Spreading paths in partially observed social networks.

PubMed

Onnela, Jukka-Pekka; Christakis, Nicholas A

2012-03-01

Understanding how and how far information, behaviors, or pathogens spread in social networks is an important problem, having implications for both predicting the size of epidemics, as well as for planning effective interventions. There are, however, two main challenges for inferring spreading paths in real-world networks. One is the practical difficulty of observing a dynamic process on a network, and the other is the typical constraint of only partially observing a network. Using static, structurally realistic social networks as platforms for simulations, we juxtapose three distinct paths: (1) the stochastic path taken by a simulated spreading process from source to target; (2) the topologically shortest path in the fully observed network, and hence the single most likely stochastic path, between the two nodes; and (3) the topologically shortest path in a partially observed network. In a sampled network, how closely does the partially observed shortest path (3) emulate the unobserved spreading path (1)? Although partial observation inflates the length of the shortest path, the stochastic nature of the spreading process also frequently derails the dynamic path from the shortest path. We find that the partially observed shortest path does not necessarily give an inflated estimate of the length of the process path; in fact, partial observation may, counterintuitively, make the path seem shorter than it actually is.

Variability in functional brain networks predicts expertise during action observation.

PubMed

Amoruso, Lucía; Ibáñez, Agustín; Fonseca, Bruno; Gadea, Sebastián; Sedeño, Lucas; Sigman, Mariano; García, Adolfo M; Fraiman, Ricardo; Fraiman, Daniel

2017-02-01

Observing an action performed by another individual activates, in the observer, similar circuits as those involved in the actual execution of that action. This activation is modulated by prior experience; indeed, sustained training in a particular motor domain leads to structural and functional changes in critical brain areas. Here, we capitalized on a novel graph-theory approach to electroencephalographic data (Fraiman et al., 2016) to test whether variability in functional brain networks implicated in Tango observation can discriminate between groups differing in their level of expertise. We found that experts and beginners significantly differed in the functional organization of task-relevant networks. Specifically, networks in expert Tango dancers exhibited less variability and a more robust functional architecture. Notably, these expertise-dependent effects were captured within networks derived from electrophysiological brain activity recorded in a very short time window (2s). In brief, variability in the organization of task-related networks seems to be a highly sensitive indicator of long-lasting training effects. This finding opens new methodological and theoretical windows to explore the impact of domain-specific expertise on brain plasticity, while highlighting variability as a fruitful measure in neuroimaging research. Copyright © 2016 Elsevier Inc. All rights reserved.

Towards the creation of a European Network of Earth Observation Networks within GEO. The ConnectinGEO project.

NASA Astrophysics Data System (ADS)

Masó, Joan; Serral, Ivette; Menard, Lionel; Wald, Lucien; Nativi, Stefano; Plag, Hans-Peter; Jules-Plag, Shelley; Nüst, Daniel; Jirka, Simon; Pearlman, Jay; De Maziere, Martine

2015-04-01

ConnectinGEO (Coordinating an Observation Network of Networks EnCompassing saTellite and IN-situ to fill the Gaps in European Observations" is a new H2020 Coordination and Support Action with the primary goal of linking existing Earth Observation networks with science and technology (S&T) communities, the industry sector, the Group on Earth Observations (GEO), and Copernicus. ConnectinGEO aims to facilitate a broader and more accessible knowledge base to support the needs of GEO, its Societal Benefit Areas (SBAs) and the users of the Global Earth Observing System of Systems (GEOSS). A broad range of subjects from climate, natural resources and raw materials, to the emerging UN Sustainable Development Goals (SDGs) will be addressed. The project will generate a prioritized list of critical gaps within available observation data and models to translate observations into practice-relevant knowledge, based on stakeholder consultation and systematic analysis. Ultimately, it will increase coherency of European observation networks, increase the use of Earth observations for assessments and forecasts and inform the planning for future observation systems. ConnectinGEO will initiate a European Network of Earth Observation Networks (ENEON) that will encompass space-based, airborne and in-situ observations networks. ENEON will be composed by project partners representing thematic observation networks along with the GEOSS Science and Technology Stakeholder Network, GEO Communities of Practices, Copernicus services, Sentinel missions and in-situ support data representatives, representatives of the space-based, airborne and in-situ observations European networks (e.g. EPOS, EMSO and GROOM, etc), representatives of the industry sector and European and national funding agencies, in particular those participating in the future ERA-PlaNET. At the beginning, the ENEON will be created and managed by the project. Then the management will be transferred to the network itself to ensure

Understanding crowd-powered search groups: a social network perspective.

PubMed

Zhang, Qingpeng; Wang, Fei-Yue; Zeng, Daniel; Wang, Tao

2012-01-01

Crowd-powered search is a new form of search and problem solving scheme that involves collaboration among a potentially large number of voluntary Web users. Human flesh search (HFS), a particular form of crowd-powered search originated in China, has seen tremendous growth since its inception in 2001. HFS presents a valuable test-bed for scientists to validate existing and new theories in social computing, sociology, behavioral sciences, and so forth. In this research, we construct an aggregated HFS group, consisting of the participants and their relationships in a comprehensive set of identified HFS episodes. We study the topological properties and the evolution of the aggregated network and different sub-groups in the network. We also identify the key HFS participants according to a variety of measures. We found that, as compared with other online social networks, HFS participant network shares the power-law degree distribution and small-world property, but with a looser and more distributed organizational structure, leading to the diversity, decentralization, and independence of HFS participants. In addition, the HFS group has been becoming increasingly decentralized. The comparisons of different HFS sub-groups reveal that HFS participants collaborated more often when they conducted the searches in local platforms or the searches requiring a certain level of professional knowledge background. On the contrary, HFS participants did not collaborate much when they performed the search task in national platforms or the searches with general topics that did not require specific information and learning. We also observed that the key HFS information contributors, carriers, and transmitters came from different groups of HFS participants.

Educational network comparative analysis of small groups: Short- and long-term communications

NASA Astrophysics Data System (ADS)

Berg, D. B.; Zvereva, O. M.; Nazarova, Yu. Yu.; Chepurov, E. G.; Kokovin, A. V.; Ranyuk, S. V.

2017-11-01

The present study is devoted to the discussion of small group communication network structures. These communications were observed in student groups, where actors were united with a regular educational activity. The comparative analysis was carried out for networks of short-term (1 hour) and long-term (4 weeks) communications, it was based on seven structural parameters, and consisted of two stages. At the first stage, differences between the network graphs were examined, and the random corresponding Bernoulli graphs were built. At the second stage, revealed differences were compared. Calculations were performed using UCINET software framework. It was found out that networks of long-term and short-term communications are quite different: the structure of a short-term communication network is close to a random one, whereas the most of long-term communication network parameters differ from the corresponding random ones by more than 30%. This difference can be explained by strong "noisiness" of a short-term communication network, and the lack of social in it.

Estimating individual contribution from group-based structural correlation networks.

PubMed

Saggar, Manish; Hosseini, S M Hadi; Bruno, Jennifer L; Quintin, Eve-Marie; Raman, Mira M; Kesler, Shelli R; Reiss, Allan L

2015-10-15

Coordinated variations in brain morphology (e.g., cortical thickness) across individuals have been widely used to infer large-scale population brain networks. These structural correlation networks (SCNs) have been shown to reflect synchronized maturational changes in connected brain regions. Further, evidence suggests that SCNs, to some extent, reflect both anatomical and functional connectivity and hence provide a complementary measure of brain connectivity in addition to diffusion weighted networks and resting-state functional networks. Although widely used to study between-group differences in network properties, SCNs are inferred only at the group-level using brain morphology data from a set of participants, thereby not providing any knowledge regarding how the observed differences in SCNs are associated with individual behavioral, cognitive and disorder states. In the present study, we introduce two novel distance-based approaches to extract information regarding individual differences from the group-level SCNs. We applied the proposed approaches to a moderately large dataset (n=100) consisting of individuals with fragile X syndrome (FXS; n=50) and age-matched typically developing individuals (TD; n=50). We tested the stability of proposed approaches using permutation analysis. Lastly, to test the efficacy of our method, individual contributions extracted from the group-level SCNs were examined for associations with intelligence scores and genetic data. The extracted individual contributions were stable and were significantly related to both genetic and intelligence estimates, in both typically developing individuals and participants with FXS. We anticipate that the approaches developed in this work could be used as a putative biomarker for altered connectivity in individuals with neurodevelopmental disorders. Copyright © 2015 Elsevier Inc. All rights reserved.

Observability and Controllability of Networks: Symmetry in Representations of Brains and Controllers for Epidemics

NASA Astrophysics Data System (ADS)

Schiff, Steven

Observability and controllability are essential concepts to the design of predictive observer models and feedback controllers of networked systems. We present a numerical and group representational framework, to quantify the observability and controllability of nonlinear networks with explicit symmetries that shows the connection between symmetries and nonlinear measures of observability and controllability. In addition to the topology of brain networks, we have advanced our ability to represent network nodes within the brain using conservation principles and more accurate biophysics that unifies the dynamics of spikes, seizures, and spreading depression. Lastly, we show how symmetries in controller design can be applied to infectious disease epidemics. NIH Grants 1R01EB014641, 1DP1HD086071.

Understanding Online Health Groups for Depression: Social Network and Linguistic Perspectives.

PubMed

Xu, Ronghua; Zhang, Qingpeng

2016-03-10

Mental health problems have become increasingly prevalent in the past decade. With the advance of Web 2.0 technologies, social media present a novel platform for Web users to form online health groups. Members of online health groups discuss health-related issues and mutually help one another by anonymously revealing their mental conditions, sharing personal experiences, exchanging health information, and providing suggestions and support. The conversations in online health groups contain valuable information to facilitate the understanding of their mutual help behaviors and their mental health problems. We aimed to characterize the conversations in a major online health group for major depressive disorder (MDD) patients in a popular Chinese social media platform. In particular, we intended to explain how Web users discuss depression-related issues from the perspective of the social networks and linguistic patterns revealed by the members' conversations. Social network analysis and linguistic analysis were employed to characterize the social structure and linguistic patterns, respectively. Furthermore, we integrated both perspectives to exploit the hidden relations between them. We found an intensive use of self-focus words and negative affect words. In general, group members used a higher proportion of negative affect words than positive affect words. The social network of the MDD group for depression possessed small-world and scale-free properties, with a much higher reciprocity ratio and clustering coefficient value as compared to the networks of other social media platforms and classic network models. We observed a number of interesting relationships, either strong correlations or convergent trends, between the topological properties and linguistic properties of the MDD group members. (1) The MDD group members have the characteristics of self-preoccupation and negative thought content, according to Beck's cognitive theory of depression; (2) the social structure

Suppressing epidemics on networks by exploiting observer nodes.

PubMed

Takaguchi, Taro; Hasegawa, Takehisa; Yoshida, Yuichi

2014-07-01

To control infection spreading on networks, we investigate the effect of observer nodes that recognize infection in a neighboring node and make the rest of the neighbor nodes immune. We numerically show that random placement of observer nodes works better on networks with clustering than on locally treelike networks, implying that our model is promising for realistic social networks. The efficiency of several heuristic schemes for observer placement is also examined for synthetic and empirical networks. In parallel with numerical simulations of epidemic dynamics, we also show that the effect of observer placement can be assessed by the size of the largest connected component of networks remaining after removing observer nodes and links between their neighboring nodes.

Suppressing epidemics on networks by exploiting observer nodes

NASA Astrophysics Data System (ADS)

Takaguchi, Taro; Hasegawa, Takehisa; Yoshida, Yuichi

2014-07-01

To control infection spreading on networks, we investigate the effect of observer nodes that recognize infection in a neighboring node and make the rest of the neighbor nodes immune. We numerically show that random placement of observer nodes works better on networks with clustering than on locally treelike networks, implying that our model is promising for realistic social networks. The efficiency of several heuristic schemes for observer placement is also examined for synthetic and empirical networks. In parallel with numerical simulations of epidemic dynamics, we also show that the effect of observer placement can be assessed by the size of the largest connected component of networks remaining after removing observer nodes and links between their neighboring nodes.

Reputation drives cooperative behaviour and network formation in human groups.

PubMed

Cuesta, Jose A; Gracia-Lázaro, Carlos; Ferrer, Alfredo; Moreno, Yamir; Sánchez, Angel

2015-01-19

Cooperativeness is a defining feature of human nature. Theoreticians have suggested several mechanisms to explain this ubiquitous phenomenon, including reciprocity, reputation, and punishment, but the problem is still unsolved. Here we show, through experiments conducted with groups of people playing an iterated Prisoner's Dilemma on a dynamic network, that it is reputation what really fosters cooperation. While this mechanism has already been observed in unstructured populations, we find that it acts equally when interactions are given by a network that players can reconfigure dynamically. Furthermore, our observations reveal that memory also drives the network formation process, and cooperators assort more, with longer link lifetimes, the longer the past actions record. Our analysis demonstrates, for the first time, that reputation can be very well quantified as a weighted mean of the fractions of past cooperative acts and the last action performed. This finding has potential applications in collaborative systems and e-commerce.

Observability and Estimation of Distributed Space Systems via Local Information-Exchange Networks

NASA Technical Reports Server (NTRS)

Rahmani, Amirreza; Mesbahi, Mehran; Fathpour, Nanaz; Hadaegh, Fred Y.

2008-01-01

In this work, we develop an approach to formation estimation by explicitly characterizing formation's system-theoretic attributes in terms of the underlying inter-spacecraft information-exchange network. In particular, we approach the formation observer/estimator design by relaxing the accessibility to the global state information by a centralized observer/estimator- and in turn- providing an analysis and synthesis framework for formation observers/estimators that rely on local measurements. The noveltyof our approach hinges upon the explicit examination of the underlying distributed spacecraft network in the realm of guidance, navigation, and control algorithmic analysis and design. The overarching goal of our general research program, some of whose results are reported in this paper, is the development of distributed spacecraft estimation algorithms that are scalable, modular, and robust to variations inthe topology and link characteristics of the formation information exchange network. In this work, we consider the observability of a spacecraft formation from a single observation node and utilize the agreement protocol as a mechanism for observing formation states from local measurements. Specifically, we show how the symmetry structure of the network, characterized in terms of its automorphism group, directly relates to the observability of the corresponding multi-agent system The ramification of this notion of observability over networks is then explored in the context of distributed formation estimation.

Distributed Observer Network

NASA Technical Reports Server (NTRS)

2008-01-01

NASA s advanced visual simulations are essential for analyses associated with life cycle planning, design, training, testing, operations, and evaluation. Kennedy Space Center, in particular, uses simulations for ground services and space exploration planning in an effort to reduce risk and costs while improving safety and performance. However, it has been difficult to circulate and share the results of simulation tools among the field centers, and distance and travel expenses have made timely collaboration even harder. In response, NASA joined with Valador Inc. to develop the Distributed Observer Network (DON), a collaborative environment that leverages game technology to bring 3-D simulations to conventional desktop and laptop computers. DON enables teams of engineers working on design and operations to view and collaborate on 3-D representations of data generated by authoritative tools. DON takes models and telemetry from these sources and, using commercial game engine technology, displays the simulation results in a 3-D visual environment. Multiple widely dispersed users, working individually or in groups, can view and analyze simulation results on desktop and laptop computers in real time.

Network Approach to Autistic Traits: Group and Subgroup Analyses of ADOS Item Scores

ERIC Educational Resources Information Center

Anderson, George M.; Montazeri, Farhad; de Bildt, Annelies

2015-01-01

A network conceptualization might contribute to understanding the occurrence and interacting nature of behavioral traits in the autism realm. Networks were constructed based on correlations of item scores of the Autism Diagnostic Observation Schedule for Modules 1, 2 and 3 obtained for a group of 477 Dutch individuals with developmental disorders.…

Reputation drives cooperative behaviour and network formation in human groups

PubMed Central

Cuesta, Jose A.; Gracia-Lázaro, Carlos; Ferrer, Alfredo; Moreno, Yamir; Sánchez, Angel

2015-01-01

Cooperativeness is a defining feature of human nature. Theoreticians have suggested several mechanisms to explain this ubiquitous phenomenon, including reciprocity, reputation, and punishment, but the problem is still unsolved. Here we show, through experiments conducted with groups of people playing an iterated Prisoner's Dilemma on a dynamic network, that it is reputation what really fosters cooperation. While this mechanism has already been observed in unstructured populations, we find that it acts equally when interactions are given by a network that players can reconfigure dynamically. Furthermore, our observations reveal that memory also drives the network formation process, and cooperators assort more, with longer link lifetimes, the longer the past actions record. Our analysis demonstrates, for the first time, that reputation can be very well quantified as a weighted mean of the fractions of past cooperative acts and the last action performed. This finding has potential applications in collaborative systems and e-commerce. PMID:25598347

Understanding Online Health Groups for Depression: Social Network and Linguistic Perspectives

PubMed Central

2016-01-01

Background Mental health problems have become increasingly prevalent in the past decade. With the advance of Web 2.0 technologies, social media present a novel platform for Web users to form online health groups. Members of online health groups discuss health-related issues and mutually help one another by anonymously revealing their mental conditions, sharing personal experiences, exchanging health information, and providing suggestions and support. The conversations in online health groups contain valuable information to facilitate the understanding of their mutual help behaviors and their mental health problems. Objective We aimed to characterize the conversations in a major online health group for major depressive disorder (MDD) patients in a popular Chinese social media platform. In particular, we intended to explain how Web users discuss depression-related issues from the perspective of the social networks and linguistic patterns revealed by the members’ conversations. Methods Social network analysis and linguistic analysis were employed to characterize the social structure and linguistic patterns, respectively. Furthermore, we integrated both perspectives to exploit the hidden relations between them. Results We found an intensive use of self-focus words and negative affect words. In general, group members used a higher proportion of negative affect words than positive affect words. The social network of the MDD group for depression possessed small-world and scale-free properties, with a much higher reciprocity ratio and clustering coefficient value as compared to the networks of other social media platforms and classic network models. We observed a number of interesting relationships, either strong correlations or convergent trends, between the topological properties and linguistic properties of the MDD group members. Conclusions (1) The MDD group members have the characteristics of self-preoccupation and negative thought content, according to Beck�

Group Colocation Behavior in Technological Social Networks

PubMed Central

Brown, Chloë; Lathia, Neal; Mascolo, Cecilia; Noulas, Anastasios; Blondel, Vincent

2014-01-01

We analyze two large datasets from technological networks with location and social data: user location records from an online location-based social networking service, and anonymized telecommunications data from a European cellphone operator, in order to investigate the differences between individual and group behavior with respect to physical location. We discover agreements between the two datasets: firstly, that individuals are more likely to meet with one friend at a place they have not visited before, but tend to meet at familiar locations when with a larger group. We also find that groups of individuals are more likely to meet at places that their other friends have visited, and that the type of a place strongly affects the propensity for groups to meet there. These differences between group and solo mobility has potential technological applications, for example, in venue recommendation in location-based social networks. PMID:25148037

Environmental lovers group: a networking of Ciliwung Depok Community

NASA Astrophysics Data System (ADS)

Mambo Tampi, Daniel; Sumabrata, Jachrizal; Darmajanti, Linda

2018-03-01

The dynamic of urban development needs is social space to bout the rights of urban society. An environmental lovers group was evoked by the environmental and Social Issues cause natural and man-made disruptions. Komunitas Ciliwung Depok (KCD) is located under Grand Depok City’s Bridge to keep an environment such as land conversion and garbage. This study aims to determine the motivation of KCD’s group and to know the social network in Ciliwung riverbank along Depok city. Data were gathered from in-depth interviews, observation and documentation within 4 months. KCD invited the local people to keep and maintain an environment of Ciliwung riverbank. Their strength lies on the actors of KCD founder and involvement of human resources, with the support of public and private sectors facilities. Activities with the local people’s participation through social medias such as Facebook as a media of communication to get volunteers’ aspirations and involvement. The conclusions of this research are KCD’s Network materialized by individual motivation, group awareness and trust between the actors to realizing the common goal.

Computational properties of networks of synchronous groups of spiking neurons.

PubMed

Dayhoff, Judith E

2007-09-01

We demonstrate a model in which synchronously firing ensembles of neurons are networked to produce computational results. Each ensemble is a group of biological integrate-and-fire spiking neurons, with probabilistic interconnections between groups. An analogy is drawn in which each individual processing unit of an artificial neural network corresponds to a neuronal group in a biological model. The activation value of a unit in the artificial neural network corresponds to the fraction of active neurons, synchronously firing, in a biological neuronal group. Weights of the artificial neural network correspond to the product of the interconnection density between groups, the group size of the presynaptic group, and the postsynaptic potential heights in the synchronous group model. All three of these parameters can modulate connection strengths between neuronal groups in the synchronous group models. We give an example of nonlinear classification (XOR) and a function approximation example in which the capability of the artificial neural network can be captured by a neural network model with biological integrate-and-fire neurons configured as a network of synchronously firing ensembles of such neurons. We point out that the general function approximation capability proven for feedforward artificial neural networks appears to be approximated by networks of neuronal groups that fire in synchrony, where the groups comprise integrate-and-fire neurons. We discuss the advantages of this type of model for biological systems, its possible learning mechanisms, and the associated timing relationships.

Robustness and Vulnerability of Networks with Dynamical Dependency Groups.

PubMed

Bai, Ya-Nan; Huang, Ning; Wang, Lei; Wu, Zhi-Xi

2016-11-28

The dependency property and self-recovery of failure nodes both have great effects on the robustness of networks during the cascading process. Existing investigations focused mainly on the failure mechanism of static dependency groups without considering the time-dependency of interdependent nodes and the recovery mechanism in reality. In this study, we present an evolving network model consisting of failure mechanisms and a recovery mechanism to explore network robustness, where the dependency relations among nodes vary over time. Based on generating function techniques, we provide an analytical framework for random networks with arbitrary degree distribution. In particular, we theoretically find that an abrupt percolation transition exists corresponding to the dynamical dependency groups for a wide range of topologies after initial random removal. Moreover, when the abrupt transition point is above the failure threshold of dependency groups, the evolving network with the larger dependency groups is more vulnerable; when below it, the larger dependency groups make the network more robust. Numerical simulations employing the Erdős-Rényi network and Barabási-Albert scale free network are performed to validate our theoretical results.

Perspectives on Social Network Analysis for Observational Scientific Data

NASA Astrophysics Data System (ADS)

Singh, Lisa; Bienenstock, Elisa Jayne; Mann, Janet

This chapter is a conceptual look at data quality issues that arise during scientific observations and their impact on social network analysis. We provide examples of the many types of incompleteness, bias and uncertainty that impact the quality of social network data. Our approach is to leverage the insights and experience of observational behavioral scientists familiar with the challenges of making inference when data are not complete, and suggest avenues for extending these to relational data questions. The focus of our discussion is on network data collection using observational methods because they contain high dimensionality, incomplete data, varying degrees of observational certainty, and potential observer bias. However, the problems and recommendations identified here exist in many other domains, including online social networks, cell phone networks, covert networks, and disease transmission networks.

The case of the religious network group.

PubMed

Friedman, R

1999-01-01

GenCorp, a Connecticut-based paper-goods manufacturer, has long supported employee-organized network groups. Its social support group for African-Americans, in fact, has been a particular success, having provided black employees with opportunities to further enhance their careers and helped the company retain top talent, meet its EEO goals, and gain favorable publicity. So when Alice Lawrence, a top accountant at GenCorp, called general manager Bill Thompson about the Christian network group being organized in one of the company's southern plants, Bill hardly flinched. After all, the Christian group was being organized by Russell Kramer, one of the company's most effective plant managers. What could be the problem there? But a couple of years ago, Alice noted, Russell had sent around a companywide letter that talked about the sinful nature of homosexuality. And that letter has made her and other gay and lesbian employees terribly uneasy. To complicate matters, the issue of "Christian rights" in the workplace was being widely discussed on radio talk shows, and several books on the topic had recently been published. An employee had even called the new region's head of human resources to get clarification on the topic. Up until now, GenCorp hadn't placed a lot of restrictions on network groups. But the emergence of a religious group was raising new questions for GenCorp's managers. Should the company accept religious groups or try to stop them? What policy, if any, should GenCorp adopt toward these network groups? Five experts comment on this fictional case study.

Update on the activities of the GGOS Bureau of Networks and Observations

NASA Technical Reports Server (NTRS)

Pearlman, Michael R.; Pavlis, Erricos C.; Ma, Chopo; Noll, Carey; Thaller, Daniela; Richter, Bernd; Gross, Richard; Neilan, Ruth; Mueller, Juergen; Barzaghi, Ricardo;

Dynamical networks of influence in small group discussions.

PubMed

Moussaïd, Mehdi; Noriega Campero, Alejandro; Almaatouq, Abdullah

2018-01-01

In many domains of life, business and management, numerous problems are addressed by small groups of individuals engaged in face-to-face discussions. While research in social psychology has a long history of studying the determinants of small group performances, the internal dynamics that govern a group discussion are not yet well understood. Here, we rely on computational methods based on network analyses and opinion dynamics to describe how individuals influence each other during a group discussion. We consider the situation in which a small group of three individuals engages in a discussion to solve an estimation task. We propose a model describing how group members gradually influence each other and revise their judgments over the course of the discussion. The main component of the model is an influence network-a weighted, directed graph that determines the extent to which individuals influence each other during the discussion. In simulations, we first study the optimal structure of the influence network that yields the best group performances. Then, we implement a social learning process by which individuals adapt to the past performance of their peers, thereby affecting the structure of the influence network in the long run. We explore the mechanisms underlying the emergence of efficient or maladaptive networks and show that the influence network can converge towards the optimal one, but only when individuals exhibit a social discounting bias by downgrading the relative performances of their peers. Finally, we find a late-speaker effect, whereby individuals who speak later in the discussion are perceived more positively in the long run and are thus more influential. The numerous predictions of the model can serve as a basis for future experiments, and this work opens research on small group discussion to computational social sciences.

Distributed Observer Network

NASA Technical Reports Server (NTRS)

Conroy, Michael; Mazzone, Rebecca; Little, William; Elfrey, Priscilla; Mann, David; Mabie, Kevin; Cuddy, Thomas; Loundermon, Mario; Spiker, Stephen; McArthur, Frank;

AMBON - the Arctic Marine Biodiversity Observing Network

NASA Astrophysics Data System (ADS)

Iken, K.; Danielson, S. L.; Grebmeier, J. M.; Cooper, L. W.; Hopcroft, R. R.; Kuletz, K.; Stafford, K.; Mueter, F. J.; Collins, E.; Bluhm, B.; Moore, S. E.; Bochenek, R. J.

2016-02-01

The goal of the Arctic Marine Biodiversity Observing Network (AMBON) is to build an operational and sustainable marine biodiversity observing network for the US Arctic Chukchi Sea continental shelf. The AMBON has four main goals: 1. To close current gaps in taxonomic biodiversity observations from microbes to whales, 2. To integrate results of past and ongoing research programs on the US Arctic shelf into a biodiversity observation network, 3. To demonstrate at a regional level how an observing network could be developed, and 4. To link with programs on the pan-Arctic to global scale. The AMBON fills taxonomic (from microbes to mammals), functional (food web structure), spatial and temporal (continuing time series) gaps, and includes new technologies such as state-of-the-art genomic tools, with biodiversity and environmental observations linked through central data management through the Alaska Ocean Observing System. AMBON is a 5-year partnership between university and federal researchers, funded through the National Ocean Partnership Program (NOPP), with partners in the National Oceanographic and Atmospheric Administration (NOAA), the Bureau of Ocean and Energy Management (BOEM), and Shell industry. AMBON will allow us to better coordinate, sustain, and synthesize biodiversity research efforts, and make data available to a broad audience of users, stakeholders, and resource managers.

A Novel Group-Fused Sparse Partial Correlation Method for Simultaneous Estimation of Functional Networks in Group Comparison Studies.

PubMed

Liang, Xiaoyun; Vaughan, David N; Connelly, Alan; Calamante, Fernando

2018-05-01

The conventional way to estimate functional networks is primarily based on Pearson correlation along with classic Fisher Z test. In general, networks are usually calculated at the individual-level and subsequently aggregated to obtain group-level networks. However, such estimated networks are inevitably affected by the inherent large inter-subject variability. A joint graphical model with Stability Selection (JGMSS) method was recently shown to effectively reduce inter-subject variability, mainly caused by confounding variations, by simultaneously estimating individual-level networks from a group. However, its benefits might be compromised when two groups are being compared, given that JGMSS is blinded to other groups when it is applied to estimate networks from a given group. We propose a novel method for robustly estimating networks from two groups by using group-fused multiple graphical-lasso combined with stability selection, named GMGLASS. Specifically, by simultaneously estimating similar within-group networks and between-group difference, it is possible to address inter-subject variability of estimated individual networks inherently related with existing methods such as Fisher Z test, and issues related to JGMSS ignoring between-group information in group comparisons. To evaluate the performance of GMGLASS in terms of a few key network metrics, as well as to compare with JGMSS and Fisher Z test, they are applied to both simulated and in vivo data. As a method aiming for group comparison studies, our study involves two groups for each case, i.e., normal control and patient groups; for in vivo data, we focus on a group of patients with right mesial temporal lobe epilepsy.

Latino Civic Group Participation, Social Networks, and Physical Activity.

PubMed

Marquez, Becky; Gonzalez, Patricia; Gallo, Linda; Ji, Ming

2016-07-01

We examined whether social networks and resource awareness for physical activity may mediate the relationship between civic group participation and physical activity. This is a cross-sectional study of a randomly selected sample of 335 Latinos (mean age 42.1 ± 16.4 years) participating in the San Diego Prevention Research Center's 2009 Household Community Survey. Serial multiple mediation analysis tested the hypothesis that civic group participation is associated with meeting physical activity recommendations through an indirect mechanism of larger social networks followed by greater knowledge of physical activity community resources. The indirect effects of level of civic group participation as well as religious, health, neighborhood, or arts group participation on meeting national physical activity recommendations were significant in models testing pathways through social network size and physical activity resource awareness. The direct effect was only significant for health group indicating that participating in a health group predicted physical activity independent of social network size and awareness of physical activity resources. Belonging to civic groups may promote physical activity engagement through social network diffusion of information on community physical activity resources which has implications for health.

An artificial network model for estimating the network structure underlying partially observed neuronal signals.

PubMed

Komatsu, Misako; Namikawa, Jun; Chao, Zenas C; Nagasaka, Yasuo; Fujii, Naotaka; Nakamura, Kiyohiko; Tani, Jun

2014-01-01

Many previous studies have proposed methods for quantifying neuronal interactions. However, these methods evaluated the interactions between recorded signals in an isolated network. In this study, we present a novel approach for estimating interactions between observed neuronal signals by theorizing that those signals are observed from only a part of the network that also includes unobserved structures. We propose a variant of the recurrent network model that consists of both observable and unobservable units. The observable units represent recorded neuronal activity, and the unobservable units are introduced to represent activity from unobserved structures in the network. The network structures are characterized by connective weights, i.e., the interaction intensities between individual units, which are estimated from recorded signals. We applied this model to multi-channel brain signals recorded from monkeys, and obtained robust network structures with physiological relevance. Furthermore, the network exhibited common features that portrayed cortical dynamics as inversely correlated interactions between excitatory and inhibitory populations of neurons, which are consistent with the previous view of cortical local circuits. Our results suggest that the novel concept of incorporating an unobserved structure into network estimations has theoretical advantages and could provide insights into brain dynamics beyond what can be directly observed. Copyright © 2014 Elsevier Ireland Ltd and the Japan Neuroscience Society. All rights reserved.

Dynamical networks of influence in small group discussions

PubMed Central

Noriega Campero, Alejandro; Almaatouq, Abdullah

2018-01-01

In many domains of life, business and management, numerous problems are addressed by small groups of individuals engaged in face-to-face discussions. While research in social psychology has a long history of studying the determinants of small group performances, the internal dynamics that govern a group discussion are not yet well understood. Here, we rely on computational methods based on network analyses and opinion dynamics to describe how individuals influence each other during a group discussion. We consider the situation in which a small group of three individuals engages in a discussion to solve an estimation task. We propose a model describing how group members gradually influence each other and revise their judgments over the course of the discussion. The main component of the model is an influence network—a weighted, directed graph that determines the extent to which individuals influence each other during the discussion. In simulations, we first study the optimal structure of the influence network that yields the best group performances. Then, we implement a social learning process by which individuals adapt to the past performance of their peers, thereby affecting the structure of the influence network in the long run. We explore the mechanisms underlying the emergence of efficient or maladaptive networks and show that the influence network can converge towards the optimal one, but only when individuals exhibit a social discounting bias by downgrading the relative performances of their peers. Finally, we find a late-speaker effect, whereby individuals who speak later in the discussion are perceived more positively in the long run and are thus more influential. The numerous predictions of the model can serve as a basis for future experiments, and this work opens research on small group discussion to computational social sciences. PMID:29338013

Research collaboration in groups and networks: differences across academic fields.

PubMed

Kyvik, Svein; Reymert, Ingvild

2017-01-01

The purpose of this paper is to give a macro-picture of collaboration in research groups and networks across all academic fields in Norwegian research universities, and to examine the relative importance of membership in groups and networks for individual publication output. To our knowledge, this is a new approach, which may provide valuable information on collaborative patterns in a particular national system, but of clear relevance to other national university systems. At the system level, conducting research in groups and networks are equally important, but there are large differences between academic fields. The research group is clearly most important in the field of medicine and health, while undertaking research in an international network is most important in the natural sciences. Membership in a research group and active participation in international networks are likely to enhance publication productivity and the quality of research.

The total carbon column observing network.

PubMed

Wunch, Debra; Toon, Geoffrey C; Blavier, Jean-François L; Washenfelder, Rebecca A; Notholt, Justus; Connor, Brian J; Griffith, David W T; Sherlock, Vanessa; Wennberg, Paul O

2011-05-28

A global network of ground-based Fourier transform spectrometers has been founded to remotely measure column abundances of CO(2), CO, CH(4), N(2)O and other molecules that absorb in the near-infrared. These measurements are directly comparable with the near-infrared total column measurements from space-based instruments. With stringent requirements on the instrumentation, acquisition procedures, data processing and calibration, the Total Carbon Column Observing Network (TCCON) achieves an accuracy and precision in total column measurements that is unprecedented for remote-sensing observations (better than 0.25% for CO(2)). This has enabled carbon-cycle science investigations using the TCCON dataset, and allows the TCCON to provide a link between satellite measurements and the extensive ground-based in situ network. © 2011 The Royal Society

Relative stability of core groups in pollination networks in a biodiversity hotspot over four years.

PubMed

Fang, Qiang; Huang, Shuang-Quan

2012-01-01

Plants and their pollinators form pollination networks integral to the evolution and persistence of species in communities. Previous studies suggest that pollination network structure remains nested while network composition is highly dynamic. However, little is known about temporal variation in the structure and function of plant-pollinator networks, especially in species-rich communities where the strength of pollinator competition is predicted to be high. Here we quantify temporal variation of pollination networks over four consecutive years in an alpine meadow in the Hengduan Mountains biodiversity hotspot in China. We found that ranked positions and idiosyncratic temperatures of both plants and pollinators were more conservative between consecutive years than in non-consecutive years. Although network compositions exhibited high turnover, generalized core groups--decomposed by a k-core algorithm--were much more stable than peripheral groups. Given the high rate of turnover observed, we suggest that identical plants and pollinators that persist for at least two successive years sustain pollination services at the community level. Our data do not support theoretical predictions of a high proportion of specialized links within species-rich communities. Plants were relatively specialized, exhibiting less variability in pollinator composition at pollinator functional group level than at the species level. Both specialized and generalized plants experienced narrow variation in functional pollinator groups. The dynamic nature of pollination networks in the alpine meadow demonstrates the potential for networks to mitigate the effects of fluctuations in species composition in a high biodiversity area.

Observations of Leonids 2009 by the Tajikistan Fireball Network

NASA Technical Reports Server (NTRS)

Borovicka, J.; Borovicka, J.

2011-01-01

The fireball network in Tajikistan has operated since 2009. Five stations of the network covering the territory of near eleven thousands square kilometers are equipped with all-sky cameras with the Zeiss Distagon "fish-eye" objectives and by digital SLR cameras Nikon with the Nikkor "fish-eye" objectives. Observations of the Leonid activity in 2009 were carried out during November 13-21. In this period, 16 Leonid fireballs have been photographed. As a result of astrometric and photometric reductions, the precise data including atmospheric trajectories, velocities, orbits, light curves, photometric masses and densities were determined for 10 fireballs. The radiant positions during the maximum night suggest that the majority of the fireball activity was caused by the annual stream component with only minor contribution from the 1466 trail. According to the PE criterion, the majority of Leonid fireballs belonged to the most fragile and weak fireball group IIIB. However, one detected Leonid belonged to the fireball group I. This is the first detection of an anomalously strong Leonid individual.

The LAAS network observation for studying time correlations in extensive air showers

NASA Astrophysics Data System (ADS)

Ochi, Nobuaki; Iyono, A.; Kimura, Hitoomi; Konishi, Takeharu; Nakamura, Toru; Nakatsuka, Takao; Ohara, Soji; Ohmori, Nobuharu; Saito, Katsuhiko; Takahashi, Nobusuke; Tsuji, Shuhei; Wada, Tomonori; Yamamoto, Isao; Yamashita, Yoshihiko; Yanagimoto, Yukio

2003-02-01

The Large Area Air Shower (LAAS) group has been performing a network observation of extensive air showers (EAS) since 1996 in Japan. Ten compact EAS arrays are operating simultaneously at distant stations (up to ≍1000 km) and detecting EAS with mean energy of ≍1015 eV. Each station has 4--12 scintillation counters and a Global Positioning System (GPS), which provides time stamps of EAS triggers with an accuracy of 1μs. As a consequence of the comparable time stamps, uniformly-adjusted detectors and a standardized data format among all stations, we can treat the independent observations as a gigantic EAS detector system as a whole. The primary purpose of the network observation is to study large-scale correlations in ultra-high-energy cosmic rays. On the other hand, three nearby stations within 1~km distance at Okayama area have a possibility to detect extremely-high-energy EAS (≍1019 eV) as coincident triggers of the three stations. The present status of the network and some results from computer simulations are reported here.

Assessing Group Interaction with Social Language Network Analysis

NASA Astrophysics Data System (ADS)

Scholand, Andrew J.; Tausczik, Yla R.; Pennebaker, James W.

In this paper we discuss a new methodology, social language network analysis (SLNA), that combines tools from social language processing and network analysis to assess socially situated working relationships within a group. Specifically, SLNA aims to identify and characterize the nature of working relationships by processing artifacts generated with computer-mediated communication systems, such as instant message texts or emails. Because social language processing is able to identify psychological, social, and emotional processes that individuals are not able to fully mask, social language network analysis can clarify and highlight complex interdependencies between group members, even when these relationships are latent or unrecognized.

A permutation testing framework to compare groups of brain networks.

PubMed

Simpson, Sean L; Lyday, Robert G; Hayasaka, Satoru; Marsh, Anthony P; Laurienti, Paul J

2013-01-01

Brain network analyses have moved to the forefront of neuroimaging research over the last decade. However, methods for statistically comparing groups of networks have lagged behind. These comparisons have great appeal for researchers interested in gaining further insight into complex brain function and how it changes across different mental states and disease conditions. Current comparison approaches generally either rely on a summary metric or on mass-univariate nodal or edge-based comparisons that ignore the inherent topological properties of the network, yielding little power and failing to make network level comparisons. Gleaning deeper insights into normal and abnormal changes in complex brain function demands methods that take advantage of the wealth of data present in an entire brain network. Here we propose a permutation testing framework that allows comparing groups of networks while incorporating topological features inherent in each individual network. We validate our approach using simulated data with known group differences. We then apply the method to functional brain networks derived from fMRI data.

Observability of Automata Networks: Fixed and Switching Cases.

PubMed

Li, Rui; Hong, Yiguang; Wang, Xingyuan

2018-04-01

Automata networks are a class of fully discrete dynamical systems, which have received considerable interest in various different areas. This brief addresses the observability of automata networks and switched automata networks in a unified framework, and proposes simple necessary and sufficient conditions for observability. The results are achieved by employing methods from symbolic computation, and are suited for implementation using computer algebra systems. Several examples are presented to demonstrate the application of the results.

Multi-phenomenology Observation Network Evaluation Tool'' (MONET)

NASA Astrophysics Data System (ADS)

Oltrogge, D.; North, P.; Vallado, D.

2014-09-01

Evaluating overall performance of an SSA "system-of-systems" observational network collecting against thousands of Resident Space Objects (RSO) is very difficult for typical tasking or scheduling-based analysis tools. This is further complicated by networks that have a wide variety of sensor types and phenomena, to include optical, radar and passive RF types, each having unique resource, ops tempo, competing customer and detectability constraints. We present details of the Multi-phenomenology Observation Network Evaluation Tool (MONET), which circumvents these difficulties by assessing the ideal performance of such a network via a digitized supply-vs-demand approach. Cells of each sensors supply time are distributed among RSO targets of interest to determine the average performance of the network against that set of RSO targets. Orbit Determination heuristics are invoked to represent observation quantity and geometry notionally required to obtain the desired orbit estimation quality. To feed this approach, we derive the detectability and collection rate performance of optical, radar and passive RF sensor physical and performance characteristics. We then prioritize the selected RSO targets according to object size, active/inactive status, orbit regime, and/or other considerations. Finally, the OD-derived tracking demands of each RSO of interest are levied against remaining sensor supply until either (a) all sensor time is exhausted; or (b) the list of RSO targets is exhausted. The outputs from MONET include overall network performance metrics delineated by sensor type, objects and orbits tracked, along with likely orbit accuracies which might result from the conglomerate network tracking.

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.

Establishing the reliability of rhesus macaque social network assessment from video observations

PubMed Central

Feczko, Eric; Mitchell, Thomas A. J.; Walum, Hasse; Brooks, Jenna M.; Heitz, Thomas R.; Young, Larry J.; Parr, Lisa A.

2015-01-01

Understanding the properties of a social environment is important for understanding the dynamics of social relationships. Understanding such dynamics is relevant for multiple fields, ranging from animal behaviour to social and cognitive neuroscience. To quantify social environment properties, recent studies have incorporated social network analysis. Social network analysis quantifies both the global and local properties of a social environment, such as social network efficiency and the roles played by specific individuals, respectively. Despite the plethora of studies incorporating social network analysis, methods to determine the amount of data necessary to derive reliable social networks are still being developed. Determining the amount of data necessary for a reliable network is critical for measuring changes in the social environment, for example following an experimental manipulation, and therefore may be critical for using social network analysis to statistically assess social behaviour. In this paper, we extend methods for measuring error in acquired data and for determining the amount of data necessary to generate reliable social networks. We derived social networks from a group of 10 male rhesus macaques, Macaca mulatta, for three behaviours: spatial proximity, grooming and mounting. Behaviours were coded using a video observation technique, where video cameras recorded the compound where the 10 macaques resided. We collected, coded and used 10 h of video data to construct these networks. Using the methods described here, we found in our data that 1 h of spatial proximity observations produced reliable social networks. However, this may not be true for other studies due to differences in data acquisition. Our results have broad implications for measuring and predicting the amount of error in any social network, regardless of species. PMID:26392632

Code 672 observational science branch computer networks

NASA Technical Reports Server (NTRS)

Hancock, D. W.; Shirk, H. G.

1988-01-01

In general, networking increases productivity due to the speed of transmission, easy access to remote computers, ability to share files, and increased availability of peripherals. Two different networks within the Observational Science Branch are described in detail.

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.

Controllability and observability of Boolean networks arising from biology

NASA Astrophysics Data System (ADS)

Li, Rui; Yang, Meng; Chu, Tianguang

2015-02-01

Boolean networks are currently receiving considerable attention as a computational scheme for system level analysis and modeling of biological systems. Studying control-related problems in Boolean networks may reveal new insights into the intrinsic control in complex biological systems and enable us to develop strategies for manipulating biological systems using exogenous inputs. This paper considers controllability and observability of Boolean biological networks. We propose a new approach, which draws from the rich theory of symbolic computation, to solve the problems. Consequently, simple necessary and sufficient conditions for reachability, controllability, and observability are obtained, and algorithmic tests for controllability and observability which are based on the Gröbner basis method are presented. As practical applications, we apply the proposed approach to several different biological systems, namely, the mammalian cell-cycle network, the T-cell activation network, the large granular lymphocyte survival signaling network, and the Drosophila segment polarity network, gaining novel insights into the control and/or monitoring of the specific biological systems.

Designing a Self-Contained Group Area Network for Ubiquitous Learning

ERIC Educational Resources Information Center

Chen, Nian-Shing; Kinshuk; Wei, Chun-Wang; Yang, Stephen J. H.

2008-01-01

A number of studies have evidenced that handheld devices are appropriate tools to facilitate face-to-face collaborative learning effectively because of the possibility of ample social interactions. Group Area Network, or GroupNet, proposed in this paper, uses handheld devices to fill the gap between Local Area Network and Body Area Network.…

Remote observing with NASA's Deep Space Network

NASA Astrophysics Data System (ADS)

Kuiper, T. B. H.; Majid, W. A.; Martinez, S.; Garcia-Miro, C.; Rizzo, J. R.

2012-09-01

The Deep Space Network (DSN) communicates with spacecraft as far away as the boundary between the Solar System and the interstellar medium. To make this possible, large sensitive antennas at Canberra, Australia, Goldstone, California, and Madrid, Spain, provide for constant communication with interplanetary missions. We describe the procedures for radioastronomical observations using this network. Remote access to science monitor and control computers by authorized observers is provided by two-factor authentication through a gateway at the Jet Propulsion Laboratory (JPL) in Pasadena. To make such observations practical, we have devised schemes based on SSH tunnels and distributed computing. At the very minimum, one can use SSH tunnels and VNC (Virtual Network Computing, a remote desktop software suite) to control the science hosts within the DSN Flight Operations network. In this way we have controlled up to three telescopes simultaneously. However, X-window updates can be slow and there are issues involving incompatible screen sizes and multi-screen displays. Consequently, we are now developing SSH tunnel-based schemes in which instrument control and monitoring, and intense data processing, are done on-site by the remote DSN hosts while data manipulation and graphical display are done at the observer's host. We describe our approaches to various challenges, our experience with what worked well and lessons learned, and directions for future development.

Small diameter symmetric networks from linear groups

NASA Technical Reports Server (NTRS)

Campbell, Lowell; Carlsson, Gunnar E.; Dinneen, Michael J.; Faber, Vance; Fellows, Michael R.; Langston, Michael A.; Moore, James W.; Multihaupt, Andrew P.; Sexton, Harlan B.

1992-01-01

In this note is reported a collection of constructions of symmetric networks that provide the largest known values for the number of nodes that can be placed in a network of a given degree and diameter. Some of the constructions are in the range of current potential engineering significance. The constructions are Cayley graphs of linear groups obtained by experimental computation.

Functional brain networks reconstruction using group sparsity-regularized learning.

PubMed

Zhao, Qinghua; Li, Will X Y; Jiang, Xi; Lv, Jinglei; Lu, Jianfeng; Liu, Tianming

2018-06-01

Investigating functional brain networks and patterns using sparse representation of fMRI data has received significant interests in the neuroimaging community. It has been reported that sparse representation is effective in reconstructing concurrent and interactive functional brain networks. To date, most of data-driven network reconstruction approaches rarely take consideration of anatomical structures, which are the substrate of brain function. Furthermore, it has been rarely explored whether structured sparse representation with anatomical guidance could facilitate functional networks reconstruction. To address this problem, in this paper, we propose to reconstruct brain networks utilizing the structure guided group sparse regression (S2GSR) in which 116 anatomical regions from the AAL template, as prior knowledge, are employed to guide the network reconstruction when performing sparse representation of whole-brain fMRI data. Specifically, we extract fMRI signals from standard space aligned with the AAL template. Then by learning a global over-complete dictionary, with the learned dictionary as a set of features (regressors), the group structured regression employs anatomical structures as group information to regress whole brain signals. Finally, the decomposition coefficients matrix is mapped back to the brain volume to represent functional brain networks and patterns. We use the publicly available Human Connectome Project (HCP) Q1 dataset as the test bed, and the experimental results indicate that the proposed anatomically guided structure sparse representation is effective in reconstructing concurrent functional brain networks.

The Global Oscillation Network Group site survey. 1: Data collection and analysis methods

NASA Technical Reports Server (NTRS)

Hill, Frank; Fischer, George; Grier, Jennifer; Leibacher, John W.; Jones, Harrison B.; Jones, Patricia P.; Kupke, Renate; Stebbins, Robin T.

