressure from managers to stimulate communication. In small venues, communication and conversations occurred more spontaneously among FEWs. Information about safer sex appeared to be more easily disseminated when the message and the approach used to convey information could be tailored to people working at different levels in the venues. Results suggest that safer sex messages should be provided consistently following an intervention to further promote intervention diffusion, and health-related employer liability systems in entertainment venues should be established, in which employers are responsible for the health of their employees. Our study suggests that existing personal networks can be used to disseminate information in entertainment venues and one should be mindful about the context-specific interactions between FEWs and others in their social networks to better achieve diffusion of interventions.

Delineating Interpersonal Communication Networks: A Study of the Diffusion of an Intervention Among Female Entertainment Workers in Shanghai, China

PubMed Central

Latkin, Carl; Celentano, David D.; Yang, Xiushi; Li, Xiaoming; Xia, Guomei; Miao, Jia; Surkan, Pamela J.

2013-01-01

Diffusion of innovation (DOI) is widely cited in the HIV behavior change literature; however there is a dearth of research on the application of DOI in interventions for sex workers. Following a randomized-controlled trial of HIV risk reduction among female entertainment workers (FEWs) in Shanghai, China, we used qualitative approaches to delineate potential interpersonal communication networks and contributing factors that promote diffusion of information in entertainment venues. Results showed that top-down communication networks from the venue owners to the FEWs were efficient for diffusion of information. Mammies/madams, who act as intermediaries between FEWs and clients form an essential part of FEWs’ social networks but do not function as information disseminators due to a conflict of interest between safer sex and maximizing profits. Diffusion of information in large venues tended to rely more on aspects of the physical environment to create intimacy and on pressure from managers to stimulate communication. In small venues, communication and conversations occurred more spontaneously among FEWs. Information about safer sex appeared to be more easily disseminated when the message and the approach used to convey information could be tailored to people working at different levels in the venues. Results suggest that safer sex messages should be provided consistently following an intervention to further promote intervention diffusion, and health-related employer liability systems in entertainment venues should be established, in which employers are responsible for the health of their employees. Our study suggests that existing personal networks can be used to disseminate information in entertainment venues and one should be mindful about the context-specific interactions between FEWs and others in their social networks to better achieve diffusion of interventions. PMID:22638867

Peer Apprenticeship Learning in Networked Learning Communities: The Diffusion of Epistemic Learning

ERIC Educational Resources Information Center

Jamaludin, Azilawati; Shaari, Imran

2016-01-01

This article discusses peer apprenticeship learning (PAL) as situated within networked learning communities (NLCs). The context revolves around the diffusion of technologically-mediated learning in Singapore schools, where teachers begin to implement inquiry-oriented learning, consistent with 21st century learning, among students. As these schools…

The diffusion of ecstasy through urban youth networks.

PubMed

Schensul, Jean J; Diamond, Sarah; Disch, William; Bermudez, Rey; Eiserman, Julie

2005-01-01

Ecstasy is a drug commonly associated with all-night, or all-weekend electronic dance events known as raves. Upper- and middle-class clubs, gay bars and clubs, and party venues are other common public settings where ecstasy use occurs. During the mid to late 1990s its use was reported in locations as distant as Australia and New Zealand, England and Scotland, and North America. In the United States, use increased dramatically at the end of the millennium, and drug monitoring systems began to report its presence among urban youth. Using social influence, social marketing and diffusion theory, this paper outlines the micro-level processes through which ecstasy traveled from downtown clubs catering to suburban young adults through urban youth networks through distributors and users. The paper is based on participant observation, and in-depth interviews with dealers and users collected during the period of peak diffusion 1999-2001, and survey data collected from 401 poly-drug users between the ages of 16 and 24 and collected at two time points from 1999-2002.

Effect of users' opinion evolution on information diffusion in online social networks

NASA Astrophysics Data System (ADS)

Zhu, Hengmin; Kong, Yuehan; Wei, Jing; Ma, Jing

2018-02-01

The process of topic propagation always interweaves information diffusion and opinion evolution, but most previous works studied the models of information diffusion and opinion evolution separately, and seldom focused on their interaction of each other. To shed light on the effect of users' opinion evolution on information diffusion in online social networks, we proposed a model which incorporates opinion evolution into the process of topic propagation. Several real topics propagating on Sina Microblog were collected to analyze individuals' propagation intentions, and different propagation intentions were considered in the model. The topic propagation was simulated to explore the impact of different opinion distributions and intervention with opposite opinion on information diffusion. Results show that the topic with one-sided opinions can spread faster and more widely, and intervention with opposite opinion is an effective measure to guide the topic propagation. The earlier to intervene, the more effectively the topic propagation would be guided.

A radio-aware routing algorithm for reliable directed diffusion in lossy wireless sensor networks.

PubMed

Kim, Yong-Pyo; Jung, Euihyun; Park, Yong-Jin

2009-01-01

In Wireless Sensor Networks (WSNs), transmission errors occur frequently due to node failure, battery discharge, contention or interference by objects. Although Directed Diffusion has been considered as a prominent data-centric routing algorithm, it has some weaknesses due to unexpected network errors. In order to address these problems, we proposed a radio-aware routing algorithm to improve the reliability of Directed Diffusion in lossy WSNs. The proposed algorithm is aware of the network status based on the radio information from MAC and PHY layers using a cross-layer design. The cross-layer design can be used to get detailed information about current status of wireless network such as a link quality or transmission errors of communication links. The radio information indicating variant network conditions and link quality was used to determine an alternative route that provides reliable data transmission under lossy WSNs. According to the simulation result, the radio-aware reliable routing algorithm showed better performance in both grid and random topologies with various error rates. The proposed solution suggested the possibility of providing a reliable transmission method for QoS requests in lossy WSNs based on the radio-awareness. The energy and mobility issues will be addressed in the future work.

HNET - A National Computerized Health Network

PubMed Central

Casey, Mark; Hamilton, Richard

1988-01-01

The HNET system demonstrated conceptually and technically a national text (and limited bit mapped graphics) computer network for use between innovative members of the health care industry. The HNET configuration of a leased high speed national packet switching network connecting any number of mainframe, mini, and micro computers was unique in it's relatively low capital costs and freedom from obsolescence. With multiple simultaneous conferences, databases, bulletin boards, calendars, and advanced electronic mail and surveys, it is marketable to innovative hospitals, clinics, physicians, health care associations and societies, nurses, multisite research projects libraries, etc.. Electronic publishing and education capabilities along with integrated voice and video transmission are identified as future enhancements.

The National Network of Libraries of Medicine

MedlinePlus

... New England Region: University of Massachusetts Bringing the World of Medical Information to Your Neighborhood By Angela ... D., Head, NN/LM National Network Office The world's largest medical library is the National Library of ...

Molecular model for the diffusion of associating telechelic polymer networks

NASA Astrophysics Data System (ADS)

Ramirez, Jorge; Dursch, Thomas; Olsen, Bradley

Understanding the mechanisms of motion and stress relaxation of associating polymers at the molecular level is critical for advanced technological applications such as enhanced oil-recovery, self-healing materials or drug delivery. In associating polymers, the strength and rates of association/dissociation of the reversible physical crosslinks govern the dynamics of the network and therefore all the macroscopic properties, like self-diffusion and rheology. Recently, by means of forced Rayleigh scattering experiments, we have proved that associating polymers of different architectures show super-diffusive behavior when the free motion of single molecular species is slowed down by association/dissociation kinetics. Here we discuss a new molecular picture for unentangled associating telechelic polymers that considers concentration, molecular weight, number of arms of the molecules and equilibrium and rate constants of association/dissociation. The model predicts super-diffusive behavior under the right combination of values of the parameters. We discuss some of the predictions of the model using scaling arguments, show detailed results from Brownian dynamics simulations of the FRS experiments, and attempt to compare the predictions of the model to experimental data.

Time reversibility of quantum diffusion in small-world networks

NASA Astrophysics Data System (ADS)

Han, Sung-Guk; Kim, Beom Jun

2012-02-01

We study the time-reversal dynamics of a tight-binding electron in the Watts-Strogatz (WS) small-world networks. The localized initial wave packet at time t = 0 diffuses as time proceeds until the time-reversal operation, together with the momentum perturbation of the strength η, is made at the reversal time T. The time irreversibility is measured by I = |Π( t = 2 T) - Π( t = 0)|, where Π is the participation ratio gauging the extendedness of the wavefunction and for convenience, t is measured forward even after the time reversal. When η = 0, the time evolution after T makes the wavefunction at t = 2 T identical to the one at t = 0, and we find I = 0, implying a null irreversibility or a complete reversibility. On the other hand, as η is increased from zero, the reversibility becomes weaker, and we observe enhancement of the irreversibility. We find that I linearly increases with increasing η in the weakly-perturbed region, and that the irreversibility is much stronger in the WS network than in the local regular network.

ESTABLISHING A NATIONAL ENVIRONMENTAL PUBLIC HEALTH TRACKING NETWORK

EPA Science Inventory

This paper describes the CDC's efforts to develop a National Environmental Public Health Tracking Network Tracking Network) with particular focus on air related issues and collaboration with EPA. A Tracking Network is needed in the United States to improve the health of communit...

The UNESCO Global Network of National Geoparks

NASA Astrophysics Data System (ADS)

Mc Keever1, P.; Zouros, N.; Patzak, M.; Missotten, R.

2009-12-01

The UNESCO Global Network of National Geoparks was founded in 2004, following the model successfully established by the European Geoparks Network in 2000. It now comprises 63 members in 19 nations across the world. A Global Geopark is an area with geological heritage of international value but where that heritage is being used for the sustainable economic benefit if the local inhabitants, primarily through education and tourism. Supported by IUGS and IUCN, the aim of the Global Geoparks Network is to facilitate exchange and sharing between members to assist in the protection and conservation of the geological heritage of our planet but to do so in way where local communities can take ownership of these special places and where they can get some sustainable economic benefit from them. While allowing for the sustainable economic development of geoparks, the network explicitly forbids the destruction or sale of the geological value of a geopark. This paper outlines the ethos of the Global Geoparks Network and describes the typical activities of geoparks and how the network functions. Using two examples it also illustrates how members of the Global Geoparks Network provide good examples as tools not only for holistic nature conservation but also for economic development.

Information Filtering via Heterogeneous Diffusion in Online Bipartite Networks

PubMed Central

Zhang, Fu-Guo; Zeng, An

2015-01-01

The rapid expansion of Internet brings us overwhelming online information, which is impossible for an individual to go through all of it. Therefore, recommender systems were created to help people dig through this abundance of information. In networks composed by users and objects, recommender algorithms based on diffusion have been proven to be one of the best performing methods. Previous works considered the diffusion process from user to object, and from object to user to be equivalent. We show in this work that it is not the case and we improve the quality of the recommendation by taking into account the asymmetrical nature of this process. We apply this idea to modify the state-of-the-art recommendation methods. The simulation results show that the new methods can outperform these existing methods in both recommendation accuracy and diversity. Finally, this modification is checked to be able to improve the recommendation in a realistic case. PMID:26125631

Information Filtering via Heterogeneous Diffusion in Online Bipartite Networks.

PubMed

Zhang, Fu-Guo; Zeng, An

2015-01-01

The rapid expansion of Internet brings us overwhelming online information, which is impossible for an individual to go through all of it. Therefore, recommender systems were created to help people dig through this abundance of information. In networks composed by users and objects, recommender algorithms based on diffusion have been proven to be one of the best performing methods. Previous works considered the diffusion process from user to object, and from object to user to be equivalent. We show in this work that it is not the case and we improve the quality of the recommendation by taking into account the asymmetrical nature of this process. We apply this idea to modify the state-of-the-art recommendation methods. The simulation results show that the new methods can outperform these existing methods in both recommendation accuracy and diversity. Finally, this modification is checked to be able to improve the recommendation in a realistic case.

The "Golden Projects": China's National Networking Initiative.

ERIC Educational Resources Information Center

Lovelock, Peter; Clark, Theodore C.; Petrazzini, Ben A.

1996-01-01

For China, information technology and communications networks are a new solution to an old problem, reconstituting hierarchical state power. This article examines China's National Networking Initiative, "Golden Projects," within the context of economic and political reform to demonstrate an alternative to traditional economic based…

Passivity analysis for uncertain BAM neural networks with time delays and reaction-diffusions

NASA Astrophysics Data System (ADS)

Zhou, Jianping; Xu, Shengyuan; Shen, Hao; Zhang, Baoyong

2013-08-01

This article deals with the problem of passivity analysis for delayed reaction-diffusion bidirectional associative memory (BAM) neural networks with weight uncertainties. By using a new integral inequality, we first present a passivity condition for the nominal networks, and then extend the result to the case with linear fractional weight uncertainties. The proposed conditions are expressed in terms of linear matrix inequalities, and thus can be checked easily. Examples are provided to demonstrate the effectiveness of the proposed results.

Suppressing disease spreading by using information diffusion on multiplex networks.

PubMed

Wang, Wei; Liu, Quan-Hui; Cai, Shi-Min; Tang, Ming; Braunstein, Lidia A; Stanley, H Eugene

2016-07-06

Although there is always an interplay between the dynamics of information diffusion and disease spreading, the empirical research on the systemic coevolution mechanisms connecting these two spreading dynamics is still lacking. Here we investigate the coevolution mechanisms and dynamics between information and disease spreading by utilizing real data and a proposed spreading model on multiplex network. Our empirical analysis finds asymmetrical interactions between the information and disease spreading dynamics. Our results obtained from both the theoretical framework and extensive stochastic numerical simulations suggest that an information outbreak can be triggered in a communication network by its own spreading dynamics or by a disease outbreak on a contact network, but that the disease threshold is not affected by information spreading. Our key finding is that there is an optimal information transmission rate that markedly suppresses the disease spreading. We find that the time evolution of the dynamics in the proposed model qualitatively agrees with the real-world spreading processes at the optimal information transmission rate.

A National Perspective on Women Owning Woodlands (WOW) Networks

ERIC Educational Resources Information Center

Huff, Emily S.

2017-01-01

This article provides a national overview of women owning woodlands (WOW) networks and the barriers and successes they encounter. Qualitative interview data with key network leaders were used for increasing understanding of how these networks operate. Network leaders were all connected professionally, and all successful WOW networks involved…

Comprehensive model-based prediction of micropollutants from diffuse sources in the Swiss river network

NASA Astrophysics Data System (ADS)

Strahm, Ivo; Munz, Nicole; Braun, Christian; Gälli, René; Leu, Christian; Stamm, Christian

2014-05-01

Water quality in the Swiss river network is affected by many micropollutants from a variety of diffuse sources. This study compares, for the first time, in a comprehensive manner the diffuse sources and the substance groups that contribute the most to water contamination in Swiss streams and highlights the major regions for water pollution. For this a simple but comprehensive model was developed to estimate emission from diffuse sources for the entire Swiss river network of 65 000 km. Based on emission factors the model calculates catchment specific losses to streams for more than 15 diffuse sources (such as crop lands, grassland, vineyards, fruit orchards, roads, railways, facades, roofs, green space in urban areas, landfills, etc.) and more than 130 different substances from 5 different substance groups (pesticides, biocides, heavy metals, human drugs, animal drugs). For more than 180 000 stream sections estimates of mean annual pollutant loads and mean annual concentration levels were modeled. This data was validated with a set of monitoring data and evaluated based on annual average environmental quality standards (AA-EQS). Model validation showed that the estimated mean annual concentration levels are within the range of measured data. Therefore simulations were considered as adequately robust for identifying the major sources of diffuse pollution. The analysis depicted that in Switzerland widespread pollution of streams can be expected. Along more than 18 000 km of the river network one or more simulated substances has a concentration exceeding the AA-EQS. In single stream sections it could be more than 50 different substances. Moreover, the simulations showed that in two-thirds of small streams (Strahler order 1 and 2) at least one AA-EQS is always exceeded. The highest number of substances exceeding the AA-EQS are in areas with large fractions of arable cropping, vineyards and fruit orchards. Urban areas are also of concern even without considering

Delay-induced Turing-like waves for one-species reaction-diffusion model on a network

NASA Astrophysics Data System (ADS)

Petit, Julien; Carletti, Timoteo; Asllani, Malbor; Fanelli, Duccio

2015-09-01

A one-species time-delay reaction-diffusion system defined on a complex network is studied. Traveling waves are predicted to occur following a symmetry-breaking instability of a homogeneous stationary stable solution, subject to an external nonhomogeneous perturbation. These are generalized Turing-like waves that materialize in a single-species populations dynamics model, as the unexpected byproduct of the imposed delay in the diffusion part. Sufficient conditions for the onset of the instability are mathematically provided by performing a linear stability analysis adapted to time-delayed differential equations. The method here developed exploits the properties of the Lambert W-function. The prediction of the theory are confirmed by direct numerical simulation carried out for a modified version of the classical Fisher model, defined on a Watts-Strogatz network and with the inclusion of the delay.

Probabilistic diffusion tractography reveals improvement of structural network in musicians.

PubMed

Li, Jianfu; Luo, Cheng; Peng, Yueheng; Xie, Qiankun; Gong, Jinnan; Dong, Li; Lai, Yongxiu; Li, Hong; Yao, Dezhong

2014-01-01

Musicians experience a large amount of information transfer and integration of complex sensory, motor, and auditory processes when training and playing musical instruments. Therefore, musicians are a useful model in which to investigate neural adaptations in the brain. Here, based on diffusion-weighted imaging, probabilistic tractography was used to determine the architecture of white matter anatomical networks in musicians and non-musicians. Furthermore, the features of the white matter networks were analyzed using graph theory. Small-world properties of the white matter network were observed in both groups. Compared with non-musicians, the musicians exhibited significantly increased connectivity strength in the left and right supplementary motor areas, the left calcarine fissure and surrounding cortex and the right caudate nucleus, as well as a significantly larger weighted clustering coefficient in the right olfactory cortex, the left medial superior frontal gyrus, the right gyrus rectus, the left lingual gyrus, the left supramarginal gyrus, and the right pallidum. Furthermore, there were differences in the node betweenness centrality in several regions. However, no significant differences in topological properties were observed at a global level. We illustrated preliminary findings to extend the network level understanding of white matter plasticity in musicians who have had long-term musical training. These structural, network-based findings may indicate that musicians have enhanced information transmission efficiencies in local white matter networks that are related to musical training.

EduOpen: Italian Network for MOOCs, First Three Months Evaluation after Initiation

ERIC Educational Resources Information Center

Rui, Marina

2016-01-01

EduOpen is an Italian national network devoted to foster the MOOCs diffusion, not just another national provider, being mainly focused to intervene in some crucial fields such as: educational innovation, internationalization strategy, educational research on OER in order to build up some strategy of diffusion and also to make an effort of training…

Program Spotlight: National Outreach Network's Community Health Educators

Cancer.gov

National Outreach Network of Community Health Educators located at Community Network Program Centers, Partnerships to Advance Cancer Health Equity, and NCI-designated cancer centers help patients and their families receive survivorship support.

National Seismic Network of Georgia

NASA Astrophysics Data System (ADS)

Tumanova, N.; Kakhoberashvili, S.; Omarashvili, V.; Tserodze, M.; Akubardia, D.

2016-12-01

Georgia, as a part of the Southern Caucasus, is tectonically active and structurally complex region. It is one of the most active segments of the Alpine-Himalayan collision belt. The deformation and the associated seismicity are due to the continent-continent collision between the Arabian and Eurasian plates. Seismic Monitoring of country and the quality of seismic data is the major tool for the rapid response policy, population safety, basic scientific research and in the end for the sustainable development of the country. National Seismic Network of Georgia has been developing since the end of 19th century. Digital era of the network started from 2003. Recently continuous data streams from 25 stations acquired and analyzed in the real time. Data is combined to calculate rapid location and magnitude for the earthquake. Information for the bigger events (Ml>=3.5) is simultaneously transferred to the website of the monitoring center and to the related governmental agencies. To improve rapid earthquake location and magnitude estimation the seismic network was enhanced by installing additional 7 new stations. Each new station is equipped with coupled Broadband and Strong Motion seismometers and permanent GPS system as well. To select the sites for the 7 new base stations, we used standard network optimization techniques. To choose the optimal sites for new stations we've taken into account geometry of the existed seismic network, topographic conditions of the site. For each site we studied local geology (Vs30 was mandatory for each site), local noise level and seismic vault construction parameters. Due to the country elevation, stations were installed in the high mountains, no accessible in winter due to the heavy snow conditions. To secure online data transmission we used satellite data transmission as well as cell data network coverage from the different local companies. As a result we've already have the improved earthquake location and event magnitudes. We

Confinement regulates complex biochemical networks: initiation of blood clotting by "diffusion acting".

PubMed

Shen, Feng; Pompano, Rebecca R; Kastrup, Christian J; Ismagilov, Rustem F

2009-10-21

This study shows that environmental confinement strongly affects the activation of nonlinear reaction networks, such as blood coagulation (clotting), by small quantities of activators. Blood coagulation is sensitive to the local concentration of soluble activators, initiating only when the activators surpass a threshold concentration, and therefore is regulated by mass transport phenomena such as flow and diffusion. Here, diffusion was limited by decreasing the size of microfluidic chambers, and it was found that microparticles carrying either the classical stimulus, tissue factor, or a bacterial stimulus, Bacillus cereus, initiated coagulation of human platelet-poor plasma only when confined. A simple analytical argument and numerical model were used to describe the mechanism for this phenomenon: confinement causes diffusible activators to accumulate locally and surpass the threshold concentration. To interpret the results, a dimensionless confinement number, Cn, was used to describe whether a stimulus was confined, and a Damköhler number, Da(2), was used to describe whether a subthreshold stimulus could initiate coagulation. In the context of initiation of coagulation by bacteria, this mechanism can be thought of as "diffusion acting", which is distinct from "diffusion sensing". The ability of confinement and diffusion acting to change the outcome of coagulation suggests that confinement should also regulate other biological "on" and "off" processes that are controlled by thresholds.

National Stream Quality Accounting Network and National Monitoring Network Basin Boundary Geospatial Dataset, 2008–13

USGS Publications Warehouse

Baker, Nancy T.

2011-01-01

This report and the accompanying geospatial data were created to assist in analysis and interpretation of water-quality data provided by the U.S. Geological Survey's National Stream Quality Accounting Network (NASQAN) and by the U.S. Coastal Waters and Tributaries National Monitoring Network (NMN), which is a cooperative monitoring program of Federal, regional, and State agencies. The report describes the methods used to develop the geospatial data, which was primarily derived from the National Watershed Boundary Dataset. The geospatial data contains polygon shapefiles of basin boundaries for 33 NASQAN and 5 NMN streamflow and water-quality monitoring stations. In addition, 30 polygon shapefiles of the closed and noncontributing basins contained within the NASQAN or NMN boundaries are included. Also included is a point shapefile of the NASQAN and NMN monitoring stations and associated basin and station attributes. Geospatial data for basin delineations, associated closed and noncontributing basins, and monitoring station locations are available at http://water.usgs.gov/GIS/metadata/usgswrd/XML/ds641_nasqan_wbd12.xml.

Mention effect in information diffusion on a micro-blogging network

PubMed Central

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

2018-01-01

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

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

PubMed

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

2018-01-01

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

34 CFR 412.4 - What is the National Network of Directors Council?

Code of Federal Regulations, 2010 CFR

2010-07-01

... 34 Education 3 2010-07-01 2010-07-01 false What is the National Network of Directors Council? 412...) OFFICE OF VOCATIONAL AND ADULT EDUCATION, DEPARTMENT OF EDUCATION NATIONAL NETWORK FOR CURRICULUM COORDINATION IN VOCATIONAL AND TECHNICAL EDUCATION General § 412.4 What is the National Network of Directors...

34 CFR 412.4 - What is the National Network of Directors Council?

Code of Federal Regulations, 2011 CFR

2011-07-01

... 34 Education 3 2011-07-01 2011-07-01 false What is the National Network of Directors Council? 412...) OFFICE OF VOCATIONAL AND ADULT EDUCATION, DEPARTMENT OF EDUCATION NATIONAL NETWORK FOR CURRICULUM COORDINATION IN VOCATIONAL AND TECHNICAL EDUCATION General § 412.4 What is the National Network of Directors...

Critical regimes driven by recurrent mobility patterns of reaction-diffusion processes in networks

NASA Astrophysics Data System (ADS)

Gómez-Gardeñes, J.; Soriano-Paños, D.; Arenas, A.

2018-04-01

Reaction-diffusion processes1 have been widely used to study dynamical processes in epidemics2-4 and ecology5 in networked metapopulations. In the context of epidemics6, reaction processes are understood as contagions within each subpopulation (patch), while diffusion represents the mobility of individuals between patches. Recently, the characteristics of human mobility7, such as its recurrent nature, have been proven crucial to understand the phase transition to endemic epidemic states8,9. Here, by developing a framework able to cope with the elementary epidemic processes, the spatial distribution of populations and the commuting mobility patterns, we discover three different critical regimes of the epidemic incidence as a function of these parameters. Interestingly, we reveal a regime of the reaction-diffussion process in which, counter-intuitively, mobility is detrimental to the spread of disease. We analytically determine the precise conditions for the emergence of any of the three possible critical regimes in real and synthetic networks.

Modelling of information diffusion on social networks with applications to WeChat

NASA Astrophysics Data System (ADS)

Liu, Liang; Qu, Bo; Chen, Bin; Hanjalic, Alan; Wang, Huijuan

2018-04-01

Traces of user activities recorded in online social networks open new possibilities to systematically understand the information diffusion process on social networks. From the online social network WeChat, we collected a large number of information cascade trees, each of which tells the spreading trajectory of a message/information such as which user creates the information and which users view or forward the information shared by which neighbours. In this work, we propose two heterogeneous non-linear models, one for the topologies of the information cascade trees and the other for the stochastic process of information diffusion on a social network. Both models are validated by the WeChat data in reproducing and explaining key features of cascade trees. Specifically, we apply the Random Recursive Tree (RRT) to model the growth of cascade trees. The RRT model could capture key features, i.e. the average path length and degree variance of a cascade tree in relation to the number of nodes (size) of the tree. Its single identified parameter quantifies the relative depth or broadness of the cascade trees and indicates that information propagates via a star-like broadcasting or viral-like hop by hop spreading. The RRT model explains the appearance of hubs, thus a possibly smaller average path length as the cascade size increases, as observed in WeChat. We further propose the stochastic Susceptible View Forward Removed (SVFR) model to depict the dynamic user behaviour including creating, viewing, forwarding and ignoring a message on a given social network. Beside the average path length and degree variance of the cascade trees in relation to their sizes, the SVFR model could further explain the power-law cascade size distribution in WeChat and unravel that a user with a large number of friends may actually have a smaller probability to read a message (s)he receives due to limited attention.

Prevalence and test characteristics of national health safety network ventilator-associated events.

PubMed

Lilly, Craig M; Landry, Karen E; Sood, Rahul N; Dunnington, Cheryl H; Ellison, Richard T; Bagley, Peter H; Baker, Stephen P; Cody, Shawn; Irwin, Richard S

2014-09-01

The primary aim of the study was to measure the test characteristics of the National Health Safety Network ventilator-associated event/ventilator-associated condition constructs for detecting ventilator-associated pneumonia. Its secondary aims were to report the clinical features of patients with National Health Safety Network ventilator-associated event/ventilator-associated condition, measure costs of surveillance, and its susceptibility to manipulation. Prospective cohort study. Two inpatient campuses of an academic medical center. Eight thousand four hundred eight mechanically ventilated adults discharged from an ICU. None. The National Health Safety Network ventilator-associated event/ventilator-associated condition constructs detected less than a third of ventilator-associated pneumonia cases with a sensitivity of 0.325 and a positive predictive value of 0.07. Most National Health Safety Network ventilator-associated event/ventilator-associated condition cases (93%) did not have ventilator-associated pneumonia or other hospital-acquired complications; 71% met the definition for acute respiratory distress syndrome. Similarly, most patients with National Health Safety Network probable ventilator-associated pneumonia did not have ventilator-associated pneumonia because radiographic criteria were not met. National Health Safety Network ventilator-associated event/ventilator-associated condition rates were reduced 93% by an unsophisticated manipulation of ventilator management protocols. The National Health Safety Network ventilator-associated event/ventilator-associated condition constructs failed to detect many patients who had ventilator-associated pneumonia, detected many cases that did not have a hospital complication, and were susceptible to manipulation. National Health Safety Network ventilator-associated event/ventilator-associated condition surveillance did not perform as well as ventilator-associated pneumonia surveillance and had several undesirable

A National Strategy for Civic Networking: A Vision of Change.

ERIC Educational Resources Information Center

Civille, Richard

1993-01-01

Presents a vision and a national strategy for civic networking based on the development of the National Information Infrastructure. Topics addressed include a public interest communications policy; benefits of civic networking, including improving services and reducing government costs, reducing poverty and health care costs, and improving…

77 FR 33229 - Notice of Proposed Information Collection: Comment Request; National Resource Network

Federal Register 2010, 2011, 2012, 2013, 2014

2012-06-05

... Information Collection: Comment Request; National Resource Network AGENCY: Office of the Assistant Secretary... information: Title of Proposal: National Resource Network. OMB Control Number, if applicable: None... and reporting information related to the proposed National Resource Network. The U.S. Department of...

78 FR 8686 - Establishment of the National Freight Network

Federal Register 2010, 2011, 2012, 2013, 2014

2013-02-06

... Network AGENCY: Federal Highway Administration (FHWA), DOT. ACTION: Notice. SUMMARY: This notice defines the planned process for the designation of the national freight network as required by Section 1115 of... the initial designation of the primary freight network, the designation of additional miles critical...

Privacy Issues of a National Research and Education Network.

ERIC Educational Resources Information Center

Katz, James E.; Graveman, Richard F.

1991-01-01

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

Diffusion with social reinforcement: The role of individual preferences

NASA Astrophysics Data System (ADS)

Tur, Elena M.; Zeppini, Paolo; Frenken, Koen

2018-02-01

The debate on diffusion in social networks has traditionally focused on the structure of the network to understand the efficiency of a network in terms of diffusion. Recently, the role of social reinforcement has been added to the debate, as it has been proposed that simple contagions diffuse better in random networks and complex contagions diffuse better in regular networks. In this paper, we show that individual preferences cannot be overlooked: complex contagions diffuse better in regular networks only if the large majority of the population is biased against adoption.

76 FR 38124 - Applications for New Awards; Americans With Disabilities Act (ADA) National Network Regional...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-06-29

...) National Network Regional Centers and ADA National Network Collaborative Research Projects AGENCY: Office... National Network Regional Centers (formerly the Disability Business Technical Assistance Centers (DBTACs), and ADA National Network Collaborative Research Projects. Notice inviting applications for new awards...

Finite-time robust passive control for a class of switched reaction-diffusion stochastic complex dynamical networks with coupling delays and impulsive control

NASA Astrophysics Data System (ADS)

Syed Ali, M.; Yogambigai, J.; Kwon, O. M.

2018-03-01

Finite-time boundedness and finite-time passivity for a class of switched stochastic complex dynamical networks (CDNs) with coupling delays, parameter uncertainties, reaction-diffusion term and impulsive control are studied. Novel finite-time synchronisation criteria are derived based on passivity theory. This paper proposes a CDN consisting of N linearly and diffusively coupled identical reaction- diffusion neural networks. By constructing of a suitable Lyapunov-Krasovskii's functional and utilisation of Jensen's inequality and Wirtinger's inequality, new finite-time passivity criteria for the networks are established in terms of linear matrix inequalities (LMIs), which can be checked numerically using the effective LMI toolbox in MATLAB. Finally, two interesting numerical examples are given to show the effectiveness of the theoretical results.

Neural connections foster social connections: a diffusion-weighted imaging study of social networks

PubMed Central

Hampton, William H.; Unger, Ashley; Von Der Heide, Rebecca J.

2016-01-01

Although we know the transition from childhood to adulthood is marked by important social and neural development, little is known about how social network size might affect neurocognitive development or vice versa. Neuroimaging research has identified several brain regions, such as the amygdala, as key to this affiliative behavior. However, white matter connectivity among these regions, and its behavioral correlates, remain unclear. Here we tested two hypotheses: that an amygdalocentric structural white matter network governs social affiliative behavior and that this network changes during adolescence and young adulthood. We measured social network size behaviorally, and white matter microstructure using probabilistic diffusion tensor imaging in a sample of neurologically normal adolescents and young adults. Our results suggest amygdala white matter microstructure is key to understanding individual differences in social network size, with connectivity to other social brain regions such as the orbitofrontal cortex and anterior temporal lobe predicting much variation. In addition, participant age correlated with both network size and white matter variation in this network. These findings suggest the transition to adulthood may constitute a critical period for the optimization of structural brain networks underlying affiliative behavior. PMID:26755769

A longitudinal study of organizational formation, innovation adoption, and dissemination activities within the National Drug Abuse Treatment Clinical Trials Network

PubMed Central

Roman, Paul M.; Abraham, Amanda J.; Rothrauff, Tanja C.; Knudsen, Hannah K.

2010-01-01

The National Institute on Drug Abuse (NIDA) established the National Drug Abuse Treatment Clinical Trials Network (CTN) to conduct trials of promising substance abuse treatment interventions in diverse clinical settings and to disseminate results of these trials. This paper focuses on three dimensions of the CTN’s organizational functioning. First, a longitudinal dataset is used to examine the CTN’s formation as a network of inter-organizational interaction among treatment practitioners and researchers. Data indicate strong relationships of interaction and trust, but a decline in problem-centered inter-organizational interaction over time. Second, adoption of buprenorphine and motivational incentives among the CTN’s affiliated CTPs is identified over three waves of data. While adoption is found to increase with CTPs’ CTN participation, there is only modest evidence of widespread penetration and implementation. Third, CTPs’ pursuit of the CTN’s dissemination goals are examined, indicating that such organizational outreach activities are underway and likely to increase innovation diffusion in the future. PMID:20307795

A longitudinal study of organizational formation, innovation adoption, and dissemination activities within the National Drug Abuse Treatment Clinical Trials Network.

PubMed

Roman, Paul M; Abraham, Amanda J; Rothrauff, Tanja C; Knudsen, Hannah K

2010-06-01

The National Institute on Drug Abuse established the National Drug Abuse Treatment Clinical Trials Network (CTN) to conduct trials of promising substance abuse treatment interventions in diverse clinical settings and to disseminate results of these trials. This article focuses on three dimensions of CTN's organizational functioning. First, a longitudinal dataset is used to examine CTN's formation as a network of interorganizational interaction among treatment practitioners and researchers. Data indicate strong relationships of interaction and trust, but a decline in problem-centered interorganizational interaction over time. Second, adoption of buprenorphine and motivational incentives among CTN's affiliated community treatment programs (CTPs) is examined over three waves of data. Although adoption is found to increase with CTPs' CTN participation, there is only modest evidence of widespread penetration and implementation. Third, CTPs' pursuit of the CTN's dissemination goals are examined, indicating that such organizational outreach activities are underway and likely to increase innovation diffusion in the future.

"Getting Practical" and the National Network of Science Learning Centres

ERIC Educational Resources Information Center

Chapman, Georgina; Langley, Mark; Skilling, Gus; Walker, John

2011-01-01

The national network of Science Learning Centres is a co-ordinating partner in the Getting Practical--Improving Practical Work in Science programme. The principle of training provision for the "Getting Practical" programme is a cascade model. Regional trainers employed by the national network of Science Learning Centres trained the cohort of local…

Confinement and diffusion modulate bistability and stochastic switching in a reaction network with positive feedback

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

Mlynarczyk, Paul J.; Pullen, Robert H.; Abel, Steven M., E-mail: abel@utk.edu

2016-01-07

Positive feedback is a common feature in signal transduction networks and can lead to phenomena such as bistability and signal propagation by domain growth. Physical features of the cellular environment, such as spatial confinement and the mobility of proteins, play important but inadequately understood roles in shaping the behavior of signaling networks. Here, we use stochastic, spatially resolved kinetic Monte Carlo simulations to explore a positive feedback network as a function of system size, system shape, and mobility of molecules. We show that these physical properties can markedly alter characteristics of bistability and stochastic switching when compared with well-mixed simulations.more » Notably, systems of equal volume but different shapes can exhibit qualitatively different behaviors under otherwise identical conditions. We show that stochastic switching to a state maintained by positive feedback occurs by cluster formation and growth. Additionally, the frequency at which switching occurs depends nontrivially on the diffusion coefficient, which can promote or suppress switching relative to the well-mixed limit. Taken together, the results provide a framework for understanding how confinement and protein mobility influence emergent features of the positive feedback network by modulating molecular concentrations, diffusion-influenced rate parameters, and spatiotemporal correlations between molecules.« less

Bulgarian National Digital Seismological Network

NASA Astrophysics Data System (ADS)

Dimitrova, L.; Solakov, D.; Nikolova, S.; Stoyanov, S.; Simeonova, S.; Zimakov, L. G.; Khaikin, L.