1994-01-01

The Global Oscillation Network Group (GONG) Project is planning to place a set of instruments around the world to observe solar oscillations as continuously as possible for at least three years. The Project has now chosen the sites that will comprise the network. This paper describes the methods of data collection and analysis that were used to make this decision. Solar irradiance data were collected with a one-minute cadence at fifteen sites around the world and analyzed to produce statistics of cloud cover, atmospheric extinction, and transparency power spectra at the individual sites. Nearly 200 reasonable six-site networks were assembled from the individual stations, and a set of statistical measures of the performance of the networks was analyzed using a principal component analysis. An accompanying paper presents the results of the survey.

Characterizing User Groups in Online Social Networks

NASA Astrophysics Data System (ADS)

Gyarmati, László; Trinh, Tuan Anh

The users’ role is crucial in the development, deployment and the success of online social networks (OSNs). Despite this fact, little is known and even less has been published about user activities in the operating OSNs. In this paper, we present a large scale measurement analysis of user behaviour, in terms of time spent online, in some popular OSNs, namely Bebo, Flixster, MySpace, and Skyrock, and characterise user groups in OSNs. We used more than 200 PlanetLab [1] nodes for our measurement, monitored more than 3000 users for three weeks by downloading repeatedly their profile pages; more than 100 million pages were processed in total. The main findings of the paper are the following. Firstly, we create a measurement framework in order to observe user activity. Secondly, we present cumulative usage statistics of the different OSNs. Thirdly, we classify the monitored users into different groups and characterise the common properties of the members. Finally, we illustrate the wide applicability of our datasets by predicting the sign out method of the OSN users.

Multi-Objective Design Of Optimal Greenhouse Gas Observation Networks

NASA Astrophysics Data System (ADS)

Lucas, D. D.; Bergmann, D. J.; Cameron-Smith, P. J.; Gard, E.; Guilderson, T. P.; Rotman, D.; Stolaroff, J. K.

2010-12-01

One of the primary scientific functions of a Greenhouse Gas Information System (GHGIS) is to infer GHG source emission rates and their uncertainties by combining measurements from an observational network with atmospheric transport modeling. Certain features of the observational networks that serve as inputs to a GHGIS --for example, sampling location and frequency-- can greatly impact the accuracy of the retrieved GHG emissions. Observation System Simulation Experiments (OSSEs) provide a framework to characterize emission uncertainties associated with a given network configuration. By minimizing these uncertainties, OSSEs can be used to determine optimal sampling strategies. Designing a real-world GHGIS observing network, however, will involve multiple, conflicting objectives; there will be trade-offs between sampling density, coverage and measurement costs. To address these issues, we have added multi-objective optimization capabilities to OSSEs. We demonstrate these capabilities by quantifying the trade-offs between retrieval error and measurement costs for a prototype GHGIS, and deriving GHG observing networks that are Pareto optimal. [LLNL-ABS-452333: This work performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344.

Complex network construction based on user group attention sequence

NASA Astrophysics Data System (ADS)

Zhang, Gaowei; Xu, Lingyu; Wang, Lei

2018-04-01

In the traditional complex network construction, it is often to use the similarity between nodes, build the weight of the network, and finally build the network. However, this approach tends to focus only on the coupling between nodes, while ignoring the information transfer between nodes and the transfer of directionality. In the network public opinion space, based on the set of stock series that the network groups pay attention to within a certain period of time, we vectorize the different stocks and build a complex network.

Trust and compactness in social network groups.

PubMed

De Meo, Pasquale; Ferrara, Emilio; Rosaci, Domenico; Sarné, Giuseppe M L

2015-02-01

Understanding the dynamics behind group formation and evolution in social networks is considered an instrumental milestone to better describe how individuals gather and form communities, how they enjoy and share the platform contents, how they are driven by their preferences/tastes, and how their behaviors are influenced by peers. In this context, the notion of compactness of a social group is particularly relevant. While the literature usually refers to compactness as a measure to merely determine how much members of a group are similar among each other, we argue that the mutual trustworthiness between the members should be considered as an important factor in defining such a term. In fact, trust has profound effects on the dynamics of group formation and their evolution: individuals are more likely to join with and stay in a group if they can trust other group members. In this paper, we propose a quantitative measure of group compactness that takes into account both the similarity and the trustworthiness among users, and we present an algorithm to optimize such a measure. We provide empirical results, obtained from the real social networks EPINIONS and CIAO, that compare our notion of compactness versus the traditional notion of user similarity, clearly proving the advantages of our approach.

Leadership in Groups: Social Networks and Perceptions of Formal and Informal Leaders

DTIC Science & Technology

2006-03-01

LEADERSHIP IN GROUPS: SOCIAL NETWORKS AND PERCEPTIONS OF FORMAL AND INFORMAL LEADERS THESIS...01 LEADERSHIP IN GROUPS: SOCIAL NETWORKS AND PERCEPTIONS OF FORMAL AND INFORMAL LEADERS THESIS Presented to the Faculty...DISTRIBUTION UNLIMITED. AFIT/GSS/ENV/06M-01 LEADERSHIP IN GROUPS: SOCIAL NETWORKS AND PERCEPTIONS OF FORMAL AND INFORMAL LEADERS

Recent Progress of Seismic Observation Networks in Japan

NASA Astrophysics Data System (ADS)

Okada, Y.

2013-04-01

Before the occurrence of disastrous Kobe earthquake in 1995, the number of high sensitivity seismograph stations operated in Japan was nearly 550 and was concentrated in the Kanto and Tokai districts, central Japan. In the wake of the Kobe earthquake, Japanese government has newly established the Headquarters for Earthquake Research Promotion and started the reconstruction of seismic networks to evenly cover the whole Japan. The basic network is composed of three seismographs, i.e. high sensitivity seismograph (Hi-net), broadband seismograph (F-net), and strong motion seismograph (K-NET). A large majority of Hi-net stations are also equipped with a pair of strong motion sensors at the bottom of borehole and the ground surface (KiK-net). A plenty of high quality data obtained from these networks are circulated at once and is producing several new seismological findings as well as providing the basis for the Earthquake Early Warning system. In March 11, 2011, "Off the Pacific coast of Tohoku Earthquake" was generated with magnitude 9.0, which records the largest in the history of seismic observation in Japan. The greatest disaster on record was brought by huge tsunami with nearly 20 thousand killed or missing people. We are again noticed that seismic observation system is quite poor in the oceanic region compared to the richness of it in the inland region. In 2012, NIED has started the construction of ocean bottom seismic and tsunami observation network along the Japan Trench. It is planned to layout 154 stations with an average spacing of 30km, each of which is equipped with an accelerometer for seismic observation and a water pressure gauge for tsunami observation. We are expecting that more rapid and accurate warning of earthquake and tsunami becomes possible by this observing network.

Reconstruction of Complex Directional Networks with Group Lasso Nonlinear Conditional Granger Causality.

PubMed

Yang, Guanxue; Wang, Lin; Wang, Xiaofan

2017-06-07

Reconstruction of networks underlying complex systems is one of the most crucial problems in many areas of engineering and science. In this paper, rather than identifying parameters of complex systems governed by pre-defined models or taking some polynomial and rational functions as a prior information for subsequent model selection, we put forward a general framework for nonlinear causal network reconstruction from time-series with limited observations. With obtaining multi-source datasets based on the data-fusion strategy, we propose a novel method to handle nonlinearity and directionality of complex networked systems, namely group lasso nonlinear conditional granger causality. Specially, our method can exploit different sets of radial basis functions to approximate the nonlinear interactions between each pair of nodes and integrate sparsity into grouped variables selection. The performance characteristic of our approach is firstly assessed with two types of simulated datasets from nonlinear vector autoregressive model and nonlinear dynamic models, and then verified based on the benchmark datasets from DREAM3 Challenge4. Effects of data size and noise intensity are also discussed. All of the results demonstrate that the proposed method performs better in terms of higher area under precision-recall curve.

The Global Geodetic Observing System: Space Geodesy Networks for the Future

NASA Technical Reports Server (NTRS)

Pearlman, Michael; Pavlis, Erricos; Ma, Chopo; Altamini, Zuheir; Noll, Carey; Stowers, David

2011-01-01

Ground-based networks of co-located space geodetic techniques (VLBI, SLR, GNSS. and DORIS) are the basis for the development and maintenance of the International Terrestrial Reference frame (ITRF), which is our metric of reference for measurements of global change, The Global Geodetic Observing System (GGOS) of the International Association of Geodesy (IAG) has established a task to develop a strategy to design, integrate and maintain the fundamental geodetic network and supporting infrastructure in a sustainable way to satisfy the long-term requirements for the reference frame. The GGOS goal is an origin definition at 1 mm or better and a temporal stability on the order of 0.1 mm/y, with similar numbers for the scale and orientation components. These goals are based on scientific requirements to address sea level rise with confidence, but other applications are not far behind. Recent studies including one by the US National Research Council has strongly stated the need and the urgency for the fundamental space geodesy network. Simulations are underway to examining accuracies for origin, scale and orientation of the resulting ITRF based on various network designs and system performance to determine the optimal global network to achieve this goal. To date these simulations indicate that 24 - 32 co-located stations are adequate to define the reference frame and a more dense GNSS and DORIS network will be required to distribute the reference frame to users anywhere on Earth. Stations in the new global network will require geologically stable sites with good weather, established infrastructure, and local support and personnel. GGOS wil seek groups that are interested in participation. GGOS intends to issues a Call for Participation of groups that would like to contribute in the network implementation and operation. Some examples of integrated stations currently in operation or under development will be presented. We will examine necessary conditions and challenges in

Ukrainian network of Optical Stations for man-made space objects observation

NASA Astrophysics Data System (ADS)

Sybiryakova, Yevgeniya

2016-07-01

The Ukrainian Network of Optical Stations (UNOS) for man-made objects research was founded in 2012 as an association of professional astronomers. The main goals of network are: positional and photometric observations of man-made space objects, calculation of orbital elements, research of shape and period of rotation. The network consists of 8 stations: Kiev, Nikolaev, Odesa, Uzhgorod, Lviv, Yevpatoriya, Alchevsk. UNOS has 12 telescopes for observation of man-made space objects. The new original methods of positional observation were developed for optical observation of geosynchronous and low earth orbit satellites. The observational campaigns of LEO satellites held in the network every year. The numerical model of space object motion, developed in UNOS, is using for orbit calculation. The results of orbital elements calculation are represented on the UNOS web-site http://umos.mao.kiev.ua/eng/. The photometric observation of selected objects is also carried out in network.

Human parietofrontal networks related to action observation detected at rest.

PubMed

Molinari, Elisa; Baraldi, Patrizia; Campanella, Martina; Duzzi, Davide; Nocetti, Luca; Pagnoni, Giuseppe; Porro, Carlo A

2013-01-01

Recent data show a broad correspondence between human resting-state and task-related brain networks. We performed a functional magnetic resonance imaging (fMRI) study to compare, in the same subjects, the spatial independent component analysis (ICA) maps obtained at rest and during the observation of either reaching/grasping hand actions or matching static pictures. Two parietofrontal networks were identified by ICA from action observation task data. One network, specific to reaching/grasping observation, included portions of the anterior intraparietal cortex and of the dorsal and ventral lateral premotor cortices. A second network included more posterior portions of the parietal lobe, the dorsomedial frontal cortex, and more anterior and ventral parts, respectively, of the dorsal and ventral premotor cortices, extending toward Broca's area; this network was more generally related to the observation of hand action and static pictures. A good spatial correspondence was found between the 2 observation-related ICA maps and 2 ICA maps identified from resting-state data. The anatomical connectivity among the identified clusters was tested in the same volunteers, using persistent angular structure-MRI and deterministic tractography. These findings extend available knowledge of human parietofrontal circuits and further support the hypothesis of a persistent coherence within functionally relevant networks during rest.

Global investigation of composition and interaction networks in gut microbiomes of individuals belonging to diverse geographies and age-groups.

PubMed

Yadav, Deepak; Ghosh, Tarini Shankar; Mande, Sharmila S

2016-01-01

Factors like ethnicity, diet and age of an individual have been hypothesized to play a role in determining the makeup of gut microbiome. In order to investigate the gut microbiome structure as well as the inter-microbial associations present therein, we have performed a comprehensive global comparative profiling of the structure (composition, relative heterogeneity and diversity) and the inter-microbial networks in the gut microbiomes of 399 individuals of eight different nationalities. The study identified certain geography-specific trends with respect to composition, intra-group heterogeneity and diversity of the gut microbiomes. Interestingly, the gut microbial association/mutual-exlusion networks were observed to exhibit several cross-geography trends. It was seen that though the composition of gut microbiomes of the American and European individuals were similar, there were distinct patterns in their microbial interaction networks. Amongst European gut-microbiomes, the co-occurrence network obtained for the Danish population was observed to be most dense. Distinct patterns were also observed within Chinese, Japanese and Indian datasets. While performing an age-wise comparison, it was observed that the microbial interactions increased with the age of individuals. Furthermore, certain bacterial groups were identified to be present only in the older age groups. The trends observed in gut microbial networks could be due to the inherent differences in the diet of individuals belonging to different nationalities. For example, the higher number of microbial associations in the Danish population as compared to the Spanish population, may be attributed to the evenly distributed diet of the later. This is in line with previously reported findings which indicate an increase in functional interdependency of microbes in individuals with higher nutritional status. To summarise, the present study identifies geography and age specific patterns in the composition as well as

Empirical Studies on the Network of Social Groups: The Case of Tencent QQ.

PubMed

You, Zhi-Qiang; Han, Xiao-Pu; Lü, Linyuan; Yeung, Chi Ho

2015-01-01

Participation in social groups are important but the collective behaviors of human as a group are difficult to analyze due to the difficulties to quantify ordinary social relation, group membership, and to collect a comprehensive dataset. Such difficulties can be circumvented by analyzing online social networks. In this paper, we analyze a comprehensive dataset released from Tencent QQ, an instant messenger with the highest market share in China. Specifically, we analyze three derivative networks involving groups and their members-the hypergraph of groups, the network of groups and the user network-to reveal social interactions at microscopic and mesoscopic level. Our results uncover interesting behaviors on the growth of user groups, the interactions between groups, and their relationship with member age and gender. These findings lead to insights which are difficult to obtain in social networks based on personal contacts.

The wireless networking system of Earthquake precursor mobile field observation

NASA Astrophysics Data System (ADS)

Wang, C.; Teng, Y.; Wang, X.; Fan, X.; Wang, X.

2012-12-01

The mobile field observation network could be real-time, reliably record and transmit large amounts of data, strengthen the physical signal observations in specific regions and specific period, it can improve the monitoring capacity and abnormal tracking capability. According to the features of scatter everywhere, a large number of current earthquake precursor observation measuring points, networking technology is based on wireless broadband accessing McWILL system, the communication system of earthquake precursor mobile field observation would real-time, reliably transmit large amounts of data to the monitoring center from measuring points through the connection about equipment and wireless accessing system, broadband wireless access system and precursor mobile observation management center system, thereby implementing remote instrument monitoring and data transmition. At present, the earthquake precursor field mobile observation network technology has been applied to fluxgate magnetometer array geomagnetic observations of Tianzhu, Xichang,and Xinjiang, it can be real-time monitoring the working status of the observational instruments of large area laid after the last two or three years, large scale field operation. Therefore, it can get geomagnetic field data of the local refinement regions and provide high-quality observational data for impending earthquake tracking forecast. Although, wireless networking technology is very suitable for mobile field observation with the features of simple, flexible networking etc, it also has the phenomenon of packet loss etc when transmitting a large number of observational data due to the wireless relatively weak signal and narrow bandwidth. In view of high sampling rate instruments, this project uses data compression and effectively solves the problem of data transmission packet loss; Control commands, status data and observational data transmission use different priorities and means, which control the packet loss rate within

New patterns in human biogeography revealed by networks of contacts between linguistic groups.

PubMed

Capitán, José A; Bock Axelsen, Jacob; Manrubia, Susanna

2015-03-07

Human languages differ broadly in abundance and are distributed highly unevenly on the Earth. In many qualitative and quantitative aspects, they strongly resemble biodiversity distributions. An intriguing and previously unexplored issue is the architecture of the neighbouring relationships between human linguistic groups. Here we construct and characterize these networks of contacts and show that they represent a new kind of spatial network with uncommon structural properties. Remarkably, language networks share a meaningful property with food webs: both are quasi-interval graphs. In food webs, intervality is linked to the existence of a niche space of low dimensionality; in language networks, we show that the unique relevant variable is the area occupied by the speakers of a language. By means of a range model analogous to niche models in ecology, we show that a geometric restriction of perimeter covering by neighbouring linguistic domains explains the structural patterns observed. Our findings may be of interest in the development of models for language dynamics or regarding the propagation of cultural innovations. In relation to species distribution, they pose the question of whether the spatial features of species ranges share architecture, and eventually generating mechanism, with the distribution of human linguistic groups. © 2015 The Author(s) Published by the Royal Society. All rights reserved.

A Network Model of Observation and Imitation of Speech

PubMed Central

Mashal, Nira; Solodkin, Ana; Dick, Anthony Steven; Chen, E. Elinor; Small, Steven L.

2012-01-01

Much evidence has now accumulated demonstrating and quantifying the extent of shared regional brain activation for observation and execution of speech. However, the nature of the actual networks that implement these functions, i.e., both the brain regions and the connections among them, and the similarities and differences across these networks has not been elucidated. The current study aims to characterize formally a network for observation and imitation of syllables in the healthy adult brain and to compare their structure and effective connectivity. Eleven healthy participants observed or imitated audiovisual syllables spoken by a human actor. We constructed four structural equation models to characterize the networks for observation and imitation in each of the two hemispheres. Our results show that the network models for observation and imitation comprise the same essential structure but differ in important ways from each other (in both hemispheres) based on connectivity. In particular, our results show that the connections from posterior superior temporal gyrus and sulcus to ventral premotor, ventral premotor to dorsal premotor, and dorsal premotor to primary motor cortex in the left hemisphere are stronger during imitation than during observation. The first two connections are implicated in a putative dorsal stream of speech perception, thought to involve translating auditory speech signals into motor representations. Thus, the current results suggest that flow of information during imitation, starting at the posterior superior temporal cortex and ending in the motor cortex, enhances input to the motor cortex in the service of speech execution. PMID:22470360

Observability of Boolean multiplex control networks

NASA Astrophysics Data System (ADS)

Wu, Yuhu; Xu, Jingxue; Sun, Xi-Ming; Wang, Wei

2017-04-01

Boolean multiplex (multilevel) networks (BMNs) are currently receiving considerable attention as theoretical arguments for modeling of biological systems and system level analysis. Studying control-related problems in BMNs may not only provide new views into the intrinsic control in complex biological systems, but also enable us to develop a method for manipulating biological systems using exogenous inputs. In this article, the observability of the Boolean multiplex control networks (BMCNs) are studied. First, the dynamical model and structure of BMCNs with control inputs and outputs are constructed. By using of Semi-Tensor Product (STP) approach, the logical dynamics of BMCNs is converted into an equivalent algebraic representation. Then, the observability of the BMCNs with two different kinds of control inputs is investigated by giving necessary and sufficient conditions. Finally, examples are given to illustrate the efficiency of the obtained theoretical results.

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

PubMed

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

2015-01-01

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

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

PubMed Central

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

2015-01-01

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

Comparing multilayer brain networks between groups: Introducing graph metrics and recommendations.

PubMed

Mandke, Kanad; Meier, Jil; Brookes, Matthew J; O'Dea, Reuben D; Van Mieghem, Piet; Stam, Cornelis J; Hillebrand, Arjan; Tewarie, Prejaas

2018-02-01

There is an increasing awareness of the advantages of multi-modal neuroimaging. Networks obtained from different modalities are usually treated in isolation, which is however contradictory to accumulating evidence that these networks show non-trivial interdependencies. Even networks obtained from a single modality, such as frequency-band specific functional networks measured from magnetoencephalography (MEG) are often treated independently. Here, we discuss how a multilayer network framework allows for integration of multiple networks into a single network description and how graph metrics can be applied to quantify multilayer network organisation for group comparison. We analyse how well-known biases for single layer networks, such as effects of group differences in link density and/or average connectivity, influence multilayer networks, and we compare four schemes that aim to correct for such biases: the minimum spanning tree (MST), effective graph resistance cost minimisation, efficiency cost optimisation (ECO) and a normalisation scheme based on singular value decomposition (SVD). These schemes can be applied to the layers independently or to the multilayer network as a whole. For correction applied to whole multilayer networks, only the SVD showed sufficient bias correction. For correction applied to individual layers, three schemes (ECO, MST, SVD) could correct for biases. By using generative models as well as empirical MEG and functional magnetic resonance imaging (fMRI) data, we further demonstrated that all schemes were sensitive to identify network topology when the original networks were perturbed. In conclusion, uncorrected multilayer network analysis leads to biases. These biases may differ between centres and studies and could consequently lead to unreproducible results in a similar manner as for single layer networks. We therefore recommend using correction schemes prior to multilayer network analysis for group comparisons. Copyright © 2017 Elsevier

Social learning strategies modify the effect of network structure on group performance.

PubMed

Barkoczi, Daniel; Galesic, Mirta

2016-10-07

The structure of communication networks is an important determinant of the capacity of teams, organizations and societies to solve policy, business and science problems. Yet, previous studies reached contradictory results about the relationship between network structure and performance, finding support for the superiority of both well-connected efficient and poorly connected inefficient network structures. Here we argue that understanding how communication networks affect group performance requires taking into consideration the social learning strategies of individual team members. We show that efficient networks outperform inefficient networks when individuals rely on conformity by copying the most frequent solution among their contacts. However, inefficient networks are superior when individuals follow the best member by copying the group member with the highest payoff. In addition, groups relying on conformity based on a small sample of others excel at complex tasks, while groups following the best member achieve greatest performance for simple tasks. Our findings reconcile contradictory results in the literature and have broad implications for the study of social learning across disciplines.

Social learning strategies modify the effect of network structure on group performance

NASA Astrophysics Data System (ADS)

Barkoczi, Daniel; Galesic, Mirta

2016-10-01

The structure of communication networks is an important determinant of the capacity of teams, organizations and societies to solve policy, business and science problems. Yet, previous studies reached contradictory results about the relationship between network structure and performance, finding support for the superiority of both well-connected efficient and poorly connected inefficient network structures. Here we argue that understanding how communication networks affect group performance requires taking into consideration the social learning strategies of individual team members. We show that efficient networks outperform inefficient networks when individuals rely on conformity by copying the most frequent solution among their contacts. However, inefficient networks are superior when individuals follow the best member by copying the group member with the highest payoff. In addition, groups relying on conformity based on a small sample of others excel at complex tasks, while groups following the best member achieve greatest performance for simple tasks. Our findings reconcile contradictory results in the literature and have broad implications for the study of social learning across disciplines.

Studying the evolutionary relationships and phylogenetic trees of 21 groups of tRNA sequences based on complex networks.

PubMed

Wei, Fangping; Chen, Bowen

2012-03-01

To find out the evolutionary relationships among different tRNA sequences of 21 amino acids, 22 networks are constructed. One is constructed from whole tRNAs, and the other 21 networks are constructed from the tRNAs which carry the same amino acids. A new method is proposed such that the alignment scores of any two amino acids groups are determined by the average degree and the average clustering coefficient of their networks. The anticodon feature of isolated tRNA and the phylogenetic trees of 21 group networks are discussed. We find that some isolated tRNA sequences in 21 networks still connect with other tRNAs outside their group, which reflects the fact that those tRNAs might evolve by intercrossing among these 21 groups. We also find that most anticodons among the same cluster are only one base different in the same sites when S ≥ 70, and they stay in the same rank in the ladder of evolutionary relationships. Those observations seem to agree on that some tRNAs might mutate from the same ancestor sequences based on point mutation mechanisms.

Representativeness of four precipitation observational networks of China

NASA Astrophysics Data System (ADS)

Ren, Yuyu; Ren, Guoyu

2012-08-01

Four precipitation observational networks with varied station densities are maintained in China. They are: the Global Climate Observation System (GCOS) Surface Network (GSN), the national Reference Climate Network (RCN), the national Basic Meteorological Network (BMN), and the national Ordinary Meteorological Network (OMN). The GSN, RCN, BMN, and the merged network of RCN and BMN (R&B) have been widely used in climatology and climate change studies. In this paper, the impact of the usage of different networks on the precipitation climatology of China is evaluated by using the merged dataset of All Station Network (ASN) as a benchmark. The results show that all networks can capture the main features of the country average precipitation and its changing trends. The differences of average annual precipitation of the various networks from that of the ASN are less than 50 mm (⩽ 10%). All networks can successfully detect the rising trend of the average annual precipitation during 1961-2009, with the R&B exhibiting the best representativeness (only 2.90% relative difference) and the GSN the poorest (39.77%). As to the change trends of country average monthly precipitation, the networks can be ranked in descending order as R&B (1.27%), RCN (2.35%), BMN (4.17%), and GSN (7.46%), and larger relative differences appear from August to November. The networks produce quite consistent spatial patterns of annual precipitation change trends, and all show an increasing trend of precipitation in Northwest and Southeast China, and a decreasing trend in North China, Northeast China, and parts of central China. However, the representativeness of the BMN and R&B are better in annual and seasonal precipitation trends, in spite of the fact that they are still far from satisfactory. The relative differences of trends in some months and regions even reach more than 50%. The results also show that the representativeness of the RCN for country average precipitation is higher than that of the

Let's Face(book) It: Analyzing Interactions in Social Network Groups for Chemistry Learning

NASA Astrophysics Data System (ADS)

Rap, Shelley; Blonder, Ron

2016-02-01

We examined how social network (SN) groups contribute to the learning of chemistry. The main goal was to determine whether chemistry learning could occur in the group discourse. The emphasis was on groups of students in the 11th and 12th grades who learn chemistry in preparation for their final external examination. A total of 1118 discourse events were tallied in the different groups. We analyzed the different events that were found in chemistry learning Facebook groups (CLFGs). The analysis revealed that seven types of interactions were observed in the CLFGs: The most common interaction (47 %) dealt with organizing learning (e.g., announcements regarding homework, the location of the next class); learning interactions were observed in 22 % of the posts, and links to learning materials and social interactions constituted about 20 % each. The learning events that were ascertained underwent a deeper examination and three different types of chemistry learning interactions were identified. This examination was based on the theoretical framework of the commognitive approach to learning (Sfard in Thinking as communicating. Cambridge University Press, Cambridge, 2008), which will be explained. The identified learning interactions that were observed in the Facebook groups illustrate the potential of SNs to serve as an additional tool for teachers to advance their students' learning of chemistry.

Leadership of healthcare commissioning networks in England: a mixed-methods study on clinical commissioning groups

PubMed Central

Zachariadis, Markos; Oborn, Eivor; Barrett, Michael; Zollinger-Read, Paul

2013-01-01

Objective To explore the relational challenges for general practitioner (GP) leaders setting up new network-centric commissioning organisations in the recent health policy reform in England, we use innovation network theory to identify key network leadership practices that facilitate healthcare innovation. Design Mixed-method, multisite and case study research. Setting Six clinical commissioning groups and local clusters in the East of England area, covering in total 208 GPs and 1 662 000 population. Methods Semistructured interviews with 56 lead GPs, practice managers and staff from the local health authorities (primary care trusts, PCT) as well as various healthcare professionals; 21 observations of clinical commissioning group (CCG) board and executive meetings; electronic survey of 58 CCG board members (these included GPs, practice managers, PCT employees, nurses and patient representatives) and subsequent social network analysis. Main outcome measures Collaborative relationships between CCG board members and stakeholders from their healthcare network; clarifying the role of GPs as network leaders; strengths and areas for development of CCGs. Results Drawing upon innovation network theory provides unique insights of the CCG leaders’ activities in establishing best practices and introducing new clinical pathways. In this context we identified three network leadership roles: managing knowledge flows, managing network coherence and managing network stability. Knowledge sharing and effective collaboration among GPs enable network stability and the alignment of CCG objectives with those of the wider health system (network coherence). Even though activities varied between commissioning groups, collaborative initiatives were common. However, there was significant variation among CCGs around the level of engagement with providers, patients and local authorities. Locality (sub) groups played an important role because they linked commissioning decisions with

Experimental determination of group flux control coefficients in metabolic networks

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

Simpson, T.W.; Shimizu, Hiroshi; Stephanopoulos, G.

1998-04-20

Grouping of reactions around key metabolite branch points can facilitate the study of metabolic control of complex metabolic networks. This top-down Metabolic Control Analysis is exemplified through the introduction of group control coefficients whose magnitudes provide a measure of the relative impact of each reaction group on the overall network flux, as well as on the overall network stability, following enzymatic amplification. In this article, the authors demonstrate the application of previously developed theory to the determination of group flux control coefficients. Experimental data for the changes in metabolic fluxes obtained in response to the introduction of six different environmentalmore » perturbations are used to determine the group flux control coefficients for three reaction groups formed around the phosphoenolpyruvate/pyruvate branch point. The consistency of the obtained group flux control coefficient estimates is systematically analyzed to ensure that all necessary conditions are satisfied. The magnitudes of the determined control coefficients suggest that the control of lysine production flux in Corynebacterium glutamicum cells at a growth base state resides within the lysine biosynthetic pathway that begins with the PEP/PYR carboxylation anaplorotic pathway.« less

Prototyping and Simulation of Robot Group Intelligence using Kohonen Networks.

PubMed

Wang, Zhijun; Mirdamadi, Reza; Wang, Qing

2016-01-01

Intelligent agents such as robots can form ad hoc networks and replace human being in many dangerous scenarios such as a complicated disaster relief site. This project prototypes and builds a computer simulator to simulate robot kinetics, unsupervised learning using Kohonen networks, as well as group intelligence when an ad hoc network is formed. Each robot is modeled using an object with a simple set of attributes and methods that define its internal states and possible actions it may take under certain circumstances. As the result, simple, reliable, and affordable robots can be deployed to form the network. The simulator simulates a group of robots as an unsupervised learning unit and tests the learning results under scenarios with different complexities. The simulation results show that a group of robots could demonstrate highly collaborative behavior on a complex terrain. This study could potentially provide a software simulation platform for testing individual and group capability of robots before the design process and manufacturing of robots. Therefore, results of the project have the potential to reduce the cost and improve the efficiency of robot design and building.

Prototyping and Simulation of Robot Group Intelligence using Kohonen Networks

PubMed Central

Wang, Zhijun; Mirdamadi, Reza; Wang, Qing

2016-01-01

Intelligent agents such as robots can form ad hoc networks and replace human being in many dangerous scenarios such as a complicated disaster relief site. This project prototypes and builds a computer simulator to simulate robot kinetics, unsupervised learning using Kohonen networks, as well as group intelligence when an ad hoc network is formed. Each robot is modeled using an object with a simple set of attributes and methods that define its internal states and possible actions it may take under certain circumstances. As the result, simple, reliable, and affordable robots can be deployed to form the network. The simulator simulates a group of robots as an unsupervised learning unit and tests the learning results under scenarios with different complexities. The simulation results show that a group of robots could demonstrate highly collaborative behavior on a complex terrain. This study could potentially provide a software simulation platform for testing individual and group capability of robots before the design process and manufacturing of robots. Therefore, results of the project have the potential to reduce the cost and improve the efficiency of robot design and building. PMID:28540284

Stochastic Geometric Network Models for Groups of Functional and Structural Connectomes

PubMed Central

Friedman, Eric J.; Landsberg, Adam S.; Owen, Julia P.; Li, Yi-Ou; Mukherjee, Pratik

2014-01-01

Structural and functional connectomes are emerging as important instruments in the study of normal brain function and in the development of new biomarkers for a variety of brain disorders. In contrast to single-network studies that presently dominate the (non-connectome) network literature, connectome analyses typically examine groups of empirical networks and then compare these against standard (stochastic) network models. Current practice in connectome studies is to employ stochastic network models derived from social science and engineering contexts as the basis for the comparison. However, these are not necessarily best suited for the analysis of connectomes, which often contain groups of very closely related networks, such as occurs with a set of controls or a set of patients with a specific disorder. This paper studies important extensions of standard stochastic models that make them better adapted for analysis of connectomes, and develops new statistical fitting methodologies that account for inter-subject variations. The extensions explicitly incorporate geometric information about a network based on distances and inter/intra hemispherical asymmetries (to supplement ordinary degree-distribution information), and utilize a stochastic choice of networks' density levels (for fixed threshold networks) to better capture the variance in average connectivity among subjects. The new statistical tools introduced here allow one to compare groups of networks by matching both their average characteristics and the variations among them. A notable finding is that connectomes have high “smallworldness” beyond that arising from geometric and degree considerations alone. PMID:25067815

Characteristics of group networks in the KOSPI and the KOSDAQ

NASA Astrophysics Data System (ADS)

Kim, Kyungsik; Ko, Jeung-Su; Yi, Myunggi

2012-02-01

We investigate the main feature of group networks in the KOSPI and KOSDAQ of Korean financial markets and analyze daily cross-correlations between price fluctuations for the 5-year time period from 2006 to 2010. We discuss the stabilities by undressing the market-wide effect using the Markowitz multi-factor model and the network-based approach. In particular we ascertain the explicit list of significant firms in the few largest eigenvectors from the undressed correlation matrix. Finally, we show the structure of group correlation by applying a network-based approach. In addition, the relation between market capitalizations and businesses is examined.

Analysis of Spatial Autocorrelation for Optimal Observation Network in Korea

NASA Astrophysics Data System (ADS)

Park, S.; Lee, S.; Lee, E.; Park, S. K.

2016-12-01

Many studies for improving prediction of high-impact weather have been implemented, such as THORPEX (The Observing System Research and Predictability Experiment), FASTEX (Fronts and Atlantic Storm-Track Experiment), NORPEX (North Pacific Experiment), WSR/NOAA (Winter Storm Reconnaissance), and DOTSTAR (Dropwindsonde Observations for Typhoon Surveillance near the TAiwan Region). One of most important objectives in these studies is to find effects of observation on forecast, and to establish optimal observation network. However, there are lack of such studies on Korea, although Korean peninsula exhibits a highly complex terrain so it is difficult to predict its weather phenomena. Through building the future optimal observation network, it is necessary to increase utilization of numerical weather prediction and improve monitoring·tracking·prediction skills of high-impact weather in Korea. Therefore, we will perform preliminary study to understand the spatial scale for an expansion of observation system through Spatial Autocorrelation (SAC) analysis. In additions, we will develop a testbed system to design an optimal observation network. Analysis is conducted with Automatic Weather System (AWS) rainfall data, global upper air grid observation (i.e., temperature, pressure, humidity), Himawari satellite data (i.e., water vapor) during 2013-2015 of Korea. This study will provide a guideline to construct observation network for not only improving weather prediction skill but also cost-effectiveness.

Pattern classification and recognition of invertebrate functional groups using self-organizing neural networks.

PubMed

Zhang, WenJun

2007-07-01

Self-organizing neural networks can be used to mimic non-linear systems. The main objective of this study is to make pattern classification and recognition on sampling information using two self-organizing neural network models. Invertebrate functional groups sampled in the irrigated rice field were classified and recognized using one-dimensional self-organizing map and self-organizing competitive learning neural networks. Comparisons between neural network models, distance (similarity) measures, and number of neurons were conducted. The results showed that self-organizing map and self-organizing competitive learning neural network models were effective in pattern classification and recognition of sampling information. Overall the performance of one-dimensional self-organizing map neural network was better than self-organizing competitive learning neural network. The number of neurons could determine the number of classes in the classification. Different neural network models with various distance (similarity) measures yielded similar classifications. Some differences, dependent upon the specific network structure, would be found. The pattern of an unrecognized functional group was recognized with the self-organizing neural network. A relative consistent classification indicated that the following invertebrate functional groups, terrestrial blood sucker; terrestrial flyer; tourist (nonpredatory species with no known functional role other than as prey in ecosystem); gall former; collector (gather, deposit feeder); predator and parasitoid; leaf miner; idiobiont (acarine ectoparasitoid), were classified into the same group, and the following invertebrate functional groups, external plant feeder; terrestrial crawler, walker, jumper or hunter; neustonic (water surface) swimmer (semi-aquatic), were classified into another group. It was concluded that reliable conclusions could be drawn from comparisons of different neural network models that use different distance

Linking metabolic network features to phenotypes using sparse group lasso.

PubMed

Samal, Satya Swarup; Radulescu, Ovidiu; Weber, Andreas; Fröhlich, Holger

2017-11-01

Integration of metabolic networks with '-omics' data has been a subject of recent research in order to better understand the behaviour of such networks with respect to differences between biological and clinical phenotypes. Under the conditions of steady state of the reaction network and the non-negativity of fluxes, metabolic networks can be algebraically decomposed into a set of sub-pathways often referred to as extreme currents (ECs). Our objective is to find the statistical association of such sub-pathways with given clinical outcomes, resulting in a particular instance of a self-contained gene set analysis method. In this direction, we propose a method based on sparse group lasso (SGL) to identify phenotype associated ECs based on gene expression data. SGL selects a sparse set of feature groups and also introduces sparsity within each group. Features in our model are clusters of ECs, and feature groups are defined based on correlations among these features. We apply our method to metabolic networks from KEGG database and study the association of network features to prostate cancer (where the outcome is tumor and normal, respectively) as well as glioblastoma multiforme (where the outcome is survival time). In addition, simulations show the superior performance of our method compared to global test, which is an existing self-contained gene set analysis method. R code (compatible with version 3.2.5) is available from http://www.abi.bit.uni-bonn.de/index.php?id=17. samal@combine.rwth-aachen.de or frohlich@bit.uni-bonn.de. Supplementary data are available at Bioinformatics online. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

Detection of social group instability among captive rhesus macaques using joint network modeling

PubMed Central

Beisner, Brianne A.; Jin, Jian; Fushing, Hsieh; Mccowan, Brenda

2015-01-01

Social stability in group-living animals is an emergent property which arises from the interaction amongst multiple behavioral networks. However, pinpointing when a social group is at risk of collapse is difficult. We used a joint network modeling approach to examine the interdependencies between two behavioral networks, aggression and status signaling, from four stable and three unstable groups of rhesus macaques in order to identify characteristic patterns of network interdependence in stable groups that are readily distinguishable from unstable groups. Our results showed that the most prominent source of aggression-status network interdependence in stable social groups came from more frequent dyads than expected with opposite direction status-aggression (i.e. A threatens B and B signals acceptance of subordinate status). In contrast, unstable groups showed a decrease in opposite direction aggression-status dyads (but remained higher than expected) as well as more frequent than expected dyads with bidirectional aggression. These results demonstrate that not only was the stable joint relationship between aggression and status networks readily distinguishable from unstable time points, social instability manifested in at least two different ways. In sum, our joint modeling approach may prove useful in quantifying and monitoring the complex social dynamics of any wild or captive social system, as all social systems are composed of multiple interconnected networks PMID:26052339

Empirical Studies on the Network of Social Groups: The Case of Tencent QQ

PubMed Central

You, Zhi-Qiang; Han, Xiao-Pu; Lü, Linyuan; Yeung, Chi Ho

2015-01-01

Background Participation in social groups are important but the collective behaviors of human as a group are difficult to analyze due to the difficulties to quantify ordinary social relation, group membership, and to collect a comprehensive dataset. Such difficulties can be circumvented by analyzing online social networks. Methodology/Principal Findings In this paper, we analyze a comprehensive dataset released from Tencent QQ, an instant messenger with the highest market share in China. Specifically, we analyze three derivative networks involving groups and their members—the hypergraph of groups, the network of groups and the user network—to reveal social interactions at microscopic and mesoscopic level. Conclusions/Significance Our results uncover interesting behaviors on the growth of user groups, the interactions between groups, and their relationship with member age and gender. These findings lead to insights which are difficult to obtain in social networks based on personal contacts. PMID:26176850

Evolution of Opinions on Social Networks in the Presence of Competing Committed Groups

PubMed Central

Xie, Jierui; Emenheiser, Jeffrey; Kirby, Matthew; Sreenivasan, Sameet; Szymanski, Boleslaw K.; Korniss, Gyorgy

2012-01-01

Public opinion is often affected by the presence of committed groups of individuals dedicated to competing points of view. Using a model of pairwise social influence, we study how the presence of such groups within social networks affects the outcome and the speed of evolution of the overall opinion on the network. Earlier work indicated that a single committed group within a dense social network can cause the entire network to quickly adopt the group's opinion (in times scaling logarithmically with the network size), so long as the committed group constitutes more than about of the population (with the findings being qualitatively similar for sparse networks as well). Here we study the more general case of opinion evolution when two groups committed to distinct, competing opinions and , and constituting fractions and of the total population respectively, are present in the network. We show for stylized social networks (including Erdös-Rényi random graphs and Barabási-Albert scale-free networks) that the phase diagram of this system in parameter space consists of two regions, one where two stable steady-states coexist, and the remaining where only a single stable steady-state exists. These two regions are separated by two fold-bifurcation (spinodal) lines which meet tangentially and terminate at a cusp (critical point). We provide further insights to the phase diagram and to the nature of the underlying phase transitions by investigating the model on infinite (mean-field limit), finite complete graphs and finite sparse networks. For the latter case, we also derive the scaling exponent associated with the exponential growth of switching times as a function of the distance from the critical point. PMID:22448238

Observability and Estimation of Distributed Space Systems via Local Information-Exchange Networks

NASA Technical Reports Server (NTRS)

Fathpour, Nanaz; Hadaegh, Fred Y.; Mesbahi, Mehran; Rahmani, Amirreza

2011-01-01

Spacecraft formation flying involves the coordination of states among multiple spacecraft through relative sensing, inter-spacecraft communication, and control. Most existing formation-flying estimation algorithms can only be supported via highly centralized, all-to-all, static relative sensing. New algorithms are proposed that are scalable, modular, and robust to variations in the topology and link characteristics of the formation exchange network. These distributed algorithms rely on a local information exchange network, relaxing the assumptions on existing algorithms. Distributed space systems rely on a signal transmission network among multiple spacecraft for their operation. Control and coordination among multiple spacecraft in a formation is facilitated via a network of relative sensing and interspacecraft communications. Guidance, navigation, and control rely on the sensing network. This network becomes more complex the more spacecraft are added, or as mission requirements become more complex. The observability of a formation state was observed by a set of local observations from a particular node in the formation. Formation observability can be parameterized in terms of the matrices appearing in the formation dynamics and observation matrices. An agreement protocol was used as a mechanism for observing formation states from local measurements. An agreement protocol is essentially an unforced dynamic system whose trajectory is governed by the interconnection geometry and initial condition of each node, with a goal of reaching a common value of interest. The observability of the interconnected system depends on the geometry of the network, as well as the position of the observer relative to the topology. For the first time, critical GN&C (guidance, navigation, and control estimation) subsystems are synthesized by bringing the contribution of the spacecraft information-exchange network to the forefront of algorithmic analysis and design. The result is a

Community detection in networks with unequal groups.

PubMed

Zhang, Pan; Moore, Cristopher; Newman, M E J

2016-01-01

Recently, a phase transition has been discovered in the network community detection problem below which no algorithm can tell which nodes belong to which communities with success any better than a random guess. This result has, however, so far been limited to the case where the communities have the same size or the same average degree. Here we consider the case where the sizes or average degrees differ. This asymmetry allows us to assign nodes to communities with better-than-random success by examining their local neighborhoods. Using the cavity method, we show that this removes the detectability transition completely for networks with four groups or fewer, while for more than four groups the transition persists up to a critical amount of asymmetry but not beyond. The critical point in the latter case coincides with the point at which local information percolates, causing a global transition from a less-accurate solution to a more-accurate one.

The primary case is not enough: Variation among individuals, groups and social networks modify bacterial transmission dynamics.

PubMed

Keiser, Carl N; Pinter-Wollman, Noa; Ziemba, Michael J; Kothamasu, Krishna S; Pruitt, Jonathan N

2018-03-01

The traits of the primary case of an infectious disease outbreak, and the circumstances for their aetiology, potentially influence the trajectory of transmission dynamics. However, these dynamics likely also depend on the traits of the individuals with whom the primary case interacts. We used the social spider Stegodyphus dumicola to test how the traits of the primary case, group phenotypic composition and group size interact to facilitate the transmission of a GFP-labelled cuticular bacterium. We also compared bacterial transmission across experimentally generated "daisy-chain" vs. "star" networks of social interactions. Finally, we compared social network structure across groups of different sizes. Groups of 10 spiders experienced more bacterial transmission events compared to groups of 30 spiders, regardless of groups' behavioural composition. Groups containing only one bold spider experienced the lowest levels of bacterial transmission regardless of group size. We found no evidence for the traits of the primary case influencing any transmission dynamics. In a second experiment, bacteria were transmitted to more individuals in experimentally induced star networks than in daisy-chains, on which transmission never exceeded three steps. In both experimental network types, transmission success depended jointly on the behavioural traits of the interacting individuals; however, the behavioural traits of the primary case were only important for transmission on star networks. Larger social groups exhibited lower interaction density (i.e. had a low ratio of observed to possible connections) and were more modular, i.e. they had more connections between nodes within a subgroup and fewer connections across subgroups. Thus, larger groups may restrict transmission by forming fewer interactions and by isolating subgroups that interacted with the primary case. These findings suggest that accounting for the traits of single exposed hosts has less power in predicting transmission

Social structure of a semi-free ranging group of mandrills (Mandrillus sphinx): a social network analysis.

PubMed

Bret, Céline; Sueur, Cédric; Ngoubangoye, Barthélémy; Verrier, Delphine; Deneubourg, Jean-Louis; Petit, Odile

2013-01-01

The difficulty involved in following mandrills in the wild means that very little is known about social structure in this species. Most studies initially considered mandrill groups to be an aggregation of one-male/multifemale units, with males occupying central positions in a structure similar to those observed in the majority of baboon species. However, a recent study hypothesized that mandrills form stable groups with only two or three permanent males, and that females occupy more central positions than males within these groups. We used social network analysis methods to examine how a semi-free ranging group of 19 mandrills is structured. We recorded all dyads of individuals that were in contact as a measure of association. The betweenness and the eigenvector centrality for each individual were calculated and correlated to kinship, age and dominance. Finally, we performed a resilience analysis by simulating the removal of individuals displaying the highest betweenness and eigenvector centrality values. We found that related dyads were more frequently associated than unrelated dyads. Moreover, our results showed that the cumulative distribution of individual betweenness and eigenvector centrality followed a power function, which is characteristic of scale-free networks. This property showed that some group members, mostly females, occupied a highly central position. Finally, the resilience analysis showed that the removal of the two most central females split the network into small subgroups and increased the network diameter. Critically, this study confirms that females appear to occupy more central positions than males in mandrill groups. Consequently, these females appear to be crucial for group cohesion and probably play a pivotal role in this species.

Social Structure of a Semi-Free Ranging Group of Mandrills (Mandrillus sphinx): A Social Network Analysis

PubMed Central

Bret, Céline; Sueur, Cédric; Ngoubangoye, Barthélémy; Verrier, Delphine; Deneubourg, Jean-Louis; Petit, Odile

2013-01-01

The difficulty involved in following mandrills in the wild means that very little is known about social structure in this species. Most studies initially considered mandrill groups to be an aggregation of one-male/multifemale units, with males occupying central positions in a structure similar to those observed in the majority of baboon species. However, a recent study hypothesized that mandrills form stable groups with only two or three permanent males, and that females occupy more central positions than males within these groups. We used social network analysis methods to examine how a semi-free ranging group of 19 mandrills is structured. We recorded all dyads of individuals that were in contact as a measure of association. The betweenness and the eigenvector centrality for each individual were calculated and correlated to kinship, age and dominance. Finally, we performed a resilience analysis by simulating the removal of individuals displaying the highest betweenness and eigenvector centrality values. We found that related dyads were more frequently associated than unrelated dyads. Moreover, our results showed that the cumulative distribution of individual betweenness and eigenvector centrality followed a power function, which is characteristic of scale-free networks. This property showed that some group members, mostly females, occupied a highly central position. Finally, the resilience analysis showed that the removal of the two most central females split the network into small subgroups and increased the network diameter. Critically, this study confirms that females appear to occupy more central positions than males in mandrill groups. Consequently, these females appear to be crucial for group cohesion and probably play a pivotal role in this species. PMID:24340074

The Emergence of Embedded Relations and Group Formation in Networks of Competition

ERIC Educational Resources Information Center

Thye, Shane R.; Lawler, Edward J.; Yoon, Jeongkoo

2011-01-01

This study examines how and when small networks of self-interested agents generate a group tie or affiliation at the network level. A group affiliation is formed when actors (a) perceive themselves as members of a group and (b) share resources with each other despite an underlying competitive structure. We apply a concept of structural cohesion to…

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

PubMed Central

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

2017-01-01

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

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

PubMed

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

2017-01-01

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

Evolution of opinions on social networks in the presence of competing committed groups.

PubMed

Xie, Jierui; Emenheiser, Jeffrey; Kirby, Matthew; Sreenivasan, Sameet; Szymanski, Boleslaw K; Korniss, Gyorgy

2012-01-01

Public opinion is often affected by the presence of committed groups of individuals dedicated to competing points of view. Using a model of pairwise social influence, we study how the presence of such groups within social networks affects the outcome and the speed of evolution of the overall opinion on the network. Earlier work indicated that a single committed group within a dense social network can cause the entire network to quickly adopt the group's opinion (in times scaling logarithmically with the network size), so long as the committed group constitutes more than about 10% of the population (with the findings being qualitatively similar for sparse networks as well). Here we study the more general case of opinion evolution when two groups committed to distinct, competing opinions A and B, and constituting fractions pA and pB of the total population respectively, are present in the network. We show for stylized social networks (including Erdös-Rényi random graphs and Barabási-Albert scale-free networks) that the phase diagram of this system in parameter space (pA,pB) consists of two regions, one where two stable steady-states coexist, and the remaining where only a single stable steady-state exists. These two regions are separated by two fold-bifurcation (spinodal) lines which meet tangentially and terminate at a cusp (critical point). We provide further insights to the phase diagram and to the nature of the underlying phase transitions by investigating the model on infinite (mean-field limit), finite complete graphs and finite sparse networks. For the latter case, we also derive the scaling exponent associated with the exponential growth of switching times as a function of the distance from the critical point.

Constructing Social Networks from Unstructured Group Dialog in Virtual Worlds

NASA Astrophysics Data System (ADS)

Shah, Fahad; Sukthankar, Gita

Virtual worlds and massively multi-player online games are rich sources of information about large-scale teams and groups, offering the tantalizing possibility of harvesting data about group formation, social networks, and network evolution. However these environments lack many of the cues that facilitate natural language processing in other conversational settings and different types of social media. Public chat data often features players who speak simultaneously, use jargon and emoticons, and only erratically adhere to conversational norms. In this paper, we present techniques for inferring the existence of social links from unstructured conversational data collected from groups of participants in the Second Life virtual world. We present an algorithm for addressing this problem, Shallow Semantic Temporal Overlap (SSTO), that combines temporal and language information to create directional links between participants, and a second approach that relies on temporal overlap alone to create undirected links between participants. Relying on temporal overlap is noisy, resulting in a low precision and networks with many extraneous links. In this paper, we demonstrate that we can ameliorate this problem by using network modularity optimization to perform community detection in the noisy networks and severing cross-community links. Although using the content of the communications still results in the best performance, community detection is effective as a noise reduction technique for eliminating the extra links created by temporal overlap alone.

Iowa observation well network; past, present, and future

USGS Publications Warehouse

Logel, John D.

1980-01-01

All present and past USGS observation wells for the State of Iowa since 1935 are listed and located on maps. It is recommended that improvement of the observation-well network by the addition of wells in specific areas should be undertaken as soon as possible.

Context-based user grouping for multi-casting in heterogeneous radio networks

NASA Astrophysics Data System (ADS)

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

2011-08-01

Along with the rise of sophisticated smartphones and smart spaces, the availability of both static and dynamic context information has steadily been increasing in recent years. Due to the popularity of social networks, these data are complemented by profile information about individual users. Making use of this information by classifying users in wireless networks enables targeted content and advertisement delivery as well as optimizing network resources, in particular bandwidth utilization, by facilitating group-based multi-casting. In this paper, we present the design and implementation of a web service for advanced user classification based on user, network, and environmental context information. The service employs simple and advanced clustering algorithms for forming classes of users. Available service functionalities include group formation, context-aware adaptation, and deletion as well as the exposure of group characteristics. Moreover, the results of a performance evaluation, where the service has been integrated in a simulator modeling user behavior in heterogeneous wireless systems, are presented.

National Marine Sanctuaries as Sentinel Sites for a Demonstration Marine Biodiversity Observation Network (MBON)

NASA Astrophysics Data System (ADS)

Muller-Karger, F. E.; Chavez, F.; Gittings, S.; Doney, S. C.; Kavanaugh, M.; Montes, E.; Breitbart, M.; Kirkpatrick, B. A.; Anderson, D. M.; Tartt, M.

2016-02-01

The U.S. Federal government (NOAA and NASA), academic researchers, and private partners are implementing a Demonstration Marine Biodiversity Observation Network (MBON) to monitor changes in marine biodiversity within two US National Marine Sanctuaries (NMS): Florida Keys and Monterey Bay. The overarching goal is to observe and understand life, from microbes to whales, in different coastal and continental shelf habitats. The specific objectives are to 1) Establish a protocol for MBON information to dynamically update Sanctuary status and trends reports; 2) Define an efficient set of observations required for implementing a useful MBON; 3) Develop technology for biodiversity assessments including emerging environmental DNA (eDNA) and remote sensing to coordinate with classical sampling; 4) Integrate and synthesize information in coordination with other MBON projects, the Smithsonian Institution's Tennenbaum Marine Observatories Network (TMON), the Integrated Ocean Observing System (IOOS), the international Group on Earth Observations Biodiversity Observation Network(GEO BON), and the UNESCO-IOC Ocean Biogeographic Information System (OBIS); and 5) Understand the linkages between marine biodiversity, ecosystem processes, and the social-economic context of a region. Pilot projects have been implemented within the Florida Keys and Monterey Bay NMS. Limited observations will be collected at the Flower Garden Banks NMS. These encompass a range of marine environments, including deep sea, continental shelves, and coastal habitats including estuaries, wetlands, and coral reefs. The program will use novel eDNA techniques and ongoing observations to evaluate diversity. Multidisciplinary remote sensing will be used to evaluate dynamic 'seascapes'. The MBON will facilitate and enable regional biodiversity assessments, and contributes to addressing U.N. Sustainable Development Goal 14 to conserve and sustainably use marine resources.

Networking observers and observatories with remote telescope markup language

NASA Astrophysics Data System (ADS)

Hessman, Frederic V.; Tuparev, Georg; Allan, Alasdair

2006-06-01

Remote Telescope Markup Language (RTML) is an XML-based protocol for the transport of the high-level description of a set of observations to be carried out on a remote, robotic or service telescope. We describe how RTML is being used in a wide variety of contexts: the transport of service and robotic observing requests in the Hands-On Universe TM, ACP, eSTAR, and MONET networks; how RTML is easily combined with other XML protocols for more localized control of telescopes; RTML as a secondary observation report format for the IVOA's VOEvent protocol; the input format for a general-purpose observation simulator; and the observatory-independent means for carrying out request transactions for the international Heterogeneous Telescope Network (HTN).

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.

Detailed temporal structure of communication networks in groups of songbirds.

PubMed

Stowell, Dan; Gill, Lisa; Clayton, David

2016-06-01

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

Controllability and observability analysis for vertex domination centrality in directed networks

NASA Astrophysics Data System (ADS)

Wang, Bingbo; Gao, Lin; Gao, Yong; Deng, Yue; Wang, Yu

2014-06-01

Topological centrality is a significant measure for characterising the relative importance of a node in a complex network. For directed networks that model dynamic processes, however, it is of more practical importance to quantify a vertex's ability to dominate (control or observe) the state of other vertices. In this paper, based on the determination of controllable and observable subspaces under the global minimum-cost condition, we introduce a novel direction-specific index, domination centrality, to assess the intervention capabilities of vertices in a directed network. Statistical studies demonstrate that the domination centrality is, to a great extent, encoded by the underlying network's degree distribution and that most network positions through which one can intervene in a system are vertices with high domination centrality rather than network hubs. To analyse the interaction and functional dependence between vertices when they are used to dominate a network, we define the domination similarity and detect significant functional modules in glossary and metabolic networks through clustering analysis. The experimental results provide strong evidence that our indices are effective and practical in accurately depicting the structure of directed networks.

The GGOS Bureau of Networks and Observations: an update on the Space Geodesy Network and the New Implementation Plan for 2017 -18

NASA Astrophysics Data System (ADS)

Pearlman, Michael R.; Ma, Chopo; Neilan, Ruth; Noll, Carey; Pavlis, Erricos; Saunier, Jérôme; Schoene, Tilo; Barzaghi, Riccardo; Thaller, Daniela; Bergstrand, Sten; Mueller, Juergen

2017-04-01

standardization in procedures, outreach and to encourage new survey groups to participate, and improve procedures to determine systems reference points. The 2017-2018 Implementation Plan for the GGOS Bureau of Networks and Observations has been posted on the GGOS website. We will outline progress over the past two years and discuss the status of the network and updated plan.

The imperatives of narrative: health interest groups and morality in network news.

PubMed

Braun, Joshua A

2007-08-01

This article examines some of the story conventions of network television news to explain the ways in which healthcare interest groups develop and maintain their presence in this medium - a process that has significant implications for public understanding of healthcare issues, and therefore to bioethics. The article is divided into three sections. The first section focuses on three major normative conventions of television news: adherence to a simple narrative structure, the balance ethic, and avoidance of the "think-piece" and outlines the basic strategies available to interest groups for exploiting these normative conventions. Section two introduces three case studies of organizations and individuals who have run high-profile media campaigns. Section three explores the implications for bioethics of the observations made in this article.

Observations of Student Behavior in Collaborative Learning Groups

NASA Astrophysics Data System (ADS)

Adams, Jeffrey P.; Brissenden, Gina; Lindell, Rebecca S.; Slater, Timothy F.; Wallace, Joy

In an effort to determine how our students were responding to the use of collaborative learning groups in our large enrollment introductory astronomy (ASTRO 101) courses, we systematically observed the behavior of 270 undergraduate students working in 48 self-formed groups. Their observed behaviors were classified as: (i) actively engaged; (ii) watching actively; (iii) watching passively; and (iv) disengaged. We found that male behavior is consistent regardless of the sex-composition of the groups. However, females were categorized as watching passively and or disengaged significantly more frequently when working in groups that contained uneven numbers of males and females. This case study observation suggests that faculty who use collaborative learning groups might find that the level of student participation in collaborative group learning activities can depend on the sex-composition of the group.

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.

Group Centric Networking: Addressing Information Sharing Requirements at the Tactical Edge

DTIC Science & Technology

2016-04-10

gateways are typically used to translate information from one network to another. The challenge with gateways is to understand what information...should be relayed from one network to another (with different message formats and technologies) and what platform should perform the gateway function such...information centric paradigm in that GCN does not specify what constitutes a group ID. Group IDs can be mapped to named data objects, content identifiers

The US Arctic Observing Network - Mobilizing Interagency Observing Actions in an Era of Rapid Change

NASA Astrophysics Data System (ADS)

Starkweather, S.

2017-12-01

US agencies have long relied upon sustained Arctic observing to achieve their missions, be they in support of long-term monitoring, operationalized forecasts, or long-term process studies. One inventory of Arctic observing activities (arcticobservingviewer.org) suggests that there are more than 10,000 sustained data collection sites that have been supported by US agencies. Yet despite calls from academia (e.g. National Research Council, 2006) and agency leadership (e.g. IARPC, 2007) for more integrated approaches, such coherence - in the form of a US Arctic Observing Network (US AON) - has been slow and ad hoc in emerging. Two approaches have been invoked in systematically creating networks of greater coherence. One involves solving the "backward problem" or drawing existing observations into interoperable, multi-sensor, value-added data products. These approaches have the benefit that they build from existing assets and extend observations over greater time and space scales than individual efforts can approach. They suffer from being high-energy undertakings, often proceeding through voluntary efforts, and are limited by the observational assets already in place. Solving the "forward problem", or designing the network that is "needed" entails its own challenges of aligning multiple agency needs and capabilities into coordinated frameworks, often tied into a societal benefit structure. The solutions to the forward problem are greatly constrained by financial and technical feasibility. The benefit of such approaches is that interoperability and user-needs are baked into the network design, and some critical prioritization has been invoked. In September 2016, NOAA and other US agencies advanced plans to formally establish and fund the coordination of a US AON initiative. This US AON initiative brings new coordination capabilities on-line to support and strengthen US engagement in sustained and coordinated pan-Arctic observing and data sharing systems that serve

The Group on Earth Observations (GEO) through 2025

NASA Astrophysics Data System (ADS)

Ryan, Barbara; Cripe, Douglas

Ministers from the Group on Earth Observations (GEO) Member governments, meeting in Geneva, Switzerland in January 2014, unanimously renewed the mandate of GEO through 2025. Through a Ministerial Declaration, they reconfirmed that GEO’s guiding principles of collaboration in leveraging national, regional and global investments and in developing and coordinating strategies to achieve full and open access to Earth observations data and information in order to support timely and knowledge-based decision-making - are catalysts for improving the quality of life of people around the world, advancing global sustainability, and preserving the planet and its biodiversity. GEO Ministers acknowledged and valued the contributions of GEO Member governments and invited all remaining Member States of the United Nations to consider joining GEO. The Ministers also encouraged all Members to strengthen national GEO arrangements, and - of particular interest to COSPAR - they highlighted the unique contributions of Participating Organizations. In this regard, ten more organizations saw their applications approved by Plenary and joined the ranks along with COSPAR to become a Participating Organization in GEO, bringing the current total to 77. Building on the efforts of a Post-2015 Working Group, in which COSPAR participated, Ministers provided additional guidance for GEO and the evolution of its Global Earth Observation System of System (GEOSS) through 2025. Five key areas of activities for the next decade include the following: 1.) Advocating for the value of Earth observations and the need to continue improving Earth observation worldwide; 2.) Urging the adoption and implementation of data sharing principles globally; 3.) Advancing the development of the GEOSS information system for the benefit of users; 4.) Developing a comprehensive interdisciplinary knowledge base defining and documenting observations needed for all disciplines and facilitate availability and accessibility of

Designing optimal greenhouse gas observing networks that consider performance and cost

DOE PAGES

Lucas, D. D.; Yver Kwok, C.; Cameron-Smith, P.; ...

2015-06-16

Emission rates of greenhouse gases (GHGs) entering into the atmosphere can be inferred using mathematical inverse approaches that combine observations from a network of stations with forward atmospheric transport models. Some locations for collecting observations are better than others for constraining GHG emissions through the inversion, but the best locations for the inversion may be inaccessible or limited by economic and other non-scientific factors. We present a method to design an optimal GHG observing network in the presence of multiple objectives that may be in conflict with each other. As a demonstration, we use our method to design a prototypemore » network of six stations to monitor summertime emissions in California of the potent GHG 1,1,1,2-tetrafluoroethane (CH 2FCF 3, HFC-134a). We use a multiobjective genetic algorithm to evolve network configurations that seek to jointly maximize the scientific accuracy of the inferred HFC-134a emissions and minimize the associated costs of making the measurements. The genetic algorithm effectively determines a set of "optimal" observing networks for HFC-134a that satisfy both objectives (i.e., the Pareto frontier). The Pareto frontier is convex, and clearly shows the tradeoffs between performance and cost, and the diminishing returns in trading one for the other. Without difficulty, our method can be extended to design optimal networks to monitor two or more GHGs with different emissions patterns, or to incorporate other objectives and constraints that are important in the practical design of atmospheric monitoring networks.« less

Controllability and observability analysis for vertex domination centrality in directed networks

PubMed Central

Wang, Bingbo; Gao, Lin; Gao, Yong; Deng, Yue; Wang, Yu

2014-01-01

Topological centrality is a significant measure for characterising the relative importance of a node in a complex network. For directed networks that model dynamic processes, however, it is of more practical importance to quantify a vertex's ability to dominate (control or observe) the state of other vertices. In this paper, based on the determination of controllable and observable subspaces under the global minimum-cost condition, we introduce a novel direction-specific index, domination centrality, to assess the intervention capabilities of vertices in a directed network. Statistical studies demonstrate that the domination centrality is, to a great extent, encoded by the underlying network's degree distribution and that most network positions through which one can intervene in a system are vertices with high domination centrality rather than network hubs. To analyse the interaction and functional dependence between vertices when they are used to dominate a network, we define the domination similarity and detect significant functional modules in glossary and metabolic networks through clustering analysis. The experimental results provide strong evidence that our indices are effective and practical in accurately depicting the structure of directed networks. PMID:24954137

Is Ecosystem-Atmosphere Observation in Long-Term Networks actually Science?

NASA Astrophysics Data System (ADS)

Schmid, H. P. E.

2015-12-01

Science uses observations to build knowledge by testable explanations and predictions. The "scientific method" requires controlled systematic observation to examine questions, hypotheses and predictions. Thus, enquiry along the scientific method responds to questions of the type "what if …?" In contrast, long-term observation programs follow a different strategy: we commonly take great care to minimize our influence on the environment of our measurements, with the aim to maximize their external validity. We observe what we think are key variables for ecosystem-atmosphere exchange and ask questions such as "what happens next?" or "how did this happen?" This apparent deviation from the scientific method begs the question whether any explanations we come up with for the phenomena we observe are actually contributing to testable knowledge, or whether their value remains purely anecdotal. Here, we present examples to argue that, under certain conditions, data from long-term observations and observation networks can have equivalent or even higher scientific validity than controlled experiments. Internal validity is particularly enhanced if observations are combined with modeling. Long-term observations of ecosystem-atmosphere fluxes identify trends and temporal scales of variability. Observation networks reveal spatial patterns and variations, and long-term observation networks combine both aspects. A necessary condition for such observations to gain validity beyond the anecdotal is the requirement that the data are comparable: a comparison of two measured values, separated in time or space, must inform us objectively whether (e.g.) one value is larger than the other. In turn, a necessary condition for the comparability of data is the compatibility of the sensors and procedures used to generate them. Compatibility ensures that we compare "apples to apples": that measurements conducted in identical conditions give the same values (within suitable uncertainty intervals

Kansas ground-water observation-well network, 1985

USGS Publications Warehouse

Dague, B.J.; Stullken, L.E.

1986-01-01

Water level measurements are made in 1,892 selected wells in 73 counties, which currently (1985) comprise the Kansas groundwater observation-well network. These measurements are made on a continuous, monthly, quarterly, or annual basis. Water level measurements have been made in observation wells since 1937 as part of a cooperative program among the Kansas Geological Survey , the Kansas State Board of Agriculture, the city of Wichita, and the U.S. Geological Survey. The objectives of the observation-well cooperative program are: (1) to provide long-term records of water level fluctuations in representative wells, (2) to facilitate the determination of possible water level trends that may indicate future availability of groundwater supplies, (3) to aid in the determination of possible changes in the base flow of streams, and (4) to provide information for use in water-resources research. This report lists for each well in the network the location, the first year of recorded water level measurement, the frequency and number of measurements, the land-surface altitude, hexagon-grid identifiers for wells in the High Plains aquifer, and the principal geologic unit(s) in which the well is completed. (USGS)

Marine Vehicle Sensor Network Architecture and Protocol Designs for Ocean Observation

PubMed Central

Zhang, Shaowei; Yu, Jiancheng; Zhang, Aiqun; Yang, Lei; Shu, Yeqiang

2012-01-01

The micro-scale and meso-scale ocean dynamic processes which are nonlinear and have large variability, have a significant impact on the fisheries, natural resources, and marine climatology. A rapid, refined and sophisticated observation system is therefore needed in marine scientific research. The maneuverability and controllability of mobile sensor platforms make them a preferred choice to establish ocean observing networks, compared to the static sensor observing platform. In this study, marine vehicles are utilized as the nodes of mobile sensor networks for coverage sampling of a regional ocean area and ocean feature tracking. A synoptic analysis about marine vehicle dynamic control, multi vehicles mission assignment and path planning methods, and ocean feature tracking and observing techniques is given. Combined with the observation plan in the South China Sea, we provide an overview of the mobile sensor networks established with marine vehicles, and the corresponding simulation results. PMID:22368475

Connecting the Dots: Social Network Structure, Conflict, and Group Cognitive Complexity

ERIC Educational Resources Information Center

Curseu, Petru L.; Janssen, Steffie E. A.; Raab, Jorg

2012-01-01

The current paper combines arguments from the social capital and group cognition literature to explain two different processes through which communication network structures and intra group conflict influence groups' cognitive complexity (GCC). We test in a sample of 44 groups the mediating role of intra group conflict in the relationship between…

Sensitivity of surface meteorological analyses to observation networks

NASA Astrophysics Data System (ADS)

Tyndall, Daniel Paul

A computationally efficient variational analysis system for two-dimensional meteorological fields is developed and described. This analysis approach is most efficient when the number of analysis grid points is much larger than the number of available observations, such as for large domain mesoscale analyses. The analysis system is developed using MATLAB software and can take advantage of multiple processors or processor cores. A version of the analysis system has been exported as a platform independent application (i.e., can be run on Windows, Linux, or Macintosh OS X desktop computers without a MATLAB license) with input/output operations handled by commonly available internet software combined with data archives at the University of Utah. The impact of observation networks on the meteorological analyses is assessed by utilizing a percentile ranking of individual observation sensitivity and impact, which is computed by using the adjoint of the variational surface assimilation system. This methodology is demonstrated using a case study of the analysis from 1400 UTC 27 October 2010 over the entire contiguous United States domain. The sensitivity of this approach to the dependence of the background error covariance on observation density is examined. Observation sensitivity and impact provide insight on the influence of observations from heterogeneous observing networks as well as serve as objective metrics for quality control procedures that may help to identify stations with significant siting, reporting, or representativeness issues.

Defining Essential Biodiversity Variables (EBVs) as a contribution to Essential Ocean Variables (EOVs): A Core Task of the Marine Biodiversity Observation Network (MBON) to Accelerate Integration of Biological Observations in the Global Ocean Observing System (GOOS)

NASA Astrophysics Data System (ADS)

Pearlman, J.; Muller-Karger, F. E.; Sousa Pinto, I.; Costello, M. J.; Duffy, J. E.; Appeltans, W.; Fischer, A. S.; Canonico, G.; Klein, E.; Obura, D.; Montes, E.; Miloslavich, P.; Howard, M.

2017-12-01

The Marine Biodiversity Observation Network (MBON) is a networking effort under the umbrella of the Group on Earth Observations Biodiversity Observation Network (GEO BON). The objective of the MBON is to link existing groups engaged in ocean observation and help define practical indices to deploy in an operational manner to track changes in the number of marine species, the abundance and biomass of marine organisms, the diverse interactions between organisms and the environment, and the variability and change of specific habitats of interest. MBON serves as the biodiversity arm of Blue Planet, the initiative of the Group on Earth Observations (GEO) for the benefit of society. The Global Ocean Observing System (GOOS) was established under the auspices of the Intergovernmental Oceanographic Commission (IOC) in 1991 to organize international ocean observing efforts. The mission of the GOOS is to support monitoring to improve the management of marine and coastal ecosystems and resources, and to enable scientific research. GOOS is engaged in a continuing, rigorous process of identifying Essential Ocean Variables (EOVs). MBON is working with GOOS and the Ocean Biogeographic Information System (OBIS, also under the IOC) to define Essential Biodiversity Variables (EBVs) as those Essential Ocean Variables (EOVs) that have explicit taxonomic records associated with them. For practical purposes, EBVs are a subset of the EOVs. The focus is to promote the integration of biological EOVs including EBVs into the existing and planned national and international ocean observing systems. The definition avoids a proliferation of 'essential' variables across multiple organizations. MBON will continue to advance practical and wide use of EBVs and related EOV. This is an effective way to contribute to several UN assessments (e.g., from IPBES, IPCC, and the World Ocean Assessment under the UN Regular Process), UN Sustainable Development Goals, and to address targets and goals defined under

Demography-based adaptive network model reproduces the spatial organization of human linguistic groups

NASA Astrophysics Data System (ADS)

Capitán, José A.; Manrubia, Susanna

2015-12-01

The distribution of human linguistic groups presents a number of interesting and nontrivial patterns. The distributions of the number of speakers per language and the area each group covers follow log-normal distributions, while population and area fulfill an allometric relationship. The topology of networks of spatial contacts between different linguistic groups has been recently characterized, showing atypical properties of the degree distribution and clustering, among others. Human demography, spatial conflicts, and the construction of networks of contacts between linguistic groups are mutually dependent processes. Here we introduce an adaptive network model that takes all of them into account and successfully reproduces, using only four model parameters, not only those features of linguistic groups already described in the literature, but also correlations between demographic and topological properties uncovered in this work. Besides their relevance when modeling and understanding processes related to human biogeography, our adaptive network model admits a number of generalizations that broaden its scope and make it suitable to represent interactions between agents based on population dynamics and competition for space.

Demography-based adaptive network model reproduces the spatial organization of human linguistic groups.

PubMed

Capitán, José A; Manrubia, Susanna

2015-12-01

The distribution of human linguistic groups presents a number of interesting and nontrivial patterns. The distributions of the number of speakers per language and the area each group covers follow log-normal distributions, while population and area fulfill an allometric relationship. The topology of networks of spatial contacts between different linguistic groups has been recently characterized, showing atypical properties of the degree distribution and clustering, among others. Human demography, spatial conflicts, and the construction of networks of contacts between linguistic groups are mutually dependent processes. Here we introduce an adaptive network model that takes all of them into account and successfully reproduces, using only four model parameters, not only those features of linguistic groups already described in the literature, but also correlations between demographic and topological properties uncovered in this work. Besides their relevance when modeling and understanding processes related to human biogeography, our adaptive network model admits a number of generalizations that broaden its scope and make it suitable to represent interactions between agents based on population dynamics and competition for space.

Observation of Interactions in Adolescent Group Therapy: A Mixed Methods Study

PubMed Central

Arias-Pujol, Eulàlia; Anguera, M. Teresa

2017-01-01

Group psychotherapy is a useful clinical practice for adolescents with mental health issues. Groups typically consist of young people of similar ages but with different personalities, and this results in a complex communication network. The goal of group psychoanalytic psychotherapy is to improve participants' mentalization abilities, facilitating interactions between peers and their therapist in a safe, containing environment. The main aim of this study was to analyze conversation turn-taking between a lead therapist, a co-therapist, and six adolescents over the course of 24 treatment sessions divided into four blocks over 8 months. We employed a mixed-methods design based on systematic observation, which we consider to be a mixed method itself, as the qualitative data collected in the initial observation phase is transformed into quantitative data and subsequently interpreted qualitatively with the aid of clinical vignettes. The observational methodology design was nomothetic, follow-up, and multidimensional. The choice of methodology is justified as we used an ad-hoc observation instrument combining a field format and a category system. Interobserver agreement was analyzed quantitatively by Cohen's kappa using the free QSEQ5 software program. Once we had confirmed the reliability of the data, these were analyzed by polar coordinate analysis, which is a powerful data reduction technique that provides a vector representation of relationships between categories. The results show significant relationships between the therapist and (1) the activation of turn-taking by the participants and the co-therapist and silence and (2) conversation-facilitating interventions and interventions designed to improve mentalization abilities. Detailed analysis of questions demonstrating interest in others showed how the communication changed from radial interactions stemming from the therapist at the beginning of therapy to circular interactions half way through. Repetition was found

The relationship between structure and function in locally observed complex networks

NASA Astrophysics Data System (ADS)

Comin, Cesar H.; Viana, Matheus P.; Costa, Luciano da F.

2013-01-01

Recently, studies looking at the small scale interactions taking place in complex networks have started to unveil the wealth of interactions that occur between groups of nodes. Such findings make the claim for a new systematic methodology to quantify, at node level, how dynamics are influenced (or differentiated) by the structure of the underlying system. Here we define a new measure that, based on the dynamical characteristics obtained for a large set of initial conditions, compares the dynamical behavior of the nodes present in the system. Through this measure, we find that the geographic and Barabási-Albert models have a high capacity for generating networks that exhibit groups of nodes with distinct dynamics compared to the rest of the network. The application of our methodology is illustrated with respect to two real systems. In the first we use the neuronal network of the nematode Caenorhabditis elegans to show that the interneurons of the ventral cord of the nematode present a very large dynamical differentiation when compared to the rest of the network. The second application concerns the SIS epidemic model on an airport network, where we quantify how different the distribution of infection times of high and low degree nodes can be, when compared to the expected value for the network.

The advances in airglow study and observation by the ground-based airglow observation network over China

NASA Astrophysics Data System (ADS)

Xu, Jiyao; Li, Qinzeng; Yuan, Wei; Liu, Xiao; Liu, Weijun; Sun, Longchang

2017-04-01

Ground-based airglow observation networks over China used to study airglow have been established, which contains 15 stations. Some new results were obtained using the networks. For OH airglow observations, firstly, an unusual outbreak of Concentric Gravity Wave (CGW) events were observed by the first no-gap network nearly every night during the first half of August 2013. Combination of the ground imager network with satellites provides multilevel observations of the CGWs from the troposphere to the mesopause region. Secondly, three-year OH airglow images (2012-2014) from Qujing (25.6°N, 103.7°E) were used to study how orographic features of the Tibetan Plateau (TP) affect the geographical distributions of gravity wave (GW) sources. We find the orographic forcings have a significant impact on the gravity wave propagation features. Thirdly, ground-based observations of the OH (9-4, 8-3, 6-2, 5-1, 3-0) band airglow over Xinglong (40°2N, 117°4E) in northern China from 2012 to 2014 are used to calculate rotational temperatures. By comparing the ground-based OH rotational temperature with SABER's observations, five Einstein coefficient datasets are evaluated. We find rotational temperatures determined using any of the available Einstein coefficient datasets have systematic errors. We have obtained a set of optimal Einstein coefficients ratios for rotational temperature derivation using three years data from ground-based OH spectra and SABER temperatures. For the OI 630.0 nm airglow observations, we used three-year (2011-2013) observations of thermospheric winds (at 250 km) by Fabry-Perot interferometers at Xinglong to study the climatology of atmospheric planetary wave-type oscillations (PWTOs) with periods of 4-19 days. We found these PWTOs occur more frequently in the months from May to October. They are consistent with the summertime preference of middle-latitude ionospheric electron density oscillations noted in other studies. By using an all-sky airglow imager

76 FR 19466 - Masco Builder Cabinet Group Including On-Site Leased Workers From Reserves Network, Reliable...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-04-07

... Builder Cabinet Group Including On-Site Leased Workers From Reserves Network, Reliable Staffing, and Third Dimension Waverly, OH; Masco Builder Cabinet Group Including On-Site Leased Workers From Reserves Network... Group including on-site leased workers from Reserves Network, Jackson, Ohio. The workers produce...

Evolution of cooperation on complex networks with synergistic and discounted group interactions

NASA Astrophysics Data System (ADS)

Zhou, Lei; Li, Aming; Wang, Long

2015-06-01

In the real world individuals often engage in group interactions and their payoffs are determined by many factors, including the typical nonlinear interactions, i.e., synergy and discounting. Previous literatures assume that individual payoffs are either synergistically enhanced or discounted with the additional cooperators. Such settings ignore the interplay of these two factors, which is in sharp contrast with the fact that they ubiquitously coexist. Here we investigate how the coexistence and periodical switching of synergistic and discounted group interactions affect the evolution of cooperation on various complex networks. We show that scale-free networks facilitate the emergence of cooperation in terms of fixation probability for group interactions. With nonlinear interactions the heterogeneity of the degree acts as a double-edged sword: below the neutral drift it is the best for cooperation while above the neutral drift it instead provides the least opportunity for cooperators to be fixed. The advantages of the heterogeneity fade as interactive attributes switch between synergy and discounting, which suggests that the heterogeneity of population structures cannot favor cooperators in group interactions even with simple nonlinear interactions. Nonetheless, scale-free networks always guarantee cooperators the fastest rate of fixation. Our work implies that even very simple nonlinear group interactions could greatly shape the fixation probability and fixation time of cooperators in structured populations indicated by complex networks.

Multi-load Groups Coordinated Load Control Strategy Considering Power Network Constraints

NASA Astrophysics Data System (ADS)

Liu, Meng; Zhao, Binchao; Wang, Jun; Zhang, Guohui; Wang, Xin

2017-05-01

Loads with energy storage property can actively participate in power balance for power systems, this paper takes air conditioner as a controllable load example, proposing a multi-load groups coordinated load control strategy considering power network constraints. Firstly, two load control modes considering recovery of load diversity are designed, blocking power oscillation of aggregated air conditioners. As the same time, air conditioner temperature setpoint recovery control strategy is presented to avoid power recovery peak. Considering inherent characteristics of two load control modes, an coordinated load control mode is designed by combining the both. Basing on this, a multi-load groups coordinated load control strategy is proposed. During the implementing of load control, power network constraints should be satisfied. An indice which can reflect the security of power system operating is defined. By minimizing its value through optimization, the change of air conditioning loads’ aggregated power on each load bus can be calculated. Simulations are conducted on an air conditioners group and New England 10-generator 39-bus system, verifying the effectiveness of the proposed multi-load groups coordinated load control strategy considering power network constraints.

Impact of observational incompleteness on the structural properties of protein interaction networks

NASA Astrophysics Data System (ADS)

Kuhnt, Mathias; Glauche, Ingmar; Greiner, Martin

2007-01-01

The observed structure of protein interaction networks is corrupted by many false positive/negative links. This observational incompleteness is abstracted as random link removal and a specific, experimentally motivated (spoke) link rearrangement. Their impact on the structural properties of gene-duplication-and-mutation network models is studied. For the degree distribution a curve collapse is found, showing no sensitive dependence on the link removal/rearrangement strengths and disallowing a quantitative extraction of model parameters. The spoke link rearrangement process moves other structural observables, like degree correlations, cluster coefficient and motif frequencies, closer to their counterparts extracted from the yeast data. This underlines the importance to take a precise modeling of the observational incompleteness into account when network structure models are to be quantitatively compared to data.

Fostering Earth Observation Regional Networks - Integrative and iterative approaches to capacity building

NASA Astrophysics Data System (ADS)

Habtezion, S.

2015-12-01

Fostering Earth Observation Regional Networks - Integrative and iterative approaches to capacity building Fostering Earth Observation Regional Networks - Integrative and iterative approaches to capacity building Senay Habtezion (shabtezion@start.org) / Hassan Virji (hvirji@start.org)Global Change SySTem for Analysis, Training and Research (START) (www.start.org) 2000 Florida Avenue NW, Suite 200 Washington, DC 20009 USA As part of the Global Observation of Forest and Land Cover Dynamics (GOFC-GOLD) project partnership effort to promote use of earth observations in advancing scientific knowledge, START works to bridge capacity needs related to earth observations (EOs) and their applications in the developing world. GOFC-GOLD regional networks, fostered through the support of regional and thematic workshops, have been successful in (1) enabling participation of scientists for developing countries and from the US to collaborate on key GOFC-GOLD and Land Cover and Land Use Change (LCLUC) issues, including NASA Global Data Set validation and (2) training young developing country scientists to gain key skills in EOs data management and analysis. Members of the regional networks are also engaged and reengaged in other EOs programs (e.g. visiting scientists program; data initiative fellowship programs at the USGS EROS Center and Boston University), which has helped strengthen these networks. The presentation draws from these experiences in advocating for integrative and iterative approaches to capacity building through the lens of the GOFC-GOLD partnership effort. Specifically, this presentation describes the role of the GODC-GOLD partnership in nurturing organic networks of scientists and EOs practitioners in Asia, Africa, Eastern Europe and Latin America.

Scalable Multicast Protocols for Overlapped Groups in Broker-Based Sensor Networks

NASA Astrophysics Data System (ADS)

Kim, Chayoung; Ahn, Jinho

In sensor networks, there are lots of overlapped multicast groups because of many subscribers, associated with their potentially varying specific interests, querying every event to sensors/publishers. And gossip based communication protocols are promising as one of potential solutions providing scalability in P(Publish)/ S(Subscribe) paradigm in sensor networks. Moreover, despite the importance of both guaranteeing message delivery order and supporting overlapped multicast groups in sensor or P2P networks, there exist little research works on development of gossip-based protocols to satisfy all these requirements. In this paper, we present two versions of causally ordered delivery guaranteeing protocols for overlapped multicast groups. The one is based on sensor-broker as delegates and the other is based on local views and delegates representing subscriber subgroups. In the sensor-broker based protocol, sensor-broker might lead to make overlapped multicast networks organized by subscriber's interests. The message delivery order has been guaranteed consistently and all multicast messages are delivered to overlapped subscribers using gossip based protocols by sensor-broker. Therefore, these features of the sensor-broker based protocol might be significantly scalable rather than those of the protocols by hierarchical membership list of dedicated groups like traditional committee protocols. And the subscriber-delegate based protocol is much stronger rather than fully decentralized protocols guaranteeing causally ordered delivery based on only local views because the message delivery order has been guaranteed consistently by all corresponding members of the groups including delegates. Therefore, this feature of the subscriber-delegate protocol is a hybrid approach improving the inherent scalability of multicast nature by gossip-based technique in all communications.

Renormalization group theory for percolation in time-varying networks.

PubMed

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

2018-05-22

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

Effect of edge pruning on structural controllability and observability of complex networks

PubMed Central

Mengiste, Simachew Abebe; Aertsen, Ad; Kumar, Arvind

2015-01-01

Controllability and observability of complex systems are vital concepts in many fields of science. The network structure of the system plays a crucial role in determining its controllability and observability. Because most naturally occurring complex systems show dynamic changes in their network connectivity, it is important to understand how perturbations in the connectivity affect the controllability of the system. To this end, we studied the control structure of different types of artificial, social and biological neuronal networks (BNN) as their connections were progressively pruned using four different pruning strategies. We show that the BNNs are more similar to scale-free networks than to small-world networks, when comparing the robustness of their control structure to structural perturbations. We introduce a new graph descriptor, ‘the cardinality curve’, to quantify the robustness of the control structure of a network to progressive edge pruning. Knowing the susceptibility of control structures to different pruning methods could help design strategies to destroy the control structures of dangerous networks such as epidemic networks. On the other hand, it could help make useful networks more resistant to edge attacks. PMID:26674854

Integrated Meteorological Observation Network in Castile-León (Spain)

NASA Astrophysics Data System (ADS)

Merino, A.; Guerrero-Higueras, A. M.; Ortiz de Galisteo, J. P.; López, L.; García-Ortega, E.; Nafría, D. A.; Sánchez, J. L.

2012-04-01

In the region of Castile-Leon, in the northwest of Spain, the study of weather risks is extremely complex because of the topography, the large land area of the region and the variety of climatic features involved. Therefore, as far as the calibration and validation of the necessary tools for the identification and nowcasting of these risks are concerned, one of the most important difficulties is the lack of observed data. The same problem arises, for example, in the analysis of particularly relevant case studies. It was hence deemed necessary to create an INTEGRATED METEOROLOGICAL OBSERVATION NETWORK FOR CASTILE-LEON. The aim of this network is to integrate within one single platform all the ground truth data available. These data enable us to detect a number of weather risks in real time. The various data sources should include the networks from the weather stations run by different public institutions - national and regional ones (AEMET, Junta de Castilla y León, Universities, etc.) -, as well as the stations run by voluntary observers. The platform will contain real or cuasi-real time data from the ground weather stations, but it will also have applications to enable voluntary observers to indicate the presence or absence of certain meteors (snow, hail) or even provide detailed information about them (hailstone size, graupel, etc.). The data managed by this network have a high scientific potential, as they may be used for a number of different purposes: calibration and validation of remote sensing tools, assimilation of observation data from numerical models, study of extreme weather events, etc. An additional aim of the network is the drawing of maps of weather risks in real time. These maps are of great importance for the people involved in risk management in each region, as well as for the general public. Finally, one of the first applications developed has been the creation of observation maps in real time. These applications have been constructed using NCL

Communication Network Integration and Group Uniformity in a Complex Organization.

ERIC Educational Resources Information Center

Danowski, James A.; Farace, Richard V.

This paper contains a discussion of the limitations of research on group processes in complex organizations and the manner in which a procedure for network analysis in on-going systems can reduce problems. The research literature on group uniformity processes and on theoretical models of these processes from an information processing perspective…

Observational properties of compact groups of galaxies

NASA Technical Reports Server (NTRS)

Hickson, Paul

1990-01-01

Compact groups are small, relatively isolated, systems of galaxies with projected separations comparable to the diameters of the galaxies themselves. Two well-known examples are Stephan's Quintet (Stephan, 1877) and Seyfert's Sextet (Seyfert 1948a,b). In groups such as these, the apparent space density of galaxies approaches 10(exp 6) Mpc(sub -3), denser even than the cores of rich clusters. The apparent unlikeliness of the chance occurrence of such tight groupings lead Ambartsumyan (1958, 1975) to conclude that compact groups must be physically dense systems. This view is supported by clear signs of galaxy interactions that are seen in many groups. Spectroscopic observations reveal that typical relative velocities of galaxies in the groups are comparable to their internal stellar velocities. This should be conducive to strong gravitational interactions - more so than in rich clusters, where galaxy velocities are typically much higher. This suggests that compact groups could be excellent laboratories in which to study galaxy interactions and their effects. Compact groups often contain one or more galaxies whose redshift differs greatly from those of the other group members. If these galaxies are at the same distance as the other members, either entire galaxies are being ejected at high velocities from these groups, or some new physical phenomena must be occurring. If their redshifts are cosmological, we must explain why so many discordant galaxies are found in compact groups. In recent years much progress has been made in addressing these questions. Here, the author discusses the current observational data on compact groups and their implications.

Understanding Groups in Outdoor Adventure Education through Social Network Analysis

ERIC Educational Resources Information Center

Jostad, Jeremy; Sibthorp, Jim; Paisley, Karen

2013-01-01

Relationships are a critical component to the experience of an outdoor adventure education (OAE) program, therefore, more fruitful ways of investigating groups is needed. Social network analysis (SNA) is an effective tool to study the relationship structure of small groups. This paper provides an explanation of SNA and shows how it was used by the…

MANGO Imager Network Observations of Geomagnetic Storm Impact on Midlatitude 630 nm Airglow Emissions

NASA Astrophysics Data System (ADS)

Kendall, E. A.; Bhatt, A.

2017-12-01

The Midlatitude Allsky-imaging Network for GeoSpace Observations (MANGO) is a network of imagers filtered at 630 nm spread across the continental United States. MANGO is used to image large-scale airglow and aurora features and observes the generation, propagation, and dissipation of medium and large-scale wave activity in the subauroral, mid and low-latitude thermosphere. This network consists of seven all-sky imagers providing continuous coverage over the United States and extending south into Mexico. This network sees high levels of medium and large scale wave activity due to both neutral and geomagnetic storm forcing. The geomagnetic storm observations largely fall into two categories: Stable Auroral Red (SAR) arcs and Large-scale traveling ionospheric disturbances (LSTIDs). In addition, less-often observed effects include anomalous airglow brightening, bright swirls, and frozen-in traveling structures. We will present an analysis of multiple events observed over four years of MANGO network operation. We will provide both statistics on the cumulative observations and a case study of the "Memorial Day Storm" on May 27, 2017.

Observer-Based Discrete-Time Nonnegative Edge Synchronization of Networked Systems.

PubMed

Su, Housheng; Wu, Han; Chen, Xia

2017-10-01

This paper studies the multi-input and multi-output discrete-time nonnegative edge synchronization of networked systems based on neighbors' output information. The communication relationship among the edges of networked systems is modeled by well-known line graph. Two observer-based edge synchronization algorithms are designed, for which some necessary and sufficient synchronization conditions are derived. Moreover, some computable sufficient synchronization conditions are obtained, in which the feedback matrix and the observer matrix are computed by solving the linear programming problems. We finally design several simulation examples to demonstrate the validity of the given nonnegative edge synchronization algorithms.

Shortwave surface radiation network for observing small-scale cloud inhomogeneity fields

NASA Astrophysics Data System (ADS)

Lakshmi Madhavan, Bomidi; Kalisch, John; Macke, Andreas

2016-03-01

As part of the High Definition Clouds and Precipitation for advancing Climate Prediction Observational Prototype Experiment (HOPE), a high-density network of 99 silicon photodiode pyranometers was set up around Jülich (10 km × 12 km area) from April to July 2013 to capture the small-scale variability of cloud-induced radiation fields at the surface. In this paper, we provide the details of this unique setup of the pyranometer network, data processing, quality control, and uncertainty assessment under variable conditions. Some exemplary days with clear, broken cloudy, and overcast skies were explored to assess the spatiotemporal observations from the network along with other collocated radiation and sky imager measurements available during the HOPE period.

Towards a Community Environmental Observation Network

NASA Astrophysics Data System (ADS)

Mertl, Stefan; Lettenbichler, Anton

2014-05-01

The Community Environmental Observation Network (CEON) is dedicated to the development of a free sensor network to collect and distribute environmental data (e.g. ground shaking, climate parameters). The data collection will be done with contributions from citizens, research institutions and public authorities like communities or schools. This will lead to a large freely available data base which can be used for public information, research, the arts,..... To start a free sensor network, the most important step is to provide easy access to free data collection and -distribution tools. The initial aims of the project CEON are dedicated to the development of these tools. A high quality data logger based on open hardware and free software is developed and a software suite of already existing free software for near-real time data communication and data distribution over the Internet will be assembled. Foremost, the development focuses on the collection of data related to the deformation of the earth (such as ground shaking, surface displacement of mass movements and glaciers) and the collection of climate data. The extent to other measurements will be considered in the design. The data logger is built using open hardware prototyping platforms like BeagleBone Black and Arduino. Main features of the data logger are: a 24Bit analog-to-digital converter; a GPS module for time reference and positioning; wireless mesh networking using Optimized Link State Routing; near real-time data transmission and communication; and near real-time differential GNSS positioning using the RTKLIB software. The project CEON is supported by the Internet Foundation Austria (IPA) within the NetIdee 2013 call.

Nowcasting of meteorological risks during the winter season using the "Integrated Meteorological Observation Network in Castilla y León, (Spain)"

NASA Astrophysics Data System (ADS)

Guerrero-Higueras, Ángel Manuel; López, Laura; Merino, Andrés; Sánchez, José Luis; Matía, Pedro; Lorente, José Manuel; Hermida, Lucía; Nafría, David; Ortiz de Galisteo, José Pablo; Marcos, José Luis; García-Ortega, Eduardo

2013-04-01

The location of Castilla y León within the Iberian Peninsula and its territorial extension make its meteorological risks diverse. The integration of various observation networks, both public and private, in the Observation Network of Castilla y León, allows us to follow the risks in real-time. One of the most frequent risks in the winter season is snow precipitation. In the present paper, we compared WRF numerical model predictions of snowfall for Castilla y León with data from the meteorological observation network and observations from the MSG satellite. Furthermore, frosts were more frequent in the area, to the point that there are parts of the study area with frost during the entire year. Thus, the data from the network allows us to determine the area where frost was registered. Finally, the situations with fog, especially with advective and radiative characteristics, are frequent in the center and south of the plateau, especially in the winter season. Additionally, the Observation Network allows us to know the areas with fog in real-time. The Observation Network is managed using a new platform, developed by Group for Atmospheric Physics, known as MeteoNet, which allows for the prompt extraction of a concrete parameter in a specific location, or, the spatial representation of a parameter determined for the entire study area. Furthermore, the management system developed for the data allows for the total representation of data from the WRF prediction model, with satellite images, observation network, radar data, etc., which is converted into a very useful tool for following risks and validating algorithms in Castilla y León. Acknowledgements The authors would like to thank the Regional Government of Castilla y León for its financial support through the project LE220A11-2.

An Observing System Simulation Experiment Approach to Meteorological Network Assessment

NASA Astrophysics Data System (ADS)

Abbasnezhadi, K.; Rasmussen, P. F.; Stadnyk, T.; Boluwade, A.