2011-12-01

The Bulgarian National Digital Seismological Network (BNDSN) consists of a National Data Center (NDC), 13 stations equipped with RefTek High Resolution Broadband Seismic Recorders - model DAS 130-01/3, 1 station equipped with Quanterra 680 and broadband sensors and accelerometers. Real-time data transfer from seismic stations to NDC is realized via Virtual Private Network of the Bulgarian Telecommunication Company. The communication interruptions don't cause any data loss at the NDC. The data are backed up in the field station recorder's 4Mb RAM memory and are retransmitted to the NDC immediately after the communication link is re-established. The recorders are equipped with 2 compact flash disks able to save more than 1 month long data. The data from the flash disks can be downloaded remotely using FTP. The data acquisition and processing hardware redundancy at the NDC is achieved by two clustered SUN servers and two Blade Workstations. To secure the acquisition, processing and data storage processes a three layer local network is designed at the NDC. Real-time data acquisition is performed using REFTEK's full duplex error-correction protocol RTPD. Data from the Quanterra recorder and foreign stations are fed into RTPD in real-time via SeisComP/SeedLink protocol. Using SeisComP/SeedLink software the NDC transfers real-time data to INGV-Roma, NEIC-USA, ORFEUS Data Center. Regional real-time data exchange with Romania, Macedonia, Serbia and Greece is established at the NDC also. Data processing is performed by the Seismic Network Data Processor (SNDP) software package running on the both Servers. SNDP includes subsystems: Real-time subsystem (RTS_SNDP) - for signal detection; evaluation of the signal parameters; phase identification and association; source estimation; Seismic analysis subsystem (SAS_SNDP) - for interactive data processing; Early warning subsystem (EWS_SNDP) - based on the first arrived P-phases. The signal detection process is performed by

Confinement Regulates Complex Biochemical Networks: Initiation of Blood Clotting by “Diffusion Acting”

PubMed Central

Shen, Feng; Pompano, Rebecca R.; Kastrup, Christian J.; Ismagilov, Rustem F.

2009-01-01

Abstract This study shows that environmental confinement strongly affects the activation of nonlinear reaction networks, such as blood coagulation (clotting), by small quantities of activators. Blood coagulation is sensitive to the local concentration of soluble activators, initiating only when the activators surpass a threshold concentration, and therefore is regulated by mass transport phenomena such as flow and diffusion. Here, diffusion was limited by decreasing the size of microfluidic chambers, and it was found that microparticles carrying either the classical stimulus, tissue factor, or a bacterial stimulus, Bacillus cereus, initiated coagulation of human platelet-poor plasma only when confined. A simple analytical argument and numerical model were used to describe the mechanism for this phenomenon: confinement causes diffusible activators to accumulate locally and surpass the threshold concentration. To interpret the results, a dimensionless confinement number, Cn, was used to describe whether a stimulus was confined, and a Damköhler number, Da2, was used to describe whether a subthreshold stimulus could initiate coagulation. In the context of initiation of coagulation by bacteria, this mechanism can be thought of as “diffusion acting”, which is distinct from “diffusion sensing”. The ability of confinement and diffusion acting to change the outcome of coagulation suggests that confinement should also regulate other biological “on” and “off” processes that are controlled by thresholds. PMID:19843446

European national healthy city networks: the impact of an elite epistemic community.

PubMed

Heritage, Zoë; Green, Geoff

2013-10-01

National healthy cities networks (NNs) were created 20 years ago to support the development of healthy cities within the WHO Europe Region. Using the concept of epistemic communities, the evolution and impact of NNs is considered, as is their future development. Healthy cities national networks are providing information, training and support to member cities. In many cases, they are also involved in supporting national public health policy development and disseminating out healthy city principles to other local authorities. National networks are a fragile but an extremely valuable resource for sharing public health knowledge.

A trust-based recommendation method using network diffusion processes

NASA Astrophysics Data System (ADS)

Chen, Ling-Jiao; Gao, Jian

2018-09-01

A variety of rating-based recommendation methods have been extensively studied including the well-known collaborative filtering approaches and some network diffusion-based methods, however, social trust relations are not sufficiently considered when making recommendations. In this paper, we contribute to the literature by proposing a trust-based recommendation method, named CosRA+T, after integrating the information of trust relations into the resource-redistribution process. Specifically, a tunable parameter is used to scale the resources received by trusted users before the redistribution back to the objects. Interestingly, we find an optimal scaling parameter for the proposed CosRA+T method to achieve its best recommendation accuracy, and the optimal value seems to be universal under several evaluation metrics across different datasets. Moreover, results of extensive experiments on the two real-world rating datasets with trust relations, Epinions and FriendFeed, suggest that CosRA+T has a remarkable improvement in overall accuracy, diversity and novelty. Our work takes a step towards designing better recommendation algorithms by employing multiple resources of social network information.

A reaction-diffusion-based coding rate control mechanism for camera sensor networks.

PubMed

Yamamoto, Hiroshi; Hyodo, Katsuya; Wakamiya, Naoki; Murata, Masayuki

2010-01-01

A wireless camera sensor network is useful for surveillance and monitoring for its visibility and easy deployment. However, it suffers from the limited capacity of wireless communication and a network is easily overflown with a considerable amount of video traffic. In this paper, we propose an autonomous video coding rate control mechanism where each camera sensor node can autonomously determine its coding rate in accordance with the location and velocity of target objects. For this purpose, we adopted a biological model, i.e., reaction-diffusion model, inspired by the similarity of biological spatial patterns and the spatial distribution of video coding rate. Through simulation and practical experiments, we verify the effectiveness of our proposal.

Inhibiting diffusion of complex contagions in social networks: theoretical and experimental results

PubMed Central

Anil Kumar, V.S.; Marathe, Madhav V.; Ravi, S.S.; Rosenkrantz, Daniel J.

2014-01-01

We consider the problem of inhibiting undesirable contagions (e.g. rumors, spread of mob behavior) in social networks. Much of the work in this context has been carried out under the 1-threshold model, where diffusion occurs when a node has just one neighbor with the contagion. We study the problem of inhibiting more complex contagions in social networks where nodes may have thresholds larger than 1. The goal is to minimize the propagation of the contagion by removing a small number of nodes (called critical nodes) from the network. We study several versions of this problem and prove that, in general, they cannot even be efficiently approximated to within any factor ρ ≥ 1, unless P = NP. We develop efficient and practical heuristics for these problems and carry out an experimental study of their performance on three well known social networks, namely epinions, wikipedia and slashdot. Our results show that these heuristics perform significantly better than five other known methods. We also establish an efficiently computable upper bound on the number of nodes to which a contagion can spread and evaluate this bound on many real and synthetic networks. PMID:25750583

Mean field approximation for biased diffusion on Japanese inter-firm trading network.

PubMed

Watanabe, Hayafumi

2014-01-01

By analysing the financial data of firms across Japan, a nonlinear power law with an exponent of 1.3 was observed between the number of business partners (i.e. the degree of the inter-firm trading network) and sales. In a previous study using numerical simulations, we found that this scaling can be explained by both the money-transport model, where a firm (i.e. customer) distributes money to its out-edges (suppliers) in proportion to the in-degree of destinations, and by the correlations among the Japanese inter-firm trading network. However, in this previous study, we could not specifically identify what types of structure properties (or correlations) of the network determine the 1.3 exponent. In the present study, we more clearly elucidate the relationship between this nonlinear scaling and the network structure by applying mean-field approximation of the diffusion in a complex network to this money-transport model. Using theoretical analysis, we obtained the mean-field solution of the model and found that, in the case of the Japanese firms, the scaling exponent of 1.3 can be determined from the power law of the average degree of the nearest neighbours of the network with an exponent of -0.7.

Cord blood banking in France: reorganising the national network.

PubMed

Katz, Gregory; Mills, Antonia

2010-06-01

Paradoxically, France is one of the leading exporters of cord blood units worldwide, but ranks only 17th in terms of cord blood units per inhabitant, and imports 64% of cord blood grafts to meet national transplantation demands. With three operational banks in 2008, the French allogeneic cord blood network is now entering an important phase of development with the creation of seven new banks collecting from local clusters of maternities. Although the French network of public banks is demonstrating a strong commitment to reorganise and scale up its activities, the revision of France's bioethics law in 2010 has sparked a debate concerning the legalisation of commercial autologous banking. The paper discusses key elements for a comprehensive national plan that would strengthen the allogeneic banking network through which France could meet its national medical needs and guarantee equal access to healthcare. Copyright 2010. Published by Elsevier Ltd.

The impact of capacity growth in national telecommunications networks.

PubMed

Lord, Andrew; Soppera, Andrea; Jacquet, Arnaud

2016-03-06

This paper discusses both UK-based and global Internet data bandwidth growth, beginning with historical data for the BT network. We examine the time variations in consumer behaviour and how this is statistically aggregated into larger traffic loads on national core fibre communications networks. The random nature of consumer Internet behaviour, where very few consumers require maximum bandwidth simultaneously, provides the opportunity for a significant statistical gain. The paper looks at predictions for how this growth might continue over the next 10-20 years, giving estimates for the amount of bandwidth that networks should support in the future. The paper then explains how national networks are designed to accommodate these traffic levels, and the various network roles, including access, metro and core, are described. The physical layer network is put into the context of how the packet and service layers are designed and the applications and location of content are also included in an overall network overview. The specific role of content servers in alleviating core network traffic loads is highlighted. The status of the relevant transmission technologies in the access, metro and core is given, showing that these technologies, with adequate research, should be sufficient to provide bandwidth for consumers in the next 10-20 years. © 2016 The Author(s).

National information network and database system of hazardous waste management in China

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

Ma Hongchang

1996-12-31

Industries in China generate large volumes of hazardous waste, which makes it essential for the nation to pay more attention to hazardous waste management. National laws and regulations, waste surveys, and manifest tracking and permission systems have been initiated. Some centralized hazardous waste disposal facilities are under construction. China`s National Environmental Protection Agency (NEPA) has also obtained valuable information on hazardous waste management from developed countries. To effectively share this information with local environmental protection bureaus, NEPA developed a national information network and database system for hazardous waste management. This information network will have such functions as information collection, inquiry,more » and connection. The long-term objective is to establish and develop a national and local hazardous waste management information network. This network will significantly help decision makers and researchers because it will be easy to obtain information (e.g., experiences of developed countries in hazardous waste management) to enhance hazardous waste management in China. The information network consists of five parts: technology consulting, import-export management, regulation inquiry, waste survey, and literature inquiry.« less

Diffusion-based neuromodulation can eliminate catastrophic forgetting in simple neural networks

PubMed Central

Clune, Jeff

2017-01-01

A long-term goal of AI is to produce agents that can learn a diversity of skills throughout their lifetimes and continuously improve those skills via experience. A longstanding obstacle towards that goal is catastrophic forgetting, which is when learning new information erases previously learned information. Catastrophic forgetting occurs in artificial neural networks (ANNs), which have fueled most recent advances in AI. A recent paper proposed that catastrophic forgetting in ANNs can be reduced by promoting modularity, which can limit forgetting by isolating task information to specific clusters of nodes and connections (functional modules). While the prior work did show that modular ANNs suffered less from catastrophic forgetting, it was not able to produce ANNs that possessed task-specific functional modules, thereby leaving the main theory regarding modularity and forgetting untested. We introduce diffusion-based neuromodulation, which simulates the release of diffusing, neuromodulatory chemicals within an ANN that can modulate (i.e. up or down regulate) learning in a spatial region. On the simple diagnostic problem from the prior work, diffusion-based neuromodulation 1) induces task-specific learning in groups of nodes and connections (task-specific localized learning), which 2) produces functional modules for each subtask, and 3) yields higher performance by eliminating catastrophic forgetting. Overall, our results suggest that diffusion-based neuromodulation promotes task-specific localized learning and functional modularity, which can help solve the challenging, but important problem of catastrophic forgetting. PMID:29145413

Overview of the new National Near-Road Air Quality Monitoring Network

EPA Science Inventory

In 2010, EPA promulgated new National Ambient Air Quality Standards (NAAQS) for nitrogen dioxide (NO2). As part of this new NAAQS, EPA required the establishment of a national near-road air quality monitoring network. This network will consist of one NO2 near-road monitoring st...

"It Takes a Network": Building National Capacity for Climate Change Interpretation

NASA Astrophysics Data System (ADS)

Spitzer, W.

2014-12-01

Since 2007, the New England Aquarium has led a national effort to increase the capacity of informal science venues to effectively communicate about climate change. We are now leading the NSF-funded National Network for Ocean and Climate Change Interpretation (NNOCCI), partnering with the Association of Zoos and Aquariums, FrameWorks Institute, Woods Hole Oceanographic Institution, Monterey Bay Aquarium, and National Aquarium, with evaluation conducted by the New Knowledge Organization, Pennsylvania State University, and Ohio State University. More than 1,500 informal science venues (science centers, museums, aquariums, zoos, nature centers, national parks) are visited annually by 61% of the U.S. population. These visitors expect reliable information about environmental issues and solutions. NNOCCI enables teams of informal science interpreters across the country to serve as "communication strategists" - beyond merely conveying information they can influence public perceptions, given their high level of commitment, knowledge, public trust, social networks, and visitor contact. Beyond providing in-depth training, we have found that our "alumni network" is assuming an increasingly important role in achieving our goals: 1. Ongoing learning - Training must be ongoing given continuous advances in climate and social science research. 2. Implementation support - Social support is critical as interpreters move from learning to practice, given complex and potentially contentious subject matter. 3. Leadership development - We rely on a national cadre of interpretive leaders to conduct workshops, facilitate study circle trainings, and support alumni. 4. Coalition building - A peer network helps to build and maintain connections with colleagues, and supports further dissemination through the informal science community. We are experimenting with a variety of online and face to face strategies to support the growing alumni network. Our goals are to achieve a systemic national

diffuStats: an R package to compute diffusion-based scores on biological networks.

PubMed

Picart-Armada, Sergio; Thompson, Wesley K; Buil, Alfonso; Perera-Lluna, Alexandre

2018-02-01

Label propagation and diffusion over biological networks are a common mathematical formalism in computational biology for giving context to molecular entities and prioritizing novel candidates in the area of study. There are several choices in conceiving the diffusion process-involving the graph kernel, the score definitions and the presence of a posterior statistical normalization-which have an impact on the results. This manuscript describes diffuStats, an R package that provides a collection of graph kernels and diffusion scores, as well as a parallel permutation analysis for the normalized scores, that eases the computation of the scores and their benchmarking for an optimal choice. The R package diffuStats is publicly available in Bioconductor, https://bioconductor.org, under the GPL-3 license. sergi.picart@upc.edu. Supplementary data are available at Bioinformatics online. © The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com

Implementation of the NCI’s National Clinical Trials Network

Cancer.gov

NCI is launching a new clinical trials research network intended to improve treatment for the more than 1.6 million Americans diagnosed with cancer each year. The new system, NCI’s National Clinical Trials Network (NCTN), will facilitate the rapid initia

USA National Phenology Network observational data documentation

USGS Publications Warehouse

Rosemartin, Alyssa H.; Denny, Ellen G.; Gerst, Katharine L.; Marsh, R. Lee; Posthumus, Erin E.; Crimmins, Theresa M.; Weltzin, Jake F.

2018-04-25

The goals of the USA National Phenology Network (USA-NPN, www.usanpn.org) are to advance science, inform decisions, and communicate and connect with the public regarding phenology and species’ responses to environmental variation and climate change. The USA-NPN seeks to advance the science of phenology and facilitate ecosystem stewardship by providing phenological information freely and openly. To accomplish these goals, the USA-NPN National Coordinating Office (NCO) delivers observational data on plant and animal phenology in several formats, including minimally processed status and intensity datasets and derived phenometrics for individual plants, sites, and regions. This document describes the suite of observational data products delivered by the USA National Phenology Network, covering the period 2009–present for the United States and accessible via the Phenology Observation Portal (http://dx.doi.org/10.5066/F78S4N1V) and via an Application Programming Interface. The data described here have been used in diverse research and management applications, including over 30 publications in fields such as remote sensing, plant evolution, and resource management.

Hemispheric Asymmetry of Human Brain Anatomical Network Revealed by Diffusion Tensor Tractography

PubMed Central

Liu, Yaou; Duan, Yunyun; Li, Kuncheng

2015-01-01

The topological architecture of the cerebral anatomical network reflects the structural organization of the human brain. Recently, topological measures based on graph theory have provided new approaches for quantifying large-scale anatomical networks. However, few studies have investigated the hemispheric asymmetries of the human brain from the perspective of the network model, and little is known about the asymmetries of the connection patterns of brain regions, which may reflect the functional integration and interaction between different regions. Here, we utilized diffusion tensor imaging to construct binary anatomical networks for 72 right-handed healthy adult subjects. We established the existence of structural connections between any pair of the 90 cortical and subcortical regions using deterministic tractography. To investigate the hemispheric asymmetries of the brain, statistical analyses were performed to reveal the brain regions with significant differences between bilateral topological properties, such as degree of connectivity, characteristic path length, and betweenness centrality. Furthermore, local structural connections were also investigated to examine the local asymmetries of some specific white matter tracts. From the perspective of both the global and local connection patterns, we identified the brain regions with hemispheric asymmetries. Combined with the previous studies, we suggested that the topological asymmetries in the anatomical network may reflect the functional lateralization of the human brain. PMID:26539535

Bibliographic Services for a National Network.

ERIC Educational Resources Information Center

Avram, Henriette D.; Pulsifer, Josephine S.

The thesis of this paper is that efficient functioning of a network is dependent upon the organization of bibliographic services so that the basic record for each bibliographic item is created once. This record must be minimally capable of serving the needs of libraries, information centers, abstracting and indexing services, and national and…

Spatial spreading of infectious disease via local and national mobility networks in South Korea

NASA Astrophysics Data System (ADS)

Kwon, Okyu; Son, Woo-Sik

2017-12-01

We study the spread of infectious disease based on local- and national-scale mobility networks. We construct a local mobility network using data on urban bus services to estimate local-scale movement of people. We also construct a national mobility network from orientation-destination data of vehicular traffic between highway tollgates to evaluate national-scale movement of people. A metapopulation model is used to simulate the spread of epidemics. Thus, the number of infected people is simulated using a susceptible-infectious-recovered (SIR) model within the administrative division, and inter-division spread of infected people is determined through local and national mobility networks. In this paper, we consider two scenarios for epidemic spread. In the first, the infectious disease only spreads through local-scale movement of people, that is, the local mobility network. In the second, it spreads via both local and national mobility networks. For the former, the simulation results show infected people sequentially spread to neighboring divisions. Yet for the latter, we observe a faster spreading pattern to distant divisions. Thus, we confirm the national mobility network enhances synchronization among the incidence profiles of all administrative divisions.

USA National Phenology Network gridded products documentation

USGS Publications Warehouse

Crimmins, Theresa M.; Marsh, R. Lee; Switzer, Jeff R.; Crimmins, Michael A.; Gerst, Katharine L.; Rosemartin, Alyssa H.; Weltzin, Jake F.

2017-02-23

The goals of the USA National Phenology Network (USA-NPN, www.usanpn.org) are to advance science, inform decisions, and communicate and connect with the public regarding phenology and species’ responses to environmental variation and climate change. The USA-NPN seeks to facilitate informed ecosystem stewardship and management by providing phenological information freely and openly. One way the USA-NPN is endeavoring to accomplish these goals is by providing data and data products in a wide range of formats, including gridded real-time, short-term forecasted, and historical maps of phenological events, patterns and trends. This document describes the suite of gridded phenologically relevant data products produced and provided by the USA National Phenology Network, which can be accessed at www.usanpn.org/data/phenology_maps and also through web services at geoserver.usanpn.org/geoserver/wms?request=GetCapabilities.

78 FR 24154 - Notice of Availability of a National Animal Health Laboratory Network Reorganization Concept Paper

Federal Register 2010, 2011, 2012, 2013, 2014

2013-04-24

...] Notice of Availability of a National Animal Health Laboratory Network Reorganization Concept Paper AGENCY... Network (NAHLN) for public review and comment. The NAHLN is a nationally coordinated network and... Coordinator, National Animal Health Laboratory Network, Veterinary Services, APHIS, 2140 Centre Avenue...

Mittag-Leffler synchronization of fractional neural networks with time-varying delays and reaction-diffusion terms using impulsive and linear controllers.

PubMed

Stamova, Ivanka; Stamov, Gani

2017-12-01

In this paper, we propose a fractional-order neural network system with time-varying delays and reaction-diffusion terms. We first develop a new Mittag-Leffler synchronization strategy for the controlled nodes via impulsive controllers. Using the fractional Lyapunov method sufficient conditions are given. We also study the global Mittag-Leffler synchronization of two identical fractional impulsive reaction-diffusion neural networks using linear controllers, which was an open problem even for integer-order models. Since the Mittag-Leffler stability notion is a generalization of the exponential stability concept for fractional-order systems, our results extend and improve the exponential impulsive control theory of neural network system with time-varying delays and reaction-diffusion terms to the fractional-order case. The fractional-order derivatives allow us to model the long-term memory in the neural networks, and thus the present research provides with a conceptually straightforward mathematical representation of rather complex processes. Illustrative examples are presented to show the validity of the obtained results. We show that by means of appropriate impulsive controllers we can realize the stability goal and to control the qualitative behavior of the states. An image encryption scheme is extended using fractional derivatives. Copyright © 2017 Elsevier Ltd. All rights reserved.

Diffusion of anti-VEGF injections in the Portuguese National Health System

PubMed Central

Marques, Ana Patrícia; Macedo, António Filipe; Perelman, Julian; Aguiar, Pedro; Rocha-Sousa, Amândio; Santana, Rui

2015-01-01

Objectives To analyse the temporal and geographical diffusion of antivascular endothelial growth factor (anti-VEGF) interventions, and its determinants in a National Health System (NHS). Setting NHS Portuguese hospitals. Participants All inpatient and day cases related to eye diseases at all Portuguese public hospitals for the period 2002–2012 were selected on the basis of four International Classification of Diseases 9th revision, Clinical Modification (ICD-9-CM) codes for procedures: 1474, 1475, 1479 and 149. Primary and secondary outcome measures We measured anti-VEGF treatment rates by year and county. The determinants of the geographical diffusion were investigated using generalised linear modelling. Results We analysed all hospital discharges from all NHS hospitals in Portugal (98 408 hospital discharges corresponding to 57 984 patients). National rates of hospitals episodes for the codes for procedures used were low before anti-VEGF approval in 2007 (less than 12% of hospital discharges). Between 2007 and 2012, the rates of hospital episodes related to the introduction of anti-VEGF injections increased by 27% per year. Patients from areas without ophthalmology departments received fewer treatments than those from areas with ophthalmology departments. The availability of an ophthalmology department in the county increased the rates of hospital episodes by 243%, and a 100-persons greater density per km2 raised the rates by 11%. Conclusions Our study shows a large but unequal diffusion of anti-VEGF treatments despite the universal coverage and very low copayments. The technological innovation in ophthalmology may thus produce unexpected inequalities related to financial constraints unless the implementation of innovative techniques is planned and regulated. PMID:26597866

Ant colony clustering with fitness perception and pheromone diffusion for community detection in complex networks

NASA Astrophysics Data System (ADS)

Ji, Junzhong; Song, Xiangjing; Liu, Chunnian; Zhang, Xiuzhen

2013-08-01

Community structure detection in complex networks has been intensively investigated in recent years. In this paper, we propose an adaptive approach based on ant colony clustering to discover communities in a complex network. The focus of the method is the clustering process of an ant colony in a virtual grid, where each ant represents a node in the complex network. During the ant colony search, the method uses a new fitness function to percept local environment and employs a pheromone diffusion model as a global information feedback mechanism to realize information exchange among ants. A significant advantage of our method is that the locations in the grid environment and the connections of the complex network structure are simultaneously taken into account in ants moving. Experimental results on computer-generated and real-world networks show the capability of our method to successfully detect community structures.

Emergent spatial synaptic structure from diffusive plasticity.

PubMed

Sweeney, Yann; Clopath, Claudia

2017-04-01

Some neurotransmitters can diffuse freely across cell membranes, influencing neighbouring neurons regardless of their synaptic coupling. This provides a means of neural communication, alternative to synaptic transmission, which can influence the way in which neural networks process information. Here, we ask whether diffusive neurotransmission can also influence the structure of synaptic connectivity in a network undergoing plasticity. We propose a form of Hebbian synaptic plasticity which is mediated by a diffusive neurotransmitter. Whenever a synapse is modified at an individual neuron through our proposed mechanism, similar but smaller modifications occur in synapses connecting to neighbouring neurons. The effects of this diffusive plasticity are explored in networks of rate-based neurons. This leads to the emergence of spatial structure in the synaptic connectivity of the network. We show that this spatial structure can coexist with other forms of structure in the synaptic connectivity, such as with groups of strongly interconnected neurons that form in response to correlated external drive. Finally, we explore diffusive plasticity in a simple feedforward network model of receptive field development. We show that, as widely observed across sensory cortex, the preferred stimulus identity of neurons in our network become spatially correlated due to diffusion. Our proposed mechanism of diffusive plasticity provides an efficient mechanism for generating these spatial correlations in stimulus preference which can flexibly interact with other forms of synaptic organisation. © 2016 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.

Hopping Diffusion of Nanoparticles in Polymer Matrices

PubMed Central

2016-01-01

We propose a hopping mechanism for diffusion of large nonsticky nanoparticles subjected to topological constraints in both unentangled and entangled polymer solids (networks and gels) and entangled polymer liquids (melts and solutions). Probe particles with size larger than the mesh size ax of unentangled polymer networks or tube diameter ae of entangled polymer liquids are trapped by the network or entanglement cells. At long time scales, however, these particles can diffuse by overcoming free energy barrier between neighboring confinement cells. The terminal particle diffusion coefficient dominated by this hopping diffusion is appreciable for particles with size moderately larger than the network mesh size ax or tube diameter ae. Much larger particles in polymer solids will be permanently trapped by local network cells, whereas they can still move in polymer liquids by waiting for entanglement cells to rearrange on the relaxation time scales of these liquids. Hopping diffusion in entangled polymer liquids and networks has a weaker dependence on particle size than that in unentangled networks as entanglements can slide along chains under polymer deformation. The proposed novel hopping model enables understanding the motion of large nanoparticles in polymeric nanocomposites and the transport of nano drug carriers in complex biological gels such as mucus. PMID:25691803

Estimating National-scale Emissions using Dense Monitoring Networks

NASA Astrophysics Data System (ADS)

Ganesan, A.; Manning, A.; Grant, A.; Young, D.; Oram, D.; Sturges, W. T.; Moncrieff, J. B.; O'Doherty, S.

2014-12-01

The UK's DECC (Deriving Emissions linked to Climate Change) network consists of four greenhouse gas measurement stations that are situated to constrain emissions from the UK and Northwest Europe. These four stations are located in Mace Head (West Coast of Ireland), and on telecommunication towers at Ridge Hill (Western England), Tacolneston (Eastern England) and Angus (Eastern Scotland). With the exception of Angus, which currently only measures carbon dioxide (CO2) and methane (CH4), the remaining sites are additionally equipped to monitor nitrous oxide (N2O). We present an analysis of the network's CH4 and N2O observations from 2011-2013 and compare derived top-down regional emissions with bottom-up inventories, including a recently produced high-resolution inventory (UK National Atmospheric Emissions Inventory). As countries are moving toward national-level emissions estimation, we also address some of the considerations that need to be made when designing these national networks. One of the novel aspects of this work is that we use a hierarchical Bayesian inversion framework. This methodology, which has newly been applied to greenhouse gas emissions estimation, is designed to estimate temporally and spatially varying model-measurement uncertainties and correlation scales, in addition to fluxes. Through this analysis, we demonstrate the importance of characterizing these covariance parameters in order to properly use data from high-density monitoring networks. This UK case study highlights the ways in which this new inverse framework can be used to address some of the limitations of traditional Bayesian inverse methods.

Federated queries of clinical data repositories: Scaling to a national network.

PubMed

Weber, Griffin M

2015-06-01

Federated networks of clinical research data repositories are rapidly growing in size from a handful of sites to true national networks with more than 100 hospitals. This study creates a conceptual framework for predicting how various properties of these systems will scale as they continue to expand. Starting with actual data from Harvard's four-site Shared Health Research Information Network (SHRINE), the framework is used to imagine a future 4000 site network, representing the majority of hospitals in the United States. From this it becomes clear that several common assumptions of small networks fail to scale to a national level, such as all sites being online at all times or containing data from the same date range. On the other hand, a large network enables researchers to select subsets of sites that are most appropriate for particular research questions. Developers of federated clinical data networks should be aware of how the properties of these networks change at different scales and design their software accordingly. Copyright © 2015 Elsevier Inc. All rights reserved.

Systemwide Reform in Districts under Pressure: The Role of Social Networks in Defining, Acquiring, Using, and Diffusing Research Evidence

ERIC Educational Resources Information Center

Finnigan, Kara S.; Daly, Alan J.; Che, Jing

2013-01-01

Purpose: The purpose of this paper is to examine the way in which low-performing schools and their district define, acquire, use, and diffuse research-based evidence. Design/methodology/approach: The mixed methods case study builds upon the prior research on research evidence and social networks, drawing on social network analyses, survey data and…

Study of Li atom diffusion in amorphous Li3PO4 with neural network potential

NASA Astrophysics Data System (ADS)

Li, Wenwen; Ando, Yasunobu; Minamitani, Emi; Watanabe, Satoshi

2017-12-01

To clarify atomic diffusion in amorphous materials, which is important in novel information and energy devices, theoretical methods having both reliability and computational speed are eagerly anticipated. In the present study, we applied neural network (NN) potentials, a recently developed machine learning technique, to the study of atom diffusion in amorphous materials, using Li3PO4 as a benchmark material. The NN potential was used together with the nudged elastic band, kinetic Monte Carlo, and molecular dynamics methods to characterize Li vacancy diffusion behavior in the amorphous Li3PO4 model. By comparing these results with corresponding DFT calculations, we found that the average error of the NN potential is 0.048 eV in calculating energy barriers of diffusion paths, and 0.041 eV in diffusion activation energy. Moreover, the diffusion coefficients obtained from molecular dynamics are always consistent with those from ab initio molecular dynamics simulation, while the computation speed of the NN potential is 3-4 orders of magnitude faster than DFT. Lastly, the structure of amorphous Li3PO4 and the ion transport properties in it were studied with the NN potential using a large supercell model containing more than 1000 atoms. The formation of P2O7 units was observed, which is consistent with the experimental characterization. The Li diffusion activation energy was estimated to be 0.55 eV, which agrees well with the experimental measurements.

Multilevel Deficiency of White Matter Connectivity Networks in Alzheimer's Disease: A Diffusion MRI Study with DTI and HARDI Models.

PubMed

Wang, Tao; Shi, Feng; Jin, Yan; Yap, Pew-Thian; Wee, Chong-Yaw; Zhang, Jianye; Yang, Cece; Li, Xia; Xiao, Shifu; Shen, Dinggang

2016-01-01

Alzheimer's disease (AD) is the most common form of dementia in elderly people. It is an irreversible and progressive brain disease. In this paper, we utilized diffusion-weighted imaging (DWI) to detect abnormal topological organization of white matter (WM) structural networks. We compared the differences between WM connectivity characteristics at global, regional, and local levels in 26 patients with probable AD and 16 normal control (NC) elderly subjects, using connectivity networks constructed with the diffusion tensor imaging (DTI) model and the high angular resolution diffusion imaging (HARDI) model, respectively. At the global level, we found that the WM structural networks of both AD and NC groups had a small-world topology; however, the AD group showed a significant decrease in both global and local efficiency, but an increase in clustering coefficient and the average shortest path length. We further found that the AD patients had significantly decreased nodal efficiency at the regional level, as well as weaker connections in multiple local cortical and subcortical regions, such as precuneus, temporal lobe, hippocampus, and thalamus. The HARDI model was found to be more advantageous than the DTI model, as it was more sensitive to the deficiencies in AD at all of the three levels.

Neurocomputation by Reaction Diffusion

NASA Astrophysics Data System (ADS)

Liang, Ping

1995-08-01

This Letter demonstrates the possible role nonsynaptic diffusion neurotransmission may play in neurocomputation using an artificial neural network model. A reaction-diffusion neural network model with field-based information-processing mechanisms is proposed. The advantages of nonsynaptic field neurotransmission from a computational viewpoint demonstrated in this Letter include long-range inhibition using only local interaction, nonhardwired and changeable (target specific) long-range communication pathways, and multiple simultaneous spatiotemporal organization processes in the same medium.

Multisite concordance of apparent diffusion coefficient measurements across the NCI Quantitative Imaging Network.

PubMed

Newitt, David C; Malyarenko, Dariya; Chenevert, Thomas L; Quarles, C Chad; Bell, Laura; Fedorov, Andriy; Fennessy, Fiona; Jacobs, Michael A; Solaiyappan, Meiyappan; Hectors, Stefanie; Taouli, Bachir; Muzi, Mark; Kinahan, Paul E; Schmainda, Kathleen M; Prah, Melissa A; Taber, Erin N; Kroenke, Christopher; Huang, Wei; Arlinghaus, Lori R; Yankeelov, Thomas E; Cao, Yue; Aryal, Madhava; Yen, Yi-Fen; Kalpathy-Cramer, Jayashree; Shukla-Dave, Amita; Fung, Maggie; Liang, Jiachao; Boss, Michael; Hylton, Nola

2018-01-01

Diffusion weighted MRI has become ubiquitous in many areas of medicine, including cancer diagnosis and treatment response monitoring. Reproducibility of diffusion metrics is essential for their acceptance as quantitative biomarkers in these areas. We examined the variability in the apparent diffusion coefficient (ADC) obtained from both postprocessing software implementations utilized by the NCI Quantitative Imaging Network and online scan time-generated ADC maps. Phantom and in vivo breast studies were evaluated for two ([Formula: see text]) and four ([Formula: see text]) [Formula: see text]-value diffusion metrics. Concordance of the majority of implementations was excellent for both phantom ADC measures and in vivo [Formula: see text], with relative biases [Formula: see text] ([Formula: see text]) and [Formula: see text] (phantom [Formula: see text]) but with higher deviations in ADC at the lowest phantom ADC values. In vivo [Formula: see text] concordance was good, with typical biases of [Formula: see text] to 3% but higher for online maps. Multiple b -value ADC implementations were separated into two groups determined by the fitting algorithm. Intergroup mean ADC differences ranged from negligible for phantom data to 2.8% for [Formula: see text] in vivo data. Some higher deviations were found for individual implementations and online parametric maps. Despite generally good concordance, implementation biases in ADC measures are sometimes significant and may be large enough to be of concern in multisite studies.

The Global Special Operations Forces Network from a Partner-Nation Perspective

DTIC Science & Technology

2014-12-01

in networks vs . management of Networks. ................................80  Figure 17.  A national SOF network with SOCOM as the manager of networks...context and are asked in the natural course of things; there is no predetermination of question topics or wording. 10 descriptive section is the...struggles and challenges that occur naturally over time. As depicted in Figure 2, the network will constantly have to examine how it is evolving and, if

Practical recommendations for strengthening national and regional laboratory networks in Africa in the Global Health Security era.