2016-12-01

A proper knowledge of the spatiotemporal distribution of rainfall is important in order to conduct a mindful investigation of water movement and storage throughout a catchment. Currently, the most accurate precipitation information available for the remote Boreal ecozones of northern Manitoba is coming from the Canadian Precipitation Analysis (CaPA) data assimilation system. Throughout the Churchill River Basin (CRB), CaPA still does not have the proper skill due to the limited number of weather stations. A new approach to experimental network design was investigated based on the concept of Observing System Simulation Experiment (OSSE). The OSSE-based network assessment procedure which simulates the CaPA system provides a scientific and hydrologically significant tool to assess the sensitivity of CaPA precipitation analysis to observation network density throughout the CRB. To simulate CaPA system, synthetic background and station data were simulated, respectively, by adding spatially uncorrelated and correlated Gaussian noises to an assumingly true daily weather field synthesized by a gridded precipitation generator which simulates CaPA data. Given the true reference field on one hand, and a set of pseudo-CaPA analyses associated with different network realizations on the other hand, a WATFLOOD hydrological model was employed to compare the modeled runoff. The simulations showed that as network density increases, the accuracy of CaPA precipitation products improves up to a certain limit beyond which adding more stations to the network does not result in further accuracy.

Results of Joint Observations of Jupiter's Atmosphere by Juno and a Network of Earth-Based Observing Stations

NASA Astrophysics Data System (ADS)

Orton, Glenn; Momary, Thomas; Bolton, Scott; Levin, Steven; Hansen, Candice; Janssen, Michael; Adriani, Alberto; Gladstone, G. Randall; Bagenal, Fran; Ingersoll, Andrew

2017-04-01

The Juno mission has promoted and coordinated a network of Earth-based observations, including both Earth-proximal and ground-based facilities, to extend and enhance observations made by the Juno mission. The spectral region and timeline of all of these observations are summarized in the web site: https://www.missionjuno.swri.edu/planned-observations. Among the earliest of these were observation of Jovian auroral phenomena at X-ray, ultraviolet and infrared wavelengths and measurements of Jovian synchrotron radiation from the Earth simultaneously with the measurement of properties of the upstream solar wind. Other observations of significance to the magnetosphere measured the mass loading from Io by tracking its observed volcanic activity and the opacity of its torus. Observations of Jupiter's neutral atmosphere included observations of reflected sunlight from the near-ultraviolet through the near-infrared and thermal emission from 5 μm through the radio region. The point of these measurements is to relate properties of the deep atmosphere that are the focus of Juno's mission to the state of the "weather layer" at much higher atmospheric levels. These observations cover spectral regions not included in Juno's instrumentation, provide spatial context for Juno's often spatially limited coverage of Jupiter, and they describe the evolution of atmospheric features in time that are measured only once by Juno. We will summarize the results of measurements during the approach phase of the mission that characterized the state of the atmosphere, as well as observations made by Juno and the supporting campaign during Juno's perijoves 1 (2016 August 27), 3 (2016 December 11), 4 (2017 February 2) and possibly "early" results from 5 (2017 March 27). Besides a global network of professional astronomers, the Juno mission also benefited from the enlistment of a network of dedicated amateur astronomers who provided a quasi-continuous picture of the evolution of features observed by

Gap analysis of the European Earth Observation Networks

NASA Astrophysics Data System (ADS)

Closa, Guillem; Serral, Ivette; Maso, Joan

2016-04-01

Earth Observations (EO) are fundamental to enhance the scientific understanding of the current status of the Earth. Nowadays, there are a lot of EO services that provide large volume of data, and the number of datasets available for different geosciences areas is increasing by the day. Despite this coverage, a glance of the European EO networks reveals that there are still some issues that are not being met; some gaps in specific themes or some thematic overlaps between different networks. This situation requires a clarification process of the actual status of the EO European networks in order to set priorities and propose future actions that will improve the European EO networks. The aim of this work is to detect the existing gaps and overlapping problems among the European EO networks. The analytical process has been done by studying the availability and the completeness of the Essential Variables (EV) data captured by the European EO networks. The concept of EVs considers that there are a number of parameters that are essential to characterize the state and trends of a system without losing significant information. This work generated a database of the existing gaps in the European EO network based on the initial GAIA-CLIM project data structure. For each theme the missing or incomplete data about each EV was indentified. Then, if incomplete, the gap was described by adding its type (geographical extent, vertical extent, temporal extent, spatial resolution, etc), the cost, the remedy, the feasibility, the impact and the priority, among others. Gaps in EO are identified following the ConnectinGEO methodology structured in 5 threads; identification of observation requirements, incorporation of international research programs material, consultation process within the current EO actors, GEOSS Discovery and Access Broker analysis, and industry-driven challenges implementation. Concretely, the presented work focuses on the second thread, which is based on

Connectivity Strength-Weighted Sparse Group Representation-Based Brain Network Construction for MCI Classification

PubMed Central

Yu, Renping; Zhang, Han; An, Le; Chen, Xiaobo; Wei, Zhihui; Shen, Dinggang

2017-01-01

Brain functional network analysis has shown great potential in understanding brain functions and also in identifying biomarkers for brain diseases, such as Alzheimer's disease (AD) and its early stage, mild cognitive impairment (MCI). In these applications, accurate construction of biologically meaningful brain network is critical. Sparse learning has been widely used for brain network construction; however, its l1-norm penalty simply penalizes each edge of a brain network equally, without considering the original connectivity strength which is one of the most important inherent linkwise characters. Besides, based on the similarity of the linkwise connectivity, brain network shows prominent group structure (i.e., a set of edges sharing similar attributes). In this article, we propose a novel brain functional network modeling framework with a “connectivity strength-weighted sparse group constraint.” In particular, the network modeling can be optimized by considering both raw connectivity strength and its group structure, without losing the merit of sparsity. Our proposed method is applied to MCI classification, a challenging task for early AD diagnosis. Experimental results based on the resting-state functional MRI, from 50 MCI patients and 49 healthy controls, show that our proposed method is more effective (i.e., achieving a significantly higher classification accuracy, 84.8%) than other competing methods (e.g., sparse representation, accuracy = 65.6%). Post hoc inspection of the informative features further shows more biologically meaningful brain functional connectivities obtained by our proposed method. PMID:28150897

Sport psychology group consultation using social networking web sites.

PubMed

Dietrich, Frederick; Shipherd, Amber M; Gershgoren, Lael; Filho, Edson Medeiros; Basevitch, Itay

2012-08-01

A social networking Web site, Facebook, was used to deliver long-term sport psychology consultation services to student-athletes (i.e., soccer players) in 30- to 60-min weekly sessions. Additional short-term team building, group cohesion, communication, anger management, injury rehabilitation, mental toughness, commitment, and leadership workshops were provided. Cohesion and overall relationships between both the student-athletes and the sport psychology consultants benefited from this process. Social networking Web sites offer a practical way of providing sport psychology consulting services that does not require use of major resources. (c) 2012 APA, all rights reserved.

Visual target modulation of functional connectivity networks revealed by self-organizing group ICA.

PubMed

van de Ven, Vincent; Bledowski, Christoph; Prvulovic, David; Goebel, Rainer; Formisano, Elia; Di Salle, Francesco; Linden, David E J; Esposito, Fabrizio

2008-12-01

We applied a data-driven analysis based on self-organizing group independent component analysis (sogICA) to fMRI data from a three-stimulus visual oddball task. SogICA is particularly suited to the investigation of the underlying functional connectivity and does not rely on a predefined model of the experiment, which overcomes some of the limitations of hypothesis-driven analysis. Unlike most previous applications of ICA in functional imaging, our approach allows the analysis of the data at the group level, which is of particular interest in high order cognitive studies. SogICA is based on the hierarchical clustering of spatially similar independent components, derived from single subject decompositions. We identified four main clusters of components, centered on the posterior cingulate, bilateral insula, bilateral prefrontal cortex, and right posterior parietal and prefrontal cortex, consistently across all participants. Post hoc comparison of time courses revealed that insula, prefrontal cortex and right fronto-parietal components showed higher activity for targets than for distractors. Activation for distractors was higher in the posterior cingulate cortex, where deactivation was observed for targets. While our results conform to previous neuroimaging studies, they also complement conventional results by showing functional connectivity networks with unique contributions to the task that were consistent across subjects. SogICA can thus be used to probe functional networks of active cognitive tasks at the group-level and can provide additional insights to generate new hypotheses for further study. Copyright 2007 Wiley-Liss, Inc.

Relationships Between Long-Range Lightning Networks and TRMM/LIS Observations

NASA Technical Reports Server (NTRS)

Rudlosky, Scott D.; Holzworth, Robert H.; Carey, Lawrence D.; Schultz, Chris J.; Bateman, Monte; Cummins, Kenneth L.; Cummins, Kenneth L.; Blakeslee, Richard J.; Goodman, Steven J.

2012-01-01

Recent advances in long-range lightning detection technologies have improved our understanding of thunderstorm evolution in the data sparse oceanic regions. Although the expansion and improvement of long-range lightning datasets have increased their applicability, these applications (e.g., data assimilation, atmospheric chemistry, and aviation weather hazards) require knowledge of the network detection capabilities. The present study intercompares long-range lightning data with observations from the Lightning Imaging Sensor (LIS) aboard the Tropical Rainfall Measurement Mission (TRMM) satellite. The study examines network detection efficiency and location accuracy relative to LIS observations, describes spatial variability in these performance metrics, and documents the characteristics of LIS flashes that are detected by the long-range networks. Improved knowledge of relationships between these datasets will allow researchers, algorithm developers, and operational users to better prepare for the spatial and temporal coverage of the upcoming GOES-R Geostationary Lightning Mapper (GLM).

Developing an Arctic Observing Network: Looking Beyond Scientific Research as a Driver to Broader Societal Benefits as Drivers

NASA Astrophysics Data System (ADS)

Jeffries, M. O.

2017-12-01

This presentation will address the first ever application of the Societal Benefit Areas approach to continuing efforts to develop an integrated pan-Arctic Observing Network. The scientific research community has been calling for an Arctic Observing Network since the early years of this century, at least. There is no question of the importance of research-driven observations at a time when rapid changes occurring throughout the Arctic environmental system are affecting people and communities in the Arctic and in regions far from the Arctic. Observations are need for continued environmental monitoring and change detection; improving understanding of how the system and its components function, and how they are connected to lower latitude regions; advancing numerical modeling capabilities for forecasting and projection; and developing value-added products and services for people and communities, and for decision- and policymaking. Scientific research is, without question, a benefit to society, but the benefits of Earth observations extend beyond scientific research. Societal Benefit Areas (SBAs) were first described by the international Group on Earth Observations (GEO) and have since been used by USGEO as the basis for its National Earth Observation Assessments. The most recent application of SBAs to Earth observing realized a framework of SBAs, SBA Sub-areas, and Key Objectives required for the completion of a full Earth observing assessment for the Arctic. This framework, described in a report released in June 2017, and a brief history of international efforts to develop an integrated pan-Arctic Observing Network, are the subjects of this presentation.

Effective Network Size Predicted From Simulations of Pathogen Outbreaks Through Social Networks Provides a Novel Measure of Structure-Standardized Group Size.

PubMed

McCabe, Collin M; Nunn, Charles L

2018-01-01

The transmission of infectious disease through a population is often modeled assuming that interactions occur randomly in groups, with all individuals potentially interacting with all other individuals at an equal rate. However, it is well known that pairs of individuals vary in their degree of contact. Here, we propose a measure to account for such heterogeneity: effective network size (ENS), which refers to the size of a maximally complete network (i.e., unstructured, where all individuals interact with all others equally) that corresponds to the outbreak characteristics of a given heterogeneous, structured network. We simulated susceptible-infected (SI) and susceptible-infected-recovered (SIR) models on maximally complete networks to produce idealized outbreak duration distributions for a disease on a network of a given size. We also simulated the transmission of these same diseases on random structured networks and then used the resulting outbreak duration distributions to predict the ENS for the group or population. We provide the methods to reproduce these analyses in a public R package, "enss." Outbreak durations of simulations on randomly structured networks were more variable than those on complete networks, but tended to have similar mean durations of disease spread. We then applied our novel metric to empirical primate networks taken from the literature and compared the information represented by our ENSs to that by other established social network metrics. In AICc model comparison frameworks, group size and mean distance proved to be the metrics most consistently associated with ENS for SI simulations, while group size, centralization, and modularity were most consistently associated with ENS for SIR simulations. In all cases, ENS was shown to be associated with at least two other independent metrics, supporting its use as a novel metric. Overall, our study provides a proof of concept for simulation-based approaches toward constructing metrics of ENS

A Secure Multicast Framework in Large and High-Mobility Network Groups

NASA Astrophysics Data System (ADS)

Lee, Jung-San; Chang, Chin-Chen

With the widespread use of Internet applications such as Teleconference, Pay-TV, Collaborate tasks, and Message services, how to construct and distribute the group session key to all group members securely is becoming and more important. Instead of adopting the point-to-point packet delivery, these emerging applications are based upon the mechanism of multicast communication, which allows the group member to communicate with multi-party efficiently. There are two main issues in the mechanism of multicast communication: Key Distribution and Scalability. The first issue is how to distribute the group session key to all group members securely. The second one is how to maintain the high performance in large network groups. Group members in conventional multicast systems have to keep numerous secret keys in databases, which makes it very inconvenient for them. Furthermore, in case that a member joins or leaves the communication group, many involved participants have to change their own secret keys to preserve the forward secrecy and the backward secrecy. We consequently propose a novel version for providing secure multicast communication in large network groups. Our proposed framework not only preserves the forward secrecy and the backward secrecy but also possesses better performance than existing alternatives. Specifically, simulation results demonstrate that our scheme is suitable for high-mobility environments.

Ground-Based Network and Supersite Observations to Complement and Enrich EOS Research

NASA Technical Reports Server (NTRS)

Tsay, Si-Chee; Holben, Brent N.; Welton, Ellsworth J.

2011-01-01

Since 1997 NASA has been successfully launching a series of satellites - the Earth Observing System (EOS) - to intensively study, and gain a better understanding of, the Earth as an integrated system. Space-borne remote sensing observations, however, are often plagued by contamination of surface signatures. Thus, ground-based in-situ and remote-sensing measurements, where signals come directly from atmospheric constituents, the sun, and/or the Earth-atmosphere interactions, provide additional information content for comparisons that confirm quantitatively the usefulness of the integrated surface, aircraft, and satellite datasets. Through numerous participations, particularly but not limited to the EOS remote-sensing/retrieval and validation projects over the years, NASA/GSFC has developed and continuously refined ground-based networks and mobile observatories that proved to be vital in providing high temporal measurements, which complement and enrich the satellite observations. These are: the AERO NET (AErosol RObotic NETwork) a federation of ground-based globally distributed network of spectral sun-sky photometers; the MPLNET (Micro-Pulse Lidar NETwork, a similarly organized network of micro-pulse lidar systems measuring aerosol and cloud vertical structure continuously; and the SMART-COMMIT (Surface-sensing Measurements for Atmospheric Radiative Transfer - Chemical, Optical & Microphysical Measurements of In-situ Troposphere, mobile observatories, a suite of spectral radiometers and in-situ probes acquiring supersite measurements. Most MPLNET sites are collocated with those of AERONET, and both networks always support the deployment of SMART-COMMIT worldwide. These data products follow the data structure of EOS conventions: Level-0, instrument archived raw data; Level-1 (or 1.5), real-time data with no (or limited) quality assurance; Level-2, not real high temporal and spectral resolutions. In this talk, we will present NASA/GSFC groundbased facilities, serving

Transformational leadership and group interaction as climate antecedents: a social network analysis.

PubMed

Zohar, Dov; Tenne-Gazit, Orly

2008-07-01

In order to test the social mechanisms through which organizational climate emerges, this article introduces a model that combines transformational leadership and social interaction as antecedents of climate strength (i.e., the degree of within-unit agreement about climate perceptions). Despite their longstanding status as primary variables, both antecedents have received limited empirical research. The sample consisted of 45 platoons of infantry soldiers from 5 different brigades, using safety climate as the exemplar. Results indicate a partially mediated model between transformational leadership and climate strength, with density of group communication network as the mediating variable. In addition, the results showed independent effects for group centralization of the communication and friendship networks, which exerted incremental effects on climate strength over transformational leadership. Whereas centralization of the communication network was found to be negatively related to climate strength, centralization of the friendship network was positively related to it. Theoretical and practical implications are discussed.

Cooperative Networks: Altruism, Group Solidarity, Reciprocity, and Sanctioning in Ugandan Producer Organizations.

PubMed

Baldassarri, Delia

2015-09-01

Repeated interaction and social networks are commonly considered viable solutions to collective action problems. This article identifies and systematically measures four general mechanisms--that is, generalized altruism, group solidarity, reciprocity, and the threat of sanctioning--and tests which of them brings about cooperation in the context of Ugandan producer organizations. Using an innovative methodological framework that combines "lab-in-the-field" experiments with survey interviews and complete social networks data, the article goes beyond the assessment of a relationship between social networks and collective outcomes to study the mechanisms that favor cooperative behavior. The article first establishes a positive relationship between position in the network structure and propensity to cooperate in the producer organization and then uses farmers' behavior in dictator and public goods games to test different mechanisms that may account for such a relationship. Results show that cooperation is induced by patterns of reciprocity that emerge through repeated interaction rather than other-regarding preferences like altruism or group solidarity.

High-order interactions observed in multi-task intrinsic networks are dominant indicators of aberrant brain function in schizophrenia

PubMed Central

Plis, Sergey M; Sui, Jing; Lane, Terran; Roy, Sushmita; Clark, Vincent P; Potluru, Vamsi K; Huster, Rene J; Michael, Andrew; Sponheim, Scott R; Weisend, Michael P; Calhoun, Vince D

2013-01-01

Identifying the complex activity relationships present in rich, modern neuroimaging data sets remains a key challenge for neuroscience. The problem is hard because (a) the underlying spatial and temporal networks may be nonlinear and multivariate and (b) the observed data may be driven by numerous latent factors. Further, modern experiments often produce data sets containing multiple stimulus contexts or tasks processed by the same subjects. Fusing such multi-session data sets may reveal additional structure, but raises further statistical challenges. We present a novel analysis method for extracting complex activity networks from such multifaceted imaging data sets. Compared to previous methods, we choose a new point in the trade-off space, sacrificing detailed generative probability models and explicit latent variable inference in order to achieve robust estimation of multivariate, nonlinear group factors (“network clusters”). We apply our method to identify relationships of task-specific intrinsic networks in schizophrenia patients and control subjects from a large fMRI study. After identifying network-clusters characterized by within- and between-task interactions, we find significant differences between patient and control groups in interaction strength among networks. Our results are consistent with known findings of brain regions exhibiting deviations in schizophrenic patients. However, we also find high-order, nonlinear interactions that discriminate groups but that are not detected by linear, pair-wise methods. We additionally identify high-order relationships that provide new insights into schizophrenia but that have not been found by traditional univariate or second-order methods. Overall, our approach can identify key relationships that are missed by existing analysis methods, without losing the ability to find relationships that are known to be important. PMID:23876245

Observation of CH⋅⋅⋅π Interactions between Methyl and Carbonyl Groups in Proteins.

PubMed

Perras, Frédéric A; Marion, Dominique; Boisbouvier, Jérôme; Bryce, David L; Plevin, Michael J

2017-06-19

Protein structure and function is dependent on myriad noncovalent interactions. Direct detection and characterization of these weak interactions in large biomolecules, such as proteins, is experimentally challenging. Herein, we report the first observation and measurement of long-range "through-space" scalar couplings between methyl and backbone carbonyl groups in proteins. These J couplings are indicative of the presence of noncovalent C-H⋅⋅⋅π hydrogen-bond-like interactions involving the amide π network. Experimentally detected scalar couplings were corroborated by a natural bond orbital analysis, which revealed the orbital nature of the interaction and the origins of the through-space J couplings. The experimental observation of this type of CH⋅⋅⋅π interaction adds a new dimension to the study of protein structure, function, and dynamics by NMR spectroscopy. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

75 FR 49528 - Freescale Semiconductor, Inc., Networking and Multimedia Group (“NMG”) Excluding the Multimedia...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-08-13

..., Inc., Networking and Multimedia Group (``NMG'') Excluding the Multimedia Applications Division..., Inc., Networking and Multimedia Group (``NMG''), excluding the Multimedia Applications Division... certification for workers of the subject firm. The workers are engaged in internal design and engineering...

Observation of Conductance Quantization in InSb Nanowire Networks

PubMed Central

2017-01-01

Majorana zero modes (MZMs) are prime candidates for robust topological quantum bits, holding a great promise for quantum computing. Semiconducting nanowires with strong spin orbit coupling offer a promising platform to harness one-dimensional electron transport for Majorana physics. Demonstrating the topological nature of MZMs relies on braiding, accomplished by moving MZMs around each other in a certain sequence. Most of the proposed Majorana braiding circuits require nanowire networks with minimal disorder. Here, the electronic transport across a junction between two merged InSb nanowires is studied to investigate how disordered these nanowire networks are. Conductance quantization plateaus are observed in most of the contact pairs of the epitaxial InSb nanowire networks: the hallmark of ballistic transport behavior. PMID:28665621

Connectivity strength-weighted sparse group representation-based brain network construction for MCI classification.

PubMed

Yu, Renping; Zhang, Han; An, Le; Chen, Xiaobo; Wei, Zhihui; Shen, Dinggang

2017-05-01

Brain functional network analysis has shown great potential in understanding brain functions and also in identifying biomarkers for brain diseases, such as Alzheimer's disease (AD) and its early stage, mild cognitive impairment (MCI). In these applications, accurate construction of biologically meaningful brain network is critical. Sparse learning has been widely used for brain network construction; however, its l 1 -norm penalty simply penalizes each edge of a brain network equally, without considering the original connectivity strength which is one of the most important inherent linkwise characters. Besides, based on the similarity of the linkwise connectivity, brain network shows prominent group structure (i.e., a set of edges sharing similar attributes). In this article, we propose a novel brain functional network modeling framework with a "connectivity strength-weighted sparse group constraint." In particular, the network modeling can be optimized by considering both raw connectivity strength and its group structure, without losing the merit of sparsity. Our proposed method is applied to MCI classification, a challenging task for early AD diagnosis. Experimental results based on the resting-state functional MRI, from 50 MCI patients and 49 healthy controls, show that our proposed method is more effective (i.e., achieving a significantly higher classification accuracy, 84.8%) than other competing methods (e.g., sparse representation, accuracy = 65.6%). Post hoc inspection of the informative features further shows more biologically meaningful brain functional connectivities obtained by our proposed method. Hum Brain Mapp 38:2370-2383, 2017. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

The GAW Aerosol Lidar Observation Network (GALION) as a source of near-real time aerosol profile data for model evaluation and assimilation

NASA Astrophysics Data System (ADS)

Hoff, R. M.; Pappalardo, G.

2010-12-01

In 2007, the WMO Global Atmospheric Watch’s Science Advisory Group on Aerosols described a global network of lidar networks called GAW Aerosol Lidar Observation Network (GALION). GALION has a purpose of providing expanded coverage of aerosol observations for climate and air quality use. Comprised of networks in Asia (AD-NET), Europe (EARLINET and CIS-LINET), North America (CREST and CORALNET), South America (ALINE) and with contribution from global networks such as MPLNET and NDACC, the collaboration provides a unique capability to define aerosol profiles in the vertical. GALION is designed to supplement existing ground-based and column profiling (AERONET, PHOTONS, SKYNET, GAWPFR) stations. In September 2010, GALION held its second workshop and one component of discussion focussed how the network would integrate into model needs. GALION partners have contributed to the Sand and Dust Storm Warning and Analysis System (SDS-WAS) and to assimilation in models such as DREAM. This paper will present the conclusions of those discussions and how these observations can fit into a global model analysis framework. Questions of availability, latency, and aerosol parameters that might be ingested into models will be discussed. An example of where EARLINET and GALION have contributed in near-real time observations was the suite of measurements during the Eyjafjallajokull eruption in Iceland and its impact on European air travel. Lessons learned from this experience will be discussed.

Time development in the early history of social networks: link stabilization, group dynamics, and segregation.

PubMed

Bruun, Jesper; Bearden, Ian G

2014-01-01

Studies of the time development of empirical networks usually investigate late stages where lasting connections have already stabilized. Empirical data on early network history are rare but needed for a better understanding of how social network topology develops in real life. Studying students who are beginning their studies at a university with no or few prior connections to each other offers a unique opportunity to investigate the formation and early development of link patterns and community structure in social networks. During a nine week introductory physics course, first year physics students were asked to identify those with whom they communicated about problem solving in physics during the preceding week. We use these students' self reports to produce time dependent student interaction networks. We investigate these networks to elucidate possible effects of different student attributes in early network formation. Changes in the weekly number of links show that while roughly half of all links change from week to week, students also reestablish a growing number of links as they progress through their first weeks of study. Using the Infomap community detection algorithm, we show that the networks exhibit community structure, and we use non-network student attributes, such as gender and end-of-course grade to characterize communities during their formation. Specifically, we develop a segregation measure and show that students structure themselves according to gender and pre-organized sections (in which students engage in problem solving and laboratory work), but not according to end-of-coure grade. Alluvial diagrams of consecutive weeks' communities show that while student movement between groups are erratic in the beginning of their studies, they stabilize somewhat towards the end of the course. Taken together, the analyses imply that student interaction networks stabilize quickly and that students establish collaborations based on who is immediately

Ethnic diversity and value sharing: A longitudinal social network perspective on interactive group processes.

PubMed

Meeussen, Loes; Agneessens, Filip; Delvaux, Ellen; Phalet, Karen

2018-04-01

People often collaborate in groups that are increasingly diverse. As research predominantly investigated effects of diversity, the processes behind these effects remain understudied. We follow recent research that shows creating shared values is important for group functioning but seems hindered in high diversity groups - and use longitudinal social network analyses to study two interpersonal processes behind value sharing: creating relations between members or 'social bonding' (network tie formation and homophily) and sharing values - potentially through these relationships - or 'social norming' (network convergence and influence). We investigate these processes in small interactive groups with low and high ethnic diversity as they collaborate over time. In both low and high diversity groups, members showed social bonding and this creation of relations between members was not organized along ethnic lines. Low diversity groups also showed social norming: Members adjusted their relational values to others they liked and achievement values converged regardless of liking. In high diversity groups, however, there was no evidence for social norming. Thus, ethnic diversity seems to especially affect processes of social norming in groups, suggesting that targeted interventions should focus on facilitating social norming to stimulate value sharing in high diversity groups. © 2018 The British Psychological Society.

Observing Arctic Ecology using Networked Infomechanical Systems

NASA Astrophysics Data System (ADS)

Healey, N. C.; Oberbauer, S. F.; Hollister, R. D.; Tweedie, C. E.; Welker, J. M.; Gould, W. A.

2012-12-01

Understanding ecological dynamics is important for investigation into the potential impacts of climate change in the Arctic. Established in the early 1990's, the International Tundra Experiment (ITEX) began observational inquiry of plant phenology, plant growth, community composition, and ecosystem properties as part of a greater effort to study changes across the Arctic. Unfortunately, these observations are labor intensive and time consuming, greatly limiting their frequency and spatial coverage. We have expanded the capability of ITEX to analyze ecological phenomenon with improved spatial and temporal resolution through the use of Networked Infomechanical Systems (NIMS) as part of the Arctic Observing Network (AON) program. The systems exhibit customizable infrastructure that supports a high level of versatility in sensor arrays in combination with information technology that allows for adaptable configurations to numerous environmental observation applications. We observe stereo and static time-lapse photography, air and surface temperature, incoming and outgoing long and short wave radiation, net radiation, and hyperspectral reflectance that provides critical information to understanding how vegetation in the Arctic is responding to ambient climate conditions. These measurements are conducted concurrent with ongoing manual measurements using ITEX protocols. Our NIMS travels at a rate of three centimeters per second while suspended on steel cables that are ~1 m from the surface spanning transects ~50 m in length. The transects are located to span soil moisture gradients across a variety of land cover types including dry heath, moist acidic tussock tundra, shrub tundra, wet meadows, dry meadows, and water tracks. We have deployed NIMS at four locations on the North Slope of Alaska, USA associated with 1 km2 ARCSS vegetation study grids including Barrow, Atqasuk, Toolik Lake, and Imnavait Creek. A fifth system has been deployed in Thule, Greenland beginning in

How to most effectively expand the global surface ozone observing network

NASA Astrophysics Data System (ADS)

Sofen, E. D.; Bowdalo, D.; Evans, M. J.

2016-02-01

Surface ozone observations with modern instrumentation have been made around the world for more than 40 years. Some of these observations have been made as one-off activities with short-term, specific science objectives and some have been made as part of wider networks which have provided a foundational infrastructure of data collection, calibration, quality control, and dissemination. These observations provide a fundamental underpinning to our understanding of tropospheric chemistry, air quality policy, atmosphere-biosphere interactions, etc. brought together eight of these networks to provide a single data set of surface ozone observations. We investigate how representative this combined data set is of global surface ozone using the output from a global atmospheric chemistry model. We estimate that on an area basis, 25 % of the globe is observed (34 % land, 21 % ocean). Whereas Europe and North America have almost complete coverage, other continents, Africa, South America, Australia, and Asia (12-17 %) show significant gaps. Antarctica is surprisingly well observed (78 %). Little monitoring occurs over the oceans, with the tropical and southern oceans particularly poorly represented. The surface ozone over key biomes such as tropical forests and savanna is almost completely unmonitored. A chemical cluster analysis suggests that a significant number of observations are made of polluted air masses, but cleaner air masses whether over the land or ocean (especially again in the tropics) are significantly under-observed. The current network is unlikely to see the impact of the El Niño-Southern Oscillation (ENSO) but may be capable of detecting other planetary-scale signals. Model assessment and validation activities are hampered by a lack of observations in regions where the models differ substantially, as is the ability to monitor likely changes in surface ozone over the next century. Using our methodology we are able to suggest new sites which

Statistical assessment of crosstalk enrichment between gene groups in biological networks.

PubMed

McCormack, Theodore; Frings, Oliver; Alexeyenko, Andrey; Sonnhammer, Erik L L

2013-01-01

Analyzing groups of functionally coupled genes or proteins in the context of global interaction networks has become an important aspect of bioinformatic investigations. Assessing the statistical significance of crosstalk enrichment between or within groups of genes can be a valuable tool for functional annotation of experimental gene sets. Here we present CrossTalkZ, a statistical method and software to assess the significance of crosstalk enrichment between pairs of gene or protein groups in large biological networks. We demonstrate that the standard z-score is generally an appropriate and unbiased statistic. We further evaluate the ability of four different methods to reliably recover crosstalk within known biological pathways. We conclude that the methods preserving the second-order topological network properties perform best. Finally, we show how CrossTalkZ can be used to annotate experimental gene sets using known pathway annotations and that its performance at this task is superior to gene enrichment analysis (GEA). CrossTalkZ (available at http://sonnhammer.sbc.su.se/download/software/CrossTalkZ/) is implemented in C++, easy to use, fast, accepts various input file formats, and produces a number of statistics. These include z-score, p-value, false discovery rate, and a test of normality for the null distributions.

Observations and analysis of self-similar branching topology in glacier networks

USGS Publications Warehouse

Bahr, D.B.; Peckham, S.D.

1996-01-01

Glaciers, like rivers, have a branching structure which can be characterized by topological trees or networks. Probability distributions of various topological quantities in the networks are shown to satisfy the criterion for self-similarity, a symmetry structure which might be used to simplify future models of glacier dynamics. Two analytical methods of describing river networks, Shreve's random topology model and deterministic self-similar trees, are applied to the six glaciers of south central Alaska studied in this analysis. Self-similar trees capture the topological behavior observed for all of the glaciers, and most of the networks are also reasonably approximated by Shreve's theory. Copyright 1996 by the American Geophysical Union.

Renormalization group contraction of tensor networks in three dimensions

NASA Astrophysics Data System (ADS)

García-Sáez, Artur; Latorre, José I.

2013-02-01

We present a new strategy for contracting tensor networks in arbitrary geometries. This method is designed to follow as strictly as possible the renormalization group philosophy, by first contracting tensors in an exact way and, then, performing a controlled truncation of the resulting tensor. We benchmark this approximation procedure in two dimensions against an exact contraction. We then apply the same idea to a three-dimensional quantum system. The underlying rational for emphasizing the exact coarse graining renormalization group step prior to truncation is related to monogamy of entanglement.

NEON, Establishing a Standardized Network for Groundwater Observations

NASA Astrophysics Data System (ADS)

Fitzgerald, M.; Schroeter, N.; Goodman, K. J.; Roehm, C. L.

2013-12-01

The National Ecological Observatory Network (NEON) is establishing a standardized set of data collection systems comprised of in-situ sensors and observational sampling to obtain data fundamental to the analysis of environmental change at a continental scale. NEON will be collecting aquatic, terrestrial, and atmospheric data using Observatory-wide standardized designs and methods via a systems engineering approach. This approach ensures a wealth of high quality data, data algorithms, and models that will be freely accessible to all communities such as academic researchers, policy makers, and the general public. The project is established to provide 30 years of data which will enable prediction and forecasting of drivers and responses of ecological change at scales ranging from localized responses through regional gradients and up to the continental scale. The Observatory is a distributed system of sites spread across the United States, including Alaska, Hawaii, and Puerto Rico, which is subdivided into 20 statistically unique domains, based on a set of 18 ecologically important parameters. Each domain contains at least one core aquatic and terrestrial site which are located in unmanaged lands, and up to 2 additional sites selected to study domain specific questions such as nitrogen deposition gradients and responses of land use change activities on the ecosystem. Here, we present the development of NEON's groundwater observation well network design and the timing strategy for sampling groundwater chemistry. Shallow well networks, up to 100 feet in depth, will be installed at NEON aquatic sites and will allow for observation of localized ecohydrologic site conditions, by providing basic spatio-temporal near-real time data on groundwater parameters (level, temperature, conductivity) collected from in situ high-resolution instrumentation positioned in each well; and biannual sampling of geochemical and nutrient (N and P) concentrations in a subset of wells for each

Classification of ion mobility spectra by functional groups using neural networks

NASA Technical Reports Server (NTRS)

Bell, S.; Nazarov, E.; Wang, Y. F.; Eiceman, G. A.

1999-01-01

Neural networks were trained using whole ion mobility spectra from a standardized database of 3137 spectra for 204 chemicals at various concentrations. Performance of the network was measured by the success of classification into ten chemical classes. Eleven stages for evaluation of spectra and of spectral pre-processing were employed and minimums established for response thresholds and spectral purity. After optimization of the database, network, and pre-processing routines, the fraction of successful classifications by functional group was 0.91 throughout a range of concentrations. Network classification relied on a combination of features, including drift times, number of peaks, relative intensities, and other factors apparently including peak shape. The network was opportunistic, exploiting different features within different chemical classes. Application of neural networks in a two-tier design where chemicals were first identified by class and then individually eliminated all but one false positive out of 161 test spectra. These findings establish that ion mobility spectra, even with low resolution instrumentation, contain sufficient detail to permit the development of automated identification systems.

Content-Based Covert Group Detection in Social Networks

DTIC Science & Technology

2017-09-06

these features to learn a model that could be applied to the holdout set. This model was then used to test on the remaining posts . Accuracy: 51.4...Content-based Covert Group Detection in Social Networks The views, opinions and/or findings contained in this report are those of the author(s) and...should not contrued as an official Department of the Army position, policy or decision, unless so designated by other documentation. 9. SPONSORING

Using social networking to understand social networks: analysis of a mobile phone closed user group used by a Ghanaian health team.

PubMed

Kaonga, Nadi Nina; Labrique, Alain; Mechael, Patricia; Akosah, Eric; Ohemeng-Dapaah, Seth; Sakyi Baah, Joseph; Kodie, Richmond; Kanter, Andrew S; Levine, Orin

2013-04-03

The network structure of an organization influences how well or poorly an organization communicates and manages its resources. In the Millennium Villages Project site in Bonsaaso, Ghana, a mobile phone closed user group has been introduced for use by the Bonsaaso Millennium Villages Project Health Team and other key individuals. No assessment on the benefits or barriers of the use of the closed user group had been carried out. The purpose of this research was to make the case for the use of social network analysis methods to be applied in health systems research--specifically related to mobile health. This study used mobile phone voice records of, conducted interviews with, and reviewed call journals kept by a mobile phone closed user group consisting of the Bonsaaso Millennium Villages Project Health Team. Social network analysis methodology complemented by a qualitative component was used. Monthly voice data of the closed user group from Airtel Bharti Ghana were analyzed using UCINET and visual depictions of the network were created using NetDraw. Interviews and call journals kept by informants were analyzed using NVivo. The methodology was successful in helping identify effective organizational structure. Members of the Health Management Team were the more central players in the network, rather than the Community Health Nurses (who might have been expected to be central). Social network analysis methodology can be used to determine the most productive structure for an organization or team, identify gaps in communication, identify key actors with greatest influence, and more. In conclusion, this methodology can be a useful analytical tool, especially in the context of mobile health, health services, and operational and managerial research.

Using Social Networking to Understand Social Networks: Analysis of a Mobile Phone Closed User Group Used by a Ghanaian Health Team

PubMed Central

Akosah, Eric; Ohemeng-Dapaah, Seth; Sakyi Baah, Joseph; Kanter, Andrew S

2013-01-01

Background The network structure of an organization influences how well or poorly an organization communicates and manages its resources. In the Millennium Villages Project site in Bonsaaso, Ghana, a mobile phone closed user group has been introduced for use by the Bonsaaso Millennium Villages Project Health Team and other key individuals. No assessment on the benefits or barriers of the use of the closed user group had been carried out. Objective The purpose of this research was to make the case for the use of social network analysis methods to be applied in health systems research—specifically related to mobile health. Methods This study used mobile phone voice records of, conducted interviews with, and reviewed call journals kept by a mobile phone closed user group consisting of the Bonsaaso Millennium Villages Project Health Team. Social network analysis methodology complemented by a qualitative component was used. Monthly voice data of the closed user group from Airtel Bharti Ghana were analyzed using UCINET and visual depictions of the network were created using NetDraw. Interviews and call journals kept by informants were analyzed using NVivo. Results The methodology was successful in helping identify effective organizational structure. Members of the Health Management Team were the more central players in the network, rather than the Community Health Nurses (who might have been expected to be central). Conclusions Social network analysis methodology can be used to determine the most productive structure for an organization or team, identify gaps in communication, identify key actors with greatest influence, and more. In conclusion, this methodology can be a useful analytical tool, especially in the context of mobile health, health services, and operational and managerial research. PMID:23552721

Steering operational synergies in terrestrial observation networks: opportunity for advancing Earth system dynamics modelling

NASA Astrophysics Data System (ADS)

Baatz, Roland; Sullivan, Pamela L.; Li, Li; Weintraub, Samantha R.; Loescher, Henry W.; Mirtl, Michael; Groffman, Peter M.; Wall, Diana H.; Young, Michael; White, Tim; Wen, Hang; Zacharias, Steffen; Kühn, Ingolf; Tang, Jianwu; Gaillardet, Jérôme; Braud, Isabelle; Flores, Alejandro N.; Kumar, Praveen; Lin, Henry; Ghezzehei, Teamrat; Jones, Julia; Gholz, Henry L.; Vereecken, Harry; Van Looy, Kris

2018-05-01

Advancing our understanding of Earth system dynamics (ESD) depends on the development of models and other analytical tools that apply physical, biological, and chemical data. This ambition to increase understanding and develop models of ESD based on site observations was the stimulus for creating the networks of Long-Term Ecological Research (LTER), Critical Zone Observatories (CZOs), and others. We organized a survey, the results of which identified pressing gaps in data availability from these networks, in particular for the future development and evaluation of models that represent ESD processes, and provide insights for improvement in both data collection and model integration. From this survey overview of data applications in the context of LTER and CZO research, we identified three challenges: (1) widen application of terrestrial observation network data in Earth system modelling, (2) develop integrated Earth system models that incorporate process representation and data of multiple disciplines, and (3) identify complementarity in measured variables and spatial extent, and promoting synergies in the existing observational networks. These challenges lead to perspectives and recommendations for an improved dialogue between the observation networks and the ESD modelling community, including co-location of sites in the existing networks and further formalizing these recommendations among these communities. Developing these synergies will enable cross-site and cross-network comparison and synthesis studies, which will help produce insights around organizing principles, classifications, and general rules of coupling processes with environmental conditions.

A Demonstration Marine Biodiversity Observation Network (MBON): Understanding Marine Life and its Role in Maintaining Ecosystem Services

NASA Astrophysics Data System (ADS)

Muller-Karger, F. E.; Iken, K.; Miller, R. J.; Duffy, J. E.; Chavez, F.; Montes, E.

2016-02-01

The U.S. Federal government (NOAA, NASA, BOEM, and the Smithsonian Institution), academic researchers, and private partners are laying the foundation for a Marine Biodiversity Observation Network (MBON). The goals of the network are to: 1) Observe and understand life, from microbes to whales, in different coastal and continental shelf habitats; 2) Define an efficient set of observations required for implementing a useful MBON; 3) Develop technology for biodiversity assessments including emerging environmental DNA (eDNA), remote sensing, and image analysis methods to coordinate with classical sampling; 4) Integrate and synthesize information in coordination with the Integrated Ocean Observing System (IOOS), the international Group on Earth Observations Biodiversity Observation Network(GEO BON), and the Ocean Biogeographic Information System (OBIS) sponsored by UNESCO's Intergovernmental Oceanographic Commission (IOC); and 5) Understand the linkages between marine biodiversity, ecosystem processes, and the social-economic context of a region. Pilot projects have been implemented within three NOAA National Marine Sanctuaries (Florida Keys, Monterey Bay, and Channel Islands), the wider Santa Barbara Channel, in the Chukchi Sea, and through the Smithsonian's Tennenbaum Marine Observatories Network (TMON) at several sites in the U.S. and collaborating countries. Together, these MBON sites encompass a wide range of marine environments, including deep sea, continental shelves, and coastal habitats including estuaries, wetlands, and coral reefs. The present MBON partners are open to growth of the MBON through additional collaborations. Given these initiatives, GEO BON is proposing an MBON effort that spans from pole to pole, with a pathfinder effort among countries in the Americas. By specializing in coastal ecosystems—where marine biodiversity and people are concentrated and interact most—the MBON and TMON initiatives aim to provide policymakers with the science to

Social management of laboratory rhesus macaques housed in large groups using a network approach: A review.

PubMed

McCowan, Brenda; Beisner, Brianne; Hannibal, Darcy

2017-12-07

Biomedical facilities across the nation and worldwide aim to develop cost-effective methods for the reproductive management of macaque breeding groups, typically by housing macaques in large, multi-male multi-female social groups that provide monkey subjects for research as well as appropriate socialization for their psychological well-being. One of the most difficult problems in managing socially housed macaques is their propensity for deleterious aggression. From a management perspective, deleterious aggression (as opposed to less intense aggression that serves to regulate social relationships) is undoubtedly the most problematic behavior observed in group-housed macaques, which can readily escalate to the degree that it causes social instability, increases serious physical trauma leading to group dissolution, and reduces psychological well-being. Thus for both welfare and other management reasons, aggression among rhesus macaques at primate centers and facilities needs to be addressed with a more proactive approach.Management strategies need to be instituted that maximize social housing while also reducing problematic social aggression due to instability using efficacious methods for detection and prevention in the most cost effective manner. Herein we review a new proactive approach using social network analysis to assess and predict deleterious aggression in macaque groups. We discovered three major pathways leading to instability, such as unusually high rates and severity of trauma and social relocations.These pathways are linked either directly or indirectly to network structure in rhesus macaque societies. We define these pathways according to the key intrinsic and extrinsic variables (e.g., demographic, genetic or social factors) that influence network and behavioral measures of stability (see Fig. 1). They are: (1) presence of natal males, (2) matrilineal genetic fragmentation, and (3) the power structure and conflict policing behavior supported by this

White matter fiber integrity of the saccadic eye movement network differs between schizophrenia and healthy groups.

PubMed

Schaeffer, David J; Rodrigue, Amanda L; Burton, Courtney R; Pierce, Jordan E; Murphy, Megan N; Clementz, Brett A; McDowell, Jennifer E

2017-12-01

Recent diffusion tensor imaging (DTI) studies suggest that altered white matter fiber integrity is a pathophysiological feature of schizophrenia. Lower white matter integrity is associated with poor cognitive control, a characteristic of schizophrenia that can be measured using antisaccade tasks. Although the functional neural correlates of poor antisaccade performance have been well documented, fewer studies have investigated the extent to which white matter fibers connecting the functional nodes of this network contribute to antisaccade performance. The aim of the present study was to assess the white matter structural integrity of fibers connecting two functional nodes (putamen and medial frontal eye fields) of the saccadic eye movement network implicated in poor antisaccade performance in schizophrenia. To evaluate white matter integrity, DTI was acquired on subjects with schizophrenia and two comparison groups: (a) behaviorally matched healthy comparison subjects with low levels of cognitive control (LCC group), and (b) healthy subjects with high levels of cognitive control (HCC group). White matter fibers were tracked between functional regions of interest generated from antisaccade fMRI activation maps, and measures of diffusivity were quantified. The results demonstrated lower white matter integrity in the schizophrenia group than in the HCC group, but not the LCC group who showed similarly poor cognitive control performance. Overall, the results suggest that these alterations are not specific to the disease process of schizophrenia, but may rather be a function of uncontrolled cognitive factors that are concomitant with the disease but also observed in some healthy people. © 2017 Society for Psychophysiological Research.

ROSAT observations of compact groups of galaxies

NASA Technical Reports Server (NTRS)

Pildis, Rachel A.; Bregman, Joel N.; Evrard, August E.

1995-01-01

We have systematically analyzed a sample of 13 new and archival ROSAT Position Sensitive Proportional Counter (PSPC) observations of compact groups of galaxies: 12 Hickson compact groups plus the NCG 2300 group. We find that approximately two-thirds of the groups have extended X-ray emission and, in four of these, the emission is resolved into diffuse emission from gas at a temperature of kT approximately 1 keV in the group potential. All but one of the groups with extended emission have a spiral fraction of less than 50%. The baryon fraction of groups with diffuse emission is 5%-19%, similar to the values in clusters of galaxies. However, with a single exception (HCG 62), the gas-to-stellar mass ratio in our groups has a median value near 5%, somewhat greater than the values for individual early-type galaxies and two orders of magnitude than in clusters of galaxies. The X-ray luminosities of individual group galaxies are comparable to those of similar field galaxies, although the L(sub X)-L(sub B) relation for early-type galaxies may be flatter in compact groups than in the field.

Associations of Bcl-2 rs956572 genotype groups in the structural covariance network in early-stage Alzheimer's disease.

PubMed

Chang, Chiung-Chih; Chang, Ya-Ting; Huang, Chi-Wei; Tsai, Shih-Jen; Hsu, Shih-Wei; Huang, Shu-Hua; Lee, Chen-Chang; Chang, Wen-Neng; Lui, Chun-Chung; Lien, Chia-Yi

2018-02-08

Alzheimer's disease (AD) is a complex neurodegenerative disease, and genetic differences may mediate neuronal degeneration. In humans, a single-nucleotide polymorphism in the B-cell chronic lymphocytic leukemia/lymphoma-2 (Bcl-2) gene, rs956572, has been found to significantly modulate Bcl-2 protein expression in the brain. The Bcl-2 AA genotype has been associated with reduced Bcl-2 levels and lower gray matter volume in healthy populations. We hypothesized that different Bcl-2 genotype groups may modulate large-scale brain networks that determine neurobehavioral test scores. Gray matter structural covariance networks (SCNs) were constructed in 104 patients with AD using T1-weighted magnetic resonance imaging with seed-based correlation analysis. The patients were stratified into two genotype groups on the basis of Bcl-2 expression (G carriers, n = 76; A homozygotes, n = 28). Four SCNs characteristic of AD were constructed from seeds in the default mode network, salience network, and executive control network, and cognitive test scores served as the major outcome factor. For the G carriers, influences of the SCNs were observed mostly in the default mode network, of which the peak clusters anchored by the posterior cingulate cortex seed determined the cognitive test scores. In contrast, genetic influences in the A homozygotes were found mainly in the executive control network, and both the dorsolateral prefrontal cortex seed and the interconnected peak clusters were correlated with the clinical scores. Despite a small number of cases, the A homozygotes showed greater covariance strength than the G carriers among all four SCNs. Our results suggest that the Bcl-2 rs956572 polymorphism is associated with different strengths of structural covariance in AD that determine clinical outcomes. The greater covariance strength in the four SCNs shown in the A homozygotes suggests that different Bcl-2 polymorphisms play different modulatory roles.

GEO Carbon and GHG Initiative Task 3: Optimizing in-situ measurements of essential carbon cycle variables across observational networks

NASA Astrophysics Data System (ADS)

Durden, D.; Muraoka, H.; Scholes, R. J.; Kim, D. G.; Loescher, H. W.; Bombelli, A.

2017-12-01

The development of an integrated global carbon cycle observation system to monitor changes in the carbon cycle, and ultimately the climate system, across the globe is of crucial importance in the 21stcentury. This system should be comprised of space and ground-based observations, in concert with modelling and analysis, to produce more robust budgets of carbon and other greenhouse gases (GHGs). A global initiative, the GEO Carbon and GHG Initiative, is working within the framework of Group on Earth Observations (GEO) to promote interoperability and provide integration across different parts of the system, particularly at domain interfaces. Thus, optimizing the efforts of existing networks and initiatives to reduce uncertainties in budgets of carbon and other GHGs. This is a very ambitious undertaking; therefore, the initiative is separated into tasks to provide actionable objectives. Task 3 focuses on the optimization of in-situ observational networks. The main objective of Task 3 is to develop and implement a procedure for enhancing and refining the observation system for identified essential carbon cycle variables (ECVs) that meets user-defined specifications at minimum total cost. This work focuses on the outline of the implementation plan, which includes a review of essential carbon cycle variables and observation technologies, mapping the ECVs performance, and analyzing gaps and opportunities in order to design an improved observing system. A description of the gap analysis of in-situ observations that will begin in the terrestrial domain to address issues of missing coordination and large spatial gaps, then extend to ocean and atmospheric observations in the future, will be outlined as the subsequent step to landscape mapping of existing observational networks.

Social Norms about a Health Issue in Work Group Networks

PubMed Central

Frank, Lauren B.

2015-01-01

The purpose of this study is to advance theorizing about how small groups understand health issues through the use of social network analysis. To achieve this goal, an adapted cognitive social structure examines group social norms around a specific health issue, H1N1 flu prevention. As predicted, individual’s attitudes, self-efficacy, and perceived social norms were each positively associated with behavioral intentions for at least one of the H1N1 health behaviors studied. Moreover, collective norms of the whole group were also associated with behavioral intentions, even after controlling for how individual group members perceive those norms. For members of work groups in which pairs were perceived to agree in their support for H1N1 vaccination, the effect of individually perceived group norms on behavioral intentions was stronger than for groups with less agreement. PMID:26389934

The African American Student Network: An Informal Networking Group as a Therapeutic Intervention for Black College Students on a Predominantly White Campus

ERIC Educational Resources Information Center

Grier-Reed, Tabitha

2013-01-01

Informal support networks as opposed to formal mental health counseling may represent a culture-specific, indigenous style of coping for Black college students. Using the African American Student Network (or as students refer to it AFAM), this article comments on the potential of an informal networking group as a culturally sensitive therapeutic…

Visual sensory networks and effective information transfer in animal groups.

PubMed

Strandburg-Peshkin, Ariana; Twomey, Colin R; Bode, Nikolai W F; Kao, Albert B; Katz, Yael; Ioannou, Christos C; Rosenthal, Sara B; Torney, Colin J; Wu, Hai Shan; Levin, Simon A; Couzin, Iain D

2013-09-09

Social transmission of information is vital for many group-living animals, allowing coordination of motion and effective response to complex environments. Revealing the interaction networks underlying information flow within these groups is a central challenge. Previous work has modeled interactions between individuals based directly on their relative spatial positions: each individual is considered to interact with all neighbors within a fixed distance (metric range), a fixed number of nearest neighbors (topological range), a 'shell' of near neighbors (Voronoi range), or some combination (Figure 1A). However, conclusive evidence to support these assumptions is lacking. Here, we employ a novel approach that considers individual movement decisions to be based explicitly on the sensory information available to the organism. In other words, we consider that while spatial relations do inform interactions between individuals, they do so indirectly, through individuals' detection of sensory cues. We reconstruct computationally the visual field of each individual throughout experiments designed to investigate information propagation within fish schools (golden shiners, Notemigonus crysoleucas). Explicitly considering visual sensing allows us to more accurately predict the propagation of behavioral change in these groups during leadership events. Furthermore, we find that structural properties of visual interaction networks differ markedly from those of metric and topological counterparts, suggesting that previous assumptions may not appropriately reflect information flow in animal groups. Copyright © 2013 Elsevier Ltd. All rights reserved.

Effects of a Group Intervention on the Career Network Ties of Finnish Adolescents

ERIC Educational Resources Information Center

Jokisaari, Markku; Vuori, Jukka

2011-01-01

The authors evaluated how a group-based career intervention affected career network ties among Finnish adolescents as they made educational choices and prepared for their transition to secondary education. They examined the career-related network ties of 868 students during their last year in comprehensive school (junior high school) in a…

New York hospital group striving for brand recognition. HealthStar Network.

PubMed

Herreria, J

1998-01-01

HealthStar Network established a new concept in its eastern market--a group of hospitals forming one association. Marketers of HealthStar are conducting a branding campaign to distinguish individual expertise under one umbrella company.

Successful twilight observations of eta-Aquarid shower in "Unified Churyumov Network"

NASA Astrophysics Data System (ADS)

Steklov, E. A.; Kruchynenko, V. G.; Steklov, A. F.; Vidmachenko, A. P.; Dashkiev, G. N.

2017-05-01

On March 29 2013, on the left bank of the Dnieper in Kiev, young amateur astronomers, in the evening twilight, observed almost simultaneous invasion of three large fragments of meteoroid. Then four images were obtained. It was proposed to create a "Club of Fireball tracks observers". As a result, in Kiev region a network of photo hunters on twilight and daytime tracks of dangerous invasions into the sky above us - was formed. This "Unified Churyumov Network" has been in operation for four years. From April 19 to May 28, we are actively observing a meteor shower of eta-Aquarids. The particles of this meteor shower are fragments of nucleus of the famous Halley comet. In May 10 at the same time four observers photographed very interesting trail of invasion from four points of Kiev. In the last few years, the authors have registered several hundred small and dozens of larger invasions in the sky over Kiev and Kiev region.

Evaluation on surface current observing network of high frequency ground wave radars in the Gulf of Thailand

NASA Astrophysics Data System (ADS)

Yin, Xunqiang; Shi, Junqiang; Qiao, Fangli

2018-05-01

Due to the high cost of ocean observation system, the scientific design of observation network becomes much important. The current network of the high frequency radar system in the Gulf of Thailand has been studied using a three-dimensional coastal ocean model. At first, the observations from current radars have been assimilated into this coastal model and the forecast results have improved due to the data assimilation. But the results also show that further optimization of the observing network is necessary. And then, a series of experiments were carried out to assess the performance of the existing high frequency ground wave radar surface current observation system. The simulated surface current data in three regions were assimilated sequentially using an efficient ensemble Kalman filter data assimilation scheme. The experimental results showed that the coastal surface current observation system plays a positive role in improving the numerical simulation of the currents. Compared with the control experiment without assimilation, the simulation precision of surface and subsurface current had been improved after assimilated the surface currents observed at current networks. However, the improvement for three observing regions was quite different and current observing network in the Gulf of Thailand is not effective and a further optimization is required. Based on these evaluations, a manual scheme has been designed by discarding the redundant and inefficient locations and adding new stations where the performance after data assimilation is still low. For comparison, an objective scheme based on the idea of data assimilation has been obtained. Results show that all the two schemes of observing network perform better than the original network and optimal scheme-based data assimilation is much superior to the manual scheme that based on the evaluation of original observing network in the Gulf of Thailand. The distributions of the optimal network of radars could be a

Harmonising and semantically linking key variables from in-situ observing networks of an Integrated Atlantic Ocean Observing System, AtlantOS

NASA Astrophysics Data System (ADS)

Darroch, Louise; Buck, Justin

2017-04-01

Atlantic Ocean observation is currently undertaken through loosely-coordinated, in-situ observing networks, satellite observations and data management arrangements at regional, national and international scales. The EU Horizon 2020 AtlantOS project aims to deliver an advanced framework for the development of an Integrated Atlantic Ocean Observing System that strengthens the Global Ocean Observing System (GOOS) and contributes to the aims of the Galway Statement on Atlantic Ocean Cooperation. One goal is to ensure that data from different and diverse in-situ observing networks are readily accessible and useable to a wider community, including the international ocean science community and other stakeholders in this field. To help achieve this goal, the British Oceanographic Data Centre (BODC) produced a parameter matrix to harmonise data exchange, data flow and data integration for the key variables acquired by multiple in-situ AtlantOS observing networks such as ARGO, Seafloor Mapping and OceanSITES. Our solution used semantic linking of controlled vocabularies and metadata for parameters that were "mappable" to existing EU and international standard vocabularies. An AtlantOS Essential Variables list of terms (aggregated level) based on Global Climate Observing System (GCOS) Essential Climate Variables (ECV), GOOS Essential Ocean Variables (EOV) and other key network variables was defined and published on the Natural Environment Research Council (NERC) Vocabulary Server (version 2.0) as collection A05 (http://vocab.nerc.ac.uk/collection/A05/current/). This new vocabulary was semantically linked to standardised metadata for observed properties and units that had been validated by the AtlantOS community: SeaDataNet parameters (P01), Climate and Forecast (CF) Standard Names (P07) and SeaDataNet units (P06). Observed properties were mapped to biological entities from the internationally assured AphiaID from the WOrld Register of Marine Species (WoRMS), http

Network Performance Measurements for NASA's Earth Observation System

NASA Technical Reports Server (NTRS)

Loiacono, Joe; Gormain, Andy; Smith, Jeff

2004-01-01

NASA's Earth Observation System (EOS) Project studies all aspects of planet Earth from space, including climate change, and ocean, ice, land, and vegetation characteristics. It consists of about 20 satellite missions over a period of about a decade. Extensive collaboration is used, both with other US. agencies (e.g., National Oceanic and Atmospheric Administration (NOA), United States Geological Survey (USGS), Department of Defense (DoD), and international agencies (e.g., European Space Agency (ESA), Japan Aerospace Exploration Agency (JAXA)), to improve cost effectiveness and obtain otherwise unavailable data. Scientific researchers are located at research institutions worldwide, primarily government research facilities and research universities. The EOS project makes extensive use of networks to support data acquisition, data production, and data distribution. Many of these functions impose requirements on the networks, including throughput and availability. In order to verify that these requirements are being met, and be pro-active in recognizing problems, NASA conducts on-going performance measurements. The purpose of this paper is to examine techniques used by NASA to measure the performance of the networks used by EOSDIS (EOS Data and Information System) and to indicate how this performance information is used.

Experimental observation of chimera and cluster states in a minimal globally coupled network

NASA Astrophysics Data System (ADS)

Hart, Joseph D.; Bansal, Kanika; Murphy, Thomas E.; Roy, Rajarshi

2016-09-01

A "chimera state" is a dynamical pattern that occurs in a network of coupled identical oscillators when the symmetry of the oscillator population is broken into synchronous and asynchronous parts. We report the experimental observation of chimera and cluster states in a network of four globally coupled chaotic opto-electronic oscillators. This is the minimal network that can support chimera states, and our study provides new insight into the fundamental mechanisms underlying their formation. We use a unified approach to determine the stability of all the observed partially synchronous patterns, highlighting the close relationship between chimera and cluster states as belonging to the broader phenomenon of partial synchronization. Our approach is general in terms of network size and connectivity. We also find that chimera states often appear in regions of multistability between global, cluster, and desynchronized states.

Experimental observation of chimera and cluster states in a minimal globally coupled network

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

Hart, Joseph D.; Department of Physics, University of Maryland, College Park, Maryland 20742; Bansal, Kanika

A “chimera state” is a dynamical pattern that occurs in a network of coupled identical oscillators when the symmetry of the oscillator population is broken into synchronous and asynchronous parts. We report the experimental observation of chimera and cluster states in a network of four globally coupled chaotic opto-electronic oscillators. This is the minimal network that can support chimera states, and our study provides new insight into the fundamental mechanisms underlying their formation. We use a unified approach to determine the stability of all the observed partially synchronous patterns, highlighting the close relationship between chimera and cluster states as belongingmore » to the broader phenomenon of partial synchronization. Our approach is general in terms of network size and connectivity. We also find that chimera states often appear in regions of multistability between global, cluster, and desynchronized states.« less

The uses of an observation team with a parent support group.

PubMed

O'Brien, P J

1994-04-01

This brief report examines the uses of an Observation Team with a Parent Support Group. In particular, attention is placed on the idea of the Observation Team acting as a Reflecting Team in the final session of the group's life. Using the Observation Team in this manner has evolved from an amalgamation of ideas from family therapy and group therapy theory.

Key observations from the NHLBI Asthma Clinical Research Network.

PubMed

Szefler, Stanley J; Chinchilli, Vernon M; Israel, Elliot; Denlinger, Loren Clark; Lemanske, Robert F; Calhoun, William; Peters, Stephen P

2012-05-01

The National Heart, Lung and Blood Institute (NHLBI) Asthma Clinical Research Network (ACRN) recently completed its work after 20 years of collaboration as a multicentre clinical trial network. When formed, its stated mission was to perform multiple controlled clinical trials for treating patients with asthma by dispassionately examining new and existing therapies, and to rapidly communicate its findings to the medical community. The ACRN conducted 15 major clinical trials. In addition, clinical data, manual of operations, protocols and template informed consents from all ACRN trials are available via NHLBI BioLINCC (https://biolincc.nhlbi.nih.gov/studies/). This network contributed major insights into the use of inhaled corticosteroids, short-acting and long-acting ß-adrenergic agonists, leukotriene receptor antagonists, and novel agents (tiotropium, colchicine and macrolide antibiotics). They also pioneered studies of the variability in drug response, predictors of treatment response and pharmacogenetics. This review highlights the major research observations from the ACRN that have impacted the current management of asthma.

A Group Neighborhood Average Clock Synchronization Protocol for Wireless Sensor Networks

PubMed Central

Lin, Lin; Ma, Shiwei; Ma, Maode

2014-01-01

Clock synchronization is a very important issue for the applications of wireless sensor networks. The sensors need to keep a strict clock so that users can know exactly what happens in the monitoring area at the same time. This paper proposes a novel internal distributed clock synchronization solution using group neighborhood average. Each sensor node collects the offset and skew rate of the neighbors. Group averaging of offset and skew rate value are calculated instead of conventional point-to-point averaging method. The sensor node then returns compensated value back to the neighbors. The propagation delay is considered and compensated. The analytical analysis of offset and skew compensation is presented. Simulation results validate the effectiveness of the protocol and reveal that the protocol allows sensor networks to quickly establish a consensus clock and maintain a small deviation from the consensus clock. PMID:25120163

The Quasar Network Observations in e-VLBI Mode

NASA Astrophysics Data System (ADS)

Bezrukov, I.; Finkelstein, A.; Ipatov, A.; Kaidanovsky, A.; Mikhailov, A.; Salnikov, A.; Yakovlev, V.

2011-07-01

This paper describes activity of the Institute of Applied Astronomy in developing real-time VLBI-system using high speed digital communication links. Real-time VLBI-technology has been developing at IAA since 2007 when the very first experiment was successfully done with Haystack observatory. All observatories of VLBI-Network Quasar were connected by "last mile" communication channels and via the Internet at 100 Mbps rate. Additional UNIX servers were installed for data buffering. Now e-VLBI sessions are carried out routinely within domestic VLBI-programs for UT1-determination. Observational data of 1-hour sessions are transmitted simultaneously from Svetloe, Zelenchukskaya and Badary observatories to the IAA Data Processing Center in Saint-Petersburg through fiber lines at 50-70 Mbps via Tsunami-UDP protocol. In September 2010 few scans were successfully transmitted from Quasar-Network observatories to Correlator Center at Shanghai observatory and vice-versa from Shanghai observatory to Correlator of RAS. Within these experiments observation data recorded by Mark 5B recorder are transmitted to the buffer server during time interval when an antenna pointed from one source to another. This procedure allows us to reduce total time of obtaining final result by 30%. Now an advanced algorithm for automation of the data transmitting process from the recorder to correlator is developing.

National Marine Sanctuaries as Sentinel Sites for a Demonstration Marine Biodiversity Observation Network (MBON)

NASA Astrophysics Data System (ADS)

Chavez, F.; Montes, E.; Muller-Karger, F. E.; Gittings, S.; Canonico, G.; Kavanaugh, M.; Iken, K.; Miller, R. J.; Duffy, J. E.; Miloslavich, P.

2016-12-01

The U.S. Federal government (NOAA, NASA, BOEM, and the Smithsonian Institution), academic researchers, and private partners in the U.S. and around the world are working on the design and implementation of a Marine Biodiversity Observation Network (MBON). The program is being coordinated internationally with the Group on Earth Observations (GEO BON) and two key Intergovernmental Oceanographic Commission (IOC) programs, namely the Global Ocean Observing System (GOOS) and the Ocean Biogeographic Information System (OBIS). The goal is to monitor changes in marine biodiversity within various geographic settings. In the U.S., demonstration projects include four National Marine Sanctuaries (NMS): Florida Keys, Monterey Bay, Flower Garden Banks, and Channel Islands. The Smithsonian is implementing several programs around the world under the Marine Global Earth Observatory (MarineGEO) partnership, directed by the Smithsonian's Tennenbaum Marine Observatories Network (TMON). The overarching goal is to observe and understand life, from microbes to whales, in different coastal and continental shelf habitats, and its role in maintaining resilient ecosystems. The project also seeks to determine biodiversity baselines in these ecosystems based on time-series observations to assess changes in populations and overall biodiversity over time. Efforts are being made to engage with various countries in the Americas to participate in an MBON Pole to Pole in the Americas initiative proposed by Mexico. We are looking to have other regions organized to conduct similar planning efforts. The present MBON pilot projects encompass a range of marine environments, including deep sea, continental shelves, and coastal habitats including estuaries, wetlands, and coral reefs. The MBON will facilitate and enable regional biodiversity assessments, and contributes to addressing several U.N. Sustainable Development Goals to conserve and sustainably use marine resources, and provide a means for countries

Group consensus control for networked multi-agent systems with communication delays.

PubMed

An, Bao-Ran; Liu, Guo-Ping; Tan, Chong

2018-05-01

This paper investigates group consensus problems in networked multi-agent systems (NMAS) with communication delays. Based on the sed state prediction scheme, the group consensus control protocol is designed to compensate the communication delay actively. In light of algebraic graph theories and matrix theories, necessary and(or) sufficient conditions of group consensus with respect to a given admissible control set are obtained for the NMAS with communication delays under mild assumptions. Finally, simulations are performed to demonstrate the effectiveness of the theoretical results. Copyright © 2018 ISA. All rights reserved.

Let's Face(book) It: Analyzing Interactions in Social Network Groups for Chemistry Learning

ERIC Educational Resources Information Center

Rap, Shelley; Blonder, Ron

2016-01-01

We examined how social network (SN) groups contribute to the learning of chemistry. The main goal was to determine whether chemistry learning could occur in the group discourse. The emphasis was on groups of students in the 11th and 12th grades who learn chemistry in preparation for their final external examination. A total of 1118 discourse…

Memory Transmission in Small Groups and Large Networks: An Agent-Based Model.

PubMed

Luhmann, Christian C; Rajaram, Suparna

2015-12-01

The spread of social influence in large social networks has long been an interest of social scientists. In the domain of memory, collaborative memory experiments have illuminated cognitive mechanisms that allow information to be transmitted between interacting individuals, but these experiments have focused on small-scale social contexts. In the current study, we took a computational approach, circumventing the practical constraints of laboratory paradigms and providing novel results at scales unreachable by laboratory methodologies. Our model embodied theoretical knowledge derived from small-group experiments and replicated foundational results regarding collaborative inhibition and memory convergence in small groups. Ultimately, we investigated large-scale, realistic social networks and found that agents are influenced by the agents with which they interact, but we also found that agents are influenced by nonneighbors (i.e., the neighbors of their neighbors). The similarity between these results and the reports of behavioral transmission in large networks offers a major theoretical insight by linking behavioral transmission to the spread of information. © The Author(s) 2015.

XMM Observations of Low Mass Groups

NASA Technical Reports Server (NTRS)

Davis, David S.

2005-01-01

The contents of this report contains discussion of the two-dimensional XMM-Newton group survey. The analysis of the NGC 2300 and Pavo observations indicated by the azimuthally averaged analysis that the temperature structure is minimal to the NGC2300 system; however, the Pavo system shows signs of a merger in progress. XMM data is used to generate two dimensional maps of the temperature and abundance used to generate maps of pressure and entropy.

Beyond dark and bright: towards a more holistic understanding of inter-group networks.

PubMed

Hejnova, Petra

2010-01-01

Networks are becoming a popular organizational form for structuring human activities. To date, scholars have addressed networks in a variety of fields, including sociology, economics, public administration, criminology, political science, and international security. However, little has been done so far to systematically examine the similarities, differences, and connections between network forms of organization across different academic disciplines. This has important implications for both theory and practice. The lack of attention paid to organizational similarities and differences prevents the exchange of knowledge developed across fields. In turn, policy-makers cannot take full advantage of existing research, and may miss opportunities to improve the work of some networks and combat that of others. To address this gap in the literature, this paper uses the combination of organizational environments and organizational goals to develop a new typology of inter-group networks, and thus improve our understanding of how human behaviour is coordinated through networks.

Performance Analysis of Hierarchical Group Key Management Integrated with Adaptive Intrusion Detection in Mobile ad hoc Networks

DTIC Science & Technology

2016-04-05

applications in wireless networks such as military battlefields, emergency response, mobile commerce , online gaming, and collaborative work are based on the...www.elsevier.com/locate/peva Performance analysis of hierarchical group key management integrated with adaptive intrusion detection in mobile ad hoc...Accepted 19 September 2010 Available online 26 September 2010 Keywords: Mobile ad hoc networks Intrusion detection Group communication systems Group

Estimating interevent time distributions from finite observation periods in communication networks

NASA Astrophysics Data System (ADS)

Kivelä, Mikko; Porter, Mason A.

2015-11-01

A diverse variety of processes—including recurrent disease episodes, neuron firing, and communication patterns among humans—can be described using interevent time (IET) distributions. Many such processes are ongoing, although event sequences are only available during a finite observation window. Because the observation time window is more likely to begin or end during long IETs than during short ones, the analysis of such data is susceptible to a bias induced by the finite observation period. In this paper, we illustrate how this length bias is born and how it can be corrected without assuming any particular shape for the IET distribution. To do this, we model event sequences using stationary renewal processes, and we formulate simple heuristics for determining the severity of the bias. To illustrate our results, we focus on the example of empirical communication networks, which are temporal networks that are constructed from communication events. The IET distributions of such systems guide efforts to build models of human behavior, and the variance of IETs is very important for estimating the spreading rate of information in networks of temporal interactions. We analyze several well-known data sets from the literature, and we find that the resulting bias can lead to systematic underestimates of the variance in the IET distributions and that correcting for the bias can lead to qualitatively different results for the tails of the IET distributions.

Social networking in online support groups for health: how online social networking benefits patients.

PubMed

Chung, Jae Eun

2014-01-01

An increasing number of online support groups (OSGs) have embraced the features of social networking. So far, little is known about how patients use and benefit from these features. By implementing the uses-and-gratifications framework, the author conducted an online survey with current users of OSGs to examine associations among motivation, use of specific features of OSG, and support outcomes. Findings suggest that OSG users make selective use of varied features depending on their needs, and that perceptions of receiving emotional and informational support are associated more with the use of some features than others. For example, those with strong motivation for social interaction use diverse features of OSG and make one-to-one connections with other users by friending. In contrast, those with strong motivation for information seeking limit their use primarily to discussion boards. Results also show that online social networking features, such as friending and sharing of personal stories on blogs, are helpful in satisfying the need for emotional support. The present study sheds light on online social networking features in the context of health-related OSGs and provides practical lessons on how to improve the capacity of OSGs to serve the needs of their users.

First results of mapping sporadic E with a passive observing network

NASA Astrophysics Data System (ADS)

Rice, D. D.; Sojka, J. J.; Eccles, J. V.; Raitt, J. W.; Brady, J. J.; Hunsucker, R. D.

2011-12-01

Sporadic E (Es) can have dramatic effects on communications in the HF and low VHF range, producing over-the-horizon propagation for signals normally restricted to line-of-sight, and sometimes blocking F region propagation of signals in the lower HF range. Measuring the E region winds believed to produce Es is difficult, and no practical means of predicting Es occurrence currently exists other than statistical models. We describe a low-cost observing network based on software-controlled receivers that continuously watches for Es in near-real time using oblique HF propagation from existing transmitters. Results from an 11-day pilot campaign in July 2008 demonstrated that even a limited number of receivers in the network can readily determine the presence and extent of Es patches. These observations indicate that Es often develops quickly over regions of several hundred kilometers rather than gradually drifting across an area. These widespread Es “blooms” have been observed near winter solstice and occasionally at other times of the year; their lifetime depends on the season but can be several hours during the summer. The current network allows the extent of Es in portions of North America to be evaluated: the geographical distribution of Es and bounds on the density of the layer are inferred from its effects on the ionospheric maximum usable frequency (MUF). This study demonstrates quantitatively that Es mapping can provide information about Es layer geographical growth and decay. The observed sudden widespread Es blooms are space weather events that can have significant impact on HF/lower VHF communications and propagation model predictions.

Observations of Adolescent Peer Group Interactions as a Function of Within- and Between-Group Centrality Status

ERIC Educational Resources Information Center

Ellis, Wendy E.; Dumas, Tara M.; Mahdy, Jasmine C.; Wolfe, David A.

2012-01-01

Observations of adolescent (n = 258; M age = 15.45) peer group triads (n = 86) were analyzed to identify conversation and interaction styles as a function of within-group and between-group centrality status. Group members' discussions about hypothetical dilemmas were coded for agreements, disagreements, commands, and opinions. Interactions during…

Strategy of thunderstorm measurement with super dense ground-based observation network

NASA Astrophysics Data System (ADS)

Takahashi, Y.; Sato, M.

2014-12-01

It's not easy to understand the inside structure and developing process of thunderstorm only with existing meteorological instruments since its horizontal extent of the storm cell is sometimes smaller than an order of 10 km while one of the densest ground network in Japan, AMEDAS, consists of sites located every 17 km in average and the resolution of meteorological radar is 1-2 km in general. Even the X-band radar realizes the resolution of 250 m or larger. Here we suggest a new super dense observation network with simple and low cost sensors that can be used for measurement both of raindrop and vertical electric field change caused by cloud-to-ground lightning discharge. This sensor consists of two aluminum plates with a diameter of 10-20 cm. We carried out an observation campaign in summer of 2013 in the foothills of Mt. Yastugatake, Yamanashi and Nagano prefectures in Japan, installing 6 plate-type sensors at a distance of about 4 km. Horizontal location, height and charge amount of each lightning discharge are estimated successfully based on the information of electric field changes at several observing sites. Moreover, it was found that the thunderstorm has a very narrow structure well smaller than 300 m that cannot be measured by any other ways, counting the positive and negative pulses caused by attachment of raindrop to the sensor plate, respectively. We plan to construct a new super dense observation network in the north Kanto region, Japan, where the lightning activity is most prominent in summer Japan, distributing more than several tens of sensors at every 4 km or shorter, such as an order of 100 m at minimum. This kind of new type network will reveal the unknown fine structures of thunderstorms and open the door for constructing real time alert system of torrential rainfall and lightning stroke especially in the city area.

Observation interventions as a means to manipulate collective efficacy in groups.

PubMed

Bruton, Adam M; Mellalieu, Stephen D; Shearer, David A

2014-02-01

The purpose of this multistudy investigation was to examine observation as an intervention for the manipulation of individual collective efficacy beliefs. Study 1 compared the effects of positive, neutral, and negative video footage of practice trials from an obstacle course task on collective efficacy beliefs in assigned groups. The content of the observation intervention (i.e., positive, neutral, and negative video footage) significantly influenced the direction of change in collective efficacy (p < .05). Study 2 assessed the influence of content familiarity (own team/sport vs. unfamiliar team/sport) on individual collective efficacy perceptions when observing positive footage of competitive basketball performance. Collective efficacy significantly increased for both the familiar and unfamiliar conditions postintervention, with the largest increase for the familiar condition (p < .05). The studies support the use of observation as an intervention to enhance individual perceptions of collective efficacy in group-based activities. The findings suggest that observations of any group displaying positive group characteristics are likely to increase collective efficacy beliefs; however, observation of one's own team leads to the greatest increases.

Estimating surface soil moisture from SMAP observations using a neural network technique

USDA-ARS?s Scientific Manuscript database

A Neural Network (NN) algorithm was developed to estimate global surface soil moisture for April 2015 to June 2016 with a 2-3 day repeat frequency using passive microwave observations from the Soil Moisture Active Passive (SMAP) satellite, surface soil temperatures from the NASA Goddard Earth Observ...

Optimal observation network design for conceptual model discrimination and uncertainty reduction

NASA Astrophysics Data System (ADS)

Pham, Hai V.; Tsai, Frank T.-C.

2016-02-01

This study expands the Box-Hill discrimination function to design an optimal observation network to discriminate conceptual models and, in turn, identify a most favored model. The Box-Hill discrimination function measures the expected decrease in Shannon entropy (for model identification) before and after the optimal design for one additional observation. This study modifies the discrimination function to account for multiple future observations that are assumed spatiotemporally independent and Gaussian-distributed. Bayesian model averaging (BMA) is used to incorporate existing observation data and quantify future observation uncertainty arising from conceptual and parametric uncertainties in the discrimination function. In addition, the BMA method is adopted to predict future observation data in a statistical sense. The design goal is to find optimal locations and least data via maximizing the Box-Hill discrimination function value subject to a posterior model probability threshold. The optimal observation network design is illustrated using a groundwater study in Baton Rouge, Louisiana, to collect additional groundwater heads from USGS wells. The sources of uncertainty creating multiple groundwater models are geological architecture, boundary condition, and fault permeability architecture. Impacts of considering homoscedastic and heteroscedastic future observation data and the sources of uncertainties on potential observation areas are analyzed. Results show that heteroscedasticity should be considered in the design procedure to account for various sources of future observation uncertainty. After the optimal design is obtained and the corresponding data are collected for model updating, total variances of head predictions can be significantly reduced by identifying a model with a superior posterior model probability.

Enabling New and More Transparent Science via DataONE—a Virtual Data Observation Network for Earth (Invited)

NASA Astrophysics Data System (ADS)

Michener, W.

2010-12-01

Addressing grand environmental science challenges requires unprecedented access to easily understood data that cross the breadth of temporal, spatial, and thematic scales. From a scientist’s perspective, the big challenges lie in discovering the relevant data, dealing with extreme data heterogeneity, and converting data to information and knowledge. Addressing these challenges requires new approaches for managing, preserving, analyzing, and sharing data. DataONE is designed to be the foundation of new innovative environmental research that addresses questions of relevance to science and society. DataONE will ensure preservation and access to multi-scale, multi-discipline, and multi-national data. Operationally, DataONE encompasses a distributed global network of Member Nodes (i.e., data repositories) that provide open and persistent access to well-described and easily discovered Earth observational data. In addition, a smaller number of Coordinating Nodes (i.e., metadata repositories and service centers) support network-wide services such as data replication and access to an array of enabling tools. DataONE’s objectives are to: make biological data available from the genome to the ecosystem; make environmental data available from atmospheric, ecological, hydrological, and oceanographic sources; provide secure and long-term preservation and access; and engage scientists, land-managers, policy makers, students, educators, and the public through logical access and intuitive visualizations. The foundation for excellence of DataONE is the established collaboration among participating organizations that have multi-decade expertise in a wide range of fields that includes: existing archive initiatives, libraries, environmental observing systems and research networks, data and information management, science synthesis centers, and professional societies. DataONE is a means to serve a broad range of science domains directly and indirectly through interoperability with

An Observational Study of Group Waterpipe Use in a Natural Environment

PubMed Central

2014-01-01

Introduction: To date research on tobacco smoking with a waterpipe (hookah, narghile, and shisha) has focused primarily on the individual user in a laboratory setting. Yet, waterpipe tobacco smoking is often a social practice that occurs in cafés, homes, and other natural settings. This observational study examined the behavior of waterpipe tobacco smokers and the social and contextual features of waterpipe use among groups in their natural environment. Methods: Trained observers visited urban waterpipe cafés on multiple occasions during an 8-month period. Observations of 241 individual users in naturally formed groups were made on smoking topography (puff frequency, duration, and interpuff interval [IPI]) and engagement in other activities (e.g., food and drink consumption, other tobacco use, and media viewing). Results: Most users were male in group sizes of 3–4 persons, on average, and each table had 1 waterpipe, on average. The predominant social features during observational periods were conversation and nonalcoholic drinking. Greater puff number was associated with smaller group sizes and more waterpipes per group, while longer IPIs were associated with larger group sizes and fewer waterpipes per group. Additionally, greater puff frequency was observed during media viewing and in the absence of other tobacco use. Conclusions: Overall, the results suggest that waterpipe smoking behavior is affected by group size and by certain social activities. Discussion focuses on how these findings enhance our understanding of factors that may influence exposure to waterpipe tobacco smoke toxicants in naturalistic environments. PMID:23943842

The European Marine Observing Network and the development of an Integrated European Ocean Observing System. An EuroGOOS perspective

NASA Astrophysics Data System (ADS)

Fernandez, Vicente; Gorringe, Patrick; Nolan, Glenn

2016-04-01

The ocean benefits many sectors of society, being the biggest reservoir of heat, water, carbon and oxygen and playing a fundamental role regulating the earth's climate. We rely on the oceans for food, transport, energy and recreation. Therefore, a sustained marine observation network is crucial to further our understanding of the oceanic environment and to supply scientific data to meet society's need. Marine data and observations in Europe, collected primarily by state governmental agencies, is offered via five Regional Operational Oceanographic Systems (ROOS) within the context of EuroGOOS (http://www.eurogos.eu), an International Non-Profit Association of national governmental agencies and research organizations (40 members from 19 member states) committed to European-scale operational oceanography within the context of the Intergovernmental Global Ocean Observing System (GOOS). Strong cooperation within these regions, enabling the involvement of additional partners and countries, forms the basis of EuroGOOS work. Ocean data collected from different type of sensors (e.g. moored buoys, tide gauges, Ferrybox systems, High Frequency radars, gliders and profiling floats) is accessible to scientist and other end users through data portals and initiatives such as the European Marine Observations and Data Network (EMODnet) (www.emodnet.eu) and the Copernicus Marine Service Copernicus (www.copernicus.eu). Although a relatively mature European ocean observing capability already exists and its well-coordinated at European level, some gaps have been identified, for example the demand for ecosystem products and services, or the case that biogeochemical observations are still relatively sparse particularly in coastal and shelf seas. Assessing gaps based on the capacity of the observing system to answer key societal challenges e.g. site suitability for aquaculture and ocean energy, oil spill response and contextual oceanographic products for fisheries and ecosystems is still

Action observation network in childhood: a comparative fMRI study with adults.

PubMed

Biagi, Laura; Cioni, Giovanni; Fogassi, Leonardo; Guzzetta, Andrea; Sgandurra, Giuseppina; Tosetti, Michela

2016-11-01

Very little is known about the action observation network and the mirror neuron system (AON/MNS) in children and its age-related properties compared with those observed in adults. In the present fMRI study we explored the activation of areas belonging to the AON/MNS in children and adults during observation of complex hand-grasping actions, as compared to observation of simple grasping acts executed with the left and the right hand, seen from a first person perspective. The results indicate that during the action observation tasks in children there was activation of a cortical network similar to that found in adults, including the premotor cortex, the posterior part of the inferior frontal gyrus and the posterior parietal lobe. However, the activation in children was more widespread and showed a higher inter-subject variability compared with adults. Furthermore, the activated network seems more lateralized to the left hemisphere in adults and more bilateral in children, with a linear growth of lateralization index as a function of age. Finally, in children the activation in the anterior intraparietal cortex (AIP) of each hemisphere was higher during observation of the contralateral hand (hand identity effect) and during the observation of complex actions relative to simple grasping acts, confirming the role of AIP for action-related hand identity previously described in adults. These results support the assumption that structure and size of action representations are sensitive to mechanisms of development and show physiological plasticity. These properties of the AON/MNS could constitute a powerful tool for spontaneous reorganization and recovery of motor deficits after brain injury in children and in adults, as well as for specific rehabilitation programmes. © 2015 John Wiley & Sons Ltd.

Sustainable Arctic observing network for predicting weather extremes in mid-latitudes

NASA Astrophysics Data System (ADS)

Inoue, J.; Sato, K.; Yamazaki, A.

2016-12-01

Routine atmospheric observations within and over the Arctic Ocean are very expensive and difficult to conduct because of factors such as logistics and the harsh environment. Nevertheless, the great benefit of such observations is their contribution to an improvement of skills of weather predictions over the Arctic and mid-latitudes. The Year of Polar Prediction (YOPP) from mid-2017 to mid-2019 proposed by the World Weather Research Programme - Polar Prediction Project (WWRP-PPP) would be the best opportunity to address the issues. The combination of observations and data assimilation is an effective way to understand the predictability of weather extremes in mid-latitudes. This talk presents the current activities related to PPP based on international special radiosonde observing network in the Arctic, and challenges toward YOPP. Comparing with summer and winter cases, the additional observations over the Arctic during winter were more effective for improving the predicting skills of weather extremes because the impact of the observations would be carried toward the mid-latitudes by the stronger jet stream and its frequent meanderings. During summer, on the other hand, the impact of extra observations was localized over the Arctic region but still important for precise weather forecasts over the Arctic Ocean, contributing to safe navigation along the Northern Sea Route. To consolidate the sustainable Arctic radiosonde observing network, increasing the frequency of observations at Arctic coastal stations, instead of commissioning special observations from ships and ice camps, would be a feasible way. In fact, several existing stations facing the Arctic Ocean have already increased the frequency of observations during winter and/or summer.

Spatiotemporal Phase Synchronization in Adaptive Reconfiguration from Action Observation Network to Mentalizing Network for Understanding Other's Action Intention.

PubMed

Zhang, Li; Gan, John Q; Zheng, Wenming; Wang, Haixian

2018-05-01

In action intention understanding, the mirror system is involved in perception-action matching process and the mentalizing system underlies higher-level intention inference. By analyzing the dynamic functional connectivity in α (8-12 Hz) and β (12-30 Hz) frequency bands over a "hand-cup interaction" observation task, this study investigates the topological transition from the action observation network (AON) to the mentalizing network (MZN), and estimates their functional relevance for intention identification from other's different action kinematics. Sequential brain microstates were extracted based on event-related potentials (ERPs), in which significantly differing neuronal responses were found in N170-P200 related to perceptually matching kinematic profiles and P400-700 involved in goal inference. Inter-electrode weighted phase lag index analysis on the ERP microstates revealed a shift of hub centrality salient in α frequency band, from the AON dominated by left-lateral frontal-premotor-temporal and temporal-parietooccipital synchronizations to the MZN consisting of more bilateral frontal-parietal and temporal-parietal synchronizations. As compared with usual actions, intention identification of unintelligible actions induces weaker synchronizations in the AON but dramatically increased connectivity in right frontal-temporal-parietal regions of the MZN, indicating a spatiotemporally complementary effect between the functional network configurations involved in mirror and mentalizing processes. Perceptual processing in observing usual/unintelligible actions decreases/increases requirements for intention inference, which would induce less/greater functional network reorganization on the way to mentalization. From the comparison, our study suggests that the adaptive topological changes from the AON to the MZN indicate implicit causal association between the mirror and mentalizing systems for decoding others' intentionality.

EOP and scale from continuous VLBI observing: CONT campaigns to future VGOS networks

NASA Astrophysics Data System (ADS)

MacMillan, D. S.

2017-07-01

Continuous (CONT) VLBI campaigns have been carried out about every 3 years since 2002. The basic idea of these campaigns is to acquire state-of-the-art VLBI data over a continuous time period of about 2 weeks to demonstrate the highest accuracy of which the current VLBI system is capable. In addition, these campaigns support scientific studies such as investigations of high-resolution Earth rotation, reference frame stability, and daily to sub-daily site motions. The size of the CONT networks and the observing data rate have increased steadily since 1994. Performance of these networks based on reference frame scale precision and polar motion/LOD comparison with global navigation satellite system (GNSS) earth orientation parameters (EOP) has been substantially better than the weekly operational R1 and R4 series. The precisions of CONT EOP and scale have improved by more than a factor of two since 2002. Polar motion precision based on the WRMS difference between VLBI and GNSS for the most recent CONT campaigns is at the 30 μas level, which is comparable to that of GNSS. The CONT campaigns are a natural precursor to the planned future VLBI observing networks, which are expected to observe continuously. We compare the performance of the most recent CONT campaigns in 2011 and 2014 with the expected performance of the future VLBI global observing system network using simulations. These simulations indicate that the expected future precision of scale and EOP will be at least 3 times better than the current CONT precision.

Aggression, grooming and group-level cooperation in white-faced capuchins (Cebus capucinus): insights from social networks.

PubMed

Crofoot, Margaret C; Rubenstein, Daniel I; Maiya, Arun S; Berger-Wolf, Tanya Y

2011-08-01

The form of animal social systems depends on the nature of agonistic and affiliative interactions. Social network theory provides tools for characterizing social structure that go beyond simple dyadic interactions and consider the group as a whole. We show three groups of capuchin monkeys from Barro Colorado Island, Panama, where there are strong connections between key aspects of aggression, grooming, and proximity networks, and, at least among females, those who incur risk to defend their group have particular "social personalities." Although there is no significant correlation for any of the network measures between giving and receiving aggression, suggesting that dominance relationships do not follow a simple hierarchy, strong correlations emerge for many measures between the aggression and grooming networks. At the local, but not global, scale, receiving aggression and giving grooming are strongly linked in all groups. Proximity shows no correlation with aggression at either the local or the global scale, suggesting that individuals neither seek out nor avoid aggressors. Yet, grooming has a global but not local connection to proximity. Extensive groomers who tend to direct their efforts at other extensive groomers also spend time in close proximity to many other individuals. These results indicate the important role that prosociality plays in shaping female social relationships. We also show that females who receive the least aggression, and thus pay low costs for group living, are most likely to participate in group defense. No consistent "social personality" traits characterize the males who invest in group defense. © 2011 Wiley-Liss, Inc.

Results from Joint Observations of Jupiter's Atmosphere by Juno and a Network of Earth-Based Observing Stations

NASA Astrophysics Data System (ADS)

Orton, G. S.; Bolton, S. J.; Levin, S.; Hansen, C. J.; Janssen, M. A.; Adriani, A.; Gladstone, R.; Bagenal, F.; Ingersoll, A. P.; Momary, T.; Payne, A.

2016-12-01

The Juno mission has promoted and coordinated a network of Earth-based observations, including both space- and ground-based facilities, to extend and enhance observations made by the Juno mission. The spectral region and timeline of all of these observations are summarized in the web site: https://www.missionjuno.swri.edu/planned-observations. Among the earliest of these were observation of Jovian auroral phenomena at X-ray, ultraviolet and infrared wavelengths and measurements of Jovian synchrotron radiation from the Earth simultaneously with the measurement of properties of the upstream solar wind described elsewhere in this meeting. Other observations of significance to the magnetosphere measured the mass loading from Io by tracking its observed volcanic activity and the opacity of its torus. Observations of Jupiter's neutral atmosphere included observations of reflected sunlight from the near-ultraviolet through the near-infrared and thermal emission from 5 microns through the radio region. The point of these measurements is to relate properties of the deep atmosphere that are the focus of Juno's mission to the state of the "weather layer" at much higher atmospheric levels. These observations cover spectral regions not included in Juno's instrumentation, provide spatial context for Juno's often spatially limited coverage of Jupiter, and they describe the evolution of atmospheric features in time that are measured only once by Juno. We will summarize the results of measurements during the approach phase of the mission that characterized the state of the atmosphere, as well as observations made by Juno and the supporting campaign during Juno's perijoves 1 (August 27), 2 (October 19), 3 (November 2), 4 (November 15), and 5 (November 30). The Juno mission also benefited from the enlistment of a network of dedicated amateur astronomers who, besides providing input needed for public operation of the JunoCam visible camera, tracked the evolution of features in Jupiter

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

NASA Astrophysics Data System (ADS)

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

2015-12-01

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

Observation and Recording Effects on Group Therapy Client Behaviors.

ERIC Educational Resources Information Center

Berman, Alan L.; Decker, Robert E.

This study assesses the effect of visual versus audio observation/recording on both client and therapist verbal and non-verbal behavior in ongoing therapy. Three co-led, therapy groups were studied over six weekly sessions under counterbalanced observation conditions. Measures of verbal behavior, verbal productivity, and non-verbal behavior were…

Investigating Patterns of Participation in an Online Support Group for Problem Drinking: a Social Network Analysis.

PubMed

Urbanoski, Karen; van Mierlo, Trevor; Cunningham, John

2017-10-01

This study contributes to emerging literature on online health networks by modeling communication patterns between members of a moderated online support group for problem drinking. Using social network analysis, we described members' patterns of joint participation in threads, parsing out the role of site moderators, and explored differences in member characteristics by network position. Posts made to the online support group of Alcohol Help Centre during 2013 were structured as a two-mode network of members (n = 205) connected via threads (n = 506). Metrics included degree centrality, clique membership, and tie strength. The network consisted of one component and no cliques of members, although most made few posts and a small number communicated only with the site's moderators. Highly active members were older and tended to have started posting prior to 2013. The distribution of members across threads varied from threads containing posts by one member to others that connected multiple members. Moderators accounted for sizable proportions of the connectivity between both members and threads. After 5 years of operation, the AHC online support group appears to be fairly cohesive and stable, in the sense that there were no isolated subnetworks comprised of specific types of members or devoted to specific topics. Participation and connectedness at the member-level was varied, however, and tended to be low on average. The moderators were among the most central in the network, although there were also members who emerged as central and dedicated contributors to the online discussions across topics. Study findings highlight a number of areas for consideration by online support group developers and managers.

A group LASSO-based method for robustly inferring gene regulatory networks from multiple time-course datasets.

PubMed

Liu, Li-Zhi; Wu, Fang-Xiang; Zhang, Wen-Jun

2014-01-01

As an abstract mapping of the gene regulations in the cell, gene regulatory network is important to both biological research study and practical applications. The reverse engineering of gene regulatory networks from microarray gene expression data is a challenging research problem in systems biology. With the development of biological technologies, multiple time-course gene expression datasets might be collected for a specific gene network under different circumstances. The inference of a gene regulatory network can be improved by integrating these multiple datasets. It is also known that gene expression data may be contaminated with large errors or outliers, which may affect the inference results. A novel method, Huber group LASSO, is proposed to infer the same underlying network topology from multiple time-course gene expression datasets as well as to take the robustness to large error or outliers into account. To solve the optimization problem involved in the proposed method, an efficient algorithm which combines the ideas of auxiliary function minimization and block descent is developed. A stability selection method is adapted to our method to find a network topology consisting of edges with scores. The proposed method is applied to both simulation datasets and real experimental datasets. It shows that Huber group LASSO outperforms the group LASSO in terms of both areas under receiver operating characteristic curves and areas under the precision-recall curves. The convergence analysis of the algorithm theoretically shows that the sequence generated from the algorithm converges to the optimal solution of the problem. The simulation and real data examples demonstrate the effectiveness of the Huber group LASSO in integrating multiple time-course gene expression datasets and improving the resistance to large errors or outliers.

Exponential Arithmetic Based Self-Healing Group Key Distribution Scheme with Backward Secrecy under the Resource-Constrained Wireless Networks

PubMed Central

Guo, Hua; Zheng, Yandong; Zhang, Xiyong; Li, Zhoujun

2016-01-01

In resource-constrained wireless networks, resources such as storage space and communication bandwidth are limited. To guarantee secure communication in resource-constrained wireless networks, group keys should be distributed to users. The self-healing group key distribution (SGKD) scheme is a promising cryptographic tool, which can be used to distribute and update the group key for the secure group communication over unreliable wireless networks. Among all known SGKD schemes, exponential arithmetic based SGKD (E-SGKD) schemes reduce the storage overhead to constant, thus is suitable for the the resource-constrained wireless networks. In this paper, we provide a new mechanism to achieve E-SGKD schemes with backward secrecy. We first propose a basic E-SGKD scheme based on a known polynomial-based SGKD, where it has optimal storage overhead while having no backward secrecy. To obtain the backward secrecy and reduce the communication overhead, we introduce a novel approach for message broadcasting and self-healing. Compared with other E-SGKD schemes, our new E-SGKD scheme has the optimal storage overhead, high communication efficiency and satisfactory security. The simulation results in Zigbee-based networks show that the proposed scheme is suitable for the resource-restrained wireless networks. Finally, we show the application of our proposed scheme. PMID:27136550

Crustal movements in Europe observed with EUROPE and IVS-T2 VLBI networks

NASA Astrophysics Data System (ADS)

Zubko, N.; Poutanen, M.