PubMed

Best, Michele; Sakande, Jean

2016-01-01

The role of national health laboratories in support of public health response has expanded beyond laboratory testing to include a number of other core functions such as emergency response, training and outreach, communications, laboratory-based surveillance and data management. These functions can only be accomplished by an efficient and resilient national laboratory network that includes public health, reference, clinical and other laboratories. It is a primary responsibility of the national health laboratory in the Ministry of Health to develop and maintain the national laboratory network in the country. In this article, we present practical recommendations based on 17 years of network development experience for the development of effective national laboratory networks. These recommendations and examples of current laboratory networks, are provided to facilitate laboratory network development in other states. The development of resilient, integrated laboratory networks will enhance each state's public health system and is critical to the development of a robust national laboratory response network to meet global health security threats.

Practical recommendations for strengthening national and regional laboratory networks in Africa in the Global Health Security era

PubMed Central

2016-01-01

The role of national health laboratories in support of public health response has expanded beyond laboratory testing to include a number of other core functions such as emergency response, training and outreach, communications, laboratory-based surveillance and data management. These functions can only be accomplished by an efficient and resilient national laboratory network that includes public health, reference, clinical and other laboratories. It is a primary responsibility of the national health laboratory in the Ministry of Health to develop and maintain the national laboratory network in the country. In this article, we present practical recommendations based on 17 years of network development experience for the development of effective national laboratory networks. These recommendations and examples of current laboratory networks, are provided to facilitate laboratory network development in other states. The development of resilient, integrated laboratory networks will enhance each state’s public health system and is critical to the development of a robust national laboratory response network to meet global health security threats. PMID:28879137

The control gain region for synchronization in non-diffusively coupled complex networks

NASA Astrophysics Data System (ADS)

Gequn, Liu; Wenhui, Li; Huijie, Yang; Knowles, Gareth

2014-07-01

The control gain region for synchronization of non-diffusively coupled networks was studied with respect to three conditions: synchronization, synchronization in finite time, and synchronization in the minimum time. Based on cancellation control methodology and master stability function formalism, we found that a complete feasible control gain region may be bounded, unbounded, empty or a union of several bounded and unbounded regions, with a similar shape to the synchronized region. An interesting possibility emerged that a network could be synchronized by both negative and positive feedback control simultaneously. By bridging synchronizability and synchronizing response speeds with a settling time index, we have developed timed synchronized region (TSR) as a substitute for the classical synchronized region to study finite time synchronization. As for the last condition, a graphical method was developed to estimate control gain with the minimum synchronization time (CGMST). Each condition has examples provided for illustration and verification.

The ADVANCE network: accelerating data value across a national community health center network

PubMed Central

DeVoe, Jennifer E; Gold, Rachel; Cottrell, Erika; Bauer, Vance; Brickman, Andrew; Puro, Jon; Nelson, Christine; Mayer, Kenneth H; Sears, Abigail; Burdick, Tim; Merrell, Jonathan; Matthews, Paul; Fields, Scott

2014-01-01

The ADVANCE (Accelerating Data Value Across a National Community Health Center Network) clinical data research network (CDRN) is led by the OCHIN Community Health Information Network in partnership with Health Choice Network and Fenway Health. The ADVANCE CDRN will ‘horizontally’ integrate outpatient electronic health record data for over one million federally qualified health center patients, and ‘vertically’ integrate hospital, health plan, and community data for these patients, often under-represented in research studies. Patient investigators, community investigators, and academic investigators with diverse expertise will work together to meet project goals related to data integration, patient engagement and recruitment, and the development of streamlined regulatory policies. By enhancing the data and research infrastructure of participating organizations, the ADVANCE CDRN will serve as a ‘community laboratory’ for including disadvantaged and vulnerable patients in patient-centered outcomes research that is aligned with the priorities of patients, clinics, and communities in our network. PMID:24821740

Diffusion archeology for diffusion progression history reconstruction.

PubMed

Sefer, Emre; Kingsford, Carl

2016-11-01

Diffusion through graphs can be used to model many real-world processes, such as the spread of diseases, social network memes, computer viruses, or water contaminants. Often, a real-world diffusion cannot be directly observed while it is occurring - perhaps it is not noticed until some time has passed, continuous monitoring is too costly, or privacy concerns limit data access. This leads to the need to reconstruct how the present state of the diffusion came to be from partial diffusion data. Here, we tackle the problem of reconstructing a diffusion history from one or more snapshots of the diffusion state. This ability can be invaluable to learn when certain computer nodes are infected or which people are the initial disease spreaders to control future diffusions. We formulate this problem over discrete-time SEIRS-type diffusion models in terms of maximum likelihood. We design methods that are based on submodularity and a novel prize-collecting dominating-set vertex cover (PCDSVC) relaxation that can identify likely diffusion steps with some provable performance guarantees. Our methods are the first to be able to reconstruct complete diffusion histories accurately in real and simulated situations. As a special case, they can also identify the initial spreaders better than the existing methods for that problem. Our results for both meme and contaminant diffusion show that the partial diffusion data problem can be overcome with proper modeling and methods, and that hidden temporal characteristics of diffusion can be predicted from limited data.

Evolving plans for the USA National Phenology Network

USGS Publications Warehouse

Betancourt, Julio L.; Schwartz, Mark D.; Breshears, David D.; Brewer, Carol A.; Frazer, Gary; Gross, John E.; Mazer, Susan J.; Reed, Bradley C.; Wilson, Bruce E.

2007-01-01

Phenology is the study of periodic plant and animal life cycle events, how these are influenced by seasonal and interannual variations in climate, and how they modulate the abundance, diversity, and interactions of organisms. The USA National Phenology Network (USA-NPN) is currently being organized to engage federal agencies, environmental networks and field stations, educational institutions, and citizen scientists. The first USA-NPN planning workshop was held August 2005, in Tucson, Ariz. (Betancourt et al. [2005]; http://www.uwm.edu/Dept/Geography/npn/; by 1 June 2007, also see http://www.usanpn.org). With sponsorship from the U.S. National Science Foundation, the U.S. Geological Survey (USGS), the U.S. Fish and Wildlife Service, and NASA, the second USA-NPN planning workshop was held at the University of Wisconsin-Milwaukee on 10–12 October 2006 to (1) develop lists of target species and observation protocols; (2) identify existing networks that could comprise the backbone of nationwide observations by 2008; (3) develop opportunities for education, citizen science, and outreach beginning in spring 2007; (4) design strategies for implementing the remote sensing component of USA-NPN; and (5) draft a data management and cyberinfrastructure plan.

The USA National Phenology Network: A national science and monitoring program for understanding climate change

NASA Astrophysics Data System (ADS)

Weltzin, J.

2009-04-01

Patterns of phenology for plants and animals control ecosystem processes, determine land surface properties, control biosphere-atmosphere interactions, and affect food production, health, conservation, and recreation. Although phenological data and models have applications related to scientific research, education and outreach, agriculture, tourism and recreation, human health, and natural resource conservation and management, until recently there was no coordinated effort to understand phenology at the national scale in the United States. The USA National Phenology Network (USA-NPN; www.usanpn.org), established in 2007, is an emerging and exciting partnership between federal agencies, the academic community, and the general public to establish a national science and monitoring initiative focused on phenology. The first year of operation of USA-NPN produced many new phenology products and venues for phenology research and citizen involvement. Products include a new web-site (www.usanpn.org) that went live in June 2008; the web-site includes a tool for on-line data entry, and serves as a clearinghouse for products and information to facilitate research and communication related to phenology. The new core Plant Phenology Program includes profiles for 200 vetted local, regional, and national plant species with descriptions and (BBCH-consistent) monitoring protocols, as well as templates for addition of new species. A partnership program describes how other monitoring networks can engage with USA-NPN to collect, manage or disseminate phenological information for science, health, education, management or predictive service applications. Project BudBurst, a USA-NPN field campaign for citizen scientists, went live in February 2008, and now includes over 3000 registered observers monitoring 4000 plants across the nation. For 2009 and beyond, we will initiate a new Wildlife Phenology Program, create an on-line clearing-house for phenology education and outreach, strengthen

Data from selected U.S. Geological Survey National Stream Water-Quality Networks (WQN)

USGS Publications Warehouse

Alexander, Richard B.; Slack, J.R.; Ludtke, A.S.; Fitzgerald, K.K.; Schertz, T.L.; Briel, L.I.; Buttleman, K.P.

1996-01-01

This CD-ROM set contains data from two USGS national stream water-quality networks, the Hydrologic Benchmark Network (HBN) and the National Stream Quality Accounting Network (NASQAN), operated during the past 30 years. These networks were established to provide national and regional descriptions of stream water-quality conditions and trends, based on uniform monitoring of selected watersheds throughout the United States, and to improve our understanding of the effects of the natural environment and human activities on water quality. The HBN, consisting of 63 relatively small, minimally disturbed watersheds, provides data for investigating naturally induced changes in streamflow and water quality and the effects of airborne substances on water quality. NASQAN, consisting of 618 larger, more culturally influenced watersheds, provides information for tracking water-quality conditions in major U.S. rivers and streams.

Computer-aided diagnostic system for diffuse liver diseases with ultrasonography by neural networks

NASA Astrophysics Data System (ADS)

Ogawa, K.; Fukushima, M.; Kubota, K.; Hisa, N.

1998-12-01

The aim of the study is to establish a computer-aided diagnostic system for diffuse liver diseases such as chronic active hepatitis (CAH) and liver cirrhosis (LC). The authors introduced an artificial neural network in the classification of these diseases. In this system the neural network was trained by feature parameters extracted from B-mode ultrasonic images of normal liver (NL), CAH and LC. For input data the authors used six parameters calculated by a region of interest (ROI) and a parameter calculated by five ROIs in each image. They were variance of pixel values, coefficient of variation, annular Fourier power spectrum, longitudinal Fourier power spectrum which were calculated for the ROI, and variation of the means of the five ROIs. In addition, the authors used two more parameters calculated from a co-occurrence matrix of pixel values in the ROI. The results showed that the neural network classifier was 83.8% in sensitivity for LC, 90.0% in sensitivity for CAH and 93.6% in specificity, and the system was considered to be helpful for clinical and educational use.

Open College Networks and National Vocational Qualifications. A Development Paper.

ERIC Educational Resources Information Center

National Council for Vocational Qualifications, London (England).

Both the National Council for Vocational Qualifications (NCVQ) and Open College Networks or Federations (OCNs) have the objective of creating nationally coherent frameworks of qualification and training in Britain. However, they are very different organizations and have distinct, though potentially complementary, roles. Issues where the two…

Building National Capacity for Climate Change Interpretation: The Role of Leaders, Partnerships, and Networks

NASA Astrophysics Data System (ADS)

Spitzer, W.

2015-12-01

Since 2007, the New England Aquarium has led a national effort to increase the capacity of informal science venues to effectively communicate about climate change. We are now leading the NSF-funded National Network for Ocean and Climate Change Interpretation (NNOCCI), partnering with the Association of Zoos and Aquariums, FrameWorks Institute, Woods Hole Oceanographic Institution, Monterey Bay Aquarium, and National Aquarium, with evaluation conducted by the New Knowledge Organization, Pennsylvania State University, and Ohio State University. NNOCCI enables teams of informal science interpreters across the country to serve as "communication strategists" - beyond merely conveying information they can influence public perceptions, given their high level of commitment, knowledge, public trust, social networks, and visitor contact. We provide in-depth training as well as an alumni network for ongoing learning, implementation support, leadership development, and coalition building. Our goals are to achieve a systemic national impact, embed our work within multiple ongoing regional and national climate change education networks, and leave an enduring legacy. Our project represents a cross-disciplinary partnership among climate scientists, social and cognitive scientists, and informal education practitioners. We have built a growing national network of more than 250 alumni, including approximately 15-20 peer leaders who co-lead both in-depth training programs and introductory workshops. We have found that this alumni network has been assuming increasing importance in providing for ongoing learning, support for implementation, leadership development, and coalition building. As we look toward the future, we are exploring potential partnerships with other existing networks, both to sustain our impact and to expand our reach. This presentation will address what we have learned in terms of network impacts, best practices, factors for success, and future directions.

Documentary of MFENET, a national computer network

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

Shuttleworth, B.O.

1977-06-01

The national Magnetic Fusion Energy Computer Network (MFENET) is a newly operational star network of geographically separated heterogeneous hosts and a communications subnetwork of PDP-11 processors. Host processors interfaced to the subnetwork currently include a CDC 7600 at the Central Computer Center (CCC) and several DECsystem-10's at User Service Centers (USC's). The network was funded by a U.S. government agency (ERDA) to provide in an economical manner the needed computational resources to magnetic confinement fusion researchers. Phase I operation of MFENET distributed the processing power of the CDC 7600 among the USC's through the provision of file transport between anymore » two hosts and remote job entry to the 7600. Extending the capabilities of Phase I, MFENET Phase II provided interactive terminal access to the CDC 7600 from the USC's. A file management system is maintained at the CCC for all network users. The history and development of MFENET are discussed, with emphasis on the protocols used to link the host computers and the USC software. Comparisons are made of MFENET versus ARPANET (Advanced Research Projects Agency Computer Network) and DECNET (Digital Distributed Network Architecture). DECNET and MFENET host-to host, host-to-CCP, and link protocols are discussed in detail. The USC--CCP interface is described briefly. 43 figures, 2 tables.« less

Diffusion archeology for diffusion progression history reconstruction

PubMed Central

Sefer, Emre; Kingsford, Carl

2015-01-01

Diffusion through graphs can be used to model many real-world processes, such as the spread of diseases, social network memes, computer viruses, or water contaminants. Often, a real-world diffusion cannot be directly observed while it is occurring — perhaps it is not noticed until some time has passed, continuous monitoring is too costly, or privacy concerns limit data access. This leads to the need to reconstruct how the present state of the diffusion came to be from partial diffusion data. Here, we tackle the problem of reconstructing a diffusion history from one or more snapshots of the diffusion state. This ability can be invaluable to learn when certain computer nodes are infected or which people are the initial disease spreaders to control future diffusions. We formulate this problem over discrete-time SEIRS-type diffusion models in terms of maximum likelihood. We design methods that are based on submodularity and a novel prize-collecting dominating-set vertex cover (PCDSVC) relaxation that can identify likely diffusion steps with some provable performance guarantees. Our methods are the first to be able to reconstruct complete diffusion histories accurately in real and simulated situations. As a special case, they can also identify the initial spreaders better than the existing methods for that problem. Our results for both meme and contaminant diffusion show that the partial diffusion data problem can be overcome with proper modeling and methods, and that hidden temporal characteristics of diffusion can be predicted from limited data. PMID:27821901

Reaction-diffusion-like formalism for plastic neural networks reveals dissipative solitons at criticality

NASA Astrophysics Data System (ADS)

Grytskyy, Dmytro; Diesmann, Markus; Helias, Moritz

2016-06-01

Self-organized structures in networks with spike-timing dependent synaptic plasticity (STDP) are likely to play a central role for information processing in the brain. In the present study we derive a reaction-diffusion-like formalism for plastic feed-forward networks of nonlinear rate-based model neurons with a correlation sensitive learning rule inspired by and being qualitatively similar to STDP. After obtaining equations that describe the change of the spatial shape of the signal from layer to layer, we derive a criterion for the nonlinearity necessary to obtain stable dynamics for arbitrary input. We classify the possible scenarios of signal evolution and find that close to the transition to the unstable regime metastable solutions appear. The form of these dissipative solitons is determined analytically and the evolution and interaction of several such coexistent objects is investigated.

External quality-assurance project report for the National Atmospheric Deposition Program/National Trends Network and Mercury Deposition Network, 2009-2010

USGS Publications Warehouse

Wetherbee, Gregory A.; Martin, RoseAnn; Rhodes, Mark F.; Chesney, Tanya A.

2014-01-01

The U.S. Geological Survey operated six distinct programs to provide external quality-assurance monitoring for the National Atmospheric Deposition Program/National Trends Network (NTN) and Mercury Deposition Network (MDN) during 2009–2010. The field-audit program assessed the effects of onsite exposure, sample handling, and shipping on the chemistry of NTN samples; a system-blank program assessed the same effects for MDN. Two interlaboratory-comparison programs assessed the bias and variability of the chemical analysis data from the Central Analytical Laboratory (CAL) and Mercury (Hg) Analytical Laboratory (HAL). The blind-audit program was also implemented for the MDN to evaluate analytical bias in total Hg concentration data produced by the HAL. The co-located-sampler program was used to identify and quantify potential shifts in NADP data resulting from replacement of original network instrumentation with new electronic recording rain gages (E-gages) and precipitation collectors that use optical sensors. The results indicate that NADP data continue to be of sufficient quality for the analysis of spatial distributions and time trends of chemical constituents in wet deposition across the United States. Results also suggest that retrofit of the NADP networks with the new precipitation collectors could cause –8 to +14 percent shifts in NADP annual precipitation-weighted mean concentrations and total deposition values for ammonium, nitrate, sulfate, and hydrogen ion, and larger shifts (+13 to +74 percent) for calcium, magnesium, sodium, potassium, and chloride. The prototype N-CON Systems bucket collector is more efficient in the catch of precipitation in winter than Aerochem Metrics Model 301 collector, especially for light snowfall.

pSCANNER: patient-centered Scalable National Network for Effectiveness Research

PubMed Central

Ohno-Machado, Lucila; Agha, Zia; Bell, Douglas S; Dahm, Lisa; Day, Michele E; Doctor, Jason N; Gabriel, Davera; Kahlon, Maninder K; Kim, Katherine K; Hogarth, Michael; Matheny, Michael E; Meeker, Daniella; Nebeker, Jonathan R

2014-01-01

This article describes the patient-centered Scalable National Network for Effectiveness Research (pSCANNER), which is part of the recently formed PCORnet, a national network composed of learning healthcare systems and patient-powered research networks funded by the Patient Centered Outcomes Research Institute (PCORI). It is designed to be a stakeholder-governed federated network that uses a distributed architecture to integrate data from three existing networks covering over 21 million patients in all 50 states: (1) VA Informatics and Computing Infrastructure (VINCI), with data from Veteran Health Administration's 151 inpatient and 909 ambulatory care and community-based outpatient clinics; (2) the University of California Research exchange (UC-ReX) network, with data from UC Davis, Irvine, Los Angeles, San Francisco, and San Diego; and (3) SCANNER, a consortium of UCSD, Tennessee VA, and three federally qualified health systems in the Los Angeles area supplemented with claims and health information exchange data, led by the University of Southern California. Initial use cases will focus on three conditions: (1) congestive heart failure; (2) Kawasaki disease; (3) obesity. Stakeholders, such as patients, clinicians, and health service researchers, will be engaged to prioritize research questions to be answered through the network. We will use a privacy-preserving distributed computation model with synchronous and asynchronous modes. The distributed system will be based on a common data model that allows the construction and evaluation of distributed multivariate models for a variety of statistical analyses. PMID:24780722

Microtomography-based Inter-Granular Network for the simulation of radionuclide diffusion and sorption in a granitic rock

NASA Astrophysics Data System (ADS)

Iraola, Aitor; Trinchero, Paolo; Voutilainen, Mikko; Gylling, Björn; Selroos, Jan-Olof; Molinero, Jorge; Svensson, Urban; Bosbach, Dirk; Deissmann, Guido

2017-12-01

Field investigation studies, conducted in the context of safety analyses of deep geological repositories for nuclear waste, have pointed out that in fractured crystalline rocks sorbing radionuclides can diffuse surprisingly long distances deep into the intact rock matrix; i.e. much longer distances than those predicted by reactive transport models based on a homogeneous description of the properties of the rock matrix. Here, we focus on cesium diffusion and use detailed micro characterisation data, based on micro computed tomography, along with a grain-scale Inter-Granular Network model, to offer a plausible explanation for the anomalously long cesium penetration profiles observed in these in-situ experiments. The sparse distribution of chemically reactive grains (i.e. grains belonging to sorbing mineral phases) is shown to have a strong control on the diffusive patterns of sorbing radionuclides. The computed penetration profiles of cesium agree well with an analytical model based on two parallel diffusive pathways. This agreement, along with visual inspection of the spatial distribution of cesium concentration, indicates that for sorbing radionuclides the medium indeed behaves as a composite system, with most of the mass being retained close to the injection boundary and a non-negligible part diffusing faster along preferential diffusive pathways.

34 CFR 412.1 - What is the National Network for Curriculum Coordination in Vocational and Technical Education?

Code of Federal Regulations, 2011 CFR

2011-07-01

... 34 Education 3 2011-07-01 2011-07-01 false What is the National Network for Curriculum... EDUCATION NATIONAL NETWORK FOR CURRICULUM COORDINATION IN VOCATIONAL AND TECHNICAL EDUCATION General § 412.1 What is the National Network for Curriculum Coordination in Vocational and Technical Education? The...

34 CFR 412.1 - What is the National Network for Curriculum Coordination in Vocational and Technical Education?

Code of Federal Regulations, 2010 CFR

2010-07-01

... 34 Education 3 2010-07-01 2010-07-01 false What is the National Network for Curriculum... EDUCATION NATIONAL NETWORK FOR CURRICULUM COORDINATION IN VOCATIONAL AND TECHNICAL EDUCATION General § 412.1 What is the National Network for Curriculum Coordination in Vocational and Technical Education? The...

Converting Multi-Shell and Diffusion Spectrum Imaging to High Angular Resolution Diffusion Imaging

PubMed Central

Yeh, Fang-Cheng; Verstynen, Timothy D.

2016-01-01

Multi-shell and diffusion spectrum imaging (DSI) are becoming increasingly popular methods of acquiring diffusion MRI data in a research context. However, single-shell acquisitions, such as diffusion tensor imaging (DTI) and high angular resolution diffusion imaging (HARDI), still remain the most common acquisition schemes in practice. Here we tested whether multi-shell and DSI data have conversion flexibility to be interpolated into corresponding HARDI data. We acquired multi-shell and DSI data on both a phantom and in vivo human tissue and converted them to HARDI. The correlation and difference between their diffusion signals, anisotropy values, diffusivity measurements, fiber orientations, connectivity matrices, and network measures were examined. Our analysis result showed that the diffusion signals, anisotropy, diffusivity, and connectivity matrix of the HARDI converted from multi-shell and DSI were highly correlated with those of the HARDI acquired on the MR scanner, with correlation coefficients around 0.8~0.9. The average angular error between converted and original HARDI was 20.7° at voxels with signal-to-noise ratios greater than 5. The network topology measures had less than 2% difference, whereas the average nodal measures had a percentage difference around 4~7%. In general, multi-shell and DSI acquisitions can be converted to their corresponding single-shell HARDI with high fidelity. This supports multi-shell and DSI acquisitions over HARDI acquisition as the scheme of choice for diffusion acquisitions. PMID:27683539

Synchronization of generalized reaction-diffusion neural networks with time-varying delays based on general integral inequalities and sampled-data control approach.

PubMed

Dharani, S; Rakkiyappan, R; Cao, Jinde; Alsaedi, Ahmed

2017-08-01

This paper explores the problem of synchronization of a class of generalized reaction-diffusion neural networks with mixed time-varying delays. The mixed time-varying delays under consideration comprise of both discrete and distributed delays. Due to the development and merits of digital controllers, sampled-data control is a natural choice to establish synchronization in continuous-time systems. Using a newly introduced integral inequality, less conservative synchronization criteria that assure the global asymptotic synchronization of the considered generalized reaction-diffusion neural network and mixed delays are established in terms of linear matrix inequalities (LMIs). The obtained easy-to-test LMI-based synchronization criteria depends on the delay bounds in addition to the reaction-diffusion terms, which is more practicable. Upon solving these LMIs by using Matlab LMI control toolbox, a desired sampled-data controller gain can be acuqired without any difficulty. Finally, numerical examples are exploited to express the validity of the derived LMI-based synchronization criteria.

23 CFR 658.21 - Identification of National Network.

Code of Federal Regulations, 2012 CFR

2012-04-01

... the efficiency of the total traffic flow, such as time of day prohibitions, or lane use controls. (2....21 Highways FEDERAL HIGHWAY ADMINISTRATION, DEPARTMENT OF TRANSPORTATION ENGINEERING AND TRAFFIC... National Network shall be signed. All signs shall conform to the Manual on Uniform Traffic Control Devices...

23 CFR 658.21 - Identification of National Network.

Code of Federal Regulations, 2013 CFR

2013-04-01

... the efficiency of the total traffic flow, such as time of day prohibitions, or lane use controls. (2....21 Highways FEDERAL HIGHWAY ADMINISTRATION, DEPARTMENT OF TRANSPORTATION ENGINEERING AND TRAFFIC... National Network shall be signed. All signs shall conform to the Manual on Uniform Traffic Control Devices...

23 CFR 658.21 - Identification of National Network.

Code of Federal Regulations, 2014 CFR

2014-04-01

... the efficiency of the total traffic flow, such as time of day prohibitions, or lane use controls. (2....21 Highways FEDERAL HIGHWAY ADMINISTRATION, DEPARTMENT OF TRANSPORTATION ENGINEERING AND TRAFFIC... National Network shall be signed. All signs shall conform to the Manual on Uniform Traffic Control Devices...

Direct2Experts: a pilot national network to demonstrate interoperability among research-networking platforms.

PubMed

Weber, Griffin M; Barnett, William; Conlon, Mike; Eichmann, David; Kibbe, Warren; Falk-Krzesinski, Holly; Halaas, Michael; Johnson, Layne; Meeks, Eric; Mitchell, Donald; Schleyer, Titus; Stallings, Sarah; Warden, Michael; Kahlon, Maninder

2011-12-01

Research-networking tools use data-mining and social networking to enable expertise discovery, matchmaking and collaboration, which are important facets of team science and translational research. Several commercial and academic platforms have been built, and many institutions have deployed these products to help their investigators find local collaborators. Recent studies, though, have shown the growing importance of multiuniversity teams in science. Unfortunately, the lack of a standard data-exchange model and resistance of universities to share information about their faculty have presented barriers to forming an institutionally supported national network. This case report describes an initiative, which, in only 6 months, achieved interoperability among seven major research-networking products at 28 universities by taking an approach that focused on addressing institutional concerns and encouraging their participation. With this necessary groundwork in place, the second phase of this effort can begin, which will expand the network's functionality and focus on the end users.

Direct2Experts: a pilot national network to demonstrate interoperability among research-networking platforms

PubMed Central

Barnett, William; Conlon, Mike; Eichmann, David; Kibbe, Warren; Falk-Krzesinski, Holly; Halaas, Michael; Johnson, Layne; Meeks, Eric; Mitchell, Donald; Schleyer, Titus; Stallings, Sarah; Warden, Michael; Kahlon, Maninder

2011-01-01

Research-networking tools use data-mining and social networking to enable expertise discovery, matchmaking and collaboration, which are important facets of team science and translational research. Several commercial and academic platforms have been built, and many institutions have deployed these products to help their investigators find local collaborators. Recent studies, though, have shown the growing importance of multiuniversity teams in science. Unfortunately, the lack of a standard data-exchange model and resistance of universities to share information about their faculty have presented barriers to forming an institutionally supported national network. This case report describes an initiative, which, in only 6 months, achieved interoperability among seven major research-networking products at 28 universities by taking an approach that focused on addressing institutional concerns and encouraging their participation. With this necessary groundwork in place, the second phase of this effort can begin, which will expand the network's functionality and focus on the end users. PMID:22037890

Synchronization of hybrid coupled reaction-diffusion neural networks with time delays via generalized intermittent control with spacial sampled-data.

PubMed

Lu, Binglong; Jiang, Haijun; Hu, Cheng; Abdurahman, Abdujelil

2018-05-04

The exponential synchronization of hybrid coupled reaction-diffusion neural networks with time delays is discussed in this article. At first, a generalized intermittent control with spacial sampled-data is introduced, which is intermittent in time and data sampling in space. This type of control strategy not only can unify the traditional periodic intermittent control and the aperiodic case, but also can lower the update rate of the controller in both temporal and spatial domains. Next, based on the designed control protocol and the Lyapunov-Krasovskii functional approach, some novel and readily verified criteria are established to guarantee the exponential synchronization of the considered networks. These criteria depend on the diffusion coefficients, coupled strengths, time delays as well as control parameters. Finally, the effectiveness of the proposed control strategy is shown by a numerical example. Copyright © 2018 Elsevier Ltd. All rights reserved.

Enzyme localization, crowding, and buffers collectively modulate diffusion-influenced signal transduction: Insights from continuum diffusion modeling

PubMed Central

Kekenes-Huskey, Peter M.; Eun, Changsun; McCammon, J. A.

2015-01-01

Biochemical reaction networks consisting of coupled enzymes connect substrate signaling events with biological function. Substrates involved in these reactions can be strongly influenced by diffusion “barriers” arising from impenetrable cellular structures and macromolecules, as well as interactions with biomolecules, especially within crowded environments. For diffusion-influenced reactions, the spatial organization of diffusion barriers arising from intracellular structures, non-specific crowders, and specific-binders (buffers) strongly controls the temporal and spatial reaction kinetics. In this study, we use two prototypical biochemical reactions, a Goodwin oscillator, and a reaction with a periodic source/sink term to examine how a diffusion barrier that partitions substrates controls reaction behavior. Namely, we examine how conditions representative of a densely packed cytosol, including reduced accessible volume fraction, non-specific interactions, and buffers, impede diffusion over nanometer length-scales. We find that diffusion barriers can modulate the frequencies and amplitudes of coupled diffusion-influenced reaction networks, as well as give rise to “compartments” of decoupled reactant populations. These effects appear to be intensified in the presence of buffers localized to the diffusion barrier. These findings have strong implications for the role of the cellular environment in tuning the dynamics of signaling pathways. PMID:26342355

SpecialNet. A National Computer-Based Communications Network.

ERIC Educational Resources Information Center

Morin, Alfred J.

1986-01-01

"SpecialNet," a computer-based communications network for educators at all administrative levels, has been established and is managed by National Systems Management, Inc. Users can send and receive electronic mail, share information on electronic bulletin boards, participate in electronic conferences, and send reports and other documents to each…

NASA/DOD Aerospace Knowledge Diffusion Research Project. Paper 47: The value of computer networks in aerospace

NASA Technical Reports Server (NTRS)

Bishop, Ann Peterson; Pinelli, Thomas E.

1995-01-01

This paper presents data on the value of computer networks that were obtained from a national survey of 2000 aerospace engineers that was conducted in 1993. Survey respondents reported the extent to which they used computer networks in their work and communication and offered their assessments of the value of various network types and applications. They also provided information about the positive impacts of networks on their work, which presents another perspective on value. Finally, aerospace engineers' recommendations on network implementation present suggestions for increasing the value of computer networks within aerospace organizations.

Understanding spatial and temporal patterning of astrocyte calcium transients via interactions between network transport and extracellular diffusion

NASA Astrophysics Data System (ADS)

Shtrahman, E.; Maruyama, D.; Olariu, E.; Fink, C. G.; Zochowski, M.

2017-02-01

Astrocytes form interconnected networks in the brain and communicate via calcium signaling. We investigate how modes of coupling between astrocytes influence the spatio-temporal patterns of calcium signaling within astrocyte networks and specifically how these network interactions promote coordination within this group of cells. To investigate these complex phenomena, we study reduced cultured networks of astrocytes and neurons. We image the spatial temporal patterns of astrocyte calcium activity and quantify how perturbing the coupling between astrocytes influences astrocyte activity patterns. To gain insight into the pattern formation observed in these cultured networks, we compare the experimentally observed calcium activity patterns to the patterns produced by a reduced computational model, where we represent astrocytes as simple units that integrate input through two mechanisms: gap junction coupling (network transport) and chemical release (extracellular diffusion). We examine the activity patterns in the simulated astrocyte network and their dependence upon these two coupling mechanisms. We find that gap junctions and extracellular chemical release interact in astrocyte networks to modulate the spatiotemporal patterns of their calcium dynamics. We show agreement between the computational and experimental findings, which suggests that the complex global patterns can be understood as a result of simple local coupling mechanisms.

Diffusion of innovations theory applied to global tobacco control treaty ratification.

PubMed

Valente, Thomas W; Dyal, Stephanie R; Chu, Kar-Hai; Wipfli, Heather; Fujimoto, Kayo

2015-11-01

This study applies diffusion of innovations theory to understand network influences on country ratification of an international health treaty, the Framework Convention for Tobacco Control (FCTC). From 2003 to 2014 approximately 90% of United Nations member countries ratified the FCTC. We hypothesized that communication between tobacco control advocates on GLOBALink, a 7000-member online communication forum in existence from 1992 to 2012, would be associated with the timing of treaty ratification. We further hypothesized dynamic network influences such that external influence decreased over time, internal influence increased over time, and the role of opinion leader countries varied over time. In addition we develop two concepts: Susceptibility and influence that uncover the micro-level dynamics of network influence. Statistical analyses lend support to the influence of co-subscriptions on GLOBALink providing a conduit for inter-country influences on treaty ratification and some support for the dynamic hypotheses. Analyses of susceptibility and infection indicated particularly influential countries. These results have implications for the study of policy diffusion as well as dynamic models of behavior change. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

National Human Trafficking Initiatives: Dimensions of Policy Diffusion.

PubMed

Yoo, Eun-Hye; Boyle, Elizabeth Heger

2015-01-01

The implementation of criminal law involves formal law enforcement, education and public outreach aimed at preventing criminal activity, and providing services for victims. Historically, quantitative research on global trends has tended to focus on a single policy dimension, potentially masking the unique factors that affect the diffusion of each policy dimension independently. Using an ordered-probit model to analyze new human trafficking policy data on national prosecution, prevention, and victim-protection efforts, we find that global ties and domestic interest groups matter more in areas where international law is less defined. While prosecution, officially mandated by the Trafficking Protocol, was relatively impervious to global ties and domestic interest groups, both trafficking prevention and victim protection were associated with these factors. Our findings also suggest that fear of repercussions is not a major driver of state actions to combat trafficking-neither ratification of the Trafficking Protocol nor levels of United States aid were associated with greater implementation of anti-trafficking measures.

Mexican national pyronometer network calibration

NASA Astrophysics Data System (ADS)

VAldes, M.; Villarreal, L.; Estevez, H.; Riveros, D.

2013-12-01

In order to take advantage of the solar radiation as an alternate energy source it is necessary to evaluate the spatial and temporal availability. The Mexican National Meterological Service (SMN) has a network with 136 meteorological stations, each coupled with a pyronometer for measuring the global solar radiation. Some of these stations had not been calibrated in several years. The Mexican Department of Energy (SENER) in order to count on a reliable evaluation of the solar resource funded this project to calibrate the SMN pyrometer network and validate the data. The calibration of the 136 pyronometers by the intercomparison method recommended by the World Meterological Organization (WMO) requires lengthy observations and specific environmental conditions such as clear skies and a stable atmosphere, circumstances that determine the site and season of the calibration. The Solar Radiation Section of the Instituto de Geofísica of the Universidad Nacional Autónoma de México is a Regional Center of the WMO and is certified to carry out the calibration procedures and emit certificates. We are responsible for the recalibration of the pyronometer network of the SMN. A continuous emission solar simulator with exposed areas with 30cm diameters was acquired to reduce the calibration time and not depend on atmospheric conditions. We present the results of the calibration of 10 thermopile pyronometers and one photovoltaic cell by the intercomparison method with more than 10000 observations each and those obtained with the solar simulator.

Some experiments to study diffusive transport through a semi interpenetrating polymeric network in the absence and presence of aqueous electrolytes

NASA Astrophysics Data System (ADS)

Biswas, Pritha; Das, Atreyee; Yasmin, Tanvee; Kanjilal, Baishali; Chakrabarti, Haimanti

2018-05-01

The study of ion transport in biological system has become a topic of great current interest. This work presents the diffusive transport properties through a typical semi interpenetrating polymeric network (SIPN) which mimics many characteristic features of the walls of human food pipes. The SIPN matrix has been synthesised from Polyvinyl alcohol, Acrylamide monomer, Glutaraldehyde and Ammonium Per sulphate in our laboratory is utilised to study the diffusive transport in the absence and presence of aqueous electrolyte (KCl) at varying concentrations. The diffusivity of the SIPN polymer hydrogel was estimated by the `Theory of Elastomer' to get an insight into process of Potassium and Chlorine ion transport through the SIPN.