2011-07-01

The comparative analysis of the EUROPE and IVS-T2 geodetic VLBI sessions has been performed. The main purpose of both campaigns is to observe and accurately determine the VLBI station coordinates and their time evolution. In this analysis our interest is to understand the influence of network configuration on the estimated parameters and, also, how much the results of these two campaigns are consistent. We have used the VieVS software developing at Vienna University of Technology to analyze the EUROPE and IVS-T2 sessions of 2002-2009. We have analyzed the difference of crustal movements obtained with these two networks and the effect of network configuration and station selection. The EPN (EUREF permanent GNSS Network) and IGS (International GNSS Service) networks can be used to compare the results.

Bootstrapping under constraint for the assessment of group behavior in human contact networks

NASA Astrophysics Data System (ADS)

Tremblay, Nicolas; Barrat, Alain; Forest, Cary; Nornberg, Mark; Pinton, Jean-François; Borgnat, Pierre

2013-11-01

The increasing availability of time- and space-resolved data describing human activities and interactions gives insights into both static and dynamic properties of human behavior. In practice, nevertheless, real-world data sets can often be considered as only one realization of a particular event. This highlights a key issue in social network analysis: the statistical significance of estimated properties. In this context, we focus here on the assessment of quantitative features of specific subset of nodes in empirical networks. We present a method of statistical resampling based on bootstrapping groups of nodes under constraints within the empirical network. The method enables us to define acceptance intervals for various null hypotheses concerning relevant properties of the subset of nodes under consideration in order to characterize by a statistical test its behavior as “normal” or not. We apply this method to a high-resolution data set describing the face-to-face proximity of individuals during two colocated scientific conferences. As a case study, we show how to probe whether colocating the two conferences succeeded in bringing together the two corresponding groups of scientists.

The U.S. Geological Survey streamflow and observation-well network in Massachusetts and Rhode Island

USGS Publications Warehouse

Zarriello, Phillip J.; Socolow, Roy S.

2003-01-01

diminishes the usefulness of these stations for many types of hydrologic analysis. Only 26 of the 103 active streamgage stations operated by the U.S. Geological Survey in Massachusetts and Rhode Island are unaffected by regulation; of these, 17 are in Massachusetts and 9 are in Rhode Island. The paucity of unregulated stations is particularly evident when the stations are grouped into five drainage-area size classes; the fact that about half of these size classes have no representative unregulated stations underscores the importance of establishing and maintaining stations that are unaffected by regulation. The observation-well network comprises 200 wells; 80 percent of these wells are finished in sand and gravel, 19 percent are finished in till, and 1 percent are finished in bedrock. About 6 percent of the wells are equipped with continuous data recorders, and about half of these are capable of transmitting data in near real time.

Thunderstorm monitoring with VLF network and super dense meteorological observation system

NASA Astrophysics Data System (ADS)

Takahashi, Yukihiro; Sato, Mitsuteru

2015-04-01

It's not easy to understand the inside structure and developing process of thunderstorm only with existing meteorological instruments since its horizontal extent of the storm cell is sometimes smaller than an order of 10 km while one of the densest ground network in Japan, AMEDAS, consists of sites located every 17 km in average and the resolution of meteorological radar is 1-2 km in general. Even the X-band radar realizes the resolution of 250 m or larger. Here we suggest a thunderstorm monitoring system consisting of the network of VLF radio wave receivers and the super dense meteorological observation system with simple and low cost plate-type sensors that can be used for measurement both of raindrop and vertical electric field change caused by cloud-to-ground lightning discharge, adding to basic equipments for meteorological measurements. The plate-type sensor consists of two aluminum plates with a diameter of 10-20 cm. We carried out an observation campaign in summer of 2013 in the foothills of Mt. Yastugatake, Yamanashi and Nagano prefectures in Japan, installing 6 plate-type sensors at a distance of about 4 km. Horizontal location, height and charge amount of each lightning discharge are estimated successfully based on the information of electric field changes at several observing sites. Moreover, it was found that the thunderstorm has a very narrow structure smaller than 300 m that cannot be measured by any other ways, counting the positive and negative pulses caused by attachment of raindrop to the sensor plate, respectively. We plan to construct a new super dense observation network in the north Kanto region, Japan, where the lightning activity is most prominent in summer Japan and surrounded by our VLF systems developed for detecting sferics from lightning discharge, distributing more than several tens of sensors at every 4 km or shorter, such as an order of 100 m at minimum. This kind of new type network will reveal the unknown fine structures of

Networked high-speed auroral observations combined with radar measurements for multi-scale insights

NASA Astrophysics Data System (ADS)

Hirsch, M.; Semeter, J. L.

2015-12-01

Networks of ground-based instruments to study terrestrial aurora for the purpose of analyzing particle precipitation characteristics driving the aurora have been established. Additional funding is pouring into future ground-based auroral observation networks consisting of combinations of tossable, portable, and fixed installation ground-based legacy equipment. Our approach to this problem using the High Speed Tomography (HiST) system combines tightly-synchronized filtered auroral optical observations capturing temporal features of order 10 ms with supporting measurements from incoherent scatter radar (ISR). ISR provides a broader spatial context up to order 100 km laterally on one minute time scales, while our camera field of view (FOV) is chosen to be order 10 km at auroral altitudes in order to capture 100 m scale lateral auroral features. The dual-scale observations of ISR and HiST fine-scale optical observations may be coupled through a physical model using linear basis functions to estimate important ionospheric quantities such as electron number density in 3-D (time, perpendicular and parallel to the geomagnetic field).Field measurements and analysis using HiST and PFISR are presented from experiments conducted at the Poker Flat Research Range in central Alaska. Other multiscale configuration candidates include supplementing networks of all-sky cameras such as THEMIS with co-locations of HiST-like instruments to fuse wide FOV measurements with the fine-scale HiST precipitation characteristic estimates. Candidate models for this coupling include GLOW and TRANSCAR. Future extensions of this work may include incorporating line of sight total electron count estimates from ground-based networks of GPS receivers in a sensor fusion problem.

Autonomous telemetry system by using mobile networks for a long-term seismic observation

NASA Astrophysics Data System (ADS)

Hirahara, S.; Uchida, N.; Nakajima, J.

2012-04-01

When a large earthquake occurs, it is important to know the detailed distribution of aftershocks immediately after the main shock for the estimation of the fault plane. The large amount of seismic data is also required to determine the three-dimensional seismic velocity structure around the focal area. We have developed an autonomous telemetry system using mobile networks, which is specialized for aftershock observations. Because the newly developed system enables a quick installation and real-time data transmission by using mobile networks, we can construct a dense online seismic network even in mountain areas where conventional wired networks are not available. This system is equipped with solar panels that charge lead-acid battery, and enables a long-term seismic observation without maintenance. Furthermore, this system enables a continuous observation at low costs with flat-rate or prepaid Internet access. We have tried to expand coverage areas of mobile communication and back up Internet access by configuring plural mobile carriers. A micro server embedded with Linux consists of automatic control programs of the Internet connection and data transmission. A status monitoring and remote maintenance are available via the Internet. In case of a communication failure, an internal storage can back up data for two years. The power consumption of communication device ranges from 2.5 to 4.0 W. With a 50 Ah lead-acid battery, this system continues to record data for four days if the battery charging by solar panels is temporarily unavailable.

ChinaSpec: a network of SIF observations to bridge flux measurements and remote sensing data

NASA Astrophysics Data System (ADS)

Zhang, Y.; Wang, S.; Liu, L.; Ju, W.; Zhu, X.

2017-12-01

Accurately quantifying atmosphere-biosphere interactions across multiple scale still remains a challenge. Remote sensing, especially satellite data, has been widely used as a solution to resolve the broad scale estimation of carbon flux by upscaling the point measurements of eddy covariance (EC) technique. However, critical gaps remain between the EC observations and coarse satellite data due to the scale mismatch. In this regard, it is necessary to build a network of in situ optical observations to bridge the scale-mismatch between EC measurements and satellite remote sensing data. Internationally, a few networks have already been established (e.g., SpecNet and EuroSpec), but still at its early stage. ChinaSpec is a network of linking in situ spectral measurements, especially sun-induce chlorophyll fluorescence (SIF), with point EC observations for better understanding the interactions of atmosphere-biosphere. One main focus of ChinsSpec is to conduct continuous field SIF measurements at multiple EC sites across the mainland of China. This will help us better understand the mechanics of SIF and photosynthesis, and resolve the missing gaps between recent SIF retrievals from coarse satellite data and EC observations. In this presentation, we introduce the background, current stage, and the development of ChinaSpec network.

A Study on Group Key Agreement in Sensor Network Environments Using Two-Dimensional Arrays

PubMed Central

Jang, Seung-Jae; Lee, Young-Gu; Lee, Kwang-Hyung; Kim, Tai-Hoon; Jun, Moon-Seog

2011-01-01

These days, with the emergence of the concept of ubiquitous computing, sensor networks that collect, analyze and process all the information through the sensors have become of huge interest. However, sensor network technology fundamentally has wireless communication infrastructure as its foundation and thus has security weakness and limitations such as low computing capacity, power supply limitations and price. In this paper, and considering the characteristics of the sensor network environment, we propose a group key agreement method using a keyset pre-distribution of two-dimension arrays that should minimize the exposure of key and personal information. The key collision problems are resolved by utilizing a polygonal shape’s center of gravity. The method shows that calculating a polygonal shape’s center of gravity only requires a very small amount of calculations from the users. The simple calculation not only increases the group key generation efficiency, but also enhances the sense of security by protecting information between nodes. PMID:22164072

Aperiodic dynamics in a deterministic adaptive network model of attitude formation in social groups

NASA Astrophysics Data System (ADS)

Ward, Jonathan A.; Grindrod, Peter

2014-07-01

Adaptive network models, in which node states and network topology coevolve, arise naturally in models of social dynamics that incorporate homophily and social influence. Homophily relates the similarity between pairs of nodes' states to their network coupling strength, whilst social influence causes coupled nodes' states to convergence. In this paper we propose a deterministic adaptive network model of attitude formation in social groups that includes these effects, and in which the attitudinal dynamics are represented by an activato-inhibitor process. We illustrate that consensus, corresponding to all nodes adopting the same attitudinal state and being fully connected, may destabilise via Turing instability, giving rise to aperiodic dynamics with sensitive dependence on initial conditions. These aperiodic dynamics correspond to the formation and dissolution of sub-groups that adopt contrasting attitudes. We discuss our findings in the context of cultural polarisation phenomena. Social influence. This reflects the fact that people tend to modify their behaviour and attitudes in response to the opinions of others [22-26]. We model social influence via diffusion: agents adjust their state according to a weighted sum (dictated by the evolving network) of the differences between their state and the states of their neighbours. Homophily. This relates the similarity of individuals' states to their frequency and strength of interaction [27]. Thus in our model, homophily drives the evolution of the weighted ‘social' network. A precise formulation of our model is given in Section 2. Social influence and homophily underpin models of social dynamics [21], which cover a wide range of sociological phenomena, including the diffusion of innovations [28-32], complex contagions [33-36], collective action [37-39], opinion dynamics [19,20,40,10,11,13,15,41,16], the emergence of social norms [42-44], group stability [45], social differentiation [46] and, of particular relevance

Predicting Drug-Target Interaction Networks Based on Functional Groups and Biological Features

PubMed Central

Shi, Xiao-He; Hu, Le-Le; Kong, Xiangyin; Cai, Yu-Dong; Chou, Kuo-Chen

2010-01-01

Background Study of drug-target interaction networks is an important topic for drug development. It is both time-consuming and costly to determine compound-protein interactions or potential drug-target interactions by experiments alone. As a complement, the in silico prediction methods can provide us with very useful information in a timely manner. Methods/Principal Findings To realize this, drug compounds are encoded with functional groups and proteins encoded by biological features including biochemical and physicochemical properties. The optimal feature selection procedures are adopted by means of the mRMR (Maximum Relevance Minimum Redundancy) method. Instead of classifying the proteins as a whole family, target proteins are divided into four groups: enzymes, ion channels, G-protein- coupled receptors and nuclear receptors. Thus, four independent predictors are established using the Nearest Neighbor algorithm as their operation engine, with each to predict the interactions between drugs and one of the four protein groups. As a result, the overall success rates by the jackknife cross-validation tests achieved with the four predictors are 85.48%, 80.78%, 78.49%, and 85.66%, respectively. Conclusion/Significance Our results indicate that the network prediction system thus established is quite promising and encouraging. PMID:20300175

Efficient traffic grooming with dynamic ONU grouping for multiple-OLT-based access network

NASA Astrophysics Data System (ADS)

Zhang, Shizong; Gu, Rentao; Ji, Yuefeng; Wang, Hongxiang

2015-12-01

Fast bandwidth growth urges large-scale high-density access scenarios, where the multiple Passive Optical Networking (PON) system clustered deployment can be adopted as an appropriate solution to fulfill the huge bandwidth demands, especially for a future 5G mobile network. However, the lack of interaction between different optical line terminals (OLTs) results in part of the bandwidth resources waste. To increase the bandwidth efficiency, as well as reduce bandwidth pressure at the edge of a network, we propose a centralized flexible PON architecture based on Time- and Wavelength-Division Multiplexing PON (TWDM PON). It can provide flexible affiliation for optical network units (ONUs) and different OLTs to support access network traffic localization. Specifically, a dynamic ONU grouping algorithm (DGA) is provided to obtain the minimal OLT outbound traffic. Simulation results show that DGA obtains an average 25.23% traffic gain increment under different OLT numbers within a small ONU number situation, and the traffic gain will increase dramatically with the increment of the ONU number. As the DGA can be deployed easily as an application running above the centralized control plane, the proposed architecture can be helpful to improve the network efficiency for future traffic-intensive access scenarios.

Pan-Eurasian experiment (PEEX) establishing a process towards high level Pan-Eurasian atmosphere-ecosystem observation networks

NASA Astrophysics Data System (ADS)

Lappalainen, Hanna K.; Petäjä, Tuukka; Zaytzeva, Nina; Viisanen, Yrjö; Kotlyakov, Vladimir; Kasimov, Nikolay; Bondur, Valery; Matvienko, Gennady; Zilitinkevich, Sergej; Kulmala, Markku

2014-05-01

Pan-Eurasian Experiment (PEEX) is a new multidisciplinary research approach aiming at resolving the major uncertainties in the Earth system science and global sustainability questions in the Arctic and boreal Pan-Eurasian regions (Kulmala et al. 2011). The main goal of PEEX Research agenda is to contribute to solving the scientific questions that are specifically important for the Pan-Eurasian region in the coming years, in particular the global climate change and its consequences to nature and human society. Pan Eurasian region represents one the Earth most extensive areas of boreal forest (taiga) and the largest natural wetlands, thus being a significant source area of trace gas emissions, biogenic aerosol particles, and source and sink area for the greenhouse gas (GHG) exchange in a global scale (Guenther et al. 1995, Timkovsky et al. 2010, Tunved et al. 2006, Glagolev et al. 2010). One of the first activities of the PEEX initiative is to establish a process towards high level Pan-Eurasian Observation Networks. Siberian region is currently lacking a coordinated, coherent ground based atmosphere-ecosystem measurement network, which would be crucial component for observing and predicting the effects of climate change in the Northern Pan- Eurasian region The vision of the Pan-Eurasion network will be based on a hierarchical SMEAR-type (Stations Measuring Atmosphere-Ecosystem Interactions) integrated land-atmosphere observation system (Hari et al. 2009). A suite of stations have been selected for the Preliminary Phase of PEEX Observation network. These Preliminary Phase stations includes the SMEAR-type stations in Finland (SMEAR-I-II-II-IV stations), in Estonia (SMEAR-Järviselja) and in China (SMEAR-Nanjing) and selected stations in Russia and ecosystem station network in China. PEEX observation network will fill in the current observational gap in the Siberian region and bring the Siberian observation setup into international context with the with standardized or

Concerted Perturbation Observed in a Hub Network in Alzheimer’s Disease

PubMed Central

Liang, Dapeng; Han, Guangchun; Feng, Xuemei; Sun, Jiya; Duan, Yong; Lei, Hongxing

2012-01-01

Alzheimer’s disease (AD) is a progressive neurodegenerative disease involving the alteration of gene expression at the whole genome level. Genome-wide transcriptional profiling of AD has been conducted by many groups on several relevant brain regions. However, identifying the most critical dys-regulated genes has been challenging. In this work, we addressed this issue by deriving critical genes from perturbed subnetworks. Using a recent microarray dataset on six brain regions, we applied a heaviest induced subgraph algorithm with a modular scoring function to reveal the significantly perturbed subnetwork in each brain region. These perturbed subnetworks were found to be significantly overlapped with each other. Furthermore, the hub genes from these perturbed subnetworks formed a connected hub network consisting of 136 genes. Comparison between AD and several related diseases demonstrated that the hub network was robustly and specifically perturbed in AD. In addition, strong correlation between the expression level of these hub genes and indicators of AD severity suggested that this hub network can partially reflect AD progression. More importantly, this hub network reflected the adaptation of neurons to the AD-specific microenvironment through a variety of adjustments, including reduction of neuronal and synaptic activities and alteration of survival signaling. Therefore, it is potentially useful for the development of biomarkers and network medicine for AD. PMID:22815752

Evaluation of Long-Range Lightning Detection Networks Using TRMM/LIS Observations

NASA Technical Reports Server (NTRS)

Rudlosky, Scott D.; Holzworth, Robert H.; Carey, Lawrence D.; Schultz, Chris J.; Bateman, Monte; Cecil, Daniel J.; Cummins, Kenneth L.; Petersen, Walter A.; Blakeslee, Richard J.; Goodman, Steven J.

2011-01-01

Recent advances in long-range lightning detection technologies have improved our understanding of thunderstorm evolution in the data sparse oceanic regions. Although the expansion and improvement of long-range lightning datasets have increased their applicability, these applications (e.g., data assimilation, atmospheric chemistry, and aviation weather hazards) require knowledge of the network detection capabilities. Toward this end, the present study evaluates data from the World Wide Lightning Location Network (WWLLN) using observations from the Lightning Imaging Sensor (LIS) aboard the Tropical Rainfall Measurement Mission (TRMM) satellite. The study documents the WWLLN detection efficiency and location accuracy relative to LIS observations, describes the spatial variability in these performance metrics, and documents the characteristics of LIS flashes that are detected by WWLLN. Improved knowledge of the WWLLN detection capabilities will allow researchers, algorithm developers, and operational users to better prepare for the spatial and temporal coverage of the upcoming GOES-R Geostationary Lightning Mapper (GLM).

The North Alabama Severe Thunderstorm Observations, Research, and Monitoring Network (STORMnet)

NASA Technical Reports Server (NTRS)

Goodman, S. J.; Blakeslee, R.; Christian, H.; Boccippio, D.; Koshak, W.; Bailey, J.; Hall, J.; Bateman, M.; McCaul, E.; Buechler, D.;

Bringing a Network-Oriented Approach to Domestic Violence Services: A Focus Group Exploration of Promising Practices.

PubMed

Goodman, Lisa A; Banyard, Victoria; Woulfe, Julie; Ash, Sarah; Mattern, Grace

2016-01-01

Despite powerful evidence that informal social support contributes to survivors' safety and well-being, mainstream domestic violence (DV) programs have not developed comprehensive models for helping isolated survivors re-engage with these networks. Although many advocates use network-oriented strategies informally, they often do so without resources, funding, or training. This qualitative focus group study explored advocates' use and perceptions of network-oriented strategies. Advocates working in a range of DV programs across one state described the importance of network-oriented work and articulated its five dimensions, including helping survivors build their capacity to form healthy relationships, identify helpful and harmful network members, re-engage with existing networks, develop new relationships, and respond more effectively to network members. © The Author(s) 2015.

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

NASA Astrophysics Data System (ADS)

Chirco, Goffredo; Oriti, Daniele; Zhang, Mingyi

2018-06-01

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

2003 Mars Report from Cooperative Observation Networks. II. After the Opposition

NASA Astrophysics Data System (ADS)

Nakakushi, Takashi; Adachi, Makoto; Iga, Yuichi; Ikemura, Toshihiko; Tokimasa, Noritaka; Narumi, Yasunori

2005-06-01

This is the second report on Mars in 2003 by two networks for cooperative Mars observations in Japan: Nishi-Harima Astronomical Observatory Mars Cooperative Observation and Association of Lunar and Planetary Observers in Japan. This paper is a summary of 4145 data for 226 nights collected by the two networks during the second half of the last apparition from 2003 September 1 through 2004 June 22, corresponding to a period of Ls ˜ 252°--51° (Ls is the areocentric longitude of the Sun). During this period, many interesting phenomena were observed: (1) Albedo features did not show a large difference from the first half of the period. (2) Blue clearings due to the opposition effect and due to the cloud effect were, respectively, observed. (3) South polar cap (SPC) recession was usual. The recession rate in ˜ 210°--270°W increased and that in ˜ 30°--60°W decreased after Ls ˜ 230°. (4) North polar hood (NPH) had a topography-synchronous wave structure with a wave number = 1. (5) Many water ice clouds (WICs) were observed. Some particular regions frequently had prominent WICs. Some of them were related to topography. (6) Dust storm ``2003c'' was detected on December 9 (Ls = 314°) in Chryse. The storm grew rapidly to a very large dimension in the southern mid-latitudes, encircling over half of Mars. Another dust core occurred on December 23 around Aurorae Sinus. (7) Another dust storm is suspected in Ls = 20° over the south polar region.

Social Transmission of False Memory in Small Groups and Large Networks.

PubMed

Maswood, Raeya; Rajaram, Suparna

2018-05-21

Sharing information and memories is a key feature of social interactions, making social contexts important for developing and transmitting accurate memories and also false memories. False memory transmission can have wide-ranging effects, including shaping personal memories of individuals as well as collective memories of a network of people. This paper reviews a collection of key findings and explanations in cognitive research on the transmission of false memories in small groups. It also reviews the emerging experimental work on larger networks and collective false memories. Given the reconstructive nature of memory, the abundance of misinformation in everyday life, and the variety of social structures in which people interact, an understanding of transmission of false memories has both scientific and societal implications. © 2018 Cognitive Science Society, Inc.

Global network structure of dominance hierarchy of ant workers

PubMed Central

Shimoji, Hiroyuki; Abe, Masato S.; Tsuji, Kazuki; Masuda, Naoki

2014-01-01

Dominance hierarchy among animals is widespread in various species and believed to serve to regulate resource allocation within an animal group. Unlike small groups, however, detection and quantification of linear hierarchy in large groups of animals are a difficult task. Here, we analyse aggression-based dominance hierarchies formed by worker ants in Diacamma sp. as large directed networks. We show that the observed dominance networks are perfect or approximate directed acyclic graphs, which are consistent with perfect linear hierarchy. The observed networks are also sparse and random but significantly different from networks generated through thinning of the perfect linear tournament (i.e. all individuals are linearly ranked and dominance relationship exists between every pair of individuals). These results pertain to global structure of the networks, which contrasts with the previous studies inspecting frequencies of different types of triads. In addition, the distribution of the out-degree (i.e. number of workers that the focal worker attacks), not in-degree (i.e. number of workers that attack the focal worker), of each observed network is right-skewed. Those having excessively large out-degrees are located near the top, but not the top, of the hierarchy. We also discuss evolutionary implications of the discovered properties of dominance networks. PMID:25100318

Minimum Number of Observation Points for LEO Satellite Orbit Estimation by OWL Network

NASA Astrophysics Data System (ADS)

Park, Maru; Jo, Jung Hyun; Cho, Sungki; Choi, Jin; Kim, Chun-Hwey; Park, Jang-Hyun; Yim, Hong-Suh; Choi, Young-Jun; Moon, Hong-Kyu; Bae, Young-Ho; Park, Sun-Youp; Kim, Ji-Hye; Roh, Dong-Goo; Jang, Hyun-Jung; Park, Young-Sik; Jeong, Min-Ji

2015-12-01

By using the Optical Wide-field Patrol (OWL) network developed by the Korea Astronomy and Space Science Institute (KASI) we generated the right ascension and declination angle data from optical observation of Low Earth Orbit (LEO) satellites. We performed an analysis to verify the optimum number of observations needed per arc for successful estimation of orbit. The currently functioning OWL observatories are located in Daejeon (South Korea), Songino (Mongolia), and Oukaïmeden (Morocco). The Daejeon Observatory is functioning as a test bed. In this study, the observed targets were Gravity Probe B, COSMOS 1455, COSMOS 1726, COSMOS 2428, SEASAT 1, ATV-5, and CryoSat-2 (all in LEO). These satellites were observed from the test bed and the Songino Observatory of the OWL network during 21 nights in 2014 and 2015. After we estimated the orbit from systematically selected sets of observation points (20, 50, 100, and 150) for each pass, we compared the difference between the orbit estimates for each case, and the Two Line Element set (TLE) from the Joint Space Operation Center (JSpOC). Then, we determined the average of the difference and selected the optimal observation points by comparing the average values.

AIDS Clinical Trials Group Network

MedlinePlus

... ACTG (PDF - 42 KB) Bylaws, SOPs, and Guidelines Leadership and Operations Center Network Coordinating Center Statistical and Data Management Center Performance Evaluation Program Sites Community General Information ...

Locating overlapping dense subgraphs in gene (protein) association networks and predicting novel protein functional groups among these subgraphs

NASA Astrophysics Data System (ADS)

Palla, Gergely; Derenyi, Imre; Farkas, Illes J.; Vicsek, Tamas

2006-03-01

Most tasks in a cell are performed not by individual proteins, but by functional groups of proteins (either physically interacting with each other or associated in other ways). In gene (protein) association networks these groups show up as sets of densely connected nodes. In the yeast, Saccharomyces cerevisiae, known physically interacting groups of proteins (called protein complexes) strongly overlap: the total number of proteins contained by these complexes by far underestimates the sum of their sizes (2750 vs. 8932). Thus, most functional groups of proteins, both physically interacting and other, are likely to share many of their members with other groups. However, current algorithms searching for dense groups of nodes in networks usually exclude overlaps. With the aim to discover both novel functions of individual proteins and novel protein functional groups we combine in protein association networks (i) a search for overlapping dense subgraphs based on the Clique Percolation Method (CPM) (Palla, G., et.al. Nature 435, 814-818 (2005), http://angel.elte.hu/clustering), which explicitly allows for overlaps among the groups, and (ii) a verification and characterization of the identified groups of nodes (proteins) with the help of standard annotation databases listing known functions.

Auditory Hallucinations and the Brain's Resting-State Networks: Findings and Methodological Observations.

PubMed

Alderson-Day, Ben; Diederen, Kelly; Fernyhough, Charles; Ford, Judith M; Horga, Guillermo; Margulies, Daniel S; McCarthy-Jones, Simon; Northoff, Georg; Shine, James M; Turner, Jessica; van de Ven, Vincent; van Lutterveld, Remko; Waters, Flavie; Jardri, Renaud

2016-09-01

In recent years, there has been increasing interest in the potential for alterations to the brain's resting-state networks (RSNs) to explain various kinds of psychopathology. RSNs provide an intriguing new explanatory framework for hallucinations, which can occur in different modalities and population groups, but which remain poorly understood. This collaboration from the International Consortium on Hallucination Research (ICHR) reports on the evidence linking resting-state alterations to auditory hallucinations (AH) and provides a critical appraisal of the methodological approaches used in this area. In the report, we describe findings from resting connectivity fMRI in AH (in schizophrenia and nonclinical individuals) and compare them with findings from neurophysiological research, structural MRI, and research on visual hallucinations (VH). In AH, various studies show resting connectivity differences in left-hemisphere auditory and language regions, as well as atypical interaction of the default mode network and RSNs linked to cognitive control and salience. As the latter are also evident in studies of VH, this points to a domain-general mechanism for hallucinations alongside modality-specific changes to RSNs in different sensory regions. However, we also observed high methodological heterogeneity in the current literature, affecting the ability to make clear comparisons between studies. To address this, we provide some methodological recommendations and options for future research on the resting state and hallucinations. © The Author 2016. Published by Oxford University Press on behalf of the Maryland Psychiatric Research Center.

Activities in a social networking-based discussion group by endoscopic retrograde cholangiopancreatography doctors.

PubMed

Kang, Xiaoyu; Zhao, Lina; Liu, Na; Wang, Xiangping; Zhang, Rongchun; Liu, Zhiguo; Liang, Shuhui; Yao, Shaowei; Tao, Qin; Jia, Hui; Pan, Yanglin; Guo, Xuegang

2017-10-01

Online social networking is increasingly being used among medical practitioners. However, few studies have evaluated its use in therapeutic endoscopy. Here, we aimed to analyze the shared topics and activities of a group of endoscopic retrograde cholangiopancreatography (ERCP) doctors in a social networking-based endoscopic retrograde cholangiopancreatography discussion group (EDG). Six ERCP trainers working in Xijing Hospital and 48 graduated endoscopists who had finished ERCP training in the same hospital were invited to join in EDG. All group members were informed not to divulge any private information of patients when using EDG. The activities of group members on EDG were retrospectively extracted. The individual data of the graduated endoscopists were collected by a questionnaire. From June 2014 to May 2015, 6924 messages were posted on EDG, half of which were ERCP related. In total, 214 ERCP-related topics were shared, which could be categorized into three types: sharing experience/cases (52.3%), asking questions (38.3%), and sharing literatures/advances (9.3%). Among the 48 graduated endoscopists, 21 had a low case volume of less than 50 per year and 27 had a high volume case volume of 50 or more. High-volume graduated endoscopists posted more ERCP-related messages (P=0.008) and shared more discussion topics (P=0.003) compared with low-volume graduated endoscopists. A survey showed that EDG was useful for graduated endoscopists in ERCP performance and management of post-ERCP complications, etc. A wide range of ERCP-related topics were shared on the social networking-based EDG. The ERCP-related behaviors on EDG were more active in graduated endoscopists with an ERCP case volume of more than 50 per year.

Distributed Observer Network (DON), Version 3.0, User's Guide

NASA Technical Reports Server (NTRS)

Mazzone, Rebecca A.; Conroy, Michael P.

2015-01-01

The Distributed Observer Network (DON) is a data presentation tool developed by the National Aeronautics and Space Administration (NASA) to distribute and publish simulation results. Leveraging the display capabilities inherent in modern gaming technology, DON places users in a fully navigable 3-D environment containing graphical models and allows the users to observe how those models evolve and interact over time in a given scenario. Each scenario is driven with data that has been generated by authoritative NASA simulation tools and exported in accordance with a published data interface specification. This decoupling of the data from the source tool enables DON to faithfully display a simulator's results and ensure that every simulation stakeholder will view the exact same information every time.

Influence of Choice of Null Network on Small-World Parameters of Structural Correlation Networks

PubMed Central

Hosseini, S. M. Hadi; Kesler, Shelli R.

2013-01-01

In recent years, coordinated variations in brain morphology (e.g., volume, thickness) have been employed as a measure of structural association between brain regions to infer large-scale structural correlation networks. Recent evidence suggests that brain networks constructed in this manner are inherently more clustered than random networks of the same size and degree. Thus, null networks constructed by randomizing topology are not a good choice for benchmarking small-world parameters of these networks. In the present report, we investigated the influence of choice of null networks on small-world parameters of gray matter correlation networks in healthy individuals and survivors of acute lymphoblastic leukemia. Three types of null networks were studied: 1) networks constructed by topology randomization (TOP), 2) networks matched to the distributional properties of the observed covariance matrix (HQS), and 3) networks generated from correlation of randomized input data (COR). The results revealed that the choice of null network not only influences the estimated small-world parameters, it also influences the results of between-group differences in small-world parameters. In addition, at higher network densities, the choice of null network influences the direction of group differences in network measures. Our data suggest that the choice of null network is quite crucial for interpretation of group differences in small-world parameters of structural correlation networks. We argue that none of the available null models is perfect for estimation of small-world parameters for correlation networks and the relative strengths and weaknesses of the selected model should be carefully considered with respect to obtained network measures. PMID:23840672

Graphing in Groups: Learning about Lines in a Collaborative Classroom Network Environment

ERIC Educational Resources Information Center

White, Tobin; Wallace, Matthew; Lai, Kevin

2012-01-01

This article presents a design experiment in which we explore new structures for classroom collaboration supported by a classroom network of handheld graphing calculators. We describe a design for small group investigations of linear functions and present findings from its implementation in three high school algebra classrooms. Our coding of the…

The Children's Oncology Group Childhood Cancer Research Network (CCRN): case catchment in the United States.

PubMed

Musselman, Jessica R B; Spector, Logan G; Krailo, Mark D; Reaman, Gregory H; Linabery, Amy M; Poynter, Jenny N; Stork, Susan K; Adamson, Peter C; Ross, Julie A

2014-10-01

The Childhood Cancer Research Network (CCRN) was established within the Children's Oncology Group (COG) in July 2008 to provide a centralized pediatric cancer research registry for investigators conducting approved etiologic and survivorship studies. The authors conducted an ecological analysis to characterize CCRN catchment at >200 COG institutions by demographic characteristics, diagnosis, and geographic location to determine whether the CCRN can serve as a population-based registry for childhood cancer. During 2009 to 2011, 18,580 US children newly diagnosed with cancer were registered in the CCRN. These observed cases were compared with age-specific, sex-specific, and race/ethnicity-specific expected numbers calculated from Surveillance, Epidemiology, and End Results (SEER) Program cancer incidence rates and 2010 US Census data. Overall, 42% of children (18,580 observed/44,267 expected) who were diagnosed with cancer at age <20 years were registered in the CCRN, including 45%, 57%, 51%, 44%, and 24% of those diagnosed at birth, ages 1 to 4 years, ages 5 to 9 years, ages 10 to 14 years, and ages 15 to 19 years, respectively. Some malignancies were better represented in the CCRN (leukemia, 59%; renal tumors, 67%) than others (retinoblastoma, 34%). There was little evidence of differences by sex or race/ethnicity, although rates in nonwhites were somewhat lower than rates in whites. Given the low observed-to-expected ratio, it will be important to identify challenges and barriers to registration to improve case ascertainment, especially for rarer diagnoses and older age groups; however, it is encouraging that some diagnoses in younger children are fairly representative of the population. Overall, the CCRN is providing centralized, real-time access to cases for research and could be used as a model for other national cooperative groups. © 2014 American Cancer Society.

Auditory Hallucinations and the Brain’s Resting-State Networks: Findings and Methodological Observations

PubMed Central

Alderson-Day, Ben; Diederen, Kelly; Fernyhough, Charles; Ford, Judith M.; Horga, Guillermo; Margulies, Daniel S.; McCarthy-Jones, Simon; Northoff, Georg; Shine, James M.; Turner, Jessica; van de Ven, Vincent; van Lutterveld, Remko; Waters, Flavie; Jardri, Renaud

2016-01-01

In recent years, there has been increasing interest in the potential for alterations to the brain’s resting-state networks (RSNs) to explain various kinds of psychopathology. RSNs provide an intriguing new explanatory framework for hallucinations, which can occur in different modalities and population groups, but which remain poorly understood. This collaboration from the International Consortium on Hallucination Research (ICHR) reports on the evidence linking resting-state alterations to auditory hallucinations (AH) and provides a critical appraisal of the methodological approaches used in this area. In the report, we describe findings from resting connectivity fMRI in AH (in schizophrenia and nonclinical individuals) and compare them with findings from neurophysiological research, structural MRI, and research on visual hallucinations (VH). In AH, various studies show resting connectivity differences in left-hemisphere auditory and language regions, as well as atypical interaction of the default mode network and RSNs linked to cognitive control and salience. As the latter are also evident in studies of VH, this points to a domain-general mechanism for hallucinations alongside modality-specific changes to RSNs in different sensory regions. However, we also observed high methodological heterogeneity in the current literature, affecting the ability to make clear comparisons between studies. To address this, we provide some methodological recommendations and options for future research on the resting state and hallucinations. PMID:27280452

Patient informed governance of distributed research networks: results and discussion from six patient focus groups.

PubMed

Mamo, Laura A; Browe, Dennis K; Logan, Holly C; Kim, Katherine K

2013-01-01

Understanding how to govern emerging distributed research networks is essential to their success. Distributed research networks aggregate patient medical data from many institutions leaving data within the local provider security system. While much is known about patients' views on secondary medical research, little is known about their views on governance of research networks. We conducted six focus groups with patients from three medical centers across the U.S. to understand their perspectives on privacy, consent, and ethical concerns of sharing their data as part of research networks. Participants positively endorsed sharing their health data with these networks believing that doing so could advance healthcare knowledge. However, patients expressed several concerns regarding security and broader ethical issues such as commercialism, public benefit, and social responsibility. We suggest that network governance guidelines move beyond strict technical requirements and address wider socio-ethical concerns by fully including patients in governance processes.

Patient Informed Governance of Distributed Research Networks: Results and Discussion from Six Patient Focus Groups

PubMed Central

Mamo, Laura A.; Browe, Dennis K.; Logan, Holly C.; Kim, Katherine K.

2013-01-01

Understanding how to govern emerging distributed research networks is essential to their success. Distributed research networks aggregate patient medical data from many institutions leaving data within the local provider security system. While much is known about patients’ views on secondary medical research, little is known about their views on governance of research networks. We conducted six focus groups with patients from three medical centers across the U.S. to understand their perspectives on privacy, consent, and ethical concerns of sharing their data as part of research networks. Participants positively endorsed sharing their health data with these networks believing that doing so could advance healthcare knowledge. However, patients expressed several concerns regarding security and broader ethical issues such as commercialism, public benefit, and social responsibility. We suggest that network governance guidelines move beyond strict technical requirements and address wider socio-ethical concerns by fully including patients in governance processes. PMID:24551383

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

PubMed Central

2014-01-01

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

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

PubMed

van Mierlo, Trevor

2014-02-04

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

Toward a national animal telemetry network for aquatic observations in the United States

USGS Publications Warehouse

Block, Barbara A.; Holbrook, Christopher; Simmons, Samantha E; Holland, Kim N; Ault, Jerald S.; Costa, Daniel P.; Mate, Bruce R; Seitz, Andrew C.; Arendt, Michael D.; Payne, John; Mahmoudi, Behzad; Moore, Peter L.; Price, James; J. J. Levenson,; Wilson, Doug; Kochevar, Randall E

2016-01-01

Animal telemetry is the science of elucidating the movements and behavior of animals in relation to their environment or habitat. Here, we focus on telemetry of aquatic species (marine mammals, sharks, fish, sea birds and turtles) and so are concerned with animal movements and behavior as they move through and above the world’s oceans, coastal rivers, estuaries and great lakes. Animal telemetry devices (“tags”) yield detailed data regarding animal responses to the coupled ocean–atmosphere and physical environment through which they are moving. Animal telemetry has matured and we describe a developing US Animal Telemetry Network (ATN) observing system that monitors aquatic life on a range of temporal and spatial scales that will yield both short- and long-term benefits, fill oceanographic observing and knowledge gaps and advance many of the U.S. National Ocean Policy Priority Objectives. ATN has the potential to create a huge impact for the ocean observing activities undertaken by the U.S. Integrated Ocean Observing System (IOOS) and become a model for establishing additional national-level telemetry networks worldwide.

Biologically plausible learning in recurrent neural networks reproduces neural dynamics observed during cognitive tasks

PubMed Central

Miconi, Thomas

2017-01-01

Neural activity during cognitive tasks exhibits complex dynamics that flexibly encode task-relevant variables. Chaotic recurrent networks, which spontaneously generate rich dynamics, have been proposed as a model of cortical computation during cognitive tasks. However, existing methods for training these networks are either biologically implausible, and/or require a continuous, real-time error signal to guide learning. Here we show that a biologically plausible learning rule can train such recurrent networks, guided solely by delayed, phasic rewards at the end of each trial. Networks endowed with this learning rule can successfully learn nontrivial tasks requiring flexible (context-dependent) associations, memory maintenance, nonlinear mixed selectivities, and coordination among multiple outputs. The resulting networks replicate complex dynamics previously observed in animal cortex, such as dynamic encoding of task features and selective integration of sensory inputs. We conclude that recurrent neural networks offer a plausible model of cortical dynamics during both learning and performance of flexible behavior. DOI: http://dx.doi.org/10.7554/eLife.20899.001 PMID:28230528

Biologically plausible learning in recurrent neural networks reproduces neural dynamics observed during cognitive tasks.

PubMed

Miconi, Thomas

2017-02-23

Neural activity during cognitive tasks exhibits complex dynamics that flexibly encode task-relevant variables. Chaotic recurrent networks, which spontaneously generate rich dynamics, have been proposed as a model of cortical computation during cognitive tasks. However, existing methods for training these networks are either biologically implausible, and/or require a continuous, real-time error signal to guide learning. Here we show that a biologically plausible learning rule can train such recurrent networks, guided solely by delayed, phasic rewards at the end of each trial. Networks endowed with this learning rule can successfully learn nontrivial tasks requiring flexible (context-dependent) associations, memory maintenance, nonlinear mixed selectivities, and coordination among multiple outputs. The resulting networks replicate complex dynamics previously observed in animal cortex, such as dynamic encoding of task features and selective integration of sensory inputs. We conclude that recurrent neural networks offer a plausible model of cortical dynamics during both learning and performance of flexible behavior.

Spatial Representativeness Error in the Ground-Level Observation Networks for Black Carbon Radiation Absorption

NASA Astrophysics Data System (ADS)

Wang, Rong; Andrews, Elisabeth; Balkanski, Yves; Boucher, Olivier; Myhre, Gunnar; Samset, Bjørn Hallvard; Schulz, Michael; Schuster, Gregory L.; Valari, Myrto; Tao, Shu

2018-02-01

There is high uncertainty in the direct radiative forcing of black carbon (BC), an aerosol that strongly absorbs solar radiation. The observation-constrained estimate, which is several times larger than the bottom-up estimate, is influenced by the spatial representativeness error due to the mesoscale inhomogeneity of the aerosol fields and the relatively low resolution of global chemistry-transport models. Here we evaluated the spatial representativeness error for two widely used observational networks (AErosol RObotic NETwork and Global Atmosphere Watch) by downscaling the geospatial grid in a global model of BC aerosol absorption optical depth to 0.1° × 0.1°. Comparing the models at a spatial resolution of 2° × 2° with BC aerosol absorption at AErosol RObotic NETwork sites (which are commonly located near emission hot spots) tends to cause a global spatial representativeness error of 30%, as a positive bias for the current top-down estimate of global BC direct radiative forcing. By contrast, the global spatial representativeness error will be 7% for the Global Atmosphere Watch network, because the sites are located in such a way that there are almost an equal number of sites with positive or negative representativeness error.

Discriminating response groups in metabolic and regulatory pathway networks.

PubMed

Van Hemert, John L; Dickerson, Julie A

2012-04-01

Analysis of omics experiments generates lists of entities (genes, metabolites, etc.) selected based on specific behavior, such as changes in response to stress or other signals. Functional interpretation of these lists often uses category enrichment tests using functional annotations like Gene Ontology terms and pathway membership. This approach does not consider the connected structure of biochemical pathways or the causal directionality of events. The Omics Response Group (ORG) method, described in this work, interprets omics lists in the context of metabolic pathway and regulatory networks using a statistical model for flow within the networks. Statistical results for all response groups are visualized in a novel Pathway Flow plot. The statistical tests are based on the Erlang distribution model under the assumption of independent and identically Exponential-distributed random walk flows through pathways. As a proof of concept, we applied our method to an Escherichia coli transcriptomics dataset where we confirmed common knowledge of the E.coli transcriptional response to Lipid A deprivation. The main response is related to osmotic stress, and we were also able to detect novel responses that are supported by the literature. We also applied our method to an Arabidopsis thaliana expression dataset from an abscisic acid study. In both cases, conventional pathway enrichment tests detected nothing, while our approach discovered biological processes beyond the original studies. We created a prototype for an interactive ORG web tool at http://ecoserver.vrac.iastate.edu/pathwayflow (source code is available from https://subversion.vrac.iastate.edu/Subversion/jlv/public/jlv/pathwayflow). The prototype is described along with additional figures and tables in Supplementary Material. julied@iastate.edu Supplementary data are available at Bioinformatics online.

Integration of numerical modeling and observations for the Gulf of Naples monitoring network

NASA Astrophysics Data System (ADS)

Iermano, I.; Uttieri, M.; Zambianchi, E.; Buonocore, B.; Cianelli, D.; Falco, P.; Zambardino, G.

2012-04-01

Lethal effects of mineral oils on fragile marine and coastal ecosystems are now well known. Risks and damages caused by a maritime accident can be reduced with the help of better forecasts and efficient monitoring systems. The MED project TOSCA (Tracking Oil Spills and Coastal Awareness Network), which gathers 13 partners from 4 Mediterranean countries, has been designed to help create a better response system to maritime accidents. Through the construction of an observational network, based on state of the art technology (HF radars and drifters), TOSCA provides real-time observations and forecasts of the Mediterranean coastal marine environmental conditions. The system is installed and assessed in five test sites on the coastal areas of oil spill outlets (Eastern Mediterranean) and on high traffic areas (Western Mediterranean). The Gulf of Naples, a small semi-closed basin opening to the Tyrrhenian Sea is one of the five test-sites. It is of particular interest from both the environmental point of view, due to peculiar ecosystem properties in the area, and because it sustains important touristic and commercial activities. Currently the Gulf of Naples monitoring network is represented by five automatic weather stations distributed along the coasts of the Gulf, one weather radar, two tide gauges, one waverider buoy, and moored physical, chemical and bio-optical instrumentation. In addition, a CODAR-SeaSonde HF coastal radar system composed of three antennas is located in Portici, Massa Lubrense and Castellammare. The system provides hourly data of surface currents over the entire Gulf with a 1km spatial resolution. A numerical modeling implementation based on Regional Ocean Modeling System (ROMS) is actually integrated in the Gulf of Naples monitoring network. ROMS is a 3-D, free-surface, hydrostatic, primitive equation, finite difference ocean model. In our configuration, the model has high horizontal resolution (250m), and 30 sigma levels in the vertical. Thanks

Global network structure of dominance hierarchy of ant workers.

PubMed

Shimoji, Hiroyuki; Abe, Masato S; Tsuji, Kazuki; Masuda, Naoki

2014-10-06

Dominance hierarchy among animals is widespread in various species and believed to serve to regulate resource allocation within an animal group. Unlike small groups, however, detection and quantification of linear hierarchy in large groups of animals are a difficult task. Here, we analyse aggression-based dominance hierarchies formed by worker ants in Diacamma sp. as large directed networks. We show that the observed dominance networks are perfect or approximate directed acyclic graphs, which are consistent with perfect linear hierarchy. The observed networks are also sparse and random but significantly different from networks generated through thinning of the perfect linear tournament (i.e. all individuals are linearly ranked and dominance relationship exists between every pair of individuals). These results pertain to global structure of the networks, which contrasts with the previous studies inspecting frequencies of different types of triads. In addition, the distribution of the out-degree (i.e. number of workers that the focal worker attacks), not in-degree (i.e. number of workers that attack the focal worker), of each observed network is right-skewed. Those having excessively large out-degrees are located near the top, but not the top, of the hierarchy. We also discuss evolutionary implications of the discovered properties of dominance networks. © 2014 The Author(s) Published by the Royal Society. All rights reserved.

Applications of neural network methods to the processing of earth observation satellite data.

PubMed

Loyola, Diego G

2006-03-01

The new generation of earth observation satellites carries advanced sensors that will gather very precise data for studying the Earth system and global climate. This paper shows that neural network methods can be successfully used for solving forward and inverse remote sensing problems, providing both accurate and fast solutions. Two examples of multi-neural network systems for the determination of cloud properties and for the retrieval of total columns of ozone using satellite data are presented. The developed algorithms based on multi-neural network are currently being used for the operational processing of European atmospheric satellite sensors and will play a key role in related satellite missions planed for the near future.

76 FR 2145 - Masco Builder Cabinet Group Including On-Site Leased Workers From Reserves Network, Jackson, OH...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-01-12

...,287B; TA-W-71,287C] Masco Builder Cabinet Group Including On-Site Leased Workers From Reserves Network, Jackson, OH; Masco Builder Cabinet Group, Waverly, OH; Masco Builder Cabinet Group, Seal Township, OH; Masco Builder Cabinet Group, Seaman, OH; Amended Certification Regarding Eligibility To Apply for Worker...

Lognormal kriging for the assessment of reliability in groundwater quality control observation networks

USGS Publications Warehouse

Candela, L.; Olea, R.A.; Custodio, E.

1988-01-01

Groundwater quality observation networks are examples of discontinuous sampling on variables presenting spatial continuity and highly skewed frequency distributions. Anywhere in the aquifer, lognormal kriging provides estimates of the variable being sampled and a standard error of the estimate. The average and the maximum standard error within the network can be used to dynamically improve the network sampling efficiency or find a design able to assure a given reliability level. The approach does not require the formulation of any physical model for the aquifer or any actual sampling of hypothetical configurations. A case study is presented using the network monitoring salty water intrusion into the Llobregat delta confined aquifer, Barcelona, Spain. The variable chloride concentration used to trace the intrusion exhibits sudden changes within short distances which make the standard error fairly invariable to changes in sampling pattern and to substantial fluctuations in the number of wells. ?? 1988.

Optimizing Observation Networks Combining Ships of Opportunity, Gliders, Moored Buoys and FerryBox in the Bay of Biscay and English Channel

NASA Astrophysics Data System (ADS)

Charria, G.; Lamouroux, J.; De Mey, P. J.; Raynaud, S.; Heyraud, C.; Craneguy, P.; Dumas, F.; Le Henaff, M.

2016-02-01

Designing optimal observation networks in coastal oceans remains one of the major challenges towards the implementation of future Integrated Ocean Observing Systems to monitor the coastal environment. In the Bay of Biscay and the English Channel, the diversity of involved processes requires to adapt observing systems to the specific targeted environments. Also important is the requirement for those systems to sustain coastal applications. An efficient way to measure the hydrological content of the water column over the continental shelf is to consider ships of opportunity. In the French observation strategy, the RECOPESCA program, as a component of the High frequency Observation network for the environment in coastal SEAs (HOSEA), aims to collect environmental observations from sensors attached to fishing nets. In the present study, we assess that network performances using the ArM method (Le Hénaff et al., 2009). A reference network, based on fishing vessels observations in 2008, is assessed using that method. Moreover, three scenarios, based on the reference network, a denser network in 2010 and a fictive network aggregated from a pluri-annual collection of profiles, are also analyzed. Two other observational network design experiments have been implemented for the spring season in two regions: 1) the Loire River plume (northern part of the Bay of Biscay) to explore different possible glider endurance lines combined with a fixed mooring to monitor temperature and salinity and 2) the Western English Channel using a glider below FerryBox measurements. These experiments combining existing and future observing systems, as well as numerical ensemble simulations, highlight the key issue of monitoring the whole water column in and close to river plumes (e.g. using gliders), the efficiency of the surface high frequency sampling from FerryBoxes in macrotidal regions and the importance of sampling key regions instead of increasing the number of Voluntary Observing Ships.

Towards Determining the Optimal Density of Groundwater Observation Networks under Uncertainty

NASA Astrophysics Data System (ADS)

Langousis, Andreas; Kaleris, Vassilios; Kokosi, Angeliki; Mamounakis, Georgios

2016-04-01

Time series of groundwater level constitute one of the main sources of information when studying the availability of ground water reserves, at a regional level, under changing climatic conditions. To that extent, one needs groundwater observation networks that can provide sufficient information to estimate the hydraulic head at unobserved locations. The density of such networks is largely influenced by the structure of the aquifer, and in particular by the spatial distribution of hydraulic conductivity (i.e. layering), dependencies in the transition rates between different geologic formations, juxtapositional tendencies, etc. In this work, we: 1) use the concept of transition probabilities embedded in a Markov chain setting to conditionally simulate synthetic aquifer structures representative of geologic formations commonly found in the literature (see e.g. Hoeksema and Kitanidis, 1985), and 2) study how the density of observation wells affects the estimation accuracy of hydraulic heads at unobserved locations. The obtained results are promising, pointing towards the direction of establishing design criteria based on the statistical structure of the aquifer, such as the level of dependence in the transition rates of observed lithologies. Reference: Hoeksema, R.J. and P.K. Kitanidis (1985) Analysis of spatial structure of properties of selected aquifers, Water Resources Research, 21(4), 563-572. Acknowledgments: This work is sponsored by the Onassis Foundation under the "Special Grant and Support Program for Scholars' Association Members".

Learning characteristics of a space-time neural network as a tether skiprope observer

NASA Technical Reports Server (NTRS)

Lea, Robert N.; Villarreal, James A.; Jani, Yashvant; Copeland, Charles

1992-01-01

The Software Technology Laboratory at JSC is testing a Space Time Neural Network (STNN) for observing tether oscillations present during retrieval of a tethered satellite. Proper identification of tether oscillations, known as 'skiprope' motion, is vital to safe retrieval of the tethered satellite. Our studies indicate that STNN has certain learning characteristics that must be understood properly to utilize this type of neural network for the tethered satellite problem. We present our findings on the learning characteristics including a learning rate versus momentum performance table.

Distributed Computer Networks in Support of Complex Group Practices

PubMed Central

Wess, Bernard P.

1978-01-01

The economics of medical computer networks are presented in context with the patient care and administrative goals of medical networks. Design alternatives and network topologies are discussed with an emphasis on medical network design requirements in distributed data base design, telecommunications, satellite systems, and software engineering. The success of the medical computer networking technology is predicated on the ability of medical and data processing professionals to design comprehensive, efficient, and virtually impenetrable security systems to protect data bases, network access and services, and patient confidentiality.

SUZAKU OBSERVATIONS OF THE X-RAY BRIGHTEST FOSSIL GROUP ESO 3060170

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

Su, Yuanyuan; White, Raymond E. III; Miller, Eric D., E-mail: ysu@crimson.ua.edu

2013-10-01

'Fossil' galaxy groups, each dominated by a relatively isolated giant elliptical galaxy, have many properties intermediate between groups and clusters of galaxies. We used the Suzaku X-ray observatory to observe the X-ray brightest fossil group, ESO 3060170, out to R{sub 200}, in order to better elucidate the relation between fossil groups, normal groups, and clusters. We determined the intragroup gas temperature, density, and metal abundance distributions and derived the entropy, pressure, and mass profiles for this group. The entropy and pressure profiles in the outer regions are flatter than in simulated clusters, similar to what is seen in observations ofmore » massive clusters. This may indicate that the gas is clumpy and/or the gas has been redistributed. Assuming hydrostatic equilibrium, the total mass is estimated to be ∼1.7 × 10{sup 14} M{sub ☉} within a radius R{sub 200} of ∼1.15 Mpc, with an enclosed baryon mass fraction of 0.13. The integrated iron mass-to-light ratio of this fossil group is larger than in most groups and comparable to those of clusters, indicating that this fossil group has retained the bulk of its metals. A galaxy luminosity density map on a scale of 25 Mpc shows that this fossil group resides in a relatively isolated environment, unlike the filamentary structures in which typical groups and clusters are embedded.« less

NON-POTENTIAL FIELDS IN THE QUIET SUN NETWORK: EXTREME-ULTRAVIOLET AND MAGNETIC FOOTPOINT OBSERVATIONS

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

Chesny, D. L.; Oluseyi, H. M.; Orange, N. B.

The quiet Sun (QS) magnetic network is known to contain dynamics which are indicative of non-potential fields. Non-potential magnetic fields forming ''S-shaped'' loop arcades can lead to the breakdown of static activity and have only been observed in high temperature X-ray coronal structures—some of which show eruptive behavior. Thus, analysis of this type of atmospheric structuring has been restricted to large-scale coronal fields. Here we provide the first identification of non-potential loop arcades exclusive to the QS supergranulation network. High-resolution Atmospheric Imaging Assembly data from the Solar Dynamics Observatory have allowed for the first observations of fine-scale ''S-shaped'' loop arcadesmore » spanning the network. We have investigated the magnetic footpoint flux evolution of these arcades from Heliospheric and Magnetic Imager data and find evidence of evolving footpoint flux imbalances accompanying the formation of these non-potential fields. The existence of such non-potentiality confirms that magnetic field dynamics leading to the build up of helicity exist at small scales. QS non-potentiality also suggests a self-similar formation process between the QS network and high temperature corona and the existence of self-organized criticality (SOC) in the form of loop-pair reconnection and helicity dissipation. We argue that this type of behavior could lead to eruptive forms of SOC as seen in active region (AR) and X-ray sigmoids if sufficient free magnetic energy is available. QS magnetic network dynamics may be considered as a coronal proxy at supergranular scales, and events confined to the network can even mimic those in coronal ARs.« less

Observer-based consensus of networked thrust-propelled vehicles with directed graphs.

PubMed

Cang, Weiye; Li, Zhongkui; Wang, Hanlei

2017-11-01

In this paper, we investigate the consensus problem for networked underactuated thrust-propelled vehicles (TPVs) interacting on directed graphs. We propose distributed observer-based consensus protocols, which avoid the reliance on the measurements of translational velocities and accelerations. Using the input-output analysis, we present necessary and sufficient conditions to ensure that the observer-based protocols can achieve consensus for both the cases without and with constant communication delays, provided that the communication graph contains a directed spanning tree. Simulation examples are finally provided to illustrate the effectiveness of the control schemes. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Multifractal cross-correlation effects in two-variable time series of complex network vertex observables

NASA Astrophysics Data System (ADS)

OświÈ©cimka, Paweł; Livi, Lorenzo; DroŻdŻ, Stanisław

2016-10-01

We investigate the scaling of the cross-correlations calculated for two-variable time series containing vertex properties in the context of complex networks. Time series of such observables are obtained by means of stationary, unbiased random walks. We consider three vertex properties that provide, respectively, short-, medium-, and long-range information regarding the topological role of vertices in a given network. In order to reveal the relation between these quantities, we applied the multifractal cross-correlation analysis technique, which provides information about the nonlinear effects in coupling of time series. We show that the considered network models are characterized by unique multifractal properties of the cross-correlation. In particular, it is possible to distinguish between Erdös-Rényi, Barabási-Albert, and Watts-Strogatz networks on the basis of fractal cross-correlation. Moreover, the analysis of protein contact networks reveals characteristics shared with both scale-free and small-world models.

Confronting weather and climate models with observational data from soil moisture networks over the United States

PubMed Central

Dirmeyer, Paul A.; Wu, Jiexia; Norton, Holly E.; Dorigo, Wouter A.; Quiring, Steven M.; Ford, Trenton W.; Santanello, Joseph A.; Bosilovich, Michael G.; Ek, Michael B.; Koster, Randal D.; Balsamo, Gianpaolo; Lawrence, David M.

2018-01-01

Four land surface models in uncoupled and coupled configurations are compared to observations of daily soil moisture from 19 networks in the conterminous United States to determine the viability of such comparisons and explore the characteristics of model and observational data. First, observations are analyzed for error characteristics and representation of spatial and temporal variability. Some networks have multiple stations within an area comparable to model grid boxes; for those we find that aggregation of stations before calculation of statistics has little effect on estimates of variance, but soil moisture memory is sensitive to aggregation. Statistics for some networks stand out as unlike those of their neighbors, likely due to differences in instrumentation, calibration and maintenance. Buried sensors appear to have less random error than near-field remote sensing techniques, and heat dissipation sensors show less temporal variability than other types. Model soil moistures are evaluated using three metrics: standard deviation in time, temporal correlation (memory) and spatial correlation (length scale). Models do relatively well in capturing large-scale variability of metrics across climate regimes, but poorly reproduce observed patterns at scales of hundreds of kilometers and smaller. Uncoupled land models do no better than coupled model configurations, nor do reanalyses outperform free-running models. Spatial decorrelation scales are found to be difficult to diagnose. Using data for model validation, calibration or data assimilation from multiple soil moisture networks with different types of sensors and measurement techniques requires great caution. Data from models and observations should be put on the same spatial and temporal scales before comparison. PMID:29645013

Confronting Weather and Climate Models with Observational Data from Soil Moisture Networks over the United States

NASA Technical Reports Server (NTRS)

Dirmeyer, Paul A.; Wu, Jiexia; Norton, Holly E.; Dorigo, Wouter A.; Quiring, Steven M.; Ford, Trenton W.; Santanello, Joseph A., Jr.; Bosilovich, Michael G.; Ek, Michael B.; Koster, Randal Dean;

Confronting weather and climate models with observational data from soil moisture networks over the United States.

PubMed

Dirmeyer, Paul A; Wu, Jiexia; Norton, Holly E; Dorigo, Wouter A; Quiring, Steven M; Ford, Trenton W; Santanello, Joseph A; Bosilovich, Michael G; Ek, Michael B; Koster, Randal D; Balsamo, Gianpaolo; Lawrence, David M

2016-04-01

Four land surface models in uncoupled and coupled configurations are compared to observations of daily soil moisture from 19 networks in the conterminous United States to determine the viability of such comparisons and explore the characteristics of model and observational data. First, observations are analyzed for error characteristics and representation of spatial and temporal variability. Some networks have multiple stations within an area comparable to model grid boxes; for those we find that aggregation of stations before calculation of statistics has little effect on estimates of variance, but soil moisture memory is sensitive to aggregation. Statistics for some networks stand out as unlike those of their neighbors, likely due to differences in instrumentation, calibration and maintenance. Buried sensors appear to have less random error than near-field remote sensing techniques, and heat dissipation sensors show less temporal variability than other types. Model soil moistures are evaluated using three metrics: standard deviation in time, temporal correlation (memory) and spatial correlation (length scale). Models do relatively well in capturing large-scale variability of metrics across climate regimes, but poorly reproduce observed patterns at scales of hundreds of kilometers and smaller. Uncoupled land models do no better than coupled model configurations, nor do reanalyses outperform free-running models. Spatial decorrelation scales are found to be difficult to diagnose. Using data for model validation, calibration or data assimilation from multiple soil moisture networks with different types of sensors and measurement techniques requires great caution. Data from models and observations should be put on the same spatial and temporal scales before comparison.

Learning characteristics of a space-time neural network as a tether skiprope observer

NASA Technical Reports Server (NTRS)

Lea, Robert N.; Villarreal, James A.; Jani, Yashvant; Copeland, Charles

1993-01-01

The Software Technology Laboratory at the Johnson Space Center is testing a Space Time Neural Network (STNN) for observing tether oscillations present during retrieval of a tethered satellite. Proper identification of tether oscillations, known as 'skiprope' motion, is vital to safe retrieval of the tethered satellite. Our studies indicate that STNN has certain learning characteristics that must be understood properly to utilize this type of neural network for the tethered satellite problem. We present our findings on the learning characteristics including a learning rate versus momentum performance table.

Network evaluation: principles, structures and outcomes of the German working group of Health Promoting Universities.

PubMed

Stock, Christiane; Milz, Simone; Meier, Sabine

2010-03-01

With more than 60 participating universities, the German working group of Health Promoting Universities (German HPU network) is the largest and most active network of universities as healthy settings. This study aims at evaluating processes and effects of the German HPU network and at supporting the future development of the network. The evaluation was based on the multi faceted network assessment instrument developed by Broesskamp-Stone (7). We used a document analysis, two expert interviews and a survey among members (n = 33) to collect relevant data for the assessment. The analysis showed that the visions of the network can be regarded as fulfilled in most aspects. The members of the network received network support through trustful and mutual relationships. The network ranked high on general network principles like implementation of mutual relationships, sharing of information, risks and resources, equal access to resources, responsibility and consensus orientation. However, a high degree of centralization was found as a negative indicator. Other critical aspects of the network's structures and processes have been the regional predominance of universities from the northern and middle part of Germany, the low representation of students in the network, and the low proportion of members that could successfully implement health promotion into the guiding principles of their university. Overall, the evaluation has shown that the network has worked effectively, has developed meaningful processes and structures and has formulated practical guidelines. Since its 12 years of existence the German HPU network has been able to adapt and to adequately respond to changing contextual conditions regarding health promotion at universities in Germany. The network should develop strategies to counteract the critical aspects and detected imbalances in order to further increase its impact on universities as healthy settings.

Configuring compute nodes of a parallel computer in an operational group into a plurality of independent non-overlapping collective networks

DOEpatents

Archer, Charles J.; Inglett, Todd A.; Ratterman, Joseph D.; Smith, Brian E.

2010-03-02

Methods, apparatus, and products are disclosed for configuring compute nodes of a parallel computer in an operational group into a plurality of independent non-overlapping collective networks, the compute nodes in the operational group connected together for data communications through a global combining network, that include: partitioning the compute nodes in the operational group into a plurality of non-overlapping subgroups; designating one compute node from each of the non-overlapping subgroups as a master node; and assigning, to the compute nodes in each of the non-overlapping subgroups, class routing instructions that organize the compute nodes in that non-overlapping subgroup as a collective network such that the master node is a physical root.

Revealing the hidden networks of interaction in mobile animal groups allows prediction of complex behavioral contagion.

PubMed

Rosenthal, Sara Brin; Twomey, Colin R; Hartnett, Andrew T; Wu, Hai Shan; Couzin, Iain D

2015-04-14

Coordination among social animals requires rapid and efficient transfer of information among individuals, which may depend crucially on the underlying structure of the communication network. Establishing the decision-making circuits and networks that give rise to individual behavior has been a central goal of neuroscience. However, the analogous problem of determining the structure of the communication network among organisms that gives rise to coordinated collective behavior, such as is exhibited by schooling fish and flocking birds, has remained almost entirely neglected. Here, we study collective evasion maneuvers, manifested through rapid waves, or cascades, of behavioral change (a ubiquitous behavior among taxa) in schooling fish (Notemigonus crysoleucas). We automatically track the positions and body postures, calculate visual fields of all individuals in schools of ∼150 fish, and determine the functional mapping between socially generated sensory input and motor response during collective evasion. We find that individuals use simple, robust measures to assess behavioral changes in neighbors, and that the resulting networks by which behavior propagates throughout groups are complex, being weighted, directed, and heterogeneous. By studying these interaction networks, we reveal the (complex, fractional) nature of social contagion and establish that individuals with relatively few, but strongly connected, neighbors are both most socially influential and most susceptible to social influence. Furthermore, we demonstrate that we can predict complex cascades of behavioral change at their moment of initiation, before they actually occur. Consequently, despite the intrinsic stochasticity of individual behavior, establishing the hidden communication networks in large self-organized groups facilitates a quantitative understanding of behavioral contagion.

Revealing the hidden networks of interaction in mobile animal groups allows prediction of complex behavioral contagion

PubMed Central

Rosenthal, Sara Brin; Twomey, Colin R.; Hartnett, Andrew T.; Wu, Hai Shan; Couzin, Iain D.

2015-01-01

Coordination among social animals requires rapid and efficient transfer of information among individuals, which may depend crucially on the underlying structure of the communication network. Establishing the decision-making circuits and networks that give rise to individual behavior has been a central goal of neuroscience. However, the analogous problem of determining the structure of the communication network among organisms that gives rise to coordinated collective behavior, such as is exhibited by schooling fish and flocking birds, has remained almost entirely neglected. Here, we study collective evasion maneuvers, manifested through rapid waves, or cascades, of behavioral change (a ubiquitous behavior among taxa) in schooling fish (Notemigonus crysoleucas). We automatically track the positions and body postures, calculate visual fields of all individuals in schools of ∼150 fish, and determine the functional mapping between socially generated sensory input and motor response during collective evasion. We find that individuals use simple, robust measures to assess behavioral changes in neighbors, and that the resulting networks by which behavior propagates throughout groups are complex, being weighted, directed, and heterogeneous. By studying these interaction networks, we reveal the (complex, fractional) nature of social contagion and establish that individuals with relatively few, but strongly connected, neighbors are both most socially influential and most susceptible to social influence. Furthermore, we demonstrate that we can predict complex cascades of behavioral change at their moment of initiation, before they actually occur. Consequently, despite the intrinsic stochasticity of individual behavior, establishing the hidden communication networks in large self-organized groups facilitates a quantitative understanding of behavioral contagion. PMID:25825752

The Quake-Catcher Network: Improving Earthquake Strong Motion Observations Through Community Engagement

NASA Astrophysics Data System (ADS)

Cochran, E. S.; Lawrence, J. F.; Christensen, C. M.; Chung, A. I.; Neighbors, C.; Saltzman, J.

2010-12-01

The Quake-Catcher Network (QCN) involves the community in strong motion data collection by utilizing volunteer computing techniques and low-cost MEMS accelerometers. Volunteer computing provides a mechanism to expand strong-motion seismology with minimal infrastructure costs, while promoting community participation in science. Micro-Electro-Mechanical Systems (MEMS) triaxial accelerometers can be attached to a desktop computer via USB and are internal to many laptops. Preliminary shake table tests show the MEMS accelerometers can record high-quality seismic data with instrument response similar to research-grade strong-motion sensors. QCN began distributing sensors and software to K-12 schools and the general public in April 2008 and has grown to roughly 1500 stations worldwide. We also recently tested whether sensors could be quickly deployed as part of a Rapid Aftershock Mobilization Program (RAMP) following the 2010 M8.8 Maule, Chile earthquake. Volunteers are recruited through media reports, web-based sensor request forms, as well as social networking sites. Using data collected to date, we examine whether a distributed sensing network can provide valuable seismic data for earthquake detection and characterization while promoting community participation in earthquake science. We utilize client-side triggering algorithms to determine when significant ground shaking occurs and this metadata is sent to the main QCN server. On average, trigger metadata are received within 1-10 seconds from the observation of a trigger; the larger data latencies are correlated with greater server-station distances. When triggers are detected, we determine if the triggers correlate to others in the network using spatial and temporal clustering of incoming trigger information. If a minimum number of triggers are detected then a QCN-event is declared and an initial earthquake location and magnitude is estimated. Initial analysis suggests that the estimated locations and magnitudes are

Parallel Group and Sunspot Counts from SDO/HMI and AAVSO Visual Observers (Abstract)

NASA Astrophysics Data System (ADS)

Howe, R.; Alvestad, J.

2015-06-01

(Abstract only) Creating group and sunspot counts from the SDO/HMI detector on the Solar Dynamics Observatory (SDO) satellite requires software that calculates sunspots from a “white light” intensity-gram (CCD image) and group counts from a filtered CCD magneto-gram. Images from the satellite come from here http://jsoc.stanford.edu/data/hmi/images/latest/ Together these two sets of images can be used to estimate the Wolf number as W = (10g + s), which is used to calculate the American Relative index. AAVSO now has approximately two years of group and sunspot counts in the SunEntry database as SDOH observer Jan Alvestad. It is important that we compare these satellite CCD image data with our visual observer daily submissions to determine if the SDO/HMI data should be included in calculating the American Relative index. These satellite data are continuous observations with excellent seeing. This contrasts with “snapshot” earth-based observations with mixed seeing. The SDO/HIM group and sunspot counts could be considered unbiased, except that they show a not normal statistical distribution when compared to the overall visual observations, which show a Poisson distribution. One challenge that should be addressed by AAVSO using these SDO/HMI data is the splitting of groups and deriving group properties from the magneto-grams. The filtered CCD detector that creates the magento-grams is not something our visual observers can relate too, unless they were to take CCD images in H-alpha and/or the Calcium spectrum line. So, questions remain as to how these satellite CCD image counts can be integrated into the overall American Relative index.

Network-constrained group lasso for high-dimensional multinomial classification with application to cancer subtype prediction.

PubMed

Tian, Xinyu; Wang, Xuefeng; Chen, Jun

2014-01-01

Classic multinomial logit model, commonly used in multiclass regression problem, is restricted to few predictors and does not take into account the relationship among variables. It has limited use for genomic data, where the number of genomic features far exceeds the sample size. Genomic features such as gene expressions are usually related by an underlying biological network. Efficient use of the network information is important to improve classification performance as well as the biological interpretability. We proposed a multinomial logit model that is capable of addressing both the high dimensionality of predictors and the underlying network information. Group lasso was used to induce model sparsity, and a network-constraint was imposed to induce the smoothness of the coefficients with respect to the underlying network structure. To deal with the non-smoothness of the objective function in optimization, we developed a proximal gradient algorithm for efficient computation. The proposed model was compared to models with no prior structure information in both simulations and a problem of cancer subtype prediction with real TCGA (the cancer genome atlas) gene expression data. The network-constrained mode outperformed the traditional ones in both cases.

A biophysical observation model for field potentials of networks of leaky integrate-and-fire neurons.

PubMed

Beim Graben, Peter; Rodrigues, Serafim

2012-01-01

We present a biophysical approach for the coupling of neural network activity as resulting from proper dipole currents of cortical pyramidal neurons to the electric field in extracellular fluid. Starting from a reduced three-compartment model of a single pyramidal neuron, we derive an observation model for dendritic dipole currents in extracellular space and thereby for the dendritic field potential (DFP) that contributes to the local field potential (LFP) of a neural population. This work aligns and satisfies the widespread dipole assumption that is motivated by the "open-field" configuration of the DFP around cortical pyramidal cells. Our reduced three-compartment scheme allows to derive networks of leaky integrate-and-fire (LIF) models, which facilitates comparison with existing neural network and observation models. In particular, by means of numerical simulations we compare our approach with an ad hoc model by Mazzoni et al. (2008), and conclude that our biophysically motivated approach yields substantial improvement.

A biophysical observation model for field potentials of networks of leaky integrate-and-fire neurons

PubMed Central

beim Graben, Peter; Rodrigues, Serafim

2013-01-01

We present a biophysical approach for the coupling of neural network activity as resulting from proper dipole currents of cortical pyramidal neurons to the electric field in extracellular fluid. Starting from a reduced three-compartment model of a single pyramidal neuron, we derive an observation model for dendritic dipole currents in extracellular space and thereby for the dendritic field potential (DFP) that contributes to the local field potential (LFP) of a neural population. This work aligns and satisfies the widespread dipole assumption that is motivated by the “open-field” configuration of the DFP around cortical pyramidal cells. Our reduced three-compartment scheme allows to derive networks of leaky integrate-and-fire (LIF) models, which facilitates comparison with existing neural network and observation models. In particular, by means of numerical simulations we compare our approach with an ad hoc model by Mazzoni et al. (2008), and conclude that our biophysically motivated approach yields substantial improvement. PMID:23316157

76 FR 28499 - Data Fortress Systems Group Ltd., Digital Youth Network Corp., Fantom Technologies, Inc., and KIK...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-05-17

... SECURITIES AND EXCHANGE COMMISSION [File No. 500-1] Data Fortress Systems Group Ltd., Digital Youth Network Corp., Fantom Technologies, Inc., and KIK Technology International, Inc., Order of... of current and accurate information concerning the securities of Data Fortress Systems Group Ltd...

Principles of data integration and interoperability in the GEO Biodiversity Observation Network

NASA Astrophysics Data System (ADS)

Saarenmaa, Hannu; Ó Tuama, Éamonn

2010-05-01

The goal of the Global Earth Observation System of Systems (GEOSS) is to link existing information systems into a global and flexible network to address nine areas of critical importance to society. One of these "societal benefit areas" is biodiversity and it will be supported by a GEOSS sub-system known as the GEO Biodiversity Observation Network (GEO BON). In planning the GEO BON, it was soon recognised that there are already a multitude of existing networks and initiatives in place worldwide. What has been lacking is a coordinated framework that allows for information sharing and exchange between the networks. Traversing across the various scales of biodiversity, in particular from the individual and species levels to the ecosystems level has long been a challenge. Furthermore, some of the major regions of the world have already taken steps to coordinate their efforts, but links between the regions have not been a priority until now. Linking biodiversity data to that of the other GEO societal benefit areas, in particular ecosystems, climate, and agriculture to produce useful information for the UN Conventions and other policy-making bodies is another need that calls for integration of information. Integration and interoperability are therefore a major theme of GEO BON, and a "system of systems" is very much needed. There are several approaches to integration that need to be considered. Data integration requires harmonising concepts, agreeing on vocabularies, and building ontologies. Semantic mediation of data using these building blocks is still not easy to achieve. Agreements on, or mappings between, the metadata standards that will be used across the networks is a major requirement that will need to be addressed early on. With interoperable metadata, service integration will be possible through registry of registries systems such as GBIF's forthcoming GBDRS and the GEO Clearinghouse. Chaining various services that build intermediate products using workflow

Pressure to drink but not to smoke: disentangling selection and socialization in adolescent peer networks and peer groups.

PubMed

Kiuru, Noona; Burk, William J; Laursen, Brett; Salmela-Aro, Katariina; Nurmi, Jari-Erik

2010-12-01

This paper examined the relative influence of selection and socialization on alcohol and tobacco use in adolescent peer networks and peer groups. The sample included 1419 Finnish secondary education students (690 males and 729 females, mean age 16 years at the outset) from nine schools. Participants identified three school friends and described their alcohol and tobacco use on two occasions one year apart. Actor-based models simultaneously examined changes in peer network ties and changes in individual behaviors for all participants within each school. Multi-level analyses examined changes in individual behaviors for adolescents entering new peer groups and adolescents in stable peer groups, both of which were embedded within the school-based peer networks. Similar results emerged from both analytic methods: Selection and socialization contributed to similarity of alcohol use, but only selection was a factor in tobacco use. Copyright © 2010 The Association for Professionals in Services for Adolescents. Published by Elsevier Ltd. All rights reserved.

The International Arctic Buoy Programme (IABP): A Cornerstone of the Arctic Observing Network

DTIC Science & Technology

2008-09-01

SEP 2008 2. REPORT TYPE 3. DATES COVERED 00-00-2008 to 00-00-2008 4. TITLE AND SUBTITLE The International Arctic Buoy Programme ( IABP ): A...Prescribed by ANSI Std Z39-18 The International Arctic Buoy Programme ( IABP ): A Cornerstone of the Arctic Observing Network Ignatius G. Rigor...changes in weather, climate and environment. It should be noted that many of these changes were first observed and studied using data from the IABP (http

Chimera-like states in structured heterogeneous networks

NASA Astrophysics Data System (ADS)

Li, Bo; Saad, David

2017-04-01

Chimera-like states are manifested through the coexistence of synchronous and asynchronous dynamics and have been observed in various systems. To analyze the role of network topology in giving rise to chimera-like states, we study a heterogeneous network model comprising two groups of nodes, of high and low degrees of connectivity. The architecture facilitates the analysis of the system, which separates into a densely connected coherent group of nodes, perturbed by their sparsely connected drifting neighbors. It describes a synchronous behavior of the densely connected group and scaling properties of the induced perturbations.

International Space Station Earth Observations Working Group

NASA Technical Reports Server (NTRS)

Stefanov, William L.; Oikawa, Koki

2015-01-01

The multilateral Earth Observations Working Group (EOWG) was chartered in May 2012 in order to improve coordination and collaboration of Earth observing payloads, research, and applications on the International Space Station (ISS). The EOWG derives its authority from the ISS Program Science Forum, and a NASA representative serves as a permanent co-chair. A rotating co-chair position can be occupied by any of the international partners, following concurrence by the other partners; a JAXA representative is the current co-chair. Primary functions of the EOWG include, 1) the exchange of information on plans for payloads, from science and application objectives to instrument development, data collection, distribution and research; 2) recognition and facilitation of opportunities for international collaboration in order to optimize benefits from different instruments; and 3) provide a formal ISS Program interface for collection and application of remotely sensed data collected in response to natural disasters through the International Charter, Space and Major Disasters. Recent examples of EOWG activities include coordination of bilateral data sharing protocols between NASA and TsNIIMash for use of crew time and instruments in support of ATV5 reentry imaging activities; discussion of continued use and support of the Nightpod camera mount system by NASA and ESA; and review and revision of international partner contributions on Earth observations to the ISS Program Benefits to Humanity publication.

Deep Chandra Observations of HCG 16. II. The Development of the Intra-group Medium in a Spiral-rich Group

NASA Astrophysics Data System (ADS)

O'Sullivan, E.; Vrtilek, J. M.; David, L. P.; Giacintucci, S.; Zezas, A.; Ponman, T. J.; Mamon, G. A.; Nulsen, P.; Raychaudhury, S.

2014-10-01

We use a combination of deep Chandra X-ray observations and radio continuum imaging to investigate the origin and current state of the intra-group medium (IGM) in the spiral-rich compact group HCG 16. We confirm the presence of a faint (L X, bolo = 1.87+1.03-0.66×1041 erg s-1), low-temperature (0.30+0.07-0.05 keV) IGM extending throughout the ACIS-S3 field of view, with a ridge linking the four original group members and extending to the southeast, as suggested by previous ROSAT and XMM-Newton observations. This ridge contains 6.6+3.9-3.3× 109 M ⊙ of hot gas and is at least partly coincident with a large-scale {H} {I} tidal filament, indicating that the IGM in the inner part of the group is highly multi-phase. We present evidence that the group is not yet virialized, and show that gas has probably been transported from the starburst winds of NGC 838 and NGC 839 into the surrounding IGM. Considering the possible origin of the IGM, we argue that material ejected by galactic winds may have played a significant role, contributing 20%-40% of the observed hot gas in the system.

Weighted Networks at the Polish Market

NASA Astrophysics Data System (ADS)

Chmiel, A. M.; Sienkiewicz, J.; Suchecki, K.; Hołyst, J. A.

During the last few years various models of networks [1,2] have become a powerful tool for analysis of complex systems in such distant fields as Internet [3], biology [4], social groups [5], ecology [6] and public transport [7]. Modeling behavior of economical agents is a challenging issue that has also been studied from a network point of view. The examples of such studies are models of financial networks [8], supply chains [9, 10], production networks [11], investment networks [12] or collective bank bankrupcies [13, 14]. Relations between different companies have been already analyzed using several methods: as networks of shareholders [15], networks of correlations between stock prices [16] or networks of board directors [17]. In several cases scaling laws for network characteristics have been observed.

Opinion dynamics in a group-based society

NASA Astrophysics Data System (ADS)

Gargiulo, F.; Huet, S.

2010-09-01

Many models have been proposed to analyze the evolution of opinion structure due to the interaction of individuals in their social environment. Such models analyze the spreading of ideas both in completely interacting backgrounds and on social networks, where each person has a finite set of interlocutors. In this paper we analyze the reciprocal feedback between the opinions of the individuals and the structure of the interpersonal relationships at the level of community structures. For this purpose we define a group-based random network and we study how this structure co-evolves with opinion dynamics processes. We observe that the adaptive network structure affects the opinion dynamics process helping the consensus formation. The results also show interesting behaviors in regards to the size distribution of the groups and their correlation with opinion structure.

Meteorological Support Interface Control Working Group (MSICWG) Instrumentation, Data Format, and Networks Document

NASA Technical Reports Server (NTRS)

Brenton, James; Roberts, Barry C.

2017-01-01

The purpose of this document is to provide an overview of instrumentation discussed at the Meteorological Interface Control Working Group (MSICWG), a reference for data formats currently used by members of the group, a summary of proposed formats for future use by the group, an overview of the data networks of the group's members. This document will be updated as new systems are introduced, old systems are retired, and when the MSICWG community necessitates a change to the formats. The MSICWG consists of personnel from the National Aeronautics and Space Administration (NASA) Kennedy Space Center (KSC), NASA Marshall Space Flight Center (MSFC), NASA Johnson Space Center (JSC), National Oceanic and Atmospheric Administration National Weather Service Spaceflight Meteorology Group (SMG), and the United States Air Force (USAF) 45th Space Wing and Weather Squadron. The purpose of the group is to coordinate the distribution of weather related data to support NASA space launch related activities.

Group Sex Events and HIV/STI Risk in an Urban Network

PubMed Central

Friedman, Samuel R.; Bolyard, Melissa; Khan, Maria; Maslow, Carey; Sandoval, Milagros; Mateu-Gelabert, Pedro; Krauss, Beatrice; Aral, Sevgi O.

2012-01-01

Objectives To describe: a. the prevalence and individual and network characteristics of group sex events (GSE) and GSE attendees; and b. HIV/STI discordance among respondents who said they went to a GSE together. Methods and Design In a sociometric network study of risk partners (defined as sexual partners, persons with whom respondents attended a GSE, or drug-injection partners) in Brooklyn, NY, we recruited a high-risk sample of 465 adults. Respondents reported on GSE attendance, the characteristics of GSEs, and their own and others’ behaviors at GSEs. Sera and urines were collected and STI prevalence was assayed. Results Of the 465 participants, 36% had attended a GSE in the last year, 26% had sex during the most recent of these GSEs, and 13% had unprotected sex there. Certain subgroups (hard drug users, men who have sex with men, women who have sex with women, and sex workers) were more likely to attend and more likely to engage in risk behaviors at these events. Among 90 GSE dyads in which at least one partner named the other as someone with whom they attended a GSE in the previous three months, STI/HIV discordance was common (HSV-2: 45% of dyads, HIV: 12% of dyads, Chlamydia: 21% of dyads). Many GSEs had 10 or more participants, and multiple partnerships at GSEs were common. High attendance rates at GSEs among members of large networks may increase community vulnerability to STI/HIV, particularly since network data show that almost all members of a large sociometric risk network either had sex with a GSE attendee or had sex with someone who had sex with a GSE attended. Conclusions Self-reported GSE attendance and participation was common among this high-risk sample. STI/HIV discordance among GSE attendees was high, highlighting the potential transmission risk associated with GSEs. Research on sexual behaviors should incorporate measures of GSE behaviors as standard research protocol. Interventions should be developed to reduce transmission at GSEs. PMID

The Inverse Contagion Problem (ICP) vs.. Predicting site contagion in real time, when network links are not observable

NASA Astrophysics Data System (ADS)

Mushkin, I.; Solomon, S.

2017-10-01

We study the inverse contagion problem (ICP). As opposed to the direct contagion problem, in which the network structure is known and the question is when each node will be contaminated, in the inverse problem the links of the network are unknown but a sequence of contagion histories (the times when each node was contaminated) is observed. We consider two versions of the ICP: The strong problem (SICP), which is the reconstruction of the network and has been studied before, and the weak problem (WICP), which requires "only" the prediction (at each time step) of the nodes that will be contaminated at the next time step (this is often the real life situation in which a contagion is observed and predictions are made in real time). Moreover, our focus is on analyzing the increasing accuracy of the solution, as a function of the number of contagion histories already observed. For simplicity, we discuss the simplest (deterministic and synchronous) contagion dynamics and the simplest solution algorithm, which we have applied to different network types. The main result of this paper is that the complex problem of the convergence of the ICP for a network can be reduced to an individual property of pairs of nodes: the "false link difficulty". By definition, given a pair of unlinked nodes i and j, the difficulty of the false link (i,j) is the probability that in a random contagion history, the nodes i and j are not contaminated at the same time step (or at consecutive time steps). In other words, the "false link difficulty" of a non-existing network link is the probability that the observations during a random contagion history would not rule out that link. This probability is relatively straightforward to calculate, and in most instances relies only on the relative positions of the two nodes (i,j) and not on the entire network structure. We have observed the distribution of false link difficulty for various network types, estimated it theoretically and confronted it

The space shuttle payload planning working groups. Volume 7: Earth observations

NASA Technical Reports Server (NTRS)

1973-01-01

The findings of the Earth Observations working group of the space shuttle payload planning activity are presented. The objectives of the Earth Observation experiments are: (1) establishment of quantitative relationships between observable parameters and geophysical variables, (2) development, test, calibration, and evaluation of eventual flight instruments in experimental space flight missions, (3) demonstration of the operational utility of specific observation concepts or techniques as information inputs needed for taking actions, and (4) deployment of prototype and follow-on operational Earth Observation systems. The basic payload capability, mission duration, launch sites, inclinations, and payload limitations are defined.

Information exchange networks for chronic illness care in primary care practices: an observational study

PubMed Central

2010-01-01

Background Information exchange networks for chronic illness care may influence the uptake of innovations in patient care. Valid and feasible methods are needed to document and analyse information exchange networks in healthcare settings. This observational study aimed to examine the usefulness of methods to study information exchange networks in primary care practices, related to chronic heart failure, diabetes and chronic obstructive pulmonary disease. Methods The study was linked to a quality improvement project in the Netherlands. All health professionals in the practices were asked to complete a short questionnaire that documented their information exchange relations. Feasibility was determined in terms of response rates and reliability in terms of reciprocity of reports of receiving and providing information. For each practice, a number of network characteristics were derived for each of the chronic conditions. Results Ten of the 21 practices in the quality improvement project agreed to participate in this network study. The response rates were high in all but one of the participating practices. For the analysis, we used data from 67 health professionals from eight practices. The agreement between receiving and providing information was, on average, 65.6%. The values for density, centralization, hierarchy, and overlap of the information exchange networks showed substantial variation between the practices as well as between the chronic conditions. The most central individual in the information exchange network could be a nurse or a physician. Conclusions Further research is needed to refine the measure of information networks and to test the impact of network characteristics on the uptake of innovations. PMID:20205758

Variable Star Observing in Hungary

NASA Astrophysics Data System (ADS)

Mizser, Attila

1986-12-01

Astronomy and variable star observing has a long history in Hungary, dating back to the private observatories erected by the Hungarian nobility in the late 19th Century. The first organized network of amateur variable star observers, the Variable Star Section of the new Hungarian Astronomical Association, was organized around the Urania Observatory in Budapest in 1948. Other groups, dedicated to various types of variables, have since been organized.

Functional network organizations of two contrasting temperament groups in dimensions of novelty seeking and harm avoidance.

PubMed

Kyeong, Sunghyon; Kim, Eunjoo; Park, Hae-Jeong; Hwang, Dong-Uk

2014-08-05

Novelty seeking (NS) and harm avoidance (HA) are two major dimensions of temperament in Cloninger׳s neurobiological model of personality. Previous neurofunctional and biological studies on temperament dimensions of HA and NS suggested that the temperamental traits have significant correlations with cortical and subcortical brain regions. However, no study to date has investigated the functional network modular organization as a function of the temperament dimension. The temperament dimensions were originally proposed to be independent of one another. However, a meta-analysis based on 16 published articles found a significant negative correlation between HA and NS (Miettunen et al., 2008). Based on this negative correlation, the current study revealed the whole-brain connectivity modular architecture for two contrasting temperament groups. The k-means clustering algorithm, with the temperamental traits of HA and NS as an input, was applied to divide the 40 subjects into two temperament groups: 'high HA and low NS' versus 'low HA and high NS'. Using the graph theoretical framework, we found a functional segregation of whole brain network architectures derived from resting-state functional MRI. In the 'high HA and low NS' group, the regulatory brain regions, such as the prefrontal cortex (PFC), are clustered together with the limbic system. In the 'low HA and high NS' group, however, brain regions lying on the dopaminergic pathways, such as the PFC and basal ganglia, are partitioned together. These findings suggest that the neural basis of inhibited, passive, and inactive behaviors in the 'high HA and low NS' group was derived from the increased network associations between the PFC and limbic clusters. In addition, supporting evidence of topological differences between the two temperament groups was found by analyzing the functional connectivity density and gray matter volume, and by computing the relationships between the morphometry and function of the brain

OWL-Net: A global network of robotic telescopes for satellite observation

NASA Astrophysics Data System (ADS)

Park, Jang-Hyun; Yim, Hong-Suh; Choi, Young-Jun; Jo, Jung Hyun; Moon, Hong-Kyu; Park, Young-Sik; Bae, Young-Ho; Park, Sun-Youp; Roh, Dong-Goo; Cho, Sungki; Choi, Eun-Jung; Kim, Myung-Jin; Choi, Jin

2018-07-01

The OWL-Net (Optical Wide-field patroL Network) is composed of 0.5-m wide-field optical telescopes spread over the globe (Mongolia, Morocco, Israel, South Korea, and USA). All the observing stations are identical, operated in a fully robotic manner, and controlled by the headquarters located in Daejeon, Korea. The main objective of the OWL-Net is to obtain the orbital information of Korean LEO and GEO satellites using purely optical means and to maintain their orbital elements. The aperture size of the mirror is 0.5 m in the Ritchey-Chretien configuration, and its field of view is 1.1 deg on the CCD sensor. The telescope is equipped with an electrically cooled 4 K CCD camera with a 9-μm pixel size, and its pixel scale is 1 arcsec/pixel. A chopper wheel with variable speed is adopted to obtain multiple points in a single shot. Each observatory is equipped with a heavy-duty environment monitoring system for robust robotic observation. The headquarters has components for status monitoring, scheduling, network operation, orbit calculation, and database management. The test-phase operation of the whole system began in early 2017, although test runs for individual sites began in 2015. Although the OWL-Net has 7 observation modes for artificial satellites and astronomical objects, we are concentrating on a few modes for LEO satellites and calibration during the early phase. Some early results and analysis for system performance will be presented, and their implications will be discussed.

Cyberinfrastructure Initiatives of the Committee on Earth Observation Satellites (CEOS) Working Group on Information Systems and Services (WGISS)

NASA Astrophysics Data System (ADS)

McDonald, K. R.; Faundeen, J. L.; Petiteville, I.

2005-12-01

The Committee on Earth Observation Satellites (CEOS) was established in 1984 in response to a recommendation from the Economic Summit of Industrialized Nations Working Group on Growth, Technology, and Employment's Panel of Experts on Satellite Remote Sensing. CEOS participants are Members, who are national or international governmental organizations who operate civil spaceborne Earth observation satellites, and Associates who are governmental organizations with civil space programs in development or international scientific or governmental bodies who have an interest in and support CEOS objectives. The primary objective of CEOS is to optimize benefits of satellite Earth observations through cooperation of its participants in mission planning and in development of compatible data products, formats, services, applications and policies. To pursue its objectives, CEOS establishes working groups and associated subgroups that focus on relevant areas of interest. While the structure of CEOS has evolved over its lifetime, today there are three permanent working groups. One is the Working Group on Calibration and Validation that addresses sensor-specific calibration and validation and geophysical parameter validation. A second is the Working Group on Education, Training, and Capacity Building that facilitates activities that enhance international education and training in Earth observation techniques, data analysis, interpretation and applications, with a particular focus on developing countries. The third permanent working group is the Working Group on Information Systems and Services (WGISS). The purpose of WGISS is to promote collaboration in the development of the systems and services based on international standards that manage and supply the Earth observation data and information from participating agencies' missions. WGISS places great emphasis on the use of demonstration projects involving user groups to solve the critical interoperability issues associated with the

Mutual information, neural networks and the renormalization group

NASA Astrophysics Data System (ADS)

Koch-Janusz, Maciej; Ringel, Zohar

2018-06-01

Physical systems differing in their microscopic details often display strikingly similar behaviour when probed at macroscopic scales. Those universal properties, largely determining their physical characteristics, are revealed by the powerful renormalization group (RG) procedure, which systematically retains `slow' degrees of freedom and integrates out the rest. However, the important degrees of freedom may be difficult to identify. Here we demonstrate a machine-learning algorithm capable of identifying the relevant degrees of freedom and executing RG steps iteratively without any prior knowledge about the system. We introduce an artificial neural network based on a model-independent, information-theoretic characterization of a real-space RG procedure, which performs this task. We apply the algorithm to classical statistical physics problems in one and two dimensions. We demonstrate RG flow and extract the Ising critical exponent. Our results demonstrate that machine-learning techniques can extract abstract physical concepts and consequently become an integral part of theory- and model-building.

Default Network Modulation and Large-Scale Network Interactivity in Healthy Young and Old Adults

PubMed Central

Schacter, Daniel L.

2012-01-01

We investigated age-related changes in default, attention, and control network activity and their interactions in young and old adults. Brain activity during autobiographical and visuospatial planning was assessed using multivariate analysis and with intrinsic connectivity networks as regions of interest. In both groups, autobiographical planning engaged the default network while visuospatial planning engaged the attention network, consistent with a competition between the domains of internalized and externalized cognition. The control network was engaged for both planning tasks. In young subjects, the control network coupled with the default network during autobiographical planning and with the attention network during visuospatial planning. In old subjects, default-to-control network coupling was observed during both planning tasks, and old adults failed to deactivate the default network during visuospatial planning. This failure is not indicative of default network dysfunction per se, evidenced by default network engagement during autobiographical planning. Rather, a failure to modulate the default network in old adults is indicative of a lower degree of flexible network interactivity and reduced dynamic range of network modulation to changing task demands. PMID:22128194

Applying a social network analysis (SNA) approach to understanding radiologists' performance in reading mammograms

NASA Astrophysics Data System (ADS)

Tavakoli Taba, Seyedamir; Hossain, Liaquat; Heard, Robert; Brennan, Patrick; Lee, Warwick; Lewis, Sarah

2017-03-01

Rationale and objectives: Observer performance has been widely studied through examining the characteristics of individuals. Applying a systems perspective, while understanding of the system's output, requires a study of the interactions between observers. This research explains a mixed methods approach to applying a social network analysis (SNA), together with a more traditional approach of examining personal/ individual characteristics in understanding observer performance in mammography. Materials and Methods: Using social networks theories and measures in order to understand observer performance, we designed a social networks survey instrument for collecting personal and network data about observers involved in mammography performance studies. We present the results of a study by our group where 31 Australian breast radiologists originally reviewed 60 mammographic cases (comprising of 20 abnormal and 40 normal cases) and then completed an online questionnaire about their social networks and personal characteristics. A jackknife free response operating characteristic (JAFROC) method was used to measure performance of radiologists. JAFROC was tested against various personal and network measures to verify the theoretical model. Results: The results from this study suggest a strong association between social networks and observer performance for Australian radiologists. Network factors accounted for 48% of variance in observer performance, in comparison to 15.5% for the personal characteristics for this study group. Conclusion: This study suggest a strong new direction for research into improving observer performance. Future studies in observer performance should consider social networks' influence as part of their research paradigm, with equal or greater vigour than traditional constructs of personal characteristics.