Preliminary Design Study for a National Digital Seismograph Network

USGS Publications Warehouse

Peterson, Jon; Hutt, Charles R.

1981-01-01

Introduction Recently, the National Research Council published a report by the Panel on National, Regional, and Local Seismograph Networks of the Committee on Seismology in which the principal recommendation was for the establishment of a national digital seismograph network (NDSN). The Panel Report (Bolt, 1980) addresses both the need and the scientific requirements for the new national network. The purpose of this study has been to translate the scientific requirements into an instrumentation concept for the NSDS. There are literally hundreds, perhaps thousands, of seismographs in operation within the United States. Each serves an important purpose, but most have limited objectives in time, in region, or in the types of data that are being recorded. The concept of a national network, funded and operated by the Federal Government, is based on broader objectives that include continuity of time, uniform coverage, standardization of data format and instruments, and widespread use of the data for a variety of research purposes. A national digital seismograph network will be an important data resource for many years to come; hence, its design is likely to be of interest to most seismologists. Seismologists have traditionally been involved in the development and field operation of seismic systems and thus have been familiar with both the potential value and the limitations of the data. However, in recent years of increasing technological sophistication, the development of data sstems has fallen more to system engineers, and this trend is likely to continue. One danger in this is that the engineers may misinterpret scientific objectives or subordinate them to purely technological considerations. Another risk is that the data users may misuse or misinterpret the data because they are not aware of the limitations of the data system. Perhaps the most important purpose of a design study such as this is to stimulate a dialogue between system engineers and potential data users

A national neurological excellence centers network.

PubMed

Pazzi, S; Cristiani, P; Cavallini, A

1998-02-01

The most relevant problems related to the management of neurological disorders are (i) the frequent hospitalization in nonspecialist departments, with the need for neurological consultation, and (ii) the frequent requests of GPs for highly specialized investigations that are very expensive and of little value in arriving at a correct diagnosis. In 1996, the Consorzio di Bioingegneria e Informatica Medica in Italy realized the CISNet project (in collaboration with the Consorzio Istituti Scientifici Neuroscienze e Tecnologie Biomediche and funded by the Centro Studi of the National Public Health Council) for the implementation of a national neurological excellence centers network (CISNet). In the CISNet project, neurologists will be able to give on-line interactive consultation and off-line consulting services identifying correct diagnostic/therapeutic procedures, evaluating the need for both examination in specialist centers and admission to specialized centers, and identifying the most appropriate ones.

A statistical summary of data from the U.S. Geological Survey's national water quality networks

USGS Publications Warehouse

Smith, R.A.; Alexander, R.B.

1983-01-01

The U.S. Geological Survey Operates two nationwide networks to monitor water quality, the National Hydrologic Bench-Mark Network and the National Stream Quality Accounting Network (NASQAN). The Bench-Mark network is composed of 51 stations in small drainage basins which are as close as possible to their natural state, with no human influence and little likelihood of future development. Stations in the NASQAN program are located to monitor flow from accounting units (subregional drainage basins) which collectively encompass the entire land surface of the nation. Data collected at both networks include streamflow, concentrations of major inorganic constituents, nutrients, and trace metals. The goals of the two water quality sampling programs include the determination of mean constituent concentrations and transport rates as well as the analysis of long-term trends in those variables. This report presents a station-by-station statistical summary of data from the two networks for the period 1974 through 1981. (Author 's abstract)

MicroRNA-integrated and network-embedded gene selection with diffusion distance.

PubMed

Huang, Di; Zhou, Xiaobo; Lyon, Christopher J; Hsueh, Willa A; Wong, Stephen T C

2010-10-29

Gene network information has been used to improve gene selection in microarray-based studies by selecting marker genes based both on their expression and the coordinate expression of genes within their gene network under a given condition. Here we propose a new network-embedded gene selection model. In this model, we first address the limitations of microarray data. Microarray data, although widely used for gene selection, measures only mRNA abundance, which does not always reflect the ultimate gene phenotype, since it does not account for post-transcriptional effects. To overcome this important (critical in certain cases) but ignored-in-almost-all-existing-studies limitation, we design a new strategy to integrate together microarray data with the information of microRNA, the major post-transcriptional regulatory factor. We also handle the challenges led by gene collaboration mechanism. To incorporate the biological facts that genes without direct interactions may work closely due to signal transduction and that two genes may be functionally connected through multi paths, we adopt the concept of diffusion distance. This concept permits us to simulate biological signal propagation and therefore to estimate the collaboration probability for all gene pairs, directly or indirectly-connected, according to multi paths connecting them. We demonstrate, using type 2 diabetes (DM2) as an example, that the proposed strategies can enhance the identification of functional gene partners, which is the key issue in a network-embedded gene selection model. More importantly, we show that our gene selection model outperforms related ones. Genes selected by our model 1) have improved classification capability; 2) agree with biological evidence of DM2-association; and 3) are involved in many well-known DM2-associated pathways.

Primary Strategy Learning Networks: A Local Study of a National Initiative

ERIC Educational Resources Information Center

Moore, Tessa A.; Rutherford, Desmond

2012-01-01

The use of networks as a means of communicating knowledge and ideas and in promoting innovation among schools has emerged globally over the past decade. Currently, inter-school collaboration is not only at the fore nationally in England, but also has become integral to the school improvement agenda. However, networking theory is a disparate field…

NATIONAL CROP LOSS ASSESSMENT NETWORK (NCLAN) 1982 ANNUAL REPORT

EPA Science Inventory

The National Crop Loss Assessment Network (NCLAN) is a group of organizations cooperating in research to assess the short- and long-term economic impact of air pollution on crop production. The primary objectives are (1) to define relationships between yield of major agricultural...

Low-altitude photographic transects of the Arctic network of national park units and Selawik National Wildlife Refuge, Alaska, July 2013

Treesearch

Bruce G. Marcot; M. Torre Jorgenson; Anthony R. DeGange

2014-01-01

During July 16–18, 2013, low-level photography flights were conducted (with a Cessna 185 with floats and a Cessna 206 with tundra tires) over the five administrative units of the National Park Service Arctic Network (Bering Land Bridge National Preserve, Cape Krusenstern National Monument, Gates of the Arctic National Park and Preserve, Kobuk Valley National Park, and...

Nation-scale adoption of new medicines by doctors: an application of the Bass diffusion model

PubMed Central

2012-01-01

Background The adoption of new medicines is influenced by a complex set of social processes that have been widely examined in terms of individual prescribers’ information-seeking and decision-making behaviour. However, quantitative, population-wide analyses of how long it takes for new healthcare practices to become part of mainstream practice are rare. Methods We applied a Bass diffusion model to monthly prescription volumes of 103 often-prescribed drugs in Australia (monthly time series data totalling 803 million prescriptions between 1992 and 2010), to determine the distribution of adoption rates. Our aim was to test the utility of applying the Bass diffusion model to national-scale prescribing volumes. Results The Bass diffusion model was fitted to the adoption of a broad cross-section of drugs using national monthly prescription volumes from Australia (median R2 = 0.97, interquartile range 0.95 to 0.99). The median time to adoption was 8.2 years (IQR 4.9 to 12.1). The model distinguished two classes of prescribing patterns – those where adoption appeared to be driven mostly by external forces (19 drugs) and those driven mostly by social contagion (84 drugs). Those driven more prominently by internal forces were found to have shorter adoption times (p = 0.02 in a non-parametric analysis of variance by ranks). Conclusion The Bass diffusion model may be used to retrospectively represent the patterns of adoption exhibited in prescription volumes in Australia, and distinguishes between adoption driven primarily by external forces such as regulation, or internal forces such as social contagion. The eight-year delay between the introduction of a new medicine and the adoption of the prescribing practice suggests the presence of system inertia in Australian prescribing practices. PMID:22876867

Understanding the Adoption Process of National Security Technology: An Integration of Diffusion of Innovations and Volitional Behavior Theories.

PubMed

Iles, Irina A; Egnoto, Michael J; Fisher Liu, Brooke; Ackerman, Gary; Roberts, Holly; Smith, Daniel

2017-11-01

After the 9/11 terrorist attacks, the U.S. government initiated several national security technology adoption programs. The American public, however, has been skeptical about these initiatives and adoption of national security technologies has been mandated, rather than voluntary. We propose and test a voluntary behavioral intention formation model for the adoption of one type of new security technology: portable radiation detectors. Portable radiation detectors are an efficient way of detecting radiological and nuclear threats and could potentially prevent loss of life and damage to individuals' health. However, their functioning requires that a critical mass of individuals use them on a daily basis. We combine the explanatory advantages of diffusion of innovation with the predictive power of two volitional behavior frameworks: the theory of reasoned action and the health belief model. A large sample survey (N = 1,482) investigated the influence of factors identified in previous diffusion of innovation research on portable radiation detector adoption intention. Results indicated that nonfinancial incentives, as opposed to financial incentives, should be emphasized in persuasive communications aimed at fostering adoption. The research provides a new integration of diffusion of innovation elements with determinants of volitional behavior from persuasion literature, and offers recommendations on effective communication about new security technologies to motivate public adoption and enhance national safety. © 2017 Society for Risk Analysis.

Landbird Monitoring Protocol for National Parks in the North Coast and Cascades Network

USGS Publications Warehouse

Siegel, Rodney B.; Wilkerson, Robert L.; Jenkins, Kurt J.; Kuntz, Robert C.; Boetsch, John R.; Schaberl, James P.; Happe, Patricia J.

2007-01-01

This protocol narrative outlines the rationale, sampling design and methods for monitoring landbirds in the North Coast and Cascades Network (NCCN) during the breeding season. The NCCN, one of 32 networks of parks in the National Park System, comprises seven national park units in the Pacific Northwest, including three large, mountainous, natural area parks (Mount Rainier [MORA] and Olympic [OLYM] National Parks, North Cascades National Park Service Complex [NOCA]), and four small historic cultural parks (Ebey's Landing National Historical Reserve [EBLA], Lewis and Clark National Historical Park [LEWI], Fort Vancouver National Historical Park [FOVA], and San Juan Island National Historical Park [SAJH]). The protocol reflects decisions made by the NCCN avian monitoring group, which includes NPS representatives from each of the large parks in the Network as well as personnel from the U.S. Geological Survey Forest and Rangeland Ecosystem Science Center (USGS-FRESC) Olympic Field Station, and The Institute for Bird Populations, at meetings held between 2000 (Siegel and Kuntz, 2000) and 2005. The protocol narrative describes the monitoring program in relatively broad terms, and its structure and content adhere to the outline and recommendations developed by Oakley and others (2003) and adopted by NPS. Finer details of the methodology are addressed in a set of standard operating procedures (SOPs) that accompany the protocol narrative. We also provide appendixes containing additional supporting materials that do not clearly belong in either the protocol narrative or the standard operating procedures.

Disrupted topological organization of structural networks revealed by probabilistic diffusion tractography in Tourette syndrome children.

PubMed

Wen, Hongwei; Liu, Yue; Rekik, Islem; Wang, Shengpei; Zhang, Jishui; Zhang, Yue; Peng, Yun; He, Huiguang

2017-08-01

Tourette syndrome (TS) is a childhood-onset neurobehavioral disorder. Although previous TS studies revealed structural abnormalities in distinct corticobasal ganglia circuits, the topological alterations of the whole-brain white matter (WM) structural networks remain poorly understood. Here, we used diffusion MRI probabilistic tractography and graph theoretical analysis to investigate the topological organization of WM networks in 44 drug-naive TS children and 41 age- and gender-matched healthy children. The WM networks were constructed by estimating inter-regional connectivity probability and the topological properties were characterized using graph theory. We found that both TS and control groups showed an efficient small-world organization in WM networks. However, compared to controls, TS children exhibited decreased global and local efficiency, increased shortest path length and small worldness, indicating a disrupted balance between local specialization and global integration in structural networks. Although both TS and control groups showed highly similar hub distributions, TS children exhibited significant decreased nodal efficiency, mainly distributed in the default mode, language, visual, and sensorimotor systems. Furthermore, two separate networks showing significantly decreased connectivity in TS group were identified using network-based statistical (NBS) analysis, primarily composed of the parieto-occipital cortex, precuneus, and paracentral lobule. Importantly, we combined support vector machine and multiple kernel learning frameworks to fuse multiple levels of network topological features for classification of individuals, achieving high accuracy of 86.47%. Together, our study revealed the disrupted topological organization of structural networks related to pathophysiology of TS, and the discriminative topological features for classification are potential quantitative neuroimaging biomarkers for clinical TS diagnosis. Hum Brain Mapp 38:3988-4008, 2017

Hopf Bifurcation Analysis of a Gene Regulatory Network Mediated by Small Noncoding RNA with Time Delays and Diffusion

NASA Astrophysics Data System (ADS)

Li, Chengxian; Liu, Haihong; Zhang, Tonghua; Yan, Fang

2017-12-01

In this paper, a gene regulatory network mediated by small noncoding RNA involving two time delays and diffusion under the Neumann boundary conditions is studied. Choosing the sum of delays as the bifurcation parameter, the stability of the positive equilibrium and the existence of spatially homogeneous and spatially inhomogeneous periodic solutions are investigated by analyzing the corresponding characteristic equation. It is shown that the sum of delays can induce Hopf bifurcation and the diffusion incorporated into the system can effect the amplitude of periodic solutions. Furthermore, the spatially homogeneous periodic solution always exists and the spatially inhomogeneous periodic solution will arise when the diffusion coefficients of protein and mRNA are suitably small. Particularly, the small RNA diffusion coefficient is more robust and its effect on model is much less than protein and mRNA. Finally, the explicit formulae for determining the direction of Hopf bifurcation and the stability of the bifurcating periodic solutions are derived by employing the normal form theory and center manifold theorem for partial functional differential equations. Finally, numerical simulations are carried out to illustrate our theoretical analysis.

78 FR 10249 - Establishment of the National Freight Network

Federal Register 2010, 2011, 2012, 2013, 2014

2013-02-13

... DEPARTMENT OF TRANSPORTATION Federal Highway Administration Establishment of the National Freight Network Correction In notice document 2013-02580 appearing on pages 8686-8689, in the issue of Wednesday, February 6, 2013, make the following correction: In the Table appearing on page 8687, in the third column...

Diffusion properties of molecules at the blood-brain interface: potential contributions of astrocyte endfeet to diffusion barrier functions.

PubMed

Nuriya, Mutsuo; Shinotsuka, Takanori; Yasui, Masato

2013-09-01

Molecular diffusion in the extracellular space (ECS) plays a key role in determining tissue physiology and pharmacology. The blood-brain barrier regulates the exchange of substances between the brain and the blood, but the diffusion properties of molecules at this blood-brain interface, particularly around the astrocyte endfeet, are poorly characterized. In this study, we used 2-photon microscopy and acute brain slices of mouse neocortex and directly assessed the diffusion patterns of fluorescent molecules. By observing the diffusion of unconjugated and 10-kDa dextran-conjugated Alexa Fluor 488 from the ECS of the brain parenchyma to the blood vessels, we find various degrees of diffusion barriers at the endfeet: Some allow the invasion of dye inside the endfoot network while others completely block it. Detailed analyses of the time course for dye clearance support the existence of a tight endfoot network capable of acting as a diffusion barrier. Finally, we show that this diffusion pattern collapses under pathological conditions. These data demonstrate the heterogeneous nature of molecular diffusion dynamics around the endfeet and suggest that these structures can serve as the diffusion barrier. Therefore, astrocyte endfeet may add another layer of regulation to the exchange of molecules between blood vessels and brain parenchyma.

Reduced integration and differentiation of the imitation network in autism: A combined functional connectivity magnetic resonance imaging and diffusion-weighted imaging study.

PubMed

Fishman, Inna; Datko, Michael; Cabrera, Yuliana; Carper, Ruth A; Müller, Ralph-Axel

2015-12-01

Converging evidence indicates that brain abnormalities in autism spectrum disorder (ASD) involve atypical network connectivity, but few studies have integrated functional with structural connectivity measures. This multimodal investigation examined functional and structural connectivity of the imitation network in children and adolescents with ASD, and its links with clinical symptoms. Resting state functional magnetic resonance imaging and diffusion-weighted imaging were performed in 35 participants with ASD and 35 typically developing controls, aged 8 to 17 years, matched for age, gender, intelligence quotient, and head motion. Within-network analyses revealed overall reduced functional connectivity (FC) between distributed imitation regions in the ASD group. Whole brain analyses showed that underconnectivity in ASD occurred exclusively in regions belonging to the imitation network, whereas overconnectivity was observed between imitation nodes and extraneous regions. Structurally, reduced fractional anisotropy and increased mean diffusivity were found in white matter tracts directly connecting key imitation regions with atypical FC in ASD. These differences in microstructural organization of white matter correlated with weaker FC and greater ASD symptomatology. Findings demonstrate atypical connectivity of the brain network supporting imitation in ASD, characterized by a highly specific pattern. This pattern of underconnectivity within, but overconnectivity outside the functional network is in contrast with typical development and suggests reduced network integration and differentiation in ASD. Our findings also indicate that atypical connectivity of the imitation network may contribute to ASD clinical symptoms, highlighting the role of this fundamental social cognition ability in the pathophysiology of ASD. © 2015 American Neurological Association.

Toward implementation of a national ground water monitoring network

USGS Publications Warehouse

Schreiber, Robert P.; Cunningham, William L.; Copeland, Rick; Frederick, Kevin D.

2008-01-01

The Federal Advisory Committee on Water Information's (ACWI) Subcommittee on Ground Water (SOGW) has been working steadily to develop and encourage implementation of a nationwide, long-term ground-water quantity and quality monitoring framework. Significant progress includes the planned submission this fall of a draft framework document to the full committee. The document will include recommendations for implementation of the network and continued acknowledgment at the federal and state level of ACWI's potential role in national monitoring toward an improved assessment of the nation's water reserves. The SOGW mission includes addressing several issues regarding network design, as well as developing plans for concept testing, evaluation of costs and benefits, and encouraging the movement from pilot-test results to full-scale implementation within a reasonable time period. With the recent attention to water resource sustainability driven by severe droughts, concerns over global warming effects, and persistent water supply problems, the SOGW mission is now even more critical.

External quality assurance project report for the National Atmospheric Deposition Program’s National Trends Network and Mercury Deposition Network, 2015–16

USGS Publications Warehouse

Wetherbee, Gregory A.; Martin, RoseAnn

2018-06-29

The U.S. Geological Survey Precipitation Chemistry Quality Assurance project operated five distinct programs to provide external quality assurance monitoring for the National Atmospheric Deposition Program’s (NADP) National Trends Network and Mercury Deposition Network during 2015–16. The National Trends Network programs include (1) a field audit program to evaluate sample contamination and stability, (2) an interlaboratory comparison program to evaluate analytical laboratory performance, and (3) a colocated sampler program to evaluate bias and variability attributed to automated precipitation samplers. The Mercury Deposition Network programs include the (4) system blank program and (5) an interlaboratory comparison program. The results indicate that NADP data continue to be of sufficient quality for the analysis of spatial distributions and time trends for chemical constituents in wet deposition.The field audit program results indicate increased sample contamination for calcium, magnesium, and potassium relative to 2010 levels, and slight fluctuation in sodium contamination. Nitrate contamination levels dropped slightly during 2014–16, and chloride contamination leveled off between 2007 and 2016. Sulfate contamination is similar to the 2000 level. Hydrogen ion contamination has steadily decreased since 2012. Losses of ammonium and nitrate resulting from potential sample instability were negligible.The NADP Central Analytical Laboratory produced interlaboratory comparison results with low bias and variability compared to other domestic and international laboratories that support atmospheric deposition monitoring. Significant absolute bias above the magnitudes of the detection limits was observed for nitrate and sulfate concentrations, but no analyte determinations exceeded the detection limits for blanks.Colocated sampler program results from dissimilar colocated collectors indicate that the retrofit of the National Trends Network with N-CON Systems Company

Self-diffusion in dense granular shear flows.

PubMed

Utter, Brian; Behringer, R P

2004-03-01

Diffusivity is a key quantity in describing velocity fluctuations in granular materials. These fluctuations are the basis of many thermodynamic and hydrodynamic models which aim to provide a statistical description of granular systems. We present experimental results on diffusivity in dense, granular shear flows in a two-dimensional Couette geometry. We find that self-diffusivities D are proportional to the local shear rate gamma; with diffusivities along the direction of the mean flow approximately twice as large as those in the perpendicular direction. The magnitude of the diffusivity is D approximately gamma;a(2), where a is the particle radius. However, the gradient in shear rate, coupling to the mean flow, and strong drag at the moving boundary lead to particle displacements that can appear subdiffusive or superdiffusive. In particular, diffusion appears to be superdiffusive along the mean flow direction due to Taylor dispersion effects and subdiffusive along the perpendicular direction due to the gradient in shear rate. The anisotropic force network leads to an additional anisotropy in the diffusivity that is a property of dense systems and has no obvious analog in rapid flows. Specifically, the diffusivity is suppressed along the direction of the strong force network. A simple random walk simulation reproduces the key features of the data, such as the apparent superdiffusive and subdiffusive behavior arising from the mean velocity field, confirming the underlying diffusive motion. The additional anisotropy is not observed in the simulation since the strong force network is not included. Examples of correlated motion, such as transient vortices, and Lévy flights are also observed. Although correlated motion creates velocity fields which are qualitatively different from collisional Brownian motion and can introduce nondiffusive effects, on average the system appears simply diffusive.

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

NASA Astrophysics Data System (ADS)

Zendejas, Gerardo; Chiasson, Mike

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

Database Software Selection for the Egyptian National STI Network.

ERIC Educational Resources Information Center

Slamecka, Vladimir

The evaluation and selection of information/data management system software for the Egyptian National Scientific and Technical (STI) Network are described. An overview of the state-of-the-art of database technology elaborates on the differences between information retrieval and database management systems (DBMS). The desirable characteristics of…

Mechanisms of Innovation Diffusion under Information Abundance and Information Scarcity--On the Contribution of Social Networks in Group vs. Individual Extension Approaches in Semi-Arid Kenya

ERIC Educational Resources Information Center

Darr, Dietrich; Pretzsch, Jurgen

2008-01-01

Purpose: The objective of this paper is to assess the effectiveness of innovation diffusion under group-oriented and individual-oriented extension. Current theoretical notions of innovation diffusion in social networks shall be briefly reviewed, and the concepts of "search" and "innovation" vis-a-vis "transfer" and…

Sentiment Diffusion of Public Opinions about Hot Events: Based on Complex Network

PubMed Central

Hao, Xiaoqing; An, Haizhong; Zhang, Lijia; Li, Huajiao; Wei, Guannan

2015-01-01

To study the sentiment diffusion of online public opinions about hot events, we collected people’s posts through web data mining techniques. We calculated the sentiment value of each post based on a sentiment dictionary. Next, we divided those posts into five different orientations of sentiments: strongly positive (P), weakly positive (p), neutral (o), weakly negative (n), and strongly negative (N). These sentiments are combined into modes through coarse graining. We constructed sentiment mode complex network of online public opinions (SMCOP) with modes as nodes and the conversion relation in chronological order between different types of modes as edges. We calculated the strength, k-plex clique, clustering coefficient and betweenness centrality of the SMCOP. The results show that the strength distribution obeys power law. Most posts’ sentiments are weakly positive and neutral, whereas few are strongly negative. There are weakly positive subgroups and neutral subgroups with ppppp and ooooo as the core mode, respectively. Few modes have larger betweenness centrality values and most modes convert to each other with these higher betweenness centrality modes as mediums. Therefore, the relevant person or institutes can take measures to lead people’s sentiments regarding online hot events according to the sentiment diffusion mechanism. PMID:26462230

Establishing the ACORN National Practitioner Database: Strategies to Recruit Practitioners to a National Practice-Based Research Network.

PubMed

Adams, Jon; Steel, Amie; Moore, Craig; Amorin-Woods, Lyndon; Sibbritt, David

2016-10-01

The purpose of this paper is to report on the recruitment and promotion strategies employed by the Australian Chiropractic Research Network (ACORN) project aimed at helping recruit a substantial national sample of participants and to describe the features of our practice-based research network (PBRN) design that may provide key insights to others looking to establish a similar network or draw on the ACORN project to conduct sub-studies. The ACORN project followed a multifaceted recruitment and promotion strategy drawing on distinct branding, a practitioner-focused promotion campaign, and a strategically designed questionnaire and distribution/recruitment approach to attract sufficient participation from the ranks of registered chiropractors across Australia. From the 4684 chiropractors registered at the time of recruitment, the project achieved a database response rate of 36% (n = 1680), resulting in a large, nationally representative sample across age, gender, and location. This sample constitutes the largest proportional coverage of participants from any voluntary national PBRN across any single health care profession. It does appear that a number of key promotional and recruitment features of the ACORN project may have helped establish the high response rate for the PBRN, which constitutes an important sustainable resource for future national and international efforts to grow the chiropractic evidence base and research capacity. Further rigorous enquiry is needed to help evaluate the direct contribution of specific promotional and recruitment strategies in attaining high response rates from practitioner populations who may be invited to participate in future PBRNs. Copyright © 2016. Published by Elsevier Inc.

Project: Toward a National Educational Testing Network. Final Report.

ERIC Educational Resources Information Center

Bock, Darrell R.

Three fiscal year 1987 deliverables due for the "Toward a National Educational Testing Network: Feasibility Study of Duplex Design" are presented. The study is concerned with implementation of statewide and interstate testing of student attainment. The report includes: (1) a duplex design (DD) review paper discussing the means by which…

Effective Instruction. National Dropout Prevention Center/Network Newsletter. Volume 21, Number 2

ERIC Educational Resources Information Center

Duckenfield, Marty, Ed.

2009-01-01

The "National Dropout Prevention Newsletter" is published quarterly by the National Dropout Prevention Center/Network. This issue contains the following articles: (1) Strategies for Success (Charles W. Hatch); (2) 2009 NDPN Crystal Star Winners; (3) Strategies for More Effective Instruction (Micki Gibson); (4) Some Thoughts on Teaching…

Service-Learning. National Dropout Prevention Center/Network Newsletter. Volume 22, Number 4

ERIC Educational Resources Information Center

Duckenfield, Marty, Ed.

2011-01-01

The "National Dropout Prevention Newsletter" is published quarterly by the National Dropout Prevention Center/Network. This issue contains the following articles: (1) Dropouts and Democracy (Robert Shumer); (2) 2011 NDPN Crystal Star Winners; (3) Service-Learning as Dropout Intervention and More (Michael VanKeulen); and (4) Teacher…

Modernization of the Slovenian National Seismic Network

NASA Astrophysics Data System (ADS)

Vidrih, R.; Godec, M.; Gosar, A.; Sincic, P.; Tasic, I.; Zivcic, M.

2003-04-01

The Environmental Agency of the Republic of Slovenia, the Seismology Office is responsible for the fast and reliable information about earthquakes, originating in the area of Slovenia and nearby. In the year 2000 the project Modernization of the Slovenian National Seismic Network started. The purpose of a modernized seismic network is to enable fast and accurate automatic location of earthquakes, to determine earthquake parameters and to collect data of local, regional and global earthquakes. The modernized network will be finished in the year 2004 and will consist of 25 Q730 remote broadband data loggers based seismic station subsystems transmitting in real-time data to the Data Center in Ljubljana, where the Seismology Office is located. The remote broadband station subsystems include 16 surface broadband seismometers CMG-40T, 5 broadband seismometers CMG-40T with strong motion accelerographs EpiSensor, 4 borehole broadband seismometers CMG-40T, all with accurate timing provided by GPS receivers. The seismic network will cover the entire Slovenian territory, involving an area of 20,256 km2. The network is planned in this way; more seismic stations will be around bigger urban centres and in regions with greater vulnerability (NW Slovenia, Krsko Brezice region). By the end of the year 2002, three old seismic stations were modernized and ten new seismic stations were built. All seismic stations transmit data to UNIX-based computers running Antelope system software. The data is transmitted in real time using TCP/IP protocols over the Goverment Wide Area Network . Real-time data is also exchanged with seismic networks in the neighbouring countries, where the data are collected from the seismic stations, close to the Slovenian border. A typical seismic station consists of the seismic shaft with the sensor and the data acquisition system and, the service shaft with communication equipment (modem, router) and power supply with a battery box. which provides energy in case

Implementation and integration of regional health care data networks in the Hellenic National Health Service.

PubMed

Lampsas, Petros; Vidalis, Ioannis; Papanikolaou, Christos; Vagelatos, Aristides

2002-12-01

Modern health care is provided with close cooperation among many different institutions and professionals, using their specialized expertise in a common effort to deliver best-quality and, at the same time, cost-effective services. Within this context of the growing need for information exchange, the demand for realization of data networks interconnecting various health care institutions at a regional level, as well as a national level, has become a practical necessity. To present the technical solution that is under consideration for implementing and interconnecting regional health care data networks in the Hellenic National Health System. The most critical requirements for deploying such a regional health care data network were identified as: fast implementation, security, quality of service, availability, performance, and technical support. The solution proposed is the use of proper virtual private network technologies for implementing functionally-interconnected regional health care data networks. The regional health care data network is considered to be a critical infrastructure for further development and penetration of information and communication technologies in the Hellenic National Health System. Therefore, a technical approach was planned, in order to have a fast cost-effective implementation, conforming to certain specifications.

Implementation and Integration of Regional Health Care Data Networks in the Hellenic National Health Service

PubMed Central

Vidalis, Ioannis; Papanikolaou, Christos; Vagelatos, Aristides

2002-01-01

Background Modern health care is provided with close cooperation among many different institutions and professionals, using their specialized expertise in a common effort to deliver best-quality and, at the same time, cost-effective services. Within this context of the growing need for information exchange, the demand for realization of data networks interconnecting various health care institutions at a regional level, as well as a national level, has become a practical necessity. Objectives To present the technical solution that is under consideration for implementing and interconnecting regional health care data networks in the Hellenic National Health System. Methods The most critical requirements for deploying such a regional health care data network were identified as: fast implementation, security, quality of service, availability, performance, and technical support. Results The solution proposed is the use of proper virtual private network technologies for implementing functionally-interconnected regional health care data networks. Conclusions The regional health care data network is considered to be a critical infrastructure for further development and penetration of information and communication technologies in the Hellenic National Health System. Therefore, a technical approach was planned, in order to have a fast cost-effective implementation, conforming to certain specifications. PMID:12554551

Bias and precision of selected analytes reported by the National Atmospheric Deposition Program and National Trends Network, 1984

USGS Publications Warehouse

Brooks, M.H.; Schroder, L.J.; Willoughby, T.C.

1987-01-01

The U.S. Geological Survey operated a blind audit sample program during 1974 to test the effects of the sample handling and shipping procedures used by the National Atmospheric Deposition Program and National Trends Network on the quality of wet deposition data produced by the combined networks. Blind audit samples, which were dilutions of standard reference water samples, were submitted by network site operators to the central analytical laboratory disguised as actual wet deposition samples. Results from the analyses of blind audit samples were used to calculate estimates of analyte bias associated with all network wet deposition samples analyzed in 1984 and to estimate analyte precision. Concentration differences between double blind samples that were submitted to the central analytical laboratory and separate analyses of aliquots of those blind audit samples that had not undergone network sample handling and shipping were used to calculate analyte masses that apparently were added to each blind audit sample by routine network handling and shipping procedures. These calculated masses indicated statistically significant biases for magnesium, sodium , potassium, chloride, and sulfate. Median calculated masses were 41.4 micrograms (ug) for calcium, 14.9 ug for magnesium, 23.3 ug for sodium, 0.7 ug for potassium, 16.5 ug for chloride and 55.3 ug for sulfate. Analyte precision was estimated using two different sets of replicate measures performed by the central analytical laboratory. Estimated standard deviations were similar to those previously reported. (Author 's abstract)

Assessment of the National Park network of mainland Spain by the Insecurity Index of vertebrate species.

PubMed

Estrada, Alba; Real, Raimundo

2018-01-01

The evaluation of protected area networks on their capacity to preserve species distributions is a key topic in conservation biology. There are different types of protected areas, with National Parks those with highest level of protection. National Parks can be declared attending to many ecological features that include the presence of certain animal species. Here, we selected 37 vertebrate species that were highlighted as having relevant natural value for at least one of the 10 National Parks of mainland Spain. We modelled species distributions with the favourability function, and applied the Insecurity Index to detect the degree of protection of favourable areas for each species. Two metrics of Insecurity Index were defined for each species: the Insecurity Index in each of the cells, and the Overall Insecurity Index of a species. The former allows the identification of insecure areas for each species that can be used to establish spatial conservation priorities. The latter gives a value of Insecurity for each species, which we used to calculate the Representativeness of favourable areas for the species in the network. As expected, due to the limited extension of the National Park network, all species have high values of Insecurity; i.e., just a narrow proportion of their favourable areas are covered by a National Park. However, the majority of species favourable areas are well represented in the network, i.e., the percentage of favourable areas covered by the National Park network is higher than the percentage of mainland Spain covered by the network (result also supported by a randomization approach). Even if a reserve network only covers a low percentage of a country, the Overall Insecurity Index allows an objective assessment of its capacity to represent species. Beyond the results presented here, the Insecurity Index has the potential to be extrapolated to other areas and to cover a wide range of species.

National Human Trafficking Initiatives: Dimensions of Policy Diffusion1

PubMed Central

Yoo, Eun-hye; Boyle, Elizabeth Heger

2014-01-01

The implementation of criminal law involves formal law enforcement, education and public outreach aimed at preventing criminal activity, and providing services for victims. Historically, quantitative research on global trends has tended to focus on a single policy dimension, potentially masking the unique factors that affect the diffusion of each policy dimension independently. Using an ordered-probit model to analyze new human trafficking policy data on national prosecution, prevention, and victim-protection efforts, we find that global ties and domestic interest groups matter more in areas where international law is less defined. While prosecution, officially mandated by the Trafficking Protocol, was relatively impervious to global ties and domestic interest groups, both trafficking prevention and victim protection were associated with these factors. Our findings also suggest that fear of repercussions is not a major driver of state actions to combat trafficking—neither ratification of the Trafficking Protocol nor levels of United States aid were associated with greater implementation of anti-trafficking measures. PMID:26538806

Group-Level Progressive Alterations in Brain Connectivity Patterns Revealed by Diffusion-Tensor Brain Networks across Severity Stages in Alzheimer’s Disease

PubMed Central

Rasero, Javier; Alonso-Montes, Carmen; Diez, Ibai; Olabarrieta-Landa, Laiene; Remaki, Lakhdar; Escudero, Iñaki; Mateos, Beatriz; Bonifazi, Paolo; Fernandez, Manuel; Arango-Lasprilla, Juan Carlos; Stramaglia, Sebastiano; Cortes, Jesus M.

2017-01-01

Alzheimer’s disease (AD) is a chronically progressive neurodegenerative disease highly correlated to aging. Whether AD originates by targeting a localized brain area and propagates to the rest of the brain across disease-severity progression is a question with an unknown answer. Here, we aim to provide an answer to this question at the group-level by looking at differences in diffusion-tensor brain networks. In particular, making use of data from Alzheimer’s Disease Neuroimaging Initiative (ADNI), four different groups were defined (all of them matched by age, sex and education level): G1 (N1 = 36, healthy control subjects, Control), G2 (N2 = 36, early mild cognitive impairment, EMCI), G3 (N3 = 36, late mild cognitive impairment, LMCI) and G4 (N4 = 36, AD). Diffusion-tensor brain networks were compared across three disease stages: stage I (Control vs. EMCI), stage II (Control vs. LMCI) and stage III (Control vs. AD). The group comparison was performed using the multivariate distance matrix regression analysis, a technique that was born in genomics and was recently proposed to handle brain functional networks, but here applied to diffusion-tensor data. The results were threefold: First, no significant differences were found in stage I. Second, significant differences were found in stage II in the connectivity pattern of a subnetwork strongly associated to memory function (including part of the hippocampus, amygdala, entorhinal cortex, fusiform gyrus, inferior and middle temporal gyrus, parahippocampal gyrus and temporal pole). Third, a widespread disconnection across the entire AD brain was found in stage III, affecting more strongly the same memory subnetwork appearing in stage II, plus the other new subnetworks, including the default mode network, medial visual network, frontoparietal regions and striatum. Our results are consistent with a scenario where progressive alterations of connectivity arise as the disease severity increases and provide the brain areas

Linking Geophysical Networks to International Economic Development Through Integration of Global and National Monitoring

NASA Astrophysics Data System (ADS)

Lerner-Lam, A.

2007-05-01

Outside of the research community and mission agencies, global geophysical monitoring rarely receives sustained attention except in the aftermath of a humanitarian disaster. The recovery and rebuilding period focuses attention and resources for a short time on regional needs for geophysical observation, often at the national or sub-national level. This can result in the rapid deployment of national monitoring networks, but may overlook the longer-term benefits of integration with global networks. Even in the case of multinational disasters, such as the Indian Ocean tsunami, it has proved difficult to promote the integration of national solutions with global monitoring, research and operations infrastructure. More importantly, continuing operations at the national or sub-national scale are difficult to sustain once the resources associated with recovery and rebuilding are depleted. Except for some notable examples, the vast infrastructure associated with global geophysical monitoring is not utilized constructively to promote the integration of national networks with international efforts. This represents a missed opportunity not only for monitoring, but for developing the international research and educational collaborations necessary for technological transfer and capacity building. The recent confluence of highly visible disasters, global multi-hazard risk assessments, evaluations of the relationships between natural disasters and socio-economic development, and shifts in development agency policies, provides an opportunity to link global geophysical monitoring initiatives to central issues in international development. Natural hazard risk reduction has not been the first priority of international development agendas for understandable, mainly humanitarian reasons. However, it is now recognized that the so-called risk premium associated with making development projects more risk conscious or risk resilient is relatively small relative to potential losses. Thus

77 FR 20010 - Notice of Public Workshop: “Designing for Impact: Workshop on Building the National Network for...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-04-03

...: ``Designing for Impact: Workshop on Building the National Network for Manufacturing Innovation'' AGENCY...), housed at the National Institute of Standards and Technology (NIST), announces the first of a series of public workshops entitled ``Designing for Impact: Workshop on Building the National Network for...

U.S. EPA's National Dioxin Air Monitoring Network: Analytical Issues

EPA Science Inventory

The U.S. EPA has established a National Dioxin Air Monitoring Network (NDAMN) to determine the temporal and geographical variability of atmospheric chlorinated dibenzo-p-dioxins (CDDs), furans (CDFs), and coplanar polychlorinated biphenyls (PCBs) at rural and non-impacted locatio...

Scale-free network provides an optimal pattern for knowledge transfer

NASA Astrophysics Data System (ADS)

Lin, Min; Li, Nan

2010-02-01

We study numerically the knowledge innovation and diffusion process on four representative network models, such as regular networks, small-world networks, random networks and scale-free networks. The average knowledge stock level as a function of time is measured and the corresponding growth diffusion time, τ is defined and computed. On the four types of networks, the growth diffusion times all depend linearly on the network size N as τ∼N, while the slope for scale-free network is minimal indicating the fastest growth and diffusion of knowledge. The calculated variance and spatial distribution of knowledge stock illustrate that optimal knowledge transfer performance is obtained on scale-free networks. We also investigate the transient pattern of knowledge diffusion on the four networks, and a qualitative explanation of this finding is proposed.

Project UNIFY. National Dropout Prevention Center/Network Newsletter. Volume 22, Number 1

ERIC Educational Resources Information Center

Duckenfield, Marty, Ed.

2011-01-01

The "National Dropout Prevention Newsletter" is published quarterly by the National Dropout Prevention Center/Network. This issue contains the following articles: (1) Special Olympics Project UNIFY (Andrea Cahn); (2) The Impact of Project UNIFY; (3) Project UNIFY Brings Youth Together to Learn and Graduate (William H. Hughes); (4)…

"Repeating Events" as Estimator of Location Precision: The China National Seismograph Network

NASA Astrophysics Data System (ADS)

Jiang, Changsheng; Wu, Zhongliang; Li, Yutong; Ma, Tengfei

2014-03-01

"Repeating earthquakes" identified by waveform cross-correlation, with inter-event separation of no more than 1 km, can be used for assessment of location precision. Assuming that the network-measured apparent inter-epicenter distance X of the "repeating doublets" indicates the location precision, we estimated the regionalized location quality of the China National Seismograph Network by comparing the "repeating events" in and around China by S chaff and R ichards (Science 303: 1176-1178, 2004; J Geophys Res 116: B03309, 2011) and the monthly catalogue of the China Earthquake Networks Center. The comparison shows that the average X value of the China National Seismograph Network is approximately 10 km. The mis-location is larger for the Tibetan Plateau, west and north of Xinjiang, and east of Inner Mongolia, as indicated by larger X values. Mis-location is correlated with the completeness magnitude of the earthquake catalogue. Using the data from the Beijing Capital Circle Region, the dependence of the mis-location on the distribution of seismic stations can be further confirmed.

Family Engagement. National Dropout Prevention Center/Network Newsletter. Volume 20, Number 2

ERIC Educational Resources Information Center

Duckenfield, Marty, Ed.

2008-01-01

The "National Dropout Prevention Newsletter" is published quarterly by the National Dropout Prevention Center/Network. This issue contains the following articles: (1) Family/School Relationships: Relationships That Matter; (2) Program Profile; (3) Engaging Families in the Pathway to College: Lessons From Schools That Are Beating the Odds (Anne T.…

Optimization of locations of diffusion spots in indoor optical wireless local area networks

NASA Astrophysics Data System (ADS)

Eltokhey, Mahmoud W.; Mahmoud, K. R.; Ghassemlooy, Zabih; Obayya, Salah S. A.

2018-03-01

In this paper, we present a novel optimization of the locations of the diffusion spots in indoor optical wireless local area networks, based on the central force optimization (CFO) scheme. The users' performance uniformity is addressed by using the CFO algorithm, and adopting different objective function's configurations, while considering maximization and minimization of the signal to noise ratio and the delay spread, respectively. We also investigate the effect of varying the objective function's weights on the system and the users' performance as part of the adaptation process. The results show that the proposed objective function configuration-based optimization procedure offers an improvement of 65% in the standard deviation of individual receivers' performance.

Network-based diffusion analysis reveals cultural transmission of lobtail feeding in humpback whales.

PubMed

Allen, Jenny; Weinrich, Mason; Hoppitt, Will; Rendell, Luke

2013-04-26

We used network-based diffusion analysis to reveal the cultural spread of a naturally occurring foraging innovation, lobtail feeding, through a population of humpback whales (Megaptera novaeangliae) over a period of 27 years. Support for models with a social transmission component was 6 to 23 orders of magnitude greater than for models without. The spatial and temporal distribution of sand lance, a prey species, was also important in predicting the rate of acquisition. Our results, coupled with existing knowledge about song traditions, show that this species can maintain multiple independently evolving traditions in its populations. These insights strengthen the case that cetaceans represent a peak in the evolution of nonhuman culture, independent of the primate lineage.

The Continuing Growth of Global Cooperation Networks in Research: A Conundrum for National Governments

PubMed Central

Wagner, Caroline S.; Park, Han Woo; Leydesdorff, Loet

2015-01-01

Global collaboration continues to grow as a share of all scientific cooperation, measured as coauthorships of peer-reviewed, published papers. The percent of all scientific papers that are internationally coauthored has more than doubled in 20 years, and they account for all the growth in output among the scientifically advanced countries. Emerging countries, particularly China, have increased their participation in global science, in part by doubling their spending on R&D; they are increasingly likely to appear as partners on internationally coauthored scientific papers. Given the growth of connections at the international level, it is helpful to examine the phenomenon as a communications network and to consider the network as a new organization on the world stage that adds to and complements national systems. When examined as interconnections across the globe over two decades, a global network has grown denser but not more clustered, meaning there are many more connections but they are not grouping into exclusive ‘cliques’. This suggests that power relationships are not reproducing those of the political system. The network has features an open system, attracting productive scientists to participate in international projects. National governments could gain efficiencies and influence by developing policies and strategies designed to maximize network benefits—a model different from those designed for national systems. PMID:26196296

Stories about ourselves: How national narratives influence the diffusion of large-scale energy technologies

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

Malone, Elizabeth L.; Hultman, Nathan E.; Anderson, Kate

Examining past examples of rapid, transformational changes in energy technologies could help governments understand the factors associated with such transitions. We used an existing dataset to assess government strategies to connect new energy technologies with national narratives. Analyzing the diffusion stories told by experts, we demonstrate how governments connected the new technologies with their national narratives. The United States government supported the development of nuclear power after World War II with the national narrative that the United States was destined to improve creation, increasing the potential of raw materials exponentially for the nation’s good (“atoms for peace,” electricity “too cheapmore » to meter”). In Brazil, the development of sugar cane ethanol was supported by the government’s invoking the national narrative of suffering leading to knowledge and redemption, coupled with the quest for improved societal well-being (technological development to produce ethanol and employment for farmers). In Sweden, biomass energy was tied to the national narrative of local control, as well as love of nature and tradition (the use of natural products). We found strong evidence that the pairing of technological transformations with national narratives facilitated the successful development and implementation of these major energy technologies in the three cases analyzed here.« less

Stories about ourselves: How national narratives influence the diffusion of large-scale energy technologies

DOE PAGES

Malone, Elizabeth L.; Hultman, Nathan E.; Anderson, Kate; ...

2017-07-03

Examining past examples of rapid, transformational changes in energy technologies could help governments understand the factors associated with such transitions. We used an existing dataset to assess government strategies to connect new energy technologies with national narratives. Analyzing the diffusion stories told by experts, we demonstrate how governments connected the new technologies with their national narratives. The United States government supported the development of nuclear power after World War II with the national narrative that the United States was destined to improve creation, increasing the potential of raw materials exponentially for the nation’s good (“atoms for peace,” electricity “too cheapmore » to meter”). In Brazil, the development of sugar cane ethanol was supported by the government’s invoking the national narrative of suffering leading to knowledge and redemption, coupled with the quest for improved societal well-being (technological development to produce ethanol and employment for farmers). In Sweden, biomass energy was tied to the national narrative of local control, as well as love of nature and tradition (the use of natural products). We found strong evidence that the pairing of technological transformations with national narratives facilitated the successful development and implementation of these major energy technologies in the three cases analyzed here.« less

Controllable uncertain opinion diffusion under confidence bound and unpredicted diffusion probability

NASA Astrophysics Data System (ADS)

Yan, Fuhan; Li, Zhaofeng; Jiang, Yichuan

2016-05-01

The issues of modeling and analyzing diffusion in social networks have been extensively studied in the last few decades. Recently, many studies focus on uncertain diffusion process. The uncertainty of diffusion process means that the diffusion probability is unpredicted because of some complex factors. For instance, the variety of individuals' opinions is an important factor that can cause uncertainty of diffusion probability. In detail, the difference between opinions can influence the diffusion probability, and then the evolution of opinions will cause the uncertainty of diffusion probability. It is known that controlling the diffusion process is important in the context of viral marketing and political propaganda. However, previous methods are hardly feasible to control the uncertain diffusion process of individual opinion. In this paper, we present suitable strategy to control this diffusion process based on the approximate estimation of the uncertain factors. We formulate a model in which the diffusion probability is influenced by the distance between opinions, and briefly discuss the properties of the diffusion model. Then, we present an optimization problem at the background of voting to show how to control this uncertain diffusion process. In detail, it is assumed that each individual can choose one of the two candidates or abstention based on his/her opinion. Then, we present strategy to set suitable initiators and their opinions so that the advantage of one candidate will be maximized at the end of diffusion. The results show that traditional influence maximization algorithms are not applicable to this problem, and our algorithm can achieve expected performance.

National network television news coverage of contraception - a content analysis.

PubMed

Patton, Elizabeth W; Moniz, Michelle H; Hughes, Lauren S; Buis, Lorraine; Howell, Joel

2017-01-01

The objective was to describe and analyze national network television news framing of contraception, recognizing that onscreen news can influence the public's knowledge and beliefs. We used the Vanderbilt Television News Archives and LexisNexis Database to obtain video and print transcripts of all relevant national network television news segments covering contraception from January 2010 to June 2014. We conducted a content analysis of 116 TV news segments covering contraception during the rollout of the Affordable Care Act. Segments were quantitatively coded for contraceptive methods covered, story sources used, and inclusion of medical and nonmedical content (intercoder reliability using Krippendorf's alpha ranged 0.6-1 for coded categories). Most (55%) news stories focused on contraception in general rather than specific methods. The most effective contraceptive methods were rarely discussed (implant, 1%; intrauterine device, 4%). The most frequently used sources were political figures (40%), advocates (25%), the general public (25%) and Catholic Church leaders (16%); medical professionals (11%) and health researchers (4%) appeared in a minority of stories. A minority of stories (31%) featured medical content. National network news coverage of contraception frequently focuses on contraception in political and social terms and uses nonmedical figures such as politicians and church leaders as sources. This focus deemphasizes the public health aspect of contraception, leading medical professionals and health content to be rarely featured. Media coverage of contraception may influence patients' views about contraception. Understanding the content, sources and medical accuracy of current media portrayals of contraception may enable health care professionals to dispel popular misperceptions. Published by Elsevier Inc.

Summer Learning. National Dropout Prevention Center/Network Newsletter. Volume 21, Number 3

ERIC Educational Resources Information Center

Duckenfield, Marty, Ed.

2010-01-01

The "National Dropout Prevention Newsletter" is published quarterly by the National Dropout Prevention Center/Network. This issue contains the following articles: (1) A New Vision of Summer Learning (Brenda McLaughlin); (2) Using Summers More Strategically to Bridge the 8th-9th Grade Transition (Brenda McLaughlin and Hillary Hardt); (3)…

GPs’ use of defibrillators and the national radio network in emergency primary healthcare in Norway

PubMed Central

Zakariassen, Erik; Hunskaar, Steinar

2008-01-01

Objective To study the geographic size of out-of-hours districts, the availability of defibrillators and use of the national radio network in Norway. Design Survey. Setting The emergency primary healthcare system in Norway. Subjects A total of 282 host municipalities responsible for 260 out-of-hours districts. Main outcome measures Size of out-of-hours districts, use of national radio network and access to a defibrillator in emergency situations. Results The out-of-hours districts have a wide range of areas, which gives a large variation in driving time for doctors on call. The median longest transport time for doctors in Norway is 45 minutes. In 46% of out-of-hours districts doctors bring their own defibrillator on emergency callouts. Doctors always use the national radio network in 52% of out-of-hours districts. Use of the radio network and access to a defibrillator are significantly greater in out-of-hours districts with a host municipality of fewer then 5000 inhabitants compared with host municipalities of more than 20 000 inhabitants. Conclusion In half of out-of-hours districts doctors on call always use the national radio network. Doctors in out-of-hours districts with a host municipality of fewer than 5000 inhabitants are in a better state of readiness to attend an emergency, compared with doctors working in larger host municipalities. PMID:18570012

Disrupted topological properties of brain white matter networks in left temporal lobe epilepsy: a diffusion tensor imaging study.

PubMed

Xu, Y; Qiu, S; Wang, J; Liu, Z; Zhang, R; Li, S; Cheng, L; Liu, Z; Wang, W; Huang, R

2014-10-24

Mesial temporal lobe epilepsy (mTLE) is the most common drug-refractory focal epilepsy in adults. Although previous functional and morphological studies have revealed abnormalities in the brain networks of mTLE, the topological organization of the brain white matter (WM) networks in mTLE patients is still ambiguous. In this study, we constructed brain WM networks for 14 left mTLE patients and 22 age- and gender-matched normal controls using diffusion tensor tractography and estimated the alterations of network properties in the mTLE brain networks using graph theoretical analysis. We found that networks for both the mTLE patients and the controls exhibited prominent small-world properties, suggesting a balanced topology of integration and segregation. However, the brain WM networks of mTLE patients showed a significant increased characteristic path length but significant decreased global efficiency, which indicate a disruption in the organization of the brain WM networks in mTLE patients. Moreover, we found significant between-group differences in the nodal properties in several brain regions, such as the left superior temporal gyrus, left hippocampus, the right occipital and right temporal cortices. The robustness analysis showed that the results were likely to be consistent for the networks constructed with different definitions of node and edge weight. Taken together, our findings may suggest an adverse effect of epileptic seizures on the organization of large-scale brain WM networks in mTLE patients. Copyright © 2014 IBRO. Published by Elsevier Ltd. All rights reserved.

The International Postal Network and Other Global Flows as Proxies for National Wellbeing.

PubMed

Hristova, Desislava; Rutherford, Alex; Anson, Jose; Luengo-Oroz, Miguel; Mascolo, Cecilia

2016-01-01

The digital exhaust left by flows of physical and digital commodities provides a rich measure of the nature, strength and significance of relationships between countries in the global network. With this work, we examine how these traces and the network structure can reveal the socioeconomic profile of different countries. We take into account multiple international networks of physical and digital flows, including the previously unexplored international postal network. By measuring the position of each country in the Trade, Postal, Migration, International Flights, IP and Digital Communications networks, we are able to build proxies for a number of crucial socioeconomic indicators such as GDP per capita and the Human Development Index ranking along with twelve other indicators used as benchmarks of national well-being by the United Nations and other international organisations. In this context, we have also proposed and evaluated a global connectivity degree measure applying multiplex theory across the six networks that accounts for the strength of relationships between countries. We conclude by showing how countries with shared community membership over multiple networks have similar socioeconomic profiles. Combining multiple flow data sources can help understand the forces which drive economic activity on a global level. Such an ability to infer proxy indicators in a context of incomplete information is extremely timely in light of recent discussions on measurement of indicators relevant to the Sustainable Development Goals.

The International Postal Network and Other Global Flows as Proxies for National Wellbeing

PubMed Central

Rutherford, Alex; Anson, Jose; Luengo-Oroz, Miguel; Mascolo, Cecilia

2016-01-01

The digital exhaust left by flows of physical and digital commodities provides a rich measure of the nature, strength and significance of relationships between countries in the global network. With this work, we examine how these traces and the network structure can reveal the socioeconomic profile of different countries. We take into account multiple international networks of physical and digital flows, including the previously unexplored international postal network. By measuring the position of each country in the Trade, Postal, Migration, International Flights, IP and Digital Communications networks, we are able to build proxies for a number of crucial socioeconomic indicators such as GDP per capita and the Human Development Index ranking along with twelve other indicators used as benchmarks of national well-being by the United Nations and other international organisations. In this context, we have also proposed and evaluated a global connectivity degree measure applying multiplex theory across the six networks that accounts for the strength of relationships between countries. We conclude by showing how countries with shared community membership over multiple networks have similar socioeconomic profiles. Combining multiple flow data sources can help understand the forces which drive economic activity on a global level. Such an ability to infer proxy indicators in a context of incomplete information is extremely timely in light of recent discussions on measurement of indicators relevant to the Sustainable Development Goals. PMID:27248142

Threshold behaviors of social dynamics and financial outcomes of Ponzi scheme diffusion in complex networks

NASA Astrophysics Data System (ADS)

Fu, Peihua; Zhu, Anding; Ni, He; Zhao, Xin; Li, Xiulin

2018-01-01

Ponzi schemes always lead to mass disasters after collapse. It is important to study the critical behaviors of both social dynamics and financial outcomes for Ponzi scheme diffusion in complex networks. We develop the potential-investor-divestor-investor (PIDI) model by considering the individual behavior of direct reinvestment. We find that only the spreading rate relates to the epidemic outbreak while the reinvestment rate relates to the zero and non-zero final states for social dynamics of both homo- and inhomogeneous networks. Financially, we find that there is a critical spreading threshold, above which the scheme needs not to use its own initial capital for taking off, i.e. the starting cost is covered by the rapidly inflowing funds. However, the higher the cost per recruit, the larger the critical spreading threshold and the worse the financial outcomes. Theoretical and simulation results also reveal that schemes are easier to take off in inhomogeneous networks. The reinvestment rate does not affect the starting. However, it improves the financial outcome in the early stages and postpones the outbreak of financial collapse. Some policy suggestions for the regulator from the perspective of social physics are proposed in the end of the paper.

Hopping Diffusion of Nanoparticles Subjected to Topological Constraints

NASA Astrophysics Data System (ADS)

Cai, Li-Heng; Panyukov, Sergey; Rubinstein, Michael

2013-03-01

We describe a novel hopping mechanism for diffusion of large non-sticky nanoparticles subjected to topological constraints in polymer solids (networks and gels) and entangled polymer liquids (melts and solutions). Probe particles with size larger than the mesh size of unentangled polymer networks (tube diameter of entangled polymer liquids) are trapped by the network (entanglement) cages at time scales longer than the relaxation time of the network (entanglement) strand. At long time scales, however, these particles can move further by hopping between neighboring confinement cages. This hopping is controlled by fluctuations of surrounding confinement cages, which could be large enough to allow particles to slip through. The terminal particle diffusion coefficient dominated by this hopping diffusion is appreciable for particles with size slightly larger than the network mesh size (tube diameter). Very large particles in polymer solids will be permanently trapped by local network cages, whereas they can still move in polymer liquids by waiting for entanglement cages to rearrange on the relaxation time scale of the liquids. We would like to acknowledge the financial support of NSF CHE-0911588, DMR-0907515, DMR-1121107, DMR-1122483, and CBET-0609087, NIH R01HL077546 and P50HL107168, and Cystic Fibrosis Foundation under grant RUBIN09XX0.

Improved knowledge diffusion model based on the collaboration hypernetwork

NASA Astrophysics Data System (ADS)

Wang, Jiang-Pan; Guo, Qiang; Yang, Guang-Yong; Liu, Jian-Guo

2015-06-01

The process for absorbing knowledge becomes an essential element for innovation in firms and in adapting to changes in the competitive environment. In this paper, we present an improved knowledge diffusion hypernetwork (IKDH) model based on the idea that knowledge will spread from the target node to all its neighbors in terms of the hyperedge and knowledge stock. We apply the average knowledge stock V(t) , the variable σ2(t) , and the variance coefficient c(t) to evaluate the performance of knowledge diffusion. By analyzing different knowledge diffusion ways, selection ways of the highly knowledgeable nodes, hypernetwork sizes and hypernetwork structures for the performance of knowledge diffusion, results show that the diffusion speed of IKDH model is 3.64 times faster than that of traditional knowledge diffusion (TKDH) model. Besides, it is three times faster to diffuse knowledge by randomly selecting "expert" nodes than that by selecting large-hyperdegree nodes as "expert" nodes. Furthermore, either the closer network structure or smaller network size results in the faster knowledge diffusion.

Rumor spreading model with noise interference in complex social networks

NASA Astrophysics Data System (ADS)

Zhu, Liang; Wang, Youguo

2017-03-01

In this paper, a modified susceptible-infected-removed (SIR) model has been proposed to explore rumor diffusion on complex social networks. We take variation of connectivity into consideration and assume the variation as noise. On the basis of related literature on virus networks, the noise is described as standard Brownian motion while stochastic differential equations (SDE) have been derived to characterize dynamics of rumor diffusion both on homogeneous networks and heterogeneous networks. Then, theoretical analysis on homogeneous networks has been demonstrated to investigate the solution of SDE model and the steady state of rumor diffusion. Simulations both on Barabási-Albert (BA) network and Watts-Strogatz (WS) network display that the addition of noise accelerates rumor diffusion and expands diffusion size, meanwhile, the spreading speed on BA network is much faster than on WS network under the same noise intensity. In addition, there exists a rumor diffusion threshold in statistical average meaning on homogeneous network which is absent on heterogeneous network. Finally, we find a positive correlation between peak value of infected individuals and noise intensity while a negative correlation between rumor lifecycle and noise intensity overall.

An historical overview of the National Network of Libraries of Medicine, 1985-2015.

PubMed

Speaker, Susan L

2018-04-01

The National Network of Libraries of Medicine (NNLM), established as the Regional Medical Library Program in 1965, has a rich and remarkable history. The network's first twenty years were documented in a detailed 1987 history by Alison Bunting, AHIP, FMLA. This article traces the major trends in the network's development since then: reconceiving the Regional Medical Library staff as a "field force" for developing, marketing, and distributing a growing number of National Library of Medicine (NLM) products and services; subsequent expansion of outreach to health professionals who are unaffiliated with academic medical centers, particularly those in public health; the advent of the Internet during the 1990s, which brought the migration of NLM and NNLM resources and services to the World Wide Web, and a mandate to encourage and facilitate Internet connectivity in the network; and the further expansion of the NLM and NNLM mission to include providing consumer health resources to satisfy growing public demand. The concluding section discusses the many challenges that NNLM staff faced as they transformed the network from a system that served mainly academic medical researchers to a larger, denser organization that offers health information resources to everyone.

Survival in Very Preterm Infants: An International Comparison of 10 National Neonatal Networks.

PubMed

Helenius, Kjell; Sjörs, Gunnar; Shah, Prakesh S; Modi, Neena; Reichman, Brian; Morisaki, Naho; Kusuda, Satoshi; Lui, Kei; Darlow, Brian A; Bassler, Dirk; Håkansson, Stellan; Adams, Mark; Vento, Maximo; Rusconi, Franca; Isayama, Tetsuya; Lee, Shoo K; Lehtonen, Liisa

2017-12-01

To compare survival rates and age at death among very preterm infants in 10 national and regional neonatal networks. A cohort study of very preterm infants, born between 24 and 29 weeks' gestation and weighing <1500 g, admitted to participating neonatal units between 2007 and 2013 in the International Network for Evaluating Outcomes of Neonates. Survival was compared by using standardized ratios (SRs) comparing survival in each network to the survival estimate of the whole population. Network populations differed with respect to rates of cesarean birth, exposure to antenatal steroids and birth in nontertiary hospitals. Network SRs for survival were highest in Japan (SR: 1.10; 99% confidence interval: 1.08-1.13) and lowest in Spain (SR: 0.88; 99% confidence interval: 0.85-0.90). The overall survival differed from 78% to 93% among networks, the difference being highest at 24 weeks' gestation (range 35%-84%). Survival rates increased and differences between networks diminished with increasing gestational age (GA) (range 92%-98% at 29 weeks' gestation); yet, relative differences in survival followed a similar pattern at all GAs. The median age at death varied from 4 days to 13 days across networks. The network ranking of survival rates for very preterm infants remained largely unchanged as GA increased; however, survival rates showed marked variations at lower GAs. The median age at death also varied among networks. These findings warrant further assessment of the representativeness of the study populations, organization of perinatal services, national guidelines, philosophy of care at extreme GAs, and resources used for decision-making. Copyright © 2017 by the American Academy of Pediatrics.

Update on Plans to Establish a National Phenology Network in the U.S.A.

NASA Astrophysics Data System (ADS)

Betancourt, J.; Schwartz, M.; Breshears, D.; Cayan, D.; Dettinger, M.; Inouye, D.; Post, E.; Reed, B.; Gray, S.

2005-12-01

The passing of the seasons is the most pervasive source of climatic and biological variability on Earth, yet phenological monitoring has been spotty worldwide. Formal phenological networks were recently established in Europe and Canada, and we are now following their lead in organizing a National Phenology Network (NPN) for the U.S.A. With support from federal agencies (NSF, USGS, NPS, USDA-FS, EPA, NOAA, NASA), on Aug. 22-26 we organized a workshop in Tucson, Arizona to begin planning a national-scale, multi-tiered phenological network. A prototype for a web-based NPN and preliminary workshop results are available at http://www.npn.uwm.edu. The main goals of NPN will be to: (1) facilitate thorough understanding of phenological phenomena, including causes and effects; (2) provide ground truthing to make the most of heavy public investment in remote sensing data; (3) allow detection and prediction of environmental change for a wide of variety of applications; (4) harness the power of mass participation and engage tens of thousands of "citizen scientists" in meeting national needs in Education, Health, Commerce, Natural Resources and Agriculture; (5) develop a model system for substantive collaboration across different levels of government, academia and the private sector. Just as the national networks of weather stations and stream gauges are critical for providing weather, climate and water-related information, NPN will help safeguard and procure goods and services that ecosystems provide. We expect that NPN will consist of a four-tiered, expandable structure: 1) a backbone network linked to existing weather stations, run by recruited public observers; 2) A smaller, second tier of intensive observations, run by scientists at established research sites; 3) a much larger network of observations made by citizen scientists; and 4) remote sensing observations that can be validated with surface observations, thereby providing wall-to-wall coverage for the U.S.A. Key to

An innovation diffusion model of a local electricity network that is influenced by internal and external factors

NASA Astrophysics Data System (ADS)

Hattam, Laura; Greetham, Danica Vukadinović

2018-01-01

Haynes et al. (1977) derived a nonlinear differential equation to determine the spread of innovations within a social network across space and time. This model depends upon the imitators and the innovators within the social system, where the imitators respond to internal influences, whilst the innovators react to external factors. Here, this differential equation is applied to simulate the uptake of a low-carbon technology (LCT) within a real local electricity network that is situated in the UK. This network comprises of many households that are assigned to certain feeders. Firstly, travelling wave solutions of Haynes' model are used to predict adoption times as a function of the imitation and innovation influences. Then, the grid that represents the electricity network is created so that the finite element method (FEM) can be implemented. Next, innovation diffusion is modelled with Haynes' equation and the FEM, where varying magnitudes of the internal and external pressures are imposed. Consequently, the impact of these model parameters is investigated. Moreover, LCT adoption trajectories at fixed feeder locations are calculated, which give a macroscopic understanding of the uptake behaviour at specific network sites. Lastly, the adoption of LCTs at a household level is examined, where microscopic and macroscopic approaches are combined.

Water diffusion in silicate glasses: the effect of glass structure

NASA Astrophysics Data System (ADS)

Kuroda, M.; Tachibana, S.

2016-12-01

Water diffusion in silicate melts (glasses) is one of the main controlling factors of magmatism in a volcanic system. Water diffusivity in silicate glasses depends on its own concentration. However, the mechanism causing those dependences has not been fully understood yet. In order to construct a general model for water diffusion in various silicate glasses, we performed water diffusion experiments in silica glass and proposed a new water diffusion model [Kuroda et al., 2015]. In the model, water diffusivity is controlled by the concentration of both main diffusion species (i.e. molecular water) and diffusion pathways, which are determined by the concentrations of hydroxyl groups and network modifier cations. The model well explains the water diffusivity in various silicate glasses from silica glass to basalt glass. However, pre-exponential factors of water diffusivity in various glasses show five orders of magnitude variations although the pre-exponential factor should ideally represent the jump frequency and the jump distance of molecular water and show a much smaller variation. Here, we attribute the large variation of pre-exponential factors to a glass structure dependence of activation energy for molecular water diffusion. It has been known that the activation energy depends on the water concentration [Nowak and Behrens, 1997]. The concentration of hydroxyls, which cut Si-O-Si network in the glass structure, increases with water concentration, resulting in lowering the activation energy for water diffusion probably due to more fragmented structure. Network modifier cations are likely to play the same role as water. With taking the effect of glass structure into account, we found that the variation of pre-exponential factors of water diffusivity in silicate glasses can be much smaller than the five orders of magnitude, implying that the diffusion of molecular water in silicate glasses is controlled by the same atomic process.

Site characterization of the national seismic network of Italy

NASA Astrophysics Data System (ADS)

Bordoni, Paola; Pacor, Francesca; Cultrera, Giovanna; Casale, Paolo; Cara, Fabrizio; Di Giulio, Giuseppe; Famiani, Daniela; Ladina, Chiara; PIschiutta, Marta; Quintiliani, Matteo

2017-04-01

The national seismic network of Italy (Rete Sismica Nazionale, RSN) run by Istituto Nazionale di Geofisica e Vulcanologia (INGV) consists of more than 400 seismic stations connected in real time to the institute data center in order to locate earthquakes for civil defense purposes. A critical issue in the performance of a network is the characterization of site condition at the recording stations. Recently INGV has started addressing this subject through the revision of all available geological and geophysical data, the acquisition of new information by means of ad-hoc field measurements and the analysis of seismic waveforms. The main effort is towards building a database, integrated with the other INGV infrastructures, designed to archive homogeneous parameters through the seismic network useful for a complete site characterization, including housing, geological, seismological and geotechnical features as well as the site class according to the European and Italian building codes. Here we present the ongoing INGV activities.

Exponential stability of impulsive stochastic genetic regulatory networks with time-varying delays and reaction-diffusion

DOE PAGES

Cao, Boqiang; Zhang, Qimin; Ye, Ming

2016-11-29

We present a mean-square exponential stability analysis for impulsive stochastic genetic regulatory networks (GRNs) with time-varying delays and reaction-diffusion driven by fractional Brownian motion (fBm). By constructing a Lyapunov functional and using linear matrix inequality for stochastic analysis we derive sufficient conditions to guarantee the exponential stability of the stochastic model of impulsive GRNs in the mean-square sense. Meanwhile, the corresponding results are obtained for the GRNs with constant time delays and standard Brownian motion. Finally, an example is presented to illustrate our results of the mean-square exponential stability analysis.

Anticipated Ethics and Regulatory Challenges in PCORnet: The National Patient-Centered Clinical Research Network.

PubMed

Ali, Joseph; Califf, Robert; Sugarman, Jeremy

2016-01-01

PCORnet, the National Patient-Centered Clinical Research Network, seeks to establish a robust national health data network for patient-centered comparative effectiveness research. This article reports the results of a PCORnet survey designed to identify the ethics and regulatory challenges anticipated in network implementation. A 12-item online survey was developed by leadership of the PCORnet Ethics and Regulatory Task Force; responses were collected from the 29 PCORnet networks. The most pressing ethics issues identified related to informed consent, patient engagement, privacy and confidentiality, and data sharing. High priority regulatory issues included IRB coordination, privacy and confidentiality, informed consent, and data sharing. Over 150 IRBs and five different approaches to managing multisite IRB review were identified within PCORnet. Further empirical and scholarly work, as well as practical and policy guidance, is essential if important initiatives that rely on comparative effectiveness research are to move forward.

The Diffusion of Evidence-Based Practice: Reviewing the Evidence-Based Practice Networks in the United States and German-Speaking Countries.

PubMed

Ghanem, Christian; Lawson, Thomas R; Pankofer, Sabine; Maragkos, Markos; Kollar, Ingo

2017-01-01

Evidence-based practice (EBP) has had a major influence on U.S. social work while it has rarely been adapted in German-speaking countries. This study investigates how knowledge about EBP is diffused within and across geographical contexts. Network analysis methods reveals different diffusion patterns and provide reasons for these differences. For example, the U.S. discourse is self-contained and based on a more homogeneous knowledge base, while the German discourse is more heterogeneous and focuses on a notion of reflexive professionalism. The different conceptual influences within the U.S. and German discourses are discussed in light of future directions of disciplinary social work.

U.S. Geological Survey external quality-assurance project report for the National Atmospheric Deposition Program / National Trends Network and Mercury Deposition Network, 2011-2012

USGS Publications Warehouse

Wetherbee, Gregory A.; Martin, RoseAnn

2014-01-01

The U.S. Geological Survey operated six distinct programs to provide external quality-assurance monitoring for the National Atmospheric Deposition Program (NADP) / National Trends Network (NTN) and Mercury Deposition Network (MDN) during 2011–2012. The field-audit program assessed the effects of onsite exposure, sample handling, and shipping on the chemistry of NTN samples; a system-blank program assessed the same effects for MDN. Two interlaboratory-comparison programs assessed the bias and variability of the chemical analysis data from the Central Analytical Laboratory and Mercury Analytical Laboratory (HAL). A blind-audit program was implemented for the MDN during 2011 to evaluate analytical bias in HAL total mercury concentration data. The co-located–sampler program was used to identify and quantify potential shifts in NADP data resulting from the replacement of original network instrumentation with new electronic recording rain gages and precipitation collectors that use optical precipitation sensors. The results indicate that NADP data continue to be of sufficient quality for the analysis of spatial distributions and time trends of chemical constituents in wet deposition across the United States. Co-located rain gage results indicate -3.7 to +6.5 percent bias in NADP precipitation-depth measurements. Co-located collector results suggest that the retrofit of the NADP networks with the new precipitation collectors could cause +10 to +36 percent shifts in NADP annual deposition values for ammonium, nitrate, and sulfate; -7.5 to +41 percent shifts for hydrogen-ion deposition; and larger shifts (-51 to +52 percent) for calcium, magnesium, sodium, potassium, and chloride. The prototype N-CON Systems bucket collector typically catches more precipitation than the NADP-approved Aerochem Metrics Model 301 collector.