Network structure exploration in networks with node attributes

NASA Astrophysics Data System (ADS)

Chen, Yi; Wang, Xiaolong; Bu, Junzhao; Tang, Buzhou; Xiang, Xin

2016-05-01

Complex networks provide a powerful way to represent complex systems and have been widely studied during the past several years. One of the most important tasks of network analysis is to detect structures (also called structural regularities) embedded in networks by determining group number and group partition. Most of network structure exploration models only consider network links. However, in real world networks, nodes may have attributes that are useful for network structure exploration. In this paper, we propose a novel Bayesian nonparametric (BNP) model to explore structural regularities in networks with node attributes, called Bayesian nonparametric attribute (BNPA) model. This model does not only take full advantage of both links between nodes and node attributes for group partition via shared hidden variables, but also determine group number automatically via the Bayesian nonparametric theory. Experiments conducted on a number of real and synthetic networks show that our BNPA model is able to automatically explore structural regularities in networks with node attributes and is competitive with other state-of-the-art models.

Extrapolating regional probability of drying of headwater streams using discrete observations and gauging networks

NASA Astrophysics Data System (ADS)

Beaufort, Aurélien; Lamouroux, Nicolas; Pella, Hervé; Datry, Thibault; Sauquet, Eric

2018-05-01

Headwater streams represent a substantial proportion of river systems and many of them have intermittent flows due to their upstream position in the network. These intermittent rivers and ephemeral streams have recently seen a marked increase in interest, especially to assess the impact of drying on aquatic ecosystems. The objective of this paper is to quantify how discrete (in space and time) field observations of flow intermittence help to extrapolate over time the daily probability of drying (defined at the regional scale). Two empirical models based on linear or logistic regressions have been developed to predict the daily probability of intermittence at the regional scale across France. Explanatory variables were derived from available daily discharge and groundwater-level data of a dense gauging/piezometer network, and models were calibrated using discrete series of field observations of flow intermittence. The robustness of the models was tested using an independent, dense regional dataset of intermittence observations and observations of the year 2017 excluded from the calibration. The resulting models were used to extrapolate the daily regional probability of drying in France: (i) over the period 2011-2017 to identify the regions most affected by flow intermittence; (ii) over the period 1989-2017, using a reduced input dataset, to analyse temporal variability of flow intermittence at the national level. The two empirical regression models performed equally well between 2011 and 2017. The accuracy of predictions depended on the number of continuous gauging/piezometer stations and intermittence observations available to calibrate the regressions. Regions with the highest performance were located in sedimentary plains, where the monitoring network was dense and where the regional probability of drying was the highest. Conversely, the worst performances were obtained in mountainous regions. Finally, temporal projections (1989-2016) suggested the highest

Deep Chandra observations of HCG 16. II. The development of the intra-group medium in a spiral-rich group

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

O'Sullivan, E.; Vrtilek, J. M.; David, L. P.

2014-10-01

We use a combination of deep Chandra X-ray observations and radio continuum imaging to investigate the origin and current state of the intra-group medium (IGM) in the spiral-rich compact group HCG 16. We confirm the presence of a faint (L {sub X,} {sub bolo} = 1.87{sub −0.66}{sup +1.03}×10{sup 41} erg s{sup –1}), low-temperature (0.30{sub −0.05}{sup +0.07} keV) IGM extending throughout the ACIS-S3 field of view, with a ridge linking the four original group members and extending to the southeast, as suggested by previous ROSAT and XMM-Newton observations. This ridge contains 6.6{sub −3.3}{sup +3.9}× 10{sup 9} M {sub ☉} of hotmore » gas and is at least partly coincident with a large-scale H I tidal filament, indicating that the IGM in the inner part of the group is highly multi-phase. We present evidence that the group is not yet virialized, and show that gas has probably been transported from the starburst winds of NGC 838 and NGC 839 into the surrounding IGM. Considering the possible origin of the IGM, we argue that material ejected by galactic winds may have played a significant role, contributing 20%-40% of the observed hot gas in the system.« less

Groups' Actions Trump Injunctive Reaction in an Incidental Observation by Young Children

PubMed Central

Turner, Cameron R.; Nielsen, Mark; Collier-Baker, Emma

2014-01-01

Children's ability to use social information to direct their behavior is key to their survival and development. However, in observing adult behavior, children are confronted with multiple forms of social information that may vary in reliability and adaptiveness. Two of the most well established biases influencing human behavior are: (1) following the majority (majority influence or conformity); and (2) the use of emotional signals. The current experiment aimed to evaluate how children respond when both information about the majority behavior of a group (descriptive norm) and attitudes of the group towards a behavior (injunctive norm, expressed through an emotional reaction) are present and what happens when they are in conflict. We used a method designed to mimic the manner in which children might observe group members' behavior during development. Novel apparatuses were constructed for which there were two discrete actions that could be performed to retrieve a reward. Three-year-olds observed four adults demonstrating one set of actions, followed by a fifth adult who presented an alternative set of actions. The first four adults' injunctive responses to this fifth adult's actions were manipulated between-groups: positive, negative, or neutral. It was found that children preferred to copy the majority action, regardless of the injunctive reaction of the group. We argue that this affirms the adaptive utility of copying the majority. PMID:25198163

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

USGS Publications Warehouse

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

2000-01-01

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

Network Support for Group Coordination

DTIC Science & Technology

2000-01-01

telecommuting and ubiquitous computing [40], the advent of networked multimedia, and less expensive technology have shifted telecollaboration into...of Computer Engineering,Santa Cruz,CA,95064 8. PERFORMING ORGANIZATION REPORT NUMBER 9. SPONSORING/ MONITORING AGENCY NAME(S) AND ADDRESS(ES) 10...participants A and B, the payoff structure for choosing two actions i and j is P = Aij + Bij . If P = 0, then the interaction is called a zero -sum game, and

On the nature of hydrogen bonding between the phosphatidylcholine head group and water and dimethylsulfoxide

NASA Astrophysics Data System (ADS)

Dabkowska, Aleksandra P.; Lawrence, M. Jayne; McLain, Sylvia E.; Lorenz, Christian D.

2013-01-01

Molecular dynamics simulations are used to provide a detailed investigation of the hydrogen bond networks around the phosphatidylcholine (PC) head group in 1,2-dipropionyl-sn-glycero-3-phosphocholine in pure water, 10 mol.% and 30 mol.% dimethylsulfoxide (DMSO)-water solutions. Specifically, it is observed that DMSO replaces those water molecules that are within the first solvation shell of the choline, phosphate and ester groups of the PC head group, but are not hydrogen-bonded to the group. The effect of the presence of DMSO on the hydrogen bond network around the PC head groups of the lipid changes with the concentration of DMSO. In comparison to the hydrogen bond network observed in the pure water system, the number of hydrogen-bonded chains of solvent molecules increases slightly for the 10 mol.% DMSO system, while, in the 30 mol.% DMSO system, the number of hydrogen-bonded chains of solvent molecules decreases.

CAN-DOO: The Climate Action Network through Direct Observations and Outreach

NASA Astrophysics Data System (ADS)

Taubman, B.; Sherman, J. P.; Perry, L. B.; Markham, J.; Kelly, G.

2011-12-01

The urgency of climate change demands a greater understanding of our climate system, not only by the leaders of today, but by the scientists, policy makers, and citizens of tomorrow. Unfortunately, a large segment of the population currently possesses inadequate knowledge of climate science. In direct response to a need for greater scientific literacy with respect to climate science, researchers from Appalachian State University's Appalachian Atmospheric Interdisciplinary Research (AppalAIR) group, with support from NASA, have developed CAN-DOO: the Climate Action Network through Direct Observations and Outreach. CAN-DOO addresses climate science literacy by 1) Developing the infrastructure for sustaining and expanding public outreach through long-term climate measurements capable of complementing existing NASA measurements, 2) Enhancing public awareness of climate science and NASA's role in advancing our understanding of the Earth System, and 3) Introducing Science, Technology, Engineering, and Mathematics principles to homeschooled, public school, and Appalachian State University students through applied climate science activities. Project partners include the Grandfather Mountain Stewardship Foundation, Pisgah Astronomical Research Institute, and local elementary schools. In partnership with Grandfather Mountain, climate science awareness is promoted through citizen science activities, interactive public displays, and staff training. CAN-DOO engages students by involving them in the entire scientific investigative process as applied to climate science. We introduce local elementary and middle school students, homeschooled students throughout North Carolina, and undergraduate students in a new Global Climate Change course and select other courses at Appalachian State University to instrument assembly, measurement techniques, data collection, hypothesis testing, and drawing conclusions. Results are placed in the proper context via comparisons with other student

Providing nearest neighbor point-to-point communications among compute nodes of an operational group in a global combining network of a parallel computer

DOEpatents

Archer, Charles J.; Faraj, Ahmad A.; Inglett, Todd A.; Ratterman, Joseph D.

2012-10-23

Methods, apparatus, and products are disclosed for providing nearest neighbor point-to-point communications among compute nodes of an operational group in a global combining network of a parallel computer, each compute node connected to each adjacent compute node in the global combining network through a link, that include: identifying each link in the global combining network for each compute node of the operational group; designating one of a plurality of point-to-point class routing identifiers for each link such that no compute node in the operational group is connected to two adjacent compute nodes in the operational group with links designated for the same class routing identifiers; and configuring each compute node of the operational group for point-to-point communications with each adjacent compute node in the global combining network through the link between that compute node and that adjacent compute node using that link's designated class routing identifier.

The Citizens and Remote Sensing Observational Network (CARSON) Guide: Merging NASA Remote Sensing Data with Local Environmental Awareness

NASA Technical Reports Server (NTRS)

Acker, James; Riebeek, Holli; Ledley, Tamara Shapiro; Herring, David; Lloyd, Steven

2008-01-01

"Citizen science" generally refers to observatoinal research and data collection conducted by non-professionals, commonly as volunteers. In the environmental science field, citizen scientists may be involved with local nad regional issues such as bird and wildlife populations, weather, urban sprawl, natural hazards, wetlands, lakes and rivers, estuaries, and a spectrum of public health concerns. Some citizen scientists may be primarily motivated by the intellectual challenge of scientific observations. Citizen scientists may now examine and utilize remote-sensing data related to their particular topics of interest with the easy-to-use NASA Web-based tools Giovanni and NEO, which allow exploration and investigation of a wide variety of Earth remote sensing data sets. The CARSON (Citizens and Remote Sensing Observational Network) Guide will be an online resource consisting of chapters each demonstrating how to utilize Giovanni and NEO to access and analyze specific remote-sensing data. Integrated in each chapter will be descriptions of methods that citizen scientists can employ to collect, monitor, analyze, and share data related to the chapter topic which pertain to environmental and ecological conditions in their local region. A workshop held in August 2008 initiated the development of prototype chapters on water quality, air quality, and precipitation. These will be the initial chapters in the first release of the CARSON Guide, which will be used in a pilot project at the Maryland Science Center in spring 2009. The goal of the CARSON Guide is to augment and enhance citizen scientist environmental research with NASA satellite data by creating a participatory network consisting of motivated individuals, environmental groups and organizations, and science-focused institutions such as museuma and nature centers. Members of the network could potentially interact with government programs, academic research projects, and not-for-profit organizations focused on

Understanding Process in Group-Based Intervention Delivery: Social Network Analysis and Intra-entity Variability Methods as Windows into the "Black Box".

PubMed

Molloy Elreda, Lauren; Coatsworth, J Douglas; Gest, Scott D; Ram, Nilam; Bamberger, Katharine

2016-11-01

Although the majority of evidence-based programs are designed for group delivery, group process and its role in participant outcomes have received little empirical attention. Data were collected from 20 groups of participants (94 early adolescents, 120 parents) enrolled in an efficacy trial of a mindfulness-based adaptation of the Strengthening Families Program (MSFP). Following each weekly session, participants reported on their relations to group members. Social network analysis and methods sensitive to intraindividual variability were integrated to examine weekly covariation between group process and participant progress, and to predict post-intervention outcomes from levels and changes in group process. Results demonstrate hypothesized links between network indices of group process and intervention outcomes and highlight the value of this unique analytic approach to studying intervention group process.

Observational Learning of Academic and Social Behaviors during Small-Group Direct Instruction

ERIC Educational Resources Information Center

Ledford, Jennifer R.; Wolery, Mark

2015-01-01

Many studies have shown that small-group direct instruction is effective and efficient for teaching students with and without disabilities, although relatively few studies have been conducted with heterogeneous groups of preschool participants. In addition, previous studies have primarily assessed whether observational learning occurred for…

Semiquantitative bacterial observations with group B streptococcal vulvovaginitis.

PubMed Central

Monif, G R

1999-01-01

OBJECTIVE: Group B streptococcal (GBS) vulvovaginitis is a poorly-delineated clinical entity. The purpose of this study is to report semiquantitative data from four cases of GBS vulvovaginitis and to comment on their significance in terms of the in vitro inhibitory capabilities of GBS. METHODOLOGY: Four patients whose clinical presentations were consistent with GBS vulvovaginitis, from whom GBS was isolated and for whom semi-quantitative as well as qualitative microbiologic data existed, were identified. RESULTS: To produce vulvovaginitis, GBS must be at a high multiplicity (10(8) CFU/g of vaginal fluid). Single coisolates were identified in three of the four cases (two cases of Escherichia coli and one case of Staphylococcus aureus). Group B streptococcus does not inhibit either of these bacteria in vitro. CONCLUSION: When the growth requirements for the demonstration of in vitro inhibition for GBS or lack thereof are met in vivo, the in vivo observations are consistent with those projected from the in vitro data. PMID:10524667

Realtime Delivery of Alarms and Key Observables in a Deployed Hydrological Sensor Network

NASA Astrophysics Data System (ADS)

Marshall, I. W.; Price, M. C.; Li, H.; Boyd, N.; Boult, S.

2007-12-01

It has widely [1-3] been proposed that sensor networks are a good solution for environmental monitoring. However, this application presents a number of major challenges for current technology. In particular environmental science involves the study of coupled non-equilibrium dynamic processes that generate time series with non-stationary means and strongly dependent variables and which operate in the presence of large amounts of noise/interference (thermal, chemical and biological) and multiple quasi-periodic forcing factors (diurnal cycles, tides, etc). This typically means that any analysis must be based on large data samples obtained at multiple scales of space and time. In addition the areas of interest are large, relatively inaccessible and typically extremely hostile to electronic instrumentation. Our analysis of these factors has encouraged us to focus on this list of generic requirements; a) Node lifetime (between visits) should be 1 yr or greater b) Communication range should be ~250m c) Nodes should be portable, unobtrusive, low cost, etc. d) Networks are expected to be sparse since areas of interest are large and budgets are small However, the characteristics of each environment, the dominant processes operating in it and the measurements that are of interest are sufficiently different that the design of an appropriate sensor network solution is normally most determined by site specific constraints. Most importantly the opportunities for exploiting contextual correlation to disambiguate observations and improve the maintenance and robustness of a deployed sensor network are always site specific. We will describe the design and initial deployment of a hydrological sensor network we are developing to assess the hydro-dynamics of surface water drainage into Great Crowden Brook in the Peak District (UK). The complete network will observe soil moisture, temperature and rainfall on a number of transects across the valley, and will also investigate water quality

Orthoscape: a cytoscape application for grouping and visualization KEGG based gene networks by taxonomy and homology principles.

PubMed

Mustafin, Zakhar Sergeevich; Lashin, Sergey Alexandrovich; Matushkin, Yury Georgievich; Gunbin, Konstantin Vladimirovich; Afonnikov, Dmitry Arkadievich

2017-01-27

There are many available software tools for visualization and analysis of biological networks. Among them, Cytoscape ( http://cytoscape.org/ ) is one of the most comprehensive packages, with many plugins and applications which extends its functionality by providing analysis of protein-protein interaction, gene regulatory and gene co-expression networks, metabolic, signaling, neural as well as ecological-type networks including food webs, communities networks etc. Nevertheless, only three plugins tagged 'network evolution' found in Cytoscape official app store and in literature. We have developed a new Cytoscape 3.0 application Orthoscape aimed to facilitate evolutionary analysis of gene networks and visualize the results. Orthoscape aids in analysis of evolutionary information available for gene sets and networks by highlighting: (1) the orthology relationships between genes; (2) the evolutionary origin of gene network components; (3) the evolutionary pressure mode (diversifying or stabilizing, negative or positive selection) of orthologous groups in general and/or branch-oriented mode. The distinctive feature of Orthoscape is the ability to control all data analysis steps via user-friendly interface. Orthoscape allows its users to analyze gene networks or separated gene sets in the context of evolution. At each step of data analysis, Orthoscape also provides for convenient visualization and data manipulation.

Data base on physical observations of near-Earth asteroids and establishment of a network to coordinate observations of newly discovered near-Earth asteroids

NASA Technical Reports Server (NTRS)

Davis, D. R.; Chapman, C. R.; Campins, H.

1990-01-01

This program consists of two tasks: (1) development of a data base of physical observations of near-earth asteroids and establishment of a network to coordinate observations of newly discovered earth-approaching asteroids; and (2) a simulation of the surface of low-activity comets. Significant progress was made on task one and, and task two was completed during the period covered by this progress report.

Demonstrating an Effective Marine Biodiversity Observation Network in the Santa Barbara Channel

NASA Astrophysics Data System (ADS)

Miller, R. J.

2016-02-01

The Santa Barbara Channel (SBC) is a transition zone characterized by high species and habitat diversity and strong environmental gradients within a relatively small area where cold- and warm-water species found from Baja to the Bering Sea coexist. These characteristics make SBC an ideal setting for our demonstration Marine Biodiversity Observation Network (BON) project that integrates biological levels from genes to habitats and links biodiversity observations to environmental forcing and biogeography. SBC BON is building a comprehensive demonstration system that includes representation of all levels of biotic diversity, key new tools to expand the scales of present observation, and a data management network to integrate new and existing data sources. Our system will be scalable to expand into a full regional Marine BON, and the methods and decision support tools we develop will be transferable to other regions. Incorporating a broad set of habitats including nearshore coast, continental shelf, and pelagic, and taxonomic breadth from microbes to whales will facilitate this transferability. The Santa Barbara Channel marine BON has three broad objectives: 1. Integrate biodiversity data to enable inferences about regional biodiversity 2. Develop advanced methods in optical and acoustic imaging and genomics for monitoring biodiversity in partnership with ongoing monitoring and research programs to begin filling the gaping gaps in our knowledge. 3. Implement a tradeoff framework that optimizes allocation of sampling effort. Here we discuss our progress towards these goals and challenges in developing an effective MBON.

Building oceanographic and atmospheric observation networks by composition: unmanned vehicles, communication networks, and planning and execution control frameworks

NASA Astrophysics Data System (ADS)

Sousa, J. T.; Pinto, J.; Martins, R.; Costa, M.; Ferreira, F.; Gomes, R.

2014-12-01

The problem of developing mobile oceanographic and atmospheric observation networks (MOAO) with coordinated air and ocean vehicles is discussed in the framework of the communications and control software tool chain developed at Underwater Systems and Technologies Laboratory (LSTS) from Porto University. This is done with reference to field experiments to illustrate key capabilities and to assess future MOAO operations. First, the motivation for building MOAO by "composition" of air and ocean vehicles, communication networks, and planning and execution control frameworks is discussed - in networked vehicle systems information and commands are exchanged among multiple vehicles and operators, and the roles, relative positions, and dependencies of these vehicles and operators change during operations. Second, the planning and execution control framework developed at LSTS for multi-vehicle systems is discussed with reference to key concepts such as autonomy, mixed-initiative interactions, and layered organization. Third, the LSTS tool software tool chain is presented to show how to develop MOAO by composition. The tool chain comprises the Neptus command and control framework for mixed initiative interactions, the underlying IMC messaging protocol, and the DUNE on-board software. Fourth, selected LSTS operational deployments illustrate MOAO capability building. In 2012 we demonstrated the use of UAS to "ferry" data from UUVs located beyond line of sight (BLOS). In 2013 we demonstrated coordinated observations of coastal fronts with small UAS and UUVs, "bent" BLOS through the use of UAS as communication relays, and UAS tracking of juvenile hammer-head sharks. In 2014 we demonstrated UUV adaptive sampling with the closed loop controller of the UUV residing on a UAS; this was done with the help of a Wave Glider ASV with a communications gateway. The results from these experiments provide a background for assessing potential future UAS operations in a compositional MOAO.

Infrared and Radio Observations of a Small Group of Protostellar Objects in the Molecular Core, L1251-C

NASA Astrophysics Data System (ADS)

Kim, Jungha; Lee, Jeong-Eun; Choi, Minho; Bourke, Tyler L.; Evans, Neal J., II; Di Francesco, James; Cieza, Lucas A.; Dunham, Michael M.; Kang, Miju

2015-05-01

We present a multi-wavelength observational study of a low-mass star-forming region, L1251-C, with observational results at wavelengths from the near-infrared to the millimeter. Spitzer Space Telescope observations confirmed that IRAS 22343+7501 is a small group of protostellar objects. The extended emission in the east-west direction with its intensity peak at the center of L1251A has been detected at 350 and 850 μm with the Caltech Submillimeter Observatory and James Clerk Maxwell telescopes, tracing dense envelope material around L1251A. The single-dish data from the Korean VLBI Network and TRAO telescopes show inconsistencies between the intensity peaks of several molecular emission lines and that of the continuum emission, suggesting complex distributions of molecular abundances around L1251A. The Submillimeter Array interferometer data, however, show intensity peaks of CO 2-1 and 13CO 2-1 located at the position of IRS 1, which is both the brightest source in the Infrared Array Camera image and the weakest source in the 1.3 mm dust-continuum map. IRS 1 is the strongest candidate for the driving source of the newly detected compact CO 2-1 outflow. Over the entire region (14‧ × 14‧) of L125l-C, 3 Class I and 16 Class II sources have been detected, including three young stellar objects (YSOs) in L1251A. A comparison between the average projected distance among the 19 YSOs in L1251-C and that among the 3 YSOs in L1251A suggests that L1251-C is an example of low-mass cluster formation where protostellar objects form in a small group.

Netgram: Visualizing Communities in Evolving Networks

PubMed Central

Mall, Raghvendra; Langone, Rocco; Suykens, Johan A. K.

2015-01-01

Real-world complex networks are dynamic in nature and change over time. The change is usually observed in the interactions within the network over time. Complex networks exhibit community like structures. A key feature of the dynamics of complex networks is the evolution of communities over time. Several methods have been proposed to detect and track the evolution of these groups over time. However, there is no generic tool which visualizes all the aspects of group evolution in dynamic networks including birth, death, splitting, merging, expansion, shrinkage and continuation of groups. In this paper, we propose Netgram: a tool for visualizing evolution of communities in time-evolving graphs. Netgram maintains evolution of communities over 2 consecutive time-stamps in tables which are used to create a query database using the sql outer-join operation. It uses a line-based visualization technique which adheres to certain design principles and aesthetic guidelines. Netgram uses a greedy solution to order the initial community information provided by the evolutionary clustering technique such that we have fewer line cross-overs in the visualization. This makes it easier to track the progress of individual communities in time evolving graphs. Netgram is a generic toolkit which can be used with any evolutionary community detection algorithm as illustrated in our experiments. We use Netgram for visualization of topic evolution in the NIPS conference over a period of 11 years and observe the emergence and merging of several disciplines in the field of information processing systems. PMID:26356538

The Group on Earth Observations and the Global Earth Observation System of Systems

NASA Astrophysics Data System (ADS)

Achache, J.

2006-05-01

The Group on Earth Observations (GEO) is leading a worldwide effort to build a Global Earth Observation System of Systems (GEOSS) over the next 10 years. The GEOSS vision, articulated in its 10-Year Implementation Plan, represents the consolidation of a global scientific and political consensus: the assessment of the state of the Earth requires continuous and coordinated observation of our planet at all scales. GEOSS aims to achieve comprehensive, coordinated and sustained observations of the Earth system in order to improve monitoring of the state of the Earth; increase understanding of Earth processes; and enhance prediction of the behaviour of the Earth system. After the World Summit on Sustainable Development in 2002 highlighted the urgent need for coordinated observations relating to the state of the Earth, GEO was established at the Third Earth Observation Summit in February 2005 and the GEOSS 10-Year Implementation Plan was endorsed. GEO currently involves 60 countries; the European Commission; and 43 international organizations and has begun implementation of the GEOSS 10-Year Implementation Plan. GEO programme activities cover nine societal benefit areas (Disasters; Health; Energy; Climate; Water; Weather; Ecosystems; Agriculture; Biodiversity) and five transverse or crosscutting elements (User Engagement; Architecture; Data Management; Capacity Building; Outreach). All these activities have as their final goal the establishment of the "system of systems" which will yield a broad range of basic societal benefits, including the reduction of loss of life and property from tsunamis, hurricanes, and other natural disasters; improved water resource and energy management; and improved understanding of environmental factors significant to public health. As a "system of systems", GEOSS will work with and build upon existing national, regional, and international systems to provide comprehensive, coordinated Earth observations from thousands of instruments worldwide

Observer design for compensation of network-induced delays in integrated communication and control systems

NASA Technical Reports Server (NTRS)

Luck, R.; Ray, A.

1988-01-01

A method for compensating the effects of network-induced delays in integrated communication and control systems (ICCS) is proposed, and a finite-dimensional time-invariant ICCS model is developed. The problem of analyzing systems with time-varying and stochastic delays is circumvented by the application of a deterministic observer. For the case of controller-to-actuator delays, the observed design must rely on an extended model which represents the delays as additional states.

Analysis of sensor network observations during some simulated landslide experiments

NASA Astrophysics Data System (ADS)

Scaioni, M.; Lu, P.; Feng, T.; Chen, W.; Wu, H.; Qiao, G.; Liu, C.; Tong, X.; Li, R.

2012-12-01

A multi-sensor network was tested during some experiments on a landslide simulation platform established at Tongji University (Shanghai, P.R. China). Here landslides were triggered by means of artificial rainfall (see Figure 1). The sensor network currently incorporates contact sensors and two imaging systems. This represent a novel solution, because the spatial sensor network incorporate either contact sensors and remote sensors (video-cameras). In future, these sensors will be installed on two real ground slopes in Sichuan province (South-West China), where Wenchuan earthquake occurred in 2008. This earthquake caused the immediate activation of several landslide, while other area became unstable and still are a menace for people and properties. The platform incorporates the reconstructed scale slope, sensor network, communication system, database and visualization system. Some landslide simulation experiments allowed ascertaining which sensors could be more suitable to be deployed in Wenchuan area. The poster will focus on the analysis of results coming from down scale simulations. Here the different steps of the landslide evolution can be followed on the basis of sensor observations. This include underground sensors to detect the water table level and the pressure in the ground, a set of accelerometers and two inclinometers. In the first part of the analysis the full data series are investigated to look for correlations and common patterns, as well as to link them to the physical processes. In the second, 4 subsets of sensors located in neighbor positions are analyzed. The analysis of low- and high-speed image sequences allowed to track a dense field of displacement on the slope surface. These outcomes have been compared to the ones obtained from accelerometers for cross-validation. Images were also used for the photogrammetric reconstruction of the slope topography during the experiment. Consequently, volume computation and mass movements could be evaluated on

Finding Sales Promotion and Making Decision for New Product Based on Group Analysis of Edge-Enhanced Product Networks

NASA Astrophysics Data System (ADS)

Huang, Yi; Tan, Jianbin; Wu, Bin

A novel method is proposed in this paper to find the promotive relationship of products from a network point of view. Firstly, a product network is built based on the dataset of handsets’ sale information collected from all outlets of a telecom operator of one province of China, with a period from Jan. 2006 to Jul. 2008. Then the edge enhanced model is applied on product network to divide all the products into several groups, according to which each outlet is assigned to class A or class B for a certain handset. Class A is defined as the outlet which sell the certain handset and contains all of handsets of its group, while other situation for class B which sell the certain handset too. It’s shown from the result of analysis on these two kinds of outlets that many handsets are sold better in outlets of class A than that of class B, even though the sales revenue of all these outlets in the time period is close. That is to say the handsets within a group would promote the sale for each other. Furthermore, a method proposed in this paper gives a way to find out the important attributes of the handsets which lead them to br divided into the same group, and it also explains how to add a new handset to an existing group and where would the new handset be sold best.

Observation of Wave Packet Distortion during a Negative-Group-Velocity Transmission

PubMed Central

Ye, Dexin; Salamin, Yannick; Huangfu, Jiangtao; Qiao, Shan; Zheng, Guoan; Ran, Lixin

2015-01-01

In Physics, causality is a fundamental postulation arising from the second law of thermodynamics. It states that, the cause of an event precedes its effect. In the context of Electromagnetics, the relativistic causality limits the upper bound of the velocity of information, which is carried by electromagnetic wave packets, to the speed of light in free space (c). In anomalously dispersive media (ADM), it has been shown that, wave packets appear to propagate with a superluminal or even negative group velocity. However, Sommerfeld and Brillouin pointed out that the “front” of such wave packets, known as the initial point of the Sommerfeld precursor, always travels at c. In this work, we investigate the negative-group-velocity transmission of half-sine wave packets. We experimentally observe the wave front and the distortion of modulated wave packets propagating with a negative group velocity in a passive artificial ADM in microwave regime. Different from previous literature on the propagation of superluminal Gaussian packets, strongly distorted sinusoidal packets with non-superluminal wave fronts were observed. This result agrees with Brillouin's assertion, i.e., the severe distortion of seemingly superluminal wave packets makes the definition of group velocity physically meaningless in the anomalously dispersive region. PMID:25631746

Efficient tree tensor network states (TTNS) for quantum chemistry: Generalizations of the density matrix renormalization group algorithm

NASA Astrophysics Data System (ADS)

Nakatani, Naoki; Chan, Garnet Kin-Lic

2013-04-01

We investigate tree tensor network states for quantum chemistry. Tree tensor network states represent one of the simplest generalizations of matrix product states and the density matrix renormalization group. While matrix product states encode a one-dimensional entanglement structure, tree tensor network states encode a tree entanglement structure, allowing for a more flexible description of general molecules. We describe an optimal tree tensor network state algorithm for quantum chemistry. We introduce the concept of half-renormalization which greatly improves the efficiency of the calculations. Using our efficient formulation we demonstrate the strengths and weaknesses of tree tensor network states versus matrix product states. We carry out benchmark calculations both on tree systems (hydrogen trees and π-conjugated dendrimers) as well as non-tree molecules (hydrogen chains, nitrogen dimer, and chromium dimer). In general, tree tensor network states require much fewer renormalized states to achieve the same accuracy as matrix product states. In non-tree molecules, whether this translates into a computational savings is system dependent, due to the higher prefactor and computational scaling associated with tree algorithms. In tree like molecules, tree network states are easily superior to matrix product states. As an illustration, our largest dendrimer calculation with tree tensor network states correlates 110 electrons in 110 active orbitals.

Coordination and Integration of Global Ocean Observing through JCOMM

NASA Astrophysics Data System (ADS)

Legler, D. M.; Meldrum, D. T.; Hill, K. L.; Charpentier, E.

2016-02-01

The primary objective of the JCOMM Observations Coordination Group (OCG) is to provide technical coordination to implement fully integrated ocean observing system across the entire marine meteorology and oceanographic community. JCOMM OCG works in partnership with the Global Ocean Observing System, , which focusses on setting observing system requirements and conducting evalutions. JCOMM OCG initially focused on major global observing networks (e.g. Argo profiling floats, moored buoys, ship based observations, sea level stations, reference sites, etc), and is now expanding its horizon in recognition of new observing needs and new technologies/networks (e.g. ocean gliders). Over the next five years the JCOMM OCG is focusing its attention on integration and coordination in four major areas: observing network implementation particularly in response to integrated ocean observing requirements; observing system monitoring and metrics; standards and best practices; and improving integrated data management and access. This presentation will describe the scope and mission of JCOMM OCG; summarize the state of the global ocean observing system; highlight recent successes and resources for the research, prediction, and assessment communities; summarize our plans for the next several years; and suggest engagement opportunities.

Computer network defense system

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

Urias, Vincent; Stout, William M. S.; Loverro, Caleb

A method and apparatus for protecting virtual machines. A computer system creates a copy of a group of the virtual machines in an operating network in a deception network to form a group of cloned virtual machines in the deception network when the group of the virtual machines is accessed by an adversary. The computer system creates an emulation of components from the operating network in the deception network. The components are accessible by the group of the cloned virtual machines as if the group of the cloned virtual machines was in the operating network. The computer system moves networkmore » connections for the group of the virtual machines in the operating network used by the adversary from the group of the virtual machines in the operating network to the group of the cloned virtual machines, enabling protecting the group of the virtual machines from actions performed by the adversary.« less

Development of an Observational Rating Schedule for Preschool Children's Peer-Group Behavior.

ERIC Educational Resources Information Center

Cunningham, Jo Lynn; Boger, Robert P.

The feasiblity of an observational rating scale which would provide objective, reliable and quantifiable measures of social and affective behavior was investigated. The Observation of Socialization Behavior (OSB), focusing on peer-group behavior of pre-school children and designed for use in unstructured situations was developed. Two forms of the…

PRISM Climate Group, Oregon State U

Science.gov Websites

FAQ PRISM Climate Data The PRISM Climate Group gathers climate observations from a wide range of monitoring networks, applies sophisticated quality control measures, and develops spatial climate datasets to reveal short- and long-term climate patterns. The resulting datasets incorporate a variety of modeling

A Quality-Control-Oriented Database for a Mesoscale Meteorological Observation Network

NASA Astrophysics Data System (ADS)

Lussana, C.; Ranci, M.; Uboldi, F.

2012-04-01

In the operational context of a local weather service, data accessibility and quality related issues must be managed by taking into account a wide set of user needs. This work describes the structure and the operational choices made for the operational implementation of a database system storing data from highly automated observing stations, metadata and information on data quality. Lombardy's environmental protection agency, ARPA Lombardia, manages a highly automated mesoscale meteorological network. A Quality Assurance System (QAS) ensures that reliable observational information is collected and disseminated to the users. The weather unit in ARPA Lombardia, at the same time an important QAS component and an intensive data user, has developed a database specifically aimed to: 1) providing quick access to data for operational activities and 2) ensuring data quality for real-time applications, by means of an Automatic Data Quality Control (ADQC) procedure. Quantities stored in the archive include hourly aggregated observations of: precipitation amount, temperature, wind, relative humidity, pressure, global and net solar radiation. The ADQC performs several independent tests on raw data and compares their results in a decision-making procedure. An important ADQC component is the Spatial Consistency Test based on Optimal Interpolation. Interpolated and Cross-Validation analysis values are also stored in the database, providing further information to human operators and useful estimates in case of missing data. The technical solution adopted is based on a LAMP (Linux, Apache, MySQL and Php) system, constituting an open source environment suitable for both development and operational practice. The ADQC procedure itself is performed by R scripts directly interacting with the MySQL database. Users and network managers can access the database by using a set of web-based Php applications.

Brain Anatomical Network and Intelligence

PubMed Central

Li, Jun; Qin, Wen; Li, Kuncheng; Yu, Chunshui; Jiang, Tianzi

2009-01-01

Intuitively, higher intelligence might be assumed to correspond to more efficient information transfer in the brain, but no direct evidence has been reported from the perspective of brain networks. In this study, we performed extensive analyses to test the hypothesis that individual differences in intelligence are associated with brain structural organization, and in particular that higher scores on intelligence tests are related to greater global efficiency of the brain anatomical network. We constructed binary and weighted brain anatomical networks in each of 79 healthy young adults utilizing diffusion tensor tractography and calculated topological properties of the networks using a graph theoretical method. Based on their IQ test scores, all subjects were divided into general and high intelligence groups and significantly higher global efficiencies were found in the networks of the latter group. Moreover, we showed significant correlations between IQ scores and network properties across all subjects while controlling for age and gender. Specifically, higher intelligence scores corresponded to a shorter characteristic path length and a higher global efficiency of the networks, indicating a more efficient parallel information transfer in the brain. The results were consistently observed not only in the binary but also in the weighted networks, which together provide convergent evidence for our hypothesis. Our findings suggest that the efficiency of brain structural organization may be an important biological basis for intelligence. PMID:19492086

Meteor Observation in a Group

NASA Astrophysics Data System (ADS)

Zimnikoval, Peter

2010-08-01

Observation in former Czechoslovakia has more than 100 years tradition. These activities started in Czech part of the republic, mostly. More serious and systematic observations began in second half of the 20-th century. Important role played the International Geophysical Year 1957/58. Part of this event was International Meteor Year. Czechoslovakian astronomers were accredited as main organisers of the IMY. It was improved observe methods for this reason. High role in meteor observations has establishment of public observatories in Slovakia in 70-ties, too. Beside of popularization of astronomy one of main task was to organise amateur observations. Important role had collaboration of Copernicus Observatory and planetarium Brno (now Czech republic) and observatory Banská Bystrica from 1972. Main purpose of the collaboration was organising of so-called National Meteor Expeditions. These expeditions runs till 1988. Tradition of expeditions continues in Slovakia until today.

A Computational Framework for Quantifying and Optimizing the Performance of Observational Networks in 4D-Var Data Assimilation

NASA Astrophysics Data System (ADS)

Cioaca, Alexandru

A deep scientific understanding of complex physical systems, such as the atmosphere, can be achieved neither by direct measurements nor by numerical simulations alone. Data assimila- tion is a rigorous procedure to fuse information from a priori knowledge of the system state, the physical laws governing the evolution of the system, and real measurements, all with associated error statistics. Data assimilation produces best (a posteriori) estimates of model states and parameter values, and results in considerably improved computer simulations. The acquisition and use of observations in data assimilation raises several important scientific questions related to optimal sensor network design, quantification of data impact, pruning redundant data, and identifying the most beneficial additional observations. These questions originate in operational data assimilation practice, and have started to attract considerable interest in the recent past. This dissertation advances the state of knowledge in four dimensional variational (4D-Var) data assimilation by developing, implementing, and validating a novel computational framework for estimating observation impact and for optimizing sensor networks. The framework builds on the powerful methodologies of second-order adjoint modeling and the 4D-Var sensitivity equations. Efficient computational approaches for quantifying the observation impact include matrix free linear algebra algorithms and low-rank approximations of the sensitivities to observations. The sensor network configuration problem is formulated as a meta-optimization problem. Best values for parameters such as sensor location are obtained by optimizing a performance criterion, subject to the constraint posed by the 4D-Var optimization. Tractable computational solutions to this "optimization-constrained" optimization problem are provided. The results of this work can be directly applied to the deployment of intelligent sensors and adaptive observations, as well as

Social factors shaping the formation of a multi-stakeholder trails network group for the Monongahela National Forest, West Virginia

Treesearch

Karen Robinson; Steven Selin; Chad Pierskalla

2009-01-01

This paper reports the results and management implications of a longitudinal research study examining the social factors affecting the formation of a trails network advisory group for the Monongahela National Forest (MNF) in West Virginia. A collaborative process of creating an MNF trails network with input from local users and stakeholders has been largely...

Reviews and syntheses: guiding the evolution of the observing system for the carbon cycle through quantitative network design

NASA Astrophysics Data System (ADS)

Kaminski, Thomas; Rayner, Peter Julian

2017-10-01

Various observational data streams have been shown to provide valuable constraints on the state and evolution of the global carbon cycle. These observations have the potential to reduce uncertainties in past, current, and predicted natural and anthropogenic surface fluxes. In particular such observations provide independent information for verification of actions as requested by the Paris Agreement. It is, however, difficult to decide which variables to sample, and how, where, and when to sample them, in order to achieve an optimal use of the observational capabilities. Quantitative network design (QND) assesses the impact of a given set of existing or hypothetical observations in a modelling framework. QND has been used to optimise in situ networks and assess the benefit to be expected from planned space missions. This paper describes recent progress and highlights aspects that are not yet sufficiently addressed. It demonstrates the advantage of an integrated QND system that can simultaneously evaluate a multitude of observational data streams and assess their complementarity and redundancy.

The Observing Working Group for the Asteroid Impact & Delfection Assessment (AIDA) Mission

NASA Astrophysics Data System (ADS)

Osip, David J.; Rivkin, Andrew S.; Pravec, Petr; Moskovitz, Nicholas; Thirouin, Audrey; Scheirich, Peter; Oszkiewicz, Dagmara Anna; Richardson, Derek C.; Polishook, David; Ryan, William; Thomas, Cristina; Busch, Michael W.; Cheng, Andrew F.; Michel, Patrick; AIDA Observing Working Group

2016-10-01

The Asteroid Impact & Deflection Assessment (AIDA) mission is a joint ESA-NASA mission concept currently under study. AIDA has two components: the Double Asteroid Redirect Test (DART) is the US component designed to demonstrate a kinetic impactor, while the Asteroid Impact Mission (AIM) spacecraft is on station to do a thorough pre- and post-impact survey of the Didymos system.Members of the DART and AIM Investigation teams have been organized into several joint and independent working groups. While there is overlap in subject matter and membership between the groups, we focus here on the activities of the Observing Working Group.The first work by the group was undertaken during the spring of 2015, before DART entered Phase A. During this period Didymos made an apparition reaching roughly V ~ 20.5 in brightness, and our top priority was constraining which of two very different pole positions for the Didymos system was correct. Several telescopes in the 2-4-m aperture range around the world attempted observations. An observed mutual event allowed the one pole position to be ruled out. Didymos is now thought to be a low-obliquity, retrograde rotator, similar to many other asteroid binary systems and consistent with expectations from a YORP-driven origin for the satellite.We have begun planning for the 2017 apparition, occurring in the first half of the year. Didymos will be ~20% brighter at opposition than the 2015 apparition. Scaling from the successful observations with the 4.3-m Lowell Discovery Channel Telescope indicates that we will need telescopes at least 4 m (or larger, for some of the tasks, or at times longer before or after the opposition) in primary diameter for the advanced characterization in 2017.Currently, we have four goals for this apparition: 1) confirming the preferred retrograde pole position; 2) gathering data to allow BYORP-driven changes in the mutual orbit to potentially be determined by later observations; 3) establishing whether or not the

Social networks in primates: smart and tolerant species have more efficient networks.

PubMed

Pasquaretta, Cristian; Levé, Marine; Claidière, Nicolas; van de Waal, Erica; Whiten, Andrew; MacIntosh, Andrew J J; Pelé, Marie; Bergstrom, Mackenzie L; Borgeaud, Christèle; Brosnan, Sarah F; Crofoot, Margaret C; Fedigan, Linda M; Fichtel, Claudia; Hopper, Lydia M; Mareno, Mary Catherine; Petit, Odile; Schnoell, Anna Viktoria; di Sorrentino, Eugenia Polizzi; Thierry, Bernard; Tiddi, Barbara; Sueur, Cédric

2014-12-23

Network optimality has been described in genes, proteins and human communicative networks. In the latter, optimality leads to the efficient transmission of information with a minimum number of connections. Whilst studies show that differences in centrality exist in animal networks with central individuals having higher fitness, network efficiency has never been studied in animal groups. Here we studied 78 groups of primates (24 species). We found that group size and neocortex ratio were correlated with network efficiency. Centralisation (whether several individuals are central in the group) and modularity (how a group is clustered) had opposing effects on network efficiency, showing that tolerant species have more efficient networks. Such network properties affecting individual fitness could be shaped by natural selection. Our results are in accordance with the social brain and cultural intelligence hypotheses, which suggest that the importance of network efficiency and information flow through social learning relates to cognitive abilities.

Calculation of intensity of high energy muon groups observed deep underground

NASA Technical Reports Server (NTRS)

Vavilov, Y. N.; Dedenko, L. G.

1985-01-01

The intensity of narrow muon groups observed in Kolar Gold Field (KGF) at the depth of 3375 m.w.e. was calculated in terms of quark-gluon strings model for high energy hadron - air nuclei interactions by the method of direct modeling of nuclear cascade in the air and muon propagation in the ground for normal primary cosmic ray composition. The calculated intensity has been found to be approx. 10 to the 4 times less than one observed experimentally.

An ontology for sensor networks

NASA Astrophysics Data System (ADS)

Compton, Michael; Neuhaus, Holger; Bermudez, Luis; Cox, Simon

2010-05-01

Sensors and networks of sensors are important ways of monitoring and digitizing reality. As the number and size of sensor networks grows, so too does the amount of data collected. Users of such networks typically need to discover the sensors and data that fit their needs without necessarily understanding the complexities of the network itself. The burden on users is eased if the network and its data are expressed in terms of concepts familiar to the users and their job functions, rather than in terms of the network or how it was designed. Furthermore, the task of collecting and combining data from multiple sensor networks is made easier if metadata about the data and the networks is stored in a format and conceptual models that is amenable to machine reasoning and inference. While the OGC's (Open Geospatial Consortium) SWE (Sensor Web Enablement) standards provide for the description and access to data and metadata for sensors, they do not provide facilities for abstraction, categorization, and reasoning consistent with standard technologies. Once sensors and networks are described using rich semantics (that is, by using logic to describe the sensors, the domain of interest, and the measurements) then reasoning and classification can be used to analyse and categorise data, relate measurements with similar information content, and manage, query and task sensors. This will enable types of automated processing and logical assurance built on OGC standards. The W3C SSN-XG (Semantic Sensor Networks Incubator Group) is producing a generic ontology to describe sensors, their environment and the measurements they make. The ontology provides definitions for the structure of sensors and observations, leaving the details of the observed domain unspecified. This allows abstract representations of real world entities, which are not observed directly but through their observable qualities. Domain semantics, units of measurement, time and time series, and location and mobility

Social networks in primates: smart and tolerant species have more efficient networks

PubMed Central

Pasquaretta, Cristian; Levé, Marine; Claidière, Nicolas; van de Waal, Erica; Whiten, Andrew; MacIntosh, Andrew J. J.; Pelé, Marie; Bergstrom, Mackenzie L.; Borgeaud, Christèle; Brosnan, Sarah F.; Crofoot, Margaret C.; Fedigan, Linda M.; Fichtel, Claudia; Hopper, Lydia M.; Mareno, Mary Catherine; Petit, Odile; Schnoell, Anna Viktoria; di Sorrentino, Eugenia Polizzi; Thierry, Bernard; Tiddi, Barbara; Sueur, Cédric

2014-01-01

Network optimality has been described in genes, proteins and human communicative networks. In the latter, optimality leads to the efficient transmission of information with a minimum number of connections. Whilst studies show that differences in centrality exist in animal networks with central individuals having higher fitness, network efficiency has never been studied in animal groups. Here we studied 78 groups of primates (24 species). We found that group size and neocortex ratio were correlated with network efficiency. Centralisation (whether several individuals are central in the group) and modularity (how a group is clustered) had opposing effects on network efficiency, showing that tolerant species have more efficient networks. Such network properties affecting individual fitness could be shaped by natural selection. Our results are in accordance with the social brain and cultural intelligence hypotheses, which suggest that the importance of network efficiency and information flow through social learning relates to cognitive abilities. PMID:25534964

Network-Based Detection and Classification of Seismovolcanic Tremors: Example From the Klyuchevskoy Volcanic Group in Kamchatka

NASA Astrophysics Data System (ADS)

Soubestre, Jean; Shapiro, Nikolai M.; Seydoux, Léonard; de Rosny, Julien; Droznin, Dmitry V.; Droznina, Svetlana Ya.; Senyukov, Sergey L.; Gordeev, Evgeniy I.