Planning and Establishment of a National Teledocumentation Network--Guidelines Based on the Spanish Experience.

ERIC Educational Resources Information Center

Mahon, F. V., Ed.

Finding that the promotion of a national information industry can best be pursued through the planning and establishment of a national teledocumentation network, this study (based on the experiences of Spain) offers a model that may be of interest to UNESCO (United Nations Educational, Scientific and Cultural Organization) member states wishing to…

The National Network forTechnology Entrepreneurship and Commercialization (N2TEC): Bringing New Technologies to Market

NASA Astrophysics Data System (ADS)

Allen, Kathleen

2003-03-01

N2TEC, the National Network for Technology Entrepreneurship and Commercialization, is a National Science Foundation "Partnerships for Innovation" initiative designed to raise the level of innovation and technology commercialization in colleges, universities, and communities across the nation. N2TEC is creating a network of people and institutions, and a set of technology tools that will facilitate the pooling of resources and knowledge and enable faculty and students to share those resources and collaborate without regard to geographic boundaries. N2TEC will become the backbone by which educational institutions across the nation can move their technologies into new venture startups. The ultimate goal is to create new wealth and strengthen local, regional and national economies.

Celebrating 25 Years. National Dropout Prevention Center/Network Newsletter. Volume 22, Number 3

ERIC Educational Resources Information Center

Duckenfield, Marty, Ed.

2011-01-01

The "National Dropout Prevention Newsletter" is published quarterly by the National Dropout Prevention Center/Network. This issue contains the following articles: (1) Leading the Way in Dropout Prevention; (2) The 15 Effective Strategies in Action; (3) Technology Changes 1986-2011 (Marty Duckenfield); (4) 25 Years of Research and Support…

Diffusion in the system K2O-SrO-SiO2. II - Cation self-diffusion coefficients.

NASA Technical Reports Server (NTRS)

Varshneya, A. K.; Cooper, A. R.

1972-01-01

The self-diffusion coefficients were measured by introducing a slab of glass previously irradiated in a reactor between two slabs of unirradiated glass. By heating the specimens, etching them sequentially and determining the radioactivity, self-diffusion coefficients for K and Sr were measured. It is pointed out that the results obtained in the investigations appear to support the proposal that the network of the base glass predominantly controls the activation energy for the diffusion of ions.

78 FR 68030 - Draft Guidance on Intellectual Property Rights for the National Network for Manufacturing...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-11-13

... Additive Manufacturing showed great promise for the defense, energy, space and commercial sectors of the Nation. In August, 2012, the selection of the National Additive Manufacturing Innovation Institute (NAMII...-01] Draft Guidance on Intellectual Property Rights for the National Network for Manufacturing...

Disruption of brain anatomical networks in schizophrenia: A longitudinal, diffusion tensor imaging based study.

PubMed

Sun, Yu; Chen, Yu; Lee, Renick; Bezerianos, Anastasios; Collinson, Simon L; Sim, Kang

2016-03-01

Despite convergent neuroimaging evidence indicating a wide range of brain abnormalities in schizophrenia, our understanding of alterations in the topological architecture of brain anatomical networks and how they are modulated over time, is still rudimentary. Here, we employed graph theoretical analysis of longitudinal diffusion tensor imaging data (DTI) over a 5-year period to investigate brain network topology in schizophrenia and its relationship with clinical manifestations of the illness. Using deterministic tractography, weighted brain anatomical networks were constructed from 31 patients experiencing schizophrenia and 28 age- and gender-matched healthy control subjects. Although the overall small-world characteristics were observed at both baseline and follow-up, a scan-point independent significant deficit of global integration was found in patients compared to controls, suggesting dysfunctional integration of the brain and supporting the notion of schizophrenia as a disconnection syndrome. Specifically, several brain regions (e.g., the inferior frontal gyrus and the bilateral insula) that are crucial for cognitive and emotional integration were aberrant. Furthermore, a significant group-by-longitudinal scan interaction was revealed in the characteristic path length and global efficiency, attributing to a progressive aberration of global integration in patients compared to healthy controls. Moreover, the progressive disruptions of the brain anatomical network topology were associated with the clinical symptoms of the patients. Together, our findings provide insights into the substrates of anatomical dysconnectivity patterns for schizophrenia and highlight the potential for connectome-based metrics as neural markers of illness progression and clinical change with treatment. Copyright © 2016 Elsevier B.V. All rights reserved.

Strategic factors in the development of the National Technology Transfer Network

NASA Technical Reports Server (NTRS)

Root, Jonathan F.; Stone, Barbara A.

1993-01-01

Broad consensus among industry and government leaders has developed over the last decade on the importance of applying the U.S. leadership in research and development (R&D) to strengthen competitiveness in the global marketplace, and thus enhance national prosperity. This consensus has emerged against the backdrop of increasing economic competition, and the dramatic reduction of military threats to national security with the end of the Cold War. This paper reviews the key factors and considerations that shaped - and continue to influence - the development of the Regional Technoloty Transfer Centers (RTTC) and the National Technology Transfer Center (NTTC). Also, the future role of the national network in support of emerging technology policy initiatives will be explored.

Analysis of Critical Mass in Threshold Model of Diffusion

NASA Astrophysics Data System (ADS)

Kim, Jeehong; Hur, Wonchang; Kang, Suk-Ho

2012-04-01

Why does diffusion sometimes show cascade phenomena but at other times is impeded? In addressing this question, we considered a threshold model of diffusion, focusing on the formation of a critical mass, which enables diffusion to be self-sustaining. Performing an agent-based simulation, we found that the diffusion model produces only two outcomes: Almost perfect adoption or relatively few adoptions. In order to explain the difference, we considered the various properties of network structures and found that the manner in which thresholds are arrayed over a network is the most critical factor determining the size of a cascade. On the basis of the results, we derived a threshold arrangement method effective for generation of a critical mass and calculated the size required for perfect adoption.

Advancing environmental health surveillance in the US through a national human biomonitoring network.

PubMed

Latshaw, Megan Weil; Degeberg, Ruhiyyih; Patel, Surili Sutaria; Rhodes, Blaine; King, Ewa; Chaudhuri, Sanwat; Nassif, Julianne

2017-03-01

The United States lacks a comprehensive, nationally-coordinated, state-based environmental health surveillance system. This lack of infrastructure leads to: • varying levels of understanding of chemical exposures at the state & local levels • often inefficient public health responses to chemical exposure emergencies (such as those that occurred in the Flint drinking water crisis, the Gold King mine spill, the Elk river spill and the Gulf Coast oil spill) • reduced ability to measure the impact of public health interventions or environmental policies • less efficient use of resources for cleaning up environmental contamination Establishing the National Biomonitoring Network serves as a step toward building a national, state-based environmental health surveillance system. The Network builds upon CDC investments in emergency preparedness and environmental public health tracking, which have created advanced chemical analysis and information sharing capabilities in the state public health systems. The short-term goal of the network is to harmonize approaches to human biomonitoring in the US, thus increasing the comparability of human biomonitoring data across states and communities. The long-term goal is to compile baseline data on exposures at the state level, similar to data found in CDC's National Report on Human Exposure to Environmental Chemicals. Barriers to success for this network include: available resources, effective risk communication strategies, data comparability & sharing, and political will. Anticipated benefits include high quality data on which to base public health and environmental decisions, data with which to assess the success of public health interventions, improved risk assessments for chemicals, and new ways to prioritize environmental health research. Copyright © 2016 Elsevier GmbH. All rights reserved.

The USA National Phenology Network's Model for Collaborative Data Generation and Dissemination

NASA Astrophysics Data System (ADS)

Rosemartin, A.; Lincicome, A.; Denny, E. G.; Marsh, L.; Wilson, B. E.

2010-12-01

The USA National Phenology Network (USA-NPN) serves science and society by promoting a broad understanding of plant and animal phenology and the relationships among phenological patterns and all aspects of environmental change. The Network was founded as an NSF-funded Research Coordination Network, for the purpose of fostering collaboration among scientists, policy-makers and the general public to address the challenges posed by global change and its impact on ecosystems and human health. With this mission in mind, the USA-NPN has developed an Information Management System (IMS) to facilitate collaboration and participatory data collection and digitization. The IMS includes components for data storage, such as the National Phenology Database, as well as a Drupal website for information-sharing and data visualization, and a Java application for collection of contemporary observational data. The National Phenology Database is designed to efficiently accommodate large quantities of phenology data and to be flexible to the changing needs of the network. The database allows for the collection, storage and output of phenology data from multiple sources (e.g., partner organizations, researchers and citizen observers), as well as integration with legacy data sets. Participants in the network can submit records (as Drupal content types) for publications, legacy data sets and phenology-related festivals. The USA-NPN’s contemporary phenology data collection effort, Nature’s Notebook also draws on the contributions of participants. Citizen scientists around the country submit data through this Java application (paired with the Drupal site through a shared login) on the life cycle stages of plants and animals in their yards and parks. The North American Bird Phenology Program, now a part of the USA-NPN, also relies on web-based crowdsourcing. Participants in this program are transcribing 6 million scanned paper cards that were collected by observers across the United States

U.S. National PM2.5 Chemical Speciation Monitoring Networks – CSN and IMPROVE: Description of Networks

EPA Science Inventory

The U.S. Environmental Protection Agency (EPA) initiated the national PM2.5 Chemical Speciation Monitoring Network (CSN) in 2000 to support evaluation of long-term trends and to better quantify the impact of sources on particulate matter (PM) concentrations in the size range belo...

On Quantifying Diffusion of Health Information on Twitter.

PubMed

Bakal, Gokhan; Kavuluru, Ramakanth

2017-02-01

With the increasing use of digital technologies, online social networks are emerging as major means of communication. Recently, social networks such as Facebook and Twitter are also being used by consumers, care providers (physicians, hospitals), and government agencies to share health related information. The asymmetric user network and the short message size have made Twitter particularly popular for propagating health related content on the Web. Besides tweeting on their own, users can choose to retweet particular tweets from other users (even if they do not follow them on Twitter.) Thus, a tweet can diffuse through the Twitter network via the follower-friend connections. In this paper, we report results of a pilot study we conducted to quantitatively assess how health related tweets diffuse in the directed follower-friend Twitter graph through the retweeting activity. Our effort includes (1). development of a retweet collection and Twitter retweet graph formation framework and (2). a preliminary analysis of retweet graphs and associated diffusion metrics for health tweets. Given the ambiguous nature (due to polysemy and sarcasm) of health relatedness of tweets collected with keyword based matches, our initial study is limited to ≈ 200 health related tweets (which were manually verified to be on health topics) each with at least 25 retweets. To our knowledge, this is first attempt to study health information diffusion on Twitter through retweet graph analysis.

Effects of equipment performance on data quality from the National Atmospheric Deposition Program/National Trends Network and the Mercury Deposition Network

USGS Publications Warehouse

Wetherbee, Gregory A.; Rhodes, Mark F.

2013-01-01

The U.S. Geological Survey Branch of Quality Systems operates the Precipitation Chemistry Quality Assurance project (PCQA) to provide independent, external quality-assurance for the National Atmospheric Deposition Program (NADP). NADP is composed of five monitoring networks that measure the chemical composition of precipitation and ambient air. PCQA and the NADP Program Office completed five short-term studies to investigate the effects of equipment performance with respect to the National Trends Network (NTN) and Mercury Deposition Network (MDN) data quality: sample evaporation from NTN collectors; sample volume and mercury loss from MDN collectors; mercury adsorption to MDN collector glassware, grid-type precipitation sensors for precipitation collectors, and the effects of an NTN collector wind shield on sample catch efficiency. Sample-volume evaporation from an NTN Aerochem Metrics (ACM) collector ranged between 1.1–33 percent with a median of 4.7 percent. The results suggest that weekly NTN sample evaporation is small relative to sample volume. MDN sample evaporation occurs predominantly in western and southern regions of the United States (U.S.) and more frequently with modified ACM collectors than with N-CON Systems Inc. collectors due to differences in airflow through the collectors. Variations in mercury concentrations, measured to be as high as 47.5 percent per week with a median of 5 percent, are associated with MDN sample-volume loss. Small amounts of mercury are also lost from MDN samples by adsorption to collector glassware irrespective of collector type. MDN 11-grid sensors were found to open collectors sooner, keep them open longer, and cause fewer lid cycles than NTN 7-grid sensors. Wind shielding an NTN ACM collector resulted in collection of larger quantities of precipitation while also preserving sample integrity.

The National Research and Education Network (NREN): Promise of New Information Environments. ERIC Digest.

ERIC Educational Resources Information Center

Bishop, Ann P.

This digest describes proposed legislation for the implementation of the National Research and Education Network (NREN). Issues and implications for teachers, students, researchers, and librarians are suggested and the emergence of the electronic network as a general communication and research tool is described. Developments in electronic…

Diffusion via space discretization method to study the concentration dependence of self-diffusivity under confinement

NASA Astrophysics Data System (ADS)

Sant, Marco; Papadopoulos, George K.; Theodorou, Doros N.

2010-04-01

The concentration dependence of self-diffusivity is investigated by means of a novel method, extending our previously developed second-order Markov process model to periodic media. Introducing the concept of minimum-crossing surface, we obtain a unique decomposition of the self-diffusion coefficient into two parameters with specific physical meanings. Two case studies showing a maximum in self-diffusivity as a function of concentration are investigated, along with two cases where such a maximum cannot be present. Subsequently, the method is applied to the large cavity pore network of the ITQ-1 (Mobil tWenty tWo, MWW) zeolite for methane (displaying a maximum in self-diffusivity) and carbon dioxide (no maximum), explaining the diffusivity trend on the basis of the evolution of the model parameters as a function of concentration.

Albemarle Sound demonstration study of the national monitoring network for US coastal waters and their tributaries

Treesearch

Michelle Moorman; Sharon Fitzgerald; Keith Loftin; Elizabeth Fensin

2016-01-01

The U.S. Geological Survey’s (USGS) is implementing a demonstration project in the Albemarle Sound for the National Monitoring Network for U.S. coastal waters and their tributaries. The goal of the National Monitoring Network is to provide information about the health of our oceans and coastal ecosystems and inland influences on coastal waters for improved resource...

Non-fragile consensus algorithms for a network of diffusion PDEs with boundary local interaction

NASA Astrophysics Data System (ADS)

Xiong, Jun; Li, Junmin

2017-07-01

In this study, non-fragile consensus algorithm is proposed to solve the average consensus problem of a network of diffusion PDEs, modelled by boundary controlled heat equations. The problem deals with the case where the Neumann-type boundary controllers are corrupted by additive persistent disturbances. To achieve consensus between agents, a linear local interaction rule addressing this requirement is given. The proposed local interaction rules are analysed by applying a Lyapunov-based approach. The multiplicative and additive non-fragile feedback control algorithms are designed and sufficient conditions for the consensus of the multi-agent systems are presented in terms of linear matrix inequalities, respectively. Simulation results are presented to support the effectiveness of the proposed algorithms.

National Health Care Network for children with oral clefts: organization, functioning, and preliminary outcomes.

PubMed

Cassinelli, Agustina; Pauselli, Nadia; Piola, Agustina; Martinelli, Claudia; Alves de Azeved, José L; Bidondo, María P; Groisman, Boris; Barbero, Pablo; Liascovich, Rosa; Sala, Ana

2018-02-01

Oral clefts are major congenital anomalies that may affect the lip and/or palate, and that may also involve the nose and nostrils. In Argentina, their prevalence is approximately 15 per 10 000 births. In 2015, the Ministry of Health of Argentina created a national health care network for children with oral clefts in Argentina through the joint work with the National Registry of Congenital Anomalies (Red Nacional de Anomalías Congénitas, RENAC) (coordinating center for the national network) and the SUMAR Program. The objective of this study was to describe the health care network and its preliminary outcomes. A total of 61 centers that provided a comprehensive treatment for oral clefts or in collaboration with other centers were identified and accredited. Maternity centers were connected with treating centers grouped in health care network nodes. In the period between March 2015 and February 2016, 550 newborn infants who were exclusively covered by the public health care system were identified. Among these, 18% had a cleft lip; 62%, cleft lip and palate; and 20%, cleft palate only; 75% were isolated cases and 25%, in association with other congenital anomalies. Approximately 70% of children were assessed by a certified treating institution and are receiving treatment. The network seeks to improve data systematization, include the largest number of centers possible, strengthen interdisciplinary team work, and promote high-quality standards for treatments. Sociedad Argentina de Pediatría

The USA National Phenology Network; taking the pulse of our planet

USGS Publications Warehouse

Weltzin, Jake F.

2011-01-01

People have tracked phenology for centuries and for the most practical reasons: it helped them know when to hunt and fish, when to plant and harvest crops, and when to navigate waterways. Now phenology is being used as a tool to assess climate change and its effects on both natural and modified ecosystems. How is the timing of events in plant and animal life cycles, like flowering or migration, responding to climate change? And how are those responses, in turn, affecting people and ecosystems? The USA National Phenology Network (the Network) is working to answer these questions for science and society by promoting a broad understanding of plant and animal phenology and their relationship to environmental change. The Network is a consortium of organizations and individuals that collect, share, and use phenology data, models, and related information to enable scientists, resource managers, and the public to adapt in response to changing climates and environments. In addition, the Network encourages people of all ages and backgrounds to observe and record phenology as a way to discover and explore the nature and pace of our dynamic world. The National Coordinating Office (NCO) of the Network is a resource center that facilitates and encourages widespread collection, integration, and sharing of phenology data and related information (for example, meteorological and hydrological data). The NCO develops and promotes standardized methods for field data collection and maintains several online user interfaces for data upload and download, as well as data exploration, visualization, and analysis. The NCO also facilitates basic and applied research related to phenology, the development of decision-support tools for resource managers and planners, and the design of educational and outreach materials

77 FR 50469 - Notice of Public Workshop: “Designing for Impact III: Workshop on Building the National Network...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-08-21

... series of public workshops entitled ``Designing for Impact: Workshop on Building the National Network for...-president-manufacturing-and-economy . The Designing for Impact workshop series is organized by the federal...: ``Designing for Impact III: Workshop on Building the National Network for Manufacturing Innovation'' AGENCY...

Building Capacity for a Long-Term, in-Situ, National-Scale Phenology Monitoring Network: Successes, Challenges and Lessons Learned

NASA Astrophysics Data System (ADS)

Weltzin, J. F.; Browning, D. M.

2014-12-01

The USA National Phenology Network (USA-NPN; www.usanpn.org) is a national-scale science and monitoring initiative focused on phenology - the study of seasonal life-cycle events such as leafing, flowering, reproduction, and migration - as a tool to understand the response of biodiversity to environmental variation and change. USA-NPN provides a hierarchical, national monitoring framework that enables other organizations to leverage the capacity of the Network for their own applications - minimizing investment and duplication of effort - while promoting interoperability. Network participants can leverage: (1) Standardized monitoring protocols that have been broadly vetted, tested and published; (2) A centralized National Phenology Database (NPDb) for maintaining, archiving and replicating data, with standard metadata, terms-of-use, web-services, and documentation of QA/QC, plus tools for discovery, visualization and download of raw data and derived data products; and/or (3) A national in-situ, multi-taxa phenological monitoring system, Nature's Notebook, which enables participants to observe and record phenology of plants and animals - based on the protocols and information management system (IMS) described above - via either web or mobile applications. The protocols, NPDb and IMS, and Nature's Notebook represent a hierarchy of opportunities for involvement by a broad range of interested stakeholders, from individuals to agencies. For example, some organizations have adopted (e.g., the National Ecological Observatory Network or NEON) -- or are considering adopting (e.g., the Long-Term Agroecosystems Network or LTAR) -- the USA-NPN standardized protocols, but will develop their own database and IMS with web services to promote sharing of data with the NPDb. Other organizations (e.g., the Inventory and Monitoring Programs of the National Wildlife Refuge System and the National Park Service) have elected to use Nature's Notebook to support their phenological monitoring

U.S. Geological Survey external quality-assurance project report to the National Atmospheric Deposition Program / National Trends Network and Mercury Deposition Network, 2007-08

USGS Publications Warehouse

Wetherbee, Gregory A.; Latysh, Natalie E.; Chesney, Tanya A.

2010-01-01

The U.S. Geological Survey (USGS) used six distinct programs to provide external quality-assurance monitoring for the National Atmospheric Deposition Program / National Trends Network (NTN) and Mercury Deposition Network (MDN) during 2007-08. The field-audit program assessed the effects of onsite exposure, sample handling, and shipping on the chemistry of NTN samples, and a system-blank program assessed the same effects for MDN. Two interlaboratory-comparison programs assessed the bias and variability of the chemical analysis data from the Central Analytical Laboratory (CAL), Mercury (Hg) Analytical Laboratory (HAL), and 12 other participating laboratories. A blind-audit program was also implemented for the MDN to evaluate analytical bias in HAL total Hg concentration data. A co-located-sampler program was used to identify and quantify potential shifts in NADP data resulting from replacement of original network instrumentation with new electronic recording rain gages (E-gages) and prototype precipitation collectors. The results indicate that NADP data continue to be of sufficient quality for the analysis of spatial distributions and time trends of chemical constituents in wet deposition across the U.S. NADP data-quality objectives continued to be achieved during 2007-08. Results also indicate that retrofit of the NADP networks with the new E-gages is not likely to create step-function type shifts in NADP precipitation-depth records, except for sites where annual precipitation depth is dominated by snow because the E-gages tend to catch more snow than the original NADP rain gages. Evaluation of prototype precipitation collectors revealed no difference in sample volumes and analyte concentrations between the original NADP collectors and modified, deep-bucket collectors, but the Yankee Environmental Systems, Inc. (YES) collector obtained samples of significantly higher volumes and analyte concentrations than the standard NADP collector.

The USA National Phenology Network: A national observatory for assessment of biotic response to environmental variation

NASA Astrophysics Data System (ADS)

Weltzin, J. F.; USA National Phenology Network National Coordinating Office

2011-12-01

The USA National Phenology Network (USA-NPN; www.usanpn.org), established in 2007, is a national science and monitoring initiative focused on phenology as a tool to understand how plants, animals and landscapes respond to climatic variability and change. Core functions of the National Coordinating Office (NCO) of USA-NPN are to provide a national information management system including databases, develop and implement internationally standardized phenology monitoring protocols, create partnerships with a variety of organizations including field stations for implementation, facilitate research and the development of decision support tools, and promote education and outreach activities related to phenology and climate change. This presentation will describe programs, tools and materials developed by USA-NPN to facilitate science, management and education related to phenology of plants, animals and landscapes within protected areas at local, regional and national scales. Particular emphasis will be placed on the on-line integrated animal and plant monitoring program, Nature's Notebook, which provides standardized protocols for phenological status monitoring and data management for over 500 animal and plant species. The monitoring system facilitates collection of sampling intensity, absence data, considerable metadata (from site to observation). We recently added functionality for recording estimates of animal abundance and plant canopy development. Real-time raw data for plants (from 2009 to present) and animals (from 2010 to present), including FGDC-compliant metadata and documented methodology, are now available for download from the website. A new data exploration tool premiered in spring 2010 allows sophisticated graphical visualization of integrated phenological and meteorological data. The network seeks to develop partnerships with other organizations interested in (1) implementing vetted, standardized protocols for phenological or ecological monitoring, and (2

Variable forgetting factor mechanisms for diffusion recursive least squares algorithm in sensor networks

NASA Astrophysics Data System (ADS)

Zhang, Ling; Cai, Yunlong; Li, Chunguang; de Lamare, Rodrigo C.

2017-12-01

In this work, we present low-complexity variable forgetting factor (VFF) techniques for diffusion recursive least squares (DRLS) algorithms. Particularly, we propose low-complexity VFF-DRLS algorithms for distributed parameter and spectrum estimation in sensor networks. For the proposed algorithms, they can adjust the forgetting factor automatically according to the posteriori error signal. We develop detailed analyses in terms of mean and mean square performance for the proposed algorithms and derive mathematical expressions for the mean square deviation (MSD) and the excess mean square error (EMSE). The simulation results show that the proposed low-complexity VFF-DRLS algorithms achieve superior performance to the existing DRLS algorithm with fixed forgetting factor when applied to scenarios of distributed parameter and spectrum estimation. Besides, the simulation results also demonstrate a good match for our proposed analytical expressions.

From Caprio's lilacs to the USA National Phenology Network

USGS Publications Warehouse

Schwartz, Mark D.; Betancourt, Julio L.; Weltzin, Jake F.

2012-01-01

Continental-scale monitoring is vital for understanding and adapting to temporal changes in seasonal climate and associated phenological responses. The success of monitoring programs will depend on recruiting, retaining, and managing members of the public to routinely collect phenological observations according to standardized protocols. Here, we trace the development of infrastructure for phenological monitoring in the US, culminating in the USA National Phenology Network, a program that engages scientists and volunteers.

Fast Rotational Diffusion of Water Molecules in a 2D Hydrogen Bond Network at Cryogenic Temperatures

NASA Astrophysics Data System (ADS)

Prisk, T. R.; Hoffmann, C.; Kolesnikov, A. I.; Mamontov, E.; Podlesnyak, A. A.; Wang, X.; Kent, P. R. C.; Anovitz, L. M.

2018-05-01

Individual water molecules or small clusters of water molecules contained within microporous minerals present an extreme case of confinement where the local structure of hydrogen bond networks are dramatically altered from bulk water. In the zinc silicate hemimorphite, the water molecules form a two-dimensional hydrogen bond network with hydroxyl groups in the crystal framework. Here, we present a combined experimental and theoretical study of the structure and dynamics of water molecules within this network. The water molecules undergo a continuous phase transition in their orientational configuration analogous to a two-dimensional Ising model. The incoherent dynamic structure factor reveals two thermally activated relaxation processes, one on a subpicosecond timescale and another on a 10-100 ps timescale, between 70 and 130 K. The slow process is an in-plane reorientation of the water molecule involving the breaking of hydrogen bonds with a framework that, despite the low temperatures involved, is analogous to rotational diffusion of water molecules in the bulk liquid. The fast process is a localized motion of the water molecule with no apparent analogs among known bulk or confined phases of water.

Fast Rotational Diffusion of Water Molecules in a 2D Hydrogen Bond Network at Cryogenic Temperatures

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

Prisk, Timothy; Hoffmann, Christina; Kolesnikov, Alexander I.

Individual water molecules or small clusters of water molecules contained within microporous minerals present an extreme case of confinement where the local structure of hydrogen bond networks are dramatically altered from bulk water. In the zinc silicate hemimorphite, the water molecules form a two-dimensional hydrogen bond network with hydroxyl groups in the crystal framework. Here in this paper, we present a combined experimental and theoretical study of the structure and dynamics of water molecules within this network. The water molecules undergo a continuous phase transition in their orientational configuration analogous to a two-dimensional Ising model. The incoherent dynamic structure factormore » reveals two thermally activated relaxation processes, one on a subpicosecond timescale and another on a 10–100 ps timescale, between 70 and 130 K. The slow process is an in-plane reorientation of the water molecule involving the breaking of hydrogen bonds with a framework that, despite the low temperatures involved, is analogous to rotational diffusion of water molecules in the bulk liquid. The fast process is a localized motion of the water molecule with no apparent analogs among known bulk or confined phases of water.« less

Fast Rotational Diffusion of Water Molecules in a 2D Hydrogen Bond Network at Cryogenic Temperatures

DOE PAGES

Prisk, Timothy; Hoffmann, Christina; Kolesnikov, Alexander I.; ...

2018-05-09

Individual water molecules or small clusters of water molecules contained within microporous minerals present an extreme case of confinement where the local structure of hydrogen bond networks are dramatically altered from bulk water. In the zinc silicate hemimorphite, the water molecules form a two-dimensional hydrogen bond network with hydroxyl groups in the crystal framework. Here in this paper, we present a combined experimental and theoretical study of the structure and dynamics of water molecules within this network. The water molecules undergo a continuous phase transition in their orientational configuration analogous to a two-dimensional Ising model. The incoherent dynamic structure factormore » reveals two thermally activated relaxation processes, one on a subpicosecond timescale and another on a 10–100 ps timescale, between 70 and 130 K. The slow process is an in-plane reorientation of the water molecule involving the breaking of hydrogen bonds with a framework that, despite the low temperatures involved, is analogous to rotational diffusion of water molecules in the bulk liquid. The fast process is a localized motion of the water molecule with no apparent analogs among known bulk or confined phases of water.« less

Development of a Coordinated National Soil Moisture Network: A Pilot Study

NASA Astrophysics Data System (ADS)

Lucido, J. M.; Quiring, S. M.; Verdin, J. P.; Pulwarty, R. S.; Baker, B.; Cosgrove, B.; Escobar, V. M.; Strobel, M.

2014-12-01

Soil moisture data is critical for accurate drought prediction, flood forecasting, climate modeling, prediction of crop yields and water budgeting. However, soil moisture data are collected by many agencies and organizations in the United States using a variety of instruments and methods for varying applications. These data are often distributed and represented in disparate formats, posing significant challenges for use. In recognition of these challenges, the President's Climate Action Plan articulated the need for a coordinated national soil moisture network. In response to this action plan, a team led by the National Integrated Drought Information System has begun to develop a framework for this network and has instituted a proof-of-concept pilot study. This pilot is located in the south-central plains of the US, and will serve as a reference architecture for the requisite data systems and inform the design of the national network. The pilot comprises both in-situ and modeled soil moisture datasets (historical and real-time) and will serve the following use cases: operational drought monitoring, experimental land surface modeling, and operational hydrological modeling. The pilot will be implemented using a distributed network design in order to serve dispersed data in real-time directly from data providers. Standard service protocols will be used to enable future integration with external clients. The pilot network will additionally contain a catalog of data sets and web service endpoints, which will be used to broker web service calls. A mediation and aggregation service will then intelligently request, compile, and transform the distributed datasets from their native formats into a standardized output. This mediation framework allows data to be hosted and maintained locally by the data owners while simplifying access through a single service interface. These data services will then be used to create visualizations, for example, views of the current soil

winderosionnetwork.org – Portal to the National Wind Erosion Research Network

USDA-ARS?s Scientific Manuscript database

The National Wind Erosion Research Network was established in 2014 as a collaborative effort led by the USDA Agricultural Research Service and Natural Resources Conservation Service, and USDI Bureau of Land Management, to address the need for standardized measurements of wind erosion and its control...

The National Stream Quality Accounting Network (NASQAN) - Some questions and answers

USGS Publications Warehouse

Ficke, John F.; Hawkinson, Richard O.

1975-01-01

One of the major new efforts of the U.S. Geological Survey is the National Stream Quality Accounting Network (NASQAN). This circular is intended to answer some of the frequently asked questions concerning concepts used in establishing NASQAN, its purposes, design, value, and future plans.

External quality-assurance results for the National Atmospheric Deposition Program and the National Trends Network during 1986

USGS Publications Warehouse

See, Randolph B.; Schroder, LeRoy J.; Willoughby, Timothy C.

1988-01-01

During 1986, the U.S. Geological Survey operated three programs to provide external quality-assurance monitoring of the National Atmospheric Deposition Program and National Trends Network. An intersite-comparison program was used to assess the accuracy of onsite pH and specific-conductance determinations at quarterly intervals. The blind-audit program was used to assess the effect of routine sample handling on the precision and bias of program and network wet-deposition data. Analytical results from four laboratories, which routinely analyze wet-deposition samples, were examined to determine if differences existed between laboratory analytical results and to provide estimates of the analytical precision of each laboratory. An average of 78 and 89 percent of the site operators participating in the intersite-comparison met the network goals for pH and specific conductance. A comparison of analytical values versus actual values for samples submitted as part of the blind-audit program indicated that analytical values were slightly but significantly (a = 0.01) larger than actual values for pH, magnesium, sodium, and sulfate; analytical values for specific conductance were slightly less than actual values. The decreased precision in the analyses of blind-audit samples when compared to interlaboratory studies indicates that a large amount of uncertainty in network deposition data may be a result of routine field operations. The results of the interlaboratory comparison study indicated that the magnitude of the difference between laboratory analyses was small for all analytes. Analyses of deionized, distilled water blanks by participating laboratories indicated that the laboratories had difficulty measuring analyte concentrations near their reported detection limits. (USGS)

The Organization as a Filter of Institutional Diffusion

ERIC Educational Resources Information Center

Penuel, William R.; Frank, Kenneth A.; Sun, Min; Kim, Chong Min; Singleton, Corrine

2013-01-01

Background/Context: Institutional theories sometimes characterize the normative influence of institutions as diffusing like waves and as exerting uniform pressures on individuals. This article contributes to a growing literature on the microfoundations of institutions, investigating how intraorganizational networks mediate the diffusion of…

Information transfer in community structured multiplex networks

NASA Astrophysics Data System (ADS)

Solé Ribalta, Albert; Granell, Clara; Gómez, Sergio; Arenas, Alex

2015-08-01

The study of complex networks that account for different types of interactions has become a subject of interest in the last few years, specially because its representational power in the description of users interactions in diverse online social platforms (Facebook, Twitter, Instagram, etc.). The mathematical description of these interacting networks has been coined under the name of multilayer networks, where each layer accounts for a type of interaction. It has been shown that diffusive processes on top of these networks present a phenomenology that cannot be explained by the naive superposition of single layer diffusive phenomena but require the whole structure of interconnected layers. Nevertheless, the description of diffusive phenomena on multilayer networks has obviated the fact that social networks have strong mesoscopic structure represented by different communities of individuals driven by common interests, or any other social aspect. In this work, we study the transfer of information in multilayer networks with community structure. The final goal is to understand and quantify, if the existence of well-defined community structure at the level of individual layers, together with the multilayer structure of the whole network, enhances or deteriorates the diffusion of packets of information.

Growing Oxide Nanowires and Nanowire Networks by Solid State Contact Diffusion into Solution-Processed Thin Films.

PubMed

Glynn, Colm; McNulty, David; Geaney, Hugh; O'Dwyer, Colm

2016-11-01

New techniques to directly grow metal oxide nanowire networks without the need for initial nanoparticle seed deposition or postsynthesis nanowire casting will bridge the gap between bottom-up formation and top-down processing for many electronic, photonic, energy storage, and conversion technologies. Whether etched top-down, or grown from catalyst nanoparticles bottom-up, nanowire growth relies on heterogeneous material seeds. Converting surface oxide films, ubiquitous in the microelectronics industry, to nanowires and nanowire networks by the incorporation of extra species through interdiffusion can provide an alternative deposition method. It is shown that solution-processed thin films of oxides can be converted and recrystallized into nanowires and networks of nanowires by solid-state interdiffusion of ionic species from a mechanically contacted donor substrate. NaVO 3 nanowire networks on smooth Si/SiO 2 and granular fluorine-doped tin oxide surfaces can be formed by low-temperature annealing of a Na diffusion species-containing donor glass to a solution-processed V 2 O 5 thin film, where recrystallization drives nanowire growth according to the crystal habit of the new oxide phase. This technique illustrates a new method for the direct formation of complex metal oxide nanowires on technologically relevant substrates, from smooth semiconductors, to transparent conducting materials and interdigitated device structures. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Social networks and alcohol use disorders: findings from a nationally representative sample

PubMed Central

Mowbray, Orion; Quinn, Adam; Cranford, James A.

2014-01-01

Background While some argue that social network ties of individuals with alcohol use disorders (AUD) are robust, there is evidence to suggest that individuals with AUDs have few social network ties, which are a known risk factor for health and wellness. Objectives Social network ties to friends, family, co-workers and communities of individuals are compared among individuals with a past-year diagnosis of alcohol dependence or alcohol abuse to individuals with no lifetime diagnosis of AUD. Method Respondents from Wave 2 of the National Epidemiologic Survey on Alcohol Related Conditions (NESARC) were assessed for the presence of past-year alcohol dependence or past-year alcohol abuse, social network ties, sociodemographics and clinical characteristics. Results Bivariate analyses showed that both social network size and social network diversity was significantly smaller among individuals with alcohol dependence, compared to individuals with alcohol abuse or no AUD. When social and clinical factors related to AUD status were controlled, multinomial logistic models showed that social network diversity remained a significant predictor of AUD status, while social network size did not differ among AUD groups. Conclusion Social networks of individuals with AUD may be different than individuals with no AUD, but this claim is dependent on specific AUD diagnosis and how social networks are measured. PMID:24405256

Exploiting Information Diffusion Feature for Link Prediction in Sina Weibo

NASA Astrophysics Data System (ADS)

Li, Dong; Zhang, Yongchao; Xu, Zhiming; Chu, Dianhui; Li, Sheng

2016-01-01

The rapid development of online social networks (e.g., Twitter and Facebook) has promoted research related to social networks in which link prediction is a key problem. Although numerous attempts have been made for link prediction based on network structure, node attribute and so on, few of the current studies have considered the impact of information diffusion on link creation and prediction. This paper mainly addresses Sina Weibo, which is the largest microblog platform with Chinese characteristics, and proposes the hypothesis that information diffusion influences link creation and verifies the hypothesis based on real data analysis. We also detect an important feature from the information diffusion process, which is used to promote link prediction performance. Finally, the experimental results on Sina Weibo dataset have demonstrated the effectiveness of our methods.

Exploiting Information Diffusion Feature for Link Prediction in Sina Weibo.

PubMed

Li, Dong; Zhang, Yongchao; Xu, Zhiming; Chu, Dianhui; Li, Sheng

2016-01-28

The rapid development of online social networks (e.g., Twitter and Facebook) has promoted research related to social networks in which link prediction is a key problem. Although numerous attempts have been made for link prediction based on network structure, node attribute and so on, few of the current studies have considered the impact of information diffusion on link creation and prediction. This paper mainly addresses Sina Weibo, which is the largest microblog platform with Chinese characteristics, and proposes the hypothesis that information diffusion influences link creation and verifies the hypothesis based on real data analysis. We also detect an important feature from the information diffusion process, which is used to promote link prediction performance. Finally, the experimental results on Sina Weibo dataset have demonstrated the effectiveness of our methods.

The Emergence Of The National Research And Education Network (NREN) And Its Implications For American Telecommunications

NASA Astrophysics Data System (ADS)

Maloff, Joel H.

1990-01-01

"The nation which most completely assimilates high performance computing into its economy will very likely emerge as the dominant intellectual, economic, and technological force in the next century", Senator Albert Gore, Jr., May 18, 1989, while introducing Senate Bill 1067, "The National High Performance Computer Technology Act of 1989". A national network designed to link supercomputers, particle accelerators, researchers, educators, government, and industry is beginning to emerge. The degree to which the United States can mobilize the resources inherent within our academic, industrial and government sectors towards the establishment of such a network infrastructure will have direct bearing on the economic and political stature of this country in the next century. This program will have significant impact on all forms of information transfer, and peripheral benefits to all walks of life similar to those experienced from the moon landing program of the 1960's. The key to our success is the involvement of scientists, librarians, network designers, and bureaucrats in the planning stages. Collectively, the resources resident within the United States are awesome; individually, their impact is somewhat more limited. The engineers, technicians, business people, and educators participating in this conference have a vital role to play in the success of the National Research and Education Network (NREN).

NDRC: A Disease-Causing Genes Prioritized Method Based on Network Diffusion and Rank Concordance.

PubMed

Fang, Minghong; Hu, Xiaohua; Wang, Yan; Zhao, Junmin; Shen, Xianjun; He, Tingting

2015-07-01

Disease-causing genes prioritization is very important to understand disease mechanisms and biomedical applications, such as design of drugs. Previous studies have shown that promising candidate genes are mostly ranked according to their relatedness to known disease genes or closely related disease genes. Therefore, a dangling gene (isolated gene) with no edges in the network can not be effectively prioritized. These approaches tend to prioritize those genes that are highly connected in the PPI network while perform poorly when they are applied to loosely connected disease genes. To address these problems, we propose a new disease-causing genes prioritization method that based on network diffusion and rank concordance (NDRC). The method is evaluated by leave-one-out cross validation on 1931 diseases in which at least one gene is known to be involved, and it is able to rank the true causal gene first in 849 of all 2542 cases. The experimental results suggest that NDRC significantly outperforms other existing methods such as RWR, VAVIEN, DADA and PRINCE on identifying loosely connected disease genes and successfully put dangling genes as potential candidate disease genes. Furthermore, we apply NDRC method to study three representative diseases, Meckel syndrome 1, Protein C deficiency and Peroxisome biogenesis disorder 1A (Zellweger). Our study has also found that certain complex disease-causing genes can be divided into several modules that are closely associated with different disease phenotype.

A Data-Gathering Scheme with Joint Routing and Compressive Sensing Based on Modified Diffusion Wavelets in Wireless Sensor Networks.

PubMed

Gu, Xiangping; Zhou, Xiaofeng; Sun, Yanjing

2018-02-28

Compressive sensing (CS)-based data gathering is a promising method to reduce energy consumption in wireless sensor networks (WSNs). Traditional CS-based data-gathering approaches require a large number of sensor nodes to participate in each CS measurement task, resulting in high energy consumption, and do not guarantee load balance. In this paper, we propose a sparser analysis that depends on modified diffusion wavelets, which exploit sensor readings' spatial correlation in WSNs. In particular, a novel data-gathering scheme with joint routing and CS is presented. A modified ant colony algorithm is adopted, where next hop node selection takes a node's residual energy and path length into consideration simultaneously. Moreover, in order to speed up the coverage rate and avoid the local optimal of the algorithm, an improved pheromone impact factor is put forward. More importantly, theoretical proof is given that the equivalent sensing matrix generated can satisfy the restricted isometric property (RIP). The simulation results demonstrate that the modified diffusion wavelets' sparsity affects the sensor signal and has better reconstruction performance than DFT. Furthermore, our data gathering with joint routing and CS can dramatically reduce the energy consumption of WSNs, balance the load, and prolong the network lifetime in comparison to state-of-the-art CS-based methods.

NASA/DoD Aerospace Knowledge Diffusion Research Project. Paper 30: The electronic transfer of information and aerospace knowledge diffusion

NASA Technical Reports Server (NTRS)

Pinelli, Thomas E.; Bishop, Ann P.; Barclay, Rebecca O.; Kennedy, John M.

1992-01-01

Increasing reliance on and investment in information technology and electronic networking systems presupposes that computing and information technology will play a major role in the diffusion of aerospace knowledge. Little is known, however, about actual information technology needs, uses, and problems within the aerospace knowledge diffusion process. The authors state that the potential contributions of information technology to increased productivity and competitiveness will be diminished unless empirically derived knowledge regarding the information-seeking behavior of the members of the social system - those who are producing, transferring, and using scientific and technical information - is incorporated into a new technology policy framework. Research into the use of information technology and electronic networks by U.S. aerospace engineers and scientists, collected as part of a research project designed to study aerospace knowledge diffusion, is presented in support of this assertion.

Educational Policies. National Dropout Prevention Center/Network Newsletter. Volume 19, Number 2, Spring 2007

ERIC Educational Resources Information Center

Duckenfield, Marty, Ed.

2007-01-01

The "National Dropout Prevention Newsletter" is published quarterly by the National Dropout Prevention Center/Network. This issue contains the following articles: (1) Policy Matters; (2) A Conversation With A State Policymaker (Stephen Canessa); (3) Policy Matters at the School Level (Steven W. Edwards); (4) EEDA: Promise or Peril? (Sam…

A National Network of Neurotechnology Centers for the BRAIN Initiative

PubMed Central

Alivisatos, A. Paul; Chun, Miyoung; Church, George M.; Greenspan, Ralph J.; Roukes, Michael L.; Yuste, Rafael

2017-01-01

We propose the creation of a national network of neurotechnology centers to enhance and accelerate the BRAIN Initiative and optimally leverage the effort and creativity of individual laboratories involved in it. As “brain observatories,” these centers could provide the critical interdisciplinary environment both for realizing ambitious and complex technologies and for providing individual investigators with access to them. PMID:26481036

National Geographic Society Kids Network: Report on 1994 teacher participants

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

NONE

In 1994, National Geographic Society Kids Network, a computer/telecommunications-based science curriculum, was presented to elementary and middle school teachers through summer programs sponsored by NGS and US DOE. The network program assists teachers in understanding the process of doing science; understanding the role of computers and telecommunications in the study of science, math, and engineering; and utilizing computers and telecommunications appropriately in the classroom. The program enables teacher to integrate science, math, and technology with other subjects with the ultimate goal of encouraging students of all abilities to pursue careers in science/math/engineering. This report assesses the impact of the networkmore » program on participating teachers.« less

Social Networks and Risk for Depressive Symptoms in a National Sample of Sexual Minority Youth

PubMed Central

Hatzenbuehler, Mark L.; McLaughlin, Katie A.; Xuan, Ziming

2012-01-01

The aim of the study was to examine the social networks of sexual minority youths and to determine the associations between social networks and depressive symptoms. Data were obtained from the National Longitudinal Study of Adolescent Health (Add Health), a nationally representative cohort study of American adolescents (N=14,212). Wave 1 (1994–1995) collected extensive information about the social networks of participants through peer nomination inventories, as well as measures of sexual minority status and depressive symptoms. Using social network data, we examined three characteristics of adolescents’ social relationships: (1) social isolation; (2) degree of connectedness; and (3) social status. Sexual minority youths, particularly females, were more isolated, less connected, and had lower social status in peer networks than opposite-sex attracted youths. Among sexual minority male (but not female) youths, greater isolation as well as lower connectedness and status within a network were associated with greater depressive symptoms. Moreover, greater isolation in social networks partially explained the association between sexual minority status and depressive symptoms among males. Finally, a significant 3-way interaction indicated that the association between social isolation and depression was stronger for sexual minority male youths than non-minority youths and sexual minority females. These results suggest that the social networks in which sexual minority male youths are embedded may confer risk for depressive symptoms, underscoring the importance of considering peer networks in both research and interventions targeting sexual minority male adolescents. PMID:22771037

Social networks and risk for depressive symptoms in a national sample of sexual minority youth.

PubMed

Hatzenbuehler, Mark L; McLaughlin, Katie A; Xuan, Ziming

2012-10-01

The aim of the study was to examine the social networks of sexual minority youths and to determine the associations between social networks and depressive symptoms. Data were obtained from the National Longitudinal Study of Adolescent Health (Add Health), a nationally representative cohort study of American adolescents (N = 14,212). Wave 1 (1994-1995) collected extensive information about the social networks of participants through peer nomination inventories, as well as measures of sexual minority status and depressive symptoms. Using social network data, we examined three characteristics of adolescents' social relationships: (1) social isolation; (2) degree of connectedness; and (3) social status. Sexual minority youths, particularly females, were more isolated, less connected, and had lower social status in peer networks than opposite-sex attracted youths. Among sexual minority male (but not female) youths, greater isolation as well as lower connectedness and status within a network were associated with greater depressive symptoms. Moreover, greater isolation in social networks partially explained the association between sexual minority status and depressive symptoms among males. Finally, a significant 3-way interaction indicated that the association between social isolation and depression was stronger for sexual minority male youths than non-minority youths and sexual minority females. These results suggest that the social networks in which sexual minority male youths are embedded may confer risk for depressive symptoms, underscoring the importance of considering peer networks in both research and interventions targeting sexual minority male adolescents. Copyright © 2012 Elsevier Ltd. All rights reserved.

77 FR 26509 - Request for Information on Proposed New Program: National Network for Manufacturing Innovation...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-05-04

...): Refining standards, materials, and equipment for additive manufacturing to enable low- cost, low-volume...-01] Request for Information on Proposed New Program: National Network for Manufacturing Innovation...: Request for information. SUMMARY: The NIST-hosted Advanced Manufacturing National Program Office (AMNPO...

Career and Technical Education. National Dropout Prevention Center/Network Newsletter. Volume 20, Number 3

ERIC Educational Resources Information Center

Duckenfield, Marty, Ed.

2008-01-01

The "National Dropout Prevention Newsletter" is published quarterly by the National Dropout Prevention Center/Network. This issue contains the following articles: (1) Why Do I Have to Learn This?; (2) 2008 NDPN Crystal Star Winners; (3) Effective Freshman Transition for School Improvement (David Livingston, John Greene, and Lindy Stahlman); (4)…

Middle College. National Dropout Prevention Center/Network Newsletter. Volume 17, Number 4, Fall 2005

ERIC Educational Resources Information Center

Duckenfield, Marty, Ed.

2005-01-01

The "National Dropout Prevention Newsletter" is published quarterly by the National Dropout Prevention Center/Network. This issue contains the following articles: (1) College As A Bridge to High School Graduation (Terry Cash); (2) 2005 NDPN Crystal Star Awards of Excellence; (3) Mott Middle College (Chery S. Wagonlander); (4) Gateway to…

Improving Schools' Partnership Programs in the National Network of Partnership Schools

ERIC Educational Resources Information Center

Sanders, Mavis; Sheldon, Steven; Epstein, Joyce

2005-01-01

The current wave of educational reform includes an emphasis on family and community involvement as a strategy for school improvement. Yet, to effectively engage families and communities in the educational process, educators need assistance and support. In 1996, the National Network of Partnership Schools (NNPS) was established to build the…

On Some Parabolic Type Problems from Thin Film Theory and Chemical Reaction-Diffusion Networks

NASA Astrophysics Data System (ADS)

Mohamed, Fatma Naser Ali

This dissertation considers some parabolic type problems from thin film theory and chemical reaction-diffusion networks. The dissertation consists of two parts: In the first part, we study the evolution of a thin film of fluid modeled by the lubrication approximation for thin viscous films. We prove an existence of (dissipative) strong solutions for the Cauchy problem when the sub-diffusive exponent ranges between 3/8 and 2; then we show that these solutions tend to zero at rates matching the decay of the source-type self-similar solutions with zero contact angle. We introduce the weaker concept of dissipative mild solutions and we show that, in this case, the surface-tension energy dissipation is the mechanism responsible for the H1-norm decay to zero of the thickness of the film at an explicit rate. Relaxed problems, with second-order nonlinear terms of porous media type, are also successfully treated by the same means. [special characters omitted]. In the second part, we are concerned with the convergence of a certain space-discretization scheme -the so-called method of lines- for mass-action reaction-diffusion systems. First, we start with a toy model, namely. [special characters omitted]. and prove convergence of method of lines for this linear case. Here weak convergence in L2(0,1) is enough to prove convergence of the method of lines. Then we adopt the framework for convergence analysis introduced in [23] and concentrate on the proof-of-concept reaction. within 1D space, while at the same time noting that our techniques are readily generalizable to other reaction-diffusion networks and to more than one space dimension. Indeed, it will be obvious how to extend our proofs to the multi-dimensional case; we only note that the proof of the comparison principle (the continuous and the discrete versions; see chapter 6) imposes a limitation on the spatial dimension (should be at most five; see [24] for details). The Method of Lines (MOL) is not a mainstream

A new matrix for scoring the functionality of national laboratory networks in Africa: introducing the LABNET scorecard

PubMed Central

Datema, Tjeerd; Keita-Sow, Mah-Sere; Ndihokubwayo, Jean-Bosco; Isadore, Jocelyn; Oskam, Linda; Nkengasong, John; Lewis, Kim

2016-01-01

Background Functional national laboratory networks and systems are indispensable to the achievement of global health security targets according to the International Health Regulations. The lack of indicators to measure the functionality of national laboratory network has limited the efficiency of past and current interventions to enhance laboratory capacity in resource-limited-settings. Scorecard for laboratory networks We have developed a matrix for the assessment of national laboratory network functionality and progress thereof, with support from the African Society of Laboratory Medicine and the Association of Public Health Laboratories. The laboratory network (LABNET) scorecard was designed to: (1) Measure the status of nine overarching core capabilities of laboratory network required to achieve global health security targets, as recommended by the main normative standards; (2) Complement the World Health Organization joint external evaluation tool for the assessment of health system preparedness to International Health Regulations (2005) by providing detailed information on laboratory systems; and (3) Serve as a clear roadmap to guide the stepwise implementation of laboratory capability to prevent, detect and act upon infectious threats. Conclusions The application of the LABNET scorecard under the coordination of the African Society of Laboratory Medicine and the Association of Public Health Laboratories could contribute to the design, monitoring and evaluation of upcoming Global Health Security Agenda-supported laboratory capacity building programmes in sub Saharan-Africa and other resource-limited settings, and inform the development of national laboratory policies and strategic plans. Endorsement by the World Health Organization Regional Office for Africa is foreseen. PMID:28879141

Multicomponent diffusion in molten salt NaF-ZrF4: Dynamical correlations and Maxwell-Stefan diffusivities

NASA Astrophysics Data System (ADS)

Baig, Mohammad Saad; Chakraborty, Brahmananda; Ramaniah, Lavanya M.

2016-05-01

NaF-ZrF4 is used as a waste incinerator and as a coolant in Generation IV reactors.Structural and dynamical properties of molten NaF-ZrF4 system were studied along with Onsagercoefficients and Maxwell-Stefan (MS) Diffusivities applying Green-Kubo formalism and molecular dynamics (MD) simulations. The zirconium ions are found to be 8 fold coordinated with fluoride ions for all temperatures and concentrations. All the diffusive flux correlations show back-scattering. Even though the MS diffusivities are expected to depend very lightly on the composition because of decoupling of thermodynamic factor, the diffusivity ĐNa-F shows interesting behavior with the increase in concentration of ZrF4. This is because of network formation in NaF-ZrF4. Positive entropy constraints have been plotted to authenticate negative diffusivities observed.

Establishment of National Gravity Base Network of Iran

NASA Astrophysics Data System (ADS)

Hatam Chavari, Y.; Bayer, R.; Hinderer, J.; Ghazavi, K.; Sedighi, M.; Luck, B.; Djamour, Y.; Le Moign, N.; Saadat, R.; Cheraghi, H.

2009-04-01

A gravity base network is supposed to be a set of benchmarks uniformly distributed across the country and the absolute gravity values at the benchmarks are known to the best accessible accuracy. The gravity at the benchmark stations are either measured directly with absolute devices or transferred by gravity difference measurements by gravimeters from known stations. To decrease the accumulation of random measuring errors arising from these transfers, the number of base stations distributed across the country should be as small as possible. This is feasible if the stations are selected near to the national airports long distances apart but faster accessible and measurable by a gravimeter carried in an airplane between the stations. To realize the importance of such a network, various applications of a gravity base network are firstly reviewed. A gravity base network is the required reference frame for establishing 1st , 2nd and 3rd order gravity networks. Such a gravity network is used for the following purposes: a. Mapping of the structure of upper crust in geology maps. The required accuracy for the measured gravity values is about 0.2 to 0.4 mGal. b. Oil and mineral explorations. The required accuracy for the measured gravity values is about 5 µGal. c. Geotechnical studies in mining areas for exploring the underground cavities as well as archeological studies. The required accuracy is about 5 µGal and better. d. Subsurface water resource explorations and mapping crustal layers which absorb it. An accuracy of the same level of previous applications is required here too. e. Studying the tectonics of the Earth's crust. Repeated precise gravity measurements at the gravity network stations can assist us in identifying systematic height changes. The accuracy of the order of 5 µGal and more is required. f. Studying volcanoes and their evolution. Repeated precise gravity measurements at the gravity network stations can provide valuable information on the gradual

Symmetrical and overloaded effect of diffusion in information filtering

NASA Astrophysics Data System (ADS)

Zhu, Xuzhen; Tian, Hui; Chen, Guilin; Cai, Shimin

2017-10-01

In physical dynamics, mass diffusion theory has been applied to design effective information filtering models on bipartite network. In previous works, researchers unilaterally believe objects' similarities are determined by single directional mass diffusion from the collected object to the uncollected, meanwhile, inadvertently ignore adverse influence of diffusion overload. It in some extent veils the essence of diffusion in physical dynamics and hurts the recommendation accuracy and diversity. After delicate investigation, we argue that symmetrical diffusion effectively discloses essence of mass diffusion, and high diffusion overload should be published. Accordingly, in this paper, we propose an symmetrical and overload penalized diffusion based model (SOPD), which shows excellent performances in extensive experiments on benchmark datasets Movielens and Netflix.

Combined inverse-forward artificial neural networks for fast and accurate estimation of the diffusion coefficients of cartilage based on multi-physics models.

PubMed

Arbabi, Vahid; Pouran, Behdad; Weinans, Harrie; Zadpoor, Amir A

2016-09-06

Analytical and numerical methods have been used to extract essential engineering parameters such as elastic modulus, Poisson׳s ratio, permeability and diffusion coefficient from experimental data in various types of biological tissues. The major limitation associated with analytical techniques is that they are often only applicable to problems with simplified assumptions. Numerical multi-physics methods, on the other hand, enable minimizing the simplified assumptions but require substantial computational expertise, which is not always available. In this paper, we propose a novel approach that combines inverse and forward artificial neural networks (ANNs) which enables fast and accurate estimation of the diffusion coefficient of cartilage without any need for computational modeling. In this approach, an inverse ANN is trained using our multi-zone biphasic-solute finite-bath computational model of diffusion in cartilage to estimate the diffusion coefficient of the various zones of cartilage given the concentration-time curves. Robust estimation of the diffusion coefficients, however, requires introducing certain levels of stochastic variations during the training process. Determining the required level of stochastic variation is performed by coupling the inverse ANN with a forward ANN that receives the diffusion coefficient as input and returns the concentration-time curve as output. Combined together, forward-inverse ANNs enable computationally inexperienced users to obtain accurate and fast estimation of the diffusion coefficients of cartilage zones. The diffusion coefficients estimated using the proposed approach are compared with those determined using direct scanning of the parameter space as the optimization approach. It has been shown that both approaches yield comparable results. Copyright © 2016 Elsevier Ltd. All rights reserved.

A National Network of Neurotechnology Centers for the BRAIN Initiative.

PubMed

Alivisatos, A Paul; Chun, Miyoung; Church, George M; Greenspan, Ralph J; Roukes, Michael L; Yuste, Rafael

2015-11-04

We propose the creation of a national network of neurotechnology centers to enhance and accelerate the BRAIN Initiative and optimally leverage the effort and creativity of individual laboratories involved in it. As "brain observatories," these centers could provide the critical interdisciplinary environment both for realizing ambitious and complex technologies and for providing individual investigators with access to them. Copyright © 2015 Elsevier Inc. All rights reserved.

Pore network modeling to explore the effects of compression on multiphase transport in polymer electrolyte membrane fuel cell gas diffusion layers

NASA Astrophysics Data System (ADS)

Fazeli, Mohammadreza; Hinebaugh, James; Fishman, Zachary; Tötzke, Christian; Lehnert, Werner; Manke, Ingo; Bazylak, Aimy

2016-12-01

Understanding how compression affects the distribution of liquid water and gaseous oxygen in the polymer electrolyte membrane fuel cell gas diffusion layer (GDL) is vital for informing the design of improved porous materials for effective water management strategies. Pore networks extracted from synchrotron-based micro-computed tomography images of compressed GDLs were employed to simulate liquid water transport in GDL materials over a range of compression pressures. The oxygen transport resistance was predicted for each sample under dry and partially saturated conditions. A favorable GDL compression value for a preferred liquid water distribution and oxygen diffusion was found for Toray TGP-H-090 (10%), yet an optimum compression value was not recognized for SGL Sigracet 25BC. SGL Sigracet 25BC exhibited lower transport resistance values compared to Toray TGP-H-090, and this is attributed to the additional diffusion pathways provided by the microporous layer (MPL), an effect that is particularly significant under partially saturated conditions.

A National Climate Change Adaptation Network for Protecting Water Security

NASA Astrophysics Data System (ADS)

Weaver, A.; Sauchyn, D.; Byrne, J. M.

2009-12-01

Water security and resource-dependent community-survival are being increasingly challenged as a consequence of climate change, and it is urgent that we plan now for the security of our water supplies which support our lives and livelihoods. However, the range of impacts of climate change on water availability, and the consequent environmental and human adaptations that are required, is so complex and serious that it will take the combined work of natural, health and social scientists working with industries and communities to solve them. Networks are needed that will identify crucial water issues under climate change at a range of scales in order to provide regionally-sensitive, solutions-oriented research and adaptation. We suggest national and supra-national water availability and community sustainability issues must be addressed by multidisciplinary research and adaptation networks. The work must be driven by a bottom-up research paradigm — science in the service of community and governance. We suggest that interdisciplinary teams of researchers, in partnership with community decision makers and local industries, are the best means to develop solutions as communities attempt to address future water demands, protect their homes from infrastructure damage, and meet their food, drinking water, and other essential resource requirements. The intention is to cover: the impact of climate change on Canadian natural resources, both marine and terrestrial; issues of long-term sustainability and resilience in human communities and the environments in which they are embedded; the making and moving of knowledge, be that between members of Indigenous and non-Indigenous communities, researchers of different disciplines, communities, industry, policymakers and the academy and the crucial involvement of the various orders of government in the response to water problems, under conditions of heightened uncertainty. Such an adaptation network must include a national

First-year Progress and Future Directions of the USA National Phenology Network

NASA Astrophysics Data System (ADS)

Weltzin, J. F.; Losleben, M. V.

2008-12-01

Background Periodic plant and animal cycles driven by seasonal variations in climate (i.e., phenology) set the stage for dynamics of ecosystem processes, determine land surface properties, control biosphere-atmosphere interactions, and affect food production, health, conservation, and recreation. Phenological data and models have applications related to scientific research, education and outreach, as well as to stakeholders interested in agriculture, tourism and recreation, human health, and natural resource conservation and management. The predictive potential of phenology requires a new data resource-a national network of integrated phenological observations and the tools to access and analyze them at multiple scales. The USA National Phenology Network (USA-NPN) is an emerging and exciting partnership between federal agencies, the academic community, and the general public to monitor and understand the influence of seasonal cycles on the Nation's resources. The USA-NPN will establish a wall-to-wall science and monitoring initiative focused on phenology as a tool to understand how plants, animals and landscapes respond to climate variation, and as a tool to facilitate human adaptation to ongoing and potential future climate change. Results The National Coordinating Office of the USA-NPN began operation in August 2007 at the University of Arizona, Tucson, AZ. This first year of operation produced many new phenology products and venues for phenology research and citizen involvement, as well as identification of future directions for the USA NPN. Products include a new web-site (www.usanpn.org) that went live in June 2008; the web-site includes a tool for on-line data entry, and serves as a clearinghouse for products and information to facilitate research and communication related to phenology. The new core Plant Phenology Program includes profiles for 185 vetted local, regional, and national plant species with descriptions and monitoring protocols, as well as

Mammal Inventory of the Mojave Network Parks-Death Valley and Joshua Tree National Parks, Lake Mead National Recreation Area, Manzanar National Historic Site, and Mojave National Preserve

USGS Publications Warehouse

Drost, Charles A.; Hart, Jan

2008-01-01

This report describes the results of a mammal inventory study of National Park Service units in the Mojave Desert Network, including Death Valley National Park, Joshua Tree National Park, Lake Mead National Recreation Area, Manzanar National Historic Site, and Mojave National Preserve. Fieldwork for the inventory focused on small mammals, primarily rodents and bats. Fieldwork for terrestrial small mammals used trapping with Sherman and Tomahawk small- and medium-sized mammal traps, along with visual surveys for diurnal species. The majority of sampling for terrestrial small mammals was carried out in 2002 and 2003. Methods used in field surveys for bats included mist-netting at tanks and other water bodies, along with acoustic surveys using Anabat. Most of the bat survey work was conducted in 2003. Because of extremely dry conditions in the first two survey years (and associated low mammal numbers), we extended field sampling into 2004, following a relatively wet winter. In addition to field sampling, we also reviewed, evaluated, and summarized museum and literature records of mammal species for all of the Park units. We documented a total of 59 mammal species as present at Death Valley National Park, with an additional five species that we consider of probable occurrence. At Joshua Tree, we also documented 50 species, and an additional four 'probable' species. At Lake Mead National Recreation Area, 57 mammal species have been positively documented, with 10 additional probable species. Manzanar National Historic Site had not been previously surveyed. We documented 19 mammal species at Manzanar, with an additional 11 probable species. Mojave National Preserve had not had a comprehensive list previously, either. There are now a total of 50 mammal species documented at Mojave, with three additional probable species. Of these totals, 23 occurrences are new at individual park units (positively documented for the first time), with most of these being at Manzanar

Global and national laboratory networks support high quality surveillance for measles and rubella.

PubMed

Xu, Wenbo; Zhang, Yan; Wang, Huiling; Zhu, Zhen; Mao, Naiying; Mulders, Mick N; Rota, Paul A

2017-05-01

Laboratory networks are an essential component of disease surveillance systems because they provide accurate and timely confirmation of infection. WHO coordinates global laboratory surveillance of vaccine preventable diseases, including measles and rubella. The more than 700 laboratories within the WHO Global Measles and Rubella Laboratory Network (GMRLN) supports surveillance for measles, rubella and congenial rubella syndrome in 191 counties. This paper describes the overall structure and function of the GMRLN and highlights the largest of the national laboratory networks, the China Measles and Rubella Laboratory Network. Published by Oxford University Press on behalf of Royal Society of Tropical Medicine and Hygiene 2017. This work is written by (a) US Government employee(s) and is in the public domain in the US.

Compliance with National Comprehensive Cancer Network anti-emesis guidelines in a Community Hospital Cancer Center.

PubMed

Daniel, Divya; Waddell, Aubrey

2016-02-01

Nausea and vomiting are common adverse events exhibited by patients receiving chemotherapy. Prophylactic use of anti-emetic agents has been shown to reduce chemotherapy-induced nausea and vomiting. Compliance with the National Comprehensive Cancer Network anti-emesis guidelines (Version 1.2013) by practitioners in a community out-patient hospital (Blount Memorial Hospital) has been reviewed and the results are presented herein. Retrospective study of patients receiving their first cycle of chemotherapy. A total of 487 patients were reviewed from January 2005 to July 2012. In total, 70 patients were categorized in the high-risk category, 292 patients were categorized in the moderate-risk category, 60 patients were categorized in the low-risk category, and 65 patients were categorized in the minimal-risk category as per the National Comprehensive Cancer Network guidelines. Included patients were being administered the first cycle of their first treatment at Blount Memorial Hospital. Data were collected retrospectively from patient chemotherapy dispensing folders. In all, 63% of the patients received appropriate anti-emetic prophylaxis medications as per the National Comprehensive Cancer Network guidelines. Post-comparison between outcomes based on the risk category showed that patients in the moderate-risk category were most likely (91%) and patients in the low-risk category were least likely (6.67%) to receive appropriate anti-emetic prophylaxis as per the National Comprehensive Cancer Network guidelines. Overall compliance with guidelines is acceptable. Patients in the moderate risk category are most likely to receive appropriate anti-emetic prophylaxis. © The Author(s) 2014.

Pathways for diffusion in the potential energy landscape of the network glass former SiO2

NASA Astrophysics Data System (ADS)

Niblett, S. P.; Biedermann, M.; Wales, D. J.; de Souza, V. K.

2017-10-01

We study the dynamical behaviour of a computer model for viscous silica, the archetypal strong glass former, and compare its diffusion mechanism with earlier studies of a fragile binary Lennard-Jones liquid. Three different methods of analysis are employed. First, the temperature and time scale dependence of the diffusion constant is analysed. Negative correlation of particle displacements influences transport properties in silica as well as in fragile liquids. We suggest that the difference between Arrhenius and super-Arrhenius diffusive behaviour results from competition between the correlation time scale and the caging time scale. Second, we analyse the dynamics using a geometrical definition of cage-breaking transitions that was proposed previously for fragile glass formers. We find that this definition accurately captures the bond rearrangement mechanisms that control transport in open network liquids, and reproduces the diffusion constants accurately at low temperatures. As the same method is applicable to both strong and fragile glass formers, we can compare correlation time scales in these two types of systems. We compare the time spent in chains of correlated cage breaks with the characteristic caging time and find that correlations in the fragile binary Lennard-Jones system persist for an order of magnitude longer than those in the strong silica system. We investigate the origin of the correlation behaviour by sampling the potential energy landscape for silica and comparing it with the binary Lennard-Jones model. We find no qualitative difference between the landscapes, but several metrics suggest that the landscape of the fragile liquid is rougher and more frustrated. Metabasins in silica are smaller than those in binary Lennard-Jones and contain fewer high-barrier processes. This difference probably leads to the observed separation of correlation and caging time scales.

Morphological inversion of complex diffusion

NASA Astrophysics Data System (ADS)

Nguyen, V. A. T.; Vural, D. C.

2017-09-01

Epidemics, neural cascades, power failures, and many other phenomena can be described by a diffusion process on a network. To identify the causal origins of a spread, it is often necessary to identify the triggering initial node. Here, we define a new morphological operator and use it to detect the origin of a diffusive front, given the final state of a complex network. Our method performs better than algorithms based on distance (closeness) and Jordan centrality. More importantly, our method is applicable regardless of the specifics of the forward model, and therefore can be applied to a wide range of systems such as identifying the patient zero in an epidemic, pinpointing the neuron that triggers a cascade, identifying the original malfunction that causes a catastrophic infrastructure failure, and inferring the ancestral species from which a heterogeneous population evolves.

Information filtering via preferential diffusion.

PubMed

Lü, Linyuan; Liu, Weiping

2011-06-01

Recommender systems have shown great potential in addressing the information overload problem, namely helping users in finding interesting and relevant objects within a huge information space. Some physical dynamics, including the heat conduction process and mass or energy diffusion on networks, have recently found applications in personalized recommendation. Most of the previous studies focus overwhelmingly on recommendation accuracy as the only important factor, while overlooking the significance of diversity and novelty that indeed provide the vitality of the system. In this paper, we propose a recommendation algorithm based on the preferential diffusion process on a user-object bipartite network. Numerical analyses on two benchmark data sets, MovieLens and Netflix, indicate that our method outperforms the state-of-the-art methods. Specifically, it can not only provide more accurate recommendations, but also generate more diverse and novel recommendations by accurately recommending unpopular objects.

Information filtering via preferential diffusion

NASA Astrophysics Data System (ADS)

Lü, Linyuan; Liu, Weiping

2011-06-01

Recommender systems have shown great potential in addressing the information overload problem, namely helping users in finding interesting and relevant objects within a huge information space. Some physical dynamics, including the heat conduction process and mass or energy diffusion on networks, have recently found applications in personalized recommendation. Most of the previous studies focus overwhelmingly on recommendation accuracy as the only important factor, while overlooking the significance of diversity and novelty that indeed provide the vitality of the system. In this paper, we propose a recommendation algorithm based on the preferential diffusion process on a user-object bipartite network. Numerical analyses on two benchmark data sets, MovieLens and Netflix, indicate that our method outperforms the state-of-the-art methods. Specifically, it can not only provide more accurate recommendations, but also generate more diverse and novel recommendations by accurately recommending unpopular objects.

Establishment of a Physical Model for Solute Diffusion in Hydrogel: Understanding the Diffusion of Proteins in Poly(sulfobetaine methacrylate) Hydrogel.

PubMed

Zhou, Yuhang; Li, Junjie; Zhang, Ying; Dong, Dianyu; Zhang, Ershuai; Ji, Feng; Qin, Zhihui; Yang, Jun; Yao, Fanglian

2017-02-02

Prediction of the diffusion coefficient of solute, especially bioactive molecules, in hydrogel is significant in the biomedical field. Considering the randomness of solute movement in a hydrogel network, a physical diffusion RMP-1 model based on obstruction theory was established in this study. The physical properties of the solute and the polymer chain and their interactions were introduced into this model. Furthermore, models RMP-2 and RMP-3 were established to understand and predict the diffusion behaviors of proteins in hydrogel. In addition, zwitterionic poly(sulfobetaine methacrylate) (PSBMA) hydrogels with wide range and fine adjustable mesh sizes were prepared and used as efficient experimental platforms for model validation. The Flory characteristic ratios, Flory-Huggins parameter, mesh size, and polymer chain radii of PSBMA hydrogels were determined. The diffusion coefficients of the proteins (bovine serum albumin, immunoglobulin G, and lysozyme) in PSBMA hydrogels were studied by the fluorescence recovery after photobleaching technique. The measured diffusion coefficients were compared with the predictions of obstruction models, and it was found that our model presented an excellent predictive ability. Furthermore, the assessment of our model revealed that protein diffusion in PSBMA hydrogel would be affected by the physical properties of the protein and the PSBMA network. It was also confirmed that the diffusion behaviors of protein in zwitterionic hydrogels can be adjusted by changing the cross-linking density of the hydrogel and the ionic strength of the swelling medium. Our model is expected to possess accurate predictive ability for the diffusion coefficient of solute in hydrogel, which will be widely used in the biomedical field.

A new matrix for scoring the functionality of national laboratory networks in Africa: introducing the LABNET scorecard.

PubMed

Ondoa, Pascale; Datema, Tjeerd; Keita-Sow, Mah-Sere; Ndihokubwayo, Jean-Bosco; Isadore, Jocelyn; Oskam, Linda; Nkengasong, John; Lewis, Kim

2016-01-01

Functional national laboratory networks and systems are indispensable to the achievement of global health security targets according to the International Health Regulations. The lack of indicators to measure the functionality of national laboratory network has limited the efficiency of past and current interventions to enhance laboratory capacity in resource-limited-settings. We have developed a matrix for the assessment of national laboratory network functionality and progress thereof, with support from the African Society of Laboratory Medicine and the Association of Public Health Laboratories. The laboratory network (LABNET) scorecard was designed to: (1) Measure the status of nine overarching core capabilities of laboratory network required to achieve global health security targets, as recommended by the main normative standards; (2) Complement the World Health Organization joint external evaluation tool for the assessment of health system preparedness to International Health Regulations (2005) by providing detailed information on laboratory systems; and (3) Serve as a clear roadmap to guide the stepwise implementation of laboratory capability to prevent, detect and act upon infectious threats. The application of the LABNET scorecard under the coordination of the African Society of Laboratory Medicine and the Association of Public Health Laboratories could contribute to the design, monitoring and evaluation of upcoming Global Health Security Agenda-supported laboratory capacity building programmes in sub Saharan-Africa and other resource-limited settings, and inform the development of national laboratory policies and strategic plans. Endorsement by the World Health Organization Regional Office for Africa is foreseen.

The National Research and Education Network (NREN): Research and Policy Perspectives.

ERIC Educational Resources Information Center

McClure, Charles R.; And Others

This book provides an overview and status report on the progress made in developing the National Research and Education Network (NREN) as of early 1991. It reports on a number of investigations that provide a research and policy perspective on the NREN and computer-mediated communication (CMC), and brings together key source documents that have…

Detecting causality in policy diffusion processes.

PubMed

Grabow, Carsten; Macinko, James; Silver, Diana; Porfiri, Maurizio

2016-08-01

A universal question in network science entails learning about the topology of interaction from collective dynamics. Here, we address this question by examining diffusion of laws across US states. We propose two complementary techniques to unravel determinants of this diffusion process: information-theoretic union transfer entropy and event synchronization. In order to systematically investigate their performance on law activity data, we establish a new stochastic model to generate synthetic law activity data based on plausible networks of interactions. Through extensive parametric studies, we demonstrate the ability of these methods to reconstruct networks, varying in size, link density, and degree heterogeneity. Our results suggest that union transfer entropy should be preferred for slowly varying processes, which may be associated with policies attending to specific local problems that occur only rarely or with policies facing high levels of opposition. In contrast, event synchronization is effective for faster enactment rates, which may be related to policies involving Federal mandates or incentives. This study puts forward a data-driven toolbox to explain the determinants of legal activity applicable to political science, across dynamical systems, information theory, and complex networks.

Detecting causality in policy diffusion processes

NASA Astrophysics Data System (ADS)

Grabow, Carsten; Macinko, James; Silver, Diana; Porfiri, Maurizio

2016-08-01

A universal question in network science entails learning about the topology of interaction from collective dynamics. Here, we address this question by examining diffusion of laws across US states. We propose two complementary techniques to unravel determinants of this diffusion process: information-theoretic union transfer entropy and event synchronization. In order to systematically investigate their performance on law activity data, we establish a new stochastic model to generate synthetic law activity data based on plausible networks of interactions. Through extensive parametric studies, we demonstrate the ability of these methods to reconstruct networks, varying in size, link density, and degree heterogeneity. Our results suggest that union transfer entropy should be preferred for slowly varying processes, which may be associated with policies attending to specific local problems that occur only rarely or with policies facing high levels of opposition. In contrast, event synchronization is effective for faster enactment rates, which may be related to policies involving Federal mandates or incentives. This study puts forward a data-driven toolbox to explain the determinants of legal activity applicable to political science, across dynamical systems, information theory, and complex networks.

Network Reliability: The effect of local network structure on diffusive processes

PubMed Central

Youssef, Mina; Khorramzadeh, Yasamin; Eubank, Stephen

2014-01-01

This paper re-introduces the network reliability polynomial – introduced by Moore and Shannon in 1956 – for studying the effect of network structure on the spread of diseases. We exhibit a representation of the polynomial that is well-suited for estimation by distributed simulation. We describe a collection of graphs derived from Erdős-Rényi and scale-free-like random graphs in which we have manipulated assortativity-by-degree and the number of triangles. We evaluate the network reliability for all these graphs under a reliability rule that is related to the expected size of a connected component. Through these extensive simulations, we show that for positively or neutrally assortative graphs, swapping edges to increase the number of triangles does not increase the network reliability. Also, positively assortative graphs are more reliable than neutral or disassortative graphs with the same number of edges. Moreover, we show the combined effect of both assortativity-by-degree and the presence of triangles on the critical point and the size of the smallest subgraph that is reliable. PMID:24329321

Journal Article: the National Dioxin Air Monitoring Network ...

EPA Pesticide Factsheets

In June, 1998, the U.S. EPA established the National Dioxin Air Monitoring Network (NDAMN). The primary goal of NDAMN is determine the temporal and geographical variability of atmospheric CDDs, CDFs, and coplanar PCBs at rural and nonimpacted locations throughout the United States. Currently operating at 32 sampling stations, NDAMN has three primary purposes: (1) to determine the atmospheric levels and occurrences of dioxin-like compounds in rural and agricultural areas where livestock, poultry and animal feed crops are grown; (2) to provide measurements of atmospheric levels of dioxin-like compounds in different geographic regions of the U.S.; and (3) to provide information regarding the long-range transport of dioxin-like compounds in air over the U.S. At Dioxin 2000, we reported on the preliminary results of monitoring at 9 rural locations from June 1998 through June 1999. By the end of 1999, NDAMN had expanded to 21 sampling stations. Then, at Dioxin 2001, we reported the results of the first 18 months of operation of NDAMN at 15 rural and 6 National Park stations in the United States. The following is intended to be an update to this national monitoring effort. We are reporting the air monitoring results of 17 rural and 8 National Park NDAMN stations operational over 4 sampling moments during calendar year 2000. Two stations located in suburban Washington DC and San Francisco, CA are more urban in character and serve as an indicator of CDD/F and cop

The HOME network: an Australian national initiative for home therapies.

PubMed

Chow, Josephine; Fortnum, Debbie; Moodie, Jo-Anne; Simmonds, Rosemary; Tomlins, Melinda

2013-01-01

Longer, more frequent dialysis at home can improve life expectancy for patients with chronic kidney disease. Increased use of home dialysis therapies also benefits the hospital system, allowing for more efficient allocation of clinic resources. However, the Australian and New Zealand Data Registry statistics highlight the low uptake of home haemodialysis and peritoneal dialysis across Australia. In August 2009, the Australia's HOME Network was established as a national initiative to engage and empower healthcare professionals working in the home dialysis specialty. The aim was to develop solutions to advocate for and ultimately increase the use of home therapies. This paper describes the development, achievement and future plan of the Australian HOME Network. Achievements to date include: a survey of HOME Network members to assess the current state of patient and healthcare professional-targeted education resources; development of two patient case studies and activities addressing how to overcome the financial burden experienced by patients on home dialysis. Future projects aim to improve patient and healthcare professional education, and advocacy for home dialysis therapies. The HOME Network is supporting healthcare professionals working in the home dialysis specialty to develop solutions and tools that will help to facilitate greater utilisation of home dialysis therapies. © 2013 European Dialysis and Transplant Nurses Association/European Renal Care Association.

The Italian National Seismic Network

NASA Astrophysics Data System (ADS)

Michelini, Alberto

2016-04-01

The Italian National Seismic Network is composed by about 400 stations, mainly broadband, installed in the Country and in the surrounding regions. About 110 stations feature also collocated strong motion instruments. The Centro Nazionale Terremoti, (National Earthquake Center), CNT, has installed and operates most of these stations, although a considerable number of stations contributing to the INGV surveillance has been installed and is maintained by other INGV sections (Napoli, Catania, Bologna, Milano) or even other Italian or European Institutions. The important technological upgrades carried out in the last years has allowed for significant improvements of the seismic monitoring of Italy and of the Euro-Mediterranean Countries. The adopted data transmission systems include satellite, wireless connections and wired lines. The Seedlink protocol has been adopted for data transmission. INGV is a primary node of EIDA (European Integrated Data Archive) for archiving and distributing, continuous, quality checked data. The data acquisition system was designed to accomplish, in near-real-time, automatic earthquake detection and hypocenter and magnitude determination (moment tensors, shake maps, etc.). Database archiving of all parametric results are closely linked to the existing procedures of the INGV seismic monitoring environment. Overall, the Italian earthquake surveillance service provides, in quasi real-time, hypocenter parameters which are then revised routinely by the analysts of the Bollettino Sismico Nazionale. The results are published on the web page http://cnt.rm.ingv.it/ and are publicly available to both the scientific community and the the general public. This presentation will describe the various activities and resulting products of the Centro Nazionale Terremoti. spanning from data acquisition to archiving, distribution and specialised products.

Geographic Diffusion and Implementation of Acute Care Surgery: An Uneven Solution to the National Emergency General Surgery Crisis.

PubMed

Khubchandani, Jasmine A; Ingraham, Angela M; Daniel, Vijaya T; Ayturk, Didem; Kiefe, Catarina I; Santry, Heena P

2018-02-01

Owing to lack of adequate emergency care infrastructure and decline in general surgery workforce, the United States faces a crisis in access to emergency general surgery (EGS) care. Acute care surgery (ACS), an organized system of trauma, general surgery, and critical care, is a proposed solution; however, ACS diffusion remains poorly understood. To investigate geographic diffusion of ACS models of care and characterize the communities in which ACS implementation is lagging. A national survey on EGS practices was developed, tested, and administered at all 2811 US acute care hospitals providing EGS to adults between August 2015 and October 2015. Surgeons responsible for EGS coverage at these hospitals were approached. If these surgeons failed to respond to the initial survey implementation, secondary surgeons or chief medical officers at hospitals with only 1 general surgeon were approached. Survey responses on ACS implementation were linked with geocoded hospital data and national census data to determine geographic diffusion of and access to ACS. We measured the distribution of hospitals with ACS models of care vs those without over time (diffusion) and by US counties characterized by sociodemographic characteristics of county residents (access). Survey response rate was 60% (n = 1690); 272 responding hospitals had implemented ACS by 2015, steadily increasing from 34 in 2001 to 125 in 2010. Acute care surgery implementation has not been uniform. Rural regions have limited ACS access, with hospitals in counties with greater than the 75th percentile population having 5.4 times higher odds (95% CI, 1.66-7.35) of implementing ACS than hospitals in counties with less than 25th percentile population. Communities with greater percentages of adults without a college degree also have limited ACS access (OR, 3.43; 95% CI, 1.81-6.48). However, incorporating EGS into ACS models may be a potential equalizer for poor, black, and Hispanic communities. Understanding and

Interplay between translational diffusion and large-amplitude angular jumps of water molecules

NASA Astrophysics Data System (ADS)

Liu, Chao; Zhang, Yangyang; Zhang, Jian; Wang, Jun; Li, Wenfei; Wang, Wei

2018-05-01

Understanding the microscopic mechanism of water molecular translational diffusion is a challenging topic in both physics and chemistry. Here, we report an investigation on the interplay between the translational diffusion and the large-amplitude angular jumps of water molecules in bulk water using molecular dynamics simulations. We found that large-amplitude angular jumps are tightly coupled to the translational diffusions. Particularly, we revealed that concurrent rotational jumps of spatially neighboring water molecules induce inter-basin translational jumps, which contributes to the fast component of the water translational diffusion. Consequently, the translational diffusion shows positional heterogeneity; i.e., the neighbors of the water molecules with inter-basin translational jumps have larger probability to diffuse by inter-basin translational jumps. Our control simulations showed that a model water molecule with moderate hydrogen bond strength can diffuse much faster than a simple Lennard-Jones particle in bulk water due to the capability of disturbing the hydrogen bond network of the surrounding water molecules. Our results added to the understanding of the microscopic picture of the water translational diffusion and demonstrated the unique features of water diffusion arising from their hydrogen bond network structure compared with those of the simple liquids.

Quality Inservice Education: Final Report of the National Inservice Network, 1978-1981.

ERIC Educational Resources Information Center

Burrello, Leonard C.; And Others

The document comprises the final report of the National Inservice Network (NIN), a program to describe and distribute regular education inservice (REGI) project abstracts, products, and lessons aimed at more effectively working with handicapped students. Initial sections contain an executive summary and an overview explaining the NIN as a…

Enhancement of the national strong-motion network in Turkey

USGS Publications Warehouse

Gulkan, Polat; Ceken, U.; Colakoglu, Z.; Ugras, T.; Kuru, T.; Apak, A.; Anderson, J.G.; Sucuoglu, H.; Celebi, M.; Akkar, D.S.; Yazgan, U.; Denizlioglu, A.Z.

2007-01-01

Two arrays comprising 20 strong-motion sensors were established in western Turkey. The 14 stations of BYTNet follow a N-S trending line about 65 km in length, normal to strands of the North Anatolian fault that runs between the cities of Bursa and Yalova. Here the dominant character of the potential fault movement is a right-lateral transform slip. The DATNet array, comprising a total of eight stations, is arranged along a 110-km-long E-W trending direction along the Menderes River valley between Denizli and Aydin. (Two stations in this array were incorporated from the existing Turkish national strong-motion network.) This is an extensional tectonic environment, and the network mornitors potential large normal-faulting earthquakes on the faults in the valley. The installation of the arrays was supported by the North Atlantic Treaty Organization (NATO) under its Science for Peace Program. Maintenance and calibration is performed by the General Directorate of Disaster Affairs (GDDA) according to a protocol between Middle East Technical University (METU) and GDDA. Many young engineers and scientists have been trained in network operation and evaluation during the course of the project, and an international workshop dealing with strong-motion instrumentation has been organized as part of the project activities.

Automated voxel classification used with atlas-guided diffuse optical tomography for assessment of functional brain networks in young and older adults.

PubMed

Li, Lin; Cazzell, Mary; Babawale, Olajide; Liu, Hanli

2016-10-01

Atlas-guided diffuse optical tomography (atlas-DOT) is a computational means to image changes in cortical hemodynamic signals during human brain activities. Graph theory analysis (GTA) is a network analysis tool commonly used in functional neuroimaging to study brain networks. Atlas-DOT has not been analyzed with GTA to derive large-scale brain connectivity/networks based on near-infrared spectroscopy (NIRS) measurements. We introduced an automated voxel classification (AVC) method that facilitated the use of GTA with atlas-DOT images by grouping unequal-sized finite element voxels into anatomically meaningful regions of interest within the human brain. The overall approach included volume segmentation, AVC, and cross-correlation. To demonstrate the usefulness of AVC, we applied reproducibility analysis to resting-state functional connectivity measurements conducted from 15 young adults in a two-week period. We also quantified and compared changes in several brain network metrics between young and older adults, which were in agreement with those reported by a previous positron emission tomography study. Overall, this study demonstrated that AVC is a useful means for facilitating integration or combination of atlas-DOT with GTA and thus for quantifying NIRS-based, voxel-wise resting-state functional brain networks.

Knowledge diffusion in the collaboration hypernetwork

NASA Astrophysics Data System (ADS)

Yang, Guang-Yong; Hu, Zhao-Long; Liu, Jian-Guo

2015-02-01

As knowledge constitutes a primary productive force, it is important to understand the performance of knowledge diffusion. In this paper, we present a knowledge diffusion model based on the local-world non-uniform hypernetwork, which introduces the preferential diffusion mechanism and the knowledge absorptive capability αj, where αj is correlated with the hyperdegree dH(j) of node j. At each time step, we randomly select a node i as the sender; a receiver node is selected from the set of nodes that the sender i has published with previously, with probability proportional to the number of papers they have published together. Applying the average knowledge stock V bar(t) , the variance σ2(t) and the variance coefficient c(t) of knowledge stock to measure the growth and diffusion of knowledge and the adequacy of knowledge diffusion, we have made 3 groups of comparative experiments to investigate how different network structures, hypernetwork sizes and knowledge evolution mechanisms affect the knowledge diffusion, respectively. As the diffusion mechanisms based on the hypernetwork combine with the hyperdegree of node, the hypernetwork is more suitable for investigating the performance of knowledge diffusion. Therefore, the proposed model could be helpful for deeply understanding the process of the knowledge diffusion in the collaboration hypernetwork.

A Gossip-based Energy Efficient Protocol for Robust In-network Aggregation in Wireless Sensor Networks

NASA Astrophysics Data System (ADS)

Fauji, Shantanu

We consider the problem of energy efficient and fault tolerant in--network aggregation for wireless sensor networks (WSNs). In-network aggregation is the process of aggregation while collecting data from sensors to the base station. This process should be energy efficient due to the limited energy at the sensors and tolerant to the high failure rates common in sensor networks. Tree based in--network aggregation protocols, although energy efficient, are not robust to network failures. Multipath routing protocols are robust to failures to a certain degree but are not energy efficient due to the overhead in the maintenance of multiple paths. We propose a new protocol for in-network aggregation in WSNs, which is energy efficient, achieves high lifetime, and is robust to the changes in the network topology. Our protocol, gossip--based protocol for in-network aggregation (GPIA) is based on the spreading of information via gossip. GPIA is not only adaptive to failures and changes in the network topology, but is also energy efficient. Energy efficiency of GPIA comes from all the nodes being capable of selective message reception and detecting convergence of the aggregation early. We experimentally show that GPIA provides significant improvement over some other competitors like the Ridesharing, Synopsis Diffusion and the pure version of gossip. GPIA shows ten fold, five fold and two fold improvement over the pure gossip, the synopsis diffusion and Ridesharing protocols in terms of network lifetime, respectively. Further, GPIA retains gossip's robustness to failures and improves upon the accuracy of synopsis diffusion and Ridesharing.

Unstructured Polyhedral Mesh Thermal Radiation Diffusion

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

Palmer, T.S.; Zika, M.R.; Madsen, N.K.

2000-07-27

Unstructured mesh particle transport and diffusion methods are gaining wider acceptance as mesh generation, scientific visualization and linear solvers improve. This paper describes an algorithm that is currently being used in the KULL code at Lawrence Livermore National Laboratory to solve the radiative transfer equations. The algorithm employs a point-centered diffusion discretization on arbitrary polyhedral meshes in 3D. We present the results of a few test problems to illustrate the capabilities of the radiation diffusion module.

Abnormal Connectional Fingerprint in Schizophrenia: A Novel Network Analysis of Diffusion Tensor Imaging Data

PubMed Central

Edwin Thanarajah, Sharmili; Han, Cheol E.; Rotarska-Jagiela, Anna; Singer, Wolf; Deichmann, Ralf; Maurer, Konrad; Kaiser, Marcus; Uhlhaas, Peter J.

2016-01-01

The graph theoretical analysis of structural magnetic resonance imaging (MRI) data has received a great deal of interest in recent years to characterize the organizational principles of brain networks and their alterations in psychiatric disorders, such as schizophrenia. However, the characterization of networks in clinical populations can be challenging, since the comparison of connectivity between groups is influenced by several factors, such as the overall number of connections and the structural abnormalities of the seed regions. To overcome these limitations, the current study employed the whole-brain analysis of connectional fingerprints in diffusion tensor imaging data obtained at 3 T of chronic schizophrenia patients (n = 16) and healthy, age-matched control participants (n = 17). Probabilistic tractography was performed to quantify the connectivity of 110 brain areas. The connectional fingerprint of a brain area represents the set of relative connection probabilities to all its target areas and is, hence, less affected by overall white and gray matter changes than absolute connectivity measures. After detecting brain regions with abnormal connectional fingerprints through similarity measures, we tested each of its relative connection probability between groups. We found altered connectional fingerprints in schizophrenia patients consistent with a dysconnectivity syndrome. While the medial frontal gyrus showed only reduced connectivity, the connectional fingerprints of the inferior frontal gyrus and the putamen mainly contained relatively increased connection probabilities to areas in the frontal, limbic, and subcortical areas. These findings are in line with previous studies that reported abnormalities in striatal–frontal circuits in the pathophysiology of schizophrenia, highlighting the potential utility of connectional fingerprints for the analysis of anatomical networks in the disorder. PMID:27445870

Abnormal Connectional Fingerprint in Schizophrenia: A Novel Network Analysis of Diffusion Tensor Imaging Data.

PubMed

Edwin Thanarajah, Sharmili; Han, Cheol E; Rotarska-Jagiela, Anna; Singer, Wolf; Deichmann, Ralf; Maurer, Konrad; Kaiser, Marcus; Uhlhaas, Peter J

2016-01-01

The graph theoretical analysis of structural magnetic resonance imaging (MRI) data has received a great deal of interest in recent years to characterize the organizational principles of brain networks and their alterations in psychiatric disorders, such as schizophrenia. However, the characterization of networks in clinical populations can be challenging, since the comparison of connectivity between groups is influenced by several factors, such as the overall number of connections and the structural abnormalities of the seed regions. To overcome these limitations, the current study employed the whole-brain analysis of connectional fingerprints in diffusion tensor imaging data obtained at 3 T of chronic schizophrenia patients (n = 16) and healthy, age-matched control participants (n = 17). Probabilistic tractography was performed to quantify the connectivity of 110 brain areas. The connectional fingerprint of a brain area represents the set of relative connection probabilities to all its target areas and is, hence, less affected by overall white and gray matter changes than absolute connectivity measures. After detecting brain regions with abnormal connectional fingerprints through similarity measures, we tested each of its relative connection probability between groups. We found altered connectional fingerprints in schizophrenia patients consistent with a dysconnectivity syndrome. While the medial frontal gyrus showed only reduced connectivity, the connectional fingerprints of the inferior frontal gyrus and the putamen mainly contained relatively increased connection probabilities to areas in the frontal, limbic, and subcortical areas. These findings are in line with previous studies that reported abnormalities in striatal-frontal circuits in the pathophysiology of schizophrenia, highlighting the potential utility of connectional fingerprints for the analysis of anatomical networks in the disorder.

Deployment of the National Transparent Optical Network around the San Francisco Bay Area

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

McCammon, K.; Haigh, R.; Armstrong, G.

1996-06-01

We report on the deployment and initial operation of the National Transparent Optical Network, an experimental WDM network testbed around the San Francisco Bay Area, during the Optical Fiber Conference (OFC`96) held in San Jose, CA. The deployment aspects of the physical plant, optical and SONET layers are examined along with a discussion of broadband applications which utilized the network during the OFC`96 demonstration. The network features dense WDM technology, transparent optical routing technology using acousto- optic tunable filter based switches, and network modules with add/drop, multicast, and wavelength translation capabilities. The physical layer consisted of over 300 km ofmore » Sprint and Pacific Bell conventional single mode fiber which was amplified with I I optical amplifiers deployed in pre-amp, post-amp, and line amp configurations. An out-of-band control network provided datacom channels from remote equipment sites to the SONET network manager deployed at the San Jose Convention Center for the conference. Data transport over five wavelengths was achieved in the 1550 nm window using a variety of signal formats including analog and digital signal transmission on different wavelengths on the same fiber. The network operated throughout the week of OFC`96 and is still in operation today.« less

Data from selected U.S. Geological Survey national stream water-quality monitoring networks (WQN) on CD-ROM

USGS Publications Warehouse

Alexander, R.B.; Ludtke, A.S.; Fitzgerald, K.K.; Schertz, T.L.

1996-01-01

Data from two U.S. Geological Survey (USGS) national stream water-quality monitoring networks, the National Stream Quality Accounting Network (NASQAN) and the Hydrologic Benchmark Network (HBN), are now available in a two CD-ROM set. These data on CD-ROM are collectively referred to as WQN, water-quality networks. Data from these networks have been used at the national, regional, and local levels to estimate the rates of chemical flux from watersheds, quantify changes in stream water quality for periods during the past 30 years, and investigate relations between water quality and streamflow as well as the relations of water quality to pollution sources and various physical characteristics of watersheds. The networks include 679 monitoring stations in watersheds that represent diverse climatic, physiographic, and cultural characteristics. The HBN includes 63 stations in relatively small, minimally disturbed basins ranging in size from 2 to 2,000 square miles with a median drainage basin size of 57 square miles. NASQAN includes 618 stations in larger, more culturally-influenced drainage basins ranging in size from one square mile to 1.2 million square miles with a median drainage basin size of about 4,000 square miles. The CD-ROMs contain data for 63 physical, chemical, and biological properties of water (122 total constituents including analyses of dissolved and water suspended-sediment samples) collected during more than 60,000 site visits. These data approximately span the periods 1962-95 for HBN and 1973-95 for NASQAN. The data reflect sampling over a wide range of streamflow conditions and the use of relatively consistent sampling and analytical methods. The CD-ROMs provide ancillary information and data-retrieval tools to allow the national network data to be properly and efficiently used. Ancillary information includes the following: descriptions of the network objectives and history, characteristics of the network stations and water-quality data, historical

Dynamics of information diffusion and its applications on complex networks

NASA Astrophysics Data System (ADS)

Zhang, Zi-Ke; Liu, Chuang; Zhan, Xiu-Xiu; Lu, Xin; Zhang, Chu-Xu; Zhang, Yi-Cheng

2016-09-01

The ongoing rapid expansion of the Word Wide Web (WWW) greatly increases the information of effective transmission from heterogeneous individuals to various systems. Extensive research for information diffusion is introduced by a broad range of communities including social and computer scientists, physicists, and interdisciplinary researchers. Despite substantial theoretical and empirical studies, unification and comparison of different theories and approaches are lacking, which impedes further advances. In this article, we review recent developments in information diffusion and discuss the major challenges. We compare and evaluate available models and algorithms to respectively investigate their physical roles and optimization designs. Potential impacts and future directions are discussed. We emphasize that information diffusion has great scientific depth and combines diverse research fields which makes it interesting for physicists as well as interdisciplinary researchers.

Evaluating the stability of DSM-5 PTSD symptom network structure in a national sample of U.S. military veterans.

PubMed

von Stockert, Sophia H H; Fried, Eiko I; Armour, Cherie; Pietrzak, Robert H

2018-03-15

Previous studies have used network models to investigate how PTSD symptoms associate with each other. However, analyses examining the degree to which these networks are stable over time, which are critical to identifying symptoms that may contribute to the chronicity of this disorder, are scarce. In the current study, we evaluated the temporal stability of DSM-5 PTSD symptom networks over a three-year period in a nationally representative sample of trauma-exposed U.S. military veterans. Data were analyzed from 611 trauma-exposed U.S. military veterans who participated in the National Health and Resilience in Veterans Study (NHRVS). We estimated regularized partial correlation networks of DSM-5 PTSD symptoms at baseline (Time 1) and at three-year follow-up (Time 2), and examined their temporal stability. Evaluation of the network structure of PTSD symptoms at Time 1 and Time 2 using a formal network comparison indicated that the Time 1 network did not differ significantly from the Time 2 network with regard to network structure (p = 0.12) or global strength (sum of all absolute associations, i.e. connectivity; p = 0.25). Centrality estimates of both networks (r = 0.86) and adjacency matrices (r = 0.69) were highly correlated. In both networks, avoidance, intrusive, and negative cognition and mood symptoms were among the more central nodes. This study is limited by the use of a self-report instrument to assess PTSD symptoms and recruitment of a relatively homogeneous sample of predominantly older, Caucasian veterans. Results of this study demonstrate the three-year stability of DSM-5 PTSD symptom network structure in a nationally representative sample of trauma-exposed U.S. military veterans. They further suggest that trauma-related avoidance, intrusive, and dysphoric symptoms may contribute to the chronicity of PTSD symptoms in this population. Published by Elsevier B.V.

The electronic transfer of information and aerospace knowledge diffusion

NASA Technical Reports Server (NTRS)

Pinelli, Thomas E.; Bishop, Ann P.; Barclay, Rebecca O.; Kennedy, John M.

1992-01-01

Increasing reliance on and investment in information technology and electronic networking systems presupposes that computing and information technology will play a motor role in the diffusion of aerospace knowledge. Little is known, however, about actual information technology needs, uses, and problems within the aerospace knowledge diffusion process. The authors state that the potential contributions of information technology to increased productivity and competitiveness will be diminished unless empirically derived knowledge regarding the information-seeking behavior of the members of the social system - those who are producing, transferring, and using scientific and technical information - is incorporated into a new technology policy framework. Research into the use of information technology and electronic networks by U.S. aerospace engineers and scientists, collected as part of a research project designed to study aerospace knowledge diffusion, is presented in support of this assertion.

National High Frequency Radar Network (hfrnet) and Pacific Research Efforts

NASA Astrophysics Data System (ADS)

Hazard, L.; Terrill, E. J.; Cook, T.; de Paolo, T.; Otero, M. P.; Rogowski, P.; Schramek, T. A.

2016-12-01

The U.S. High Frequency Radar Network (HFRNet) has been in operation for over ten years with representation from 31 organizations spanning academic institutions, state and local government agencies, and private organizations. HFRNet currently holds a collection from over 130 radar installations totaling over 10 million records of surface ocean velocity measurements. HFRNet is a primary example of inter-agency and inter-institutional partnerships for improving oceanographic research and operations. HF radar derived surface currents have been used in several societal applications including coastal search and rescue, oil spill response, water quality monitoring and marine navigation. Central to the operational success of the large scale network is an efficient data management, storage, access, and delivery system. The networking of surface current mapping systems is characterized by a tiered structure that extends from the individual field installations to local regional operations maintaining multiple sites and on to centralized locations aggregating data from all regions. The data system development effort focuses on building robust data communications from remote field locations (sites) for ingestion into the data system via data on-ramps (Portals or Site Aggregators) to centralized data repositories (Nodes). Centralized surface current data enables the aggregation of national surface current grids and allows for ingestion into displays, management tools, and models. The Coastal Observing Research and Development Center has been involved in international relationships and research in the Philippines, Palau, and Vietnam. CORDC extends this IT architecture of surface current mapping data systems leveraging existing developments and furthering standardization of data services for seamless integration of higher level applications. Collaborations include the Philippine Atmospheric Geophysical and Astronomical Services Administration (PAGASA), The Coral Reef Research

Product diffusion through on-demand information-seeking behaviour.

PubMed

Riedl, Christoph; Bjelland, Johannes; Canright, Geoffrey; Iqbal, Asif; Engø-Monsen, Kenth; Qureshi, Taimur; Sundsøy, Pål Roe; Lazer, David

2018-02-01

Most models of product adoption predict S-shaped adoption curves. Here we report results from two country-scale experiments in which we find linear adoption curves. We show evidence that the observed linear pattern is the result of active information-seeking behaviour: individuals actively pulling information from several central sources facilitated by modern Internet searches. Thus, a constant baseline rate of interest sustains product diffusion, resulting in a linear diffusion process instead of the S-shaped curve of adoption predicted by many diffusion models. The main experiment seeded 70 000 (48 000 in Experiment 2) unique voucher codes for the same product with randomly sampled nodes in a social network of approximately 43 million individuals with about 567 million ties. We find that the experiment reached over 800 000 individuals with 80% of adopters adopting the same product-a winner-take-all dynamic consistent with search engine driven rankings that would not have emerged had the products spread only through a network of social contacts. We provide evidence for (and characterization of) this diffusion process driven by active information-seeking behaviour through analyses investigating (a) patterns of geographical spreading; (b) the branching process; and (c) diffusion heterogeneity. Using data on adopters' geolocation we show that social spreading is highly localized, while on-demand diffusion is geographically independent. We also show that cascades started by individuals who actively pull information from central sources are more effective at spreading the product among their peers. © 2018 The Authors.

Product diffusion through on-demand information-seeking behaviour

PubMed Central

Bjelland, Johannes; Canright, Geoffrey; Iqbal, Asif; Qureshi, Taimur; Sundsøy, Pål Roe

2018-01-01

Most models of product adoption predict S-shaped adoption curves. Here we report results from two country-scale experiments in which we find linear adoption curves. We show evidence that the observed linear pattern is the result of active information-seeking behaviour: individuals actively pulling information from several central sources facilitated by modern Internet searches. Thus, a constant baseline rate of interest sustains product diffusion, resulting in a linear diffusion process instead of the S-shaped curve of adoption predicted by many diffusion models. The main experiment seeded 70 000 (48 000 in Experiment 2) unique voucher codes for the same product with randomly sampled nodes in a social network of approximately 43 million individuals with about 567 million ties. We find that the experiment reached over 800 000 individuals with 80% of adopters adopting the same product—a winner-take-all dynamic consistent with search engine driven rankings that would not have emerged had the products spread only through a network of social contacts. We provide evidence for (and characterization of) this diffusion process driven by active information-seeking behaviour through analyses investigating (a) patterns of geographical spreading; (b) the branching process; and (c) diffusion heterogeneity. Using data on adopters' geolocation we show that social spreading is highly localized, while on-demand diffusion is geographically independent. We also show that cascades started by individuals who actively pull information from central sources are more effective at spreading the product among their peers. PMID:29467257

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

NASA Astrophysics Data System (ADS)

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

2016-05-01

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

Precision and bias of selected analytes reported by the National Atmospheric Deposition Program and National Trends Network, 1983; and January 1980 through September 1984

USGS Publications Warehouse

Schroder, L.J.; Bricker, A.W.; Willoughby, T.C.

1985-01-01

Blind-audit samples with known analyte concentrations have been prepared by the U.S. Geological Survey and distributed to the National Atmospheric Deposition Program 's Central Analytical Laboratory. The difference between the National Atmospheric Deposition Program and National Trends Network reported analyte concentrations and known analyte concentrations have been calculated, and the bias has been determined. Calcium, magnesium , sodium, and chloride were biased at the 99-percent confidence limit; potassium and sulfate were unbiased at the 99-percent confidence limit, for 1983 results. Relative-percent differences between the measured and known analyte concentration for calcium , magnesium, sodium, potassium, chloride, and sulfate have been calculated for 1983. The median relative percent difference for calcium was 17.0; magnesium was 6.4; sodium was 10.8; potassium was 6.4; chloride was 17.2; and sulfate was -5.3. These relative percent differences should be used to correct the 1983 data before user-analysis of the data. Variances have been calculated for calcium, magnesium, sodium, potassium, chloride, and sulfate determinations. These variances should be applicable to natural-sample analyte concentrations reported by the National Atmospheric Deposition Program and National Trends Network for calendar year 1983. (USGS)